Assessing parameter uncertainty in semi-distributed hydrological model based on type-2 fuzzy analysis: a case study of Kaidu River Basin

In this study, a type-2 fuzzy simulation method (TFSM) is developed for modeling hydrological processes associated with vague information through coupling type-2 fuzzy analysis technique with the semi-distributed land use based runoff processes (SLURP) model. TFSM can handle fuzzy sets with uncertain membership function related to hydrological modeling parameters and reveal the effects of such uncertain parameters on the hydrological processes. Streamflow calibration and verification are performed using the hydrological data for the Kaidu River Basin, China. The statistical values of Nash–Sutcliffe efficiency, determination coefficient, and deviation of volume indicate a good performance of SLURP in describing the streamflow at the outlet of the Kaidu River Basin. Based on TFSM, the effects of four uncertain parameters such as precipitation factor (PF), maximum capacity for fast store, retention constant for fast store (RF), and retention constant for slow store, on the hydrological processes are analyzed under different α-cut levels. Results demonstrate that the uncertainty associated with PF has significant effect on the simulated streamflow, while the uncertainty associated with RF has slight effect among the four parameters. These findings are helpful for improving efficiency in hydrological prediction and enhancing the model applicability.