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1,658 records · Page 14Linked to original sources
USGS2026

Assessing natural recharge in Indian Wells Valley, California: A Basin Characterization Model case study

The communities in Indian Wells Valley (IWV), in the northern Mojave Desert in California, rely on groundwater for domestic and agricultural use. Mountain front recharge from the surrounding Sierra Nevada is the main source of natural recharge to the valley. Increased urbanization, agricultural development, and groundwater pumping during recent decades put IWV in a state of critical overdraft. The U.S. Geological Survey Basin Characterization Model, version 8 (BCMv8) was used to evaluate historical and future climate and hydrologic conditions in IWV. The BCMv8 estimated natural recharge in IWV at 10.7 million cubic meters (Mm 3 ) per year for the period from 1981 to 2010. Future patterns of water balance variables using three future climate scenarios, hot-wet, hot-dry, and warm-moderately wet, were calculated for mid-century (2040–69) and end-of-century (2070–99) periods. Results for both wet models projected an increase in recharge in both periods, whereas the hot-dry model projected a decrease in recharge in both periods. All models reported a large increase in seasonal variability in recharge, indicating more future availability and frequent occurrences of drought years. All climate scenarios projected an increase in climatic water deficit in both periods. These increases in irrigation demand and variability of water supply highlight the importance of strategic management planning for the sustainability of water resources in IWV.

California↗
USGS2022

New Hampshire and Landsat

At its widest point, a mere 80 miles separate the eastern and western borders of New Hampshire. Its northern and southern borders are just 175 miles apart. Even so, few States can boast as much rugged natural beauty per mile as the Nation’s fifth smallest. Nestled within New Hampshire are 93 State parks teeming with moose, Ursus americanus (Pallas, 1780; black bears), coyotes, beavers, river otters, and foxes. The largest section of White Mountain National Forest cuts across north-central New Hampshire, drawing visitors to its lakes, streams, mountain peaks, and hardwood forests. New Hampshire also is home to Lake Winnipesaukee, the State’s largest lake, notable for its floating post offices, the annual “ice-out” contest that sees residents vying to guess the date its surface ice dissipates, and its supporting role in films such as “On Golden Pond” and “What About Bob?” However, the scenic forests of New Hampshire face challenges in the form of invasive species such as Lymantria dispar (Linnaeus, 1758; spongy moth), Adelges piceae (balsam woolly adelgid), and Agrilus planipennis (emerald ash borer). In recent years, New Hampshire’s lakes and streams have seen more cyanobacterial blooms as well. The U.S. Geological Survey Landsat Program offers a consistent, reliable, and historically unmatched source of Earth observations that can aid in the mapping, monitoring, and management of New Hampshire’s land and water resources. Here are a few ways Landsat data have been used in the Granite State.

New Hampshire↗
USGS2024

Potential climate and human water-use effects on water-quality trends in a semiarid, western U.S. watershed: Fountain Creek, Colorado, USA

Nutrients, total dissolved solids (TDS), and trace elements affect the suitability of water for human and natural needs. Here, trends in such water-quality constituents are analyzed for 1999–2022 for eight nested monitoring sites in the 24,000 km 2 Fountain Creek watershed in Colorado, USA, by using the weighted regressions on time, discharge, and season (WRTDS) methodology. Fountain Creek shares characteristics with other western U.S. watersheds: (1) an expanding but more water-efficient population, (2) a heavy reliance on imported water, (3) a semiarid climate trending towards warmer and drier conditions, and (4) shifts of water from agricultural to municipal uses. The WRTDS analysis found both upward and downward trends in the concentrations of nutrients that reflected possible shifts in effluent management, instream uptake, and water conservation by a watershed population that grew by about 40%. Selenium, other trace elements, and TDS can pose water-quality challenges downstream and their concentrations were found to have a downwards trend. Those trends could be driven by either a warming and drying of the local climate or decreased agricultural irrigation, as both would reduce recharge and subsequent mobilization from natural geologic sources via groundwater discharge. The patterns illustrate how changes in climate and water use may have affected water quality in Fountain Creek and demonstrate the patterns to look for in other western watersheds.

Colorado↗
USGS2025

Review and synthesis of the applications of machine learning to coalbed methane recovery

Over the last 30 years, a substantial literature has evolved on the use of machine learning (ML) to assess, predict, and improve the efficiency of coalbed methane (CBM) recovery. In the United States, the production of CBM declined as shale gas production matured, but CBM continues to be an important energy resource in other parts of the world. ML applications that have the potential to improve CBM reservoir management and production forecasts, and to increase exploration and operational efficiency, are still of significant interest. The integration of geostatistical techniques into the CBM ML applications has been largely absent but represents an opportunity for improvement. The literature demonstrates the widespread interest in, and applicability of, ML algorithms applied to CBM problems, and that they continue to result in improvements in predictive performance. However, (1) much of the research is more academic than operational, (2) many results are based on simulations, or small or proprietary datasets, (3) ML performance information can be inconsistent and sometimes entirely omitted, (4) most methodologies are unique to the specific CBM situation and likely not generalizable, (5) no standard data repositories are available to directly compare the performance of competing algorithms, and (6) the spatial component is often omitted. Finally, relatively new ML protocols involving causality analysis and reinforced learning, as well as hybrid workflows combining both supervised and unsupervised learning, are anticipated to dominate the future investigations. Integration of geostatistical and geospatial analysis with ML should enhance performance.

Book chapter↗
USGS2026

Transit time modeling framework for predicting freshwater salinization in urban catchments

The salinity of inland freshwaters is rising globally, particularly in urban watersheds where winter road deicers are widely applied. Attributing stream salinity dynamics to specific sources and transport pathways remains challenging due to episodic salt inputs, engineered drainage, and strong coupling between hydrology and subsurface storage. We present a modeling framework that couples climate-driven deicer build-up and wash-off with transient transit time distribution theory to simulate salt transport through drainage, interflow, and groundwater pathways. Applied to an urban watershed in Northern Virginia (USA), the model reproduces ten years of high-frequency stream salinity measurements across daily-to-decadal timescales. The calibrated model implies an average deicer application of 206 tonnes Cl −1 yr −1 , or roughly one 20 kg bag of rock salt person −1 yr −1 when normalized by the 20,000 people living in the watershed. In winter months, higher infiltration routes a large fraction of snowmelt and deicers into shallow subsurface pathways, enhancing vadose-zone and interflow contributions to stream salinity. Limited subsurface storage capacity and seasonal hydrologic turnover flush excess chloride from the vadose zone and groundwater during subsequent summer storms. By linking climate-driven deicer inputs, hydrologic connectivity, and stream water age, the framework provides a transferable basis for diagnosing and managing freshwater salinization in urban watersheds.

Virginia↗
USGS2026

Flood-inundation maps for Río Grande De Loíza in and near Caguas, Puerto Rico, 2026

Digital flood-inundation maps for a 2.7-mile reach of Río Grande De Loíza in Caguas, Puerto Rico, were created by the U.S. Geological Survey. Water-surface profiles were computed for the stream reach by using a one-dimensional, steady-state, step-backwater model. The model was calibrated to the current (2025) stage-streamflow relation (rating curve) for the U.S. Geological Survey streamgage 50055000, Río Grande De Loíza, Puerto Rico. The resulting hydraulic model was then used to compute 16 water-surface profiles for water levels (flood stages) ranging from 19.00 to 34.00 feet at the streamgage; these flood stages range from “moderate flood stage” to above “major flood stage” as defined by the National Weather Service. The 34.00-foot stage exceeds the historical maximum peak stage of 33.20 feet, recorded at the streamgage in 1945. The simulated water-surface profiles were used in combination with a digital elevation model derived from light detection and ranging (lidar) data to map the inundated areas associated with each flood profile. The flood-inundation maps and the supporting hydraulic model produced by this study can be used by emergency managers and local officials to assess flood-mitigation strategies and to define flood-hazard areas to help protect life and property, to coordinate flood-response activities such as evacuations and road closures, and to aid post-flood recovery efforts.

Puerto Rico↗
USGS2025

Wetter winters, drier summers: Quantifying the change in hydrological response around the Puget Sound area using the wflow_sbm hydrological model and CMIP6 projections

Climate change is expected to impact hydrological regimes worldwide, including the Pacific Northwest of the United States. This study investigates how climate change will affect river discharge in the Puget Sound region of the State of Washington, with a focus on King and Pierce Counties. We simulated river discharge under historical and future conditions using the physically based, spatially distributed wflow_sbm hydrological model, which was calibrated and validated against U.S. Geological Survey discharge records. Future forcing was based on an ensemble of six high-resolution CMIP6 climate models, which were bias corrected using empirical quantile mapping. The results indicate a decrease in summer discharges (5–10%) and an increase in winter discharges (5–10%) across the study region. The high discharges (90th percentile) are projected to increase in winter, and the low discharges are projected to decrease in summer, due to shifts in precipitation regimes, snowpack hydrology, and evapotranspiration. However, variability between individual CMIP6 models often exceeds the magnitude of ensemble mean changes, underscoring substantial uncertainty in climate projections and the importance of including multiple climate models in climate change analysis. Furthermore, model consensus increased with elevation, which could be the result of the higher elevation areas being driven by less diverse hydrological processes. These findings highlight potential challenges for regional water management, ecosystem health, and flood risk mitigation in the Puget Sound region under future climate conditions.

EarthArXiv↗
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↗
USGS2024

Utilization of stochastic ground motion simulations for scenario-based performance assessment of geo-structures

Probabilistic seismic performance assessments of engineered structures can be highly sensitive to the seismic input excitation and its variability. In the present study, the scenario-based performance assessment recommended by Federal Emergency Management Agency (FEMA) P-58 guidelines is adopted to estimate seismic fragility of concrete dams for various seismic hazard scenarios. Due to the scarcity of recorded ground motions and thereby their poor representation of uncertainties, stochastic ground motion simulation methods are utilized to obtain the required input excitations. Moreover, to understand the uncertainty in ground motion simulation models, two broadband stochastic simulation models are used to generate input excitations representing six seismic hazard scenarios defined by earthquake magnitude, source-to-site distance, and soil conditions. Optimal intensity measure parameters for each scenario are identified using a systematic procedure that considers criteria such as efficiency, practicality, proficiency, sufficiency, and hazard compatibility. Fragility curves and surfaces are derived using the cloud analysis technique, taking into account various damage measures and limit state functions. The study finds that the derived fragility curves are particularly sensitive to the selection of earthquake scenarios, the choice of records, and the methods used to calculate fragility curves, with less sensitivity observed to different engineering demand parameters. Given this sensitivity, particularly to ground motion selection, the study highlights the necessity of incorporating both model-to-model variability (epistemic uncertainty) and record-to-record variability (aleatory uncertainty), alongside the established material and modeling uncertainties, in the probabilistic seismic assessment.

Reliability Engineering and System Safety (RESS)↗
USGS2025

Flood-inundation maps for Río de la Plata in and near Comerío, Puerto Rico, 2025

Digital flood-inundation maps for a 3.1-mile reach of Río de la Plata in and near Comerío, Puerto Rico, were created by the U.S. Geological Survey (USGS). Water-surface profiles were computed for the stream reach by using a one-dimensional steady-state step-backwater model. The model was calibrated to the current (2025) stage-streamflow relation (rating curve 11.0) for the USGS streamgage 50043800, Río de la Plata at Comerío, Puerto Rico. The resulting hydraulic model was then used to compute 16 water-surface profiles for water levels (flood stages) ranging from 10.00 to 40.00 feet at the streamgage and ranging from “action stage” to above “major flood stage” as reported by the National Weather Service. The 40.00-foot stage was selected because it exceeds the peak stage of 34.86 ft recorded during Hurricane Maria at the USGS streamgage 50043800, Río de Plata at Comerío, Puerto Rico. The simulated water-surface profiles were then used in combination with a digital elevation model derived from light detection and ranging data to map the inundated areas associated with each flood profile. The flood-inundation maps and the supporting hydraulic model produced by this study can be used by emergency managers and local officials to assess flood mitigation strategies and to define flood hazard areas to help protect life and property, to coordinate flood response activities such as evacuations and road closures, and to aid post-flood recovery efforts.

Comerio↗
USGS2025

Uncertainty reduction for subaerial landslide-tsunami hazards

Subaerial rock slopes may generate a tsunami by rapidly moving into the water. Large uncertainty in landslide characteristics propagates into large uncertainty in tsunami hazard, making hazard assessment more difficult for land and emergency managers. Once a potentially tsunamigenic landslide is identified, it may not be clear which landslide characteristics contribute most significantly to uncertainty in the tsunami hazard. Our aim is to document the relative worth of different landslide characteristics (e.g., size, material properties) for reducing uncertainty in landslide-tsunami hazard assessments. Isolating the relative importance of specific landslide characteristics may inform prioritization of data collection and improve efficiency in understanding hazard. To accomplish this, we generated a set of 288 landslide-tsunami simulations in which we systematically varied the size and material properties of possible failure extents at the Barry Arm landslide complex in northwestern Prince William Sound, Alaska, USA. We find that for landslides smaller than the receiving waterbody, the landslide volume has the strongest effect on resulting wave characteristics and thus the highest leverage on reducing uncertainty in tsunami hazard. In contrast, for landslides substantially larger than the waterbody, the duration of rapid movement of the landslide has the highest leverage. Based on our results, we propose a classification scheme for subaerial landslides based on the relative size of the landslide and waterbody. Additionally, our results support the generation of a tsunami height transfer function between existing tide gages and a nearby coastal city. These results have direct implications for the practice of operational early warning.

Alaska↗
USGS2026

Software to support remote sensing of river discharge based on critical flow theory

Water resource management requires accurate observations of streamflow but standard field methods for measuring river discharge ( Q ) are costly and can be hazardous for equipment and personnel. Remote sensing has become a viable alternative, but many image-based techniques require field data for calibration and depth and velocity can seldom be mapped with a single sensor. A new approach based on critical flow theory, in contrast, allows both of these attributes to be inferred from readily available image data. This technique only pertains to sites with standing waves, called undular hydraulic jumps (UHJs), but a recent investigation demonstrated its potential to provide accurate discharge estimates. This paper introduces software designed to facilitate Inferring Q from UHJs Identified in River Images (InQUIRI). The package includes modules for retrieving data from image servers, making the measurements of wavelength and width required to calculate discharge, inferring a representative wavelength from a profile digitized along a wave train, combining multiple estimates to obtain an ensemble median discharge, and assessing accuracy via comparison to gage records from the U.S. Geological Survey. By making these steps easier to implement, InQUIRI enables users to apply the workflow to a variety of UHJ-containing images. Accumulating more case studies, some successful and others less so, would help constrain the range of applicability of the critical flow approach and foster development of refined guidelines for selecting and measuring waves. The software described herein could play an important role in promoting informed use of this new technique for non-contact streamflow measurement.

Arizona, Colorado, New Mexico, Utah↗
USGS1998

Continuous hydrologic simulation of runoff for the Middle Fork and South Fork of the Beargrass Creek basin in Jefferson County, Kentucky

The Hydrological Simulation Pro-gram-FORTRAN (HSPF) was applied to an urban drainage basin in Jefferson County, Ky to integrate the large amounts of information being collected on water quantity and quality into an analytical framework that could be used as a management and planning tool. Hydrologic response units were developed using geographic data and a K-means analysis to characterize important hydrologic and physical factors in the basin. The Hydrological Simulation Program FORTRAN Expert System (HSPEXP) was used to calibrate the model parameters for the Middle Fork Beargrass Creek Basin for 3 years (June 1, 1991, to May 31, 1994) of 5-minute streamflow and precipitation time series, and 3 years of hourly pan-evaporation time series. The calibrated model parameters were applied to the South Fork Beargrass Creek Basin for confirmation. The model confirmation results indicated that the model simulated the system within acceptable tolerances. The coefficient of determination and coefficient of model-fit efficiency between simulated and observed daily flows were 0.91 and 0.82, respectively, for model calibration and 0.88 and 0.77, respectively, for model confirmation. The model is most sensitive to estimates of the area of effective impervious land in the basin; the spatial distribution of rain-fall; and the lower-zone evapotranspiration, lower-zone nominal storage, and infiltration-capacity parameters during recession and low-flow periods. The error contribution from these sources varies with season and antecedent conditions.

Kentucky↗
USGS2024

Using surficial geologic maps, vegetation, and monitoring to address erosion impacts from grazing in Channel Islands National Park, California

Employing a map-unit classification scheme based on geomorphic process and age, the U.S. Geological Survey (USGS) mapped Quaternary surficial deposits of the five islands comprising Channel Islands National Park (CHIS), California, as no such maps previously existed. Mapping was motivated through an agreement with the National Park Service (NPS) to aid natural resource assessments, including post-grazing disturbance recovery and identification of mass wasting and tectonic hazards. The resulting detailed (1:12,000 scale) maps portray areas of upland erosional transport processes and alluvial, fluvial, eolian, beach, marine terrace, mass wasting, and mixed depositional processes at a scale commensurate with the process signal on the landscape. Detailed, GPS-located observations of sedimentology, pedogenic development, landscape position, and geomorphology constrain map unit identification. In addition, map-unit boundary delineation was determined in a GIS using a variety of high-resolution (sub-meter) aerial imagery and lidar-based DEMs complemented by derivative raster products. The GIS geodatabase schema used is GeMS compliant. Resolvable map-unit widths are as small as 10-15 meter. Locational accuracy of unit boundaries is estimated to be as low as 10 m or better. Detailed mapping is at a scale allowing determination of geomorphic transport processes operating on the landscape and conveys geologic information to land managers at a resolution commensurate with park resources. Map unit ages are constrained by relative soil chronostratigraphy, vertebrate and invertebrate fossils, and materials collected for dating control using radiogenic, luminescence, and cosmogenic radionuclide techniques. Associated topical studies examined connections between geology, surface water, and vegetation distribution and restoration.

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↗
USGS2025

How do hydrological variability and human activities control the spatiotemporal changes of riverine nitrogen export in the Upper Mississippi River Basin?

Excessive nitrogen export from agricultural watersheds remains a critical water quality challenge, with the Upper Mississippi River Basin (UMRB) significantly contributing to downstream eutrophication and hypoxia in the Gulf. This study investigates the spatiotemporal dynamics of riverine nitrate plus nitrite (NO 3 – + NO 2 – -N) export across the UMRB at high spatial resolution (12-digit Hydrologic Unit Codes or HUC12 subwatershed scale) during 2001–2020 and quantifies the effects of anthropogenic activities and hydrological variability on riverine NO 3 – + NO 2 – -N export changes in the region between 2001–2005 and 2016–2020. Our results revealed hotspots of substantial increases in NO 3 – + NO 2 – -N yields across the UMRB, with distinct regional patterns in driving factors. Over the entire UMRB, NO 3 – + NO 2 – -N yields increased by 9.7 kg/ha/yr on average from 2001–2005 to 2016–2020, with anthropogenic activities contributing 4.8 kg/ha/yr and hydrological variability contributing 4.9 kg/ha/yr. The northern and western UMRB had combined influences from both anthropogenic activities and hydrological variability, while the east-central regions had predominantly hydrologically driven changes. Agricultural sources, including fertilizer, manure, and biological nitrogen fixation, collectively contributed over 80% of NO 3 – + NO 2 – -N loading throughout the basin. This framework for disentangling human and hydrological impacts provides critical insights for developing effective and targeted watershed management strategies to reduce nutrient losses and improve water quality.

Upper Mississippi River Basin↗
USGS2025

Light absorbing particles deposited to snow cover across the Upper Colorado River Basin, Colorado Rocky Mountains, 2013-16: Interannual variations from multiple natural and anthropogenic sources

Atmospheric particulate matter (PM) as light-absorbing particles (LAPs) deposited to snow cover can result in early onset and rapid snow melting, challenging management of downstream water resources. We identified LAPs in 38 snow samples (water years 2013–2016) from the mountainous Upper Colorado River basin by comparing among laboratory-measured spectral reflectance, chemical, physical, and magnetic properties. Dust sample reflectance, averaged over the wavelength range of 0.35–2.50 μm, varied by a factor of 1.9 (range, 0.2300–0.4444) and was suppressed mainly by three components: (a) carbonaceous matter measured as total organic carbon (1.6–22.5 wt. %) including inferred black carbon, natural organic matter, and carbon-based synthetic, black road-tire-wear particles, (b) dark rock and mineral particles, indicated by amounts of magnetite (0.11–0.37 wt. %) as their proxy, and (c) ferric oxide minerals identified by reflectance spectroscopy and magnetic properties. Fundamental compositional differences were associated with different iron oxide groups defined by dominant hematite, goethite, or magnetite. These differences in iron oxide mineralogy are attributed to temporally varying source-area contributions implying strong interannual changes in regional source behavior, dust-storm frequency, and (or) transport tracks. Observations of dust-storm activity in the western U.S. and particle-size averages for all samples (median, 25 μm) indicated that regional dust from deserts dominated mineral-dust masses. Fugitive contaminants, nevertheless, contributed important amounts of LAPs from many types of anthropogenic sources.

Colorado↗
USGS2024

ShakeAlert® and schools: Incorporating earthquake early warning in school districts in Alaska, California, Oregon, and Washington

The U.S. Geological Survey-managed ShakeAlert® earthquake early warning system is the first public alerting system in the United States to provide rapid mass notification when an earthquake is detected. Although public alert delivery via mobile phones began in California in 2019 followed by Oregon and Washington in 2021, little is known about what might drive widespread implementation in at-risk institutional settings such as schools. For example, there has been limited research on how to best integrate earthquake early warning into existing emergency plans, alert systems, and drills to keep school children and personnel safe in an earthquake. To address this gap, in the spring of 2022, every school district superintendent in Alaska, California, Oregon, and Washington was sent a 15-min online survey. The survey assessed superintendent knowledge of ShakeAlert, preferences for alert messaging, and perceived opportunities and barriers to incorporating the system in schools. The results showed that superintendents had low awareness of ShakeAlert but held positive perceptions of the system's potential to enable life-saving protective actions. A major barrier to adoption included the perceived financial cost of implementing and maintaining the system. There were some statistically significant differences in state responses, and future research could investigate the specific needs of each state based on school district size and composition, hazard exposure, and earthquake experience. Together these findings can help inform targeted strategies to increase ShakeAlert adoption in schools and ultimately improve the safety of school children and staff during earthquakes.

Alaska, California, Oregon, Washington↗