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Water Productivity Mapping for Irrigated Crops in California Using Farm-Level Assessments and Hyper-Spatial and Spectral Remote Sensing: Michael Marshall   MICHAEL MARSHALL

Project Title: Water Productivity Mapping for Irrigated Crops in California Using Farm-Level Assessments and Hyper-Spatial and Spectral Remote Sensing
Mendenhall Fellow: Michael Marshall, mmarshall@usgs.gov
Duty Station: Flagstaff, Arizona
Start Date: February 28, 2011
Education: Ph.D. Geography, University of California–Santa Barbara, 2010
Research Advisor: Prasad Thenkabail, pthenkabail@usgs.gov
Project Description: In California, the water supply deficit is expected to increase to 2 million acre-feet by the end of this year, further straining a critical resource. Agricultural production is primarily watered through irrigation in California and comprises approximately 75 to 80 percent of the State’s annual water budget. Improving the water productivity of irrigated crops (“more crop per drop”) in the State could therefore significantly reduce water consumption in California. Crop water productivity (WP) is the ratio of crop biomass (or yield) to evapotranspiration (ET).  Water productive fields have high yields and lose less moisture to the atmosphere via ET. 

This project uses a suite of hyper-spatial and spectral remote sensing data, geographic information system (GIS) layers, and groundtruth data to estimate WP for four key irrigated crops in California (alfalfa, corn, cotton, and rice). Groundtruth data include information on crop spectral properties and physiology, topography, soils, irrigation practices and hydrology, and meteorology. Sampling is conducted near sites measuring ET using eddy covariance, lysimeters, or surface renewal systems.

Following the field campaign at the end of summer 2011, the project will meet four objectives:
    1. Identify hyper-spatial and spectral bands using the techniques described in Thenkabail and others (2004) that accurately and independently describe the magnitude and variability in crop biomass on the ground and remotely, and using these bands, compare standard statistical and vegetation index (VI) techniques of measuring biomass to the inversion of a biophysical model.
    2. Identify hyper-spatial and spectral bands using the relationship described by Choudhury and others (1994) that accurately and independently describe the magnitude and variability in crop evapotranspiration, and using these bands to define the fraction of total vegetation cover, compare various remote sensing based models (SEBAL, METRIC, SSiB, etc.) to observed ET.
    3. Determine WP for irrigated crops by extrapolating the biomass model identified in bullet point 1 and the evapotranspiration model identified in bullet point 2 over large areas of California through time. A second (categorical) product will identify fields with low WP and the factors contributing to it.
    4. Given the various resolutions of the remote sensing data employed and the added benefit of detailed field data, this project will also explore the uncertainties in biomass and evapotranspiration across various spatial scales.
Selected Bibliography

Choudhury, B.J.,Ahmed, N.U., Idso, S.B., Reginato, R.J., and Daughtry, C.S.T., 1994, Relations between evaporation coefficients and vegetation indices studied by model simulations: Remote Sensing of Environment, v. 50, p. 1–17.

Thenkabail, P.S., Enclonab, E.A., Ashtonb, M.S., and Van Der Meer, B., 2004, Accuracy assessments of hyperspectral waveband performance for vegetation analysis application: Remote Sensing of Environment,v. 91, p. 354–376.

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Last modified: 16:08:30 Thu 13 Dec 2012