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At least 649 records · Page 36Linked to original sources
USGS2014

Historic and contemporary mercury exposure and potential risk to yellow-billed loons ( Gavia adamsii ) breeding in Alaska and Canada

The Yellow-billed Loon (Gavia adamsii) is one of the rarest breeding birds in North America. Because of the small population size and patchy distribution, any stressor to its population is of concern. To determine risks posed by environmental mercury (Hg) loads, we captured 115 Yellow-billed Loons between 2002 and 2012 in the North American Arctic and sampled their blood and/or feather tissues and collected nine eggs. Museum samples from Yellow-billed Loons also were analyzed to examine potential changes in Hg exposure over time. An extensive database of published Hg concentrations and associated adverse effects in Common Loons (G. immer) is highly informative and representative for Yellow-billed Loons. Blood Hg concentrations reflect dietary uptake of methylmercury (MeHg) from breeding areas and are generally considered near background levels if less than 1.0 µg/g wet weight (ww). Feather (grown at wintering sites) and egg Hg concentrations can represent a mix of breeding and wintering dietary uptake of MeHg. Based on Common Loon studies, significant risk of reduced reproductive success generally occurs when adult Hg concentrations exceed 2.0 µg/g ww in blood, 20.0 µg/g fresh weight (fw) in flight feathers and 1.0 µg/g ww in eggs. Contemporary mercury concentrations for 176 total samples (across all study sites for 115 Yellow-billed Loons) ranged from 0.08 to 1.45 µg/g ww in blood, 3.0 to 24.9 µg/g fw in feathers and 0.21 to 1.23 µg/g ww in eggs. Mercury concentrations in blood, feather and egg tissues indicate that some individual Yellow-billed Loons in breeding populations across North America are at risk of lowered productivity resulting from Hg exposure. Most Yellow-billed Loons breeding in Alaska overwinter in marine waters of eastern Asia. Although blood Hg concentrations from most breeding loons in Alaska are within background levels, some individuals exhibit elevated feather and egg Hg concentrations, which likely indicate the uptake of MeHg originating from eastern Asia. Feather Hg concentrations tended to be highest in individuals overwintering farthest west (closer to Asia). A retrospective analysis of museum specimens (n = 25) found a two-fold increase in Yellow-billed Loon feather Hg concentrations from the pre-1920s (as early as 1845) to the present. The projected increase in Hg deposition (approximately four-fold by 2050) along with the uncertainty of Hg being released through the thawing of permafrost and Arctic sea ice suggest that Hg body burdens in Yellow-billed Loons may increase. These findings indicate that Hg is a current and potentially increasing environmental stressor for the Yellow-billed Loon and possibly other Nearctic-Palearctic migrant birds.

Alaska↗
USGS2025

Evaluating drought risk of the Red River of the North Basin using historical and stochastic streamflow upstream from Emerson, Manitoba

Drought and its effect on streamflow are important to understand because of the potential to adversely affect water supply, agricultural production, and ecological conditions. The Red River of the North Basin in north-central United States and central Canada is susceptible to dry conditions. During an extended drought, streamflow conditions in the Red River of the North may become inadequate to support existing water supply needs in the basin for agriculture, industry, human use, and aquatic life. To understand potential future low-streamflow conditions in the Red River of the North Basin, the U.S. Geological Survey, in cooperation with the International Joint Commission, North Dakota Department of Water Resources, Red River Joint Water Resource District, and Red River Watershed Management Board, developed a water-balance model of the Red River of the North Basin upstream from Emerson, Manitoba, Canada, and coupled the model with stochastic weather inputs to simulate possible future low-streamflow conditions. Historical changes in low-streamflow conditions were characterized across the Red River of the North Basin using multiple change-point analysis for 12 streamgages. Across these stations, significant change-point years in 1943 and 1994 marked increases in the magnitude of low-streamflow conditions. During 1920–2015, conversion of primary land (not affected by human use) to agricultural and secondary land was followed by a conversion from smalls grains to corn and soybeans as the dominant crop type. From land-use analysis, 1940–2000 was determined to have relatively stable land use and therefore was used as the calibration period for the water-balance model. A deterministic water-balance model was developed for the Red River of the North Basin upstream from Emerson, Manitoba. The water-balance model was calibrated with data from 37 U.S. Geological Survey streamgages for 1940–2000 and verified using data for 2001–15. The calibrated water-balance model simulated streamflow distributions that mirrored the seasonal patterns of the observed mean monthly streamflow and the standard deviation of the monthly streamflow data, especially during the fall and winter months when streamflow was lowest. For the verification period, during the low-streamflow months of December through January, the difference between simulated and observed data was similar to the calibration comparison and successfully reproduced seasonal trends in the distribution of streamflow, even when using weather data that were outside the calibration period. To determine the future risk of low-streamflow conditions in the Red River of the North Basin, a block-bootstrap method was used to generate multiple possible future climates. These stochastically generated weather time series were then input to a water-balance model to simulate a distribution of possible streamflows. Three sets of experiments were performed, with each experiment containing a set of scenarios. The first set of experiments from the stochastic streamflow model were designed to investigate how changes in reservoir management would affect the distribution of low streamflow. Relative to scenario 1 (present-day [2023] reservoir operation), scenario 2 (no reservoir operation) shifted the low-streamflow frequency curves downward, reducing the annual minimum monthly streamflow for the Emerson subbasin. Subbasins were defined by the contributing area upstream from a selected streamgage station. Relative to scenario 1, scenario 3 (regulated streamflow with an increased reservoir capacity of 10 percent) shifted the low-streamflow frequency curves upward for the Emerson subbasin. The magnitude of this upward shift, caused by increased reservoir capacity, was lower than the magnitude of the shift caused by the absence of the reservoirs, which indicates that the streamflow was most affected when the reservoirs were first constructed. The second set of experiments from the stochastic streamflow model included two scenarios that were performed to better understand how the Red River of the North Basin responds to long periods of low or high precipitation. The results indicate that the model consistently overestimated streamflow, but the relative change between a wet and dry climate state of simulated streamflow distribution reasonably matched the relative change of historical streamflow. Across the subbasins, the model was most accurate for low-streamflow conditions associated with nonexceedance probabilities between 20 and 40 percent. The third set of experiments from the stochastic streamflow model were done to investigate low-streamflow response across the basin to several drought events. Low-end streamflow was reduced when the basin was exposed to a drought, and the magnitude of the reduction increased with longer or more intense droughts. Compared to the low-intensity drought scenarios, the range of percent reductions (as indicated by the interquartile range) was larger for the high-intensity drought scenarios for all subbasins, and the subbasins of Grand Forks and Emerson had a smaller range of reductions compared to the other three subbasins. The larger drainage area—combined with the large contribution of the Red Lake River and several other Minnesota tributaries that generally experience wetter climate conditions—upstream from the Emerson and Grand Forks subbasins may contribute to the smaller range in reductions under the high intensity scenarios. Comparison of the percent reduction in low-end streamflow among subbasins also indicated that the effects of drought duration and intensity could be cumulative. Combining factors of time and intensity produced a larger reduction in streamflow than when each effect was isolated. The array of drought scenarios can be used to determine how a subbasin would respond to multiple possible future conditions. Based on climate predictions, the drought scenario that best matches a future anticipated drought scenario can be used to estimate a low streamflow response for a given subbasin.

Manitoba, Minnesota, North Dakota↗
USGS2008

The human footprint in the west: a large-scale analysis of anthropogenic impacts.

Anthropogenic features such as urbanization, roads, and power lines, are increasing in western United States landscapes in response to rapidly growing human populations. However, their spatial effects have not been evaluated. Our goal was to model the human footprint across the western United States. We first delineated the actual area occupied by anthropogenic features, the physical effect area. Next, we developed the human footprint model based on the ecological effect area, the zone influenced by features beyond their physical presence, by combining seven input models: three models quantified top-down anthropogenic influences of synanthropic predators (avian predators, domestic dog and cat presence risk), and four models quantified bottom-up anthropogenic influences on habitat (invasion of exotic plants, human-caused fires, energy extraction, and anthropogenic wildland fragmentation). Using independent bird population data, we found bird abundance of four synanthropic species to correlate positively with human footprint intensity and negatively for three of the six species influenced by habitat fragmentation. We then evaluated the extent of the human footprint in relation to terrestrial (ecoregions) and aquatic systems (major rivers and lakes), regional management and conservation status, physical environment, and temporal changes in human actions. The physical effect area of anthropogenic features covered 13% of the western United States with agricultural land (9.8%) being most dominant. High-intensity human footprint areas (class 8 – 10) overlapped highly productive low-elevation private landholdings and covered 7% of the western United States compared to 48% for low-intensity areas (class 1 – 3), which were confined to low-productivity high-elevation federal landholdings. Areas within 1 km of rivers were more affected by the human footprint compared to lakes. Percentage human population growth was higher in low-intensity human footprint areas. The disproportional regional effects of the human footprint on landscapes in the western United States create a challenge to management of ecosystems and wildlife populations. Using footprint models, managers can plan land use actions, develop restoration scenarios, and identify areas of high conservation value at local landscapes within a regional context. Moreover, human footprint models serve as a tool to stratify landscapes for studies investigating floral and faunal response to human disturbance intensity gradients.

Ecological Applications↗
USGS2019

Analysis of groundwater response to tidal fluctuations, Operable Unit 1, Naval Base Kitsap, Keyport, Washington

Chlorinated volatile organic compounds have affected groundwater beneath a former 9-acre landfill at Operable Unit 1 (OU 1) of Naval Base Kitsap (NBK) Keyport, in Keyport, Washington. The landfill was the primary disposal area for domestic and industrial waste generated by NBK Keyport from the 1930s through 1973. Naval Facilities Engineering Command Northwest, in conjunction with the Environmental Protection Agency, Washington State Department of Ecology, and the Suquamish Tribe, is charged with collecting necessary data to monitor the contamination left in place and to ensure that the site does not pose a risk to human health or the environment. To support these efforts, refined information was collected on how groundwater levels throughout OU 1 respond to tidal fluctuations at this nearshore site adjacent to Liberty Bay, an inlet of Puget Sound. The information was analyzed to determine the optimal times during the semidiurnal and the neap-spring tidal cycles to sample groundwater for contaminants associated with fresh groundwater originating from OU 1. The optimal times for sampling are presumed to be when fresh groundwater flowing seaward is least impeded by elevated tides, and those times are related to predicted tide levels by tidal lags, the durations between low tides, and corresponding low groundwater levels. Discrete groundwater-specific conductance data also were collected to determine if a seawater/freshwater interface was present at any of the monitoring wells, and to inform decisions on the depth at which groundwater should be sampled in existing wells. Groundwater and surface-water levels were monitored at 19 monitoring wells and five adjacent surface-water sites. Specific conductance was monitored in each surface-water site. All time-series data parameters were collected every 15 minutes during a 4-week duration to measure how nearshore groundwater responds to tidal forcing. Time-series data were collected from July 12, 2018, to August 8, 2018, a period that included neap and spring tides. Vertical water-quality profiles were measured once in the screened interval of nine selected monitoring wells. The profiles included measurements at the top, middle, and bottom of each saturated screen interval. Tidal lag times were determined relative to tidal levels in Liberty Bay (rather than in the more nearby Tide Flats) because the predicted tides for the Poulsbo, Washington Station (National Oceanic and Atmospheric Administration [NOAA] Station 9445719) that are used to schedule groundwater sampling represent open-water conditions in the area; a sill that separates Dogfish Bay from the Tide Flats clearly affects the timing and magnitude of low-low tides in the Tide Flats. Calculated tidal lag times were divided into three general groups: (1) wells where groundwater responded to tidal level changes immediately, (2) wells where groundwater responded to tidal level changes within about 2–5 hours, and (3) wells where groundwater had minimal response to tidal level changes. Groundwater levels in the middle group of wells primarily responded in concert with tidal level changes in the Tide Flats rather than tidal level changes in Liberty Bay. An intended sampling depth refinement based on an assessment of transient seawater intrusion was not completed because of a failure to collect specific-conductance time-series data in select wells. Instead, discrete specific-conductance data from this and prior studies were evaluated to determine that the midpoint of well screens in OU 1 wells can be assumed to be a reasonably representative of undiluted groundwater. When sampling during spring (rather than neap) tides (as has generally been the standard practice at OU 1), the optimal time to sample the monitoring wells influenced by tides would be to add the tidal lags presented in this report to the time of the predicted low-low tide for Liberty Bay as measured at NOAA Station 9445719 at Poulsbo, Washington. Sampling schedules for the six wells where groundwater levels were only minimally influenced by tide changes should not be constrained by tidal conditions.

Washington↗
USGS2024

Evaluation of anticoagulant rodenticide sensitivity by examining in vivo and in vitro responses in avian species, focusing on raptors

Anticoagulant rodenticides (ARs) are used to control pest rodent species but can result in secondary poisoning of non-target animals, especially raptors. In the present study, differences in AR sensitivity among avian species were evaluated by comparing in vivo warfarin pharmacokinetics and effects, measuring cytochrome P450s (CYPs) expression involved in AR metabolism, and conducting in vitro inhibition assays of the AR target enzyme Vitamin K 2,3-epoxide reductase (VKOR). Oral administration of warfarin at 4 mg/kg body weight did not prolong prothrombin time in chickens ( Gallus gallus ), rock pigeons ( Columba livia ), or Eastern buzzards ( Buteo japonicus ). Rock pigeons and buzzards exhibited shorter plasma half-life of warfarin compared to chickens. For the metabolite analysis, 4′-hydroxywarfarin was predominantly detected in all birds, while 10-hydroxywarfarin was only found in pigeons and raptors, indicating interspecific differences in AR metabolism among birds likely due to differential expression of CYP enzymes involved in the metabolism of ARs and variation of VKOR activities among these avian species. The present findings, and results of our earlier investigations, demonstrate pronounced differences in AR sensitivity and pharmacokinetics among bird species, and in particular raptors. While ecological risk assessment and mitigation efforts for ARs have been extensive, AR exposure and adverse effects in predatory and scavenging wildlife continues. Toxicokinetic and toxicodynamic data will assist in such risk assessments and mitigation efforts.

Environmental Pollution↗
USGS2024

Geothermal Play Fairway Analysis, Part 2: GIS methodology

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results.

Geothermics↗
USGS2017

Landscape context and the biophysical response of rivers to dam removal in the United States

Dams have been a fundamental part of the U.S. national agenda over the past two hundred years. Recently, however, dam removal has emerged as a strategy for addressing aging, obsolete infrastructure and more than 1,100 dams have been removed since the 1970s. However, only 130 of these removals had any ecological or geomorphic assessments, and fewer than half of those included before- and after-removal (BAR) studies. In addition, this growing, but limited collection of dam-removal studies is limited to distinct landscape settings. We conducted a meta-analysis to compare the landscape context of existing and removed dams and assessed the biophysical responses to dam removal for 63 BAR studies. The highest concentration of removed dams was in the Northeast and Upper Midwest, and most have been removed from 3 rd and 4 th order streams, in low-elevation (< 500 m) and low-slope (< 5%) watersheds that have small to moderate upstream watershed areas (10–1000 km 2 ) with a low risk of habitat degradation. Many of the BAR-studied removals also have these characteristics, suggesting that our understanding of responses to dam removals is based on a limited range of landscape settings, which limits predictive capacity in other environmental settings. Biophysical responses to dam removal varied by landscape cluster, indicating that landscape features are likely to affect biophysical responses to dam removal. However, biophysical data were not equally distributed across variables or clusters, making it difficult to determine which landscape features have the strongest effect on dam-removal response. To address the inconsistencies across dam-removal studies, we provide suggestions for prioritizing and standardizing data collection associated with dam removal activities.

PLoS ONE↗
USGS2019

Grounding simulation models with qualitative case studies: Toward a holistic framework to make climate science usable for US public land management

Policies directing agencies and public land managers to incorporate climate change into management face several barriers. These stem, in part, from a disconnect between the information that is produced and the information needs of local resource managers. A disproportionate focus on the natural and physical sciences in climate vulnerability and adaptation assessment obscure understandings of complex social systems and the interactions and feedbacks in social-ecological systems. We use a qualitative case study of bison management on Department of the Interior-managed and tribal lands to explore how a social-science driven Determinants and Analogue Vulnerability Assessment (DAVA) can inform ecological response models, specifically simulation models that account for multiple drivers of change. First, we illustrate how a DAVA approach can help to: 1) identify key processes, entities, and interactions across scales; 2) document local impacts, indicators, and monitoring efforts of drought and climate; and 3) identify major tradeoffs and uncertainties. We then demonstrate how qualitative narratives can inform simulation models by: 1) prioritizing model components included in modeling efforts; 2) framing joint management and climate scenarios; and 3) parameterizing and evaluating model performance. We do this by presenting a conceptual joint agent-based/state-and-transition simulation modeling framework. Simulation models can represent multiple interacting variables and can identify surprising, emergent outcomes that might not be evident from qualitative analysis alone, and we argue that qualitative case studies can ground simulation models in local contexts and help make them more structurally realistic and useful. Together, these can provide a step toward developing actionable climate change adaptation strategies.

Climate Risk Management↗
USGS2012

Modelling effects of chemical exposure on birds wintering in agricultural landscapes: The western burrowing owl ( Athene cunicularia hypugaea ) as a case study

We describe an ecotoxicological model that simulates the sublethal and lethal effects of chronic, low-level, chemical exposure on birds wintering in agricultural landscapes. Previous models estimating the impact on wildlife of chemicals used in agro-ecosystems typically have not included the variety of pathways, including both dermal and oral, by which individuals are exposed. The present model contains four submodels simulating (1) foraging behavior of individual birds, (2) chemical applications to crops, (3) transfers of chemicals among soil, insects, and small mammals, and (4) transfers of chemicals to birds via ingestion and dermal exposure. We demonstrate use of the model by simulating the impacts of a variety of commonly used herbicides, insecticides, growth regulators, and defoliants on western burrowing owls ( Athene cunicularia hypugaea ) that winter in agricultural landscapes in southern Texas, United States. The model generated reasonable movement patterns for each chemical through soil, water, insects, and rodents, as well as into the owl via consumption and dermal absorption. Sensitivity analysis suggested model predictions were sensitive to uncertainty associated with estimates of chemical half-lives in birds, soil, and prey, sensitive to parameters associated with estimating dermal exposure, and relatively insensitive to uncertainty associated with details of chemical application procedures (timing of application, amount of drift). Nonetheless, the general trends in chemical accumulations and the relative impacts of the various chemicals were robust to these parameter changes. Simulation results suggested that insecticides posed a greater potential risk to owls of both sublethal and lethal effects than do herbicides, defoliants, and growth regulators under crop scenarios typical of southern Texas, and that use of multiple indicators, or endpoints provided a more accurate assessment of risk due to agricultural chemical exposure. The model should prove useful in helping prioritize the chemicals and transfer pathways targeted in future studies and also, as these new data become available, in assessing the relative danger to other birds of exposure to different types of agricultural chemicals.

Texas↗
USGS2024

An open-source workflow for scaling burn severity metrics from drone to satellite to support post-fire watershed management

Wildfires are increasing in size and severity across much of the western United States, exposing vulnerable wildland-urban interfaces to post-fire hazards. The Mediterranean chaparral region of Northern California contains many high sloping watersheds prone to hazardous post-fire flood events and identifying watersheds at high risk of soil loss and debris flows is a priority for post-fire response and management. Uncrewed Aerial Systems (UAS; aka drones) offer post-fire management teams the ability to quickly mobilize and survey burned areas with very high-resolution imagery (∼1 cm), facilitating emergency management and post-fire hazard assessment. However, adoption of this technology by hazard response teams may be hindered by complicated workflows for UAS data acquisition, image processing and analysis. We present an open-source workflow using mature Geographic Information Systems (GIS) software and Python packages in a Jupyter Notebook environment that guides users through classification of true-color UAS imagery to generate high resolution burn severity maps which can then be scaled across larger watersheds using Sentinel-2 normalized burn ratio (NBR) images. Soil burn severity classifications using a weighted brightness (WB) image and Char Index (CI) generated from UAS imagery were validated with in-situ data and random stratified points, resulting in the CI having the highest overall accuracy of 87.5%. CI also displayed a marginally stronger relationship over the WB with the post-fire Sentinel-2 NBR, R 2 = 0.79 and R 2 = 0.78 respectively. Our methods offer the unique opportunity to standardize GIS workflows, promoting replication through transparency, while improving the user's understanding of scientific GIS functionality.

California↗
USGS1998

Simulating cholinesterase inhibition in birds caused by dietary insecticide exposure

We describe a stochastic simulation model that simulates avian foraging in an agricultural landscape to evaluate factors affecting dietary insecticide exposure and to predict post-exposure cholinesterase (ChE) inhibition. To evaluate the model, we simulated published field studies and found that model predictions of insecticide decay and ChE inhibition reasonably approximated most observed results. Sensitivity analysis suggested that foraging location usually influenced ChE inhibition more than diet preferences or daily intake rate. Although organophosphorus insecticides usually caused greater inhibition than carbamate insecticides, insecticide toxicity appeared only moderately important. When we simulated impact of heavy insecticide applications during breeding seasons of 15 wild bird species, mean maximum ChE inhibition in most species exceeded 20% at some point. At this level of inhibition, birds may experience nausea and/or may exhibit minor behavioral changes. Simulated risk peaked in April–May and August–September and was lowest in July. ChE inhibition increased with proportion of vegetation in the diet. This model, and ones like it, may help predict insecticide exposure of and sublethal ChE inhibition in grassland animals, thereby reducing dependence of ecological risk assessments on field studies alone.

Ecological Modelling↗
USGS2026

Potential flood events in the lower Missouri River basin over multiple centuries identified using tree-ring based multi-model streamflow reconstructions

The Missouri River basin (MRB), the largest river basin in the United States, presents major water management challenges due to its complex topology and extensive infrastructure designed to manage high annual flows. Severe hydroclimatic events, particularly floods in 1993, 2011, and 2019, have highlighted vulnerabilities, leading the U.S. Army Corps of Engineers to enhance flood risk assessments in 2023. This study focuses on the full MRB, using tree-ring based streamflow reconstructions to extend the Basin's historic streamflow perspective. We developed annual streamflow reconstructions for the Hermann, Missouri streamgage from water years 1360–1900 using K-nearest neighbor and principal component regression methods. These reconstructions incorporate 183 tree-ring chronologies (1360–2020) and modeled natural streamflow (1901–‍2020). Reconstructions were evaluated for consistency using statistical measures and wavelet analysis. Both methods produced similar results, confirming their reliability in reconstructing multi-century streamflows. This novel methodology, guided by wavelet analysis, was developed to identify potential flood events in the lower Missouri River basin (LMRB), resulting in the identification of 172 potential flood events from water years 1360–2020, with 126 events common to the two versions of the MRB reconstructions. The reconstructed streamflow records showed an increase in the number of events until the late-18th- or mid-19th-century. These findings provide insights into evolving flood characteristics in the LMRB. The novel methodology developed in this study can be used to identify potential flood events from tree-ring based annual streamflow reconstructions and generally be applicable to other river basins.

Colorado, Iowa, Kansas, Missouri, Nebraska, Wyomin↗
USGS2022

Determination of optimal set of spatio-temporal features for predicting burn probability in the state of California, USA

Wildfires play a critical role in determining ecosystem structure and function and pose serious risks to human life, property and ecosystem services. Burn probability (BP) models the likelihood that a location could burn. Simulation models are typically used to predict BP but are computationally intensive. Machine learning (ML) pipelines can predict BP and reduce computational intensity. In this work, we tested approaches to reduce the set of input features used in an ML model to estimate BP for the state of California, USA, without loss of predictive performance. We used Principal Component Analysis (PCA) to determine the optimal set of features to use in our ML pipeline. Then, we mapped BP and compared model performance when using the reduced set and when using the whole set of features. Models using optimized input achieved similar prediction performance while using less than 50% of the input features.

California↗
USGS2022

Areas contributing recharge to priority wells in valley-fill aquifers in the Neversink River and Rondout Creek drainage basins, New York

In southeastern New York, the villages of Ellenville, Wurtsboro, Woodridge, the hamlet of Mountain Dale, and surrounding communities in the Neversink River and Rondout Creek drainage basins rely on wells that pump groundwater from valley-fill glacial aquifers for public water supply. Glacial aquifers are vulnerable to contamination because they are highly permeable and have a shallow depth to water table. To protect the quality of these water resources, water managers need accurate information about the areas that contribute recharge to production wells that pump from these aquifers. The New York State Department of Environmental Conservation and the New York State Department of Health designated eight priority wells in this region for which water supply protection is of primary concern. The U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation and the New York State Department of Health, began an investigation in 2019 with the general objectives of (1) improving understanding of regional groundwater-flow system, (2) delineating areas contributing recharge to eight priority production wells, and (3) quantifying the uncertainty of these contributing areas in a probabilistic way that can be used to inform decision-making related to priority well source-water protection. To complete these objectives, a MODFLOW 6 groundwater model was created encompassing the eight priority wells and the surrounding flow system, which includes parts of the Neversink River and Rondout Creek Basins in Sullivan County and Ulster County, New York. The model was built using Python tools (such as flopy , modflow-setup , and sfrmaker ) that facilitate transparent and repeatable model development using existing datasets. The model parameters were estimated with a stepwise approach using an iterative ensemble smoother implementation of the Parameter ESTimation software PEST++ (version 5.0.0). We evaluated initial “best guess” parameter bounds with a prior Monte Carlo analysis. Results of the first prior Monte Carlo analysis were used to make informed adjustments to model parameter bounds (typically resulting in expanded bounds), and a second prior Monte Carlo analysis was run to identify improved ranges for model parameters during history matching. The history matching effort produced an ensemble of parameter values for the groundwater-flow model that spans the range of values within prior uncertainty bounds. The ensemble is informed by the historical observation data, within a reasonable range of uncertainty on those observations. This history-matched ensemble was used in a particle tracking Monte Carlo analysis to delineate the areas contributing recharge to priority wells. The groundwater-flow and particle tracking (MODPATH7) models were run once for each ensemble member. Deterministic contributing areas computed for each ensemble member were aggregated to produce maps showing the probability that a location contributes recharge to priority wells. Finally, the particle tracking Monte Carlo analysis was repeated for six pumping scenarios, representing a wide range of possible pumping levels, to incorporate uncertainty in future pumping rates related to population growth or other management decisions. Increasing pumping rates generally led to larger contributing recharge areas and larger areas of high probability that a location contributes recharge to priority wells. These maps show the overall uncertainty of the areas contributing recharge to priority wells in the study area and provide a tool for risk-based decision making for protection of well source water.

New York↗
USGS2024

Potential corrosivity of untreated groundwater in Louisiana

Corrosive groundwater can cause lead, copper, and other metals to leach from pipes and plumbing fixtures in water distribution systems. Metals, if ingested, could lead to serious health implications to the nearly 2.9 million people in Louisiana who obtain their drinking water from groundwater sources. Four indices—the Langelier Saturation Index (LSI), Ryznar Stability Index (RSI), Puckorius Scaling Index (PSI), and the Potential to Promote Galvanic Corrosion (PPGC)—in addition to an analysis which normalized the results from the existing indices, the Combined Index (CI), were used to assess the corrosivity of groundwater in Louisiana and identify areas within eight major aquifers and aquifer systems with moderate to high corrosivity potential. The purpose of this study is to provide State and local governments, public water system managers, and the nearly 500,000 private well owners in Louisiana with information needed to manage drinking-water supplies and mitigate potential health risks related to leaching of metals from water pipes and fixtures. The average scores of untreated groundwater samples from approximately 375 wells by index are as follows: LSI, −1.28; RSI, 9.78; PSI, 9.34; and CI, 4.14. The PPGC does not produce a numerical score, but the total percentage of class counts can be used to assign a classification; overall, samples in Louisiana were classified as significant concern. The percentages of groundwater samples from wells classified as potentially corrosive, by index, are as follows: LSI, 53 percent; RSI, 94 percent; PSI, 81 percent; PPGC, 98 percent; and CI, 81 percent. The percentages of samples classified as indeterminate, by index, are as follows: LSI, 46 percent; RSI, 5 percent; PSI, 12 percent; PPGC, 0 percent; and CI, 18 percent.

Louisiana↗
USGS1995

Effect of the Cedar River on the quality of the ground-water supply for Cedar Rapids, Iowa

The Surface Water Treatment Rule under the 1986 Amendment to the Safe Drinking Water Act requires that public-water supplies be evaluated for susceptibility to surface-water effects. The alluvial aquifer adjacent to the Cedar River is evaluated for biogenic material and monitored for selected water-quality properties and constituents to determine the effect of surface water on the water supply for the City of Cedar Rapids, Iowa. Results from monitoring of selected water-quality properties and constituents showed an inverse relation to river stage or discharge. Water-quality properties and constituents of the alluvial aquifer changed as water flowed from the river to the municipal well as a result of drawdown. The values of specific conductance, pH, temperature, and dissolved oxygen at observation well CRM-4 and municipal well Seminole 10 generally follow the trends of values for the Cedar River. Values at observation well CRM-3 and the municipal water-treatment plant showed very little correlation with values from the river. The traveltime of water through the aquifer could be an indication of the susceptibility of the alluvial aquifer to surface-water effects. Estimated traveltimes from the Cedar River to municipal well Seminole 10 ranged from 7 to 17 days. Above-normal streamflow and precipitation during the study could have increased the effect the river had on the alluvial aquifer and on the possibility of contamination by a pathogen. Microscopic particulate analysis of 29 samples found no Giardia cysts or Crytosporidium oocysts in water collected from municipal wells. Data also indicate that the aquifer is filtering out large numbers of algae, diatoms, rotifers, and nematodes as well as filtering out Cryptosporidium , Giardia , and other protozoa. The number of algae, diatoms, rotifers, protozoa, and vegetative debris for selected municipal wells tested showed at least a reduction to 1 per 1,000 of the number found in the river. A relative risk factor and a log-reduction rate were determined for the aquifer in the vicinity of selected wells. One municipal well had a high-risk factor, three other wells had a moderate-risk factor, and four wells had a low-risk factor. The filtering efficiency of the aquifer is equivalent to a 3 log-reduction rate or 99.99-percent reduction in particulates.

Iowa↗
USGS2026

Trends in subdaily to daily rainfall in Florida, 1990–2022

Changing rainfall patterns and intensifying rainfall extremes affect urban infrastructure and can increase flash-flood risk. Understanding how climate change has altered rainfall can support state and local agencies as they adapt and build resiliency. In this study, rainfall data from 23 weather stations in Florida were used to examine temporal and spatial trends over the period 1990–2022. Subdaily to daily rainfall events of durations 1, 2, 3, 6, 12, and 24 h were examined. A variety of statistical methods were applied to examine annual and seasonal trends, including quantile regression, extreme value analysis, run theory using the Mann–Kendall test, Sen–Theil slope, and Poisson and negative binomial tests, and threshold exceedance rates using generalized additive models. Using subdaily rainfall data posed challenges, including equipment failures, limited documentation of the quality assurance and control process, and potential measurement interferences. Results indicated that over 1990–2022, there was a decrease in hourly rainfall extremes but an increase at moderate quantiles. Overall, the number of rainfall events increased, particularly at shorter durations, but the mean total rainfall per event decreased. Additionally, the annual number of daily rainfall extremes showed more decreases than increases.

Florida↗
USGS2022

Advancing geophysical techniques to image a stratigraphic hydrothermal resource

Sedimentary-hosted geothermal energy systems are permeable structural, structural-stratigraphic, and/or stratigraphic horizons with sufficient temperature for direct use and/or electricity generation. Sedimentary-hosted (i.e., stratigraphic) geothermal reservoirs may be present in multiple locations across the central and eastern Great Basin of the USA, thereby constituting a potentially large base of untapped, economically accessible energy resources. Sandia National Laboratories has partnered with a multi-disciplinary group of collaborators to evaluate a stratigraphic system in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. The goal of this study is to inform an optimized strategy for subsequent exploration and development of this and analogous resources. Building from prior Nevada Play Fairway Analysis (PFA), this team is primarily 1) collecting additional geophysical data, 2) employing novel joint geophysical inversion/modeling techniques to update existing 3D geologic models, and 3) integrating the geophysical results to produce a working, geologically constrained thermo-hydrological reservoir model. Prior PFA work highlights Steptoe Valley as a favorable resource basin that likely has both sedimentary and hydrothermal characteristics. However, there remains significant uncertainty on the nature and architecture of the resource(s) at depth, which increases the risk in exploratory drilling. Newly acquired gravity, magnetic, magnetotelluric, and controlled-source electromagnetic data, in conjunction with new and preceding geoscientific measurements and observations, are being integrated and evaluated in this study for efficacy in understanding stratigraphic geothermal resources and mitigating exploration risk. Furthermore, the influence of hydrothermal activity on sedimentary-hosted reservoirs in favorable structural settings (i.e., whether fault-controlled systems may locally enhance temperature and permeability in some deep stratigraphic reservoirs) will also be evaluated. This paper provides details and current updates on the course of this study in-progress.

Geothermal Resources Council Transactions↗