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.

中文翻译：

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植被动态影响下海拉尔河流域蒸散发模拟研究的改进

在降水量<400毫米的干旱、半干旱地区，蒸散量(ET)约占降水量的80%，是流域的主要耗水量。但近年来植被绿化会通过影响根系土壤水分而增加ET，加剧该地区的干旱。植被变化具有区域性和空间异质性，因此，为了表征植被动态下的蒸散变化，需要扩大蒸散模拟的空间尺度。然而，广泛使用的蒸散模拟模型，如Shuttleworth-Wallace模型（SW模型），不足以反映垂直（即土壤深度）和水平（即植被动态）方向的直接和间接影响。基于实地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湿度来间接影响蒸散量。在此基础上，基于SEM，确定草原植被带的权重系数为0.85、0.15，林草交错带的权重系数分别为0.3、0.15、0.20、0.25、0.10，林草植被带的权重系数分别为0.20、0.55、0.25。结果。在不同植被类型区内定义不同的土壤水分权重系数​​，改进的SW模型称为SW-α。将模拟结果与实测数据进行对比，SW-α将该区域的蒸散模拟精度提高了33.92%，改进后的蒸散空间趋势能够响应植被的动态变化。将Block-wise使用的TOPMODEL和Muskingum-Cunge方法模式（BTOP模型）中的ET模块替换为改进后的SW-α，结果表明改进模型的仿真精度提高了25%，纳什为速率期和验证期均高于75%，实现了模型从点尺度向流域尺度的扩展。修正模型可为生态脆弱地区蒸散发模拟和生态系统健康管理提供技术支持。