Uncertainty analysis of hydrological processes based on ARMA-GARCH model

Uncertainty analysis and risk analysis are two important areas of modern water resource management, in which accurate variance estimation is required. The traditional runoff model is established under the assumption that the variance is a constant or it changes with the seasons. However, hydrological processes in the real world are often heteroscedastic, which can be tested by McLeod-Li test and Engle Lagrange multiplier test. In such cases, the GARCH model of hydrological processes is established in this article. First, the seasonal factors in the sequence are removed. Second, the traditional ARMA model is established. Then, the GARCH model is used to correct the residual. At last, the daily runoff data in 1949-2001 of Yichang Hydrological Station is taken to be an example. The result shows that compared to the traditional ARMA model, the GARCH model has the ability to predict more accurate confidence intervals under the same confidence level.