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At least 397 records · Page 22Linked to original sources
USGS2025

Exposure, sensitivity, or adaptive capacity? Reviewing assessments that use only two of three elements of climate change vulnerability

As climate change accelerates, understanding which species are most vulnerable and why they are vulnerable will be vital to inform conservation action. Climate change vulnerability assessments (CCVAs) are tools to assess species' responses to climate change, detect drivers of vulnerability, and inform conservation planning. CCVAs are commonly composed of three elements: exposure, sensitivity, and adaptive capacity. Incorporating all three elements can be challenging, and including only two of the three elements may be a more feasible approach in many systems. Although two-element CCVA approaches have become more common, their utility and procedures remain poorly documented. We conducted a literature review to explore the scope, methods, and rationale of CCVAs that use a two-element approach to assess vertebrate vulnerability. Despite the potential to expand CCVAs into understudied systems, two-element assessments had similar geographic and taxonomic biases as those previously detected in CCVAs in general. Methods varied, yet we found that variables used in two-element studies could be condensed into standardized categories to enhance comparability. Finally, limitations in data availability and computational resources were common rationales for using a two-element approach. By clarifying the purposes, opportunities, and limitations of two-element assessment, this review can aid in selecting appropriate methods for CCVAs.

Conservation Science and Practice↗
USGS2017

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↗
USGS2014

Sediment data collected in 2012 from the northern Chandeleur Islands, Louisiana

As part of the Barrier Island Evolution Research project, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center collected sediment samples from the northern Chandeleur Islands in March and September 2012. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to better understand the depositional and erosional processes that drive the morphologic evolution of barrier islands over annual to interannual timescales (1 to 5 years). Between June 2010 and April 2011, in response to the Deepwater Horizon oil spill, the State of Louisiana constructed a sand berm extending more than 14 kilometers along the northern Chandeleur Islands platform. The construction of the berm provided a unique opportunity to investigate how this new sediment source will interact with and affect the morphologic evolution of the barrier-island system. Data collected from this study will be used to describe differences in the physical characteristics and spatial distribution of sediments both along the axis of the berm and also along transects across the berm and onto the adjacent barrier island. Comparison of these data with data from subsequent sampling efforts will provide information about sediment interactions and movement between the berm and the natural island platform, improving our understanding of short-term morphologic change and processes in this barrier-island system. This data series serves as an archive of sediment data collected in March and September 2012 from the Chandeleur Islands sand berm and adjacent barrier-island environments. Data products include descriptive core logs, core photographs and x-radiographs, results of sediment grain-size analyses, sample location maps, and Geographic Information System data files with accompanying formal Federal Geographic Data Committee metadata.

Louisiana↗
USGS2000

Forest soil chemistry and terrain attributes in a Catskills watershed

Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pH(w), effective cation-exchange capacity (CEC(e)), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pH(w) together explained 33 to 66% of the variation in exchangeable bases and CEC(e). Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CEC(e) (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CEC(e) occupied by H explained 44% of the variation in pH(w). Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pHw, effective cation-exchange capacity (CECe), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pHw together explained 33 to 66% of the variation in exchangeable bases and CECe. Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CECe (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CECe occupied by H explained 44% of the variation in pHw. Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.

New York↗
USGS2012

U.S. Geological Survey, National Wildlife Health Center, 2011 report of selected wildlife diseases

The National Wildlife Health Center (NWHC) was founded in 1975 to provide technical assistance in identifying, controlling, and preventing wildlife losses from diseases, conduct research to understand the impact of diseases on wildlife populations, and devise methods to more effectively manage these disease threats. The impetus behind the creation of the NWHC was, in part, the catastrophic loss of tens of thousands of waterfowl as a result of an outbreak of duck plague at the Lake Andes National Wildlife Refuge in South Dakota during January 1973. In 1996, the NWHC, along with other Department of Interior research functions, was transferred from the U.S. Fish and Wildlife Service to the U.S. Geological Survey (USGS), where we remain one of many entities that provide the independent science that forms the bases of the sound management of the Nation’s natural resources. Our mission is to provide national leadership to safeguard wildlife and ecosystem health through dynamic partnerships and exceptional science. The main campus of the NWHC is located in Madison, Wis., where we maintain biological safety level 3 (BSL–3) diagnostic and research facilities purposefully designed for work with wildlife species. The NWHC provides research and technical assistance on wildlife health issues to State, Federal, and international agencies. In addition, since 1992 we have maintained a field station in Hawaii, the Honolulu Field Station, which focuses on marine and terrestrial natural resources throughout the Pacific region. The NWHC conducts diagnostic investigations of unusual wildlife morbidity and mortality events nationwide to detect the presence of wildlife pathogens and determine the cause of death. This is also an important activity for detecting new, emerging and resurging diseases. The NWHC provides this crucial information on the presence of wildlife diseases to wildlife managers to support sound management decisions. The data and information generated also allows for further indepth analyses for determining the biological and ecological significance of disease events, detecting disease trends over time and space, as well as detecting any significant changes to how diseases manifest in the field. Moreover, this information allows us to gain insight into the significance of future wildlife disease events. The purpose of this report is to provide a sample of NWHC data that are available from our Laboratory Information Management System (LIMS). These data are presented in summary format with minimal statistical analysis and interpretation. The goal is to share these data with wildlife managers and other stakeholders, promote the use of NHWC data, and encourage the sharing of wildlife disease data to improve temporal and geographic surveillance coverage. Continued national surveillance for wildlife diseases is essential for providing early detection and warning of events that have the potential to result in harm to human health, economic losses, declines in wildlife populations, and subsequent ecological disturbances. Increased collaboration, coordination, and sharing of surveillance data will enhance this Nation’s ability to detect and respond to wildlife disease threats.

Scientific Investigations Report↗
USGS2012

Temporal genetic monitoring of hybridization between native westslope cutthroat trout and introduced rainbow trout in the Stehekin River, Washington

Introgressive hybridization with introduced rainbow trout (RBT) ( Oncorhynchus mykiss ) has led to the loss of native cutthroat trout species ( O. clarkii ) throughout their range, creating conservation concerns. Monitoring temporal hybridization trends provides resource managers with a tool for determining population status and information for establishing conservation goals for native cutthroat trout. In this study, we re-sampled six locations in 2010 within the Stehekin River watershed, North Cascades National Park, which were originally sampled between 1999 and 2003. We used genetic markers to monitor changes in hybridization levels between sampling periods in the native westslope cutthroat trout (WCT) ( O. c. lewisi ) stemming from past RBT introductions. Additionally, two new locations from the lower Stehekin drainage were added to the baseline data. We found that the frequency of WCT, RBT, and their hybrids was not significantly different between monitoring periods, but that RBT allele frequencies decreased in two locations and increased in one location. We also found a consistent, substantial reduction in the frequency of RBT alleles over the monitoring period in the Stehekin River upstream of Bridge Creek (SR3) compared to the Stehekin River downstream of Bridge Creek (SR1 -2) and within lower Bridge Creek (BR1) although these three locations are confined to a small geographic area (approximately 5 km). Ecological and/or evolutionary processes likely restrict the dispersal of RBT alleles in the Stehekin River upstream of Bridge Creek.

Washington↗
USGS2019

Handbook to the partners in flight population estimates database, version 3.0

This document describes the content of Version 3.0 of the Partners in Flight (PIF) Population Estimates Database, which provides population estimates for breeding USA/Canada landbirds at several geographic scales following the Partners in Flight approach described initially in Rich et al. (2004) and by Rosenberg and Blancher (2005) and most recently refined by Stanton et al. (2019). The Handbook also provides details about how the estimates were derived, information on limitations and caveats, a guide to using the estimates, and future desired directions for improving the estimates. This version of the database is intended as a companion to the Partners in Flight Landbird Conservation Plan: 2016 Revision for Canada and Continental United States (Rosenberg et al. 2016), although estimates for most species included in the database have been updated from those used in the 2016 Plan. Most of the estimates in the database are based on North American Breeding Bird Survey (BBS) data for landbirds from the decade 2006–2015. The information in this 2019 Version of the Handbook, for Version 3.0 of the database, describes all changes that have been made to the database since 2007 (Version 1.0, cf. Blancher et al. 2007)—including the additions documented in the Handbook for Version 2.0 (Blancher et al. 2013)—and therefore serves as a single source document describing the current database. Version 3.0 of the database addresses some of the recommendations suggested by Thogmartin et al. (2006) but does not yet fully address other limitations noted by Thogmartin et al. (2006), Blancher et al. (2007), Thogmartin (2010), Matsuoka et al. (2012), and Twedt (2015). By far, the most substantial change to the database comprises the incorporation of quantitative uncertainty bounds around population estimates for most species (see Stanton et al. 2019 for details). PIF Science anticipates that future versions of the database will occur in stages: first, improving elements of the basic PIF approach (e.g., incorporating more recent BBS data, updating Time of Day Adjustments, and refining Pair Adjustments); next, addressing additional concerns inherent in the PIF approach (e.g., replacing average maximum detection distance bins with research-derived species-specific effective detection radii); and later, perhaps replacing the sample-based PIF approach with a spatially-explicit, model-based (pixel-based) approach that more deliberately incorporates habitat and road biases and the proportion of birds available but not detected by current sampling methodology. This current Version 3.1 of the Handbook updates citations in the Literature Cited and incorporates relatively minor improvements in text clarity over the previous 3.0 version. The content of the Population Estimates Database itself remains the same except for changes to the global and USA/Canada estimates for Northern Bobwhite and Black Vulture.

Partners in Flight Technical Publication↗
USGS2012

Flood-inundation maps for Suwanee Creek from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, Gwinnett County, Georgia

Digital flood-inundation maps for a 6.9-mile reach of Suwanee Creek, from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, were developed by the U.S. Geological Survey (USGS) in cooperation with Gwinnett County, Georgia. 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 Suwanee Creek at Suwanee, Georgia (02334885). Current stage at this USGS streamgage may be obtained at http://waterdata.usgs.gov/ and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood-warning system ( http://water.weather.gov/ahps/ ). The NWS forecasts flood hydrographs at many places that commonly are collocated at USGS streamgages. The forecasted peak-stage information for the USGS streamgage at Suwanee Creek at Suwanee (02334885), available through the AHPS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers HEC-RAS software for Suwanee Creek and was used to compute flood profiles for a 6.9-mile reach of the creek. The model was calibrated using the most current stage-discharge relations at the Suwanee Creek at Suwanee streamgage (02334885). The hydraulic model was then used to determine 19 water-surface profiles for flood stages at the Suwanee Creek streamgage at 0.5-foot intervals referenced to the streamgage. The profiles ranged from just above bankfull stage (7.0 feet) to approximately 1.7 feet above the highest recorded water level at the streamgage (16.0 feet). The simulated water-surface profiles were then combined with a geographic information system digital elevation model - derived from light detection and ranging (LiDAR) data having a 5.0-foot horizontal resolution - to delineate the area flooded for each 0.5-foot increment of stream stage. The availability of these maps, when combined with real-time stage information from USGS streamgages and forecasted stream stage from the NWS, provides emergency management personnel and residents with critical information during flood-response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

Georgia↗
USGS2024

Existing evidence on the effects of climate variability and climate change on ungulates in North America: A systematic map

Background Climate is an important driver of ungulate life-histories, population dynamics, and migratory behaviors. Climate conditions can directly impact ungulates via changes in the costs of thermoregulation and locomotion, or indirectly, via changes in habitat and forage availability, predation, and species interactions. Many studies have documented the effects of climate variability and climate change on North America’s ungulates, recording impacts to population demographics, physiology, foraging behavior, migratory patterns, and more. However, ungulate responses are not uniform and vary by species and geography. Here, we present a systematic map describing the abundance and distribution of evidence on the effects of climate variability and climate change on native ungulates in North America. Methods We searched for all evidence documenting or projecting how climate variability and climate change affect the 15 ungulate species native to the U.S., Canada, Mexico, and Greenland. We searched Web of Science, Scopus, and the websites of 62 wildlife management agencies to identify relevant academic and grey literature. We screened English-language documents for inclusion at both the title and abstract and full-text levels. Data from all articles that passed full-text review were extracted and coded in a database. We identified knowledge clusters and gaps related to the species, locations, climate variables, and outcome variables measured in the literature. Review findings We identified a total of 674 relevant articles published from 1947 until September 2020. Caribou ( Rangifer tarandus ), elk ( Cervus canadensis ), and white-tailed deer ( Odocoileus virginianus ) were the most frequently studied species. Geographically, more research has been conducted in the western U.S. and western Canada, though a notable concentration of research is also located in the Great Lakes region. Nearly 75% more articles examined the effects of precipitation on ungulates compared to temperature, with variables related to snow being the most commonly measured climate variables. Most studies examined the effects of climate on ungulate population demographics, habitat and forage, and physiology and condition, with far fewer examining the effects on disturbances, migratory behavior, and seasonal range and corridor habitat. Conclusions The effects of climate change, and its interactions with stressors such as land-use change, predation, and disease, is of increasing concern to wildlife managers. With its broad scope, this systematic map can help ungulate managers identify relevant climate impacts and prepare for future changes to the populations they manage. Decisions regarding population control measures, supplemental feeding, translocation, and the application of habitat treatments are just some of the management decisions that can be informed by an improved understanding of climate impacts. This systematic map also identified several gaps in the literature that would benefit from additional research, including climate effects on ungulate migratory patterns, on species that are relatively understudied yet known to be sensitive to changes in climate, such as pronghorn ( Antilocapra americana ) and mountain goats ( Oreamnos americanus ), and on ungulates in the eastern U.S. and Mexico.

Environmental Evidence↗
USGS2017

Coastal bathymetry data collected in 2013 from the Chandeleur Islands, Louisiana

As part of the Barrier Island Evolution Research Project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys around the northern Chandeleur Islands, Louisiana, in July and August of 2013. The objective of the study is to better understand barrier-island geomorphic evolution, particularly storm-related depositional and erosional processes that shape the islands over annual to interannual timescales (1‒5 years). Collecting geophysical data will allow us to identify relationships between the geologic history of the island and its present day morphology and sediment distribution. This mapping effort was the third in a series of three planned surveys in this area. High resolution geophysical data collected in each of three consecutive years along this rapidly changing barrier island system will provide a unique time-series dataset that will significantly further the analyses and geomorphological interpretations of this and other coastal systems, improving our understanding of coastal response and evolution over short time scales (1‒5 years). This data series includes the geophysical data that were collected during two cruises (USGS Field Activity Numbers (FAN) 13BIM02, 13BIM03, and 13BIM04, in July 2013; and FANs 13BIM07 and 13BIM08 in August 2013) aboard the R/V Sallenger , the R/V Jabba Jaw , and the R/V Shark along the northern portion of the Chandeleur Islands, Breton National Wildlife Refuge, Louisiana. Primary data were acquired with the following equipment: (1) a Systems Engineering and Assessment, Ltd., SWATHplus interferometric sonar (468 kilohertz [kHz]), (2) an EdgeTech 424 (4‒24 kHz) chirp sub-bottom profiling system, and (3) two Odom Hydrographic Systems, Incorporated, Echotrach CV100 single beam echosounders. This data series report serves as an archive of processed interferometric swath and single-beam bathymetry data. Geographic information system data products include an interpolated digital elevation model, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata.

Louisiana↗
USGS2012

Flood-inundation maps for the Saddle River from Rochelle Park to Lodi, New Jersey, 2012

Digital flood-inundation maps for a 2.75-mile reach of the Saddle River from 0.2 mile upstream from the Interstate 80 bridge in Rochelle Park to 1.5 miles downstream from the U.S. Route 46 bridge in Lodi, New Jersey, were created by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection (NJDEP). 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 Saddle River at Lodi, New Jersey (station 01391500). 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/nwis/uv?site_no=01391500 . The National Weather Service (NWS) forecasts flood hydrographs at many places that are often collocated 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 using the most current stage-discharge relations at the Saddle River at Lodi, New Jersey streamgage and documented high-water marks from recent floods. The hydraulic model was then used to determine 11 water-surface profiles for flood stages at the Saddle River streamgage at 1-ft intervals referenced to the streamgage datum, North American Vertical Datum of 1988 (NAVD 88), and ranging from bankfull, 0.5 ft below NWS Action Stage, to the extent of the stage-discharge rating, which is approximately 1 ft higher than the highest recorded water level at the streamgage. Action Stage is the stage which when reached by a rising stream the NWS or a partner needs to take some type of mitigation action in preparation for possible significant hydrologic activity. The simulated water-surface profiles were then combined with a geographic information system 3-meter (9.84-ft) digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. 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.

New Jersey↗
USGS2020

A socio-environmental geodatabase for integrative research in the transboundary Rio Grande/Río Bravo basin

Management of water resources in the transboundary Rio Grande/Río Bravo Basin (the Basin) presents challenges for state and Federal entities in the United States and Mexico making management decisions on shared water resources. Damming, channelization, water availability, and allocation are governed by water rights and water-sharing agreements. Data and information sharing are important aspects of transboundary cooperation, but differences in format, content, spatial and temporal resolution, and language hinder collaboration. In addition, data on the kinds and geographic distribution of water governance and management institutions across the Basin have not been consistently documented. Existing data disparities parallel the hydrological and social fragmentation of the Basin. Seeking to underscore the interdependence between social and environmental processes in the Basin, anthropologists and modelers collaborated to develop a socio-environmental geodatabase. This geodatabase is a first step in modeling the social components of decision making and their connectivity to environmental processes across the Basin. The geodatabase is available in an open-access domain and contains geospatial data related to water and land governance, hydrology, water use and hydraulic infrastructure, socioeconomics, and the biophysical environment necessary to advance the understanding of basin dynamics. Having these data documented and compiled in a central location serves as a resource to help decision makers better understand upstream and downstream social-environmental characteristics. This knowledge is useful for developing sustainable water management policies in a region where water resources are increasingly under pressure from climatic, environmental, and human-related changes.

Chihuahua, New Mexico, Texas↗
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↗
USGS2017

Flood-inundation maps for the Meramec River at Valley Park and at Fenton, Missouri, 2017

Two sets of digital flood-inundation map libraries that spanned a combined 16.7-mile reach of the Meramec River that extends upstream from Valley Park, Missouri, to downstream from Fenton, Mo., were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers, St. Louis Metropolitan Sewer District, Missouri Department of Transportation, Missouri American Water, and Federal Emergency Management Agency Region 7. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website 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 the cooperative USGS streamgages on the Meramec River at Valley Park, Mo., (USGS station number 07019130) and the Meramec River at Fenton, Mo. (USGS station number 07019210). Near-real-time stage data at these streamgages may be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/ , which also forecasts flood hydrographs at these sites (listed as NWS sites vllm7 and fnnm7, respectively). Flood profiles were computed for the stream reaches by means of a calibrated one-dimensional step-backwater hydraulic model. The model was calibrated using a stage-discharge relation at the Meramec River near Eureka streamgage (USGS station number 07019000) and documented high-water marks from the flood of December 2015 through January 2016. The calibrated hydraulic model was used to compute two sets of water-surface profiles: one set for the streamgage at Valley Park, Mo. (USGS station number 07019130), and one set for the USGS streamgage on the Meramec River at Fenton, Mo. (USGS station number 07019210). The water-surface profiles were produced for stages at 1-foot (ft) intervals referenced to the datum from each streamgage and ranging from the NWS action stage, or near bankfull discharge, to the stage corresponding to the estimated 0.2-percent annual exceedance probability (500-year recurrence interval) flood, as determined at the Eureka streamgage (USGS station number 07019000). The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.28-ft vertical accuracy and 3.28-ft horizontal resolution) to delineate the area flooded at each flood stage (water level). The availability of these maps, along with internet information regarding current stage from the USGS streamgages and forecasted high-flow stages from the NWS, 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.

Missouri↗
USGS2013

Flood-inundation maps for the Saddle River from Upper Saddle River Borough to Saddle River Borough, New Jersey, 2013

Digital flood-inundation maps for a 4.1-mile reach of the Saddle River from 0.6 miles downstream from the New Jersey-New York State boundary in Upper Saddle River Borough to 0.2 miles downstream from the East Allendale Road bridge in Saddle River Borough, New Jersey, were created by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection (NJDEP). 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 select water levels (stages) at the USGS streamgage 01390450, Saddle River at Upper Saddle River, New Jersey. 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/nwis/uv?site_no=01390450. The National Weather Service (NWS) forecasts flood hydrographs at many places that are often collocated 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 (in effect March 2013) at USGS streamgage 01390450, Saddle River at Upper Saddle River, New Jersey, and documented high-water marks from recent floods. The hydraulic model was then used to determine eight water-surface profiles for flood stages at 0.5-foot (ft) intervals referenced to the streamgage datum, North American Vertical Datum of 1988 (NAVD 88), and ranging from bankfull, 0.5 ft below NWS Action Stage, to the upper extent of the stage-discharge rating which is approximately 1 ft higher than the highest recorded water level at the streamgage. Action Stage is the stage which when reached by a rising stream the NWS or a partner needs to take some type of mitigation action in preparation for possible significant hydrologic activity. The simulated water-surface profiles were then combined with a geographic information system 3-meter (9.84 ft) digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps along with real-time streamflow data and 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.

New Jersey↗
USGS2014

Flood inundation maps for the Wabash and Eel Rivers at Logansport, Indiana

Digital flood-inundation maps for an 8.3-mile reach of the Wabash River and a 7.6-mile reach of the Eel River at Logansport, 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 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 Wabash River at Logansport, Ind. (sta. no. 03329000) and USGS streamgage Eel River near Logansport, Ind. (sta. no. 03328500). 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 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. 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 stream reaches by means of a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgages 03329000, Wabash River at Logansport, Ind., and 03328500, Eel River near Logansport, Ind. The calibrated hydraulic model was then used to determine five water-surface profiles for flood stage at 1-foot intervals referenced to the Wabash River streamgage datum, and four water-surface profiles for flood stages at 1-foot intervals referenced to the Eel River streamgage datum. The stages range from bankfull to approximately the highest stages that have occurred since 1967 when three flood control dams were built upstream of Logansport, Ind. 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 0.37-foot vertical accuracy and 3.9-foot horizontal resolution) in order to delineate the area flooded at each stage. The availability of these maps, along with information available on the Internet regarding current stages from the USGS streamgages at Logansport, 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 post flood recovery efforts.

Indiana↗
USGS2013

Flood-inundation maps for a 6.5-mile reach of the Kentucky River at Frankfort, Kentucky

Digital flood-inundation maps for a 6.5-mile reach of Kentucky River at Frankfort, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Frankfort Office of Emergency Management. 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 Kentucky River at Lock 4 at Frankfort, Kentucky (station no. 03287500). Current conditions for the USGS streamgage may be obtained online at the USGS National Water Information System site (http://waterdata.usgs.gov/nwis/inventory?agency_code=USGS&site_no=03287500). 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 at USGS streamgages. The forecasted peak-stage information, also available on the Internet, 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 Kentucky River reach by using HEC–RAS, a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current (2013) stage-discharge relation for the Kentucky River at Lock 4 at Frankfort, Kentucky, in combination with streamgage and high-water-mark measurements collected for a flood event in May 2010. The calibrated model was then used to calculate 26 water-surface profiles for a sequence of flood stages, at 1-foot intervals, referenced to the streamgage datum and ranging from a stage near bankfull to the elevation that breached the levees protecting the City of Frankfort. To delineate the flooded area at each interval flood stage, the simulated water-surface profiles were combined with a digital elevation model (DEM) of the study area by using geographic information system software. The DEM consisted of bare-earth elevations within the study area and was derived from a Light Detection And Ranging (LiDAR) dataset having a 5.0-foot horizontal resolution and an accuracy of 0.229 foot. The availability of these maps, along with Internet information regarding current stages from USGS streamgages and forecasted stages from the NWS, provides emergency management personnel and local residents with critical information for flood response activities such as evacuations, road closures, and postflood recovery efforts.

Kentucky↗
USGS2015

Flood-inundation maps for Big Creek from the McGinnis Ferry Road bridge to the confluence of Hog Wallow Creek, Alpharetta and Roswell, Georgia

Digital flood-inundation maps for a 12.4-mile reach of Big Creek that extends from 260 feet above the McGinnis Ferry Road bridge to the U.S. Geological Survey (USGS) streamgage at Big Creek below Hog Wallow Creek at Roswell, Georgia (02335757), were developed by the USGS in cooperation with the cities of Alpharetta and Roswell, Georgia. 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 Big Creek near Alpharetta, Georgia (02335700). Real-time stage information from this USGS streamgage may be obtained at http://waterdata.usgs.gov/ and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood-warning system http://water.weather.gov/ahps/ ). The NWS forecasts flood hydrographs for many streams where the USGS operates streamgages and provides flow data. The forecasted peak-stage information for the USGS streamgage at Big Creek near Alpharetta (02335700), available through the AHPS Web site, may be used in conjunction with the maps developed for this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers HEC–RAS software for Big Creek and was used to compute flood profiles for a 12.4-mile reach of Big Creek. The model was calibrated using the most current (2015) stage-discharge relations at two USGS streamgages on Big Creek: Big Creek near Alpharetta (02335700) and Big Creek below Hog Wallow Creek at Roswell (02335757). The hydraulic model was then used to simulate 19 water-surface profiles at 0.5-foot intervals at the Big Creek near Alpharetta streamgage. The profiles ranged from just above bankfull stage (6.0 feet) to approximately 1.95 feet above the highest recorded water level at the Alpharetta streamgage site (15.0 feet). The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from light detection and ranging data having a 3.0-foot horizontal resolution—to delineate the area flooded at each 0.5-foot interval of stream stage. The availability of these maps, when combined with real-time stage information from USGS streamgages and forecasted stream stage from the NWS, provides emergency management personnel and residents with critical information during flood-response activities such as evacuations and road closures, in addition to post-flood recovery efforts.

Georgia↗