(1.School of Geography and Information Engineering， China University of Geosciences (Wuhan)， Wuhan 430074，China；2.Hubei Key Laboratory of Watershed Critical Zone Evolution， China University of Geosciences (Wuhan)，Wuhan 430074，China)
Abstract：Environmental changes have a great impact on the hydrological cycle of the basin， and soil water content and groundwater recharge are key elements in the hydrological cycle. The study establishes a SWAT model based on a variety of data to simulate the soil water content (SW) and groundwater recharge (GW) in the Madu River basin from 1981—2018， analyzes the characteristics of the temporal and spatial variations of the basin's GW and SW over the years and explores the response between them and the environmental factors. The results of the study are as follows： 1) The SWAT model of Madu River basin was established， and remote sensing data were used to rate the model parameters. The accuracy of the seven selected sub-basins in the rate period was good (R2 〉0.5， NSE〉0.5)， and the accuracy was verified using the remotely sensed ET data and the measured data of Fangxian County， and the accuracy met the requirements. 2) The average values of SW and GW in the basin are 18.7% and 50.93 mm/year respectively， and the distribution of GW in the basin is bimodal， while the distribution of SW in the basin is unimodal. 3) Spatially， the distribution of SW and GW in the basin shows the characteristics of “low in the north and high in the south”， and both of them show a weak downward trend. 4) Different soil types and different land use types have some influence on the GW and SW of the watershed. Among the land use types， the cropland type has the largest GW and SW mean value in the watershed； among the soil types， the colorful and highly active leachate soil has the largest SW， and the calcareous loose rocky soil has the largest GW； the watershed SW does not have a significant response to changes in the different slope classes， and the GW has the characteristic that the smaller the slope is， the larger the value of GW is. 5) The watershed SW and GW show significant correlation with the rainfall and wind speed on the yearly and monthly scales， and the GW of a year's delayed GW is significantly correlated with the wind speed， and GW with one year delay showed significant correlation for precipitation.
吴 帆,张利华,陈俊宏,陈佩佩. 基于SWAT的马渡河流域水文模拟及环境响应分析[J]. 华中师范大学学报(自然科学版), 2025, 59(2): 247-258.
WU Fan,ZHANG Lihua,CHEN Junhong,CHEN Peipei. Hydrologic simulation based on SWAT and environmental response analysis in the Madu River basin. journal1, 2025, 59(2): 247-258.
2025, Vol. 59 
