Time scale dependent sensitivities of the XinAnJiang model parameters

The objective of this study was to investigate the sensitivities of the parameters of the XinAnJiang model, hereinafter referred to as XAJ model. The XAJ model is the most popular rainfall-runoff model in China, and widely used all over the world. There were fifteen parameters in the modified XAJ model used in this study. Understanding the sensitivities is undoubtedly crucial for parameter optimization, even for manual calibration by trial and error. A sensitivity analysis technique proposed by Morris was used to analyze parameter sensitivities at time scales of year, month and day. The sensitivities of these parameters were shown to change. At annual scale, the parameters for input data adjustment are most sensitive. On the other hand, the parameters concerning runoff component separation and runoff concentration are sensitive at daily scale. The parameters relating to runoff generation are less sensitive at all three temporal scales. Additionally, strong interactions between the parameters were detected at all three temporal scales. The time scale dependent nature of the sensitivities offers the possibility to design more efficient optimization schemes for automatic model calibration of the XAJ model.