Geology topics

Stefanie Kagone

Publications and source records attributed to Stefanie Kagone.

18 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

VegET evapotranspiration for Africa: Continental-scale simulation, multi-product evaluation, and drought assessment

Study region Continental Africa, encompassing diverse climatic zones—tropical, arid, and temperate—and spanning major transboundary river basins such as the Nile, Niger, Congo, Volta, and Zambezi River Basins. The region exhibits pronounced hydroclimatic gradients and heterogeneous land use systems ranging from rainfed croplands and rangelands to dense tropical forests and irrigated schemes. Study focus Actual evapotranspiration (ETa) is a central component of the terrestrial water balance, governing the redistribution of water and energy between the land surface and the atmosphere. Accurate estimation of ETa at continental scale is critical for hydrological monitoring, water resource management, and climate adaptation, as well as for quantifying water, energy, and carbon fluxes that underpin sustainable development. In this study, we applied the agro-hydrologic VegET v2 model to simulate a new, high-resolution, continental-scale ETa dataset for Africa (2000–2021). The model results were benchmarked against four widely used remote sensing-based products—MODIS16 v6.1, SSEBop v6.1, WaPOR v3, and GLEAM v4.1a—across major climate zones, land use types, and River Basins, providing a comprehensive multi-product evaluation of evapotranspiration dynamics across the continent. New hydrological insights for the region Validation against eddy covariance flux tower observations at eight representative sites confirmed that VegET v2 accurately reproduces the seasonal dynamics of observed ETa, achieving a correlation (r) of 0.8 and an RMSE of 25 mm month⁻¹ —accuracy that is comparable to or higher than accuracies of satellite-based products MODIS16, SSEBop, and GLEAM. This study represents one of the first Africa-wide hydrological simulations of ETa, extending the VegET model beyond basin-scale applications. Intercomparisons reveal that VegET aligns closely with MODIS16, SSEBop, and GLEAM in humid and tropical regions (r = 0.80–0.90; RMSE < 20 mm month⁻¹), while greater discrepancies appear in arid and semi-arid zones, where WaPOR tends to overestimate ETa (RMSE ≥ 28 mm month⁻¹). Despite these differences, VegET effectively captures spatial and temporal ETa variability across rainfed croplands, forests, and savannas, supporting its utility in regional water balance assessments, water accounting, and drought monitoring. A key application of VegET v2 is the Evapotranspiration Deficit Index (ETDI), derived by integrating VegET-based ETa with potential evapotranspiration (PET) to quantify water stress. ETDI successfully captured major drought episodes across Africa, including persistent Sahelian and southern African dry spells, the 2020–2021 winter drought in the Maghreb, and the 2018–2019 austral summer drought in southern Africa, while identifying positive anomalies over central Africa indicative of recurrent wetness. These results underscore VegET’s capability as a hydrologically consistent, operational tool for continental ETa monitoring and drought assessment, offering support for basin-scale water balance studies, food security planning, and climate resilience across Africa’s diverse hydrological environments.

Journal of Hydrology: Regional Studies↗

USGS2025

Chapter three - Global SSEBop actual evapotranspiration modeling and mapping using the VIIRS data

A Actual evapotranspiration (ETa) is an essential climate variable that can be used for drought monitoring and water availability assessment because of its close connection with vegetation, soil moisture, and the water cycle. An operational ETa using the Visible Infrared Imaging Radiometer Suite (VIIRS) and global weather datasets was developed through the Simplified Surface Energy Balance Model (SSEBop) model. An operational framework is established with the Famine Early Warning System Network ( https://earlywarning.usgs.gov/fews ) to generate and update global 1 km ETa at dekadal (∼10 day), monthly, and yearly time scales since February 2012. Modeled ETa at monthly and annual time scales was evaluated using 67 eddy covariance (EC) flux tower stations around the world and water balance-based ETa based on 810 United States eight-digit Hydrologic Unit Code (HUC8) and 18 Global Runoff Data Center (GRDC) basins. The correlation coefficient ( r =0.68–0.94) shows relatively strong and consistent performance across the three datasets, capturing the spatiotemporal variability in HUC8 and GRDC basins and EC tower sites reliably. The bias (3%–15%) and root mean square error (RMSE: 13%–34%) showed relatively large errors and high variability among the three datasets. The evaluation results indicate the usefulness of the VIIRS ETa for drought monitoring and early warning applications without further adjustments, while bias-correction and calibration procedures may be required before using the VIIRS ETa data for localized water budget assessments. Availability of gridded actual ETa data from a combination of flux towers and basin-scale ETa is desired to establish bias-correction procedures to improve the absolute accuracy of remote-sensing ETa such as the SSEBop VIIRS operational products.

Book chapter↗

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, ↗

USGS2024

Advancing water security in Africa with new high-resolution discharge data

VegDischarge v1 is a comprehensive river discharge across Africa (2000–2021), produced by coupling the agro-hydrologic VegET model and the mizuRoute routing framework. Using remote sensing data and hydrological modeling, the 1-km runoff field simulated by VegET, and routed with mizuRoute, covers over 64,000 river segments in Africa. The VegET model simulates runoff based on vegetation and soil moisture dynamics, while mizuRoute processes this runoff through a detailed river network. Performance metrics show strong model reliability, with R² ranging from 0.5 to 0.9, NSE between 0.6 and 0.9, and KGE from 0.5 to 0.8. The total annual average discharge for Africa is quantified at 3238.1 km³ . year-1, with contributions to various oceanic basins: 989.9 km³ . year-1 to the North Atlantic, primarily from West African rivers like the Senegal, Gambia, Volta, and Niger; 1313.7 km³ . year-1 to the South Atlantic, largely from the Congo River; 212.5 km³ . year-1 to the Mediterranean Sea, predominantly from the Nile River; and 722.0 km³ . year-1 to the Indian Ocean, with substantial inputs from rivers such as the Zambezi. This VegDischarge v1 is valuable for policymakers, stakeholders, and researchers to better understand water availability, its temporal and spatial variations, that impact water-related infrastructure planning, sustainable resource allocation, and the development of climate resilience mitigation strategies.

Scientific Data↗

USGS2024

Developing version 2 of satellite-estimated precipitation monthly reports for selected locations in the Republic of the Marshall Islands

The Republic of the Marshall Islands (RMI; also known as the Marshall Islands) is a nation of more than 30 low-lying atolls and islands, most of which are inhabited, dispersed across an Exclusive Economic Zone over 770,000 square miles in the tropical central north Pacific Ocean. The study objectives and methods were originally presented in U.S. Geological Survey Data Report 1181 and are summarized herein. Monitoring environmental conditions for potential drought risk is challenging in such a dispersed island nation, and current drought hazard products provide generalities regarding conditions on a broad geographic scale. In 2022–23, a team of U.S. Geological Survey scientists, and managers of natural resources and natural hazards in the RMI, used Integrated Multi-satellitE Retrievals for Global Precipitation Measurement satellite estimates of precipitation to develop content and a template for timely monthly reporting of precipitation for 23 inhabited atolls and islands. After a year of report production and user feedback, the team incorporated lessons learned and revised user priorities to update the content and layout of the template. This data report describes the collaboration process and results of revising the report content and layout into version 2 of the monthly satellite-estimated precipitation report.

Data Report↗

USGS2024

A framework for disaggregating remote-sensing cropland into rainfed and irrigated classes at continental scale

Agriculture consumes the largest share of freshwater globally; therefore, distinguishing between rainfed and irrigated croplands is essential for agricultural water management and food security. In this study, a framework incorporating the Budyko model was used to differentiate between rainfed and irrigated cropland areas in Africa for eight remote sensing landcover products and a high-confidence cropland map (HCCM). The HCCM was generated for calibration and validation of the crop partitioning framework as an alternative to individual cropland masks which exhibit high disagreement. The accuracy of the framework in partitioning the HCCM was evaluated using an independent validation dataset, yielding an overall accuracy rate of 73 %. The findings of this study indicate that out of the total area covered by the HCCM (2.36 million km 2 ), about 461,000 km 2 (19 %) is irrigated cropland. The partitioning framework was applied on eight landcover products, and the extent of irrigated areas varied between 19 % and 30 % of the total cropland area. The framework demonstrated high precision and specificity scores, indicating its effectiveness in correctly identifying irrigated areas while minimizing the misclassification of rainfed areas as irrigated. This study provides an enhanced understanding of rainfed and irrigation patterns across Africa, supporting efforts towards achieving sustainable and resilient agricultural systems. Consequently, the approach outlined expands on the suite of remote sensing landcover products that can be used for agricultural water studies in Africa by enabling the extraction of irrigated and rainfed cropland data from landcover products that do not have disaggregated cropland classes.

International Journal of Applied Earth Observation↗

USGS2023

Developing satellite-estimated precipitation monthly reports for selected locations in the Republic of the Marshall Islands

The Republic of the Marshall Islands (also known as the Marshall Islands) is a nation of more than 30 low-lying atolls and islands, most of which are inhabited, dispersed across an Exclusive Economic Zone over 770,000 square miles in the tropical central north Pacific Ocean. Monitoring environmental conditions for potential drought risk is challenging in such a dispersed island nation, and current drought hazard products provide generalities regarding conditions on a broad geographic scale. U.S. Geological Survey scientists and managers of natural resources and natural hazards in the Marshall Islands used Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (called “IMERG”) satellite estimates of precipitation to develop content and a template for timely monthly reporting of precipitation for 23 inhabited atolls and islands. The IMERG data are available in a U.S. Geological Survey data release at https://doi.org/10.5066/P95ANG3N . The monthly reports itself are available in a U.S. Geological Survey data release at https://doi.org/10.5066/P90J1426 . This Data Report describes the collaboration process and results of developing the report content and layout.

Data Report↗

USGS2023

Improvements and evaluation of the agro-hydrologic VegET model for large-area water budget analysis and drought monitoring

We enhanced the agro-hydrologic VegET model to include snow accumulation and melt processes and the separation of runoff into surface runoff and deep drainage. Driven by global weather datasets and parameterized by land surface phenology (LSP), the enhanced VegET model was implemented in the cloud to simulate daily soil moisture (SM), actual evapotranspiration (ETa), and runoff (R) for the conterminous United States (CONUS) and the Greater Horn of Africa (GHA). Evaluation of the VegET model with independent data showed satisfactory performance, capturing the temporal variability of SM (Pearson correlation r: 0.22–0.97), snowpack (r: 0.86–0.88), ETa (r: 0.41–0.97), and spatial variability of R (r: 0.81–0.90). Absolute magnitudes showed some biases, indicating the need of calibrating the model for water budget analysis. The seasonal Landscape Water Requirement Satisfaction Index (L-WRSI) for CONUS and GHA showed realistic depictions of drought hazard extent and severity, indicating the usefulness of the L-WRSI for the convergence of an evidence toolkit used by the Famine Early Warning System Network to monitor potential food insecurity conditions in different parts of the world. Using projected weather datasets and landcover-based LSP, the VegET model can be used not only for global monitoring of drought conditions, but also for evaluating scenarios on the effect of a changing climate and land cover on agriculture and water resources.

Horn of Africa↗

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↗

USGS2023

Satellite precipitation bias estimation and correction using in situ observations and climatology isohyets for the MENA region

The availability of reliable gridded precipitation datasets is limited around the world, especially in arid regions. In this study, we utilized observations from satellite-based precipitation data and in situ rain gauge observations to determine a suitable precipitation dataset in the Middle East & North Africa (MENA) region. First, we evaluated seven different precipitation products using rain gauge observations. The validation was conducted at the daily, monthly, and annual time scales. Results indicated a weaker correlation between in situ rain gauge observation and satellite precipitation data at the daily time step (r: 0.02 to 0.44), mainly due to the lack of range in precipitation distribution. However, the agreement between precipitation estimates and in situ gauge observations improved at monthly (r: 0.02 to 0.66) and annual time scales (r: −0.22 to 0.57), indicating greater reliability of satellite-based precipitation at monthly and annual time scales. Based on the results and dataset availability, the Multi-Source Weighted-Ensemble Precipitation (MSWEP) was deemed suitable to create a bias-corrected new precipitation dataset for the MENA region. This study highlights the benefits of an adjusted regional precipitation product for hydrologic applications in the MENA region, such as streamflow or runoff estimation, to improve the reliability of the model outputs.

West Bank↗

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

Historical changes in plant water use and need in the continental United States

A robust method for characterizing the biophysical environment of terrestrial vegetation uses the relationship between Actual Evapotranspiration (AET) and Climatic Water Deficit (CWD). These variables are usually estimated from a water balance model rather than measured directly and are often more representative of ecologically-significant changes than temperature or precipitation. We evaluate trends and spatial patterns in AET and CWD in the Continental United States (CONUS) during 1980–2019 using a gridded water balance model. The western US had linear regression slopes indicating increasing CWD and decreasing AET (drying), while the eastern US had generally opposite trends. When limits to plant performance characterized by AET and CWD are exceeded, vegetation assemblages change. Widespread increases in aridity throughout the west portends shifts in the distribution of plants limited by available moisture. A detailed look at Sequoia National Park illustrates the high degree of fine-scale spatial variability that exists across elevation and topographical gradients. Where such topographical and climatic diversity exists, appropriate use of our gridded data will require sub-setting to an appropriate area and analyzing according to categories of interest such as vegetation communities or across obvious physical gradients. Recent studies have successfully applied similar water balance models to fire risk and forest structure in both western and eastern U.S. forests, arid-land spring discharge, amphibian colonization and persistence in wetlands, whitebark pine mortality and establishment, and the distribution of arid-land grass species and landscape scale vegetation condition. Our gridded dataset is available free for public use. Our findings illustrate how a simple water balance model can identify important trends and patterns at site to regional scales. However, at finer scales, environmental heterogeneity is driving a range of responses that may not be simply characterized by a single trend.

PLoS ONE↗

USGS2021

Dynamics of green and blue water supply stress index across major global cropland basins

Global food and water insecurity could be serious problems in the upcoming decades with growing demands from the increasing global population and more frequent effect of climatic extremes. As the available water resources are diminishing and facing continuous stress, it is crucial to monitor water demand and water availability to understand the associated water stresses. This study assessed the water stress by applying the water supply stress index (WaSSI) in relation to green (WaSSI G ) and blue (WaSSI B ) water resources across six major cropland basins including the Mississippi (North America), San Francisco (South America), Nile (Africa), Danube (Europe), Ganges-Brahmaputra (Asia), and Murray-Darling (Australia) for the past 17-years (2003–2019). The WaSSI G and WaSSI B results indicated that the Murray-Darling Basin experienced the most severe (maximum WaSSI G and WaSSI B anomalies) green and blue water stresses and the Mississippi Basin had the least. All basins had both green and blue water stresses for at least 35% (6 out of 17 years) of the study period. The interannual variations in green water stress were driven by both crop water demand and green water supply, whereas the blue water stress variations were primarily driven by blue water supply. The WaSSI G and WaSSI B provided a better understanding of water stress (blue or green) and their drivers (demand or supply driven) across cropland basins. This information can be useful for basin-specific resource mobilization and interventions to ensure food and water security.

Frontiers in Climate↗

USGS2020

A novel approach for next generation water use mapping using Landsat and Sentinel-2 satellite data

Evapotranspiration (ET) is needed in a range of applications in hydrology, climatology, ecology, and agriculture. Remote sensing-based estimation is the only viable and economical method for ET estimation over large areas. The current Landsat satellites provide images every 16 days limiting the ability to capture biophysical changes affecting ET. Thus, we explored the potential integration of Landsat 8 and Sentinel-2 data for estimating ET using a surface energy balance model. The results indicate the proposed Landsat-Sentinel data fusion approach substantially reduced relative errors from 48% to 10% on area-wide and from 49% to 17% on pixel-wide compared to linear interpolation between two Landsat images. The proposed approach had a better agreement with expected actual ET maps across high-vegetation conditions than in low-vegetation conditions. The finer temporal resolution and better accuracy of ET maps based on Landsat-Sentinel integration is of great importance in managing limited water resources.

Arizona, California↗

USGS2020

Operational global actual evapotranspiration: Development, evaluation, and dissemination

Satellite-based actual evapotranspiration (ETa) is becoming increasingly reliable and available for various water management and agricultural applications from water budget studies to crop performance monitoring. The Operational Simplified Surface Energy Balance (SSEBop) model is currently used by the US Geological Survey (USGS) Famine Early Warning System Network (FEWS NET) to routinely produce and post multitemporal ETa and ETa anomalies online for drought monitoring and early warning purposes. Implementation of the global SSEBop using the Aqua satellite’s Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and global gridded weather datasets is presented. Evaluation of the SSEBop ETa data using 12 eddy covariance (EC) flux tower sites over six continents indicated reasonable performance in capturing seasonality with a correlation coefficient up to 0.87. However, the modeled ETa seemed to show regional biases whose natures and magnitudes require a comprehensive investigation using complete water budgets and more quality-controlled EC station datasets. While the absolute magnitude of SSEBop ETa would require a one-time bias correction for use in water budget studies to address local or regional conditions, the ETa anomalies can be used without further modifications for drought monitoring. All ETa products are freely available for download from the USGS FEWS NET website.

Article↗

USGS2019

Evaluating the temperature difference parameter in the SSEBop model with satellite observed land surface temperature data

The Operational Simplified Surface Energy Balance (SSEBop) model uses the principle of satellite psychrometry to produce spatially explicit actual evapotranspiration (ETa) with remotely sensed and weather data. The temperature difference ( dT ) in the model is a predefined parameter quantifying the difference between surface temperature at bare soil and air temperature at canopy level. Because dT is derived from the average-sky net radiation based primarily on climate data, validation of the dT estimation is critical for assuring a high-quality ETa product. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) data to evaluate the SSEBop dT estimation for the conterminous United States. MODIS data (2008–2017) were processed to compute the 10-year average land surface temperature (LST) and normalized difference vegetation index (NDVI) at 1 km resolution and 8-day interval. The observed dT ( dT o ) was computed from the LST difference between hot (NDVI < 0.25) and cold (NDVI > 0.7) pixels within each 2° × 2° sampling block. There were enough hot and cold pixels within each block to create dT o timeseries in the West Coast and South-Central regions. The comparison of dT o and modeled dT ( dT m ) showed high agreement, with a bias of 0.8 K and a correlation coefficient of 0.88 on average. This study concludes that the dT m estimation from the SSEBop model is reliable, which further assures the accuracy of the ETa estimation.

Conterminous United States↗

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↗