Land Use–Future Climate Coupling Mechanism Analysis of Regional Agricultural Drought Spatiotemporal Patterns

Jing Wang, Zhenjiang Si (), Tao Liu, Yan Liu and Longfei Wang
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Jing Wang: School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150006, China
Zhenjiang Si: School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150006, China
Tao Liu: School of Hydraulic and Electric Power, Heilongjiang University, Harbin 150006, China
Yan Liu: Heilongjiang Provincial Water Resources Research Institute, Harbin 150080, China
Longfei Wang: Heilongjiang Provincial Water Resources Research Institute, Harbin 150080, China

Sustainability, 2025, vol. 17, issue 15, 1-41

Abstract: This study assesses future agricultural drought risk in the Ganjiang River Basin under climate change and land use change. A coupled analysis framework was established using the SWAT hydrological model, the CMIP6 climate models (SSP1-2.6, SSP2-4.5, SSP5-8.5), and the PLUS land use simulation model. Key methods included the Standardized Soil Moisture Index (SSMI), travel time theory for drought event identification and duration analysis, Mann–Kendall trend test, and the Pettitt change-point test to examine soil moisture dynamics from 2027 to 2100. The results indicate that the CMIP6 ensemble performs excellently in temperature simulations, with a correlation coefficient of R 2 = 0.89 and a root mean square error of RMSE = 1.2 °C, compared to the observational data. The MMM-Best model also performs well in precipitation simulations, with R 2 = 0.82 and RMSE = 15.3 mm, compared to observational data. Land use changes between 2000 and 2020 showed a decrease in forestland (−3.2%), grassland (−2.8%), and construction land (−1.5%), with an increase in water (4.8%) and unused land (2.7%). Under all emission scenarios, the SSMI values fluctuate with standard deviations of 0.85 (SSP1-2.6), 1.12 (SSP2-4.5), and 1.34 (SSP5-8.5), with the strongest drought intensity observed under SSP5-8.5 (minimum SSMI = −2.8). Drought events exhibited spatial and temporal heterogeneity across scenarios, with drought-affected areas ranging from 25% (SSP1-2.6) to 45% (SSP5-8.5) of the basin. Notably, abrupt changes in soil moisture under SSP5-8.5 occurred earlier (2045–2050) due to intensified land use change, indicating strong human influence on hydrological cycles. This study integrated the CMIP6 climate projections with high-resolution human activity data to advance drought risk assessment methods. It established a framework for assessing agricultural drought risk at the regional scale that comprehensively considers climate and human influences, providing targeted guidance for the formulation of adaptive water resource and land management strategies.

Keywords: agricultural drought; land use; SSMI; SWAT; PLUS; CMIP6 (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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