Drought risk analysis based on multivariate copula function in Henan Province, China

Abstract

AbstractGlobal droughts have become more frequent in recent years, posing a serious threat to human production and life. In order to overcome the limitations of traditional studies in quantifying drought risk, this study uses runs theory to extract drought duration, severity and kurtosis as drought characteristic variables from standardized precipitation index (SPI) in Henan Province. Drought risk analysis models based on multivariate copula function are constructed to reveal the response relationships between drought characteristic variables. The results show that the smaller the SPI scale, the higher the sensitivity to identify drought processes. In addition, the multivariate copula function shows good fitting performance for the optimal joint distribution of drought characteristic variables, with R2 values exceeding 0.9. Drought joint recurrence period is positively correlated with drought characteristic variables, and the recurrence period within the duration of 4–6 months occur frequently, indicating a higher probability of experiencing short-term droughts and cross-seasonal droughts. When the drought duration, severity and kurtosis are greater than 2.5, 2200 and 1300, respectively, the drought joint recurrence period reaches 20 months. The research results have provided new methods for drought risk analysis and data support for formulating drought mitigation strategies in Henan Province.

Keywords

• Drought
• Standardized Precipitation Index (SPI)
• Runs theory
• multivariate copula function
• risk analysis