Find in Library

Accurate hydrological simulation plays an important role in the research of hydrological problems; the accuracy of the watershed hydrological model is seriously affected by model-parameter uncertainty and model-input uncertainty. Thus, in this study, different calibration methods and rainfall inputs were introduced into the SWAT (Soil and Water Assessment Tool) model for watershed hydrological simulation. The Chengbi River basin, a typical karst basin in Southwest China, was selected as the target basin. The indicators of the <i>NSE</i> (Nash efficiency coefficient), <i>Re</i> (relative error) and <i>R²</i> (coefficient of determination) were adopted to evaluate the model performance. The results showed that: on the monthly and daily scales, the simulated runoff with the single-site method calibrated model had the lowest <i>NSE</i> value of 0.681 and highest <i>NSE</i> value of 0.900, the simulated runoff with the multi-site method calibrated model had the lowest <i>NSE</i> value of 0.743 and highest <i>NSE</i> value of 0.953, increased correspondingly, indicating that adopting the multi-site method could reduce the parameter uncertainty and improve the simulation accuracy. Moreover, the <i>NSE</i> values with IMERG (Integrated Multisatellite Retrievals for Global Rainfall Measurement) satellite rainfall data were the lowest, 0.660 on the monthly scale and 0.534 on the daily scale, whereas the <i>NSE</i> values with fusion rainfall data processed by the GWR (geographical weighted regression) method greatly increased to 0.854 and 0.717, respectively, and the <i>NSE</i> values with the measured rainfall data were the highest, 0.933 and 0.740, respectively, demonstrating that the latter two rainfall inputs were more suitable sources for hydrological simulation.