Hydrological performance of the ERA5 reanalysis for flood modeling in Tunisia with the LISFLOOD and GR4J models

This study is focused on 6 catchments in Tunisia, in North Africa, under a semi-arid climate where daily river discharge and precipitation observations are available between 1992 and 2006. The distributed hydrological model LISFLOOD has been compared with a lumped model, GR4J, to reproduce river run...

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Veröffentlicht in:Journal of hydrology. Regional studies 2022-08, Vol.42, p.101169, Article 101169
Hauptverfasser: Cantoni, Elia, Tramblay, Yves, Grimaldi, Stefania, Salamon, Peter, Dakhlaoui, Hamouda, Dezetter, Alain, Thiemig, Vera
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Sprache:eng
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Zusammenfassung:This study is focused on 6 catchments in Tunisia, in North Africa, under a semi-arid climate where daily river discharge and precipitation observations are available between 1992 and 2006. The distributed hydrological model LISFLOOD has been compared with a lumped model, GR4J, to reproduce river runoff and floods, using observed rainfall interpolated from rain gauges and from the ERA5 reanalysis. LISFLOOD and GR4J with their default parameters have little skill in Tunisia, but when calibrated, both hydrological models provide similar performance to reproduce river discharge, with a mean KGE of 0.65 for GR4J driven by observed rainfall, and 0.59 with ERA5, and similarly a mean KGE of 0.59 for LISFLOOD driven by observed rainfall and 0.48 with ERA5. All model simulations perform very similarly using either observed rainfall data from rain gauges interpolated over the basins or ERA5 rainfall, indicating its value as an alternative to observations in data-scarce areas such as Tunisia. The development of regional databases of river discharge observations in North Africa could allow the calibration of such hydrological models on a larger scale for operational flood modeling and forecasting. •First evaluation of the ERA5 reanalysis for flood modelling in North Africa.•The LISFLOOD and GR4J models have been compared for 6 basins in Tunisia.•ERA5 is as efficient as observed rainfall for river runoff simulation.
ISSN:2214-5818
2214-5818
DOI:10.1016/j.ejrh.2022.101169