Abstract

Waterlogging refers to the damage to plants by water stress due to excess soil water in the crop’s root zone that exceeds the maximum water holding capacity of the field. It is one of the major disasters affecting agricultural production. This study aims to add a crop waterlogging identification module to the coupled SWAT (Soil and Water Assessment Tools)-MODFLOW (Modular Finite Difference Groundwater Flow Model) model and to accurately identify and predict crop waterlogging risk areas under the CMIP6 (Coupled Model Intercomparison Project 6) climate scenarios. The result showed that: (1) The SWAT-MODFLOW model, which coupled with a crop waterlogging identification module, had good simulation results for LAI (Leaf Area Index), ET (Evapotranspiration), spring wheat yield, and groundwater level in the middle and lower reaches of the Bayin River; (2) The precipitation showed an overall increasing trend in the Bayin River watersheds over the next 80 years under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios. The temperature showed a clear increasing trend over the next 80 years under the SSP2-4.5 and SSP5-8.5 scenarios; (3) Under the SSP1-2.6 scenario, the mountain runoff from the upper reaches of the Bayin River was substantially higher than in other scenarios after 2041. The mountain runoff in the next 80 years will decrease substantially under the SSP2-4.5 scenario. The mountain runoff over the next 80 years showed an initial decrease and then an increasing trend under the SSP5-8.5 scenario; (4) During the historical period, the crop waterlogging risk area was 10.9 km2. In the next 80 years, the maximum crop waterlogging area will occur in 2055 under the SSP1-2.6 scenario. The minimum crop waterlogging area, 9.49 km2, occurred in 2042 under the SSP2-4.5 scenario. The changes in the area at risk of crop waterlogging under each scenario are mainly influenced by the mountain runoff from the upper reaches of the Bayin River.

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