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<p>Human activities and climate change together have caused hydrometeorological extremes in watersheds to become increasingly nonstationary, posing potential risks to water resources management. This study proposes a dynamic C-Vine Copula-based (DCC) risk attribution framework to uncover the amplified role of urbanization and mitigating role of vegetation greening on the multivariate drought risk (MR) at the Yangtze River Delta (YZD: humid watershed) and Weihe River Basin (WRB: arid watershed). In order to simplify the process of model selection, a two-step optimization strategy combined with a series of modelling selection tests (including LR test, <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\:{GOF}_{ec}\)</EquationSource> </InlineEquation> test, and the minimum <i>AICc</i> criterion) was implemented to efficiently model the nonstationary multivariate dependence structure characterized by drought intensity (I), duration (D), and affected area (A). A linear regression-derived slope comparative approach was proposed to quantify and differentiate the urbanization-induced and vegetation greening-induced impact on MR. Results demonstrated that the multivariate drought risk of WRB, as an arid region, had been alleviated mostly by the soil and water conservation projects promoted in the recent 20 years. Although both urbanization (denoted by PISA) and vegetation greening index (denoted by NDVI) were detected as significant covariates of nonstationary DCC model for the YZD, only the amplified role of urbanization on drought MR was apparent. The impact of urbanization and vegetation greening on drought risk varies slightly depending on regional development differences. The results are anticipated to offer insights for mitigating drought impacts and informing related policy decisions.</p>

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Quantifying the Urbanization and Vegetation Greening Effect on Spatiotemporal Continuous Drought Risk Via Nonstationary C-Vine Copula Model

  • 期刊论文

  • 发表日期：

    2025年12月20日

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  • Pengcheng Xu,
  • Dong Wang,
  • Yuankun Wang,
  • Vijay P. Singh

摘要

Human activities and climate change together have caused hydrometeorological extremes in watersheds to become increasingly nonstationary, posing potential risks to water resources management. This study proposes a dynamic C-Vine Copula-based (DCC) risk attribution framework to uncover the amplified role of urbanization and mitigating role of vegetation greening on the multivariate drought risk (MR) at the Yangtze River Delta (YZD: humid watershed) and Weihe River Basin (WRB: arid watershed). In order to simplify the process of model selection, a two-step optimization strategy combined with a series of modelling selection tests (including LR test, \(\:{GOF}_{ec}\) test, and the minimum AICc criterion) was implemented to efficiently model the nonstationary multivariate dependence structure characterized by drought intensity (I), duration (D), and affected area (A). A linear regression-derived slope comparative approach was proposed to quantify and differentiate the urbanization-induced and vegetation greening-induced impact on MR. Results demonstrated that the multivariate drought risk of WRB, as an arid region, had been alleviated mostly by the soil and water conservation projects promoted in the recent 20 years. Although both urbanization (denoted by PISA) and vegetation greening index (denoted by NDVI) were detected as significant covariates of nonstationary DCC model for the YZD, only the amplified role of urbanization on drought MR was apparent. The impact of urbanization and vegetation greening on drought risk varies slightly depending on regional development differences. The results are anticipated to offer insights for mitigating drought impacts and informing related policy decisions.