Li et al. (2026) Mapping Groundwater‐Dependent Ecosystems for Contiguous China With Selected Hydroclimatic Windows

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

Identification

• Journal: Water Resources Research
• Year: 2026
• Date: 2026-09-01
• Authors: Huixiang Li, Yun Pan, Huade Guan
• DOI: 10.1029/2025wr042737

Research Groups

Not specified in the provided text.

Short Summary

The study developed a mapping framework integrating remote sensing, soil, and modeled groundwater depth to identify Groundwater-dependent ecosystems (GDEs) across contiguous China, identifying varying levels of GDE potential across the region.

Objective

• To systematically map the distribution of Groundwater-dependent ecosystems (GDEs) across both arid and humid regions of contiguous China to improve water resource management and ecosystem conservation.

Study Configuration

• Spatial Scale: Contiguous China.
• Temporal Scale: Long-term (utilizing long-term remote sensing data).

Methodology and Data

• Models used: Modeled groundwater depth (GWD) data.
• Data sources: Remote sensing data, soil data, and drought-related climatic data.

Main Results

• GDEs were categorized by potential: high-potential (1.6%), moderate-potential (7.7%), and low-potential (22.1%) of the mapped area.
• The map demonstrated a commission error of 13.6% against observed GWD, assuming a vegetation rooting depth within $10\text{ m}$.
• The reliability of the mapping was validated through the analysis of vegetation responses to drought and characteristic topographic settings.

Contributions

• Establishes a systematic framework for mapping GDEs across diverse climatic zones (arid to humid) in China, addressing a significant gap in the known distribution of these critical ecosystems.

Funding

Not specified in the provided text.

Citation

@article{Li2026Mapping,
  author = {Li, Huixiang and Pan, Yun and Guan, Huade},
  title = {Mapping Groundwater‐Dependent Ecosystems for Contiguous China With Selected Hydroclimatic Windows},
  journal = {Water Resources Research},
  year = {2026},
  doi = {10.1029/2025wr042737},
  url = {https://doi.org/10.1029/2025wr042737}
}