The added value of spatially distributed meteorological data for simulating hydrological processes in a small Mediterranean catchment

Gara, Ahlem; Gader, Khouloud; Khlifi, Slaheddine; Vanclooster, Marnik; Jendoubi, Donia; Bouvier, Christophe (2020). The added value of spatially distributed meteorological data for simulating hydrological processes in a small Mediterranean catchment. Acta geophysica, 68(1), pp. 133-153. Versita 10.1007/s11600-019-00379-y

Text Gara2020_Article_TheAddedValueOfSpatiallyDistri.pdf - Published Version Restricted to registered users only Available under License Publisher holds Copyright. Download (2MB) | Request a copy

The purpose of this paper was to demonstrate the added value of the spatial distribution of rainfall and potential evapotranspi-ration (PE) in the prediction of the discharge for a small Mediterranean catchment located in the Medjerda basin in Tunisia, i.e. the Raghay. We compare therefore the performance of a conceptual hydrological model available in the ATHYS platform, using global and spatial distributed input data. The model was implemented in two different ways. The first implementation was in a spatially distributed mode, and the second one was in a non-distributed lumped mode by using spatially averaged data weighed with a Thiessen-interpolated factor. The performance of the model was analysed for the distributed mode and for the lumped mode with a cross-validation test and through several modelling evaluation criteria. Simultaneously, the impact of the spatial distribution of meteorological data was assessed for the two cases when estimating the model parameters, the flow and water amounts, and the flow duration curves. The cross-validation of the split-sample test shows a preference for the spatially distributed model based on accuracy criteria and graphical comparison. The distributed mode required, however, more simulation time. Finally, the results reported for the Raghay indicated that the added value of the spatial distribution of rainfall and PE is not constant for the whole series of data, depending on the spatial and temporal variability of climate data over the catchment that should be assessed prior to the modelling implementations.

Interest & Impact

Downloads

3 since deposited on 29 Apr 2020
0 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item