State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China; Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University, Beijing, China.
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China; Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University, Beijing, China.
J Contam Hydrol. 2024 Mar;262:104324. doi: 10.1016/j.jconhyd.2024.104324. Epub 2024 Feb 24.
In arid and semi-arid areas with <400 mm of precipitation, evapotranspiration (ET) accounts for about 80% of precipitation and is the main water consumer in the watershed. However, vegetation greening in recent years will increase ET and exacerbate the aridity of the area by affecting soil moisture in the root system. Vegetation changes are regional and spatially heterogeneous, therefore, in order to characterize ET changes under vegetation dynamics, it is necessary to expand the spatial scale of ET simulation. However, widely used evapotranspiration simulation models, such as the Shuttleworth-Wallace model (SW model), are deficient in reflecting the direct and indirect effects of vertical (i.e., soil depths) and horizontal (i.e., vegetation dynamics) directions. Based on field sampling and constructed structural equation model (SEM), we found that vegetation dynamics affect evapotranspiration not only directly, but also indirectly by affecting soil moisture at different depths. On this basis, we defined the weighting coefficients of 0.85 and 0.15 for grassland vegetation zones, 0.3, 0.15, 0.20, 0.25, 0.10 for forest-grass interspersed zones, and 0.20, 0.55, 0.25 for forested zones, respectively, based on the SEM results. Different soil moisture weighting coefficients were defined within different vegetation type zones and the improved SW model is called S-W-α. Comparing the simulation results with the measured data, S-W-α improved the ET simulation accuracy in this region by 33.92% and the improved ET spatial trend can respond to the dynamic changes of vegetation. Replacing the ET module in the Block-wise use of TOPMODEL and Muskingum-Cunge method mode (BTOP model) with the modified S-W-α, the results show that the simulation accuracy of the improved model is increased by 25%, and the Nash is higher than 75% for both the rate period and the validation period, which realizes the extension of the model from the point scale to the basin scale. The modified model may provide technical support for simulation of evapotranspiration and management of ecosystem health in ecologically fragile areas.
在年降水量小于 400 毫米的干旱和半干旱地区，蒸散量（ET）约占降水量的 80%，是流域的主要耗水方。然而，近年来植被的绿化会增加蒸散量，并通过影响根系土壤水分使该地区更加干旱。植被变化具有区域性和空间异质性，因此，为了描述植被动态下的蒸散量变化，有必要扩大蒸散量模拟的空间尺度。然而，广泛使用的蒸散量模拟模型，如 Shuttleworth-Wallace 模型（SW 模型），在反映垂直（即土壤深度）和水平（即植被动态）方向的直接和间接影响方面存在不足。基于野外采样和构建的结构方程模型（SEM），我们发现植被动态不仅直接影响蒸散量，而且还通过影响不同深度的土壤水分间接影响蒸散量。在此基础上，我们根据 SEM 结果分别为草地植被区、林草交错区和森林区定义了权重系数 0.85 和 0.15、0.3、0.15、0.20、0.25、0.10 和 0.20、0.55、0.25。在不同的植被类型区定义了不同的土壤水分权重系数，改进后的 SW 模型称为 S-W-α。通过将改进后的 S-W-α 代替 Block-wise use of TOPMODEL and Muskingum-Cunge method 模式（BTOP 模型）中的 ET 模块，将模拟结果与实测数据进行比较，结果表明，该模型在该区域的蒸散量模拟精度提高了 33.92%，并且改进后的 ET 空间趋势能够响应植被的动态变化。改进后的模型的模拟精度提高了 25%，且纳什系数在率定期和验证期均高于 75%，实现了从点尺度到流域尺度的模型扩展。改进后的模型可为生态脆弱地区的蒸散量模拟和生态系统健康管理提供技术支持。
