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Mapping Annual Riparian Water Use Based on the Single-Satellite-Scene Approach

机译:基于单卫星场景方法的年度河岸用水量图

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The accurate estimation of water use by groundwater-dependent riparian vegetation is of great importance to sustainable water resource management in arid/semi-arid regions. Remote sensing methods can be effective in this regard, as they capture the inherent spatial variability in riparian ecosystems. The single-satellite-scene (SSS) method uses a derivation of the Normalized Difference Vegetation Index (NDVI) from a single space-borne image during the peak growing season and minimal ground-based meteorological data to estimate the annual riparian water use on a distributed basis. This method was applied to a riparian ecosystem dominated by tamarisk along a section of the lower Colorado River in southern California. The results were compared against the estimates of a previously validated remotely sensed energy balance model for the year 2008 at two different spatial scales. A pixel-wide comparison showed good correlation (R 2 = 0.86), with a mean residual error of less than 104 mm?year ?1 (18%). This error reduced to less than 95 mm?year ?1 (15%) when larger areas were used in comparisons. In addition, the accuracy improved significantly when areas with no and low vegetation cover were excluded from the analysis. The SSS method was then applied to estimate the riparian water use for a 23-year period (1988–2010). The average annual water use over this period was 748 mm?year ?1 for the entire study area, with large spatial variability depending on vegetation density. Comparisons with two independent water use estimates showed significant differences. The MODIS evapotranspiration product (MOD16) was 82% smaller, and the crop-coefficient approach employed by the US Bureau of Reclamation was 96% larger, than that from the SSS method on average.
机译:依赖于地下水的河岸植被对用水的准确估算对于干旱/半干旱地区的可持续水资源管理至关重要。在这方面,遥感方法可能是有效的,因为它们捕获了河岸生态系统中固有的空间变异性。单卫星场景(SSS)方法使用峰值生长期期间单个星载图像的归一化植被指数(NDVI)的推导和最少的地面气象数据来估算每年的河岸用水量。分布式基础。该方法应用于沿加利福尼亚南部科罗拉多河下游的部分由mar柳为主的河岸生态系统。将结果与先前验证的两种不同空间尺度上的2008年遥感能量平衡模型的估计值进行了比较。像素范围的比较显示出良好的相关性(R 2 = 0.86),平均残留误差小于104毫米?年?1(18%)。当使用较大的面积进行比较时,该误差减小到小于95 mm?year?1(15%)。此外,当分析中没有植被覆盖度低的区域时,准确度显着提高。然后采用SSS方法估算了23年(1988-2010年)的河岸用水量。整个研究区域在此期间的年平均用水量为748 mm?year?1,其空间变异性取决于植被密度。与两个独立的用水量估算值的比较显示出显着差异。平均而言,MODIS蒸散量(MOD16)要小82%,美国垦殖局采用的作物系数法要大96%。

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