Study on the Probability of Meteorological-to-Hydrological Drought Propagation Based on a Bayesian Network

Xiangyang Zhang, Huiliang Wang, Zhilei Yu (), Dengming Yan, Ruxue Liu, Simin Liu, Yujia Zhu, Yifan Chen and Zening Wu
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Xiangyang Zhang: School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China
Huiliang Wang: School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China
Zhilei Yu: School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China
Dengming Yan: Yellow River Engineering Consulting Co., Ltd., Zhengzhou 450003, China
Ruxue Liu: Yellow River Conservancy Commission Hydrology and Water Resources Bureau of Henen, Zhengzhou 450003, China
Simin Liu: China National Forestry-Grassland Development Research Center, Beijing 100714, China
Yujia Zhu: School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China
Yifan Chen: Yellow River Conservancy Technical Institute, North China University of Water Resources and Electric Power, Kaifeng 475004, China
Zening Wu: School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China

Land, 2025, vol. 14, issue 3, 1-24

Abstract: With accelerating climate change, droughts have increased in frequency and exerted a substantial influence on socioeconomic factors. Under conditions of insufficient precipitation and high temperatures, meteorological droughts have the potential to develop into more intense hydrological droughts, and the independent impact of temperature factors on drought propagation has not been considered separately. This study constructed a Standardized Temperature Index (STI) and, combined with time-series datasets of standardized indices of precipitation and runoff (SPI and SRI), based on Bayesian network principles, analyzed the probabilistic characteristics of drought propagation from meteorology to hydrology due to the influence of single or dual factors in the Yiluo River Basin (1961–2020). It also explored the transmission mechanisms of temperature and precipitation that drive and affect meteorological and hydrological drought. The results showed that propagation of meteorological to hydrological droughts increased with rising temperatures, and the propagation probability to severe and extreme hydrological drought increased by approximately 5%. Under the most adverse circumstances (high temperature and precipitation shortage scenarios), the likelihood of meteorological droughts progressing into intense hydrological drought events rose to 80%. Increasing temperature is expected to lead to more severe hydrological droughts. This study offers a theoretical foundation for drought prevention and mitigation.

Keywords: drought propagation; meteorological drought; precipitation; temperature; hydrological drought; Bayesian network (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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