The performance of semi-distributed modelling in urban drainage: the trade-off between hydrological measurements and geographical data

Abstract

Nowadays, high resolution geographical data are widely available for research and operational purposes. The inclusion of these data into hydrological models may suggest a direct and clear improvement of their performances. Different configurations and model structures, including an increasing quantity of geographical information, are tested using the widely used Stormwater Management Model 5 on a 2.5 km2 pilot catchment (located in Sucy en Brie, close to Paris, France). The Nash-Sutcliffe criterion is used to estimate the goodness of fit between model simulations and available measurements. If including some basic spatial information on landuse clearly improves the performance of the uncalibrated model, the increase in performance is less obvious if the user continues to refine geographical information on the catchment. Moreover, model predictions are comparable between a model calibrated with an efficient calibration procedure and a more physical approach including a fine spatial description and no calibration. Finally, the quality of data used for calibration and validation seems to be a key parameter to obtain a good fit between measurements and model predictions.