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A Remote Sensing Model Estimating Water Body Evaporation. Junming Wang, Ted Sammis, Vince Gutschick Department of Plant and Environmental Sciences New Mexico State University. 2008 International Workshop on Earth Observation and Remote Sensing Applications June 30- July 2, Beijing, China.

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a remote sensing model estimating water body evaporation

A Remote Sensing Model Estimating Water Body Evaporation

Junming Wang, Ted Sammis, Vince Gutschick

Department of Plant and Environmental Sciences

New Mexico State University

2008 International Workshop on Earth Observation and Remote Sensing Applications

June 30- July 2, Beijing, China

introduction
Introduction

Elephant Butte Lake

introduction3
Introduction

Figure 1. Map of Elephant Butte Reservoir and Las Cruces area, NM, USA.

From maps.google.com

introduction4
Introduction
  • Mexico had amassed a water deficit to the US since 1992 that reached 1.5 million acre-feet at its highest point, costing U.S. agricultural producers in the Rio Grande Valley $1 billion.
evaporation loss
Evaporation loss
  • Part of the water delivery problems for both countries was the amount of water being used by reservoir evaporation in the upstream storage reservoirs.
objective
Objective
  • The general objective of the research was to develop a remote sensing tool to estimate evaporation (E) loss (mm/day or m3) from reservoirs to aid international water delivery management.
ground measurements of evaporation
Ground measurements of evaporation
  • inflow–outflow water balance method,

pan measurement method,

or eddy covariance method

are time- and labor-intensive

and one point measurement can not integrate the spatial variability of lake evaporation.

remote sensing methods to estimate et
Remote sensing methods to estimate ET
  • SEBAL (surface energy balance algorithm for land) is a residual method of energy budget, developed by [Bastiaanssen et a., 1998]
  • It is more operational than other models for ET
  • Need to calibrate the parameters for water body
method
Method
  • Based on SEBAL, a Remote Sensing ET model was developed and validated for ASTER data for land ET
  • The model was modified for MODIS input data and was calibrate and validate using a water balance lake evaporation calculation .
build the model theory
Build the modelTheory

Build the ASTERModel

ETins = Rn - G - H

R

H

n

ETins

G

Graph from Allen, et. al., (2002)

slide11

Start

Build the ASTER Model

Satellite inputs: surface temperature and reflectance.

Local weather inputs: solar radiation, humidity and wind speed

Rn=f(Rs, reflectance)

General flowchart

NDVI=f(reflectance)

G=f(NDVI, solar radiation, reflectance)

H=f(NDVI, temperature, reflectance, solar radiation, wind speed)

ETins=Rn-H-G

End

slide19
G/Rn
  • Using Roosevelt lake E data (Water balance)

ETins = Rn - G - H

modis model validation
MODIS model validation

Figure 5. Modelled ET from MODIS data taken on June 8, 2005. ET unit: mm/day.

slide23

ET values obtained from MODIS data compared with the ET values from ASTER data at Las Cruces, NM, USA for June 8, 2005, September 7, 2003, May 18, 2003, and September 4, 2002, .

conclusions
Conclusions
  • For the summer time E estimate, the accuracy is within 1.5 mm/day. The evapotranspiration accuracy is about 85%.
  • The model is capable for aiding international water delivery management.
  • The average evaporation of Elephant Butte Reservoir in summer time was 5.6 mm/day.
acknowledgements
Acknowledgements
  • This publication was made possible by a grant from the Southwest Consortium for Environmental Research and Policy (SCERP).