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Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the eastern United States

This assessment was conducted to fulfill the requirements of section 712 of the Energy Independence and Security Act of 2007 and to conduct a comprehensive national assessment of storage and flux (flow) of carbon and the fluxes of other greenhouse gases in ecosystems of the Eastern United States. These carbon and greenhouse gas variables were examined for major terrestrial ecosystems (forests, grasslands/shrublands, agricultural lands, and wetlands) and aquatic ecosystems (rivers, streams, lakes, estuaries, and coastal waters) in the Eastern United States in two time periods: baseline (from 2001 through 2005) and future (projections from the end of the baseline through 2050). The Great Lakes were not included in this assessment due to a lack of input data. The assessment was based on measured and observed data collected by the U.S. Geological Survey and many other agencies and organizations and used remote sensing, statistical methods, and simulation models.

Professional Paper↗

Linking urbanization to the Biological Condition Gradient (BCG) for stream ecosystems in the Northeastern United States using a Bayesian network approach

Urban development alters important physical, chemical, and biological processes that define urban stream ecosystems. An approach was developed for quantifying the effects of these processes on aquatic biota, and then linking those effects to endpoints that can be used for environmental management. These complex, interacting systems are challenging to model from a scientific standpoint. A desirable model clearly shows the system, simulates the interactions, and ultimately predicts results of management actions. Traditional regression techniques that calculate empirical relations between pairs of environmental factors do not capture the interconnected web of multiple stressors, but urban development effects are not yet understood at the detailed scales required to make mechanistic modeling approaches feasible. Therefore, in contrast to a fully deterministic or fully statistical modeling approach, a Bayesian network model provides a hybrid approach that can be used to represent known general associations between variables while acknowledging uncertainty in predicted outcomes. It does so by quantifying an expert-elicited network of probabilistic relations between variables. Advantages of this modeling approach include (1) flexibility in accommodating many model specifications and information types; (2) efficiency in storing and manipulating complex information, and to parameterize; and (3) transparency in describing the relations using nodes and arrows and in describing uncertainties with discrete probability distributions for each variable. In realization of the aforementioned advantages, a Bayesian network model was constructed to characterize the effect of urban development on aquatic macroinvertebrate stream communities through three simultaneous, interacting ecological pathways affecting stream hydrology, habitat, and water quality across watersheds in the Northeastern United States. This model incorporates both empirical data and expert knowledge to calculate the probabilities of attaining desired aquatic ecosystem conditions under different urban stress levels, environmental conditions, and management options. Ecosystem conditions are characterized in terms of standardized Biological Condition Gradient (BCG) management endpoints. This approach to evaluating urban development-induced perturbations in watersheds integrates statistical and mechanistic perspectives, different information sources, and several ecological processes into a comprehensive description of the system that can be used to support decision making. The completed model can be used to infer which management actions would lead to the highest likelihood of desired BCG tier achievement. For example, if best management practices (BMP) were implemented in a highly urbanized watershed to reduce flashiness to medium levels and specific conductance to low levels, the stream would have a 70-percent chance of achieving BCG Tier 3 or better, relative to a 24-percent achievement likelihood for unmanaged high urban land cover. Results are reported probabilistically to account for modeling uncertainty that is inherent in sources such as natural variability and model simplification error.

Scientific Investigations Report↗

Documentation of single-well aquifer tests and integrated borehole analyses, Pahute Mesa and Vicinity, Nevada

Single-well aquifer testing has been carried out at Pahute Mesa in southern Nevada since 1962. These tests include single-well pumping and slug tests to estimate geologic formation hydraulic properties. Initially, aquifer tests focused on identifying low-permeability rocks suitable for testing large-yield nuclear devices, whereas later hydrologic investigations focused on potential subsurface transport of radionuclides away from Pahute Mesa. The number of single-well aquifer tests analyzed for Pahute Mesa and vicinity was much greater than the number of actual tests because each response to a water-level displacement was interpreted multiple times using different analytical models by different investigators, which were reported as distinct, individual aquifer tests. Some aquifer tests also were reinterpreted multiple times because the wells had not been defined uniquely. Previous databases and reports identified wells by different borehole names, reported various depths to top and bottom of open intervals, and used inconsistent wetted-aquifer thicknesses, which were coupled with inappropriate analytical methods to interpret aquifer-test data. This work standardized the reporting of single-well aquifer-test results at Pahute Mesa and vicinity. A hydraulic-parameter database was created that uniquely identifies tested wells, reports all replicated aquifer tests in each well, and identifies the best transmissivity estimate for each well. Datasets, interpreted models, and results from 1,459 analyses are presented and evaluated for 360 unique wells. Integrated borehole analyses were used to estimate hydraulic conductivity by depth in Pahute Mesa because vertical variations in hydraulic conductivity greatly affect groundwater velocities, which directly affect subsurface transport rates and directions. The integrated analyses reconciled differences between transmissivity estimated from pumping tests and the summed transmissivity from straddle-packer slug tests done at different depth intervals in a borehole. An integration borehole database was created that presents integrated aquifer-test results from 17 boreholes.

Nevada↗

Model documentation for relations between continuous real-time and discrete water-quality constituents in Indian Creek, Johnson County, Kansas, June 2004 through May 2013

Johnson County is the fastest growing county in Kansas, with a population of about 560,000 people in 2012. Urban growth and development can have substantial effects on water quality, and streams in Johnson County are affected by nonpoint-source pollutants from stormwater runoff and point-source discharges such as municipal wastewater effluent. Understanding of current (2014) water-quality conditions and the effects of urbanization is critical for the protection and remediation of aquatic resources in Johnson County, Kansas and downstream reaches located elsewhere. The Indian Creek Basin is 194 square kilometers and includes parts of Johnson County, Kansas and Jackson County, Missouri. Approximately 86 percent of the Indian Creek Basin is located in Johnson County, Kansas. The U.S. Geological Survey, in cooperation with Johnson County Wastewater, operated a series of six continuous real-time water-quality monitoring stations in the Indian Creek Basin during June 2011 through May 2013; one of these sites has been operating since February 2004. Five monitoring sites were located on Indian Creek and one site was located on Tomahawk Creek. The purpose of this report is to document regression models that establish relations between continuously measured water-quality properties and discretely collected water-quality constituents. Continuously measured water-quality properties include streamflow, specific conductance, pH, water temperature, dissolved oxygen, turbidity, and nitrate. Discrete water-quality samples were collected during June 2011 through May 2013 at five new sites and June 2004 through May 2013 at a long-term site and analyzed for sediment, nutrients, bacteria, and other water-quality constituents. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to estimate concentrations of those constituents of interest that are not easily measured in real time because of limitations in sensor technology and fiscal constraints. Regression models for 28 water-quality constituents were developed and documented. The water-quality information in this report is important to Johnson County Wastewater because it allows the concentrations of many potential pollutants of interest, including nutrients and sediment, to be estimated in real time and characterized during conditions and time scales that would not be possible otherwise.

Kansas↗

A Streamflow Statistics (StreamStats) Web Application for Ohio

A StreamStats Web application was developed for Ohio that implements equations for estimating a variety of streamflow statistics including the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year peak streamflows, mean annual streamflow, mean monthly streamflows, harmonic mean streamflow, and 25th-, 50th-, and 75th-percentile streamflows. StreamStats is a Web-based geographic information system application designed to facilitate the estimation of streamflow statistics at ungaged locations on streams. StreamStats can also serve precomputed streamflow statistics determined from streamflow-gaging station data. The basic structure, use, and limitations of StreamStats are described in this report. To facilitate the level of automation required for Ohio's StreamStats application, the technique used by Koltun (2003)1 for computing main-channel slope was replaced with a new computationally robust technique. The new channel-slope characteristic, referred to as SL10-85, differed from the National Hydrography Data based channel slope values (SL) reported by Koltun (2003)1 by an average of -28.3 percent, with the median change being -13.2 percent. In spite of the differences, the two slope measures are strongly correlated. The change in channel slope values resulting from the change in computational method necessitated revision of the full-model equations for flood-peak discharges originally presented by Koltun (2003)1. Average standard errors of prediction for the revised full-model equations presented in this report increased by a small amount over those reported by Koltun (2003)1, with increases ranging from 0.7 to 0.9 percent. Mean percentage changes in the revised regression and weighted flood-frequency estimates relative to regression and weighted estimates reported by Koltun (2003)1 were small, ranging from -0.72 to -0.25 percent and -0.22 to 0.07 percent, respectively.

Scientific Investigations Report↗

Simulation of selected ground-water pumping scenarios at Fort Stewart and Hunter Army Airfield, Georgia

A regional MODFLOW ground-water flow model of parts of coastal Georgia, Florida, and South Carolina was used to evaluate the effects of current and hypothetical groundwater withdrawal, and the relative effects of pumping in specific areas on ground-water flow in the Upper Floridan aquifer near Fort Stewart and Hunter Army Airfield (HAAF), coastal Georgia. Simulation results for four steady-state pumping scenarios were compared to each other and to a Base Case condition. The Base Case represents year 2000 pumping rates throughout the model area, with the exception that permitted annual average pumping rates for the year 2005 were used for 26 production wells at Fort Stewart and HAAF. The four pumping scenarios focused on pumping increases at HAAF resulting from projected future demands and additional personnel stationed at the facility and on reductions in pumping at Fort Stewart. Scenarios A and B simulate 1- and 2-million-gallon-perday (Mgal/d) increases, respectively, at HAAF. Simulated water-level change maps for these scenarios indicate an area of influence that extends into parts of Bryan, Bulloch, Chatham, Effingham, and Liberty Counties, Ga., and Beaufort and Jasper Counties, S.C., with maximum drawdowns from 0.5 to 4 feet (ft) for scenario A and 1 to 8 ft for Scenario B. For scenarios C and D, increases in pumping at HAAF were offset by decreases in pumping at Fort Stewart. Scenario C represents a 1-Mgal/d increase at HAAF and a 1-Mgal/d decrease at Fort Stewart; simulated water-level changes range from 0.4 to -4 ft. Scenario D represents a 2-Mgal/d increase at HAAF and 2-Mgal/d decrease at Fort Stewart; simulated water-level changes range from 0.04 to -8 ft. The simulated water-level changes indicate an area of influence that extends into parts of Bryan, Bulloch, Chatham, Effingham, Liberty, and McIntosh Counties, Ga., and Jasper and Beaufort Counties, S.C. In general, decreasing pumping at Fort Stewart by an equivalent amount to pumping increases at HAAF reduced the magnitude and extent of drawdown resulting from the additional pumping. None of the scenarios resulted in large changes in the configuration of the simulated potentiometric surface and related ground-water flow directions. The scenarios simulated vary from the original model only by increasing pumpage less than 1 percent of the total calibrated model withdrawals. The changes in pumpage are located near the center of the original model area. Thus, the scenarios described in this report are considered to be reasonable with no less uncertainty than the original calibrated model.

Georgia↗

Potential distribution of the viral haemorrhagic septicaemia virus in the Great Lakes region

Viral haemorrhagic septicaemia virus (VHSV) genotype IVb has been responsible for large-scale fish mortality events in the Great Lakes of North America. Anticipating the areas of potential VHSV occurrence is key to designing epidemiological surveillance and disease prevention strategies in the Great Lakes basin. We explored the environmental features that could shape the distribution of VHSV, based on remote sensing and climate data via ecological niche modelling. Variables included temperature measured during the day and night, precipitation, vegetation, bathymetry, solar radiation and topographic wetness. VHSV occurrences were obtained from available reports of virus confirmation in laboratory facilities. We fit a Maxent model using VHSV-IVb reports and environmental variables under different parameterizations to identify the best model to determine potential VHSV occurrence based on environmental suitability. VHSV reports were generated from both passive and active surveillance. VHSV occurrences were most abundant near shore sites. We were, however, able to capture the environmental signature of VHSV based on the environmental variables employed in our model, allowing us to identify patterns of VHSV potential occurrence. Our findings suggest that VHSV is not at an ecological equilibrium and more areas could be affected, including areas not in close geographic proximity to past VHSV reports.

Great Lakes↗

Strontium isotope geochemistry of soil and playa deposits near Yucca Mountain, Nevada

The isotopic composition of strontium contained in the carbonate fractions of soils provides an excellent tracer which can be used to test models for their origin. This paper reports data on surface coatings and cements, eolian sediments, playas and alluvial fan soils which help to constrain a model for formation of the extensive calcretes and fault infillings in the Yucca Mountain region. The playas contain carbonate with a wide range of strontium compositions; further work will be required to fully understand their possible contributions to the pedogenic carbonate system. Soils from an alluvial fan to the west of Yucca Mountain show that only small amounts of strontium are derived from a fan draining a carbonate terrane have strontium component. Although much evidence points to an eolian source for at least some of the strontium in the pedogenic carbonates near Yucca Mountain, an additional component or past variation of strontium composition in the eolian source is required to model the pedogenic carbonate system

Nevada↗

Lidar estimation of storage capacity for managed water resources used by Desert Bighorn Sheep (Ovis canadensis mexicana) at Cabeza Prieta National Wildlife Refuge, Arizona

In cooperation with the U.S. Fish and Wildlife Service, the U.S. Geological Survey Southwest Biological Science Center employed ground-based light detection and ranging (lidar) during February 2022 to help meet two resource management objectives at the Cabeza Prieta National Wildlife Refuge (CPNWR), Arizona. The two objectives are (1) characterize the water storage capacity for one developed and two modified tanks, which are bedrock catchments also referred to as tinajas, that are important water sources for desert bighorn sheep ( Ovis canadensis mexicana ) in designated wilderness at the CPNWR; and (2) develop a stage-storage model to estimate water volumes from monitoring observations of water surface levels in each tank. We measured storage capacity for the three tanks identified by refuge managers, Buckhorn, Senita, and Eagle, using ground-based lidar collected during February 2022. These data produced high-resolution (centimeter scale) topographic models that improved estimates of maximum water storage capacity over previous geometry-based estimates, permitting estimations of storage capacity at multiple water surface levels (stage heights). We found that the maximum water storage capacity for the Buckhorn, Senita, and Eagle tanks was 9,108.730, 8,623.308, and 6,039.603 US gallons (gal), respectively. For each tank we report a stage-storage model based on a polynomial function that best explained variability in water storage capacity as a function of water stage height. The results presented herein will permit the CPNWR managers to (1) easily estimate water available for wildlife at any point of time, (2) interpret tank recharge following rainstorms, and (3) decide whether and when to transport water via vehicles to mechanically refill the tanks in designated wilderness.

Arizona↗

A satellite model of Southwestern Willow Flycatcher ( Empidonax traillii extimus ) breeding habitat and a simulation of potential effects of tamarisk leaf beetles ( Diorhabda spp.), southwestern United States

Executive Summary The study described in this report represents the first time that a satellite model has been used to identify potential Southwestern Willow Flycatcher ( Empidonax traillii extimus ) (hereinafter referred to as “flycatcher”) breeding habitat rangewide for 2013–15. Fifty-seven Landsat scenes were required to map the entire range of the flycatcher, encompassing parts of six States and more than 1 billion 30-meter pixels. Predicted flycatcher habitat was summarized in a hierarchical fashion from largest to smallest: regionwide, State, U.S. Fish and Wildlife Service (FWS) management unit, 7.5-minute quadrangle, and critical-habitat reach. The term “predicted habitat” is used throughout this report to distinguish areas the satellite model predicts as suitable flycatcher habitat from what may actually exist on the ground. A rangewide accuracy assessment was done with 758 territories collected in 2014, and change detection was done with yearly habitat maps to identify how and where habitat changed over time. Additionally, effects of tamarisk leaf beetles ( Diorhabda spp.) on flycatcher habitat were summarized for the lower Virgin River from 2010 to 2015, and simulations of how tamarisk leaf beetles may affect flycatcher habitat in the lower Colorado and upper Gila Rivers were done for 2015. Model results indicated that the largest areas of predicted flycatcher habitat at elevations below 1,524 meters were in New Mexico and Arizona, areas followed in descending order by California, Texas, Nevada, Utah, and Colorado. By FWS management unit, the largest area of flycatcher habitat during all 3 years were the Middle Rio Grande (New Mexico), followed by the Upper Gila (Arizona and New Mexico) and Middle Gila/San Pedro (Arizona) management units. The area of predicted flycatcher habitat varied considerably in 7.5-minute quadrangles, ranging from 0 to1,398 hectares (ha). Averaged across 3 years, the top three producing quadrangles were Paraje Well (New Mexico), San Marcial (New Mexico), and San Carlos Reservoir (Arizona). The top three FWS critical-habitat reaches in 2015 were Rio Grande-middle (9,544 ha), San Pedro River (1,779 ha), and Gila River-mid San Carlos (1,356 ha); this ranking did not change in 2013 or 2014. Change detection among years showed a large shift in predicted flycatcher habitat influenced by drought patterns, with California habitat decreasing and New Mexico habitat increasing. An accuracy assessment indicated that 88 percent of territories were correctly classified at a 40 percent probability threshold, with an exponential relationship between territory densities and five probability classes. A spatially explicit analysis indicated that beetles decreased predicted flycatcher habitat 94.2 percent from 2010 to 2015 along the lower Virgin River, with only 5.8 percent persisting. In contrast, beetle simulations indicated that 64.1 percent of habitat will persist along the lower Colorado River and 45 percent will persist along the upper Gila River. This project shows that the satellite model adequately predicts flycatcher habitat rangewide, but it lacks the ability to predict which patches will be occupied in a given year. The next logical step is the development of an occupancy model that ties the habitat predictions of the satellite model to patch occupancy so managers can better allocate their resources for survey and restoration activities. Finally, the methods presented in this report seem well suited for automated mapping applications and cloud-based resources.

Open-File Report↗

Upscaling of U (VI) desorption and transport from decimeter‐scale heterogeneity to plume‐scale modeling

Scientifically defensible predictions of field scale U(VI) transport in groundwater requires an understanding of key processes at multiple scales. These scales range from smaller than the sediment grain scale (less than 10 μm) to as large as the field scale which can extend over several kilometers. The key processes that need to be considered include both geochemical reactions in solution and at sediment surfaces as well as physical transport processes including advection, dispersion, and pore-scale diffusion. The research summarized in this report includes both experimental and modeling results in batch, column and tracer tests. The objectives of this research were to: (1) quantify the rates of U(VI) desorption from sediments acquired from a uranium contaminated aquifer in batch experiments;(2) quantify rates of U(VI) desorption in column experiments with variable chemical conditions, and(3) quantify nonreactive tracer and U(VI) transport in field tests.

Colorado↗

Potential effects of sea level rise on nearshore habitat availability for surf smelt (Hypomesus pretiosus) and eelgrass (Zostera marina), Puget Sound, Washington

In this study we examine the potential effects of three predicted sea level rise (SLR) scenarios on the nearshore eelgrass ( Zostera marina L.) and surf smelt ( Hypomesus pretiosus ) spawning habitats along a beach on Bainbridge Island, Washington. Baseline bathymetric, geomorphological, and biological surveys were conducted to determine the existing conditions at the study site. The results of these surveys were coupled with a predictive model that estimates SLR-induced changes to coastal ecosystems based upon local topography and land-cover data. This model simulates the changes in nearshore habitat through time. The model inputs for SLR are probable values reported by the Intergovernmental Panel on Climate Change, and by user-defined values. The predicted effects of SLR are presented as (1) habitat type change and (2) the graphic response of developed dry land depicting the influence of shoreline armoring. This report describes the geophysical and biological characteristics at the Bainbridge Island study site, the modeling methods used to produce depictions of habitat changes, and a possible decrease in surf smelt spawning and an increase in eelgrass habitat availability in response to increases in sea level.

Washington↗

A-DROP: A predictive model for the formation of oil particle aggregates (OPAs)

Oil–particle interactions play a major role in removal of free oil from the water column. We present a new conceptual–numerical model, A-DROP, to predict oil amount trapped in oil–particle aggregates. A new conceptual formulation of oil–particle coagulation efficiency is introduced to account for the effects of oil stabilization by particles, particle hydrophobicity, and oil–particle size ratio on OPA formation. A-DROP was able to closely reproduce the oil trapping efficiency reported in experimental studies. The model was then used to simulate the OPA formation in a typical nearshore environment. Modeling results indicate that the increase of particle concentration in the swash zone would speed up the oil–particle interaction process; but the oil amount trapped in OPAs did not correspond to the increase of particle concentration. The developed A-DROP model could become an important tool in understanding the natural removal of oil and developing oil spill countermeasures by means of oil–particle aggregation.

Marine Pollution Bulletin↗

Environmental systems and management activities on the Kennedy Space Center, Merritt Island, Florida: results of a modeling workshop

In the early 1960's, the National Aeronautics and Space Administration (NASA) began purchasing 140,000 acres on Merritt Island, Florida, in order to develop a center for space exploration. Most of this land was acquired to provide a safety and security buffer around NASA facilities. NASA, as the managing agency for the Kennedy Space Center (KSC), is responsible for preventing or controlling environmental pollution from the Federal facilities and activities at the Space Center and is committed to use all practicable means to protect and enhance the quality of the surrounding environment. The Merritt Island National Wildlife Refuge was established in 1963 when management authority for undeveloped lands at KSC was transferred to the U.S. Fish and Wildlife Service. In addition to manage for 11 Federally-listed threatened and endangered species and other resident and migratory fish and wildlife populations, the Refuge has comanagement responsibility for 19,000 acres of mosquito control impoundments and 2,500 acres of citrus groves. The Canaveral National Seashore was developed in 1975 when management of a portion of the coastal lands was transferred from NASA to the National Park Service. This multiagency jurisdiction on Merritt Island has resulted in a complex management environment. The modeling workshop described in this report was conducted May 21-25, 1984, at the Kennedy Space Center to: (1) enhance communication among the agencies with management responsibilities on Merritt Island; (2) integrate available information concerning the development, management, and ecology of Merritt Island; and (3) identify key research and monitoring needs associated with the management and use of the island's resources. The workshop was structured around the formulation of a model that would simulate primary management and use activities on Merritt Island and their effects on upland, impoundment, and estuarine vegetation and associated wildlife. The simulation model is composed of four connected submodels. The Uplands submodel calculates changes in acres and structural components of vegetation communities resulting from succession, fire, facilities development, and shuttle launch depositions, as well as the quantity and quality of surface runoff and aquifer input to an impoundment and an estuary. The Impoundment submodel next determines water quality and quantity and changes in vegetation resulting from water level manipulation and prescribed burning. The Estuary submodel than determines water quality parameters and acres of seagrass beds. Finally, the Wildlife submodel calculates habitat suitability indices for key species of interest, based on vegetation conditions in the uplands and impoundments and on several hydrologic parameters. The model represents a hypothetical management unit with 2,500 acres of uplands, a 600-acre impoundment, and a 1,500-acre section of estuary. Two management scenarios were run to analyze model behavior. The scenarios differ in the frequency of shuttle launches and prescribed burning, the extent of facilities development, the amount of land disposed waste material applied, and the nature and timing of impoundment water level control. Early in a model development project, the process of building the model is usually of greater benefit than the model itself. The model building process stimulates interaction among agencies, assists in integrating existing information, and helps identify research needs. These benefits usually accrue even in the absence of real predictive power in the resulting model. Open communication occurs among the Federal, State, and local agencies involved with activities on Merritt Island and the agencies have a cooperative working relationship. The workshop provided an opportunity for all of these agencies to meet at one time and have focused discussions on the key environmental and multiagency resource management issues. The workshop framework helped to integrate information and assumptions from a number of disciplines and agencies. This integration occurred in the computer simulation model and among workshop participants as submodel linkages were developed and scenario results discussed. A number of research needs were identified at the workshop during the model building and testing exercises and associated discussions. These needs were based on the informed judgement of researchers and managers familiar with Merritt Island or similar areas, rather than on a comprehensive literature review of sensitivity analysis of the preliminary model developed at the workshop. Some of the needs can be addressed by interpreting the results of completed studies from similar geographic areas as they relate to Merritt Island, while other will require additional research studies on Merritt Island. Major research needs associated with the Upland submodel include behavior of the near-surface aquifer, factors limiting slash pine regeneration, frequency and effects of natural fire on various cover types, cumulative effects of shuttle launches, and fate in upland soils of nitrogen and phosphorous from land applied waste material. Key Impoundment submodel needs include documentation of vegetation changes in response to altered water depth, salinity, and nutrient concentrations and better specification of the functional characteristics of impoundments as chemical filters. Important information gaps identified in the Estuary submodel include a more complete analysis of factors contributing to phytoplankton abundance, evaluation of sources of turbidity other than phytoplankton, and identification and quantification of factors limiting seagrass distribution. Primary research needs associated with the Wildlife submodel include a survey of breeding habitat, production data, and harvest data for mottled ducks; data on the emigration and immigration of juvenile mullet (and other transient fish) in the impoundment; the contribution of various seagrasses to habitat requirements of sea trout; and the effects of dissolved oxygen on survival of juvenile sea trout. Ideally, the modeling workshop process is iterative in nature. Periods between workshops are used for research, data collection, and model refinement. Each workshop integrates information collected since the last workshop and produces a more credible model that is more useful in evaluating management alternatives. Participants felt that continued application of this process would help provide ongoing integration and communication among agencies and would allow each agency's planning and management activities to be viewed within the context of an overall assessment.

Report↗

Groundwater withdrawals and regional flow paths at and near Willow Grove and Warminster, Pennsylvania—Data compilation and preliminary simulations for conditions in 1999, 2010, 2013, 2016, and 2017

In 2014, groundwater samples from residential and public supply wells in the vicinity of two former U.S. Navy bases at Willow Grove and Warminster, and an active Air National Guard Station at Horsham, Bucks and Montgomery Counties, Pennsylvania, were found to have concentrations of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), which are per- and polyfluoroalkyl substances (PFAS), above U.S. Environmental Protection Agency (EPA) provisional health advisory (HA) levels for drinking water. Five supply wells near the bases were shut down because of PFAS contamination. In 2016, after EPA established a Lifetime HA for PFAS in drinking water that is lower than the provisional HA in place in 2014, at least 13 additional supply wells near the bases were shut down because of PFAS contamination. At the request of the U.S. Navy, and in consultation with other Federal and State agencies and local stakeholders, the U.S. Geological Survey used historical and recent data on well withdrawals, recharge rates, aquifer properties, groundwater levels, and stream base flow to evaluate regional groundwater-flow paths from identified areas of PFAS groundwater contamination or potential PFAS sources at the bases. Groundwater withdrawals near the bases from public supply and other large wells decreased substantially from the 1990s to 2017, increasing the proportion of groundwater recharge that discharged to local streams. A preliminary groundwater-flow model, calibrated using 1,009 groundwater levels and 17 stream base flow estimates, simulated regional flow paths from the bases and showed that recharge at the bases discharged to withdrawal wells and local streams, generally within a mile or two of the bases. Supply and remediation wells at the bases captured some of the recharge on base areas of possible PFAS contamination, whereas other base recharge was simulated to flow to nearby public supply wells and streams, depending on water use and aquifer recharge conditions between 1999 and 2017. The locations of many residential wells near the bases that were identified by the Navy and Air National Guard as having elevated PFAS concentrations were generally consistent with the simulated flow paths from possible sources at the bases. However, there are some areas of observed PFAS contamination where no flow paths from base sources were simulated. Additionally, no data were available on PFAS concentrations in groundwater in some areas of simulated flow paths from base sources. Data and models used for this study are provided in this report and in digital data releases to support further investigations and model revisions.

Pennsylvania↗

Potential postwildfire debris-flow hazards—A prewildfire evaluation for the Jemez Mountains, north-central New Mexico

Wildfire can substantially increase the probability of debris flows, a potentially hazardous and destructive form of mass wasting, in landscapes that have otherwise been stable throughout recent history. Although the exact location, extent, and severity of wildfire or subsequent rainfall intensity and duration cannot be known, probabilities of fire and debris‑flow occurrence for given locations can be estimated with geospatial analysis and modeling. The purpose of this report is to provide information on which watersheds might constitute the most serious potential debris - flow hazards in the event of a large - scale wildfire and subsequent rainfall in the Jemez Mountains. Potential probabilities and estimated volumes of postwildfire debris flows in both the unburned and previously burned areas of the Jemez Mountains and surrounding areas were estimated using empirical debris - flow models developed by the U.S. Geological Survey in combination with fire behavior and burn probability models developed by the U.S. Forest Service. Of the 4,998 subbasins modeled for this study, computed debris-flow probabilities in 671 subbasins were greater than 80 percent in response to the 100 - year recurrence interval, 30-minute duration rainfall event. These subbasins ranged in size from 0.01 to 6.57 square kilometers (km 2 ), with an average area of 0.29 km 2 , and were mostly steep, upstream tributaries to larger channels in the area. Modeled debris-flow volumes in 465 subbasins were greater than 10,000 cubic meters (m 3 ), and 14 of those subbasins had modeled debris‑flow volumes greater than 100,000 m 3 . The rankings of integrated relative debris - flow hazard indexes for each subbasin were generated by multiplying the individual subbasin values for debris - flow volume, debris‑flow probability, and average burn probability. The subbasins with integrated hazard index values in the top 2 percent typically are large, upland tributaries to canyons and channels primarily in the Upper Rio Grande and Rio Grande-Santa Fe watershed areas. No subbasins in this group have basin areas less than 1.0 km 2 . Many of these areas already had significant mass‑wasting episodes following the Las Conchas Fire in 2011. Other subbasins with integrated hazard index values in the top 2 percent are scattered throughout the Jemez River watershed area, including some subbasins in the interior of the Valles Caldera. Only a few subbasins in the top integrated hazard index group are in the Rio Chama watershed area. This prewildfire assessment approach is valuable to resource managers because the analysis of the debris-flow threat is made before a wildfire occurs, which facilitates prewildfire management, planning, and mitigation. In north‑central New Mexico, widespread watershed restoration efforts are being done to safeguard vital watersheds against the threat of catastrophic wildfire. This study was designed to help select ideal locations for the restoration efforts that could have the best return on investment.

New Mexico↗

Improving regression-model-based streamwater constituent load estimates derived from serially correlated data

A regression-model based approach is a commonly used, efficient method for estimating streamwater constituent load when there is a relationship between streamwater constituent concentration and continuous variables such as streamwater discharge, season and time. A subsetting experiment using a 30-year dataset of daily suspended sediment observations from the Mississippi River at Thebes, Illinois, was performed to determine optimal sampling frequency, model calibration period length, and regression model methodology, as well as to determine the effect of serial correlation of model residuals on load estimate precision. Two regression-based methods were used to estimate streamwater loads, the Adjusted Maximum Likelihood Estimator (AMLE), and the composite method, a hybrid load estimation approach. While both methods accurately and precisely estimated loads at the model’s calibration period time scale, precisions were progressively worse at shorter reporting periods, from annually to monthly. Serial correlation in model residuals resulted in observed AMLE precision to be significantly worse than the model calculated standard errors of prediction. The composite method effectively improved upon AMLE loads for shorter reporting periods, but required a sampling interval of at least 15-days or shorter, when the serial correlations in the observed load residuals were greater than 0.15. AMLE precision was better at shorter sampling intervals and when using the shortest model calibration periods, such that the regression models better fit the temporal changes in the concentration–discharge relationship. The models with the largest errors typically had poor high flow sampling coverage resulting in unrepresentative models. Increasing sampling frequency and/or targeted high flow sampling are more efficient approaches to ensure sufficient sampling and to avoid poorly performing models, than increasing calibration period length.

Illinois↗

A digital model for simulation of ground-water hydrology in the Houston area, Texas

This report documents the construction and calibration of a digital model for the simulation of hydrologic conditions in the Chicot and Evangeline aquifers in the Houston area of southeastern Texas. The model is a five-layer finite-difference model, with a grid pattern of 63 x 67 nodes representing an area of 27,000 square miles, for simulation of three- dimensional ground-water flow. The hydrologic properties and processes modeled were ground-water withdrawals, transmissivities, storage coefficients of the aquifers and clays, quantity of water derived from storage in the clays, and vertical hydraulic conductivity and vertical leakage. The model, which simulates water-level declines, changes in storage in the clay layers, and land-surface subsidence, was calibrated by use of historical records from 1890 to 1975. It is very sensitive to variations in transmissivities and to variations in water-table and artesian storage. It is less sensitive to variations in clay storage.

Texas↗