Characteristics and prediction of extreme drought event using LSTM model in Wei River Basin

As one of the natural disasters, drought has caused a large amount of financial loss in the past few centuries. It is quite essential to reveal the variation of extreme drought event in Wei River Basin (WRB) of China. This paper investigated the change patterns of extreme drought event using Standardized Precipitation Evapo-transpiration Index (SPEI). Furthermore, the SPEI is predicted by combining different influencing factors in the WRB using Long Short-Term Memory (LSTM) model. The spatiotemporal variation characteristics were examined using non-parametric Mann-Kendall test, and the nonlinear relationships between El Nino-Southern Oscillation (ENSO) and SPEI were quantified using wavelet coherence analysis (WTC). Results showed that midland of the WRB have the highest probability of extreme drought events. Meanwhile, changes in SPEI in the northeast were more erratic than in other regions. The area with extreme drought had increased at a rate of 2.4% per decade. The prediction result of SPEI-24 was the best by LSTM model, and the prediction result of SPEI-3 was the worst. The R-square between the predicted value and the actual value of SPEI-24 is 0.87. The results help to realize the characteristics of extreme drought in the last hundreds of years, which can provide scientific basis and reference for drought emergency response and management in the WRB.