Feng et al. (2026) Processes and driving mechanisms of drought propagation in Central Asia: A coupled perspective of meteorological, surface water, agricultural, and groundwater drought

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2026
• Date: 2026-03-31
• Authors: Sen Feng, Long Ma, Lingxin Kong, Jing Zhang, Jilili Abuduwaili, Gulnura Issanova
• DOI: 10.1016/j.ejrh.2026.103392

Research Groups

• State Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences
• Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences
• University of Chinese Academy of Sciences
• Xinjiang Key Laboratory of Water Cycle and Utilization in Arid Zone
• China-Kazakhstan Joint Laboratory for Remote Sensing Technology and Application, Al-Farabi Kazakh National University
• Faculty of Geography and Environment, Al-Farabi Kazakh National University

Short Summary

This study investigated the propagation processes and driving mechanisms of meteorological, surface water, agricultural, and groundwater droughts in Central Asia from 2003 to 2023. It found that meteorological, agricultural, and groundwater droughts intensified, with meteorological drought propagating rapidly to surface water (1.43 months) and agricultural drought (3.32 months), but much slower to groundwater drought (14.91–18.63 months), primarily driven by temperature, elevation, and precipitation, with regional variations influenced by aridity and mountain hydrology.

Objective

• Analyze the spatial and temporal evolution of meteorological drought (MD), surface water drought (SD), agricultural drought (AD), and groundwater drought (GD).
• Evaluate the propagation processes of multiple drought types and their regional differences.
• Identify the factors influencing the propagation process of multiple drought types.

Study Configuration

• Spatial Scale: Central Asia (46°29′–87°19′ E, 35°07′–55°26′ N).
• Temporal Scale: 2003–2023, with data processed on a monthly basis.

Methodology and Data

• Models used:
  • Run theory (for drought event detection)
  • Center of gravity model (for migration characteristics)
  • Maximal correlation analysis (for propagation processes)
  • Wavelet analyses (Cross wavelet transform (XWT), Wavelet coherence (WTC), Multiple wavelet coherence (MWC)) (for propagation processes)
  • Geodetector (for identifying key drivers and spatial differentiation)
  • XGBoost-SHAP (for identifying key drivers, nonlinear relationships, and directionality)
  • Mann–Kendall test (for trend detection)
  • Sen’s slope analysis (for trend magnitude)
  • Pearson correlation coefficient (for correlations)
  • Standardized Precipitation Index (SPI)
  • Standardized Soil Moisture Index (SSI)
  • Standardized Runoff Index (SRI)
  • Groundwater Drought Index (GDI)
• Data sources:
  • Precipitation (PRE): CRU TS4.08
  • Temperature (TMP): CRU TS4.08
  • Actual Evaporation (AE): GLEAM4.2 (The Global Land Evaporation Amsterdam Model)
  • Soil moisture (SM): GLDASNOAH025M (GLDAS Noah Land Surface Model L4)
  • Snow water equivalent (SWE): GLDASNOAH025M
  • Canopy water storage (CWE): GLDASNOAH025M
  • Terrestrial water storage anomaly (TWSA): CSR GRACE/GRACE-FO RL06 v03 Mascon
  • Normalized difference vegetation index (NDVI): MODIS/MOD13A2
  • Land cover type: MODIS/MCD12Q1
  • Elevation (Elev): EarthEnv Project Global Topography
  • Slope: EarthEnv Project Global Topography

Main Results

• Meteorological drought (MD), agricultural drought (AD), and groundwater drought (GD) generally intensified in Central Asia from 2003–2023, while surface water drought (SD) showed a slight alleviation.
• Drought centers of high frequency, duration, and intensity were primarily concentrated in the heart of Central Asia (approximately 61.3°–71.5° E, 43.1°–48.2° N).
• The average propagation time (PT) from MD to SD was relatively short (1.43 months), followed by MD to AD (3.32 months).
• The PT values from MD, SD, and AD to GD were significantly longer, averaging 14.91 months, 16.38 months, and 18.63 months, respectively.
• The propagation of MD to SD and AD was most pronounced in arid regions, with shorter PTs (1.01 months for MD-SD, 2.27 months for MD-AD) compared to semi-arid regions.
• Temperature (TMP), elevation (ELEV), and precipitation (PRE) were identified as the main drivers of drought propagation.
  • TMP (q value of 0.392) was the main driver for the maximum correlation coefficient (MCC) between MD and SD.
  • Runoff (q value of 0.544) was the main driver for PT between MD and SD.
  • TMP (q value of 0.214) and ELEV (q value of 0.207) were main drivers for MCC between MD and AD.
  • TMP (q value of 0.240) and PRE (q value of 0.182) were main drivers for PT between MD and AD.
  • TMP, soil moisture (SM), PRE, and Normalized Difference Vegetation Index (NDVI) were primary controls for MCC between MD and GD.
  • SM and runoff largely influenced MCC between SD and GD.
  • SM and TMP mainly affected MCC between AD and GD.
• High TMP positively contributed to MCC between MD and SD, AD, GD, and negatively to PT, indicating accelerated propagation.
• High PRE values consistently showed a positive contribution to drought propagation relationships and delayed PT.
• Mountain precipitation and snowmelt were crucial regulatory factors influencing regional drought development.
• Anthropogenic activities, particularly agricultural irrigation and groundwater extraction, significantly influenced GD and weakened its correlation with other drought types.

Contributions

• Provided novel insights into the dynamics and mechanisms of drought propagation in Central Asia under global change.
• Developed an integrated analytical framework combining maximal correlation, wavelet analyses, Geodetector, and XGBoost-SHAP to comprehensively understand drought propagation processes and driving mechanisms.
• Quantified the distinct propagation times and pathways among meteorological, surface water, agricultural, and groundwater droughts in Central Asia.
• Identified the key natural (temperature, elevation, precipitation, mountain precipitation, snowmelt) and anthropogenic (agricultural activities, groundwater extraction) drivers influencing different drought propagation stages, highlighting their complex, non-linear interactions and regional specificities.

Funding

• Natural Science Foundation of Xinjiang Uygur Autonomous Region (2023D01A07)
• Tianshan Talent Training Program (2023TSYCCX0083)
• Regional Collaborative Innovation Program of the Xinjiang Uygur Autonomous Region (2025E01057)
• Chinese Academy of Sciences Key Project for International Cooperation (E4610104)

Citation

@article{Feng2026Processes,
  author = {Feng, Sen and Ma, Long and Kong, Lingxin and Zhang, Jing and Abuduwaili, Jilili and Issanova, Gulnura},
  title = {Processes and driving mechanisms of drought propagation in Central Asia: A coupled perspective of meteorological, surface water, agricultural, and groundwater drought},
  journal = {Journal of Hydrology Regional Studies},
  year = {2026},
  doi = {10.1016/j.ejrh.2026.103392},
  url = {https://doi.org/10.1016/j.ejrh.2026.103392}
}