<p><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">The most significant human impacts on the hydrological system are due to land-use change. The conversion of land to agricultural, mining, industrial, or residential uses significantly alters the hydrological characteristics of the land surface and modifies pathways and rates of water flow. If this occurs over large or critical areas of a catchment, it can have significant short and long-term impacts, on the quality of water. While there are methods available to quantify the pollutants in surface water, methods of linking non-point source pollution to water quality at catchment scale are lacking. Therefore, the research presented in this thesis investigated modelling techniques to estimate the effect of land-cover type on water quality. The main goal of the study was to contribute towards improving the understanding of how different land-covers in an urbanizing catchment affect surface water quality. The aim of the research presented in this thesis was to explain how the quality of surface runoff varies on different land-cover types and to provide guidelines for minimizing water pollution that may be occurring in the Kuils-Eerste River catchment. The research objectives were / (1) to establish types and spatial distribution of land-cover types within the Kuils-Eerste River catchment, (2) to establish water quality characteristics of surface runoff from specific land-cover types at the experimental plot level, (3) to establish the contribution of each land-cover type to pollutant loads at the catchment scale.<span style="mso-spacerun:yes"> </span><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">Land-cover characteristics and water quality were investigated using GIS and Remote Sensing tools. The application of these tools resulted in the development of a land-cover map with 36 land classifications covering the whole catchment. Land-cover in the catchment is predominantly agricultural with vineyards and grassland covering the northern section of the catchment. Vineyards occupy over 35% of the total area followed by fynbos (indigenous vegetation) (12.5 %), open hard rock area (5.8 %), riparian forest (5.2 %), mountain forest<span style="mso-spacerun:yes">&nbsp / &nbsp / </span>(5 %), dense scrub (4.4 %), and improved grassland (3.6 %). The residential area covers about 14 %. Roads cover 3.4 % of the total area. </span><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">Surface runoff is responsible for the transportation of large quantities of pollutants that affect the quality of water in the Kuils-Eerste River catchment. The different land-cover types and the distribution and concentration levels of the pollutants are not uniform. Experimental work was conducted at plot scale to understand whether land-cover types differed in their contributions to the concentration of water quality attributes emerging from them.<span style="color:black"> Four plots each with a length of 10 m to 12 m and 5 m width were set up. Plot I was set up on open grassland, Plot II represented the vineyards, Plot III covered the mountain forests, and Plot IV represented the fynbos land-cover.</span> Soil samples analyzed from the experimental plots fell in the category of sandy soil (Sa) with the top layer of Plot IV (fynbos) having loamy sand (LmSa). The soil particle sizes range between fine sand (59.1 % and 78.9 %) to coarse sand (between 7 % and 22 %). The content of clay and silt was between 0.2 % and 2.4 %. Medium sand was between 10.7 % and 17.6 %. In terms of vertical distribution of the particle sizes, a general decrease with respect to the size of particles was noted from the top layer (15 cm) to the bottom layer (30 cm) for all categories of the particle sizes. There was variation in particle size with depth and location within the experimental plots.</span><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">Two primary methods of collecting water samples were used / grab sampling and composite sampling. The quality of water as represented by the samples collected during storm events during the rainfall season of 2006 and 2007 was<span style="mso-spacerun:yes">&nbsp / </span>used to establish <span style="mso-spacerun:yes">&nbsp / </span>water quality characteristics for the different land-cover types. The concentration of total average suspended solids was highest in the following land-cover types, cemeteries (5.06 mg L^-1), arterial roads/main roads (3.94 mg L^-1), low density residential informal squatter camps (3.21 mg L^-1) and medium density residential informal townships (3.21 mg L^-1). Chloride concentrations were high on the following land-cover types, recreation grass/ golf course (2.61 mg L^-1), open area/barren land (1.59 mg L^-1), and improved grassland/vegetation crop (1.57 mg L^-1). The event mean concentration (EMC) values for NO₃-N were high on commercial mercantile (6 mg L^-1) and water channel (5 mg L^-1). The total phosphorus concentration mean values recorded high values on improved grassland/vegetation crop (3.78 mg L^-1), medium density residential informal townships (3mgL^-1) and low density residential informal squatter camps (3 mg L^-1). Surface runoff may also contribute soil particles into rivers during rainfall events, particularly from areas of disturbed soil, for example areas where market gardening is taking place. The study found that different land cover types contributed differently to nonpoint source pollution. </span><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">A GIS model was used to estimate the diffuse pollution of five pollutants (chloride, phosphorus, TSS, nitrogen and NO₃-N) in response to land cover variation using water quality data. The GIS model linked land cover information to diffuse nutrient signatures in response to surface runoff using the Curve Number method and EMC data were developed. Two models (RINSPE and N-SPECT) were used to estimate nonpoint source pollution using various GIS databases. The outputs from the GIS-based model were compared with recommended water quality standards. It was found that the RINSPE model gave accurate results in cases where NPS pollution dominate the total pollutant inputs over a given land cover type. However, the N-SPECT model simulations were too uncertain in cases where there were large numbers of land cover types with diverse NPS pollution load. All land-cover types with concentration values above the recommended national water quality standard were considered as areas that needed measures to mitigate the adverse effects of nonpoint pollution. </span><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">The expansion of urban areas and agricultural land has a direct effect on land cover types within the catchment. 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<p><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">The most significant human impacts on the hydrological system are due to land-use change. The conversion of land to agricultural, mining, industrial, or residential uses significantly alters the hydrological characteristics of the land surface and modifies pathways and rates of water flow. If this occurs over large or critical areas of a catchment, it can have significant short and long-term impacts, on the quality of water. While there are methods available to quantify the pollutants in surface water, methods of linking non-point source pollution to water quality at catchment scale are lacking. Therefore, the research presented in this thesis investigated modelling techniques to estimate the effect of land-cover type on water quality. The main goal of the study was to contribute towards improving the understanding of how different land-covers in an urbanizing catchment affect surface water quality. The aim of the research presented in this thesis was to explain how the quality of surface runoff varies on different land-cover types and to provide guidelines for minimizing water pollution that may be occurring in the Kuils-Eerste River catchment. The research objectives were / (1) to establish types and spatial distribution of land-cover types within the Kuils-Eerste River catchment, (2) to establish water quality characteristics of surface runoff from specific land-cover types at the experimental plot level, (3) to establish the contribution of each land-cover type to pollutant loads at the catchment scale.<span style="mso-spacerun:yes"> </span><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">Land-cover characteristics and water quality were investigated using GIS and Remote Sensing tools. The application of these tools resulted in the development of a land-cover map with 36 land classifications covering the whole catchment. Land-cover in the catchment is predominantly agricultural with vineyards and grassland covering the northern section of the catchment. Vineyards occupy over 35% of the total area followed by fynbos (indigenous vegetation) (12.5 %), open hard rock area (5.8 %), riparian forest (5.2 %), mountain forest<span style="mso-spacerun:yes">&nbsp / &nbsp / </span>(5 %), dense scrub (4.4 %), and improved grassland (3.6 %). The residential area covers about 14 %. Roads cover 3.4 % of the total area. </span><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">Surface runoff is responsible for the transportation of large quantities of pollutants that affect the quality of water in the Kuils-Eerste River catchment. The different land-cover types and the distribution and concentration levels of the pollutants are not uniform. Experimental work was conducted at plot scale to understand whether land-cover types differed in their contributions to the concentration of water quality attributes emerging from them.<span style="color:black"> Four plots each with a length of 10 m to 12 m and 5 m width were set up. Plot I was set up on open grassland, Plot II represented the vineyards, Plot III covered the mountain forests, and Plot IV represented the fynbos land-cover.</span> Soil samples analyzed from the experimental plots fell in the category of sandy soil (Sa) with the top layer of Plot IV (fynbos) having loamy sand (LmSa). The soil particle sizes range between fine sand (59.1 % and 78.9 %) to coarse sand (between 7 % and 22 %). The content of clay and silt was between 0.2 % and 2.4 %. Medium sand was between 10.7 % and 17.6 %. In terms of vertical distribution of the particle sizes, a general decrease with respect to the size of particles was noted from the top layer (15 cm) to the bottom layer (30 cm) for all categories of the particle sizes. There was variation in particle size with depth and location within the experimental plots.</span><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">Two primary methods of collecting water samples were used / grab sampling and composite sampling. The quality of water as represented by the samples collected during storm events during the rainfall season of 2006 and 2007 was<span style="mso-spacerun:yes">&nbsp / </span>used to establish <span style="mso-spacerun:yes">&nbsp / </span>water quality characteristics for the different land-cover types. The concentration of total average suspended solids was highest in the following land-cover types, cemeteries (5.06 mg L^-1), arterial roads/main roads (3.94 mg L^-1), low density residential informal squatter camps (3.21 mg L^-1) and medium density residential informal townships (3.21 mg L^-1). Chloride concentrations were high on the following land-cover types, recreation grass/ golf course (2.61 mg L^-1), open area/barren land (1.59 mg L^-1), and improved grassland/vegetation crop (1.57 mg L^-1). The event mean concentration (EMC) values for NO₃-N were high on commercial mercantile (6 mg L^-1) and water channel (5 mg L^-1). The total phosphorus concentration mean values recorded high values on improved grassland/vegetation crop (3.78 mg L^-1), medium density residential informal townships (3mgL^-1) and low density residential informal squatter camps (3 mg L^-1). Surface runoff may also contribute soil particles into rivers during rainfall events, particularly from areas of disturbed soil, for example areas where market gardening is taking place. The study found that different land cover types contributed differently to nonpoint source pollution. </span><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">A GIS model was used to estimate the diffuse pollution of five pollutants (chloride, phosphorus, TSS, nitrogen and NO₃-N) in response to land cover variation using water quality data. The GIS model linked land cover information to diffuse nutrient signatures in response to surface runoff using the Curve Number method and EMC data were developed. Two models (RINSPE and N-SPECT) were used to estimate nonpoint source pollution using various GIS databases. The outputs from the GIS-based model were compared with recommended water quality standards. It was found that the RINSPE model gave accurate results in cases where NPS pollution dominate the total pollutant inputs over a given land cover type. However, the N-SPECT model simulations were too uncertain in cases where there were large numbers of land cover types with diverse NPS pollution load. All land-cover types with concentration values above the recommended national water quality standard were considered as areas that needed measures to mitigate the adverse effects of nonpoint pollution. </span><span lang="EN-GB" style="font-size: 12.0pt / line-height:150% / font-family:&quot / Times New Roman&quot / ,&quot / serif&quot / ">The expansion of urban areas and agricultural land has a direct effect on land cover types within the catchment. 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Philosophiae Doctor - PhD / The most significant human impacts on the hydrological system are due to land-use change. The conversion of land to agricultural, mining, industrial, or residential uses significantly alters the hydrological characteristics of the land surface and modifies pathways and rates of water flow. If this occurs over large or critical areas of a catchment, it can have significant short and long-term impacts, on the quality of water. While there are methods available to quantify the pollutants in surface water, methods of linking non-point source pollution to water quality at catchment scale are lacking. Therefore, the research presented in this thesis investigated modelling techniques to estimate the effect of land-cover type on water quality. The main goal of the study was to contribute towards improving the understanding of how different landcovers in an urbanizing catchment affect surface water quality. The aim of the research presented in this thesis was to explain how the quality of surface runoff varies on different land-cover types and to provide guidelines for minimizing water pollution that may be occurring in the Kuils-Eerste River catchment. The research objectives were; (1) to establish types and spatial distribution of land-cover types within the Kuils-Eerste River catchment, (2) to establish water quality characteristics of surface runoff from specific land-cover types at the experimental plot level, (3) to establish the contribution of each land-cover type to pollutant loads at the catchment scale. Land-cover characteristics and water quality were investigated using GIS and Remote Sensing tools. The application of these tools resulted in the development of a landcover map with 36 land classifications covering the whole catchment. Land-cover in the catchment is predominantly agricultural with vineyards and grassland covering the northern section of the catchment. Vineyards occupy over 35% of the total area followed by fynbos (indigenous vegetation) (12.5 %), open hard rock area (5.8 %), riparian forest (5.2 %), mountain forest (5 %), dense scrub (4.4 %), and improved grassland (3.6 %). The residential area covers about 14 %. Roads cover 3.4 % of the total area. Surface runoff is responsible for the transportation of large quantities of pollutants that affect the quality of water in the Kuils-Eerste River catchment. The different land-cover types and the distribution and concentration levels of the pollutants are not uniform. Experimental work was conducted at plot scale to understand whether landcover types differed in their contributions to the concentration of water quality attributes emerging from them. Four plots each with a length of 10 m to 12 m and 5 m width were set up. Plot I was set up on open grassland, Plot II represented the neyards, Plot III covered the mountain forests, and Plot IV represented the fynbos landcover. Soil samples analyzed from the experimental plots fell in the category of sandy soil (Sa) with the top layer of Plot IV (fynbos) having loamy sand (LmSa). The soil particle sizes range between fine sand (59.1 % and 78.9 %) to coarse sand (between 7 % and 22 %). The content of clay and silt was between 0.2 % and 2.4 %. Medium sand was between 10.7 % and 17.6 %. In terms of vertical distribution of the particle sizes, a general decrease with respect to the size of particles was noted from the top layer (15 cm) to the bottom layer (30 cm) for all categories of the particle sizes. There was variation in particle size with depth and location within the experimental plots. Two primary methods of collecting water samples were used; grab sampling and composite sampling. The quality of water as represented by the samples collected during storm events during the rainfall season of 2006 and 2007 was used to establish water quality characteristics for the different land-cover types. The concentration of total average suspended solids was highest in the following land-cover types, cemeteries (5.06 mg L-1), arterial roads/main roads (3.94 mg L-1), low density residential informal squatter camps (3.21 mg L-1) and medium density residential informal townships (3.21 mg L-1). Chloride concentrations were high on the following land-cover types, recreation grass/ golf course (2.61 mg L-1), open area/barren land (1.59 mg L- 1), and improved grassland/vegetation crop (1.57 mg L-1). The event mean concentration (EMC) values for NO3-N were high on commercial mercantile (6 mg L-1) and water channel (5 mg L-1). The total phosphorus concentration mean values recorded high values on improved grassland/vegetation crop (3.78 mg L-1), medium density residential informal townships (3mgL-1) and low density residential informal squatter camps (3 mg L-1). Surface runoff may also contribute soil particles into rivers during rainfall events, particularly from areas of disturbed soil, for example areas where market gardening is taking place. The study found that different land cover types contributed differently to nonpoint source pollution. GIS model was used to estimate the diffuse pollution of five pollutants (chloride, phosphorus, TSS, nitrogen and NO3-N) in response to land cover variation using water quality data. The GIS model linked land cover information to diffuse nutrient signatures in response to surface runoff using the Curve Number method and EMC data were developed. Two models (RINSPE and N-SPECT) were used to estimate nonpoint source pollution using various GIS databases. The outputs from the GIS-based model were compared with recommended water quality standards. It was found that the RINSPE model gave accurate results in cases where NPS pollution dominate the total pollutant inputs over a given land cover type. However, the N-SPECT model simulations were too uncertain in cases where there were large numbers of land cover types with diverse NPS pollution load. All land-cover types with concentration values above the recommended national water quality standard were considered as areas that needed measures to mitigate the adverse effects of nonpoint pollution. The expansion of urban areas and agricultural land has a direct effect on land cover types within the catchment. The land cover changes have adverse effect which has a potential to contribute to pollution.

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.

L'économie du Pakistan, fondée sur l'agriculture, est hautement dépendante de l'approvisionnement en eau issu de la fonte de la neige et des glaciers du Haut Bassin de l'Indus (UIB) qui s'étend sur les chaînes de l'Himalaya, du Karakoram et de l'Hindukush. Il est par conséquent essentiel pour la gestion des ressources en eau d'appréhender la dynamique de la cryosphère (neige et glace), ainsi que les régimes hydrologiques de cette région dans le contexte de scénarios de changement climatique. La base de données satellitaire du produit de couverture neigeuse MODIS MOD10A2 a été utilisée de mars 2000 à décembre 2009 pour analyser la dynamique du couvert neigeux de l'UIB. Les données journalières de débits à 13 stations hydrométriques et de précipitation et température à 18 postes météorologiques ont été exploitées sur des périodes variables selon les stations pour étudier le régime hydro-climatique de la région. Les analyses satellitaires de la couverture neigeuse et glaciaire suggèrent une très légère extension de la cryosphère au cours de la dernière décade (2000‒2009) en contradiction avec la rapide fonte des glaciers observée dans la plupart des régions du monde. Le modèle « Snowmelt Runoff » (SRM), associé aux produits neige du capteur MODIS a été utilisé avec succès pour simuler les débits journaliers et étudier les impacts du changement climatique sur ces débits dans les sous-bassins à contribution nivo-glaciaire de l'UIB. L'application de SRM pour différents scénarios futurs de changement climatique indique un doublement des débits pour le milieu du siècle actuel. La variation des écoulement de l'UIB, la capacité décroissante des réservoirs existants (barrage de Tarbela) à cause de la sédimentation, ainsi que la demande croissante pour les différents usages de l'eau, laissent penser que de nouveaux réservoirs sont à envisager pour stocker les écoulements d'été et répondre aux nécessités de l'irrigation, de la production hydro-électrique, de la prévention des crues et de l'alimentation en eau domestique. / Agriculture based economy of Pakistan is highly dependent on the snow and glacier melt water supplies from the Upper Indus River Basin (UIB), situated in the Himalaya, Karakoram and Hindukush ranges. It is therefore essential to understand the cryosphere (snow and ice) dynamics and hydrological regime of this area under changed climate scenarios, for water resource management. The MODIS MOD10A2 remote-sensing database of snow cover products from March 2000 to December 2009 was selected to analyse the snow cover dynamics in the UIB. A database of daily flows from 13 hydrometric stations and climate data (precipitation and temperature) from 18 gauging stations, over different time periods for different stations, was made available to investigate the hydro-climatological regime in the area. Analysis of remotely sensed cryosphere (snow and ice cover) data during the last decade (2000‒2009) suggest a rather slight expansion of cryosphere in the area in contrast to most of the regions in the world where glaciers are melting rapidly. The Snowmelt Runoff Model (SRM) integrated with MODIS remote-sensing snow cover products was successfully used to simulate the daily discharges and to study the climate change impact on these discharges in the snow and glacier fed sub-catchments of UIB. The application of the SRM under future climate change scenarios indicates a doubling of summer runoff until the middle of this century. This variation in the Upper Indus River flow, decreasing capacity of existing reservoirs (Tarbela Dam) by sedimentation and the increasing demand of water uses suggests that new reservoirs shall be planned for summer flow storage to meet with the needs of irrigation supply, increasing power generation demand, flood control and water supply.

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.