Physically based distributed hydrological model calibration based on a short period of streamflow data: case studies in four Chinese basins

作者：Wenchao Sun, Yuanyuan Wang, Guoqiang Wang, Xingqi Cui, Jingshan Yu, Depeng Zuo, Zongxue Xu · 发表于：Hydrology and earth system sciences · 年份：2017 · DOI：10.5194/hess-21-251-2017 · 被引用次数：63 · 研究领域：Hydrology and Watershed Management Studies、Hydrological Forecasting Using AI、Flood Risk Assessment and Management

Abstract. Physically based distributed hydrological models are widely used for hydrological simulations in various environments. As with conceptual models, they are limited in data-sparse basins by the lack of streamflow data for calibration. Short periods of observational data (less than 1 year) may be obtained from fragmentary historical records of previously existing gauging stations or from temporary gauging during field surveys, which might be of value for model calibration. However, unlike lumped conceptual models, such an approach has not been explored sufficiently for physically based distributed models. This study explored how the use of limited continuous daily streamflow data might support the application of a physically based distributed model in data-sparse basins. The influence of the length of the observation period on the calibration of the widely applied soil and water assessment tool model was evaluated in four Chinese basins with differing climatic and geophysical characteristics. The evaluations were conducted by comparing calibrations based on short periods of data with calibrations based on data from a 3-year period, which were treated as benchmark calibrations of the four basins, respectively. To ensure the differences in the model simulations solely come from differences in the calibration data, the generalized likelihood uncertainty analysis scheme was employed for the automatic calibration and uncertainty analysis. In the four basins, contrary to the...