中国气象干旱时空特征与混合模型预测OA

To enhance drought prediction accuracy,this study uses Chinese ground meteorological observations from 1980 to 2023 and selects the standardized precipitation evapotranspiration index(SPEI)as the drought indi-cator.Key predictors were identified through correlation analysis,and a hybrid wavelet transform-long short-term memory(WT-LSTM)model was developed using Theil-Sen Median trend analysis and related methods.Two pre-diction schemes—single-factor and multifactor—were designed to analyze the spatiotemporal evolution of meteo-rological drought in China.Results show(1)Spatial trends of factors are uneven;precipitation and potential evapotranspiration generally increase,with precipitation showing an"increase-decrease-increase-decrease"pat-tern from southeast to northwest,and potential evapotranspiration increasing from northwest to southeast.SPEI trends are negative in 88.87%of areas,indicating widespread drought intensification.(2)The average annual drought duration is mostly 1-2 months,with significant increases in average annual drought severity mainly in northwest,north,and northern northeast China.Trends in average annual drought characteristics exhibit a spatial pattern of higher values in the north and lower values in the south.(3)Regions with long seasonal drought dura-tions in each season do not correspond to high drought intensity;high-value areas of summer drought frequency are widely distributed,while winter drought frequency is lowest.(4)Compared with LSTM,the WT-LSTM mod-el performs better,and for single-factor predictions,the multi-factor approach enhances the ability of the model to represent complex drought patterns,significantly improving prediction performance.(5)Under the hybrid model,single-factor prediction is more suitable for regions with relatively stable climatic drought patterns,while multi-factor prediction better captures drought trends in climatically complex areas such as Xinjiang Uygur Autono-mous Region and the Qinghai-Xizang Plateau.