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Drought Assessment and Prediction in the Yellow River Basin Based on Multi-Index Machine Learning

Author(s): Yiqi Yan; Yuqiong He; Zuoqiang Han

Linked Author(s): Yiqi Yan

Keywords: Yellow River Basin Multi drought index Periodic analysis The evolution law of drought Pettitt mutation test Time series machine learning Drought trend prediction

Abstract: This paper is based on the multi drought index, combined with periodic analysis, Pettitt mutation test, and time series machine learning, to analyze and evaluate the spatiotemporal evolution of drought in the Yellow River Basin, and predict the future development trend of drought in the Yellow River. The results show that from the 1950s and 1960s to 2023, the Yellow River Basin was mainly characterized by mild meteorological droughts, with a higher frequency of moderate meteorological droughts. The frequency of severe and extreme droughts in the middle and lower reaches was higher than in other regions. There is a certain correspondence between hydrological drought and meteorological drought in the Yellow River Basin, but they also vary differently. Except for a slight increase in the short-term hydrological drought index in the upper reach, the hydrological drought index in the upper reach and other areas has shown a decreasing trend. Combined with frequency analysis, the results show that, the frequency and intensity of hydrological droughts in the Yellow River Basin have been increasing since the 1950s and 1960s. Periodic analysis shows that the precipitation drought index exhibits periodic fluctuations of 3a, 6a, and 35a. Pettitt mutation test analysis shows that there was a significant negative mutation in precipitation in the Yellow River Basin in the late 1980s and early 1990s, and meteorological hydrological drought significantly intensified after the mutation. Using machine learning to predict slight short-term relief of future meteorological drought, while the hydrological drought index shows a long-term downward trend, indicating that the Yellow River hydrological drought will intensify and water resource management will face greater challenges.

DOI:

Year: 2025

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