Uncertainty analysis and prediction of river runoff with multi-time scales

Abstract

Increasing water-issues demand that water resources managers know and predict the uncertain characteristics of river runoff well. In this paper, the fluctuating periods and local features of runoff with multi-time scales are analyzed by the empirical mode decomposition method. With the set pair analysis method, the uncertainty properties of runoff series with different multi-time scales are expressed. Meanwhile, cointegration theory is introduced to indicate the long-term equilibrium relationships between runoff series, and then the runoff prediction model is proposed based on the error correction model (ECM). The results show that the runoff series of Heihe River in northwest China exhibit complex relations with different periodic fluctuations and changing laws. The identity degree is the main relation between two runoff series, especially in the short period. Both the original series and decomposed components are all cointegrated, and the established runoff prediction model based on the ECM can simulate and predict river runoff well.