@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{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{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{Reusser2011,
  author    = {Reusser, Dominik Edwin},
  title     = {Combining smart model diagnostics and effective data collection for snow catchments},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-52574},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Complete protection against flood risks by structural measures is impossible. Therefore flood prediction is important for flood risk management. Good explanatory power of flood models requires a meaningful representation of bio-physical processes. Therefore great interest exists to improve the process representation. Progress in hydrological process understanding is achieved through a learning cycle including critical assessment of an existing model for a given catchment as a first step. The assessment will highlight deficiencies of the model, from which useful additional data requirements are derived, giving a guideline for new measurements. These new measurements may in turn lead to improved process concepts. The improved process concepts are finally summarized in an updated hydrological model. In this thesis I demonstrate such a learning cycle, focusing on the advancement of model evaluation methods and more cost effective measurements. For a successful model evaluation, I propose that three questions should be answered: 1) when is a model reproducing observations in a satisfactory way? 2) If model results deviate, of what nature is the difference? And 3) what are most likely the relevant model components affecting these differences? To answer the first two questions, I developed a new method to assess the temporal dynamics of model performance (or TIGER - TIme series of Grouped Errors). This method is powerful in highlighting recurrent patterns of insufficient model behaviour for long simulation periods. I answered the third question with the analysis of the temporal dynamics of parameter sensitivity (TEDPAS). For calculating TEDPAS, an efficient method for sensitivity analysis is necessary. I used such an efficient method called Fourier Amplitude Sensitivity Test, which has a smart sampling scheme. Combining the two methods TIGER and TEDPAS provided a powerful tool for model assessment. With WaSiM-ETH applied to the Weisseritz catchment as a case study, I found insufficient process descriptions for the snow dynamics and for the recession during dry periods in late summer and fall. Focusing on snow dynamics, reasons for poor model performance can either be a poor representation of snow processes in the model, or poor data on snow cover, or both. To obtain an improved data set on snow cover, time series of snow height and temperatures were collected with a cost efficient method based on temperature measurements on multiple levels at each location. An algorithm was developed to simultaneously estimate snow height and cold content from these measurements. Both, snow height and cold content are relevant quantities for spring flood forecasting. Spatial variability was observed at the local and the catchment scale with an adjusted sampling design. At the local scale, samples were collected on two perpendicular transects of 60 m length and analysed with geostatistical methods. The range determined from fitted theoretical variograms was within the range of the sampling design for 80\% of the plots. No patterns were found, that would explain the random variability and spatial correlation at the local scale. At the watershed scale, locations of the extensive field campaign were selected according to a stratified sample design to capture the combined effects of elevation, aspect and land use. The snow height is mainly affected by the plot elevation. The expected influence of aspect and land use was not observed. To better understand the deficiencies of the snow module in WaSiM-ETH, the same approach, a simple degree day model was checked for its capability to reproduce the data. The degree day model was capable to explain the temporal variability for plots with a continuous snow pack over the entire snow season, if parameters were estimated for single plots. However, processes described in the simple model are not sufficient to represent multiple accumulation-melt-cycles, as observed for the lower catchment. Thus, the combined spatio-temporal variability at the watershed scale is not captured by the model. Further tests on improved concepts for the representation of snow dynamics at the Weißeritz are required. From the data I suggest to include at least rain on snow and redistribution by wind as additional processes to better describe spatio-temporal variability. Alternatively an energy balance snow model could be tested. Overall, the proposed learning cycle is a useful framework for targeted model improvement. The advanced model diagnostics is valuable to identify model deficiencies and to guide field measurements. The additional data collected throughout this work helps to get a deepened understanding of the processes in the Weisseritz catchment.},
  language  = {en}
}
@phdthesis{Voss2005,
  author    = {Voß, Frank},
  title     = {Integrierte Modellierung von Durchflussdynamik und salinarer Stofftransportprozesse unter Ber{\"u}cksichtigung anthropogener Steuerungen am Beispiel der Unstrut},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-6403},
  school      = {Universit{\"a}t Potsdam},
  year      = {2005},
  abstract  = {Durch die Stilllegung der Kali-Gewinnung und -Produktion zwischen 1990 und 1993 sowie die begonnene Rekultivierung der Kali-R{\"u}ckstandshalden haben sich die Salzfrachteintragsbedingungen f{\"u}r die Fließgwew{\"a}sser im "S{\"u}dharz-Kalirevier" in Th{\"u}ringen zum Teil deutlich ver{\"a}ndert. Aufgrund erheblich geringerer Salzeintr{\"a}ge in die Vorfluter Wipper und Bode ist es m{\"o}glich geworden, zu einer {\"o}kologisch vertr{\"a}glichen Salzfrachtsteuerung {\"u}berzugehen. Die Komplexit{\"a}t der zugrunde liegenden Stofftransportprozesse im Einzugsgebiet der Wipper macht es jedoch unumg{\"a}nglich, den Steuerungsvorgang nicht nur durch reine Bilanzierungsvorg{\"a}nge auf der betrachteten Steuerstrecke zu erfassen (so wie bisher praktiziert), sondern auch die Abflussdynamik im Fließgew{\"a}sser und den Wasserhaushalt im Gebiet mit einzubeziehen. Die Ergebnisse dieser Arbeit dienen zum einen einer Vertiefung der Prozessverst{\"a}ndnisse und der Interaktion von Wasserhaushalt, Abflussbildung sowie Stofftransport in bergbaubeeinflussten Einzugsgebieten am Beispiel der Unstrut bzw. ihrer relevanten Nebenfl{\"u}sse. Zum anderen sollen sie zur Analyse und Bewertung eines Bewirtschaftungsplanes f{\"u}r die genannten Fließgew{\"a}sser herangezogen werden k{\"o}nnen. Ziel dieser Arbeit ist die Erstellung eines prognosetauglichen Steuerungsinstrumentes, das f{\"u}r die Bewirtschaftung von Flusseinzugsgebieten unterschiedlicher Gr{\"o}ße genutzt und unter den Rahmenbedingungen der bergbaubedingten salinaren Eintr{\"a}ge effektiv zur Steuerung der anthropogenen Frachten eingesetzt werden kann. Die Quellen der anthropogen eingeleiteten Salzfracht sind vor allem die R{\"u}ckstandshalden der stillgelegten Kaliwerke. Durch Niederschl{\"a}ge entstehen salzhaltige Haldenabw{\"a}sser, die zum Teil ungesteuert {\"u}ber oberfl{\"a}chennahe Ausbreitungsvorg{\"a}nge direkt in die Vorfluter gelangen, ein anderer Teil wird {\"u}ber die Speichereinrichtungen gefasst und gezielt abgestoßen. Durch Undichtigkeiten des Laugenstapelbeckens in Wipperdorf gelangen ebenfalls ungesteuerte Frachteintr{\"a}ge in die Wipper. Ein weiterer Eintragspfad ist zudem die geogene Belastung. Mit Hilfe detaillierter Angaben zu den oben genannten Eintragspfaden konnten Modellrechnungen im Zeitraum von 1992 bis 2003 durchgef{\"u}hrt werden. Durch die Ausarbeitung eines neuartigen Steuerungskonzeptes f{\"u}r das Laugenstapelbecken Wipperdorf, war es nun m{\"o}glich, die gefasste Haldenlauge entsprechend der aktuellen Abflusssituation gezielt abstoßen zu k{\"o}nnen. Neben der modelltechnischen Erfassung der aktuellen hydrologischen Situation und der Vorgabe eines Chlorid-Konzentrationssteuerzieles f{\"u}r den Pegel Hachelbich, mussten dabei weitere Randbedingungen (Beckenkapazit{\"a}t, Beckenf{\"u}llstand, Mindestf{\"u}llstand, Kapazit{\"a}t des Ableitungskanals, usw.) ber{\"u}cksichtigt werden. Es zeigte sich, dass unter Anwendung des Steuerungskonzeptes die Schwankungsbreite der Chloridkonzentration insgesamt gesehen deutlich verringert werden konnte. Die {\"U}berschreitungsh{\"a}ufigkeiten bez{\"u}glich eines Grenzwertes von 2 g Chlorid/l am Pegel Hachelbich fielen deutlich, und auch die maximale Dauer einer solchen Periode konnte stark verk{\"u}rzt werden. Kritische Situationen bei der modelltechnischen Frachtzusteuerung traten nur dann auf, wenn Niedrigwasserverh{\"a}ltnisse durch die Simulationsberechnungen noch untersch{\"a}tzt wurden. Dies hatte deutliche {\"U}berschreitungen der Zielvorgaben f{\"u}r den Pegel Hachelbich zur Folge. Mit Hilfe des Steuerungsalgorithmus konnten desweiteren auch Szenarienberechnungen durchgef{\"u}hrt werden, um die Auswirkungen zuk{\"u}nftig zu erwartender Salzfrachten n{\"a}her spezifizieren zu k{\"o}nnen. Dabei konnte festgestellt werden, dass Abdichtungsmaßnahmen der Haldenk{\"o}rper sich direkt positiv auf die Entwicklung der Konzentration in Hachelbich auswirkten. Durch zus{\"a}tzlich durchgef{\"u}hrte Langzeitszenarien konnte dar{\"u}ber hinaus nachgewiesen werden, dass langfristig eine Grenzwertfestlegung auf 1,5 g Chlorid/l in Hachelbich m{\"o}glich ist, und die Stapelkapazit{\"a}ten dazu ausreichend bemessen sind.},
  subject      = {Hydrologie},
  language  = {de}
}
@phdthesis{Hattermann2005,
  author    = {Hattermann, Fred},
  title     = {Integrated modelling of Global Change impacts in the German Elbe River Basin},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-6052},
  school      = {Universit{\"a}t Potsdam},
  year      = {2005},
  abstract  = {The scope of this study is to investigate the environmental change in the German part of the Elbe river basin, whereby the focus is on two water related problems: having too little water and having water of poor quality. The Elbe region is representative of humid to semi-humid landscapes in central Europe, where water availability during the summer season is the limiting factor for plant growth and crop yields, especially in the loess areas, where the annual precipitation is lower than 500 mm. It is most likely that water quantity problems will accelerate in future, because both the observed and the projected climate trend show an increase in temperature and a decrease in annual precipitation, especially in the summer. Another problem is nutrient pollution of rivers and lakes. In the early 1990s, the Elbe was one of the most heavily polluted rivers in Europe. Even though nutrient emissions from point sources have notably decreased in the basin due to reduction of industrial sources and introduction of new and improved sewage treatment facilities, the diffuse sources of pollution are still not sufficiently controlled. The investigations have been done using the eco-hydrological model SWIM (Soil and Water Integrated Model), which has been embedded in a model framework of climate and agro-economic models. A global scenario of climate and agro-economic change has been regionalized to generate transient climate forcing data and land use boundary conditions for the model. The model was used to transform the climate and land use changes into altered evapotranspiration, groundwater recharge, crop yields and river discharge, and to investigate the development of water quality in the river basin. Particular emphasis was given to assessing the significance of the impacts on the hydrology, taking into account in the analysis the inherent uncertainty of the regional climate change as well as the uncertainty in the results of the model. The average trend of the regional climate change scenario indicates a decrease in mean annual precipitation up to 2055 of about 1.5 \%, but with high uncertainty (covering the range from -15.3 \% to +14.8 \%), and a less uncertain increase in temperature of approximately 1.4 K. The relatively small change in precipitation in conjunction with the change in temperature leads to severe impacts on groundwater recharge and river flow. Increasing temperature induces longer vegetation periods, and the seasonality of the flow regime changes towards longer low flow spells in summer. As a results the water availability will decrease on average of the scenario simulations by approximately 15 \%. The increase in temperatures will improve the growth conditions for temperature limited crops like maize. The uncertainty of the climate trend is particularly high in regions where the change is the highest. The simulation results for the Nuthe subbasin of the Elbe indicate that retention processes in groundwater, wetlands and riparian zones have a high potential to reduce the nitrate concentrations of rivers and lakes in the basin, because they are located at the interface between catchment area and surface water bodies, where they are controlling the diffuse nutrient inputs. The relatively high retention of nitrate in the Nuthe basin is due to the long residence time of water in the subsurface (about 40 years), with good conditions for denitrification, and due to nitrate retention and plant uptake in wetlands and riparian zones. The concluding result of the study is that the natural environment and communities in parts of Central Europe will have considerably lower water resources under scenario conditions. The water quality will improve, but due to the long residence time of water and nutrients in the subsurface, this improvement will be slower in areas where the conditions for nutrient turn-over in the subsurface are poor.},
  subject      = {Hydrologie},
  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}
}