@article{AichnerMakhmudovRajabovetal.2019,
  author    = {Aichner, Bernhard and Makhmudov, Zafar and Rajabov, Iljomjon and Zhang, Qiong and Pausata, Francesco Salvatore R. and Werner, Martin and Heinecke, Liv and Kuessner, Marie L. and Feakins, Sarah J. and Sachse, Dirk and Mischke, Steffen},
  title     = {Hydroclimate in the Pamirs Was Driven by Changes in Precipitation-Evaporation Seasonality Since theLast Glacial Period},
  series = {Geophysical research letters},
  volume    = {46},
  journal   = {Geophysical research letters},
  number    = {23},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {0094-8276},
  doi       = {10.1029/2019GL085202},
  pages     = {13972 -- 13983},
  year      = {2019},
  abstract  = {The Central Asian Pamir Mountains (Pamirs) are a high-altitude region sensitive to climatic change, with only few paleoclimatic records available. To examine the glacial-interglacial hydrological changes in the region, we analyzed the geochemical parameters of a 31-kyr record from Lake Karakul and performed a set of experiments with climate models to interpret the results. delta D values of terrestrial biomarkers showed insolation-driven trends reflecting major shifts of water vapor sources. For aquatic biomarkers, positive delta D shifts driven by changes in precipitation seasonality were observed at ca. 31-30, 28-26, and 17-14 kyr BP. Multiproxy paleoecological data and modelling results suggest that increased water availability, induced by decreased summer evaporation, triggered higher lake levels during those episodes, possibly synchronous to northern hemispheric rapid climate events. We conclude that seasonal changes in precipitation-evaporation balance significantly influenced the hydrological state of a large waterbody such as Lake Karakul, while annual precipitation amount and inflows remained fairly constant.},
  language  = {en}
}
@article{Ayzel2021,
  author    = {Ayzel, Georgy},
  title     = {Deep neural networks in hydrology},
  series = {Vestnik of Saint Petersburg University. Earth Sciences},
  volume    = {66},
  journal   = {Vestnik of Saint Petersburg University. Earth Sciences},
  number    = {1},
  publisher = {Univ. Press},
  address   = {St. Petersburg},
  issn      = {2541-9668},
  doi       = {10.21638/spbu07.2021.101},
  pages     = {5 -- 18},
  year      = {2021},
  abstract  = {For around a decade, deep learning - the sub-field of machine learning that refers to artificial neural networks comprised of many computational layers - modifies the landscape of statistical model development in many research areas, such as image classification, machine translation, and speech recognition. Geoscientific disciplines in general and the field of hydrology in particular, also do not stand aside from this movement. Recently, the proliferation of modern deep learning-based techniques and methods has been actively gaining popularity for solving a wide range of hydrological problems: modeling and forecasting of river runoff, hydrological model parameters regionalization, assessment of available water resources. identification of the main drivers of the recent change in water balance components. This growing popularity of deep neural networks is primarily due to their high universality and efficiency. The presented qualities, together with the rapidly growing amount of accumulated environmental information, as well as increasing availability of computing facilities and resources, allow us to speak about deep neural networks as a new generation of mathematical models designed to, if not to replace existing solutions, but significantly enrich the field of geophysical processes modeling. This paper provides a brief overview of the current state of the field of development and application of deep neural networks in hydrology. Also in the following study, the qualitative long-term forecast regarding the development of deep learning technology for managing the corresponding hydrological modeling challenges is provided based on the use of "Gartner Hype Curve", which in the general details describes a life cycle of modern technologies.},
  language  = {en}
}
@misc{AyzelIzhitskiy2019,
  author    = {Ayzel, Georgy and Izhitskiy, Alexander},
  title     = {Climate change impact assessment on freshwater inflow into the Small Aral Sea},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1071},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-47279},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-472794},
  pages     = {21},
  year      = {2019},
  abstract  = {During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007-2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash-Sutcliffe efficiency of 0.72 and a Kling-Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.},
  language  = {en}
}
@article{AyzelIzhitskiy2019,
  author    = {Ayzel, Georgy and Izhitskiy, Alexander},
  title     = {Climate Change Impact Assessment on Freshwater Inflow into the Small Aral Sea},
  series = {Water},
  volume    = {11},
  journal   = {Water},
  number    = {11},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2073-4441},
  doi       = {10.3390/w11112377},
  pages     = {19},
  year      = {2019},
  abstract  = {During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007-2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash-Sutcliffe efficiency of 0.72 and a Kling-Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.},
  language  = {en}
}
@phdthesis{Baese2016,
  author    = {B{\"a}se, Frank},
  title     = {Interception loss of changing land covers in the humid tropical lowland of Latin America},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ix, 85 Seiten},
  year      = {2016},
  abstract  = {Das Gebiet der feuchten Tropen ist die am st{\"a}rksten durch den Landnutzungswandel betroffene Region der Erde. Vor allem die Rodung tropischer W{\"a}lder, um Platz f{\"u}r Rinderweiden oder den Anbau von Soja zu schaffen, aber auch seit j{\"u}ngster Zeit die Bem{\"u}hungen um Wiederaufforstungen pr{\"a}gen diesen Landnutzungswandel. Dabei beeinflusst die {\"A}nderung der Vegetationsbedeckung den regionalen Wasserhaushalt auf vielf{\"a}ltige Weise. Betroffen ist unter anderem die Verdunstung von feuchten Oberfl{\"a}chen. Die so genannte Interzeptionsverdunstung bzw. der Interzeptionsverlust tr{\"a}gt erheblich zum Wasserdampfgehalt in der unteren Atmosph{\"a}re und schließlich zur Niederschlagsbildung bei. Ziele dieser Dissertation waren (1) die experimentelle Untersuchung der Interzeptionsverlustunterschiede zwischen einem nat{\"u}rlichen, tropischen Wald und einer Sojaplantage im s{\"u}dlichen Amazonasgebiet, (2) die Modellierung des Interzeptionsverlustes dieser beiden Vegetationsformen im Vergleich zu einem jungen Sekund{\"a}rwald unter dem Aspekt der Unsicherheiten bei der Ableitung notwendiger Modellparameter sowohl im S{\"u}damazonas als auch im Einzugsgebietes des Panamakanals sowie (3) die Wasserhaushaltsanalyse eines vom Landnutzungswandel gepr{\"a}gten Teileinzugsgebietes des Panamakanals in Hinblick auf die Ver{\"a}nderung der Interzeptionsverdunstung durch sich ver{\"a}ndernde Landnutzung und der {\"A}nderung der klimatischen Bedingungen. Die Messung des Interzeptionsverlustes zeigte, dass in der Hauptwachstumsphase vom Soja von dessen Oberfl{\"a}che mehr Wasserverdunstet als von der Oberfl{\"a}che des Waldes. Allerdings ist in der Jahresbilanz der Interzeptionsverlust vom Wald h{\"o}her, da diese Studie nur eine Momentaufnahme zur Zeit der vollen Vegetationsentwicklung des Sojas mit einem Zeitfenster von zwei Monaten widerspiegelt. Durch die geringere ganzj{\"a}hrige Verdunstung von den mit Soja bestandenen Fl{\"a}chen, wird hier der Niederschlag schneller dem Abfluss zugef{\"u}hrt und schell aus der Region ausgetragen. Somit tr{\"a}gt der Landnutzungswandel von Wald zu Soja zu einer mittelfristigen Reduktion des in der Region verf{\"u}gbaren Wassers bei. Die anschließende Modellierung des Interzeptionsverlustes zeigte Einerseits einen starken Einfluss der Datenqualit{\"a}t auf die Plausibilit{\"a}t der Ergebnisse und Andererseits, dass die Sensitivit{\"a}t der einzelnen Parameter zwischen den Untersuchungsgebieten variiert. Eine Schl{\"u}sselrolle nimmt die Wasserspeicherkapazit{\"a}t der Vegetationskrone ein. Dennoch ist die Evaporationsrate die treibende Gr{\"o}ße im Interzeptionsprozess, so dass von ihr die gr{\"o}ßte Unsicherheit ausgeht. Je nach verwendeter Methode zur Ableitung dieses Parameters unterscheiden sich die gewonnenen Parameterwerte erheblich. Die Wirkungsanalyse der Interzeptionsverdunstung auf den Wasserhaushalt im Wirkungsgeflecht der {\"A}nderungen von Temperatur, Niederschlag und Landnutzung im Landschaftsmosaik eines Flusseinzugsgebiets mit Hilfe eines Wasserhaushaltsmodels zeigte den Einfluss der Landnutzungs{\"a}nderung auf die Abflussbildung mittels verschiedener Landnutzungsszenarien. Die Ergebnisse belegen, dass die Landnutzungs{\"a}nderung im Gebiet nur einen geringen Einfluss auf den Jahresabfluss hat. St{\"a}rker scheint sich der gemessene Temperaturanstieg auf die Verdunstung auszuwirken. Der mit einer h{\"o}heren Temperatur einhergehende Anstieg der Transpiration und Interzeptionsverdunstung gleicht die gemessene Zunahme des Gebietsniederschlages aus, sodass keine signifikanten {\"A}nderungen im Jahresabfluss nachgewiesen werden konnten. Die Ergebnisse der drei Studien verdeutlichen den Einfluss der Landnutzung auf die Interzeptionsverdunstung. Allerdings veranschaulichten die Resultate der Wasserhaushalts-modellierung, wie sehr dieser Einfluss durch die Ver{\"a}nderung der {\"a}ußeren Rahmenbedingungen, vor allem durch den Anstieg der Temperatur, {\"u}berpr{\"a}gt werden kann. Dies belegt, dass eine einfache {\"U}bertragung der Ergebnisse zwischen den Untersuchungsgebiet nicht m{\"o}glich ist. Somit bleibt die experimentelle Erhebung von Vegetationsparametern sowie des Interzeptionsverlustes an den jeweils zu untersuchenden Standort f{\"u}r die Anwendung von Modellen unerl{\"a}sslich.},
  language  = {en}
}
@article{CochLamoureuxKnoblauchetal.2018,
  author    = {Coch, Caroline and Lamoureux, Scott F. and Knoblauch, Christian and Eischeid, Isabell and Fritz, Michael and Obu, Jaroslav and Lantuit, Hugues},
  title     = {Summer rainfall dissolved organic carbon, solute, and sediment fluxes in a small Arctic coastal catchment on Herschel Island (Yukon Territory, Canada)},
  series = {Artic science},
  volume    = {4},
  journal   = {Artic science},
  number    = {4},
  publisher = {Canadian science publishing},
  address   = {Ottawa},
  issn      = {2368-7460},
  doi       = {10.1139/as-2018-0010},
  pages     = {750 -- 780},
  year      = {2018},
  abstract  = {Coastal ecosystems in the Arctic are affected by climate change. As summer rainfall frequency and intensity are projected to increase in the future, more organic matter, nutrients and sediment could bemobilized and transported into the coastal nearshore zones. However, knowledge of current processes and future changes is limited. We investigated streamflow dynamics and the impacts of summer rainfall on lateral fluxes in a small coastal catchment on Herschel Island in the western Canadian Arctic. For the summer monitoring periods of 2014-2016, mean dissolved organic matter flux over 17 days amounted to 82.7 +/- 30.7 kg km(-2) and mean total dissolved solids flux to 5252 +/- 1224 kg km(-2). Flux of suspended sediment was 7245 kg km(-2) in 2015, and 369 kg km(-2) in 2016. We found that 2.0\% of suspended sediment was composed of particulate organic carbon. Data and hysteresis analysis suggest a limited supply of sediments; their interannual variability is most likely caused by short-lived localized disturbances. In contrast, our results imply that dissolved organic carbon is widely available throughout the catchment and exhibits positive linear relationship with runoff. We hypothesize that increased projected rainfall in the future will result in a similar increase of dissolved organic carbon fluxes.},
  language  = {en}
}
@phdthesis{Guentner2002,
  author    = {G{\"u}ntner, Andreas},
  title     = {Large-scale hydrological modelling in the semi-arid north-east of Brazil},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-0000511},
  school      = {Universit{\"a}t Potsdam},
  year      = {2002},
  abstract  = {Semi-arid areas are, due to their climatic setting, characterized by small water resources. An increasing water demand as a consequence of population growth and economic development as well as a decreasing water availability in the course of possible climate change may aggravate water scarcity in future, which often exists already for present-day conditions in these areas. Understanding the mechanisms and feedbacks of complex natural and human systems, together with the quantitative assessment of future changes in volume, timing and quality of water resources are a prerequisite for the development of sustainable measures of water management to enhance the adaptive capacity of these regions. For this task, dynamic integrated models, containing a hydrological model as one component, are indispensable tools. The main objective of this study is to develop a hydrological model for the quantification of water availability in view of environmental change over a large geographic domain of semi-arid environments. The study area is the Federal State of Cear{\´a} (150 000 km2) in the semi-arid north-east of Brazil. Mean annual precipitation in this area is 850 mm, falling in a rainy season with duration of about five months. Being mainly characterized by crystalline bedrock and shallow soils, surface water provides the largest part of the water supply. The area has recurrently been affected by droughts which caused serious economic losses and social impacts like migration from the rural regions. The hydrological model Wasa (Model of Water Availability in Semi-Arid Environments) developed in this study is a deterministic, spatially distributed model being composed of conceptual, process-based approaches. Water availability (river discharge, storage volumes in reservoirs, soil moisture) is determined with daily resolution. Sub-basins, grid cells or administrative units (municipalities) can be chosen as spatial target units. The administrative units enable the coupling of Wasa in the framework of an integrated model which contains modules that do not work on the basis of natural spatial units. The target units mentioned above are disaggregated in Wasa into smaller modelling units within a new multi-scale, hierarchical approach. The landscape units defined in this scheme capture in particular the effect of structured variability of terrain, soil and vegetation characteristics along toposequences on soil moisture and runoff generation. Lateral hydrological processes at the hillslope scale, as reinfiltration of surface runoff, being of particular importance in semi-arid environments, can thus be represented also within the large-scale model in a simplified form. Depending on the resolution of available data, small-scale variability is not represented explicitly with geographic reference in Wasa, but by the distribution of sub-scale units and by statistical transition frequencies for lateral fluxes between these units. Further model components of Wasa which respect specific features of semi-arid hydrology are: (1) A two-layer model for evapotranspiration comprises energy transfer at the soil surface (including soil evaporation), which is of importance in view of the mainly sparse vegetation cover. Additionally, vegetation parameters are differentiated in space and time in dependence on the occurrence of the rainy season. (2) The infiltration module represents in particular infiltration-excess surface runoff as the dominant runoff component. (3) For the aggregate description of the water balance of reservoirs that cannot be represented explicitly in the model, a storage approach respecting different reservoirs size classes and their interaction via the river network is applied. (4) A model for the quantification of water withdrawal by water use in different sectors is coupled to Wasa. (5) A cascade model for the temporal disaggregation of precipitation time series, adapted to the specific characteristics of tropical convective rainfall, is applied for the generating rainfall time series of higher temporal resolution. All model parameters of Wasa can be derived from physiographic information of the study area. Thus, model calibration is primarily not required. Model applications of Wasa for historical time series generally results in a good model performance when comparing the simulation results of river discharge and reservoir storage volumes with observed data for river basins of various sizes. The mean water balance as well as the high interannual and intra-annual variability is reasonably represented by the model. Limitations of the modelling concept are most markedly seen for sub-basins with a runoff component from deep groundwater bodies of which the dynamics cannot be satisfactorily represented without calibration. Further results of model applications are: (1) Lateral processes of redistribution of runoff and soil moisture at the hillslope scale, in particular reinfiltration of surface runoff, lead to markedly smaller discharge volumes at the basin scale than the simple sum of runoff of the individual sub-areas. Thus, these processes are to be captured also in large-scale models. The different relevance of these processes for different conditions is demonstrated by a larger percentage decrease of discharge volumes in dry as compared to wet years. (2) Precipitation characteristics have a major impact on the hydrological response of semi-arid environments. In particular, underestimated rainfall intensities in the rainfall input due to the rough temporal resolution of the model and due to interpolation effects and, consequently, underestimated runoff volumes have to be compensated in the model. A scaling factor in the infiltration module or the use of disaggregated hourly rainfall data show good results in this respect. The simulation results of Wasa are characterized by large uncertainties. These are, on the one hand, due to uncertainties of the model structure to adequately represent the relevant hydrological processes. On the other hand, they are due to uncertainties of input data and parameters particularly in view of the low data availability. Of major importance is: (1) The uncertainty of rainfall data with regard to their spatial and temporal pattern has, due to the strong non-linear hydrological response, a large impact on the simulation results. (2) The uncertainty of soil parameters is in general of larger importance on model uncertainty than uncertainty of vegetation or topographic parameters. (3) The effect of uncertainty of individual model components or parameters is usually different for years with rainfall volumes being above or below the average, because individual hydrological processes are of different relevance in both cases. Thus, the uncertainty of individual model components or parameters is of different importance for the uncertainty of scenario simulations with increasing or decreasing precipitation trends. (4) The most important factor of uncertainty for scenarios of water availability in the study area is the uncertainty in the results of global climate models on which the regional climate scenarios are based. Both a marked increase or a decrease in precipitation can be assumed for the given data. Results of model simulations for climate scenarios until the year 2050 show that a possible future change in precipitation volumes causes a larger percentage change in runoff volumes by a factor of two to three. In the case of a decreasing precipitation trend, the efficiency of new reservoirs for securing water availability tends to decrease in the study area because of the interaction of the large number of reservoirs in retaining the overall decreasing runoff volumes.},
  subject      = {Cear{\´a} / Semiarides Gebiet / Wasserreserve / Hydrologie / Mathematisches Modell},
  language  = {en}
}
@article{HayhoeNeillPorderetal.2011,
  author    = {Hayhoe, Shelby J. and Neill, Christopher and Porder, Stephen and McHorney, Richard and Lefebvre, Paul and Coe, Michael T. and Elsenbeer, Helmut and Krusche, Alex V.},
  title     = {Conversion to soy on the Amazonian agricultural frontier increases streamflow without affecting stormflow dynamics},
  series = {Global change biology},
  volume    = {17},
  journal   = {Global change biology},
  number    = {5},
  publisher = {Wiley-Blackwell},
  address   = {Malden},
  issn      = {1354-1013},
  doi       = {10.1111/j.1365-2486.2011.02392.x},
  pages     = {1821 -- 1833},
  year      = {2011},
  abstract  = {Large-scale soy agriculture in the southern Brazilian Amazon now rivals deforestation for pasture as the region's predominant form of land use change. Such landscape-level change can have substantial consequences for local and regional hydrology, but these effects remain relatively unstudied in this ecologically and economically important region. We examined how the conversion to soy agriculture influences water balances and stormflows using stream discharge (water yields) and the timing of discharge (stream hydrographs) in small (2.5-13.5 km2) forested and soy headwater watersheds in the Upper Xingu Watershed in the state of Mato Grosso, Brazil. We monitored water yield for 1 year in three forested and four soy watersheds. Mean daily water yields were approximately four times higher in soy than forested watersheds, and soy watersheds showed greater seasonal variability in discharge. The contribution of stormflows to annual streamflow in all streams was low (< 13\% of annual streamflow), and the contribution of stormflow to streamflow did not differ between land uses. If the increases in water yield observed in this study are typical, landscape-scale conversion to soy substantially alters water-balance, potentially altering the regional hydrology over large areas of the southern Amazon.},
  language  = {en}
}
@techreport{HuđekŽganecPusch2020,
  author    = {Huđek, Helena and Žganec, Krešimir and Pusch, Martin T.},
  title     = {A review of hydropower dams in Southeast Europe},
  series = {Renewable \& sustainable energy reviews},
  volume    = {117},
  journal   = {Renewable \& sustainable energy reviews},
  publisher = {Elsevier Science},
  address   = {Amsterdam [u.a.]},
  issn      = {1364-0321},
  doi       = {10.1016/j.rser.2019.109434},
  pages     = {11},
  year      = {2020},
  abstract  = {Currently, Southeast Europe (SEE) is witnessing a boom in hydropower plant (HPP) construction, which has not even spared protected areas. As SEE includes global hotspots of aquatic biodiversity, it is expected that this boom will result in a more severe impact on biodiversity than that of other regions. A more detailed assessment of the environmental risks resulting from HPP construction would have to rely on the existence of nearby hydrological and biological monitoring stations. For this reason, we review the distribution and trends of HPPs in the area, as well as the availability of hydrological and biological monitoring data from national institutions useable for environmental impact assessment. Our analysis samples tributary rivers of the Danube in Slovenia, Croatia, Bosnia and Herzegovina, Serbia, and Montenegro, referred to hereafter as TRD rivers. Currently, 636 HPPs are operating along the course of TRD rivers, most of which are small (<1 MW). An additional 1315 HPPs are currently planned to be built, mostly in Serbia and in Bosnia and Herzegovina. As official monitoring stations near HPPs are rare, the impact of those HPPs on river flow, fish and macro-invertebrates is difficult to assess. This manuscript represents the first regional review of hydropower use and of available data sources on its environmental impact for an area outside of the Alps. We conclude that current hydrological and biological monitoring in TRD rivers is insufficient for an assessment of the ecological impacts of HPPs. This data gap also prevents an adequate assessment of the ecological impacts of planned HP projects, as well as the identification of appropriate measures to mitigate the environmental effects of existing HPPs.},
  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}
}