@phdthesis{Lenz2016,
  author    = {Lenz, Josefine},
  title     = {Thermokarst dynamics in central-eastern Beringia},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-101364},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XII, 128, A-47},
  year      = {2016},
  abstract  = {Widespread landscape changes are presently observed in the Arctic and are most likely to accelerate in the future, in particular in permafrost regions which are sensitive to climate warming. To assess current and future developments, it is crucial to understand past environmental dynamics in these landscapes. Causes and interactions of environmental variability can hardly be resolved by instrumental records covering modern time scales. However, long-term environmental variability is recorded in paleoenvironmental archives. Lake sediments are important archives that allow reconstruction of local limnogeological processes as well as past environmental changes driven directly or indirectly by climate dynamics. This study aims at reconstructing Late Quaternary permafrost and thermokarst dynamics in central-eastern Beringia, the terrestrial land mass connecting Eurasia and North America during glacial sea-level low stands. In order to investigate development, processes and influence of thermokarst dynamics, several sediment cores from extant lakes and drained lake basins were analyzed to answer the following research questions: 1. When did permafrost degradation and thermokarst lake development take place and what were enhancing and inhibiting environmental factors? 2. What are the dominant processes during thermokarst lake development and how are they reflected in proxy records? 3. How did, and still do, thermokarst dynamics contribute to the inventory and properties of organic matter in sediments and the carbon cycle? Methods applied in this study are based upon a multi-proxy approach combining sedimentological, geochemical, geochronological, and micropaleontological analyses, as well as analyses of stable isotopes and hydrochemistry of pore-water and ice. Modern field observations of water quality and basin morphometrics complete the environmental investigations. The investigated sediment cores reveal permafrost degradation and thermokarst dynamics on different time scales. The analysis of a sediment core from GG basin on the northern Seward Peninsula (Alaska) shows prevalent terrestrial accumulation of yedoma throughout the Early to Mid Wisconsin with intermediate wet conditions at around 44.5 to 41.5 ka BP. This first wetland development was terminated by the accumulation of a 1-meter-thick airfall tephra most likely originating from the South Killeak Maar eruption at 42 ka BP. A depositional hiatus between 22.5 and 0.23 ka BP may indicate thermokarst lake formation in the surrounding of the site which forms a yedoma upland till today. The thermokarst lake forming GG basin initiated 230 ± 30 cal a BP and drained in Spring 2005 AD. Four years after drainage the lake talik was still unfrozen below 268 cm depth. A permafrost core from Mama Rhonda basin on the northern Seward Peninsula preserved a full lacustrine record including several lake phases. The first lake generation developed at 11.8 cal ka BP during the Lateglacial-Early Holocene transition; its old basin (Grandma Rhonda) is still partially preserved at the southern margin of the study basin. Around 9.0 cal ka BP a shallow and more dynamic thermokarst lake developed with actively eroding shorelines and potentially intermediate shallow water or wetland phases (Mama Rhonda). Mama Rhonda lake drainage at 1.1 cal ka BP was followed by gradual accumulation of terrestrial peat and top-down refreezing of the lake talik. A significant lower organic carbon content was measured in Grandma Rhonda deposits (mean TOC of 2.5 wt\%) than in Mama Rhonda deposits (mean TOC of 7.9 wt\%) highlighting the impact of thermokarst dynamics on biogeochemical cycling in different lake generations by thawing and mobilization of organic carbon into the lake system. Proximal and distal sediment cores from Peatball Lake on the Arctic Coastal Plain of Alaska revealed young thermokarst dynamics since about 1,400 years along a depositional gradient based on reconstructions from shoreline expansion rates and absolute dating results. After its initiation as a remnant pond of a previous drained lake basin, a rapidly deepening lake with increasing oxygenation of the water column is evident from laminated sediments, and higher Fe/Ti and Fe/S ratios in the sediment. The sediment record archived characterizing shifts in depositional regimes and sediment sources from upland deposits and re-deposited sediments from drained thaw lake basins depending on the gradually changing shoreline configuration. These changes are evident from alternating organic inputs into the lake system which highlights the potential for thermokarst lakes to recycle old carbon from degrading permafrost deposits of its catchment. The lake sediment record from Herschel Island in the Yukon (Canada) covers the full Holocene period. After its initiation as a thermokarst lake at 11.7 cal ka BP and intense thermokarst activity until 10.0 cal ka BP, the steady sedimentation was interrupted by a depositional hiatus at 1.6 cal ka BP which likely resulted from lake drainage or allochthonous slumping due to collapsing shore lines. The specific setting of the lake on a push moraine composed of marine deposits is reflected in the sedimentary record. Freshening of the maturing lake is indicated by decreasing electrical conductivity in pore-water. Alternation of marine to freshwater ostracods and foraminifera confirms decreasing salinity as well but also reflects episodical re-deposition of allochthonous marine sediments. Based on permafrost and lacustrine sediment records, this thesis shows examples of the Late Quaternary evolution of typical Arctic permafrost landscapes in central-eastern Beringia and the complex interaction of local disturbance processes, regional environmental dynamics and global climate patterns. This study confirms that thermokarst lakes are important agents of organic matter recycling in complex and continuously changing landscapes.},
  language  = {en}
}
@phdthesis{Morgenstern2012,
  author    = {Morgenstern, Anne},
  title     = {Thermokarst and thermal erosion : degradation of Siberian ice-rich permafrost},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-62079},
  school      = {Universit{\"a}t Potsdam},
  year      = {2012},
  abstract  = {Current climate warming is affecting arctic regions at a faster rate than the rest of the world. This has profound effects on permafrost that underlies most of the arctic land area. Permafrost thawing can lead to the liberation of considerable amounts of greenhouse gases as well as to significant changes in the geomorphology, hydrology, and ecology of the corresponding landscapes, which may in turn act as a positive feedback to the climate system. Vast areas of the east Siberian lowlands, which are underlain by permafrost of the Yedoma-type Ice Complex, are particularly sensitive to climate warming because of the high ice content of these permafrost deposits. Thermokarst and thermal erosion are two major types of permafrost degradation in periglacial landscapes. The associated landforms are prominent indicators of climate-induced environmental variations on the regional scale. Thermokarst lakes and basins (alasses) as well as thermo-erosional valleys are widely distributed in the coastal lowlands adjacent to the Laptev Sea. This thesis investigates the spatial distribution and morphometric properties of these degradational features to reconstruct their evolutionary conditions during the Holocene and to deduce information on the potential impact of future permafrost degradation under the projected climate warming. The methodological approach is a combination of remote sensing, geoinformation, and field investigations, which integrates analyses on local to regional spatial scales. Thermokarst and thermal erosion have affected the study region to a great extent. In the Ice Complex area of the Lena River Delta, thermokarst basins cover a much larger area than do present thermokarst lakes on Yedoma uplands (20.0 and 2.2 \%, respectively), which indicates that the conditions for large-area thermokarst development were more suitable in the past. This is supported by the reconstruction of the development of an individual alas in the Lena River Delta, which reveals a prolonged phase of high thermokarst activity since the Pleistocene/Holocene transition that created a large and deep basin. After the drainage of the primary thermokarst lake during the mid-Holocene, permafrost aggradation and degradation have occurred in parallel and in shorter alternating stages within the alas, resulting in a complex thermokarst landscape. Though more dynamic than during the first phase, late Holocene thermokarst activity in the alas was not capable of degrading large portions of Pleistocene Ice Complex deposits and substantially altering the Yedoma relief. Further thermokarst development in existing alasses is restricted to thin layers of Holocene ice-rich alas sediments, because the Ice Complex deposits underneath the large primary thermokarst lakes have thawed completely and the underlying deposits are ice-poor fluvial sands. Thermokarst processes on undisturbed Yedoma uplands have the highest impact on the alteration of Ice Complex deposits, but will be limited to smaller areal extents in the future because of the reduced availability of large undisturbed upland surfaces with poor drainage. On Kurungnakh Island in the central Lena River Delta, the area of Yedoma uplands available for future thermokarst development amounts to only 33.7 \%. The increasing proximity of newly developing thermokarst lakes on Yedoma uplands to existing degradational features and other topographic lows decreases the possibility for thermokarst lakes to reach large sizes before drainage occurs. Drainage of thermokarst lakes due to thermal erosion is common in the study region, but thermo-erosional valleys also provide water to thermokarst lakes and alasses. Besides these direct hydrological interactions between thermokarst and thermal erosion on the local scale, an interdependence between both processes exists on the regional scale. A regional analysis of extensive networks of thermo-erosional valleys in three lowland regions of the Laptev Sea with a total study area of 5,800 km² found that these features are more common in areas with higher slopes and relief gradients, whereas thermokarst development is more pronounced in flat lowlands with lower relief gradients. The combined results of this thesis highlight the need for comprehensive analyses of both, thermokarst and thermal erosion, in order to assess past and future impacts and feedbacks of the degradation of ice-rich permafrost on hydrology and climate of a certain region.},
  language  = {en}
}
@phdthesis{Jongejans2022,
  author    = {Jongejans, Loeka Laura},
  title     = {Organic matter stored in ice-rich permafrost},
  doi       = {10.25932/publishup-56491},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-564911},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxiii, 178},
  year      = {2022},
  abstract  = {The Arctic is changing rapidly and permafrost is thawing. Especially ice-rich permafrost, such as the late Pleistocene Yedoma, is vulnerable to rapid and deep thaw processes such as surface subsidence after the melting of ground ice. Due to permafrost thaw, the permafrost carbon pool is becoming increasingly accessible to microbes, leading to increased greenhouse gas emissions, which enhances the climate warming. The assessment of the molecular structure and biodegradability of permafrost organic matter (OM) is highly needed. My research revolves around the question "how does permafrost thaw affect its OM storage?" More specifically, I assessed (1) how molecular biomarkers can be applied to characterize permafrost OM, (2) greenhouse gas production rates from thawing permafrost, and (3) the quality of OM of frozen and (previously) thawed sediments. I studied deep (max. 55 m) Yedoma and thawed Yedoma permafrost sediments from Yakutia (Sakha Republic). I analyzed sediment cores taken below thermokarst lakes on the Bykovsky Peninsula (southeast of the Lena Delta) and in the Yukechi Alas (Central Yakutia), and headwall samples from the permafrost cliff Sobo-Sise (Lena Delta) and the retrogressive thaw slump Batagay (Yana Uplands). I measured biomarker concentrations of all sediment samples. Furthermore, I carried out incubation experiments to quantify greenhouse gas production in thawing permafrost. I showed that the biomarker proxies are useful to assess the source of the OM and to distinguish between OM derived from terrestrial higher plants, aquatic plants and microbial activity. In addition, I showed that some proxies help to assess the degree of degradation of permafrost OM, especially when combined with sedimentological data in a multi-proxy approach. The OM of Yedoma is generally better preserved than that of thawed Yedoma sediments. The greenhouse gas production was highest in the permafrost sediments that thawed for the first time, meaning that the frozen Yedoma sediments contained most labile OM. Furthermore, I showed that the methanogenic communities had established in the recently thawed sediments, but not yet in the still-frozen sediments. My research provided the first molecular biomarker distributions and organic carbon turnover data as well as insights in the state and processes in deep frozen and thawed Yedoma sediments. These findings show the relevance of studying OM in deep permafrost sediments.},
  language  = {en}
}
@phdthesis{Brill2022,
  author    = {Brill, Fabio Alexander},
  title     = {Applications of machine learning and open geospatial data in flood risk modelling},
  doi       = {10.25932/publishup-55594},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-555943},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 124},
  year      = {2022},
  abstract  = {Der technologische Fortschritt erlaubt es, zunehmend komplexe Vorhersagemodelle auf Basis immer gr{\"o}ßerer Datens{\"a}tze zu produzieren. F{\"u}r das Risikomanagement von Naturgefahren sind eine Vielzahl von Modellen als Entscheidungsgrundlage notwendig, z.B. in der Auswertung von Beobachtungsdaten, f{\"u}r die Vorhersage von Gefahrenszenarien, oder zur statistischen Absch{\"a}tzung der zu erwartenden Sch{\"a}den. Es stellt sich also die Frage, inwiefern moderne Modellierungsans{\"a}tze wie das maschinelle Lernen oder Data-Mining in diesem Themenbereich sinnvoll eingesetzt werden k{\"o}nnen. Zus{\"a}tzlich ist im Hinblick auf die Datenverf{\"u}gbarkeit und -zug{\"a}nglichkeit ein Trend zur {\"O}ffnung (open data) zu beobachten. Thema dieser Arbeit ist daher, die M{\"o}glichkeiten und Grenzen des maschinellen Lernens und frei verf{\"u}gbarer Geodaten auf dem Gebiet der Hochwasserrisikomodellierung im weiteren Sinne zu untersuchen. Da dieses {\"u}bergeordnete Thema sehr breit ist, werden einzelne relevante Aspekte herausgearbeitet und detailliert betrachtet. Eine prominente Datenquelle im Bereich Hochwasser ist die satellitenbasierte Kartierung von {\"U}berflutungsfl{\"a}chen, die z.B. {\"u}ber den Copernicus Service der Europ{\"a}ischen Union frei zur Verf{\"u}gung gestellt werden. Große Hoffnungen werden in der wissenschaftlichen Literatur in diese Produkte gesetzt, sowohl f{\"u}r die akute Unterst{\"u}tzung der Einsatzkr{\"a}fte im Katastrophenfall, als auch in der Modellierung mittels hydrodynamischer Modelle oder zur Schadensabsch{\"a}tzung. Daher wurde ein Fokus in dieser Arbeit auf die Untersuchung dieser Flutmasken gelegt. Aus der Beobachtung, dass die Qualit{\"a}t dieser Produkte in bewaldeten und urbanen Gebieten unzureichend ist, wurde ein Verfahren zur nachtr{\"a}glichenVerbesserung mittels maschinellem Lernen entwickelt. Das Verfahren basiert auf einem Klassifikationsalgorithmus der nur Trainingsdaten von einer vorherzusagenden Klasse ben{\"o}tigt, im konkreten Fall also Daten von {\"U}berflutungsfl{\"a}chen, nicht jedoch von der negativen Klasse (trockene Gebiete). Die Anwendung f{\"u}r Hurricane Harvey in Houston zeigt großes Potenzial der Methode, abh{\"a}ngig von der Qualit{\"a}t der urspr{\"u}nglichen Flutmaske. Anschließend wird anhand einer prozessbasierten Modellkette untersucht, welchen Einfluss implementierte physikalische Prozessdetails auf das vorhergesagte statistische Risiko haben. Es wird anschaulich gezeigt, was eine Risikostudie basierend auf etablierten Modellen leisten kann. Solche Modellketten sind allerdings bereits f{\"u}r Flusshochwasser sehr komplex, und f{\"u}r zusammengesetzte oder kaskadierende Ereignisse mit Starkregen, Sturzfluten, und weiteren Prozessen, kaum vorhanden. Im vierten Kapitel dieser Arbeit wird daher getestet, ob maschinelles Lernen auf Basis von vollst{\"a}ndigen Schadensdaten einen direkteren Weg zur Schadensmodellierung erm{\"o}glicht, der die explizite Konzeption einer solchen Modellkette umgeht. Dazu wird ein staatlich erhobener Datensatz der gesch{\"a}digten Geb{\"a}ude w{\"a}hrend des schweren El Ni{\~n}o Ereignisses 2017 in Peru verwendet. In diesem Kontext werden auch die M{\"o}glichkeiten des Data-Mining zur Extraktion von Prozessverst{\"a}ndnis ausgelotet. Es kann gezeigt werden, dass diverse frei verf{\"u}gbare Geodaten n{\"u}tzliche Informationen f{\"u}r die Gefahren- und Schadensmodellierung von komplexen Flutereignissen liefern, z.B. satellitenbasierte Regenmessungen, topographische und hydrographische Information, kartierte Siedlungsfl{\"a}chen, sowie Indikatoren aus Spektraldaten. Zudem zeigen sich Erkenntnisse zu den Sch{\"a}digungsprozessen, die im Wesentlichen mit den vorherigen Erwartungen in Einklang stehen. Die maximale Regenintensit{\"a}t wirkt beispielsweise in St{\"a}dten und steilen Schluchten st{\"a}rker sch{\"a}digend, w{\"a}hrend die Niederschlagssumme in tiefliegenden Flussgebieten und bewaldeten Regionen als aussagekr{\"a}ftiger befunden wurde. L{\"a}ndliche Gebiete in Peru weisen in der pr{\"a}sentierten Studie eine h{\"o}here Vulnerabilit{\"a}t als die Stadtgebiete auf. Jedoch werden auch die grunds{\"a}tzlichen Grenzen der Methodik und die Abh{\"a}ngigkeit von spezifischen Datens{\"a}tzen and Algorithmen offenkundig. In der {\"u}bergreifenden Diskussion werden schließlich die verschiedenen Methoden - prozessbasierte Modellierung, pr{\"a}diktives maschinelles Lernen, und Data-Mining - mit Blick auf die Gesamtfragestellungen evaluiert. Im Bereich der Gefahrenbeobachtung scheint eine Fokussierung auf neue Algorithmen sinnvoll. Im Bereich der Gefahrenmodellierung, insbesondere f{\"u}r Flusshochwasser, wird eher die Verbesserung von physikalischen Modellen, oder die Integration von prozessbasierten und statistischen Verfahren angeraten. In der Schadensmodellierung fehlen nach wie vor die großen repr{\"a}sentativen Datens{\"a}tze, die f{\"u}r eine breite Anwendung von maschinellem Lernen Voraussetzung ist. Daher ist die Verbesserung der Datengrundlage im Bereich der Sch{\"a}den derzeit als wichtiger einzustufen als die Auswahl der Algorithmen.},
  language  = {en}
}
@article{JaraMunozMelnickLietal.2022,
  author    = {Jara Mu{\~n}oz, Julius and Melnick, Daniel and Li, Shaoyang and Socquet, Anne and Cort{\´e}s-Aranda, Joaqu{\´i}n and Brill, Dominik and Strecker, Manfred},
  title     = {The cryptic seismic potential of the Pichilemu blind fault in Chile revealed by off-fault geomorphology},
  series = {Nature Communications},
  volume    = {13},
  journal   = {Nature Communications},
  publisher = {Springer Nature},
  address   = {London},
  issn      = {2041-1723},
  doi       = {10.1038/s41467-022-30754-1},
  pages     = {13},
  year      = {2022},
  abstract  = {The first step towards assessing hazards in seismically active regions involves mapping capable faults and estimating their recurrence times. While the mapping of active faults is commonly based on distinct geologic and geomorphic features evident at the surface, mapping blind seismogenic faults is complicated by the absence of on-fault diagnostic features. Here we investigated the Pichilemu Fault in coastal Chile, unknown until it generated a Mw 7.0 earthquake in 2010. The lack of evident surface faulting suggests activity along a partly-hidden blind fault. We used off-fault deformed marine terraces to estimate a fault-slip rate of 0.52 ± 0.04 m/ka, which, when integrated with satellite geodesy suggests a 2.12 ± 0.2 ka recurrence time for Mw~7.0 normal-faulting earthquakes. We propose that extension in the Pichilemu region is associated with stress changes during megathrust earthquakes and accommodated by sporadic slip during upper-plate earthquakes, which has implications for assessing the seismic potential of cryptic faults along convergent margins and elsewhere.},
  language  = {en}
}