Tang et al. (2025) Analyzing the Driving Mechanism of Drought Using the Ecological Aridity Index Considering the Evapotranspiration Deficit—A Case Study in Xinjiang, China

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Agriculture
• Year: 2025
• Date: 2025-09-26
• Authors: Hao Tang, Qiao Li, Hongfei Tao, Pingan Jiang, Chenqian Tang, Xiangzhi Kong
• DOI: 10.3390/agriculture15192016

Research Groups

The provided text does not specify the research groups, labs, or departments involved.

Short Summary

This study developed a multivariate comprehensive drought index (MCDI) by integrating evapotranspiration deficit (ED) for the first time, alongside atmospheric water deficit, soil moisture, and runoff, using both Copula and nonparametric methods. It found that the nonparametric method was superior, soil moisture was the main driver of ecological drought in Xinjiang, China, and a strong synergistic effect exists between soil moisture and ED.

Objective

• To develop a rational ecological drought monitoring and assessment model.
• To incorporate evapotranspiration deficit (ED) into the construction of an ecological drought index for the first time.
• To construct a multivariate comprehensive drought index (MCDI) using both Copula and nonparametric methods, considering atmospheric water deficit (WD), soil moisture (SM), and runoff (RF).
• To evaluate the MCDI using various statistical methods to assess differences between construction methods.
• To analyze the drivers and sensitivities of ecological drought in Xinjiang, China.
• To specifically explore the role of ED in ecological drought.

Study Configuration

• Spatial Scale: Xinjiang, China (arid regions).
• Temporal Scale: Time series analysis, specific duration not provided.

Methodology and Data

• Models used:
  • Copula method (for MCDI construction)
  • Nonparametric method (for MCDI construction)
  • Pearson correlation
  • Actual drought validation
  • Theil–Sen estimator
  • Mann–Kendall test
  • ExtraTrees+SHAP methods (for driver analysis and sensitivity assessment)
• Data sources: The study utilized evapotranspiration deficit (ED), atmospheric water deficit (WD), soil moisture (SM), and runoff (RF). Specific data acquisition methods (e.g., satellite, observation, reanalysis) for these variables are not detailed in the provided text.

Main Results

• Evapotranspiration deficit (ED) based on the ratio form is more suitable for capturing soil moisture (SM) changes.
• The performance of the composite drought index improved in all aspects when cumulative effects were considered.
• The ecological drought index constructed using the nonparametric method was superior to the index using the Copula method.
• Soil moisture (SM) was identified as the main contributor to ecological drought in Xinjiang.
• The strongest synergistic effect occurred between soil moisture (SM) and evapotranspiration deficit (ED).
• The sensitivity of ecological drought to soil moisture within arid regions increased nonlinearly along the decreasing SM gradient.
• The sensitivity to all drivers (runoff, soil moisture, evapotranspiration deficit) increased over time, with the largest increase observed for runoff (RF), followed by soil moisture (SM), and then evapotranspiration deficit (ED).

Contributions

• First-time integration of evapotranspiration deficit (ED) into an ecological drought index, providing a novel component for drought assessment.
• Development and validation of a multivariate comprehensive drought index (MCDI) that considers multiple hydrological components.
• Identification of the nonparametric method as a superior and computationally efficient approach for drought index construction, offering a useful reference for global-scale applications.
• Pinpointing soil moisture as the primary driver of ecological drought in the arid Xinjiang region.
• Discovery of a significant synergistic effect between ED and SM, which provides a new theoretical basis for ecological drought prevention and management strategies in arid environments.

Funding

The provided text does not contain information regarding funding sources.

Citation

@article{Tang2025Analyzing,
  author = {Tang, Hao and Li, Qiao and Tao, Hongfei and Jiang, Pingan and Tang, Chenqian and Kong, Xiangzhi},
  title = {Analyzing the Driving Mechanism of Drought Using the Ecological Aridity Index Considering the Evapotranspiration Deficit—A Case Study in Xinjiang, China},
  journal = {Agriculture},
  year = {2025},
  doi = {10.3390/agriculture15192016},
  url = {https://doi.org/10.3390/agriculture15192016}
}