基于陆地卫星的METRIC模型估算尼泊尔陆面蒸散
Estimation of land surface Evapotranspiration in Nepal using Landsat based METRIC model
摘要：
尼泊尔的地形多样，从平原到小范围内的高山和山脉。由于缺乏丰富的地面测量站点，很难估计尼泊尔大部分地区从低海拔到高海拔的蒸散量（ET）。在这项研究中，我们提出了使用遥感为基础的METRIC（映射蒸散在高分辨率与内部校准）模型估计ET在尼泊尔。Landsat 8图像提供了精细的空间分辨率（30米），用于估计。从METRIC模型获得的结果进行了比较，从一个独立的涡流协方差（EC）站的地面测量。除ET外，还将遥感模型估计的地面温度（Ts）与地面测量值进行了比较，以验证模型。从遥感模型获得的结果接近地面测量，建立模型的准确性。每小时和每日ET的均方根误差（RMSE）分别为0.06 mm/h和1.24 mm/d，而每小时和每日ET的平均偏倚误差（MBE）分别为0.03 mm/h和0.29 mm/d。此外，我们分析了6个不同月份ET随海拔的变化，发现ET与海拔呈负相关，一般来说，在尼泊尔地区。这是建立在不同海拔的Ts和植被分布的影响。据我们所知，我们的研究是第一次调查ET估计在尼泊尔地形多样的地区与陆地卫星8提供的优良空间分辨率。在尼泊尔，这种大规模的ET估计有几个应用。在一个大多数人口仍然依赖农业维持日常生计的国家，这可以用于农业规划和预测。
英文摘要：
Nepal has a topographically diverse terrain with variations from plain flatland to high hills and mountains within a small region. Due to the lack of abundant ground-based measurement sites, it is difficult to estimate evapotranspiration (ET) covering most of the areas of Nepal from lower to higher elevations. In this study, we proposed to use a remote sensing-based METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model for estimating ET in Nepal. Landsat 8 imagery, which provides a fine spatial resolution (30 m), was used for the estimation. The results obtained from the METRIC model were compared with ground-based measurements from an independent Eddy-Covariance (EC) station. Besides ET, the estimated surface temperatures (Ts) from the remote sensing model were also compared with ground-based measurements for model validation. The results obtained from the remote sensing model were close to the ground-based measurements which establish the accuracy of the model. Root mean square error (RMSE) for hourly and daily ET was obtained as 0.06 mm/hr and 1.24 mm/day while mean bias error (MBE) for hourly and daily ET was observed as 0.03 mm/hr and 0.29 mm/day, respectively. Further, we analyzed the variations of ET with elevation for six different months and found that ET was inversely related to elevation, in general, over the regions of Nepal. This was established as an effect of Ts and vegetation distribution over different elevations. To the best of our knowledge, our study is a first that has investigated ET estimation over a topographically diverse region of Nepal with fine spatial resolution afforded by Landsat 8. Such large-scale ET estimation in Nepal has several applications. This can be leveraged for agricultural planning and forecasting in a country where most of the population still relies on agriculture for their daily livelihood.
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