TY - JOUR A1 - Fernandez-Palomino, Carlos Antonio A1 - Hattermann, Fred A1 - Krysanova, Valentina A1 - Vega-Jacome, Fiorella A1 - Bronstert, Axel T1 - Towards a more consistent eco-hydrological modelling through multi-objective calibration BT - a case study in the Andean Vilcanota River basin, Perú JF - Hydrological sciences journal = Journal des sciences hydrologiques N2 - Most hydrological studies rely on a model calibrated using discharge alone. However, judging the model reliability based on such calibration is problematic, as it does not guarantee the correct representation of internal hydrological processes. This study aims (a) to develop a comprehensive multi-objective calibration framework using remote sensing vegetation data and hydrological signatures (flow duration curve - FDC, and baseflow index) in addition to discharge, and (b) to apply this framework for calibration of the Soil and Water Assessment Tool (SWAT) in a typical Andean catchment. Overall, our calibration approach outperformed traditional discharge-based and FDC signature-based calibration strategies in terms of vegetation, streamflow, and flow partitioning simulation. New hydrological insights for the region are the following: baseflow is the main component of the streamflow sustaining the long dry-season flow, and pasture areas offer higher water yield and baseflow than other land-cover types. The proposed approach could be used in other data-scarce regions with complex topography. KW - Andes KW - eco-hydrology KW - SWAT KW - hydrological signatures KW - remote sensing KW - equifinality Y1 - 2020 U6 - https://doi.org/10.1080/02626667.2020.1846740 SN - 0262-6667 SN - 2150-3435 VL - 66 IS - 1 SP - 59 EP - 74 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - GEN A1 - Fernandez-Palomino, Carlos Antonio A1 - Hattermann, Fred A1 - Krysanova, Valentina A1 - Vega-Jacome, Fiorella A1 - Bronstert, Axel T1 - Towards a more consistent eco-hydrological modelling through multi-objective calibration BT - a case study in the Andean Vilcanota River basin, Perú T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Most hydrological studies rely on a model calibrated using discharge alone. However, judging the model reliability based on such calibration is problematic, as it does not guarantee the correct representation of internal hydrological processes. This study aims (a) to develop a comprehensive multi-objective calibration framework using remote sensing vegetation data and hydrological signatures (flow duration curve - FDC, and baseflow index) in addition to discharge, and (b) to apply this framework for calibration of the Soil and Water Assessment Tool (SWAT) in a typical Andean catchment. Overall, our calibration approach outperformed traditional discharge-based and FDC signature-based calibration strategies in terms of vegetation, streamflow, and flow partitioning simulation. New hydrological insights for the region are the following: baseflow is the main component of the streamflow sustaining the long dry-season flow, and pasture areas offer higher water yield and baseflow than other land-cover types. The proposed approach could be used in other data-scarce regions with complex topography. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1377 KW - Andes KW - eco-hydrology KW - SWAT KW - hydrological signatures KW - remote sensing KW - equifinality Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-568766 SN - 1866-8372 IS - 1 ER - TY - THES A1 - Purinton, Benjamin T1 - Remote sensing applications to earth surface processes in the Eastern Central Andes T1 - Fernerkundungsanwendungen für Erdoberflächenprozesse in den östlichen Zentralanden N2 - Geomorphology seeks to characterize the forms, rates, and magnitudes of sediment and water transport that sculpt landscapes. This is generally referred to as earth surface processes, which incorporates the influence of biologic (e.g., vegetation), climatic (e.g., rainfall), and tectonic (e.g., mountain uplift) factors in dictating the transport of water and eroded material. In mountains, high relief and steep slopes combine with strong gradients in rainfall and vegetation to create dynamic expressions of earth surface processes. This same rugged topography presents challenges in data collection and process measurement, where traditional techniques involving detailed observations or physical sampling are difficult to apply at the scale of entire catchments. Herein lies the utility of remote sensing. Remote sensing is defined as any measurement that does not disturb the natural environment, typically via acquisition of images in the visible- to radio-wavelength range of the electromagnetic spectrum. Remote sensing is an especially attractive option for measuring earth surface processes, because large areal measurements can be acquired at much lower cost and effort than traditional methods. These measurements cover not only topographic form, but also climatic and environmental metrics, which are all intertwined in the study of earth surface processes. This dissertation uses remote sensing data ranging from handheld camera-based photo surveying to spaceborne satellite observations to measure the expressions, rates, and magnitudes of earth surface processes in high-mountain catchments of the Eastern Central Andes in Northwest Argentina. This work probes the limits and caveats of remote sensing data and techniques applied to geomorphic research questions, and presents important progress at this disciplinary intersection. N2 - Die Geomorphologie versucht die Art, Geschwindigkeit und Ausmaße des Sediment- und Wassertransports zu charakterisieren welche zur Formung der Landschaften beitragen. Diese werden im Allgemeinen als Erdoberflächenprozesse bezeichnet, welche den Einfluss biologischer (z.B. Vegetation), klimatischer (z.B. Niederschlag) und tektonischer (z.B. Gebirgshebung) Faktoren auf den Transport von Wasser und das erodierte Material beschreiben. Im Hochgebirge entsteht eine dynamische Wechselwirkung zwischen hohen Reliefs und steilen Hängen und infolge dessen starke Regen- und Vegetationsgradienten. Die gleiche raue Topographie stellt wiederum eine Herausforderung bei der Datenerfassung und Prozessmessung dar, da hier herkömmliche Techniken zur detaillierten Beobachtung oder physikalischen Probenahmen im Maßstab ganzer Einzugsgebiete an ihre Grenzen stoßen. Hier zeigt sich der Nutzen der Fernerkundung. Fernerkundung ist definiert als Messung, welche die natürliche Umgebung nicht stört, typischerweise durch Aufnahme von Bildern im sichtbaren bis Radio-Wellenlängenbereich des elektromagnetischen Spektrums. Fernerkundung ist eine besonders vorteilhafte Option für die Messung von Erdoberflächenprozessen, da großflächige Messungen mit wesentlich geringerem Aufwand als bei herkömmlichen Methoden durchgeführt werden können. Diese Messungen ermöglichen nicht nur das Erfassen der topografischen Form, sondern auch das der Klima- und Umwelteinflüsse, die wiederum bei der Untersuchung von Erdoberflächenprozessen miteinander verknüpft sind. In dieser Dissertation werden Fernerkundungsdaten verwendet, die von kamerabasierten Handaufnahmen bis zu weltraumgestützten Satellitenbeobachtungen reichen, um die Auswirkungen, Geschwindigkeiten und das Ausmaß von Erdoberflächenprozessen in hochgebirgigen Einzugsgebieten der östlichen Zentralanden im Nordwesten Argentiniens zu messen. Diese Arbeit untersucht die Möglichkeiten und Grenzen von Fernerkundungsdaten und -techniken, die auf geomorphologische Forschungsfragen angewendet werden und präsentiert wichtige Fortschritte an diesem disziplinären Schnittpunkt. KW - Fernerkundung KW - remote sensing KW - Geomorphologie KW - geomorphology KW - Anden KW - Andes Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-445926 ER - TY - JOUR A1 - Coesfeld, Jacqueline A1 - Kuester, Theres A1 - Kuechly, Helga U. A1 - Kyba, Christopher C. M. T1 - Reducing variability and removing natural light from nighttime satellite imagery: A case study using the VIIRS DNB JF - Sensors N2 - Temporal variation of natural light sources such as airglow limits the ability of night light sensors to detect changes in small sources of artificial light (such as villages). This study presents a method for correcting for this effect globally, using the satellite radiance detected from regions without artificial light emissions. We developed a routine to define an approximate grid of locations worldwide that do not have regular light emission. We apply this method with a 5 degree equally spaced global grid (total of 2016 individual locations), using data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB). This code could easily be adapted for other future global sensors. The correction reduces the standard deviation of data in the Earth Observation Group monthly DNB composites by almost a factor of two. The code and datasets presented here are available under an open license by GFZ Data Services, and are implemented in the Radiance Light Trends web application. KW - airglow KW - artificial light KW - calibration KW - VIIRS DNB KW - nightlights KW - remote sensing Y1 - 2020 VL - 20 PB - MDPI CY - Basel ER - TY - GEN A1 - Coesfeld, Jacqueline A1 - Kuester, Theres A1 - Kuechly, Helga U. A1 - Kyba, Christopher C. M. T1 - Reducing variability and removing natural light from nighttime satellite imagery: A case study using the VIIRS DNB T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Temporal variation of natural light sources such as airglow limits the ability of night light sensors to detect changes in small sources of artificial light (such as villages). This study presents a method for correcting for this effect globally, using the satellite radiance detected from regions without artificial light emissions. We developed a routine to define an approximate grid of locations worldwide that do not have regular light emission. We apply this method with a 5 degree equally spaced global grid (total of 2016 individual locations), using data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB). This code could easily be adapted for other future global sensors. The correction reduces the standard deviation of data in the Earth Observation Group monthly DNB composites by almost a factor of two. The code and datasets presented here are available under an open license by GFZ Data Services, and are implemented in the Radiance Light Trends web application. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1181 KW - airglow KW - artificial light KW - calibration KW - VIIRS DNB KW - nightlights KW - remote sensing Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-524397 SN - 1866-8372 IS - 11 ER - TY - GEN A1 - Ozturk, Ugur A1 - Pittore, Massimiliano A1 - Behling, Robert A1 - Rößner, Sigrid A1 - Andreani, Louis A1 - Korup, Oliver T1 - How robust are landslide susceptibility estimates? T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Much of contemporary landslide research is concerned with predicting and mapping susceptibility to slope failure. Many studies rely on generalised linear models with environmental predictors that are trained with data collected from within and outside of the margins of mapped landslides. Whether and how the performance of these models depends on sample size, location, or time remains largely untested. We address this question by exploring the sensitivity of a multivariate logistic regression-one of the most widely used susceptibility models-to data sampled from different portions of landslides in two independent inventories (i.e. a historic and a multi-temporal) covering parts of the eastern rim of the Fergana Basin, Kyrgyzstan. We find that considering only areas on lower parts of landslides, and hence most likely their deposits, can improve the model performance by >10% over the reference case that uses the entire landslide areas, especially for landslides of intermediate size. Hence, using landslide toe areas may suffice for this particular model and come in useful where landslide scars are vague or hidden in this part of Central Asia. The model performance marginally varied after progressively updating and adding more landslides data through time. We conclude that landslide susceptibility estimates for the study area remain largely insensitive to changes in data over about a decade. Spatial or temporal stratified sampling contributes only minor variations to model performance. Our findings call for more extensive testing of the concept of dynamic susceptibility and its interpretation in data-driven models, especially within the broader framework of landslide risk assessment under environmental and land-use change. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1346 KW - Landslide susceptibility KW - logistic regression KW - Southern Kyrgyzstan KW - Landslide inventory KW - remote sensing Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-541980 SN - 1866-8372 IS - 2 ER - TY - THES A1 - Barbosa, Luís Romero T1 - Groundwater recharge in tropical wet regions via GIS-based and cosmic-ray neutron sensing T1 - Recarga de águas subterrâneas em regiões úmidas tropicais por métodos baseados em SIG e Detecção de Nêutrons de Raios Cósmicos T1 - Grundwasserneubildung in tropisch-feuchten Gebieten über GIS-basierte Methoden und Messung der Neutronen aus kosmischer Höhenstrahlung N2 - Studies on the unsustainable use of groundwater resources are still considered incipient since it is frequently a poorly understood and managed, devalued and inadequately protected natural resource. Groundwater Recharge (GWR) is one of the most challenging elements to estimate since it can rarely be measured directly and cannot easily be derived from existing data. To overcome these limitations, many hydro(geo)logists have combined different approaches to estimate large-scale GWR, namely: remote sensing products, such as IMERG product; Water Budget Equation, also in combination with hydrological models, and; Geographic Information System (GIS), using estimation formulas. For intermediary-scale GWR estimation, there exist: Non-invasive Cosmic-Ray Neutron Sensing (CRNS); wireless networks from local soil probes; and soil hydrological models, such as HYDRUS. Accordingly, this PhD thesis aims, on the one hand, to demonstrate a GIS-based model coupling for estimating the GWR distribution on a large scale in tropical wet basins. On the other hand, it aims to use the time series from CRNS and invasive soil moisture probes to inversely calibrate the soil hydraulic properties, and based on this, estimating the intermediary-scale GWR using a soil hydrological model. For such purpose, two tropical wet basins located in a complex sedimentary aquifer in the coastal Northeast region of Brazil were selected. These are the João Pessoa Case Study Area and the Guaraíra Experimental Basin. Several satellite products in the first area were used as input to the GIS-based water budget equation model for estimating the water balance components and GWR in 2016 and 2017. In addition, the point-scale measurement and CRNS data were used in the second area to determine the soil hydraulic properties, and to estimate the GWR in the 2017-2018 and 2018-2019 hydrological years. The resulting values of GWR on large- and intermediary-scale were then compared and validated by the estimates obtained by groundwater table fluctuations. The GWR rates for IMERG- and rain-gauge-based scenarios showed similar coefficients between 68% and 89%, similar mean errors between 30% and 34%, and slightly-different bias between -13% and 11%. The results of GWR rates for soil probes and CRNS soil moisture scenarios ranged from -5.87 to -61.81 cm yr-1, which corresponds to 5% and 38% of the precipitation. The calculations of the mean GWR rates on large-scale, based on remote sensing data, and on intermediary-scale, based on CRNS data, held similar results for the Podzol soil type, namely 17.87% and 17% of the precipitation. It is then concluded that the proposed methodologies allowed for estimating realistically the GWR over the study areas, which can be a ground-breaking step towards improving the water management and decision-making in the Northeast of Brazil. N2 - Studien über die nicht nachhaltige Nutzung von Grundwasserressourcen gelten nach wie vor als am Anfang, da es sich oft um eine schlecht verstandene und unkontrolliert genutzte, geringgeschätzte und unzureichend geschützte natürliche Ressource handelt. Die Grundwasserneubildung (GWR) ist eines der am schwierigsten abzuschätzenden Einflussgrößen, da sie selten direkt gemessen werden kann und nicht einfach aus vorhandenen Daten abzuleiten ist. Um diese Einschränkungen zu überwinden, haben viele Hydro(geo)logen verschiedene Ansätze kombiniert, um die GWR in großem Maßstab zu ermitteln, darunter sind: Fernerkundungsprodukte, wie das IMERG-Produkt; Wasserbilanz-Abschätzungen, auch in Kombination mit hydrologischen Modellen und; Geographische Informationssysteme (GIS) unter Nutzung von Abschätzungsformeln. Für die Ermittlung von GWR auf mittleren Flächenskalen existieren: Nicht-invasive Messung der Albedoneutronen an der Landoberfläche (CRNS); Drahtlosnetzwerke von lokalen Bodensonden, und bodenhydrologische Modelle, wie bspw. HYDRUS. In diesem Kontext zielt die Doktorarbeit zum einen darauf ab, eine GIS-basiert Modellkopplung zur Schätzung der GWR-Verteilung im großen Maßstab in tropisch-feuchte Einzugsgebiete aufzuzeigen. Zum anderen verwendet sie CRNS- und invasive Bodenfeuchtesonden-Zeitreihen zur inversen Kalibrierung der hydraulischen Bodeneigenschaften und darauf aufbauend zur Schätzung der GWR im mittleren Maßstab über ein bodenhydrologisches Modell. Zu diesem Zweck wurden zwei tropisch-feuchte Einzugsgebiete ausgewählt, die sich in einem komplexen Sedimentgrundwasserleiter der Küstenregion des Nordosten-Brasilien befinden. Dies sind das João Pessoa-Fallstudiengebiet und das Guaraíra-Flusseinzugsgebiet. Mehrere Satellitenprodukte wurden im ersten Gebiet als Eingangsdaten für das GIS-basierte Wasserbilanz-Modell zur Schätzung der Wasserhaushaltskomponenten und der GWR in den Jahren 2016 und 2017 verwendet. Daneben wurden im zweiten Gebiet die Punktmessungen- und CRNS-Daten verwendet, um über ein bodenhydrologisches HYDRUS-1D-Modell die hydraulischen Bodeneigenschaften zu ermitteln und die GWR in den hydrologischen Jahren 2017-2018 und 2018-2019 abzuschätzen. Die resultierenden GWR-Werte im großen und mittleren Maßstab wurden dann mit den gemessenen Schwankungen der Grundwasserstände verglichen und daran überprüft. Die GWR-Raten aus IMERG- und Niederschlagsmessern-basierten Szenarien zeigten ähnliche Korrelationen zwischen 68% und 89%, mittlere Fehler zwischen 30% und 34%, und leicht unterschiedliche Abweichungen zwischen -13% und 11%. Die berechneten GWR-Raten für Bodensonden- und CRNS-Bodenfeuchtewerte lagen im Bereich von 58,7 bis 618,1 mm im Jahr, was 5% bzw. 38% der Niederschlagsmengen entspricht. Die Berechnung der mittleren GWR-Raten auf großer Landschaftsskala, basierend auf Fernerkundungsdaten, und auf mittlerer Skala, basierend auf CRNS-Daten, ergaben für den Bodentyp Podsol ähnliche Ergebnisse, nämlich 17,87% bzw. 17% der Niederschläge. Daraus wurde der Schluss gezogen, dass die vorgeschlagenen Methoden eine realistische Schätzung der GWR in den Untersuchungsgebieten ermöglichen, was ein wegweisender Schritt zur Verbesserung des Wassermanagements und Nutzungsentscheidungen im Nordosten Brasiliens sein kann. N2 - Estudos sobre o uso insustentável dos recursos hídricos subterrâneos ainda são considerados incipientes, por se tratar de um recurso natural pouco compreendido e gerenciado, desvalorizado e mal protegido. A Recarga de Água Subterrânea (GWR) é um dos elementos mais desafiadores para estimar, pois raramente pode ser medido diretamente e não pode ser facilmente derivado dos dados existentes. Para superar essas limitações, muitos hidro(geo)logistas têm combinado diferentes abordagens para estimar a GWR em larga escala, a saber: produtos de sensoriamento remoto, como o produto IMERG; Equação do Balanço Hídrico, também em combinação com modelos hidrológicos no solo, e; Sistema de Informação Geográfica (GIS), com o uso de fórmulas de estimativa. Para as estimativas de GWR em escala intermediária, existem: Detecção Não-invasiva de Nêutrons de Raios Cósmicos (CRNS); redes sem fio a partir de sondas locais inseridos no solo; e modelos hidrológicos, como o HYDRUS. Neste contexto, a tese de doutorado visa, por um lado, demonstrar um acoplamento de modelo baseado em GIS para estimar a distribuição da GWR em larga escala em bacias tropicais úmidas. Por outro lado, visa utilizar as séries temporais de CRNS e de umidade do solo de sondas invasivas para calibrar inversamente as propriedades hidráulicas do solo, e com base nisso, estimar a GWR em escala intermediária usando um modelo hidrológico do solo. Para tanto, foram selecionadas duas bacias hidrográficas úmidas tropicais, localizadas em um aquífero sedimentar complexo na região costeira do Nordeste do Brasil. Estas são a Área de Estudo de Caso de João Pessoa e a Bacia Experimental do Guaraíra. Vários produtos de satélite foram usados na primeira área como entrada no modelo de balanço hídrico baseado em GIS para estimar os componentes do balanço hídrico e a GWR em 2016 e 2017. Além disso, as medições em escala pontual e os dados de CRNS foram usados na segunda área para determinar as propriedades hidráulicas do solo, e estimar GWR nos anos hidrológicos 2017-2018 e 2018-2019. Os valores resultantes de GWR em escala larga e intermediária foram então comparadas e validadas pelas estimativas obtidas pelas flutuações do lençol freático. As taxas de GWR para os cenários baseados no IMERG e em medidores de precipitação mostraram correlações semelhantes entre 68% e 89, erros médios semelhantes entre 30% e 34%, e viés ligeiramente diferentes entre -13% e 11%. Os resultados das taxas de GWR para os cenários de umidade do solo para sensores inseridos no solo e CRNS variaram de -5,87 a -61,81 cm ano-1, o que corresponde a 5% e 38% da precipitação. Os cálculos das taxas médias de GWR em grande escala, com base em dados de sensoriamento remoto, e em média escala, com base em dados de CRNS, apresentaram resultados semelhantes para o tipo de solo Espodossolo, a saber 17,87% e 17% da precipitação. Conclui-se então que as metodologias propostas permitiram estimar realisticamente a GWR nas áreas de estudo, o que pode ser um passo inovador no tocante ao aprimoramento do gerenciamento e tomada de decisão da água no Nordeste do Brasil. KW - groundwater recharge KW - remote sensing KW - cosmic-ray neutron sensing KW - soil hydraulic properties KW - northeast of Brazil KW - Grundwasserneubildung KW - Fernerkundungsprodukte KW - Neutronen aus kosmischer Höhenstrahlung KW - hydraulische Bodeneigenschaften KW - Nordostbrasilien KW - recarga de águas subterrâneas KW - sensoriamento remoto KW - detecção de nêutrons de raios cósmicos KW - propriedades hidráulicas do solo KW - nordeste do Brasil Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-460641 ER -