Wang et al. (2026) A multivariate framework to quantify propagation characteristics from soil drought to socio-ecological productivity

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2026
• Date: 2026-01-06
• Authors: Chengyun Wang, Jie Chen, Sung‐Ching Lee, Chong-Yu Xu
• DOI: 10.1016/j.ejrh.2025.103080

Research Groups

• State Key Laboratory of Water Resources Engineering and Management, Wuhan University, China.
• Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany.
• Department of Geosciences, University of Oslo, Norway.

Short Summary

This study develops a multivariate framework to quantify how soil moisture deficits propagate into vegetation productivity losses and evaluates the resulting exposure of crops, GDP, and population across China under historical and future climate scenarios. The findings reveal that the proportion of vegetation-loss events triggered by soil drought will increase significantly, with distinct regional shifts in ecosystem resistance and socio-economic vulnerability.

Objective

• To investigate the dynamics of drought propagation characteristics (duration, severity, response lag, and recovery length) from soil moisture to socio-ecological productivity.
• To quantify the joint risk of drought-induced vegetation loss and its impact on major crops, GDP, and population under various RCP–SSP pathways.

Study Configuration

• Spatial Scale: National scale (China), divided into seven distinct climatic and ecological sub-regions, with a spatial resolution of 0.25° × 0.25°.
• Temporal Scale: Historical period (1989–2019), near-future (2030–2060), and far-future (2070–2099).

Methodology and Data

• Models used: Six Dynamic Global Vegetation Models (DGVMs) from ISIMIP2b; three crop models (GEPIC, LPJmL, PEPIC); and four CMIP5 General Circulation Models (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC5).
• Data sources: ERA5 reanalysis (soil moisture), VODCA2GPP satellite-derived archive (historical GPP), EarthStat (crop area), and gridded population/GDP projections under Shared Socioeconomic Pathways (SSPs).
• Analytical Techniques: Run theory for event identification; Multivariate Bias Correction (MBCn); Copula-based joint probability modeling; and the Most Likely Realization (MLR) method for multivariate risk assessment.

Main Results

• Propagation Frequency: The proportion of vegetation productivity loss events triggered by soil drought is projected to rise from 33% historically to 57% in future scenarios.
• Regional Dynamics: Northern China is characterized by shorter but more intense droughts with rapid vegetation response and prolonged recovery. Southern China experiences longer droughts but shows increasing vegetation resistance.
• Vegetation Resistance: Areas exhibiting drought resistance are projected to expand from 19–24% (2030–2060) to 22–29% (2070–2099), particularly under high-emission scenarios (RCP8.5).
• Socio-ecological Exposure: Soybean (53.0%) and maize (52.7%) are the most exposed crops to drought propagation risks. GDP and population exposure cluster heavily in the North China Plain and southeastern coastal regions, with exposure indices often reaching ~0.9.
• Atmospheric Drivers: Propagation events are strongly linked to land–atmosphere coupling, specifically suppressed moisture convergence, low convective potential (CAPE), and high evaporative demand.

Contributions

• Establishes a novel, transferable multivariate framework that integrates event-based matching with copula-based probability to link biophysical drought processes with socio-economic impacts.
• Quantifies the "response-recovery" trade-off in ecosystems, identifying a shift toward faster onset and slower recovery in northern Chinese ecosystems.
• Provides a spatially explicit assessment of socio-economic vulnerability in China, highlighting the intersection of climate forcing and development pathways (SSP-RCP).

Funding

• National Natural Science Foundation of China (Grant No. W2412158).
• Hubei Provincial Natural Science Foundation of China (Grant No. 2025AFA023).
• Overseas Expertise Introduction Project for Discipline Innovation (111 Project) (Grant No. B18037).

Citation

@article{Wang2026multivariate,
  author = {Wang, Chengyun and Chen, Jie and Lee, Sung‐Ching and Xu, Chong-Yu},
  title = {A multivariate framework to quantify propagation characteristics from soil drought to socio-ecological productivity},
  journal = {Journal of Hydrology Regional Studies},
  year = {2026},
  doi = {10.1016/j.ejrh.2025.103080},
  url = {https://doi.org/10.1016/j.ejrh.2025.103080}
}

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