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Remote Sens. 2013, 5(8), 3849-3871; doi:10.3390/rs5083849

Estimating Riparian and Agricultural Actual Evapotranspiration by Reference Evapotranspiration and MODIS Enhanced Vegetation Index

1
Sonoran Desert Research Station, Southwest Biological Science Center, US Geological Survey, 1110 E. South Campus Drive, Room 123, Tucson, AZ 85721, USA
2
CSIRO Land and Water, Waite Road, Gate 4, Glen Osmund, SA 5064, Australia
3
Environmental Research Laboratory, University of Arizona, 2601 E. Airport Dr., Tucson, AZ 85706, USA
4
USDA-Agricultural Research Service, 2000 E. Allen Rd., Tucson, AZ 85719, USA
*
Author to whom correspondence should be addressed.
Received: 26 June 2013 / Revised: 22 July 2013 / Accepted: 22 July 2013 / Published: 5 August 2013
(This article belongs to the Special Issue Advances in Remote Sensing of Crop Water Use Estimation)
View Full-Text   |   Download PDF [2035 KB, 19 June 2014; original version 19 June 2014]   |  

Abstract

Dryland river basins frequently support both irrigated agriculture and riparian vegetation and remote sensing methods are needed to monitor water use by both crops and natural vegetation in irrigation districts. We developed an algorithm for estimating actual evapotranspiration (ETa) based on the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the EOS-1 Terra satellite and locally-derived measurements of reference crop ET (ETo). The algorithm was calibrated with five years of ETa data from three eddy covariance flux towers set in riparian plant associations on the upper San Pedro River, Arizona, supplemented with ETa data for alfalfa and cotton from the literature. The algorithm was based on an equation of the form ETa = ETo [a(1 − e−bEVI) − c], where the term (1 − e−bEVI) is derived from the Beer-Lambert Law to express light absorption by a canopy, with EVI replacing leaf area index as an estimate of the density of light-absorbing units. The resulting algorithm capably predicted ETa across riparian plants and crops (r2 = 0.73). It was then tested against water balance data for five irrigation districts and flux tower data for two riparian zones for which season-long or multi-year ETa data were available. Predictions were within 10% of measured results in each case, with a non-significant (P = 0.89) difference between mean measured and modeled ETa of 5.4% over all validation sites. Validation and calibration data sets were combined to present a final predictive equation for application across crops and riparian plant associations for monitoring individual irrigation districts or for conducting global water use assessments of mixed agricultural and riparian biomes. View Full-Text
Keywords: remote sensing; leaf area index; water balance; alfalfa; saltcedar; common reed; mesquite remote sensing; leaf area index; water balance; alfalfa; saltcedar; common reed; mesquite
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Nagler, P.L.; Glenn, E.P.; Nguyen, U.; Scott, R.L.; Doody, T. Estimating Riparian and Agricultural Actual Evapotranspiration by Reference Evapotranspiration and MODIS Enhanced Vegetation Index. Remote Sens. 2013, 5, 3849-3871.

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