Li et al. (2026) An Interpretable Index-Based Analysis and Scenario-Based Spatial Simulation of Vegetation Drought in the Yellow River Water Conservation Area

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Identification

• Journal: Land
• Year: 2026
• Date: 2026-02-06
• Authors: Rong Li, Rui Zhu, Zhenliang Yin, Tong Li, Mengwei Li, Ganlin Zhou
• DOI: 10.3390/land15020276

Research Groups

Specific research groups, labs, or departments are not explicitly mentioned in the provided paper text.

Short Summary

This study developed a Temperature–Vegetation–Precipitation Drought Index (TVPDI) to characterize vegetation drought dynamics in the Yellow River Water Conservation Area (YRWC) and analyzed the nonlinear responses of key factors, finding that precipitation is the primary driver and high-emission scenarios significantly exacerbate future drought severity.

Objective

• To characterize the spatio-temporal dynamics of vegetation drought in the Yellow River Water Conservation Area (YRWC) for 2003, 2012, and 2019.
• To quantitatively analyze the nonlinear response characteristics and relative contributions of key factors within the TVPDI framework using XGBoost–SHAP.
• To conduct scenario-based spatial simulations of vegetation drought for 2035 to assess future impacts under different emission pathways.

Study Configuration

• Spatial Scale: Yellow River Water Conservation Area (YRWC), a core water source of the Yellow River Basin.
• Temporal Scale: Analysis for 2003, 2012, and 2019; scenario-based simulations for 2035.

Methodology and Data

• Models used:
  • Temperature–Vegetation–Precipitation Drought Index (TVPDI) - constructed for drought characterization.
  • XGBoost–SHAP framework - employed for quantitative analysis of nonlinear responses and relative contributions of factors.
  • GeoSOS-FLUS model - used for scenario-based spatial simulations of vegetation drought.
• Data sources:
  • Precipitation data (component of TVPDI).
  • Land surface temperature data (component of TVPDI).
  • NDVI (Normalized Difference Vegetation Index) data (component of TVPDI).
  • Atmospheric moisture conditions data (external factor).
  • Topographic factors data (external factor).
  • Human activity factors data (external factor).

Main Results

• Vegetation drought in the YRWC exhibits a relatively stable spatial pattern, with severity gradually intensifying from southeast to northwest.
• Moderate drought is identified as the dominant type of vegetation drought in the region.
• Precipitation is the key variable influencing TVPDI, followed by land surface temperature.
• NDVI primarily plays a nonlinear regulatory role within the TVPDI framework.
• Among external factors, atmospheric moisture conditions demonstrate relatively higher explanatory relevance for vegetation drought.
• Topographic and human activity factors exert comparatively weaker influences on vegetation drought.
• Scenario-based simulations suggest that vegetation drought may be alleviated under low-emission pathways by 2035.
• High-emission scenarios are projected to substantially exacerbate drought severity and associated risks by 2035.

Contributions

• Presents an interpretable, index-based analytical framework (TVPDI) for characterizing vegetation drought.
• Integrates the TVPDI framework with scenario-based spatial simulation using the GeoSOS-FLUS model.
• Utilizes the XGBoost–SHAP framework to quantitatively analyze nonlinear responses and relative contributions of key drought factors.
• Provides scientific support for ecological management and climate adaptation strategies in the Yellow River Basin.

Funding

No specific funding projects, programs, or reference codes are mentioned in the provided paper text.

Citation

@article{Li2026Interpretable,
  author = {Li, Rong and Zhu, Rui and Yin, Zhenliang and Li, Tong and Li, Mengwei and Zhou, Ganlin},
  title = {An Interpretable Index-Based Analysis and Scenario-Based Spatial Simulation of Vegetation Drought in the Yellow River Water Conservation Area},
  journal = {Land},
  year = {2026},
  doi = {10.3390/land15020276},
  url = {https://doi.org/10.3390/land15020276}
}