高寒内陆河流域植被覆盖增加对地下水补给的影响

地下水是干旱区内陆河流域的主要基础性资源，对流域生态安全、可持续发展等具有重要意义。干旱/半干旱区的地下水补给比湿润地区更易受到地表覆盖条件的影响。为揭示干旱区内陆河流域植被覆盖增加对地下水补给的影响，以巴音河中下游为例，针对土壤和水评价工具(SWAT)模型未有效考虑降水、地形等因素对植被覆盖影响的缺陷，改进SWAT模型，采用全球地表卫星叶面积指数(GLASS LAI)数据代替其LAI计算模块，再结合SWAT土地利用更新模块，准确刻画区域植被覆盖变化。将改进后的SWAT模型与模块化有限拆分地下水流耦合(MODFLOW)模型耦合，准确模拟并分析植被覆盖增加对流域地下水补给的影响。结果表明：基于植被动态变化的土壤和水评价工具与模块化有限拆分地下水流耦合模型(DVSWAT-MODFLOW)模型的月蒸散发及月地下水位模拟效果较好；巴音河中下游2019年林地及草地面积以及LAI较2001年明显增加；2019年植被覆盖情况对应的年际及月际尺度地下水补给量较2001年分别减少了6.1—26.52 mm以及0—15.03 mm;植被覆盖增加对年际尺度地下水补给量的影响强弱在一定程度上取决于年降水量，对...

Impacts of the increasing vegetation coverage on groundwater recharge in an alpine and arid endorheic river watershed

The groundwater is one of the most important basic resources in arid land. The groundwater recharge is easier to be affected by vegetation coverage in the arid and semi-arid areas than the wet areas. Bayin River Basin, a typical alpine and arid endorheic river watershed is located in the northeast of the Qaidam Basin. In the past 20 years, because of the warmer and more humid climate and human activities, the vegetation coverage condition of the watershed was becoming better. Calculation of the groundwater recharge in endorheic watershed is difficult. Soil and Water Assessment Tool (SWAT) is one of the most important tools that can simulate the watershed hydrological processes and its impact factors. However, it has considerable limitations in vegetation coverage and groundwater processes simulation. For the vegetation coverage simulation (leaf area index, LAI), it neglects the precipitation and terrain, which is important in arid land; For the groundwater simulation, it only is based on a simple linear mathematical formula without consideration of the physical processes. To better reveal the impacts of the vegetation coverage increasing on groundwater recharge in arid inland river, this research modified the SWAT model by replacing the LAI module with Global Land Surface Satellite (GLASS) based on LAI. The land use/cover change of the Middle and Lower Reaches of the Bayin River was further considered to better simulate the vegetation dynamics. After that, the modified SWAT model (named Dynamic Vegetation SWAT, DVSWAT) was coupled with the MODFLOW (MODular finite difference groundwater FLOW model), a professional groundwater processes simulation model. The latest GLEAM (Global Land Evaporation Amsterdam Model) v3 based on monthly evapotranspiration data and the observed groundwater level data were used to calibrate the DVSWAT-MODFLOW. We further used the variable-controlling approach to analyze the impacts of the vegetation coverage increasing on groundwater recharge based on the simulation results of the calibrated DVSWAT-MODFLOW. The results showed that the performance of the DVSWAT-MODFLOW in modelling the monthly evapotranspiration was good, with the R² value of over 0.83, NSE value of over 0.68, and PBIAS value within -22%-22% for each subbasin. The performance of the DVSWAT-MODFLOW in modelling the monthly groundwater level was good as well, with the R² value of over 0.95 and absolute bias of below 1 m for each groundwater level observation well. The area of the forest land and grassland in the study area increased 5.41 times and 98.96%, respectively, in 2019 compared to 2001. In addition, the annually average LAI of the study in 2019 increased 28.83% than 2001. The yearly and monthly groundwater recharge reduced about 6.1-26.52 mm and 0-15.03 mm, respectively, under the impacts of the increased vegetation coverage. The influence of the increasing vegetation coverage on the annual groundwater recharge depends on the annual precipitation to a certain extent. The months with strong influence on the monthly groundwater recharge are concentrated in the period of vigorous plant growth and more precipitation.