Matching Degree between Agricultural Water and Land Resources in the Xijiang River Basin under Changing Environment

Abstract

The matching degree between agricultural water and land resources directly determines the sustainable development of regional agriculture. Based on climate data corrected by delta statistical downscaling from five global climate models (GCMs) in the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a multi-model ensemble, this study simulated the runoff used by the Variable Infiltration Capacity (VIC-3L) model under four emission scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) and analyzed the land use changing trend to obtain the matching degree between agricultural water and land resources. The results demonstrate that annual climate factors exhibit an increasing trend, and the average annual runoff was 2128.08–2247.73 × 108 m3, during 2015–2100 under the four scenarios. The area of farmland changed with an increased area of 4201 km2 from 1980 to 2020. The agricultural water and land resources would be well matched under the SSP1-2.6 and SSP2-4.5 scenarios in 2021–2100. However, the risks of mismatch would occur in the 2030–2040 and 2050–2060 periods under the SSP3-7.0 scenario, and the 2030–2040 and 2080–2090 periods under the SSP5-8.5 scenario. This study can provide insight into the scientific decision support for government departments to address the challenges of mismatching risks of agricultural water and land resources.