@phdthesis{Rasche2024,
  author    = {Rasche, Daniel},
  title     = {Cosmic-ray neutron sensing for the estimation of soil moisture},
  doi       = {10.25932/publishup-63646},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-636465},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xvi, 194},
  year      = {2024},
  abstract  = {Water stored in the unsaturated soil as soil moisture is a key component of the hydrological cycle influencing numerous hydrological processes including hydrometeorological extremes. Soil moisture influences flood generation processes and during droughts when precipitation is absent, it provides plant with transpirable water, thereby sustaining plant growth and survival in agriculture and natural ecosystems. Soil moisture stored in deeper soil layers e.g. below 100 cm is of particular importance for providing plant transpirable water during dry periods. Not being directly connected to the atmosphere and located outside soil layers with the highest root densities, water in these layers is less susceptible to be rapidly evaporated and transpired. Instead, it provides longer-term soil water storage increasing the drought tolerance of plants and ecosystems. Given the importance of soil moisture in the context of hydro-meteorological extremes in a warming climate, its monitoring is part of official national adaption strategies to a changing climate. Yet, soil moisture is highly variable in time and space which challenges its monitoring on spatio-temporal scales relevant for flood and drought risk modelling and forecasting. Introduced over a decade ago, Cosmic-Ray Neutron Sensing (CRNS) is a noninvasive geophysical method that allows for the estimation of soil moisture at relevant spatio-temporal scales of several hectares at a high, subdaily temporal resolution. CRNS relies on the detection of secondary neutrons above the soil surface which are produced from high-energy cosmic-ray particles in the atmosphere and the ground. Neutrons in a specific epithermal energy range are sensitive to the amount of hydrogen present in the surroundings of the CRNS neutron detector. Due to same mass as the hydrogen nucleus, neutrons lose kinetic energy upon collision and are subsequently absorbed when reaching low, thermal energies. A higher amount of hydrogen therefore leads to fewer neutrons being detected per unit time. Assuming that the largest amount of hydrogen is stored in most terrestrial ecosystems as soil moisture, changes of soil moisture can be estimated through an inverse relationship with observed neutron intensities. Although important scientific advancements have been made to improve the methodological framework of CRNS, several open challenges remain, of which some are addressed in the scope of this thesis. These include the influence of atmospheric variables such as air pressure and absolute air humidity, as well as, the impact of variations in incoming primary cosmic-ray intensity on observed epithermal and thermal neutron signals and their correction. Recently introduced advanced neutron-to-soil moisture transfer functions are expected to improve CRNS-derived soil moisture estimates, but potential improvements need to be investigated at study sites with differing environmental conditions. Sites with strongly heterogeneous, patchy soil moisture distributions challenge existing transfer functions and further research is required to assess the impact of, and correction of derived soil moisture estimates under heterogeneous site conditions. Despite its capability of measuring representative averages of soil moisture at the field scale, CRNS lacks an integration depth below the first few decimetres of the soil. Given the importance of soil moisture also in deeper soil layers, increasing the observational window of CRNS through modelling approaches or in situ measurements is of high importance for hydrological monitoring applications. By addressing these challenges, this thesis aids to closing knowledge gaps and finding answers to some of the open questions in CRNS research. Influences of different environmental variables are quantified, correction approaches are being tested and developed. Neutron-to-soil moisture transfer functions are evaluated and approaches to reduce effects of heterogeneous soil moisture distributions are presented. Lastly, soil moisture estimates from larger soil depths are derived from CRNS through modified, simple modelling approaches and in situ estimates by using CRNS as a downhole technique. Thereby, this thesis does not only illustrate the potential of new, yet undiscovered applications of CRNS in future but also opens a new field of CRNS research. Consequently, this thesis advances the methodological framework of CRNS for above-ground and downhole applications. Although the necessity of further research in order to fully exploit the potential of CRNS needs to be emphasised, this thesis contributes to current hydrological research and not least to advancing hydrological monitoring approaches being of utmost importance in context of intensifying hydro-meteorological extremes in a changing climate.},
  language  = {en}
}
@phdthesis{Hartmann2024,
  author    = {Hartmann, Anne},
  title     = {Tracing the evolution of hillslope structure and hillslope hydrological response over ten millennia in two glacial forefields of different geology},
  doi       = {10.25932/publishup-62862},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-628629},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XVIII, 138, XLIV},
  year      = {2024},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Schmidt2024,
  author    = {Schmidt, Lena Katharina},
  title     = {Altered hydrological and sediment dynamics in high-alpine areas - Exploring the potential of machine-learning for estimating past and future changes},
  doi       = {10.25932/publishup-62330},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-623302},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxi, 129},
  year      = {2024},
  abstract  = {Climate change fundamentally transforms glaciated high-alpine regions, with well-known cryospheric and hydrological implications, such as accelerating glacier retreat, transiently increased runoff, longer snow-free periods and more frequent and intense summer rainstorms. These changes affect the availability and transport of sediments in high alpine areas by altering the interaction and intensity of different erosion processes and catchment properties. Gaining insight into the future alterations in suspended sediment transport by high alpine streams is crucial, given its wide-ranging implications, e.g. for flood damage potential, flood hazard in downstream river reaches, hydropower production, riverine ecology and water quality. However, the current understanding of how climate change will impact suspended sediment dynamics in these high alpine regions is limited. For one, this is due to the scarcity of measurement time series that are long enough to e.g. infer trends. On the other hand, it is difficult - if not impossible - to develop process-based models, due to the complexity and multitude of processes involved in high alpine sediment dynamics. Therefore, knowledge has so far been confined to conceptual models (which do not facilitate deriving concrete timings or magnitudes for individual catchments) or qualitative estimates ('higher export in warmer years') that may not be able to capture decreases in sediment export. Recently, machine-learning approaches have gained in popularity for modeling sediment dynamics, since their black box nature tailors them to the problem at hand, i.e. relatively well-understood input and output data, linked by very complex processes. Therefore, the overarching aim of this thesis is to estimate sediment export from the high alpine {\"O}tztal valley in Tyrol, Austria, over decadal timescales in the past and future - i.e. timescales relevant to anthropogenic climate change. This is achieved by informing, extending, evaluating and applying a quantile regression forest (QRF) approach, i.e. a nonparametric, multivariate machine-learning technique based on random forest. The first study included in this thesis aimed to understand present sediment dynamics, i.e. in the period with available measurements (up to 15 years). To inform the modeling setup for the two subsequent studies, this study identified the most important predictors, areas within the catchments and time periods. To that end, water and sediment yields from three nested gauges in the upper {\"O}tztal, Vent, S{\"o}lden and Tumpen (98 to almost 800 km² catchment area, 930 to 3772 m a.s.l.) were analyzed for their distribution in space, their seasonality and spatial differences therein, and the relative importance of short-term events. The findings suggest that the areas situated above 2500 m a.s.l., containing glacier tongues and recently deglaciated areas, play a pivotal role in sediment generation across all sub-catchments. In contrast, precipitation events were relatively unimportant (on average, 21 \% of annual sediment yield was associated to precipitation events). Thus, the second and third study focused on the Vent catchment and its sub-catchment above gauge Vernagt (11.4 and 98 km², 1891 to 3772 m a.s.l.), due to their higher share of areas above 2500 m. Additionally, they included discharge, precipitation and air temperature (as well as their antecedent conditions) as predictors. The second study aimed to estimate sediment export since the 1960s/70s at gauges Vent and Vernagt. This was facilitated by the availability of long records of the predictors, discharge, precipitation and air temperature, and shorter records (four and 15 years) of turbidity-derived sediment concentrations at the two gauges. The third study aimed to estimate future sediment export until 2100, by applying the QRF models developed in the second study to pre-existing precipitation and temperature projections (EURO-CORDEX) and discharge projections (physically-based hydroclimatological and snow model AMUNDSEN) for the three representative concentration pathways RCP2.6, RCP4.5 and RCP8.5. The combined results of the second and third study show overall increasing sediment export in the past and decreasing export in the future. This suggests that peak sediment is underway or has already passed - unless precipitation changes unfold differently than represented in the projections or changes in the catchment erodibility prevail and override these trends. Despite the overall future decrease, very high sediment export is possible in response to precipitation events. This two-fold development has important implications for managing sediment, flood hazard and riverine ecology. This thesis shows that QRF can be a very useful tool to model sediment export in high-alpine areas. Several validations in the second study showed good performance of QRF and its superiority to traditional sediment rating curves - especially in periods that contained high sediment export events, which points to its ability to deal with threshold effects. A technical limitation of QRF is the inability to extrapolate beyond the range of values represented in the training data. We assessed the number and severity of such out-of-observation-range (OOOR) days in both studies, which showed that there were few OOOR days in the second study and that uncertainties associated with OOOR days were small before 2070 in the third study. As the pre-processed data and model code have been made publically available, future studies can easily test further approaches or apply QRF to further catchments.},
  language  = {en}
}
@phdthesis{Zhou2024,
  author    = {Zhou, Xiangqian},
  title     = {Modeling of spatially distributed nitrate transport to investigate the effects of drought and river restoration in the Bode catchment, Central Germany},
  doi       = {10.25932/publishup-62105},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-621059},
  school      = {Universit{\"a}t Potsdam},
  pages     = {VIII, 168},
  year      = {2024},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Li2024,
  author    = {Li, Yunfei},
  title     = {On the influence of density and morphology on the Urban Heat Island intensity},
  doi       = {10.25932/publishup-62150},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-621504},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xviii, 119},
  year      = {2024},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Zhang2023,
  author    = {Zhang, Xiaolin},
  title     = {Evaluation of nitrogen dynamics in high-order streams and rivers based on high-frequency monitoring},
  doi       = {10.25932/publishup-60764},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-607642},
  school      = {Universit{\"a}t Potsdam},
  pages     = {X, 113},
  year      = {2023},
  abstract  = {Nutrient storage, transform and transport are important processes for achieving environmental and ecological health, as well as conducting water management plans. Nitrogen is one of the most noticeable elements due to its impacts on tremendous consequences of eutrophication in aquatic systems. Among all nitrogen components, researches on nitrate are blooming because of widespread deployments of in-situ high-frequency sensors. Monitoring and studying nitrate can become a paradigm for any other reactive substances that may damage environmental conditions and cause economic losses. Identifying nitrate storage and its transport within a catchment are inspiring to the management of agricultural activities and municipal planning. Storm events are periods when hydrological dynamics activate the exchange between nitrate storage and flow pathways. In this dissertation, long-term high-frequency monitoring data at three gauging stations in the Selke river were used to quantify event-scale nitrate concentration-discharge (C-Q) hysteretic relationships. The Selke catchment is characterized into three nested subcatchments by heterogeneous physiographic conditions and land use. With quantified hysteresis indices, impacts of seasonality and landscape gradients on C-Q relationships are explored. For example, arable area has deep nitrate legacy and can be activated with high intensity precipitation during wetting/wet periods (i.e., the strong hydrological connectivity). Hence, specific shapes of C-Q relationships in river networks can identify targeted locations and periods for agricultural management actions within the catchment to decrease nitrate output into downstream aquatic systems like the ocean. The capacity of streams for removing nitrate is of both scientific and social interest, which makes the quantification motivated. Although measurements of nitrate dynamics are advanced compared to other substances, the methodology to directly quantify nitrate uptake pathways is still limited spatiotemporally. The major problem is the complex convolution of hydrological and biogeochemical processes, which limits in-situ measurements (e.g., isotope addition) usually to small streams with steady flow conditions. This makes the extrapolation of nitrate dynamics to large streams highly uncertain. Hence, understanding of in-stream nitrate dynamic in large rivers is still necessary. High-frequency monitoring of nitrate mass balance between upstream and downstream measurement sites can quantitatively disentangle multi-path nitrate uptake dynamics at the reach scale (3-8 km). In this dissertation, we conducted this approach in large stream reaches with varying hydro-morphological and environmental conditions for several periods, confirming its success in disentangling nitrate uptake pathways and their temporal dynamics. Net nitrate uptake, autotrophic assimilation and heterotrophic uptake were disentangled, as well as their various diel and seasonal patterns. Natural streams generally can remove more nitrate under similar environmental conditions and heterotrophic uptake becomes dominant during post-wet seasons. Such two-station monitoring provided novel insights into reach-scale nitrate uptake processes in large streams. Long-term in-stream nitrate dynamics can also be evaluated with the application of water quality model. This is among the first time to use a data-model fusion approach to upscale the two-station methodology in large-streams with complex flow dynamics under long-term high-frequency monitoring, assessing the in-stream nitrate retention and its responses to drought disturbances from seasonal to sub-daily scale. Nitrate retention (both net uptake and net release) exhibited substantial seasonality, which also differed in the investigated normal and drought years. In the normal years, winter and early spring seasons exhibited extensive net releases, then general net uptake occurred after the annual high-flow season at later spring and early summer with autotrophic processes dominating and during later summer-autumn low-flow periods with heterotrophy-characteristics predominating. Net nitrate release occurred since late autumn until the next early spring. In the drought years, the late-autumn net releases were not so consistently persisted as in the normal years and the predominance of autotrophic processes occurred across seasons. Aforementioned comprehensive results of nitrate dynamics on stream scale facilitate the understanding of instream processes, as well as raise the importance of scientific monitoring schemes for hydrology and water quality parameters.},
  language  = {en}
}
@phdthesis{Riebold2023,
  author    = {Riebold, Johannes},
  title     = {On the linkage between future Arctic sea ice retreat, the large-scale atmospheric circulation and temperature extremes over Europe},
  doi       = {10.25932/publishup-60488},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-604883},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xi, 126},
  year      = {2023},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Duy2023,
  author    = {Duy, Nguyen Le},
  title     = {Hydrological processes in the Vietnamese Mekong Delta},
  doi       = {10.25932/publishup-60260},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-602607},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxi, 153},
  year      = {2023},
  abstract  = {Understanding hydrological processes is of fundamental importance for the Vietnamese national food security and the livelihood of the population in the Vietnamese Mekong Delta (VMD). As a consequence of sparse data in this region, however, hydrologic processes, such as the controlling processes of precipitation, the interaction between surface and groundwater, and groundwater dynamics, have not been thoroughly studied. The lack of this knowledge may negatively impact the long-term strategic planning for sustainable groundwater resources management and may result in insufficient groundwater recharge and freshwater scarcity. It is essential to develop useful methods for a better understanding of hydrological processes in such data-sparse regions. The goal of this dissertation is to advance methodologies that can improve the understanding of fundamental hydrological processes in the VMD, based on the analyses of stable water isotopes and monitoring data. The thesis mainly focuses on the controlling processes of precipitation, the mechanism of surface-groundwater interaction, and the groundwater dynamics. These processes have not been fully addressed in the VMD so far. The thesis is based on statistical analyses of the isotopic data of Global Network of Isotopes in Precipitation (GNIP), of meteorological and hydrological data from Vietnamese agencies, and of the stable water isotopes and monitoring data collected as part of this work. First, the controlling processes of precipitation were quantified by the combination of trajectory analysis, multi-factor linear regression, and relative importance analysis (hereafter, a model-based statistical approach). The validity of this approach is confirmed by similar, but mainly qualitative results obtained in other studies. The total variation in precipitation isotopes (δ18O and δ2H) can be better explained by multiple linear regression (up to 80\%) than single-factor linear regression (30\%). The relative importance analysis indicates that atmospheric moisture regimes control precipitation isotopes rather than local climatic conditions. The most crucial factor is the upstream rainfall along the trajectories of air mass movement. However, the influences of regional and local climatic factors vary in importance over the seasons. The developed model-based statistical approach is a robust tool for the interpretation of precipitation isotopes and could also be applied to understand the controlling processes of precipitation in other regions. Second, the concept of the two-component lumped-parameter model (LPM) in conjunction with stable water isotopes was applied to examine the surface-groundwater interaction in the VMD. A calibration framework was also set up to evaluate the behaviour, parameter identifiability, and uncertainties of two-component LPMs. The modelling results provided insights on the subsurface flow conditions, the recharge contributions, and the spatial variation of groundwater transit time. The subsurface flow conditions at the study site can be best represented by the linear-piston flow distribution. The contributions of the recharge sources change with distance to the river. The mean transit time (mTT) of riverbank infiltration increases with the length of the horizontal flow path and the decreasing gradient between river and groundwater. River water infiltrates horizontally mainly via the highly permeable aquifer, resulting in short mTTs (<40 weeks) for locations close to the river (<200 m). The vertical infiltration from precipitation takes place primarily via a low-permeable overlying aquitard, resulting in considerably longer mTTs (>80 weeks). Notably, the transit time of precipitation infiltration is independent of the distance to the river. All these results are hydrologically plausible and could be quantified by the presented method for the first time. This study indicates that the highly complex mechanism of surface-groundwater interaction at riverbank infiltration systems can be conceptualized by exploiting two-component LPMs. It is illustrated that the model concept can be used as a tool to investigate the hydrological functioning of mixing processes and the flow path of multiple water components in riverbank infiltration systems. Lastly, a suite of time series analysis approaches was applied to examine the groundwater dynamics in the VMD. The assessment was focused on the time-variant trends of groundwater levels (GWLs), the groundwater memory effect (representing the time that an aquifer holds water), and the hydraulic response between surface water and multi-layer alluvial aquifers. The analysis indicates that the aquifers act as low-pass filters to reduce the high-frequency signals in the GWL variations, and limit the recharge to the deep groundwater. The groundwater abstraction has exceeded groundwater recharge between 1997 and 2017, leading to the decline of groundwater levels (0.01-0.55 m/year) in all considered aquifers in the VMD. The memory effect varies according to the geographical location, being shorter in shallow aquifers and flood-prone areas and longer in deep aquifers and coastal regions. Groundwater depth, season, and location primarily control the variation of the response time between the river and alluvial aquifers. These findings are important contributions to the hydrogeological literature of a little-known groundwater system in an alluvial setting. It is suggested that time series analysis can be used as an efficient tool to understand groundwater systems where resources are insufficient to develop a physical-based groundwater model. This doctoral thesis demonstrates that important aspects of hydrological processes can be understood by statistical analysis of stable water isotope and monitoring data. The approaches developed in this thesis can be easily transferred to regions in similar tropical environments, particularly those in alluvial settings. The results of the thesis can be used as a baseline for future isotope-based studies and contribute to the hydrogeological literature of little-known groundwater systems in the VMD.},
  language  = {en}
}
@phdthesis{Calitri2023,
  author    = {Calitri, Francesca},
  title     = {Co-evolution of erosion rates, weathering and profile development in soil landscapes of hummocky ground moraines},
  doi       = {10.25932/publishup-60138},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-601387},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XXVII, 163, V},
  year      = {2023},
  abstract  = {Soil is today considered a non-renewable resource on societal time scale, as the rate of soil loss is higher than the one of soil formation. Soil formation is complex, can take several thousands of years and is influenced by a variety of factors, one of them is time. Oftentimes, there is the assumption of constant and progressive conditions for soil and/or profile development (i.e., steady-state). In reality, for most of the soils, their (co-)evolution leads to a complex and irregular soil development in time and space characterised by "progressive" and "regressive" phases. Lateral transport of soil material (i.e., soil erosion) is one of the principal processes shaping the land surface and soil profile during "regressive" phases and one of the major environmental problems the world faces. Anthropogenic activities like agriculture can exacerbate soil erosion. Thus, it is of vital importance to distinguish short-term soil redistribution rates (i.e., within decades) influenced by human activities differ from long-term natural rates. To do so, soil erosion (and denudation) rates can be determined by using a set of isotope methods that cover different time scales at landscape level. With the aim to unravel the co-evolution of weathering, soil profile development and lateral redistribution on a landscape level, we used Pluthonium-239+240 (239+240Pu), Beryllium-10 (10Be, in situ and meteoric) and Radiocarbon (14C) to calculate short- and long-term erosion rates in two settings, i.e., a natural and an anthropogenic environment in the hummocky ground moraine landscape of the Uckermark, North-eastern Germany. The main research questions were: 1. How do long-term and short-term rates of soil redistributing processes differ? 2. Are rates calculated from in situ 10Be comparable to those of using meteoric 10Be? 3. How do soil redistribution rates (short- and long-term) in an agricultural and in a natural landscape compare to each other? 4. Are the soil patterns observed in northern Germany purely a result of past events (natural and/or anthropogenic) or are they imbedded in ongoing processes? Erosion and deposition are reflected in a catena of soil profiles with no or almost no erosion on flat positions (hilltop), strong erosion on the mid-slope and accumulation of soil material at the toeslope position. These three characteristic process domains were chosen within the CarboZALF-D experimental site, characterised by intense anthropogenic activities. Likewise, a hydrosequence in an ancient forest was chosen for this study and being regarded as a catena strongly influenced by natural soil transport. The following main results were obtained using the above-mentioned range of isotope methods available to measure soil redistribution rates depending on the time scale needed (e.g., 239+240Pu, 10Be, 14C): 1. Short-term erosion rates are one order of magnitude higher than long-term rates in agricultural settings. 2. Both meteoric and in situ 10Be are suitable soil tracers to measure the long-term soil redistribution rates giving similar results in an anthropogenic environment for different landscape positions (e.g., hilltop, mid-slope, toeslope) 3. Short-term rates were extremely low/negligible in a natural landscape and very high in an agricultural landscape - -0.01 t ha-1 yr-1 (average value) and -25 t ha-1 yr-1 respectively. On the contrary, long-term rates in the forested landscape are comparable to those calculated in the agricultural area investigated with average values of -1.00 t ha-1 yr-1 and -0.79 t ha-1 yr-1. 4. Soil patterns observed in the forest might be due to human impact and activities started after the first settlements in the region, earlier than previously postulated, between 4.5 and 6.8 kyr BP, and not a result of recent soil erosion. 5. Furthermore, long-term soil redistribution rates are similar independently from the settings, meaning past natural soil mass redistribution processes still overshadow the present anthropogenic erosion processes. Overall, this study could make important contributions to the deciphering of the co-evolution of weathering, soil profile development and lateral redistribution in North-eastern Germany. The multi-methodological approach used can be challenged by the application in a wider range of landscapes and geographic regions.},
  language  = {en}
}
@phdthesis{Kemper2023,
  author    = {Kemper, Tarek},
  title     = {KLIMAGRAR - Neue Methoden der Begleitforschung am Beispiel des klimagerechten Handelns in der Landwirtschaft},
  doi       = {10.25932/publishup-60192},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-601924},
  school      = {Universit{\"a}t Potsdam},
  pages     = {109},
  year      = {2023},
  abstract  = {In Forschungsprogrammen werden zahlreiche Akteure mit unterschiedlichen Hintergr{\"u}nden und fachlichen Expertisen in Einzel- oder Verbundvorhaben vereint, die jedoch weitestgehend unabh{\"a}ngig voneinander durchgef{\"u}hrt werden. Vor dem Hintergrund, dass gesamtgesellschaftliche Herausforderungen wie die globale Erw{\"a}rmung zunehmend disziplin{\"u}bergreifende L{\"o}sungsans{\"a}tze erfordern, sollten Vernetzungs- und Transferprozesse in Forschungsprogrammen st{\"a}rker in den Fokus r{\"u}cken. Mit der Implementierung einer Begleitforschung kann dieser Forderung Rechnung getragen werden. Begleitforschung unterscheidet sich in ihrer Herangehensweise und ihrer Zielvorstellung von den „{\"u}blichen" Projekten und kann in unterschiedlichen theoretischen Reinformen auftreten. Verk{\"u}rzt dargestellt agiert sie entweder (1) inhaltlich komplement{\"a}r zu den jeweiligen Forschungsprojekten, (2) auf einer Metaebene mit Fokus auf die Prozesse im Forschungsprogramm oder (3) als integrierende, synthetisierende Instanz, f{\"u}r die die Vernetzung der Projekte im Forschungsprogramm sowie der Wissenstransfer von Bedeutung sind. Zwar sind diese Formen analytisch in theoretische Reinformen trennbar, in der Praxis ergibt sich in der Regel jedoch ein Mix aus allen dreien. In diesem Zusammenhang schließt die vorliegende Dissertation als erg{\"a}nzende Studie an bisherige Ans{\"a}tze zum methodischen Handwerkszeug der Begleitforschung an und fokussiert auf folgende Fragestellungen: Auf welcher Basis kann die Vernetzung der Akteure in einem Forschungsprogramm durchgef{\"u}hrt werden, um diese effektiv zusammenzubringen? Welche weiteren methodischen Elemente sollten daran ansetzen, um einen Mehrwert zu generieren, der die Summe der Einzelergebnisse des Forschungsprogrammes {\"u}bersteigt? Von welcher Art kann dann ein solcher Mehrwert sein und welche Rolle spielt dabei die Begleitforschung? Das erste methodische Element bildet die Erhebung und Aufbereitung einer Ausgangsdatenbasis. Durch eine auf semantischer Analyse basierenden Verschlagwortung projektbezogener Texte l{\"a}sst sich eine umfassende Datenbasis aus den Inhalten der Forschungsprojekte generieren. Die Schlagw{\"o}rter werden dabei anhand eines kontrollierten Vokabulars in einem Schlagwortkatalog strukturiert. Parallel dazu werden sie wiederum den jeweiligen Projekten zugeordnet, wodurch diese thematische Merkmale erhalten. Um thematische {\"U}berschneidungen zwischen Forschungsprojekten sichtbar und interpretierbar zu machen, beinhaltet das zweite Element Ans{\"a}tze zur Visualisierung. Dazu werden die Informationen in einen Netzwerkgraphen transferiert, der sowohl alle im Forschungsprogramm involvierten Projekte als auch die identifizierten Schlagw{\"o}rter in Relation zueinander abbilden kann. So kann zum Beispiel sichtbar gemacht werden, welche Forschungsprojekte sich auf Basis ihrer Inhalte „n{\"a}her" sind als andere. Genau diese Information wird im dritten methodischen Element als Planungsgrundlage f{\"u}r unterschiedliche Veranstaltungsformate wie Arbeitstagungen oder Transferwerkst{\"a}tten genutzt. Das vierte methodische Element umfasst die Synthesebildung. Diese gestaltet sich als Prozess {\"u}ber den gesamten Zeitraum der Zusammenarbeit zwischen Begleitforschung und den weiteren Forschungsprojekten hinweg, da in die Synthese unter anderem Zwischen-, Teil- und Endergebnisse der Projekte einfließen, genauso wie Inhalte aus den unterschiedlichen Veranstaltungen. Letztendlich ist dieses vierte Element auch das Mittel, um aus den integrierten und synthetisierten Informationen Handlungsempfehlungen f{\"u}r zuk{\"u}nftige Vorhaben abzuleiten. Die Erarbeitung der methodischen Elemente erfolgte im laufenden Prozess des Begleitforschungsprojektes KlimAgrar, welches der vorliegenden Dissertation als Fallbeispiel dient und dessen Hintergr{\"u}nde in der Thematik Klimaschutz und Klimaanpassung in der Landwirtschaft im Text ausf{\"u}hrlich erl{\"a}utert werden.},
  language  = {de}
}
@phdthesis{Schmitz2023,
  author    = {Schmitz, Se{\´a}n},
  title     = {Using low-cost sensors to gather high resolution measurements of air quality in urban environments and inform mobility policy},
  doi       = {10.25932/publishup-60105},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-601053},
  school      = {Universit{\"a}t Potsdam},
  pages     = {180},
  year      = {2023},
  abstract  = {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 B{\"o}ckhstrasse, 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.},
  language  = {en}
}
@phdthesis{Luna2023,
  author    = {Luna, Lisa Victoria},
  title     = {Rainfall-triggered landslides: conditions, prediction, and warning},
  doi       = {10.25932/publishup-60092},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-600927},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 119},
  year      = {2023},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Mtilatila2023,
  author    = {Mtilatila, Lucy Mphatso Ng'ombe},
  title     = {Climate change effects on drought, freshwater availability and hydro-power generation in an African environment},
  doi       = {10.25932/publishup-59929},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-599298},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xv, 167},
  year      = {2023},
  abstract  = {The work is designed to investigate the impacts and sensitivity of climate change on water resources, droughts and hydropower production in Malawi, the South-Eastern region which is highly vulnerable to climate change. It is observed that rainfall is decreasing and temperature is increasing which calls for the understanding of what these changes may impact the water resources, drought occurrences and hydropower generation in the region. The study is conducted in the Greater Lake Malawi Basin (Lake Malawi and Shire River Basins) and is divided into three projects. The first study is assessing the variability and trends of both meteorological and hydrological droughts from 1970-2013 in Lake Malawi and Shire River basins using the standardized precipitation index (SPI) and standardized precipitation and evaporation Index (SPEI) for meteorological droughts and the lake level change index (LLCI) for hydrological droughts. And later the relationship of the meteorological and hydrological droughts is established. While the second study extends the drought analysis into the future by examining the potential future meteorological water balance and associated drought characteristics such as the drought intensity (DI), drought months (DM), and drought events (DE) in the Greater Lake Malawi Basin. The sensitivity of drought to changes of rainfall and temperature is also assessed using the scenario-neutral approach. The climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021-2050 and 2071-2100 are used. The study also investigates the effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble in reproducing observed drought characteristics as compared to raw climate projections. The sensitivity of key hydrologic variables and hydropower generation to climate change in Lake Malawi and Shire River basins is assessed in third study. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Similar to second study, the scenario-neutral approach is also applied to determine the sensitivity of climate change on water resources more particularly Lake Malawi level and Shire River flow which later helps to estimate the hydropower production susceptibility. Results suggest that meteorological droughts are increasing due to a decrease in precipitation which is exacerbated by an increase in temperature (potential evapotranspiration). The hydrological system of Lake Malawi seems to have a >24-month memory towards meteorological conditions since the 36-months SPEI can predict hydrological droughts ten-months in advance. The study has found the critical lake level that would trigger hydrological drought to be 474.1 m.a.s.l. Despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher DI and longer events (DM). DI is projected to increase between +25\% and +50\% during 2021-2050 and between +131\% and +388\% during 2071-2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, DE is decreasing. Projected droughts based on RCP8.5 are 1.7 times more severe than droughts based on RCP4.5. It is also found that an annual temperature increase of 1°C decreases mean lake level and outflow by 0.3 m and 17\%, respectively, signifying the importance of intensified evaporation for Lake Malawi's water budget. Meanwhile, a +5\% (-5\%) deviation in annual rainfall changes mean lake level by +0.7 m (-0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows on Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5°C (3.5°C) and -20\% (-15\%). The study further projects a reduction in annual hydropower production between 1\% (RCP8.5) and 2.5\% (RCP4.5) during 2021-2050 and between 5\% (RCP4.5) and 24\% (RCP8.5) during 2071-2100. The findings are later linked to global policies more particularly the United Nations Framework Convention on Climate Change (UNFCCC)'s Paris Agreement and the United Nations (UN)'s Sustainable Development Goals (SDGs), and how the failure to adhere the restriction of temperature increase below the global limit of 1.5°C will affect drought and the water resources in Malawi consequently impact the hydropower production. As a result, the achievement of most of the SDGs will be compromised. The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change. The information generation is important for decision making more especially supporting the climate action required to fight against climate change. The frequency of extreme climate events due to climate change has reached the climate emergency as saving lives and livelihoods require urgent action.},
  language  = {en}
}
@phdthesis{Seleem2023,
  author    = {Seleem, Omar},
  title     = {Towards urban pluvial flood mapping using data-driven models},
  doi       = {10.25932/publishup-59813},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-598137},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xv, 95},
  year      = {2023},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Serwene2023,
  author    = {Serwene, Pola},
  title     = {Geographie verstehen durch Zweisprachigkeit},
  series = {Potsdamer Geographische Praxis},
  journal   = {Potsdamer Geographische Praxis},
  number    = {19},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-557-6},
  issn      = {2194-1599},
  doi       = {10.25932/publishup-57848},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-578486},
  school      = {Universit{\"a}t Potsdam},
  pages     = {360},
  year      = {2023},
  abstract  = {Bilingualer Unterricht gilt als das Erfolgsmodell f{\"u}r den schulischen Fremdsprachenerwerb in Deutschland und die Beherrschung einer Fremdsprache in Wort und Schrift ist eine entscheidende berufsqualifizierende Kompetenz in unserer globalisierten Welt. Insbesondere die Verzahnung fachlicher und sprachlicher Inhalte im Kontext Bilingualen Unterrichts scheint gewinnbringend f{\"u}r den Fremdspracherwerb zu sein. Dabei ist die Diskrepanz zwischen den zumeist noch geringen fremdsprachlichen F{\"a}higkeiten der Lernenden und den fachlichen Anspr{\"u}chen des Geographieunterrichts eine große Herausforderung f{\"u}r fachliches Lernen im bilingualen Sachfachunterricht. Es stellt sich die Frage, wie der Bilinguale Unterricht gestaltet sein muss, um einerseits geographische Themen fachlich komplex behandeln zu k{\"o}nnen und andererseits die Lernenden fremdsprachlich nicht zu {\"u}berfordern. Im Rahmen einer Design-Based-Research-Studie im bilingualen Geographieunterricht wurde untersucht, wie fachliches Lernen im bilingualen Geographieunterricht durch den Einsatz beider beteiligter Sprachen (Englisch/Deutsch) gef{\"o}rdert werden kann. Auf Grundlage eines theoretisch fundierten Kenntnisstands zum Bilingualen Unterricht und zum Lernen mit Fachkonzepten im Geographieunterricht wurde eine Lernumgebung konzipiert, im Unterricht erprobt und weiterentwickelt, in der Strategien des Sprachwechsels zum Einsatz kommen. Die Ergebnisse der Studie sind kontextbezogene Theorien einer zweisprachigen Didaktik f{\"u}r den bilingualen Geographieunterricht und Erkenntnisse zum Lernen mit Fachkonzepten im Geographieunterricht am Beispiel des geographischen Konzepts Wandel. Produkt der Studie ist eine unterrichtstaugliche Lernumgebung zum Thema Wandlungsprozesse an ausgew{\"a}hlten Orten f{\"u}r den bilingualen Geographieunterricht mit didaktischem Konzept, Unterrichtsmaterialien und -medien.},
  language  = {de}
}
@phdthesis{Schoppa2023,
  author    = {Schoppa, Lukas},
  title     = {Dynamics in the flood vulnerability of companies},
  doi       = {10.25932/publishup-59242},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-592424},
  school      = {Universit{\"a}t Potsdam},
  pages     = {X, 165},
  year      = {2023},
  abstract  = {River flooding is a constant peril for societies, causing direct economic losses in the order of \$100 billion worldwide each year. Under global change, the prolonged concentration of people and assets in floodplains is accompanied by an emerging intensification of flood extremes due to anthropogenic global warming, ultimately exacerbating flood risk in many regions of the world. Flood adaptation plays a key role in the mitigation of impacts, but poor understanding of vulnerability and its dynamics limits the validity of predominant risk assessment methods and impedes effective adaptation strategies. Therefore, this thesis investigates new methods for flood risk assessment that embrace the complexity of flood vulnerability, using the understudied commercial sector as an application example. Despite its importance for accurate risk evaluation, flood loss modeling has been based on univariable and deterministic stage-damage functions for a long time. However, such simplistic methods only insufficiently describe the large variation in damage processes, which initiated the development of multivariable and probabilistic loss estimation techniques. The first study of this thesis developed flood loss models for companies that are based on emerging statistical and machine learning approaches (i.e., random forest, Bayesian network, Bayesian regression). In a benchmarking experiment on basis of object-level loss survey data, the study showed that all proposed models reproduced the heterogeneity in damage processes and outperformed conventional stage-damage functions with respect to predictive accuracy. Another advantage of the novel methods is that they convey probabilistic information in predictions, which communicates the large remaining uncertainties transparently and, hence, supports well-informed risk assessment. Flood risk assessment combines vulnerability assessment (e.g., loss estimation) with hazard and exposure analyses. Although all of the three risk drivers interact and change over time, such dependencies and dynamics are usually not explicitly included in flood risk models. Recently, systemic risk assessment that dissolves the isolated consideration of risk drivers has gained traction, but the move to holistic risk assessment comes with limited thoroughness in terms of loss estimation and data limitations. In the second study, I augmented a socio-hydrological system dynamics model for companies in Dresden, Germany, with the multivariable Bayesian regression loss model from the first study. The additional process-detail and calibration data improved the loss estimation in the systemic risk assessment framework and contributed to more accurate and reliable simulations. The model uses Bayesian inference to quantify uncertainty and learn the model parameters from a combination of prior knowledge and diverse data. The third study demonstrates the potential of the socio-hydrological flood risk model for continuous, long-term risk assessment and management. Using hydroclimatic ad socioeconomic forcing data, I projected a wide range of possible risk trajectories until the end of the century, taking into account the adaptive behavior of companies. The study results underline the necessity of increased adaptation efforts to counteract the expected intensification of flood risk due to climate change. A sensitivity analysis of the effectiveness of different adaptation measures and strategies revealed that optimized adaptation has the potential to mitigate flood risk by up to 60\%, particularly when combining structural and non-structural measures. Additionally, the application shows that systemic risk assessment is capable of capturing adverse long-term feedbacks in the human-flood system such as the levee effect. Overall, this thesis advances the representation of vulnerability in flood risk modeling by offering modeling solutions that embrace the complexity of human-flood interactions and quantify uncertainties consistently using probabilistic modeling. The studies show how scarce information in data and previous experiments can be integrated in the inference process to provide model predictions and simulations that are reliable and rich in information. Finally, the focus on the flood vulnerability of companies provides new insights into the heterogeneous damage processes and distinct flood coping of this sector.},
  language  = {en}
}
@phdthesis{Nomosatryo2023,
  author    = {Nomosatryo, Sulung},
  title     = {Biogeochemical characteristics of a tropical lake},
  doi       = {10.25932/publishup-59400},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-594006},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 175},
  year      = {2023},
  abstract  = {Biogeochemical analyses of lacustrine environments are well-established methods that allow exploring and understanding complex systems in the lake ecosystem. However, most were conducted in temperate lakes controlled by entirely different physical conditions than in tropical climates. The most important difference between the temperate and tropical lakes is lacking seasonal temperature fluctuations in the latter, which leads to a stable temperature gradient in the water column. Thus, the water column in tropical latitudes generally is void of perturbations that can be seen in their temperate counterparts. Permanent stratification in the water column provides optimal conditions for intact sedimentation. The geochemical processes in the water column and the weathering process in the distinct lithology in the catchment leads to the different biogeochemical characteristic in the sediment. Conducting a biogeochemical study in this lake sediment, especially in the Sediment Water Interface (SWI) helps reveal the sedimentation and diagenetic process records influenced by the internal or external loading. Lake Sentani, the study area, is one of the thousands of lakes in Indonesia and located in the Papua province. This tropical lake has a unique feature, as it consists of four interconnected sub-basins with different water depths. More importantly, its catchment is comprised of various different lithologies. Hence, its lithological characteristics are highly diverse, and range from mafic and ultramafic rocks to clastic sediment and carbonates. Each sub-basin receives a distinct sediment input. Equally important, besides the natural loading, Lake Sentani is also influenced by anthropogenic input. Previous studies have elaborated that there is an increase in population growth rate around the lake which has direct consequences on eutrophication. Considering these factors, the government of The Republic of Indonesia put Lake Sentani on the list of national priority lakes for restoration. This thesis aims to develop a fundamental understanding of Lake Sentani's sedimentary geochemistry and geomicrobiology with a special focus on the effects of different lithologies and anthropogenic pressures in the catchment area. We conducted geochemical and geomicrobiology research on Lake Sentani to meet this objective. We investigated geochemical characteristics in the water column, porewater, and sediment core of the four sub-basins. Additional to direct investigations of the lake itself, we also studied the sediments in the tributary rivers, of which some are ephemeral, as well as the river mouths, as connections between riverine and the lacustrine habitat. The thesis is composed of three main publications about Lake Sentani and supported by several publications that focus on other tropical lakes in Indonesia. The first main publication investigates the geochemical characterization of the water column, porewater, and surface sediment (upper 40-50 cm) from the center of the four sub-basins. It reveals that besides catchment lithology, the water column heavily influences the geochemical characteristics in the lake sediments and their porewater. The findings indicate that water column stratification has a strong influence on overall chemistry. The four sub-basins are very different with regard to their water column chemistry. Based on the physicochemical profiles, especially dissolved oxygen, one sub-basin is oxygenated, one intermediate i.e. just reaches oxygen depletion at the sediment-water interface, and two sub-basins are fully meromictic. However, all four sub-basins share the same surface water chemistry. The structure of the water column creates differences on the patterns of anions and cations in the porewater. Likewise, the distinct differences in geochemical composition between the sub-basins show that the lithology in the catchment affects the geochemical characteristic in the sediment. Overall, water column stratification and particularly bottom water oxygenation strongly influence the overall elemental composition of the sediment and porewater composition. The second publication reveals differences in surface sediment composition between habitats, influenced by lithological variations in the catchment area. The macro-element distribution shows that the geochemical characteristics between habitats are different. Furthermore, the geochemical composition also indicates a distinct distribution between the sub-basins. The geochemical composition of the eastern sub-basin suggests that lithogenic elements are more dominant than authigenic elements. This is also supported by sulfide speciation, particle distribution, and smear slide data. The third publication is a geomicrobiological study of the surface sediment. We compare the geochemical composition of the surface sediment and its microbiological composition and compare the different signals. Next Generation Sequencing (NGS) of the 16S rRNA gene was applied to determine the microbial community composition of the surface sediment from a great number of locations. We use a large number of sampling sites in all four sub-basins as well as in the rivers and river mouths to illustrate the links between the river, the river mouth, and the lake. Rigorous assessment of microbial communities across the diverse Lake Sentani habitats allowed us to study some of these links and report novel findings on microbial patterns in such ecosystems. The main result of the Principal Coordinates Analysis (PCoA) based on microbial community composition highlighted some commonalities but also differences between the microbial community analysis and the geochemical data. The microbial community in rivers, river mouths and sub-basins is strongly influenced by anthropogenic input from the catchment area. Generally, Bacteroidetes and Firmicutes could be an indicator for river sediments. The microbial community in the river is directly influenced by anthropogenic pressure and is markedly different from the lake sediment. Meanwhile, the microbial community in the lake sediment reflects the anoxic environment, which is prevalent across the lake in all sediments below a few mm burial depth. The lake sediments harbour abundant sulfate reducers and methanogens. The microbial communities in sediments from river mouths are influenced by both rivers and lake ecosystems. This study provides valuable information to understand the basic processes that control biogeochemical cycling in Lake Sentani. Our findings are critical for lake managers to accurately assess the uncertainties of the changing environmental conditions related to the anthropogenic pressure in the catchment area. Lake Sentani is a unique study site directly influenced by the different geology across the watershed and morphometry of the four studied basins. As a result of these factors, there are distinct geochemical differences between the habitats (river, river mouth, lake) and the four sub-basins. In addition to geochemistry, microbial community composition also shows differences between habitats, although there are no obvious differences between the four sub-basins. However, unlike sediment geochemistry, microbial community composition is impacted by human activities. Therefore, this thesis will provide crucial baseline data for future lake management.},
  language  = {en}
}
@phdthesis{Han2023,
  author    = {Han, Sungju},
  title     = {Perceptions of nature-based solutions in the context of floods},
  doi       = {10.25932/publishup-57952},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-579524},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiv, 150},
  year      = {2023},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Fischer2022,
  author    = {Fischer, Melanie},
  title     = {Outburst floods in the Greater Himalayas},
  doi       = {10.25932/publishup-56997},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-569972},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xviii, 155},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Zeitz2022,
  author    = {Zeitz, Maria},
  title     = {Modeling the future resilience of the Greenland Ice Sheet},
  doi       = {10.25932/publishup-56883},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-568839},
  school      = {Universit{\"a}t Potsdam},
  pages     = {x, 189},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Burgold2022,
  author    = {Burgold, Julia},
  title     = {Erfahrung und Reflexion von Obdachlosigkeit},
  series = {Potsdamer Geographische Praxis},
  journal   = {Potsdamer Geographische Praxis},
  number    = {18},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-541-5},
  issn      = {2194-1599},
  doi       = {10.25932/publishup-55393},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-553932},
  school      = {Universit{\"a}t Potsdam},
  pages     = {342},
  year      = {2022},
  abstract  = {Die Arbeit gibt einen Einblick in die Verst{\"a}ndigungspraxen bei Stadtf{\"u}hrungen mit (ehemaligen) Obdachlosen, die in ihrem Selbstverst{\"a}ndnis auf die Herstellung von Verst{\"a}ndnis, Toleranz und Anerkennung f{\"u}r von Obdachlosigkeit betroffene Personen zielen. Zun{\"a}chst wird in den Diskurs des Slumtourismus eingef{\"u}hrt und, angesichts der Vielfalt der damit verbundenen Erscheinungsformen, Slumming als organisierte Begegnung mit sozialer Ungleichheit definiert. Die zentralen Diskurslinien und die darin eingewobenen moralischen Positionen werden nachvollzogen und im Rahmen der eigenommenen wissenssoziologischen Perspektive als Ausdruck einer per se polykontexturalen Praxis re-interpretiert. Slumming erscheint dann als eine organisierte Begegnung von Lebensformen, die sich in einer Weise fremd sind, als dass ein unmittelbares Verstehen unwahrscheinlich erscheint und genau aus diesem Grund auf der Basis von g{\"a}ngigen Interpretationen des Common Sense ausgehandelt werden muss. Vor diesem Hintergrund untersucht die vorliegende Arbeit, wie sich Teilnehmer und Stadtf{\"u}hrer {\"u}ber die Erfahrung der Obdachlosigkeit praktisch verst{\"a}ndigen und welcher Art das hier{\"u}ber erzeugte Verst{\"a}ndnis f{\"u}r die im {\"o}ffentlichen Diskurs mit vielf{\"a}ltigen stigmatisierenden Zuschreibungen versehenen Obdachlosen ist. Dabei interessiert besonders, in Bezug auf welche Aspekte der Erfahrung von Obdachlosigkeit ein gemeinsames Verst{\"a}ndnis m{\"o}glich wird und an welchen Stellen dieses an Grenzen ger{\"a}t. Dazu wurden die Gespr{\"a}chsverl{\"a}ufe auf neun Stadtf{\"u}hrungen mit (ehemaligen) obdachlosen Stadtf{\"u}hrern unterschiedlicher Anbieter im deutschsprachigen Raum verschriftlicht und mit dem Verfahren der Dokumentarischen Methode ausgewertet. Die vergleichende Betrachtung der Verst{\"a}ndigungspraxen er{\"o}ffnet nicht zuletzt eine differenzierte Perspektive auf die in den Prozessen der Verst{\"a}ndigung immer schon eingewobenen Anerkennungspraktiken. Mit Blick auf die moralische Debatte um organisierte Begegnungen mit sozialer Ungleichheit wird dadurch eine ethische Perspektive angeregt, in deren Zentrum Fragen zur Vermittlungsarbeit stehen.},
  language  = {de}
}
@phdthesis{Trautmann2022,
  author    = {Trautmann, Tina},
  title     = {Understanding global water storage variations using model-data integration},
  doi       = {10.25932/publishup-56595},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-565954},
  school      = {Universit{\"a}t Potsdam},
  pages     = {VIII, 141},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Krummenauer2022,
  author    = {Krummenauer, Linda},
  title     = {Global heat adaptation among urban populations and its evolution under different climate futures},
  doi       = {10.25932/publishup-55929},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-559294},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 161},
  year      = {2022},
  abstract  = {Heat and increasing ambient temperatures under climate change represent a serious threat to human health in cities. Heat exposure has been studied extensively at a global scale. Studies comparing a defined temperature threshold with the future daytime temperature during a certain period of time, had concluded an increase in threat to human health. Such findings however do not explicitly account for possible changes in future human heat adaptation and might even overestimate heat exposure. Thus, heat adaptation and its development is still unclear. Human heat adaptation refers to the local temperature to which populations are adjusted to. It can be inferred from the lowest point of the U- or V-shaped heat-mortality relationship (HMR), the Minimum Mortality Temperature (MMT). While epidemiological studies inform on the MMT at the city scale for case studies, a general model applicable at the global scale to infer on temporal change in MMTs had not yet been realised. The conventional approach depends on data availability, their robustness, and on the access to daily mortality records at the city scale. Thorough analysis however must account for future changes in the MMT as heat adaptation happens partially passively. Human heat adaptation consists of two aspects: (1) the intensity of the heat hazard that is still tolerated by human populations, meaning the heat burden they can bear and (2) the wealth-induced technological, social and behavioural measures that can be employed to avoid heat exposure. The objective of this thesis is to investigate and quantify human heat adaptation among urban populations at a global scale under the current climate and to project future adaptation under climate change until the end of the century. To date, this has not yet been accomplished. The evaluation of global heat adaptation among urban populations and its evolution under climate change comprises three levels of analysis. First, using the example of Germany, the MMT is calculated at the city level by applying the conventional method. Second, this thesis compiles a data pool of 400 urban MMTs to develop and train a new model capable of estimating MMTs on the basis of physical and socio-economic city characteristics using multivariate non-linear multivariate regression. The MMT is successfully described as a function of the current climate, the topography and the socio-economic standard, independently of daily mortality data for cities around the world. The city-specific MMT estimates represents a measure of human heat adaptation among the urban population. In a final third analysis, the model to derive human heat adaptation was adjusted to be driven by projected climate and socio-economic variables for the future. This allowed for estimation of the MMT and its change for 3 820 cities worldwide for different combinations of climate trajectories and socio-economic pathways until 2100. The knowledge on the evolution of heat adaptation in the future is a novelty as mostly heat exposure and its future development had been researched. In this work, changes in heat adaptation and exposure were analysed jointly. A wide range of possible health-related outcomes up to 2100 was the result, of which two scenarios with the highest socio-economic developments but opposing strong warming levels were highlighted for comparison. Strong economic growth based upon fossil fuel exploitation is associated with a high gain in heat adaptation, but may not be able to compensate for the associated negative health effects due to increased heat exposure in 30\% to 40\% of the cities investigated caused by severe climate change. A slightly less strong, but sustainable growth brings moderate gains in heat adaptation but a lower heat exposure and exposure reductions in 80\% to 84\% of the cities in terms of frequency (number of days exceeding the MMT) and intensity (magnitude of the MMT exceedance) due to a milder global warming. Choosing a 2 ° C compatible development by 2100 would therefore lower the risk of heat-related mortality at the end of the century. In summary, this thesis makes diverse and multidisciplinary contributions to a deeper understanding of human adaptation to heat under the current and the future climate. It is one of the first studies to carry out a systematic and statistical analysis of urban characteristics which are useful as MMT drivers to establish a generalised model of human heat adaptation, applicable at the global level. A broad range of possible heat-related health options for various future scenarios was shown for the first time. This work is of relevance for the assessment of heat-health impacts in regions where mortality data are not accessible or missing. The results are useful for health care planning at the meso- and macro-level and to urban- and climate change adaptation planning. Lastly, beyond having met the posed objective, this thesis advances research towards a global future impact assessment of heat on human health by providing an alternative method of MMT estimation, that is spatially and temporally flexible in its application.},
  language  = {en}
}
@phdthesis{Kemter2022,
  author    = {Kemter, Matthias},
  title     = {River floods in a changing world},
  doi       = {10.25932/publishup-55856},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-558564},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xvii, 120},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{SamprognaMohor2022,
  author    = {Samprogna Mohor, Guilherme},
  title     = {Exploring the transferability of flood loss models across flood types},
  doi       = {10.25932/publishup-55714},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-557141},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XXIV, 182},
  year      = {2022},
  abstract  = {The estimation of financial losses is an integral part of flood risk assessment. The application of existing flood loss models on locations or events different from the ones used to train the models has led to low performance, showing that characteristics of the flood damaging process have not been sufficiently well represented yet. To improve flood loss model transferability, I explore various model structures aiming at incorporating different (inland water) flood types and pathways. That is based on a large survey dataset of approximately 6000 flood-affected households which addresses several aspects of the flood event, not only the hazard characteristics but also information on the affected building, socioeconomic factors, the household's preparedness level, early warning, and impacts. Moreover, the dataset reports the coincidence of different flood pathways. Whilst flood types are a classification of flood events reflecting their generating process (e.g. fluvial, pluvial), flood pathways represent the route the water takes to reach the receptors (e.g. buildings). In this work, the following flood pathways are considered: levee breaches, river floods, surface water floods, and groundwater floods. The coincidence of several hazard processes at the same time and place characterises a compound event. In fact, many flood events develop through several pathways, such as the ones addressed in the survey dataset used. Earlier loss models, although developed with one or multiple predictor variables, commonly use loss data from a single flood event which is attributed to a single flood type, disregarding specific flood pathways or the coincidence of multiple pathways. This gap is addressed by this thesis through the following research questions: 1. In which aspects do flood pathways of the same (compound inland) flood event differ? 2. How much do factors which contribute to the overall flood loss in a building differ in various settings, specifically across different flood pathways? 3. How well can Bayesian loss models learn from different settings? 4. Do compound, that is, coinciding flood pathways result in higher losses than a single pathway, and what does the outcome imply for future loss modelling? Statistical analysis has found that households affected by different flood pathways also show, in general, differing characteristics of the affected building, preparedness, and early warning, besides the hazard characteristics. Forecasting and early warning capabilities and the preparedness of the population are dominated by the general flood type, but characteristics of the hazard at the object-level, the impacts, and the recovery are more related to specific flood pathways, indicating that risk communication and loss models could benefit from the inclusion of flood-pathway-specific information. For the development of the loss model, several potentially relevant predictors are analysed: water depth, duration, velocity, contamination, early warning lead time, perceived knowledge about self-protection, warning information, warning source, gap between warning and action, emergency measures, implementation of property-level precautionary measures (PLPMs), perceived efficacy of PLPMs, previous flood experience, awareness of flood risk, ownership, building type, number of flats, building quality, building value, house/flat area, building area, cellar, age, household size, number of children, number of elderly residents, income class, socioeconomic status, and insurance against floods. After a variable selection, descriptors of the hazard, building, and preparedness were deemed significant, namely: water depth, contamination, duration, velocity, building area, building quality, cellar, PLPMs, perceived efficacy of PLPMs, emergency measures, insurance, and previous flood experience. The inclusion of the indicators of preparedness is relevant, as they are rarely involved in loss datasets and in loss modelling, although previous studies have shown their potential in reducing losses. In addition, the linear model fit indicates that the explanatory factors are, in several cases, differently relevant across flood pathways. Next, Bayesian multilevel models were trained, which intrinsically incorporate uncertainties and allow for partial pooling (i.e. different groups of data, such as households affected by different flood pathways, can learn from each other), increasing the statistical power of the model. A new variable selection was performed for this new model approach, reducing the number of predictors from twelve to seven variables but keeping factors of the hazard, building, and preparedness, namely: water depth, contamination, duration, building area, PLPMs, insurance, and previous flood experience. The new model was trained not only across flood pathways but also across regions of Germany, divided according to general socioeconomic factors and insurance policies, and across flood events. The distinction across regions and flood events did not improve loss modelling and led to a large overlap of regression coefficients, with no clear trend or pattern. The distinction of flood pathways showed credibly distinct regression coefficients, leading to a better understanding of flood loss modelling and indicating one potential reason why model transferability has been challenging. Finally, new model structures were trained to include the possibility of compound inland floods (i.e. when multiple flood pathways coincide on the same affected asset). The dataset does not allow for verifying in which sequence the flood pathway waves occurred and predictor variables reflect only their mixed or combined outcome. Thus, two Bayesian models were trained: 1. a multi-membership model, a structure which learns the regression coefficients for multiple flood pathways at the same time, and 2. a multilevel model wherein the combination of coinciding flood pathways makes individual categories. The multi-membership model resulted in credibly different coefficients across flood pathways but did not improve model performance in comparison to the model assuming only a single dominant flood pathway. The model with combined categories signals an increase in impacts after compound floods, but due to the uncertainty in model coefficients and estimates, it is not possible to ascertain such an increase as credible. That is, with the current level of uncertainty in differentiating the flood pathways, the loss estimates are not credibly distinct from individual flood pathways. To overcome the challenges faced, non-linear or mixed models could be explored in the future. Interactions, moderation, and mediation effects, as well as non-linear effects, should also be further studied. Loss data collection should regularly include preparedness indicators, and either data collection or hydraulic modelling should focus on the distinction of coinciding flood pathways, which could inform loss models and further improve estimates. Flood pathways show distinct (financial) impacts, and their inclusion in loss modelling proves relevant, for it helps in clarifying the different contribution of influencing factors to the final loss, improving understanding of the damaging process, and indicating future lines of research.},
  language  = {en}
}
@phdthesis{Muench2021,
  author    = {M{\"u}nch, Steffen},
  title     = {The relevance of the aeolian transport path for the spread of antibiotic-resistant bacteria on arable fields},
  doi       = {10.25932/publishup-53608},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-536089},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XVI, 140},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Wienecke2021,
  author    = {Wienecke, Maik},
  title     = {Wohin mit der sozialistischen Pers{\"o}nlichkeit?},
  series = {Potsdamer Geographische Praxis},
  journal   = {Potsdamer Geographische Praxis},
  number    = {16},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-518-7},
  issn      = {2194-1599},
  doi       = {10.25932/publishup-51591},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-515911},
  school      = {Universit{\"a}t Potsdam},
  pages     = {254},
  year      = {2021},
  abstract  = {Das Schulfach Geographie war in der DDR eines der F{\"a}cher, das sehr stark mit politischen Themen im Sinne des Marxismus-Leninismus best{\"u}ckt war. Ein anderer Aspekt sind die sozialistischen Erziehungsziele, die in der Schulbildung der DDR hoch im Kurs standen. Im Fokus stand diesbez{\"u}glich die Erziehung der Kinder zu sozialistischen Pers{\"o}nlichkeiten. Die Arbeit versucht einen klaren Blick auf diesen Umstand zu werfen, um zu erfahren, was da von den Lehrkr{\"a}ften gefordert wurde und wie es in der Schule umzusetzen war. Durch den Fall der Mauer war nat{\"u}rlich auch eine Umstrukturierung des Bildungssystems im Osten unausweichlich. Hier will die Arbeit Einblicke geben, wie die Geographielehrkr{\"a}fte diese Transformation mitgetragen und umgesetzt haben. Welche Wesensz{\"u}ge aus der Sozialisierung in der DDR haben sich bei der Gestaltung des Unterrichtes und dessen Ausrichtung auf die neuen Erziehungsziele erhalten? Hierzu wurden Geographielehrkr{\"a}fte 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, w{\"a}hrend 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 Ver{\"a}nderung des Geographieunterrichts. Schon zu DDR-Zeiten wurden durch die Lehrkr{\"a}fte offenbar eigenm{\"a}chtig 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 gepr{\"a}gte Werteerziehung des DDR-Bildungssystems wurde unter Ausklammerung des sozialistischen Aspektes ebenso fortgef{\"u}hrt, da es auch hier viele Parallelen zum westdeutschen System gegeben hat. Deutlich wird eine Charakterisierung des Faches als Naturwissenschaft von Seiten der ostdeutschen Lehrkr{\"a}fte, obwohl das Fach an den Schulen den Gesellschaftswissenschaften zugeordnet wird und auch in der DDR eine starke wirtschaftsgeographische Ausrichtung hatte. Von der Verantwortung sozialistische Pers{\"o}nlichkeiten zu erziehen, wurden die Lehrkr{\"a}fte mit dem Ende der DDR entbunden und die in dieser Arbeit aufgef{\"u}hrten Interviewausz{\"u}ge 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.},
  language  = {de}
}
@phdthesis{Mahata2021,
  author    = {Mahata, Khadak Singh},
  title     = {Spatiotemporal variations of key air pollutants and greenhouse gases in the Himalayan foothills},
  doi       = {10.25932/publishup-51991},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-519910},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xv, 144},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Rottler2021,
  author    = {Rottler, Erwin},
  title     = {Transient merging of two Rhine flow regimes from climate change},
  doi       = {10.25932/publishup-51766},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-517665},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XXXII, 155},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Koc2021,
  author    = {Ko{\c{c}}, Gamze},
  title     = {A comprehensive analysis of severe flood events in Turkey},
  doi       = {10.25932/publishup-51785},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-517853},
  school      = {Universit{\"a}t Potsdam},
  pages     = {209},
  year      = {2021},
  abstract  = {Over the past decades, natural hazards, many of which are aggravated by climate change and reveal an increasing trend in frequency and intensity, have caused significant human and economic losses and pose a considerable obstacle to sustainable development. Hence, dedicated action toward disaster risk reduction is needed to understand the underlying drivers and create efficient risk mitigation plans. Such action is requested by the Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR), a global agreement launched in 2015 that establishes stating priorities for action, e.g. an improved understanding of disaster risk. Turkey is one of the SFDRR contracting countries and has been severely affected by many natural hazards, in particular earthquakes and floods. However, disproportionately little is known about flood hazards and risks in Turkey. Therefore, this thesis aims to carry out a comprehensive analysis of flood hazards for the first time in Turkey from triggering drivers to impacts. It is intended to contribute to a better understanding of flood risks, improvements of flood risk mitigation and the facilitated monitoring of progress and achievements while implementing the SFDRR. In order to investigate the occurrence and severity of flooding in comparison to other natural hazards in Turkey and provide an overview of the temporal and spatial distribution of flood losses, the Turkey Disaster Database (TABB) was examined for the years 1960-2014. The TABB database was reviewed through comparison with the Emergency Events Database (EM-DAT), the Dartmouth Flood Observatory database, the scientific literature and news archives. In addition, data on the most severe flood events between 1960 and 2014 were retrieved. These served as a basis for analyzing triggering mechanisms (i.e. atmospheric circulation and precipitation amounts) and aggravating pathways (i.e. topographic features, catchment size, land use types and soil properties). For this, a new approach was developed and the events were classified using hierarchical cluster analyses to identify the main influencing factor per event and provide additional information about the dominant flood pathways for severe floods. The main idea of the study was to start with the event impacts based on a bottom-up approach and identify the causes that created damaging events, instead of applying a model chain with long-term series as input and searching for potentially impacting events as model outcomes. However, within the frequency analysis of the flood-triggering circulation pattern types, it was discovered that events in terms of heavy precipitation were not included in the list of most severe floods, i.e. their impacts were not recorded in national and international loss databases but were mentioned in news archives and reported by the Turkish State Meteorological Service. This finding challenges bottom-up modelling approaches and underlines the urgent need for consistent event and loss documentation. Therefore, as a next step, the aim was to enhance the flood loss documentation by calibrating, validating and applying the United Nations Office for Disaster Risk Reduction (UNDRR) loss estimation method for the recent severe flood events (2015-2020). This provided, a consistent flood loss estimation model for Turkey, allowing governments to estimate losses as quickly as possible after events, e.g. to better coordinate financial aid. This thesis reveals that, after earthquakes, floods have the second most destructive effects in Turkey in terms of human and economic impacts, with over 800 fatalities and US\$ 885.7 million in economic losses between 1960 and 2020, and that more attention should be paid on the national scale. The clustering results of the dominant flood-producing mechanisms (e.g. circulation pattern types, extreme rainfall, sudden snowmelt) present crucial information regarding the source and pathway identification, which can be used as base information for hazard identification in the preliminary risk assessment process. The implementation of the UNDRR loss estimation model shows that the model with country-specific parameters, calibrated damage ratios and sufficient event documentation (i.e. physically damaged units) can be recommended in order to provide first estimates of the magnitude of direct economic losses, even shortly after events have occurred, since it performed well when estimates were compared to documented losses. The presented results can contribute to improving the national disaster loss database in Turkey and thus enable a better monitoring of the national progress and achievements with regard to the targets stated by the SFDRR. In addition, the outcomes can be used to better characterize and classify flood events. Information on the main underlying factors and aggravating flood pathways further supports the selection of suitable risk reduction policies. All input variables used in this thesis were obtained from publicly available data. The results are openly accessible and can be used for further research. As an overall conclusion, it can be stated that consistent loss data collection and better event documentation should gain more attention for a reliable monitoring of the implementation of the SFDRR. Better event documentation should be established according to a globally accepted standard for disaster classification and loss estimation in Turkey. Ultimately, this enables stakeholders to create better risk mitigation actions based on clear hazard definitions, flood event classification and consistent loss estimations.},
  language  = {en}
}
@phdthesis{Nguyen2021,
  author    = {Nguyen, Van Khanh Triet},
  title     = {Flood dynamics in the Vietnamese Mekong Delta},
  doi       = {10.25932/publishup-51283},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-512830},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xx, 113},
  year      = {2021},
  abstract  = {Today, the Mekong Delta in the southern of Vietnam is home for 18 million people. The delta also accounts for more than half of the country's food production and 80\% of the exported rice. Due to the low elevation, it is highly susceptible to the risk of fluvial and coastal flooding. Although extreme floods often result in excessive damages and economic losses, the annual flood pulse from the Mekong is vital to sustain agricultural cultivation and livelihoods of million delta inhabitants. Delta-wise risk management and adaptation strategies are required to mitigate the adverse impacts from extreme events while capitalising benefits from floods. However, a proper flood risk management has not been implemented in the VMD, because the quantification of flood damage is often overlooked and the risks are thus not quantified. So far, flood management has been exclusively focused on engineering measures, i.e. high- and low- dyke systems, aiming at flood-free or partial inundation control without any consideration of the actual risks or a cost-benefit analysis. Therefore, an analysis of future delta flood dynamics driven these stressors is valuable to facilitate the transition from sole hazard control towards a risk management approach, which is more cost-effective and also robust against future changes in risk. Built on these research gaps, this thesis investigates the current state and future projections of flood hazard, damage and risk to rice cultivation, the most important economic activity in the VMD. The study quantifies the changes in risk and hazard brought by the development of delta-based flood control measures in the last decades, and analyses the expected changes in risk driven by the changing climate, rising sea-level and deltaic land subsidence, and finally the development of hydropower projects in the Mekong Basin. For this purpose, flood trend analyses and comprehensive hydraulic modelling were performed, together with the development of a concept to quantify flood damage and risk to rice plantation. The analysis of observed flood levels revealed strong and robust increasing trends of peak and duration downstream of the high-dyke areas with a step change in 2000/2001, i.e. after the disastrous flood which initiated the high-dyke development. These changes were in contrast to the negative trends detected upstream, suggested that high-dyke development has shifted flood hazard downstream. Findings of the trend's analysis were later confirmed by hydraulic simulations of the two recent extreme floods in 2000 and 2011, where the hydrological boundaries and dyke system settings were interchanged. However, the high-dyke system was not the only and often not the main cause for a shift of flood hazard, as a comparative analysis of these two extreme floods proved. The high-dyke development was responsible for 20-90\% of the observed changes in flood level between 2000 and 2011, with large spatial variances. The particular flood hydrograph of the two events had the highest contribution in the northern part of the delta, while the tidal level had 2-3 times higher influence than the high-dyke in the lower-central and coastal areas downstream of high-dyke areas. The impact of the high-dyke development was highest in the areas closely downstream of the high-dyke area just south of the Cambodia-Vietnam border. The hydraulic simulations also validated that the concurrence of the flood peak with spring tides, i.e. high sea level along the coast, amplified the flood level and inundation in the central and coastal regions substantially. The risk assessment quantified the economic losses of rice cultivation to USD 25.0 and 115 million (0.02-0.1\% of the total GDP of Vietnam in 2011) corresponding to the 10-year and the 100-year floods, with an expected annual damage of about USD 4.5 million. A particular finding is that the flood damage was highly sensitive to flood timing. Here, a 10-year event with an early peak, i.e. late August-September, could cause as much damage as a 100-year event that peaked in October. This finding underlines the importance of a reliable early flood warning, which could substantially reduce the damage to rice crops and thus the risk. The developed risk assessment concept was furthermore applied to investigate two high-dyke development alternatives, which are currently under discussion among the administrative bodies in Vietnam, but also in the public. The first option favouring the utilization of the current high-dyke compartments as flood retention areas instead for rice cropping during the flood season could reduce flood hazard and expected losses by 5-40\%, depending on the region of the delta. On the contrary, the second option promoting the further extension of the areas protected by high-dyke to facilitate third rice crop planting on a larger area, tripled the current expected annual flood damage. This finding challenges the expected economic benefit of triple rice cultivation, in addition to the already known reducing of nutrient supply by floodplain sedimentation and thus higher costs for fertilizers. The economic benefits of the high-dyke and triple rice cropping system is further challenged by the changes in the flood dynamics to be expected in future. For the middle of the 21st century (2036-2065) the effective sea-level rise an increase of the inundation extent by 20-27\% was projected. This corresponds to an increase of flood damage to rice crops in dry, normal and wet year by USD 26.0, 40.0 and 82.0 million in dry, normal and wet year compared to the baseline period 1971-2000. Hydraulic simulations indicated that the planned massive development of hydropower dams in the Mekong Basin could potentially compensate the increase in flood hazard and agriculture losses stemming from climate change. However, the benefits of dams as mitigation of flood losses are highly uncertain, because a) the actual development of the dams is highly disputed, b) the operation of the dams is primarily targeted at power generation, not flood control, and c) this would require international agreements and cooperation, which is difficult to achieve in South-East Asia. The theoretical flood mitigation benefit is additionally challenged by a number of negative impacts of the dam development, e.g. disruption of floodplain inundation in normal, non-extreme flood years. Adding to the certain reduction of sediment and nutrient load to the floodplains, hydropower dams will drastically impair rice and agriculture production, the basis livelihoods of million delta inhabitants. In conclusion, the VMD is expected to face increasing threats of tidal induced floods in the coming decades. Protection of the entire delta coastline solely with "hard" engineering flood protection structures is neither technically nor economically feasible, adaptation and mitigation actions are urgently required. Better control and reduction of groundwater abstraction is thus strongly recommended as an immediate and high priority action to reduce the land subsidence and thus tidal flooding and salinity intrusion in the delta. Hydropower development in the Mekong basin might offer some theoretical flood protection for the Mekong delta, but due to uncertainties in the operation of the dams and a number of negative effects, the dam development cannot be recommended as a strategy for flood management. For the Vietnamese authorities, it is advisable to properly maintain the existing flood protection structures and to develop flexible risk-based flood management plans. In this context the study showed that the high-dyke compartments can be utilized for emergency flood management in extreme events. For this purpose, a reliable flood forecast is essential, and the action plan should be materialised in official documents and legislation to assure commitment and consistency in the implementation and operation.},
  language  = {en}
}
@phdthesis{Ayzel2021,
  author    = {Ayzel, Georgy},
  title     = {Advancing radar-based precipitation nowcasting},
  doi       = {10.25932/publishup-50426},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-504267},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xx, 68},
  year      = {2021},
  abstract  = {Precipitation forecasting has an important place in everyday life - during the day we may have tens of small talks discussing the likelihood that it will rain this evening or weekend. Should you take an umbrella for a walk? Or should you invite your friends for a barbecue? It will certainly depend on what your weather application shows. While for years people were guided by the precipitation forecasts issued for a particular region or city several times a day, the widespread availability of weather radars allowed us to obtain forecasts at much higher spatiotemporal resolution of minutes in time and hundreds of meters in space. Hence, radar-based precipitation nowcasting, that is, very-short-range forecasting (typically up to 1-3 h), has become an essential technique, also in various professional application contexts, e.g., early warning, sewage control, or agriculture. There are two major components comprising a system for precipitation nowcasting: radar-based precipitation estimates, and models to extrapolate that precipitation to the imminent future. While acknowledging the fundamental importance of radar-based precipitation retrieval for precipitation nowcasts, this thesis focuses only on the model development: the establishment of open and competitive benchmark models, the investigation of the potential of deep learning, and the development of procedures for nowcast errors diagnosis and isolation that can guide model development. The present landscape of computational models for precipitation nowcasting still struggles with the availability of open software implementations that could serve as benchmarks for measuring progress. Focusing on this gap, we have developed and extensively benchmarked a stack of models based on different optical flow algorithms for the tracking step and a set of parsimonious extrapolation procedures based on image warping and advection. We demonstrate that these models provide skillful predictions comparable with or even superior to state-of-the-art operational software. We distribute the corresponding set of models as a software library, rainymotion, which is written in the Python programming language and openly available at GitHub (https://github.com/hydrogo/rainymotion). That way, the library acts as a tool for providing fast, open, and transparent solutions that could serve as a benchmark for further model development and hypothesis testing. One of the promising directions for model development is to challenge the potential of deep learning - a subfield of machine learning that refers to artificial neural networks with deep architectures, which may consist of many computational layers. Deep learning showed promising results in many fields of computer science, such as image and speech recognition, or natural language processing, where it started to dramatically outperform reference methods. The high benefit of using "big data" for training is among the main reasons for that. Hence, the emerging interest in deep learning in atmospheric sciences is also caused and concerted with the increasing availability of data - both observational and model-based. The large archives of weather radar data provide a solid basis for investigation of deep learning potential in precipitation nowcasting: one year of national 5-min composites for Germany comprises around 85 billion data points. To this aim, we present RainNet, a deep convolutional neural network for radar-based precipitation nowcasting. RainNet was trained to predict continuous precipitation intensities at a lead time of 5 min, using several years of quality-controlled weather radar composites provided by the German Weather Service (DWD). That data set covers Germany with a spatial domain of 900 km x 900 km and has a resolution of 1 km in space and 5 min in time. Independent verification experiments were carried out on 11 summer precipitation events from 2016 to 2017. In these experiments, RainNet was applied recursively in order to achieve lead times of up to 1 h. In the verification experiments, trivial Eulerian persistence and a conventional model based on optical flow served as benchmarks. The latter is available in the previously developed rainymotion library. RainNet significantly outperformed the benchmark models at all lead times up to 60 min for the routine verification metrics mean absolute error (MAE) and critical success index (CSI) at intensity thresholds of 0.125, 1, and 5 mm/h. However, rainymotion turned out to be superior in predicting the exceedance of higher intensity thresholds (here 10 and 15 mm/h). The limited ability of RainNet to predict high rainfall intensities is an undesirable property which we attribute to a high level of spatial smoothing introduced by the model. At a lead time of 5 min, an analysis of power spectral density confirmed a significant loss of spectral power at length scales of 16 km and below. Obviously, RainNet had learned an optimal level of smoothing to produce a nowcast at 5 min lead time. In that sense, the loss of spectral power at small scales is informative, too, as it reflects the limits of predictability as a function of spatial scale. Beyond the lead time of 5 min, however, the increasing level of smoothing is a mere artifact - an analogue to numerical diffusion - that is not a property of RainNet itself but of its recursive application. In the context of early warning, the smoothing is particularly unfavorable since pronounced features of intense precipitation tend to get lost over longer lead times. Hence, we propose several options to address this issue in prospective research on model development for precipitation nowcasting, including an adjustment of the loss function for model training, model training for longer lead times, and the prediction of threshold exceedance. The model development together with the verification experiments for both conventional and deep learning model predictions also revealed the need to better understand the source of forecast errors. Understanding the dominant sources of error in specific situations should help in guiding further model improvement. The total error of a precipitation nowcast consists of an error in the predicted location of a precipitation feature and an error in the change of precipitation intensity over lead time. So far, verification measures did not allow to isolate the location error, making it difficult to specifically improve nowcast models with regard to location prediction. To fill this gap, we introduced a framework to directly quantify the location error. To that end, we detect and track scale-invariant precipitation features (corners) in radar images. We then consider these observed tracks as the true reference in order to evaluate the performance (or, inversely, the error) of any model that aims to predict the future location of a precipitation feature. Hence, the location error of a forecast at any lead time ahead of the forecast time corresponds to the Euclidean distance between the observed and the predicted feature location at the corresponding lead time. Based on this framework, we carried out a benchmarking case study using one year worth of weather radar composites of the DWD. We evaluated the performance of four extrapolation models, two of which are based on the linear extrapolation of corner motion; and the remaining two are based on the Dense Inverse Search (DIS) method: motion vectors obtained from DIS are used to predict feature locations by linear and Semi-Lagrangian extrapolation. For all competing models, the mean location error exceeds a distance of 5 km after 60 min, and 10 km after 110 min. At least 25\% of all forecasts exceed an error of 5 km after 50 min, and of 10 km after 90 min. Even for the best models in our experiment, at least 5 percent of the forecasts will have a location error of more than 10 km after 45 min. When we relate such errors to application scenarios that are typically suggested for precipitation nowcasting, e.g., early warning, it becomes obvious that location errors matter: the order of magnitude of these errors is about the same as the typical extent of a convective cell. Hence, the uncertainty of precipitation nowcasts at such length scales - just as a result of locational errors - can be substantial already at lead times of less than 1 h. Being able to quantify the location error should hence guide any model development that is targeted towards its minimization. To that aim, we also consider the high potential of using deep learning architectures specific to the assimilation of sequential (track) data. Last but not least, the thesis demonstrates the benefits of a general movement towards open science for model development in the field of precipitation nowcasting. All the presented models and frameworks are distributed as open repositories, thus enhancing transparency and reproducibility of the methodological approach. Furthermore, they are readily available to be used for further research studies, as well as for practical applications.},
  language  = {en}
}
@phdthesis{WegerCoenen2021,
  author    = {Weger Coenen, Lindsey},
  title     = {Exploring potential impacts from transitions in German and European energy on GHG and air pollutant emissions and on ozone air quality},
  doi       = {10.25932/publishup-49698},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-496986},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xvi, 161},
  year      = {2021},
  abstract  = {Energy is at the heart of the climate crisis—but also at the heart of any efforts for climate change mitigation. Energy consumption is namely responsible for approximately three quarters of global anthropogenic greenhouse gas (GHG) emissions. Therefore, central to any serious plans to stave off a climate catastrophe is a major transformation of the world's energy system, which would move society away from fossil fuels and towards a net-zero energy future. Considering that fossil fuels are also a major source of air pollutant emissions, the energy transition has important implications for air quality as well, and thus also for human and environmental health. Both Europe and Germany have set the goal of becoming GHG neutral by 2050, and moreover have demonstrated their deep commitment to a comprehensive energy transition. Two of the most significant developments in energy policy over the past decade have been the interest in expansion of shale gas and hydrogen, which accordingly have garnered great interest and debate among public, private and political actors. In this context, sound scientific information can play an important role by informing stakeholder dialogue and future research investments, and by supporting evidence-based decision-making. This thesis examines anticipated environmental impacts from possible, relevant changes in the European energy system, in order to impart valuable insight and fill critical gaps in knowledge. Specifically, it investigates possible future shale gas development in Germany and the United Kingdom (UK), as well as a hypothetical, complete transition to hydrogen mobility in Germany. Moreover, it assesses the impacts on GHG and air pollutant emissions, and on tropospheric ozone (O3) air quality. The analysis is facilitated by constructing emission scenarios and performing air quality modeling via the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). The work of this thesis is presented in three research papers. The first paper finds that methane (CH4) leakage rates from upstream shale gas development in Germany and the UK would range between 0.35\% and 1.36\% in a realistic, business-as-usual case, while they would be significantly lower - between 0.08\% and 0.15\% - in an optimistic, strict regulation and high compliance case, thus demonstrating the value and potential of measures to substantially reduce emissions. Yet, while the optimistic case is technically feasible, it is unlikely that the practices and technologies assumed would be applied and accomplished on a systematic, regular basis, owing to economics and limited monitoring resources. The realistic CH4 leakage rates estimated in this study are comparable to values reported by studies carried out in the US and elsewhere. In contrast, the optimistic rates are similar to official CH4 leakage data from upstream gas production in Germany and in the UK. Considering that there is a lack of systematic, transparent and independent reports supporting the official values, this study further highlights the need for more research efforts in this direction. Compared with national energy sector emissions, this study suggests that shale gas emissions of volatile organic compounds (VOCs) could be significant, though relatively insignificant for other air pollutants. Similar to CH4, measures could be effective for reducing VOCs emissions. The second paper shows that VOC and nitrogen oxides (NOx) emissions from a future shale gas industry in Germany and the UK have potentially harmful consequences for European O3 air quality on both the local and regional scale. The results indicate a peak increase in maximum daily 8-hour average O3 (MDA8) ranging from 3.7 µg m-3 to 28.3 µg m-3. Findings suggest that shale gas activities could result in additional exceedances of MDA8 at a substantial percentage of regulatory measurement stations both locally and in neighboring and distant countries, with up to circa one third of stations in the UK and one fifth of stations in Germany experiencing additional exceedances. Moreover, the results reveal that the shale gas impact on the cumulative health-related metric SOMO35 (annual Sum of Ozone Means Over 35 ppb) could be substantial, with a maximum increase of circa 28\%. Overall, the findings suggest that shale gas VOC emissions could play a critical role in O3 enhancement, while NOx emissions would contribute to a lesser extent. Thus, the results indicate that stringent regulation of VOC emissions would be important in the event of future European shale gas development to minimize deleterious health outcomes. The third paper demonstrates that a hypothetical, complete transition of the German vehicle fleet to hydrogen fuel cell technology could contribute substantially to Germany's climate and air quality goals. The results indicate that if the hydrogen were to be produced via renewable-powered water electrolysis (green hydrogen), German carbon dioxide equivalent (CO2eq) emissions would decrease by 179 MtCO2eq annually, though if electrolysis were powered by the current electricity mix, emissions would instead increase by 95 MtCO2eq annually. The findings generally reveal a notable anticipated decrease in German energy emissions of regulated air pollutants. The results suggest that vehicular hydrogen demand is 1000 PJ annually, which would require between 446 TWh and 525 TWh for electrolysis, hydrogen transport and storage. When only the heavy duty vehicle segment (HDVs) is shifted to green hydrogen, the results of this thesis show that vehicular hydrogen demand drops to 371 PJ, while a deep emissions cut is still realized (-57 MtCO2eq), suggesting that HDVs are a low-hanging fruit for contributing to decarbonization of the German road transport sector with hydrogen energy.},
  language  = {en}
}
@phdthesis{MetinUsta2021,
  author    = {Metin Usta, Ay{\c{s}}e Duha},
  title     = {The role of risk components and spatial dependence in flood risk estimations},
  doi       = {10.25932/publishup-49255},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-492554},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XIX, 97},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Wang2020,
  author    = {Wang, Weishi},
  title     = {Influence of river reconstruction at a bank filtration site},
  doi       = {10.25932/publishup-49023},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-490234},
  school      = {Universit{\"a}t Potsdam},
  pages     = {IIV, 120},
  year      = {2020},
  abstract  = {Bank filtration is an effective water treatment technique and is widely adopted in Europe along major rivers. It is the process where surface water penetrates the riverbed, flows through the aquifer, and then is extracted by near-bank production wells. By flowing in the subsurface flow passage, the water quality can be improved by a series of beneficial processes. Long-term riverbank filtration also produces colmation layers on the riverbed. The colmation layer may act as a bioactive zone that is governed by biochemical and physical processes owing to its enrichment of microbes and organic matter. Low permeability may strongly limit the surface water infiltration and further lead to a decreasing recoverable ratio of production wells.The removal of the colmation layer is therefore a trade-off between the treatment capacity and treatment efficiency. The goal of this Ph.D. thesis is to focus on the temporal and spatial change of the water quality and quantity along the flow path of a hydrogeological heterogeneous riverbank filtration site adjacent to an artificial-reconstructed (bottom excavation and bank reconstruction) canal in Potsdam, Germany. To quantify the change of the infiltration rate, travel time distribution, and the thermal field brought by the canal reconstruction, a three-dimensional flow and heat transport model was created. This model has two scenarios, 1) 'with' canal reconstruction, and 2) 'without' canal reconstruction. Overall, the model calibration results of both water heads and temperatures matched those observed in the field study. In comparison to the model without reconstruction, the reconstruction model led to more water being infiltrated into the aquifer on that section, on average 521 m3/d, which corresponded to around 9\% of the total pumping rate. Subsurface travel-time distribution substantially shifted towards shorter travel times. Flow paths with travel times <200 days increased by ~10\% and those with <300 days by 15\%. Furthermore, the thermal distribution in the aquifer showed that the seasonal variation in the scenario with reconstruction reaches deeper and laterally propagates further. By scatter plotting of δ18O versus δ 2H, the infiltrated river water could be differentiated from water flowing in the deep aquifer, which may contain remnant landside groundwater from further north. In contrast, the increase of river water contribution due to decolmation could be shown by piper plot. Geological heterogeneity caused a substantial spatial difference in redox zonation among different flow paths, both horizontally and vertically. Using the Wilcoxon rank test, the reconstruction changed the redox potential differently in observation wells. However, taking the small absolute concentration level, the change is also relatively minor. The treatment efficiency for both organic matter and inorganic matter is consistent after the reconstruction, except for ammonium. The inconsistent results for ammonium could be explained by changes in the Cation Exchange Capacity (CEC) in the newly paved riverbed. Because the bed is new, it was not yet capable of keeping the newly produced ammonium by sorption and further led to the breakthrough of the ammonium plume. By estimation, the peak of the ammonium plume would reach the most distant observation well before February 2024, while the peaking concentration could be further dampened by sorption and diluted by the afterward low ammonium flow. The consistent DOC and SUVA level suggests that there was no clear preference for the organic matter removal along the flow path.},
  language  = {en}
}
@phdthesis{Yang2020,
  author    = {Yang, Xiaoqiang},
  title     = {Spatial and temporal analyses of catchment and in-stream nitrate dynamics},
  doi       = {10.25932/publishup-47702},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-477029},
  school      = {Universit{\"a}t Potsdam},
  pages     = {VIII, 146},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Pilz2020,
  author    = {Pilz, Tobias},
  title     = {Pursuing the understanding of uncertainties in hydrological modelling},
  doi       = {10.25932/publishup-47664},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-476643},
  school      = {Universit{\"a}t Potsdam},
  pages     = {136},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Rolf2020,
  author    = {Rolf, Werner},
  title     = {Peri-urban farmland included in green infrastructure strategies promotes transformation pathways towards sustainable urban development},
  doi       = {10.25932/publishup-47700},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-477002},
  school      = {Universit{\"a}t Potsdam},
  pages     = {IV, 116},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Crisologo2019,
  author    = {Crisologo, Irene},
  title     = {Using spaceborne radar platforms to enhance the homogeneity of weather radar calibration},
  doi       = {10.25932/publishup-44570},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-445704},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xvii, 61},
  year      = {2019},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Barbosa2020,
  author    = {Barbosa, Lu{\´i}s Romero},
  title     = {Groundwater recharge in tropical wet regions via GIS-based and cosmic-ray neutron sensing},
  doi       = {10.25932/publishup-46064},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-460641},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XXVI, 175},
  year      = {2020},
  abstract  = {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 Jo{\~a}o Pessoa Case Study Area and the Guara{\´i}ra 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.},
  language  = {en}
}
@phdthesis{GaeteRojas2020,
  author    = {Gaete Rojas, Ayleen Barbara},
  title     = {Monitoring and modeling observations of plumbing systems at caldera-like topography},
  doi       = {10.25932/publishup-44613},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-446135},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ix, 96},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Michalczyk2019,
  author    = {Michalczyk, Anna},
  title     = {Modelling of nitrogen cycles in intensive winter wheat-summer maize double cropping systems in the North China Plain},
  doi       = {10.25932/publishup-44421},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-444213},
  school      = {Universit{\"a}t Potsdam},
  pages     = {X, 154},
  year      = {2019},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{LeBot2019,
  author    = {Le Bot, Nils},
  title     = {Quel avenir pour les gares m{\´e}tropolitaines fran{\c{c}}aises et allemandes ?},
  doi       = {10.25932/publishup-44220},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-442201},
  school      = {Universit{\"a}t Potsdam},
  pages     = {589},
  year      = {2019},
  abstract  = {Cette th{\`e}se d'urbanisme s'est donn{\´e}e pour objectif de r{\´e}fl{\´e}chir {\`a} l'avenir des gares m{\´e}tropolitaines fran{\c{c}}aises et allemandes {\`a} horizon 2050. Elle porte une interrogation sur les fondements de la gare comme objet urbain conceptuel (abord{\´e} comme un syst{\`e}me) et pose comme hypoth{\`e}se qu'il serait en quelque sorte dot{\´e} de propri{\´e}t{\´e}s autonomes. Parmi ces propri{\´e}t{\´e}s, c'est le processus d'expansion et de dialogue sans cesse renouvel{\´e} et conflictuel, entre la gare et son tissu urbain environnant, qui guide cette recherche ; notamment dans le rapport qu'il entretient avec l'hypermobilit{\´e} des m{\´e}tropoles. Pour ce faire, cette th{\`e}se convoque quatre terrains d'{\´e}tudes : 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 d{\´e}taill{\´e} de leurs {\´e}volutions morphologiques, pour d{\´e}gager une s{\´e}rie de variables architectoniques et urbaines. Il proc{\`e}de dans un deuxi{\`e}me temps {\`a} une s{\´e}rie d'analyse prospective, permettant de juger de l'influence possible des politiques publiques en mati{\`e}re transports et de mobilit{\´e}, sur l'avenir conceptuel des gares. Cette th{\`e}se propose alors le concept de syst{\`e}me-gare, pour d{\´e}crire l'expansion et l'int{\´e}gration des gares m{\´e}tropolitaines avec leur environnement urbain ; un processus de n{\´e}gociation dialectique qui ne trouve pas sa r{\´e}solution dans le concept de gare comme lieu de vie/ville. Elle invite alors {\`a} penser la gare comme une h{\´e}t{\´e}rotopie, et propose une lecture d{\´e}polaris{\´e}e et d{\´e}hi{\´e}rarchis{\´e}e de ces espaces, en introduisant les concepts d'orchestre de gares et de m{\´e}tagare. Cette recherche propose enfin une lecture critique de la « ville num{\´e}rique » et du concept de « mobilit{\´e} comme service. » Pour {\´e}viter une mise en flux tendus potentiellement dommageables, l'application de ces concepts en gare ne pourra se soustraire {\`a} une augmentation simultan{\´e}e des espaces physiques.},
  language  = {fr}
}
@phdthesis{Schmidt2019,
  author    = {Schmidt, Martin},
  title     = {Fragmentation of landscapes: modelling ecosystem services of transition zones},
  doi       = {10.25932/publishup-44294},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-442942},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XV, 103},
  year      = {2019},
  abstract  = {For millennia, humans have affected landscapes all over the world. Due to horizontal expansion, agriculture plays a major role in the process of fragmentation. This process is caused by a substitution of natural habitats by agricultural land leading to agricultural landscapes. These landscapes are characterized by an alternation of agriculture and other land use like forests. In addition, there are landscape elements of natural origin like small water bodies. Areas of different land use are beside each other like patches, or fragments. They are physically distinguishable which makes them look like a patchwork from an aerial perspective. These fragments are each an own ecosystem with conditions and properties that differ from their adjacent fragments. As open systems, they are in exchange of information, matter and energy across their boundaries. These boundary areas are called transition zones. Here, the habitat properties and environmental conditions are altered compared to the interior of the fragments. This changes the abundance and the composition of species in the transition zones, which in turn has a feedback effect on the environmental conditions. The literature mainly offers information and insights on species abundance and composition in forested transition zones. Abiotic effects, the gradual changes in energy and matter, received less attention. In addition, little is known about non-forested transition zones. For example, the effects on agricultural yield in transition zones of an altered microclimate, matter dynamics or different light regimes are hardly researched or understood. The processes in transition zones are closely connected with altered provisioning and regulating ecosystem services. To disentangle the mechanisms and to upscale the effects, models can be used. My thesis provides insights into these topics: literature was reviewed and a conceptual framework for the quantitative description of gradients of matter and energy in transition zones was introduced. The results of measurements of environmental gradients like microclimate, aboveground biomass and soil carbon and nitrogen content are presented that span from within the forest into arable land. Both the measurements and the literature review could not validate a transition zone of 100 m for abiotic effects. Although this value is often reported and used in the literature, it is likely to be smaller. Further, the measurements suggest that on the one hand trees in transition zones are smaller compared to those in the interior of the fragments, while on the other hand less biomass was measured in the arable lands' transition zone. These results support the hypothesis that less carbon is stored in the aboveground biomass in transition zones. The soil at the edge (zero line) between adjacent forest and arable land contains more nitrogen and carbon content compared to the interior of the fragments. One-year measurements in the transition zone also provided evidence that microclimate is different compared to the fragments' interior. To predict the possible yield decreases that transition zones might cause, a modelling approach was developed. Using a small virtual landscape, I modelled the effect of a forest fragment shading the adjacent arable land and the effects of this on yield using the MONICA crop growth model. In the transition zone yield was less compared to the interior due to shading. The results of the simulations were upscaled to the landscape level and exemplarily calculated for the arable land of a whole region in Brandenburg, Germany. The major findings of my thesis are: (1) Transition zones are likely to be much smaller than assumed in the scientific literature; (2) transition zones aren't solely a phenomenon of forested ecosystems, but significantly extend into arable land as well; (3) empirical and modelling results show that transition zones encompass biotic and abiotic changes that are likely to be important to a variety of agricultural landscape ecosystem services.},
  language  = {en}
}
@phdthesis{Weisshuhn2020,
  author    = {Weißhuhn, Peter},
  title     = {Assessing biotope vulnerability to landscape changes},
  doi       = {10.25932/publishup-44277},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-442777},
  school      = {Universit{\"a}t Potsdam},
  pages     = {v, 134},
  year      = {2020},
  abstract  = {Largescale patterns of global land use change are very frequently accompanied by natural habitat loss. To assess the consequences of habitat loss for the remaining natural and semi-natural biotopes, inclusion of cumulative effects at the landscape level is required. The interdisciplinary concept of vulnerability constitutes an appropriate assessment framework at the landscape level, though with few examples of its application for ecological assessments. A comprehensive biotope vulnerability analysis allows identification of areas most affected by landscape change and at the same time with the lowest chances of regeneration. To this end, a series of ecological indicators were reviewed and developed. They measured spatial attributes of individual biotopes as well as some ecological and conservation characteristics of the respective resident species community. The final vulnerability index combined seven largely independent indicators, which covered exposure, sensitivity and adaptive capacity of biotopes to landscape changes. Results for biotope vulnerability were provided at the regional level. This seems to be an appropriate extent with relevance for spatial planning and designing the distribution of nature reserves. Using the vulnerability scores calculated for the German federal state of Brandenburg, hot spots and clusters within and across the distinguished types of biotopes were analysed. Biotope types with high dependence on water availability, as well as biotopes of the open landscape containing woody plants (e.g., orchard meadows) are particularly vulnerable to landscape changes. In contrast, the majority of forest biotopes appear to be less vulnerable. Despite the appeal of such generalised statements for some biotope types, the distribution of values suggests that conservation measures for the majority of biotopes should be designed specifically for individual sites. Taken together, size, shape and spatial context of individual biotopes often had a dominant influence on the vulnerability score. The implementation of biotope vulnerability analysis at the regional level indicated that large biotope datasets can be evaluated with high level of detail using geoinformatics. Drawing on previous work in landscape spatial analysis, the reproducible approach relies on transparent calculations of quantitative and qualitative indicators. At the same time, it provides a synoptic overview and information on the individual biotopes. It is expected to be most useful for nature conservation in combination with an understanding of population, species, and community attributes known for specific sites. The biotope vulnerability analysis facilitates a foresighted assessment of different land uses, aiding in identifying options to slow habitat loss to sustainable levels. It can also be incorporated into planning of restoration measures, guiding efforts to remedy ecological damage. Restoration of any specific site could yield synergies with the conservation objectives of other sites, through enhancing the habitat network or buffering against future landscape change. Biotope vulnerability analysis could be developed in line with other important ecological concepts, such as resilience and adaptability, further extending the broad thematic scope of the vulnerability concept. Vulnerability can increasingly serve as a common framework for the interdisciplinary research necessary to solve major societal challenges.},
  language  = {en}
}
@phdthesis{Wendi2018,
  author    = {Wendi, Dadiyorto},
  title     = {Recurrence Plots and Quantification Analysis of Flood Runoff Dynamics},
  doi       = {10.25932/publishup-43191},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-431915},
  school      = {Universit{\"a}t Potsdam},
  pages     = {114},
  year      = {2018},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Veh2019,
  author    = {Veh, Georg},
  title     = {Outburst floods from moraine-dammed lakes in the Himalayas},
  doi       = {10.25932/publishup-43607},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-436071},
  school      = {Universit{\"a}t Potsdam},
  pages     = {124},
  year      = {2019},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Roezer2018,
  author    = {R{\"o}zer, Viktor},
  title     = {Pluvial flood loss to private households},
  doi       = {10.25932/publishup-42991},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-429910},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XXII, 109},
  year      = {2018},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Sterzel2019,
  author    = {Sterzel, Till},
  title     = {Analyzing global typologies of socio-ecological vulnerability},
  doi       = {10.25932/publishup-42883},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-428837},
  school      = {Universit{\"a}t Potsdam},
  pages     = {137},
  year      = {2019},
  abstract  = {On a planetary scale human populations need to adapt to both socio-economic and environmental problems amidst rapid global change. This holds true for coupled human-environment (socio-ecological) systems in rural and urban settings alike. Two examples are drylands and urban coasts. Such socio-ecological systems have a global distribution. Therefore, advancing the knowledge base for identifying socio-ecological adaptation needs with local vulnerability assessments alone is infeasible: The systems cover vast areas, while funding, time, and human resources for local assessments are limited. They are lacking in low an middle-income countries (LICs and MICs) in particular. But places in a specific socio-ecological system are not only unique and complex - they also exhibit similarities. A global patchwork of local rural drylands vulnerability assessments of human populations to socio-ecological and environmental problems has already been reduced to a limited number of problem structures, which typically cause vulnerability. However, the question arises whether this is also possible in urban socio-ecological systems. The question also arises whether these typologies provide added value in research beyond global change. Finally, the methodology employed for drylands needs refining and standardizing to increase its uptake in the scientific community. In this dissertation, I set out to fill these three gaps in research. The geographical focus in my dissertation is on LICs and MICs, which generally have lower capacities to adapt, and greater adaptation needs, regarding rapid global change. Using a spatially explicit indicator-based methodology, I combine geospatial and clustering methods to identify typical configurations of key factors in case studies causing vulnerability to human populations in two specific socio-ecological systems. Then I use statistical and analytical methods to interpret and appraise both the typical configurations and the global typologies they constitute. First, I improve the indicator-based methodology and then reanalyze typical global problem structures of socio-ecological drylands vulnerability with seven indicator datasets. The reanalysis confirms the key tenets and produces a more realistic and nuanced typology of eight spatially explicit problem structures, or vulnerability profiles: Two new profiles with typically high natural resource endowment emerge, in which overpopulation has led to medium or high soil erosion. Second, I determine whether the new drylands typology and its socio-ecological vulnerability concept advance a thematically linked scientific debate in human security studies: what drives violent conflict in drylands? The typology is a much better predictor for conflict distribution and incidence in drylands than regression models typically used in peace research. Third, I analyze global problem structures typically causing vulnerability in an urban socio-ecological system - the rapidly urbanizing coastal fringe (RUCF) - with eleven indicator datasets. The RUCF also shows a robust typology, and its seven profiles show huge asymmetries in vulnerability and adaptive capacity. The fastest population increase, lowest income, most ineffective governments, most prevalent poverty, and lowest adaptive capacity are all typically stacked in two profiles in LICs. This shows that beyond local case studies tropical cyclones and/or coastal flooding are neither stalling rapid population growth, nor urban expansion, in the RUCF. I propose entry points for scaling up successful vulnerability reduction strategies in coastal cities within the same vulnerability profile. This dissertation shows that patchworks of local vulnerability assessments can be generalized to structure global socio-ecological vulnerabilities in both rural and urban socio-ecological systems according to typical problems. In terms of climate-related extreme events in the RUCF, conflicting problem structures and means to deal with them are threatening to widen the development gap between LICs and high-income countries unless successful vulnerability reduction measures are comprehensively scaled up. The explanatory power for human security in drylands warrants further applications of the methodology beyond global environmental change research in the future. Thus, analyzing spatially explicit global typologies of socio-ecological vulnerability is a useful complement to local assessments: The typologies provide entry points for where to consider which generic measures to reduce typical problem structures - including the countless places without local assessments. This can save limited time and financial resources for adaptation under rapid global change.},
  language  = {en}
}
@phdthesis{Lubitz2017,
  author    = {Lubitz, Christin},
  title     = {Investigating local surface displacements associated with anthropogenic activities by satellite radar interferometry},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-416001},
  school      = {Universit{\"a}t Potsdam},
  pages     = {III, vii, 96, xii},
  year      = {2017},
  abstract  = {Direct anthropogenic influences on the Earth's subsurface during drilling, extraction or injection activities, can affect land stability by causing subsidence, uplifts or lateral displacements. They can occur in localized as well as in uninhabited and inhabited regions. Thus the associated risks for humans, infrastructure, and environment must be minimized. To achieve this, appropriate surveillance methods must be found that can be used for simultaneous monitoring during such activities. Multi-temporal synthetic aperture radar interferometry (MT-InSAR) methods like the Persistent Scatterer Interferometry (PSI) and the Small BAseline Subsets (SBAS) have been developed as standard approaches for satellite-based surface displacement monitoring. With increasing spatial resolution and availability of SAR sensors in recent years, MT-InSAR can be valuable for the detection and mapping of even the smallest man-made displacements. This doctoral thesis aims at investigating the capacities of the mentioned standard methods for this purpose, and comprises three main objectives against the backdrop of a user-friendly surveillance service: (1) the spatial and temporal significance assessment against leveling, (2) the suitability evaluation of PSI and SBAS under different conditions, and (3) the analysis of the link between surface motion and subsurface processes. Two prominent case studies on anthropogenic induced subsurface processes in Germany serve as the basis for this goal. The first is the distinct urban uplift with severe damages at Staufen im Breisgau that has been associated since 2007 with a failure to implement a shallow geothermal energy supply for an individual building. The second case study considers the pilot project of geological carbon dioxide (CO2) storage at Ketzin, and comprises borehole drilling and fluid injection of more than 67 kt CO2 between 2008 and 2013. Leveling surveys at Staufen and comprehensive background knowledge of the underground processes gained from different kinds of in-situ measurements at both locations deliver a suitable basis for this comparative study and the above stated objectives. The differences in location setting, i.e. urban versus rural site character, were intended to investigate the limitations in the applicability of PSI and SBAS. For the MT-InSAR analysis, X-band images from the German TerraSAR-X and TanDEM-X satellites were acquired in the standard Stripmap mode with about 3 m spatial resolution in azimuth and range direction. Data acquisition lasted over a period of five years for Staufen (2008-2013), and four years for Ketzin (2009-2013). For the first approximation of the subsurface source, an inversion of the InSAR outcome in Staufen was applied. The modeled uplift based on complex hydromechanical simulations and a correlation analysis with bottomhole pressure data were used for comparison with MT-InSAR measurements at Ketzin. In response to the defined objectives of this thesis, a higher level of detail can be achieved in mapping surface displacements without in-situ effort by using MT-InSAR in comparison to leveling (1). A clear delineation of the elliptical shaped uplift border and its magnitudes at different parts was possible at Staufen, with the exception of a vegetated area in the northwest. Vegetation coverage and the associated temporal signal decorrelation are the main limitations of MT-InSAR as clearly demonstrated at the Ketzin test site. They result in insufficient measurement point density and unwrapping issues. Therefore, spatial resolutions of one meter or better are recommended to achieve an adequate point density for local displacement analysis and to apply signal noise reduction. Leveling measurements can provide a complementary data source here, but require much effort pertaining to personnel even at the local scale. Horizontal motions could be identified at Staufen by only comparing the temporal evolution of the 1D line of sight (LOS) InSAR measurements with the available leveling data. An exception was the independent LOS decomposition using ascending and descending data sets for the period 2012-2013. The full 3D displacement field representation failed due to insufficient orbit-related, north-south sensitivity of the satellite-based measurements. By using the dense temporal mapping capabilities of the TerraSAR-X/TanDEM-X satellites after every 11 days, the temporal displacement evolution could be captured as good as that with leveling. With respect to the tested methods and in the view of generality, SBAS should be preferred over PSI (2). SBAS delivered a higher point density, and was therefore less affected by phase unwrapping issues in both case studies. Linking surface motions with subsurface processes is possible when considering simplified geophysical models (3), but it still requires intensive research to gain a deep understanding.},
  language  = {en}
}