Hydrological Drought Identification and Prediction Based on Statistics and Chaos Theory

This study is based on the daily runoff data from 1960 to 2020 at the Huaxian Hydrological Station in the Weihe River Basin. Using a combination of statistical and dynamic methods, We explore drought events by integrating drought probability P with chaotic fractal dimension D₂ and the maximum Lyapunov exponent LE. Furthermore, by reconstructing the phase space from the standardized runoff drought index SRDI series, we identify and predict future drought events in the phase space using the LE index prediction method, local phase point prediction method, and inverse distance weighting method. The Analytic Hierarchy Process AHP is applied to weight the prediction results. The results indicate a strong correlation between the statistical drought parameter P and the chaotic parameters D₂ and LE. Phase space prediction results show that the runoff SRDI index for 2021 is 0.50, indicating "no drought" according to the hydrological drought classification, which is consistent with the actual situation. The methods used in this study may provide a new approach to traditional drought research.