State Water Resources Research Institute Program

Project ID: 2008OK104B
Title: Evaluation of Water Use Monitoring by Remote Sensing ET Estimation Methods
Project Type: Research
Start Date: 3/01/2008
End Date: 2/28/2009
Congressional District: 4
Focus Categories: Water Use, Agriculture, Hydrology
Keywords: ET, Remote Sensing, Irrigation, Water Use
Principal Investigators: Hong, Yang (University of Oklahoma); Vieux, Baxter
Federal Funds: $ 25,000
Non-Federal Matching Funds: $ 53,478
Abstract: Background: The World Bank estimates more than 70% of freshwater use is for irrigation. Oklahoma typically hosts irrigated agriculture, rainfed agriculture, wetlands, and riparian vegetation, all of which transmit water into the atmosphere through Evapo-Transpiration (ET). As demand for water increases, water managers need to know how much water is actually consumed in agriculture. For the past decades, the primary method for estimating ET relies on in-situ weather station measurements. However, the inevitable spatial variability of ET in large irrigation schemes makes this practice almost impossible to monitor water consumption through ET over large regions. With the advent of new satellite technology and comprehensive water balance and runoff models, opportunities exist to develop algorithms and apply remote sensing information for the benefit of water resources management.

Objective: Remote sensing methods can provide ET maps over large areas at very high resolutions (30m and daily). However, transforming remotely sensed images into quantitative water use information at scales relevant to water management agencies is a primary goal that has not been fully realized. Main objective of this project is to evaluate and improve the ability and usefulness of the remote sensing ET estimation algorithms in Oklahoma that does not require placement of in-situ monitoring/metering devices.

Proposed Studies: We will first review and evaluate the remote sensing ET algorithms that have only been applied to western U.S. Then we will calibrate and improve remote sensing algorithms, with focus on surface irrigation water usage, specifically for applications in Oklahoma agricultural counties (e.g. Texas and Tillman) given its unique climate, soil, and land surface types. As a natural extension, we also propose to combine a water balance model Vflo with remote sensing ET estimates to provide more accurate prediction of runoff, soil moisture etc for water use management. Accuracy of the estimated ET, runoff, and soil moisture results will be evaluated at both field and catchment scales using available Mesonet weather station and other in-situ observations.

Deliverables: 1) Evaluation of current satellite remote sensing-based ET estimation algorithms to monitor water use in Oklahoma; 2) Calibration of an improved algorithm to estimate seamless high-resolution actual ET for irrigation land in OK; 3) Assessment of the feasibility of implementing a real-time remote sensing-based ET estimation system for water managers to better monitor actual ET and thus regulate water use in Oklahoma.

Significance: Water regulators have long wanted an efficient, inexpensive procedure to accurately map ET and improve water resource management. Mapping ET with satellite imagery eliminates a lot of expensive equipments and other time intensive tasks. This project will also combine the seamless satellite observations and our existing knowledge for water balance modeling by assimilating the remote sensing ET estimates into a distributed water balance model.Application in water resource allocation and operational flood forecasting are follow-on contributions expected from this research.

Progress/Completion Report, PDF

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