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At least 559 records · Page 31Linked to original sources
USGS2018

New England and northern New York forest ecosystem vulnerability assessment and synthesis: A report from the New England Climate Change Response Framework project

Forest ecosystems will face direct and indirect impacts from a changing climate over the 21st century. This assessment evaluates the vulnerability of forest ecosystems across the New England region (Connecticut, Maine, Massachusetts, New Hampshire, northern New York, Rhode Island, and Vermont) under a range of future climates. We synthesized and summarized information on the contemporary landscape, provided information on past climate trends, and described a range of projected future climates. This information was used to parameterize and run multiple vegetation impact models, which provided a range of potential vegetative responses to climate. Finally, we brought these results before a multidisciplinary panel of scientists and natural resource professionals familiar with the forests of this region to assess ecosystem vulnerability through a formal consensus-based expert elicitation process. Observed trends in climate over the historical record from 1901 through 2011 show that the mean annual temperature has increased across the region by 2.4 °F, with even greater warming during winter. Precipitation patterns also changed during this time, with a slight trend toward greater annual precipitation and a substantial increase in extreme precipitation events. Projected climate trends using downscaled global climate model data indicate a potential increase in mean annual temperature of 3 to 8 °F for the assessment area by 2100. Projections for precipitation indicate an increase in fall and winter precipitation, and spring and summer precipitation projections vary by scenario. We identified potential impacts on forests by incorporating these future climate projections into three forest impact models (DISTRIB, LINKAGES, and LANDIS PRO). Model projections suggest that many northern and boreal species, including balsam fir, red spruce, and black spruce, may fare worse under future conditions, but other species may benefit from projected changes in climate. Published literature on climate impacts related to wildfire, invasive species, and forest pests and diseases also contributed to the overall determination of climate change vulnerability. We assessed vulnerability for eight forest communities in the assessment area. The assessment was conducted through a formal elicitation process with 20 scientists and resource managers from across the area, who considered vulnerability in terms of the potential impacts and the adaptive capacity for an individual community. Montane spruce-fir, low-elevation spruce-fir, and lowland mixed conifer forests were determined to be the most vulnerable communities. Central hardwoods, transition hardwoods, and pitch pine-scrub oak forests were perceived as having lower vulnerability to projected changes in climate. These projected changes in climate and the associated impacts and vulnerabilities will have important implications for economically valuable timber species, forest-dependent animals and plants, recreation, and long-term natural resource planning.

Connecticut, Maine, Massachusetts, New Hampshire, ↗
USGS2017

Using science to inform management and improve biological conservation in the Desert Renewable Energy Conservation Plan

The Mojave and Colorado deserts of southern California have been viewed as vast wilderness since early exploration and, until recently, were considered the most untrammeled among western landscapes in the contiguous lower 48 states (United States Department of Agriculture 1893; Leu et al. 2008). However, the factors that define desert wilderness—small human population, temperature differentials that create unrelenting winds, low rainfall, and cloudless skies—are attractive for renewable energy development. The demand for clean, renewable energy is a national and regional priority and has increased demand for large-scale solar and wind farms in the deserts, particularly in California. The need to balance these national and state energy priorities with existing natural resource and land conservation policies has emerged as a landscape-scale land-use planning initiative known as the Desert Renewable Energy Conservation Plan (DRECP). One of the primary goals for the DRECP was to establish Development Focus Areas (DFAs) where high-quality renewable energy potential of up to 20 gigawatts (GW) could be implemented by the year 2040. DFAs were designed to provide expedited project approvals in locations where environmental impacts could be managed and mitigated, and proximity to transmission corridors provides for the efficient dissemination of energy to users. The DRECP also aims to identify protections for natural resources, recreation, and cultural resources. This plan identifies 37 covered species that receive special consideration in the DRECP. Among the special considerations are climate adaptation requirements, such as the ability to maintain population connectivity through wildlife corridors, while protecting several special recreation areas and 32,000 known cultural sites that are dispersed throughout the region. We evaluated several particular aspects of the DRECP design and process. In particular, we examined land designations in relation to published studies on Mohave ground squirrel (Xerospermophilus mohavensis) habitat and genetic diversity patterns of a suite of broadly distributed desert animal species. The squirrel and its habitat are of particular interest because the entire range of the squirrel is encompassed by the DRECP. We describe the framework of the DRECP, provide a case study of how the DRECP accommodates the needs of the Mohave ground squirrel and its habitat, illustrate DFAs in relation to the genetic diversity of a broad range of terrestrial biota, and conclude with some observations on how land-use issues were resolved across the landscape under various scenarios.

Conference Paper↗
USGS2017

A guide to multi-objective optimization for ecological problems with an application to cackling goose management

Choices in ecological research and management are the result of balancing multiple, often competing, objectives. Multi-objective optimization (MOO) is a formal decision-theoretic framework for solving multiple objective problems. MOO is used extensively in other fields including engineering, economics, and operations research. However, its application for solving ecological problems has been sparse, perhaps due to a lack of widespread understanding. Thus, our objective was to provide an accessible primer on MOO, including a review of methods common in other fields, a review of their application in ecology, and a demonstration to an applied resource management problem. A large class of methods for solving MOO problems can be separated into two strategies: modelling preferences pre-optimization (the a priori strategy), or modelling preferences post-optimization (the a posteriori strategy). The a priori strategy requires describing preferences among objectives without knowledge of how preferences affect the resulting decision. In the a posteriori strategy, the decision maker simultaneously considers a set of solutions (the Pareto optimal set) and makes a choice based on the trade-offs observed in the set. We describe several methods for modelling preferences pre-optimization, including: the bounded objective function method, the lexicographic method, and the weighted-sum method. We discuss modelling preferences post-optimization through examination of the Pareto optimal set. We applied each MOO strategy to the natural resource management problem of selecting a population target for cackling goose ( Branta hutchinsii minima ) abundance. Cackling geese provide food security to Native Alaskan subsistence hunters in the goose's nesting area, but depredate crops on private agricultural fields in wintering areas. We developed objective functions to represent the competing objectives related to the cackling goose population target and identified an optimal solution first using the a priori strategy, and then by examining trade-offs in the Pareto set using the a posteriori strategy. We used four approaches for selecting a final solution within the a posteriori strategy; the most common optimal solution, the most robust optimal solution, and two solutions based on maximizing a restricted portion of the Pareto set. We discuss MOO with respect to natural resource management, but MOO is sufficiently general to cover any ecological problem that contains multiple competing objectives that can be quantified using objective functions.

Ecological Modelling↗
USGS2014

Optimization in the utility maximization framework for conservation planning: a comparison of solution procedures in a study of multifunctional agriculture

Quantitative methods of spatial conservation prioritization have traditionally been applied to issues in conservation biology and reserve design, though their use in other types of natural resource management is growing. The utility maximization problem is one form of a covering problem where multiple criteria can represent the expected social benefits of conservation action. This approach allows flexibility with a problem formulation that is more general than typical reserve design problems, though the solution methods are very similar. However, few studies have addressed optimization in utility maximization problems for conservation planning, and the effect of solution procedure is largely unquantified. Therefore, this study mapped five criteria describing elements of multifunctional agriculture to determine a hypothetical conservation resource allocation plan for agricultural land conservation in the Central Valley of CA, USA. We compared solution procedures within the utility maximization framework to determine the difference between an open source integer programming approach and a greedy heuristic, and find gains from optimization of up to 12%. We also model land availability for conservation action as a stochastic process and determine the decline in total utility compared to the globally optimal set using both solution algorithms. Our results are comparable to other studies illustrating the benefits of optimization for different conservation planning problems, and highlight the importance of maximizing the effectiveness of limited funding for conservation and natural resource management.

California↗
USGS2015

Aquatics Systems Branch: transdisciplinary research to address water-related environmental problems

The Aquatic Systems Branch at the Fort Collins Science Center is a group of scientists dedicated to advancing interdisciplinary science and providing science support to solve water-related environmental issues. Natural resource managers have an increasing need for scientific information and stakeholders face enormous challenges of increasing and competing demands for water. Our scientists are leaders in ecological flows, riparian ecology, hydroscape ecology, ecosystem management, and contaminant biology. The Aquatic Systems Branch employs and develops state-of-the-science approaches in field investigations, laboratory experiments, remote sensing, simulation and predictive modeling, and decision support tools. We use the aquatic experimental laboratory, the greenhouse, the botanical garden and other advanced facilities to conduct unique research. Our scientists pursue research on the ground, in the rivers, and in the skies, generating and testing hypotheses and collecting quantitative information to support planning and design in natural resource management and aquatic restoration.

Fact Sheet↗
USGS2022

Use of a riverscape-scale model of fundamental physical habitat requirements for freshwater mussels to quantify mussel declines in a mining-contaminated stream: The Big River, Old Lead Belt, Southeast Missouri

The research described in this report was conducted as part of the Natural Resource Damage Assessment and Restoration process in the Big River. Our purpose was to compare habitat features and landscape factors that may be important for the establishment and persistence of mussel concentrations between the Big River and the adjacent Bourbeuse and Meramec rivers, thereby testing their appropriateness as reference systems for establishing baseline expectations of mussel populations in the absence of mining impacts for the Big River. Based on these comparisons and a published model dileneating suitable habitat for freshwater mussels, we establish expected baseline conditions related to suitable freshwater mussel habitat in the Big River to assist injury determination for mining-related impacts in the Southeast Missouri Lead Mining District Natural Resource Damage Assessment case.

Missouri↗
USGS2022

Tennessee and Landsat

From the flat, rich soil of western Tennessee to the Appalachian Mountains in the east, and rolling hills in between, “the Volunteer State” enjoys a wealth of natural resources. The Tennessee, Cumberland, and Mississippi Rivers supply economically crucial navigation routes, along with recreation for residents and visitors. Additionally, 14 million acres of hardwood and softwood forests cover roughly one-half of the State, contributing an estimated $24 billion and nearly 100,000 jobs to Tennessee’s economy. Within a span of more than 400 miles, the State’s diverse agricultural products include cotton, corn, soybeans, poultry, horses, cattle, goats, hay, vegetables, nursery crops, and tobacco. Energy production is important to Tennessee and the region, and power sources range from coal and nuclear to hydroelectric sources. Tourism also is a key industry, and music attractions and historical sites are balanced by natural features such as the Great Smoky Mountains National Park, which recorded 14.1 million visits and ranked second for most visited National Park Service site in the United States in 2021. Landsat imagery’s broad geographic scale and rich historical archive have proven useful to land managers and State agencies for monitoring natural resources. Here are several ways Landsat has benefited Tennessee.

Tennessee↗
USGS2026

Colocating artificial intelligence data centers with energy infrastructure on Federal public lands—A science synthesis and spatial analysis to inform decision making

Executive Summary Artificial intelligence (AI) is rapidly transforming industries and economies, creating an urgent need to strategically plan for the energy and infrastructure required to support increasing AI use. U.S. Federal agencies and bureaus have been directed to explore ways to accelerate permitting, development, and deployment of energy resources and AI technologies, including encouraging the colocation of energy infrastructure and data centers. To inform these initiatives, this report synthesizes relevant scientific information and presents a spatial analysis of existing energy infrastructure and data centers on or near U.S. Federal public lands managed by the Bureau of Land Management (BLM). The purpose of this science synthesis and spatial analysis is to provide the BLM with foundational information for considering potential colocation of data centers with energy infrastructure on Federal public lands to support evidence-based decisions. Additionally, this report provides insight into current (2025) and potential future energy demands by providing projections of a range of potential future environmental conditions relevant to maintaining industry-recommended cooling temperature standards necessary for efficient data center operations. As a part of this effort, a rapid response literature review was conducted of the best available science on the topic of data center development and energy infrastructure in July–August 2025, supplemented by additional resources recommended by U.S. Federal agency and bureau subject matter experts (hereafter experts; including the U.S. Department of Energy National Laboratory of the Rockies) and peer reviewers. To better understand current conditions relevant to AI data center development, a spatial analysis was conducted across Alaska and 11 States in the Western United States, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming, all of which contain extensive BLM-managed surface lands (hereafter referred to as “BLM lands”) that could be considered for the colocation of energy infrastructure and AI data centers. This effort identified BLM lands within 10 miles of existing transmission lines, consistent with methods used in previous BLM programmatic environmental impact statements. This report describes the types of data centers operating within the United States, which vary in ownership, size, technology, and proximity to end users. This report then outlines the primary considerations of data center development, including reliable energy supply, natural resources (such as water availability to support cooling requirements), and relevant policy and regulatory considerations. Energy supply considerations are pivotal for data center operation. Between 2014 and 2018, data centers in the United States accounted for nearly 2 percent of the Nation’s total electricity consumption, and data center energy consumption is projected to increase from 2 to 6.7–12 percent of total U.S. electricity use by 2028. These energy requirements necessitate careful consideration of energy supply when considering potentially suitable locations for data center development. Experts anticipate that an increase in renewable energy generation will likely support most potential future power demand needs, including for data centers, followed by increases in natural gas, nuclear, and geothermal energy production. Additional capacity in the form of battery storage will likely not generate electricity, but may improve the reliability and flexibility of supply, helping to ensure that growing data center loads can be met. However, the U.S. Department of Energy estimates that the United States will need, on average, 57 percent more energy transmission infrastructure by 2035 to account for the growing power demand introduced by development such as data centers. Cooling server equipment in data centers requires large amounts of electricity and water, and this demand can be exacerbated by hot and humid conditions. Energy efficient water-based cooling technologies may reduce electricity consumption onsite but require more water consumption. This additional water demand has the potential to increase water stress and competition with other users. As such, developing data centers will likely need a thorough assessment of current and potential future water availability, as well as consideration of how water demand may change across other sectors. Data center development involves policy and regulatory considerations, as projects must undergo environmental review and authorization processes that can take 18–24 months. Coordinating these environmental reviews and authorizations with other energy development projects, such as building new transmission lines, may cause additional delays. Recent efforts by the U.S. Department of Energy and U.S. Department of the Interior aim to expedite environmental reviews and authorizations and improve coordination across agencies. The spatial analysis identified 771 existing AI data centers and more than 3,300 power plants. The spatial analysis found that 6 percent of AI data centers and 22 percent of power plants in the Western United States were on or within 1 mile of BLM lands, and California had the largest number of facilities. Most existing AI data centers were near high-voltage transmission lines and close to power plants, supporting efficient energy delivery. More than 90,000,000 acres of BLM lands were within 10 miles of existing high-voltage transmission lines, representing 38 percent of BLM lands in the study area. Available transmission infrastructure and the overlap with BLM lands varied by State, and Alaska had limited overlap compared to the rest of the Western United States. To operate most efficiently, data center temperatures must be at or below 80.6 degrees Fahrenheit. This analysis of future temperature and precipitation projections indicated increasing cooling demands for data centers, particularly in Arizona, California, and Nevada, where rising temperatures are expected to increase energy and operational costs while potentially stressing current regional electrical grid infrastructure. This report highlights relevant energy supply, natural resources, and regulatory considerations for data center development on BLM lands. This report does not provide a comprehensive ecological, regulatory, land suitability, or permitting analysis. The factors described here are contextual considerations only and are not intended to identify, rank, quantify, or recommend optimal areas for data center colocation. This spatial analysis focused solely on energy considerations relevant to data centers and did not consider water availability, critical habitats, BLM National Conservation Lands, areas of cultural or historical significance, and other sensitive resources. These topics are recognized as critical but were not within the scope of this science synthesis and spatial analysis.

Scientific Investigations Report↗
USGS2000

Ground-water flow and water quality of the Indian Island well field near Grand Island, Nebraska, 1994-95

Ground water is the principal source of water for public and self-supplied domestic use in Nebraska. Ground water supplied about 235 Mgal/d (million gallons per day) in 1990, or about 78 percent of the estimated public-water supply in Nebraska. In addition, ground water supplied about 1,017 Mgal/d, or about 83 percent of the irrigation water in the Platte River Valley (Nebraska Natural Resources Commission, 1994). Withdrawing ground water in the valley induces recharge from the river and has the potential to change ground-water quality near the river where many public-supply wells are located. The Platte River alluvial aquifer, which underlies the Platte River Valley (fig. 1), is the single most important source of water for public supply in central and eastern Nebraska. The aquifer, which is part of the High Plains aquifer, consists of stream-laid deposits of sand and gravel with discontinuous layers of clay and silt, and is connected hydraulically to the Platte River. The aquifer provides about 117 Mgal/d, or nearly 50 percent of the total daily ground-water production for Nebraska (Nebraska Natural Resources Commission, 1994). The aquifer also supplies water to Nebraska's largest cities including Kearney, Grand Island, Lincoln, and Omaha.

Fact Sheet↗
USGS2018

Aligning environmental management with ecosystem resilience: a First Foods example from the Confederated Tribes of the Umatilla Indian Reservation, Oregon, USA

The concept of “reciprocity” between humans and other biota arises from the creation belief of the Confederated Tribes of the Umatilla Indian Reservation (CTUIR). The concept acknowledges a moral and practical obligation for humans and biota to care for and sustain one another, and arises from human gratitude and reverence for the contributions and sacrifices made by other biota to sustain human kind. Reciprocity has become a powerful organizing principle for the CTUIR Department of Natural Resources, fostering continuity across the actions and policies of environmental management programs at the CTUIR. Moreover, reciprocity is the foundation of the CTUIR “First Foods” management approach. We describe the cultural significance of First Foods, the First Foods management approach, a resulting management vision for resilient and functional river ecosystems, and subsequent shifts in management goals and planning among tribal environmental staff during the first decade of managing for First Foods. In presenting this management approach, we highlight how reciprocity has helped align human values and management goals with ecosystem resilience, yielding management decisions that benefit individuals and communities, indigenous and nonindigenous, as well as human and nonhuman. We further describe the broader applicability of reciprocity-based approaches to natural resource management.

Oregon↗
USGS2016

Participatory modeling and structured decision making

Structured decision making (SDM) provides a framework for making sound decisions even when faced with uncertainty, and is a transparent, defensible, and replicable method used to understand complex problems. A hallmark of SDM is the explicit incorporation of values and science, which often includes participation from multiple stakeholders, helping to garner trust and ultimately result in a decision that is more likely to be implemented. The core steps in the SDM process are used to structure thinking about natural resources management choices, and include: (1) properly defining the problem and the decision context, (2) determining the objectives that help describe the aspirations of the decision maker, (3) devising management actions or alternatives that can achieve those objectives, (4) evaluating the outcomes or consequences of each alternative on each of the objectives, (5) evaluating trade-offs, and (6) implementing the decision. Participatory modeling for SDM includes engaging stakeholders in some or all of the steps of the SDM process listed above. In addition, participatory modeling often is crucial for creating qualitative and quantitative models of how the system works, providing data for these models, and eliciting expert opinion when data are unavailable. In these ways, SDM provides a framework for decision making in natural resources management that includes participation from stakeholder groups throughout the process, including the modeling phase.

Book chapter↗
USGS2007

Comparison of peak-flow estimation methods for small drainage basins in Maine

Understanding the accuracy of commonly used methods for estimating peak streamflows is important because the designs of bridges, culverts, and other river structures are based on these flows. Different methods for estimating peak streamflows were analyzed for small drainage basins in Maine. For the smallest basins, with drainage areas of 0.2 to 1.0 square mile, nine peak streamflows from actual rainfall events at four crest-stage gaging stations were modeled by the Rational Method and the Natural Resource Conservation Service TR-20 method and compared to observed peak flows. The Rational Method had a root mean square error (RMSE) of -69.7 to 230 percent (which means that approximately two thirds of the modeled flows were within -69.7 to 230 percent of the observed flows). The TR-20 method had an RMSE of -98.0 to 5,010 percent. Both the Rational Method and TR-20 underestimated the observed flows in most cases. For small basins, with drainage areas of 1.0 to 10 square miles, modeled peak flows were compared to observed statistical peak flows with return periods of 2, 50, and 100 years for 17 streams in Maine and adjoining parts of New Hampshire. Peak flows were modeled by the Rational Method, the Natural Resources Conservation Service TR-20 method, U.S. Geological Survey regression equations, and the Probabilistic Rational Method. The regression equations were the most accurate method of computing peak flows in Maine for streams with drainage areas of 1.0 to 10 square miles with an RMSE of -34.3 to 52.2 percent for 50-year peak flows. The Probabilistic Rational Method was the next most accurate method (-38.5 to 62.6 percent). The Rational Method (-56.1 to 128 percent) and particularly the TR-20 method (-76.4 to 323 percent) had much larger errors. Both the TR-20 and regression methods had similar numbers of underpredictions and overpredictions. The Rational Method overpredicted most peak flows and the Probabilistic Rational Method tended to overpredict peak flows from the smaller (less than 5 square miles) drainage basins and underpredict peak flows from larger drainage basins. The results of this study are consistent with the most comprehensive analysis of observed and modeled peak streamflows in the United States, which analyzed statistical peak flows from 70 drainage basins in the Midwest and the Northwest.

Maine↗
USGS2020

Trends in streamflow and precipitation for selected sites in the Elkhorn River Basin and in streamflow in the Salt Creek and Platte River Basins, Nebraska, 1961–2011

To better understand the streamflow trends at the streamgages in the Elkhorn River Basin in Nebraska, the U.S. Geological Survey (USGS) in cooperation with the Lower Elkhorn Natural Resources District further investigated streamflow trends at the eight streamgages on the Elkhorn River, Salt Creek, and the Lower Platte River that indicated a positive trend in streamflow characteristics and analyzed precipitation trends in the four basins upstream from the Elkhorn River Basin streamgages. An analysis of four streamgages in the Elkhorn River Basin, one streamgage in Salt Creek Basin, and three streamgages in the Lower Platte River Basin that had previously indicated trends in selected annual mean streamflow, annual low flows, fall low flows, and growing season monthly mean streamflows metrics were analyzed for the period from 1961 to 2011. A streamgage in the Upper Elkhorn River Basin (Elkhorn River at Neligh, Nebraska [USGS station 06798500; maintained by USGS from water years 1930 to 1993, maintained by Nebraska Department of Natural Resources from water years 1994 to 2019]) had significant positive trends in annual mean streamflow and insignificant trends for other streamflow metrics whereas the lower three sites (Logan Creek near Uehling, Nebr. [USGS station 06799500]; Maple Creek at Nickerson, Nebr. [USGS station 06800000]; and Elkhorn River at Waterloo, Nebr. [USGS station 06800500]) had significant positive trends for annual mean streamflow, for all durations of the annual low-flow periods (1-day, 2-day, 3-day, 7-day, 14-day, 30-day, 60-day, 90-day, and 183-day periods), for all durations of the low-flow periods in October–November (1-day, 2-day, 3-day, 7-day, 14-day, 30-day, and 60-day periods), and for monthly mean streamflow for July, August, and September. Upstream from the confluence of the Elkhorn River and the Platte River, the Platte River at North Bend, Nebr. (USGS station 06796000), streamgage indicated insignificant trends for most streamflow metrics. A streamgage in the Salt Creek Basin (Salt Creek at Greenwood, Nebr. [USGS station 06803555]) also indicated positive trends in some low-flows metrics. Streamflow at the Platte River at Louisville, Nebr. (USGS station 06805500), streamgage, downstream from the Salt Creek and Elkhorn River inflows, indicated significant positive trends in most annual and all October–November low flows and August mean streamflow but insignificant trends in annual mean streamflow and June, July, and September monthly mean streamflows. Streamflow records for the Platte River near Duncan, Nebr. (USGS station 06774000), streamgage only indicated a significant trend in the August mean streamflow; no other metrics had significant trends at the streamgage. The trend analyses are sensitive to the period that is analyzed for trends. Sites with the most significant trends for low-flow metrics for the period 1961–2011 have fewer significant trends for low-flow metrics for the period after 1980–2011. The results indicate that positive trends in low flows at the Salt Creek and Elkhorn River streamgages may be contributing to positive trends in low flows for the Platte River at Louisville, Nebr., streamgage. Likewise, streamflow in the Salt Creek and Elkhorn River Basins may be contributing to the positive trend in August mean streamflow for the Platte River at Louisville, Nebr., streamgage, three lower Elkhorn River streamgages, and the Salt Creek streamgage. Precipitation was also examined as a primary cause for streamflow trends in the Elkhorn River Basin. For the four streamgages in the Elkhorn River Basin, relations between precipitation and streamflow were examined on an annual and monthly basis using linear regression. In general, the goodness of fit for the linear relations was poor with coefficient of determination values of less than or equal to 0.10 for four of the eight relations. Only one significant increase in annual precipitation upstream from the four streamgages and the frequent detection of significant increases in streamflow after removing the effect of precipitation indicate that other factors besides precipitation may have played a role in the significant positive trends in low-flow periods in the lower Elkhorn River and its tributaries.

Nebraska↗
USGS1995

Ground-water conditions in Utah, spring of 1995

This is the thirty-second in a series of annual reports that describe ground-water conditions in Utah. Reports in this series, published cooperatively by the U.S. Geological Survey and the Utah Department of Natural Resources, Division of Water Resources, provide data to enable interested parties to keep abreast of changing ground-water conditions. This report, like the others in the series, contains information on well construction, ground-water withdrawal from wells, water-level changes, related changes in precipitation and streamflow, and chemical quality of water. Supplementary data, such as maps showing water-level contours, are included in reports of this series only for those years or areas for which applicable data are available and are important to a discussion of changing ground-water conditions. This report includes individual discussions of selected significant areas of ground-water development in the State for calendar year 1994. Much of the reported data were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Divisions of Water Rights and Water Resources.

Utah↗
USGS1996

Ground-water conditions in Utah, spring of 1996

This is the thirty-third in a series of annual reports that describe ground-water conditions in Utah. Reports in this series, published cooperatively by the U.S. Geological Survey and the Utah Department of Natural Resources, Division of Water Resources, provide data to enable interested parties to keep abreast of changing ground-water conditions. This report, like the others in the series, contains information on well construction, ground-water withdrawal from wells, water-level changes, related changes in precipitation and streamflow, and chemical quality of water. Supplementary data, such as maps showing water-level contours, are included in reports of this series only for those years or areas for which applicable data are available and are important to a discussion of changing ground-water conditions. This report includes individual discussions of selected significant areas of ground-water development in the State for calendar year 1995. Most of the reported data were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Divisions of Water Rights and Water Resources.

Utah↗
USGS2021

Mapping climate change vulnerability of aquatic-riparian ecosystems using decision-relevant indicators

Climate change has and is projected to continue to alter historical regimes of temperature, precipitation, and hydrology. To assess the vulnerability of climate change from a land management perspective and spatially identify where the most extreme changes are anticipated to occur, we worked in collaboration with land managers to develop a climate change vulnerability map for the midwestern United States with a focus on riparian systems. The map is intended for use by regional administrators to help them work across various program areas (e.g. fisheries, endangered species) to prioritize locations needing support for adaptation planning. The tool can also be utilized locally by managers to better understand the effects that projected climate scenarios have on the hydrology of management units as they develop adaptation strategies. The vulnerability map is watershed-based (360 watershed units within the region) and combines 15 climate change indicators that were selected by U.S. Fish and Wildlife Service natural resource managers based upon known and anticipated effects to species and habitats. The projected change in each of these indicators from the historical period (1986–2005) to the future period (2040–2059) was aggregated into a composite score for each watershed. Landscape-scale metrics reflective of a watershed’s adaptive capacity were combined with the climate change indicators to produce a vulnerability score. We found sub-regional variation in vulnerability to climate change with the greatest vulnerability in Iowa, central Illinois, and northwest Ohio. Greater vulnerability was seen in the higher greenhouse gas concentration scenario, Representative Concentration Pathway (RCP) 8.5 compared to the lower greenhouse gas concentration scenario RCP 4.5, when looking at the mean of the five downscaled climate models used in this study. By quantifying and mapping climate change vulnerability, natural resource managers can better understand the degree of vulnerability for individual watersheds and identify areas of prioritization in regional and local planning efforts.

Iowa, Illinois, Indiana, Michigan, Minnesota, Miss↗
USGS2010

StreamStats in Oklahoma– Drainage-basin characteristics and peak-flow frequency statistics for ungaged streams

The USGS Streamflow Statistics (StreamStats) Program was created to make geographic information systems-based estimation of streamflow statistics easier, faster, and more consistent than previously used manual techniques. The StreamStats user interface is a map-based internet application that allows users to easily obtain streamflow statistics, basin characteristics, and other information for user-selected U.S. Geological Survey data-collection stations and ungaged sites of interest. The application relies on the data collected at U.S. Geological Survey streamflow-gaging stations, computer aided computations of drainage-basin characteristics, and published regression equations for several geographic regions comprising the United States. The StreamStats application interface allows the user to (1) obtain information on features in selected map layers, (2) delineate drainage basins for ungaged sites, (3) download drainage-basin polygons to a shapefile, (4) compute selected basin characteristics for delineated drainage basins, (5) estimate selected streamflow statistics for ungaged points on a stream, (6) print map views, (7) retrieve information for U.S. Geological Survey streamflow-gaging stations, and (8) get help on using StreamStats. StreamStats was designed for national application, with each state, territory, or group of states responsible for creating unique geospatial datasets and regression equations to compute selected streamflow statistics. With the cooperation of the Oklahoma Department of Transportation, StreamStats has been implemented for Oklahoma and is available at http://water.usgs.gov/osw/streamstats/. The Oklahoma StreamStats application covers 69 processed hydrologic units and most of the state of Oklahoma. Basin characteristics available for computation include contributing drainage area, contributing drainage area that is unregulated by Natural Resources Conservation Service floodwater retarding structures, mean-annual precipitation at the drainage-basin outlet for the period 1961-1990, 10-85 channel slope (slope between points located at 10 percent and 85 percent of the longest flow-path length upstream from the outlet), and percent impervious area. The Oklahoma StreamStats application interacts with the National Streamflow Statistics database, which contains the peak-flow regression equations in a previously published report. Fourteen peak-flow (flood) frequency statistics are available for computation in the Oklahoma StreamStats application. These statistics include the peak flow at 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals for rural, unregulated streams; and the peak flow at 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals for rural streams that are regulated by Natural Resources Conservation Service floodwater retarding structures. Basin characteristics and streamflow statistics cannot be computed for locations in playa basins (mostly in the Oklahoma Panhandle) and along main stems of the largest river systems in the state, namely the Arkansas, Canadian, Cimarron, Neosho, Red, and Verdigris Rivers, because parts of the drainage areas extend outside of the processed hydrologic units.

Oklahoma↗
USGS1997

Ground-water conditions in Utah, spring of 1997

This is the thirty-fourth in a series of annual reports that describe ground-water conditions in Utah. Reports in this series, published cooperatively by the U.S. Geological Survey and the Utah Department of Natural Resources, Division of Water Resources, provide data to enable interested parties to keep aware of changing ground-water conditions. This report, like the others in the series, contains information on well construction, ground-water withdrawal from wells, water-level changes, precipitation, streamflow, and chemical quality of water. Information on well construction included in this report refers only to wells constructed for new appropriations of ground water. Supplementary data are included in reports of this series only for those years or areas for which applicable data are available and are important to a discussion of changing ground-water conditions. This report includes individual discussions of selected significant areas of ground-water development in the State for calendar year 1996. Most of the reported data were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Divisions of Water Rights and Water Resources.

Utah↗