The management of New Zealand’s freshwater resources has come under increasing pressure from different industrial and environmental stakeholders. Land use change and the pressure it can put on water resources has been a significant issue regarding resource management in New Zealand. A significant mechanism driving land use change has been the growth of forestry, dairy farming, and other agricultural industries. Improvements in agricultural and forestry science and irrigation techniques have allowed new, previously less arable areas of New Zealand to be subject to land use change, such as the conversion of tussock grassland to pasture in steep, mountainous regions in the South Island. Studies regarding the effects of land use change in such catchments, especially with focus on flood hydrology, appear to be limited, despite the importance of managing catchment headwaters to minimise flood risk downstream. The TopNet model was used in this research project to evaluate the potential effects of land use change on flood hydrology in mountain catchments. It is a semi-distributed continuous rainfall-runoff model developed by the National Institute of Water and Atmospheric Research (NIWA). It has been widely used in New Zealand, and applications have included modelling water yield and the effect of climate change in catchment networks. However, it was not developed specifically for predicting flood flows. Hence, testing the model for flood peak prediction in mountainous catchments was also performed, and may show that TopNet can be a useful tool in resource management in New Zealand. The Ahuriri and Pelorus River catchments were used in this investigation. Both are steep catchments located in the South Island. The Ahuriri River catchment, in the Waitaki Basin on the eastern side of the Southern Alps, is a semi-arid catchment dominated by tussock grassland. The surrounding catchments are heavily influenced by infrastructure for hydroelectric power (HEP) generation and more recently irrigation for dairy farming. The Pelorus River catchment is located at the northern end of the South Island. It is primarily covered in native forest, but adjacent catchments are subject to agricultural and forestry development. The ability of the TopNet model for each catchment to predict flood flows were tested using a selection of historical flood events. Rainfall input to the model was at a daily timestep from the virtual climate station network (VCSN), and the method of disaggregating the daily estimate into an hourly rainfall series to be used by the model was found to have a significant influence on flood prediction. Where an accurate historical rainfall record was provided from a rainfall gauge station within the catchments, the disaggregation of the daily rainfall estimate based on the station data produced a significantly more accurate flood prediction when compared to predictions made using a stochastic disaggregation of the daily rainfall estimate. The TopNet models were modified to reflect land use change scenarios: the conversion of tussock grassland to pasture and the afforestation of tussock in the Ahuriri River catchment, and the conversion of forested land to pasture and the harvest of plantation forestry in the Pelorus River catchment. Following a past study into modelling the effects of land use change using TopNet, three key model parameters were modified to reflect each land use scenario: saturated hydraulic conductivity KS, canopy storage capacity, and the canopy enhancement factor. Past studies suggested a wide range of suitable values for KS, although also acknowledged that KS depends heavily on the specific catchment characteristics. A sensitivity analysis showed that KS had a significant influence on flood peak prediction in TopNet. It is recommended that further investigation be conducted into suitable values for KS. TopNet appeared to predict the effect of land use change on flood magnitude in mountainous catchments conservatively. Past studies of land use change suggested that the effect on flood flows should be significant, whereas TopNet generally predicted small changes in flood peaks for the scenarios in each catchment. However, this may suggest that the topography, geology, and soil properties of steep catchments are more important to flood hydrology than land cover. Further investigation into the effect of such catchment characteristics is recommended. Nevertheless, TopNet was shown to have the potential to be a useful tool for evaluating and managing the effects of land use change on the flood hydrology of mountainous catchments in New Zealand.

Deux volets distincts de l'hydrologie sont abordés, prévision et prédétermination, au travers d'une problématique commune : le transfert à l'exutoire des bassins versants d' une information hydrologique distribuée. Dans le domaine de la prévision des crues, la technologie radar procure une information pluviométrique spatialement continue. Les hydrologues disposent ainsi en temps réel de la connaissance des champs de pluie, atout indéniable pour l'anticipation des crues notamment sur des petits bassins versants par le biais de la modélisation de la pluie en débit. Dans le cadre de la méthode AIGA d'alerte crues, développée au Cemagref, une modélisation mise en oeuvre à l'échelle du pixel de pluie fournit une cartographie des contributions de débit des pixels. Dans le domaine de la prédétermination, le Cemagref a développé la méthode SHYREG qui associe un modèle régionalisé de simulation de pluies horaires à une modélisation de la pluie en débit. Une estimation statistique régionale des pluies et des débits spécifiques de différentes durées, dans une large plage de fréquence (du courant à l'exceptionnel) peut ainsi être proposée et cartographiée. L'objectif du travail présenté est d'étudier et d'élaborer des méthodologies simples de transfert de ces deux informations débitmétriques discrétisées information temps réel pour le volet prévision et information statistique pour le volet prédétermination - à l'information débit à l'exutoire du bassin versant. La méthodologie met en oeuvre des informations spatiales et une modélisation de la pluie en débit. Pour répondre à l'objectif fixé, trois axes de travail sont développés. Le premier est l'étude du comportement d'un modèle pluie-débit simple développé pour être mis en oeuvre à la maille du km². On examine en particulier s'il satisfait les caractéristiques d'invariance et de parcimonie souhaitée pour une utilisation à la fois en reconstitution de crues et en simulation. Le second axe de travail concerne l'agglomération, en prédétermination, de l'information débit statistique connue au km² pour l'estimation des quantiles de débit à l' exutoire de bassins versants de superficie plus importante dans le cadre de la méthode SHYREG. Il s'agit de tenir compte de deux phénomènes hydrologiques distincts : l'abattement spatial de la pluie et le transfert dans le réseau hydraulique. Le troisième axe de travail concerne l'agglomération de l'information hydrologique distribuée pour la reconstitution des crues dans le cadre de l'outil AIGA d'alerte crues. Différentes modélisations sont proposées pour transférer à l'exutoire les contributions des débits modélisées aux pixels. / We address the routing of distributed hydrological information to the outlet of watersheds, in the fields of flood forecasting and flood prediction on ungauged watersheds in the French Mediterranean area.Flood forecasting can benefit of areal rainfall data provided in real-time by radar networks. This data used as an input to rainfall runoff models gives access to flood anticipation on small ungauged watersheds. Within the framework of the AIGA method, developed by CEMAGREF to provide floods alert, a rainfall-runoff model is implemented at the spatial resolution of the radar data, thus providing a map of the 1 km² pixel contributions to the runoff at the catchment outlet.Flood prediction consists of assessing the frequency of occurrence of floods of different given magnitude without reference to the times at which they would occur. The SHYREG flood prediction method, developed by Cemagref associates a regionalized rainfall model with a rainfall-runoff model. It provides grids of statistical estimates of rain and runoff for various duration and return periods. Our purpose is to study and work out simple methodologies to aggregate these two gridded hydrological data - real time information for the AIGA forecasting method and statistical data for the SHYREG prediction method to the catchments outlets. Our methodology implements distributed information and a rainfall-runoff model. We have first studied the behaviour of a simple rainfall-runoff model developed to be implemented in a gridded resolution (1 km² cells) for prediction as well as for forecasting purposes. We have checked that the model parameters show no redundancy and no link with the characteristics of the rainfall events. We have then addressed the question of the aggregation of gridded hydrological data. Within the SHYREG method, it consists of assessing statistical flow estimates at catchments outlets, knowing simulated flow distributions in each cell of the catchments. This aggregation would combine two distinct hydrological phenomena: areal reduction of rainfall and discharge attenuation in the channel network. Within the AIGA method, we have focused on the routing function of the rainfall-runoff model at the 1 km² cell scale, this scale being the first step of the runoff routing from the production area to the outlet of the catchment. We have then produced streamflow hindcasts for selected observed events using different routing function, within our rainfall-runoff model.

Die deterministische Modellierung des Niederschlags-Abfluss(N-A)-Prozesses mit flächendifferenzierten, prozessbasierten Modellen ist von zahlreichen Unsicherheiten beeinflusst. Diese Unsicherheiten resultieren hauptsächlich aus den genutzten Daten, die Messfehlern unterliegen sowie für eine flächendifferenzierte Modellierung entsprechend aufbereitet werden müssen, und der Abstraktion der natürlichen Prozesse im Modell selbst. Da N-A-Modelle in der hydrologischen Praxis vielfältig eingesetzt werden, sind Zuverlässigkeitsaussagen im Hinblick auf eine spezielle Anwendung nötig, um das Vertrauen in die Modellergebnisse zu festigen. Die neu entwickelte Strategie zur Analyse und Simulation der Unsicherheiten eines flächendifferenzierten, prozessbasierten N-A-Modells ermöglicht eine umfassende, globale und komponentenbasierte Unsicherheitsbestimmung. Am Beispiel des mesoskaligen Einzugsgebiets der Schwarzen Pockau/Pegel Zöblitz im mittleren Erzgebirge wird der Einfluss maßgebender Unsicherheiten im N-A-Prozess sowie deren Kombination zu einer Gesamt-Unsicherheit auf den Gebietsabfluss aufgezeigt. Zunächst werden die maßgebenden Unsicherheiten separat quantifiziert, wobei die folgenden Methoden eingesetzt werden: (i) Monte-Carlo Simulationen mit flächendifferenzierten stochastischen Bodenparametern zur Analyse des Einflusses unsicherer Bodeninformationen, (ii) Bayes’sche Inferenz und Markov-Ketten-Monte-Carlo Simulationen, die eine Unsicherheitsbestimmung der konzeptionellen Modellparameter der Abflussbildung und -konzentration ermöglichen und (iii) Monte-Carlo Simulationen mit stochastisch generierten Niederschlagsfeldern, die die raum-zeitliche Variabilität interpolierter Niederschlagsdaten beschreiben. Die Kombination der Unsicherheiten zu einer hydrologischen Unsicherheit und einer Gesamt-Unsicherheit erfolgt ebenfalls mit Monte-Carlo Methoden. Dieses Vorgehen ermöglicht die Korrelationen der Zufallsvariablen zu erfassen und die mehrdimensionale Abhängigkeitsstruktur innerhalb der Zufallsvariablen empirisch zu beschreiben. Die Ergebnisse zeigen für das Untersuchungsgebiet eine Dominanz der Unsicherheit aus der raum-zeitlichen Niederschlagsverteilung im Gebietsabfluss gefolgt von den Unsicherheiten aus den Bodeninformationen und den konzeptionellen Modellparametern. Diese Dominanz schlägt sich auch in der Gesamt-Unsicherheit nieder. Die aus Messdaten abgeleiteten Unsicherheiten weisen eine Heteroskedastizität auf, die durch den Prozessablauf geprägt ist. Weiterhin sind Indizien für eine Abhängigkeit der Unsicherheit von der Niederschlagsintensität sowie strukturelle Defizite des N-A-Modells sichtbar. Die neu entwickelte Strategie ist prinzipiell auf andere Gebiete und Modelle übertragbar. / Modelling rainfall-runoff (R-R) processes using deterministic, spatial distributed, process-based models is affected by numerous uncertainties. One major source of these uncertainties origins from measurement errors together with the errors occurring in the process of data processing. Inadequate representation of the governing processes in the model with respect to a given application is another source of uncertainty. Considering that R-R models are commonly used in the hydrologic practise a quantification of the uncertainties is essential for a realistic interpretation of the model results. The presented new framework allows for a comprehensive, total as well as component-based estimation of the uncertainties of model results from spatial distributed, process-based R-R modelling. The capabilities of the new framework to estimate the influence of the main sources of uncertainties as well as their combination to a total uncertainty is shown and analysed at the mesoscale catchment of the Schwarze Pockau of the Ore Mountains. The approach employs the following methods to quantify the uncertainties: (i) Monte Carlo simulations using spatial distributed stochastic soil parameters allow for the analysis of the impact of uncertain soil data (ii) Bayesian inference und Markov Chain Monte Carlo simulations, yield an estimate of the uncertainty of the conceptual model parameters governing the runoff formation and - concentration processes. (iii) Monte Carlo simulations using stochastically generated rainfall patterns describing the spatiotemporal variability of interpolated rainfall data. Monte Carlo methods are also employed to combine the single sources of uncertainties to a hydrologic uncertainty and a total uncertainty. This approach accounts for the correlations between the random variables as well as an empirical description of their multidimensional dependence structure. The example application shows a dominance of the uncertainty resulting from the spatio-temporal rainfall distribution followed by the uncertainties from the soil data and the conceptual model parameters with respect to runoff. This dominance is also reflected in the total uncertainty. The uncertainties derived from the data show a heteroscedasticity which is dominated by the process. Furthermore, the degree of uncertainty seems to depend on the rainfall intensity. The analysis of the uncertainties also indicates structural deficits of the R-R model. The developed framework can principally be transferred to other catchments as well as to other R-R models.

L'aménagement des versants méditerranéens en terrasses et en fossés avait pour but d'augmenter la surface agricole et de permettre une meilleure gestion de l'eau. La dégradation des terrasses et des drains peut conduire à une augmentation des risques d'inondation, d'érosion et de maintien des cultures. Pour améliorer la connaissance de l'impact réel sur la réponse hydrologique des versants, cette thèse suit différentes approches de modélisation. D'abord la réponse hydrologique d'un bassin versant méditerranéen (0.91 km2) avec des terrasses et des fossés aménagés est simulée à l'aide d'un modèle distribué, événementiel, à base physique, adapté aux bassins versants agricoles. La performance est très satisfaisante pour certains événements simulés, même si le modèle ne tient pas compte des terrasses. Afin de modéliser l'impact des terrasses agricoles et de l'écoulement artificiel, nous avons conçu un nouveau modèle distribué et parcimonieux qui utilise une distribution linéaire du temps de réponse, combiné avec l'hydrogramme unitaire instantané géomorphologique. Les simulations sur des versants et bassins virtuels avec un réseau non-optimal de drainage (non-OCN) montrent que (i) pour de longues interfaces entre une parcelle et un cours d'eau la réponse hydrologique est plus rapide et le débit de pointe plus élevé; (ii) la vitesse du ruissellement de surface a un plus grand impact sur le débit de pointe que la vitesse d'écoulement dans les fossés; et (iii) la densité de drainage accrue combinée avec la création de terrasses résulte en un débit de pointe plus élevé en aval et moins élevé en amont. / Terrace cultivation and artificial drainage were implemented on Mediterranean hillslopes for multiple reasons: agricultural terraces increase arable land surface and artificial drainage allows for better water management. Degradation of terraces and channels inevitably leads to an increase in flood risk, erosion and, eventually, crop damage. Little is known about their effect on hillslope hydrologic response, and therefore this thesis presents an integrated method where we compare different modelling approaches. We first simulated the hydrologic response of a Mediterranean catchment (0.91 km2) with terrace cultivation and artificial drainage using a physically-based, fully distributed storm flow model for agricultural catchments. Simulation performance is impressive for some storms, even though the model does not account for terraces. In order to model the effects of terrace cultivation and artificial drainage on hillslope hydrologic response explicitly, we subsequently developed a new distributed model with only geometric and flow velocity parameters, using a linear response time distribution combined with the hillslope geomorphologic instantaneous unit hydrograph. Simulations on virtual hillslopes and catchments with a non-optimal channel network suggest that (i) drainage is faster and attains higher peak flows for longer interface lengths between agricultural fields and drainage channels; (ii) overland flow velocity has greater influence on peak flow than channel flow velocity; and (iii) the combined effect of increased drainage density and introduction of terrace cultivation is enhanced peak flow at the outlet, and a reduction of peak flow from upstream terraces.

Cette thèse vise à explorer la question du changement d'échelle temporelle en modélisation hydrologique conceptuelle. Les principaux objectifs sont : (i) étudier les effets du changement du pas de temps sur les performances, les paramètres et la structure des modèles hydrologiques ; (ii) mettre au point un modèle pluie-débit applicable à différents pas de temps. Notre point de départ est le modèle global journalier GR4J, développé à Irstea. Ce modèle a été choisi comme le modèle de référence à adapter à d'autres résolutions plus fines, jusqu'à des pas de temps infra-horaires, en suivant une approche descendante. Pour nos tests, nous avons construit une base de données de 240 bassins versants non influencés en France, à différents pas de temps allant de 6 minutes à 1 jour, en utilisant: (i) les données pluviométriques à 6 minutes et la réanalyse des lames d'eau journalières à plus haute résolution spatiale ; (ii) les données de température journalière pour le calcul de l'évapotranspiration potentielle ; (iii) les données hydrométriques à pas de temps variable. Nous avons étudié l'impact de la distribution temporelle des entrées sur les performances du modèle en se focalisant sur la simulation de crue, sur la base de 2400 événements. Ensuite, notre évaluation du modèle a porté sur l'analyse de la cohérence des flux internes du modèle à différents pas de temps, afin d'assurer une performance satisfaisante à travers un fonctionnement du modèle cohérent. Notre diagnostic du modèle nous a permis d'identifier une amélioration de la structure du modèle à différents pas de temps infra-journaliers basée sur la complexification de la composante d'interception du modèle. / This thesis aims at exploring the question of temporal scaling in lumped conceptual hydrological modelling. The main objectives of the thesis are to: (i) study the effects of varying the modelling time step on the performance, parameters and structure of hydrological models; (ii) develop a hydrological model operating at different time steps, from daily to sub-hourly, through a unified, robust and coherent modelling framework at different time scales. Our starting point is the chain of conceptual rainfall-runoff models called ‘GR’, developed at Irstea, and in particular the daily ‘GR4J’ lumped model. The GR4J model will be the baseline model to be effectively downscaled up to sub-hourly time steps following a top-down approach. An hourly adaptation of this model had already been proposed in previous research studies, but some questions on the optimality of the structure at sub-daily time steps were still open. This thesis builds on these previous studies on the hourly model and responds to the operational expectations of improving and adapting the model at multiple sub-daily and sub-hourly time steps, which is particularly interesting for flood forecasting applications. For our modelling tests, we built a database of 240 unregulated catchments in metropolitan France, at multiple time steps, from 6-minute to 1 day, using fine time step hydro-climatic datasets available: (i) 6-min rain gauges and higher spatial-density daily reanalysis data for precipitation; (ii) daily temperature data for potential evapotranspiration (making assumptions on sub-daily patterns); (iii) sub-hourly variable time step streamflow data. We investigated the impact of the inputs temporal distribution on model outputs and performance in a flood simulation perspective based on 2400 selected flood events. Then our model evaluation focused on the consistency of model internal fluxes at different time steps, in order to ensure obtaining a satisfactory model performance by a coherent model functioning at multiple time steps. Our model diagnosis led us to identify and test a significant improvement of the model structure at sub-daily time steps based on the complexification of the interception component of the model. Thus, we propose a new version of the model at multiple sub-daily time steps, with the addition of an interception store without extra free parameters. Our tests also confirm the suitability at multiple time steps of a modified groundwater exchange function proposed earlier, leading to overall improved model accuracy and coherence.

Die deterministische Modellierung des Niederschlags-Abfluss(N-A)-Prozesses mit flächendifferenzierten, prozessbasierten Modellen ist von zahlreichen Unsicherheiten beeinflusst. Diese Unsicherheiten resultieren hauptsächlich aus den genutzten Daten, die Messfehlern unterliegen sowie für eine flächendifferenzierte Modellierung entsprechend aufbereitet werden müssen, und der Abstraktion der natürlichen Prozesse im Modell selbst. Da N-A-Modelle in der hydrologischen Praxis vielfältig eingesetzt werden, sind Zuverlässigkeitsaussagen im Hinblick auf eine spezielle Anwendung nötig, um das Vertrauen in die Modellergebnisse zu festigen. Die neu entwickelte Strategie zur Analyse und Simulation der Unsicherheiten eines flächendifferenzierten, prozessbasierten N-A-Modells ermöglicht eine umfassende, globale und komponentenbasierte Unsicherheitsbestimmung. Am Beispiel des mesoskaligen Einzugsgebiets der Schwarzen Pockau/Pegel Zöblitz im mittleren Erzgebirge wird der Einfluss maßgebender Unsicherheiten im N-A-Prozess sowie deren Kombination zu einer Gesamt-Unsicherheit auf den Gebietsabfluss aufgezeigt. Zunächst werden die maßgebenden Unsicherheiten separat quantifiziert, wobei die folgenden Methoden eingesetzt werden: (i) Monte-Carlo Simulationen mit flächendifferenzierten stochastischen Bodenparametern zur Analyse des Einflusses unsicherer Bodeninformationen, (ii) Bayes’sche Inferenz und Markov-Ketten-Monte-Carlo Simulationen, die eine Unsicherheitsbestimmung der konzeptionellen Modellparameter der Abflussbildung und -konzentration ermöglichen und (iii) Monte-Carlo Simulationen mit stochastisch generierten Niederschlagsfeldern, die die raum-zeitliche Variabilität interpolierter Niederschlagsdaten beschreiben. Die Kombination der Unsicherheiten zu einer hydrologischen Unsicherheit und einer Gesamt-Unsicherheit erfolgt ebenfalls mit Monte-Carlo Methoden. Dieses Vorgehen ermöglicht die Korrelationen der Zufallsvariablen zu erfassen und die mehrdimensionale Abhängigkeitsstruktur innerhalb der Zufallsvariablen empirisch zu beschreiben. Die Ergebnisse zeigen für das Untersuchungsgebiet eine Dominanz der Unsicherheit aus der raum-zeitlichen Niederschlagsverteilung im Gebietsabfluss gefolgt von den Unsicherheiten aus den Bodeninformationen und den konzeptionellen Modellparametern. Diese Dominanz schlägt sich auch in der Gesamt-Unsicherheit nieder. Die aus Messdaten abgeleiteten Unsicherheiten weisen eine Heteroskedastizität auf, die durch den Prozessablauf geprägt ist. Weiterhin sind Indizien für eine Abhängigkeit der Unsicherheit von der Niederschlagsintensität sowie strukturelle Defizite des N-A-Modells sichtbar. Die neu entwickelte Strategie ist prinzipiell auf andere Gebiete und Modelle übertragbar. / Modelling rainfall-runoff (R-R) processes using deterministic, spatial distributed, process-based models is affected by numerous uncertainties. One major source of these uncertainties origins from measurement errors together with the errors occurring in the process of data processing. Inadequate representation of the governing processes in the model with respect to a given application is another source of uncertainty. Considering that R-R models are commonly used in the hydrologic practise a quantification of the uncertainties is essential for a realistic interpretation of the model results. The presented new framework allows for a comprehensive, total as well as component-based estimation of the uncertainties of model results from spatial distributed, process-based R-R modelling. The capabilities of the new framework to estimate the influence of the main sources of uncertainties as well as their combination to a total uncertainty is shown and analysed at the mesoscale catchment of the Schwarze Pockau of the Ore Mountains. The approach employs the following methods to quantify the uncertainties: (i) Monte Carlo simulations using spatial distributed stochastic soil parameters allow for the analysis of the impact of uncertain soil data (ii) Bayesian inference und Markov Chain Monte Carlo simulations, yield an estimate of the uncertainty of the conceptual model parameters governing the runoff formation and - concentration processes. (iii) Monte Carlo simulations using stochastically generated rainfall patterns describing the spatiotemporal variability of interpolated rainfall data. Monte Carlo methods are also employed to combine the single sources of uncertainties to a hydrologic uncertainty and a total uncertainty. This approach accounts for the correlations between the random variables as well as an empirical description of their multidimensional dependence structure. The example application shows a dominance of the uncertainty resulting from the spatio-temporal rainfall distribution followed by the uncertainties from the soil data and the conceptual model parameters with respect to runoff. This dominance is also reflected in the total uncertainty. The uncertainties derived from the data show a heteroscedasticity which is dominated by the process. Furthermore, the degree of uncertainty seems to depend on the rainfall intensity. The analysis of the uncertainties also indicates structural deficits of the R-R model. The developed framework can principally be transferred to other catchments as well as to other R-R models.

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.<br /> 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.<br /> The study area is the Federal State of Ceará (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. <br /> 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.<br /> 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.<br /> Further model components of Wasa which respect specific features of semi-arid hydrology are: <br /> (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. <br /> (2) The infiltration module represents in particular infiltration-excess surface runoff as the dominant runoff component. <br /> (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. <br /> (4) A model for the quantification of water withdrawal by water use in different sectors is coupled to Wasa. <br /> (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.<br /> All model parameters of Wasa can be derived from physiographic information of the study area. Thus, model calibration is primarily not required.<br /> 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.<br /> Further results of model applications are:<br /> (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.<br /> (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.<br /> 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:<br /> (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.<br /> (2) The uncertainty of soil parameters is in general of larger importance on model uncertainty than uncertainty of vegetation or topographic parameters.<br /> (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.<br /> (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.<br /> 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. / Semiaride Gebiete sind auf Grund der klimatischen Bedingungen durch geringe Wasserressourcen gekennzeichnet. Ein zukünftig steigender Wasserbedarf in Folge von Bevölkerungswachstum und ökonomischer Entwicklung sowie eine geringere Wasserverfügbarkeit durch mögliche Klimaänderungen können dort zu einer Verschärfung der vielfach schon heute auftretenden Wasserknappheit führen. Das Verständnis der Mechanismen und Wechselwirkungen des komplexen Systems von Mensch und Umwelt sowie die quantitative Bestimmung zukünftiger Veränderungen in der Menge, der zeitlichen Verteilung und der Qualität von Wasserressourcen sind eine grundlegende Voraussetzung für die Entwicklung von nachhaltigen Maßnahmen des Wassermanagements mit dem Ziel einer höheren Anpassungsfähigkeit dieser Regionen gegenüber künftigen Änderungen. Hierzu sind dynamische integrierte Modelle unerlässlich, die als eine Komponente ein hydrologisches Modell beinhalten. <br /> Vorrangiges Ziel dieser Arbeit ist daher die Erstellung eines hydrologischen Modells zur großräumigen Bestimmung der Wasserverfügbarkeit unter sich ändernden Umweltbedingungen in semiariden Gebieten.<br /> Als Untersuchungsraum dient der im semiariden tropischen Nordosten Brasiliens gelegene Bundestaat Ceará (150 000 km2). Die mittleren Jahresniederschläge in diesem Gebiet liegen bei 850 mm innerhalb einer etwa fünfmonatigen Regenzeit. Mit vorwiegend kristallinem Grundgebirge und geringmächtigen Böden stellt Oberflächenwasser den größten Teil der Wasserversorgung bereit. Die Region war wiederholt von Dürren betroffen, die zu schweren ökonomischen Schäden und sozialen Folgen wie Migration aus den ländlichen Gebieten geführt haben. <br /> Das hier entwickelte hydrologische Modell Wasa (Model of Water Availability in Semi-Arid Environments) ist ein deterministisches, flächendifferenziertes Modell, das aus konzeptionellen, prozess-basierten Ansätzen aufgebaut ist. Die Wasserverfügbarkeit (Abfluss im Gewässernetz, Speicherung in Stauseen, Bodenfeuchte) wird mit täglicher Auflösung bestimmt. Als räumliche Zieleinheiten können Teileinzugsgebiete, Rasterzellen oder administrative Einheiten (Gemeinden) gewählt werden. Letztere ermöglichen die Kopplung des Modells im Rahmen der integrierten Modellierung mit Modulen, die nicht auf der Basis natürlicher Raumeinheiten arbeiten.<br /> Im Rahmen eines neuen skalenübergreifenden, hierarchischen Ansatzes werden in Wasa die genannten Zieleinheiten in kleinere räumliche Modellierungseinheiten unterteilt. Die ausgewiesenen Landschaftseinheiten erfassen insbesondere die strukturierte Variabilität von Gelände-, Boden- und Vegetationseigenschaften entlang von Toposequenzen in ihrem Einfluss auf Bodenfeuchte und Abflussbildung. Laterale hydrologische Prozesse auf kleiner Skala, wie die für semiaride Bedingungen bedeutsame Wiederversickerung von Oberflächenabfluss, können somit auch in der erforderlichen großskaligen Modellanwendung vereinfacht wiedergegeben werden. In Abhängigkeit von der Auflösung der verfügbaren Daten wird in Wasa die kleinskalige Variabilität nicht räumlich explizit sondern über die Verteilung von Flächenanteilen subskaliger Einheiten und über statistische Übergangshäufigkeiten für laterale Flüsse zwischen den Einheiten berücksichtigt.<br /> Weitere Modellkomponenten von Wasa, die spezifische Bedingungen semiarider Gebiete berücksichtigen, sind: <br /> (1) Ein Zwei-Schichten-Modell zur Bestimmung der Evapotranspiration berücksichtigt auch den Energieumsatz an der Bodenoberfläche (inklusive Bodenverdunstung), der in Anbetracht der meist lichten Vegetationsbedeckung von Bedeutung ist. Die Vegetationsparameter werden zudem flächen- und zeitdifferenziert in Abhängigkeit vom Auftreten der Regenzeit modifiziert. <br /> (2) Das Infiltrationsmodul bildet insbesondere Oberflächenabfluss durch Infiltrationsüberschuss als dominierender Abflusskomponente ab. <br /> (3) Zur aggregierten Beschreibung der Wasserbilanz von im Modell nicht einzeln erfassbaren Stauseen wird ein Speichermodell unter Berücksichtigung verschiedener Größenklassen und ihrer Interaktion über das Gewässernetz eingesetzt. <br /> (4) Ein Modell zur Bestimmung der Entnahme durch Wassernutzung in verschiedenen Sektoren ist an Wasa gekoppelt. <br /> (5) Ein Kaskadenmodell zur zeitlichen Disaggregierung von Niederschlagszeitreihen, das in dieser Arbeit speziell für tropische konvektive Niederschlagseigenschaften angepasst wird, wird zur Erzeugung höher aufgelöster Niederschlagsdaten verwendet.<br /> Alle Modellparameter von Wasa können von physiographischen Gebietsinformationen abgeleitet werden, sodass eine Modellkalibrierung primär nicht erforderlich ist. <br /> Die Modellanwendung von Wasa für historische Zeitreihen ergibt im Allgemeinen eine gute Übereinstimmung der Simulationsergebnisse für Abfluss und Stauseespeichervolumen mit Beobachtungsdaten in unterschiedlich großen Einzugsgebieten. Die mittlere Wasserbilanz sowie die hohe monatliche und jährliche Variabilität wird vom Modell angemessen wiedergegeben. Die Grenzen der Anwendbarkeit des Modell-konzepts zeigen sich am deutlichsten in Teilgebieten mit Abflusskomponenten aus tieferen Grundwasserleitern, deren Dynamik ohne Kalibrierung nicht zufriedenstellend abgebildet werden kann.<br /> Die Modellanwendungen zeigen weiterhin:<br /> (1) Laterale Prozesse der Umverteilung von Bodenfeuchte und Abfluss auf der Hangskala, vor allem die Wiederversickerung von Oberflächenabfluss, führen auf der Skala von Einzugsgebieten zu deutlich kleineren Abflussvolumen als die einfache Summe der Abflüsse der Teilflächen. Diese Prozesse sollten daher auch in großskaligen Modellen abgebildet werden. Die unterschiedliche Ausprägung dieser Prozesse für unterschiedliche Bedingungen zeigt sich an Hand einer prozentual größeren Verringerung der Abflussvolumen in trockenen im Vergleich zu feuchten Jahren.<br /> (2) Die Niederschlagseigenschaften haben einen sehr großen Einfluss auf die hydrologische Reaktion in semiariden Gebieten. Insbesondere die durch die grobe zeitliche Auflösung des Modells und durch Interpolationseffekte unterschätzten Niederschlagsintensitäten in den Eingangsdaten und die daraus folgende Unterschätzung von Abflussvolumen müssen im Modell kompensiert werden. Ein Skalierungsfaktor in der Infiltrationsroutine oder die Verwendung disaggregierter stündlicher Niederschlagsdaten zeigen hier gute Ergebnisse.<br /> Die Simulationsergebnisse mit Wasa sind insgesamt durch große Unsicherheiten gekennzeichnet. Diese sind einerseits in Unsicherheiten der Modellstruktur zur adäquaten Beschreibung der relevanten hydrologischen Prozesse begründet, andererseits in Daten- und Parametersunsicherheiten in Anbetracht der geringen Datenverfügbarkeit. Von besonderer Bedeutung ist: <br /> (1) Die Unsicherheit der Niederschlagsdaten in ihrem räumlichen Muster und ihrer zeitlichen Struktur hat wegen der stark nicht-linearen hydrologischen Reaktion einen großen Einfluss auf die Simulationsergebnisse.<br /> (2) Die Unsicherheit von Bodenparametern hat im Vergleich zu Vegetationsparametern und topographischen Parametern im Allgemeinen einen größeren Einfluss auf die Modellunsicherheit.<br /> (3) Der Effekt der Unsicherheit einzelner Modellkomponenten und -parameter ist für Jahre mit unter- oder überdurchschnittlichen Niederschlagsvolumen zumeist unterschiedlich, da einzelne hydrologische Prozesse dann jeweils unterschiedlich relevant sind. Die Unsicherheit einzelner Modellkomponenten- und parameter hat somit eine unterschiedliche Bedeutung für die Unsicherheit von Szenarienrechnungen mit steigenden oder fallenden Niederschlagstrends.<br /> (4) Der bedeutendste Unsicherheitsfaktor für Szenarien der Wasserverfügbarkeit für die Untersuchungsregion ist die Unsicherheit der den regionalen Klimaszenarien zu Grunde liegenden Ergebnisse globaler Klimamodelle. Eine deutliche Zunahme oder Abnahme der Niederschläge bis 2050 kann gemäß den hier vorliegenden Daten für das Untersuchungsgebiet gleichermaßen angenommen werden.<br /> Modellsimulationen für Klimaszenarien bis zum Jahr 2050 ergeben, dass eine mögliche zukünftige Veränderung der Niederschlagsmengen zu einer prozentual zwei- bis dreifach größeren Veränderung der Abflussvolumen führt. Im Falle eines Trends von abnehmenden Niederschlagsmengen besteht in der Untersuchungsregion die Tendenz, dass auf Grund der gegenseitigen Beeinflussung der großen Zahl von Stauseen beim Rückhalt der tendenziell abnehmenden Abflussvolumen die Effizienz von neugebauten Stauseen zur Sicherung der Wasserverfügbarkeit zunehmend geringer wird.

The Wadi Dhuliel catchment/ North east Jordan, as any other arid area has distinctive hydrological features with limited water resources. The hydrological regime is characterized by high variability of temporal and spatial rainfall distributions, flash floods, absence of base flow, and high rates of evapotranspiration. The aim of this Ph.D. thesis was to apply lumped and distributed models to simulate stream flow in the Wadi Dhuliel arid catchment. Intensive research was done to estimate the spatial and temporal rainfall distributions using remote sensing. Because most rainfall-runoff models were undertaken for other climatic zones, an attempt was made to study limitations and challenges and improve rainfall-runoff modeling in arid areas in general and for the Wadi Dhuliel in particular. The thesis is divided into three hierarchically ordered research topics. In the first part and research paper, the metric conceptual IHACRES model was applied to daily and storm events time scales, including data from 19 runoff events during the period 1986-1992. The IHACRES model was extended for snowfall in order to cope with such extreme events. The performance of the IHACRES model on daily data was rather poor while the performance on the storm events scale shows a good agreement between observed and simulated streamflow. The modeled outputs were expected to be sensitive when the observed flood was relatively small. The optimum parameter values were influenced by the length of a time series used for calibration and event specific changes. In the second research paper, the Global Satellite Mapping of Precipitation (GSMaP_MVK+) dataset was used to evaluate the precipitation rates over the Wadi Dhuliel arid catchment for the period from January 2003 to March 2008. Due to the scarcity of the ground rain gauge network, the detailed structure of the rainfall distribution was inadequate, so an independent from interpolation techniques was used. Three meteorological stations and six rain gauges were used to adjust and compare with GSMaP_MVK+ estimates. Comparisons between GSMaP_MVK+ measurements and ground rain gauge records show distinct regions of correlation, as well as areas where GSMaP_MVK+ systematically over- and underestimated ground rain gauge records. A multiple linear regression (MLR) model was used to derive the relationship between rainfall and GSMaP_MVK+ in conjunction with temperature, relative humidity, and wind speed. The MLR equations were defined for the three meteorological stations. The ‘best’ fit of the MLR model for each station was chosen and used to interpolate a multiscale temporal and spatial distribution. Results show that the rainfall distribution over the Wadi Dhuliel is characterized by clear west-east and north-south gradients. Estimates from the monthly MLR model were more reliable than estimates obtained using daily data. The adjusted GSMaP_MVK+ dataset performed well in capturing the spatial patterns of the rainfall at monthly and annual time scales, while daily estimation showed some weakness for light and moderate storms. In the third research paper, the HEC-HMS and IHACRES rainfall runoff models were applied to simulate a single streamflow event in the Wadi Dhuliel catchment that occurred in 30-31.01.2008. Both models are considered suitable for arid conditions. The HEC-HMS model application was done in conjunction with the HEC-GeoHMS extension in ArcView 3.3. Streamflow estimation was performed on hourly data. The aim of this study was to develop a new framework of rainfall-runoff model applications in arid catchment by integrating a re-adjusted satellite derived rainfall dataset (GSMaP_MVK+) to determine the location of the rainfall storm. Each model has its own input data sets. HEC-HMS input data include soil type, land use/land cover map, and slope map. IHACRES input data sets include hourly rainfall and temperature. The model was calibrated and validated using observed stream flow data collected from Al-Za’atari discharge station. IHACRES shows some weaknesses, while the flow comparison between the calibrated streamflow results agrees well with the observed streamflow data of the HEC-HMS model. The Nash-Sutcliffe efficiency (Ef) for both models was 0.51, and 0.88 respectively. The application of HEC-HMS model in this study is considered to be satisfactory.

The Wadi Dhuliel catchment/ North east Jordan, as any other arid area has distinctive hydrological features with limited water resources. The hydrological regime is characterized by high variability of temporal and spatial rainfall distributions, flash floods, absence of base flow, and high rates of evapotranspiration. The aim of this Ph.D. thesis was to apply lumped and distributed models to simulate stream flow in the Wadi Dhuliel arid catchment. Intensive research was done to estimate the spatial and temporal rainfall distributions using remote sensing. Because most rainfall-runoff models were undertaken for other climatic zones, an attempt was made to study limitations and challenges and improve rainfall-runoff modeling in arid areas in general and for the Wadi Dhuliel in particular. The thesis is divided into three hierarchically ordered research topics. In the first part and research paper, the metric conceptual IHACRES model was applied to daily and storm events time scales, including data from 19 runoff events during the period 1986-1992. The IHACRES model was extended for snowfall in order to cope with such extreme events. The performance of the IHACRES model on daily data was rather poor while the performance on the storm events scale shows a good agreement between observed and simulated streamflow. The modeled outputs were expected to be sensitive when the observed flood was relatively small. The optimum parameter values were influenced by the length of a time series used for calibration and event specific changes. In the second research paper, the Global Satellite Mapping of Precipitation (GSMaP_MVK+) dataset was used to evaluate the precipitation rates over the Wadi Dhuliel arid catchment for the period from January 2003 to March 2008. Due to the scarcity of the ground rain gauge network, the detailed structure of the rainfall distribution was inadequate, so an independent from interpolation techniques was used. Three meteorological stations and six rain gauges were used to adjust and compare with GSMaP_MVK+ estimates. Comparisons between GSMaP_MVK+ measurements and ground rain gauge records show distinct regions of correlation, as well as areas where GSMaP_MVK+ systematically over- and underestimated ground rain gauge records. A multiple linear regression (MLR) model was used to derive the relationship between rainfall and GSMaP_MVK+ in conjunction with temperature, relative humidity, and wind speed. The MLR equations were defined for the three meteorological stations. The ‘best’ fit of the MLR model for each station was chosen and used to interpolate a multiscale temporal and spatial distribution. Results show that the rainfall distribution over the Wadi Dhuliel is characterized by clear west-east and north-south gradients. Estimates from the monthly MLR model were more reliable than estimates obtained using daily data. The adjusted GSMaP_MVK+ dataset performed well in capturing the spatial patterns of the rainfall at monthly and annual time scales, while daily estimation showed some weakness for light and moderate storms. In the third research paper, the HEC-HMS and IHACRES rainfall runoff models were applied to simulate a single streamflow event in the Wadi Dhuliel catchment that occurred in 30-31.01.2008. Both models are considered suitable for arid conditions. The HEC-HMS model application was done in conjunction with the HEC-GeoHMS extension in ArcView 3.3. Streamflow estimation was performed on hourly data. The aim of this study was to develop a new framework of rainfall-runoff model applications in arid catchment by integrating a re-adjusted satellite derived rainfall dataset (GSMaP_MVK+) to determine the location of the rainfall storm. Each model has its own input data sets. HEC-HMS input data include soil type, land use/land cover map, and slope map. IHACRES input data sets include hourly rainfall and temperature. The model was calibrated and validated using observed stream flow data collected from Al-Za’atari discharge station. IHACRES shows some weaknesses, while the flow comparison between the calibrated streamflow results agrees well with the observed streamflow data of the HEC-HMS model. The Nash-Sutcliffe efficiency (Ef) for both models was 0.51, and 0.88 respectively. The application of HEC-HMS model in this study is considered to be satisfactory.

The Håga river, located west of the Swedish city Uppsala, is currently without a proper gauging station. Knowing the streamflow is nonetheless important to, for example, be able to calculate the nutrient transport in the river. This project aimed to evaluate different indirect methods of streamflow estimation to investigate how they perform, in particular in relation to SMHI’s S-HYPE model. Two of the methods used were based on transferring streamflow of nearby catchments to Håga, either by using relationships between the mean and standard deviation of the streamflow time series (MOVE), or by simply scaling relative to catchment size (DAR). Furthermore, a hydrological model, HBV, was calibrated for Håga using different amounts and types of calibration data. All the methods were then compared to streamflow data from a previously active gauging station in Håga.  It was found that the overall best method to estimate the streamflow in Håga was using the MOVE method with one particular donor catchment. However, the performance of the simpler MOVE and DAR methods varied a lot from catchment to catchment. HBV was found to be able to produce better performing simulations than S-HYPE, despite being a simpler model. Even HBV-calibrations using alternative or limited data could perform rather well, although rarely at the level of a calibration utilising all available streamflow data. A big uncertainty of the study was the fact that the most recent available validation data for the Håga catchment was from two decades ago, when the old gauging station was decommissioned. Most likely the methods that worked well during the 90s would work well today as well, but this is a matter that could be studied further. / Hågaån, ett vattendrag som ligger väster om Uppsala, saknar i nuläget en mätstation för vattenföring. Att känna till flödet är dock ändå intressant, bland annat för att kunna beräkna näringstransporten i ån. Syftet med detta projekt var därmed att utvärdera och jämföra olika metoder för att uppskatta vattenflödet i Hågaån, särskilt för att undersöka hur de presterade i jämförelse med SMHI:s S-HYPE-modell. Två av metoderna som användes för detta baserades på att överföra flöden från närliggande vattendrag till Håga, antingen genom att använda förhållanden mellan medelvärde och standardavvikelse för flödes-datan (MOVE), eller genom att bara utgå från skillnader i områdenas storlek (DAR). Utöver det kalibrerades även den hydrologiska modellen HBV för Håga med olika typer och mängder av kalibreringsdata. Alla metoderna jämfördes sedan med data från en mätstation som tidigare funnits i Hågaån. Resultaten visade att den över lag bästa metoden för att uppskatta flödet i Håga var MOVE-metoden i kombination med ett av de närliggande vattendragen. Hur väl dessa simplare MOVE- och DAR-metoder presterade varierade dock mycket beroende på vilket vattendrag som användes som donator. Det visade sig även att det gick att erhålla bättre resultat med HBV än de som gavs av S-HYPE, trots att HBV är en enklare modell. Även HBV-kalibreringar baserade på alternativ eller begränsad data kunde producera välpresterande simulationer, dock sällan på samma nivå som den kalibrering som använt all tillgänglig flödesdata. En stor osäkerhet i projektet kretsar kring att den nyaste tillgängliga valideringsdatan från Hågaån var över två decennier gammal, då den mätstation som funnits stängdes ner. Med stor sannolikhet kommer metoderna som fungerade väl under 90-talet även fungera bra i modern tid, men detta är något som kräver vidare studier.