Hydrological systems seem simple, "everything flows", but prove to be even more complex when one tries to differentiate and characterize flows in detail. Hydrology has thus developed a plurality of models that testify to the complexity of hydrological systems and the variety of their causal representations, from the simplest to the most sophisticated. Beyond a subjective complexity linked to our difficulty in understanding or our attention to detail, hydrological systems also present an intrinsic complexity. These include the nonlinearity of processes and interactions between variables, the number of variables in the system, or dimension, and how they are organized to further simplify or complicate the system's dynamics. The thesis addresses these aspects of hydrological complexity. An epistemological and historical analysis of the concept of causality explores the human understanding of hydrological systems. Based on empirical approaches applied to the limestone karstic system of the Lhomme at Rochefort in Belgium, the thesis then studies methods to analyze the nonlinearity of the Lhomme river recession and associate it with the geomorphological complexity of the watershed. The thesis also handles the discrimination of dominant dynamic behaviors in the hydrological continuum of the Rochefort caves subsurface based on an electrical resistivity model of the subsurface and clustering methods grouping time-series according to their similarity. Finally, the study maps the Rochefort Caves system's organization by detecting causal interactions between several environmental data - gravity, the dynamics of subsurface resistivity, and percolations measured in the caves - using time-series analysis and causal inference methods. ; (AGRO - Sciences agronomiques et ingénierie biologique) -- UCL, 2020