论文标题
使用基于Landsat的度量模型估算尼泊尔陆地表面蒸散量的估计
Estimation of land surface Evapotranspiration in Nepal using Landsat based METRIC model
论文作者
论文摘要
尼泊尔的地形具有不同的地形，从平原平地到一个小区域内的山和山脉的变化。由于缺乏大量地面测量地点，因此很难估计蒸散量（ET），涵盖了尼泊尔的大多数区域，从较低到更高的海拔。在这项研究中，我们建议使用基于遥感的度量（高分辨率以高分辨率的抗疏松量与内部化校准）模型来估计尼泊尔的ET。 Landsat 8图像可提供精细的空间分辨率（30 m），用于估计。将从公制模型获得的结果与独立涡流（EC）站的地面测量值进行了比较。除ET外，还将遥感模型的估计表面温度（TS）与基于地面的测量值进行了比较。从遥感模型获得的结果接近基于地面的测量，这些测量值确定了模型的准确性。每小时的均方根误差（RMSE）和每日ET为0.06 mm/hr和1.24 mm/天，而每小时和每日ET的平均偏置误差（MBE）分别为0.03 mm/hr和0.29 mm和0.29 mm/天/天。此外，我们分析了升高六个月的ET的变化，发现ET在尼泊尔的区域一般而言与升高成反比。这是在不同海拔高度的TS和植被分布的作用中确定的。据我们所知，我们的研究是对尼泊尔的地形多样区域进行了ET估计，并提供了Landsat 8提供的精细空间分辨率。尼泊尔的大规模ET估计有多种应用。在这个国家，大多数人民仍然依靠农业来谋生，这可以用于农业规划和预测。
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.
