Abstract
Improving knowledge of karst hydrodynamics represents a global challenge for water resource because karst aquifers provide approximately 25% of the world population in fresh water. Nevertheless, complexity, anisotropy, heterogeneity, non-linearity and possible non-stationarity of these aquifers makes them underexploited objects due to the difficulty to characterize their morphology and hydrodynamics. In this context, the systemic paradigm proposes others methods by studying these hydrosystems through input-output (rainfall-runoff) relations.This work covers the use of: i) correlation and spectral analysis to characterize response of karst aquifers, ii) neural networks to study and model linear and non-linear relations of these hydrosystems. In order to achieve this, different types of neural networks model configurations are explored to compare behavior and performances of these models. We are looking to constrain these models to make them interpretable in terms of hydrodynamic processes by making the operation of the model closer to the natural system in order to obtain a good representation and extract knowledge from the model parameters.The results obtained by correlation and spectral analysis are used to manage the configuration of neural networks models. Applied on the Lez hydrosystem over the period 1950-1967, results show that neural networks models are capable to model non-linear operation of the karst.Application of neural modelling on two non stationary hydrosystems (Durance in France and Fernow in the the USA) proved the ability of neural networks to model satisfactorily non-stationary conditions. Moreover, two real-time adjustment methods (adaptativity and data assimilation) enhanced the performance of neural network models face to changing conditions of the inputs or of the system itself.Finally, these various methods to analyze and model allow improving knowledge of the rainfall-runoff relationship. Methodological tools developed in this thesis were developed thanks to the application on Lez hydrosystem which has been studied for decades. This study and modeling methodology have the advantage of being applicable to other systems provided the availability of a sufficient database.