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Flash floods forecasting in the Mediterranean area is a major economic and\udsocietal issue. Specifically, considering karst basins, heterogeneous\udstructure and nonlinear behaviour make the flash flood forecasting very\uddifficult. In this context, this work proposes a methodology to estimate the\udcontribution from karst and non-karst components using toolbox including\udneural networks and various hydrological methods. The chosen case study is\udthe flash flooding of the Lez river, known for his complex behaviour and huge\udstakes, at the gauge station of Lavallette, upstream of Montpellier (400 000 inhabitants). After\udapplication of the proposed methodology, discharge at the station of\udLavallette is spited between hydrographs of karst flood and surface runoff,\udfor the two events of 2014. Generalizing the method to future events will allow\uddesigning forecasting models specifically for karst and surface flood\udincreasing by this way the reliability of the forecasts

proceedings of iahs

Neural network modeling and geochemical water analyses to understand and forecast karst and non-karst part of flash floods (case study on the &amp;lt;i&amp;gt;Lez&amp;lt;/i&amp;gt; river, Southern France)