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Seit dem Zusammenbruch der Sowjetunion kamen in diesem Raum neue Migrationsprozesse wie die Arbeitsmigration zwischen den südlichen GUS-Republiken und Russland, aber auch grenzüberschreitende Bevölkerungsbewegungen ethnischer Gruppen in ihre „historischen Herkunftsgebiete“ auf. Die in der vorliegenden Arbeit untersuchten, dynamischen Wanderungsprozesse von Kasachen zwischen der Mongolei und Kasachstan weisen Kennzeichen dieses Migrationstypus, aber auch einige Besonderheiten auf. Die vorliegende Arbeit hat längere Forschungsaufenthalte in Kasachstan und der Mongolei von 2006 bis 2009 zur Grundlage. Aus der Mongolei stammende kasachische Migranten im Umland von Almaty und Kasachen im westlichsten aymag der Mongolei, Bayan-Ölgiy, wurden mittels quantitativer und qualitativer Methoden empirischer Sozialforschung befragt. Ergänzend wurden in beiden Staaten Befragungen von Experten aus gesellschaftlichen, wissenschaftlichen und politischen Institutionen durchgeführt, um eine möglichst ausgeglichene Sicht auf die postsowjetischen Migrations- und Inkorporationsprozesse zwischen beiden Staaten sicherzustellen. Zwischen den Migranten in Kasachstan und ihren – noch bzw. wieder – in der Mongolei lebenden Verwandten haben sich in den letzten Jahrzehnten enge soziale Netzwerke entwickelt. Die Aufrechterhaltung der Bindungen wird durch eine Verbesserung der Transport- und Kommunikationsmöglichkeiten zwischen beiden Staaten gefördert. Zirkuläre Migrationsmuster, regelmäßige Besuche und Telefongespräche sowie grenzüberschreitende sozioökonomische Unterstützungsmechanismen haben sich insbesondere in den vergangenen Jahren intensiviert. Diese Interaktionen sind im Kontext der rechtlichen, politischen und wirtschaftlichen Bedingungen im Migrationssystem Mongolei-Kasachstan – und insbesondere in Wechselwirkung mit der staat¬lichen Migrations- und Inkorpora-tionspolitik – einzuordnen. Die Erkenntnisse der vorliegenden Untersuchung lassen sich in aller Kürze so zusammenfassen: (I) Die in sozialen Netzwerken organisierten Interaktionen der Kasachen aus der Mongolei weisen Merkmale von, aber auch Unterschiede zu Konzepten des Transnationalismus-Ansatzes auf. (II) Die sozialen Bindungen zwischen Verwandten generieren Sozialkapital und tragen zur alltäglichen Unterstützung bei. (III) Die lokalen und grenzüberschreitenden Aktivitäten der Migranten sind als Strategien der sozioökonomischen Eingliederung zu deuten. (IV) Ein wesentlicher Teil der aus der Mongolei stammenden Kasachen artikuliert von der Mehrheitsbevölkerung abweichende, hybride Identifikationsmuster, die die politischen Eliten in Kasachstan bisher zu wenig wahrnehmen.
Im Landschaftszustand und in der Landschaftsentwicklung kommen funktionale Beziehungen zwischen dem naturbedingten Energie-, Wasser- und Stoffhaushalt einerseits und den Auswirkungen der Landnutzung andererseits zum Ausdruck. Gegenwärtig verändert der globale Anstieg der bodennahen Temperaturen vielerorts den landschaftlichen Energie-, Wasser- und Stoffhaushalt, wobei besonders in Trockengebieten zu erwarten ist, dass dieser Trend in Verbindung mit einer unangepassten Landnutzung das Regenerationsvermögen der Vegetation einschränkt und zur Zerstörung der Bodendecke führt. Für die Mongolei und für benachbarte Gebiete Asiens sind in Szenarien zur globalen Erwärmung hohe Werte des Temperaturanstiegs prognostiziert worden. Eine globale Einschätzung der anthropogen induzierten Bodendegradation hat diese Region als stark oder extrem stark betroffen eingestuft. Vor diesem Hintergrund wurde im Uvs-Nuur-Becken, das im Nordwesten der Mongolei und damit in einer der trockensten Regionen des Landes gelegen ist, untersucht, wie sich der globale Temperaturanstieg auf der lokalen und regionalen Ebene widerspiegelt und wie der Landschaftshaushalt dabei verändert wird. Die Auswirkungen des sommerlichen Witterungsverlaufes auf den Landschaftszustand sind 1997 bis 1999 an einem Transsekt erfasst worden, das sich zwischen dem Kharkhiraa-Gebirge am Westrand des Beckens und dem See Uvs Nuur im Beckeninneren von den Polsterfluren und Matten der alpinen Stufe über die Gebirgswaldsteppe, die Trockensteppe bis zur Halbwüste erstreckt. An neun Messpunkten wurden witterungsklimatische Daten in Verbindung mit Merkmalen der Vegetation, des Bodens und der Bodenfeuchte aufgenommen. Die im Sommer 1998 gewonnenen Messwerte wurden mit Hilfe einer Clusteranalyse gebündelt und verdichtet. Auf dieser Grundlage konnten landschaftliche Zustandsformen inhaltlich gekennzeichnet, zeitlich eingeordnet und durch Zeit-Verhaltens-Modelle (Stacks) abgebildet werden. Aus den Zeit-Verhaltens-Modellen wird ersichtlich, dass man Zustandsformen, in denen die Hitze und die Trockenheit des Sommers 1998 besonders stark zum Ausdruck kommen, an allen Messpunkten beobachten kann, nimmt man die Station auf dem fast 3.000 m hohen Gipfel des Khukh Uul sowie die grundwasserbeeinflusste Station in unmittelbarer Seenähe aus. In ihrer extremen Form sind Trockenperioden jedoch nur im Beckeninneren und am Fuß der Randgebirge, also in der Halbwüste, in der Trockensteppe und in der Wiesensteppe aufgetreten. Im Bergwald sowie im Bereich der alpinen Matten und Polsterfluren fehlen sie. Am stärksten sind die grundwasserfreien Bereiche der Halbwüste von der Hitze und Niederschlagsarmut des Sommers 1998 betroffen. An vier Fünfteln der Tage des Beobachtungszeitraumes herrscht an diesem Messpunkt extreme Trockenheit. Es fällt entweder gar kein Niederschlag oder nur so wenig, dass der seit dem Frühjahr erschöpfte Bodenwasservorrat nicht aufgefüllt wird. Das Verhältnis zwischen Niederschlag und potenzieller Verdunstung liegt hier bei 1:12. In der Halbwüste zeichnet sich eine fortschreitende Desertifikation ab, zumal hier eine nichtangepasste Weidenutzung dominiert, in der Ziegen eine immer größere Rolle spielen. Dies gilt insbesondere für Bereiche in Siedlungsnähe. Örtlich ist auch der Bestand der Trockensteppe gefährdet, die sich an die Halbwüste zum Beckenrand hin anschließt. Hier ist nicht nur die Viehdichte am höchsten, sondern hier werden auch die meisten unbefestigten Fahrwege wild angelegt und die Bodendecke damit zerstört. Dies kann im Endeffekt zu einem Übergreifen von Prozessen der Desertifikation führen. Aus methodischer Sicht zeigt sich, dass die Kennzeichnung landschaftlicher Zustandsformen durch Zeit-Verhaltens-Modelle die Ermittlung der Auswirkungen von Witterung und Klima auf den Landschaftszustand erleichtert, da sie deren Aussage konzentriert. Zur Interpretation der Ergebnisse ist jedoch ein Rückgriff auf die beschreibende Darstellung der Messwerte notwendig. Die im westlichen Uvs-Nuur-Becken und seinen Randgebirgen angewandte Verfahrensweise ermöglicht es, globale Aussagen zur globalen Erwärmung der Kontinente regional oder lokal zu überprüfen und zu untersetzen."
Die Hochwasserereignisse der letzten Jahre haben Mängel bei der schnellen Verfügbarkeit des klassischen Darstellungs-, Entscheidungs- und Analyseinstruments Karte offenbart. Die Erfahrungen von 1997 und 2002 verdeutlichen, dass eine homogene digitale Datengrundlage, die neben rein topographischen zusätzlich auch fachspezifische Informationen des Hochwasserschutzes enthält, für eine effektive Bekämpfung solcher Ereignisse notwendig ist. Mit den Daten des ,Amtlichen Topographisch-Kartographischen Informationssystems’ (ATKIS) liegen topographische Basisdaten in graphikfreier Form als digitales Landschaftsmodell (DLM) flächendeckend für die Bundesrepublik vor. Anhand der exemplarischen Ableitung von nutzerorientierten Kartenmodellen aus diesen graphikfreien Daten wurde deren Eignung für den besonderen Verwendungszweck im Rahmen eines Hochwasserschutz-Informationssystems überprüft. Als Anwendungsbeispiel wurde das Gebiet der Ziltendorfer Niederung, die während des Oder-Hochwassers 1997 überflutet wurde, gewählt. In Expertengesprächen wurden zunächst Inhalte identifiziert, die für einen wirksamen Hochwasserschutz Relevanz besitzen; diese Inhalte wurden anschließend analog zum ATKIS-Systemdesign strukturiert und als Objekte eines separaten Objektbereichs im digitalen Fachmodell (DFM) erfasst. Bei der Ableitung von (Bildschirm-) Karten aus den graphikfreien Daten wurden jeweils unterschiedliche Kriterien für die Basiskarte und die Fachinhalte berücksichtigt. Dabei wurden verschiedene kartographische Regeln und Gesetze mit dem Ziel der prägnanten Visualisierung und damit der eindeutigen Lesbarkeit der Karten angewendet. Beispielhaft sei hier die Schaffung einer visuellen Hierarchie zwischen Basiskarte und Fachinhalten genannt. Die besonderen Nutzungsbedingungen von Karten im Einsatzfall erfordern u.a., dass die Karten auch von Personen, die nur über geringe oder keine Erfahrung im Umgang mit Karten verfügen, schnell und einfach zu lesen sind, um so eine sichere Informationsvermittlung zu gewährleisten. Voraussetzung dafür ist einerseits die Beschränkung auf die Darstellung der wesentlichen Inhalte, andererseits die Verwendung leicht lesbarer Kartenzeichen. Aus diesem Grund wurden einheitliche Kartenzeichen zur Darstellung der Fachinhalte entwickelt, die entweder aus allgemein bekannten Symbolen, aus den im Katastrophenschutz üblicherweise verwendeten sog. taktischen Zeichen oder aus Fachzeichen des Hochwasserschutzes abgeleitet wurden. Die entwickelten Kartenmodelle wurden abschließend in qualitativen Experteninterviews in Bezug auf ihre Qualität und Verwendbarkeit im Hochwasserschutz geprüft. Die Auswertung der Interviews ergab eine insgesamt positive Beurteilung der Karten für den Einsatz in Hochwasserschutz-Informationssystemen. Damit leistet die vorliegende Arbeit einen Beitrag zur Entwicklung von (Bildschirm-) Karten zur Unterstützung bei der Entscheidungsfindung im Katastrophenmanagement.
In den letzten 20 Jahren sind Evaluationen Schritt für Schritt zu einem festen und gleichzeitig kontrovers diskutierten Bestandteil politischer Förderung geworden. Auf der Basis langjähriger Beobachtungen der Evaluationspraxis des Förderprogramms „Soziale Stadt“ zeigt dieses Buch zunächst, dass Evaluationstätigkeiten in Ministerien, Kommunalverwaltungen und Planungsbüros mit ganz unterschiedlichen Erwartungen, Herausforderungen, Widersprüchen und Irritationen verknüpft werden. Evaluationen werden dabei sowohl als Hoffnungsträger, als auch als Schreckgespenst gesehen. Der Autor nimmt diese Beobachtungen zum Anlass, den Umgang mit Evaluationen in politischen Organisationen kritisch zu hinterfragen und systematisch zu erklären. Reduziert auf die Frage „Wozu Evaluation?“ wird auf der Basis eines systemtheoretischen Zugangs erklärt, welche unterschiedlichen Funktionen Evaluationen in Organisationen erfüllen können. Vertiefend wird dabei auf organisationales Lernen, auf politische Steuerungslogik und auf die Notwendigkeit von Symbolisierungen eingegangen.
Das Schulfach Geographie war in der DDR eines der Fächer, das sehr stark mit politischen Themen im Sinne des Marxismus-Leninismus bestückt war. Ein anderer Aspekt sind die sozialistischen Erziehungsziele, die in der Schulbildung der DDR hoch im Kurs standen. Im Fokus stand diesbezüglich die Erziehung der Kinder zu sozialistischen Persönlichkeiten. Die Arbeit versucht einen klaren Blick auf diesen Umstand zu werfen, um zu erfahren, was da von den Lehrkräften gefordert wurde und wie es in der Schule umzusetzen war.
Durch den Fall der Mauer war natürlich auch eine Umstrukturierung des Bildungssystems im Osten unausweichlich. Hier will die Arbeit Einblicke geben, wie die Geographielehrkräfte diese Transformation mitgetragen und umgesetzt haben. Welche Wesenszüge aus der Sozialisierung in der DDR haben sich bei der Gestaltung des Unterrichtes und dessen Ausrichtung auf die neuen Erziehungsziele erhalten?
Hierzu wurden Geographielehrkräfte befragt, die sowohl in der DDR als auch im geeinten Deutschland unterrichtet haben. Die Fragen bezogen sich in erster Linie auf die Art und Weise des Unterrichtens vor, während und nach der Wende und der daraus entstandenen Systemtransformation.
Die Befragungen kommen zu dem Ergebnis, dass sich der Geographieunterricht in der DDR thematisch von dem in der BRD nicht sonderlich unterschied. Von daher bedurfte es keiner umfangreichen inhaltlichen Veränderung des Geographieunterrichts. Schon zu DDR-Zeiten wurden durch die Lehrkräfte offenbar eigenmächtig ideologiefreie physisch-geographische Themen oft ausgedehnt, um die Ideologie des Faches zu reduzieren. So fiel den meisten eine Anpassung ihres Unterrichts an das westdeutsche System relativ leicht. Die humanistisch geprägte Werteerziehung des DDR-Bildungssystems wurde unter Ausklammerung des sozialistischen Aspektes ebenso fortgeführt, da es auch hier viele Parallelen zum westdeutschen System gegeben hat. Deutlich wird eine Charakterisierung des Faches als Naturwissenschaft von Seiten der ostdeutschen Lehrkräfte, obwohl das Fach an den Schulen den Gesellschaftswissenschaften zugeordnet wird und auch in der DDR eine starke wirtschaftsgeographische Ausrichtung hatte.
Von der Verantwortung sozialistische Persönlichkeiten zu erziehen, wurden die Lehrkräfte mit dem Ende der DDR entbunden und die in dieser Arbeit aufgeführten Interviewauszüge lassen keinen Zweifel daran, dass es dem Großteil der Befragten darum nicht leidtat, sie sich aber bis heute an der Werteorientierung aus DDR-Zeiten orientieren.
The functioning of the surface water-groundwater interface as buffer, filter and reactive zone is important for water quality, ecological health and resilience of streams and riparian ecosystems. Solute and heat exchange across this interface is driven by the advection of water. Characterizing the flow conditions in the streambed is challenging as flow patterns are often complex and multidimensional, driven by surface hydraulic gradients and groundwater discharge. This thesis presents the results of an integrated approach of studies, ranging from the acquisition of field data, the development of analytical and numerical approaches to analyse vertical temperature profiles to the detailed, fully-integrated 3D numerical modelling of water and heat flux at the reach scale. All techniques were applied in order to characterize exchange flux between stream and groundwater, hyporheic flow paths and temperature patterns.
The study was conducted at a reach-scale section of the lowland Selke River, characterized by distinctive pool riffle sequences and fluvial islands and gravel bars. Continuous time series of hydraulic heads and temperatures were measured at different depths in the river bank, the hyporheic zone and within the river. The analyses of the measured diurnal temperature variation in riverbed sediments provided detailed information about the exchange flux between river and groundwater. Beyond the one-dimensional vertical water flow in the riverbed sediment, hyporheic and parafluvial flow patterns were identified. Subsurface flow direction and magnitude around fluvial islands and gravel bars at the study site strongly depended on the position around the geomorphological structures and on the river stage. Horizontal water flux in the streambed substantially impacted temperature patterns in the streambed. At locations with substantial horizontal fluxes the penetration depths of daily temperature fluctuations was reduced in comparison to purely vertical exchange conditions.
The calibrated and validated 3D fully-integrated model of reach-scale water and heat fluxes across the river-groundwater interface was able to accurately represent the real system. The magnitude and variations of the simulated temperatures matched the observed ones, with an average mean absolute error of 0.7 °C and an average Nash Sutcliffe Efficiency of 0.87. The simulation results showed that the water and heat exchange at the surface water-groundwater interface is highly variable in space and time with zones of daily temperature oscillations penetrating deep into the sediment and spots of daily constant temperature following the average groundwater temperature. The average hyporheic flow path temperature was found to strongly correlate with the flow path residence time (flow path length) and the temperature gradient between river and groundwater. Despite the complexity of these processes, the simulation results allowed the derivation of a general empirical relationship between the hyporheic residence times and temperature patterns. The presented results improve our understanding of the complex spatial and temporal dynamics of water flux and thermal processes within the shallow streambed. Understanding these links provides a general basis from which to assess hyporheic temperature conditions in river reaches.
Der boomende Wirtschaftsriese China erfährt weltweit immer mehr Aufmerksamkeit von Politik, Wirtschaft, Wissenschaft und Öffentlichkeit. Gleichzeitig werden aber auch innere soziale Probleme und die großen regionalen Disparitäten des Landes angesprochen. Auch Berichte über die Situation der Wanderarbeiter in den Großstädten des Landes häufen sich. Obwohl sich die Wissenschaft ebenfalls dieses Themas angenommen hat, mangelt es noch an Untersuchungen darüber, insbesondere an solchen, die eingehend und systematisch mit empirischen Erhebungen „vor Ort“ dieses Phänomen studieren. In diese Lücke stößt die Dissertation von Ling He. In ihrem Mittelpunkt steht das Alltagsleben der Arbeitsmigranten in Peking. Dabei werden behandelt: die Migrationsmotive, die strukturellen und individuellen Rahmenbedingungen für die Arbeitsmigranten und ihre Familien, die Arbeits- und Lebensbedingungen, die Bildung finanzieller Ressourcen sowie auch die Konstruktion sozialer Netzwerke und die Integration der Migranten in Peking. Außerdem geht die Dissertation ein auf die Vorteile, die für die etwa 17 Millionen Einwohner zählende Stadt durch die Beschäftigung der etwa 3 Millionen Arbeitsmigranten geschaffen werden, und sie weist auf die sozialen und ökonomischen Probleme hin, die im Zusammenhang mit der Arbeitsmigration gelöst werden müssten.
Volcano dome deformation processes analysed with high resolution InSAR and camera-based techniques
(2017)
Die visuelle Kommunikation ist eine effiziente Methode, um dynamische Phänomene zu beschreiben. Informationsobjekte präzise wahrzunehmen, einen schnellen Zugriff auf strukturierte und relevante Informationen zu ermöglichen, erfordert konsistente und nach dem formalen Minimalprinzip konzipierte Analyse- und Darstellungsmethoden. Dynamische Raumphänomene in Geoinformationssystemen können durch den Mangel an konzeptionellen Optimierungsanpassungen aufgrund ihrer statischen Systemstruktur nur bedingt die Informationen von Raum und Zeit modellieren. Die Forschung in dieser Arbeit ist daher auf drei interdisziplinäre Ansätze fokussiert. Der erste Ansatz stellt eine echtzeitnahe Datenerfassung dar, die in Geodatenbanken zeitorientiert verwaltet wird. Der zweite Ansatz betrachtet Analyse- und Simulationsmethoden, die das dynamische Verhalten analysieren und prognostizieren. Der dritte Ansatz konzipiert Visualisierungsmethoden, die insbesondere dynamische Prozesse abbilden. Die Symbolisierung der Prozesse passt sich bedarfsweise in Abhängigkeit des Prozessverlaufes und der Interaktion zwischen Datenbanken und Simulationsmodellen den verschiedenen Entwicklungsphasen an. Dynamische Aspekte können so mit Hilfe bewährter Funktionen aus der GI-Science zeitnah mit modularen Werkzeugen entwickelt und visualisiert werden. Die Analyse-, Verschneidungs- und Datenverwaltungsfunktionen sollen hierbei als Nutzungs- und Auswertungspotential alternativ zu Methoden statischer Karten dienen. Bedeutend für die zeitliche Komponente ist das Verknüpfen neuer Technologien, z. B. die Simulation und Animation, basierend auf einer strukturierten Zeitdatenbank in Verbindung mit statistischen Verfahren. Methodisch werden Modellansätze und Visualisierungstechniken entwickelt, die auf den Bereich Verkehr transferiert werden. Verkehrsdynamische Phänomene, die nicht zusammenhängend und umfassend darstellbar sind, werden modular in einer serviceorientierten Architektur separiert, um sie in verschiedenen Ebenen räumlich und zeitlich visuell zu präsentieren. Entwicklungen der Vergangenheit und Prognosen der Zukunft werden über verschiedene Berechnungsmethoden modelliert und visuell analysiert. Die Verknüpfung einer Mikrosimulation (Abbildung einzelner Fahrzeuge) mit einer netzgesteuerten Makrosimulation (Abbildung eines gesamten Straßennetzes) ermöglicht eine maßstabsunabhängige Simulation und Visualisierung des Mobilitätsverhaltens ohne zeitaufwendige Bewertungsmodellberechnungen. Zukünftig wird die visuelle Analyse raum-zeitlicher Veränderungen für planerische Entscheidungen ein effizientes Mittel sein, um Informationen übergreifend verfügbar, klar strukturiert und zweckorientiert zur Verfügung zu stellen. Der Mehrwert durch visuelle Geoanalysen, die modular in einem System integriert sind, ist das flexible Auswerten von Messdaten nach zeitlichen und räumlichen Merkmalen.
Flugzeug- und Shuttle getragene SAR-Systeme werden zur Ableitung des Bodenwassergehalt im Oberboden verwendet. Die Untersuchungsgebiete lagen auf der Insel Rügen, in Oberbayern (Oberpfaffenhofen) und in Oklahoma (Little Washita). Die Regionalierung mit Fernerkundungsdaten wird anhand von geostatistisch aufbereiteten Referenzmessungen aus dem Feld verifiziert. Verschiedene Ableitungsverfahren (Regression, Rückstreuungsmodellierung, Nomogramme und Inversionsmodellierung) werden verglichen und Fehlermargen werden abgeleitet.
Accurate weather observations are the keystone to many quantitative applications, such as precipitation monitoring and nowcasting, hydrological modelling and forecasting, climate studies, as well as understanding precipitation-driven natural hazards (i.e. floods, landslides, debris flow). Weather radars have been an increasingly popular tool since the 1940s to provide high spatial and temporal resolution precipitation data at the mesoscale, bridging the gap between synoptic and point scale observations. Yet, many institutions still struggle to tap the potential of the large archives of reflectivity, as there is still much to understand about factors that contribute to measurement errors, one of which is calibration. Calibration represents a substantial source of uncertainty in quantitative precipitation estimation (QPE). A miscalibration of a few dBZ can easily deteriorate the accuracy of precipitation estimates by an order of magnitude. Instances where rain cells carrying torrential rains are misidentified by the radar as moderate rain could mean the difference between a timely warning and a devastating flood.
Since 2012, the Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA) has been expanding the country’s ground radar network. We had a first look into the dataset from one of the longest running radars (the Subic radar) after devastating week-long torrential rains and thunderstorms in August 2012 caused by the annual southwestmonsoon and enhanced by the north-passing Typhoon Haikui. The analysis of the rainfall spatial distribution revealed the added value of radar-based QPE in comparison to interpolated rain gauge observations. However, when compared with local gauge measurements, severe miscalibration of the Subic radar was found. As a consequence, the radar-based QPE would have underestimated the rainfall amount by up to 60% if they had not been adjusted by rain gauge observations—a technique that is not only affected by other uncertainties, but which is also not feasible in other regions of the country with very sparse rain gauge coverage.
Relative calibration techniques, or the assessment of bias from the reflectivity of two radars, has been steadily gaining popularity. Previous studies have demonstrated that reflectivity observations from the Tropical Rainfall Measuring Mission (TRMM) and its successor, the Global Precipitation Measurement (GPM), are accurate enough to serve as a calibration reference for ground radars over low-to-mid-latitudes (± 35 deg for TRMM; ± 65 deg for GPM). Comparing spaceborne radars (SR) and ground radars (GR) requires cautious consideration of differences in measurement geometry and instrument specifications, as well as temporal coincidence. For this purpose, we implement a 3-D volume matching method developed by Schwaller and Morris (2011) and extended by Warren et al. (2018) to 5 years worth of observations from the Subic radar. In this method, only the volumetric intersections of the SR and GR beams are considered.
Calibration bias affects reflectivity observations homogeneously across the entire radar domain. Yet, other sources of systematic measurement errors are highly heterogeneous in space, and can either enhance or balance the bias introduced by miscalibration. In order to account for such heterogeneous errors, and thus isolate the calibration bias, we assign a quality index to each matching SR–GR volume, and thus compute the GR calibration bias as a qualityweighted average of reflectivity differences in any sample of matching SR–GR volumes. We exemplify the idea of quality-weighted averaging by using beam blockage fraction (BBF) as a quality variable. Quality-weighted averaging is able to increase the consistency of SR and GR observations by decreasing the standard deviation of the SR–GR differences, and thus increasing the precision of the bias estimates.
To extend this framework further, the SR–GR quality-weighted bias estimation is applied to the neighboring Tagaytay radar, but this time focusing on path-integrated attenuation (PIA) as the source of uncertainty. Tagaytay is a C-band radar operating at a lower wavelength and is therefore more affected by attenuation. Applying the same method used for the Subic radar, a time series of calibration bias is also established for the Tagaytay radar.
Tagaytay radar sits at a higher altitude than the Subic radar and is surrounded by a gentler terrain, so beam blockage is negligible, especially in the overlapping region. Conversely, Subic radar is largely affected by beam blockage in the overlapping region, but being an SBand radar, attenuation is considered negligible. This coincidentally independent uncertainty contributions of each radar in the region of overlap provides an ideal environment to experiment with the different scenarios of quality filtering when comparing reflectivities from the two ground radars. The standard deviation of the GR–GR differences already decreases if we consider either BBF or PIA to compute the quality index and thus the weights. However, combining them multiplicatively resulted in the largest decrease in standard deviation, suggesting that taking both factors into account increases the consistency between the matched samples.
The overlap between the two radars and the instances of the SR passing over the two radars at the same time allows for verification of the SR–GR quality-weighted bias estimation method. In this regard, the consistency between the two ground radars is analyzed before and after bias correction is applied. For cases when all three radars are coincident during a significant rainfall event, the correction of GR reflectivities with calibration bias estimates from SR overpasses dramatically improves the consistency between the two ground radars which have shown incoherent observations before correction. We also show that for cases where adequate SR coverage is unavailable, interpolating the calibration biases using a moving average can be used to correct the GR observations for any point in time to some extent. By using the interpolated biases to correct GR observations, we demonstrate that bias correction reduces the absolute value of the mean difference in most cases, and therefore improves the consistency between the two ground radars.
This thesis demonstrates that in general, taking into account systematic sources of uncertainty that are heterogeneous in space (e.g. BBF) and time (e.g. PIA) allows for a more consistent estimation of calibration bias, a homogeneous quantity. The bias still exhibits an unexpected variability in time, which hints that there are still other sources of errors that remain unexplored. Nevertheless, the increase in consistency between SR and GR as well as between the two ground radars, suggests that considering BBF and PIA in a weighted-averaging approach is a step in the right direction.
Despite the ample room for improvement, the approach that combines volume matching between radars (either SR–GR or GR–GR) and quality-weighted comparison is readily available for application or further scrutiny. As a step towards reproducibility and transparency in atmospheric science, the 3D matching procedure and the analysis workflows as well as sample data are made available in public repositories. Open-source software such as Python and wradlib are used for all radar data processing in this thesis. This approach towards open science provides both research institutions and weather services with a valuable tool that can be applied to radar calibration, from monitoring to a posteriori correction of archived data.
Air pollution has been a persistent global problem in the past several hundred years. While some industrialized nations have shown improvements in their air quality through stricter regulation, others have experienced declines as they rapidly industrialize. The WHO’s 2021 update of their recommended air pollution limit values reflects the substantial impacts on human health of pollutants such as NO2 and O3, as recent epidemiological evidence suggests substantial long-term health impacts of air pollution even at low concentrations. Alongside developments in our understanding of air pollution's health impacts, the new technology of low-cost sensors (LCS) has been taken up by both academia and industry as a new method for measuring air pollution. Due primarily to their lower cost and smaller size, they can be used in a variety of different applications, including in the development of higher resolution measurement networks, in source identification, and in measurements of air pollution exposure. While significant efforts have been made to accurately calibrate LCS with reference instrumentation and various statistical models, accuracy and precision remain limited by variable sensor sensitivity. Furthermore, standard procedures for calibration still do not exist and most proprietary calibration algorithms are black-box, inaccessible to the public. This work seeks to expand the knowledge base on LCS in several different ways: 1) by developing an open-source calibration methodology; 2) by deploying LCS at high spatial resolution in urban environments to test their capability in measuring microscale changes in urban air pollution; 3) by connecting LCS deployments with the implementation of local mobility policies to provide policy advice on resultant changes in air quality.
In a first step, it was found that LCS can be consistently calibrated with good performance against reference instrumentation using seven general steps: 1) assessing raw data distribution, 2) cleaning data, 3) flagging data, 4) model selection and tuning, 5) model validation, 6) exporting final predictions, and 7) calculating associated uncertainty. By emphasizing the need for consistent reporting of details at each step, most crucially on model selection, validation, and performance, this work pushed forward with the effort towards standardization of calibration methodologies. In addition, with the open-source publication of code and data for the seven-step methodology, advances were made towards reforming the largely black-box nature of LCS calibrations.
With a transparent and reliable calibration methodology established, LCS were then deployed in various street canyons between 2017 and 2020. Using two types of LCS, metal oxide (MOS) and electrochemical (EC), their performance in capturing expected patterns of urban NO2 and O3 pollution was evaluated. Results showed that calibrated concentrations from MOS and EC sensors matched general diurnal patterns in NO2 and O3 pollution measured using reference instruments. While MOS proved to be unreliable for discerning differences among measured locations within the urban environment, the concentrations measured with calibrated EC sensors matched expectations from modelling studies on NO2 and O3 pollution distribution in street canyons. As such, it was concluded that LCS are appropriate for measuring urban air quality, including for assisting urban-scale air pollution model development, and can reveal new insights into air pollution in urban environments.
To achieve the last goal of this work, two measurement campaigns were conducted in connection with the implementation of three mobility policies in Berlin. The first involved the construction of a pop-up bike lane on Kottbusser Damm in response to the COVID-19 pandemic, the second surrounded the temporary implementation of a community space on Böckhstrasse, and the last was focused on the closure of a portion of Friedrichstrasse to all motorized traffic. In all cases, measurements of NO2 were collected before and after the measure was implemented to assess changes in air quality resultant from these policies. Results from the Kottbusser Damm experiment showed that the bike-lane reduced NO2 concentrations that cyclists were exposed to by 22 ± 19%. On Friedrichstrasse, the street closure reduced NO2 concentrations to the level of the urban background without worsening the air quality on side streets. These valuable results were communicated swiftly to partners in the city administration responsible for evaluating the policies’ success and future, highlighting the ability of LCS to provide policy-relevant results.
As a new technology, much is still to be learned about LCS and their value to academic research in the atmospheric sciences. Nevertheless, this work has advanced the state of the art in several ways. First, it contributed a novel open-source calibration methodology that can be used by a LCS end-users for various air pollutants. Second, it strengthened the evidence base on the reliability of LCS for measuring urban air quality, finding through novel deployments in street canyons that LCS can be used at high spatial resolution to understand microscale air pollution dynamics. Last, it is the first of its kind to connect LCS measurements directly with mobility policies to understand their influences on local air quality, resulting in policy-relevant findings valuable for decisionmakers. It serves as an example of the potential for LCS to expand our understanding of air pollution at various scales, as well as their ability to serve as valuable tools in transdisciplinary research.
Untersuchungen zur räumlichen Analyse und Visualisierung von Mietpreisdaten für Immobilienportale
(2015)
Die vorliegende Arbeit verfolgt das Ziel, aus geoinformatischer Sicht eine konzeptionelle Grundlage zur räumlichen Optimierung von Immobilienportalen zu schaffen. Die Arbeit geht dabei von zwei Hypothesen aus:
1. Verfahren der räumlichen Statistik und des Maschinellen Lernens zur Mietpreisschätzung sind den bisher eingesetzten Verfahren der hedonischen Regression überlegen und eignen sich zur räumlichen Optimierung von Immobilienportalen.
2. Die von Immobilienportalen publizierten webbasierten Mietpreiskarten geben nicht die tatsächlichen räumlichen Verhältnisse auf Immobilienmärkten wieder. Alternative webbasierte Darstellungsformen, wie z.B. Gridmaps, sind dem Status Quo der Immobilienpreiskarten von Immobilienportalen überlegen und visualisieren die tatsächlichen räumlichen Verhältnisse von Immobilienpreisen zweckmäßiger.
Beide Thesen können bewiesen werden.
Es erfolgt zunächst eine umfangreiche Erhebung des Forschungsbedarfs mittels Literaturstudien und technologischer Recherche. Zur Beantwortung der Forschungsfragen wird als quantitative Datenbasis ein 74.098 Mietangebote umfassender Datensatz (von Januar 2007 bis September 2013) eines Immobilienportals akquiriert. Dieser reicht jedoch nicht in vollem Umfang zur Beantwortung der Fragestellungen aus. Deshalb führt der Autor Experteninterviews zur Erhebung einer qualitativen Datenbasis. Deren Analyse ergibt in Kombination mit der Literaturstudie und der technologischen Recherche ein umfassendes, bisher so nicht verfügbares Bild. Es stellt den Status Quo der räumlichen Sicht sowie der raumanalytischen und geovisuellen Defizite von Immobilienportalen dar.
Zur Optimierung der raumanalytischen und geovisuellen Defizite werden forschungsbasierte Lösungsansätze herausgearbeitet und teilimplementiert. Methoden des Maschinellen Lernens und räumliche Schätzverfahren werden als Alternativen zu den von Immobilienportalen bisher genutzten „nicht räumlichen“ Analyseverfahren zur Preismodellierung untersucht. Auf Grundlage eines hierfür konzipierten Validierungsrahmens werden diese Methoden für die Nutzung im Kontext von Immobilienportalen adaptiert. Die prototypische Teilimplementierung zeigt die programmiertechnische Umsetzung des Konzeptes auf. Eine umfassende Analyse geeigneter Sekundärvariablensets zur Mietpreisschätzung liefert als methodisches Resultat, dass Interpolatoren, die Sekundärvariablen benötigen (Kriging with external drift, Ordinary Cokriging), kaum zu valideren Mietpreisschätzergebnissen gelangen als die Methode des Ordinary Kriging, die keine Sekundärvariablen benötigt. Die Methoden Random Forest aus dem Maschinellen Lernen und die Geographisch Gewichtete Regression hingegen bergen großes Potential zur Nutzung der räumlichen Mietpreisschätzung im Kontext von Immobilien-portalen. Die Forschungsergebnisse der räumlichen Preismodellierung werden in die räumliche Visualisierung von Mietpreisen transferiert.
Für die webbasierte Mietpreisdarstellung wird ein Set alternativer Darstellungsmethoden entwickelt, um Mietpreiskarten-Prototypen abzuleiten. Ein methodisches Ergebnis der Entwicklung der Mietpreiskarten-Prototypen ist die Entwicklung eines geeigneten Ansatzes der Loslösung des Preisbezugs von fachfremd verwendeten Bezugsgeometrien. Hierfür wird vom Autor der Begriff der zonenlosen Preiskarte geprägt. Diese werden mit Methoden des Gridmapping erstellt. Es werden optimale Rasterauflösungen zur Darstellung interpolierter Rastergrößen ermittelt. Zonenlose Preiskarten mit Methoden des Gridmapping, gepaart mit einer optionalen gebäudescharfen Darstellung in größeren Maßstäben, sind als Resultate der Forschung die bestmögliche, sich an realen Verhältnissen orientierende, räumliche Mietpreisdarstellung. Die entstandenen Prototypen sind eine Annäherung der wahren Verteilung des Mietpreises im Raum und um einiges schärfer, als die auf der hedonischen Regression basierenden Darstellungen. Somit kann die wahre „Topographie“ der Mietpreislandschaft abgebildet werden. Ein Einsatz der Karten für Nutzergruppen wie Makler, Investoren oder Kommunen zur Analyse städtischer Mietmärkte ist denkbar. Alle entstandenen Prototypen sind unter der Nutzung von Map APIs umgesetzt. Ein Ergebnis dessen ist, dass Map APIs noch an diversen „Kinderkrankheiten“ leiden und derart umgesetzte Mietpreiskarten noch einen weiten Weg vor sich haben, bis sie das Niveau thematischer Karten von Immhof oder Arnberger erreichen.
Die konzeptionellen Überlegungen und Teilimplementierungen münden in drei Prozessketten, die Umsetzungsoptionen für eine räumliche Optimierung von Immobilienportalen darstellen. Dabei werden zwei Szenarien für eine räumlich optimierte Mietpreisschätzung und ein Szenario für eine räumlich optimierte Mietpreisdarstellung herausgearbeitet.
Das Ziel dieser Arbeit ist die Untersuchung der Wasserhaushaltsprozesse und Stofftransportvorgänge innerhalb der grundwassergeprägten Talauenlandschaften von Tieflandeinzugsgebieten am Beispiel der im Nordostdeutschen Tiefland gelegenen Havel. Die Arbeiten in verschieden skaligen Teileinzugsgebieten der Havel beschäftigen sich dabei zum einen mit der experimentellen Untersuchung und vorrangig qualitativen Beschreibung der Wasserhaushaltsdynamik, zum anderen mit der Entwicklung eines zur quantitativen Analyse von Wasserhaushalts- und Stofftransportprozessen geeigneten Modells und der anschließenden Modellsimulation von Wasserhaushalt und Stickstoffmetabolik im Grundwasser sowie der Simulation von Landnutzungs- und Gewässerstrukturszenarien. Für die experimentelle Untersuchung der Abflussbildung und der Wasserhaushaltsprozesse in den Talauenlandschaften des Haveleinzugsgebiets wurde Einzugsgebiet der ”Unteren Havel Niederung“ ein umfangreiches Messnetz installiert. Dabei wurden an mehreren Messstationen und Pegeln meteorologische Parameter, Bodenfeuchte sowie Grundwasserstände und Abflüsse beobachtet. Die Analyse der Messergebnisse führte zu einem verbesserten Verständnis von Wasserhaushaltsprozessen in der durch das oberflächennahe Grundwasser und die Oberflächengewässerdynamik beeinflussten Talauenzone. Darüber hinaus konnten durch die Implementierung der Messergebnisse konsistente Anfangs- und Randbedingungen für die Wasserhaushalts- und Grundwassermodellierung im Modellkonzept IWAN realisiert werden. Mit dem Modell IWAN (Integrated Modelling of Water Balance and Nutrient Dynamics) wurde ein Werkzeug geschaffen, welches die Berücksichtigung spezifischer hydrologischer Eigenschaften von Tieflandauen, wie z. B. den Einfluss des oberflächennahen Grundwassers bzw. der Dynamik von Oberflächenwasserständen auf den Wasserhaushalt, ermöglicht. Es basiert auf der Kopplung des deterministischen distribuierten hydrologischen Modells WASIM-ETH mit dem dreidimensionalen Finite-Differenzen-basierten Grundwassermodel MODFLOW. Die Modellierung der Stickstoffmetabolik im Grundwasser erfolgt durch das mit Grundwassermodell gekoppelte Stofftransportmodel MT3D. Zur modellbasierten Simulation des Wasserhaushalts der Tieflandauenlandschaften wurde das Modellkonzept IWAN für verschieden skalige Teileinzugsgebiete an der Havel für Simulationszeiträume von 2 Wochen bis zu 13 Jahren angewandt. Dabei wurden die Teilmodelle für Wasserhaushalts- und Grundwassermodellierung in zwei unterschiedlichen Teileinzugsgebieten der ”Unteren Havel Niederung“ kalibriert. Die anschließende Validierung erfolgte für das gesamte Einzugsgebiet der ”Unteren Havel“. Die Unsicherheiten des Modellansatzes sowie die Anwendbarkeit des Modells im Untersuchungsraum wurden geprüft und die Limitierung der Übertragbarkeit auf andere grundwasserbeeinflusste Tieflandeinzugsgebiete analysiert. Die Ergebnisse der Wasserhaushaltssimulationen führen einerseits zum erweiterten Prozessverständnis des Wasserhaushalts in Flachlandeinzugsgebieten, andererseits ermöglichten sie durch die Quantifizierung einzelner Prozessgrößen die Beurteilung der Steuerungsfunktion einzelner Wasserhaushaltsprozesse. Auf der Basis lokaler Simulationsergebnisse sowie geomorphologischer und gewässermorphologischer Analysen wurde ein Algorithmus entwickelt, welcher die Abgrenzung des direkten Eigeneinzugsgebiets der Havel als Raum der direkten Interaktion zwischen Oberflächengewässer und umgebendem Einzugsgebiet beschreibt. Durch Simulation des Wasserhaushalts im Eigeneinzugsgebiet mit dem Modell IWAN konnten die Interaktionsprozesse zwischen Fluss und Talauenlandschaft quantitativ beschrieben werden. Dies ermöglichte eine Bewertung der Abflussanteile aus dem Eigeneinzugsgebiet sowie eine Quantifizierung der zeitlich variablen Retentionskapazität der Auenlandschaft während Hochwasserereignissen. Zur Abschätzung des Einflusses veränderter Landnutzung und angepassten Managements auf den Wasserhaushalt der Talaue wurden Szenarien entwickelt, welche Änderungen der Landnutzung sowie der Gewässergeometrie implizieren. Die Simulation des Wasserhaushalts unter jeweiligen Szenariobedingungen ermöglichte die detaillierte Analyse sich ändernder Randbedingungen auf den Gebietswasserhaushalt und auf die Austauschprozesse zwischen Grundwasser und Oberflächengewässer. Zur Untersuchung der Stickstoffmetabolik im Grundwasser der Talauenlandschaft wurde das im Modellkonzept IWAN integrierte Stofftransportmodell MT3D für das Eigeneinzugsgebiet der Havel angewandt. Dies ermöglichte eine Bilanzierung der aus dem Grundwasser des Eigeneinzugsgebiets stammenden Nitratfrachtanteile der Havel sowie von Nitratkonzentrationen im Grundwasser. Szenariensimulationen, welche verminderte Nitrateinträge aus der durchwurzelten Bodenzone annehmen, ermöglichten die Quantifizierung der Effizienz von Managementmaßnahmen und Landnutzungsänderungen in Hinblick auf die Minimierung von Einträgen in Grundwasser und Oberflächengewässer.
Ziel dieser Arbeit war es, die Stickstoff- und Phosphorprozesse im nordostdeutschen Tiefland detailliert zu untersuchen und Handlungsoptionen hinsichtlich der Landnutzung zur nachhaltigen Steuerung der Stickstoff- und Phosphoreinträge in die Fließgewässer aufzuzeigen. Als Grundvoraussetzung für die Modellierung des Nährstoffhaushaltes mussten zunächst die hydrologischen Prozesse und die Abflüsse für die Einzugsgebiete validiert werden. Dafür wurde in dieser Arbeit das ökohydrologische Modell SWIM verwendet. Die Abflussmodellierung umfasste den Zeitraum 1991 - 2000. Die Ergebnisse dazu zeigen, dass SWIM in der Lage war, die hydrologischen Prozesse in den Untersuchungsgebieten adäquat wiederzugeben. Auf der Grundlage der Modellierung des Wasserhaushaltes wurden mit SWIM die Stoffumsatzprozesse für den Zeitraum 1996 - 2000 simuliert. Um dabei besonders das Prozessgeschehen im Tiefland zu berücksichtigen, war die Erweiterung von SWIM um einen Ammonium-Pool mit dessen Umsatzprozessen erforderlich. Außerdem wurde der Prozess der Nährstoffversickerung so ergänzt, dass neben Nitrat auch Ammonium und Phosphat durch das gesamte Bodenprofil verlagert und über die Abflusskomponenten zum Gebietsauslass transportiert werden können. Mit diesen Modellerweiterungen konnten die Stickstoff und Phosphorprozesse in den Untersuchungsgebieten gut abgebildet werden. Mit dem so validierten Modell wurden weitere Anwendungen ermöglicht. Nährstoffsimulationen für den Zeitraum 1981 bis 2000 dienten der Untersuchung des abnehmenden Trends in den Nährstoffkonzentrationen der Nuthe. Die Untersuchungsergebnisse lassen deutlich erkennen, dass sich die Konzentrationen nach 1990 hauptsächlich auf Grund der Reduzierung der Einträge aus punktförmigen Quellen und Rieselfeldern verringert haben. Weitere Modellrechnungen zur Herkunft der Nährstoffe haben ergeben, dass Nitrat überwiegend aus diffusen Quellen, Ammonium und Phosphat dagegen aus punktförmigen Quellen stammen. Als besonders sensitiv auf die Modellergebnisse haben sich die Parameter zu Landnutzung und -management und die Durchwurzelungstiefe der Pflanzen herausgestellt. Abschließend wurden verschiedene Landnutzungsszenarien angewendet. Die Ergebnisse zu den Szenariorechnungen zeigen, dass fast alle vorgegebenen Landnutzungsszenarien zu einer Verringerung der Stickstoff- bzw. Phosphoremissionen führten. Die Anwendung von Szenarien, die alle relevanten Zielvorgaben und Empfehlungen zum Ressourcenschutz berücksichtigen, zeigen die größten Veränderungen.
Large Central European flood events of the past have demonstrated that flooding can affect several river basins at the same time leading to catastrophic economic and humanitarian losses that can stretch emergency resources beyond planned levels of service. For Germany, the spatial coherence of flooding, the contributing processes and the role of trans-basin floods for a national risk assessment is largely unknown and analysis is limited by a lack of systematic data, information and knowledge on past events. This study investigates the frequency and intensity of trans-basin flood events in Germany. It evaluates the data and information basis on which knowledge about trans-basin floods can be generated in order to improve any future flood risk assessment. In particu-lar, the study assesses whether flood documentations and related reports can provide a valuable data source for understanding trans-basin floods. An adaptive algorithm was developed that systematically captures trans-basin floods using series of mean daily discharge at a large number of sites of even time series length (1952-2002). It identifies the simultaneous occurrence of flood peaks based on the exceedance of an initial threshold of a 10 year flood at one location and consecutively pools all causally related, spatially and temporally lagged peak recordings at the other locations. A weighted cumulative index was developed that accounts for the spatial extent and the individual flood magnitudes within an event and allows quantifying the overall event severity. The parameters of the method were tested in a sensitivity analysis. An intensive study on sources and ways of information dissemination of flood-relevant publications in Germany was conducted. Based on the method of systematic reviews a strategic search approach was developed to identify relevant documentations for each of the 40 strongest trans-basin flood events. A novel framework for assessing the quality of event specific flood reports from a user’s perspective was developed and validated by independent peers. The framework was designed to be generally applicable for any natural hazard type and assesses the quality of a document addressing accessibility as well as representational, contextual, and intrinsic dimensions of quality. The analysis of time-series of mean daily discharge resulted in the identification of 80 trans-basin flood events within the period 1952-2002 in Germany. The set is dominated by events that were recorded in the hydrological winter (64%); 36% occurred during the summer months. The occurrence of floods is characterised by a distinct clustering in time. Dividing the study period into two sub-periods, we find an increase in the percentage of winter events from 58% in the first to 70.5% in the second sub-period. Accordingly, we find a significant increase in the number of extreme trans-basin floods in the second sub-period. A large body of 186 flood relevant documentations was identified. For 87.5% of the 40 strongest trans-basin floods in Germany at least one report has been found and for the most severe floods a substantial amount of documentation could be obtained. 80% of the material can be considered grey literature (i.e. literature not controlled by commercial publishers). The results of the quality assessment show that the majority of flood event specific reports are of a good quality, i.e. they are well enough drafted, largely accurate and objective, and contain a substantial amount of information on the sources, pathways and receptors/consequences of the floods. The inclusion of this information in the process of knowledge building for flood risk assessment is recommended. Both the results as well as the data produced in this study are openly accessible and can be used for further research. The results of this study contribute to an improved spatial risk assessment in Germany. The identified set of trans-basin floods provides the basis for an assessment of the chance that flooding occurs simultaneously at a number of sites. The information obtained from flood event documentation can usefully supplement the analysis of the processes that govern flood risk.
Climate change is one of the greatest challenges to humanity in this century, and most noticeable consequences are expected to be impacts on the water cycle – in particular the distribution and availability of water, which is fundamental for all life on Earth. In this context, it is essential to better understand where and when water is available and what processes influence variations in water storages. While estimates of the overall terrestrial water storage (TWS) variations are available from the GRACE satellites, these represent the vertically integrated signal over all water stored in ice, snow, soil moisture, groundwater and surface water bodies. Therefore, complementary observational data and hydrological models are still required to determine the partitioning of the measured signal among different water storages and to understand the underlying processes. However, the application of large-scale observational data is limited by their specific uncertainties and the incapacity to measure certain water fluxes and storages. Hydrological models, on the other hand, vary widely in their structure and process-representation, and rarely incorporate additional observational data to minimize uncertainties that arise from their simplified representation of the complex hydrologic cycle.
In this context, this thesis aims to contribute to improving the understanding of global water storage variability by combining simple hydrological models with a variety of complementary Earth observation-based data. To this end, a model-data integration approach is developed, in which the parameters of a parsimonious hydrological model are calibrated against several observational constraints, inducing GRACE TWS, simultaneously, while taking into account each data’s specific strengths and uncertainties. This approach is used to investigate 3 specific aspects that are relevant for modelling and understanding the composition of large-scale TWS variations.
The first study focusses on Northern latitudes, where snow and cold-region processes define the hydrological cycle. While the study confirms previous findings that seasonal dynamics of TWS are dominated by the cyclic accumulation and melt of snow, it reveals that inter-annual TWS variations on the contrary, are determined by variations in liquid water storages. Additionally, it is found to be important to consider the impact of compensatory effects of spatially heterogeneous hydrological variables when aggregating the contribution of different storage components over large areas. Hence, the determinants of TWS variations are scale-dependent and underlying driving mechanism cannot be simply transferred between spatial and temporal scales. These findings are supported by the second study for the global land areas beyond the Northern latitudes as well.
This second study further identifies the considerable impact of how vegetation is represented in hydrological models on the partitioning of TWS variations. Using spatio-temporal varying fields of Earth observation-based data to parameterize vegetation activity not only significantly improves model performance, but also reduces parameter equifinality and process uncertainties. Moreover, the representation of vegetation drastically changes the contribution of different water storages to overall TWS variability, emphasizing the key role of vegetation for water allocation, especially between sub-surface and delayed water storages. However, the study also identifies parameter equifinality regarding the decay of sub-surface and delayed water storages by either evapotranspiration or runoff, and thus emphasizes the need for further constraints hereof.
The third study focuses on the role of river water storage, in particular whether it is necessary to include computationally expensive river routing for model calibration and validation against the integrated GRACE TWS. The results suggest that river routing is not required for model calibration in such a global model-data integration approach, due to the larger influence other observational constraints, and the determinability of certain model parameters and associated processes are identified as issues of greater relevance. In contrast to model calibration, considering river water storage derived from routing schemes can already significantly improve modelled TWS compared to GRACE observations, and thus should be considered for model evaluation against GRACE data.
Beyond these specific findings that contribute to improved understanding and modelling of large-scale TWS variations, this thesis demonstrates the potential of combining simple modeling approaches with diverse Earth observational data to improve model simulations, overcome inconsistencies of different observational data sets, and identify areas that require further research. These findings encourage future efforts to take advantage of the increasing number of diverse global observational data.
River flooding poses a threat to numerous cities and communities all over the world. The detection, quantification and attribution of changes in flood characteristics is key to assess changes in flood hazard and help affected societies to timely mitigate and adapt to emerging risks. The Rhine River is one of the major European rivers and numerous large cities reside at its shores. Runoff from several large tributaries superimposes in the main channel shaping the complex from regime. Rainfall, snowmelt as well as ice-melt are important runoff components. The main objective of this thesis is the investigation of a possible transient merging of nival and pluvial Rhine flood regimes under global warming. Rising temperatures cause snowmelt to occur earlier in the year and rainfall to be more intense. The superposition of snowmelt-induced floods originating from the Alps with more intense rainfall-induced runoff from pluvial-type tributaries might create a new flood type with potentially disastrous consequences.
To introduce the topic of changing hydrological flow regimes, an interactive web application that enables the investigation of runoff timing and runoff season- ality observed at river gauges all over the world is presented. The exploration and comparison of a great diversity of river gauges in the Rhine River Basin and beyond indicates that river systems around the world undergo fundamental changes. In hazard and risk research, the provision of background as well as real-time information to residents and decision-makers in an easy accessible way is of great importance. Future studies need to further harness the potential of scientifically engineered online tools to improve the communication of information related to hazards and risks.
A next step is the development of a cascading sequence of analytical tools to investigate long-term changes in hydro-climatic time series. The combination of quantile sampling with moving average trend statistics and empirical mode decomposition allows for the extraction of high resolution signals and the identification of mechanisms driving changes in river runoff. Results point out that the construction and operation of large reservoirs in the Alps is an important factor redistributing runoff from summer to winter and hint at more (intense) rainfall in recent decades, particularly during winter, in turn increasing high runoff quantiles. The development and application of the analytical sequence represents a further step in the scientific quest to disentangling natural variability, climate change signals and direct human impacts.
The in-depth analysis of in situ snow measurements and the simulations of the Alpine snow cover using a physically-based snow model enable the quantification of changes in snowmelt in the sub-basin upstream gauge Basel. Results confirm previous investigations indicating that rising temperatures result in a decrease in maximum melt rates. Extending these findings to a catchment perspective, a threefold effect of rising temperatures can be identified: snowmelt becomes weaker, occurs earlier and forms at higher elevations. Furthermore, results indicate that due to the wide range of elevations in the basin, snowmelt does not occur simultaneously at all elevation, but elevation bands melt together in blocks. The beginning and end of the release of meltwater seem to be determined by the passage of warm air masses, and the respective elevation range affected by accompanying temperatures and snow availability. Following those findings, a hypothesis describing elevation-dependent compensation effects in snowmelt is introduced: In a warmer world with similar sequences of weather conditions, snowmelt is moved upward to higher elevations, i.e., the block of elevation bands providing most water to the snowmelt-induced runoff is located at higher elevations. The movement upward the elevation range makes snowmelt in individual elevation bands occur earlier. The timing of the snowmelt-induced runoff, however, stays the same. Meltwater from higher elevations, at least partly, replaces meltwater from elevations below.
The insights on past and present changes in river runoff, snow covers and underlying mechanisms form the basis of investigations of potential future changes in Rhine River runoff. The mesoscale Hydrological Model (mHM) forced with an ensemble of climate projection scenarios is used to analyse future changes in streamflow, snowmelt, precipitation and evapotranspiration at 1.5, 2.0 and
3.0 ◦ C global warming. Simulation results suggest that future changes in flood characteristics in the Rhine River Basin are controlled by increased precipitation amounts on the one hand, and reduced snowmelt on the other hand. Rising temperatures deplete seasonal snowpacks. At no time during the year, a warming climate results in an increase in the risk of snowmelt-driven flooding. Counterbalancing effects between snowmelt and precipitation often result in only little and transient changes in streamflow peaks. Although, investigations point at changes in both rainfall and snowmelt-driven runoff, there are no indications of a transient merging of nival and pluvial Rhine flood regimes due to climate warming. Flooding in the main tributaries of the Rhine, such as the Moselle River, as well as the High Rhine is controlled by both precipitation and snowmelt. Caution has to be exercised labelling sub-basins such as the Moselle catchment as purely pluvial-type or the Rhine River Basin at Basel as purely nival-type. Results indicate that this (over-) simplifications can entail misleading assumptions with regard to flood-generating mechanisms and changes in flood hazard. In the framework of this thesis, some progress has been made in detecting, quantifying and attributing past, present and future changes in Rhine flow/flood characteristics. However, further studies are necessary to pin down future changes in the flood genesis of Rhine floods, particularly very rare events.
Assessing the impact of global change on hydrological systems is one of the greatest hydrological challenges of our time. Changes in land cover, land use, and climate have an impact on water quantity, quality, and temporal availability. There is a widespread consensus that, given the far-reaching effects of global change, hydrological systems can no longer be viewed as static in their structure; instead, they must be regarded as entire ecosystems, wherein hydrological processes interact and coevolve with biological, geomorphological, and pedological processes. To accurately predict the hydrological response under the impact of global change, it is essential to understand this complex coevolution. The knowledge of how hydrological processes, in particular the formation of subsurface (preferential) flow paths, evolve within this coevolution and how they feed back to the other processes is still very limited due to a lack of observational data.
At the hillslope scale, this intertwined system of interactions is known as the hillslope feedback cycle. This thesis aims to enhance our understanding of the hillslope feedback cycle by studying the coevolution of hillslope structure and hillslope hydrological response. Using chronosequences of moraines in two glacial forefields developed from siliceous and calcareous glacial till, the four studies shed light on the complex coevolution of hydrological, biological, and structural hillslope properties, as well as subsurface hydrological flow paths over an evolutionary period of 10 millennia in these two contrasting geologies. The findings indicate that the contrasting properties of siliceous and calcareous parent materials lead
to variations in soil structure, permeability, and water storage. As a result, different plant species and vegetation types are favored on siliceous versus calcareous parent material, leading to diverse ecosystems with distinct hydrological dynamics. The siliceous parent material was found to show a higher activity level in driving the coevolution. The soil pH resulting from parent material weathering emerges as a crucial factor, influencing vegetation development, soil formation, and consequently, hydrology. The acidic weathering of the siliceous parent material favored the accumulation of organic matter, increasing the soils’ water storage capacity and attracting acid-loving shrubs, which further promoted organic matter accumulation and ultimately led to podsolization after 10 000 years. Tracer experiments revealed that the subsurface flow path evolution was influenced by soil and vegetation development, and vice versa. Subsurface flow paths changed from vertical, heterogeneous matrix flow to finger-like flow paths over a few hundred years, evolving into macropore flow, water storage, and lateral subsurface flow after several thousand years. The changes in flow paths among younger age classes were driven by weathering processes altering soil structure, as well as by vegetation development and root activity. In the older age
class, the transition to more water storage and lateral flow was attributed to substantial organic matter accumulation and ongoing podsolization. The rapid vertical water transport in the finger-like flow paths, along with the conductive sandy material, contributed to podsolization and thus to the shift in the hillslope hydrological response.
In contrast, the calcareous site possesses a high pH buffering capacity, creating a neutral to basic environment with relatively low accumulation of dead organic matter, resulting in a lower water storage capacity and the establishment of predominantly grass vegetation. The coevolution was found to be less dynamic over the millennia. Similar to the siliceous site, significant changes in subsurface flow paths occurred between the young age classes. However, unlike the siliceous site, the subsurface flow paths at the calcareous site only altered in shape and not in direction. Tracer experiments showed that flow paths changed from vertical, heterogeneous matrix flow to vertical, finger-like flow paths after a few hundred to thousands of years, which was driven by root activities and weathering processes. Despite having a finer soil texture, water storage at the calcareous site was significantly lower than at the siliceous site, and water transport remained primarily rapid and vertical, contributing to the flourishing of grass vegetation.
The studies elucidated that changes in flow paths are predominantly shaped by the characteristics of the parent material and its weathering products, along with their complex interactions with initial water flow paths and vegetation development. Time, on the other hand, was not found to be a primary factor in describing the evolution of the hydrological response. This thesis makes a valuable contribution to closing the gap in the observations of the coevolution of hydrological processes within the hillslope feedback cycle, which is important to improve predictions of hydrological processes in changing landscapes. Furthermore, it emphasizes the importance of interdisciplinary studies in addressing the hydrological challenges arising from global change.
Casualties and damages from urban pluvial flooding are increasing. Triggered by short, localized, and intensive rainfall events, urban pluvial floods can occur anywhere, even in areas without a history of flooding. Urban pluvial floods have relatively small temporal and spatial scales. Although cumulative losses from urban pluvial floods are comparable, most flood risk management and mitigation strategies focus on fluvial and coastal flooding. Numerical-physical-hydrodynamic models are considered the best tool to represent the complex nature of urban pluvial floods; however, they are computationally expensive and time-consuming. These sophisticated models make large-scale analysis and operational forecasting prohibitive. Therefore, it is crucial to evaluate and benchmark the performance of other alternative methods.
The findings of this cumulative thesis are represented in three research articles. The first study evaluates two topographic-based methods to map urban pluvial flooding, fill–spill–merge (FSM) and topographic wetness index (TWI), by comparing them against a sophisticated hydrodynamic model. The FSM method identifies flood-prone areas within topographic depressions while the TWI method employs maximum likelihood estimation to calibrate a TWI threshold (τ) based on inundation maps from the 2D hydrodynamic model. The results point out that the FSM method outperforms the TWI method. The study highlights then the advantage and limitations of both methods.
Data-driven models provide a promising alternative to computationally expensive hydrodynamic models. However, the literature lacks benchmarking studies to evaluate the different models' performance, advantages and limitations. Model transferability in space is a crucial problem. Most studies focus on river flooding, likely due to the relative availability of flow and rain gauge records for training and validation. Furthermore, they consider these models as black boxes. The second study uses a flood inventory for the city of Berlin and 11 predictive features which potentially indicate an increased pluvial flooding hazard to map urban pluvial flood susceptibility using a convolutional neural network (CNN), an artificial neural network (ANN) and the benchmarking machine learning models random forest (RF) and support vector machine (SVM). I investigate the influence of spatial resolution on the implemented models, the models' transferability in space and the importance of the predictive features. The results show that all models perform well and the RF models are superior to the other models within and outside the training domain. The models developed using fine spatial resolution (2 and 5 m) could better identify flood-prone areas. Finally, the results point out that aspect is the most important predictive feature for the CNN models, and altitude is for the other models.
While flood susceptibility maps identify flood-prone areas, they do not represent flood variables such as velocity and depth which are necessary for effective flood risk management. To address this, the third study investigates data-driven models' transferability to predict urban pluvial floodwater depth and the models' ability to enhance their predictions using transfer learning techniques. It compares the performance of RF (the best-performing model in the previous study) and CNN models using 12 predictive features and output from a hydrodynamic model. The findings in the third study suggest that while CNN models tend to generalise and smooth the target function on the training dataset, RF models suffer from overfitting. Hence, RF models are superior for predictions inside the training domains but fail outside them while CNN models could control the relative loss in performance outside the training domains. Finally, the CNN models benefit more from transfer learning techniques than RF models, boosting their performance outside training domains.
In conclusion, this thesis has evaluated both topographic-based methods and data-driven models to map urban pluvial flooding. However, further studies are crucial to have methods that completely overcome the limitation of 2D hydrodynamic models.
Flooding is a vast problem in many parts of the world, including Europe. It occurs mainly due to extreme weather conditions (e.g. heavy rainfall and snowmelt) and the consequences of flood events can be devastating. Flood risk is mainly defined as a combination of the probability of an event and its potential adverse impacts. Therefore, it covers three major dynamic components: hazard (physical characteristics of a flood event), exposure (people and their physical environment that being exposed to flood), and vulnerability (the elements at risk). Floods are natural phenomena and cannot be fully prevented. However, their risk can be managed and mitigated. For a sound flood risk management and mitigation, a proper risk assessment is needed. First of all, this is attained by a clear understanding of the flood risk dynamics. For instance, human activity may contribute to an increase in flood risk. Anthropogenic climate change causes higher intensity of rainfall and sea level rise and therefore an increase in scale and frequency of the flood events. On the other hand, inappropriate management of risk and structural protection measures may not be very effective for risk reduction. Additionally, due to the growth of number of assets and people within the flood-prone areas, risk increases. To address these issues, the first objective of this thesis is to perform a sensitivity analysis to understand the impacts of changes in each flood risk component on overall risk and further their mutual interactions. A multitude of changes along the risk chain are simulated by regional flood model (RFM) where all processes from atmosphere through catchment and river system to damage mechanisms are taken into consideration. The impacts of changes in risk components are explored by plausible change scenarios for the mesoscale Mulde catchment (sub-basin of the Elbe) in Germany.
A proper risk assessment is ensured by the reasonable representation of the real-world flood event. Traditionally, flood risk is assessed by assuming homogeneous return periods of flood peaks throughout the considered catchment. However, in reality, flood events are spatially heterogeneous and therefore traditional assumption misestimates flood risk especially for large regions. In this thesis, two different studies investigate the importance of spatial dependence in large scale flood risk assessment for different spatial scales. In the first one, the “real” spatial dependence of return period of flood damages is represented by continuous risk modelling approach where spatially coherent patterns of hydrological and meteorological controls (i.e. soil moisture and weather patterns) are included. Further the risk estimations under this modelled dependence assumption are compared with two other assumptions on the spatial dependence of return periods of flood damages: complete dependence (homogeneous return periods) and independence (randomly generated heterogeneous return periods) for the Elbe catchment in Germany. The second study represents the “real” spatial dependence by multivariate dependence models. Similar to the first study, the three different assumptions on the spatial dependence of return periods of flood damages are compared, but at national (United Kingdom and Germany) and continental (Europe) scales. Furthermore, the impacts of the different models, tail dependence, and the structural flood protection level on the flood risk under different spatial dependence assumptions are investigated.
The outcomes of the sensitivity analysis framework suggest that flood risk can vary dramatically as a result of possible change scenarios. The risk components that have not received much attention (e.g. changes in dike systems and in vulnerability) may mask the influence of climate change that is often investigated component.
The results of the spatial dependence research in this thesis further show that the damage under the false assumption of complete dependence is 100 % larger than the damage under the modelled dependence assumption, for the events with return periods greater than approximately 200 years in the Elbe catchment. The complete dependence assumption overestimates the 200-year flood damage, a benchmark indicator for the insurance industry, by 139 %, 188 % and 246 % for the UK, Germany and Europe, respectively. The misestimation of risk under different assumptions can vary from upstream to downstream of the catchment. Besides, tail dependence in the model and flood protection level in the catchments can affect the risk estimation and the differences between different spatial dependence assumptions.
In conclusion, the broader consideration of the risk components, which possibly affect the flood risk in a comprehensive way, and the consideration of the spatial dependence of flood return periods are strongly recommended for a better understanding of flood risk and consequently for a sound flood risk management and mitigation.
The spread of antibiotic-resistant bacteria poses a globally increasing threat to public health care. The excessive use of antibiotics in animal husbandry can develop resistances in the stables. Transmission through direct contact with animals and contamination of food has already been proven. The excrements of the animals combined with a binding material enable a further potential path of spread into the environment, if they are used as organic manure in agricultural landscapes. As most of the airborne bacteria are attached to particulate matter, the focus of the work will be the atmospheric dispersal via the dust fraction.
Field measurements on arable lands in Brandenburg, Germany and wind erosion studies in a wind tunnel were conducted to investigate the risk of a potential atmospheric dust-associated spread of antibiotic-resistant bacteria from poultry manure fertilized agricultural soils. The focus was to (i) characterize the conditions for aerosolization and (ii) qualify and quantify dust emissions during agricultural operations and wind erosion.
PM10 (PM, particulate matter with an aerodynamic diameter smaller than 10 µm) emission factors and bacterial fluxes for poultry manure application and incorporation have not been previously reported before. The contribution to dust emissions depends on the water content of the manure, which is affected by the manure pretreatment (fresh, composted, stored, dried), as well as by the intensity of manure spreading from the manure spreader. During poultry manure application, PM10 emission ranged between 0.05 kg ha-1 and 8.37 kg ha-1. For comparison, the subsequent land preparation contributes to 0.35 – 1.15 kg ha-1 of PM10 emissions. Manure particles were still part of dust emissions but they were accounted to be less than 1% of total PM10 emissions due to the dilution of poultry manure in the soil after manure incorporation. Bacterial emissions of fecal origin were more relevant during manure application than during the subsequent manure incorporation, although PM10 emissions of manure incorporation were larger than PM10 emissions of manure application for the non-dried manure variants.
Wind erosion leads to preferred detachment of manure particles from sandy soils, when poultry manure has been recently incorporated. Sorting effects were determined between the low-density organic particles of manure origin and the soil particles of mineral origin close above the threshold of 7 m s-1. In dependence to the wind speed, potential erosion rates between 101 and 854 kg ha-1 were identified, if 6 t ha-1 of poultry manure were applied. Microbial investigation showed that manure bacteria got detached more easily from the soil surface during wind erosion, due to their attachment on manure particles.
Although antibiotic-resistant bacteria (ESBL-producing E. coli) were still found in the poultry barns, no further contamination could be detected with them in the manure, fertilized soils or in the dust generated by manure application, land preparation or wind erosion. Parallel studies of this project showed that storage of poultry manure for a few days (36 – 72 h) is sufficient to inactivate ESBL-producing E. coli. Further antibiotic-resistant bacteria, i.e. MRSA and VRE, were only found sporadically in the stables and not at all in the dust. Therefore, based on the results of this work, the risk of a potential infection by dust-associated antibiotic-resistant bacteria can be considered as low.
Forests are a key resource serving a multitude of functions such as providing income to forest owners, supplying industries with timber, protecting water resources, and maintaining biodiversity. Recently much attention has been given to the role of forests in the global carbon cycle and their management for increased carbon sequestration as a possible mitigation option against climate change. Furthermore, the use of harvested wood can contribute to the reduction of atmospheric carbon through (i) carbon sequestration in wood products, (ii) the substitution of non-wood products with wood products, and (iii) through the use of wood as a biofuel to replace fossil fuels. Forest resource managers are challenged by the task to balance these multiple while simultaneously meeting economic requirements and taking into consideration the demands of stakeholder groups. Additionally, risks and uncertainties with regard to uncontrollable external variables such as climate have to be considered in the decision making process. In this study a scientific stakeholder dialogue with forest-related stakeholder groups in the Federal State of Brandenburg was accomplished. The main results of this dialogue were the definition of major forest functions (carbon sequestration, groundwater recharge, biodiversity, and timber production) and priority setting among them by the stakeholders using the pair-wise comparison technique. The impact of different forest management strategies and climate change scenarios on the main functions of forest ecosystems were evaluated at the Kleinsee management unit in south-east Brandenburg. Forest management strategies were simulated over 100 years using the forest growth model 4C and a wood product model (WPM). A current climate scenario and two climate change scenarios based on global circulation models (GCMs) HadCM2 and ECHAM4 were applied. The climate change scenario positively influenced stand productivity, carbon sequestration, and income. The impact on the other forest functions was small. Furthermore, the overall utility of forest management strategies were compared under the priority settings of stakeholders by a multi-criteria analysis (MCA) method. Significant differences in priority setting and the choice of an adequate management strategy were found for the environmentalists on one side and the more economy-oriented forest managers of public and private owned forests on the other side. From an ecological perspective, a conservation strategy would be preferable under all climate scenarios, but the business as usual management would also fit the expectations under the current climate. In contrast, a forest manager in public-owned forests or a private forest owner would prefer a management strategy with an intermediate thinning intensity and a high share of pine stands to enhance income from timber production while maintaining the other forest functions. The analysis served as an example for the combined application of simulation tools and a MCA method for the evaluation of management strategies under multi-purpose and multi-user settings with changing climatic conditions. Another focus was set on quantifying the overall effect of forest management on carbon sequestration in the forest sector and the wood industry sector plus substitution effects. To achieve this objective, the carbon emission reduction potential of material and energy substitution (Smat and Sen) was estimated based on a literature review. On average, for each tonne of dry wood used in a wood product substituting a non-wood product, 0.71 fewer tonnes of fossil carbon are emitted into to the atmosphere. Based on Smat and Sen, the calculation of the carbon emission reduction through substitution was implemented in the WPM. Carbon sequestration and substitution effects of management strategies were simulated at three local scales using the WPM and the forest growth models 4C (management unit level) or EFISCEN (federal state of Brandenburg and Germany). An investigation was conducted on the influence of uncertainties in the initialisation of the WPM, Smat, and basic conditions of the wood product sector on carbon sequestration. Results showed that carbon sequestration in the wood industry sector plus substitution effects exceeded sequestration in the forest sector. In contrast to the carbon pools in the forest sector, which acted as sink or source, the substitution effects continually reduced carbon emission as long as forests are managed and timber is harvested. The main climate protection function was investigated for energy substitution which accounted for about half of the total carbon sequestration, followed by carbon storage in landfills. In Germany, the absolute annual carbon sequestration in the forest and wood industry sector plus substitution effects was 19.9 Mt C. Over 50 years the wood industry sector contributed 70% of the total carbon sequestration plus substitution effects.
This thesis aims to quantify the human impact on the natural resource water at the landscape scale. The drivers in the federal state of Brandenburg (Germany), the area under investigation, are land-use changes induced by policy decisions at European and federal state level. The water resources of the federal state are particularly sensitive to changes in land-use due to low precipitation rates in the summer combined with sandy soils and high evapotranspiration rates. Key elements in landscape hydrology are forests because of their unique capacity to transport water from the soil to the atmosphere. Given these circumstances, decisions made at any level of administration that may have effects on the forest sector in the state are critical in relation to the water cycle. It is therefore essential to evaluate any decision that may change forest area and structure in such a sensitive region. Thus, as a first step, it was necessary to develop and implement a model able to simulate possible interactions and feedbacks between forested surfaces and the hydrological cycle at the landscape scale. The result is a model for simulating the hydrological properties of forest stands based on a robust computation of the temporal and spatial LAI (leaf area index) dynamics. The approach allows the simulation of all relevant hydrological processes with a low parameter demand. It includes the interception of precipitation and transpiration of forest stands with and without groundwater in the rooting zone. The model also considers phenology, biomass allocation, as well as mortality and simple management practices. It has been implemented as a module in the eco-hydrological model SWIM (Soil and Water Integrated Model). This model has been tested in two pre-studies to verify the applicability of its hydrological process description for the hydrological conditions typical for the state. The newly implemented forest module has been tested for Scots Pine (Pinus sylvestris) and in parts for Common Oak (Quercus robur and Q. petraea) in Brandenburg. For Scots Pine the results demonstrate a good simulation of annual biomass increase and LAI in addition to the satisfactory simulation of litter production. A comparison of the simulated and measured data of the May sprout for Scots pine and leaf unfolding for Oak, as well as the evaluation against daily transpiration measurements for Scots Pine, does support the applicability of the approach. The interception of precipitation has also been simulated and compared with weekly observed data for a Scots Pine stand which displays satisfactory results in both the vegetation periods and annual sums. After the development and testing phase, the model is used to analyse the effects of two scenarios. The first scenario is an increase in forest area on abandoned agricultural land that is triggered by a decrease in European agricultural production support. The second one is a shift in species composition from predominant Scots Pine to Common Oak that is based on decisions of the regional forestry authority to support a more natural species composition. The scenario effects are modelled for the federal state of Brandenburg on a 50m grid utilising spatially explicit land-use patterns. The results, for the first scenario, suggest a negative impact of an increase in forest area (9.4% total state area) on the regional water balance, causing an increase in mean long-term annual evapotranspiration of 3.7% at 100% afforestation when compared to no afforestation. The relatively small annual change conceals a much more pronounced seasonal effect of a mean long-term evapotranspiration increase by 25.1% in the spring causing a pronounced reduction in groundwater recharge and runoff. The reduction causes a lag effect that aggravates the scarcity of water resources in the summer. In contrast, in the second scenario, a change in species composition in existing forests (29.2% total state area) from predominantly Scots Pine to Common Oak decreases the long-term annual mean evapotranspiration by 3.4%, accompanied by a much weaker, but apparent, seasonal pattern. Both scenarios exhibit a high spatial heterogeneity because of the distinct natural conditions in the different regions of the state. Areas with groundwater levels near the surface are particularly sensitive to changes in forest area and regions with relatively high proportion of forest respond strongly to the change in species composition. In both cases this regional response is masked by a smaller linear mean effect for the total state area. Two critical sources of uncertainty in the model results have been investigated. The first one originates from the model calibration parameters estimated in the pre-study for lowland regions, such as the federal state. The combined effect of the parameters, when changed within their physical meaningful limits, unveils an overestimation of the mean water balance by 1.6%. However, the distribution has a wide spread with 14.7% for the 90th percentile and -9.9% for the 10th percentile. The second source of uncertainty emerges from the parameterisation of the forest module. The analysis exhibits a standard deviation of 0.6 % over a ten year period in the mean of the simulated evapotranspiration as a result of variance in the key forest parameters. The analysis suggests that the combined uncertainty in the model results is dominated by the uncertainties of calibration parameters. Therefore, the effect of the first scenario might be underestimated because the calculated increase in evapotranspiration is too small. This may lead to an overestimation of the water balance towards runoff and groundwater recharge. The opposite can be assumed for the second scenario in which the decrease in evapotranspiration might be overestimated.
The sustainability of agro-bioenergy systems is dependent on many factors, some local or regional in implementation, some others global in nature. This study assessed the effects of often ignored local and regional factors (e.g. alternative agronomic factor options, alternative agricultural production systems, alternative biomass flows, alternative conversion technologies etc. The results from this study suggests that key to enhancing the energy efficiency (and by extension the sustainability) of agro-bioenergy systems is paying attention to local and regional factors such as biomass conversion technology, alternative agronomic factor options, alternative agricultural production systems and available biomass flows.
Understanding the distribution of species is fundamental for biodiversity conservation, ecosystem management, and increasingly also for climate impact assessment. The presence of a species in a given site depends on physiological limitations (abiotic factors), interactions with other species (biotic factors), migratory or dispersal processes (site accessibility) as well as the continuing
effects of past events, e.g. disturbances (site legacy). Existing approaches to predict species distributions either (i) correlate observed species occurrences with environmental variables describing abiotic limitations, thus ignoring biotic interactions, dispersal and legacy effects (statistical species distribution model, SDM); or (ii) mechanistically model the variety of processes determining species distributions (process-based model, PBM). SDMs are widely used due to their easy applicability and ability to handle varied data qualities. But they fail to reproduce the dynamic response of species distributions to changing conditions. PBMs are expected to be superior in this respect, but they need very specific data unavailable for many species, and are often more complex and require more computational effort. More recently, hybrid models link the two approaches to combine their respective strengths.
In this thesis, I apply and compare statistical and process-based approaches to predict species distributions, and I discuss their respective limitations, specifically for applications in changing environments. Detailed analyses of SDMs for boreal tree species in Finland reveal that nonclimatic predictors - edaphic properties and biotic interactions - are important limitations at the treeline, contesting the assumption of unrestricted, climatically induced range expansion. While the estimated SDMs are successful within their training data range, spatial and temporal model transfer fails. Mapping and comparing sampled predictor space among data subsets identifies spurious extrapolation as the plausible explanation for limited model transferability. Using these findings, I analyze the limited success of an established PBM (LPJ-GUESS) applied to the same problem. Examination of process representation and parameterization in the PBM identifies implemented processes to adjust (competition between species, disturbance) and missing processes that are crucial in boreal forests (nutrient limitation, forest management). Based on climatic correlations shifting over time, I stress the restricted temporal transferability of bioclimatic limits used in LPJ-GUESS and similar PBMs. By critically assessing the performance of SDM and PBM in this application, I demonstrate the importance of understanding the limitations of the
applied methods.
As a potential solution, I add a novel approach to the repertoire of existing hybrid models. By simulation experiments with an individual-based PBM which reproduces community dynamics resulting from biotic factors, dispersal and legacy effects, I assess the resilience of coastal vegetation to abrupt hydrological changes. According to the results of the resilience analysis, I then modify temporal SDM predictions, thereby transferring relevant process detail from PBM to
SDM. The direction of knowledge transfer from PBM to SDM avoids disadvantages of current hybrid models and increases the applicability of the resulting model in long-term, large-scale applications. A further advantage of the proposed framework is its flexibility, as it is readily extended to other model types, disturbance definitions and response characteristics.
Concluding, I argue that we already have a diverse range of promising modelling tools at hand, which can be refined further. But most importantly, they need to be applied more thoughtfully. Bearing their limitations in mind, combining their strengths and openly reporting underlying assumptions and uncertainties is the way forward.
Spatiotemporal variations of key air pollutants and greenhouse gases in the Himalayan foothills
(2021)
South Asia is a rapidly developing, densely populated and highly polluted region that is facing the impacts of increasing air pollution and climate change, and yet it remains one of the least studied regions of the world scientifically. In recognition of this situation, this thesis focuses on studying (i) the spatial and temporal variation of key greenhouse gases (CO2 and CH4) and air pollutants (CO and O3) and (ii) the vertical distribution of air pollutants (PM, BC) in the foothills of the Himalaya. Five sites were selected in the Kathmandu Valley, the capital region of Nepal, along with two sites outside of the valley in the Makawanpur and Kaski districts, and conducted measurements during the period of 2013-2014 and 2016. These measurements are analyzed in this thesis.
The CO measurements at multiple sites in the Kathmandu Valley showed a clear diurnal cycle: morning and evening levels were high, with an afternoon dip. There are slight differences in the diurnal cycles of CO2 and CH4, with the CO2 and CH4 mixing ratios increasing after the afternoon dip, until the morning peak the next day. The mixing layer height (MLH) of the nocturnal stable layer is relatively constant (~ 200 m) during the night, after which it transitions to a convective mixing layer during the day and the MLH increases up to 1200 m in the afternoon. Pollutants are thus largely trapped in the valley from the evening until sunrise the following day, and the concentration of pollutants increases due to emissions during the night. During afternoon, the pollutants are diluted due to the circulation by the valley winds after the break-up of the mixing layer. The major emission sources of GHGs and air pollutants in the valley are transport sector, residential cooking, brick kilns, trash burning, and agro-residue burning. Brick industries are influential in the winter and pre-monsoon season. The contribution of regional forest fires and agro-residue burning are seen during the pre-monsoon season. In addition, relatively higher CO values were also observed at the valley outskirts (Bhimdhunga and Naikhandi), which indicates the contribution of regional emission sources. This was also supported by the presence of higher concentrations of O3 during the pre-monsoon season.
The mixing ratios of CO2 (419.3 ±6.0 ppm) and CH4 (2.192 ±0.066 ppm) in the valley were much higher than at background sites, including the Mauna Loa observatory (CO2: 396.8 ± 2.0 ppm, CH4:1.831 ± 0.110 ppm) and Waligaun (CO2: 397.7 ± 3.6 ppm, CH4: 1.879 ± 0.009 ppm), China, as well as at an urban site Shadnagar (CH4: 1.92 ± 0.07 ppm) in India.
The daily 8 hour maximum O3 average in the Kathmandu Valley exceeds the WHO recommended value during more than 80% of the days during the pre-monsoon period, which represents a significant risk for human health and ecosystems in the region. Moreover, in the measurements of the vertical distribution of particulate matter, which were made using an ultralight aircraft, and are the first of their kind in the region, an elevated polluted layer at around ca. 3000 m asl. was detected over the Pokhara Valley. The layer could be associated with the large-scale regional transport of pollution. These contributions towards understanding the distributions of key air pollutants and their main sources will provide helpful information for developing management plans and policies to help reduce the risks for the millions of people living in the region.
As land-cover conversion continues to expand into ever more remote areas in the humid tropics, montane rainforests are increasingly threatened. In the south Ecuadorian Andes, they are not only subject to man-made disturbances but also to naturally occurring landslides. I was interested in the impact of this ecosystem dynamics on a key parameter of the hydrologic cycle, the soil saturated hydraulic conductivity (synonym: permeability; Ks from here on), because it is a sensitive indicator for soil disturbances. My general objective was to quantify the effects of the regional natural and human disturbances on the saturated hydraulic conductivity and to describe the resulting spatial-temporal patterns. The main hypotheses were: 1) disturbances cause an apparent displacement of the less permeable soil layer towards the surface, either due to a loss of the permeable surface soil after land-sliding, or as a consequence of the surface soil compaction under cattle pastures; 2) ‘recovery’ from disturbance, either because of landslide re-vegetation or because of secondary succession after pasture abandonment, involves an apparent displacement of the less permeable layer back towards the original depth an 3) disturbances cause a simplification of the Ks spatial structure, i.e. the spatially dependent random variation diminishes; the subsequent recovery entails the re-establishment of the original structure. In my first study, I developed a synthesis of recent geostatistical research regarding its applicability to soil hydraulic data, including exploratory data analysis and variogram estimation techniques; I subsequently evaluated the results in terms of spatial prediction uncertainty. Concerning the exploratory data analysis, my main results were: 1) Gaussian uni- and bivariate distributions of the log-transformed data; 2) the existence of significant local trends; 3) no need for robust estimation; 4) no anisotropic variation. I found partly considerable differences in covariance parameters resulting from different variogram estimation techniques, which, in the framework of spatial prediction, were mainly reflected in the spatial connectivity of the Ks-field. Ignoring the trend component and an arbitrary use of robust estimators, however, would have the most severe consequences in this respect. Regarding variogram modeling, I encouraged restricted maximum likelihood estimation because of its accuracy and independence on the selected lags needed for experimental variograms. The second study dealt with the Ks spatial-temporal pattern in the sequences of natural and man-made disturbances characteristic for the montane rainforest study area. To investigate the disturbance effects both on global means and the spatial structure of Ks, a combined design-and model-based sampling approach was used for field-measurements at soil depths of 12.5, 20, and 50 cm (n=30-150/depth) under landslides of different ages (2 and 8 years), under actively grazed pasture, fallows following pasture abandonment (2 to 25 years of age), and under natural forest. Concerning global means, our main findings were 1) global means of the soil permeability generally decrease with increasing soil depth; 2) no significant Ks differences can be observed among landslides and compared to the natural forest; 3) a distinct permeability decrease of two orders of magnitude occurs after forest conversion to pasture at shallow soil depths, and 4) the slow regeneration process after pasture abandonment requires at least one decade. Regarding the Ks spatial structure, we found that 1) disturbances affect the Ks spatial structure in the topsoil, and 2) the largest differences in spatial patterns are associated with the subsoil permeability. In summary, the regional landslide activity seems to affect soil hydrology to a marginal extend only, which is in contrast to the pronounced drop of Ks after forest conversion. We used this spatial-temporal information combined with local rain intensities to assess the partitioning of rainfall into vertical and lateral flowpaths under undisturbed, disturbed, and regenerating land-cover types in the third study. It turned out that 1) the montane rainforest is characterized by prevailing vertical flowpaths in the topsoil, which can switch to lateral directions below 20 cm depth for a small number of rain events, which may, however, transport a high portion of the annual runoff; 2) similar hydrological flowpaths occur under the landslides except for a somewhat higher probability of impermeable layer formation in the topsoil of a young landslide, and 3) pronounced differences in runoff components can be observed for the human disturbance sequence involving the development of near-surface impeding layers for 24, 44, and 8 % of rain events for pasture, a two-year-old fallow, and a ten-year-old fallow, respectively.
This PhD thesis presents the spatio-temporal distribution of terrestrial carbon fluxes for the time period of 1982 to 2002 simulated by a combination of the process-based dynamic global vegetation model LPJ and a 21-year time series of global AVHRR-fPAR data (fPAR – fraction of photosynthetically active radiation). Assimilation of the satellite data into the model allows improved simulations of carbon fluxes on global as well as on regional scales. As it is based on observed data and includes agricultural regions, the model combined with satellite data produces more realistic carbon fluxes of net primary production (NPP), soil respiration, carbon released by fire and the net land-atmosphere flux than the potential vegetation model. It also produces a good fit to the interannual variability of the CO2 growth rate. Compared to the original model, the model with satellite data constraint produces generally smaller carbon fluxes than the purely climate-based stand-alone simulation of potential natural vegetation, now comparing better to literature estimates. The lower net fluxes are a result of a combination of several effects: reduction in vegetation cover, consideration of human influence and agricultural areas, an improved seasonality, changes in vegetation distribution and species composition. This study presents a way to assess terrestrial carbon fluxes and elucidates the processes contributing to interannual variability of the terrestrial carbon exchange. Process-based terrestrial modelling and satellite-observed vegetation data are successfully combined to improve estimates of vegetation carbon fluxes and stocks. As net ecosystem exchange is the most interesting and most sensitive factor in carbon cycle modelling and highly uncertain, the presented results complementary contribute to the current knowledge, supporting the understanding of the terrestrial carbon budget.
Water quality in river systems is of growing concern due to rising anthropogenic pressures and climate change. Mitigation efforts have been placed under the guidelines of different governance conventions during last decades (e.g., the Water Framework Directive in Europe). Despite significant improvement through relatively straightforward measures, the environmental status has likely reached a plateau. A higher spatiotemporal accuracy of catchment nitrate modeling is, therefore, needed to identify critical source areas of diffuse nutrient pollution (especially for nitrate) and to further guide implementation of spatially differentiated, cost-effective mitigation measures. On the other hand, the emerging high-frequency sensor monitoring upgrades the monitoring resolution to the time scales of biogeochemical processes and enables more flexible monitoring deployments under varying conditions. The newly available information offers new prospects in understanding nitrate spatiotemporal dynamics. Formulating such advanced process understanding into catchment models is critical for model further development and environmental status evaluation. This dissertation is targeting on a comprehensive analysis of catchment and in-stream nitrate dynamics and is aiming to derive new insights into their spatial and temporal variabilities through the new fully distributed model development and the new high-frequency data.
Firstly, a new fully distributed, process-based catchment nitrate model (the mHM-Nitrate model) is developed based on the mesoscale Hydrological Model (mHM) platform. Nitrate process descriptions are adopted from the Hydrological Predictions for the Environment (HYPE), with considerable improved implementations. With the multiscale grid-based discretization, mHM-Nitrate balances the spatial representation and the modeling complexity. The model has been thoughtfully evaluated in the Selke catchment (456 km2), central Germany, which is characterized by heterogeneous physiographic conditions. Results show that the model captures well the long-term discharge and nitrate dynamics at three nested gauging stations. Using daily nitrate-N observations, the model is also validated in capturing short-term fluctuations due to changes in runoff partitioning and spatial contribution during flooding events. By comparing the model simulations with the values reported in the literature, the model is capable of providing detailed and reliable spatial information of nitrate concentrations and fluxes. Therefore, the model can be taken as a promising tool for environmental scientists in advancing environmental modeling research, as well as for stakeholders in supporting their decision-making, especially for spatially differentiated mitigation measures.
Secondly, a parsimonious approach of regionalizing the in-stream autotrophic nitrate uptake is proposed using high-frequency data and further integrated into the new mHM-Nitrate model. The new regionalization approach considers the potential uptake rate (as a general parameter) and effects of above-canopy light and riparian shading (represented by global radiation and leaf area index data, respectively). Multi-parameter sensors have been continuously deployed in a forest upstream reach and an agricultural downstream reach of the Selke River. Using the continuous high-frequency data in both streams, daily autotrophic uptake rates (2011-2015) are calculated and used to validate the regionalization approach. The performance and spatial transferability of the approach is validated in terms of well-capturing the distinct seasonal patterns and value ranges in both forest and agricultural streams. Integrating the approach into the mHM-Nitrate model allows spatiotemporal variability of in-stream nitrate transport and uptake to be investigated throughout the river network.
Thirdly, to further assess the spatial variability of catchment nitrate dynamics, for the first time the fully distributed parameterization is investigated through sensitivity analysis. Sensitivity results show that parameters of soil denitrification, in-stream denitrification and in-stream uptake processes are the most sensitive parameters throughout the Selke catchment, while they all show high spatial variability, where hot-spots of parameter sensitivity can be explicitly identified. The Spearman rank correlation is further analyzed between sensitivity indices and multiple catchment factors. The correlation identifies that the controlling factors vary spatially, reflecting heterogeneous catchment responses in the Selke catchment. These insights are, therefore, informative in informing future parameter regionalization schemes for catchment water quality models. In addition, the spatial distributions of parameter sensitivity are also influenced by the gauging information that is being used for sensitivity evaluation. Therefore, an appropriate monitoring scheme is highly recommended to truly reflect the catchment responses.
Sicherung und Entwicklung von Böden und ihren Funktionen in Niederungen durch Naturschutzmaßnahmen
(2007)
Mit dem 1999 in Kraft getretenen Bundesbodenschutzgesetz ist eine wichtige Grundlage geschaffen, den Boden u. a. stärker in Planungs- und Zulassungsverfahren zu berücksichtigen. Die Ziele des Gesetzes, die nachhaltige Sicherung und Wiederherstellung von Bodenfunktionen, können wegen fehlender gesetzlicher Instrumente allerdings nicht eigenständig umgesetzt werden. Eine Schnittstelle zur Realisierung bodenbezogener Erhaltungs- und Entwicklungsziele bieten deshalb naturschutzrechtliche Instrumente wie die Landschaftsplanung, die Eingriffsregelung und Pflege- und Entwicklungspläne von Schutzgebieten. Am Beispiel beeinträchtigter Niederungsböden wird in der Arbeit hinterfragt und aufgezeigt, inwieweit auf das Schutzgut Boden bezogene Maßnahmenplanungen wie Wiedervernässung und Extensivierung mit naturschutzrechtlichen Instrumenten effektiv erstellt und umgesetzt werden können. Es liegt die Hypothese zugrunde, dass eine genaue Ist-Zustandserfassung von Niederungsböden auf Grundlage der in der naturschutzfachlichen Planungspraxis gängig herangezogenen Kartengrundlagen nicht möglich ist. Für die Bestimmung der Entwicklungspotenziale von Niederungsböden sowie die Erarbeitung detaillierter Maßnahmenplanungen ist eine gezielte Vor-Ort-Erhebung planungsrelevanter Bodenmerkmale erforderlich, auf die jedoch häufig verzichtet wird. Zudem wird bisher den Wirkungen von Maßnahmen auf das Leistungsvermögen und die Funktionsfähigkeit sowie den erforderlichen Ausgangsvoraussetzungen zu wenig Beachtung geschenkt. Dies erschwert die Umsetzung mit naturschutzrechtlichen Instrumenten. Ziel der Arbeit ist es, verallgemeinerbare Handlungsempfehlungen für die Durchführung von Vor-Ort-Erhebungen und die Ableitung von Aufwertungspotenzialen von Niederungsböden für eine zielgerichtete Maßnahmenkonzeption und sachgerechte Umsetzung zu formulieren. Auf der Basis einer Literaturanalyse und einer Untersuchung der aktuellen Standortausprägung in einem Beispielgebiet, dem Polder "Götz-Gollwitz", der in der entwässerten Niederung der "Mittleren Havel" (Bundesland Brandenburg)liegt, - wird untersucht, wie die Maßnahmen Wiedervernässung und Extensivierung auf die Bodeneigenschaften wirken und welche Veränderungen zum Erhalt und zur Verbesserung der Funktionsfähigkeit der Böden führen. - werden die aktuellen Substrat- und Bodentypen, die hydromorphen Verhältnisse sowie die Vegetationsausprägung gekennzeichnet. Es erfolgt ein Vergleich der Ergebnisse mit der Aussagekraft von standortkundlichen Kartenwerken. - werden Entwicklungsszenarien skizziert. Es wird aufgezeigt, welche Ausgangsvoraussetzungen und durchzuführenden Maßnahmen für die Erreichung bodenbezogener Ziele im Polder "Götz-Gollwitz" erforderlich und welche Wirkungen dabei auf den Boden, die derzeitige Flächennutzung sowie auf die Biotop- und Artenausstattung zu erwarten sind. Auf Basis der prognostizierten Standortveränderungen erfolgt die Diskussion, inwieweit es in Abhängigkeit der Szenarien bzw. der dabei getätigten Maßnahmen im Einzelnen zum Erhalt bzw. zur Verbesserung der Funktionsfähigkeit von Böden kommt. Für die Formulierung von Handlungsempfehlungen - wird anhand dreier häufig auftretender Ausgangszustände eine vom Beispielgebiet losgelöste Diskussion zum Erhalt und zu Verbesserungsmöglichkeiten der Leistungs- und Funktionsfähigkeit von Böden geführt. Dabei erfolgt die Unterscheidung, ob konkrete Maßnahmen als Ausgleichs- und Ersatzmaßnahmen aus der naturschutzrechtlichen Eingriffsregelung oder durch Pflege- und Entwicklungspläne als sonstige Minderungs-, Erhaltungs- oder Entwicklungsmaßnahmen umgesetzt werden können. - werden die Aktualität sowie Flächen- und Aussagenschärfe von Kartengrundlagen bewertet und ein Teil der Bodenparameter bestimmt, die unbedingt im Gelände zu erheben sind, um Ziele und Maßnahmen gezielter abzuleiten. - wird aus den Untersuchungen abgeleitet, mit welchem Aufwand und Methoden eine Überprüfung der aktuellen Standortausprägung zu erfolgen hat. Die Herleitung eines vertretbaren Erhebungsaufwandes (Punktdichte und -anordnung) wird durch verschiedene Rechenbeispiele unterstützt, die auf Basis der Honorarordnung für Architekten und Ingenieure (HOAI) und der im Beispielgebiet aufgebrachten Arbeitszeit kalkuliert werden. Die Vorgehensweise für die Prüfung und Erhebung des aktuellen Bodenzustandes sowie Ableitung der Aufwertungspotenziale von Bodenfunktionen wird in einem Ablaufschema dargestellt. Schlussfolgerungen beziehen sich auf Erreichung bodenbezogener Zielvorstellung in Abhängigkeit von den Anforderungen naturschutzrechtlicher Planungsinstrumente. Es wird die Bedeutung von Vor-Ort-Erhebungen als wertvollen Planungsbeitrag herausgestellt und die Notwendigkeit und Möglichkeiten aufgezeigt, für die Ebene der Maßnahmenplanung finanzielle Mittel zur Begleichung der Kosten von Vor-Ort-Erhebungen aufzubringen. Die vorliegende Arbeit leistet einen substanziellen Beitrag dazu, bodenbezogene Maßnahmenplanungen in Niederungsgebieten künftig realistischer und sachgerecht mit Instrumenten des Naturschutzes durchführen zu können.
This study investigates spatial patterns of Ks and tests the hypothesis of whether structural variance emerges from noise with increasing sampling precision. We analyzed point measurements of Ks along independent transects at sampling intervals of 25, 10, 1 and 0.25 m. The field area is a tropical rainforest catena (i.e. toposequence) characterized by systematic downslope changes in soil properties including color (red to yellow), mineralogy (kaolinite- illite to kaolinite) and texture (sandy clay to sand). Independent tramsects spanning the entire catena at lag intervals of 25 and 10 in reveal little to no spatial patterns in Ks; i.e. scatter plots are noisy and lack apparent spatial trends, and semivariograms suggest little to no autocorrelation in Ks. As sampling precision is increased (h = 1 and 0.25 m), spatial patterns emerge in Ks for the downslope areas, in which distinctive hydraulic boundaries in Ks correlate with relatively small-scale, topography-controlled soils with coarse textures (greater than or equal to 80% sand). For these areas, semivariograms of Ks and those of %sand and %clay exhibit similar spatial structure characterized by small nugget variances and large ranges, and nugget variance is reduced as sampling precision increases from 1 to 0.25 m. In the upslope, clay-rich locations along this toposequence, Ks exhibits few spatial patterns, irrespective of sampling scale. For these locations, scatter plots are noisy without apparent spatial trends, and semivariograms show almost complete nugget variance, suggesting little to no correlation in this hydraulic parameter at any scale. This study suggests that in the absence of coarse textures (greater than or equal to 80% sand), there is little predictability in Ks, even at sampling intervals of 0.25 m. We believe this lack of spatial structure is due to a predominance of small-scale processes such as biological activity that largely control Ks in this forested setting. (C) 2003 Elsevier B.V. All rights reserved
River floods are among the most devastating natural hazards worldwide. As their generation is highly dependent on climatic conditions, their magnitude and frequency are projected to be affected by future climate change. Therefore, it is crucial to study the ways in which a changing climate will, and already has, influenced flood generation, and thereby flood hazard. Additionally, it is important to understand how other human influences - specifically altered land cover - affect flood hazard at the catchment scale.
The ways in which flood generation is influenced by climatic and land cover conditions differ substantially in different regions. The spatial variability of these effects needs to be taken into account by using consistent datasets across large scales as well as applying methods that can reflect this heterogeneity. Therefore, in the first study of this cumulative thesis a complex network approach is used to find 10 clusters of similar flood behavior among 4390 catchments in the conterminous United States. By using a consistent set of 31 hydro-climatological and land cover variables, and training a separate Random Forest model for each of the clusters, the regional controls on flood magnitude trends between 1960-2010 are detected. It is shown that changes in rainfall are the most important drivers of these trends, while they are regionally controlled by land cover conditions.
While climate change is most commonly associated with flood magnitude trends, it has been shown to also influence flood timing. This can lead to trends in the size of the area across which floods occur simultaneously, the flood synchrony scale. The second study is an analysis of data from 3872 European streamflow gauges and shows that flood synchrony scales have increased in Western Europe and decreased in Eastern Europe. These changes are attributed to changes in flood generation, especially a decreasing relevance of snowmelt. Additionally, the analysis shows that both the absolute values and the trends of flood magnitudes and flood synchrony scales are positively correlated. If these trends persist in the future and are not accounted for, the combined increases of flood magnitudes and flood synchrony scales can exceed the capacities of disaster relief organizations and insurers.
Hazard cascades are an additional way through which climate change can influence different aspects of flood hazard. The 2019/2020 wildfires in Australia, which were preceded by an unprecedented drought and extinguished by extreme rainfall that led to local flooding, present an opportunity to study the effects of multiple preceding hazards on flood hazard. All these hazards are individually affected by climate change, additionally complicating the interactions within the cascade. By estimating and analyzing the burn severity, rainfall magnitude, soil erosion and stream turbidity in differently affected tributaries of the Manning River catchment, the third study shows that even low magnitude floods can pose a substantial hazard within a cascade.
This thesis shows that humanity is affecting flood hazard in multiple ways with spatially and temporarily varying consequences, many of which were previously neglected (e.g. flood synchrony scale, hazard cascades). To allow for informed decision making in risk management and climate change adaptation, it will be crucial to study these aspects across the globe and to project their trajectories into the future. The presented methods can depict the complex interactions of different flood drivers and their spatial variability, providing a basis for the assessment of future flood hazard changes. The role of land cover should be considered more in future flood risk modelling and management studies, while holistic, transferable frameworks for hazard cascade assessment will need to be designed.
Natural hazards pose a threat to human health and life. In Germany, where the research for this thesis was conducted, numerous weather extremes occurred in the recent past that caused high numbers of fatalities and huge financial losses. The focus of this research is centred around two relevant natural hazards: heat stress and flooding. Preventing negative health impacts and deaths, as well as structural and monetary damage is the purpose of risk management and this requires citizens to adapt as well. Risk communication is implemented to foster people’s risk perception and motivate individual adaptation. However, methods of risk and crisis communication are often not evaluated in a structured manner. Much interdisciplinary research exists on both risk perception and adaptation, however, not much is known on the connection between the two. Furthermore, the existing research on risk communication is often not theory-driven and its impact on individual adaptation and risk perception is not thoroughly documented. This dissertation follows three research aims: (1) Compare psychological theories that contribute to natural hazard research. (2) Explore risk perception and adaptive behaviour by applying multiple methods. And (3) evaluate one risk communication method and one crisis communication method in a theory-driven manner to determine their impact on risk perception and adaptive behaviour. First, a literature review is provided on existing psychological theories which aim to explain the behaviour of individuals with regards to natural hazards. The three key theories included are the Protection Motivation Theory (PMT), the Protective Action Decision Model (PADM), and the Risk Information Seeking and Processing Model (RISP). Each of these are described and compared to each other with a focus on their explanatory power and practical significance in interdisciplinary research. Theoretical adaptations and possible extensions for future research are proposed for the presented approaches. Second, a multimethod field study on heat stress at an open-air event is presented. Face-to-face surveys (n = 306) and behavioural observations (n = 2750) were carried out at a horticultural show in Würzburg in summer 2018. The visitors’ risk perception, adaptive behaviour, and activity level were analysed and compared between hot days, summer days, and rainy days, applying correlation analyses, ANOVA, and multiple regression analyses. Heat risk perception was generally high, but most respondents were unaware of heat warnings on the day of their visit. During hot days the highest level of adaptation and lower activity levels were observed. Discrepancies between reported and observed adaptation emerged for different age groups.. Third, a telephone and web-based household survey on heat stress was conducted in the cities of Würzburg, Potsdam, and Remscheid in 2019 (n = 1417). The PADM served as the study’s theoretical framework. In multiple regression analyses the PADM factors of environmental and demographic context, risk communication, and psychological processes explained a substantial share of variance of protection motivation, protective response, and emotion-focused coping. Elements of crisis communication of a heat warning were evaluated experimentally. Results showed that understanding and adaptation intention was significantly higher in individuals that had received action recommendations alongside the heat warning. Fourth, the focus is set on a risk communication method of the flood context. A series of workshops on individual flood protection was carried out in six different settings. The participants (n = 115) answered a pretest-posttest questionnaire. Mixed-model analyses revealed significant increases in self-efficacy, subjective knowledge, and protection motivation. Stronger effects were observed in younger participants and those with lower levels of previous knowledge on flood adaptation as well as no flood experience. The findings of this thesis help to understand individual adaptation, as well as possible impacts of risk and crisis communication on risk perception and adaptation. The scientific background of this work is rooted in the disciplines of psychology and geosciences. The two theories PMT and PADM proved to be useful theoretical frameworks for the presented studies to suggest improvements in risk communication methods. A broad picture of individual adaptation is captured through a variety of methods of self-reports (face-to-face, telephone-based, web-based, and paper-pencil surveys) and behavioural observations, which recorded past and intended behaviour. Alongside with further methodological recommendations, the theory-driven evaluations of risk and crisis communication methods can serve as best-practice examples for future evaluation studies in natural hazard research but also other sciences dealing with risk behaviour to identify and improve effective risk communication pathways.
Semiaride Gebiete sind hauptsächlich durch geringe Wasserressourcen gekennzeichnet und unterliegen häufig dem Risiko der Wasserknappheit. In diesen Gebieten ist die Wasserbereitstellung für Bewässerung und Trinkwasserversorgung stark von der oberflächlichen Speicherung in Stauseen abhängig, deren Wasserverfügbarkeit nachteilig durch Sedimentablagerung beeinflusst wird. Zur Wiedergabe des komplexen Sedimentablagerungsverhaltens in Stauseen von semiariden Gebieten und die Auswirkungen von Sedimentmanagementmaßnahmen wird ein Sedimentationsmodell entwickelt und mit dem WASA-SED Modell gekoppelt, das für die Modellierung der Abflussbildung und des Sedimenttransportes in Einzugsgebieten geeignet ist. Das Sedimentationsmodell beinhaltet zwei Ansätze, die unter der Berücksichtigung verschiedener Stauseengrößenklassen und Datenverfügbarkeit eingesetzt werden können. Für die Stauseen mit verfügbaren Informationen über ihre geometrischen Eigenschaften (wie Stauseetopographie und Höhe-Fläche-Volumen-Beziehung) und weitere Kenngrößen wie Ablagerungsmächtigkeit, Korngrößenverteilung und Sedimentdichte, kann ein detaillierter Modellansatz für die Sedimentablagerung verwendet werden. Wo diese Informationen nicht verfügbar sind, wird auf einen vereinfachten Ansatz zurückgegriffen. Der detaillierte Modellansatz ermöglicht die Betrachtung von Ablagerungsmustern im Stausee und Einschätzungen über die Effektivität von Sedimentmanagementmaßnahmen hinsichtlich der Sedimententlastung. Dieser Ansatz beruht auf der Simulation des Sedimenttransportes entlang eines Stauseelängsprofils. Für die Berechnung des Sedimenttransfers wird der Stauseekörper in einer Folge von Querprofilen repräsentiert. Der Sedimenttransport wird dabei korngrößenspezifisch entsprechend der Transportkapazität berechnet. Dafür stehen vier verschiedenen Sedimenttransportgleichungen zur Verfügung. Der vereinfachte Modellansatz ist für die Simulation des Sedimenttransfers in Gebieten mit hoher Stauseedichte geeignet, jedoch können weder Sedimentmanagementmaßnahmen noch die räumliche Verteilung der Ablagerungen berücksichtigt werden. Dafür werden die Stauseen in Abhängigkeit von ihrer Größe und Position in kleine und strategische Stauseen unterteilt. Dabei sind strategische Stausseen solche mit mittlerem bis großem Volumen sowie einer Lage im Hauptgerinne oder solche mit sonstiger besonderer Bedeutung. Kleine Stauseen hingegen befinden sich an den Nebenflüssen und werden im Modell in aggregierter Form durch ihre Einteilung in Stauseegrößenklassen repräsentiert. Ein Kaskadenverfahren wird für den Wasser- und Sedimentlauf zwischen den Stauseeklassen verwendet. Dabei werden für jede Stauseeklasse der Wasser- sowie Sedimenthaushalt für einen hypothetischen repräsentativen Stausee mit mittleren Eigenschaften berechnet. Die Sedimentaufnahme und die Korngrößenverteilung des abgegebenen Sediments werden mit dem Überlaufanteil-Ansatz berechnet. In dieser Studie werden drei Modellanwendungen vorgestellt: • Für den 92,2 Mio.m³-großen Barasona-Stausee (Vorland der Zentralpyrenäen, Aragon, Spanien) wird die Modellierung der Sedimentablagerung mit dem detaillierten Modellansatz vorgenommen. Die Kalibrierung dafür wurde in zwei Schritten durchgeführt, um Änderungen im Stauseemanagement Rechnung zu tragen. Die ModellValidierung wird schließlich für eine andere Simulationsperiode vorgenommen. Dabei wird ersichtlich, dass die Prozesse der Sedimentablagerung gut durch das Modell wiedergegeben werden. • Das Modell wird auf das 933 km²-große Benguê-Einzugsgebiet, das sich im semiariden Nordosten Brasiliens befindet, angewendet. Dieses Einzugsgebiet ist durch eine hohe Dichte an kleinen Stauseen, charakterisiert, die fast 45% des Gebietes umfasst, wofür jedoch wenige Messdaten verfügbar sind. Deshalb werden der Wasser- und Sedimenttransport mit dem vereinfachten Modellansatz berechnet. Dabei werden drei Konfigurationen des Kaskadenverfahrens getestet. • Die Modellanwendung erfolgt erneut für den Barasona-Stausee bezüglich der Effektivität der Sedimentmanagementmaßnahmen. Eine Kostenanalyse ermöglicht die Auswahl geeigneter Maßnahmen für den Stausee. Dadurch wird eine Beurteilung der verschiedenen Sedimentmanagementstrategien ermöglicht. Im Allgemeinen unterliegen die Simulationsergebnisse großen Unsicherheiten, teilweise wegen der geringen Datenverfügbarkeit, andererseits durch die Unsicherheiten in der Modellstruktur zur korrekten Wiedergabe der Sedimentablagerungsprozesse.
This paper introduces a novel measure to assess similarity between event hydrographs. It is based on Cross Recurrence Plots and Recurrence Quantification Analysis which have recently gained attention in a range of disciplines when dealing with complex systems. The method attempts to quantify the event runoff dynamics and is based on the time delay embedded phase space representation of discharge hydrographs. A phase space trajectory is reconstructed from the event hydrograph, and pairs of hydrographs are compared to each other based on the distance of their phase space trajectories. Time delay embedding allows considering the multi-dimensional relationships between different points in time within the event. Hence, the temporal succession of discharge values is taken into account, such as the impact of the initial conditions on the runoff event. We provide an introduction to Cross Recurrence Plots and discuss their parameterization. An application example based on flood time series demonstrates how the method can be used to measure the similarity or dissimilarity of events, and how it can be used to detect events with rare runoff dynamics. It is argued that this methods provides a more comprehensive approach to quantify hydrograph similarity compared to conventional hydrological signatures.
Rainfall-triggered landslides are a globally occurring hazard that cause several thousand fatalities per year on average and lead to economic damages by destroying buildings and infrastructure and blocking transportation networks. For people living and governing in susceptible areas, knowing not only where, but also when landslides are most probable is key to inform strategies to reduce risk, requiring reliable assessments of weather-related landslide hazard and adequate warning. Taking proper action during high hazard periods, such as moving to higher levels of houses, closing roads and rail networks, and evacuating neighborhoods, can save lives. Nevertheless, many regions of the world with high landslide risk currently lack dedicated, operational landslide early warning systems.
The mounting availability of temporal landslide inventory data in some regions has increasingly enabled data-driven approaches to estimate landslide hazard on the basis of rainfall conditions. In other areas, however, such data remains scarce, calling for appropriate statistical methods to estimate hazard with limited data. The overarching motivation for this dissertation is to further our ability to predict rainfall-triggered landslides in time in order to expand and improve warning. To this end, I applied Bayesian inference to probabilistically quantify and predict landslide activity as a function of rainfall conditions at spatial scales ranging from a small coastal town, to metropolitan areas worldwide, to a multi-state region, and temporal scales from hourly to seasonal. This thesis is composed of three studies.
In the first study, I contributed to developing and validating statistical models for an online landslide warning dashboard for the small town of Sitka, Alaska, USA. We used logistic and Poisson regressions to estimate daily landslide probability and counts from an inventory of only five reported landslide events and 18 years of hourly precipitation measurements at the Sitka airport. Drawing on community input, we established two warning thresholds for implementation in the dashboard, which uses observed rainfall and US National Weather Service forecasts to provide real-time estimates of landslide hazard.
In the second study, I estimated rainfall intensity-duration thresholds for shallow landsliding for 26 cities worldwide and a global threshold for urban landslides. I found that landslides in urban areas occurred at rainfall intensities that were lower than previously reported global thresholds, and that 31% of urban landslides were triggered during moderate rainfall events. However, landslides in cities with widely varying climates and topographies were triggered above similar critical rainfall intensities: thresholds for 77% of cities were indistinguishable from the global threshold, suggesting that urbanization may harmonize thresholds between cities, overprinting natural variability. I provide a baseline threshold that could be considered for warning in cities with limited landslide inventory data.
In the third study, I investigated seasonal landslide response to annual precipitation patterns in the Pacific Northwest region, USA by using Bayesian multi-level models to combine data from five heterogeneous landslide inventories that cover different areas and time periods. I quantitatively confirmed a distinctly seasonal pattern of landsliding and found that peak landslide activity lags the annual precipitation peak. In February, at the height of the landslide season, landslide intensity for a given amount of monthly rainfall is up to ten times higher than at the season onset in November, underlining the importance of antecedent seasonal hillslope conditions.
Together, these studies contributed actionable, objective information for landslide early warning and examples for the application of Bayesian methods to probabilistically quantify landslide hazard from inventory and rainfall data.
Motivations and research objectives: During the passage of rain water through a forest canopy two main processes take place. First, water is redistributed; and second, its chemical properties change substantially. The rain water redistribution and the brief contact with plant surfaces results in a large variability of both throughfall and its chemical composition. Since throughfall and its chemistry influence a range of physical, chemical and biological processes at or below the forest floor the understanding of throughfall variability and the prediction of throughfall patterns potentially improves the understanding of near-surface processes in forest ecosystems. This thesis comprises three main research objectives. The first objective is to determine the variability of throughfall and its chemistry, and to investigate some of the controlling factors. Second, I explored throughfall spatial patterns. Finally, I attempted to assess the temporal persistence of throughfall and its chemical composition. Research sites and methods: The thesis is based on investigations in a tropical montane rain forest in Ecuador, and lowland rain forest ecosystems in Brazil and Panama. The first two studies investigate both throughfall and throughfall chemistry following a deterministic approach. The third study investigates throughfall patterns with geostatistical methods, and hence, relies on a stochastic approach. Results and Conclusions: Throughfall is highly variable. The variability of throughfall in tropical forests seems to exceed that of many temperate forests. These differences, however, do not solely reflect ecosystem-inherent characteristics, more likely they also mirror management practices. Apart from biotic factors that influence throughfall variability, rainfall magnitude is an important control. Throughfall solute concentrations and solute deposition are even more variable than throughfall. In contrast to throughfall volumes, the variability of solute deposition shows no clear differences between tropical and temperate forests, hence, biodiversity is not a strong predictor of solute deposition heterogeneity. Many other factors control solute deposition patterns, for instance, solute concentration in rainfall and antecedent dry period. The temporal variability of the latter factors partly accounts for the low temporal persistence of solute deposition. In contrast, measurements of throughfall volume are quite stable over time. Results from the Panamanian research site indicate that wet and dry areas outlast consecutive wet seasons. At this research site, throughfall exhibited only weak or pure nugget autocorrelation structures over the studies lag distances. A close look at the geostatistical tools at hand provided evidence that throughfall datasets, in particular those of large events, require robust variogram estimation if one wants to avoid outlier removal. This finding is important because all geostatistical throughfall studies that have been published so far analyzed their data using the classical, non-robust variogram estimator.
Cette thèse d’urbanisme s’est donnée pour objectif de réfléchir à l’avenir des gares métropolitaines françaises et allemandes à horizon 2050. Elle porte une interrogation sur les fondements de la gare comme objet urbain conceptuel (abordé comme un système) et pose comme hypothèse qu’il serait en quelque sorte doté de propriétés autonomes. Parmi ces propriétés, c’est le processus d’expansion et de dialogue sans cesse renouvelé et conflictuel, entre la gare et son tissu urbain environnant, qui guide cette recherche ; notamment dans le rapport qu’il entretient avec l’hypermobilité des métropoles. Pour ce faire, cette thèse convoque quatre terrains d’études : les gares principales de Cologne et de Stuttgart en Allemagne et les gares de Paris-Montparnasse et Lyon-Part-Dieu en France ; et commence par un historique détaillé de leurs évolutions morphologiques, pour dégager une série de variables architectoniques et urbaines. Il procède dans un deuxième temps à une série d’analyse prospective, permettant de juger de l’influence possible des politiques publiques en matière transports et de mobilité, sur l’avenir conceptuel des gares. Cette thèse propose alors le concept de système-gare, pour décrire l’expansion et l’intégration des gares métropolitaines avec leur environnement urbain ; un processus de négociation dialectique qui ne trouve pas sa résolution dans le concept de gare comme lieu de vie/ville. Elle invite alors à penser la gare comme une hétérotopie, et propose une lecture dépolarisée et déhiérarchisée de ces espaces, en introduisant les concepts d’orchestre de gares et de métagare. Cette recherche propose enfin une lecture critique de la « ville numérique » et du concept de « mobilité comme service. » Pour éviter une mise en flux tendus potentiellement dommageables, l’application de ces concepts en gare ne pourra se soustraire à une augmentation simultanée des espaces physiques.
Die Zielsetzung der vorliegenden Arbeit ist die Beschreibung hydrophober Bodeneigenschaften und deren Auswirkungen auf Oberflächenabfluss und Erosion auf verschiedenen Skalen. Die dazu durchgeführten Untersuchungen fanden auf einer Rekultivierungsfläche im Braunkohlegebiet Welzow Süd (Südostdeutschland) statt. Die Prozesse wurden auf drei Skalen untersucht, die von der Plotskala (1m²) über die Hangskala (300m²) bis zur Betrachtung eines kleinen Einzugsgebietes (4ha) reichen. Der Grad der hydrophoben Bodeneigenschaften wurde sowohl direkt, über die Bestimmung des Kontaktwinkel, als auch indirekt, über die Bestimmung der Persistenz, ermittelt. Dabei zeigte sich, dass der Boden im Winterhalbjahr hydrophil reagierte, während er im Sommerhalbjahr hydrophobe Bodeneigenschaften aufwies. Die Ergebnisse deuten darauf hin, dass ansteigende Bodenwassergehalte, die in der Literatur häufig als Ursache für einen Wechsel der Bodeneigenschaften angegeben werden, auf dieser Fläche nicht zu einem Umbruch der Bodenbedingungen führen. Stattdessen kam es als Folge des Auftauens von gefrorenem Boden zu hydrophilen Bodeneigenschaften, die zu einem Anstieg des Bodenwassergehalts führten. Räumliche Unterschiede zeigten sich in den geomorphologischen Einheiten. Rinnen und Rillen wiesen seltener hydrophobe Eigenschaften als die Zwischenrillenbereiche und Kuppen auf. Diese räumlichen und zeitlichen Variabilitäten wirkten sich auch auf den Oberflächenabfluss aus, der als Abflussbeiwert (ABW: Quotient aus Abfluss und Niederschlag) untersucht wurde. Der ABW liegt auf Böden mit hydrophoben Bodeneigenschaften (ABW=0,8) deutlich höher als bei jenen mit hydrophilen Eigenschaften(ABW=0,2), wie sie im Winter oder auf anderem Substrat vorzufinden sind (diese Werte beziehen sich auf die Plotskala). Betrachtet man die Auswirkungen auf unterschiedlichen Skalen, nimmt der Abflussbeiwert mit zunehmender Flächengröße ab (ABW = 0,8 auf der Plotskala, ABW = 0,5 auf der Hangskala und ABW = 0,2 im gesamten Gebiet), was in den hydrophil reagierenden Rillen und Rinnen auf der Hangskala und dem hydrophilen Substrat im Einzugsgebiet begründet ist. Zur Messung der Erosion wurden verschiedene, zum Teil neu entwickelte Methoden eingesetzt, um eine hohe zeitliche und räumliche Auflösung zu erreichen. Bei einer neu entwickelten Methode wird der Sedimentaustrag ereignisbezogen über eine Waage bestimmt. In Kombination mit einer Kippwaage ermöglicht sie die gleichzeitige Messung des Oberflächenabflusses. Die Messapparatur wurde für Gebiete entwickelt, die eine überwiegend grobsandige Textur aufweisen und nur geringe Mengen Ton und Schluff enthalten. Zusätzlich wurden zwei Lasersysteme zur Messung der räumlichen Verteilung der Erosion eingesetzt. Für die erste Methode wurde ein punktuell messender Laser in einer fest installierten Apparatur über die Fläche bewegt und punktuell Höhenunterschiede in einem festen Raster bestimmt. Durch Interpolation konnten Bereiche mit Sedimentabtrag von Akkumulationsbereiche unterschieden werden. Mit dieser Methode können auch größere Flächen vermessen werden (hier 16 m²), allerdings weisen die Messungen in den Übergangsbereichen von Rinne zu Zwischenrille große Fehler auf. Bei der zweiten Methode wird mit einer Messung ein Quadratmeter mit einer hohen räumlichen Auflösung komplett erfasst. Um ein dreidimensionales Bild zu erstellen, müssen insgesamt vier Aufnahmen von jeweils unterschiedlichen Seiten aufgenommen werden. So lassen sich Abtrag und Akkumulation sehr genau bestimmen, allerdings ist die Messung relativ aufwendig und erfasst nur eine kleine Fläche. Zusätzlich wurde der Sedimentaustrag noch auf der Plotskala erfasst. Die Messungen zeigen, korrespondierend zu den Bodeneigenschaften, große Sedimentausträge während des Sommerhalbjahrs und kaum Austräge im Winter. Weiterhin belegen die Ergebnisse eine größere Bedeutung der Rillenerosion gegenüber der Zwischenrillenerosion für Niederschlagsereignisse hoher Intensität (>25 mm/h in einem zehnminütigem Intervall). Im Gegensatz dazu dominierte die Zwischenrillenerosion bei Ereignissen geringerer Intensität (<20 mm/h in einem zehnminütigem Intervall), wobei mindestens 9 mm Niederschlag in einer Intensität von mindesten 3,6 mm/h nötig sind, damit es zur Erosion kommt. Basierend auf den gemessenen Abflüssen und Sedimentausträgen wurden Regressiongleichungen abgeleitet, die eine Berechnung dieser beiden Prozesse für die untersuchte Fläche ermöglichen. Während die Menge an Oberflächenabfluss einen starken Zusammenhang zu der Menge an gefallenem Niederschlag zeigt (r² = 0,9), ist die Berechnung des ausgetragenen Sedimentes eher ungenau (r² = 0,7). Zusammenfassend beschreibt die Arbeit Einflüsse hydrophober Bodeneigenschaften auf verschiedenen Skalen und arbeitet die Auswirkungen, die vor allem auf der kleinen Skala von großer Bedeutung sind, heraus.
Hydrological models are important tools for the simulation and quantification of the water cycle.
They therefore aid in the understanding of hydrological processes, prediction of river discharge, assessment of the impacts of land use and climate changes, or the management of water resources.
However, uncertainties associated with hydrological modelling are still large.
While significant research has been done on the quantification and reduction of uncertainties, there are still fields which have gained little attention so far, such as model structural uncertainties that are related to the process implementations in the models.
This holds especially true for complex process-based models in contrast to simpler conceptual models.
Consequently, the aim of this thesis is to improve the understanding of structural uncertainties with focus on process-based hydrological modelling, including methods for their quantification.
To identify common deficits of frequently used hydrological models and develop further strategies on how to reduce them, a survey among modellers was conducted.
It was found that there is a certain degree of subjectivity in the perception of modellers, for instance with respect to the distinction of hydrological models into conceptual groups.
It was further found that there are ambiguities on how to apply a certain hydrological model, for instance how many parameters should be calibrated, together with a large diversity of opinion regarding the deficits of models.
Nevertheless, evapotranspiration processes are often represented in a more physically based manner, while processes of groundwater and soil water movement are often simplified, which many survey participants saw as a drawback.
A large flexibility, for instance with respect to different alternative process implementations or a small number of parameters that needs to be calibrated, was generally seen as strength of a model.
Flexible and efficient software, which is straightforward to apply, has been increasingly acknowledged by the hydrological community.
This work further elaborated on this topic in a twofold way.
First, a software package for semi-automated landscape discretisation has been developed, which serves as a tool for model initialisation.
This was complemented by a sensitivity analysis of important and commonly used discretisation parameters, of which the size of hydrological sub-catchments as well as the size and number of hydrologically uniform computational units appeared to be more influential than information considered for the characterisation of hillslope profiles.
Second, a process-based hydrological model has been implemented into a flexible simulation environment with several alternative process representations and a number of numerical solvers.
It turned out that, even though computation times were still long, enhanced computational capabilities nowadays in combination with innovative methods for statistical analysis allow for the exploration of structural uncertainties of even complex process-based models, which up to now was often neglected by the modelling community.
In a further study it could be shown that process-based models may even be employed as tools for seasonal operational forecasting.
In contrast to statistical models, which are faster to initialise and to apply, process-based models produce more information in addition to the target variable, even at finer spatial and temporal scales, and provide more insights into process behaviour and catchment functioning.
However, the process-based model was much more dependent on reliable rainfall forecasts.
It seems unlikely that there exists a single best formulation for hydrological processes, even for a specific catchment.
This supports the use of flexible model environments with alternative process representations instead of a single model structure.
However, correlation and compensation effects between process formulations, their parametrisation, and other aspects such as numerical solver and model resolution, may lead to surprising results and potentially misleading conclusions.
In future studies, such effects should be more explicitly addressed and quantified.
Moreover, model functioning appeared to be highly dependent on the meteorological conditions and rainfall input generally was the most important source of uncertainty.
It is still unclear, how this could be addressed, especially in the light of the aforementioned correlations.
The use of innovative data products, e.g.\ remote sensing data in combination with station measurements, and efficient processing methods for the improvement of rainfall input and explicit consideration of associated uncertainties is advisable to bring more insights and make hydrological simulations and predictions more reliable.
At present, carbon sequestration in terrestrial ecosystems slows the growth rate of atmospheric CO2 concentrations, and thereby reduces the impact of anthropogenic fossil fuel emissions on the climate system. Changes in climate and land use affect terrestrial biosphere structure and functioning at present, and will likely impact on the terrestrial carbon balance during the coming decades - potentially providing a positive feedback to the climate system due to soil carbon releases under a warmer climate. Quantifying changes, and the associated uncertainties, in regional terrestrial carbon budgets resulting from these effects is relevant for the scientific understanding of the Earth system and for long-term climate mitigation strategies. A model describing the relevant processes that govern the terrestrial carbon cycle is a necessary tool to project regional carbon budgets into the future. This study (1) provides an extensive evaluation of the parameter-based uncertainty in model results of a leading terrestrial biosphere model, the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM), against a range of observations and under climate change, thereby complementing existing studies on other aspects of model uncertainty; (2) evaluates different hypotheses to explain the age-related decline in forest growth, both from theoretical and experimental evidence, and introduces the most promising hypothesis into the model; (3) demonstrates how forest statistics can be successfully integrated with process-based modelling to provide long-term constraints on regional-scale forest carbon budget estimates for a European forest case-study; and (4) elucidates the combined effects of land-use and climate changes on the present-day and future terrestrial carbon balance over Europe for four illustrative scenarios - implemented by four general circulation models - using a comprehensive description of different land-use types within the framework of LPJ-DGVM. This study presents a way to assess and reduce uncertainty in process-based terrestrial carbon estimates on a regional scale. The results of this study demonstrate that simulated present-day land-atmosphere carbon fluxes are relatively well constrained, despite considerable uncertainty in modelled net primary production. Process-based terrestrial modelling and forest statistics are successfully combined to improve model-based estimates of vegetation carbon stocks and their change over time. Application of the advanced model for 77 European provinces shows that model-based estimates of biomass development with stand age compare favourably with forest inventory-based estimates for different tree species. Driven by historic changes in climate, atmospheric CO2 concentration, forest area and wood demand between 1948 and 2000, the model predicts European-scale, present-day age structure of forests, ratio of biomass removals to increment, and vegetation carbon sequestration rates that are consistent with inventory-based estimates. Alternative scenarios of climate and land-use change in the 21<sup>st century suggest carbon sequestration in the European terrestrial biosphere during the coming decades will likely be on magnitudes relevant to climate mitigation strategies. However, the uptake rates are small in comparison to the European emissions from fossil fuel combustion, and will likely decline towards the end of the century. Uncertainty in climate change projections is a key driver for uncertainty in simulated land-atmosphere carbon fluxes and needs to be accounted for in mitigation studies of the terrestrial biosphere.
Today, more than half of the world’s population lives in urban areas. With a high density of population and assets, urban areas are not only the economic, cultural and social hubs of every society, they are also highly susceptible to natural disasters. As a consequence of rising sea levels and an expected increase in extreme weather events caused by a changing climate in combination with growing cities, flooding is an increasing threat to many urban agglomerations around the globe.
To mitigate the destructive consequences of flooding, appropriate risk management and adaptation strategies are required. So far, flood risk management in urban areas is almost exclusively focused on managing river and coastal flooding. Often overlooked is the risk from small-scale rainfall-triggered flooding, where the rainfall intensity of rainstorms exceeds the capacity of urban drainage systems, leading to immediate flooding. Referred to as pluvial flooding, this flood type exclusive to urban areas has caused severe losses in cities around the world. Without further intervention, losses from pluvial flooding are expected to increase in many urban areas due to an increase of impervious surfaces compounded with an aging drainage infrastructure and a projected increase in heavy precipitation events. While this requires the integration of pluvial flood risk into risk management plans, so far little is known about the adverse consequences of pluvial flooding due to a lack of both detailed data sets and studies on pluvial flood impacts. As a consequence, methods for reliably estimating pluvial flood losses, needed for pluvial flood risk assessment, are still missing.
Therefore, this thesis investigates how pluvial flood losses to private households can be reliably estimated, based on an improved understanding of the drivers of pluvial flood loss. For this purpose, detailed data from pluvial flood-affected households was collected through structured telephone- and web-surveys following pluvial flood events in Germany and the Netherlands.
Pluvial flood losses to households are the result of complex interactions between impact characteristics such as the water depth and a household’s resistance as determined by its risk awareness, preparedness, emergency response, building properties and other influencing factors. Both exploratory analysis and machine-learning approaches were used to analyze differences in resistance and impacts between households and their effects on the resulting losses. The comparison of case studies showed that the awareness around pluvial flooding among private households is quite low. Low awareness not only challenges the effective dissemination of early warnings, but was also found to influence the implementation of private precautionary measures. The latter were predominately implemented by households with previous experience of pluvial flooding. Even cases where previous flood events affected a different part of the same city did not lead to an increase in preparedness of the surveyed households, highlighting the need to account for small-scale variability in both impact and resistance parameters when assessing pluvial flood risk.
While it was concluded that the combination of low awareness, ineffective early warning and the fact that only a minority of buildings were adapted to pluvial flooding impaired the coping capacities of private households, the often low water levels still enabled households to mitigate or even prevent losses through a timely and effective emergency response.
These findings were confirmed by the detection of loss-influencing variables, showing that cases in which households were able to prevent any loss to the building structure are predominately explained by resistance variables such as the household’s risk awareness, while the degree of loss is mainly explained by impact variables.
Based on the important loss-influencing variables detected, different flood loss models were developed. Similar to flood loss models for river floods, the empirical data from the preceding data collection was used to train flood loss models describing the relationship between impact and resistance parameters and the resulting loss to building structures. Different approaches were adapted from river flood loss models using both models with the water depth as only predictor for building structure loss and models incorporating additional variables from the preceding variable detection routine.
The high predictive errors of all compared models showed that point predictions are not suitable for estimating losses on the building level, as they severely impair the reliability of the estimates. For that reason, a new probabilistic framework based on Bayesian inference was introduced that is able to provide predictive distributions instead of single loss estimates. These distributions not only give a range of probable losses, they also provide information on how likely a specific loss value is, representing the uncertainty in the loss estimate.
Using probabilistic loss models, it was found that the certainty and reliability of a loss estimate on the building level is not only determined by the use of additional predictors as shown in previous studies, but also by the choice of response distribution defining the shape of the predictive distribution. Here, a mix between a beta and a Bernoulli distribution to account for households that are able to prevent losses to their building’s structure was found to provide significantly more certain and reliable estimates than previous approaches using Gaussian or non-parametric response distributions.
The successful model transfer and post-event application to estimate building structure loss in Houston, TX, caused by pluvial flooding during Hurricane Harvey confirmed previous findings, and demonstrated the potential of the newly developed multi-variable beta model for future risk assessments. The highly detailed input data set constructed from openly available data sources containing over 304,000 affected buildings in Harris County further showed the potential of data-driven, building-level loss models for pluvial flood risk assessment.
In conclusion, pluvial flood losses to private households are the result of complex interactions between impact and resistance variables, which should be represented in loss models. The local occurrence of pluvial floods requires loss estimates on high spatial resolutions, i.e. on the building level, where losses are variable and uncertainties are high.
Therefore, probabilistic loss estimates describing the uncertainty of the estimate should be used instead of point predictions. While the performance of probabilistic models on the building level are mainly driven by the choice of response distribution, multi-variable models are recommended for two reasons:
First, additional resistance variables improve the detection of cases in which households were able to prevent structural losses.
Second, the added variability of additional predictors provides a better representation of the uncertainties when loss estimates from multiple buildings are aggregated.
This leads to the conclusion that data-driven probabilistic loss models on the building level allow for a reliable loss estimation at an unprecedented level of detail, with a consistent quantification of uncertainties on all aggregation levels. This makes the presented approach suitable for a wide range of applications, from decision support in spatial planning to impact- based early warning systems.
Planetary research is often user-based and requires considerable skill, time, and effort. Unfortunately, self-defined boundary conditions, definitions, and rules are often not documented or not easy to comprehend due to the complexity of research. This makes a comparison to other studies, or an extension of the already existing research, complicated. Comparisons are often distorted, because results rely on different, not well defined, or even unknown boundary conditions. The purpose of this research is to develop a standardized analysis method for planetary surfaces, which is adaptable to several research topics. The method provides a consistent quality of results. This also includes achieving reliable and comparable results and reducing the time and effort of conducting such studies. A standardized analysis method is provided by automated analysis tools that focus on statistical parameters. Specific key parameters and boundary conditions are defined for the tool application. The analysis relies on a database in which all key parameters are stored. These databases can be easily updated and adapted to various research questions. This increases the flexibility, reproducibility, and comparability of the research. However, the quality of the database and reliability of definitions directly influence the results. To ensure a high quality of results, the rules and definitions need to be well defined and based on previously conducted case studies. The tools then produce parameters, which are obtained by defined geostatistical techniques (measurements, calculations, classifications). The idea of an automated statistical analysis is tested to proof benefits but also potential problems of this method. In this study, I adapt automated tools for floor-fractured craters (FFCs) on Mars. These impact craters show a variety of surface features, occurring in different Martian environments, and having different fracturing origins. They provide a complex morphological and geological field of application. 433 FFCs are classified by the analysis tools due to their fracturing process. Spatial data, environmental context, and crater interior data are analyzed to distinguish between the processes involved in floor fracturing. Related geologic processes, such as glacial and fluvial activity, are too similar to be separately classified by the automated tools. Glacial and fluvial fracturing processes are merged together for the classification. The automated tools provide probability values for each origin model. To guarantee the quality and reliability of the results, classification tools need to achieve an origin probability above 50 %. This analysis method shows that 15 % of the FFCs are fractured by intrusive volcanism, 20 % by tectonic activity, and 43 % by water & ice related processes. In total, 75 % of the FFCs are classified to an origin type. This can be explained by a combination of origin models, superposition or erosion of key parameters, or an unknown fracturing model. Those features have to be manually analyzed in detail. Another possibility would be the improvement of key parameters and rules for the classification. This research shows that it is possible to conduct an automated statistical analysis of morphologic and geologic features based on analysis tools. Analysis tools provide additional information to the user and are therefore considered assistance systems.
The length of the vegetation period (VP) plays a central role for the interannual variation of carbon fixation of terrestrial ecosystems. Observational data analysis has indicated that the length of the VP has increased in the last decades in the northern latitudes mainly due to an advancement of bud burst (BB). This phenomenon has been widely discussed in the context of Global Warming because phenology is correlated to temperatures. Analyzing the patterns of spring phenology over the last century in Southern Germany provided two main findings: - The strong advancement of spring phases especially in the decade before 1999 is not a singular event in the course of the 20th century. Similar trends were also observed in earlier decades. Distinct periods of varying trend behavior for important spring phases could be distinguished. - Marked differences in trend behavior between the early and late spring phases were detected. Early spring phases changed as regards the magnitude of their negative trends from strong negative trends between 1931 and 1948 to moderate negative trends between 1948 and 1984 and back to strong negative trends between 1984 and 1999. Late spring phases showed a different behavior. Negative trends between 1931 and 1948 are followed by marked positive trends between 1948 and 1984 and then strong negative trends between 1984 and 1999. This marked difference in trend development between early and late spring phases was also found all over Germany for the two periods 1951 to 1984 and 1984 to 1999. The dominating influence of temperature on spring phenology and its modifying effect on autumn phenology was confirmed in this thesis. However, - temperature functions determining spring phenology were not significantly correlated with a global annual CO2 signal which was taken as a proxy for a Global Warming pattern. - an index for large scale regional circulation patterns (NAO index) could only to a small part explain the observed phenological variability in spring. The observed different trend behavior of early and late spring phases is explained by the differing behavior of mean March and April temperatures. Mean March temperatures have increased on average over the 20th century accompanied by an increasing variation in the last 50 years. April temperatures, however, decreased between the end of the 1940s and the mid-1980s, followed by a marked warming after the mid-1980s. It can be concluded that the advancement of spring phenology in recent decades are part of multi-decadal fluctuations over the 20th century that vary with the species and the relevant seasonal temperatures. Because of these fluctuations a correlation with an observed Global Warming signal could not be found. On average all investigated spring phases advanced between 5 and 20 days between 1951 and 1999 for all Natural Regions in Germany. A marked difference be! tween late and early spring phases is due to the above mentioned differing behavior before and after the mid-1980s. Leaf coloring (LC) was delayed between 1951 and 1984 for all tree species. However, after 1984 LC was advanced. Length of the VP increased between 1951 and 1999 for all considered tree species by an average of ten days throughout Germany. It is predominately the change in spring phases which contributes to a change in the potentially absorbed radiation. Additionally, it is the late spring species that are relatively more favored by an advanced BB because they can additionally exploit longer days and higher temperatures per day advancement. To assess the relative change in potentially absorbed radiation among species, changes in both spring and autumn phenology have to be considered as well as where these changes are located in the year. For the detection of the marked difference between early and late spring phenology a new time series construction method was developed. This method allowed the derivation of reliable time series that spanned over 100 years and the construction of locally combined time series increasing the available data for model development. Apart from analyzed protocolling errors, microclimatic site influences, genetic variation and the observers were identified as sources of uncertainty of phenological observational data. It was concluded that 99% of all phenological observations at a certain site will vary within approximately 24 days around the parametric mean. This supports to the proposed 30-day rule to detect outliers. New phenology models that predict local BB from daily temperature time series were developed. These models were based on simple interactions between inhibitory and promotory agents that are assumed to control the developmental status of a plant. Apart from the fact that, in general, the new models fitted and predicted the observations better than classical models, the main modeling results were: - The bias of the classical models, i.e. overestimation of early observations and underestimation of late observations, could be reduced but not completely removed. - The different favored model structures for each species indicated that for the late spring phases photoperiod played a more dominant role than for early spring phases. - Chilling only plays a subordinate role for spring BB compared to temperatures directly preceding BB.
Personal Big Data
(2017)
Many users of cloud-based services are concerned about questions of data privacy. At the same time, they want to benefit from smart data-driven services, which require insight into a person’s individual behaviour. The modus operandi of user modelling is that data is sent to a remote server where the model is constructed and merged with other users’ data. This thesis proposes selective cloud computing, an alternative approach, in which the user model is constructed on the client-side and only an abstracted generalised version of the model is shared with the remote services.
In order to demonstrate the applicability of this approach, the thesis builds an exemplary client-side user modelling technique. As this thesis is carried out in the area of Geoinformatics and spatio-temporal data is particularly sensitive, the application domain for this experiment is the analysis and prediction of a user’s spatio-temporal behaviour.
The user modelling technique is grounded in an innovative conceptual model, which builds upon spatial network theory combined with time-geography. The spatio-temporal constraints of time-geography are applied to the network structure in order to create individual spatio-temporal action spaces. This concept is translated into a novel algorithmic user modelling approach which is solely driven by the user’s own spatio-temporal trajectory data that is generated by the user’s smartphone.
While modern smartphones offer a rich variety of sensory data, this thesis only makes use of spatio-temporal trajectory data, enriched by activity classification, as the input and foundation for the algorithmic model. The algorithmic model consists of three basal components: locations (vertices), trips (edges), and clusters (neighbourhoods).
After preprocessing the incoming trajectory data in order to identify locations, user feedback is used to train an artificial neural network to learn temporal patterns for certain location types (e.g. work, home, bus stop, etc.). This Artificial Neural Network (ANN) is used to automatically detect future location types by their spatio-temporal patterns. The same is done in order to predict the duration of stay at a certain location. Experiments revealed that neural nets were the most successful statistical and machine learning tool to detect those patterns. The location type identification algorithm reached an accuracy of 87.69%, the duration prediction on binned data was less successful and deviated by an average of 0.69 bins. A challenge for the location type classification, as well as for the subsequent components, was the imbalance of trips and connections as well as the low accuracy of the trajectory data. The imbalance is grounded in the fact that most users exhibit strong habitual patterns (e.g. home > work), while other patterns are rather rare by comparison. The accuracy problem derives from the energy-saving location sampling mode, which creates less accurate results.
Those locations are then used to build a network that represents the user’s spatio-temporal behaviour. An initial untrained ANN to predict movement on the network only reached 46% average accuracy. Only lowering the number of included edges, focusing on more common trips, increased the performance. In order to further improve the algorithm, the spatial trajectories were introduced into the predictions. To overcome the accuracy problem, trips between locations were clustered into so-called spatial corridors, which were intersected with the user’s current trajectory. The resulting intersected trips were ranked through a k-nearest-neighbour algorithm. This increased the performance to 56%. In a final step, a combination of a network and spatial clustering algorithm was built in order to create clusters, therein reducing the variety of possible trips. By only predicting the destination cluster instead of the exact location, it is possible to increase the performance to 75% including all classes.
A final set of components shows in two exemplary ways how to deduce additional inferences from the underlying spatio-temporal data. The first example presents a novel concept for predicting the ‘potential memorisation index’ for a certain location. The index is based on a cognitive model which derives the index from the user’s activity data in that area. The second example embeds each location in its urban fabric and thereby enriches its cluster’s metadata by further describing the temporal-semantic activity in an area (e.g. going to restaurants at noon).
The success of the client-side classification and prediction approach, despite the challenges of inaccurate and imbalanced data, supports the claimed benefits of the client-side modelling concept. Since modern data-driven services at some point do need to receive user data, the thesis’ computational model concludes with a concept for applying generalisation to semantic, temporal, and spatial data before sharing it with the remote service in order to comply with the overall goal to improve data privacy. In this context, the potentials of ensemble training (in regards to ANNs) are discussed in order to highlight the potential of only sharing the trained ANN instead of the raw input data.
While the results of our evaluation support the assets of the proposed framework, there are two important downsides of our approach compared to server-side modelling. First, both of these server-side advantages are rooted in the server’s access to multiple users’ data. This allows a remote service to predict spatio-in the user-specific data, which represents the second downside. While minor classes will likely be minor classes in a bigger dataset as well, for each class, there will still be more variety than in the user-specific dataset. The author emphasises that the approach presented in this work holds the potential to change the privacy paradigm in modern data-driven services. Finding combinations of client- and server-side modelling could prove a promising new path for data-driven innovation.
Beyond the technological perspective, throughout the thesis the author also offers a critical view on the data- and technology-driven development of this work. By introducing the client-side modelling with user-specific artificial neural networks, users generate their own algorithm. Those user-specific algorithms are influenced less by generalised biases or developers’ prejudices. Therefore, the user develops a more diverse and individual perspective through his or her user model. This concept picks up the idea of critical cartography, which questions the status quo of how space is perceived and represented.
Urbanization and agricultural land use are two of the main drivers of global changes with effects on ecosystem functions and human wellbeing. Green Infrastructure is a new approach in spatial planning contributing to sustainable urban development, and to address urban challenges, such as biodiversity conservation, climate change adaptation, green economy development, and social cohesion. Because the research focus has been mainly on open green space structures, such as parks, urban forest, green building, street green, but neglected spatial and functional potentials of utilizable agricultural land, this thesis aims at fill this gap.
This cumulative thesis addresses how agricultural land in urban and peri-urban landscapes can contribute to the development of urban green infrastructure as a strategy to promote sustainable urban development. Therefore, a number of different research approaches have been applied. First, a quantitative, GIS-based modeling approach looked at spatial potentials, addressing the heterogeneity of peri-urban landscape that defines agricultural potentials and constraints. Second, a participatory approach was applied, involving stakeholder opinions to evaluate multiple urban functions and benefits. Finally, an evidence synthesis was conducted to assess the current state of research on evidence to support future policy making at different levels.
The results contribute to the conceptual understanding of urban green infrastructures as a strategic spatial planning approach that incorporates inner-urban utilizable agricultural land and the agriculturally dominated landscape at the outer urban fringe. It highlights the proposition that the linkage of peri-urban farmland with the green infrastructure concept can contribute to a network of multifunctional green spaces to provide multiple benefits to the urban system and to successfully address urban challenges. Four strategies are introduced for spatial planning with the contribution of peri-urban farmland to a strategically planned multifunctional network, namely the connecting, the productive, the integrated, and the adapted way. Finally, this thesis sheds light on the opportunities that arise from the integration of the peri- urban farmland in the green infrastructure concept to support transformation towards a more sustainable urban development. In particular, the inherent core planning principle of multifunctionality endorses the idea of co-benefits that are considered crucial to trigger transformative processes.
This work concludes that the linkage of peri-urban farmland with the green infrastructure concept is a promising action field for the development of new pathways for urban transformation towards sustainable urban development. Along with these outcomes, attention is drawn to limitations that remain to be addressed by future research, especially the identification of further mechanisms required to support policy integration at all levels.
Traditional ways of reducing flood risk have encountered limitations in a climate-changing and rapidly urbanizing world. For instance, there has been a demanding requirement for massive investment in order to maintain a consistent level of security as well as increased flood exposure of people and property due to a false sense of security arising from the flood protection infrastructure. Against this background, nature-based solutions (NBS) have gained popularity as a sustainable and alternative way of dealing with diverse societal challenges such as climate change and biodiversity loss. In particular, their ability to reduce flood risks while also offering ecological benefits has recently received global attention. Diverse co-benefits of NBS that favor both humans and nature are viewed as promising a wide endorsement of NBS. However, people’s perceptions of NBS are not always positive. Local resistance to NBS projects as well as decision-makers’ and practitioners’ unwillingness to adopt NBS have been pointed out as a bottleneck to the successful realization and mainstreaming of NBS. In this regard, there has been a growing necessity to investigate people’s perceptions of NBS. Current research has lacked an integrative perspective of both attitudinal and contextual factors that guide perceptions of NBS; it not only lacks empirical evidence, but a few existing ones are rather conflicting without having underlying theories. This has led to the overarching research question of this dissertation, "What shapes people’s perceptions of NBS in the context of flooding?" The dissertation aims to answer the following sub-questions in the three papers that make up this dissertation: 1. What are the topics reflected in the previous literature influencing perceptions of NBS as a means to reduce hydro-meteorological risks? (Paper I) 2. What are the stimulating and hampering attitudinal and contextual factors for mainstreaming NBS for flood risk management? How are NBS conceptualized? (Paper II) 3. How are public attitudes toward the NBS projects shaped? How do risk-and place-related factors shape individual attitudes toward NBS? (Paper III) This dissertation follows an integrative approach of considering “place” and “risk”, as well as the surrounding context, by analyzing attitudinal (i.e., individual) and contextual (i.e., systemic) factors. “Place” is mainly concerned with affective elements (e.g., bond to locality and natural environment) whereas “risk” is related to cognitive elements (e.g., threat appraisal). The surrounding context provides systemic drivers and barriers with the possibility of interfering the influence of place and risk for perceptions of NBS. To empirically address the research questions, the current status of the knowledge about people’s perceptions of NBS for flood risks was investigated by conducting a systematic review (Paper I). Based on these insights, a case study of South Korea was used to demonstrate key contextual and attitudinal factors for mainstreaming NBS through the lens of experts (Paper II). Lastly, by conducting a citizen survey, it investigated the relationship between the previously discussed concepts in Papers I and II using structural equation modeling, focusing on the core concepts, namely risk and place (Paper III). As a result, Paper I identified the key topics relating to people’s perceptions, including the perceived value of co-benefits, perceived effectiveness of risk reduction effectiveness, participation of stakeholders, socio-economic and place-specific conditions, environmental attitude, and uncertainty of NBS. Paper II confirmed Paper I's findings regarding attitudinal factors. In addition, several contextual hampering or stimulating factors were found to be similar to those of any emerging technologies (i.e., path dependence, lack of operational and systemic capacity). Among all, one of the distinctive features in NBS contexts, at least in the South Korean case, is the politicization of NBS, which can lead to polarization of ideas and undermine the decision-making process. Finally, Paper III provides a framework with the core topics (i.e., place and risk) that were considered critical in Paper I and Paper II. This place-based risk appraisal model (PRAM) connects people at risk and places where hazards (i.e., floods) and interventions (i.e., NBS) take place. The empirical analysis shows that, among the place-related variables, nature bonding was a positive predictor of the perceived risk-reduction effectiveness of NBS, and place identity was a negative predictor of supportive attitude. Among the risk-related variables, threat appraisal had a negative effect on perceived risk reduction effectiveness and supportive attitude, while well-communicated information, trust in flood risk management, and perceived co-benefit were positive predictors. This dissertation proves that the place and risk attributes of NBS shape people’s perceptions of NBS. In order to optimize the NBS implementation, it is necessary to consider the meanings and values held in place before project implementation and how these attributes interact with individual and/or community risk profiles and other contextual factors. With the increasing necessity of using NBS to lower flood risks, these results make important suggestions for the future NBS project strategy and NBS governance.
Uncertainty is an essential part of atmospheric processes and thus inherent to weather forecasts. Nevertheless, weather forecasts and warnings are still predominately issued as deterministic (yes or no) forecasts, although research suggests that providing weather forecast users with additional information about the forecast uncertainty can enhance the preparation of mitigation measures. Communicating forecast uncertainty would allow for a provision of information on possible future events at an earlier time. The desired benefit is to enable the users to start with preparatory protective action at an earlier stage of time based on the their own risk assessment and decision threshold. But not all users have the same threshold for taking action. In the course of the project WEXICOM (‘Wetterwarnungen: Von der Extremereignis-Information zu Kommunikation und Handlung’) funded by the Deutscher Wetterdienst (DWD), three studies were conducted between the years 2012 and 2016 to reveal how weather forecasts and warnings are reflected in weather-related decision-making. The studies asked which factors influence the perception of forecasts and the decision to take protective action and how forecast users make sense of probabilistic information and the additional lead time. In a first exploratory study conducted in 2012, members of emergency services in Germany were asked questions about how weather warnings are communicated to professional endusers in the emergency community and how the warnings are converted into mitigation measures. A large number of open questions were selected to identify new topics of interest. The questions covered topics like users’ confidence in forecasts, their understanding of probabilistic information as well as their lead time and decision thresholds to start with preparatory mitigation measures. Results show that emergency service personnel generally have a good sense of uncertainty inherent in weather forecasts. Although no single probability threshold could be identified for organisations to start with preparatory mitigation measures, it became clear that emergency services tend to avoid forecasts based on low probabilities as a basis for their decisions. Based on this findings, a second study conducted with residents of Berlin in 2014 further investigated the question of decision thresholds. The survey questions related to the topics of the perception of and prior experience with severe weather, trustworthiness of forecasters and confidence in weather forecasts, and socio-demographic and social-economic characteristics. Within the questionnaire a scenario was created to determine individual decision thresholds and see whether subgroups of the sample lead to different thresholds. The results show that people’s willingness to act tends to be higher and decision thresholds tend to be lower if the expected weather event is more severe or the property at risk is of higher value. Several influencing factors of risk perception have significant effects such as education, housing status and ability to act, whereas socio-demographic determinants alone are often not sufficient to fully grasp risk perception and protection behaviour. Parallel to the quantitative studies, an interview study was conducted with 27 members of German civil protection between 2012 and 2016. The results show that the latest developments in (numerical) weather forecasting do not necessarily fit the current practice of German emergency services. These practices are mostly carried out on alarms and ground truth in a reactive manner rather than on anticipation based on prognosis or forecasts. As the potential consequences rather than the event characteristics determine protective action, the findings support the call and need for impact-based warnings. Forecasters will rely on impact data and need to learn the users’ understanding of impact. Therefore, it is recommended to enhance weather communication not only by improving computer models and observation tools, but also by focusing on the aspects of communication and collaboration. Using information about uncertainty demands awareness about and acceptance of the limits of knowledge, hence, the capabilities of the forecaster to anticipate future developments of the atmosphere and the capabilities of the user to make sense of this information.
Parameterisierung atmosphärischer Grenzschichtprozesse in einem regionalen Klimamodell der Arktis
(1998)
High-mountain regions provide valuable ecosystem services, including food, water, and energy production, to more than 900 million people worldwide. Projections hold, that this population number will rapidly increase in the next decades, accompanied by a continued urbanisation of cities located in mountain valleys. One of the manifestations of this ongoing socio-economic change of mountain societies is a rise in settlement areas and transportation infrastructure while an increased power need fuels the construction of hydropower plants along rivers in the high-mountain regions of the world. However, physical processes governing the cryosphere of these regions are highly sensitive to changes in climate and a global warming will likely alter the conditions in the headwaters of high-mountain rivers. One of the potential implications of this change is an increase in frequency and magnitude of outburst floods – highly dynamic flows capable of carrying large amounts of water and sediments. Sudden outbursts from lakes formed behind natural dams are complex geomorphological processes and are often part of a hazard cascade. In contrast to other types of natural hazards in high-alpine areas, for example landslides or avalanches, outburst floods are highly infrequent. Therefore, observations and data describing for example the mode of outburst or the hydraulic properties of the downstream propagating flow are very limited, which is a major challenge in contemporary (glacial) lake outburst flood research. Although glacial lake outburst floods (GLOFs) and landslide-dammed lake outburst floods (LLOFs) are rare, a number of documented events caused high fatality counts and damage. The highest documented losses due to outburst floods since the start of the 20th century were induced by only a few high-discharge events. Thus, outburst floods can be a significant hazard to downvalley communities and infrastructure in high-mountain regions worldwide.
This thesis focuses on the Greater Himalayan region, a vast mountain belt stretching across 0.89 million km2. Although potentially hundreds of outburst floods have occurred there since the beginning of the 20th century, data on these events is still scarce. Projections of cryospheric change, including glacier-mass wastage and permafrost degradation, will likely result in an overall increase of the water volume stored in meltwater lakes as well as the destabilisation of mountain slopes in the Greater Himalayan region. Thus, the potential for outburst floods to affect the increasingly more densely populated valleys of this mountain belt is also likely to increase in the future. A prime example of one of these valleys is the Pokhara valley in Nepal, which is drained by the Seti Khola, a river crossing one of the steepest topographic gradients in the Himalayas. This valley is also home to Nepal’s second largest, rapidly growing city, Pokhara, which currently has a population of more than half a million people – some of which live in informal settlements within the floodplain of the Seti Khola. Although there is ample evidence for past outburst floods along this river in recent and historic times, these events have hardly been quantified.
The main motivation of my thesis is to address the data scarcity on past and potential future outburst floods in the Greater Himalayan region, both at a regional and at a local scale. For the former, I compiled an inventory of >3,000 moraine-dammed lakes, of which about 1% had a documented sudden failure in the past four decades. I used this data to test whether a number of predictors that have been widely applied in previous GLOF assessments are statistically relevant when estimating past GLOF susceptibility. For this, I set up four Bayesian multi-level logistic regression models, in which I explored the credibility of the predictors lake area, lake-area dynamics, lake elevation, parent-glacier-mass balance, and monsoonality. By using a hierarchical approach consisting of two levels, this probabilistic framework also allowed for spatial variability on GLOF susceptibility across the vast study area, which until now had not been considered in studies of this scale. The model results suggest that in the Nyainqentanglha and Eastern Himalayas – regions with strong negative glacier-mass balances – lakes have been more prone to release GLOFs than in regions with less negative or even stable glacier-mass balances. Similarly, larger lakes in larger catchments had, on average, a higher probability to have had a GLOF in the past four decades. Yet, monsoonality, lake elevation, and lake-area dynamics were more ambiguous. This challenges the credibility of a lake’s rapid growth in surface area as an indicator of a pending outburst; a metric that has been applied to regional GLOF assessments worldwide.
At a local scale, my thesis aims to overcome data scarcity concerning the flow characteristics of the catastrophic May 2012 flood along the Seti Khola, which caused 72 fatalities, as well as potentially much larger predecessors, which deposited >1 km³ of sediment in the Pokhara valley between the 12th and 14th century CE. To reconstruct peak discharges, flow depths, and flow velocities of the 2012 flood, I mapped the extents of flood sediments from RapidEye satellite imagery and used these as a proxy for inundation limits. To constrain the latter for the Mediaeval events, I utilised outcrops of slackwater deposits in the fills of tributary valleys. Using steady-state hydrodynamic modelling for a wide range of plausible scenarios, from meteorological (1,000 m³ s-1) to cataclysmic outburst floods (600,000 m³ s-1), I assessed the likely initial discharges of the recent and the Mediaeval floods based on the lowest mismatch between sedimentary evidence and simulated flood limits. One-dimensional HEC-RAS simulations suggest, that the 2012 flood most likely had a peak discharge of 3,700 m³ s-1 in the upper Seti Khola and attenuated to 500 m³ s-1 when arriving in Pokhara’s suburbs some 15 km downstream.
Simulations of flow in two-dimensions with orders of magnitude higher peak discharges in ANUGA show extensive backwater effects in the main tributary valleys. These backwater effects match the locations of slackwater deposits and, hence, attest for the flood character of Mediaeval sediment pulses. This thesis provides first quantitative proof for the hypothesis, that the latter were linked to earthquake-triggered outbursts of large former lakes in the headwaters of the Seti Khola – producing floods with peak discharges of >50,000 m³ s-1.
Building on this improved understanding of past floods along the Seti Khola, my thesis continues with an analysis of the impacts of potential future outburst floods on land cover, including built-up areas and infrastructure mapped from high-resolution satellite and OpenStreetMap data. HEC-RAS simulations of ten flood scenarios, with peak discharges ranging from 1,000 to 10,000 m³ s-1, show that the relative inundation hazard is highest in Pokhara’s north-western suburbs. There, the potential effects of hydraulic ponding upstream of narrow gorges might locally sustain higher flow depths. Yet, along this reach, informal settlements and gravel mining activities are close to the active channel. By tracing the construction dynamics in two of these potentially affected informal settlements on multi-temporal RapidEye, PlanetScope, and Google Earth imagery, I found that exposure increased locally between three- to twentyfold in just over a decade (2008 to 2021).
In conclusion, this thesis provides new quantitative insights into the past controls on the susceptibility of glacial lakes to sudden outburst at a regional scale and the flow dynamics of propagating flood waves released by past events at a local scale, which can aid future hazard assessments on transient scales in the Greater Himalayan region. My subsequent exploration of the impacts of potential future outburst floods to exposed infrastructure and (informal) settlements might provide valuable inputs to anticipatory assessments of multiple risks in the Pokhara valley.
The Himalayas are a region that is most dependent, but also frequently prone to hazards from changing meltwater resources. This mountain belt hosts the highest mountain peaks on earth, has the largest reserve of ice outside the polar regions, and is home to a rapidly growing population in recent decades. One source of hazard has attracted scientific research in particular in the past two decades: glacial lake outburst floods (GLOFs) occurred rarely, but mostly with fatal and catastrophic consequences for downstream communities and infrastructure. Such GLOFs can suddenly release several million cubic meters of water from naturally impounded meltwater lakes. Glacial lakes have grown in number and size by ongoing glacial mass losses in the Himalayas. Theory holds that enhanced meltwater production may increase GLOF frequency, but has never been tested so far. The key challenge to test this notion are the high altitudes of >4000 m, at which lakes occur, making field work impractical. Moreover, flood waves can attenuate rapidly in mountain channels downstream, so that many GLOFs have likely gone unnoticed in past decades. Our knowledge on GLOFs is hence likely biased towards larger, destructive cases, which challenges a detailed quantification of their frequency and their response to atmospheric warming. Robustly quantifying the magnitude and frequency of GLOFs is essential for risk assessment and management along mountain rivers, not least to implement their return periods in building design codes.
Motivated by this limited knowledge of GLOF frequency and hazard, I developed an algorithm that efficiently detects GLOFs from satellite images. In essence, this algorithm classifies land cover in 30 years (~1988–2017) of continuously recorded Landsat images over the Himalayas, and calculates likelihoods for rapidly shrinking water bodies in the stack of land cover images. I visually assessed such detected tell-tale sites for sediment fans in the river channel downstream, a second key diagnostic of GLOFs. Rigorous tests and validation with known cases from roughly 10% of the Himalayas suggested that this algorithm is robust against frequent image noise, and hence capable to identify previously unknown GLOFs. Extending the search radius to the entire Himalayan mountain range revealed some 22 newly detected GLOFs. I thus more than doubled the existing GLOF count from 16 previously known cases since 1988, and found a dominant cluster of GLOFs in the Central and Eastern Himalayas (Bhutan and Eastern Nepal), compared to the rarer affected ranges in the North. Yet, the total of 38 GLOFs showed no change in the annual frequency, so that the activity of GLOFs per unit glacial lake area has decreased in the past 30 years. I discussed possible drivers for this finding, but left a further attribution to distinct GLOF-triggering mechanisms open to future research.
This updated GLOF frequency was the key input for assessing GLOF hazard for the entire Himalayan mountain belt and several subregions. I used standard definitions in flood hydrology, describing hazard as the annual exceedance probability of a given flood peak discharge [m3 s-1] or larger at the breach location. I coupled the empirical frequency of GLOFs per region to simulations of physically plausible peak discharges from all existing ~5,000 lakes in the Himalayas. Using an extreme-value model, I could hence calculate flood return periods. I found that the contemporary 100-year GLOF discharge (the flood level that is reached or exceeded on average once in 100 years) is 20,600+2,200/–2,300 m3 s-1 for the entire Himalayas. Given the spatial and temporal distribution of historic GLOFs, contemporary GLOF hazard is highest in the Eastern Himalayas, and lower for regions with rarer GLOF abundance. I also calculated GLOF hazard for some 9,500 overdeepenings, which could expose and fill with water, if all Himalayan glaciers have melted eventually. Assuming that the current GLOF rate remains unchanged, the 100-year GLOF discharge could double (41,700+5,500/–4,700 m3 s-1), while the regional GLOF hazard may increase largest in the Karakoram.
To conclude, these three stages–from GLOF detection, to analysing their frequency and estimating regional GLOF hazard–provide a framework for modern GLOF hazard assessment. Given the rapidly growing population, infrastructure, and hydropower projects in the Himalayas, this thesis assists in quantifying the purely climate-driven contribution to hazard and risk from GLOFs.
Permafrost, defined as ground that is frozen for at least two consecutive years, is a distinct feature of the terrestrial unglaciated Arctic. It covers approximately one quarter of the land area of the Northern Hemisphere (23,000,000 km²). Arctic landscapes, especially those underlain by permafrost, are threatened by climate warming and may degrade in different ways, including active layer deepening, thermal erosion, and development of rapid thaw features. In Siberian and Alaskan late Pleistocene ice-rich Yedoma permafrost, rapid and deep thaw processes (called thermokarst) can mobilize deep organic carbon (below 3 m depth) by surface subsidence due to loss of ground ice. Increased permafrost thaw could cause a feedback loop of global significance if its stored frozen organic carbon is reintroduced into the active carbon cycle as greenhouse gases, which accelerate warming and inducing more permafrost thaw and carbon release. To assess this concern, the major objective of the thesis was to enhance the understanding of the origin of Yedoma as well as to assess the associated organic carbon pool size and carbon quality (concerning degradability). The key research questions were:
- How did Yedoma deposits accumulate?
- How much organic carbon is stored in the Yedoma region?
- What is the susceptibility of the Yedoma region's carbon for future decomposition?
To address these three research questions, an interdisciplinary approach, including detailed field studies and sampling in Siberia and Alaska as well as methods of sedimentology, organic biogeochemistry, remote sensing, statistical analyses, and computational modeling were applied. To provide a panarctic context, this thesis additionally includes results both from a newly compiled northern circumpolar carbon database and from a model assessment of carbon fluxes in a warming Arctic.
The Yedoma samples show a homogeneous grain-size composition. All samples were poorly sorted with a multi-modal grain-size distribution, indicating various (re-) transport processes. This contradicts the popular pure loess deposition hypothesis for the origin of Yedoma permafrost. The absence of large-scale grinding processes via glaciers and ice sheets in northeast Siberian lowlands, processes which are necessary to create loess as material source, suggests the polygenetic origin of Yedoma deposits.
Based on the largest available data set of the key parameters, including organic carbon content, bulk density, ground ice content, and deposit volume (thickness and coverage) from Siberian and Alaskan study sites, this thesis further shows that deep frozen organic carbon in the Yedoma region consists of two distinct major reservoirs, Yedoma deposits and thermokarst deposits (formed in thaw-lake basins). Yedoma deposits contain ~80 Gt and thermokarst deposits ~130 Gt organic carbon, or a total of ~210 Gt. Depending on the approach used for calculating uncertainty, the range for the total Yedoma region carbon store is ±75 % and ±20 % for conservative single and multiple bootstrapping calculations, respectively. Despite the fact that these findings reduce the Yedoma region carbon pool by nearly a factor of two compared to previous estimates, this frozen organic carbon is still capable of inducing a permafrost carbon feedback to climate warming. The complete northern circumpolar permafrost region contains between 1100 and 1500 Gt organic carbon, of which ~60 % is perennially frozen and decoupled from the short-term carbon cycle.
When thawed and reintroduced into the active carbon cycle, the organic matter qualities become relevant. Furthermore, results from investigations into Yedoma and thermokarst organic matter quality studies showed that Yedoma and thermokarst organic matter exhibit no depth-dependent quality trend. This is evidence that after freezing, the ancient organic matter is preserved in a state of constant quality. The applied alkane and fatty-acid-based biomarker proxies including the carbon-preference and the higher-land-plant-fatty-acid indices show a broad range of organic matter quality and thus no significantly different qualities of the organic matter stored in thermokarst deposits compared to Yedoma deposits. This lack of quality differences shows that the organic matter biodegradability depends on different decomposition trajectories and the previous decomposition/incorporation history. Finally, the fate of the organic matter has been assessed by implementing deep carbon pools and thermokarst processes in a permafrost carbon model. Under various warming scenarios for the northern circumpolar permafrost region, model results show a carbon release from permafrost regions of up to ~140 Gt and ~310 Gt by the years 2100 and 2300, respectively. The additional warming caused by the carbon release from newly-thawed permafrost contributes 0.03 to 0.14°C by the year 2100. The model simulations predict that a further increase by the 23rd century will add 0.4°C to global mean surface air temperatures.
In conclusion, Yedoma deposit formation during the late Pleistocene was dominated by water-related (alluvial/fluvial/lacustrine) as well as aeolian processes under periglacial conditions. The circumarctic permafrost region, including the Yedoma region, contains a substantial amount of currently frozen organic carbon. The carbon of the Yedoma region is well-preserved and therefore available for decomposition after thaw. A missing quality-depth trend shows that permafrost preserves the quality of ancient organic matter. When the organic matter is mobilized by deep degradation processes, the northern permafrost region may add up to 0.4°C to the global warming by the year 2300.
Extreme weather and climate events are one of the greatest dangers for present-day society. Therefore, it is important to provide reliable statements on what changes in extreme events can be expected along with future global climate change. However, the projected overall response to future climate change is generally a result of a complex interplay between individual physical mechanisms originated within the different climate subsystems. Hence, a profound understanding of these individual contributions is required in order to provide meaningful assessments of future changes in extreme events. One aspect of climate change is the recently observed phenomenon of Arctic Amplification and the related dramatic Arctic sea ice decline, which is expected to continue over the next decades. The question to what extent Arctic sea ice loss is able to affect atmospheric dynamics and extreme events over mid-latitudes has received a lot of attention over recent years and still remains a highly debated topic.
In this respect, the objective of this thesis is to contribute to a better understanding on the impact of future Arctic sea ice retreat on European temperature extremes and large-scale atmospheric dynamics.
The outcomes are based on model data from the atmospheric general circulation model ECHAM6. Two different sea ice sensitivity simulations from the Polar Amplification Intercomparison Project are employed and contrasted to a present day reference experiment: one experiment with prescribed future sea ice loss over the entire Arctic, as well as another one with sea ice reductions only locally prescribed over the Barents-Kara Sea.% prescribed over the entire Arctic, as well as only locally over the Barent/Karasea with a present day reference experiment.
The first part of the thesis focuses on how future Arctic sea ice reductions affect large-scale atmospheric dynamics over the Northern Hemisphere in terms of occurrence frequency changes of five preferred Euro-Atlantic circulation regimes. When compared to circulation regimes computed from ERA5 it shows that ECHAM6 is able to realistically simulate the regime structures. Both ECHAM6 sea ice sensitivity experiments exhibit similar regime frequency changes. Consistent with tendencies found in ERA5, a more frequent occurrence of a Scandinavian blocking pattern in midwinter is for instance detected under future sea ice conditions in the sensitivity experiments. Changes in occurrence frequencies of circulation regimes in summer season are however barely detected.
After identifying suitable regime storylines for the occurrence of European temperature extremes in winter, the previously detected regime frequency changes are used to quantify dynamically and thermodynamically driven contributions to sea ice-induced changes in European winter temperature extremes.
It is for instance shown how the preferred occurrence of a Scandinavian blocking regime under low sea ice conditions dynamically contributes to more frequent midwinter cold extreme occurrences over Central Europe. In addition, a reduced occurrence frequency of a Atlantic trough regime is linked to reduced winter warm extremes over Mid-Europe. Furthermore, it is demonstrated how the overall thermodynamical warming effect due to sea ice loss can result in less (more) frequent winter cold (warm) extremes, and consequently counteracts the dynamically induced changes.
Compared to winter season, circulation regimes in summer are less suitable as storylines for the occurrence of summer heat extremes.
Therefore, an approach based on circulation analogues is employed in order to quantify thermodyamically and dynamically driven contributions to sea ice-induced changes of summer heat extremes over three different European sectors. Reduced occurrences of blockings over Western Russia are detected in the ECHAM6 sea ice sensitivity experiments; however, arguing for dynamically and thermodynamically induced contributions to changes in summer heat extremes remains rather challenging.
The urban heat island (UHI) effect, describing an elevated temperature of urban areas compared with their natural surroundings, can expose urban dwellers to additional heat stress, especially during hot summer days. A comprehensive understanding of the UHI dynamics along with urbanization is of great importance to efficient heat stress mitigation strategies towards sustainable urban development. This is, however, still challenging due to the difficulties of isolating the influences of various contributing factors that interact with each other. In this work, I present a systematical and quantitative analysis of how urban intrinsic properties (e.g., urban size, density, and morphology) influence UHI intensity.
To this end, we innovatively combine urban growth modelling and urban climate simulation to separate the influence of urban intrinsic factors from that of background climate, so as to focus on the impact of urbanization on the UHI effect. The urban climate model can create a laboratory environment which makes it possible to conduct controlled experiments to separate the influences from different driving factors, while the urban growth model provides detailed 3D structures that can be then parameterized into different urban development scenarios tailored for these experiments. The novelty in the methodology and experiment design leads to the following achievements of our work.
First, we develop a stochastic gravitational urban growth model that can generate 3D structures varying in size, morphology, compactness, and density gradient. We compare various characteristics, like fractal dimensions (box-counting, area-perimeter scaling, area-population scaling, etc.), and radial gradient profiles of land use share and population density, against those of real-world cities from empirical studies. The model shows the capability of creating 3D structures resembling real-world cities. This model can generate 3D structure samples for controlled experiments to assess the influence of some urban intrinsic properties in question. [Chapter 2]
With the generated 3D structures, we run several series of simulations with urban structures varying in properties like size, density and morphology, under the same weather conditions. Analyzing how the 2m air temperature based canopy layer urban heat island (CUHI) intensity varies in response to the changes of the considered urban factors, we find the CUHI intensity of a city is directly related to the built-up density and an amplifying effect that urban sites have on each other. We propose a Gravitational Urban Morphology (GUM) indicator to capture the neighbourhood warming effect. We build a regression model to estimate the CUHI intensity based on urban size, urban gross building volume, and the GUM indicator. Taking the Berlin area as an example, we show the regression model capable of predicting the CUHI intensity under various urban development scenarios. [Chapter 3]
Based on the multi-annual average summer surface urban heat island (SUHI) intensity derived from Land surface temperature, we further study how urban intrinsic factors influence the SUHI effect of the 5,000 largest urban clusters in Europe. We find a similar 3D GUM indicator to be an effective predictor of the SUHI intensity of these European cities. Together with other urban factors (vegetation condition, elevation, water coverage), we build different multivariate linear regression models and a climate space based Geographically Weighted Regression (GWR) model that can better predict SUHI intensity. By investigating the roles background climate factors play in modulating the coefficients of the GWR model, we extend the multivariate linear model to a nonlinear one by integrating some climate parameters, such as the average of daily maximal temperature and latitude. This makes it applicable across a range of background climates. The nonlinear model outperforms linear models in SUHI assessment as it captures the interaction of urban factors and the background climate. [Chapter 4]
Our work reiterates the essential roles of urban density and morphology in shaping the urban thermal environment. In contrast to many previous studies that link bigger cities with higher UHI intensity, we show that cities larger in the area do not necessarily experience a stronger UHI effect. In addition, the results extend our knowledge by demonstrating the influence of urban 3D morphology on the UHI effect. This underlines the importance of inspecting cities as a whole from the 3D perspective. While urban 3D morphology is an aggregated feature of small-scale urban elements, the influence it has on the city-scale UHI intensity cannot simply be scaled up from that of its neighbourhood-scale components. The spatial composition and configuration of urban elements both need to be captured when quantifying urban 3D morphology as nearby neighbourhoods also cast influences on each other. Our model serves as a useful UHI assessment tool for the quantitative comparison of urban intervention/development scenarios. It can support harnessing the capacity of UHI mitigation through optimizing urban morphology, with the potential of integrating climate change into heat mitigation strategies.
Human transformation of the Earth’s land surface has far-reaching and important consequences for the functioning of hydrological and hydrochemical processes in watersheds. In nowadays land-use change from forest to pasture is a major issue in particular in the tropics. A sustainable management of deforested areas requires an in-depth understanding of the water and nutrient cycle. On this basis we compared the involved hydrological pathways for rainfall to reach streams and the nutrient budgets of a tropical rainforest and a pasture. In addition we studied the links of hydrochemical differences to differences of the relative importance of flowpaths. This study was conducted in the southwestern part of the Brazilian Amazon basin. An intensive hydrological and hydrochemical sampling and monitoring network was set up. The results indicate that the hydrology was modified in many ways due to land-use change. The most important alteration was the increased importance of the fast flowpath overland flow. Solute exports were in particular linked to the increased volume of overland flow that resulted from the land-use change. An additional reason for the increased nutrient exports from the pasture are the high concentrations of these nutrients in pasture overland flow probably as a due to cattle excrements. Tight nutrient cycles with minimal nutrient losses could not be maintained after the land-use change. This study provides the first attempt to quantify the respective nutrient losses.
In this dissertation, I describe the mechanisms involved in magmatic plumbing system establishment and evolution. Magmatic plumbing systems play a key role in determining volcanic activity style and recognizing its complexities can help in forecasting eruptions, especially within hazardous volcanic systems such as calderas. I explore the mechanisms of dike emplacement and intrusion geometry that shape magmatic plumbing systems beneath caldera-like topographies and how their characteristics relate to precursory activity of a volcanic eruption. For this purpose, I use scaled laboratory models to study the effect of stress field reorientation on a propagating dike induced by caldera topography. I construct these models by using solid gelatin to mimic the elastic properties of the earth's crust with a caldera on the surface. I inject water as the magma analog and track the evolution of the experiments through qualitative (geometry and stress evolution) and quantitative (displacement and strain computation) descriptions. The results show that a vertical dike deviates towards and outside of the caldera-like margin due to stress field reorientation beneath the caldera-like topography. The propagating intrusion forms a circumferential-eruptive dike when the caldera-like size is small, whereas a cone sheet develops beneath the large caldera-like topography.
To corroborate the results obtained from the experimental models, this thesis also describes the results of a case study utilizing seismic monitoring data associated with the unrest period of the 2015 phreatic eruption of Lascar volcano. Lascar has a crater with a small-scale caldera-like topography and exhibited long-lasting anomalous evolution of the number of long-period (LP) events preceding the 2015 eruption. I apply seismic techniques to constrain the hypocentral locations of LP events and characterize their spatial distribution, obtaining an image of Lascar's plumbing system. I observe an agreement in shallow hypocentral locations obtained through four different seismic techniques; nevertheless, the cross-correlation technique provides the best results. These results depict a plumbing system with a narrow sub-vertical deep conduit and a shallow hydrothermal system, where most LP events are located. These two regions are connected through an intermediate region of path divergence, whose geometry and orientation likely is influenced by stress reorientation due to topographic effects of the caldera-like crater.
Finally, in order to further enhance the interpretations of the previous case study, the seismic data was analyzed in tandem with a complementary multiparametric monitoring dataset. This complementary study confirms that the anomalous LP activity occurred as a sign of unrest in the preparatory phase of the phreatic eruption. In addition, I show how changes observed in other monitored parameters enabled to detect further signs of unrest in the shallow hydrothermal system. Overall, this study demonstrates that detecting complex geometric regions within plumbing systems beneath volcanoes is fundamental to produce an effective forecast of eruptions that from a first view seem to occur without any precursory activity.
Furthermore, through the development of this research I show that combining methods that include both observations and models allows one to obtain a more precise interpretation of the volcanic processes.
Chemical transformations and hydraulic processes in soil and groundwater often lead to an apparent retention of nitrate in lowland catchments. Models are needed to evaluate the interaction of these processes in space and time. The objectives of this study are i) to develop a specific modelling approach by combining selected modelling tools simulating N-transport and turnover in soils and groundwater of lowland catchments, ii) to study interactions between catchment properties and nitrogen transport. Special attention was paid to potential N-loads to surface waters. The modelling approach combines various submodels for water flow and solute transport in soil and groundwater: The soil-water- and nitrogen-model mRISK-N, the groundwater flow model MODFLOW and the solute transport model RT3D. In order to investigate interactions of N-transport and catchment characteristics, the distribution and availability of reaction partners have to be taken into account. Therefore, a special reaction-module is developed, which simulates various chemical processes in groundwater, such as the degradation of organic matter by oxygen, nitrate, sulphate or pyrite oxidation by oxygen and nitrate. The model approach is applied to different simulation, focussing on specific submodels. All simulation studies are based on field data from the Schaugraben catchment, a pleistocene catchment of approximately 25 km², close to Osterburg(Altmark) in the North of Saxony-Anhalt. The following modelling studies have been carried out: i) evaluation of the soil-water- and nitrogen-model based on lysimeter data, ii) modelling of a field scale tracer experiment on nitrate transport and turnover in the groundwater as a first application of the reaction module, iii) evaluation of interactions between hydraulic and chemical aquifer properties in a two-dimensional groundwater transect, iv) modelling of distributed groundwater recharge and soil nitrogen leaching in the study area, to be used as input data for subsequent groundwater simulations, v) study of groundwater nitrate distribution and nitrate breakthrough to the surface water system in the Schaugraben catchment area and a subcatchment, using three-dimensional modelling of reactive groundwater transport. The various model applications prove the model to be capable of simulating interactions between transport, turnover and hydraulic and chemical catchment properties. The distribution of nitrate in the sediment and the resulting loads to surface waters are strongly affected by the amount of reactive substances and by the residence time within the aquifer. In the Schaugraben catchment simulations, it is found that a period of 70 years is needed to raise the average seepage concentrations of nitrate to a level corresponding to the given input situation, if no reactions are considered. Under reactive transport conditions, nitrate concentrations are reduced effectively. Simulation results show that groundwater exfiltration does not contribute considerably to the nitrate pollution of surface waters, as most nitrate entering soils and groundwater is lost by denitrification. Additional sources, such as direct inputs or tile drains have to be taken into account to explain surface water loads. The prognostic value of the models for the study site is limited by uncertainties of input data and estimation of model parameters. Nevertheless, the modelling approach is a useful aid for the identification of source and sink areas of nitrate pollution as well as the investigation of system response to management measures or landuse changes with scenario simulations. The modelling approach assists in the interpretation of observed data, as it allows to integrate local observations into a spatial and temporal framework.
The North China Plain (NCP) is one of the most productive and intensive agricultural regions in China. High doses of mineral nitrogen (N) fertiliser, often combined with flood irrigation, are applied, resulting in N surplus, groundwater depletion and environmental pollution. The objectives of this thesis were to use the HERMES model to simulate the N cycle in winter wheat (Triticum aestivum L.)–summer maize (Zea mays L.) double crop rotations and show the performance of the HERMES model, of the new ammonia volatilisation sub-module and of the new nitrification inhibition tool in the NCP. Further objectives were to assess the models potential to save N and water on plot and county scale, as well as on short and long-term. Additionally, improved management strategies with the help of a model-based nitrogen fertiliser recommendation (NFR) and adapted irrigation, should be found.
Results showed that the HERMES model performed well under growing conditions of the NCP and was able to describe the relevant processes related to soil–plant interactions concerning N and water during a 2.5 year field experiment. No differences in grain yield between the real-time model-based NFR and the other treatments of the experiments on plot scale in Quzhou County could be found. Simulations with increasing amounts of irrigation resulted in significantly higher N leaching, higher N requirements of the NFR and reduced yields. Thus, conventional flood irrigation as currently practised by the farmers bears great uncertainties and exact irrigation amounts should be known for future simulation studies. In the best-practice scenario simulation on plot-scale, N input and N leaching, but also irrigation water could be reduced strongly within 2 years. Thus, the model-based NFR in combination with adapted irrigation had the highest potential to reduce nitrate leaching, compared to farmers practice and mineral N (Nmin)-reduced treatments. Also the calibrated and validated ammonia volatilisation sub-module of the HERMES model worked well under the climatic and soil conditions of northern China. Simple ammonia volatilisation approaches gave also satisfying results compared to process-oriented approaches. During the simulation with Ammonium sulphate Nitrate with nitrification inhibitor (ASNDMPP) ammonia volatilisation was higher than in the simulation without nitrification inhibitor, while the result for nitrate leaching was the opposite. Although nitrification worked well in the model, nitrification-born nitrous oxide emissions should be considered in future. Results of the simulated annual long-term (31 years) N losses in whole Quzhou County in Hebei Province were 296.8 kg N ha−1 under common farmers practice treatment and 101.7 kg N ha−1 under optimised treatment including NFR and automated irrigation (OPTai). Spatial differences in simulated N losses throughout Quzhou County, could only be found due to different N inputs. Simulations of an optimised treatment, could save on average more than 260 kg N ha−1a−1 from fertiliser input and 190 kg N ha−1a−1 from N losses and around 115.7 mm a−1 of water, compared to farmers practice. These long-term simulation results showed lower N and water saving potential, compared to short-term simulations and underline the necessity of long-term simulations to overcome the effect of high initial N stocks in soil.
Additionally, the OPTai worked best on clay loam soil except for a high simulated denitrification loss, while the simulations using farmers practice irrigation could not match the actual water needs resulting in yield decline, especially for winter wheat. Thus, a precise adaption of management to actual weather conditions and plant growth needs is necessary for future simulations. However, the optimised treatments did not seem to be able to maintain the soil organic matter pools, even with full crop residue input. Extra organic inputs seem to be required to maintain soil quality in the optimised treatments.
HERMES is a relatively simple model, with regard to data input requirements, to simulate the N cycle. It can offer interpretation of management options on plot, on county and regional scale for extension and research staff. Also in combination with other N and water saving methods the model promises to be a useful tool.
Seit 1990 waren mehrere der großen Flussgebiete Mitteleuropas wiederholt von extremen Hochwassern betroffen. Da sowohl die Landoberfläche als auch die Flusssysteme weiter Teile Mitteleuropas in der Vergangenheit weitreichenden Eingriffen ausgesetzt gewesen sind, wird bei der Suche nach den Ursachen für diese Häufung von Extremereignissen auch die Frage nach der Verantwortung des Menschen hierfür diskutiert. Gewässerausbau, Flächenversiegelung, intensive landwirtschaftliche Bodenbearbeitung, Flurbereinigung und Waldschäden sind nur einige Beispiele und Folgen der anthropogenen Eingriffe in die Landschaft. Aufgrund der Vielfalt der beteiligten Prozesse und deren Wechselwirkungen gibt es allerdings bislang nur Schätzungen darüber, wie sehr sich die Hochwassersituation hierdurch verändert hat. Vorrangiges Ziel dieser Arbeit ist es, mit Hilfe eines hydrologischen Modells systematisch darzustellen, in welcher Weise, in welcher Größenordnung und unter welchen Umständen die Art der Landnutzung auf die Hochwasserentstehung Einfluss nimmt. Dies wird anhand exemplarischer Modellanwendungen in der hydrologischen Mesoskala untersucht. Zu diesem Zweck wurde das deterministische und flächendifferenzierte hydrologische Modell wasim-eth ausgewählt, das sich durch eine ausgewogene Mischung aus physikalisch begründeten und konzeptionellen Ansätzen auszeichnet. Das Modell wurde im Rahmen dieser Arbeit um verschiedene Aspekte erweitert, die für die Charakterisierung des Einflusses der Landnutzung auf die Hochwasserentstehung wichtig sind: (1) Bevorzugtes Fließen in Makroporen wird durch eine Zweiteilung des Bodens in Makroporen und Bodenmatrix dargestellt, die schnelle Infiltration und Perkolation jenseits der hydraulischen Leitfähigkeit der Bodenmatrix ermöglicht. (2) Verschlämmung äußert sich im Modell abhängig von Niederschlagsintensität und Vegetationsbedeckungsgrad als Verschlechterung der Infiltrationsbedingungen an der Bodenoberfläche. (3) Das heterogene Erscheinungsbild bebauter Flächen mit einer Mischung aus versiegelten Bereichen und Freiflächen wird berücksichtigt, indem jede Teilfläche je nach Versiegelungsgrad in einen unversiegelten Bereich und einen versiegelten Bereich mit Anschluss an die Kanalisation aufgeteilt wird. (4) Dezentraler Rückhalt von Niederschlagswasser kann sowohl für natürliche Mulden als auch für gezielt angelegte Versickerungsmulden mit definierten Infiltrationsbedingungen simuliert werden. Das erweiterte Modell wird exemplarisch auf drei mesoskalige Teileinzugsgebiete des Rheins angewandt. Diese drei Gebiete mit einer Fläche von zwischen 100 und 500 km² wurden im Hinblick darauf ausgewählt, dass jeweils eine der drei Hauptlandnutzungskategorien Bebauung, landwirtschaftliche Nutzung oder Wald dominiert. Für die drei Untersuchungsgebiete sind räumlich explizite Landnutzungs- und Landbedeckungsszenarien entworfen worden, deren Einfluss auf die Hochwasserentstehung mit Hilfe des erweiterten hydrologischen Modells simuliert wird. Im Einzelnen werden die Auswirkungen von Verstädterung, Maßnahmen zur Niederschlagsversickerung in Siedlungsgebieten, Stilllegung agrarisch genutzter Flächen, veränderter landwirtschaftlicher Bodenbearbeitung, Aufforstung sowie von Sturmschäden in Wäldern untersucht. Diese Eingriffe beeinflussen die Interzeption von Niederschlag, dessen Infiltration, die oberflächennahen unterirdischen Fließprozesse sowie, zum Beispiel im Fall der Kanalisation, auch die Abflusskonzentration. Die hydrologischen Simulationen demonstrieren, dass die Versiegelung einer Fläche den massivsten Eingriff in die natürlichen Verhältnisse darstellt und deshalb die stärksten (negativen) Veränderungen der Hochwassersituation hervorbringt. Außerdem wird deutlich, dass eine bloße Änderung des Interzeptionsvermögens zu keinen wesentlichen Veränderungen führt, da die Speicherkapazität der Pflanzenoberflächen im Verhältnis zum Volumen hochwasserauslösender Niederschläge eher klein ist. Stärkere Veränderungen ergeben sich hingegen aus einer Änderung der Infiltrationsbedingungen. Die Grenzen der entwickelten Methodik zeigen sich am deutlichsten bei der Simulation veränderter landwirtschaftlicher Bewirtschaftungsmethoden, deren mathematische Beschreibung und zahlenmäßige Charakterisierung aufgrund der Komplexität der beteiligten Prozesse mit großen Unsicherheiten behaftet ist. Die Modellierungsergebnisse belegen darüber hinaus, dass pauschale Aussagen zum Einfluss der Landnutzung auf die Hochwasserentstehung aufgrund der entscheidenden Bedeutung der klimatischen und physiographischen Randbedingungen unzulässig sind. Zu den klimatischen Randbedingungen zählen sowohl Niederschlagsintensität und -dauer als auch die Feuchtebedingungen vor einem hochwasserauslösenden Niederschlag. Die physiographischen Randbedingungen sind von der geomorphologischen und geologischen Ausstattung des Gebiets vorgegeben. Weiterhin muss der räumliche und zeitliche Maßstab, über den Aussagen getroffen werden, klar definiert sein, da sich mit steigender Einzugsgebietsgröße die relative Bedeutung sowohl der verschiedenen Niederschlagstypen als auch der physiographischen Eigenschaften verschiebt. Dies wird in der vorliegenden Arbeit im Gegensatz zu vielen anderen Untersuchungen konsequent berücksichtigt. In Abhängigkeit von Randbedingungen und räumlichen Maßstab sind aufgrund der gewonnen Erkenntnisse folgende Aussagen zum Einfluss von Landnutzungsänderungen auf die Hochwasserentstehung möglich: (1) Für intensive konvektive Niederschlagsereignisse mit tendenziell geringer Vorfeuchte ist der Einfluss der Landnutzung größer als für langanhaltende advektive Niederschläge geringer Intensität, da im ersten Fall veränderte Infiltrationsbedingungen stärker zum Tragen kommen als bei kleinen Niederschlagsintensitäten. (2) In kleinen Einzugsgebieten, wo kleinräumige Konvektivzellen zu Hochwassern führen können, ist der Einfluss der Landnutzung dementsprechend größer als in großen Flussgebieten wie dem Rheingebiet, wo vor allem langanhaltende advektive Ereignisse (unter Umständen verbunden mit Schneeschmelze) relevant sind. (3) In Gebieten mit guten Speichereigenschaften wie mächtigen, gut durchlässigen Böden und gut durchlässigem Gesteinsuntergrund ist der Einfluss der Landnutzung größer als in Gebieten mit geringmächtigen Böden und geringdurchlässigem Festgestein. Dies ist darin begründet, dass in Gebieten mit guten Speichereigenschaften bei einer Verschlechterung der Infiltrationsbedingungen mehr Speicherraum für Niederschlag verloren geht als in anderen Gebieten.
The Greenland Ice Sheet is the second-largest mass of ice on Earth. Being almost 2000 km long, more than 700 km wide, and more than 3 km thick at the summit, it holds enough ice to raise global sea levels by 7m if melted completely. Despite its massive size, it is particularly vulnerable to anthropogenic climate change: temperatures over the Greenland Ice Sheet have increased by more than 2.7◦C in the past 30 years, twice as much as the global mean temperature. Consequently, the ice sheet has been significantly losing mass since the 1980s and the rate of loss has increased sixfold since then. Moreover, it is one of the potential tipping elements of the Earth System, which might undergo irreversible change once a warming threshold is exceeded. This thesis aims at extending the understanding of the resilience of the Greenland Ice Sheet against global warming by analyzing processes and feedbacks relevant to its centennial to multi-millennial stability using ice sheet modeling.
One of these feedbacks, the melt-elevation-feedback is driven by the temperature rise with decreasing altitudes: As the ice sheet melts, its thickness and surface elevation decrease, exposing the ice surface to warmer air and thus increasing the melt rates even further. The glacial isostatic adjustment (GIA) can partly mitigate this melt-elevation feedback as the bedrock lifts in response to an ice load decrease, forming the negative GIA feedback. In my thesis, I show that the interaction between these two competing feedbacks can lead to qualitatively different dynamical responses of the Greenland Ice Sheet to warming – from permanent loss to incomplete recovery, depending on the feedback parameters. My research shows that the interaction of those feedbacks can initiate self-sustained oscillations of the ice volume while the climate forcing remains constant.
Furthermore, the increased surface melt changes the optical properties of the snow or ice surface, e.g. by lowering their albedo, which in turn enhances melt rates – a process known as the melt-albedo feedback. Process-based ice sheet models often neglect this melt-albedo feedback. To close this gap, I implemented a simplified version of the diurnal Energy Balance Model, a computationally efficient approach that can capture the first-order effects of the melt-albedo feedback, into the Parallel Ice Sheet Model (PISM). Using the coupled model, I show in warming experiments that the melt-albedo feedback almost doubles the ice loss until the year 2300 under the low greenhouse gas emission scenario RCP2.6, compared to simulations where the melt-albedo feedback is neglected,
and adds up to 58% additional ice loss under the high emission scenario RCP8.5. Moreover, I find that the melt-albedo feedback dominates the ice loss until 2300, compared to the melt-elevation feedback.
Another process that could influence the resilience of the Greenland Ice Sheet is the warming induced softening of the ice and the resulting increase in flow. In my thesis, I show with PISM how the uncertainty in Glen’s flow law impacts the simulated response to warming. In a flow line setup at fixed climatic mass balance, the uncertainty in flow parameters leads to a range of ice loss comparable to the range caused by different warming levels.
While I focus on fundamental processes, feedbacks, and their interactions in the first three projects of my thesis, I also explore the impact of specific climate scenarios on the sea level rise contribution of the Greenland Ice Sheet. To increase the carbon budget flexibility, some warming scenarios – while still staying within the limits of the Paris Agreement – include a temporal overshoot of global warming. I show that an overshoot by 0.4◦C increases the short-term and long-term ice loss from Greenland by several centimeters. The long-term increase is driven by the warming at high latitudes, which persists even when global warming is reversed. This leads to a substantial long-term commitment of the sea level rise contribution from the Greenland Ice Sheet.
Overall, in my thesis I show that the melt-albedo feedback is most relevant for the ice loss of the Greenland Ice Sheet on centennial timescales. In contrast, the melt-elevation feedback and its interplay with the GIA feedback become increasingly relevant on millennial timescales. All of these influence the resilience of the Greenland Ice Sheet against global warming, in the near future and on the long term.
The European Water Framework Directive (WFD) has identified river morphological alteration and diffuse pollution as the two main pressures affecting water bodies in Europe at the catchment scale. Consequently, river restoration has become a priority to achieve the WFD's objective of good ecological status. However, little is known about the effects of stream morphological changes, such as re-meandering, on in-stream nitrate retention at the river network scale. Therefore, catchment nitrate modeling is necessary to guide the implementation of spatially targeted and cost-effective mitigation measures. Meanwhile, Germany, like many other regions in central Europe, has experienced consecutive summer droughts from 2015-2018, resulting in significant changes in river nitrate concentrations in various catchments. However, the mechanistic exploration of catchment nitrate responses to changing weather conditions is still lacking.
Firstly, a fully distributed, process-based catchment Nitrate model (mHM-Nitrate) was used, which was properly calibrated and comprehensively evaluated at numerous spatially distributed nitrate sampling locations. Three calibration schemes were designed, taking into account land use, stream order, and mean nitrate concentrations, and they varied in spatial coverage but used data from the same period (2011–2019). The model performance for discharge was similar among the three schemes, with Nash-Sutcliffe Efficiency (NSE) scores ranging from 0.88 to 0.92. However, for nitrate concentrations, scheme 2 outperformed schemes 1 and 3 when compared to observed data from eight gauging stations. This was likely because scheme 2 incorporated a diverse range of data, including low discharge values and nitrate concentrations, and thus provided a better representation of within-catchment heterogenous. Therefore, the study suggests that strategically selecting gauging stations that reflect the full range of within-catchment heterogeneity is more important for calibration than simply increasing the number of stations.
Secondly, the mHM-Nitrate model was used to reveal the causal relations between sequential droughts and nitrate concentration in the Bode catchment (3200 km2) in central Germany, where stream nitrate concentrations exhibited contrasting trends from upstream to downstream reaches. The model was evaluated using data from six gauging stations, reflecting different levels of runoff components and their associated nitrate-mixing from upstream to downstream. Results indicated that the mHM-Nitrate model reproduced dynamics of daily discharge and nitrate concentration well, with Nash-Sutcliffe Efficiency ≥ 0.73 for discharge and Kling-Gupta Efficiency ≥ 0.50 for nitrate concentration at most stations. Particularly, the spatially contrasting trends of nitrate concentration were successfully captured by the model. The decrease of nitrate concentration in the lowland area in drought years (2015-2018) was presumably due to (1) limited terrestrial export loading (ca. 40% lower than that of normal years 2004-2014), and (2) increased in-stream retention efficiency (20% higher in summer within the whole river network). From a mechanistic modelling perspective, this study provided insights into spatially heterogeneous flow and nitrate dynamics and effects of sequential droughts, which shed light on water-quality responses to future climate change, as droughts are projected to be more frequent.
Thirdly, this study investigated the effects of stream restoration via re-meandering on in-stream nitrate retention at network-scale in the well-monitored Bode catchment. The mHM-Nitrate model showed good performance in reproducing daily discharge and nitrate concentrations, with median Kling-Gupta values of 0.78 and 0.74, respectively. The mean and standard deviation of gross nitrate retention efficiency, which accounted for both denitrification and assimilatory uptake, were 5.1 ± 0.61% and 74.7 ± 23.2% in winter and summer, respectively, within the stream network. The study found that in the summer, denitrification rates were about two times higher in lowland sub-catchments dominated by agricultural lands than in mountainous sub-catchments dominated by forested areas, with median ± SD of 204 ± 22.6 and 102 ± 22.1 mg N m-2 d-1, respectively. Similarly, assimilatory uptake rates were approximately five times higher in streams surrounded by lowland agricultural areas than in those in higher-elevation, forested areas, with median ± SD of 200 ± 27.1 and 39.1 ± 8.7 mg N m-2 d-1, respectively. Therefore, restoration strategies targeting lowland agricultural areas may have greater potential for increasing nitrate retention. The study also found that restoring stream sinuosity could increase net nitrate retention efficiency by up to 25.4 ± 5.3%, with greater effects seen in small streams. These results suggest that restoration efforts should consider augmenting stream sinuosity to increase nitrate retention and decrease nitrate concentrations at the catchment scale.
The relationship between climate and forest productivity is an intensively studied subject in forest science. This Thesis is embedded within the general framework of future forest growth under climate change and its implications for the ongoing forest conversion. My objective is to investigate the future forest productivity at different spatial scales (from a single specific forest stand to aggregated information across Germany) with focus on oak-pine forests in the federal state of Brandenburg. The overarching question is: how are the oak-pine forests affected by climate change described by a variety of climate scenarios. I answer this question by using a model based analysis of tree growth processes and responses to different climate scenarios with emphasis on drought events. In addition, a method is developed which considers climate change uncertainty of forest management planning.
As a first 'screening' of climate change impacts on forest productivity, I calculated the change in net primary production on the base of a large set of climate scenarios for different tree species and the total area of Germany. Temperature increases up to 3 K lead to positive effects on the net primary production of all selected tree species. But, in water-limited regions this positive net primary production trend is dependent on the length of drought periods which results in a larger uncertainty regarding future forest productivity. One of the regions with the highest uncertainty of net primary production development is the federal state of Brandenburg.
To enhance the understanding and ability of model based analysis of tree growth sensitivity to drought stress two water uptake approaches in pure pine and mixed oak-pine stands are contrasted. The first water uptake approach consists of an empirical function for root water uptake. The second approach is more mechanistic and calculates the differences of soil water potential along a soil-plant-atmosphere continuum. I assumed the total root resistance to vary at low, medium and high total root resistance levels. For validation purposes three data sets on different tree growth relevant time scales are used. Results show that, except the mechanistic water uptake approach with high total root resistance, all transpiration outputs exceeded observed values. On the other hand high transpiration led to a better match of observed soil water content. The strongest correlation between simulated and observed annual tree ring width occurred with the mechanistic water uptake approach and high total root resistance. The findings highlight the importance of severe drought as a main reason for small diameter increment, best supported by the mechanistic water uptake approach with high root resistance. However, if all aspects of the data sets are considered no approach can be judged superior to the other. I conclude that the uncertainty of future productivity of water-limited forest ecosystems under changing environmental conditions is linked to simulated root water uptake.
Finally my study aimed at the impacts of climate change combined with management scenarios on an oak-pine forest to evaluate growth, biomass and the amount of harvested timber. The pine and the oak trees are 104 and 9 years old respectively. Three different management scenarios with different thinning intensities and different climate scenarios are used to simulate the performance of management strategies which explicitly account for the risks associated with achieving three predefined objectives (maximum carbon storage, maximum harvested timber, intermediate). I found out that in most cases there is no general management strategy which fits best to different objectives. The analysis of variance in the growth related model outputs showed an increase of climate uncertainty with increasing climate warming. Interestingly, the increase of climate-induced uncertainty is much higher from 2 to 3 K than from 0 to 2 K.
Model frameworks for the calculation of annual runoff and nitrogen emission from danish catchments
(2001)
In der vorliegenden Dissertation werden Migrationsdiskurse in der deutschen Grenzregion zu Polen im Vorfeld der EU-Erweiterung zum 1. Mai 2004 exemplarisch in drei deutschen Grenzstädten, der jeweils westliche Teil der ehemals gemeinsamen, seit 1945 durch eine nationalstaatliche Grenze mit dem jeweils zeitspezifischen Grenzregime geteilten, deutsch-polnischen Zwillingsstädte Frankfurt (Oder) – Słubice, Guben – Gubin und Görlitz – Zgorzelec, analysiert.
Ausgewählt wurde der Untersuchungsraum mit Blick auf die tiefgreifenden europäischen Transformationsprozesse seit den späten 1980er Jahren, die für die örtliche Bevölkerung gravierende lebensweltliche Strukturumbrüche zur Folge hatten. Die Region wurde mit der Vereinigung der beiden deutschen Staaten überdies zu einem zentralen Aktionsraum nationaler und internationaler Migrationspolitik; ihr wurde eine wichtige stellvertretende Funktion betreffend die Zutrittsregelung zugewiesen. Mit der EU-Erweiterung waren für die Region neuerliche, unmittelbare Veränderungen verbunden, die vor Ort gerade auch aufgrund damit (mutmaßlich) einhergehender Migration eher als Bedrohung denn als Chance gedeutet wurden.
Den diskurstheoretischen Hintergrund der Untersuchungen stellen in erster Linie die Arbeiten von Michel Foucault und die von Siegfried Jäger darauf aufruhend konzipierte Kritische Diskursanalyse bereit. Diskurs wird – grob vereinfacht – als Fluss von sozialen Wissensbeständen und Bewusstseinsinhalten durch die Zeit verstanden, der individuelles und kollektives Handeln von Menschen bestimmt; Diskurse sind der Ort, an dem (Be-)Deutungen von Menschen ausgehandelt, verändert und der Wirklichkeit zugewiesen werden. Der Forschungszugang versteht sich als Teil der Neuen Kulturgeographie, die konsequent nicht-essentialistisch und erkenntnistheoretisch nicht-fundamentalistisch ist.
Die Datenbasis der empirischen Analysen repräsentieren zwei Ebenen bzw. Teilsektoren des Diskurses. Zum einen die Berichterstattung der jeweils monopolartigen regionalen Tageszeitung in Frankfurt (Oder), Guben und Görlitz (Märkische Oderzeitung/Frankfurter Stadtbote, Lausitzer Rundschau/Lokalausgabe Guben, Sächsische Zeitung/Görlitzer Zeitung). Zum anderen ein Sample von insgesamt 17 Experteninterviews mit lokalen Funktionsträgern, die mit Blick auf ihr, an ihre spezifische professionelle und/oder ehrenamtliche Tätigkeit gebundenes, praxisgesättigtes Sonder- bzw. Insiderwissen zum Thema Migration ausgewählt und befragt wurden.
Die durchgeführten Analysen verdeutlichen unter anderem die Bedeutung diskurssemantischer Grundfiguren des deutschen Migrationsdiskurses im Sinne politisch und alltagskulturell konservierter migrationskritischer Vorstellungsinhalte und Bedeutungszuweisungen zu Kategorien des Fremden und Konstruktionen von Wir und/vs. Sie. Ebenso explizieren sie eine gravierende Diskrepanz zwischen dem lokalen Staat und der Lebenswelt der lokalen Bevölkerung.
Water shortage is a serious threat for many societies worldwide. In drylands, water management measures like the construction of reservoirs are affected by eroded sediments transported in the rivers. Thus, the capability of assessing water and sediment fluxes at the river basin scale is of vital importance to support management decisions and policy making. This subject was addressed by the DFG-funded SESAM-project (Sediment Export from large Semi-Arid catchments: Measurements and Modelling). As a part of this project, this thesis focuses on (1) the development and implementation of an erosion module for a meso-scale catchment model, (2) the development of upscaling and generalization methods for the parameterization of such model, (3) the execution of measurements to obtain data required for the modelling and (4) the application of the model to different study areas and its evaluation. The research was carried out in two meso-scale dryland catchments in NE-Spain: Ribera Salada (200 km²) and Isábena (450 km²). Adressing objective 1, WASA-SED, a spatially semi-distributed model for water and sediment transport at the meso-scale was developed. The model simulates runoff and erosion processes at the hillslope scale, transport processes of suspended and bedload fluxes in the river reaches, and retention and remobilisation processes of sediments in reservoirs. This thesis introduces the model concept, presents current model applications and discusses its capabilities and limitations. Modelling at larger scales faces the dilemma of describing relevant processes while maintaining a manageable demand for input data and computation time. WASA-SED addresses this challenge by employing an innovative catena-based upscaling approach: the landscape is represented by characteristic toposequences. For deriving these toposequences with regard to multiple attributes (eg. topography, soils, vegetation) the LUMP-algorithm (Landscape Unit Mapping Program) was developed and related to objective 2. It incorporates an algorithm to retrieve representative catenas and their attributes, based on a Digital Elevation Model and supplemental spatial data. These catenas are classified to provide the discretization for the WASA-SED model. For objective 3, water and sediment fluxes were monitored at the catchment outlet of the Isábena and some of its sub-catchments. For sediment yield estimation, the intermittent measurements of suspended sediment concentration (SSC) had to be interpolated. This thesis presents a comparison of traditional sediment rating curves (SRCs), generalized linear models (GLMs) and non-parametric regression using Random Forests (RF) and Quantile Regression Forests (QRF). The observed SSCs are highly variable and range over six orders of magnitude. For these data, traditional SRCs performed poorly, as did GLMs, despite including other relevant process variables (e.g. rainfall intensities, discharge characteristics). RF and QRF proved to be very robust and performed favourably for reproducing sediment dynamics. QRF additionally excels in providing estimates on the accuracy of the predictions. Subsequent analysis showed that most of the sediment was exported during intense storms of late summer. Later floods yielded successively less sediment. Comparing sediment generation to yield at the outlet suggested considerable storage effects within the river channel. Addressing objective 4, the WASA-SED model was parameterized for the two study areas in NE Spain and applied with different foci. For Ribera Salada, the uncalibrated model yielded reasonable results for runoff and sediment. It provided quantitative measures of the change in runoff and sediment yield for different land-uses. Additional land management scenarios were presented and compared to impacts caused by climate change projections. In contrast, the application for the Isábena focussed on exploring the full potential of the model's predictive capabilities. The calibrated model achieved an acceptable performance for the validation period in terms of water and sediment fluxes. The inadequate representation of the lower sub-catchments inflicted considerable reductions on model performance, while results for the headwater catchments showed good agreement despite stark contrasts in sediment yield. In summary, the application of WASA-SED to three catchments proved the model framework to be a practicable multi-scale approach. It successfully links the hillslope to the catchment scale and integrates the three components hillslope, river and reservoir in one model. Thus, it provides a feasible approach for tackling issues of water and sediment yield at the meso-scale. The crucial role of processes like transmission losses and sediment storage in the river has been identified. Further advances can be expected when the representation of connectivity of water and sediment fluxes (intra-hillslope, hillslope-river, intra-river) is refined and input data improves.
Semi-arid areas are, due to their climatic setting, characterized by small water resources. An increasing water demand as a consequence of population growth and economic development as well as a decreasing water availability in the course of possible climate change may aggravate water scarcity in future, which often exists already for present-day conditions in these areas. Understanding the mechanisms and feedbacks of complex natural and human systems, together with the quantitative assessment of future changes in volume, timing and quality of water resources are a prerequisite for the development of sustainable measures of water management to enhance the adaptive capacity of these regions. For this task, dynamic integrated models, containing a hydrological model as one component, are indispensable tools. The main objective of this study is to develop a hydrological model for the quantification of water availability in view of environmental change over a large geographic domain of semi-arid environments. The study area is the Federal State of Ceará (150 000 km2) in the semi-arid north-east of Brazil. Mean annual precipitation in this area is 850 mm, falling in a rainy season with duration of about five months. Being mainly characterized by crystalline bedrock and shallow soils, surface water provides the largest part of the water supply. The area has recurrently been affected by droughts which caused serious economic losses and social impacts like migration from the rural regions. The hydrological model Wasa (Model of Water Availability in Semi-Arid Environments) developed in this study is a deterministic, spatially distributed model being composed of conceptual, process-based approaches. Water availability (river discharge, storage volumes in reservoirs, soil moisture) is determined with daily resolution. Sub-basins, grid cells or administrative units (municipalities) can be chosen as spatial target units. The administrative units enable the coupling of Wasa in the framework of an integrated model which contains modules that do not work on the basis of natural spatial units. The target units mentioned above are disaggregated in Wasa into smaller modelling units within a new multi-scale, hierarchical approach. The landscape units defined in this scheme capture in particular the effect of structured variability of terrain, soil and vegetation characteristics along toposequences on soil moisture and runoff generation. Lateral hydrological processes at the hillslope scale, as reinfiltration of surface runoff, being of particular importance in semi-arid environments, can thus be represented also within the large-scale model in a simplified form. Depending on the resolution of available data, small-scale variability is not represented explicitly with geographic reference in Wasa, but by the distribution of sub-scale units and by statistical transition frequencies for lateral fluxes between these units. Further model components of Wasa which respect specific features of semi-arid hydrology are: (1) A two-layer model for evapotranspiration comprises energy transfer at the soil surface (including soil evaporation), which is of importance in view of the mainly sparse vegetation cover. Additionally, vegetation parameters are differentiated in space and time in dependence on the occurrence of the rainy season. (2) The infiltration module represents in particular infiltration-excess surface runoff as the dominant runoff component. (3) For the aggregate description of the water balance of reservoirs that cannot be represented explicitly in the model, a storage approach respecting different reservoirs size classes and their interaction via the river network is applied. (4) A model for the quantification of water withdrawal by water use in different sectors is coupled to Wasa. (5) A cascade model for the temporal disaggregation of precipitation time series, adapted to the specific characteristics of tropical convective rainfall, is applied for the generating rainfall time series of higher temporal resolution. All model parameters of Wasa can be derived from physiographic information of the study area. Thus, model calibration is primarily not required. Model applications of Wasa for historical time series generally results in a good model performance when comparing the simulation results of river discharge and reservoir storage volumes with observed data for river basins of various sizes. The mean water balance as well as the high interannual and intra-annual variability is reasonably represented by the model. Limitations of the modelling concept are most markedly seen for sub-basins with a runoff component from deep groundwater bodies of which the dynamics cannot be satisfactorily represented without calibration. Further results of model applications are: (1) Lateral processes of redistribution of runoff and soil moisture at the hillslope scale, in particular reinfiltration of surface runoff, lead to markedly smaller discharge volumes at the basin scale than the simple sum of runoff of the individual sub-areas. Thus, these processes are to be captured also in large-scale models. The different relevance of these processes for different conditions is demonstrated by a larger percentage decrease of discharge volumes in dry as compared to wet years. (2) Precipitation characteristics have a major impact on the hydrological response of semi-arid environments. In particular, underestimated rainfall intensities in the rainfall input due to the rough temporal resolution of the model and due to interpolation effects and, consequently, underestimated runoff volumes have to be compensated in the model. A scaling factor in the infiltration module or the use of disaggregated hourly rainfall data show good results in this respect. The simulation results of Wasa are characterized by large uncertainties. These are, on the one hand, due to uncertainties of the model structure to adequately represent the relevant hydrological processes. On the other hand, they are due to uncertainties of input data and parameters particularly in view of the low data availability. Of major importance is: (1) The uncertainty of rainfall data with regard to their spatial and temporal pattern has, due to the strong non-linear hydrological response, a large impact on the simulation results. (2) The uncertainty of soil parameters is in general of larger importance on model uncertainty than uncertainty of vegetation or topographic parameters. (3) The effect of uncertainty of individual model components or parameters is usually different for years with rainfall volumes being above or below the average, because individual hydrological processes are of different relevance in both cases. Thus, the uncertainty of individual model components or parameters is of different importance for the uncertainty of scenario simulations with increasing or decreasing precipitation trends. (4) The most important factor of uncertainty for scenarios of water availability in the study area is the uncertainty in the results of global climate models on which the regional climate scenarios are based. Both a marked increase or a decrease in precipitation can be assumed for the given data. Results of model simulations for climate scenarios until the year 2050 show that a possible future change in precipitation volumes causes a larger percentage change in runoff volumes by a factor of two to three. In the case of a decreasing precipitation trend, the efficiency of new reservoirs for securing water availability tends to decrease in the study area because of the interaction of the large number of reservoirs in retaining the overall decreasing runoff volumes.
Large-scale floodplain sediment dynamics in the Mekong Delta : present state and future prospects
(2014)
The Mekong Delta (MD) sustains the livelihood and food security of millions of people in Vietnam and Cambodia. It is known as the “rice bowl” of South East Asia and has one of the world’s most productive fisheries. Sediment dynamics play a major role for the high productivity of agriculture and fishery in the delta. However, the MD is threatened by climate change, sea level rise and unsustainable development activities in the Mekong Basin. But despite its importance and the expected threats, the understanding of the present and future sediment dynamics in the MD is very limited. This is a consequence of its large extent, the intricate system of rivers, channels and floodplains and the scarcity of observations. Thus this thesis aimed at (1) the quantification of suspended sediment dynamics and associated sediment-nutrient deposition in floodplains of the MD, and (2) assessed the impacts of likely future boundary changes on the sediment dynamics in the MD. The applied methodology combines field experiments and numerical simulation to quantify and predict the sediment dynamics in the entire delta in a spatially explicit manner. The experimental part consists of a comprehensive procedure to monitor quantity and spatial variability of sediment and associated nutrient deposition for large and complex river floodplains, including an uncertainty analysis. The measurement campaign applied 450 sediment mat traps in 19 floodplains over the MD for a complete flood season. The data also supports quantification of nutrient deposition in floodplains based on laboratory analysis of nutrient fractions of trapped sedimentation.The main findings are that the distribution of grain size and nutrient fractions of suspended sediment are homogeneous over the Vietnamese floodplains. But the sediment deposition within and between ring dike floodplains shows very high spatial variability due to a high level of human inference. The experimental findings provide the essential data for setting up and calibration of a large-scale sediment transport model for the MD. For the simulation studies a large scale hydrodynamic model was developed in order to quantify large-scale floodplain sediment dynamics. The complex river-channel-floodplain system of the MD is described by a quasi-2D model linking a hydrodynamic and a cohesive sediment transport model. The floodplains are described as quasi-2D presentations linked to rivers and channels modeled in 1D by using control structures. The model setup, based on the experimental findings, ignored erosion and re-suspension processes due to a very high degree of human interference during the flood season. A two-stage calibration with six objective functions was developed in order to calibrate both the hydrodynamic and sediment transport modules. The objective functions include hydraulic and sediment transport parameters in main rivers, channels and floodplains. The model results show, for the first time, the tempo-spatial distribution of sediment and associated nutrient deposition rates in the whole MD. The patterns of sediment transport and deposition are quantified for different sub-systems. The main factors influencing spatial sediment dynamics are the network of rivers, channels and dike-rings, sluice gate operations, magnitude of the floods and tidal influences. The superposition of these factors leads to high spatial variability of the sediment transport and deposition, in particular in the Vietnamese floodplains. Depending on the flood magnitude, annual sediment loads reaching the coast vary from 48% to 60% of the sediment load at Kratie, the upper boundary of the MD. Deposited sediment varies from 19% to 23% of the annual load at Kratie in Cambodian floodplains, and from 1% to 6% in the compartmented and diked floodplains in Vietnam. Annual deposited nutrients (N, P, K), which are associated to the sediment deposition, provide on average more than 50% of mineral fertilizers typically applied for rice crops in non-flooded ring dike compartments in Vietnam. This large-scale quantification provides a basis for estimating the benefits of the annual Mekong floods for agriculture and fishery, for assessing the impacts of future changes on the delta system, and further studies on coastal deposition/erosion. For the estimation of future prospects a sensitivity-based approach is applied to assess the response of floodplain hydraulics and sediment dynamics to the changes in the delta boundaries including hydropower development, climate change in the Mekong River Basin and effective sea level rise. The developed sediment model is used to simulate the mean sediment transport and sediment deposition in the whole delta system for the baseline (2000-2010) and future (2050-2060) periods. For each driver we derive a plausible range of future changes and discretize it into five levels, resulting in altogether 216 possible factor combinations. Our results thus cover all plausible future pathways of sediment dynamics in the delta based on current knowledge. The uncertainty of the range of the resulting impacts can be decreased in case more information on these drivers becomes available. Our results indicate that the hydropower development dominates the changes in sediment dynamics of the Mekong Delta, while sea level rise has the smallest effect. The floodplains of Vietnamese Mekong Delta are much more sensitive to the changes compared to the other subsystems of the delta. In terms of median changes of the three combined drivers, the inundation extent is predicted to increase slightly, but the overall floodplain sedimentation would be reduced by approximately 40%, while the sediment load to the Sea would diminish to half of the current rates. These findings provide new and valuable information on the possible impacts of future development on the delta, and indicate the most vulnerable areas. Thus, the presented results are a significant contribution to the ongoing international discussion on the hydropower development in the Mekong basin and its impact on the Mekong delta.