WetSpa model application in the Distributed Model Intercomparison Project (DMIP2)

Safari, A., De Smedt, F., & Moreda, F. (2012). WetSpa model application in the Distributed Model Intercomparison Project (DMIP2). Journal of Hydrology, 418-419, 78-89. DOI: 10.1016/j.jhydrol.2009.04.001

This paper describes the application of a spatially distributed hydrologic model (WetSpa) Water and Energy Transfer between Soil, Plants and Atmosphere, for the second phase of the Distributed Model Intercomparison Project (DMIP2) study. The model implementation is based on 30-m spatial resolution and 1 h time-step for all basins and interior watersheds involved in the DMIP study. Rainfall inputs are derived from Next Generation Radar (NEXRAD). The distributed model parameters are based on an extensive database of watershed characteristics available for the region, including digital maps of topography, soil type, and landuse. The model is calibrated and validated on part of the river flow records for each basin and applied to the smaller interior watersheds not used in calibration to assess the model performance in ungaged basins. The statistics improve significantly with calibration of the global model parameters but even for uncalibrated simulations, the WetSpa model reproduces flow rates of acceptable accuracy for most cases. To evaluate the model performance during calibration and validation periods, an Aggregated Measure (AM) is introduced that measures different aspects of the simulated hydrograph such as shape, size and volume. The statistics for the five calibration basins show that the model produces very good to excellent results for the calibration period. With the exception of Blue River basin, the overall model performance for the validation period remains good to very good, indicating that the model is able to simulate the relevant hydrologic processes in the basins accurately. The performance of the uncalibrated model for the subcatchments is more variable, but the hourly flow rates generally reproduced with reasonable accuracy indicating an encouraging performance of the model.