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Simple Linear Modeling Approach for Linking Hydrological Model Parameters to the Physical Features of a River Basin

Huang, Chengcheng, Wang, Guoqiang, Zheng, Xiaogu, Yu, Jingshan, Xu, Xinyi
Water resources management 2015 v.29 no.9 pp. 3265-3289
basins, cluster analysis, hydrologic models, linear models, regression analysis, watersheds, China
Physically-based distributed hydrological models are drawing more attention in recent years. Generally they have some parameters to be adjusted for satisfactory simulation performance. However, the parameter calibration procedure requires abundant input data. Fortunately, parameters of physical-based models are generally related to specific basin characteristics. If these relationships are generalized with caution, they could be used to simplify the parameter calibration procedure and facilitate estimation of parameters in ungauged basins. In this study, comprehensive tests between sensitive hydrological model parameters and all available basin characteristics, including two new defined characteristics, are done to exploit their potential relationships using Cluster Analysis. Then linear regression model is adopted to fit a reliable relation for each sensitive parameter respectively. The matrix condition number is used to diagnose the multicollinearity in explanatory variables to ensure effective and robust relations. Moreover, two new characteristics are defined to make better use of characteristics consisting of component data. Their remarkable performance suggests their irreplaceable role in fitting a reliable and robust relationship. When the relations for sensitive parameters are fitted out, they are used to transfer parameters to independent sub-basin from other sub-basins. The leave-one-out cross validation is used to evaluate transferring performances. The BTOPMC model is used to apply the above approach in the Yalong River Basin, Southwest China. Thus the samples of this study are various and representative. It shows that the transferred parameters have satisfactory performance, which suggests that the proposed approach is effective with application prospect.