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USGS2023

Model-based surveillance system design under practical constraints with application to white-nose syndrome

Infectious diseases are powerful ecological forces structuring ecosystems, causing devastating economic impacts and disrupting society. Successful prevention and control of pathogens requires knowledge of the current scope and severity of disease, as well as the ability to forecast future disease dynamics. Assessment of the current situation as well as prediction of the future conditions, rely on spatially referenced information regarding the presence or absence of a pathogen, and the prevalence of the pathogen in the population. In particular, knowledge about the location of the disease front is foundational for deploying disease countermeasures to prevent further disease spread and focusing control efforts to reduce disease intensity in affected areas. In this paper, we develop a model-based approach to designing sampling strategies for wildlife disease surveillance at the disease front. Specifically, we use a mechanistic spatio-temporal model based on an underlying partial differential equation to track the disease dynamics and predict the disease prevalence in the future. We also devise an optimal surveillance system design at the disease front that takes into account the practical constraints of sampling. We evaluate the effectiveness of our proposed design via a simulation study and demonstrate the application of the proposed approach by designing a surveillance strategy for the pathogen that causes white-nose syndrome.

Environmental and Ecological Statistics↗

USGS2017

Evaluation of radon occurrence in groundwater from 16 geologic units in Pennsylvania, 1986–2015, with application to potential radon exposure from groundwater and indoor air

Results from 1,041 groundwater samples collected during 1986‒2015 from 16 geologic units in Pennsylvania, associated with 25 or more groundwater samples with concentrations of radon-222, were evaluated in an effort to identify variations in radon-222 activities or concentrations and to classify potential radon-222 exposure from groundwater and indoor air. Radon-222 is hereafter referred to as “radon.” Radon concentrations in groundwater greater than or equal to the proposed U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL) for public-water supply systems of 300 picocuries per liter (pCi/L) were present in about 87 percent of the water samples, whereas concentrations greater than or equal to the proposed alternative MCL (AMCL) for public water-supply systems of 4,000 pCi/L were present in 14 percent. The highest radon concentrations were measured in groundwater from the schists, gneisses, and quartzites of the Piedmont Physiographic Province. In this study, conducted by the U.S. Geological Survey in cooperation with the Pennsylvania Department of Health and the Pennsylvania Department of Environmental Protection, groundwater samples were aggregated among 16 geologic units in Pennsylvania to identify units with high median radon concentrations in groundwater. Graphical plots and statistical tests were used to determine variations in radon concentrations in groundwater and indoor air. Median radon concentrations in groundwater samples and median radon concentrations in indoor air samples within the 16 geologic units were classified according to proposed and recommended regulatory limits to explore potential radon exposure from groundwater and indoor air. All of the geologic units, except for the Allegheny (Pa) and Glenshaw (Pcg) Formations in the Appalachian Plateaus Physiographic Province, had median radon concentrations greater than the proposed EPA MCL of 300 pCi/L, and the Peters Creek Schist (Xpc), which is in the Piedmont Physiographic Province, had a median radon concentration greater than the EPA proposed AMCL of 4,000 pCi/L. Median concentrations of radon in groundwater and indoor air were determined to differ significantly among the geologic units (Kruskal-Wallis test, significance probability, p<0.001), and Tukey’s test indicated that radon concentrations in groundwater and indoor air in the Peters Creek Schist (Xpc) were significantly higher than those in the other units. Also, the Peters Creek Schist (Xpc) was determined to be the area with highest potential of radon exposure from groundwater and indoor air and one of two units with the highest percentage of population assumed to be using domestic self-supplied water (81 percent), which puts the population at greater potential of exposure to radon from groundwater. Potential radon exposure determined from classification of geologic units by median radon concentrations in groundwater and indoor air according to proposed and recommended regulatory limits is useful for drawing general conclusions about the presence, variation, and potential radon exposure in specific geologic units, but the associated data and maps have limitations. The aggregated indoor air radon data have spatial accuracy limitations owing to imprecision of geocoded test locations. In addition, the associated data describing geologic units and the public water supplier’s service areas have spatial and interpretation accuracy limitations. As a result, data and maps associated with this report are not recommended for use in predicting individual concentrations at specific sites nor for use as a decision-making tool for property owners to decide whether to test for radon concentrations at specific locations. Instead, the data and maps are meant to promote awareness regarding potential radon exposure in Pennsylvania and to point out data gaps that exist throughout the State.

Pennsylvania↗

USGS2012

The United States National Climate Assessment - Alaska Technical Regional Report

The Alaskan landscape is changing, both in terms of effects of human activities as a consequence of increased population, social and economic development and their effects on the local and broad landscape; and those effects that accompany naturally occurring hazards such as volcanic eruptions, earthquakes, and tsunamis. Some of the most prevalent changes, however, are those resulting from a changing climate, with both near term and potential upcoming effects expected to continue into the future. Alaska's average annual statewide temperatures have increased by nearly 4°F from 1949 to 2005, with significant spatial variability due to the large latitudinal and longitudinal expanse of the State. Increases in mean annual temperature have been greatest in the interior region, and smallest in the State's southwest coastal regions. In general, however, trends point toward increases in both minimum temperatures, and in fewer extreme cold days. Trends in precipitation are somewhat similar to those in temperature, but with more variability. On the whole, Alaska saw a 10-percent increase in precipitation from 1949 to 2005, with the greatest increases recorded in winter. The National Climate Assessment has designated two well-established scenarios developed by the Intergovernmental Panel on Climate Change (Nakicenovic and others, 2001) as a minimum set that technical and author teams considered as context in preparing portions of this assessment. These two scenarios are referred to as the Special Report on Emissions Scenarios A2 and B1 scenarios, which assume either a continuation of recent trends in fossil fuel use (A2) or a vigorous global effort to reduce fossil fuel use (B1). Temperature increases from 4 to 22°F are predicted (to 2070-2099) depending on which emissions scenario (A2 or B1) is used with the least warming in southeast Alaska and the greatest in the northwest. Concomitant with temperature changes, by the end of the 21st century the growing season is expected to lengthen by 15-25 days in some areas of Alaska, with much of that corresponding with earlier spring snow melt. Future projections of precipitation (30-80 years) over Alaska show an increase across the State, with the largest changes in the northwest and smallest in the southeast. Because of increasing temperatures and growing season length, however, increased precipitation may not correspond with increased water availability, due to temperature related increased evapotranspiration. The extent of snow cover in the Northern Hemisphere has decreased by about 10 percent since the late 1960s, with stronger trends noted since the late 1980s. Alaska has experienced similar trends, with a strong decrease in snow cover extent occurring in May. When averaged across the State, the disappearance of snow in the spring has occurred from 4 to 6 days earlier per decade, and snow return in fall has occurred approximately 2 days later per decade. This change appears to be driven by climate warming rather than a decrease in winter precipitation, with average winter temperatures also increasing by about 2.5°F. The extent of sea ice has been declining, as has been widely published in both national and scientific media outlets, and is projected to continue to decline during this century. The observed decline in annual sea ice minimum extent (September) has occurred more rapidly than was predicted by climate models and has been accompanied by decreases in ice thickness and in the presence of multi-year ice. This decrease was first documented by satellite imagery in the late 1970s for the Bering and Chukchi Seas, and is projected to continue, with the potential for the disappearance of summer sea ice by mid- to late century. A new phenomenon that was not reported in previous assessments is ocean acidification. Uptake of carbon dioxide (CO2) by oceans has a significant effect on marine biogeochemistry by reducing seawater pH. Ocean acidification is of particular concern in Alaska, because cold sea water absorbs CO2 more rapidly than warm water, and a decrease in sea ice extent has allowed increased sea surface exposure and more uptake of CO2 into these northern waters. Ocean acidification will likely affect the ability of organisms to produce and maintain shell material, such as aragonite or calcite (calcium carbonate minerals structured from carbonate ions), required by many shelled organism, from mollusks to corals to microscopic organisms at the base of the food chain. Direct biological effects in Alaska further along the food chain have yet to be studied and may vary among organisms. Some of the potentially most significant changes to Alaska that could result from a changing climate are the effects on the terrestrial cryosphere - particularly glaciers and permafrost. Alaskan glaciers are changing at a rapid rate, the primary driver appearing to be temperature. Statewide, glaciers lost 13 cubic miles of ice annually from the 1950s to the 1990s, and that rate doubled in the 2000s. However, like temperature and precipitation, glacier ice loss is not spatially uniform; most glaciers are losing mass, yet some are growing (for example Hubbard Glacier in southeast Alaska). Alaska glaciers with the most rapid loss are those terminating in sea water or lakes. With this increasing rate of melt, the contribution of surplus fresh water entering into the oceans from Alaska's glaciers, as well as those in neighboring British Columbia, Canada, is approximately 20 percent of that contributed by the Greenland Ice Sheet. Permafrost degradation (that is, the thawing of ice-rich soils) is currently (2012) impacting infrastructure and surface-water availability in areas of both discontinuous and continuous ground ice. Over most of the State, the permafrost is warming, with increasing temperatures broadly consistent with increasing air temperatures. On the Arctic coastal plain of Alaska, permafrost temperatures showed some cooling in the 1950s and 1960s but have been followed by a roughly 5°F increase since the 1980s. Many areas in the continuous permafrost zone have seen increases in temperature in the seasonally active layer and a decrease in re-freezing rates. Changes in the discontinuous permafrost zone are initially much more observable due to the resulting thermokarst terrain (land surface formed as ice rich permafrost thaws), most notable in boreal forested areas. Climate warming in Alaska has potentially broad implications for human health and food security, especially in rural areas, as well as increased risk for injury with changing winter ice conditions. Additionally, such warming poses the potential for increasing damage to existing water and sanitation facilities and challenges for development of new facilities, especially in areas underlain by permafrost. Non-infectious and infectious diseases also are becoming an increasing concern. For example, from 1999 to 2006 there was a statistically significant increase in medical claims for insectbite reactions in five of six regions of Alaska, with the largest percentage increase occurring in the most northern areas. The availability and quality of subsistence foods, normally considered to be very healthy, may change due to changing access, changing habitats, and spoilage of meat in food storage cellars. These and other trends and potential outcomes resulting from a changing climate are further described in this report. In addition, we describe new science leadership activities that have been initiated to address and provide guidance toward conducting research aimed at making available information for policy makers and land management agencies to better understand, address, and plan for changes to the local and regional environment. This report cites data in both metric and standard units due to the contributions by numerous authors and the direct reference of their data.

Alaska↗

USGS1997

Nitrate in ground water and stream base flow in the lower Susquehanna River Basin, Pennsylvania and Maryland

High concentrations of nitrate in both ground and surface water have been identified as a significant water-quality issue in the Lower Susquehanna River Basin. This report uses data collected by the National Water Quality Assessment (NAWQA) Program in the basin and compares nitrate concentrations found in ground water and surface water on both a spatial and temporal basis and relates nitrate concentrations to land use. Nitrate concentrations in the Lower Susquehanna River Basin in Pennsylvania and Maryland were higher in ground water than in surface water in agricultural areas underlain by carbonate bedrock and agricultural areas underlain by crystalline bedrock. Nitrate concentrations were higher in surface water than in ground water in urban areas underlain by carbonate bedrock. Nitrate concentrations also were higher in surface water than ground water in both agricultural and forested areas underlain by sandstone and shale. Nitrate concentrations in ground water vary in areas with different land use and bedrock type. Ground-water nitrate concentrations were highest in agricultural areas underlain by carbonate bedrock, where 45 percent of the samples exceeded the U.S. Environmental Protection Agency (USEPA) Maximum Contaminant Level (MCL) of 10 mg/L (milligrams per liter as N). Waters from 36 percent of the wells in agricultural areas underlain by crystalline bedrock also had nitrate concentrations greater than 10 mg/L. Nitrate concentrations in water from wells in urban areas underlain by carbonate bedrock and in forested and agricultural areas underlain by sandstone and shale seldom exceeded the MCL. Nitrate concentrations were generally higher in surface water in areas underlain by carbonate bedrock than in areas underlain by noncarbonate bedrock; however, when an agricultural area underlain by carbonate bedrock and an agricultural area underlain by sandstone and shale with similar manure application rates were compared, nitrate concentrations in surface water were not significantly different. A comparison of three agricultural areas underlain by carbonate bedrock shows that the manure application rate is strongly correlated with nitrate concentration. Nitrate concentrations in stream base flow at seven sites where samples were collected throughout the year were commonly higher in the winter months than in the summer months. A statistically significant correlation between streamflow and nitrate concentration existed for six of the seven sites, indicating that seasonal variability in precipitation may be the cause of some of the seasonal variation in concentration. Other possible explanations for this variation include the seasonal cycle in plant uptake of nitrogen and seasonal fluctuations in uptake of nitrate by algae in streams. Because no information was available about the traveltime for ground water, interpretation of this temporal variation was not conclusive. Estimates of base-flow loads and yields of nitrate showed that agricultural areas underlain by carbonate bedrock provide the highest yield of nitrate when compared with the other areas studied. Agricultural areas underlain by sandstone and shale and crystalline bedrock also provide large amounts of nitrate to the river. The large amount of nitrate in the water from these areas cause a significant increase in nitrate loads transported by the Susquehanna River to the Chesapeake Bay. Urban areas underlain by carbonate bedrock had a high yield of nitrate but comprise such a small part of the basin that the nitrate load from these areas was small. In contrast, forested areas underlain by sandstone and shale bedrock had low base-flow nitrate yields, but these areas comprise a large percentage of the basin, making the overall nitrate load from these areas high.

Maryland, Pennsylvania↗

USGS2023

Quantification of geodetic strain rate uncertainties and implications for seismic hazard estimates

Geodetic velocity data provide first-order constraints on crustal surface strain rates, which in turn are linked to seismic hazard. Estimating the 2-D surface strain tensor everywhere requires knowledge of the surface velocity field everywhere, while geodetic data such as Global Navigation Satellite System (GNSS) only have spatially scattered measurements on the surface of the Earth. To use these data to estimate strain rates, some type of interpolation is required. In this study, we review methodologies for strain rate estimation and compare a suite of methods, including a new implementation based on the geostatistical method of kriging, to compare variation between methods with uncertainty based on one method. We estimate the velocity field and calculate strain rates in southern California using a GNSS velocity field and five different interpolation methods to understand the sources of variability in inferred strain rates. Uncertainty related to data noise and station spacing (aleatoric uncertainty) is minimal where station spacing is dense and maximum far from observations. Differences between methods, related to epistemic uncertainty, are usually highest in areas of high strain rate due to differences in how gradients in the velocity field are handled by different interpolation methods. Parameter choices, unsurprisingly, have a strong influence on strain rate field, and we propose the traditional L -curve approach as one method for quantifying the inherent trade-off between fit to the data and models that are reflective of tectonic strain rates. Doing so, we find total variability between five representative strain rate models to be roughly 40 per cent, a much lower value than roughly 100 per cent that was found in previous studies (Hearn et al .). Using multiple methods to tune parameters and calculate strain rates provides a better understanding of the range of acceptable models for a given velocity field. Finally, we present an open-source Python package (Materna et al .) for calculating strain rates, Strain_2D, which allows for the same data and model grid to be used in multiple strain rate methods, can be extended with other methods from the community, and provides an interface for comparing strain rate models, calculating statistics and estimating strain rate uncertainty for a given GNSS data set.

Geophysical Journal International↗

USGS2016

Assessing the role of climate and resource management on groundwater dependent ecosystem changes in arid environments with the Landsat archive

Groundwater dependent ecosystems (GDEs) rely on near-surface groundwater. These systems are receiving more attention with rising air temperature, prolonged drought, and where groundwater pumping captures natural groundwater discharge for anthropogenic use. Phreatophyte shrublands, meadows, and riparian areas are GDEs that provide critical habitat for many sensitive species, especially in arid and semi-arid environments. While GDEs are vital for ecosystem services and function, their long-term (i.e. ~ 30 years) spatial and temporal variability is poorly understood with respect to local and regional scale climate, groundwater, and rangeland management. In this work, we compute time series of NDVI derived from sensors of the Landsat TM, ETM +, and OLI lineage for assessing GDEs in a variety of land and water management contexts. Changes in vegetation vigor based on climate, groundwater availability, and land management in arid landscapes are detectable with Landsat. However, the effective quantification of these ecosystem changes can be undermined if changes in spectral bandwidths between different Landsat sensors introduce biases in derived vegetation indices, and if climate, and land and water management histories are not well understood. The objective of this work is to 1) use the Landsat 8 under-fly dataset to quantify differences in spectral reflectance and NDVI between Landsat 7 ETM + and Landsat 8 OLI for a range of vegetation communities in arid and semiarid regions of the southwestern United States, and 2) demonstrate the value of 30-year historical vegetation index and climate datasets for assessing GDEs. Specific study areas were chosen to represent a range of GDEs and environmental conditions important for three scenarios: baseline monitoring of vegetation and climate, riparian restoration, and groundwater level changes. Google's Earth Engine cloud computing and environmental monitoring platform is used to rapidly access and analyze the Landsat archive along with downscaled North American Land Data Assimilation System gridded meteorological data, which are used for both atmospheric correction and correlation analysis. Results from the cross-sensor comparison indicate a benefit from the application of a consistent atmospheric correction method, and that NDVI derived from Landsat 7 and 8 are very similar within the study area. Results from continuous Landsat time series analysis clearly illustrate that there are strong correlations between changes in vegetation vigor, precipitation, evaporative demand, depth to groundwater, and riparian restoration. Trends in summer NDVI associated with riparian restoration and groundwater level changes were found to be statistically significant, and interannual summer NDVI was found to be moderately correlated to interannual water-year precipitation for baseline study sites. Results clearly highlight the complementary relationship between water-year PPT, NDVI, and evaporative demand, and are consistent with regional vegetation index and complementary relationship studies. This work is supporting land and water managers for evaluation of GDEs with respect to climate, groundwater, and resource management.

Remote Sensing of Environment↗

USGS1997

Pesticides in surface water of the Mid-Atlantic region

Water-quality data from 463 surface-water sites were compiled and analyzed to document the occurrence and distribution of pesticides in surface water of the Mid-Atlantic region as part of the Mid-Atlantic Integrated Assessment program of the U.S. Environmental Protection Agency. Those data collected by the U.S. Geological Survey from October 1973 through March 1997 were used in the analyses. Data are available for a large part of the Mid-Atlantic region, but large spatial gaps in the data do exist. USGS data bases contained analyses of surface-water samples for 127 pesticide compounds, including 12 degradates, but only 16 of the compounds were commonly detected. Atrazine, metolachlor, simazine, prometon, alachlor, tebuthiuron, cyanazine, diazinon, carbaryl, chlorpyrifos, pendimethalin, 2,4-D, dieldrin, DCPA, metribuzin, and desethylatrazine (an atrazine degradate) were detected in more than 100 of the samples analyzed. At least one pesticide was detected in about 75 percent of the samples collected and at more than 90 percent of the sites sampled. Concentrations greater than the Federal Maximum Contaminant Level (MCL) for drinking water of 3 micrograms per liter (ug/L) for atrazine were found in 67 of 2,076 samples analyzed; concentrations greater than the MCL of 2ug/L for alachlor were found in 13 of 1,693 samples analyzed, and concentrations greater than the MCL of 4 ug/L for simazine were found in 17 of 1,995 samples analyzed. Concentrations of four pesticides were greater than Federal Health Advisory levels for drinking water, and concentrations of nine pesticides were greater than Federal Ambient Water-Quality Criteria for the Protection of Aquatic Organisms. Streams draining basins with different land uses tend to have different pesticide detection frequencies and median concentrations. Median concentrations of herbicides tend to be highest in streams draining basins in which the major land use is agriculture, whereas median concentrations of insecticides tend to be highest in streams draining extensively urbanized basins. Concentrations of both herbicides and insecticides are usually highest during the spring and summer, although many pesticides are present at low concentrations in surface water throughout the year. Pesticide concentrations vary greatly seasonally and over different hydrologic conditions, with overall variation sometimes exceeding four orders of magnitude. During periods of pesticide application (typically spring and summer), the occurrence of selected pesticides in some streams in the Mid-Atlantic region is related to streamflow. Correlations between concentrations of selected pesticides and streamflow are statistically significant during spring and summer for small (draining less than 55 square miles) streams. Concentrations of selected pesticides in small streams increase during high flows in the growing season, up to 30 times the concentrations present during low-flow conditions in the growing season. In small streams draining urban areas, concentrations of atrazine decrease during high-flow events but concentrations of the insecticides diazinon and chlorpyrifos increase. This may be due to the differences in the pesticides used in agricultural and urban areas and the amounts applied.

Water-Resources Investigations Report↗

USGS2022

Yuma Ridgway’s rail selenium exposure and occupancy within managed and unmanaged emergent marshes at the Salton Sea

Yuma Ridgway’s rail ( Rallus obsoletus yumanensis , hereafter, rail) is an endangered species for which patches of emergent marsh within the Salton Sea watershed comprise a substantial part of habitat for the species’ disjointed range in the southwestern United States. These areas of emergent marsh include (1) marshes managed by federal (particularly the U.S. Fish and Wildlife Service’s Sonny Bono Salton Sea National Wildlife Refuge), state (California Department of Fish and Wildlife), and local (Imperial Irrigation District) resource agencies that are sustained by direct deliveries of Colorado River water and (2) unmanaged marshes sustained by agricultural drainage water. Management of rail habitat in this arid environment is complicated by increasingly limited availability of unimpaired freshwater owing to water management decisions associated with the Quantification Settlement Agreement and risks posed by potentially harmful concentrations of selenium found in agricultural drainage water that can readily bioaccumulate in aquatic food webs. To provide timely science for managers, herein we report summary statistics for managed and unmanaged emergent marshes sampled at the Salton Sea during the rail breeding season of 2016 pertaining to (1) selenium concentrations in food webs representing dietary pathways of selenium exposure and (2) patterns of rail occupancy and inter-marsh movements, estimated abundance, and regional population size of rail. For selenium-specific objectives, we sampled unfiltered surface water, midge larvae (Chironomidae), water boatmen (Corixidae), mosquitofish ( Gambusia spp.), and crayfish (Astacidae). Selenium samples were collected from 15 fixed sampling points, each in managed and unmanaged marshes, during late February, April, and June 2016, which corresponded to rail pre-nesting, nesting, and fledgling reproductive life-stages, respectively. Two areas within the two treatment types (managed versus unmanaged marsh) were of particular interest to help assess risks associated with changing sea dynamics and different water-management strategies: (1) a large unmanaged marsh (Morton Bay) unintentionally created in approximately 2008 when it became separated from the Salton Sea as water inflows began to drop and a berm formed from accumulated sediment and (2) a restored marsh (HZ9A) managed by the Sonny Bono Salton Sea National Wildlife Refuge, which is currently supplied with Colorado River water but may be sustained in the future by a blend of clean (that is, low selenium) Colorado River and agricultural drainage water with higher selenium from the Alamo River. Hence, baseline data for these marshes are important for future management decisions. We also report selenium concentrations in rail blood, head feathers, and breast feathers from rails captured as part of the movement study. Results indicated relatively higher risks from dietary selenium exposure for rails occupying unmanaged marshes compared to managed marshes and similar risks among unmanaged marshes. However, risks also were potentially elevated for rails occupying some managed marshes (that is, the Hazard Marshes), where relatively high proportions of Chironomidae and mosquitofish exceeded dietary thresholds for selenium effects on avian reproduction. For rail-specific objectives, we quantified occupancy and spatial distribution using call count data analyzed with imperfect detection models. Imperfect detection models allowed us to jointly estimate detection probability and abundance of detected rails in association with habitats. We then used estimates of detection probability and abundance at the habitat level to extrapolate rail population abundance for the Salton Sea region. Inter- and intra-marsh movements were described from over 5,000 locations obtained from 15 radio-marked rails. Resultant space use patterns indicated that, in general, selenium risk to individuals is not equally shared because of high levels of territoriality and very limited movement throughout the landscape. Moreover, the largest contiguous blocks of habitat are associated with unmanaged marshlands located on the former southeastern shoreline and outside traditional management areas and authorities. Thus, a substantial proportion of the rail population that is using unmanaged marsh on the southeastern shoreline may have disproportionate risk of elevated selenium exposure, yet how that risk translates to population-level effects remains unknown.

California↗

USGS2017

Fena Valley Reservoir watershed and water-balance model updates and expansion of watershed modeling to southern Guam

In 2014, the U.S. Geological Survey, in cooperation with the U.S. Department of Defense’s Strategic Environmental Research and Development Program, initiated a project to evaluate the potential impacts of projected climate-change on Department of Defense installations that rely on Guam’s water resources. A major task of that project was to develop a watershed model of southern Guam and a water-balance model for the Fena Valley Reservoir. The southern Guam watershed model provides a physically based tool to estimate surface-water availability in southern Guam. The U.S. Geological Survey’s Precipitation Runoff Modeling System, PRMS-IV, was used to construct the watershed model. The PRMS-IV code simulates different parts of the hydrologic cycle based on a set of user-defined modules. The southern Guam watershed model was constructed by updating a watershed model for the Fena Valley watersheds, and expanding the modeled area to include all of southern Guam. The Fena Valley watershed model was combined with a previously developed, but recently updated and recalibrated Fena Valley Reservoir water-balance model. Two important surface-water resources for the U.S. Navy and the citizens of Guam were modeled in this study; the extended model now includes the Ugum River watershed and improves upon the previous model of the Fena Valley watersheds. Surface water from the Ugum River watershed is diverted and treated for drinking water, and the Fena Valley watersheds feed the largest surface-water reservoir on Guam. The southern Guam watershed model performed “very good,” according to the criteria of Moriasi and others (2007), in the Ugum River watershed above Talofofo Falls with monthly Nash-Sutcliffe efficiency statistic values of 0.97 for the calibration period and 0.93 for the verification period (a value of 1.0 represents perfect model fit). In the Fena Valley watershed, monthly simulated streamflow volumes from the watershed model compared reasonably well with the measured values for the gaging stations on the Almagosa, Maulap, and Imong Rivers—tributaries to the Fena Valley Reservoir—with Nash-Sutcliffe efficiency values of 0.87 or higher. The southern Guam watershed model simulated the total volume of the critical dry season (January to May) streamflow for the entire simulation period within –0.54 percent at the Almagosa River, within 6.39 percent at the Maulap River, and within 6.06 percent at the Imong River. The recalibrated water-balance model of the Fena Valley Reservoir generally simulated monthly reservoir storage volume with reasonable accuracy. For the calibration and verification periods, errors in end-of-month reservoir-storage volume ranged from 6.04 percent (284.6 acre-feet or 92.7 million gallons) to –5.70 percent (–240.8 acre-feet or –78.5 million gallons). Monthly simulation bias ranged from –0.48 percent for the calibration period to 0.87 percent for the verification period; relative error ranged from –0.60 to 0.88 percent for the calibration and verification periods, respectively. The small bias indicated that the model did not consistently overestimate or underestimate reservoir storage volume. In the entirety of southern Guam, the watershed model has a “satisfactory” to “very good” rating when simulating monthly mean streamflow for all but one of the gaged watersheds during the verification period. The southern Guam watershed model uses a more sophisticated climate-distribution scheme than the older model to make use of the sparse climate data, as well as includes updated land-cover parameters and the capability to simulate closed depression areas. The new Fena Valley Reservoir water-balance model is useful as an updated tool to forecast short-term changes in the surface-water resources of Guam. Furthermore, the now spatially complete southern Guam watershed model can be used to evaluate changes in streamflow and recharge owing to climate or land-cover changes. These are substantial improvements to the previous models of the Fena Valley watershed and Reservoir. Datasets associated with this report are available as a U.S. Geological Survey data release (Rosa and Hay, 2017; DOI:10.5066/F7HH6HV4).

Scientific Investigations Report↗

USGS2010

Effects of selected low-impact-development (LID) techniques on water quality and quantity in the Ipswich River Basin, Massachusetts: Field and modeling studies

During the months of August and September, flows in the Ipswich River, Massachusetts, dramatically decrease largely due to groundwater withdrawals needed to meet increased residential and commercial water demands. In the summer, rates of groundwater recharge are lower than during the rest of the year, and water demands are higher. From 2005 to 2008, the U.S. Geological Survey, in a cooperative funding agreement with the Massachusetts Department of Conservation and Recreation, monitored small-scale installations of low-impact-development (LID) enhancements designed to diminish the effects of storm runoff on the quantity and quality of surface water and groundwater. Funding for the studies also was contributed by the U.S. Environmental Protection Agency’s Targeted Watersheds Grant Program through a financial assistance agreement with Massachusetts Department of Conservation and Recreation. The monitoring studies examined the effects of (1) replacing an impervious parking lot surface with a porous surface on groundwater quality, (2) installing rain gardens and porous pavement in a neighborhood of 3 acres on the quantity and quality of stormwater runoff, and (3) installing a 3,000-square foot (ft2) green roof on the quantity and quality of stormwater runoff. In addition, the effects of broad-scale implementation of LID techniques, reduced water withdrawals, and water-conservation measures on streamflow in large areas of the basin were simulated using the U.S. Geological Survey’s Ipswich River Basin model. From June 2005 to 2007, groundwater quality was monitored at the Silver Lake town beach parking lot in Wilmington, MA, prior to and following the replacement of the conventional, impervious-asphalt surface with a porous surface consisting primarily of porous asphalt and porous pavers. Changes in the concentrations of the water-quality constituents, phosphorus, nitrogen, cadmium, chromium, copper, lead, nickel, zinc, and total petroleum hydrocarbons, were monitored. Increased infiltration of precipitation did not result in discernible increases in concentrations of these potential groundwater contaminants. Concentrations of dissolved oxygen increased slightly in groundwater profiles following the removal of the impervious asphalt parking lot surface. In Wilmington, MA, in a 3-acre neighborhood, stormwater runoff volume and quality were monitored to determine the ability of selected LID enhancements (rain gardens and porous paving stones) to reduce flows and loads of the above constituents to Silver Lake. Flow-proportional water-quality samples were analyzed for nutrients, metals, total petroleum hydrocarbons, and total-coliform and Escherichia coli bacteria. In general, when all storms were considered, no substantial decreases were observed in runoff volume as a result of installing LID enhancements. However, the relation between rainfall and runoff did provide some insight into how the LID enhancements affected the effective impervious area for the neighborhood. A decrease in runoff was observed for storms of 0.2 inches (in.) or less of precipitation, which indicated a reduction in effective impervious area from approximately 10 percent to about 4.5 percent for the 3-acre area. Water-quality-monitoring results were inconclusive; there were no statistically significant differences in concentrations or loads when the pre- and post-installation-period samples were compared. Three factors were probably most important in minimizing differences: (1) the small decrease in effective impervious area, (2) the differences in the size of storms sampled for water-quality constituents before and after installation of the infiltration enhancing measures, and (3) small sample sizes. In a third field study, the characteristics of runoff from a vegetated “green” roof and a conventional, rubber-membrane roof were compared. The amount of precipitation and the length of the antecedent dry period were the two primary factors affecting the green roof’s water-storage capacity. The green roof retained more than 50 percent of the precipitation from storms with 0.04 to 1.0 in. of rain. Approximately 95 percent of the precipitation from one storm of nearly 2 in. was retained by the green roof. On the rubber-membrane roof, only a small, shallow puddle of insubstantial volume ever remained after a storm. Bulk precipitation from 10 storms was monitored for the same constituents (nutrients, metals, and total petroleum hydrocarbons) as the roof runoff, and the results were compared with those for roof-runoff samples. The use of fertilizers to help establish the vegetation during the study probably distorted any effect the plants and growing medium may have had on the retention of target analytes. As a result of the fertilizer and growing medium chemistry, median concentrations of total nitrogen, total phosphorus, cadmium, copper, and nickel in runoff from the green roof were greater than in the runoff from the conventional roof or in bulk precipitation. Concentrations of lead and zinc were greater in runoff from the conventional roof, probably a result of passage through the old, metal drainpipes. Simulations of the effects of LID on streamflow in the Ipswich River Basin were conducted with a previously calibrated Hydrological Simulation Program-FORTRAN (HSPF) precipitation-runoff model. Simulations were conducted at multiple spatial scales to evaluate the effects of (1) updated water withdrawals for the towns of Reading and Wilmington; (2) potential land-use changes at buildout (potential future development); (3) effective impervious area reductions upstream from the South Middleton streamgage to represent the effects of widespread implementation of LID retrofit techniques; (4) basin-scale water withdrawal reductions scaled up (expanded to the town level) from water-conservation pilot programs conducted by the Massachusetts Department of Conservation and Recreation; and (5) land-use change and LID techniques at a local scale, which is smaller than the HSPF subbasin. Effects on streamflow generally were evaluated by comparing results of two or more related simulations for selected reaches in the basin; thus, relative rather than absolute changes in simulated flow were the focus of the assessment. Simulations indicated that reduced withdrawals for the towns of Reading and Wilmington led to substantially higher medium and low flows in most of the reaches upstream from the South Middleton streamgage. Simulations of water-conservation measures resulted in negligible effects on streamflow. Overall, simulations indicated that spatial scale is an important factor in determining the effects of land-use change and LID practices on streamflow. Potential land-use changes at buildout had modest (percent differences of less than 20 percent) effects on streamflow in most subbasins because relatively little land in the basin was available for development (about 17 percent); moreover, most of the available open land is zoned for low-density residential development, and this land-use category was simulated to contain relatively little effective impervious area and to be similar hydrologically to the forested land in place prior to development. Results of the simulations conducted to evaluate widespread effective impervious area reductions upstream from the South Middleton streamgage indicated that the percentage of urban land use and associated effective impervious area was too small for a 50-percent reduction of effective impervious area to appreciably affect streamflow (percent differences of less than 20 percent) in most subbasins. In contrast, the results of the hypothetical local-scale simulations indicated that for smaller streams, where the percentage of urban land use and associated effective impervious area in the drainage area may be substantially higher, land-use change, development patterns, and LID practices potentially have much greater effects on streamflow. Modeling results also indicated that LID was potentially most beneficial for minimizing streamflow alteration when applied to dense urban development, largely because larger tracts of effective impervious area were available for reduction than were available for other land-use categories. For example, commercial-industrial-transportation land use is composed of 37 percent pervious area and 63 percent effective impervious area in the HSPF model, whereas low-density residential area is composed of 97.5 percent pervious area and only 2.5 percent effective impervious area. Field and modeling studies concurred in the assessment that LID enhancements would likely have the greatest effect on decreasing stormwater runoff when broadly applied to highly impervious urban areas. A measurable effect for small rainfall events (less than 0.25 inch) was determined in the small, highly pervious area that was monitored in this study, but the volume difference was not great.

Massachusetts↗

USGS2012

Lahar hazard zones for eruption-generated lahars in the Lassen Volcanic Center, California

Lahar deposits are found in drainages that head on or near Lassen Peak in northern California, demonstrating that these valleys are susceptible to future lahars. In general, lahars are uncommon in the Lassen region. Lassen Peak's lack of large perennial snowfields and glaciers limits its potential for lahar development, with the winter snowpack being the largest source of water for lahar generation. The most extensive lahar deposits are related to the May 1915 eruption of Lassen Peak, and evidence for pre-1915 lahars is sparse and spatially limited. The May 1915 eruption of Lassen Peak was a small-volume eruption that generated a snow and hot-rock avalanche, a pyroclastic flow, and two large and four smaller lahars. The two large lahars were generated on May 19 and 22 and inundated sections of Lost and Hat Creeks. We use 80 years of snow depth measurements from Lassen Peak to calculate average and maximum liquid water depths, 2.02 meters (m) and 3.90 m respectively, for the month of May as estimates of the 1915 lahars. These depths are multiplied by the areal extents of the eruptive deposits to calculate a water volume range, 7.05-13.6x10 6 cubic meters (m 3 ). We assume the lahars were a 50/50 mix of water and sediment and double the water volumes to provide an estimate of the 1915 lahars, 13.2-19.8x10 6 m 3 . We use a representative volume of 15x106 m 3 in the software program LAHARZ to calculate cross-sectional and planimetric areas for the 1915 lahars. The resultant lahar inundation zone reasonably portrays both of the May 1915 lahars. We use this same technique to calculate the potential for future lahars in basins that head on or near Lassen Peak. LAHARZ assumes that the total lahar volume does not change after leaving the potential energy, H/L , cone (the height of the edifice, H , down to the approximate break in slope at its base, L ); therefore, all water available to initiate a lahar is contained inside this cone. Because snow is the primary source of water for lahar generation, we assume that the maximum historical water equivalent, 3.90 m, covers the entire basin area inside the H/L cone. The product of planimetric area of each basin inside the H/L and the maximum historical water equivalent yields the maximum water volume available to generate a lahar. We then double the water volumes to approximate maximum lahar volumes. The maximum lahar volumes and an understanding of the statistical uncertainties inherent to the LAHARZ calculations guided our selection of six hypothetical volumes, 1, 3, 10, 30, 60, and 90x10 6 m 3 , to delineate concentric lahar inundation zones. The lahar inundation zones extend, in general, tens of kilometers away from Lassen Peak. The small, more-frequent lahar inundation zones (1 and 3x10 6 m 3 ) are, on average, 10 km long. The exceptions are the zones in Warner Creek and Mill Creek, which extend much further. All but one of the small, more-frequent lahar inundation zones reach outside of the Lassen Volcanic National Park boundary, and the zone in Mill Creek extends well past the park boundary. All of the medium, moderately frequent lahar inundation zones (10 and 30x10 6 m 3 ) extend past the park boundary and could potentially impact the communities of Viola and Old Station and State Highways 36 and 44, both north and west of Lassen Peak. The approximately 27-km-long on average, large, less-frequent lahar inundation zones (60 and 90x10 6 m 3 ) represent worst-case lahar scenarios that are unlikely to occur. Flood hazards continue downstream from the toes of the lahars, potentially affecting communities in the Sacramento River Valley.

California↗

USGS2020

Comparison of machine learning approaches used to identify the drivers of Bakken oil well productivity

Geologists and petroleum engineers have struggled to identify the mechanisms that drive productivity in horizontal hydraulically fractured oil wells. The machine learning algorithms of Random Forest (RF), gradient boosting trees (GBT) and extreme gradient boosting (XGBoost) were applied to a dataset containing 7311 horizontal hydraulically fractured wells drilled into the middle member of the Bakken Formation from 2010 through 2017. The initial goal is to use these data‐driven machine learning algorithms to identify the most important explanatory predictors of well productivity within nine subareas and the composite area. Predictor variables representing initial gas production, the initial 180‐day water cut, and vertical depth vary spatially and are identified with geologically favorable areas. Well‐completion predictors include the well lateral length, number of fracture stages, volume of proppant per stage, and the volume of injected fluids per stage. The performance of methods is compared based on a common test sample. The analysis then examines the comparative predictive performance of the three algorithms for 1330 wells that had initiated production after the initial 7311 well sample had been producing. The computations of predictor importance identified the initial 180‐day water cut and the 30‐day initial gas production predictors as having a dominant influence in most subareas and for the composite area. The relative importance of well completion predictor variables, that is, the number of fracture stages per well, volume of injected proppant per stage, volume of injected fluids per stage, and lateral length, varied considerably across the subareas. For the common test or holdout sample, the models calibrated with the XGBoost algorithm had superior predictive power. The predictive power of all the algorithms trained on the data from the original sample suffered some loss when tested with a sample of wells that had started production after the end of that period. Implications of the empirical findings and strategies to mitigate loss of predictive power are discussed in the concluding section.

Statistical Analysis and Data Mining↗

USGS2012

Surface heat flow and CO2 emissions within the Ohaaki hydrothermal field, Taupo Volcanic Zone, New Zealand

Carbon dioxide emissions and heat flow have been determined from the Ohaaki hydrothermal field, Taupo Volcanic Zone (TVZ), New Zealand following 20 a of production (116 MW e ). Soil CO 2 degassing was quantified with 2663 CO 2 flux measurements using the accumulation chamber method, and 2563 soil temperatures were measured and converted to equivalent heat flow (W m −2 ) using published soil temperature heat flow functions. Both CO 2 flux and heat flow were analysed statistically and then modelled using 500 sequential Gaussian simulations. Forty subsoil CO 2 gas samples were also analysed for stable C isotopes. Following 20 a of production, current CO 2 emissions equated to 111 ± 6.7 T/d. Observed heat flow was 70 ± 6.4 MW, compared with a pre-production value of 122 MW. This 52 MW reduction in surface heat flow is due to production-induced drying up of all alkali–Cl outflows (61.5 MW) and steam-heated pools (8.6 MW) within the Ohaaki West thermal area (OHW). The drying up of all alkali–Cl outflows at Ohaaki means that the soil zone is now the major natural pathway of heat release from the high-temperature reservoir. On the other hand, a net gain in thermal ground heat flow of 18 MW (from 25 MW to 43.3 ± 5 MW) at OHW is associated with permeability increases resulting from surface unit fracturing by production-induced ground subsidence. The Ohaaki East (OHE) thermal area showed no change in distribution of shallow and deep soil temperature contours despite 20 a of production, with an observed heat flow of 26.7 ± 3 MW and a CO 2 emission rate of 39 ± 3 T/d. The negligible change in the thermal status of the OHE thermal area is attributed to the low permeability of the reservoir beneath this area, which has limited production (mass extraction) and sheltered the area from the pressure decline within the main reservoir. Chemistry suggests that although alkali–Cl outflows once contributed significantly to the natural surface heat flow (∼50%) they contributed little (<1%) to pre-production CO 2 emissions due to the loss of >99% of the original CO 2 content due to depressurisation and boiling as the fluids ascended to the surface. Consequently, the soil has persisted as the major (99%) pathway of CO 2 release to the atmosphere from the high temperature reservoir at Ohaaki. The CO 2 flux and heat flow surveys indicate that despite 20 a of production the variability in location, spatial extent and magnitude of CO 2 flux remains consistent with established geochemical and geophysical models of the Ohaaki Field. At both OHW and OHE carbon isotopic analyses of soil gas indicate a two-stage fractionation process for moderate-flux (>60 g m −2 d −1 ) sites; boiling during fluid ascent within the underlying reservoir and isotopic enrichment as CO 2 diffuses through porous media of the soil zone. For high-flux sites (>300 g m −2 d −1 ), the δ 13 CO 2 signature (−7.4 ± 0.3‰ OHW and −6.5 ± 0.6‰ OHE) is unaffected by near-surface (soil zone) fractionation processes and reflects the composition of the boiled magmatic CO 2 source for each respective upflow. Flux thresholds of <30 g m −2 d −1 for purely diffusive gas transport, between 30 and 300 g m −2 d −1 for combined diffusive–advective transport, and ⩾300 g m −2 d −1 for purely advective gas transport at Ohaaki were assigned. δ 13 CO 2 values and cumulative probability plots of CO 2 flux data both identified a threshold of ∼15 g m −2 d −1 by which background (atmospheric and soil respired) CO 2 may be differentiated from hydrothermal CO 2 .

Taupo Volcanic Zone↗

USGS2018

Characterization of water quality in Bushy Park Reservoir, South Carolina, 2013–15

The Bushy Park Reservoir is the principal water supply for 400,000 people in the greater Charleston, South Carolina, area, which includes homes as well as businesses and industries in the Bushy Park Industrial Complex. Charleston Water System and the U.S. Geological Survey conducted a cooperative study during 2013–15 to assess the circulation of Bushy Park Reservoir and its effects on water-quality conditions, specifically, recurring taste-and-odor episodes. This report describes the water-quality data collected for the study that included a combination of discrete water-column sampling at seven locations in the reservoir and longitudinal water-quality profiling surveys of the reservoir and tributaries to characterize the temporal and spatial water-quality dynamics of Bushy Park Reservoir. Water-quality profiling surveys were conducted with an autonomous underwater vehicle equipped with a multiparameter water-quality-sonde bulkhead. Data collected by the autonomous underwater vehicle included water temperature, dissolved oxygen, pH, specific conductance, turbidity, total chlorophyll as fluorescence (estimate of algal biomass), and phycocyanin as fluorescence (estimate of cyanobacteria biomass) data. Characterization of the water-quality conditions in the reservoir included comparison to established State nutrient guidelines, identification of any spatial and seasonal variation in water-quality conditions and phytoplankton community structures, and assessment of the degree of influence of water-quality conditions related to Foster Creek and Durham Canal inflows, especially during periods of elevated taste-and-odor concentrations. Depth-profile and autonomous underwater vehicle survey data were used to identify areas within the reservoir where greater phytoplankton and cyanobacteria densities were most likely occurring. Water-quality survey results indicated that Bushy Park Reservoir tended to stratify thermally at a depth of about 20 feet from June to early October. The stratification was limited to the deeper portions of the reservoir near the dam and often dissipated within the reservoir near the CWS intake less than a mile upstream from the dam. Where thermally stratified, a corresponding depletion of dissolved oxygen also occurred at about the same depth and resulted in an anoxic hypolimnion below the 25-foot depth and an increase in specific conductance, likely due to re-mobilized metals and phosphorus under reducing conditions. In general, chlorophyll estimated from fluorescence exhibited some spatial variation, but no strong consistent pattern or “hot spot” was observed. Phycocyanin, estimated from relative fluorescence unit output as blue-green algae cell density, periodically seemed to be greater in the upper portion of the reservoir, but those differences may be attributed to increased turbidity and the potential change in phytoplankton community structure that affects fluorescence. Increased phycocyanin was observed at about the 10-foot depth during the summer months. A constant production of 2-methylisoborneol (MIB) near the dam and geosmin in the middle and upper portions of the reservoir appears to be occurring during the summer and early fall in the reservoir, but concentrations of these compounds tend to be between 10 and 15 nanograms per liter, which is at the Charleston Water System treatment threshold. At the Bushy Park Reservoir intake, the dominant taste-and-odor compound tended to be MIB, measured at a 2- or 3-to-1 ratio with geosmin during the summer and fall. During springtime episodes, however, when taste-and-odor compound concentrations typically are elevated above the Charleston Water System treatment threshold, the spatial distribution of geosmin concentrations greater than 15 nanograms per liter (28 to 38 nanograms per liter) was best explained by in situ production in the lower portion of the Bushy Park Reservoir near the dam rather than transport from Foster Creek. This pattern seems to indicate a possible shift in phytoplankton communities (or, at least, cyanobacteria communities) from MIB producers to geosmin producers. The spatial and seasonal assessment of water-quality conditions in Bushy Park Reservoir identified seasonal differences in water chemistry and spatial differences between the upper and lower portions of the reservoir that correspond to the location of elevated geosmin concentrations. On the basis of the spatial and seasonal assessment of actinomycetes concentrations compared to taste-and-odor compound concentrations, cyanobacteria production likely was the dominant source of the taste-and-odor episodes rather than actinomycetes. The lack of spatial and seasonal patterns in actinomycetes concentrations did not correspond to the springtime geosmin concentrations that were elevated above the Charleston Water System treatment threshold in the lower portion of the reservoir. Additionally, actinomycetes concentrations, although ubiquitous, had a median of about 9 and maximum of about 20 colonies per milliliter, which can be considered low for elevated taste-and-odor compound production. Nonetheless, the potential exists for actinomycetes to be a secondary source of taste-and-odor production and could explain some of the ubiquitous occurrence of low-level taste-and-odor production, such as MIB concentrations, observed throughout the summer and early fall months. When evaluated by biovolume, cyanobacteria were not the dominant phytoplankton group in Bushy Park Reservoir during the study period. Dolichospermum planctonicum (previously Anabaena planktonica ) was the dominant genera of the cyanobacteria group during spring periods. The geosmin-producing genera that were identified in the 2014 and 2015 spring communities in Bushy Park Reservoir were not observed in the 1999 and 2000 algal taxonomic data. A more robust examination of phytoplankton species was conducted by using a multivariate analysis that identified seasonal changes in phytoplankton community structure. These seasonal phytoplankton communities appeared to be explained by seasonal changes in water chemistry and may be responsible for episodes of taste-and-odor occurrence, especially geosmin. The most probable source of geosmin identified during the study was D. planctonicum . In a synoptic sampling event during a taste-and-odor episode in April 2015, cyanobacteria, not acinomycetes, also was indicated to be the more prevalent source of the geosmin. Although the Edisto River intake and its associated supply tunnel to the treatment facility had relatively high actinomycetes concentrations (130 and 140 colonies per milliliter, respectively) compared to the Bushy Park intake and tunnel (2 colonies per milliliter), corresponding geosmin concentrations were below 5 nanograms per liter for source water from the Edisto River intake and tunnel. Elevated geosmin concentrations above the Charleston Water System treatment threshold were identified in source waters from the Bushy Park Reservoir. The cyanobacteria community at the sampled sites in April 2015 was statistically similar to the community in the Bushy Park Reservoir in April 2014, when geosmin concentrations also were elevated. The only geosmin-producing genus identified at the Bushy Park intake, however, was D. planctonicum .

South Carolina↗

USGS2024

Assessment of water levels, nitrate, and arsenic in the Carson Valley Alluvial Aquifer and the development of a data visualization tool for the Carson River Basin, Nevada

Residents of Carson Valley, Douglas County, Nevada, rely on the basin-fill alluvial aquifer underlying the valley for drinking water. Since the 1980s, groundwater levels and water-quality data have been collected to monitor the status of the aquifer system and to assist in planning efforts to address current (2024) and future demand. The U.S. Geological Survey (USGS), in cooperation with Douglas County, Nevada, evaluated trends in water levels, nitrate, and arsenic concentrations from a network of monitoring and domestic wells in Carson Valley. This work also assessed the monitoring well network to determine the suitability of wells for characterizing the occurrence of arsenic in the groundwater. Monitoring of constituents, such as nitrate and arsenic concentrations, is needed to assess changes in contaminant distribution and to evaluate the effect that changing land use and groundwater pumping has on their occurrence and transport. Results of the trend analysis indicate water levels are declining ( p <0.05) in 17 of 26 selected monitoring wells (65 percent). Areas with the largest change in water levels, with more than 20 feet of declines, were within the community areas of Johnson Lane, Ruhenstroth, South Agricultural, East Valley, and Fish Springs. Variations in water levels measured in wells from the Central Agricultural, Minden, Foothill, Alpine County (one well), and Gardnerville Ranchos areas show periods of increase and decrease over time, but they also maintain long-term declining trends ( p <0.05). Increases in nitrate concentrations in groundwater samples collected from 9 out of 14 selected monitoring wells (64 percent) are statistically significant ( p <0.05) within the Ruhenstroth, Gardnerville Ranchos, East Valley, Genoa, and Johnson Lane community areas. Samples collected from a well in Indian Hills/Jacks Valley indicated a decreasing trend in nitrate concentration over time. Nitrate concentrations in samples collected from wells in East Valley, Genoa, Johnson Lane, and Indian Hills/Jack Valley were consistently low (less than 3 milligrams per liter [mg/L]) and stable. Nitrate concentrations from selected wells in Johnson Lane and Garnerville Ranchos exceeded the U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL) of 10 mg/L (as nitrogen) and have trends that are increasing over time. In 2022, a sample collected from Johnson Lane had a concentration (7.3 mg/L) below the MCL with an increasing trend over time. Temporal trend analyses for groundwater arsenic concentrations in Carson Valley could not be done because of a lack of temporal data. However, using available historical data, arsenic concentrations seem to be greater in groundwater from wells located on the eastern and northern areas of the valley than in wells located on the western or southern areas. Groundwater arsenic concentrations exceed 5 micrograms per liter (μg/L) in most samples collected from wells in Johnson Lane, Airport, Central Agricultural, and East Valley areas and in many cases exceed the U.S. Environmental Protection Agency (EPA) MCL of 10 μg/L. Data indicate that groundwater from domestic wells screened at deeper intervals are likely more vulnerable to elevated arsenic concentrations than shallower wells. A groundwater network evaluation for Carson Valley identified potential modifications in the sampling locations and frequency to better understand the effect of groundwater pumping in communities where municipal and domestic demand are greatest, potentially enhancing understanding of contaminant transport in these areas. Potential modifications to the active well network include reducing the frequency of sample collection from existing network wells (6 out of 11) that have consistently shown low and stable nitrate concentrations, adding wells in areas where data are sparse, and increasing the number of wells in areas with elevated groundwater nitrate concentrations. Including the analysis of arsenic in samples from the active groundwater monitoring well network will provide more detail on the temporal and spatial variability of arsenic concentrations. A visualization tool for the Carson River Basin was developed to provide access to discrete and near real-time hydrologic and water-quality data. The Carson River Basin Hydro Mapper (CBH; U.S. Geological Survey, 2023b) shows active and historical discrete water levels measured by the USGS and the State of Nevada Division of Water Resources, discrete groundwater nitrate and arsenic concentration data collected by the USGS, near real-time streamflow, and surface water levels for select waterbodies. The hydrologic data in the CBH provides resource managers, the public, and the scientific community with an easily accessible tool to present and communicate the most up-to-date information available about local and basin-wide water resources.

Nevada↗

USGS2011

Status and understanding of groundwater quality in the San Diego Drainages Hydrogeologic Province, 2004: California GAMA Priority Basin Project

Groundwater quality in the approximately 3,900-square-mile (mi 2 ) San Diego Drainages Hydrogeologic Province (hereinafter San Diego) study unit was investigated from May through July 2004 as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is located in southwestern California in the counties of San Diego, Riverside, and Orange. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory. The GAMA San Diego study was designed to provide a statistically robust assessment of untreated-groundwater quality within the primary aquifer systems. The assessment is based on water-quality and ancillary data collected by the USGS from 58 wells in 2004 and water-quality data from the California Department of Public Health (CDPH) database. The primary aquifer systems (hereinafter referred to as the primary aquifers) were defined by the depth interval of the wells listed in the California Department of Public Health (CDPH) database for the San Diego study unit. The San Diego study unit consisted of four study areas: Temecula Valley (140 mi 2 ), Warner Valley (34 mi 2 ), Alluvial Basins (166 mi 2 ), and Hard Rock (850 mi 2 ). The quality of groundwater in shallow or deep water-bearing zones may differ from that in the primary aquifers. For example, shallow groundwater may be more vulnerable to surficial contamination than groundwater in deep water-bearing zones. This study had two components: the status assessment and the understanding assessment. The first component of this study-the status assessment of the current quality of the groundwater resource-was assessed by using data from samples analyzed for volatile organic compounds (VOC), pesticides, and naturally occurring inorganic constituents, such as major ions and trace elements. The status assessment is intended to characterize the quality of groundwater resources within the primary aquifers of the San Diego study unit, not the treated drinking water delivered to consumers by water purveyors. The second component of this study-the understanding assessment-identified the natural and human factors that affect groundwater quality by evaluating land use, well construction, and geochemical conditions of the aquifer. Results from these evaluations were used to help explain the occurrence and distribution of selected constituents in the study unit. Relative-concentrations (sample concentration divided by benchmark concentration) were used as the primary metric for relating concentrations of constituents in groundwater samples to water-quality benchmarks for those constituents that have Federal and (or) California benchmarks. For organic and special-interest constituents, relative-concentrations were classified as high (> 1.0), moderate (> 0.1 and ≤1.0), and low (≤0.1). For inorganic constituents, relative concentrations were classified as high (> 1.0), moderate (> 0.5 and ≤1.0), and low (≤0.5). Grid-based and spatially weighted approaches were then used to evaluate the proportion of the primary aquifers (aquifer-scale proportions) with high, moderate, and low relative-concentrations for individual compounds and classes of constituents. One or more of the inorganic constituents with health-based benchmarks were high (relative to those benchmarks) in 17.6 percent of the primary aquifers in the Temecula Valley, Warner Valley, and Alluvial Basins study areas (hereinafter also collectively referred to as the Alluvial Fill study areas because they are composed of alluvial fill aquifers), and in 25.0 percent of the Hard Rock study area. Inorganic constituents with health-based benchmarks that were frequently detected at high relative-concentrations included vanadium (V), arsenic (As), and boron (B). Vanadium and As concentrations were not significantly correlated to either urban or agricultural land use indicating natural sources as the primary contributors of these constituents to groundwater. The positive correlation of B concentration to urban land-use was significant which indicates that anthropogenic activities are a contributing source of B to groundwater. The correlation of V, As and B concentrations to pH was positive, indicating that in alkaline groundwater these constituents are being desorbed from, or being inhibited from adsorbing to, particle surfaces. Inorganic constituents with aesthetic benchmarks that were detected at high relative-concentrations include manganese (Mn), iron (Fe), and total dissolved solids (TDS). In the Alluvial Fill study areas, Mn and TDS were detected at high relative-concentrations in 13.7 percent of the primary aquifers, and Fe in 6.9 percent. In the Hard Rock study area, Mn was detected at high relative-concentrations in 33.3 percent of the primary aquifers, and TDS in 16.7 percent; Fe was not detected at high relative-concentrations. Total dissolved solids concentrations were significantly correlated to agricultural land use suggesting that agricultural practices are a contributing source of TDS to groundwater. Manganese and Fe concentrations were highest in groundwater with low dissolved oxygen and pH indicating that the reductive dissolution of oxyhydroxides may be an important mechanism for the mobilization of Mn and Fe in groundwater. TDS concentrations were highest in shallow wells and in modern (< 50 yrs) groundwater which indicates anthropogenic activities as a source of TDS concentrations in groundwater. The relative-concentrations of organic constituents with health-based benchmarks were high in 3.0 percent of the primary aquifers in the Alluvial Fill study areas. A single detection in the Alluvial Basins study area of the discontinued gasoline oxygenate methyl tert-butyl ether (MTBE) was the only organic constituent detected at a high relative-concentration; high relative-concentrations of these constituents were not detected in the Hard Rock study area. Twelve of 88 VOCs and 14 of 123 pesticides and pesticide degradates analyzed in grid wells were detected. Chloroform was the only VOC detected in more than 10 percent of the grid wells. The herbicides simazine, atrazine, and prometon were each detected in greater than 10 percent of the grid wells. Perchlorate was detected in 22 percent of the grid wells sampled. The understanding assessment showed a significant correlation of trihalomethanes (THMs) and solvents to urban land-use, indicating that detections of these constituents are more likely to occur in groundwater underlying urbanized areas of the study unit. MTBE concentrations were negatively correlated to the distance from the nearest leaking underground fuel tank, indicating that point sources are the most significant contributing factor for MTBE concentrations to groundwater in the study unit. The positive correlation of THM and herbicide concentrations to modern groundwater was significant, as was the negative correlation of herbicide concentrations to pH and anoxic groundwater. The negative correlation of herbicides to pH and anoxic groundwater was likely due to the fact that these constituents were detected more frequently in shallow wells where groundwater conditions tend to be oxic with relatively low pH.

California↗

USGS2016

Groundwater contaminant plume maps and volumes, 100-K and 100-N Areas, Hanford Site, Washington

This study provides an independent estimate of the areal and volumetric extent of groundwater contaminant plumes which are affected by waste disposal in the 100-K and 100-N Areas (study area) along the Columbia River Corridor of the Hanford Site. The Hanford Natural Resource Trustee Council requested that the U.S. Geological Survey perform this interpolation to assess the accuracy of delineations previously conducted by the U.S. Department of Energy and its contractors, in order to assure that the Natural Resource Damage Assessment could rely on these analyses. This study is based on previously existing chemical (or radionuclide) sampling and analysis data downloaded from publicly available Hanford Site Internet sources, geostatistically selected and interpreted as representative of current (from 2009 through part of 2012) but average conditions for groundwater contamination in the study area. The study is limited in scope to five contaminants—hexavalent chromium, tritium, nitrate, strontium-90, and carbon-14, all detected at concentrations greater than regulatory limits in the past. All recent analytical concentrations (or activities) for each contaminant, adjusted for radioactive decay, non-detections, and co-located wells, were converted to log-normal distributions and these transformed values were averaged for each well location. The log-normally linearized well averages were spatially interpolated on a 50 × 50-meter (m) grid extending across the combined 100-N and 100-K Areas study area but limited to avoid unrepresentative extrapolation, using the minimum curvature geostatistical interpolation method provided by SURFER ® data analysis software. Plume extents were interpreted by interpolating the log-normally transformed data, again using SURFER ® , along lines of equal contaminant concentration at an appropriate established regulatory concentration . Total areas for each plume were calculated as an indicator of relative environmental damage. These plume extents are shown graphically and in tabular form for comparison to previous estimates. Plume data also were interpolated to a finer grid (10 × 10 m) for some processing, particularly to estimate volumes of contaminated groundwater. However, hydrogeologic transport modeling was not considered for the interpolation. The compilation of plume extents for each contaminant also allowed estimates of overlap of the plumes or areas with more than one contaminant above regulatory standards. A mapping of saturated aquifer thickness also was derived across the 100-K and 100–N study area, based on the vertical difference between the groundwater level (water table) at the top and the altitude of the top of the Ringold Upper Mud geologic unit, considered the bottom of the uppermost unconfined aquifer. Saturated thickness was calculated for each cell in the finer (10 × 10 m) grid. The summation of the cells’ saturated thickness values within each polygon of plume regulatory exceedance provided an estimate of the total volume of contaminated aquifer, and the results also were checked using a SURFER ® volumetric integration procedure. The total volume of contaminated groundwater in each plume was derived by multiplying the aquifer saturated thickness volume by a locally representative value of porosity (0.3). Estimates of the uncertainty of the plume delineation also are presented. “Upper limit” plume delineations were calculated for each contaminant using the same procedure as the “average” plume extent except with values at each well that are set at a 95-percent upper confidence limit around the log-normally transformed mean concentrations, based on the standard error for the distribution of the mean value in that well; “lower limit” plumes are calculated at a 5-percent confidence limit around the geometric mean. These upper- and lower-limit estimates are considered unrealistic because the statistics were increased or decreased at each well simultaneously and were not adjusted for correlation among the well distributions (i.e., it is not realistic that all wells would be high simultaneously). Sources of the variability in the distributions used in the upper- and lower-extent maps include time varying concentrations and analytical errors. The plume delineations developed in this study are similar to the previous plume descriptions developed by U.S. Department of Energy and its contractors. The differences are primarily due to data selection and interpolation methodology. The differences in delineated plumes are not sufficient to result in the Hanford Natural Resource Trustee Council adjusting its understandings of contaminant impact or remediation.

Washington↗

USGS2014

Spatially explicit habitat models for 28 fishes from the Upper Mississippi River System (AHAG 2.0)

Environmental management actions in the Upper Mississippi River System (UMRS) typically require pre-project assessments of predicted benefits under a range of project scenarios. The U.S. Army Corps of Engineers (USACE) now requires certified and peer-reviewed models to conduct these assessments. Previously, habitat benefits were estimated for fish communities in the UMRS using the Aquatic Habitat Appraisal Guide (AHAG v.1.0; AHAG from hereon). This spreadsheet-based model used a habitat suitability index (HSI) approach that drew heavily upon Habitat Evaluation Procedures (HEP; U.S. Fish and Wildlife Service, 1980) by the U.S. Fish and Wildlife Service (USFWS). The HSI approach requires developing species response curves for different environmental variables that seek to broadly represent habitat. The AHAG model uses species-specific response curves assembled from literature values, data from other ecosystems, or best professional judgment. A recent scientific review of the AHAG indicated that the model’s effectiveness is reduced by its dated approach to large river ecosystems, uncertainty regarding its data inputs and rationale for habitat-species response relationships, and lack of field validation (Abt Associates Inc., 2011). The reviewers made two major recommendations: (1) incorporate empirical data from the UMRS into defining the empirical response curves, and (2) conduct post-project biological evaluations to test pre-project benefits estimated by AHAG. Our objective was to address the first recommendation and generate updated response curves for AHAG using data from the Upper Mississippi River Restoration-Environmental Management Program (UMRR-EMP) Long Term Resource Monitoring Program (LTRMP) element. Fish community data have been collected by LTRMP (Gutreuter and others, 1995; Ratcliff and others, in press) for 20 years from 6 study reaches representing 1,930 kilometers of river and >140 species of fish. We modeled a subset of these data (28 different species; occurrences at sampling sites as observed in day electrofishing samples) using multiple logistic regression with presence/absence responses. Each species’ probability of occurrence, at each sample site, was modeled as a function of 17 environmental variables observed at each sample site by LTRMP standardized protocols. The modeling methods used (1) a forward-selection process to identify the most important predictors and their relative contributions to predictions; (2) partial methods on the predictor set to control variance inflation; and (3) diagnostics for LTRMP design elements that may influence model fits. Models were fit for 28 species, representing 3 habitat guilds (Lentic, Lotic, and Generalist). We intended to develop “systemic models” using data from all six LTRMP study reaches simultaneously; however, this proved impossible. Thus, we “regionalized” the models, creating two models for each species: “Upper Reach” models, using data from Pools 4, 8, and 13; and “Lower Reach” models, using data from Pool 26, the Open River Reach of the Mississippi River, and the La Grange reach of the Illinois River. A total of 56 models were attempted. For any given site-scale prediction, each model used data from the three LTRMP study reaches comprising the regional model to make predictions. For example, a site-scale prediction in Pool 8 was made using data from Pools 4, 8, and 13. This is the fundamental nature and trade-off of regionalizing these models for broad management application. Model fits were deemed “certifiably good” using the Hosmer and Lemeshow Goodness-of-Fit statistic (Hosmer and Lemeshow, 2000). This test post-partitions model predictions into 10 groups and conducts inferential tests on correspondences between observed and expected probability of occurrence across all partitions, under Chi-square distributional assumptions. This permits an inferential test of how well the models fit and a tool for reporting when they did not (and perhaps why). Our goal was to develop regionalized models, and to assess and describe circumstances when a good fit was not possible. Seven fish species composed the Lentic guild. Good fits were achieved for six Upper Reach models. In the Lower Reach, no model produced good fits for the Lentic guild. This was due to (1) lentic species being much less prominent in the Lower Reach study areas, and (2) those that do express greater prominence principally do so only in the La Grange reach of the Illinois River. Thus, developing Lower Reach models for Lentic species will require parsing La Grange from the other two Lower Reach study areas and fitting separate models. We did not do that as part of this study, but it could be done at a later time. Nine species comprised the Lotic guild. Good fits were achieved for seven Upper Reach models and six Lower Reach models. Four species had good fits for both regions (flathead catfish, blue sucker, sauger, and shorthead redhorse). Three species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (blue catfish, rock bass, and skipjack herring). Twelve species comprised the Generalist guild. Good fits were achieved for five Upper Reach models and eight Lower Reach models. Six species had good fits for both regions (brook silverside, emerald shiner, freshwater drum, logperch, longnose gar, and white bass). Two species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (red shiner and blackstripe topminnow). Poorly fit models were almost always due to the diagnostic variable “field station,” a surrogate for river mile. In these circumstances, the residuals for “field station” were non-randomly distributed and often strongly ordered. This indicates either fitting “pool scale” models for these species and regions, or explicitly model covariances between “field station” and the other predictors within the existing modeling framework. Further efforts on these models should seek to resolve these issues using one of these two approaches. In total, nine species, representing two of the three guilds (Lotic and Generalist), produced well-fit models for both regions. These nine species should comprise the basis for AHAG 2.0. Additional work, likely requiring downscaling of the regional models to pool-scale models, will be needed to incorporate additional species. Alternately, a regionalized AHAG could be comprised of those species, per region, that achieved well-fit models. The number of species and the composition of the regional species pools will differ among regions as a consequence. Each of these alternatives has both pros and cons, and managers are encouraged to consider them fully before further advancing this approach to modeling multi-species habitat suitability.

Upper Mississippi River System↗