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Results for “Advances in Water Resources”

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At least 91 records · Page 5Linked to original sources
USGS2016

Toward improved simulation of river operations through integration with a hydrologic model

Advanced modeling tools are needed for informed water resources planning and management. Two classes of modeling tools are often used to this end–(1) distributed-parameter hydrologic models for quantifying supply and (2) river-operation models for sorting out demands under rule-based systems such as the prior-appropriation doctrine. Within each of these two broad classes of models, there are many software tools that excel at simulating the processes specific to each discipline, but have historically over-simplified, or at worse completely neglected, aspects of the other. As a result, water managers reliant on river-operation models for administering water resources need improved tools for representing spatially and temporally varying groundwater resources in conjunctive-use systems. A new tool is described that improves the representation of groundwater/surface-water (GW-SW) interaction within a river-operations modeling context and, in so doing, advances evaluation of system-wide hydrologic consequences of new or altered management regimes.

Environmental Modelling and Software↗
USGS2022

Modflow-setup: Robust automation of groundwater model construction

In an age of both big data and increasing strain on water resources, sound management decisions often rely on numerical models. Numerical models provide a physics-based framework for assimilating and making sense of information that by itself only provides a limited description of the hydrologic system. Often, numerical models are the best option for quantifying even intuitively obvious connections between human activities and water resource impacts. However, despite many recent advances in model data assimilation and uncertainty quantification, the process of constructing numerical models remains laborious, expensive, and opaque, often precluding their use in decision making. Modflow-setup aims to provide rapid and consistent construction of MODFLOW groundwater models through robust and repeatable automation. Common model construction tasks are distilled in an open-source, online code base that is tested and extensible through collaborative version control. Input to Modflow-setup consists of a single configuration file that summarizes the workflow for building a model, including source data, construction options, and output packages. Source data providing model structure and parameter information including shapefiles, rasters, NetCDF files, tables, and other (geolocated) sources to MODFLOW models are read in and mapped to the model discretization, using Flopy and other general open-source scientific Python libraries. In a few minutes, an external array-based MODFLOW model amenable to parameter estimation and uncertainty quantification is produced. This paper describes the core functionality of Modflow-setup, including a worked example of a MODFLOW 6 model for evaluating pumping impacts to a lake in central Wisconsin, United States.

Wisconsin↗
USGS2025

Second Integrated Hydro-Terrestrial Modeling (IHTM 2.0) workshop: USGCRP federal agency perspectives

U.S. federal leadership, mobilizing close interagency coordination across sectors, is key to tackling compound climate and human impacts on our nation’s water resources. Recognizing this need, federal agencies and academic collaborators conducted a series of workshops to advance Integrated Hydro-Terrestrial Modeling (IHTM). IHTM is focused on supporting a multiscale framework to accelerate research insights, better integrate operational and planning perspectives, and bridge national-to-regional capabilities to address major interdependent societal water challenges. This framework leverages the capabilities of different agencies and institutional partners across sectors to advance a shared vision for use-inspired modeling and open science. The IHTM conceptual framework has developed over several community workshops in recent years: ● In September 2019, a community coordinating group on IHTM hosted an interagency workshop (“IHTM 1.0”) with support from NSF, DOE, and USGS. The resulting report identified the need for agencies to invest resources in designing pilot use cases, setting the stage for an integrated national IHTM capability. ● In November 2020, the U.S. Global Change Research Program (USGCRP) held a virtual Coastal-IHTM (C-IHTM) workshop in collaboration with the MultiSector Dynamics Community of Practice, which engages researchers across universities and national labs. Building on IHTM 1.0, this workshop aimed to identify coastal modeling capabilities and appropriate coastal applications of the IHTM framework. The workshop report detailed needs for open science, geographical or topical use cases, integrated modeling frameworks, and linking communities of practice. ● From October 31 to November 2, 2023, USGCRP hosted a hybrid IHTM 2.0 community workshop that brought together 160 scientists and managers from nine federal departments/agencies (DHS-FEMA, DOC-NOAA, DoD-USACE, DOE, DOI [U.S. Bureau of Reclamation (USBR), USGS], EPA, NASA, NSF, USDA [ARS, FS, NRCS]) and 32 non-federal academic, non-profit, and private institutions and consortiums. The workshop was organized by a federal Interagency Steering Committee with representatives from DOE, USGS, NSF, NASA, and NOAA, as well as a Scientific Organizing Committee comprising experts from academia and additional federal agency technical experts. The IHTM 2.0 workshop focused on moving the IHTM 1.0 concepts to action by making advances in designing national and regional integrated modeling experiments in five geographic testbeds. These modeling testbeds seek to facilitate collaborative water resources research and assessment that responds to societal needs, extending from basic research to resource management operations, including the assessment of water quantity, quality, and use at national and regional scales. Ultimately, we envision that the IHTM testbeds will improve our ability to provide water resources assessment scenarios to decision-makers and the public. This document summarizes USGCRP and member agencies’ perspectives of the IHTM 2.0 workshop. Sections 2 and 3 build on the work of the IHTM 2.0 workshop Scientific Organizing Committee to outline the importance of IHTM, summarize the workshop, and propose near- and medium-term IHTM priorities. Section 4 presents select ongoing and potential interagency activities that could help realize the IHTM 2.0 vision and align with three of USGCRP’s strategic goals for this decade: Advancing Science, Informing Decisions, and Engaging the Nation. Finally, Section 5 summarizes this report and offers information about how to connect with USGCRP’s IHTM activities. USGCRP and its member agencies are well-positioned to coordinate federal efforts to enhance IHTM capabilities in the coming years.

Conference Paper↗
USGS2018

Current research in land, water, and agroecosystems: ASABE journals 2017 year in review

This article highlights current research into land and water resources, agroecosystems, and agricultural production systems published by the Natural Resources and Environmental Systems (NRES) community of ASABE journals (Transactions of the ASABE and Applied Engineering in Agriculture) in 2017. This article reviews the context, scope, and key results of the published articles and perhaps more importantly recommends areas for increased research attention. Experimental and modeling advances were described in hydrology, agroecosystems, climate-change effects, soil erosion, irrigation, drainage, forest resources, livestock systems, natural treatment systems, international water issues, and water quality topic areas. Three special collections were published (International Watershed Technology, Crop Modeling to Optimize Water Use, and Advances in Drainage). Other focal areas included 14 articles relating to livestock waste management, 13 concerning irrigated agricultural systems, 8 addressing climate change effects on land and water resources, and 16 on various aspects of soil erosion measurement and modeling. Building on the articles reviewed from 2017 and toward a vision of future agroecosystems research, the NRES community of ASABE journals strives to grow its role in making new knowledge accessible to sustain agricultural and natural systems in a changing world. In this vane, recommendations for future research direction are discussed with an emphasis on increased application of remote sensing data to agroecosystems research, improved assessment of agroecosystem resiliency and vulnerability to land and climate change, development of integrated models of agroecosystem services, meeting stubborn water management challenges in agricultural production systems, and focusing on publishing fully reproducible model results.

Transactions of the ASABE↗
USGS2018

Ecosystems science: Genes to landscapes

Bountiful fisheries, healthy and resilient wildlife, flourishing forests and vibrant grasslands are coveted resources that benefit all Americans. U.S. Geological Survey (USGS) science supports the conservation and management of the Nation’s fish and wildlife, and the landscapes they inhabit. Our biological resources—ecosystems and the wild things that live in them—are the foundation of our conservation heritage and an economic asset to current and future generations of Americans. The USGS Ecosystems Mission Area, the biological research arm of the Department of the Interior (DOI), provides science to help America achieve sustainable management and conservation of its biological resources. This work is done within the broader mission of the USGS—to serve the Nation with science that advances understanding of our natural resources, informs land and water stewardship, and helps safeguard communities from natural and environmental hazards. The Ecosystems Mission Area provides research, technical assistance, and education conducted by Cooperative Research Units and Science Centers located in nearly every State. The quality of life and economic strength in America hinges on healthy ecosystems that support living things and natural processes. Ecosystem science better enables society to understand how and why ecosystems change and to guide actions that can prevent damage to, and restore and sustain ecosystems. It is through this knowledge that informed decisions are made about natural resources that can enhance our Nation’s economic and environmental well-being.

Fact Sheet↗
USGS2014

On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates

Downscaling is one of the important ways of utilizing the combined benefits of the high temporal resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) images and fine spatial resolution of Landsat images. We have evaluated the output regression with intercept method and developed the Linear with Zero Intercept (LinZI) method for downscaling MODIS-based monthly actual evapotranspiration (AET) maps to the Landsat-scale monthly AET maps for the Colorado River Basin for 2010. We used the 8-day MODIS land surface temperature product (MOD11A2) and 328 cloud-free Landsat images for computing AET maps and downscaling. The regression with intercept method does have limitations in downscaling if the slope and intercept are computed over a large area. A good agreement was obtained between downscaled monthly AET using the LinZI method and the eddy covariance measurements from seven flux sites within the Colorado River Basin. The mean bias ranged from −16 mm (underestimation) to 22 mm (overestimation) per month, and the coefficient of determination varied from 0.52 to 0.88. Some discrepancies between measured and downscaled monthly AET at two flux sites were found to be due to the prevailing flux footprint. A reasonable comparison was also obtained between downscaled monthly AET using LinZI method and the gridded FLUXNET dataset. The downscaled monthly AET nicely captured the temporal variation in sampled land cover classes. The proposed LinZI method can be used at finer temporal resolution (such as 8 days) with further evaluation. The proposed downscaling method will be very useful in advancing the application of remotely sensed images in water resources planning and management.

Remote Sensing↗
USGS2026

Computational electromagnetic geophysics for groundwater system studies: A review on established practices and recent advances

Identifying effective solutions for locating groundwater resources and ensuring the quality of drinking water is increasingly urgent, given the challenges posed by climate change and population growth. This review investigates electromagnetic geophysical imaging techniques, in both time- and frequency-domain, that can provide valuable insights for groundwater assessment. We explore computational electromagnetic methods used to evaluate electromagnetic data and several recent hydrogeophysical case studies. As open-source frameworks for modeling electromagnetic geophysical problems become available, a broader range of researchers can interpret their data with computationally advanced software. We provide an overview of documented open-source codes for evaluating electromagnetic data and analyze various hydrological targets in relation to their electromagnetic surveying technique and the computational method applied. Furthermore, we evaluate the potential of advanced computational techniques, including three-dimensional modeling, non-deterministic inversion and machine learning, to couple geophysical with numerical groundwater modeling and apply it in groundwater system studies. Despite obstacles such as complexity and resource demands, our findings indicate that the quantification and integration of predictive uncertainties from both electromagnetic and hydrological data and simulations would significantly improve the reliability of hydrogeophysical models. This can lead to a deeper understanding of groundwater systems and improved management practices.

Journal of Hydrology↗
USGS1952

Preliminary report on ground water in the Michaud Flats Project, Power County, Idaho

The Michaud Flats Project area, as here described, includes about 65 square miles in central Power County, south of the Snake River in the southeastern Snake River Plain of Idaho. The principal town and commercial center of the area is American Falls. The immediate purpose of work in the area by the U.S. Geological Survey was to investigate the possibility of developing substantial quantities of ground water for irrigating high and outlying lands in the proposed Michaud Flats Project area of the U.S. Bureau of Reclamation. Initial findings are sufficiently favorable to warrant comprehensive further investigation. Advanced study would assist proper utilization of ground-water resources and would aid ultimate evaluation of total water resources available in the area. About 10,000 acres of low-lying lands in the Michaud Flats project could be irrigated with water from the Snake River under a low-line distribution system involving a maximum pumping lift of about 200 feet above the river. An additional larger area of high and outlying lands is suitable for irrigation with water pumped from wells. If sufficient ground water is economically available, the expense of constructing and operating a costly highline distribution system for surface water could be saved. Reconnaissance of the ground-water geology of the area disclosed surface outcrops of late Cenozoic sedimentary, pyroclastic, and volcanic rocks. Well logs and test borings show that similar materials are present beneath the land surface in the zone of saturation. Ground water occurs under perched, unconfined, and confined (artesian) conditions, but the aquifers have not been adequately explored. Existing irrigation wells, 300 feet or less in depth, yield several hundred to 1,400 gallons of water a minute, with pumping drawdowns of 6 to 50 feet, and perhaps more. A few wells have been pumped out at rates of less than 800 gallons a minute. Scientific well-construction and development methods would lead to more efficient well performance. A generalized water-table contour map of the area shows that the principal general direction of ground-water movement is toward the west and northwest. The southwestern part of the American Falls Reservoir, and a segment of the Snake River below the dam, may be perched above the water table. Ground water appears to move beneath this segment of the river to the Snake River Plain on the northwest side. So far as is known, recharge to the ground-water reservoir is chiefly from local sources and from the runoff from the mountain area southeast of the project. Seepage losses from surface water spread for irrigation would contribute a substantial amount of new recharge to the ground water, but the amount of such recharge might be less than the depletion of ground water by pumping. Therefore, with ground-water irrigation a part of the project, return flow to the American Falls Reservoir might be less than it is in the existing regimen. Ground-water pumping where the ground water is not tributary to the reservoir might not deplete the reservoir appreciably, but would reduce the net supply of water available west of Neeley. Evidence indicates that at least moderate supplies of ground water can be obtained in low-lying areas southwest and northeast of American Falls, but the safe perennial yields of the aquifers cannot now be estimated. The ground-water potential in high and outlying lands is not known. It is unlikely that this potential is sufficient to supply all high and outlying lands, but the supply may be adequate for a substantial part of these lands. Thorough investigation appears to be warranted.

Open-File Report↗
USGS2015

Accelerating advances in continental domain hydrologic modeling

In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

Water Resources Research↗
USGS2026

Origins, evolutions, and future directions of Landsat science products for advancing global inland water and coastal ocean observations

In April 2020, the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center introduced a Level 2 provisional Aquatic Reflectance (AR) product for the Landsat 8 Operational Land Imager (OLI), marking the initial phase in developing a standardized global product for Landsat-derived surface water measurements. The goal of USGS EROS aquatic product research and development is to prepare for an operational processing architecture for Landsat Collection 3 in the late 2020s that will enable use of quality-controlled data for emerging Landsat aquatic science applications. To achieve this, we released a subset of the Landsat 8/9 provisional AR products (Crawford et al., 2025, https://doi.org/10.5066/P14MBBRM) and examined its general performance through the Science Algorithms to Operations (SATO) framework alongside quantitative assessment using community made inland water data records (GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments, GLORIA) and radiometric coastal validation platforms (NASA’s Ocean Color component of the Aerosol Robotic Network, AERONET-OC). Variability within the validation datasets indicate that the performance of the Landsat 8/9 provisional AR retrieval is highly context-dependent; errors are minimal in optically simple waters (e.g., clear to moderately turbid coastal waters) but increase considerably in optically complex waters where factors such as elevated levels of turbidity, chlorophyll (Chl a ) concentrations, or colored dissolved organic matter (CDOM) dominate the water column. Additionally, this paper examines key algorithmic considerations for atmospheric correction, highlighting factors that influence accuracy, scalability, and computational efficiency necessary for collection processing in the operational Landsat Product Generation System (LPGS). This paper is intended to communicate with aquatic scientists, satellite oceanographers, and the broader Earth observation community on the origins, requirements, challenges, successes, and future objectives for operationalizing global AR data products for Landsat satellite missions.

Earth System Science Data↗
USGS1998

Successful water quality monitoring: The right combination of intent, measurement, interpretation, and a cooperating ecosystem

Water quality monitoring is invaluable to ensure compliance with regulations, detect trends or patterns, and advance ecological understanding. However, monitoring typically measures only a few characteristics in a small fraction of a large and complex system, and thus the information contained in monitoring data depends upon which features of the ecosystem are actually captured by the measurements. Difficulties arise when these data contain something other than intended, but this can be minimized if the purpose of the sampling is clear, and the sampling design, measurements, and data interpretations are all compatible with this purpose. The monitoring program and data interpretation must also be properly matched to the structure and functioning of the system. Obtaining this match is sometimes an iterative process that demands a close link between research and monitoring. This paper focuses on water quality monitoring that is intended to track trends in aquatic resources and advance ecological understanding. It includes examples from three monitoring programs and a simulation exercise that illustrate problems that arise when the information content of monitoring data differs from expectation. The examples show (1) how inconsistencies among, or lack of information about, the basic elements of a monitoring program (intent, design, measurement, interpretation, and the monitored system) can produce a systematic difference (bias) between monitoring measurements and sampling intent or interpretation, and (2) that bias is not just a statistical consideration, but an insidious problem that can undermine the scientific integrity of a monitoring program. Some general suggestions are provided and hopefully these examples will help those engaged in water quality monitoring to enhance and protect the value of their monitoring investment.

Lake and Reservoir Management↗
USGS2025

Confluence of time and space: An innovation for quantifying dynamics of hydrologic floodplain connectivity with remote sensing and GIS

Hydrologic connectivity is a crucial determinant of aquatic ecosystem services, governing the exchange of nutrients, sediments, chemicals, and biota. Various indices and metrics exist for quantifying hydrologic connectivity across diverse environments and scales. However, existing methodologies often fail to adequately capture lateral connectivity between floodplain lakes and streams across vast, low-relief, multi-lake floodplain systems. This study introduces a novel approach for quantifying lateral hydrologic connectivity specifically tailored for floodplain lakes connecting to streams within the expansive floodplain of the Lower Mississippi River. This approach centers on the spatial and temporal intersection of lakes and streams, leveraging remote sensing and GIS data to estimate nine distinct metrics of hydrologic connectivity. To assess the reliability of the method, the study estimated connectivity metrics for 92 randomly selected floodplain lakes, comprising 53 lakes connected to large streams (Strahler order >7), 13 lakes connected to medium (order 4-6) streams, and 26 lakes connected to small (order 1-3) streams. As expected, there was significant variability in hydrologic connectivity across different stream size classes. The outlined approach contributes valuable insights into the hydrologic connectivity of floodplain lakes and offers a generalizable framework applicable to other floodplains. Its versatility makes it a practical tool for understanding connectivity requirements for biota and facilitating applications in conservation and water resources management. Thus, this work represents a meaningful step toward advancing our understanding of lateral hydrologic connectivity dynamics in complex aquatic ecosystems.

Arkansas, Illinois, Kentucky, Louisiana, Mississip↗
USGS2019

Process-guided deep learning predictions of lake water temperature

The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use of advanced deep learning tools. Hybrid models that integrate theory with state‐of‐the art empirical techniques have the potential to improve predictions while remaining true to physical laws. This paper evaluates the Process‐Guided Deep Learning (PGDL) hybrid modeling framework with a use‐case of predicting depth‐specific lake water temperatures. The PGDL model has three primary components: a deep learning model with temporal awareness (long short‐term memory recurrence), theory‐based feedback (model penalties for violating conversation of energy), and model pretraining to initialize the network with synthetic data (water temperature predictions from a process‐based model). In situ water temperatures were used to train the PGDL model, a deep learning (DL) model, and a process‐based (PB) model. Model performance was evaluated in various conditions, including when training data were sparse and when predictions were made outside of the range in the training data set. The PGDL model performance (as measured by root‐mean‐square error (RMSE)) was superior to DL and PB for two detailed study lakes, but only when pretraining data included greater variability than the training period. The PGDL model also performed well when extended to 68 lakes, with a median RMSE of 1.65 °C during the test period (DL: 1.78 °C, PB: 2.03 °C; in a small number of lakes PB or DL models were more accurate). This case‐study demonstrates that integrating scientific knowledge into deep learning tools shows promise for improving predictions of many important environmental variables.

Minnesota, Wisconsin↗
USGS2018

Recent advances in environmental flows science and water management—Innovation in the Anthropocene

The implementation of environmental flow regimes offers a promising means to protect and restore riverine, wetland and estuarine ecosystems, their critical environmental services and cultural/societal values. This Special Issue expands the scope of environmental flows and water science in theory and practice, offering 20 papers from academics, agency researchers and non‐governmental organisations, each with fresh perspectives on the science and management of environmental water allocations. Contributions confront the grand challenge for environmental flows and water management in the Anthropocene—the urgent need for innovations that will help to sustain the innate resilience of social–ecological systems under dynamic and uncertain environmental and societal futures. Basin‐scale and regional assessments of flow requirements mark a necessary advance in environmental water science in the face of rapid changes in water‐resource management activities worldwide (e.g. increases in dams, diversions, retention and reuse). Techniques for regional‐scale hydrological and ecohydrological modelling support ecological risk assessment and identification of priority flow management and river restoration actions. Changing flood–drought cycles, long‐term climatic shifts and associated effects on hydrological, thermal and water quality regimes add enormous uncertainty to the prediction of future ecological outcomes, regardless of environmental water allocations. An improved capacity to predict the trajectories of ecological change in rivers degraded by legacies of past impact interacting with current conditions and future climate change is essential. Otherwise, we risk unrealistic expectations from restoration of river and estuarine flow regimes. A more robust, dynamic and predictive approach to environmental water science is emerging. It encourages the measurement of process rates (e.g. birth rate, colonisation rate) and species traits (e.g. physiological requirements, morphological adaptations) as well as ecosystem states (e.g. species richness, assemblage structure), as the variables representing ecological responses to flow variability and environmental water allocations. Another necessary development is the incorporation of other environmental variables such as water temperature and sedimentary processes in flow–ecological response models. Based on contributions to this Special Issue, several recent compilations and the wider literature, we identify six major scientific challenges for further exploration, and seven themes for advancing the management of environmental water. We see the emerging frontier of environmental flows and water science as urgent and challenging, with numerous opportunities for reinvigorated science and methodological innovation in the expanding enterprise of environmental water linked to ecological sustainability and social well‐being.

Freshwater Biology↗
USGS2015

Aquatics Systems Branch: transdisciplinary research to address water-related environmental problems

The Aquatic Systems Branch at the Fort Collins Science Center is a group of scientists dedicated to advancing interdisciplinary science and providing science support to solve water-related environmental issues. Natural resource managers have an increasing need for scientific information and stakeholders face enormous challenges of increasing and competing demands for water. Our scientists are leaders in ecological flows, riparian ecology, hydroscape ecology, ecosystem management, and contaminant biology. The Aquatic Systems Branch employs and develops state-of-the-science approaches in field investigations, laboratory experiments, remote sensing, simulation and predictive modeling, and decision support tools. We use the aquatic experimental laboratory, the greenhouse, the botanical garden and other advanced facilities to conduct unique research. Our scientists pursue research on the ground, in the rivers, and in the skies, generating and testing hypotheses and collecting quantitative information to support planning and design in natural resource management and aquatic restoration.

Fact Sheet↗
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↗
USGS2012

Strategic directions for U.S. Geological Survey water science, 2012-2022 - Observing, understanding, predicting, and delivering water science to the Nation

Executive Summary This report expands the Water Science Strategy that was begun in the USGS Science Strategy, “Facing Tomorrow’s Challenges—U.S. Geological Survey Science in the Decade 2007–2017” (U.S. Geological Survey, 2007). The report looks at the relevant issues facing society and develops a strategy built around observing, understanding, predicting, and delivering water science for the next 5 to 10 years by building new capabilities, tools, and delivery systems to meet the Nation’s water-resource needs. This report begins by presenting the vision of water science for the USGS and the societal issues that are influenced by, and in turn influence, the water resources of our Nation. The essence of the Water Strategic Science Plan is built on the concept of “water availability,” defined as spatial and temporal distribution of water quantity and quality, as related to human and ecosystem needs, as affected by human and natural influences . The report also describes the core capabilities of the USGS in water science—the strengths, partnerships, and science integrity that the USGS has built over its 130-year history. Nine priority actions are presented in the report, which combine and elevate the numerous specific strategic actions listed throughout the report. Priority actions were developed as a means of providing the audience of this report with a list for focused attention, even if resources and time limit the ability of managers to address all of the strategic actions in the report. Priority actions focus on the following: Improve integrated science planning for water. Expand and enhance water-resource monitoring networks. Characterize the water cycle through development of state-of-the-art 3-D/4-D hydrogeologic framework models at multiple scales. Clarify the linkage between human water use (engineered hydrology) and the water cycle (natural hydrology). Advance ecological flow science. Provide flood-inundation science and information. Develop rapid deployment teams for water-related emergencies. Conduct integrated watershed assessment, research, and modeling. Deliver water data and analyses to the Nation. The body of the report is presented as a hierarchal set of 5 goals, 14 objectives, and 27 strategic actions that the USGS should undertake to advance water science through year 2022. The goals deal with: Providing society the information it needs regarding the amount and quality of water in all components of the water cycle at high temporal and spatial resolution, nationwide; Advancing our understanding of processes that determine water availability; Predicting changes in the quantity and quality of water resources in response to changing climate, population, land use, and management scenarios; Anticipating and responding to water-related emergencies and conflicts; and Delivering timely hydrologic data, analyses, and decision-support tools seamlessly across the Nation to support water-resource decisions. Scientific information produced on water resources would be without value if it were not communicated to society in a fashion that can inform decisions and actions. Therefore, the chapter following the goals describes how the USGS should inform, involve, and educate society about the science it produces. This includes discussions on local outreach and the use of social media for effective communication. This report concludes with a chapter devoted to the crosscutting science issues of the Water Mission Area with the other USGS Mission Areas: Climate and Land Use Change, Core Science Systems, Ecosystems, Energy and Minerals, Environmental Health Science, and Natural Hazards. Not one of these Mission Areas stands alone—all must work together and integrate their actions to fulfill the USGS science mission for the future. This final chapter identifies the important linkages that must be realized and maintained for this integration to occur.

Open-File Report↗
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↗