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An Empirical Algorithm for Estimating Agricultural and Riparian Evapotranspiration Using MODIS Enhanced Vegetation Index and Ground Measurements of ET. II. Application to the Lower Colorado River, U.S.

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dc.contributor.author Murray, R. Scott
dc.contributor.author Nagler, Pamela L.
dc.contributor.author Morino, Kiyomi
dc.contributor.author Glenn, Edward P.
dc.date.accessioned 2011-01-12T19:14:52Z
dc.date.available 2011-01-12T19:14:52Z
dc.date.issued 2009 en_US
dc.identifier.uri https://hdl.handle.net/10535/6750
dc.description.abstract "Large quantities of water are consumed by irrigated crops and riparian vegetation in western U.S. irrigation districts. Remote sensing methods for estimating evaporative water losses by soil and vegetation (evapotranspiration, ET) over wide river stretches are needed to allocate water for agricultural and environmental needs. We used the Enhanced Vegetation Index (EVI) from MODIS sensors on the Terra satellite to scale ET over agricultural and riparian areas along the Lower Colorado River in the southwestern U.S., using a linear regression equation between ET of riparian plants and alfalfa measured on the ground, and meteorological and remote sensing data, with an error or uncertainty of about 20%. The algorithm was applied to irrigation districts and riparian areas from Lake Mead to the U.S./Mexico border. The results for agricultural crops were similar to results produced by crop coefficients developed for the irrigation districts along the river. However, riparian ET was only half as great as crop coefficient estimates set by expert opinion, equal to about 40% of reference crop evapotranspiration. Based on reported acreages in 2007, agricultural crops (146,473 ha) consumed 2.2 × 109 m3 yr−1 of water. All riparian shrubs and trees (47,014 ha) consumed 3.8 × 108 m3 yr−1, of which saltcedar, the dominant riparian shrub (25,044 ha), consumed 1.8 × 108 m3 yr−1, about 1% of the annual flow of the river. This method could supplement existing protocols for estimating ET by providing an estimate based on the actual state of the canopy as determined by frequent-return satellite data." en_US
dc.language English en_US
dc.subject remote sensing en_US
dc.subject salinization en_US
dc.subject water management en_US
dc.title An Empirical Algorithm for Estimating Agricultural and Riparian Evapotranspiration Using MODIS Enhanced Vegetation Index and Ground Measurements of ET. II. Application to the Lower Colorado River, U.S. en_US
dc.type Journal Article en_US
dc.type.published published en_US
dc.type.methodology Case Study en_US
dc.subject.sector Water Resource & Irrigation en_US
dc.identifier.citationjournal Remote Sensing en_US
dc.identifier.citationvolume 1 en_US
dc.identifier.citationpages 1125-1138 en_US


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