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USGS2025

Estimated hydrogeologic, spatial, and temporal distribution of self-supplied domestic groundwater withdrawals for aquifers of the Virginia Coastal Plain

Water use from private-domestic wells accounts for nearly 40 percent of total groundwater withdrawals in the Virginia Coastal Plain Physiographic Province (henceforth called the Virginia Coastal Plain). However, because self-supplied domestic water use generally falls below the Virginia Department of Environmental Quality (VDEQ) reporting and management threshold of 300,000 gallons per month, quantifying these withdrawals is challenging. This report builds upon the foundation of previous U.S. Geological Survey investigations by providing revised techniques to improve estimates of the aquifer source, spatial distribution, and monthly magnitude of these groundwater withdrawals. The aquifer sources of private-domestic wells in the Virginia Coastal Plain were estimated by cross-referencing 8,264 well records from the VDEQ and the Virginia Department of Health to a digital model of the Virginia Coastal Plain hydrogeologic framework. This analysis highlights the regional importance of the Yorktown-Eastover, Potomac, and surficial aquifers. Collectively, these three aquifers account for 80 percent of self-supplied domestic groundwater withdrawals. The population using self-supplied domestic water was estimated using census blocks, well-use ratios, building footprints, and land-use and land-cover data to produce a high-resolution, disaggregated, raster-based dataset. This approach improves upon previous models at the census-block or road-network scale by reducing the low-density spread of the self-supplied domestic population across undeveloped areas and concentrating the population and its corresponding water use in the areas where it is most likely to occur. Results show that an estimated 475,332 people comprise the 2020 self-supplied domestic population of the Virginia Coastal Plain, an increase of 5.7 percent since 2010, and the greatest concentrations of self-supplied domestic population surround large cities. Estimates could be further refined with the addition of current and complete spatial data on public water-system service areas. The quantity of water used by the self-supplied domestic population was estimated by modifying published state per-capita water-use coefficients with the corresponding monthly variability assessed from Virginia Coastal Plain public water-system withdrawal data. This analysis estimates an average increase of 12 percent from June through August and an average decrease of 8 percent from December through March from the baseline annual average of 80 gallons per day per capita, which generally matches similar studies in the eastern United States. The application of these revised methodologies for the estimation of private-domestic wells and the self-supplied domestic population improves understanding of domestic groundwater use in the Virginia Coastal Plain across hydrogeologic, spatial, and temporal scales. These revisions help better inform water-resource managers and decision makers and support higher resolution groundwater modeling. Furthermore, these methods are transferrable to other areas where self-supplied domestic water withdrawals are important to the overall water budget.

Virginia↗

USGS2026

Investigation of drivers and sources of potential harmful algal blooms in Lake Anna, Virginia, 2023-24

Algal blooms in freshwater reservoirs are an increasing concern because of the risk to aquatic ecosystem health, recreational use, and water quality. Among the taxa that comprise an algal bloom, cyanobacteria are of particular concern due to the potential to produce toxic compounds which can cause acute and chronic illness in humans if ingested through contaminated water or shellfish. When toxins are above a toxin-specific threshold in the water column, the Commonwealth of Virginia categorizes the bloom as a harmful algal bloom (HAB), distinguishing it from an algal bloom without toxins present. Toxins are of particular concern in bodies of water which serve as major recreational areas, such as Lake Anna in central Virginia. Lake Anna is a 27 km-long and 47 km2 reservoir in central Virginia. Since the Commonwealth of Virginia revised the HAB monitoring framework in 2018, algal bloom advisories for potentially toxigenic blooms have been issued in the western, riverine zone of the reservoir. There were detections of microcystin and anatoxin production but no detections of cylindrospermopsin and saxitoxin production in Lake Anna; however, toxin concentrations were low, at values less than 0.65 µg/L. In 2023, the U.S. Geological Survey, in cooperation with Virginia Department of Environmental Quality, initiated a 19-month intensive and extensive study of western Lake Anna and its tributaries (North Anna River and Pamunkey Creek) to (1) characterize the algal community, biomass, and toxin production; (2) identify potential drivers leading to algal bloom initiation, persistence, and decline; and (3) assess the primary sources of the drivers contributing to algal blooms. Continuous and discrete monitoring of water quality within the lake, watershed inputs, meteorological conditions, and algal communities were monitored. Multiple modeling scenarios identified that the formation and persistence of algal blooms in Lake Anna are driven by interactions among chemical, macro- and micronutrient, and physical factors. Key drivers include total nitrogen, total phosphorus, water temperature, suspended sediment concentration, wind speed, copper, iron, molybdenum, nickel, sodium, and alkalinity. During this study, winter stormflow events delivered the highest loading of macro- and micronutrients from the tributaries to the lake. The lake is a sink for these nutrients in the water column or in the lake-bed sediments. During high-occupancy and recreation periods on the lake in the summer months, boating activity can promote internal loading by the resuspension of the lake-bed sediments, thereby increasing the nutrient availability for algal uptake. Thermal stratification and hypoxic conditions were observed, which can contribute to the passive release of nutrients into the water column, further facilitating algal bloom proliferation. These processes may create a positive feedback loop that supports the formation, persistence, and annual recurrence of algal blooms in the western region of Lake Anna. Continued water-quality monitoring of early warning indicators may improve the detection and forecasting of algal growth in the lake and help managers proactively manage water quality and algal growth.

EarthArXiv↗

USGS2024

Taking heat (downstream): Simulating groundwater and thermal equilibrium controls on annual paired air–water temperature signal transport in headwater streams

Headwater stream temperature often exhibits spatial variation at the kilometer-scale, but the relative importance of the underlying hydrogeological processes and riverine perturbations remains poorly understood. In this study, we investigated the relative importance of groundwater (GW) and other processes on downstream annual stream temperature signal characteristics using deterministic heat budget model (HFLUX) scenarios within an idealized stream reach representative of mountainous forested conditions. We summarized annual stream thermal regimes from the relationship of paired sinusoidal air and water temperature signals (amplitude ratio, phase lag, and mean ratio). Results showed that downstream changes in annual temperature depended on the thermal gradient between water and the hypothetical equilibrium temperature (where all heat fluxes sum to zero). GW inflow, riparian shading, and the boundary input signal were the most significant factors affecting downstream annual water temperature signals, while flow volume and channel dimensions impacted how quickly annual temperature signals changed. Effects of GW were dominated by advective rather than conductive heat exchange processes, but conduction played a larger role when GW input was more spatially diffuse. Our results indicated several mechanisms by which local processes may affect stream thermal resilience to disturbances and can help guide management of wildfire and climate change.

Journal of Hydrology↗

USGS2026

Decadal-scale characteristics of natural and anthropogenic dune morphology along North Carolina Barrier Islands (SE Atlantic Coast)

Dunes offer protection to coastal communities from storms, yet quantitative research characterizing human influences on dune systems across decades and 10–100 km spatial scales constitutes a known data gap. This study analyzed a multidecadal archive of dune crest elevations and positions to map mesoscale spatiotemporal trends in foredune morphology across the barrier island coastline of North Carolina, SE Atlantic coast. Results are summarized within four categories of coastline representing a range of coastal management intensities, integrating beach width and dune lateral accommodation space to assess the comparative influence of differing intensities of anthropogenic intervention on dune morphology. These categories account for the presence of structures, roads, and alongshore connectivity to anthropogenic sediment sources (beach nourishment). These categories show distinct dune and beach system characteristics. Dunes are largest in the areas with the longest legacy of coastal management. As categories decrease in development intensity, dune and beach system characteristics generally depart from the large, static dunes and narrow beaches consistent with hold-the-line management. Where small or transgressive dunes exist on heavily developed coasts, they coincide with relatively strong hydrodynamic forcing or sediment-limiting geology. There is evidence of indirect coastal management influence on undeveloped barrier islands with alongshore connectivity to developed barriers. While this analysis was conducted at the mesoscale, the results provide researchers with the framework to make insights at smaller scales than those demonstrated in this study.

North Carolina↗

USGS2026

Simulation of groundwater flow in the Silurian aquifer, eastern Iowa, 2020–45

The Silurian aquifer is an important water source for municipalities, industry, and rural households and communities in eastern Iowa, including Johnson County. Increasing demand for groundwater from the aquifer indicated that analytical tools may be beneficial to quantify groundwater resources and inform water-management decisions for the aquifer. The U.S. Geological Survey, in cooperation with the Johnson County Board of Supervisors, developed conceptual and numerical groundwater models to simulate water levels in the Silurian aquifer, determine groundwater budgets, and forecast changes in groundwater levels through 2045. A MODFLOW numerical model was constructed to match water levels for 2020 through 2022. Model performance was assessed by comparing simulated and observed water-level hydrographs at several pumping and monitoring wells. Hydrograph comparison indicates that the model simulates water levels accurately at monitoring wells that are not near areas of pumping and generally overpredicts water levels near pumping wells, while accurately simulating the drawdown trend over time at pumping wells. This transient model framework was then used to predict water levels through 2045 in a scenario of moderate drought and increased groundwater withdrawals. Results from the predictive model indicate as much as 13 meters of additional drawdown in 2045 from 2020 water levels in the area of pumping wells.

Iowa↗

USGS2026

Final project peport for “Mapping riparian vegetation response to climate change on the San Carlos Apache Reservation and Upper Gila River watershed to inform restoration priorities: 1935 to present – Phase 2: Focus on tamarisk vegetation”

Riparian ecosystems play a critical role in supporting wildlife habitats, maintaining water quality, and sustaining ecological resilience in arid landscapes. In the Upper Gila River level-4 Hydrologic Unit Code (HUC-4; Identification Number – 1504) watershed of Arizona and New Mexico, and across areas of the San Carlos Apache Tribe of the San Carlos Apache Reservation (hereafter, Tribe/Tribal – entity; or Reservation - place), riparian ecosystems have been substantially altered by the widespread expansion of tamarisk ( Tamarix spp.), an invasive and non-native riparian species. Tamarisk has high water use and increased flammability, making it a growing concern as droughts intensify across the southwestern United States (U.S.). Recent research indicates that tamarisk is increasingly stressed under prolonged drought conditions, which can elevate wildfire risk and further degrade riparian habitat. In response, the U.S. Geological Survey (USGS) Western Geographic Science Center, in collaboration with the Tribe, developed remote sensing–based tools to map riparian vegetation composition and monitor vegetation condition over time. These tools enable accurate identification of tamarisk extent, detection of vegetation stress, and comparison with native species such as cottonwood and willow. This information directly supports restoration and management actions, including targeted tamarisk removal, protection of endangered species habitat, and prioritization of areas for native vegetation recovery. The tools also provide insight into how riparian vegetation responds to changing climate and hydrologic conditions, strengthening long-term planning for riparian forest management. Findings from this work demonstrate that riparian vegetation responses vary across river systems, indicating differences in plant composition and hydro-climatic conditions. Tamarisk on both the Gila and San Carlos Rivers generally exhibit greater declines in greenness in response to higher temperature as well as lower precipitation and river flow, while cottonwood ( Populus fremontii ) and willow (Salix spp.) are particularly sensitive to changes in discharge along the San Carlos River and respond more directly to both high and low flows, with more moderate responses to precipitation and temperature. By providing actionable, science-based information, this research supports climate adaptation planning, wildfire risk reduction, and improved riparian ecosystem health, with benefits that extend beyond the Reservation to regional water and wildlife conservation efforts.

Arizona, New Mexico↗

USGS2025

U.S. Geological Survey Integrated Water Availability Assessment—2010–20

This professional paper is a multichapter report that assesses water availability in the United States for water years 2010–20. This work was conducted as part of the fulfillment of the mandates of Subtitle F of the Omnibus Public Land Management Act of 2009 (Public Law 111-11), also known as the SECURE Water Act. As such, this work examines the spatial and temporal distribution of water quantity and quality in surface water and groundwater, as related to human and ecosystem needs and as affected by human and natural influences. Chapter A introduces the National Integrated Water Availability Assessment and provides important background and definitions for how the report characterizes water availability and its components. Chapter A also presents the key findings of Chapters B–F and thus acts as a summary of the entire report. Chapter B is a national assessment of water supply, which is the quantity of water supplied through climatic inputs. Chapter C is a national assessment of water quality, which is the chemical and physical characteristics of water. Chapter D assesses water use including withdrawals and consumptive use in the conterminous United States. Chapter E presents an analysis of factors affecting future water availability under changing climate conditions. The National Integrated Water Availability Assessment culminates with Chapter F, which is an integrated assessment of water availability that considers the amount and quality of water coupled with the suitability of that water for specific uses. Together, these six chapters constitute the National Integrated Water Availability Assessment for water years 2010–20.

Professional Paper↗

USGS2025

Analyzing multi-year nitrate concentration evolution in Alabama aquatic systems using a machine learning model

Rising nitrate contamination in water systems poses significant risks to public health and ecosystem stability, necessitating advanced modeling to understand nitrate dynamics more accurately. This study applies the long short-term memory (LSTM) modeling to investigate the hydrologic and environmental factors influencing nitrate concentration dynamics in rivers and aquifers across the state of Alabama in the southeast of the United States. By integrating dynamic data such as streamflow and groundwater levels with static catchment attributes, the machine learning model identifies primary drivers of nitrate fluctuations, offering detailed insights into the complex interactions affecting multi-year nitrate concentrations in natural aquatic systems. In addition, a novel LSTM-based approach utilizes synthetic surface water nitrate data to predict groundwater nitrate levels, helping to address monitoring gaps in aquifers connected to these rivers. This method reveals potential correlations between surface water and groundwater nitrate dynamics, which is particularly meaningful given the lack of water quality observations in many aquifers. Field applications further show that, while the LSTM model effectively captures seasonal trends, limitations in representing extreme nitrate events suggest areas for further refinement. These findings contribute to data-driven water quality management, enhancing understanding of nitrate behavior in interconnected water systems.

Alabama↗

USGS2025

Geochemistry and Soils of the Big Smoky Valley Fens, Nevada

Fens are groundwater-fed wetlands that can provide habitat for plants and animals. Due to anthropogenic activities and climate change, many fens around the world are at risk. This paper presents the results of a study of the hydrology and geochemistry of fens in Big Smoky Valley, central Nevada to support the Bureau of Land Management’s activities in the area. A water sample from the largest fen in the study area was analyzed for its water chemistry and compared to a nearby alluvial aquifer and hot spring. The high SiO 2 concentration of the fen sample implies that the fen water may originate from geothermal water. A soil core was taken to analyze radiocarbon age and soil type. A majority of the core was composed of silt and clay interlayered with water-filled voids. Changes in the character of the clay with depth suggest that there may have been changes in the depositional environment over time. Radiocarbon dating of Ruppia seeds showed longevity of the fen, with the minimum 14 C age of the core as 4,375±40 years. This paper provides reconnaissance-level information on the Big Smoky Valley fens, but further information would be needed to better understand the source of water to the fens or how the fen environment has changed over time with climate.

Nevada↗

USGS1998

Assessment of the hydraulic connection between ground water and the Peace River, west-central Florida

The hydraulic connection between the Peace River and the underlying aquifers along the length of the Peace River from Bartow to Arcadia was assessed to evaluate flow exchanges between these hydrologic systems. Methods included an evaluation of hydrologic and geologic records and seismic-reflection profiles, seepage investigations, and thermal infrared imagery interpretation. Along the upper Peace River, a progressive long-term decline in streamflow has occurred since 1931 due to a lowering of the potentiometric surface of the Upper Floridan aquifer by as much as 60 feet because of intensive ground-water withdrawals for phosphate mining and agriculture. Another effect from lowering the potentiometric surface has been the cessation of flow at several springs located near and within the Peace River channel, including Kissengen Spring, that once averaged a flow of about 19 million gallons a day. The lowering of ground-water head resulted in flow reversals at locations where streamflow enters sinkholes along the streambed and floodplain. Hydrogeologic conditions along the Peace River vary from Bartow to Arcadia. Three distinctive hydrogeologic areas along the Peace River were delineated: (1) the upper Peace River near Bartow, where ground-water recharge occurs; (2) the middle Peace River near Bowling Green, where reversals of hydraulic gradients occur; and (3) the lower Peace River near Arcadia, where ground-water discharge occurs. Seismic-reflection data were used to identify geologic features that could serve as potential conduits for surface-water and ground-water exchange. Depending on the hydrologic regime, this exchange could be recharge of surface water into the aquifer system or discharge of ground water into the stream channel. Geologic features that would provide pathways for water movement were identified in the seismic record; they varied from buried irregular surfaces to large-scale subsidence flexures and vertical fractures or enlarged solution conduits. Generally, the upper Peace River is characterized by a shallow, buried irregular top of rock, numerous observed sinkholes, and subsidence depressions. The downward head gradient provides potential for the Peace River to lose water to the ground-water system. Along the middle Peace River area, head gradients alternate between downward and upward, creating both recharging and discharging ground-water conditions. Seismic records show that buried, laterally continuous reflectors in the lower Peace River pinch out in the middle Peace River streambed. Small springs have been observed along the streambed where these units pinch out. This area corresponds to the region where highest ground-water seepage volumes were measured during this study. Further south, along the lower Peace River, upward head gradients provide conditions for ground-water discharge into the Peace River. Generally, confinement between the surficial aquifer and the confined ground-water systems in this area is better than to the north. However, localized avenues for surface-water and ground-water interactions may exist along discontinuities observed in seismic reflectors associated with large-scale flexures or subsidence features. Ground-water seepage gains or losses along the Peace River were quantified by making three seepage runs during periods of: (1) low base flow, (2) high base flow, and (3) high flow. Low and high base-flow seepage runs were performed along a 74-mile length of the Peace River, between Bartow and Nocatee. Maximum losses of 17.3 cubic feet per second (11.2 million gallons per day) were measured along a 3.2-mile reach of the upper Peace River. The high-flow seepage run was conducted to quantify losses in the Peace River channel and floodplain between Bartow and Fort Meade. Seepage losses calculated during high-flow along a 7.2-mile reach of the Peace River, from the Clear Springs Mine bridge to the Mobil Mine bridge, were approximately 10 percent of the river flow, or 118 cubic feet per second. Calculated seepages along the Peace River in Hardee and De Soto Counties were inconclusive, because most seepages were within the range of discharge measurement error. Two continuous aerial thermal infrared imagery surveys were conducted to locate sites of ground-water discharge along the Peace River. Although temperature and hydrologic conditions were ideal to observe spring flow using thermal infrared imaging techniques, no sources of ground-water discharge were identified using this method. Diffuse ground-water seepage may, however, provide significant ground-water discharge.

Florida↗

USGS2025

Exploring the science and data foundation for Federal public lands decisions

Public lands provide diverse resources, values, and services worldwide. Laws and policies typically require consideration of science in public lands decisions, and resource managers are committed to science-informed decision-making. However, it can be challenging for managers to use, and document the use of, science and data in their decisions. To better understand science and data use in Federal public lands decisions in the United States, we assessed the number, type, and age of documents cited in 70 Environmental Assessments (EAs) completed by the Bureau of Land Management (BLM) in Colorado from 2015–2019. We focused on the BLM, as they manage the largest area of public lands in the United States. We selected Colorado as our study area, as actions proposed on BLM lands in Colorado are representative of those across the nation. Fifty percent of citations were categorized as science and 23% as data. EAs contained an average of 17 citations (range 0–111), with documents analyzing effects of oil and gas development and recreation actions including the highest and lowest mean number of citations (41 and 6, respectively). Of individual resource analysis sections within EAs, 24% contained ≥1 science citation and 21% contained ≥1 data citation. Journal articles were the most cited type of document (26% of citations) followed by non-BLM inventories (13%). Forty-seven percent of citations were relatively recent (2010 or later); the oldest citation was from 1927. Commonly analyzed resources with the highest mean number of citations were socioeconomics, mineral resources, and noise. Fourteen of 33 commonly analyzed resources included <1 citation on average. Actions and resources with no or few citations represent opportunities for strengthening the transparent use of science and data in public lands decision-making.

Colorado↗

USGS2026

Design and function of the Autonomous Benthic Imaging and Surveying System (ABISS) for remote sensing of lake and seabed environments

Lake and seabed environments are home to fisheries and other biota that are important to ecosystems and economies, yet these environments and the species that use them are difficult to accurately assess and monitor. Traditional benthic survey techniques, like bottom trawling used by the U.S. Geological Survey, are limited by substrate constraints, poor spatial resolution and precision, and operational depth limits, hindering accurate assessment of benthic species and habitats. In response to these limitations, the U.S. Geological Survey developed the Autonomous Benthic Imaging and Surveying System, a camera system integrated into underwater vehicles, to capture high-resolution images of the lakebed. The system uses color and stereo cameras to collect imagery, which can be analyzed using computational methods to detect organisms and (or) characterize habitat features, such as geologic substrate types. The system has been integrated into autonomous underwater vehicles and into an underwater housing used by self-contained underwater breathing apparatus (SCUBA) divers. Although the engineering of the system was motivated by the need for data collection in the Great Lakes, it has potential to collect high quality data in any aqueous setting with sufficient water clarity and safe operating conditions. The Autonomous Benthic Imaging and Surveying System can operate across diverse depths and light conditions to map and quantify ecological patterns that were difficult or impossible to assess using traditional methods. The Autonomous Benthic Imaging and Surveying System offers the potential for accurate and precise monitoring and assessment of native benthic biota, invasive species, and habitat, potentially providing natural resource managers with improved information to support decision making about benthic resource management.

Great Lakes↗

USGS2026

A practical decision tool for marine bird mortality assessments

Given the rise in anthropogenic, environmental, and disease events contributing to marine bird mortality, there is a critical need to improve the rigor of mortality assessments. Deficits in data collection and mortality estimation can hinder a manager’s ability to document the scale of events and assess population level impacts. Therefore, to inform decisions required during activities, such as conservation status assessments or harvest management, organizations may choose to incorporate mortality assessments into response plans. Resources, capacity, and assets to assess mortality vary across jurisdictions (federal, state, Indigenous, local, etc.), and clear guidance to support mortality assessments is often unavailable or not clearly addressed. Here, we present a decision support tool to help managers identify and evaluate survey options to assess bird mortality in a diverse array of scenarios. The objective of the decision tool is to improve data collection and availability, which will increase the ability to estimate mortality robustly, given situation-specific attributes and constraints. This decision tool is designed to guide the response when a mortality event is initially encountered and offers suggestions for assessment and reporting procedures in the absence of other guidance or to complement existing protocols. The decision tool is also meant to inform decision making for response determination and resource allocation. The tool facilitates examination of options for further assessment and monitoring, which users determine by examining questions pertaining to species prioritization, determination of mortality minimum spatial extent, and the potential magnitude of impacts on affected species. Finally, identification of appropriate survey methods that address imperfect detection when a complete census is not possible are determined by exploring location, spatial and temporal extent, and the type of species affected. Ultimately, this decision tool aims to facilitate and improve the standardization of mortality assessments, equipping managers with a practical resource to navigate the decision-making process for marine bird mortality estimation.

Ornithological Applications↗

USGS2025

Using public participatory geographic information systems (PPGIS) to explore uses and values for Mojave Trails National Monument, California

Many people ascribe a variety of values to public lands and waters, but some values are more difficult to assess and quantify than others. Public participatory geographic information systems (PPGIS) are tools that have been used to help quantify and map the public’s diverse values for a landscape. This work describes the first known Office of Management and Budget–approved use of PPGIS by a Department of the Interior bureau. The U.S. Geological Survey developed an internet-based application to aid in gathering PPGIS data, called Values Mapping for Planning in Regional Ecosystems (VaMPIRE). Further, this work describes the first pilot of the VaMPIRE application in coordination with the Bureau of Land Management to collect spatial data and other survey data regarding the public’s uses of and values for locations within Mojave Trails National Monument. We emailed the link to the VaMPIRE application to an interested party email list in 2024 with 207 valid emails and received 74 responses; we also received 47 responses from members of an off-roading social media group. Of the list of 16 value options, recreation was the most popular value for the monument, followed by wilderness and inspirational. Over 1,000 points were placed throughout the monument, indicating locations people use or value, with the locations spread throughout the entire monument. Additionally, most survey respondents stated their ability to receive benefits in locations they mapped would not change in response to a hypothetical scenario related to recreational facility development. This report describes exploratory results from the first use of the VaMPIRE tool in Mojave Trails National Monument and includes reflections on how the process went and considerations for future use of VaMPIRE.

California↗

USGS1976

An environmental assessment of impacts of coal development on the water resources of the Yampa River basin, Colorado and Wyoming; Phase I work plan

Coal resources of the western United States are being developed at ever-increasing rates, causing concerns of the effects of mining and associated activities on the environment. The Yampa River basin in northwestern Colorado and south-central Wyoming is undergoing economic development of its coal, oil and gas, and uranium resources. The Yampa River basin assessment is a 21-year program of the U.S. Geological Survey. It is designed primarily to assess the availability and quality of the basin's water resources. The basin assessment also will evaluate potential environmental and selected socioeconomic impacts of energy-resource development plans proposed by mining and power companies. This report serves as a project work plan for the basin assessment's first-phase work activities. Economic development in the Yampa River basin will result in higher levels of residuals (noneconomic byproducts) being discharged into the environment. Residuals-management encompasses the technological and economic interrelationships that should be considered in order to comply with Federal and State environmental-control regulations regarding air quality, water quality, and disposal of solid wastes. The basin assessment, the first phase that is described by this report, is designed to provide Federal, State, and local decision-makers with the basic environmental information needed to formulate and to evaluate policies for the development of energy resources. The techniques applied and conclusions reached in the Yampa River basin assessment should aid similar studies of other energy-rich basins in the western United States.

Colorado, Wyoming↗

USGS2026

Global performance of remote sensing-based and reanalysis-driven models to estimate open water evaporation

Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, we analyze the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. We compare 3 remote sensing-based models, 1 reanalysis-driven model and 1 ensemble approach, using in situ observations from 27 lakes representing a diverse range of geographic and climatic regions. Our results demonstrate that, overall, the ensemble outperformed any individual model in terms of accuracy, with a RMSE and a bias of 1.3 and 0.3 mm day −1 , respectively. These findings highlight the benefits of using an ensemble approach to estimate open water evaporation with satellite-based models at the global scale, leveraging the unique strengths of each model. For the individual models, differences in the representation of heat storage changes and advection effects led to lower values of RMSE and bias, depending on the location and depth of the lakes. This study sets the path for future improvement of open water evaporation algorithms globally, while remote sensing techniques are proven satisfactory to monitoring of water loss in lakes globally, an essential step toward effective large-scale water resources management.

Water Resources Research↗

USGS2025

Simulation of the impacts of projected climate change on groundwater resources in the urban, semiarid Yucaipa Valley watershed, southern California using an integrated hydrologic model

Managing water resources in semiarid watersheds is challenging due to limited supply and uncertain future climate conditions. This paper examines the impact of future climate changes on an urban watershed in southern California using an integrated hydrologic model. GSFLOW modeling software is used to simulate the nonlinear relationships between climate trends and precipitation partitioning into ET, runoff, and subsurface storage. Four global circulation models (GCMs), each with two greenhouse-gas scenarios, RCP45 and RCP85 are used to project future climate conditions. GCMs include the CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 models. The model's simulated hydrologic conditions are compared with historical data to assess changes in water budgets and groundwater supply. Results indicate decreased groundwater storage in most scenarios due to increased natural evapotranspiration, vegetation consumptive use, and streamflow out of the watershed. Only scenarios with substantially increased future precipitation show increased groundwater storage. The study also highlights increased future aridity despite the rise in precipitation and large precipitation events forecast by GCMs, which increase the risk of urban floods and decrease stream leakage and water available to vegetation.

California↗

USGS2025

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California↗