Pierre-Alain Ayral

Rainfall-runoff modeling of flash floods in the absence of rainfall forecasts: the case of Cévenol flash floods

Abstract“Cévenol flash floods” are famous in the field of hydrology, because they are archetypical of flash floods that occur in populated areas, thereby causing heavy damages and casualties. As a consequence, their prediction has become a stimulating challenge to designers of mathematical models, whether physics based or machine learning based. Because current, state-of-the-art hydrological models have difficulty performing forecasts in the absence of rainfall previsions, new approaches are necessary. In the present paper, we show that an appropriate model selection methodology, applied to neural network models, provides reliable two-hour ahead flood forecasts.

Grid Technology Reliability for Flash Flood Forecasting: End-user Assessment

The flash flood forecasting is one of the most important challenges for research in hydrology. The anticipation of extreme hydrological scenarios through rainfall–runoff models is still limited, mainly because of the high uncertainty of rainfall forecasts, as of limited computing resources. The authors propose to simulate an ensemble of potential hydrological scenarios in order to support the forecaster’s decision-making process. The developed applicative layer takes advantage of the computing capabilities of Grid technology, significantly enhancing the management of independent modelling operations in an operational lead time. A set of experimentations is deployed in order to firstly assess efficiency of this applicative layer and secondly to gauge more broadly the potentialities of Grid to handle flood crisis management operations. Finally, in managing more than one hundred hydrological simulations simultaneously, this experimental platform opens new perspectives for the improvement of hydrological forecast modelling, limited up to now by the lack of computing resources.

Forecasting Flash Floods with an Operational Model

The flash flood forecasting model ALHTAIR (“Alarme Hydrologique Territoriale Automatisee par Indicateur de Risque”) has been developed during the last five years by the flood-warning service of the Gard Region (SAC-30), in the South-East of France. A spatial version for the flash flood forecasting model is described in this paper. This flash flood forecasting model is divided in three separate tools, which allow a flood hydrograph simulation for each location, covering all the rivers of the Gard Region, in a real time processing: CALAMAR® simulates the rainfall intensity on each square kilometre of the study area every five minutes. This georeferenced information is obtained by the interpretation of radar images. HYDROKIT® gives the hydrographical characteristics of a studied watershed using a DEM (Digital Elevation Model) for calculating the concentration time. ALHTAIR software, processes the data obtained by the two previous tools and with a module of time concentration and a module of production (calculation of effective rainfall) calculating in real time the flood hydrograph. The model that calculates the effective rainfall, based on the Horton principle, takes six parameters into account. For the first version of ALHTAIR, these parameters are the same for the whole SAC-30 supervised territory. The principal results of this version show a good flood crest synchronization but a general overestimation of the peak flow. This result was observed during the flash floods of the Gard Region in September 2002. To improve the ALTHAIR results, a spatial approach has been tested. The results presented in the paper, show that the spatial approach according to infiltration capacity improves the reconstitution of the flood hydrograph