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.

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)

Satellite NDVI Assisted Monitoring of Vegetable Crop Evapotranspiration in California’s San Joaquin Valley

“…Yet, compared with direct ETa estimation procedures that involve energy balance remote sensing [31], vegetation index methods are more approachable and can be less costly to implement [32]. Further, by avoiding the need for thermal imagery, vegetation index methods can potentially exploit viewing opportunities offered by a larger variety of satellite and airborne imaging systems [33] and can generate output at higher spatial resolution for use on smaller fields.…”

Validation of Global Evapotranspiration Product (MOD16) using Flux Tower Data in the African Savanna, South Africa

“…• empirical methods that involve the use of statistically-derived relationships between ET and vegetation indices such as the normalized difference vegetation index (NDVI) or the enhanced vegetation index (EVI) [20][21][22][23][24][25], • residual methods of surface energy balance (single-and dual-source models) [8,26] which include the Surface Energy Balance Algorithm over Land (SEBAL) [27,28], Surface Energy Balance System (SEBS) [8,29,30] and Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) [6,31,32], • physically-based methods that involve the application of the combination of Penman-Monteith [7,33,34] and Priestley-Taylor types of equations [35][36][37][38][39], and • Data assimilation methods adjoined to the heat diffusion equation [40] and through the radiometric surface temperature sequences [41].…”

An Empirical Algorithm for Estimating Agricultural and Riparian Evapotranspiration Using MODIS Enhanced Vegetation Index and Ground Measurements of ET. I. Description of Method

“…The resulting algorithm for ET actual had an error or uncertainty of about 20%, within the range of other remote sensing methods for ET actual , and allowed ET actual to be scaled across irrigation districts and riparian areas on the Lower Colorado River (see [68]). Similar locally calibrated and validated algorithms can be developed for other applications for which frequent-return satellite imagery and ground meteorological and ET actual data are available.…”