Analyzing the Driving Mechanism of Drought Using the Ecological Aridity Index Considering the Evapotranspiration Deficit—A Case Study in Xinjiang, China

With global warming, the increasing frequency of drought events threatens the stability of ecosystems, so the development of a rational ecological drought monitoring and assessment model is urgently needed. In this study, an evapotranspiration deficit (ED) was added for the first time into the construction of an ecological drought index. Considering atmospheric water deficit (WD), soil moisture (SM) and runoff (RF), both the Copula method and a nonparametric method were used to construct a multivariate comprehensive drought index (MCDI) to monitor ecological drought. The MCDI was evaluated using Pearson, actual drought validation, Theil–Sen, Mann–Kendall and ExtraTrees+SHAP methods, in order to assess differences between construction methods, analyze the drivers and sensitivities of ecological drought in Xinjiang, China, and specifically explore the role of ED in ecological drought. The results showed that (1) ED based on the ratio form is more suitable for capturing SM changes; (2) the performance of the composite drought index was improved in all aspects when cumulative effects were considered, and the ecological drought index based on the nonparametric method was superior to the index using the Copula method; (3) soil moisture was identified as the main contributor to ecological drought in Xinjiang, with the strongest synergistic effect occurring between SM and ED; and (4) the sensitivity of ecological drought to soil moisture within the arid regions increased nonlinearly along the decreasing SM gradient. In addition, the sensitivity to all drivers increased over time, with the largest increase observed for RF, followed by SM and then ED. The findings of this paper provide a useful reference for constructing a comprehensive drought index at the global scale, since the nonparametric method requires considerably fewer computational resources compared with the Copula method. In addition, the identified synergistic effect of ED and SM offers a new theoretical basis for ecological drought prevention and management in arid regions.

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Publication Details

Journal
Agriculture
Published
2025-09-26
DOI
https://doi.org/10.3390/agriculture15192016
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.11

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article

Analyzing the Driving Mechanism of Drought Using the Ecological Aridity Index Considering the Evapotranspiration Deficit—A Case Study in Xinjiang, China

Pingan Jiang, Chenqian Tang, Qiao Li, Hongfei Tao et al.
1 citations
Agriculture
Climate variability and models
1.11
article

Analyzing the Driving Mechanism of Drought Using the Ecological Aridity Index Considering the Evapotranspiration Deficit—A Case Study in Xinjiang, China

Pingan Jiang, Chenqian Tang, Qiao Li, Hongfei Tao, Xiangzhi Kong, Hao Tang
article en
1 citations

Abstract

With global warming, the increasing frequency of drought events threatens the stability of ecosystems, so the development of a rational ecological drought monitoring and assessment model is urgently needed. In this study, an evapotranspiration deficit (ED) was added for the first time into the construction of an ecological drought index. Considering atmospheric water deficit (WD), soil moisture (SM) and runoff (RF), both the Copula method and a nonparametric method were used to construct a multivariate comprehensive drought index (MCDI) to monitor ecological drought. The MCDI was evaluated using Pearson, actual drought validation, Theil–Sen, Mann–Kendall and ExtraTrees+SHAP methods, in order to assess differences between construction methods, analyze the drivers and sensitivities of ecological drought in Xinjiang, China, and specifically explore the role of ED in ecological drought. The results showed that (1) ED based on the ratio form is more suitable for capturing SM changes; (2) the performance of the composite drought index was improved in all aspects when cumulative effects were considered, and the ecological drought index based on the nonparametric method was superior to the index using the Copula method; (3) soil moisture was identified as the main contributor to ecological drought in Xinjiang, with the strongest synergistic effect occurring between SM and ED; and (4) the sensitivity of ecological drought to soil moisture within the arid regions increased nonlinearly along the decreasing SM gradient. In addition, the sensitivity to all drivers increased over time, with the largest increase observed for RF, followed by SM and then ED. The findings of this paper provide a useful reference for constructing a comprehensive drought index at the global scale, since the nonparametric method requires considerably fewer computational resources compared with the Copula method. In addition, the identified synergistic effect of ED and SM offers a new theoretical basis for ecological drought prevention and management in arid regions.

AgricultureVol. 15(19)
Xinjiang Agricultural University (CN), Xinjiang Institute of Water Resources and Hydropower Research (CN)
Natural Science Foundation of Xinjiang
Openalex Percentile: Top 19%
Climate variability and models
1.11
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