Author(s): Liting Zhou; Xiaojing Zhang; Hairong Zhang; Huaming Yao; Pan Liu
Linked Author(s):
Keywords: Non-stationarity; Runoff generation; Saturation-excess; Infiltration-excess; Bayesian model averaging
Abstract: The stationarity of hydrological models is increasingly questioned under the impact of climate change and natural variability. Specifically, it is challenging to identify whether the intrinsic structure of the hydrological model varies with different climatic conditions. To address this issue, the presented study focuses on diagnosing the non-stationarity of runoff generation by considering two typical structures, i. e., saturation-excess and infiltration-excess models. First, the historical data were divided into wet and dry periods based on annual anomaly rainfall. For each period, saturation-excess and infiltration-excess models were then calibrated, respectively. Finally, the Bayesian model averaging method was used to combine these two models into one model by estimating model weights for wet and dry periods, respectively. The data used in this study came from three catchments in southeastern Australia, which experienced a decadal-long millennium drought. Results show that weights of the infiltration-excess model are 0.45,0. 44,0. 33 in wet periods for the three catchments, while they are changed to 0.58,0. 54,0. 45 in dry periods. The incremental weights show that the infiltration-excess model is more appropriate in drier climatic conditions, demonstrating the non-stationarity of runoff generation after an extreme drought. It is indicated that the Bayesian model averaging method is helpful to diagnose non-stationarity of runoff generation under a changing climate.
Year: 2024