Abstract
This study proposes a new method for downscaling ETWatch 1-km actual evapotranspiration (ET) products to a spatial resolution of 30 m using Landsat8 normalized difference vegetation index (NDVI) data. The NDVI is employed as an indicator of land-surface vegetation, which displays periodic spatial patterns on the land surface. A 30-m-resolution ten-day ET dataset is then calculated primarily using the NDVI and the historical ratio of coarse NDVI and ET that considers different land cover types. Good agreement and correlations were obtained between the downscaled data and observations from three flux sites in two study areas. The mean bias (MB) per ten-day period ranges from 4.21 mm in Guantao to 1.55 mm in Huazhaizi, and the coefficient of determination (R2) varies from 0.87 to 0.95. The downscaling results show good consistency with the original ETWatch 1-km data over both temporal and spatial scales for different land cover types, with R2 values ranging from 0.82 to 0.98. In addition, the downscaled results capture the progression of vegetation growth well. This study demonstrates the applicability of the new “de-pixelation” downscaling method in the management of water resources.
Highlights
Evapotranspiration (ET) is one of the major processes in the hydrologic cycle and plays an essential role in controlling energy and water exchanges between the land surface and the atmosphere.ET is a key component in water resource management across multiple scales for agricultural and ecological applications [1]
Given the dwindling supplies of available water resources due to over-withdrawal of groundwater and water pollution, water resource management has shifted from traditional large-scale approaches to approaches that rely on ET to estimate temporal changes, which concentrate to a greater degree on identifying temporal changes and the spatial distribution of water consumption, especially in intensely irrigated farming areas [2]
This study aims to introduce Landsat8 30-m normalized difference vegetation index (NDVI) data as a readily available and applicable source of information on spatial patterns combined with land cover information at the same spatial scale
Summary
Evapotranspiration (ET) is one of the major processes in the hydrologic cycle and plays an essential role in controlling energy and water exchanges between the land surface and the atmosphere.ET is a key component in water resource management across multiple scales for agricultural and ecological applications [1]. ET is the summation of evaporation and transpiration, which consume water to different degrees in areas with different land cover types; this parameter is significantly affected by the land-surface characteristics. Given the dwindling supplies of available water resources due to over-withdrawal of groundwater and water pollution, water resource management has shifted from traditional large-scale approaches to approaches that rely on ET to estimate temporal changes, which concentrate to a greater degree on identifying temporal changes and the spatial distribution of water consumption, especially in intensely irrigated farming areas [2]. Enhancing the ability of farmers to efficiently manage available irrigation water supplies [3,4,5,6]. Gridded ET from remote sensing (RS)-based methods, suffers from the temporal and spatial limitations from RS sensors. Trade-offs exist between different RS-based methods, and
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