Long-term runoff prediction for reservoir based on Mahalanobis distance discrimination

Abstract

An accurate and timely forecast of medium and long-term runoff forecast is of great significance to reservoir safety and water resources scheduling. In order to improve the long-term runoff forecast accuracy of the reservoir, a long-term runoff forecasting model was constructed based on the principle of Mahalanobis distance discrimination analysis. The data sequence from 1952 to 2008 of Danjiangkou reservoir was selected, the correlation coefficient method and AIC criterion were used to sift out the highly correlated and independent factors, a long-term runoff forecasting model was constructed based on the principle of Mahalanobis distance discrimination analysis. The result showed that under the permutation error of 10%，the pass rate during the simulation period was 93.9%, and the pass rate during the inspection period was 87.5%. The research results serve as a reference for the operation of Danjiangkou reservoir.