EVIDENCE FOR DETERMINISTIC CHAOS IN LONG-TERM HIGH-RESOLUTION KARSTIC STREAMFLOW TIME SERIES

David Labat (1) , B. Sivakumar , A. Mangin

1 GET - Géosciences Environnement Toulouse

One of the major challenges in hydrology consists in the conception of models to predict runoff evolution in time, as this is of crucial importance in water resource assessment and management. These models are required to provide estimations of high flows and low flows, so that appropriate short-term (flood) emergency measures and long-term (drought) management activities can be undertaken. However, due to the inherent nonlinearity of climate inputs (e.g. rainfall) and the heterogeneous nature of watersheds, understanding and modeling the catchment hydrologic response is tremendously challenging. This is particularly the case for karstic watersheds that are generally highly nonlinear and also sensitive to initial conditions. Investigation of the dynamic nature of hydrologic response is an important first step towards developing reliable models for such watersheds. To this end, this study examines the dynamic nature of streamflow discharge from karstic watersheds, especially the short-term variations. A nonlinear dynamic method, the correlation dimension method, is employed to unique long, continuous, and high-resolution (30-min) streamflow data from two karstic watersheds in the Pyrénées Mountains (Ariège) of France: the Aliou spring and the Baget spring. The results reveal the presence of deterministic chaos in the streamflow dynamics of the two watersheds, with attractor dimension values below 3. These results have great significance regarding the presence of deterministic chaos in karstic flows and in the issue of data size regarding chaos studies in hydrology.

Mots clés: Karstic springs; streamflow; nonlinearity; chaos; time series analysis; correlation dimension

Domaines: Milieux et Changements globaux; Interfaces continentales, environnement

David Labat, B. Sivakumar, A. Mangin. EVIDENCE FOR DETERMINISTIC CHAOS IN LONG-TERM HIGH-RESOLUTION KARSTIC STREAMFLOW TIME SERIES. Stochastic Environmental Research and Risk Assessment, 2016, 30 (8), pp.2189-2196. ⟨hal-03239245⟩