Quantifying driving mechanisms and spatial optimization of water supply-demand dynamics in humid subtropical regions: Evidence from a typical hilly region of southern China (1996–2023)

Humid regions, traditionally regarded as relatively water-abundant, are increasingly facing localized water scarcity and spatial mismatches between water supply and demand under the combined pressures of rapid urbanization, industrial agglomeration, and climate change. This study focused on Jiangxi Province, a representative humid subtropical region in China. We developed an integrated analytical framework by coupling the InVEST model, bivariate spatial autocorrelation analysis, and XGBoost-SHAP interpretable machine learning. This framework was used to systematically examine the spatiotemporal dynamics of regional water supply (WS) and water demand (WD) from 1996 to 2023, identify spatial clustering patterns, quantify key influencing factors and their spatially heterogeneous model-based contributions, and delineate differentiated water-resource management zones. The results showed that: (1) Jiangxi Province generally remained in a water-surplus condition during 1996–2023, with a mean water security index (WSI) of 0.36; however, WD increased by 21.57%, far exceeding the increase in WS of 2.21%. The spatial distributions of regional water supply and demand exhibited a relatively stable pattern characterized by long-term supply–demand surplus in mountainous areas and intensifying imbalance in the northern plain. (2) based on a two-dimensional zoning framework integrating WSI surplus–deficit status and spatial clustering patterns, the study area was divided into five functional zones, and corresponding management strategies were proposed for each zone. (3) gross domestic product (GDP) and precipitation (PRE) were the most important contributing factors associated with WSI. The negative contribution of GDP was most pronounced in the urban agglomerations of the northern plain, whereas the positive contributions of PRE, slope, and plant available water content (PAWC) were concentrated in the eastern and southern mountainous areas, highlighting the spatially heterogeneous associations of natural endowments and human activities with WSI. This study provides a transferable methodological reference for identifying water supply–demand mismatches, diagnosing WSI, formulating differentiated management strategies, and the understanding of driving mechanisms in humid subtropical regions

Authors

Institutions

Publication Details

Journal
Ecological Indicators
Published
2026-07-28
DOI
https://doi.org/10.1016/j.ecolind.2026.115275
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantifying driving mechanisms and spatial optimization of water supply-demand dynamics in humid subtropical regions: Evidence from a typical hilly region of southern China (1996–2023)

Peng Li, Shi Qi
Ecological Indicators
Land Use and Ecosystem Services
article

Quantifying driving mechanisms and spatial optimization of water supply-demand dynamics in humid subtropical regions: Evidence from a typical hilly region of southern China (1996–2023)

Peng Li, Shi Qi
article en

Abstract

Humid regions, traditionally regarded as relatively water-abundant, are increasingly facing localized water scarcity and spatial mismatches between water supply and demand under the combined pressures of rapid urbanization, industrial agglomeration, and climate change. This study focused on Jiangxi Province, a representative humid subtropical region in China. We developed an integrated analytical framework by coupling the InVEST model, bivariate spatial autocorrelation analysis, and XGBoost-SHAP interpretable machine learning. This framework was used to systematically examine the spatiotemporal dynamics of regional water supply (WS) and water demand (WD) from 1996 to 2023, identify spatial clustering patterns, quantify key influencing factors and their spatially heterogeneous model-based contributions, and delineate differentiated water-resource management zones. The results showed that: (1) Jiangxi Province generally remained in a water-surplus condition during 1996–2023, with a mean water security index (WSI) of 0.36; however, WD increased by 21.57%, far exceeding the increase in WS of 2.21%. The spatial distributions of regional water supply and demand exhibited a relatively stable pattern characterized by long-term supply–demand surplus in mountainous areas and intensifying imbalance in the northern plain. (2) based on a two-dimensional zoning framework integrating WSI surplus–deficit status and spatial clustering patterns, the study area was divided into five functional zones, and corresponding management strategies were proposed for each zone. (3) gross domestic product (GDP) and precipitation (PRE) were the most important contributing factors associated with WSI. The negative contribution of GDP was most pronounced in the urban agglomerations of the northern plain, whereas the positive contributions of PRE, slope, and plant available water content (PAWC) were concentrated in the eastern and southern mountainous areas, highlighting the spatially heterogeneous associations of natural endowments and human activities with WSI. This study provides a transferable methodological reference for identifying water supply–demand mismatches, diagnosing WSI, formulating differentiated management strategies, and the understanding of driving mechanisms in humid subtropical regions

Ecological IndicatorsVol. 189
Beijing Forestry University (CN)
Sustainable cities and communities
Openalex Percentile: Top 10%
Land Use and Ecosystem Services
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.