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USGS2011

Setting limits: Using air pollution thresholds to protect and restore US ecosystems

More than four decades of research provide unequivocal evidence that sulfur, nitrogen, and mercury pollution have altered, and will continue to alter, our nation's lands and waters. The emission and deposition of air pollutants harm native plants and animals, degrade water quality, affect forest productivity, and are damaging to human health. Many air quality policies limit emissions at the source but these control measures do not always consider ecosystem impacts. Air pollution thresholds at which ecological effects are observed, such as critical loads, are effective tools for assessing the impacts of air pollution on essential ecosystem services and for informing public policy. U.S. ecosystems can be more effectively protected and restored by using a combination of emissions-based approaches and science-based thresholds of ecosystem damage.

Issues in Ecology↗

USGS2014

An expanded model: flood-inundation maps for the Leaf River at Hattiesburg, Mississippi, 2013

Digital flood-inundation maps for a 6.8-mile reach of the Leaf River at Hattiesburg, Mississippi (Miss.), were created by the U.S. Geological Survey (USGS) in cooperation with the City of Hattiesburg, City of Petal, Forrest County, Mississippi Emergency Management Agency, Mississippi Department of Homeland Security, and the Emergency Management District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Leaf River at Hattiesburg, Miss. (station no. 02473000). Current conditions for estimating near-real-time areas of inundation by use of USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/ . In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system ( http://water.weather.gov/ahps/ ). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the most current stage-discharge relations at the Leaf River at Hattiesburg, Miss. streamgage (02473000) and documented high-water marks from recent and historical floods. The hydraulic model was then used to determine 13 water-surface profiles for flood stages at 1.0-foot intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from light detection and ranging (lidar) data having a 0.6-foot vertical and 9.84-foot horizontal resolution) in order to delineate the area flooded at each water level. Development of the estimated flood inundation maps as described in this report update previously published inundation estimates by including reaches of the Bouie and Leaf Rivers above their confluence. The availability of these maps along with Internet information regarding current stage from USGS streamgages and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post flood recovery efforts.

Mississippi↗

USGS2011

Proceedings of a Coastal and Marine Spatial Planning Workshop for the Western United States

Recent scientific and ocean policy assessments demonstrate that a fundamental change in our current management system is required to achieve the long-term health of our ocean, coasts, and Great Lakes in order to sustain the services and benefits they provide to society. The present (2011) species- and sector-centric way we manage these ecosystems cannot account properly for cumulative effects, sustaining multiple ecosystem services, and holistically and explicitly evaluating the tradeoffs associated with proposed alternative and multiple human uses. A transition to an ecosystem-based approach to management and conservation of coastal and marine resources is needed. Competing uses and activities such as commerce, recreation, cultural practices, energy development, conservation, and national security are increasing pressure for new and expanded resource usage in coastal marine ecosystems. Current management efforts use a sector-by-sector approach that mostly focuses on a limited range of tools and outcomes [for example, oil and gas leases, fishery management plans, and Marine Protected Areas (MPAs)]. A comprehensive, ecosystem-based, and proactive approach to planning and managing these uses and activities is needed. Further, scientific understanding and information are essential to achieve an integrated decision-making process that includes knowledge of ecosystem services, existing and possible future conditions, and potential consequences of natural and anthropogenic events. Because no single government agency has executive authority for coastal or ocean resources, conflicting objectives around competing uses abound. In recent years, regional- and state-level initiatives in Coastal and Marine Spatial Planning (CMSP) have emerged to coordinate management activities. In some respects, the components and steps of the overall CMSP process are similar to how existing ocean resources are regulated and managed. For example, the Bureau of Ocean Energy Management Regulation and Enforcement (BOEMRE) uses spatial planning exercises in State Renewable Energy Task Force meetings to identify competing and conflicting ocean uses, and to delineate areas suitable for renewable energy development. Similarly terrestrial areas such as in national parks and national wildlife refuges managed by the Department of the Interior (DOI) prepare management plans for preservation and restoration of species and habitats of concern, some of which are protected by law. The analogy to CMSP is clear - multiple users and multiple expectations, resulting in the requirement to establish spatial plans for management of different resources and different ecosystem services. A two-day workshop on December 1-2, 2010, was convened for DOI representatives and several key non-DOI participants with roles in CMSP as a step toward clarifying national perspectives and consequences of the National Ocean Policy for the West (appendix 1). Discussions helped to develop an understanding of CMSP from the federal perspective and to identify regional priorities. An overarching theme was to promote a better understanding of current and future science needs. The workshop format included briefings by key Federal agencies on their understanding of the national focus followed by discussion of regional issues, including the needs for scientific information and coordination. The workshop also explored potential science contributions by Federal agencies and others; utilizing current capabilities, data, and information systems; and provided a foundation for possible future regional workshops focusing in turn on the West Coast Region (California, Oregon, and Washington), Pacific Islands (sometimes referred to as Oceania) and Alaska. Participants were asked to share information in the following areas, recognizing that the purpose would be to learn more about the national perspective (see appendixes 2-4): Explore how the Western U.S. (Alaska, Pacific Islands, and West Coast Region) migh

Open-File Report↗

USGS2011

Observed and forecast flood-inundation mapping application-A pilot study of an eleven-mile reach of the White River, Indianapolis, Indiana

Near-real-time and forecast flood-inundation mapping products resulted from a pilot study for an 11-mile reach of the White River in Indianapolis. The study was done by the U.S. Geological Survey (USGS), Indiana Silver Jackets hazard mitigation taskforce members, the National Weather Service (NWS), the Polis Center, and Indiana University, in cooperation with the City of Indianapolis, the Indianapolis Museum of Art, the Indiana Department of Homeland Security, and the Indiana Department of Natural Resources, Division of Water. The pilot project showed that it is technically feasible to create a flood-inundation map library by means of a two-dimensional hydraulic model, use a map from the library to quickly complete a moderately detailed local flood-loss estimate, and automatically run the hydraulic model during a flood event to provide the maps and flood-damage information through a Web graphical user interface. A library of static digital flood-inundation maps was created by means of a calibrated two-dimensional hydraulic model. Estimated water-surface elevations were developed for a range of river stages referenced to a USGS streamgage and NWS flood forecast point colocated within the study reach. These maps were made available through the Internet in several formats, including geographic information system, Keyhole Markup Language, and Portable Document Format. A flood-loss estimate was completed for part of the study reach by using one of the flood-inundation maps from the static library. The Federal Emergency Management Agency natural disaster-loss estimation program HAZUS-MH, in conjunction with local building information, was used to complete a level 2 analysis of flood-loss estimation. A Service-Oriented Architecture-based dynamic flood-inundation application was developed and was designed to start automatically during a flood, obtain near real-time and forecast data (from the colocated USGS streamgage and NWS flood forecast point within the study reach), run the two-dimensional hydraulic model, and produce flood-inundation maps. The application used local building data and depth-damage curves to estimate flood losses based on the maps, and it served inundation maps and flood-loss estimates through a Web-based graphical user interface.

Indiana↗

USGS2022

Perceptions of conservation introduction to inform decision support among U.S. Fish and Wildlife Service employees

Executive Summary Around the globe, fish and wildlife managers are facing increasingly complex management issues because of multiscale ecological effects like climate change, species invasion, and land-use change. Managers seeking to prevent extinctions or preserve ecosystems are increasingly considering more interventionist techniques to overcome the resulting changes. Among those techniques, translocation methods that intentionally move species into new, less impacted habitats are being considered. These types of translocations are known by a range of terms, including “managed relocation” and “assisted migration,” but the International Union for the Conservation of Nature’s Species Survival Commission (IUCN SSC, 2013) has proposed “conservation introduction” (CI) as a standard term. As defined by the IUCN SSC, CI is the intentional movement of a species or population outside its indigenous range for conservation purposes. CI can be divided into two forms: assisted colonization and ecological replacement. Assisted colonization is moving species outside its indigenous range to prevent extinction or extirpation of a population. Ecological replacement is moving species to fulfill an important niche that is necessary within an ecosystem. Proponents suggest these methods are necessary to address the ecological challenges managers are trying to overcome. Opponents point out the potential for species to become invasive, introduce disease or parasites, and cause other cascading impacts throughout the ecosystem. The result is controversy and disagreement. As such, it will be imperative to develop clear guidelines and best practices to be followed within wildlife management agencies to prevent potential To this end, the U.S. Fish and Wildlife Service (USFWS) partnered with the U.S. Geological Survey (USGS) to develop the current project. The intent was to describe the perceptions of USFWS personnel across many aspects of CI so that the USFWS could use this information in the planning and development of their own internal decision-support framework for CI. This report is presented in five sections. Section 1 introduces the project and provides an in-depth overview of background literature related to CI. Section 2 describes the study design, methods, and study participant characteristics. Section 3 describes key results and recommendations related to the development of a USFWS decision framework. Section 4 investigates a range of perceptions held by participants and establishes baseline information for how USFWS personnel may view CI and its application. Types of viewpoints surveyed include preferred terms and definitions, perceived barriers, perceived risks and tradeoffs, and aspects of success. Perceived barriers refers to factors that may prevent successful implementation of CI and perceived risks refers to potential negative outcomes that may occur as a result of implementing CI. Section 5 provides an overview of our conclusions for this project. Overall, we found that CI is likely to be viewed positively within the USFWS, but employees offered cautions and caveats. Most participants we interviewed feel that it is a necessary tool that will be indispensable in certain situations but also feel that there is more risk associated than with more traditional methods. For this reason, many participants are concerned about the assessment and planning that should be conducted prior to any CI effort. Our results indicate that many USFWS personnel will be open to CI being adopted more regularly but will be looking for clear guidance on how it should be implemented.

Scientific Investigations Report↗

USGS2016

Social-value maps for Arapaho, Roosevelt, Medicine Bow, Routt, and White River National Forests, Colorado and Wyoming

Executive Summary The continued pressures of population growth on the life-sustaining, economic, and cultural ecosystem services provided by our national forests, particularly those located near rapidly growing urban areas, present ongoing challenges to forest managers. Achieving an effective assessment of these ecosystem services includes a proper accounting of the ecological, economic, and social values attributable to them. However, assessments of ecosystem goods and services notably lack information describing the spatial distribution and relative intensity of social values—the perceived, nonmarket values derived particularly from cultural ecosystem services. A geographic information system (GIS) tool developed to fill this need, Social Values for Ecosystem Services (SolVES; http://solves.cr.usgs.gov ), now provides the capability to generate social-value maps at a range of spatial scales. This report presents some of the methods behind SolVES, procedures needed to apply the tool, the first formal map products resulting from its application at a regional scale, and a discussion of the management implications associated with this type of information. In this study, we use SolVES to identify the location and relative intensity of social values as derived from survey responses gathered from residents living in counties adjacent to Arapaho, Roosevelt, Medicine Bow, Routt, and White River National Forests. The results, presented as a series of social-value maps, represent the first publicly available spatial data on social-value intensity for the southern Rocky Mountain region. Our analysis identified high-value areas for social values including aesthetic, biodiversity, and life sustaining within wilderness areas. Other values, like recreation, show high-value areas both within wilderness and throughout the general forest areas, which can be attributed to people using the forests for a diverse set of recreational activities. The economic social-value type was lower within wilderness areas, which was an expected outcome because of the restrictions inside wilderness areas that preclude resource extraction, development, and motorized or mechanized recreation. Providing spatially explicit social-value information collected from residents in counties adjacent to these national forests can assist in facilitating the U.S. Department of Agriculture Forest Service’s Multiple-Use Sustained-Yield Act of 1960 (16 U.S.C. 528) note and the 2012 Forest Service Planning Rule (36 CFR Part 219), which encourage public participation in planning and management. By making these maps available to the public, we hope to encourage exploration of potential uses of these data for resource management and planning.

Colorado, Wyoming↗

USGS1996

Using a geographic information system and scanning technology to create high-resolution land-use data sets

A geographic information system (GIS) procedure was developed to compile low-altitude aerial photography, digitized data, and land-use data from U.S. Department of Agriculture Consolidated Farm Service Agency (CFSA) offices into a high-resolution (approximately 5 meters) land-use GIS data set. The aerial photography consisted of 35-mm slides which were scanned into tagged information file format (TIFF) images. These TIFF images were then imported into the GIS where they were registered into a geographically referenced coordinate system. Boundaries between land use were delineated from these GIS data sets using on-screen digitizing techniques. Crop types were determined using information obtained from the U.S. Department of Agriculture CFSA offices. Crop information not supplied by the CFSA was attributed by manual classification procedures. Automated methods to provide delineation of the field boundaries and land-use classification were investigated. It was determined that using these data sources, automated methods were less efficient and accurate than manual methods of delineating field boundaries and classifying land use.

Water-Resources Investigations Report↗

USGS2016

Integrated groundwater data management

The goal of a data manager is to ensure that data is safely stored, adequately described, discoverable and easily accessible. However, to keep pace with the evolution of groundwater studies in the last decade, the associated data and data management requirements have changed significantly. In particular, there is a growing recognition that management questions cannot be adequately answered by single discipline studies. This has led a push towards the paradigm of integrated modeling, where diverse parts of the hydrological cycle and its human connections are included. This chapter describes groundwater data management practices, and reviews the current state of the art with enterprise groundwater database management systems. It also includes discussion on commonly used data management models, detailing typical data management lifecycles. We discuss the growing use of web services and open standards such as GWML and WaterML2.0 to exchange groundwater information and knowledge, and the need for national data networks. We also discuss cross-jurisdictional interoperability issues, based on our experience sharing groundwater data across the US/Canadian border. Lastly, we present some future trends relating to groundwater data management.

Book chapter↗

USGS1986

Structure contour map of the tops of the Kreyenhagen Formation and Cretaceous strata in the Coalinga area, Fresno and Kings counties, California

This structure contour map, originally compiled during a study of the 1983 Coalinga earthquakes, shows the general structural configuration of the upper several kilometers of section in the Coalinga area. It was compiled by using electric well-log data available through April 1982 (Ammann Map Services, 1978; Petroleum Information Corporation, 1982; California Division of Oil and Gas, 1982) and surface geology (Dibblee, 1971; Mansfield, 1971).

California↗

USGS2001

A spatially referenced regression model (SPARROW) for suspended sediment in streams of the Conterminous U.S.

Suspended sediment has long been recognized as an important contaminant affecting water resources. Besides its direct role in determining water clarity, bridge scour and reservoir storage, sediment serves as a vehicle for the transport of many binding contaminants, including nutrients, trace metals, semi-volatile organic compounds, a nd numerous pesticides (U.S. Environmental Protection Agency, 2000a). Recent efforts to addr ess water-quality concerns through the Total Maximum Daily Load (TMDL) process have iden tified sediment as the single most prevalent cause of impairment in the Nation’s streams a nd rivers (U.S. Environmental Protection Agency, 2000b). Moreover, sediment has been identified as a medium for the tran sport and sequestration of organic carbon, playing a potentia lly important role in understa nding sources and sinks in the global carbon budget (Stallard, 1998). A comprehensive understanding of sediment fate a nd transport is considered essential to the design and implementation of effective plans for sediment management (Osterkamp and others, 1998, U.S. General Accounting Office, 1990). An exte nsive literature addr essing the problem of quantifying sediment transport has produced a nu mber of methods for estimating its flux (see Cohn, 1995, and Robertson and Roerish, 1999, for us eful surveys). The accuracy of these methods is compromised by uncertainty in the concentration measurements and by the highly episodic nature of sediment movement, particul arly when the methods are applied to smaller basins. However, for annual or decadal flux es timates, the methods are generally reliable if calibrated with extended periods of data (Robertson and Roerish, 1999). A substantial literature also supports the Universal Soil Loss Equation (U SLE) (Soil Conservation Service, 1983), an engineering method for estimating sheet and rill erosion, although the empirical credentials of the USLE have recently been questioned (Tri mble and Crosson, 2000). Conversely, relatively little direct evidence is available concerning the fate of sediment. The common practice of quantifying sediment fate with a sediment deliv ery ratio, estimated from a simple empirical relation with upstream basin area, does not artic ulate the relative importance of individual storage sites within a basin (Wolman, 1977). Rates of sediment deposition in reservoirs and flood plains can be determined from empirical measurement s , but only a limited number of sites have been monitored, and net rates of deposition or loss from other potential sinks and sources is largely unknown (Stallard, 1998). In particular, little is known about how much sediment loss from fields ultimately makes its way to stream channels, and how much sediment is subsequently stored in or lost from th e streambed (Meade and Parker, 1985, Trimble and Crosson, 2000). This paper reports on recent progress made to a ddress empirically the question of sediment fate and transport on a national scale. The model pres ented here is based on the SPAtially Referenced Regression On Watershed attr ibutes (SPARROW) methodology, fi rst used to estimate the distribution of nutrients in str eams and rivers of the United Stat es, and subsequently shown to describe land and stream processes affecting the delivery of nutrients (Smith and others, 1997, Alexander and others, 2000, Preston and Brakeb ill, 1999). The model makes use of numerous spatial datasets, available at the national level, to explain long-term sediment water-quality conditions in major streams and rivers throughou t the United States. Sediment sources are identified using sediment erosion rates from the National Resources I nventory (NRI) (Natural Resources Conservation Service, 2000) and apportioned over the landscape according to 30- meter resolution land-use information from th e National Land Cover Data set (NLCD) (U.S. Geological Survey, 2000a). More than 76,000 reservoirs from the National Inventory of Dams (NID) (U.S. Army Corps of Engin eers, 1996) are identified as pot ential sediment sinks. Other, non-anthropogenic sources and sinks are identified using soil in formation from the State Soil Survey Geographic (STATSGO) data base (Schwarz and Alexander, 1995) and spatial coverages representing surficial rock t ype and vegetative cover. The SPA RROW model empirically relates these diverse spatial datasets to estimates of long-term, mean annual sediment flux computed from concentration and flow measurements co llected over the period 1985 -95 from more than 400 monitoring stations maintained by the Na tional Stream Quality Accounting Network (Alexander and others, 1998), the National Wa ter Quality Assessment Program, and U.S. Geological Survey District offices (Turcios and Gray, in press). Th e calibrated model is used to estimate sediment flux for over 60,000 stream segments included in the River Reach File 1 (RF1) stream network (Alexander and others, 1999). SPARROW uses statis tical methods to calibrate a simple, structural model of riverine water quality, one that imposes mass ba lance in accounting for changes in contaminant flux. As applied here, the mass-balance approach facilitates the interpretation of model results in terms of physical processes affecting sediment transport, and makes possible the estimation of various rates of sediment generation and loss associated with stream channels and features of the landscape. The statistical approach provides a basi s for assessing the error of these inferred rates and of the error in extrapolated estimates of sediment flux made for streams in the RF1 network. An important implication of the holistic modeling approach adopted in this analysis is that estimates of sediment production and loss ar e based on, and therefore consistent with, measurements of in-stream flux. Other ancillary information, such as direct measurements of long-term sediment storage and release from rese rvoirs (Steffen, 1996), is incorporated into the analysis by specifying additional equations expl aining these ancillary variables. The imposition of cross-equation constraints affords this info rmation a statistically consistent weight in explaining in-stream sediment flux. Thus, the me thodology described here represents a general framework for synthesizing a wide spectrum of available information relevant to the understanding of sediment fate and transport.

Conterminous United States↗

USGS2022

Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density

Near-term ecological forecasts provide resource managers advance notice of changes in ecosystem services, such as fisheries stocks, timber yields, or water quality. Importantly, ecological forecasts can identify where there is uncertainty in the forecasting system, which is necessary to improve forecast skill and guide interpretation of forecast results. Uncertainty partitioning identifies the relative contributions to total forecast variance introduced by different sources, including specification of the model structure, errors in driver data, and estimation of current states (initial conditions). Uncertainty partitioning could be particularly useful in improving forecasts of highly variable cyanobacterial densities, which are difficult to predict and present a persistent challenge for lake managers. As cyanobacteria can produce toxic and unsightly surface scums, advance warning when cyanobacterial densities are increasing could help managers mitigate water quality issues. Here, we fit 13 Bayesian state-space models to evaluate different hypotheses about cyanobacterial densities in a low nutrient lake that experiences sporadic surface scums of the toxin-producing cyanobacterium, Gloeotrichia echinulata . We used data from several summers of weekly cyanobacteria samples to identify dominant sources of uncertainty for near-term (1- to 4-week) forecasts of G. echinulata densities. Water temperature was an important predictor of cyanobacterial densities during model fitting and at the 4-week forecast horizon. However, no physical covariates improved model performance over a simple model including the previous week's densities in 1-week-ahead forecasts. Even the best fit models exhibited large variance in forecasted cyanobacterial densities and did not capture rare peak occurrences, indicating that significant explanatory variables when fitting models to historical data are not always effective for forecasting. Uncertainty partitioning revealed that model process specification and initial conditions dominated forecast uncertainty. These findings indicate that long-term studies of different cyanobacterial life stages and movement in the water column as well as measurements of drivers relevant to different life stages could improve model process representation of cyanobacteria abundance. In addition, improved observation protocols could better define initial conditions and reduce spatial misalignment of environmental data and cyanobacteria observations. Our results emphasize the importance of ecological forecasting principles and uncertainty partitioning to refine and understand predictive capacity across ecosystems.

New Hampshire↗

USGS2014

Flood-inundation maps for the East Fork White River near Bedford, Indiana

Digital flood-inundation maps for an 1.8-mile reach of the East Fork White River near Bedford, Indiana (Ind.) were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent and depth of flooding corresponding to selectedwater levels (stages) at USGS streamgage 03371500, East Fork White River near Bedford, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/in/nwis/uv?site_no=03371500. In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages, including the East Fork White River near Bedford, Ind. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the East Fork White River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgage 03371500, East Fork White River near Bedford, Ind., and documented high-water marks from the flood of June 2008. The calibrated hydraulic model was then used to determine 20 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging (LiDAR) data having a 0.593-foot vertical accuracy) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage near Bedford, Ind., and forecasted stream stages from the NWS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery eforts.

Indiana↗

USGS2016

Flood-inundation maps for the Yellow River at Plymouth, Indiana

Digital flood-inundation maps for a 4.9-mile reach of the Yellow River at Plymouth, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 05516500, Yellow River at Plymouth, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/in/nwis/uv?site_no=05516500 . In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood-warning system ( http:/water.weather.gov/ahps/ ). The NWS AHPS forecasts flood hydrographs at many sites that are often collocated with USGS streamgages, including the Yellow River at Plymouth, Ind. NWS AHPS-forecast peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood and forecasts of flood hydrographs at this site. For this study, flood profiles were computed for the Yellow River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the current stage-discharge relations at the Yellow River streamgage, in combination with the flood-insurance study for Marshall County (issued in 2011). The calibrated hydraulic model was then used to determine eight water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The 1-percent annual exceedance probability flood profile elevation (flood elevation with recurrence intervals within 100 years) is within the calibrated water-surface elevations for comparison. The simulated water-surface profiles were then used with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging [lidar]) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage 05516500, Yellow River at Plymouth, Ind., and forecast stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.

Indiana↗

USGS2019

Framework for monitoring shrubland community integrity in California Mediterranean type ecosystems: Information for policy makers and land managers

Shrublands in Mediterranean‐type ecosystems worldwide support important ecosystem services including high levels of biodiversity and are threatened by multiple factors in heavily used landscapes. Use, conservation, and management of these landscapes involve diverse stakeholders, making decision processes complex. To be effective, management and land use decisions should be informed by current information on ecosystem quality and resilience. However, obtaining this information is often a challenge due to the extent of landscapes involved. Here we present a conceptual integrity monitoring framework based on simple easily observable ecosystem components readily understood by nonspecialists. Community integrity is defined by plant functional group based on relative proportion of shrubs and nonnative annual grasses. The ability to use these straightforward metrics results from four factors: relatively good alignment of characteristic bird, mammal, and insect communities with shrub cover, positive feedback between annual grasses and short fire intervals, the inhibitory effect of annual grasses on shrub seedling establishment, and similar functional group response to different disturbances. Two additional metrics, indicator species and shrub species diversity, capture subtle yet persistent signatures of disturbance on integrity not reflected in functional group composition. The framework is designed to: categorize habitats into ecosystem integrity classes, forecast likely integrity class changes caused by threats and environmental conditions, and provide a simple reporting mechanism that can be overlain with data on conservation status and vulnerabilities. The proposed framework includes a pilot phase to validate empirical relationships, thresholds, and sampling efficiency. The accessibility of these metrics to nonspecialists is anticipated to enhance communication among stakeholders and thus facilitate problem solving. Leveraging monitoring and mapping programs driven by other needs (e.g., species conservation and fire management) affords meaningful opportunities to offset program costs.

California↗

USGS2014

Flood-inundation maps for the North Branch Elkhart River at Cosperville, Indiana

Digital flood-inundation maps for a reach of the North Branch Elkhart River at Cosperville, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers, Detroit District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/in/nwis/uv?site_no=04100222 . In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system ( http:/water.weather.gov/ahps/ ). The NWS AHPS forecasts flood hydrographs at many places that are often colocated with USGS streamgages, including the North Branch Elkhart River at Cosperville, Ind. NWS AHPS-forecast peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the North Branch Elkhart River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind., and preliminary high-water marks from the flood of March 1982. The calibrated hydraulic model was then used to determine four water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging [LiDAR]) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind., and forecast stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

Indiana↗

USGS2018

Flood-inundation maps for the Wabash River at Lafayette, Indiana

Digital flood-inundation maps for an approximately 4.8-mile reach of the Wabash River at Lafayette, Indiana (Ind.) were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science web site at https://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 03335500, Wabash River at Lafayette, Ind. Current streamflow conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the internet at https://waterdata.usgs.gov/in/nwis/uv?site_no=03335500 . In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood-warning system ( https://water.weather.gov/ahps/ ). The NWS AHPS forecasts flood hydrographs at many places that are often colocated with USGS streamgages, including the Wabash River at Lafayette, Ind. NWS AHPS-forecast peak-stage information may be used with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the Wabash River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgage 03335500, Wabash River at Lafayette, Ind., and high-water marks from the flood of July 2003 (U.S. Army Corps of Engineers [USACE], 2007). The calibrated hydraulic model was then used to determine 23 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system digital elevation model derived from light detection and ranging to delineate the area flooded at each water level. The availability of these maps, along with internet information regarding current stage from the USGS streamgage 03335500, Wabash River at Lafayette, Ind., and forecasted high-flow stages from the NWS AHPS, will provide emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, and for postflood recovery efforts.

Indiana↗

USGS2012

Ecosystem services valuation to support decisionmaking on public lands—A case study of the San Pedro River watershed, Arizona

This report details the findings of the Bureau of Land Management–U.S. Geological Survey Ecosystem Services Valuation Pilot Study. This project evaluated alternative methods and tools that quantify and value ecosystem services, and it assessed the tools’ readiness for use in the Bureau of Land Management decisionmaking process. We tested these tools on the San Pedro River watershed in northern Sonora, Mexico, and southeast Arizona. The study area includes the San Pedro Riparian National Conservation Area (managed by the Bureau of Land Management), which has been a focal point for conservation activities and scientific research in recent decades. We applied past site-specific primary valuation studies, value transfer, the Wildlife Habitat Benefits Estimation Toolkit, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Artificial Intelligence for Ecosystem Services (ARIES) models to value locally important ecosystem services for the San Pedro River watershed—water, carbon, biodiversity, and cultural values. We tested these approaches on a series of scenarios to evaluate ecosystem service changes and the ability of the tools to accommodate scenarios. A suite of additional tools were either at too early a stage of development to run, were proprietary, or were place-specific tools inappropriate for application to the San Pedro River watershed. We described the strengths and weaknesses of these additional ecosystem service tools against a series of evaluative criteria related to their usefulness for Bureau of Land Management decisionmaking. Using these tools, we quantified gains or losses of ecosystem services under three categories of scenarios: urban growth, mesquite management, and water augmentation. These results quantify tradeoffs and could be useful for decisionmaking within Bureau of Land Management district or field offices. Results are accompanied by a relatively high level of uncertainty associated with model outputs, valuation methods, and discount rates applied. Further guidance on representing uncertainty and applying uncertain results in decisionmaking would benefit both tool developers and those offices in using ecosystem services to compare management tradeoffs. Decisionmakers and Bureau of Land Management managers at the State-, district-, and field-office level would also benefit from continuing model improvements, training, and guidance on tool use that can be provided by the U.S. Geological Survey, the Bureau of Land Management, and the Department of the Interior. Tradeoffs were identified in the level of effort needed to parameterize and run tools and the amount and quality of information they provide to the decision process. We found the Wildlife Habitat Benefits Estimation Toolkit, Ecosystem Services Review, and United Nations Environment Programme–World Conservation Monitoring Centre Ecosystem Services Toolkit to be immediately feasible for application by the Bureau of Land Management, given proper guidance on their use. It is also feasible for the Bureau of Land Management to use the InVEST model, but in early 2012 the process of parameterizing the model required resources and expertise that are unlikely to be available in most Bureau of Land Management district or field offices. Application of past primary valuation is feasible, but developing new primary-valuation studies is too time consuming for regular application. Value transfer approaches (aside from the Wildlife Habitat Benefits Estimation Toolkit) are best applied carefully on the basis of guidelines described in this report, to reduce transfer error. The ARIES model can provide useful information in regions modeled in the past (Arizona, California, Colorado, and Washington), but it lacks some features that will improve its usability, such as a generalized model that could be applied anywhere in the United States. Eleven other tools described in this report could become useful as the tools more fully develop, in high-profile cases for which additional resources are available for tool application or in case-study regions where place-specific models have already been developed. To improve the value of these tools in decisionmaking, we suggest scientific needs that agencies such as U.S. Geological Survey can help meet—for instance, development and support of data archives. Such archives could greatly reduce resource needs and improve the reliability and consistency of results. Given the rapid state of evolution in the field, periodic follow-up studies on ecosystem services tools would help to ensure that the Bureau of Land Management and other public land management agencies are kept up to date on new tools and features that bring ecosystem services closer to readiness for use in regular decisionmaking.

Arizona;Sonora↗

USGS2004

Three-dimensional geologic framework modeling of faulted hydrostratigraphic units within the Edwards aquifer, northern Bexar County, Texas

This report includes a digital, three-dimensional (3-D) faulted hydrostratigraphic model we have constructed to represent the geologic framework of the Edwards aquifer system in the area of San Antonio, northern Bexar County, Texas. The model is based on mapped geologic relationships that reflect the complex structures of the Balcones fault zone, detailed lithologic descriptions and interpretations of about 40 principal wells (and qualified data from numerous other wells), and a conceptual model of the gross geometry of the Edwards Group units derived from prior interpretations of depositional environments and paleogeography. The EarthVision 3-D software included in this publication is provided for use on four platforms: Windows 2000/XP, SGI, SUN, and Linux. Please see the Readme1.txt file for information about starting and using the software on each platform. The 3-D model and viewer software can be downloaded from this Web site, and they are also available on the CD-ROM version of this report, which is available as a sales item from Information Services, U.S. Geological Survey (1-888-ASK-USGS). Earth Vision software is the intellectual property of Dynamic Graphics, Inc., and is used here with their permission. Other than those rights granted to the USGS and third parties to assist them in using this product (any venue), Dynamic Graphics, Inc., reserves all rights in their software. Any appearances of trade, product, or firm names, or private logos, in or on this product do not, and are not intended to, imply endorsement by the U.S. Government.

Texas↗