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227 records · Page 13Linked to original sources

User manuals for the Delaware River Basin Water Availability Tool for Environmental Resources (DRB–WATER) and associated WATER application utilities

The Water Availability Tool for Environmental Resources (WATER) is a decision support system (DSS) for the nontidal part of the Delaware River Basin (DRB) that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that have been parameterized using three hydrologic response units—forested, agricultural, and developed land cover. It is this integration that enables the regional hydrologic-modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model. The DSS provides a “historical” database, ideal for simulating streamflow for 2001–11, in addition to land-cover forecasts that focus on 2030 and 2060. The WATER Application Utilities are provided with the DSS and apply change factors for precipitation, temperature, and potential evapotranspiration to a 1981–2011 climatic record provided with the DSS. These change factors were derived from a suite of general circulation models (GCMs) and representative concentration pathway (RCP) emission scenarios. These change factors are based on 25-year monthly averages (normals) that are centere on 2030 and 2060. The WATER Application Utilities also can be used to apply a 2010 snapshot of water use for the DRB; a factorial approach enables scenario testing of increased or decreased water use for each simulation. Finally, the WATER Application Utilities can be used to reformat streamflow time series for input to statistical or reservoir management software.

Delaware, Maryland, New Jersey, New York, Pennsylv↗

Modeling geologic sequestration of carbon dioxide in a deep saline carbonate reservoir with TOUGH2–ChemPlugin, a new tool for reactive transport modeling

This paper outlines the development and demonstration of a new tool, TOUGH2–ChemPlugin (T2CPI) for predicting rock–water–CO 2 interaction following injection of supercritical CO 2 into a heterogeneous carbonate system. Specifically, modeling capabilities of TOUGH2, which examines multiphase flow and supercritical CO 2 behavior, were combined with the geochemical modeling capabilities of The Geochemist’s Workbench ® (GWB), using ChemPlugin TM . ChemPlugin is a self-linking re-entrant software object that, when coupled to a transport simulator, retains the flow and transport capabilities of the simulator but enables incorporation of reactive chemistry via GWB. To test and assess the capabilities of T2CPI, results from T2CPI simulations were compared to those of TOUGHREACT, using the same carbonate reservoir parameters (based on the Dollar Bay Formation of the South Florida Basin). Overall, results of simulations from TOUGHREACT and T2CPI were very similar for nearly all evaluated parameters. Dissimilarities between the two programs included qualitative differences in how TOUGHREACT and T2CPI predicted calcite dissolution and the subsequent spatial pattern of the porosity gain caused by how each handles evaporation of water near the injection point. The TOUGHREACT program is a proven, widely used tool for evaluating CO 2 –brine–rock interaction following supercritical CO 2 injection. The T2CPI tool offers similar capabilities and strengths of TOUGHREACT, with the ability to read in and use databases for a wide range of activity coefficient types. This program also has abilities to use a wide range of kinetic constraints, define those kinetic constraints with scripts or compiled libraries, account for colloidal transport, and/or account for a wide range of surface sorption models.

Florida↗

Acetylenotrophic and diazotrophic Bradyrhizobium sp. strain I71 from TCE-contaminated soils

Abstract Acetylene (C 2 H 2 ) is a molecule rarely found in nature, with very few known natural sources, but acetylenotrophic microorganisms can use acetylene as their primary carbon and energy source. As of 2018 there were 15 known strains of aerobic and anaerobic acetylenotrophs; however, we hypothesize there may yet be unrecognized diversity of acetylenotrophs in nature. This study expands the known diversity of acetylenotrophs by isolating the aerobic acetylenotroph, Bradyrhizobium sp. strain I71, from trichloroethylene (TCE)-contaminated soils. Strain I71 is a member of the class Alphaproteobacteria and exhibits acetylenotrophic and diazotrophic activities, the only two enzymatic reactions known to transform acetylene. This unique capability in the isolated strain may increase the genus’ economic impact beyond agriculture as acetylenotrophy is closely linked to bioremediation of chlorinated contaminants. Computational analyses indicate that the Bradyrhizobium sp. strain I71 genome contains 522 unique genes compared to close relatives. Moreover, applying a novel hidden Markov model of known acetylene hydratase (AH) enzymes identified a putative AH enzyme. Protein annotation with I-TASSER software predicted the AH from the microbe Syntrophotalea acetylenica as the closest structural and functional analog. Furthermore, the putative AH was flanked by horizontal gene transfer (HGT) elements, like that of AH in anaerobic acetylenotrophs, suggesting an unknown source of acetylene or acetylenic substrate in the environment that is selecting for the presence of AH. Importance The isolation of Bradyrhizobium strain I71 expands the distribution of acetylene-consuming microbes to include a group of economically important microorganisms. Members of Bradyrhizobium are well studied for their abilities to improve plant health and increase crop yields by providing bioavailable nitrogen. Additionally, acetylene-consuming microbes have been shown to work in tandem with other microbes to degrade soil contaminants. Based on genome, cultivation, and protein prediction analysis, the ability to consume acetylene is likely not widespread within the genus Bradyrhizobium . These findings suggest that the suite of phenotypic capabilities of strain I71 may be unique and make it a good candidate for further study in several research avenues.

California↗

Simulation of Runoff and Reservoir Inflow for Use in a Flood-Analysis Model for the Delaware River, Pennsylvania, New Jersey, and New York, 2004-2006

A model was developed to simulate inflow to reservoirs and watershed runoff to streams during three high-flow events between September 2004 and June 2006 for the main-stem subbasin of the Delaware River draining to Trenton, N.J. The model software is a modified version of the U.S. Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS), a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The PRMS model simulates time periods associated with main-stem flooding that occurred in September 2004, April 2005, and June 2006 and uses both daily and hourly time steps. Output from the PRMS model was formatted for use as inflows to a separately documented reservoir and riverrouting model, the HEC-ResSim model, developed by the U.S. Army Corps of Engineers Hydrologic Engineering Center to evaluate flooding. The models were integrated through a graphical user interface. The study area is the 6,780 square-mile watershed of the Delaware River in the states of Pennsylvania, New Jersey, and New York that drains to Trenton, N.J. A geospatial database was created for use with a geographic information system to assist model discretization, determine land-surface characterization, and estimate model parameters. The USGS National Elevation Dataset at 100-meter resolution, a Digital Elevation Model (DEM), was used for model discretization into streams and hydrologic response units. In addition, geospatial processing was used to estimate initial model parameters from the DEM and other data layers, including land use. The model discretization represents the study area using 869 hydrologic response units and 452 stream segments. The model climate data for point stations were obtained from multiple sources. These sources included daily data for 22 National Weather Service (NWS) Cooperative Climate Station network stations, hourly data for 15 stations from the National Climatic Data Center, hourly data for 1 station from the NWS Middle Atlantic River Forecast Center records, and daily and hourly data for 7 stations operated by the New York City Department of Environmental Protection. The NWS Multisensor Precipitation Estimate data set for 2001-2007 was used for computing daily precipitation for the model and for computing hourly precipitation for storm simulation periods. Calibration of the PRMS model included regression and optimization algorithms, as well as manual adjustments of model parameters. The general goal of the calibration procedure was to minimize the difference between discharge measured at USGS streamgages and the corresponding discharge simulated by the model. Daily streamflow data from 35 USGS streamgages were used in model calibration. The streamflow data represent areas draining from 20.2 to 6,780 square miles. The PRMS model simulates reservoir inflow and watershed runoff for use as input into HECResSim for the purpose of evaluating and comparing the effects of different watershed conditions on main-stem flooding in the Delaware River watershed draining to Trenton, N.J. The PRMS model is useful as a planning tool to simulate the effects of land-use changes and different antecedent conditions on local runoff and reservoir inflow and, as input to the HEC-ResSim model, on flood flows in the main stem of the Delaware River.

Open-File Report↗

USGS Telemetry Project

Telemetry of acoustically tagged bigheaded carp (i.e., bighead carp Hypophthalmichthys nobilis and silver carp H. molitrix ) and surrogate fish species has become an invaluable tool in management for these species in the upper Illinois Waterway Systems (i.e., upper Illinois River, lower Des Plaines River, and Chicago Area Waterway System). For example, movement probabilities between adjacent navigation pools need to be estimated to parameterize the Spatially Explicit Asian Carp Population Model (SEAcarP). SEAcarP is a population model used in scenario planning by the Monitoring and Response Workgroup (MRWG) to evaluate alternative management actions. These movement probabilities are estimated from the telemetry data obtained from a longitudinal network of strategically placed receivers that detect bigheaded carp that have been implanted with acoustic transmitters. In addition, fish removal by contracted fishers has become the primary method of controlling bigheaded carp in the upper Illinois and lower Des Plaines Rivers. Variable patterns in bigheaded carp distribution, habitat, and movement, influenced by seasonal and environmental conditions, make targeting bigheaded carp for removal and containment challenging and costly. Understanding these movement patterns for bigheaded carp through modeling and real-time telemetry applications informs removal efforts and facilitates monitoring and contingency actions based on fish movements. To develop a better understanding of fish movement dynamics to meet management objectives, an existing network of real-time and data-logging acoustic receivers in the upper Illinois Waterway Systems is collaboratively managed by a multi-agency team (see Participating Agencies section above). A Telemetry Workgroup has been established by the MRWG to ensure that the multi-agency telemetry efforts are coordinated to efficiently and effectively meet the MRWG goals. This workgroup plans and executes the placement of receivers, tagging of bigheaded carp with acoustic tags, and management of the telemetry data. Three primary objectives to meet MRWG goals identified by the Telemetry Workgroup included (1) development of a common standardized telemetry database with visualization and analysis tools, (2) transitioning from Program MARK (http://www.phidot.org/software/mark/) to a custom Bayesian multi-state model for estimating movement probabilities needed for SEAcarP and (3) deploying, maintaining, and serving data from real-time acoustic receivers to inform contingency planning and fish removal. A telemetry database and visualization tools (FishTracks) will facilitate standardization, archiving, sharing, quality assurance, visualization and analysis of the telemetry data needed for management. Modifications and additions to FishTracks will facilitate more problem-free use of the database and associated applications, as well as useful extraction of information to meet management goals. The transition to a custom Bayesian multi-state model to estimate movement probabilities will support more efficient, effective, and robust population modeling with SEAcarP by overcoming short comings of Program MARK for this purpose. These shortcomings include lack of customizability and extensibility, problems of singularities and poor-convergence, software crashes, parameter exclusion from models, an inability to consistently generate estimates of movement probability, and a lack of uncertainty estimates for movement probabilities. A real-time receiver network that is maintained and tested annually will ensure reliability and accuracy of the real-time alerts to bigheaded carp movements that can be used by management to plan contingency actions.

Illinois↗

Strategic restoration planning for land birds in the Colorado River Delta, Mexico

Ecological restoration is an essential strategy for mitigating the current biodiversity crisis, yet restoration actions are costly. We used systematic conservation planning principles to design an approach that prioritizes restoration sites for birds and tested it in a riparian forest restoration program in the Colorado River Delta. Restoration goals were to maximize the abundance and diversity of 15 priority birds with a variety of habitat preferences. We built abundance models for priority birds based on the current landscape, and predicted bird distributions and relative abundances under a scenario of complete riparian forest restoration throughout our study area. Then, we used Zonation conservation planning software to rank this restored landscape based on core areas for all priority birds. The locations with the highest ranks represented the highest priorities for restoration and were located throughout the river reach. We optimized how much of the available landscape to restore by simulating restoration of the top 10–90% of ranked sites in 10% intervals. We found that total diversity was maximized when 40% of the landscape was restored, and mean relative abundance was maximized when 80% of the landscape was restored. The results suggest that complete restoration is not optimal for this community of priority birds and restoration of approximately 60% of the landscape would provide a balance between maximum relative abundance and diversity. Subsequent planning efforts will combine our results with an assessment of restoration costs to provide further decision support for the restoration-siting process. Our approach can be applied to any landscape-scale restoration program to improve the return on investment of limited economic resources for restoration.

Colorado River Delta↗

A computerized data base of nitrate concentrations in Indiana ground water

As part of a cooperative study with the Indiana Department of Environmental Management, the U.S. Geological Survey compiled a computerized data base of nitrate concentrations in Indiana ground water. The data included nitrate determinations from more than 29 studies by five Federal and State agencies during June 1973 through August 1991. The National Water Information System software of the U.S. Geological Survey was used to store the data at the U.S. Geological Survey office in Indianapolis, Indiana. Electronic data sets were converted to a standard format of well data, sample data, and analytical data. Data were screened by several error-checking procedures before they were retained in the data base; they were examined for potential duplicates of well location and name. The data base of nitrate concentrations in Indiana ground water contains records of 5,525 samples collected from 4,448 wells in 88 of 92 counties during 1973-91. Those wells included 3,832 drinking-water wells; 536 monitoring wells, 38 livestock-supply wells; and 42 irrigation wells. Nitrate concentrations greater than minimum reporting limits of 0.0 to 0.5 milligrams per liter (mg/L) were determined in 2,453 samples (44 percent of the total). Nitrate in ground water at concentrations greater than 3 mg/L have been considered to be the result of human activities. Nitrate concentrations ranged from 0.005 to 380 mg/L with a median nitrate concentration of 0.3 mg/L. Nitrate concentrations were greater than or equal to 3 mg/L in 704 samples (13 percent of the total). Nitrate concentrations were greater than or equal to the U.S. Environmental Protection Agency Maximum Contaminant Level of 10 mg/L in 188 samples (3.4 percent of the total). Of the 3,832 drinking- water wells in the data base, 147 had at least one sample in which a nitrate concentration was greater than the Maximum Contaminant Level. The percentage of samples with nitrate concentrations greater than or equal to 3 mg/L and greater than or equal to 10 mg/L generally increased during the period 1973 through 1991. The nitrate data base was compiled from numerous data sets that were readily accessible in electronic format. The uses of these data may be limited because they were neither comprehensive nor of a single statistical design. Nonetheless, the nitrate data can be used in several ways: (1) to identify geographic areas with and without nitrate data; (2) to evaluate assumptions, models, and maps of ground-water-contamination potential; and (3) to investigate the relation between environmental factors, land-use types, and the occurrence of nitrate.

Indiana↗

Numerical model simulations of nitrate concentrations in groundwater using various nitrogen input scenarios, mid-Snake region, south-central Idaho

As part of the U.S. Geological Survey’s National Water Quality Assessment (NAWQA) program nitrate transport in groundwater was modeled in the mid-Snake River region in south-central Idaho to project future concentrations of nitrate. Model simulation results indicated that nitrate concentrations would continue to increase over time, eventually exceeding the U.S. Environmental Protection Agency maximum contaminant level for drinking water of 10 milligrams per liter in some areas. A subregional groundwater model simulated the change of nitrate concentrations in groundwater over time in response to three nitrogen input scenarios: (1) nitrogen input fixed at 2008 levels; (2) nitrogen input increased from 2008 to 2028 using the same rate of increase as the average rate of increase during the previous 10 years (1998 through 2008); after 2028, nitrogen input is fixed at 2028 levels; and (3) nitrogen input related to agriculture completely halted, with only nitrogen input from precipitation remaining. Scenarios 1 and 2 project that nitrate concentrations in groundwater continue to increase from 10 to 50 years beyond the year nitrogen input is fixed, depending on the location in the model area. Projected nitrate concentrations in groundwater increase by as much as 2–4 milligrams per liter in many areas, with nitrate concentrations in some areas reaching 10 milligrams per liter. Scenario 3, although unrealistic, estimates how long (20–50 years) it would take nitrate in groundwater to return to background concentrations—the “flushing time” of the system. The amount of nitrate concentration increase cannot be explained solely by differences in nitrogen input; in fact, some areas with the highest amount of nitrogen input have the lowest increase in nitrate concentration. The geometry of the aquifer and the pattern of regional groundwater flow through the aquifer greatly influence nitrate concentrations. The aquifer thins toward discharge areas along the Snake River which forces upward convergence of good-quality regional groundwater that mixes with the nitrate-laden groundwater in the uppermost parts of the aquifer, which results in lowered nitrate concentrations. A new method of inputting nitrogen to the subregional groundwater model was used that prorates nitrogen input by the probability of detecting nitrate concentrations greater than 2 mg/L. The probability map is based on correlations with physical factors, and prorates an existing nitrogen input dataset providing an estimate of nitrogen flux to the water table that accounts for new factors such as soil properties. The effectiveness of this updated nitrogen input method was evaluated using the software UCODE_2005.

Idaho↗

Estimation of baseline daily mean streamflows for ungaged locations on Pennsylvania streams, water years 1960-2008

Water-resource managers use daily mean streamflows to generate streamflow statistics and analyze streamflow conditions. An in-depth evaluation of flow regimes to promote instream ecological health often requires streamflow information obtainable only from a time series hydrograph. Historically, it has been difficult to estimate daily mean streamflow for an ungaged location. The U.S. Geological Survey (USGS), in cooperation with the Pennsylvania Department of Environmental Protection, Susquehanna River Basin Commission, and The Nature Conservancy, has developed the Ba seline S treamflow E stimator (BaSE) to estimate baseline streamflow at a daily time scale for ungaged streams in Pennsylvania using data collected during water years 1960–2008. Baseline streamflow is minimally altered by regulation, diversion, or mining, and other anthropogenic activities. Daily mean streamflow is estimated in BaSE using a methodology that equates streamflow as a percentile from a flow duration curve for a particular day at an ungaged location with streamflow as a percentile from the flow duration curve for the same day at a reference streamgage that is considered to be hydrologically similar to the ungaged location. An appropriate reference streamgage is selected using map correlation, in which variogram models are developed that correlate streamflow at one streamgage with streamflows at all other streamgages. The percentiles from a flow duration curve for the ungaged location are converted to streamflow through the use of regression equations. Regression equations used to predict 17 flow-duration exceedance probabilities were developed for Pennsylvania using geographic information system-derived basin characteristics. The standard error of prediction for the regression equations ranged from 11 percent to 92 percent with the mean of 31 percent. The map correlation method for estimating streamflow was tested at locations within two pilot basins, the Upper Delaware River Basin and the Lower Susquehanna River Basin, before being applied statewide. Reference streamgages within the pilot basins were used as ungaged locations for analyzing the map correlation method. Correlation using Spearman’s rho and centroid distance performed as well as, or better than, the method using the closest streamgage as a reference streamgage. Map correlation using the correlation metrics identified in the pilot basins was applied to 156 streamgages in and near Pennsylvania. BaSE uses the map correlation method and flow-duration exceedance probability regression equations to estimate baseline daily mean streamflow for an ungaged location. The output from BaSE is a Microsoft Excel® report file that summarizes the reference streamgage and ungaged location information, including basin characteristics, percent difference in basin characteristics between the two locations, any warning associated with the basin characteristics, mean and median streamflow for the ungaged location, and a daily hydrograph of streamflow for water years 1960–2008 for the ungaged location. The daily mean streamflow for the ungaged location can be exported as a text file to be used as input into other statistical software packages. BaSE estimates daily mean streamflow for baseline conditions only, and any alterations to streamflow from regulation, large water use, or substantial mining are not reflected in the estimated streamflow.

Pennsylvania↗

Determination of dilution factors for discharge of aluminum-containing wastes by public water-supply treatment facilities into lakes and reservoirs in Massachusetts

Dilution of aluminum discharged to reservoirs in filter-backwash effluents at water-treatment facilities in Massachusetts was investigated by a field study and computer simulation. Determination of dilution is needed so that permits for discharge ensure compliance with water-quality standards for aquatic life. The U.S. Environmental Protection Agency chronic standard for aluminum, 87 micrograms per liter (μg/L), rather than the acute standard, 750 μg/L, was used in this investigation because the time scales of chronic exposure (days) more nearly match rates of change in reservoir concentrations than do the time scales of acute exposure (hours). Whereas dilution factors are routinely computed for effluents discharged to streams solely on the basis of flow of the effluent and flow of the receiving stream, dilution determination for effluents discharged to reservoirs is more complex because (1), compared to streams, additional water is available for dilution in reservoirs during low flows as a result of reservoir flushing and storage during higher flows, and (2) aluminum removal in reservoirs occurs by aluminum sedimentation during the residence time of water in the reservoir. Possible resuspension of settled aluminum was not considered in this investigation. An additional concern for setting discharge standards is the substantial concentration of aluminum that can be naturally present in ambient surface waters, usually in association with dissolved organic carbon (DOC), which can bind aluminum and keep it in solution. A method for dilution determination was developed using a mass-balance equation for aluminum and considering sources of aluminum from groundwater, surface water, and filter-backwash effluents and losses caused by sedimentation, water withdrawal, and spill discharge from the reservoir. The method was applied to 13 reservoirs. Data on aluminum and DOC concentrations in reservoirs and influent water were collected during the fall of 2009. Complete reservoir volume was determined to be available for mixing on the basis of vertical and horizontal aluminum-concentration profiling. Losses caused by settling of aluminum were assumed to be proportional to aluminum concentration and reservoir area. The constant of proportionality, as a function of DOC concentration, was established by simulations in each of five reservoirs that differed in DOC concentration. In addition to computing dilution factors, the project determined dilution factors that would be protective with the same statistical basis (frequency of exceedance of the chronic standard) as dilutions computed for streams at the 7-day-average 10-year-recurrence annual low flow (the 7Q10). Low-flow dilutions are used for permitting so that receiving waters are protected even at the worst-case flow levels. The low-flow dilution factors that give the same statistical protection are the lowest annual 7-day-average dilution factors with a recurrence of 10 years, termed 7DF10s. Determination of 7DF10 values for reservoirs required that long periods of record be simulated so that dilution statistics could be determined. Dilution statistics were simulated for 13 reservoirs from 1960 to 2004 using U.S. Geological Survey Firm-Yield Estimator software to model reservoir inputs and outputs and present-day values of filter-effluent discharge and aluminum concentration. Computed settling velocities ranged from 0 centimeters per day (cm/d) at DOC concentrations of 15.5 milligrams per liter (mg/L) to 21.5 cm/d at DOC concentrations of 2.7 mg/L. The 7DF10 values were a function of aluminum effluent discharged. At current (2009) effluent discharge rates, the 7DF10 values varied from 1.8 to 115 among the 13 reservoirs. In most cases, the present-day (2009) discharge resulted in receiving water concentrations that did not exceed the standard at the 7DF10. Exceptions were one reservoir with a very small area and three reservoirs with high concentrations of DOC. Maximum permissible discharges were determined for water-treatment plants by adjusting discharges upward in simulations until the 7DF10 resulted in reservoir concentrations that just met the standard. In terms of aluminum flux, these discharges ranged from 0 to 28 kilograms of aluminum per day.

Massachusetts↗

Capacity assessment for Earth Monitoring, Analysis, and Prediction (EarthMAP) and future integrated monitoring and predictive science at the U.S. Geological Survey

Executive Summary Managers of our Nation’s resources face unprecedented challenges driven by the convergence of increasing, competing societal demands and a changing climate that affects the stability, vulnerability, and predictability of those resources. To help meet these challenges, the scientific community must take advantage of all available technologies, data, and integrative Earth systems modeling capacity to better inform resource and risk management decisions. This is the overarching goal of the U.S. Geological Survey (USGS) Earth Monitoring, Analysis, and Prediction (EarthMAP) vision: “By 2030, the USGS will deliver well integrated observations and predictions of the future state of natural systems—water, ecosystems, energy, minerals, hazards—at regional and national scales, working primarily with federal, state, and academic partners to develop and operate the capability” (U.S. Geological Survey, 2021). Providing more integrated Earth systems science and actionable information to decision makers, stakeholders, and the public requires a better understanding of the depth and distribution of existing capacity (capabilities, tools, and techniques) across the Bureau. Identifying existing capacity is also a critical first step toward gap analysis and targeted investments to increase capacity over time. The USGS formed a Capacity Assessment Team (CAT) and charged it with (1) conducting a Request for Information (RFI) to identify existing USGS expertise and activities supportive of integrated and predictive science to inform decision making, (2) developing a strategy and proof-of-concept for a continuously updated capacity assessment capability, and (3) identifying lessons learned to inform development of best practices for future capacity assessment efforts. The RFI took the form of a survey, with content guided by the science and technology needs identified in a USGS report titled “Grand Challenges for Integrated U.S. Geological Survey Science—A Workshop Report” (Jenni and others, 2017). The 44-question survey provided respondents the ability to rate their level of experience with a suite of priority disciplines, analysis and modeling approaches, technologies, and stakeholder engagement strategies and to enter optional narrative text for supporting context. An introductory portion focused on general science capacity assessment, followed by three sections targeting capabilities related to the foundational components of EarthMAP: (1) data and information integration, (2) integrated predictive science, and (3) actionable information. The survey results provided a high-level snapshot of USGS capacity in the targeted areas. Respondents (1,035 individuals) represented approximately 13 percent of the USGS across all mission areas and regions. Seventy-four percent of the respondents held a science-focused position title and the remainder had position titles in information technology, computer science, management, administrative, or other (contractors, volunteers, emeritus, and unknown). To provide greater insight into respondent capabilities and activities, information from the U.S. Department of the Interior and USGS enterprise information systems were used to further characterize topical expertise and organizational associations of survey respondents. To address the ongoing need to assess the Bureau’s capacity to address integrated predictive science priorities, the CAT developed a software-based proof-of-concept called the Integrated Science Assessment Information Database (iSAID) for assembling various information sources together toward making the full extent of USGS capabilities and scientific assets available for routine capacity assessment. This proof-of-concept is intended to serve as a catalyst for further development. The process of implementing the EarthMAP capacity assessment survey, analyzing survey responses, and developing the proof-of-concept resulted in lessons learned, findings, and recommendations. Example scenarios throughout the report demonstrate how capacity assessment data can inform science planning. Three overarching findings and recommendations are: (1) Finding: Capacity is limited in some critical disciplines, skills, and technology applications, but “sufficient” depends on the question and the need relative to availability at a given point in time. Recommendation: Develop an on-demand capacity assessment framework that enables rapid identification and evaluation of existing and available expertise to support decision needs as they arise. (2) Finding: Institutional barriers and lack of awareness constrain the ability of USGS staff to adopt new technologies, collaborate across administrative boundaries, and deliver actionable information to stakeholders in a timely manner. However, these barriers are not universally experienced. Recommendation: Pursue more targeted inquiries to clarify which institutional barriers are obstructing the adoption of new technologies and approaches or the sharing of expertise and equipment across organizational and regional boundaries. These inquiries should inform USGS leadership, mission areas, and regions whether policies can be revised or whether a lack of understanding is creating perceived obstacles. Highlight cases when staff have successfully adopted new technologies and approaches to advance EarthMAP priorities and provide actionable information in a timely manner to spread awareness of how perceived obstacles can be navigated and overcome when appropriate. (3) Finding: Examples of people and projects integrating across disciplines and scales and applying advanced approaches to meet complex stakeholder needs exist. Such examples provide transfer value across the spectrum from approach to decision making. Many projects, already underway, appear to meet elements of the EarthMAP vision, and the USGS has people who can provide leadership in multiple types of specific integrated science efforts. Recommendation: Use these findings as a starting point for near-term strategic planning for integrated science. Highlight, incentivize, and build on existing interdisciplinary predictive science and information delivery activities across the USGS to advance toward further realization of an EarthMAP capacity. The CAT efforts to develop and assess existing USGS capacity to advance the EarthMAP vision revealed a fundamental challenge for not only this effort but any effort to assess existing capacity: A considerable amount of thought, time, and effort is required to survey and assess capabilities and tools available to support a given need, yet best results are still likely to provide an incomplete assessment. To better meet the frequent need to assess capabilities, tools, products, and projects that address an expressed strategic priority, the CAT proposes the concept of an on-demand capacity assessment framework supported by a software package that dynamically pulls and integrates information from existing USGS information systems and public domain registries. Although existing USGS enterprise information systems currently lack the structure, cross-system consistency, interoperability, and stability to support a continuously updated capacity assessment capability, we identify reasonable near-term steps to improve the utility of information gathered on expertise and project capacity and to improve the consistency and completeness of information and the ability of USGS systems to share that information. The ability to search and characterize this information will make future assessments of capacity faster, more complete, more efficient, and more targeted. This approach would grow the Bureau’s capacity knowledge over time, iteratively improving the ability to access, leverage, and synthesize existing capabilities and assets as well as identify and fill critical gaps. The greatest promise for developing integrated science could lie in linking across existing projects and expertise to create a multi-project capacity for addressing large, complex environmental issues.

Open-File Report↗