Coupled model for long-term runoff prediction considering non-stationarity
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Abstract:
Climate change can cause non-stationarity in hydrological series, bringing more challenges to hydrological prediction. Taking Shule rive as a case, this paper explores a new long-term runoff prediction model under non-stationarity. Based on runoff recharge sources and climate change in upper reaches of the river, this paper first analyzes the trend term and periodic term of the runoff series, and then builds a multiple regression model based on hydro-climatic teleconnection analysis to predict the stochastic term. The issued model couples auto-correlation model and hydro-climatic teleconnection model by merging the three terms together, and yields ultimate prediction runoff values. Prediction results of the teleconnection based model, the time series model, and the coupling model, are compared. It is shown that the coupling model has the highest precision and provides the most efficient results. Meanwhile, it can capture the nonstationary trend of streamflow.
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