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At least 1,243 records · Page 69Linked to original sources

Profiles of reservoir properties of oil-bearing plays for selected petroleum provinces in the United States

Profiles of reservoir properties of oil-bearing plays for selected petroleum provinces in the United States were developed to characterize the database to be used for a potential assessment by the U.S. Geological Survey (USGS) of oil that would be technically recoverable by the application of enhanced oil recovery methods using injection of carbon dioxide (CO 2 -EOR). The USGS assessment methodology may require reservoir-level data for the purposes of screening conventional oil reservoirs and projecting CO 2 -EOR performance in terms of the incremental recoverable oil. The information used in this report is based on reservoir properties from the “Significant Oil and Gas Fields of the United States Database” prepared by Nehring Associates, Inc. (2012). As described by Nehring Associates, Inc., the database “covers all producing provinces (basins) in the United States except the Appalachian Basin and the Cincinnati Arch.” Under contract to the USGS, INTEK, Inc., developed and applied algorithms to estimate variables useful in projecting EOR performance at the reservoir level and to complete some partial reservoir records of the “Significant Oil and Gas Fields of the United States Database” (Nehring Associates, Inc., 2012). The augmented database is referred to here as the “Comprehensive Resource Database” (CRD). The CRD play and province classification scheme corresponds to the definitions used in the 1995 USGS National Oil and Gas Assessment (NOGA). The profiles in this report consist of a resource table and a six-part figure showing the variation of reservoir parameters selected because of their importance in the choice of a miscible or immiscible method for CO 2 -EOR and in the assessment of potential oil recovery using the EOR processes. A subset of these reservoirs may be available for either miscible- or immiscible-type flooding for CO 2 -EOR. Plays with fewer than 10 oil reservoirs were not graphed and were omitted from the province profiles. For this report and for the purposes of screening reservoirs as candidates for the application of CO 2 -EOR methods, oil reservoirs must have no more than 10,000 standard cubic feet of natural gas per barrel of oil at surface conditions. Oil-bearing plays presented in this report must contain at least one oil reservoir so defined. The profile plots allow geologists to evaluate the range of empirical and default values of the oil reservoir characteristics within a play and across plays that belong to the same province in the CRD. For most plays, the default estimates can be identified by the stacking of points at a single value on strip charts in the profiles. Reasonable default values should be within the range of the reservoir parameter values assigned by Nehring Associates, Inc. (2012), to reservoirs of that particular play. Each province profile figure consists of five strip charts and a boxplot. The five strip charts display for individual plays the following reservoir-fluid and reservoir properties: A , oil density (American Petroleum Institute [API] gravity in degrees); B , computed pseudo-Dykstra-Parsons coefficient; C , reservoir porosity (in percent); D , reservoir permeability (in millidarcies); and E , estimates of the original oil in place (OOIP) per unit volume of reservoir rock (in barrels per acre-foot). The OOIP per unit volume of reservoir rock is an indicator of the relative richness of the oil reservoir and is derived from estimates in the CRD of OOIP, reservoir acreage, and net pay. The net pay is the interval of productive reservoir rock. The same data for OOIP per unit volume are graphed as a strip chart ( E ) and a boxplot ( F ).

Open-File Report↗

QRev—Software for computation and quality assurance of acoustic doppler current profiler moving-boat streamflow measurements—User’s manual for version 2.8

The software program, QRev computes the discharge from moving-boat acoustic Doppler current profiler measurements using data collected with any of the Teledyne RD Instrument or SonTek bottom tracking acoustic Doppler current profilers. The computation of discharge is independent of the manufacturer of the acoustic Doppler current profiler because QRev applies consistent algorithms independent of the data source. In addition, QRev automates filtering and quality checking of the collected data and provides feedback to the user of potential quality issues with the measurement. Various statistics and characteristics of the measurement, in addition to a simple uncertainty assessment are provided to the user to assist them in properly rating the measurement. QRev saves an extensible markup language file that can be imported into databases or electronic field notes software. The user interacts with QRev through a tablet-friendly graphical user interface. This report is the manual for version 2.8 of QRev.

Open-File Report↗

Concentration, flux, and trend estimates with uncertainty for nutrients, chloride, and total suspended solids in tributaries of Lake Champlain, 1990–2014

The U.S. Geological Survey, in cooperation with the New England Interstate Water Pollution Control Commission and the Vermont Department of Environmental Conservation, estimated daily and 9-month concentrations and fluxes of total and dissolved phosphorus, total nitrogen, chloride, and total suspended solids from 1990 (or first available date) through 2014 for 18 tributaries of Lake Champlain. Estimates of concentration and flux, provided separately in Medalie (2016), were made by using the Weighted Regressions on Time, Discharge, and Season (WRTDS) regression model and update previously published WRTDS model results with recent data. Assessment of progress towards meeting phosphorus-reduction goals outlined in the Lake Champlain management plan relies on annual estimates of phosphorus flux. The percent change in annual concentration and flux is provided for two time periods. The R package EGRETci was used to estimate the uncertainty of the trend estimate. Differences in model specification and function between this study and previous studies that used WRTDS to estimate concentration and flux using data from Lake Champlain tributaries are described. Winter data were too sparse and nonrepresentative to use for estimates of concentration and flux but were sufficient for estimating the percentage of total annual flux over the period of record. Median winter-to-annual fractions ranged between 21 percent for total suspended solids and 27 percent for dissolved phosphorus. The winter contribution was largest for all constituents from the Mettawee River and smallest from the Ausable River. For the full record (1991 through 2014 for total and dissolved phosphorus and chloride and 1993 through 2014 for nitrogen and total suspended solids), 6 tributaries had decreasing trends in concentrations of total phosphorus, and 12 had increasing trends; concentrations of dissolved phosphorus decreased in 6 and increased in 8 tributaries; fluxes of total phosphorus decreased in 5 and increased in 10 tributaries; and fluxes of dissolved phosphorus decreased in 4 and increased in 10 tributaries (where the number of increasing and decreasing trends does not add up to 18, the remainder of tributaries had no trends). Concentrations and fluxes of nitrogen decreased in 10 and increased in 4 tributaries and of chloride decreased in 2 and increased in 15 tributaries. Concentrations of total suspended solids decreased in 4 and increased in 8 tributaries, and fluxes of total suspended solids decreased in 3 and increased in 11 tributaries. Although time intervals for the percent changes from this report are not completely synchronous with those from previous studies, the numbers of and specific tributaries with overall negative percent changes in concentration and flux are similar. Concentration estimates of total phosphorus in the Winooski River were used to trace whether changes in trends between a previous study and the current study were due generally to differences in model specifications or differences from 4 years of additional data. The Winooski River analysis illustrates several things: that keeping all model specifications equal, concentration estimates increased from 2010 to 2014; the effects of a smoothing algorithm used in the current study that was not available previously; that narrowing model half-window widths increased year-to-year variations; and that the change from an annual to a 9-month basis by omitting winter estimates changed a few individual points but not the overall shape of the flow-normalized curve. Similar tests for other tributaries showed that the primary effect of differences in model specifications between the previous and current studies was perhaps to increase scatter over time but that changes in trends generally were the result of 4 years of additional data rather than artifacts of model differences.

New York, Vermont↗

Semiautomatic approaches to account for 3-D distortion of the electric field from local, near-surface structures in 3-D resistivity inversions of 3-D regional magnetotelluric data

This report summarizes the results of three-dimensional (3-D) resistivity inversion simulations that were performed to account for local 3-D distortion of the electric field in the presence of 3-D regional structure, without any a priori information on the actual 3-D distribution of the known subsurface geology. The methodology used a 3-D geologic model to create a 3-D resistivity forward (“known”) model that depicted the subsurface resistivity structure expected for the input geologic configuration. The calculated magnetotelluric response of the modeled resistivity structure was assumed to represent observed magnetotelluric data and was subsequently used as input into a 3-D resistivity inverse model that used an iterative 3-D algorithm to estimate 3-D distortions without any a priori geologic information. A publicly available inversion code, WSINV3DMT, was used for all of the simulated inversions, initially using the default parameters, and subsequently using adjusted inversion parameters. A semiautomatic approach of accounting for the static shift using various selections of the highest frequencies and initial models was also tested. The resulting 3-D resistivity inversion simulation was compared to the “known” model and the results evaluated. The inversion approach that produced the lowest misfit to the various local 3-D distortions was an inversion that employed an initial model volume resistivity that was nearest to the maximum resistivities in the near-surface layer.

Open-File Report↗

Evaluation of recommended revisions to Bulletin 17B

For the past 36 years, Bulletin 17B, published by the Interagency Committee on Water Data in 1982, has guided flood-frequency analyses in the United States. During this period, much has been learned about both hydrology and statistical methods. In keeping with the tradition of periodically updating the Bulletin 17B guidelines in light of advances in our understanding and methods, the Hydrologic Frequency Analysis Work Group (HFAWG) was charged by the Subcommittee on Hydrology (SOH) of the Advisory Committee on Water Information (ACWI) to consider possible updates to Bulletin 17B. The purpose of this report is to consider the statistical performance of possible revisions to Bulletin 17B procedures. Of particular interest are procedures designed to accommodate more general forms of flood information. The concern is how the proposed procedures would affect the precision, accuracy and robustness of flood-frequency estimates. The investigations reported here focus on techniques for the following: incorporating information related to historical flooding that occurred outside the period of systematic streamgaging; and identification of potentially influential low floods (PILFs). The proposed changes, which mostly involve generalizing Bulletin 17B’s method-of-moments procedures by using the Expected Moments Algorithm (EMA), are relatively modest, at least in the sense that they would not affect the main features of Bulletin 17B. The proposed methods include the following: continued use of the log-Pearson Type 3 (LP3) distribution; continued use of the Method-of-Moments fitting method applied to the logarithms of annual-peak-flow data; and a generalization of the Grubbs-Beck test used in Bulletin 17B to identify low outliers. The new multiple Grubbs-Beck test is sensitive to multiple PILFs. The hydrological literature already provides extensive support for the theory behind the proposed changes. The remaining question is practical: How well do the proposed methods perform under typical and realistic conditions and, specifically, with difficult records occasionally encountered in practice? In order to answer these questions, the HFAWG commissioned the work reported here. The following four major sets of results are provided: Monte Carlo simulations of fitting procedures employing data drawn from simulated LP3 populations; Monte Carlo simulations of fitting procedures employing data drawn from non-LP3 populations that were selected to reflect likely deviations of flood series from LP3 distributions, based on the experience of HFAWG members; a direct comparison of the fitted LP3 distributions for 82 real “test sites” identified by an independent data group as both “typical” and “challenging” for flood-frequency estimation; and simulations of fitting procedures using records obtained by resampling with replacement from the longest of the 82 test-site records. Collectively, these studies provide a reasonably comprehensive, valid, and robust assessment of the properties of the Bulletin 17B methods and proposed alternatives. The experiments and analysis indicate that the flood quantile estimators, proposed as a revision of Bulletin 17B, do the following: perform generally as well as, and in some cases much better than, Bulletin 17B estimators in terms of the mean square error of flood quantiles estimates; allow for incorporation and efficient statistical treatment of broader classes of flood-frequency data and information, including historical information, binomial data and interval data; and generally confirm studies and the theoretical findings reported in the hydrological literature that would support use of updated estimation procedures that have been developed since Bulletin 17B was published.

Open-File Report↗

Using object-based image analysis to conduct high-resolution conifer extraction at regional spatial scales

The distribution and abundance of pinyon ( Pinus monophylla ) and juniper ( Juniperus osteosperma, J. occidentalis ) trees (hereinafter, "pinyon-juniper") in sagebrush ( Artemisia spp.) ecosystems of the Great Basin in the Western United States has increased substantially since the late 1800s. Distributional expansion and infill of pinyon-juniper into sagebrush ecosystems threatens the ecological function and economic viability of these ecosystems within the Great Basin, and is now a major contemporary challenge facing land and wildlife managers. Particularly, pinyon-juniper encroachment into intact sagebrush ecosystems has been identified as a primary threat facing populations of greater sage-grouse ( Centrocercus urophasianus ; hereinafter, "sage-grouse"), which is a sagebrush obligate species. Even seemingly innocuous scatterings of isolated pinyon-juniper in an otherwise intact sagebrush landscape can negatively affect survival and reproduction of sage-grouse. Therefore, accurate and high-resolution maps of pinyon-juniper distribution and abundance (indexed by canopy cover) across broad geographic extents would help guide land management decisions that better target areas for pinyon-juniper removal projects (for example, fuel reduction, habitat improvement for sage-grouse, and other sagebrush species) and facilitate science that further quantifies ecological effects of pinyon-juniper encroachment on sage-grouse populations and sagebrush ecosystem processes . Hence, we mapped pinyon-juniper (referred to as conifers for actual mapping) at a 1 × 1-meter (m) high resolution across the entire range of previously mapped sage-grouse habitat in Nevada and northeastern California. We used digital orthophoto quad tiles from National Agriculture Imagery Program (2010, 2013) as base imagery, and then classified conifers using automated feature extraction methodology with the program Feature Analyst ™ . This method relies on machine learning algorithms that extract features from imagery based on their spectral and spatial signatures. We classified conifers in 6,230 tiles and then tested for errors of omission and commission using confusion matrices. Accuracy ranged from 79.1 to 96.8, with an overall accuracy of 84.3 percent across all mapped areas. An estimated accuracy coefficient (kappa) indicated substantial to nearly perfect agreement, which varied across mapped areas. For this mapping process across the entire mapping extent, four sets of products are available at https://doi.org/10.5066/F7348HVC , including (1) a shapefile representing accuracy results linked to mapping subunits; (2) binary rasters representing conifer presence or absence at a 1 × 1 m resolution; (3) a 30 × 30 m resolution raster representing percentages of conifer canopy cover within each cell from 0 to 100; and (4) 1 × 1 m resolution canopy cover classification rasters derived from a 50-m-radius moving window analysis. The latter two products can be reclassified in a geographic information system (GIS) into user-specified bins to meet different objectives, which include approximations for phases of encroachment. These products complement, and in some cases improve upon, existing conifer maps in the Western United States, and will help facilitate sage-grouse habitat management and sagebrush ecosystem restoration.

California, Nevada↗

Visualization of groundwater withdrawals

Generating an informative display of groundwater withdrawals can sometimes be difficult because the symbols for closely spaced wells can overlap. An alternative method for displaying groundwater withdrawals is to generate a “footprint” of the withdrawals. WellFootprint version 1.0 implements the Footprint algorithm with two optional variations that can speed up the footprint calculation. ModelMuse has been modified in order to generate the input for WellFootprint and to read and graphically display the output from WellFootprint.

Open-File Report↗

Revised technical implementation plan for the ShakeAlert system—An earthquake early warning system for the West Coast of the United States

The U.S. Geological Survey (USGS), along with partner organizations, has developed an earthquake early warning (EEW) system called ShakeAlert for the highest risk areas of the United States: namely, California, Oregon, and Washington. The purpose of the system is to reduce the impact of earthquakes and save lives and property by providing alerts to institutional users and the public. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Alerts can then be sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking. ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System. However, these networks were not originally designed for EEW; old equip­ment needs to be updated and new stations must be added to construct EEW-capable networks. The ShakeAlert data-processing infrastructure includes redundant servers that are geographically distributed at monitoring centers in Seattle, Washington, as well as Menlo Park, Berkeley, and Pasadena in California. Three data-processing layers collect raw ground-motion data from field stations (data layer), analyze these data to estimate the area and intensity of the resulting shaking (production layer), and publish alert products as appropriate for end users (alert layer). The alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission, infrastructure, or expertise to perform public notifications and is therefore recruiting technology enablers from the private sector. Additionally, ShakeAlert will coordinate with both public and private partners to accomplish consistent and ongoing public communication, education, and outreach. The estimated cost of completing the ShakeAlert infrastructure and sensor networks is \$39.4 million and has an estimated annual operation and maintenance cost of \$28.6 million per year. Building a highly reliable data telemetry infrastructure would cost another \$20.5 million and operating this telemetry system would add \$49.8 million per year; however, these costs could be reduced if project partners provide bandwidth on existing systems.

Open-File Report↗

VS30 at three strong-motion recording stations in Napa and Napa County, California — Main Street in downtown Napa, Napa fire station number 3, and Kreuzer Lane — Calculations determined from s-wave refraction tomography and multichannel analysis of surface waves (Rayleigh and Love)

The August 24, 2014, moment magnitude ( M w ) 6.0 South Napa earthquake caused an estimated $400 million in structural damage to the City of Napa, California. In 2015, we acquired high-resolution P- and S-wave seismic data near three strong-motion recording stations in Napa County where high peak ground accelerations (PGAs) were recorded during the South Napa earthquake. In this report, we present results from three sites—Main Street in Downtown Napa (Northern California Seismic Network station, NCSN N016), Napa Fire Station Number 3 (National Strong Motion Project station, NSMP 1765), and Kreuzer Lane (station KRE, temporary deployment). To characterize the recording sites in terms of shallow-depth shear-wave velocities ( V S ), we used both surface waves (Rayleigh and Love) and body waves (S-wave) to evaluate the time-averaged V S in the upper 30 meters of the subsurface ( V S30 ). We used two-dimensional multichannel analysis of surface waves (MASW) to evaluate V S from the surface waves, and a refraction tomography inversion algorithm, developed by Hole in 1992, to evaluate V S from the body waves. As determined by the various methods, we found V S30 near the strong-motion recording stations on Main Street in Downtown Napa, Napa Fire Station Number 3, and on Kreuzer Lane to be from 281 meters per second (m/s) to 286 m/s, 297 to 371 m/s, and 885 to 916 m/s, respectively. The V S30 calculated from Love waves were slightly lower (10 m/s) than those calculated from Rayleigh waves at the Downtown Napa location and at Napa Fire Station Number 3 (4 m/s); however, V S30 calculated from Love waves was higher (190 m/s) than those calculated from Rayleigh waves at Kreuzer Lane. We also found that V S30 determined from MASW for both Love and Rayleigh waves varied depending on the number of shots along the profiles, and V S30 was not systematic based on the number of shots used in the analysis. Furthermore, V S30 calculated from S-wave refraction tomography are closer to those determined from MASW calculated from Love waves than from using Rayleigh waves.

California↗

VS30 at three strong-motion recording stations in Napa and Solano Counties, California — Lovall Valley Road, Broadway Street and Sereno Drive in Vallejo, and Vallejo Fire Station — Calculations determined from S-wave refraction tomography and multichannel analysis of surface waves (Rayleigh and Love)

The August 24, 2014, moment magnitude ( M w ) 6.0 South Napa earthquake caused an estimated $400 million in structural damage to the City of Napa, California. In 2015, we acquired high-resolution P- and S-wave seismic data near three strong-motion recording stations in Napa and Solano Counties where high peak ground accelerations (PGAs) were recorded during the South Napa earthquake. In this report, we present results from three sites—Lovall Valley Loop Road in Napa County (Northern California Seismic Network station, NCSN N019B) and Broadway Street and Sereno Drive (California Geological Survey station, CGS 68294) and Vallejo Fire Station (National Strong Motion Project station, NSMP 1759) in the City of Vallejo, California. To characterize the recording sites in terms of shallow-depth, shear-wave velocities ( V S ), we used both surface waves (Rayleigh and Love) and body waves (S-wave) to evaluate the time-averaged V S in the upper 30 meters of the subsurface ( V S30 ). We used two-dimensional (2D) multichannel analysis of surface waves (MASW) to evaluate V S from surface waves, and a refraction tomography inversion algorithm, developed by Hole in 1992, to evaluate V S from the body waves. As determined by the tomography and MASW analysis for Love waves, we found V S30 near the strong-motion recording stations at Lovall Valley Loop Road, Broadway Street and Sereno Drive, and the Vallejo Fire Station to be from 711 meters per second (m/s) to 767 m/s, 455 to 673 m/s, and 490 to 583 m/s, respectively. We found that V S30 determined from Love waves were higher than those determined from Rayleigh waves at the Lovall Valley Loop Road recording site (221 m/s higher) and at the Vallejo Fire Station site (62 and 48 m/s higher); however, V S30 from Love waves was lower than those from Rayleigh waves at the Broadway Street and Sereno Drive site (78 m/s lower). We also found that V S30 varied depending on the number of shot points used in our MASW analysis for both Love and Rayleigh waves. Furthermore, V S30 values determined from S-wave refraction tomography are generally closer to those determined from MASW using Love waves than those determined using Rayleigh waves.

California↗

Optimizing historical preservation under climate change—An overview of the optimal preservation model and pilot testing at Cape Lookout National Seashore

Adapting cultural resources to climate-change effects challenges traditional cultural resource decision making because some adaptation strategies can negatively affect the integrity of cultural resources. Yet, the inevitability of climate-change effects—even given the uncertain timing of those effects—necessitates that managers begin prioritizing resources for climate-change adaptation. Prioritization imposes an additional management challenge: managers must make difficult tradeoffs to achieve desired management outcomes related to maximizing the resource values. This report provides an overview of a pilot effort to integrate vulnerability (exposure and sensitivity), significance, and use potential metrics in a decision framework—the Optimal Preservation (OptiPres) Model—to inform climate adaptation planning of a subset of buildings in historic districts (listed on the National Register of Historic Places) at Cape Lookout National Seashore. The OptiPres Model uses a numerical optimization algorithm to assess the timing and application of a portfolio of adaptation actions that could most effectively preserve an assortment of buildings associated with different histories, intended uses, and construction design and materials over a 30-year planning horizon. The outputs from the different budget scenarios, though not prescriptive, provide visualizations of and insights to the sequence and type of optimal actions and the changes to individual building resource values and accumulated resource values. Study findings suggest the OptiPres Model has planning utility related to fiscal efficiency by identifying a budget threshold necessary to maintain the historical significance and use potential of historical buildings while reducing vulnerability (collectively, the accumulated resource value). Specifically, findings identify that a minimum of the industry standard ($222,000 annually for the 17 buildings) is needed to maintain the current accumulated resource value. Additionally, results suggest that additional appropriations provided on regular intervals when annual appropriations are at the industry standard are nearly as efficient as annual appropriations at twice the rate of industry standards and increase the amount of accumulated resource values to nearly the same level. However, periodic increases in funding may increase the risks posed to buildings from the probability of a natural hazard (that is, damage or loss from a hurricane). Suggestions for model refinements include developing standardized cost estimations for adaptation actions based on square footage and building materials, developing metrics to quantify the historical integrity of buildings, integrating social values data, including additional objectives (such as public safety) in the model, refining vulnerability data and transforming the data to include risk assessment, and incorporating stochastic events (that is, hurricane and wind effects) into the model.

North Carolina↗

Simulation of the probabilistic plume extent for a potential replacement wastewater-infiltration lagoon, and probabilistic contributing areas for supply wells for the Town of Lac du Flambeau, Vilas County, Wisconsin

An existing two-dimensional, steady-state groundwater-flow model of the shallow groundwater-flow system of the Lac du Flambeau Reservation in Vilas County, Wisconsin, originally developed by the U.S. Geological Survey, was used to simulate the potential for wastewater from a proposed relocation of a wastewater lagoon to contaminate the Lac du Flambeau Band of Lake Superior Chippewa’s drinking-water-supply wells. This simulation was completed by the U.S. Geological Survey in cooperation with the Lac du Flambeau Band of Lake Superior Chippewa and Indian Health Service. The simulated scenarios consisted of removing wastewater infiltration from existing lagoons and re-applying that infiltration at the proposed location. Two analyses were performed for the scenarios. First, the probable extent of the plume discharging from the proposed infiltration lagoons was mapped with a Monte Carlo algorithm that used uncertainty identified during the calibration process to simulate thousands of possible outcomes. Second, the Monte Carlo method was again used to simulate a probabilistic contributing area for the Tribe’s nearby “Main Pumphouse” supply wells. The purpose of the simulations was to evaluate the potential for infiltrated wastewater to be captured by the public-supply wells. Most features of the previously developed model remained unchanged, including calibrated parameters such as hydraulic conductivity and recharge. Thus, the same covariance distributions that were generated during calibration of the regional model (Juckem and others, 2014) remained unchanged and were used to inform the Monte Carlo simulations for the scenario simulations described in this report. The reader is encouraged to read the full report by Juckem and others (available at https://doi.org/10.3133/sir20145020 ) for a detailed description of the model design and calibration, as well as a description of the Monte Carlo method, its limitations, and the original results. Results for these new scenarios indicate that the probabilistic plume extent for the proposed infiltration lagoons does not reach the Main Pumphouse wells using pumping rates and wastewater volumes estimated for 2010. Similarly, the contributing area for the Main Pumphouse wells does not capture water from within the proposed infiltration lagoon footprint. However, at higher pumping rates and wastewater volumes, as projected by the Tribe for about 2035, the contributing area for the Main Pumphouse wells do include particles that originated within the proposed lagoon footprint, albeit at low probabilities. That is, for a few of the thousands of simulations that represented a range of calibration-informed parameter covariances, some amount of infiltrated wastewater was captured by the Main Pumphouse wells under projected 2035 conditions.

Wisconsin↗

Cliff Feature Delineation Tool and Baseline Builder version 1.0 user guide

Coastal cliffs constitute 80 percent of the world’s coastline, with seacliffs fronting a large proportion of the U.S. West Coast shoreline, particularly in California. Erosion of coastal cliffs can threaten infrastructure and human life, yet the spatial and temporal scope of cliff studies have been limited by cumbersome traditional methods that rely on the manual interpretation of seacliff features—especially seacliff toes and top edges. The Cliff Feature Delineation Tool (CFDT) and the Baseline Builder Tool are designed to increase the efficiency of deriving seacliff features from remote sensing datasets by utilizing an automated, quantitative approach that eliminates traditional interpretive methods and ensures reproducibility. This document functions as a user guide for operating the Cliff Feature Delineation Tool and Baseline Builder Tool and includes a walkthrough of data-visualization and data-review workflows for the tools’ three-dimensional (3D) cliff feature outputs. Also included is a brief overview of cliff feature delineation at the U.S. Geological Survey (USGS) and a detailed description of the tools’ algorithmic logic.

Open-File Report↗

Range-wide greater sage-grouse hierarchical monitoring framework—Implications for defining population boundaries, trend estimation, and a targeted annual warning system

Incorporating spatial and temporal scales into greater sage-grouse ( Centrocercus urophasianus ) population monitoring strategies is challenging and rarely implemented. Sage-grouse populations experience fluctuations in abundance that lead to temporal oscillations, making trend estimation difficult. Accounting for stochasticity is critical to reliably estimate population trends and investigate variation related to deterministic factors on the landscape, which are amenable to management action. Here, we describe a novel, range-wide hierarchical monitoring framework for sage-grouse centered on four objectives: (1) create a standardized database of lek counts, (2) develop spatial population structures by clustering leks, (3) estimate spatial trends at different temporal extents based on abundance nadirs (troughs), and (4) develop a targeted annual warning system to help inform management decisions. Using automated and repeatable methods (software), we compiled a lek database (as of 2019) that contained 262,744 counts and 8,421 unique lek locations from disparate state data. The hierarchical population units (clusters) included 13 nested levels, identifying biologically relevant units and population structure that minimized inter-cluster sage-grouse movements. With these products, we identified spatiotemporal variation in trends in population abundance using Bayesian state-space models. We estimated 37.0, 65.2, and 80.7-percent declines in abundance range-wide during short (17 years), medium (33 years), and long (53 years) temporal scales, respectively. However, some areas exhibited evidence of increasing trends in abundance in recent decades. Models predicted 12.3, 19.2, and 29.6 percent of populations (defined as clusters of neighboring leks) consisted of over 50-percent probability of extirpation at 19, 38, and 56-year projections from 2019, respectively, based on averaged annual rate of change in apparent abundance across two, four, and six oscillations (average period of oscillation is 9.4 years). At the lek level, models predicted 45.7, 60.1, and 78.0 percent of leks with over 50-percent extirpation probabilities over the same time periods, respectively, mostly located on the periphery of the species’ range. The targeted annual warning system automates annual identification of local populations exhibiting asynchronous decline relative to regional population patterns using simulated management actions and an optimization algorithm for evaluating range-wide stabilization of population abundance. In 2019, approximately 3.2 percent of leks and 2.0 percent of populations were identified by the targeted annual warning system for management intervention range-wide.

California, Colorado, Idaho, Montana, Nevada, Nort↗

Cape Romain partnership for coastal protection

This final report summarizes activities, outcomes, and lessons learned from a 3-year project titled “Climate Change Adaptation for Coastal National Wildlife Refuges” with the Cape Romain National Wildlife Refuge (NWR) and local partners in the surrounding South Carolina Lowcountry. The Lowcountry is classified as the 10-county area encompassing the coastal plain of South Carolina (this report specifically focuses on Berkeley, Charleston, and Georgetown Counties). The goals of this work, sponsored by the U.S. Geological Survey’s Southeast Climate Adaptation Science Center (SECASC), were to foster active engagement with stakeholders; to develop a comprehensive definition of adaptation problems faced by agencies, organizations, and individuals near the Cape Romain NWR that accounts for global change, local values, knowledge and perceptions; and to encourage social learning and building of effective networks and trust across South Carolina Lowcountry organizations and individuals. Although project scoping began at the scale of the Atlantic seaboard, by engaging with NWRs from Massachusetts to Florida, participating refuge personnel eventually selected the Cape Romain NWR to serve as a case study for testing our goals. The Cape Romain Partnership for Coastal Conservation was established to address global change impacts at a regional level and includes representation from Federal and State resource agencies, local conservation nongovernmental organizations, and organizations representing underserved community interests. Research topics, originating from discussions with Cape Romain Partnership for Coastal Conservation members, focused on quantifying key drivers of change including localized sea-level rise (SLR) predictions, estimates of coastal hurricane inundation as amplified by SLR, and urban growth trends and forecasts. These key drivers provided a foundation to engage stakeholders in planning exercises to begin a process of collective understanding and collaborative decision making. The goal of this process was to develop collective strategies of adaptation to enhance community and ecosystem resilience in the South Carolina Lowcountry. South Carolina’s Lowcountry is experiencing rapid environmental and social transformation because of SLR rates approaching twice the global average, chronic tidal flooding and catastrophic storm surges, erosion and loss of habitats that provide essential services to wildlife and humans, and increasing social polarization fueled by aggressive low-density urban growth and other forms of land conversion. To support characterizations of plausible future scenarios, we used available or, in some cases, developed new models to project future conditions of key environmental and social-economic drivers. Because of the imprecision of mean global SLR projections, the SECASC commissioned a climatological study to account for local conditions and multiple representative concentration pathways to project a tailored distribution of future sea levels. These projections were matched to SLR scenarios provided by existing models to anticipate the range of future coastal habitat changes in the South Carolina Lowcountry. SLR scenarios were also incorporated into existing storm-surge models, which do not account for alternate baseline sea levels, to project the local effects of future hurricanes. To evaluate the extent and effects of population growth and urban expansion, we relied on an existing urban-growth model to map the spatial distribution of land-conversion probabilities, the total area of which is predicted to increase twofold to threefold over the next 60 years. In addition to this simplified model, an econometric model is in development to account for nonlinear feedback dynamics in land value, land use, and ecosystem service production. Although not yet completed, the goals of this model are to produce more-detailed projections of growth dynamics and to allow predictions of development patterns resulting from alternate land-use planning policies and incentives. Collaborative planning for an uncertain future requires more than providing decision makers with information on future physical and ecological conditions; developing effective and consensual strategies must also integrate sociological values, multiple cultural perspectives, and an understanding of human behavior. To support broad stakeholder engagement in integrative approaches to adaptation planning, emphasis was placed on the importance of considering differences in how individuals perceive their environment and create meaning. Because cultural frameworks form the basis for perceptions and, ultimately, the behaviors of individuals and institutions, we describe a model of human behavior and how it can be used to understand the effect of cultural complexity and variation in perception on choices, behavioral change, and long-term maintenance of behaviors. We consider a model commonly used in the field of behavioral health that accommodates variation in human perception when describing stages of behavior and the dynamics of behavioral change. Tailoring communication and engagement activities to targeted stakeholders is likely to benefit from increased understanding of behavioral change processes. The complex nature of this problem limited the usefulness of a traditional decision-analytic approach, we explored alternative methods for engagement, collaborative learning and decision making. Recognizing that project partners and Lowcountry stakeholders may be at different stages of preparedness and interest level for modifying behavior as a function of global change, we facilitated a scenario-planning exercise to familiarize partners with this well-established approach for communicating the opportunities and threats arising under alternative, plausible futures. We developed narratives for four alternative South Carolina Lowcountry scenarios to be used in later strategic planning that focus on quantitative trends for three primary drivers with high impact and high uncertainty: manifestations of climate change, social-political shifts at a global level, and forces of local value and power structures. This scenario-planning exercise underscored the complex relation between the temporospatial scale of the production of ecological goods and services and the institutional scale at which they are managed. We then guided the partners through an assessment of the relevant strengths and weaknesses of the Cape Romain Partnership for Coastal Protection, using the threats and opportunities characterized by each scenario to understand how the partnership might respond when attempting to meet conservation and societal objectives. The partnership identified key strengths including partnership experience, outreach and technical capacities, a substantial conservation land base, and high social cohesion in the South Carolina Lowcountry. Limited communication expertise, institutional inertia, and insufficient staffing and funding were recognized as important weaknesses across the partnership. By examining and scoring combinations of internal strengths and weaknesses and external threats and opportunities, the partnership developed sets of prioritized strategies to consider in the context of a given scenario. Although we had insufficient time to examine all scenarios in detail, the intent was to identify a portfolio of strategic actions to address threats and opportunities represented in multiple plausible futures. Top-ranking strategies encompassed a range of actions that focused on strengthening the conservation community and communicating the benefits of nature (that is, ecosystem services) to leveraging partnerships to expand land protection. This report also details the methods and preliminary results of several models developed or applied in support of this project. Two parcel-selection algorithms were used to evaluate anticipated habitat changes and patterns of urban growth to guide decisions on optimal conservation reserve design to protect habitat communities. One approach used a widely available planning software (MARXAN) to maximize conservation benefits near the Cape Romain NWR, whereas the other approach was a novel application of economic theory to account for uncertainty in future conditions and for the risks of unanticipated habitat loss. This latter model applies modern portfolio theory to estimate the risk of investing in any portfolio of land parcels (that is, candidate “reserves”) under climate-change uncertainty by quantifying the variation and spatial correlation of conservation benefits derived from each portfolio. We expanded the range of actions beyond simply whether or not to invest in a set of land parcels, an approach commonly used in spatial conservation planning, to also include consideration of divestment from currently protected lands. Such refinements allow for better accounting of system dynamics and can evaluate the benefits of flexible conservation tools such as rolling easements. Model results were conditional on a decision maker’s risk tolerance but highlighted general strategies of land conservation to increase future habitat representation beyond what is expected under the current protected land base. We built models that may help inform coastal planning by estimating salinity dynamics and the performance of oyster reef restoration efforts to predict the combined effects of global change and management of freshwater flows on coastal habitats and the processes that contribute to their resilience. These models can support restoration decisions by evaluating the expected benefits of site locations for shoreline protection and fisheries production. Lastly, we developed a spatially explicit economic model that predicts feedback dynamics among land value, land-use change, and effects on ecosystem service provision to explore zoning policies and incentives on urban growth and ecosystem services. We summarize these efforts with insights and considerations for the Cape Romain Partnership for Coastal Protection to continue to engage stakeholders in effective adaptation planning. First, notions of place attachment (referred to as sense of place), and the role of culture in social discourse are increasingly being used to understand the complex interactions between society and the environment and how societies respond and adapt to climate change. Sense of place was a unifying theme whenever the future of the South Carolina Lowcountry was discussed. The contribution of the South Carolina Lowcountry’s environmental wealth, rich cultural heritage, and quality of life to sense of place has important implications for how adaptation planning might best be pursued. More community-based governance of the commons (in other words, natural and cultural resources held in common), in which broad stakeholder participation and power sharing are key elements, is considered important. This devolution of governance is characterized by polycentric institutions and self-organizing social networks that promote a local culture of knowledge sharing, problem solving, and learning. These so-called bridging organizations (or individuals) often provide the leadership necessary to bring together potentially disparate Government agencies and institutions, private organizations, and individuals in a collective process of problem solving. Our observations also suggest that the conservation community in the South Carolina Lowcountry views its activities as integral to the broader governance of social-ecological systems, in which responses to the forces of global change are mediated through culture, economics, and politics. Rather than directly competing with other interests, the South Carolina Lowcountry conservation community seems to embrace an interpretation of conservation in which the fundamental objective is the quality of human life rather than environmental protection. Fundamental to the types of governance reforms described above is the notion of coproduction, in which experts and users collaborate to develop a shared body of knowledge. In this approach, scientists work with stakeholders to help frame questions, design research, and collect and analyze data. Such sustained collaborations are increasingly believed to be an effective way to produce useable (or actionable) science. The emphasis on social learning, leveraging strong social networks, coordinating and deliberating among diverse stakeholders, and applying principles of adaptive management is an essential contribution to adaptive capacity. The diverse and robust set of scientific approaches, methods to help stakeholders collaborate in effective and goal-driven planning processes, and decision tools resulting from this project hopefully will assist Cape Romain NWR and its partners prepare for climatic, ecological, and social changes over the coming decades.

South Carolina↗

Changes in forest connectivity from beech bark disease in Pictured Rocks National Lakeshore in the Upper Peninsula of Michigan

Within the forests of Pictured Rocks National Lakeshore, biologists are trying to understand the effects beech bark disease has on wildlife species, especially species that need forest connectivity to thrive. This project used aerial imagery collected in 2005, shortly after beech bark disease infestation, and satellite imagery from 2018. The 2018 imagery represents present day conditions and was used to locate forest canopy gaps through object-based image analysis. Forest canopy gaps were identified using the multiresolution segmentation algorithm within Trimble’s eCognition software. A time change analysis was completed to understand how the forest canopy had changed from 2005 to 2018. The analysis showed areas that had maintained forest canopy, maintained a forest canopy gap, created a new canopy gap (closed forest canopy in 2005 but open canopy gap in 2018), or created new forest canopy (open canopy gap in 2005 but closed forest canopy in 2018). There were 9,127 acres of forest canopy lost, and 72.8 percent of that lost canopy occurred in a forest type where Fagus grandifolia Ehrh. (American beech) is a common tree species. The datasets developed through this project can enhance knowledge of where canopy gaps exist and help place focus on certain areas for wildlife studies. In addition, these datasets can be used in future studies to monitor the health of the forest and conduct additional change analyses.

Michigan↗

Simulation of regional groundwater flow and advective transport of per- and polyfluoroalkyl substances, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018

A three-dimensional numerical model of groundwater flow was developed and calibrated for the unconsolidated New Jersey Coastal Plain aquifers underlying Joint Base McGuire-Dix-Lakehurst (JBMDL) and vicinity, New Jersey, to evaluate groundwater flow pathways of per- and polyfluoroalkyl substances (PFAS) contamination associated with use of aqueous film forming foam (AFFF) at the base. The regional subsurface flow model spans an area of approximately 518 square miles around JBMDL and is based on a previously developed hydrogeologic framework of the area. Steady-state flow in the unconsolidated aquifers was simulated using the MODFLOW 6 groundwater flow model, which is able to account for hydrostratigraphic pinchouts and discontinuities in the Coastal Plain aquifers underlying JBMDL. To account for local patterns of fluid flow driving advective subsurface migration of PFAS, the grid was refined using quadtree meshes spanning 21 areas where historical AFFF use was identified, five off-site reconnaissance areas identified by AFCEC as areas in which the occurrence of PFAS is most likely to pose a potential danger to local drinking water supplies, and along streams that behave as drains in the base-flow-dominated Coastal Plain. Following grid refinement, four physical processes known to govern subsurface flow were introduced to the model. These included effective precipitation recharge, discharge to streams and stream-connected wetlands, regional inflows and outflows along the model bottom, and withdrawals from wells, each of which were incorporated into the model as either external or internal boundary conditions. To account for effective precipitation recharge, a specified-flow boundary was assigned along the top of the model. Similarly, regional flows predicted using the modified U.S Geological Survey’s New Jersey Coastal Plain Regional Aquifer System Analysis model were treated as specified-flow boundary conditions along the bottom of the model. Base-flow losses were treated as drains along streams delineated using a 10-foot LiDAR dataset. Drains were also assigned to cells falling within stream-connected National Hydrologic Database wetlands. Finally, well-pumpage data mined from the New Jersey Water Transfer database were added to the model to account for extraction of groundwater through pumping from industrial-supply and drinking-water-supply wells. Along model edges established at groundwater divides, where the net flux of water across the boundary is equal to zero, natural no-flow boundary conditions were imposed. The refined flow model was calibrated using the parameter-estimation (PEST) program, which adjusts model parameters by performing a gradient search over the sum-of-squared-error objective function until the parameter set that produces simulated water levels and base flows most closely matches 544 water levels and 20 estimated base flows and closely adheres to initial parameter estimates. Based on the analysis of calibration residuals, the model did not appear to be affected by significant model structural error. The MODPATH particle-tracking algorithm was used to estimate advective transport paths of PFAS in the vicinity of JBMDL. Forward tracking was used to determine paths of PFAS away from AFFF source areas to streams, wetlands, pumping wells, and geographic areas that PFAS may contaminate. Additionally, reverse tracking was used to determine particle pathlines away from off-site PFAS reconnaissance areas, or areas within which all sources of PFAS might be advectively transported into subsurface drinking-water supplies, to locations at land surface that may indicate a source of PFAS. The coupled and calibrated groundwater flow and particle-tracking transport model provide valuable tools for predicting the relative extent of PFAS contamination from onsite legacy source areas. The calibrated model also provides measures of water-level and base-flow observation influence that can help guide future data-collection efforts related to groundwater and surface water sampling for PFAS.

New Jersey↗

Crustal thickness and the VP/VS ratio within the Arabia Plate from P-wave receiver functions at 154 broadband seismic stations

As part of a joint Saudi Geological Survey (SGS) and United States Geological Survey project, we analyzed P-wave receiver functions from seismic stations covering most of the Kingdom of Saudi Arabia to map the thickness of the crust across the Arabia Plate. We present an update of crustal thickness estimates and fill in gaps for the western Arabian Shield and the rifted margin at the Red Sea (the coastal plain), as well as the eastern Arabian Platform. We applied a conventional H-k stacking algorithm and included careful attention to stacking weights, two forms of sedimentary corrections for stations located on the Arabian Platform, and additional processing for noisy stations. We obtained useful results at 154 stations from 898 teleseismic events over a 2-year period from 1995–1997 (for non-SGS stations) and a 6-year period from 2008–2014 (for SGS stations). Average crustal thickness (that is, depth to the Mohorovičić discontinuity [Moho] below the surface) beneath the Red Sea coastal plain (the rift margin) is 29 kilometers (km), beneath the volcanic fields (known in Arabic as harra [plural] or harrat [singular]) is 35 km, beneath the Arabian Shield (excluding harrats) is 37 km, and beneath the Arabian Platform is 38 km. Crustal thinning appears not to extend east of the rift escarpment, suggesting uniform extension that is no broader at depth than at the surface. In contrast to some previous interpretations that the Arabian Platform crust is thicker than that of the Arabian Shield, we find no statistically significant difference between their whole crustal thicknesses. However, the average sub-sedimentary crustal thickness (that is, the crystalline crust) for stations on the Arabian Platform is 34 km, 3 km thinner than the crust of the Arabian Shield. Individual station P-wave (pressure) velocity and S-wave (shear) velocity ratios (VP/VS) are highly variable for the Arabia Plate, ranging from 1.60 to 1.97 and averaging 1.75, with a standard deviation of 0.07. There are no statistically significant differences between VP/VS ratios of the different geologic regions of Saudi Arabia. Similar VP/ VS ratios, coupled with similar crustal thicknesses for harrats and the Arabian Shield, indicate that Cenozoic magmatism has contributed negligibly to crustal growth.

Open-File Report↗