The regional-scale estimation of crop evapotranspiration (ET_c) over a heterogeneous surface is an important tool for the decision-makers in managing and allocating water resources. This is especially critical in the arid to semi-arid regions that require supplemental water due to insufficient precipitation, soil moisture, or groundwater. Over the years, various remote sensing-based surface energy balance (SEB) models have been developed to accurately estimate ET_c over a regional scale. However, it is important to carry out the SEB model assessment for a particular geographical setting to ensure the suitability of a model. Thus, in this study, four commonly used and contrasting remote sensing models viz. METRIC (mapping evapotranspiration at high resolution with internalized calibration), SEBAL (surface energy balance algorithm for land), S-SEBI (simplified surface energy balance index), and SEBS (surface energy balance system) were compared and used to quantify and map the spatio-temporal variation of ET_c in the semi-arid to arid inter-mountain region of Big Horn Basin, Wyoming (Landsat Path/Row: 37/29). Model estimates from 19 cloud-free Landsat 7 and 8 images were compared with the Bowen ratio energy balance system (BREBS) flux stationed in a center pivot irrigated field during 2017 (sugar beet), 2018 (dry bean), and 2019 (barley) growing seasons. The results indicated that all SEB models are effective in capturing the variation of ET_c with R² ranging in between 0.06 to 0.95 and RMSD between 0.07 to 0.15 mm h⁻¹. Pooled data over three vegetative surfaces for three years under irrigated conditions revealed that METRIC (NSE = 0.9) performed better across all land cover types, followed by SEBS (NSE = 0.76), S-SEBI (NSE = 0.73), and SEBAL (NSE = 0.65). In general, all SEB models substantially overestimated ET_c and underestimated sensible heat (H) fluxes under dry conditions when only crop residue was available at the surface. A mid-season density plot and absolute difference maps at image scale between the models showed that models involving METRIC, SEBAL, and S-SEBI are close in their estimates of daily crop evapotranspiration (ET₂₄) with pixel-wise RMSD ranged from 0.54 to 0.76 mm d⁻¹ and an average absolute difference across the study area ranged from 0.47 to 0.56 mm d⁻¹. Likewise, all the SEB models underestimated the seasonal ET_c, except SEBS.

中文翻译：

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估算半干旱至干旱山间地区作物蒸散量的卫星驱动地表能量平衡模型的比较

异质表面上作物蒸散量（ET _c）的区域规模估算是决策者管理和分配水资源的重要工具。在干旱到半干旱地区，由于降水，土壤湿度或地下水不足而需要补充水时，这一点尤为重要。多年来，已经开发了各种基于遥感的表面能平衡（SEB）模型来准确估算ET _c。在区域范围内。但是，对于特定的地理环境进行SEB模型评估很重要，以确保模型的适用性。因此，在这项研究中，使用了四种常用的对比遥感模型。比较了METRIC（具有内部校准的高分辨率制图蒸散量），SEBAL（土地的表面能平衡算法），S-SEBI（简化的表面能平衡指数）和SEBS（表面能平衡系统），并对其进行了量化和制图ET _c的时空变化在怀俄明州大霍恩盆地的半干旱至山间干旱地区（陆地卫星路径/行：37/29）。在2017年（甜菜），2018年（干豆）和2019年（大麦）期间，将来自19个无云Landsat 7和8个图像的模型估计值与位于中心枢轴灌溉田中的Bowen比能量平衡系统（BREBS）通量进行了比较生长季节。结果表明，所有SEB模型均能有效捕获ET _c的变化，R ^2的范围在0.06至0.95之间，RMSD在0.07至0.15 mm h ^-1之间。。在灌溉条件下，三年中三个植被表面的汇总数据显示，METRIC（NSE = 0.9）在所有土地覆盖类型上均表现更好，其次是SEBS（NSE = 0.76），S-SEBI（NSE = 0.73）和SEBAL（NSE = 0.65）。一般而言，所有SEB模型在干旱条件下（仅在表层可获得农作物残渣的情况下）都大大高估了ET _c并低估了显热（H）通量。两个模型之间的中期季节密度图和图像比例上的绝对差异图显示，涉及METRIC，SEBAL和S-SEBI的模型的每日作物蒸散量（ET ₂₄）估算值接近，像素方式的RMSD为0.54至0.76毫米d ^-1研究区域的平均绝对差为0.47至0.56 mm d ^-1。同样，除SEBS外，所有SEB模型都低估了季节性ET _c。