Mapping evapotranspiration at high resolution with internalized calibration (METRIC) is a satellite-based image-processing model for calculating evapotranspiration (ET) as a residual of the surface energy balance. METRIC uses as its foundation the pioneering SEBAL energy balance process developed in The Netherlands by Bastiaanssen, where the near-surface temperature gradients are an indexed function of radiometric surface temperature, thereby eliminating the need for absolutely accurate surface temperature and the need for air-temperature measurements. The surface energy balance is internally calibrated using ground-based reference ET to reduce computational biases inherent to remote sensing-based energy balance and to provide congruency with traditional methods for ET. Slope and aspect functions and temperature lapsing are used in applications in mountainous terrain. METRIC algorithms are designed for relatively routine application by trained engineers and other technical professionals who possess a fami...

Recent satellite image processing developments have provided the means to calculate evapotranspiration (ET) as a residual of the surface energy balance to produce ET “maps.” These ET maps (i.e., images) provide the means to quantify ET on a field by field basis in terms of both the rate and spatial distribution. The ET images show a progression of ET during the year or growing season as well as its spatial distribution. The mapping evapotranspiration at high resolution with internalized calibration (METRIC) is a satellite-based image-processing procedure for calculating ET. METRIC has been applied with high resolution Landsat images in southern Idaho, southern California, and New Mexico to quantify monthly and seasonal ET for water rights accounting, operation of ground water models, and determination of crop coefficient populations and mean curves for common crops. Comparisons between ET by METRIC, ET measured by lysimeter, and ET predicted using traditional methods have been made on a daily and monthly ...

This paper presents a rapid, operational method for estimating at-surface albedo applicable to Landsat and MODIS satellite sensors for typical cloud-free, low-haze conditions and sensor view angles less than 20°. At-surface albedo estimates are required input to various surface energy balance models that are applied operationally. The albedo calculation method was developed using the SMARTS2 radiative transfer model and has been applied in recent versions of the University of Idaho METRIC model as a component of the surface energy balance for determining evapotranspiration. The albedo procedure uses atmospheric correction functions developed to require only general humidity data and a digital elevation model. The atmospheric correction functions have a reduced structure to enhance their operational applicability in routine instantaneous surface energy balances and to estimate evapotranspiration. The method does not require high levels of knowledge in atmospheric physics and radiation transfer processes, c...

When managing local and regional water resources, the estimation of evapotranspiration is important and has generally been one of the components of the hydrological cycle that has the greatest uncertainty. With the development of suitable models and algorithms applied to high resolution (30 m) satellite imagery, evapotranspiration may be estimated with greater accuracy, and in a cost effective and time efficient manner. The METRIC image processing procedure calculates net radiation, soil heat flux and sensible heat flux through a number of steps before estimating evapotranspiration as the residual from the energy balance. Sensible heat flux is calibrated using the so-called "cold" and "hot" anchor pixels. These pixels are selected by the user, which may introduce some operator dependency or human errors on the estimation of sensible heat flux and subsequently error in the final map of evapotranspiration. A procedure for automated selection of the anchor pixels is presented. The automated pixel selection procedure will reduce the user dependency of the estimations of sensible heat flux. Additionally, it may allow more novice users to obtain good results when applying METRIC.

Landsat images are highly preferred to images by MODIS for producing evapotranspiration (ET) maps for specific land use types because of their higher resolution (30 m). However, Landsat images are potentially available only each 16 days, and, with the expected failure of Landsat 5 within the next five years and the likelihood of no thermal sensor on Landsat 8 scheduled for launch in 2011, the prospect of images from Landsat that are useful for application with energy balance determination of evapotranspiration (ET) is dim. Therefore, more use of coarse resolution satellite images, such as 1 km thermal images from MODIS, will occur. One advantage of MODIS satellites is that images having view angle < ∼15° are potentially available about each four to five days. Application of METRIC energy balance processes along the Middle Rio Grande of New Mexico using MODIS imagery indicates that one can successfully reproduce monthly and annual ET estimates that were obtained using Landsat imagery. However, spatial fidelity is highly degraded. This paper compares ET images for the Rio Grande region as produced by both MODIS and by Landsat.

Satellite-based surface energy balance has become a very useful tool for determining actual evapotranspiration (ET) over large areas. Major uncertainties in derived ET exist, however, due to error and bias introduced to the surface energy balance and ET by components of the energy balance. These biases include biases in atmospheric correction, albedo calculation, net radiation calculation, thermal band and surface temperature, air temperature gradient used in sensible heat flux calculation, soil heat flux function, and extrapolation to 24-hour and longer periods. At the University of Idaho, we use calculated hourly reference evapotranspiration (ET_r) to calibrate the surface energy balance during processing to remove a majority of these biases. The ET_r method uses alfalfa reference ET calculated with the ASCE-EWRI standardized Penman-Monteith equation. Experience and field verification with this method has created confidence in using ET_r for image calibration rather than using available energy only. In addition to its use to calibrate the energy balance, ET_r is used to extrapolate ET images to 24-hour and longer periods. The use of ET_r provides equivalency and congraency with ET as estimated using the traditional crop coefficient x ET_r approach. With Landsat images, full-cover alfalfa or other high leaf area vegetation can be identified, and ET from these fields is expected to be near the value of alfalfa ET_r. Comparisons between ET by METRIC, ET by lysimeter and ET by traditional methods suggest that METRIC or similar methods hold promise as efficient, accurate, and inexpensive procedures to predict actual evaporation fluxes throughout a growing season.