This paper summarizes results from the Distributed Model Intercomparison Project (DMIP) study. DMIP simulations from twelve different models are compared with both observed streamflow and lumped model simulations. The lumped model simulations were produced using the same techniques used at National Weather Service River Forecast Centers (NWS-RFCs) for historical calibrations and serve as a useful benchmark for comparison. The differences between uncalibrated and calibrated model performance are also assessed. Overall statistics are used to compare simulated and observed flows during all time steps, flood event statistics are calculated for selected storm events, and improvement statistics are used to measure the gains from distributed models relative to the lumped models and calibrated models relative to uncalibrated models. Although calibration strategies for distributed models are not as well defined as strategies for lumped models, the DMIP results show that some calibration efforts applied to distributed models significantly improve simulation results. Although for the majority of basin-distributed model combinations, the lumped model showed better overall performance than distributed models, some distributed models showed comparable results to lumped models in many basins and clear improvements in one or more basins. Noteworthy improvements in predicting flood peaks were demonstrated in a basin distinguishable from other basins studied in its shape, orientation, and soil characteristics. Greater uncertainties inherent to modeling small basins in general and distinguishable inter-model performance on the smallest basin (65 km 2 ) in the study point to the need for more studies with nested basins of various sizes. This will improve our understanding of the applicability and reliability of distributed models at various scales.
Journal of Hydrology – Elsevier
Published: Oct 1, 2004
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