Multi-period calibration of a semi-distributed hydrological model based on hydroclimatic clustering

Changing climatic conditions contribute to a time varying nature of hydrological responses over different temporal scales. The temporal dynamics of hydrological systems bring uncertainties into hydrological simulation which are different to uncertainties from spatial heterogeneity of soil and land use. This study develops a new approach to improve the calibration of hydrological based on hydroclimatic similarities. Six climatic indexes are integrated using Principal Component Analysis and Fuzzy C-mean Clustering methods to transform hydrological years into hydroclimatic periods. Parameter sets of SWAT model are calibrated independently for each period and used together to generate continuous simulation for a prairie watershed in southern Canada. Results indicate that the multi-period model exhibits comprehensive advantages over the traditional single-period model under various flow conditions. The simulation ability of the model is improved through using period-specific parameter sets in fitting the observations to compensate for deficiencies in the model structure or input data.

► We calibrate SWAT based on hydro-climatic similarities. ► Six climatic indexes are integrated into clusters. ► Method is applied to a prairie watershed in Canada. ► Prediction ability of SWAT is improved using period-specific parameters.