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At least 163 records · Page 9Linked to original sources
USGS2004

Guidelines for preparation of state water-use estimates for 2000

This report describes the water-use categories and data elements required for the 2000 national water-use compilation conducted by the U.S. Geological Survey (USGS) as part of its National Water Use Information Program. It identifies sources of water-use information, guidelines for estimating water use, and required documentation for preparation of the national compilation by State for the United States, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. The data are published in USGS Circular 1268, Estimated Use of Water in the United States in 2000. USGS has published circulars on estimated use of water in the United States at 5-year intervals since 1950. As part of this USGS program to document water use on a national scale for the year 2000, all States prepare estimates of water withdrawals for public supply, industrial, irrigation, and thermoelectric power generation water uses at the county level. All States prepare estimates of domestifc use and population served by public supply at least at the State level. All States provide estimates of irrigated acres by irrigation system type (sprinkler, surface, or microirrigation) at the county level. County-level estimates of withdrawals for mining, livestock, and aquaculture uses are compiled by selected States that comprised the largest percentage of national use in 1995 for these categories, and are optional for other States. Ground-water withdrawals for public-supply, industrial, and irrigation use are aggregated by principal aquifer or aquifer system, as identified by the USGS Office of Ground Water. Some categories and data elements that were mandatory in previous compilations are optional for the 2000 compilation, in response to budget considerations at the State level. Optional categories are commercial, hydroelectric, and wastewater treatment. Estimation of deliveries from public supply to domestic, commercial, industrial, and thermoelectric uses, consumptive use for any category, and irrigation conveyance loss are optional data elements. Aggregation of data by the eight-digit hydrologic cataloging unit is optional. Water-use data compiled by the States are stored in the USGS Aggregated Water-Use Data System (AWUDS). This database is designed to store both mandatory and optional data elements. AWUDS contains several routines that can be used for quality assurance and quality control of the data, and also produces tables of water-use data compiled for 1985, 1990, 1995, and 2000. These water-use data are used by USGS, other agencies, organizations, academic institutions, and the public for research, water-management decisions, trend analysis, and forecasting.

Techniques and Methods↗
USGS2022

What’s It worth? Estimating the potential value of early warnings of cyanobacterial harmful algal blooms for managing freshwater reservoirs in Kansas, United States

Cyanobacterial blooms are an issue drawing increasing concern in freshwater lakes and reservoirs in the United States due to the real and sometimes perceived harms they can cause through cyanotoxin production or other effects. These types of blooms are often referred to as cyanobacterial harmful algal blooms (cyanoHABs). Cyanotoxin exposure can potentially lead to human health effects through recreation and consumption of drinking water and may impact fisheries, wildlife, domestic pets, and livestock. Characterizing the societal impacts of cyanotoxin production, exposure, and effects and estimating the potential value of information of an early warning system can inform and support freshwater lake and reservoir management decisions and future research directions. A Bayesian decision tree analysis was utilized to identify uses, users, and benefits of the information provided by this research. Specifically, the potential value related to a cyanoHAB early warning system, based on potential toxicity, was analyzed that would provide information two additional days earlier relative to cyanoHAB toxicity. The evaluation considers the application of this information for freshwater lake management - whether or not to post an advisory or warning to avoid recreational water contact. The model was parameterized with data from the state of Kansas and the value of avoided foregone recreation and avoided health effects was derived. The estimated annual value of information ranges between \$565 thousand to \$2.3 million (2018 United States Dollars (USD)) for the state of Kansas alone based on provided assumptions. The results demonstrate a lower bound of the value of a cyanoHAB early warning system and suggest additional research to understand how the use and value of this information could support research prioritization and further illustrate the return on research investment. This analysis does not incorporate the full suite of potential societal costs that may be associated with a cyanoHAB event such as drinking water treatment, impacts to irrigation, or power generation.

Kansas↗
USGS2003

Exploration of satellite-measured vegetation seasonality for Landfire land cover

The purpose of this study is to explore the use of satellite data and other sources of spatial data for large area classification in the western United States to support research on potential fire hazards. Extensive field information was made available to this project from two sources: Forest Inventory and Assessment (FIA) and Utah State University. Seasonal spectral patterns of reflectance generated for select vegetation communities indicated that substantial spectral changes occurred through the growing season for most land cover types. In many cases, pronounced spectral differences characterized different types of vegetation, indicating a high probability that classification will accurately separate these particular types of land cover. However, spectral similarities between other types of land cover, such as Douglas fir and white fir, indicate potential classification challenges. Results from this study also show that decision tree analysis is highly effective for assessing quality of input field data and for generating large area land cover classification data sets. It was found that a 5-7% improvement in classification results could be achieved simply by not using those field plots that appeared to be sub-optimal for classification purposes based on image interpretation.

Conference Paper↗
USGS2024

Best practices for incorporating climate change science into Department of the Interior analyses, consultations, and decision making

The purpose of this document is to provide technical guidance, practical application examples, and resource lists for those who conduct, manage, and/or interpret technical workflows within the Department of the Interior. This document is intended to support implementation of Department of the Interior policy 526 DM 1 and establish best practices for using climate change science to inform analysis, consultation, and decision making. The Earth’s climate is an interconnected system that distributes energy, heat, and water around the planet. Due to human-driven increases in long-lived greenhouse gases, the Earth’s climate is now changing. For Departmental decision-making purposes, assuming a static, unchanging baseline climate is no longer consistent with current knowledge about the climate system. There are uncertainties about future climate and how resources or assets (RoAs) will respond to new conditions. To depict the possibilities, the global climate science community develops scenarios and models to explore how future climate may respond to socioeconomic and technological development in the world. Principles for informing policy development, planning and decisions, and regulatory processes using climate change science must: 1) consider the effects of future climate change, 2) characterize the risks, and 3) characterize the uncertainties. Best practices include: Use multiple scenarios to assess risks from a range of plausible societal pathways. When constraints prevent the use of multiple scenarios or if decision makers are risk averse, ensure that the chosen scenario considers higher risk outcomes. This is particularly important for large investments or irreversible decisions and reduces the chances of overconfident decision making. Use multiple climate models within each scenario to account for the range of outcomes due to model uncertainty. Do not rely solely on a single model or an ensemble average. Use relevant climate data . Use a time-period for model projections of the future climate change consistent with the relevant timeframe of the policy, action, or decision being considered. Historical observations are useful for understanding past conditions and climate trends for the next several years, but not beyond the next decade. Consult with climate data and modeling experts to assess which data and model resources are most appropriate for any given application. Clearly describe key analysis uncertainties (including with any climate observations, models, and scenarios used), and how they were addressed in the analysis and/or decision process. This ensures transparency and learning among analysts and decision makers.

Report↗
USGS2005

The no-project alternative analysis: An early product of the Tahoe Decision Support System

We report on the development of a No-project alternative analysis (NPAA) or “business as usual” scenario with respect to a 20-year projection of 21 indicators of environmental and socioeconomic conditions in the Lake Tahoe Basin for the Tahoe Regional Planning Agency (TRPA). Our effort was inspired by earlier work that investigated the tradeoffs between an environmental and an economic objective. The NPAA study has implications for a longer term goal of building a Tahoe Decision Support System (TDSS) to assist the TRPA and other Basin agencies in assessing the outcomes of management strategies. The NPAA assumes no major deviations from current management practices or from recent environmental or societal trends and planned Environmental Improvement Program (EIP) projects. Quantitative “scenario generation” tools were constructed to simulate site-specific land uses, various population categories, and associated vehicle miles traveled. Projections of each indicator’s attainment status were made by building visual conceptual models of the relevant natural and social processes, extrapolating trends, and using available models, research, and expert opinion. We present results of the NPAA, projected indicator status, key factors affecting the indicators, indicator functionality, and knowledge gaps. One important result is that current management practices may slow the loss or degradation of environmental qualities but not halt or reverse it. Our analysis also predicts an increase in recreation and commuting into and within the basin, primarily in private vehicles. Private vehicles, which are a critical mechanism by which the Basin population affects the surrounding environment, are a key determinant of air-quality indicators, a source of particulate matter affecting Secchi depth, a source of noise, and a factor in recreational and scenic quality, largely owing to congestion. Key uncertainties in the NPAA include climate change, EIP project effectiveness, and external population, economic activity, and air pollution.

Lake Tahoe Basin↗
USGS2021

GIS-based identification of areas that have resource potential for lode gold in Alaska

Several comprehensive, data-driven geographic information system (GIS) analyses were conducted to assess prospectivity for lode gold in Alaska. These analyses use available geospatial datasets of lithologic, geochemical, mineral occurrence, and geophysical data to build models for recognizing different types of gold deposits within physiographic units defined by stream drainage basins that are approximately 100 square kilometers in area. The analytical methods successfully delineated areas in the State that contain known lode gold deposits and occurrences, providing some measure of confidence in their ability to predict gold prospectivity in areas of unknown lode gold potential. The results of our analyses indicate high prospectivity in a few areas scattered around the State that are not known to contain lode gold deposits. In addition to assessing the potential for lode gold deposits in Alaska, we designed analyses to distinguish different lode gold deposit types, including orogenic, reduced-intrusion-related, epithermal, and gold-bearing porphyry. These can primarily be differentiated using their unique trace element geochemical fingerprints and elemental enrichments, which reflect the characteristics of the geologic environment and chemistry of the ore-forming fluids. We identified multiple parameters that would discriminate the different types of gold deposits, but owing to the limits of available data, the compositional similarity of ore-forming fluids among some types of lode gold deposits, and overlapping geologic environments, distinguishing deposit types at the state scale in Alaska remains problematic. These limitations resulted in overlapping areas of prospectivity for different deposit types, highlighting the challenges for targeted gold exploration in Alaska. Adjustment of some scoring parameters and recharacterization at smaller scales to highlight individual mineral systems for application of prospectivity analyses may be helpful at a district scale. At a regional scale, the aerial overlap of individual deposit type analyses reinforces confidence in prospectivity for a lode gold resource in a drainage basin. Our analysis for undivided lode gold deposits will be the most practical analysis for landuse decisions in which delineation of areas that have confident potential for gold deposits in general is the primary goal. Data-driven GIS analysis for lode gold potential in Alaska, although limited by the size and uneven coverage of available datasets, objectively indicates prospectivity in areas where exposure is good as well as in areas under cover. The results of our analyses show medium to high prospectivity in areas that surround known deposits, indicating an overall expansion of areas that have the potential to contain gold deposits. Exploration in these areas may help improve the balance between the volume of gold produced in placer districts statewide and the relatively low volume of identified lode resources that contribute to these placer deposits. The results of our analyses can help focus future investigations in areas that show prospectivity but are not known to contain gold deposits, as well as in areas where data are lacking and the geology is poorly understood, and acquisition of additional data may help better define and constrain gold prospectivity.

Alaska↗
USGS2012

Identifying the decision to be supported: a review of papers from environmental modelling and software

Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for consideration by journal editors to aid them in filtering papers that use the term, “decision support”.

Leipzig↗
USGS2018

Development of a species status assessment process for decisions under the U.S. Endangered Species Act

Decisions under the U.S. Endangered Species Act (ESA) require scientific input on the risk that the species will become extinct. A series of critiques on the role of science in ESA decisions have called for improved consistency and transparency in species risk assessments and clear distinctions between science input and policy application. To address the critiques and document the emerging practice of the U.S. Fish and Wildlife Service (USFWS), we outline an assessment process based on principles and practices of risk and decision analyses that results in a scientific report on species status. The species status assessment (SSA) process has three successive stages: 1) document the life history and ecological relationships of the species in question to provide the foundation for the assessment, 2) describe and hypothesize causes for the current condition of the species, and 3) forecast the species' future condition. The future condition refers to the ability of a species to sustain populations in the wild under plausible future scenarios. The scenarios help explore the species' response to future environmental stressors and to assess the potential for conservation to intervene to improve its status. The SSA process incorporates modeling and scenario planning for prediction of extinction risk and applies the conservation biology principles of representation, resiliency, and redundancy to evaluate the current and future condition. The SSA results in a scientific report distinct from policy application, which contributes to streamlined, transparent, and consistent decision-making and allows for greater technical participation by experts outside of the USFWS, for example, by state natural resource agencies. We present two case studies based on assessments of the eastern massasauga rattlesnake Sistrurus catenatus and the Sonoran Desert tortoise Gopherus morafkai to illustrate the process. The SSA builds upon the past threat-focused assessment by including systematic and explicit analyses of a species' future response to stressors and conservation, and as a result, we believe it provides an improved scientific analysis for ESA decisions.

Journal of Fish and Wildlife Management↗
USGS2013

Choices in recreational water quality monitoring: new opportunities and health risk trade-offs

With the recent release of new recreational water quality monitoring criteria, there are more options for regulatory agencies seeking to protect beachgoers from waterborne pathogens. Included are methods that can reduce analytical time, providing timelier estimates of water quality, but the application of these methods has not been examined at most beaches for expectation of health risk and management decisions. In this analysis, we explore health and monitoring outcomes expected at Lake Michigan beaches using protocols for indicator bacteria including culturable Escherichia coli (E. coli; EC), culturable enterococci (ENT), and enterococci as analyzed by qPCR (QENT). Correlations between method results were generally high, except at beaches with historically high concentrations of EC. The “beach action value” was exceeded most often when using EC or ENT as the target indicator; QENT exceeded the limit far less frequently. Measured water quality between years was varied. Although methods with equivalent health expectation have been established, the lack of relationship among method outcomes and annual changes in mean indicator bacteria concentrations complicates the decision-making process. The monitoring approach selected by beach managers may be a combination of available tools that maximizes timely health protection, cost efficiency, and collaboration among beach jurisdictions.

Environmental Science & Technology↗
USGS2013

Influence of multi-source and multi-temporal remotely sensed and ancillary data on the accuracy of random forest classification of wetlands in northern Minnesota

Wetland mapping at the landscape scale using remotely sensed data requires both affordable data and an efficient accurate classification method. Random forest classification offers several advantages over traditional land cover classification techniques, including a bootstrapping technique to generate robust estimations of outliers in the training data, as well as the capability of measuring classification confidence. Though the random forest classifier can generate complex decision trees with a multitude of input data and still not run a high risk of over fitting, there is a great need to reduce computational and operational costs by including only key input data sets without sacrificing a significant level of accuracy. Our main questions for this study site in Northern Minnesota were: (1) how does classification accuracy and confidence of mapping wetlands compare using different remote sensing platforms and sets of input data; (2) what are the key input variables for accurate differentiation of upland, water, and wetlands, including wetland type; and (3) which datasets and seasonal imagery yield the best accuracy for wetland classification. Our results show the key input variables include terrain (elevation and curvature) and soils descriptors (hydric), along with an assortment of remotely sensed data collected in the spring (satellite visible, near infrared, and thermal bands; satellite normalized vegetation index and Tasseled Cap greenness and wetness; and horizontal-horizontal (HH) and horizontal-vertical (HV) polarization using L-band satellite radar). We undertook this exploratory analysis to inform decisions by natural resource managers charged with monitoring wetland ecosystems and to aid in designing a system for consistent operational mapping of wetlands across landscapes similar to those found in Northern Minnesota.

Minnesota↗
USGS2004

Fort Collins Science Center: Policy Analysis and Science Assistance

Most resource management decisions involve the integrated use of biological, sociological, and economic information. Combining this information provides a more comprehensive basis for making effective land management and conservation decisions. Toward this end, scientists in the Policy Analysis and Science Assistance Branch (PASA) of the Fort Collins Science Center (FORT) contribute expert knowledge for natural resources management by conducting biological, social, economic, and institutional analyses of conservation policies and management practices. PASA's mission is to integrate biological, social, and economic research so that resource managers can use the resulting information to make informed decisions and resolve resource management conflicts. PASA scientists pursue and conduct scientific analyses that help agencies and Native American tribes to (1) identify impending policy controversies and areas where social and natural science research is needed to address future policy questions; (2) develop methods and approaches to assist researchers in preparing scientific evidence; (3) assess habitat alteration in a manner consistent with policy needs; and (4) evaluate policy options. Branch scientists also evaluate policy options (e.g., effects of different land treatments, fish and wildlife management practices, or visitor/recreation management practices) in response to specific questions faced by policymakers and managers.

Fact Sheet↗
USGS2018

Resilience and resistance in sagebrush ecosystems are associated with seasonal soil temperature and water availability

Invasion and dominance of exotic grasses and increased fire frequency threaten native ecosystems worldwide. In the Great Basin region of the western United States, woody and herbaceous fuel treatments are implemented to decrease the effects of wildfire and increase sagebrush ( Artemisia spp.) ecosystem resilience to disturbance and resistance to exotic annual grasses. High cover of the exotic annual cheatgrass ( Bromus tectorum ) after treatments increases fine fuels, which in turn increases the risk of passing over a biotic threshold to a state of increased wildfire frequency and conversion to cheatgrass dominance. Sagebrush ecosystem resilience to wildfire and resistance to cheatgrass depend on climatic conditions and abundance of perennial herbaceous species that compete with cheatgrass. In this study, we used longer‐term data to evaluate the relationships among soil climate conditions, perennial herbaceous cover, and cheatgrass cover following fuel management treatments across the environmental gradients that characterize sagebrush ecosystems in the Great Basin. We examined the effects of woody and herbaceous fuel treatments on soil temperature, soil water availability (13–30 and 50 cm depths), and native and exotic plant cover on six sagebrush sites lacking piñon ( Pinus spp.) or juniper ( Juniperus spp.) tree expansion and 11 sagebrush sites with tree expansion. Both prescribed fire and mechanical treatments increased soil water availability on woodland sites and perennial herbaceous cover on some woodland and sagebrush sites. Prescribed fire also slightly increased soil temperatures and especially increased cheatgrass cover compared to no treatment and mechanical treatments on most sites. Non‐metric dimensional scaling ordination and decision tree partition analysis indicated that sites with warmer late springs and warmer and wetter falls had higher cover of cheatgrass. Sites with wetter winters and early springs (March–April) had higher cover of perennial herbs. Our findings suggest that site resistance to cheatgrass after fire and fuel control treatments decreases with a warmer and drier climate. This emphasizes the need for management actions to maintain and enhance perennial herb cover, such as implementing appropriate grazing management, and revegetating sites that have low abundance of perennial herbs in conjunction with fuel control treatments.

Ecosphere↗
USGS2011

Application of MODFLOW for oil reservoir simulation during the Deepwater Horizon Crisis

When the Macondo well was shut in on July 15, 2010, the shut-in pressure recovered to a level that indicated the possibility of oil leakage out of the well casing into the surrounding formation. Such a leak could initiate a hydraulic fracture that might eventually breach the seafloor, resulting in renewed and uncontrolled oil flow into the Gulf of Mexico. To help evaluate whether or not to reopen the well, a MODFLOW model was constructed within 24 h after shut in to analyze the shut-in pressure. The model showed that the shut-in pressure can be explained by a reasonable scenario in which the well did not leak after shut in. The rapid response provided a scientific analysis for the decision to keep the well shut, thus ending the oil spill resulting from the Deepwater Horizon blow out.

Gulf of Mexico↗
USGS2011

88 hours: The U.S. Geological Survey National Earthquake Information Center response to the March 11, 2011 Mw 9.0 Tohoku earthquake

The M 9.0 11 March 2011 Tohoku, Japan, earthquake and associated tsunami near the east coast of the island of Honshu caused tens of thousands of deaths and potentially over one trillion dollars in damage, resulting in one of the worst natural disasters ever recorded. The U.S. Geological Survey National Earthquake Information Center (USGS NEIC), through its responsibility to respond to all significant global earthquakes as part of the National Earthquake Hazards Reduction Program, quickly produced and distributed a suite of earthquake information products to inform emergency responders, the public, the media, and the academic community of the earthquake's potential impact and to provide scientific background for the interpretation of the event's tectonic context and potential for future hazard. Here we present a timeline of the NEIC response to this devastating earthquake in the context of rapidly evolving information emanating from the global earthquake-response community. The timeline includes both internal and publicly distributed products, the relative timing of which highlights the inherent tradeoffs between the requirement to provide timely alerts and the necessity for accurate, authoritative information. The timeline also documents the iterative and evolutionary nature of the standard products produced by the NEIC and includes a behind-the-scenes look at the decisions, data, and analysis tools that drive our rapid product distribution.

Tohoku↗
USGS1995

Isohaline position as a habitat indicator for estuarine populations

Populations of native and introduced aquatic organisms in the San Francisco Bay/Sacramento-San Joaquin Delta Estuary ("Bay/Delta") have undergone significant declines over the past two decades. Decreased river inflow due to drought and increased freshwater diversion have contributed to the decline of at least some populations. Effective management of the estuary's biological resources requires a sensitive indicator of the response to freshwater inflow that has ecological significance, can be measured accurately and easily, and could be used as a "policy" variable to set standards for managing freshwater inflow. Positioning of the 2% (grams of salt per kilogram of seawater) bottom salinity value along the axis of the estuary was examined for this purpose. The 2% bottom salinity position (denoted by X 2 ) has simple and significant statistical relationships with annual measures of many estuarine resources, including the supply of phytoplankton and phytoplankton-derived detritus from local production and river loading; benthic macroinvertebrates (molluscs); mysids and shrimp; larval fish survival; and the abundance of planktivorous, piscivorous, and bottom-foraging fish. The actual mechanisms are understood for only a few of these populations. X 2 also satisfies other recognized requirements for a habitat indicator and probably can be measured with greater accuracy and precision than alternative habitat indicators such as net freshwater inflow into the estuary. The 2% value may not have special ecological significance for other estuaries (in the Bay/Delta, it marks the locations of an estuarine turbidity maximum and peaks in the abundance of several estuarine organisms), but the concept of using near-bottom isohaline position as a habitat indicator should be widely applicable. Although X 2 is a sensitive index of the estuarine community's response to net freshwater inflow, other hydraulic features of the estuary also determine population abundances and resource levels. In particular, diversion of water for export from or consumption within the estuary can have a direct effect on population abundance independent of its effect on X 2 . The need to consider diversion, in addition to X 2 , for managing certain estuarine resources is illustrated using striped bass survival as an example. The striped bass survival data were also used to illustrate a related important point: incorporating additional explanatory variables may decrease the prediction error for a population or process, but it can increase the uncertainty in parameter estimates and management strategies based on these estimates. Even in cases where the uncertainty is currently too large to guide management decisions, an uncertainty analysis can identify the most practical direction for future data acquisition.

California↗
USGS1979

Mathematics and mallard management

Waterfowl managers can effectively use simple population models to aid in making management decisions. We present a basic model of the change in population size as related to survival and recruitment. A management technique designed to increase survival of mallards (Anas platyrhynchos) by limiting harvest on the Chippewa National Forest, Minnesota, is used to illustrate the application of models in decision making. The analysis suggests that the management technique would be of limited effectiveness. In a 2nd example, the change in mallard population in central North Dakota is related to implementing programs to create dense nesting cover with or without supplementary predator control. The analysis suggests that large tracts of land would be required to achieve a hypothetical management objective of increasing harvest by 50% while maintaining a stable population. Less land would be required if predator reduction were used in combination with cover management, but questions about effectiveness and ecological implications of large scale predator reduction remain unresolved. The use of models as a guide to planning research responsive to the needs of management is illustrated.

Journal of Wildlife Management↗
USGS2019

Adaptive management of flows from R.L. Harris Dam (Tallapoosa River, Alabama)—Stakeholder process and use of biological monitoring data for decision making

Adaptive management has been applied to problems with multiple conflicting objectives in various natural resources settings to learn how management actions affect divergent values regarding system response. Hydropower applications have only recently begun to emerge in the field, yet in the specific example reported herein, stakeholders invested in determining the best management alternatives for attainment of a suite of objectives outlined in a long-term adaptive management program below R.L. Harris Dam, a large, privately owned dam in Alabama. Stakeholders convened an objective-setting workshop to engage a governance structure and developed a decision support model to determine appropriate actions that optimized stakeholder values. The process led to implemented change in dam operation inclusive of incorporating hypothetical responses in system parameters to management. To account for the iterative loop of adaptive management, yearly monitoring of state variables that approximated many stakeholder objectives was performed from 2005 to 2016 and data collected were incorporated into the decision model. Specific analysis of fish and macroinvertebrate population responses indicated a less than satisfactory response for some stakeholders to the flow-management changes at the dam. Uncertainty regarding the best management to provide adequate hydrologic and thermal habitats for fauna and boatable days for recreationists still exists. The project led to a Federal Energy Regulatory Commission process for renewing the license to operate the dam (beginning in 2018); adaptive management could be a viable path forward to ensure stakeholder satisfaction related to new management options.

Alabama↗