Improving Alpine Summertime Streamflow Simulations by the Incorporation of Evapotranspiration Data
Improving Alpine Summertime Streamflow Simulations by the Incorporation of Evapotranspiration Data
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DOI：
10.3390/w11010112
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发表时间：
2019-01
期刊：
影响因子：
3.4
通讯作者：
K. Tobin;M. Bennett
中科院分区：
文献类型：
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作者：
K. Tobin;M. Bennett
在过去的十年中，自动校准例程已成为司空见惯的流域建模。这种方法最常用于模拟流域出口处的径流。在高山设置，春季/初夏融雪是迄今为止在这个系统中的主导信号。因此，模拟流域在一年中的其他时间表现不佳的可能性很大。这一趋势在许多先前的研究中已经注意到。在这项工作中，土壤和水资源评估工具（SWAT）模型自动校准与SUFI-2例程。研究了爱达荷州的一个山区流域（上北福克）。在这项研究中，这个盆地进行了校准使用三种估计蒸散量（ET）：中分辨率成像光谱仪（MODIS），简化的表面能量平衡，全球陆地蒸发：阿姆斯特丹模型。特别是中分辨率成像光谱仪的产品，有最大的效用，有助于限制SWAT参数，有一个高灵敏度的ET。利用这些ET参数值的径流模拟在校准（2007年至2011年）和验证（2012年至2014年）期间改善了衰退和夏季径流性能。径流性能进行了监测与标准的客观指标（偏见和纳什Sutcliffe系数），量化整体，衰退，夏季高峰流量。这种方法对所有三个观测结果都产生了显著的增强。这些结果表明，这种方法的实用性，提高流域建模保真度以外的主要融雪季节。
Over the last decade, autocalibration routines have become commonplace in watershed modeling. This approach is most often used to simulate a streamflow at a basin’s outlet. In alpine settings, spring/early summer snowmelt is by far the dominant signal in this system. Therefore, there is great potential for a modeled watershed to underperform during other times of the year. This tendency has been noted in many prior studies. In this work, the Soil and Water Assessment Tool (SWAT) model was auto-calibrated with the SUFI-2 routine. A mountainous watershed from Idaho was examined (Upper North Fork). In this study, this basin was calibrated using three estimates of evapotranspiration (ET): Moderate Resolution Imagining Spectrometer (MODIS), Simplified Surface Energy Balance, and Global Land Evaporation: the Amsterdam Model. The MODIS product in particular, had the greatest utility in helping to constrain SWAT parameters that have a high sensitivity to ET. Streamflow simulations that utilize these ET parameter values have improved recessional and summertime streamflow performances during calibration (2007 to 2011) and validation (2012 to 2014) periods. Streamflow performance was monitored with standard objective metrics (Bias and Nash Sutcliffe coefficients) that quantified overall, recessional, and summertime peak flows. This approach yielded dramatic enhancements for all three observations. These results demonstrate the utility of this approach for improving watershed modeling fidelity outside the main snowmelt season.