Evidence for deterministic chaos in long-term high-resolution karstic streamflow time series

作者: David Labat , B. Sivakumar , A. Mangin

DOI: 10.1007/S00477-015-1175-5

关键词:

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

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