Geology topics

MacKenzie Friedrichs

Publications and source records attributed to MacKenzie Friedrichs.

17 recordsLinked to original sources

USGS2026

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment↗

USGS2026

Towards affordable wetland evapotranspiration monitoring using the Variance-Bowen Ratio method: Insights from three contrasting wetlands

Accurate measurement of evapotranspiration (ET) is essential for sustainable water management. Standard methods such as eddy covariance (EC) are costly, while alternatives such as surface renewal are cheaper but require calibration and complex data processing. This study evaluates the utility of the Variance-Bowen Ratio (VBR) method for estimating ET across three California’s wetlands. Using data from 2023, half-hourly latent heat flux (λE) and daily/monthly ET from VBR were compared with EC at one non-tidal (site A) and two tidal (sites B and C) wetlands. λE VBR consistently underestimated λE EC , with root mean squared errors (RMSE) of 61.2 W m -2 at sites A, 106.1 W m -2 at site B, and 137.2 W m -2 at site C, largely due to storage fluxes across sites. Temporal integration improved VBR’s performance at tidal sites, where compensating water heat storage errors yielded low daily and monthly biases (site B: RMSE = 0.78 mm/d and 12 mm/month; r = 0.93; site C: RMSE = 0.90 mm/d and 13 mm/month; r = 0.93), with reduced major axis (RMA) regression slopes of 0.98 and ~0.91. In contrast, biomass heat storage at site A caused persistent biases (RMSEs = 0.97 mm/d and 23 mm/month; daily and monthly RMA slopes ~0.75; r = 0.85). These results highlight VBR’s limitations in environments with substantial storage fluxes. Despite this, VBR is cost-effective for estimating daily and monthly ET, with sensor costs at least tenfold lower than EC and simpler setup, making it suitable for ET monitoring in resource-limited and hard-to-access regions.

California↗

USGS2025

A novel approach to increase accuracy in remotely sensed evapotranspiration through basin water balance and flux tower constraints

Remote sensing-derived evapotranspiration (RSET) products capture the spatiotemporal variations of evapotranspiration (ET) from field to basin scales with unprecedented details. However, their accuracy varies across RSET estimation methods and diverse hydroclimate regions. While ET modeling efforts to account for biophysical processes and controlling parameters have made good progress in recent years, a parallel approach of integrating in-situ ET with RSET could reduce biases in RSET products. Basin water balance ET (WBET) and flux tower ET are widely applied to evaluate RSET accuracy, yet such ET measurements are rarely used for RSET bias corrections, especially for large area applications. To address this issue, we propose a novel approach: the water balance equivalence (WABE) method, which generates spatially continuous WBET for correcting biases in RSET products. The WABE method computes synthetic WBET by integrating observed WBET and flux tower-derived FLUXCOM ET, which fills the spatial gaps of observed WBET and generates a spatially continuous WBET dataset. Synthetic WBET (2002–2015 annual average) of eight-digit hydrologic unit code (HUC8) basins across the conterminous United States (CONUS), constituting 44 % (887 out of 2035 basins) of CONUS basins, was determined within 2.0 % (RMSE = 12 %) of observed WBET at CONUS and between 1–12 % (RMSE = 3–33 %) across 18 regions in CONUS. With WABE-based bias corrections, the overall annual bias of RSET decreased from 10 % (RMSE = 34 %) to 6 % (RMSE = 26 %) across 37 flux tower sites. The WABE method offers a new approach for RSET accuracy improvement and shows great promise for large area implementations with a potential to yield substantial benefits for building accurate basin water budgets and water management decisions.

Conterminous United States↗

USGS2025

Estimating agricultural irrigation water consumption for the High Plains aquifer region with integrated energy- and water-balance evapotranspiration modeling approaches

Estimation of irrigation water use provides essential information for the management and conservation of agricultural water resources. Conventionally, water use data are created based on reports and surveys from water users, whereas manual records may not be complete due to lacking flow meters, measurement gaps, inconsistent methods across regions, and time- and cost-consuming data processing. Alternatively, spatially explicit estimation of irrigation water use can be conducted efficiently using remote sensing evapotranspiration (ET) modeling approaches. In this study, we created a gridded blue water evapotranspiration (BWET) dataset to estimate historical irrigation water consumption (1986 – 2020) in the croplands across the United States High Plains aquifer region. The BWET data were generated by integrating an energy-balance ET model [Operational Simplified Surface Energy Balance model (SSEBop)] and a water-balance ET model [Vegetation ET model (VegET)]. BWET in croplands indicates crop consumptive use of irrigation water extracted from surface water and groundwater resources. The BWET estimates were compared with reported irrigation water use data for all counties within the aquifer region. The results revealed high agreement between growing season (May – September) BWET and annual water withdrawal at county level. Specifically, correlation coefficients of volumetric BWET and water withdrawal were 0.90 and 0.96, respectively, for the entire aquifer region and western Kansas. The timeseries of BWET and water withdrawal showed similar temporal trends and high covariations. The BWET estimates were systematically lower than the water withdrawal measurements, which was primarily attributed to blue water losses in the irrigation system. The irrigation efficiency, calculated as the ratio of BWET to water withdrawal depth, was 0.57 and 0.74 for the entire aquifer region and western Kansas, respectively. This study demonstrates the capability of using satellite-based ET models (e.g., SSEBop and VegET) to efficiently estimate crop water consumption and evaluate irrigation efficiency at landscape, county, and regional scales.

Colorado, Kansas, Nebraska, New Mexico, Oklahoma, ↗

USGS2025

Estimating irrigation consumptive use for the conterminous United States: Coupling satellite-sourced estimates of actual evapotranspiration with a national hydrologic model

Irrigation consumptive use is crucial information for water resource management and this information is generally not available for most regional and national assessments. From 2000 to 2020, daily estimates of consumptive use were produced for the conterminous U.S. at the 12-digit hydrologic unit code watershed level. Using the Simplified Surface Energy Balance model within the OpenET tool on Google Earth Engine, actual evapotranspiration estimates were derived from Landsat land surface temperature data. These estimates were mapped to the National Hydrologic Model (NHM) spatial units for irrigated areas defined by the Landsat Irrigation Dataset (LANID). The NHM allows for simultaneous estimation of consumptive use and effective precipitation. Results were compared to the 2015 USGS water use report, revealing annual maximum difference in consumptive use of 37 cm, with an average absolute difference of 13 cm and a bias of 2.7 %. Comparisons to field resolution irrigation withdrawals reported by growers in 4 major irrigation regions across the nation were made using efficiencies reported in the literature. These comparisons resulted in root mean square errors that ranged between 10 and 18 cm per year and biases of −18.2 to 15.8 %. Significant differences in these different reported estimates represent challenges in accurate data availability and inconsistent methods and definitions used in assessments. Annual consumptive use in the U.S. can vary by 37 % due to droughts, particularly in regions more heavily dependent on precipitation. Significant increases in consumptive use were noted over the 20-year period in western states, especially the Colorado River basin from 2010 to 2020, exacerbating water supply declines.

conterminous United States↗

USGS2024

An ensemble mean method for remote sensing of actual evapotranspiration to estimate water budget response across a restoration landscape

Estimates of actual evapotranspiration (ETa) are valuable for effective monitoring and management of water resources. In areas that lack ground-based monitoring networks, remote sensing allows for accurate and consistent estimates of ETa across a broad scale—though each algorithm has limitations (i.e., ground-based validation, temporal consistency, spatial resolution). We developed an ensemble mean ETa (EMET) product to incorporate advancements and reduce uncertainty among algorithms (e.g., energy-balance, optical-only), which we use to estimate vegetative water use in response to restoration practices being implemented on the ground using management interventions (i.e., fencing pastures, erosion control structures) on a private ranch in Baja California Sur, Mexico. This paper describes the development of a monthly EMET product, the assessment of changes using EMET over time and across multiple land use/land cover types, and the evaluation of differences in vegetation and water distribution between watersheds treated by restoration and their controls. We found that in the absence of a ground-based monitoring network, the EMET product is more robust than using a single ETa data product and can augment the efficacy of ETa-based studies. We then found increased ETa within the restored watershed when compared to the control sites, which we attribute to increased plant water availability.

Baja California Sur↗

USGS2024

SSEBop evapotranspiration estimates using synthetically derived Landsat data from the continuous change detection and classification algorithm

The operational Simplified Surface Energy Balance (SSEBop) model has been utilized to generate gridded evapotranspiration data from Landsat images. These estimates are primarily driven by two sources of information: reference evapotranspiration and Landsat land surface temperature (LST) values. Hence, SSEBop is limited by the availability of Landsat data. Here, in this proof-of-concept paper, we utilize the Continuous Change Detection and Classification (CCDC) algorithm to generate synthetic Landsat data, which are then used as input for SSEBop to generate evapotranspiration estimates for six target areas in the continental United States, representing forests, shrublands, and irrigated agriculture. These synthetic land cover data are then used to generate the LST data required for SSEBop evapotranspiration estimates. The synthetic LST, evaporative fractions, and evapotranspiration data from CCDC closely mirror the phenological cycles in the observed Landsat data. Across the six sites, the median correlation in seasonal LST was 0.79, and the median correlation in seasonal evapotranspiration was 0.8. The median root mean squared error (RMSE) values were 2.82 °C for LST and 0.50 mm/day for actual evapotranspiration. CCDC predictions typically underestimate the average evapotranspiration by less than 1 mm/day. The average performance of the CCDC evaporative fractions, and corresponding evapotranspiration estimates, were much better than the initial LST estimates and, therefore, promising. Future work could include bias correction to improve CCDC’s ability to accurately reproduce synthetic Landsat data during the summer, allowing for more accurate evapotranspiration estimates, and determining the ability of SSEBop to predict regional evapotranspiration at seasonal timescales based on projected land cover change from CCDC.

Remote Sensing↗

USGS2024

Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications

Remotely sensed evapotranspiration (ET) data offer strong potential to support data-driven approaches for sustainable water management. However, practitioners require robust and rigorous accuracy assessments of such data. The OpenET system, which includes an ensemble of six remote sensing models, was developed to increase access to field-scale (30 m) ET data for the contiguous United States. Here we compare OpenET outputs against data from 152 in situ stations, primarily eddy covariance flux towers, deployed across the contiguous United States. Mean absolute error at cropland sites for the OpenET ensemble value is 15.8 mm per month (17% of mean observed ET), mean bias error is −5.3 mm per month (6%) and r 2 is 0.9. Results for shrublands and forested sites show higher inter-model variability and lower accuracy relative to croplands. High accuracy and multi-model convergence across croplands demonstrate the utility of a model ensemble approach, and enhance confidence among ET data practitioners, including the agricultural water resource management community.

Nature Water↗

USGS2023

Improving the operational simplified surface energy balance evapotranspiration model using the forcing and normalizing operation

Actual evapotranspiration modeling is providing useful information for researchers and resource managers in agriculture and water resources around the world. The performance of models depends on the accuracy of forcing inputs and model parameters. We developed an improved approach to the parameterization of the Operational Simplified Surface Energy Balance (SSEBop) model using the Forcing and Normalizing Operation (FANO). SSEBop has two key model parameters that define the model boundary conditions. The FANO algorithm computes the wet-bulb boundary condition using a linear FANO Equation relating surface temperature, surface psychrometric constant, and the Normalized Difference Vegetation Index (NDVI). The FANO parameterization was implemented on two computing platforms using Landsat and gridded meteorological datasets: (1) Google Earth Engine (GEE) and (2) Earth Resources Observation and Science (EROS) Center Science Processing Architecture (ESPA). Evaluation was conducted by comparing modeled actual evapotranspiration ( ETa ) estimates with AmeriFlux eddy covariance (EC) and water balance ETa from level-8 Hydrologic Unit Code sub-basins in the conterminous United States. FANO brought substantial improvements in model accuracy and operational implementation. Compared to the earlier version (v0.1.7), SSEBop FANO (v0.2.6) reduced grassland bias from 47% to −2% while maintaining comparable bias for croplands (11% versus −7%) against EC data. A water balance-based ETa bias evaluation showed an overall improvement from 7% to −1%. Climatology versus annual gridded reference evapotranspiration ( ETr ) produced comparable ETa results, justifying the use of climatology ETr for the global SSEBop Landsat ETa that is accessible through the ESPA website. Besides improvements in model accuracy, SSEBop FANO increases the spatiotemporal coverage of ET modeling due to the elimination of high NDVI requirements for model parameterization. Because of the existence of potential biases from forcing inputs and model parameters, continued evaluation and bias corrections are necessary to improve the absolute magnitude of ETa for localized water budget applications.

Remote Sensing↗

USGS2022

Mapping actual evapotranspiration using Landsat for the conterminous United States: Google Earth Engine implementation and assessment of the SSEBop model

The estimation and mapping of actual evapotranspiration (ETa) is an active area of applied research in the fields of agriculture and water resources. Thermal remote sensing-based methods, using coarse resolution satellites, have been successful at estimating ETa over the conterminous United States (CONUS) and other regions of the world. In this study, we present CONUS-wide ETa from Landsat thermal imagery-using the Operational Simplified Surface Energy Balance (SSEBop) model in the Google Earth Engine (GEE) cloud computing platform. Over 150,000 Landsat satellite images were used to produce 10 years of annual ETa (2010–2019) at unprecedented scale. The accuracy assessment of the SSEBop results included point-based evaluation using monthly Eddy Covariance (EC) data from 25 AmeriFlux stations as well as basin-scale comparison with annual Water Balance ETa (WBET) for more than 1000 sub-basins. Evaluations using EC data showed generally mixed performance with weaker (R 2 < 0.6) correlation on sparsely vegetated surfaces such as grasslands or woody savanna and stronger correlation (R 2 > 0.7) over well-vegetated surfaces such as croplands and forests, but location-specific conditions rather than cover type were attributed to the variability in accuracy. Croplands performed best with R 2 of 0.82, root mean square error of 29 mm/month, and average bias of 12%. The WBET evaluation indicated that the SSEBop model is strong in explaining the spatial variability (up to R 2 > 0.90) of ETa across large basins, but it also identified broad hydro-climatic regions where the SSEBop ETa showed directional biases, requiring region-specific model parameter improvement and/or bias correction with an overall 7% bias nationwide. Annual ETa anomalies over the 10-year period captured widely reported drought-affected regions, for the most part, in different parts of the CONUS, indicating their potential applications for mapping regional- and field-scale drought and fire effects. Due to the coverage of the Landsat Path/Row system, the availability of cloud-free image pixels ranged from less than 12 (mountainous cloud-prone regions and U.S. Northeast) to more than 60 (U.S. Southwest) per year. However, this study reinforces a promising application of Landsat satellite data with cloud-computing for quick and efficient mapping of ETa for agricultural and water resources assessments at the field scale.

Remote Sensing of Environment↗

USGS2021

OpenET: Filling a critical data gap in water management for the western United States

The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.

western United States↗

USGS2021

Using satellite imagery to estimate consumptive water use from irrigated lands in the Milk River Basin, United States and Canada

The U.S. Geological Survey, with the support of the International Joint Commission, and in cooperation with Alberta Environment and Parks, Blackfeet Nation, Environment and Climate Change Canada, and Montana Department of Natural Resources and Conservation, is leading a project that should improve information available to apportion water between Canada and the United States in the St. Mary and Milk River Basins. One component of the water budget, consumptive use of irrigation water (the amount of supplemental water used by crops), can be estimated at 100-meter resolution almost every week using imagery recorded by satellites from 1985 to present (2021) and weather data, when conditions permit. Better estimates of consumptive water use should improve understanding of water availability and use in the basin and should assist with water apportionment procedures.

Alberta, Montana, Saskatchewan↗

USGS2021

Characterization of water use and water balance for the croplands of Kansas using satellite, climate, and irrigation data

Kansas is one of the most productive agricultural states in the United States, where agricultural irrigation is a primary user of underground and surface water. Because of low precipitation and declining groundwater levels in western and central Kansas, sustainable management of irrigation water resources is a critical issue in the agricultural productivity of the state. The objective of this study is to analyze and characterize the water use and water balance in the croplands of Kansas using satellite observations, meteorological data, and in situ irrigation water use records. We used actual evapotranspiration ( ETa ), precipitation, soil moisture, and irrigation water use to calculate water balance for Kansas in 2015 at scales of counties, climatic divisions, and groundwater management districts (GMD). The Operational Simplified Surface Energy Balance model was implemented to estimate 30-m resolution ETa . Results showed that the seasonal (May – September) precipitation, soil water storage change, and ETa are 528 mm, 80 mm, and 555 mm, respectively, on average of all croplands in the state. The annual net irrigation water consumption was 293 mm for irrigated croplands, indicating that irrigation water constitutes an substantial portion of the water supply in the state. The total volumetric irrigation water use was 3.24 km 3 for all croplands within five GMDs in western and south-central Kansas, while only 0.38 km 3 was outside of GMDs. The multiple regression models of ETa against precipitation and irrigation water use were statistically significant with R 2 values of 0.71 and 0.87, respectively, at county and climate division scales. Regression models also indicated a higher rate of ETa response to irrigation water use than that to precipitation. Our study demonstrated the spatial patterns of crop water use and water balance in Kansas, which could provide useful information for management of irrigation agriculture and water resources for the state.

Kansas↗

USGS2020

Evaluation of hydrologic impact of an irrigation curtailment program in the Upper Klamath Lake Basin using Landsat satellite data

Upper Klamath Lake (UKL) is the source of the Klamath river that flows through southern Oregon and northern California. The UKL basin is home to two endangered species and provides water for 81,000+ ha (200,000+ acres) of irrigation on the United States Bureau of Reclamation (USBR) Klamath Project located downstream of the UKL basin. Irrigated agriculture also occurs along the tributaries to UKL. During 2013–2016, water right calls resulted in various levels of curtailment of irrigation diversions from the tributaries to UKL. However, information on the extent of curtailment, how much irrigation water was saved, and its impact on the UKL is unknown. In this study, we combined Landsat-based actual evapotranspiration (ETa) data obtained from the Operational Simplified Surface Energy Balance (SSEBop) model with gridded precipitation and USGS station discharge data to evaluate the hydrologic impact of the curtailment program. Analysis was performed for five base years (2004, 2006, 2008-2010) and four target years (2013-2016) over irrigated areas above UKL. Our results indicated that the impact of the curtailment program over the June to September time-period was highest during 2013 and declined in each of the following years. The total on-field water savings were approximately 60 hm3 in 2013 and 2014, 44 hm3 in 2015, and 32 hm3 in 2016. The instream water flow change or extra water available (EWA) were found at 92, 68, 45, and 26 hm3 respectively for 2013, 2014, 2015 and 2016. Most water savings came from pasture and wetlands. Alfalfa showed the most decline in water use among grain crops. The resulting EWA from the curtailment contributed to a maximum of 19% of the lake inflows and 50% of the lake volume. This study presents the use of Landsat-based ETa and other remote sensing datasets for evaluating water-related impacts of the irrigation curtailment program.

Upper Klamath Lake Basin↗

USGS2019

Long-term (1986–2015) crop water use characterization over the Upper Rio Grande Basin of United States and Mexico using Landsat-based evapotranspiration

The evaluation of historical water use in the Upper Rio Grande Basin (URGB), United States and Mexico, using Landsat-derived actual evapotranspiration (ETa) from 1986 to 2015 is presented here as the first study of its kind to apply satellite observations to quantify long-term, basin-wide crop consumptive use in a large basin. The rich archive of Landsat imagery combined with the Operational Simplified Surface Energy Balance (SSEBop) model was used to estimate and map ETa across the basin and over irrigated fields for historical characterization of water-use dynamics. Monthly ETa estimates were evaluated using six eddy-covariance (EC) flux towers showing strong correspondence (r2 > 0.80) with reasonable error rates (root mean square error between 6 and 19 mm/month). Detailed spatiotemporal analysis using peak growing season (June–August) ETa over irrigated areas revealed declining regional crop water-use patterns throughout the basin, a trend reinforced through comparisons with gridded ETa from the Max Planck Institute (MPI). The interrelationships among seven agro-hydroclimatic variables (ETa, Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), maximum air temperature (Ta), potential ET (ETo), precipitation, and runoff) are all summarized to support the assessment and context of historical water-use dynamics over 30 years in the URGB.

Colorado, New Mexico, Texas↗

USGS2017

Satellite-based water use dynamics using historical Landsat data (1984–2014) in the southwestern United States

Remote sensing-based field-scale evapotranspiration (ET) maps are useful for characterizing water use patterns and assessing crop performance. The relative impact of climate variability and water management decisions are better studied and quantified using historical data that are derived using a set of consistent datasets and methodology. Historical (1984–2014) Landsat-based ET maps were generated for major irrigation districts in California, i.e., Palo Verde and eight other sub-basins in parts of the middle and lower Central Valley. A total of 3396 Landsat images were processed using the Operational Simplified Surface Energy Balance (SSEBop) model that integrates weather and remotely sensed images to estimate monthly and annual ET within the study sites over the 31 years. Model output evaluation and validation using gridded-flux data and water balance ET approaches indicated relatively good correspondence (R 2 up to 0.88, root mean square error as low as 14 mm/month) between SSEBop ET and validation datasets. In a pairwise comparison, annual variability of agro-hydrologic parameters of actual evapotranspiration ( ET a ), land surface temperature ( T s ), and runoff ( Q ) were found to be more variable than their corresponding climatic counterparts of atmospheric water demand ( ET o ), air temperature ( T a ), and precipitation ( P ), revealing process differences between regional climatic drivers and localized agro-hydrologic responses. However, only T a showed a consistent increase (up to 1.2 K) over study sites during the 31 years, whereas other climate variables such as ET o and P showed a generally neutral trend. This study demonstrates a useful application of “Big Data” science where large volumes of historical Landsat and weather datasets were used to quantify and understand the relative importance of water management and climate variability in crop water use dynamics in regards to the linkages among water management decisions, hydrologic processes and economic transactions. Irrigation district-wide ET a estimates were used to compute historical crop water use volumes and monetary equivalents of water savings for the Palo Verde Irrigation District (PVID). During the peak crop fallowing year in PVID, the water saved reached a maximum of ~ 107,200 acre-feet in 2011 with an estimated monetary payout value of $20.5 million. A significant decreasing trend in actual ET despite an increasing atmospheric demand in PVID highlights the role of management decisions in affecting local hydrologic processes. This study has importance for planning water resource allocation, managing water rights, sustaining agricultural production, and quantifying impacts of climate and land use/land cover changes on water resources. With increased computational efficiency, similar studies can be conducted in other parts of the world to help policy and decision makers understand and quantify various aspects of water resources management.

Arizona, California↗

USGS2016

Evaluating Landsat 8 evapotranspiration for water use mapping in the Colorado River Basin

Evapotranspiration (ET) mapping at the Landsat spatial resolution (100 m) is essential to fully understand water use and water availability at the field scale. Water use estimates in the Colorado River Basin (CRB), which has diverse ecosystems and complex hydro-climatic regions, will be helpful to water planners and managers. Availability of Landsat 8 images, starting in 2013, provides the opportunity to map ET in the CRB to assess spatial distribution and patterns of water use. The Operational Simplified Surface Energy Balance (SSEBop) model was used with 528 Landsat 8 images to create seamless monthly and annual ET estimates at the inherent 100 m thermal band resolution. Annual ET values were summarized by land use/land cover classes. Croplands were the largest consumer of “blue” water while shrublands consumed the most “green” water. Validation using eddy covariance (EC) flux towers and water balance approaches showed good accuracy levels with R 2 ranging from 0.74 to 0.95 and the Nash–Sutcliffe model efficiency coefficient ranging from 0.66 to 0.91. The root mean square error (and percent bias) ranged from 0.48 mm (13%) to 0.60 mm (22%) for daily (days of satellite overpass) ET and from 7.75 mm (2%) to 13.04 mm (35%) for monthly ET. The spatial and temporal distribution of ET indicates the utility of Landsat 8 for providing important information about ET dynamics across the landscape. Annual crop water use was estimated for five selected irrigation districts in the Lower CRB where annual ET per district ranged between 681 mm to 772 mm. Annual ET by crop type over the Maricopa Stanfield irrigation district ranged from a low of 384 mm for durum wheat to a high of 990 mm for alfalfa fields. A rainfall analysis over the five districts suggested that, on average, 69% of the annual ET was met by irrigation. Although the enhanced cloud-masking capability of Landsat 8 based on the cirrus band and utilization of the Fmask algorithm improved the removal of contaminated pixels, the ability to reliably estimate ET over clouded areas remains an important challenge. Overall, the performance of Landsat 8 based ET compared to available EC datasets and water balance estimates for a complex basin such as the CRB demonstrates the potential of using Landsat 8 for annual water use estimation at a national scale. Future efforts will focus on (a) use of consistent methodology across years, (b) integration of multiple sensors to maximize images used, and (c) employing cloud-computing platforms for large scale processing capabilities.

Arizona, California, Colorado, Nevada, New Mexico,↗