Wei et al. (2026) Antecedent soil moisture controls meteorological-to-agricultural drought triggering thresholds

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Date: 2026-09-19
• Authors: Xiaoting Wei, Shengzhi Huang, Dong Liu, Qiang Huang, Qingqing Qi, Zezhong Zhang, Yifei Li, Hao Cui, Mingjiang Deng
• DOI: 10.1016/j.agwat.2026.110803

Research Groups

• College of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, China
• State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an, China

Short Summary

This study developed an improved vine copula-based framework to quantify meteorological-to-agricultural drought triggering thresholds across mainland China by explicitly incorporating antecedent soil moisture. It found that drier antecedent conditions lead to higher triggering thresholds, making croplands more vulnerable, and identified land-atmosphere coupling as the dominant control on threshold spatial variability.

Objective

• To develop an improved drought-triggering-threshold framework that explicitly incorporates antecedent soil moisture into the estimation of meteorological-to-agricultural drought propagation using a vine copula model.
• To quantify the propagation time from meteorological drought to agricultural drought.
• To estimate meteorological drought triggering thresholds under different trigger probabilities, antecedent soil moisture conditions, and agricultural drought severities.
• To examine the temporal changes in triggering thresholds using a moving-window approach.
• To identify the dominant factors controlling the spatial variability of triggering thresholds using the Geodetector method.

Study Configuration

• Spatial Scale: Mainland China, with all variables resampled to a spatial resolution of 0.5° × 0.5°.
• Temporal Scale: Summer months (June, July, August) at monthly resolution, with an 18-year moving window (e.g., 1982–1999 to 2001–2018) for trend analysis.

Methodology and Data

• Models used:
  • Vine copula functions (Gumbel, Clayton, Frank, Gaussian, Student’s t copulas) for multivariate dependence modeling.
  • Akaike Information Criterion (AIC) and Root Mean Square Error (RMSE) for optimal copula selection.
  • Standardized Precipitation Index (SPI) for meteorological drought.
  • Standardized Soil Moisture Index (SMI) for agricultural drought.
  • Geodetector method for quantifying driving forces and interaction effects.
  • Mann-Kendall test for detecting long-term trends.
• Data sources:
  • Monthly precipitation and monthly mean temperature: National Meteorological Science Data Center.
  • Soil moisture (average across 0–7 cm, 7–28 cm, 28–100 cm, and 100–289 cm layers): ERA5-Land reanalysis dataset.
  • Soil type, land use, Gross Domestic Product (GDP): Resources and Environmental Science and Data Center of the Chinese Academy of Sciences.
  • Nighttime light data: National Tibetan Plateau Data Center.
  • Normalized Difference Vegetation Index (NDVI): National Earth System Science Data Center.
  • Topographic variables (elevation, slope, aspect): Geospatial Data Cloud.
  • Large-scale climate indices (El Niño–Southern Oscillation (ENSO), Arctic Oscillation (AO), Southern Oscillation Index (SOI), Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO)): NOAA Physical Sciences Laboratory.

Main Results

• Drought propagation from meteorological to agricultural drought is generally rapid, mostly occurring within three months, with faster propagation observed in southern China.
• Drier antecedent soil moisture systematically leads to higher triggering thresholds (i.e., less severe meteorological drought is needed to trigger agricultural drought), indicating enhanced likelihood of propagation under dry antecedent conditions.
• Croplands consistently exhibit higher triggering thresholds than non-croplands across varying antecedent moisture conditions, reflecting their heightened vulnerability to precipitation deficits.
• Approximately 70% of mainland China exhibits an increasing trend in triggering thresholds, with the drought sensitivity of croplands intensifying at a significantly faster rate than that of natural environments.
• Land-atmosphere coupling, particularly the correlation between precipitation and soil moisture (Corr(P, SM)), is the dominant control on the spatial variability of triggering thresholds.
• Interactions among meteorological, surface, and coupling factors consistently exhibit strong nonlinear enhancement effects on triggering thresholds.

Contributions

• Developed an improved vine copula-based framework that explicitly incorporates antecedent soil moisture memory into the estimation of meteorological-to-agricultural drought triggering thresholds.
• Provided a more process-consistent and risk-relevant estimate of drought propagation thresholds compared to conventional bivariate copula approaches.
• Quantified the distinct vulnerabilities of croplands versus non-croplands to drought propagation under varying antecedent conditions.
• Identified the dominant role of land-atmosphere coupling and the complex, nonlinear interactions of multiple factors in controlling drought triggering thresholds.

Funding

• National Key R&D Program of China (grant number 2024YFC3212900)
• National Natural Science Foundation of China (grant number 52279026)
• National Natural Science Foundation of China (grant number 52509017)
• Key Science Foundation Project of Henan Provincial Natural Science Foundation (grant number 252300421259)
• Project of Nyingchi Science and Technology Program (QYXTZX2026–01)
• Henan Province University Science and Technology Innovation Team Support Plan (grant number 26IRTSTHN022)
• China Postdoctoral Science Foundation (2025M783185)
• Natural Science Foundation of Henan (grant number 262300421970)
• Postdoctoral Fellowship Program (Grade C) of China Postdoctoral Science Foundation (grant Number GZC20261697)

Citation

@article{Wei2026Antecedent,
  author = {Wei, Xiaoting and Huang, Shengzhi and Liu, Dong and Huang, Qiang and Qi, Qingqing and Zhang, Zezhong and Li, Yifei and Cui, Hao and Deng, Mingjiang},
  title = {Antecedent soil moisture controls meteorological-to-agricultural drought triggering thresholds},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2026.110803},
  url = {https://doi.org/10.1016/j.agwat.2026.110803}
}