Assess the impact of climate change on water resources and management systems associated, is a major concern of our society. This requires the establishment of a simulation chain which allows, on the basis of future climate experiments i) to estimate the possible changes in regional resource and its variability, ii) to simulate the behavior of the systems used to manage them in order to iii) estimate the possible changes in performance. This thesis aims to test the feasibility of establishing a chain simulation of such a management system to identify what are the real components to consider in this case. To do this, we have to provide answers to the following questions: - How can we represent an operational management system in a climate change context? - What elements of evaluation can be used to estimate the impact of climate change on the management system? - What are the sources of uncertainty influencing this assessment? What are the relative contributions to the total uncertainty of these different methods and models used? We consider the system of management of the reservoir of Serre-Ponçon, built on the high basin of the Durance. This dam, operated by EDF, is one of the largest artificial dams Europe. It is multi-purpose (irrigation, low-flow support, hydropower, tourism). As a first step, we will present the context of the current management system. Then, we will establish a management model to reproduce - in a realistic way from the point of view of the current manager (EDF), but simplified to be applied in future scenarios - the current management of the Serre-Ponçon reserve. We will develop for this, i) different models to estimate different water demands and ii) an optimization model with constraints management. This model will simulate the management system in daily time step on several decades of recent climate or future climate change. We then propose a set of indicators to provide an estimate of the performance of such a system from the outputs of the management model obtained by simulation for different periods of 30 years. We will explore how the estimated performance depends on the model chosen to represent the current management system, and more specifically how the strategy used to optimize the management is developed. To this end, we will propose three management models based on three types of strategies, obtained for different degrees of predictability of future inflows and constraints. For these simulations, the impact models require meteorological forcing scenarios at watershed scale (eg hydrological model, model of water use model of resource management). These scenarios can be obtained by statistical downscaling methods (SDM), on the basis of large-scale simulations of global climate models. Finally, we will evaluate the uncertainties associated with the two types of models and will estimate their relative contributions to the overall uncertainty. We have used this scenario from different GCM/SDM simulations over the period 1860-2100 obtained within the RIWER2030 project. We show that these two sources of uncertainty are of the same order of magnitude estimate of changes in performance.
