This article describes current and likely near-term future frameworks for calculating evapotranspiration.These include structures for estimating crop coefficients (Kc) primarily centered on the FAO-56 dual Kc approach, with example applications.Emphasis is placed on estimation of parameters and special cases to be considered.Newer, and often preferred, bases for establishing Kcb curves include thermal units and vegetation indices.Also described and discussed are the application of reference ET calculations using hourly vs. 24-hour timesteps, the use of and conditioning of gridded weather data sets, and the likelihood of movement toward multi-layer and multi-source resistance models for ET estimation.Complementing this is satellite-based determination of ET using both vegetation indices and surface energy balance.

HighlightsThe FAO-56 dual crop coefficient procedure was applied over the entire agricultural areas of Idaho and Nevada to determine evapotranspiration (ET) and net irrigation water requirements (IWR).Basal crop coefficients were expressed as functions of normalized cumulative growing degree days.ET during dormant seasons was included in the estimates.The procedure was applied to a U.S. West-wide study of climate change effects on ET and IWR.Abstract. The FAO-56 dual crop coefficient procedure was used to determine evapotranspiration (ET) and net irrigation water requirements for all agricultural areas of the states of Idaho and Nevada and in a western U.S. study on effects of climate change on future irrigation water requirements. The products of the applications are for use by state governments for water rights management, irrigation system planning and design, wastewater application system design and review, hydrologic water balances, and groundwater modeling. The products have been used by the U.S. federal government for assessing impacts of current and future climate change on irrigation water demands. The procedure was applied to data from more than 200 weather station locations across the state of Idaho, 200 weather station locations across the state of Nevada, and eight major river basins in the western U.S. for available periods of weather records. Estimates were made over daily, monthly, and annual time intervals. Methods from FAO-56 were employed for calculating reference ET and crop coefficients (Kc), with ET calculations performed for all times of the calendar year including winter. Expressing Kc as a function of thermal-time units allowed application across a wide range of local climates and elevations. The ET estimates covered a wide range of agricultural crops grown in the western U.S. plus a number of native plant systems, including wetlands, rangeland, and riparian trees. Evaporation was estimated for three types of open-water surfaces ranging from deep reservoirs to small farm ponds. Keywords: Consumptive use, Dual crop coefficient, Evapotranspiration, FAO-56, Irrigation water requirements.

A novel ArcGIS toolbox that applies the Mapping Evapotranspiration with Internalized Calibration model was developed and tested in a semi-arid environment. The tool, named METRIC-GIS, facilitates the pre-processing operations and the automatic identification of potential calibration and pixels review. The energy balance components obtained from METRIC-GIS were contrasted with those from the original METRIC version (R-2 = 1; RMSE = 0 W m(-2) or mm day(-1) for ETc) Additionally, an irrigated scheme located at southern Spain was considered for assessing K-c variability in the maize fields with METRIC-GIS. The identified spatial variability was mainly due to differences in irrigation regimes, crop management practices, and planting and harvesting dates. This information is critical for developing irrigation advisory strategies that contribute to the area sustainability. The developed tool facilitates data input introduction and reduces computational time by up to 50%, providing a more user-friendly alternative to other existing platforms that use METRIC.

Reliable evapotranspiration (ET) estimation is a key factor for water resources planning, attaining sustainable water resources use, irrigation water management, and water regulation. During the past few decades, researchers have developed a variety of remote sensing techniques to estimate ET. The Earth Engine Evapotranspiration Flux (EEFlux) application uses Landsat imagery archives on the Google Earth Engine platform to calculate the daily evapotranspiration at the local field scale (30 m). Automatically calibrated for each Landsat image, the EEFlux application design is based on the widely vetted Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) model and produces ET estimation maps for any Landsat 5, 7 or 8 scene in a matter of seconds. In this research we evaluate the consistency and accuracy of EEFlux products that are produced when standard US and global assets are used. Processed METRIC products for 58 scenes distributed around the western and central United States were used as the baseline for comparison. The goal of this paper is to compare the results from EEFlux with the standard METRIC applications to illustrate the utility of the EEFlux products as they currently stand. Given that EEFlux is derived from METRIC, differences are expected to occur due to differing calibration methods (automatic versus manual) and differing input datasets. The products compared include the fraction of reference ET (ETrF), actual ET (ETa), and surface energy balance components net radiation (Rn), ground heat flux (G), and sensible heat flux (H), as well as Ts, albedo and NDVI. The product comparisons show that the intermediate products of Ts, Albedo, and NDVI, and also Rn have similar values and behavior for both EEFlux and METRIC. Larger differences were found for H and G. Despite the more significant differences in H and G, results show that EEFlux is able to calculate ETrF and ETa values comparable to the values from trained expert METRIC users for agricultural areas. For non-agricultural areas such as semi-arid rangeland and forests, the automated EEFlux calibration algorithm needs to be improved in order to be able to reproduce ETrF and ETa that is similar to the manually calibrated METRIC products.

We made an assessment on the use of 12-bit resolution of Landsat 8 (L8) on evapotranspiration (ET) retrievals via the METRIC process as compared to using 8-bit resolution imagery of previous Landsat missions. METRIC (Mapping Evapotranspiration at high Resolution using Internalized Calibration) is an ET retrieval system commonly used in water and water rights management where the surface energy balance process is coupled with an extreme-end point calibration process to remove most impacts of systematic bias in remotely sensed inputs. We degraded L8 thermal images by grouping sequential digital numbers to reduce the apparent numerical resolution and then recomputed ET using METRIC and compared to nondegraded ET products. The use of 8-bit thermal data did not substantially impair the accuracy of ET retrievals derived from METRIC, as compared to the use of 12-bit thermal data. The largest error introduced into ET was <1%. We also compared ET retrieved from images processed during the L8 and Landsat 7 (L7) March 2013 underfly to assess differences in ET caused by differences in signal to noise ratio (SNR) and scaling of the two systems.We evaluated the impact of bias in land surface temperature (LST) retrievals on ET determination using the CIMEC calibration approach (Calibration using Inverse Modeling using Extreme Member Calibration) employed in METRIC by introducing globally systematic biases into LST retrievals from L7 and L8 and comparing to ET from non-biased retrievals. The impacts of the introduction of both additive and multiplicative biases into surface temperature on ET were small for the three regions of the US studied, and for both L7 and L8 satellite systems. An independent study showed that METRIC-produced ET compared to within 3% of measured ET for the California site.The study assessed the impact of the February 2014 recalibration of L8 thermal data that caused a 3K downward shift in LST estimation and changed reflectance values by about 0.7%. We found that the use of the recalibrated LST and shortwave data sets in METRIC did not change the accuracy of ET retrievals due to the automatic compensation for systematic biases employed by METRIC.

A backward-averaged iterative two-source surface temperature and energy balance solution (BAITSSS) algorithm was developed to estimate evapotranspiration (ET) during the period between Landsat satellite overpass dates. The METRIC (mapping evapotranspiration at high resolution with internalized calibration) model was used to estimate ET using short wave and thermal data from the Landsat images. METRIC generated ET was used to define initial surface characteristics, soil water conditions and initialize the soil water content for the surface and root zone at the start of the simulation period, and to adjust the results from BAITSSS at the next satellite overpass date if needed. North American Regional Reanalysis (NARR) weather data were used to estimate the surface energy balance components in between the satellite overpasses. The fraction of vegetation cover (f(c)) was used to partition surface energy balance components, as defined by the normalized difference vegetation index. Soil surface resistance (r(ss)) and Jarvis-model-type canopy resistance (r(sc)) were used to calculate latent heat flux using the aerodynamic equations. A water balance was implemented to track the water content at the surface and root zone. An irrigation sub-model was developed to consider the role of irrigation for known irrigated agricultural fields, which is critical when computing ET in an agriculture-dominant area. Any mismatch between the estimated and METRIC ET at the next satellite overpass can be adjusted back over the simulation period with a time-based linear correction to increase the accuracy and reduce computation time. In this study, BAITSSS results from southern Idaho and northern California are presented for 3 h time steps.

Abstract. “EEFlux” is an acronym for ‘Earth Engine Evapotranspiration Flux.‘ EEFlux is based on the operational surface energy balance model “METRIC” (Mapping ET at high Resolution with Internalized Calibration), and is a Landsat-image-based process. Landsat imagery supports the production of ET maps at resolutions of 30 m, which is the scale of many human-impacted and human-interest activities including agricultural fields, forest clearcuts and vegetation systems along streams. ET over extended time periods provides valuable information regarding impacts of water consumption on Earth resources and on humans. EEFlux uses North American Land Data Assimilation System hourly gridded weather data collection for energy balance calibration and time integration of ET. Reference ET is calculated using the ASCE (2005) Penman-Monteith and GridMET weather data sets. The Statsgo soil data base of the USDA provides soil type information. EEFlux will be freely available to the public and includes a web-based operating console. This work has been supported by Google, Inc. and is possible due to the free Landsat image access afforded by the USGS.

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.

A surface energy balance was conducted to calculate the latent heat flux (λE) using aerodynamic methods and the Penman–Monteith (PM) method. Computations were based on gridded weather and Landsat satellite reflected and thermal data. The surface energy balance facilitated a comparison of impacts of different parameterizations and assumptions, while calculating λE over large areas through the use of remote sensing. The first part of the study compares the full aerodynamic method for estimating latent heat flux against the appropriately parameterized PM method with calculation of bulk surface resistance (rs). The second part of the study compares the appropriately parameterized PM method against the PM method, with various relaxations on parameters. This study emphasizes the use of separate aerodynamic equations (latent heat flux and sensible heat flux) against the combined Penman–Monteith equation to calculate λE when surface temperature (Ts) is much warmer than air temperature (Ta), as will occur under water stressed conditions. The study was conducted in southern Idaho for a 1000-km2 area over a range of land use classes and for two Landsat satellite overpass dates. The results show discrepancies in latent heat flux (λE) values when the PM method is used with simplifications and relaxations, compared to the appropriately parameterized PM method and full aerodynamic method. Errors were particularly significant in areas of sparse vegetation where differences between Ts and Ta were high. The maximum RMSD between the correct PM method and simplified PM methods was about 56 W/m2 in sparsely vegetated sagebrush desert where the same surface resistance was applied.

Landsat satellite imagery is commonly used to produce estimates of evapotranspiration (ET) at field scale with energy balance methods because of the onboard thermal imager and the high spatial resolution. Monthly and, ultimately, seasonal ET depths are generally based on only one "snapshot" of ET per month. A potential shortfall in basing integrated ET averages on periodic snapshots from a satellite is that local or regional precipitation events antecedent to the satellite images may unduly dominate the ET,F image and may not represent evaporation from rainfall averaged over the monthly period. In addition, some rain events may occur in between satellite images that are not "seen" in a subsequent image, and therefore those evaporation amounts are not fully accounted for.

Satellite images often have clouds in portions of the images. When estimating vegetation consumptive water use using the surface energy balance method METRIC, the evapotranspiration, expressed as ETrF = ET / ETr, where ETr is tall reference evapotranspiration computed from weather data, ETrF cannot be directly estimated for these areas because cloud temperature masks surface temperature and cloud albedo masks surface albedo. ETrF for clouded areas must be filled in before application of further integration processes so that those processes can be uniformly applied to an entire image. A linear interpolation is used to fill in ETrF for clouded portions of images. The linear interpolation is used rather than curvilinear interpolation, such as the spline introduced later to interpolate between cloud-corrected images, because some periods between cloud-free pixel locations can be as long as several months. Often, the change in crop vegetation amount, and thus ETrF, is uncertain during that period. Thus the use of curvilinear interpolation can become speculative.

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.

It is important to quantify the consumptive water use by the vegetation when managing regional water resources in irrigated areas. Suitable models and algorithms applied to high resolution (30 m) satellite imagery provide a cost effective and time efficient method to obtain evapotranspiration estimations from bare soil and vegetation. The METRIC image processing model 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 algorithms are calibrated using an operator selected wet and dry pixel. The complete energy balance obtained from the satellite images is calibrated using ground based reference evapotranspiration estimations. The paper describes an application of the METRIC model on parts of the South Platte and North Platte rivers in Colorado and Nebraska for individual days in 1997, 2001 and 2002. Landsat 5 and Landsat 7 shortwave and longwave bands were used. Weather data from selected meteorological stations within the study area was screened and used to estimate reference evapotranspiration. A water balance model was used to estimate evaporation from the soil. During the image processing it was necessary to iterate the selection of the wet and dry pixels after reviewing evapotranspiration behavior for natural vegetation and wet fields at full cover. Uneven distribution of recent precipitation events and operator dependency needed to be addressed. The resulting evapotranspiration maps appear to be congruent with ET from previous studies and will be used by local water management entities.

Evapotranspiration (ET) is the major consumptive use of irrigation water, and thus, spatial and temporal quantification of ET is important to agricultural water management. In water rights management and precision irrigation, information on ET is desirable on a field or subfield scale. Therefore, fine resolution satellite imagery such as Landsat and ET products derived from the satellite imagery are highly desirable. However, for a majority of satellites, spatial resolution of the longwave (thermal) band(s) is coarser than the coincident shortwave bands, which creates a compatibility and correspondence issue for the data used for energy balance (EB) and increases the net pixel resolution and reduces fidelity of ET calculations. Typically, surface temperature (T s ) and vegetation indices (VI) are closely correlated, especially under conditions of high availability of soil water, due to the effects of evaporative cooling by vegetation, especially some days after wetting events, when the exposed soil surface is dry and warm relative to vegetation. This physical relationship can be exploited to sharpen T s using VI if the assumption of cooled surface by vegetation holds. This paper describes a technique developed for application with the METRIC and SEBAL EB procedures that uses the concept of hot and cold thermal conditions associated with dry and wet surface conditions during calibration as a means to distribute T s at a subpixel scale using subpixel VI. The result is an image of T s that has the same spatial resolution of the short wave images. Therefore, the resolution of ET images created during the METRIC or SEBAL processes can have equally high resolution. Applications made in Idaho and New Mexico using sharpened thermal imagery are described.

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 energy balance determination of evapotranspiration (ET) from Landsat scale resolution (30 m) is dim. An alternative to the computation of a full energy balance is to use the presence of vegetation cover, characterized using a vegetation index, to estimate the relative rate of transpiration from a pixel and then add an additional evaporation amount that stems from a wet soil surface. The wet surface is modeled using precipitation and irrigation amounts and weather data. This approach, while lacking accuracy of the full energy balance, provides means to create ET images using short wave reflectances produced by future medium resolution satellites. The relatively simple evaporation model of FAO-56 is used to compute daily evaporation losses in the context of transpiration from vegetation. These evaporation losses are added to transpiration derived from a vegetation index to produce a complete estimate for ET. Because of the enormous number of pixels in a Landsat scale image (30 million), it is not possible to know specific irrigation timings by field, so that synthetic irrigation events are simulated. Comparisons between synthesized ET from the described approach and ET from a full energy balance computed using METRIC are explored for parts of south central Idaho and error is quantified.

Evapotranspiration (ET) is the major consumptive use of irrigation water, and thus, spatial and temporal quantification of ET is important to agricultural water management. In water rights management and precision irrigation, information on ET is desirable on a field or subfield scale. Therefore, fine resolution satellite imagery such as Landsat and ET products derived from the satellite imagery are highly desirable. However, for a majority of satellites, spatial resolution of the longwave (thermal) band(s) is coarser than the coincident shortwave bands, which creates a compatibility and correspondence issue for the data used for energy balance (EB) and increases the net pixel resolution and reduces fidelity of ET calculations. Typically, surface temperature (Ts) and vegetation indices (VI) are closely correlated, especially under conditions of high availability of soil water, due to the effects of evaporative cooling by vegetation, especially some days after wetting events, when the exposed soil surface is dry and warm relative to vegetation. This physical relationship can be exploited to sharpen Ts using VI if the assumption of cooled surface by vegetation holds. This paper describes a technique developed for application with the METRIC and SEBAL EB procedures that uses the concept of hot and cold thermal conditions associated with dry and wet surface conditions during calibration as a means to distribute Ts at a subpixel scale using subpixel VI. The result is an image of Ts that has the same spatial resolution of the short wave images. Therefore, the resolution of ET images created during the METRIC or SEBAL processes can have equally high resolution. Applications made in Idaho and New Mexico using sharpened thermal imagery are described.

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 basis for a variety of crop types and land uses. Error in estimated growing season ET was 4% for irrigated meadow in the Bear River basin of Idaho and 1% for an irrigated sugar beet crop near Kimberly, Id. Standard deviation of error for time periods represented by each satellite image averaged about 13 to 20% in both applications. The results indicate that METRIC and similar methods such as SEBAL hold substantial promise as efficient, accurate, and inexpensive procedures to estimate actual evaporation fluxes from irrigated lands throughout growing seasons.

The Clean Water Act and Safe Drinking Water Act and the Environmental Protection Agency of the United States Federal Government have provided means and encouragement to irrigation projects and entities to improve the quality of surface water returns flowing to river systems. In Idaho, state and federal partnerships have set maximum concentration limits for suspended sediment (52 mg/l) and phosphorus (0.1 mg/l) on portions of the Snake River system and its tributaries through the total maximum daily load process. The irrigation community has responded by implementing programs and partnerships for improving quality of returning water. These programs include education, water quality improvement facilities and best management practices, and monitoring.