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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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Type: Journal Article
Author: Murray, R. Scott; Nagler, Pamela L.; Morino, Kiyomi; Glenn, Edward P.
Journal: Remote Sensing
Volume: 1
Page(s): 1125-1138
Date: 2009
URI: https://hdl.handle.net/10535/6750
Sector: Water Resource & Irrigation
Region:
Subject(s): remote sensing
salinization
water management
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."

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