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At least 19 recordsLinked to original sources
USGS1996

Behavioral avoidance as evidence of injury to fishery resources: Applications to natural resource damage assessment

Natural Resource Damage Assessment (NRDA) provisions enacted under Comprehensive Environmental Response Compensation and Liability Act (CERCLA) and the Oil Pollution Act (OPA) empower natural resource trustees to seek compensation for environmental injury resulting from the release of oil or hazardous substances. Under NRDA regulations promulgated under CERCLA, fish avoidance behavior is recognized as an accepted injury, and may be used to support damage claims. In support of an ongoing damage assessment, tests were conducted to determine if avoidance of ambient metals concentrations may contribute to reductions in local salmonid populations. In laboratory tests, rainbow trout ( Oncorhynchus mykiss ) and brown trout ( Salmo trutta ) avoided mixtures of metals (Cd, Cu, Pb, and Zn) at concentrations that occur in impacted river reaches at a contaminated site (Clark Fork River, MT). Avoidance of metal contamination may contribute to population reductions and preclude restoration of instream populations by prohibiting movement of fish into contaminated areas of the river from uncontaminated tributaries. Laboratory avoidance tests were performed at two testing facilities. The similar avoidance responses observed at the two laboratories demonstrated the reproducibility of avoidance measures.

Book chapter↗
USGS2007

Alaska Science Center: Providing Timely, Relevant, and Impartial Study of the Landscape, Natural Resources, and Natural Hazards for Alaska and Our Nation

The U.S. Geological Survey (USGS), the Nation's largest water, earth, and biological science and civilian mapping agency, has studied the natural features of Alaska since its earliest geologic expeditions in the 1800s. The USGS Alaska Science Center (ASC), with headquarters in Anchorage, Alaska, studies the complex natural science phenomena of Alaska to provide scientific products and results to a wide variety of partners. The complexity of Alaska's unique landscapes and ecosystems requires USGS expertise from many science disciplines to conduct thorough, integrated research.

Fact Sheet↗
USGS2015

Markov decision processes in natural resources management: observability and uncertainty

The breadth and complexity of stochastic decision processes in natural resources presents a challenge to analysts who need to understand and use these approaches. The objective of this paper is to describe a class of decision processes that are germane to natural resources conservation and management, namely Markov decision processes, and to discuss applications and computing algorithms under different conditions of observability and uncertainty. A number of important similarities are developed in the framing and evaluation of different decision processes, which can be useful in their applications in natural resources management. The challenges attendant to partial observability are highlighted, and possible approaches for dealing with it are discussed.

Ecological Modelling↗
USGS1996

Use of behavioral avoidance testing in natural resource damage assessment

Natural Resource Damage Assessment (NRDA) provisions established under federal and state statutes enable natural resource trustees to recover compensation from responsible parties to restore injured natural resources. Behavioral avoidance testing with fish has been used in NRDAs to determine injuries to natural resources and to establish restoration thresholds. In this manuscript we evaluate the use of avoidance testing to NRDA. Specifically, we discuss potential “acceptance criteria” to evaluate the applicability and relevance of avoidance testing. These acceptance criteria include: (1) regulatory relevance, (2) reproducibility of testing, (3) ecological significance, (4) quality assurance/quality control, and (5) relevance to restoration. We discuss each of these criteria with respect to avoidance testing. Overall, we conclude that avoidance testing can be an appropriate, defensible, and desirable aspect of an NRDA.

ASTM Symposium on Environmental Toxicology and Ris↗
USGS2014

Organizing phenological data resources to inform natural resource conservation

Changes in the timing of plant and animal life cycle events, in response to climate change, are already happening across the globe. The impacts of these changes may affect biodiversity via disruption to mutualisms, trophic mismatches, invasions and population declines. To understand the nature, causes and consequences of changed, varied or static phenologies, new data resources and tools are being developed across the globe. The USA National Phenology Network is developing a long-term, multi-taxa phenological database, together with a customizable infrastructure, to support conservation and management needs. We present current and potential applications of the infrastructure, across scales and user groups. The approaches described here are congruent with recent trends towards multi-agency, large-scale research and action.

Biological Conservation↗
USGS2019

Multi-resource analysis: A proof of concept study of natural resource tradeoffs in the Piceance Basin, Colorado, using the net resources assessment (NetRA) decision support tool

Executive Summary The U.S. Geological Survey (USGS) is developing a multi-resource analysis (MRA) line of products to inform land-use decision makers. Specifically, MRA products will integrate scientific information, include considerations for natural resource interrelations, and quantify the effects of resource management decisions in biophysical, economic, and societal terms. As part of the establishment of the MRA, the USGS, in collaboration with the University of New Mexico, has developed the Net Resources Assessment (NetRA) decision support tool. As a proof of concept analysis, the NetRA was applied to the Piceance basin in Colorado in a hypothetical example to illustrate how resource managers could use the NetRA to consider tradeoffs of natural resources among alternative development plans and land cover patterns within a geographic region. The NetRA is a policy-relevant approach to assess the availability of multiple natural resources. It is an analytical toolset that may be used to examine the spatiotemporal relations between development of energy and mineral resources and delivery of biological natural resources. The NetRA operates at multiple map scales and contains a set of integrated, compatible submodels with specific data requirements for natural resource stocks, engineering economics, biophysical, and ecological data for ecosystem services stocks, market prices, regulations, and nonmarket values. The NetRA includes an explicit process to consider the interdependence between development and conservation, which is a crucial consideration in land-management and land-use decisions. The NetRA is used to estimate an expected net resource value (NRV). The NRV is the expected, present value, economic benefit from the extraction of a resource (for example, natural gas) minus the total cost of production, which is the aggregation of the development, production, and social costs. Social costs include private costs plus any external costs. There can be external social benefits associated with natural gas production, such as increased demand for locally produced goods and increased employment in the local area through backward and forward linkages of natural gas production. The NRV is used to compare development outcomes (scenarios) from a range of exploration and development plans for cumulative energy production. The Piceance basin application of the NetRA uses the NRV to assess the tradeoff between continuous natural gas extraction and the effects to the local populations of Odocoileus hemionus (mule deer) and aquatic species and to consumptive water uses for an area the size and resolution of a USGS energy resource assessment unit. In the proof of concept simulation, the 2.9-square-mile-area of USGS oil and gas assessment unit 50200263 (Piceance basin continuous gas unit of the Mesaverde Total Petroleum System) was gridded into 588 cells. From this area, seven clusters with potential for development and three that cannot be developed were identified; the three clusters that cannot be developed were identified as wilderness study areas, areas of critical environmental concern, and national forests. On the basis of these criteria, there are 118 cells unsuitable for development in the oil and gas assessment unit: 84 are in national forests, 23 are areas of critical environmental concern, and 11 are wilderness study areas. The remaining cells in the oil and gas assessment unit can be developed on both private and public lands. Two scenarios were considered that are distinguished as plan 1 and plan 2. Plan 1 keeps the amount of land disturbance unchanged and limits the number of development locations to 140 grid cells for the production period, which constrains the amount of the energy resources available for development; the plan requires the usage of the Bureau of Land Management (BLM) unsuitability criteria. Plan 2 also limits the number of development locations to 140 grid cells for the production period but provides a constant volume of energy production by increasing the density of well pads within the cells. The effects of plan 2 to the NRV when there are five wells per pad and five pads per square mile happen mostly in the first 5 years of development, even though the effects on the population of mule deer continue in later years. This outcome is the result of the upfront development and investment costs and the initial effect to the ecosystem services.

Colorado↗
USGS2021

Paths to computational fluency for natural resource educators, researchers, and managers

Natural resource management and supporting research teams need computational fluency in the data and model-rich 21st century. Computational fluency describes the ability of practitioners and scientists to conduct research and represent natural systems within the computer's environment. Advancement in information synthesis for natural resource management requires more sophisticated computational approaches, as well as reproducible, reusable, extensible, and transferable methods. Despite this importance, many new and current natural resource practitioners lack computational fluency and no common set of recommended resources and practices exist for learning these skills. Broadly, attaining computational fluency entails moving beyond the simple use of computers to applying sound computational principles and methods and including computational experts (such as computer scientists) on research teams. Our path for computational fluency includes using open-source tools when possible; reproducible data management, statistics, and modeling; understanding and applying the benefits of basic computer programming to carry out more complex procedures; tracking code with version control; working in controlled computer environments; and using advanced computing resources.

Natural Resource Modelling↗
USGS2012

The Adaptation for Conservation Targets (ACT) Framework: A tool for incorporating climate change into natural resource management

As natural resource management agencies and conservation organizations seek guidance on responding to climate change, myriad potential actions and strategies have been proposed for increasing the long-term viability of some attributes of natural systems. Managers need practical tools for selecting among these actions and strategies to develop a tailored management approach for specific targets at a given location. We developed and present one such tool, the participatory Adaptation for Conservation Targets (ACT) framework, which considers the effects of climate change in the development of management actions for particular species, ecosystems and ecological functions. Our framework is based on the premise that effective adaptation of management to climate change can rely on local knowledge of an ecosystem and does not necessarily require detailed projections of climate change or its effects. We illustrate the ACT framework by applying it to an ecological function in the Greater Yellowstone Ecosystem (Montana, Wyoming, and Idaho, USA)—water flows in the upper Yellowstone River. We suggest that the ACT framework is a practical tool for initiating adaptation planning, and for generating and communicating specific management interventions given an increasingly altered, yet uncertain, climate.

Environmental Management↗
USGS2010

Resolving disputes over science in natural resource agency decisionmaking

Natural resource agencies make decisions involving public resources in which the public, by definition, have a stake. These resources are often finite. Thus, different viewpoints, interests, or beliefs may conflict when parties are perceived to be interdependent or one party is perceived to block or oppose other parties' use of a scarce resource. These confl icts may occur regard less of whether there are any real differences between the parties or whether one party's actions actually affect the other (Thomas 1992; Robbins 1994; Appelbaum et al. 1999). Conflicts are defined here as "a process of social interaction involving a struggle over claims to resources, power and status, beliefs, and other preferences and desires" (Appelbaum et al. 1999, 63). Such conflicts can occur at multiple stages or levels of decisionmaking and can be embedded within other conflicts.

Technical Memorandum↗
USGS2024

Writing SMART objectives for natural resource and environmental management

In natural resource and environmental management, well-written objectives are critical for effective decision-making and the achievement of desired outcomes. This article aims to improve practitioners' ability to identify and write SMART ( S pecific, M easurable, A chievable, R elevant, T ime-bound) objectives for natural resource and environmental management. We differentiate between research and management objectives, define each SMART criterion, and introduce a template to help write management objectives. We demonstrate the use of the SMART management objectives template with a hypothetical example and two recent applications. The template simplifies the process of writing SMART management objectives. It is applicable to popular management frameworks like management by objectives and structured decision making. The implementation of SMART criteria and the provided template can lead to better outcomes in natural resource and environmental management, benefiting current and future generations.

Ecological Solutions and Evidence↗
USGS2019

Natural resource condition assessment: Channel Islands National Park

The Natural Resource Condition Assessment (NRCA) Program aims to provide documentation about the current conditions of important Park natural resources through a spatially explicit, multidisciplinary synthesis of existing scientific data and knowledge. Findings from the NRCA will help Channel Islands National Park (CINP) managers to develop near-term management priorities. The central objectives of this assessment were to evaluate the current conditions and trends of key Park resources, identify important knowledge gaps, and determine key stressors and threats. Because a recent report provided an assessment of marine resources (Engle 2006), which constitute 50% of the park, this NRCA focused on terrestrial resources. For this NRCA, CINP resource managers identified that the greatest Park need was to know whether or not vegetation (primarily woody vegetation) is recovering on the Channel Islands and how this may be influencing recovery of the native terrestrial vertebrates. To address this, the CINP NRCA team evaluated the condition of island vegetation and vertebrate communities using both: 1) already available, summarized information from reports, theses, and journal articles and 2) new analyses of recently available, existing data collected on the islands. Descriptions of specific methods used to analyze available data by the NRCA team are provided within the assessment sections in Chapter 4 of this report. The Team used the Vital Signs indicators as identified by Fancy et al. (2009) for monitoring the condition of Natural Resources in U.S. National Parks. Using this framework, the focal study resource components were the five CINP islands, because these are the bio-geophysical resources of greatest interest to the CINP. Each of the islands has its own unique history of human impacts, ecological conditions, restoration efforts, and natural resource monitoring. The Team evaluated island scrub recovery by assessing changes over time in two metrics: 1) vegetation community structure (species composition, cover, and spatial extent), and 2) vertebrate abundance, relative to the reference condition of each island. The reference conditions for this NRCA were the particular island’s ecological state prior to European settlement or ranching, which represent the ecological state to which the NPS desires the park return. For each metric, the Team determined the Reference Conditions/Values, Current Condition, Trend, and Recovery Potential (based on a review of the literature and from the NRCA team’s analysis of newly available data), Threats and Stressors, Data Gaps, Overall Condition. A qualitative statement of overall current condition was created for each metric, after all data and literature relevant to the measures (i.e., vegetation and vertebrates) of each resource component (i.e., island) were reviewed and evaluated. All information gathered for this NRCA is available and managed by CINP, so that the compilation of resources would be available not only for the assessment team, but will be provided for future Park reference. Chapter 1 of this NRCA provides a descriptive background of NRCAs. Chapter 2 provides Park-wide natural resource background information, while Chapter 3 describes the overall methodological approach used in this assessment. Chapter 4 provides a detailed assessment of each island’s condition, which is then summarized Park-wide and for each island in Chapter 5. Based on both vegetation recovery and vertebrate population abundances, our assessment found Santa Cruz Island (SCI), Santa Rosa Island (SRI), San Miguel Island (SMI), and Anacapa Island (AI) to be, overall, in moderate condition and slowly recovering following the removal of non-native herbivores. The condition of Santa Barbara Island (SBI) is poor and remains in a state that is not likely to improve without assisted recovery by the Park. All islands have exhibited some level of native vegetation recovery, with most of the observed natural recovery occurring on SCI, SRI, SMI, and AI; very little recovery has occurred at present on SBI. Vegetation recovery is uneven across each island and largely limited to mesic areas, such as north-facing slopes. Areas that will likely require some assisted recovery efforts are those that are: at risk of erosion, isolated, lacking native seed banks, and plagued with high competition of non-native grasses and other invasives. Some plant communities, such as exposed upland vegetation on SRI, also have lower natural recovery potential and will likely require assisted recovery. The overall condition of the Park’s terrestrial island vertebrate species generally appears to be good and improving, with high potential for further recovery to reach pre-ranching era reference conditions. This is particularly true for vertebrates on SCI, SRI, and SMI. Although there are limited data for AI, the data that are available suggest that vertebrates on that island are in good condition and improving as well. However, the condition of SBI vertebrates is only moderate, with natural recovery potential being low, with many landbird species’ populations currently declining, extinct, or not improving. An overarching theme across the Park’s terrestrial island vertebrate populations is that many of them are in good condition because the particular animals are habitat generalists, so their population dynamics are not strongly tied to habitat conditions. However, those landbirds associated with riparian vegetation are not showing signs of recovery across the Park islands, and riparian areas appear to be one of the habitats with limited natural recovery potential on the islands. Overwhelmingly, the most critical data gap that emerged from our analysis was the lack of current vegetation maps for most of the islands (AI, SCI, SRI, SMI). The lack of this information made it difficult to assess spatial changes in island vegetation over time, and to relate those changes to observed changes in vertebrate species abundances. Therefore, we were limited in our spatial assessment of vegetation recovery for AI, SCI, SRI, and SMI, and were only able to relate the current vegetation with island landbird analysis for SBI. Another common theme across islands was the lack of information on best techniques for shrub reintroduction and recovery, and the success of invasive species removal and re-vegetation efforts. Abundance, distribution, and habitat affinities of reptiles and amphibians are poorly known for AI, SCI, SRI, and SMI, making it difficult to assess their population condition and trends, and their potential responses to shrub recovery. Mammal and landbird populations are reasonably well-sampled across most of the islands, but data are lacking for most vertebrates from AI, especially West and Middle AI where no vertebrate sampling occurs. The population status, cause of declines, and recovery needs are lacking for several landbird species across multiple islands, including loggerhead shrikes ( Lanius ludovicianus ssp.) on SCI and SRI, and Santa Cruz Island rufous crowned sparrows ( Aimophila ruficeps obscura ) on AI. Additionally, island song sparrows ( Melospiza melodia graminea ) remain extirpated on SBI and data are needed for assessing their recovery potential on the island. The potentially major threats facing the islands’ flora and fauna today are: areas of continued erosion, potential new non-native introductions, and climate change. The Park islands have already experienced warming over the last several decades due to human-induced climate change, and are projected to experience continued warming. These increasing stresses imposed by climate change may slow and inhibit natural recovery potentials for island fauna, and especially flora.

California↗
USGS2022

Natural resource system size can be used for managing recreational use

Outdoor recreation provides societal benefits that are often measured by the amount of use natural resource systems receive. Still, the amount of resource use natural resource systems receive is often unknown or unstudied. Monitoring and quantifying resource use is often logistically difficult and costly but is paramount to optimize societal benefits. Identifying a simple and readily available metric that can indicate the quantity of recreational use of natural resource systems would benefit natural resource management. Using recreational angler participation data during an 11-year study period from 73 public waterbodies in Nebraska, USA, we developed a resource size-use model that demonstrates the ability of natural resource system size to indicate the quantity of recreational use they receive. We demonstrate how resource size-use models can estimate use for unsampled systems, produce broad-scale estimations of use, guide the allocation of resources, and predict how changes in resource system size may affect use. Resource size-use models provide opportunities to manage recreational use, which has been previously elusive for social-ecological systems.

Nebraska↗
USGS2013

The state of human dimensions capacity for natural resource management: needs, knowledge, and resources

The social sciences have become increasingly important in understanding natural resource management contexts and audiences, and are essential in design and delivery of effective and durable management strategies. Yet many agencies and organizations do not have the necessary resource management. We draw on the textbook definition of HD: how and why people value natural resources, what benefits people seek and derive from those resources, and how people affect and are affected by those resources and their management (Decker, Brown, and Seimer 2001). Clearly articulating how HD information can be used and integrated into natural resource management planning and decision-making is an important challenge faced by the HD field. To address this challenge, we formed a collaborative team to explore the issue of HD capacity-building for natural resource organizations and to advance the HD field. We define HD capacity as activities, efforts, and resources that enhance the ability of HD researchers and practitioners and natural managers and decision-makers to understand and address the social aspects of conservation. Specifically, we sought to examine current barriers to integration of HD into natural resource management, knowledge needed to improve HD capacity, and existing HD tools, resources, and training opportunities. We conducted a needs assessment of HD experts and practitioners, developed a framework for considering HD activities that can contribute both directly and indirectly throughout any phase of an adaptive management cycle, and held a workshop to review preliminary findings and gather additional input through breakout group discussions. This paper provides highlights from our collaborative initiative to help frame and inform future HD capacity-building efforts and natural resource organizations and also provides a list of existing human dimensions tools and resources.

The George Wright Forum↗
USGS2017

Review of dynamic optimization methods in renewable natural resource management

In recent years, the applications of dynamic optimization procedures in natural resource management have proliferated. A systematic review of these applications is given in terms of a number of optimization methodologies and natural resource systems. Optimization methods are characterized by (1) the mathematical model used to describe a natural resource system, (2) a set of feasible strategies available to the resource manager, and (3) an objective functional by which to measure benefits and costs of strategies. A formal statement of the control problem is used to describe six approaches to optimal utilization of renewable natural resources: variational mathematics, specifically Pontryagin's Maximum Principle; dynamic programming; linear programming; nonlinear programming; simulation-optimization; and classical procedures. Solution methodologies are illustrated for each of these approaches, and examples from the ecological and natural resource literature are described for various subject matter areas. Applications are highlighted in terms of model structures, objective functionals, and system constraints. To the extent possible, optimal management patterns are characterized. Finally, the applicability of the methods to renewable natural resource systems are compared in terms of system complexity, system size, and precision of the optimal solutions. Recommendations are made concerning the appropriate methods for certain kinds of biological resource problems.

Natural Resource Modeling↗
USGS2023

A novel approach to assessing natural resource injury with Bayesian networks

Quantifying the effects of environmental stressors on natural resources is problematic because of complex interactions among environmental factors that influence endpoints of interest. This complexity, coupled with data limitations, propagates uncertainty that can make it difficult to causally associate specific environmental stressors with injury endpoints. The Natural Resource Damage Assessment and Restoration (NRDAR) regulations under the Comprehensive Environmental Response, Compensation, and Liability Act and Oil Pollution Act aim to restore natural resources injured by oil spills and hazardous substances released into the environment; exploration of alternative statistical methods to evaluate effects could help address NRDAR legal claims. Bayesian networks (BNs) are statistical tools that can be used to estimate the influence and interrelatedness of abiotic and biotic environmental variables on environmental endpoints of interest. We investigated the application of a BN for injury assessment using a hypothetical case study by simulating data of acid mine drainage (AMD) affecting a fictional stream-dwelling bird species. We compared the BN-generated probability estimates for injury with a more traditional approach using toxicity thresholds for water and sediment chemistry. Bayesian networks offered several distinct advantages over traditional approaches, including formalizing the use of expert knowledge, probabilistic estimates of injury using intermediate direct and indirect effects, and the incorporation of a more nuanced and ecologically relevant representation of effects. Given the potential that BNs have for natural resource injury assessment, more research and field-based application are needed to determine their efficacy in NRDAR. We expect the resulting methods will be of interest to many US federal, state, and tribal programs devoted to the evaluation, mitigation, remediation, and/or restoration of natural resources injured by releases or spills of contaminants

Integrated Environmental Assessment and Management↗
USGS2018

Integrating adaptive management and ecosystem services concepts to improve natural resource management: Challenges and opportunities

Executive Summary—Overview Natural resource managers must make decisions that affect broad-scale ecosystem processes involving large spatial areas, complex biophysical interactions, numerous competing stakeholder interests, and highly uncertain outcomes. Natural and social science information and analyses are widely recognized as important for informing effective management. Chief among the systematic approaches for improving the integration of science into natural resource management are two emergent science concepts, adaptive management and ecosystem services. Adaptive management (also referred to as “adaptive decision making”) is a deliberate process of learning by doing that focuses on reducing uncertainties about management outcomes and system responses to improve management over time. Ecosystem services is a conceptual framework that refers to the attributes and outputs of ecosystems (and their components and functions) that have value for humans. This report explores how ecosystem services can be moved from concept into practice through connection to a decision framework—adaptive management—that accounts for inherent uncertainties. Simultaneously, the report examines the value of incorporating ecosystem services framing and concepts into adaptive management efforts. Adaptive management and ecosystem services analyses have not typically been used jointly in decision making. However, as frameworks, they have a natural—but to date underexplored—affinity. Both are policy and decision oriented in that they attempt to represent the consequences of resource management choices on outcomes of interest to stakeholders. Both adaptive management and ecosystem services analysis take an empirical approach to the analysis of ecological systems. This systems orientation is a byproduct of the fact that natural resource actions affect ecosystems—and corresponding societal outcomes—often across large geographic scales. Moreover, because both frameworks focus on resource systems, both must confront the analytical challenges of systems modeling—in terms of complexity, dynamics, and uncertainty. Given this affinity, the integration of ecosystem services analysis and adaptive management poses few conceptual hurdles. In this report, we synthesize discussions from two workshops that considered ways in which adaptive management approaches and ecosystem service concepts may be complementary, such that integrating them into a common framework may lead to improved natural resource management outcomes. Although the literature on adaptive management and ecosystem services is vast and growing, the report focuses specifically on the integration of these two concepts rather than aiming to provide new definitions or an indepth review or primer of the concepts individually. Key issues considered include the bidirectional links between adaptive decision making and ecosystem services, as well as the potential benefits and inevitable challenges arising in the development and use of an integrated framework. Specifically, the workshops addressed the following questions: How can application of ecosystem service analysis within an adaptive decision process improve the outcomes of management and advance understanding of ecosystem service identification, production, and valuation? How can these concepts be integrated in concept and practice? What are the constraints and challenges to integrating adaptive management and ecosystem services? And, should the integration of these concepts be moved forward to wider application—and if so, how?

Circular↗
USGS2015

Simulation of groundwater flow and analysis of the effects of water-management options in the North Platte Natural Resources District, Nebraska

The North Platte Natural Resources District (NPNRD) has been actively collecting data and studying groundwater resources because of concerns about the future availability of the highly inter-connected surface-water and groundwater resources. This report, prepared by the U.S. Geological Survey in cooperation with the North Platte Natural Resources District, describes a groundwater-flow model of the North Platte River valley from Bridgeport, Nebraska, extending west to 6 miles into Wyoming. The model was built to improve the understanding of the interaction of surface-water and groundwater resources, and as an optimization tool, the model is able to analyze the effects of water-management options on the simulated stream base flow of the North Platte River. The groundwater system and related sources and sinks of water were simulated using a newton formulation of the U.S. Geological Survey modular three-dimensional groundwater model, referred to as MODFLOW–NWT, which provided an improved ability to solve nonlinear unconfined aquifer simulations with wetting and drying of cells. Using previously published aquifer-base-altitude contours in conjunction with newer test-hole and geophysical data, a new base-of-aquifer altitude map was generated because of the strong effect of the aquifer-base topography on groundwater-flow direction and magnitude. The largest inflow to groundwater is recharge originating from water leaking from canals, which is much larger than recharge originating from infiltration of precipitation. The largest component of groundwater discharge from the study area is to the North Platte River and its tributaries, with smaller amounts of discharge to evapotranspiration and groundwater withdrawals for irrigation. Recharge from infiltration of precipitation was estimated with a daily soil-water-balance model. Annual recharge from canal seepage was estimated using available records from the Bureau of Reclamation and then modified with canal-seepage potentials estimated using geophysical data. Groundwater withdrawals were estimated using land-cover data, precipitation data, and published crop water-use data. For fields irrigated with surface water and groundwater, surface-water deliveries were subtracted from the estimated net irrigation requirement, and groundwater withdrawal was assumed to be equal to any demand unmet by surface water. The groundwater-flow model was calibrated to measured groundwater levels and stream base flows estimated using the base-flow index method. The model was calibrated through automated adjustments using statistical techniques through parameter estimation using the parameter estimation suite of software (PEST). PEST was used to adjust 273 parameters, grouped as hydraulic conductivity of the aquifer, spatial multipliers to recharge, temporal multipliers to recharge, and two specific recharge parameters. Base flow of the North Platte River at Bridgeport, Nebraska, streamgage near the eastern, downstream end of the model was one of the primary calibration targets. Simulated base flow reasonably matched estimated base flow for this streamgage during 1950–2008, with an average difference of 15 percent. Overall, 1950–2008 simulated base flow followed the trend of the estimated base flow reasonably well, in cases with generally increasing or decreasing base flow from the start of the simulation to the end. Simulated base flow also matched estimated base flow reasonably well for most of the North Platte River tributaries with estimated base flow. Average simulated groundwater budgets during 1989–2008 were nearly three times larger for irrigation seasons than for non-irrigation seasons. The calibrated groundwater-flow model was used with the Groundwater-Management Process for the 2005 version of the U.S. Geological Survey modular three-dimensional groundwater model, MODFLOW–2005, to provide a tool for the NPNRD to better understand how water-management decisions could affect stream base flows of the North Platte River at Bridgeport, Nebr., streamgage in a future period from 2008 to 2019 under varying climatic conditions. The simulation-optimization model was constructed to analyze the maximum increase in simulated stream base flow that could be obtained with the minimum amount of reductions in groundwater withdrawals for irrigation. A second analysis extended the first to analyze the simulated base-flow benefit of groundwater withdrawals along with application of intentional recharge, that is, water from canals being released into rangeland areas with sandy soils. With optimized groundwater withdrawals and intentional recharge, the maximum simulated stream base flow was 15–23 cubic feet per second (ft 3 /s) greater than with no management at all, or 10–15 ft 3 /s larger than with managed groundwater withdrawals only. These results indicate not only the amount that simulated stream base flow can be increased by these management options, but also the locations where the management options provide the most or least benefit to the simulated stream base flow. For the analyses in this report, simulated base flow was best optimized by reductions in groundwater withdrawals north of the North Platte River and in the western half of the area. Intentional recharge sites selected by the optimization had a complex distribution but were more likely to be closer to the North Platte River or its tributaries. Future users of the simulation-optimization model will be able to modify the input files as to type, location, and timing of constraints, decision variables of groundwater withdrawals by zone, and other variables to explore other feasible management scenarios that may yield different increases in simulated future base flow of the North Platte River.

Nebraska↗