This PhD thesis presents the development of a methodology that analyzes potential climate change impacts on hydrological extremes along rivers in Flanders (Belgium).The main objective of this study is to show whether hydrological modelling techniques driven by climate modelling techniques and climate change scenarios enable a prediction of the long-term evolution of the hydrological system of the studied area. The climate change impact analysis is based on a continuous simulation approach: The hydrological system behaviour of the main rivers in the Scheldt River Basin District is modeled for an observed historical period and for a future change from the control period (1961-1990) to the predicted period (2071-2100) under forcing of a modified (predicted) climate. The climate change impact on hydrological extremes is assessed through the comparison of key variables of the hydrological system for the two periods (e.g., runoff peaks, low flow values, overland flow and potential evapo(transpi)ration). The overall modelling procedure is completed through a set of 24 climate model simulations highly resolute (derived from the PRUDENCE climate project), local scale lumped conceptual hydrological models (NAM of DHI), hydrodynamic models (MIKE11 of DHI), models for topographical information (DEM: Digital Elevation Models) and risk calculation models covering the studied area. The local scale models have been already developed for water management and flood monitoring purposes by the Waterbouwkundig Laboratorium of the Flemish government. An appropriate downscaling method has been developed in this study counting for variable statistical properties as intensity and frequency. This method lead to created potential climate change scenarios for Flanders based on sequences of low, mean and high variation factors of the variables of precipitation and potential evapo(transpi)ration. The modelling procedure results state that the predicted climate evolution induces a significant reduction of the low flows due to a considerable hydrological regime modification. As for high flows (flood risk), the results range from increasing to decreasing depending on the climate change scenario and thus counting for a large uncertainty. Overland flow follows similar patterns as for the high flows while evapo(transpi)ration shows systematic increase as a result of regional warming. A statistical method has been implemented to assess the hydrological response sensitivity to changes induced by the created climate change scenarios and by natural variability. It is based on ensemble modelling of the regional climate model simulations and on Monte Carlo simulations to account for the effect natural variability (randomness) when comparing the climate model results with historical data. The overall prediction uncertainty and the contribution of all sources of modelling uncertainty are still far to be quantified.
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