Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Environmental Modeling & Assessment”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,513 records · Page 84Linked to original sources
USGS2002

Ground-Water Resource Assessment in the Rio Grande de Manati Alluvial Plain, Rio Arriba Saliente Area, Puerto Rico

The alluvial aquifer within a 160-acre area of the Rio Grande de Manati alluvial plain was investigated to evaluate its potential as a water-supply source for the Barrios Rio Arriba Saliente and Pugnado Afuera, municipio of Manati, Puerto Rico. Analysis of well boring samples and the results of electric resistivity surveys indicate that the average thickness of the unconsolidated alluvial deposits in the study area is about 100 to 110 feet. The alluvium is a mixture of sand and gravel, which generally has a porosity of 0.2 to 0.35. Short-duration pump tests in small-diameter piezometers indicate that the alluvial aquifer has a hydraulic conductivity of about 200 feet per day and a transmissivity of about 7,900 feet squared per day. Analyses of water levels in piezometers, combined with stage measurements at a series of surveyed reference points along the Rio Grande de Manati channel, indicate that the water-table gradient in the alluvial aquifer is about 0.001, and that ground-water flow is generally from south to north, in the general direction of river flow. The water-table data indicate that the Rio Grande de Manati is the principal source of ground-water recharge to the alluvial aquifer in the study area. Because base flow for the Rio Grande de Manati is usually greater than 44 cubic feet per second, a continuous withdrawal rate of 0.5 to 1.0 cubic foot per second (225 to 450 gallons per minute) from a production well is possible. Chemical analysis of a ground-water sample indicates that the alluvial aquifer water meets U.S. Environmental Protection Agency secondary standards for selected constituents. Bacteriological analysis of ground-water samples indicates that the ground water contains little or no fecal coliform or fecal streptococcus bacteria. Although long-term data from upstream of the study area indicate high levels of fecal coliform and fecal streptococcus prior to 1996, bacteriological analyses of Rio Grande de Manati water samples obtained during the present study indicate that fecal coliform and fecal streptococcus concentrations are within the standards for surface water intended for use (or with the potential for use) as a raw source of public water supply in Puerto Rico. If a production well were constructed in the study area, it would be located close to the river channel (within 500 to 800 feet). Pumping from the porous and permeable alluvial aquifer close to the river channel could substantially enhance recharge from the Rio Grande de Manati channel to the aquifer. Enhanced recharge could shorten travel times for ground water in the aquifer, which might not allow sufficient time to attenuate bacteria and viruses. Travel times for bacteria moving from the river channel to a hypothetical production well were estimated using the numerical transport model MODFLOW/MT3DMS with an uncalibrated model of the alluvial aquifer. The model assumes a well pumping at 1 cubic foot per second. The transport of particles from the river to the well is most sensitive to the porosity of the aquifer and the pumping rate of the well. Sensitivity analysis indicates that a decrease in pumpage will increase the time of travel for particles to move from the river to the pumping well. The model indicates that the leading edge of a plume would reach the production well in about 40 days assuming a porosity of 0.20, 60 days assuming a porosity of 0.275, and about 70 days assuming a porosity of 0.35. If the well were moved 50 feet further from the river, the leading edge of the plume would reach the well in about 50 days assuming a porosity of 0.20 and about 70 days assuming a porosity of 0.275. These estimates are considered worse case estimates because no decay rate was included in the simulation, and because the hypothetical well was located in the center of the alluvial plain rather than further eastward, away from the river channel.

Water-Resources Investigations Report↗
USGS1985

Environmental systems and management activities on the Kennedy Space Center, Merritt Island, Florida: results of a modeling workshop

In the early 1960's, the National Aeronautics and Space Administration (NASA) began purchasing 140,000 acres on Merritt Island, Florida, in order to develop a center for space exploration. Most of this land was acquired to provide a safety and security buffer around NASA facilities. NASA, as the managing agency for the Kennedy Space Center (KSC), is responsible for preventing or controlling environmental pollution from the Federal facilities and activities at the Space Center and is committed to use all practicable means to protect and enhance the quality of the surrounding environment. The Merritt Island National Wildlife Refuge was established in 1963 when management authority for undeveloped lands at KSC was transferred to the U.S. Fish and Wildlife Service. In addition to manage for 11 Federally-listed threatened and endangered species and other resident and migratory fish and wildlife populations, the Refuge has comanagement responsibility for 19,000 acres of mosquito control impoundments and 2,500 acres of citrus groves. The Canaveral National Seashore was developed in 1975 when management of a portion of the coastal lands was transferred from NASA to the National Park Service. This multiagency jurisdiction on Merritt Island has resulted in a complex management environment. The modeling workshop described in this report was conducted May 21-25, 1984, at the Kennedy Space Center to: (1) enhance communication among the agencies with management responsibilities on Merritt Island; (2) integrate available information concerning the development, management, and ecology of Merritt Island; and (3) identify key research and monitoring needs associated with the management and use of the island's resources. The workshop was structured around the formulation of a model that would simulate primary management and use activities on Merritt Island and their effects on upland, impoundment, and estuarine vegetation and associated wildlife. The simulation model is composed of four connected submodels. The Uplands submodel calculates changes in acres and structural components of vegetation communities resulting from succession, fire, facilities development, and shuttle launch depositions, as well as the quantity and quality of surface runoff and aquifer input to an impoundment and an estuary. The Impoundment submodel next determines water quality and quantity and changes in vegetation resulting from water level manipulation and prescribed burning. The Estuary submodel than determines water quality parameters and acres of seagrass beds. Finally, the Wildlife submodel calculates habitat suitability indices for key species of interest, based on vegetation conditions in the uplands and impoundments and on several hydrologic parameters. The model represents a hypothetical management unit with 2,500 acres of uplands, a 600-acre impoundment, and a 1,500-acre section of estuary. Two management scenarios were run to analyze model behavior. The scenarios differ in the frequency of shuttle launches and prescribed burning, the extent of facilities development, the amount of land disposed waste material applied, and the nature and timing of impoundment water level control. Early in a model development project, the process of building the model is usually of greater benefit than the model itself. The model building process stimulates interaction among agencies, assists in integrating existing information, and helps identify research needs. These benefits usually accrue even in the absence of real predictive power in the resulting model. Open communication occurs among the Federal, State, and local agencies involved with activities on Merritt Island and the agencies have a cooperative working relationship. The workshop provided an opportunity for all of these agencies to meet at one time and have focused discussions on the key environmental and multiagency resource management issues. The workshop framework helped to integrate information and assumptions from a number of disciplines and agencies. This integration occurred in the computer simulation model and among workshop participants as submodel linkages were developed and scenario results discussed. A number of research needs were identified at the workshop during the model building and testing exercises and associated discussions. These needs were based on the informed judgement of researchers and managers familiar with Merritt Island or similar areas, rather than on a comprehensive literature review of sensitivity analysis of the preliminary model developed at the workshop. Some of the needs can be addressed by interpreting the results of completed studies from similar geographic areas as they relate to Merritt Island, while other will require additional research studies on Merritt Island. Major research needs associated with the Upland submodel include behavior of the near-surface aquifer, factors limiting slash pine regeneration, frequency and effects of natural fire on various cover types, cumulative effects of shuttle launches, and fate in upland soils of nitrogen and phosphorous from land applied waste material. Key Impoundment submodel needs include documentation of vegetation changes in response to altered water depth, salinity, and nutrient concentrations and better specification of the functional characteristics of impoundments as chemical filters. Important information gaps identified in the Estuary submodel include a more complete analysis of factors contributing to phytoplankton abundance, evaluation of sources of turbidity other than phytoplankton, and identification and quantification of factors limiting seagrass distribution. Primary research needs associated with the Wildlife submodel include a survey of breeding habitat, production data, and harvest data for mottled ducks; data on the emigration and immigration of juvenile mullet (and other transient fish) in the impoundment; the contribution of various seagrasses to habitat requirements of sea trout; and the effects of dissolved oxygen on survival of juvenile sea trout. Ideally, the modeling workshop process is iterative in nature. Periods between workshops are used for research, data collection, and model refinement. Each workshop integrates information collected since the last workshop and produces a more credible model that is more useful in evaluating management alternatives. Participants felt that continued application of this process would help provide ongoing integration and communication among agencies and would allow each agency's planning and management activities to be viewed within the context of an overall assessment.

Report↗
USGS2013

Perception, experience, and indigenous knowledge of climate change and variability: the case of Accra, a sub-Saharan African city

Several recent international assessments have concluded that climate change has the potential to reverse the modest economic gains achieved in many developing countries over the past decade. The phenomenon of climate change threatens to worsen poverty or burden populations with additional hardships, especially in poor societies with weak infrastructure and economic well-being. The importance of the perceptions, experiences, and knowledge of indigenous peoples has gained prominence in discussions of climate change and adaptation in developing countries and among international development organizations. Efforts to evaluate the role of indigenous knowledge in adaptation planning, however, have largely focused on rural people and their agricultural livelihoods. This paper presents the results of a study that examines perceptions, experiences, and indigenous knowledge relating to climate change and variability in three communities of metropolitan Accra, which is the capital of Ghana. The study design is based on a three-part conceptual framework and interview process involving risk mapping, mental models, and individual stressor cognition. Most of the residents interviewed in the three communities of urban Accra attributed climate change to the combination of deforestation and the burning of firewood and rubbish. None of the residents associated climate change with fossil fuel emissions from developed countries. Numerous potential adaptation strategies were suggested by the residents, many of which have been used effectively during past drought and flood events. Results suggest that ethnic residential clustering as well as strong community bonds in metropolitan Accra have allowed various groups and long-settled communities to engage in the sharing and transmission of knowledge of weather patterns and trends. Understanding and building upon indigenous knowledge may enhance the design, acceptance, and implementation of climate change adaptation strategies in Accra and urban regions of other developing nations.

Accra↗
USGS2024

Predicting redox conditions in groundwater at a national scale using random forest classification

Redox conditions in groundwater may markedly affect the fate and transport of nutrients, volatile organic compounds, and trace metals, with significant implications for human health. While many local assessments of redox conditions have been made, the spatial variability of redox reaction rates makes the determination of redox conditions at regional or national scales problematic. In this study, redox conditions in groundwater were predicted for the contiguous United States using random forest classification by relating measured water quality data from over 30,000 wells to natural and anthropogenic factors. The model correctly predicted the oxic/suboxic classification for 78 and 79% of the samples in the out-of-bag and hold-out data sets, respectively. Variables describing geology, hydrology, soil properties, and hydrologic position were among the most important factors affecting the likelihood of oxic conditions in groundwater. Important model variables tended to relate to aquifer recharge, groundwater travel time, or prevalence of electron donors, which are key drivers of redox conditions in groundwater. Partial dependence plots suggested that the likelihood of oxic conditions in groundwater decreased sharply as streams were approached and gradually as the depth below the water table increased. The probability of oxic groundwater increased as base flow index values increased, likely due to the prevalence of well-drained soils and geologic materials in high base flow index areas. The likelihood of oxic conditions increased as topographic wetness index (TWI) values decreased. High topographic wetness index values occur in areas with a propensity for standing water and overland flow, conditions that limit the delivery of dissolved oxygen to groundwater by recharge; higher TWI values also tend to occur in discharge areas, which may contain groundwater with long travel times. A second model was developed to predict the probability of elevated manganese (Mn) concentrations in groundwater (i.e., ≥50 μg/L). The Mn model relied on many of the same variables as the oxic/suboxic model and may be used to identify areas where Mn-reducing conditions occur and where there is an increased risk to domestic water supplies due to high Mn concentrations. Model predictions of redox conditions in groundwater produced in this study may help identify regions of the country with elevated groundwater vulnerability and stream vulnerability to groundwater-derived contaminants.

contiguous United States↗
USGS2017

Water quality and quantity and simulated surface-water and groundwater flow in the Laurel Hill Creek Basin, southwestern Pennsylvania, 1991–2007

Laurel Hill Creek is considered one of the most pristine waterways in southwestern Pennsylvania and has high recreational value as a high-quality cold-water fishery; however, the upper parts of the basin have documented water-quality impairments. Groundwater and surface water are withdrawn for public water supply and the basin has been identified as a Critical Water Planning Area (CWPA) under the State Water Plan. The U.S. Geological Survey, in cooperation with the Somerset County Conservation District, collected data and developed modeling tools to support the assessment of water-quality and water-quantity issues for a basin designated as a CWPA. Streams, springs, and groundwater wells were sampled for water quality in 2007. Streamflows were measured concurrent with water-quality sampling at main-stem sites on Laurel Hill Creek and tributaries in 2007. Stream temperatures were monitored continuously at five main-stem sites from 2007 to 2010. Water usage in the basin was summarized for 2003 and 2009 and a Water-Analysis Screening Tool (WAST) developed for the Pennsylvania State Water Plan was implemented to determine whether the water use in the basin exceeded the “safe yield” or “ the amount of water that can be withdrawn from a water resource over a period of time without impairing the long-term utility of a water resource .” A groundwater and surface-water flow (GSFLOW) model was developed for Laurel Hill Creek and calibrated to the measured daily streamflow from 1991 to 2007 for the streamflow-gaging station near the outlet of the basin at Ursina, Pa. The CWPA designation requires an assessment of current and future water use. The calibrated GSFLOW model can be used to assess the hydrologic effects of future changes in water use and land use in the basin. Analyses of samples collected for surface-water quality during base-flow conditions indicate that the highest nutrient concentrations in the main stem of Laurel Hill Creek were at sites in the northeastern part of the basin where agricultural activity is prominent. All of the total nitrogen (N) and a majority of the total phosphorus (P) concentrations in the main stem exceeded regional nutrient criteria levels of 0.31 and 0.01 milligrams per liter (mg/L), respectively. The highest total N and total P concentrations in the main stem were 1.42 and 0.06 mg/L, respectively. Tributary sites with the highest nutrient concentrations are in subbasins where treated wastewater is discharged, such as Kooser Run and Lost Creek. The highest total N and total P concentrations in subbasins were 3.45 and 0.11 mg/L, respectively. Dissolved chloride and sodium concentrations were highest in the upper part of the basin downstream from Interstate 76 because of road deicing salts. The mean base-flow concentrations of dissolved chloride and sodium were 117 and 77 mg/L, respectively, in samples from the main stem just below Interstate 76, and the mean concentrations in Clear Run were 210 and 118 mg/L, compared to concentrations less than 15 mg/L in tributaries that were not affected by highway runoff. Water quality in forested tributary subbasins underlain by the Allegheny and Pottsville Formations was influenced by acidic precipitation and, to a lesser extent, the underlying geology as indicated by pH values less than 5.0 and corresponding specific conductance ranging from 26 to 288 microsiemens per centimeter at 25 degrees Celsius for some samples; in contrast, pH values for main stem sites ranged from 6.6 to 8.5. Manganese (Mn) was the only dissolved constituent in the surface-water samples that exceeded the secondary maximum contaminant level (SMCL). More than one-half the samples from the main stem had Mn concentrations exceeding the SMCL level of 50 micrograms per liter (μg/L), whereas only 19 percent of samples from tributaries exceeded the SMCL for Mn. Stream temperatures along the main stem of Laurel Hill Creek became higher moving downstream. During the summer months of June through August, the daily mean temperatures at the five sites exceeded the limit of 18.9 degrees Celsius (°C) for a cold-water fishery. The maximum instantaneous values for each site ranged from 27.2 to 32.8 °C. Water-quality samples collected at groundwater sites (wells and springs) indicate that wells developed within the Mauch Chunk Formation had the best water quality, whereas wells developed within the Allegheny and Pottsville Formations yielded the poorest water quality. Waters from the Mauch Chunk Formation had the highest median pH (7.6) and alkalinity (80 mg/L calcium carbonate) values. The lowest pH and alkalinity median values were in waters from the Allegheny and Pottsville Formations. Groundwater samples collected from wells in the Allegheny and Pottsville Formations also had the highest concentrations of dissolved iron (Fe) and dissolved Mn. Seventy-eight percent of the groundwater samples collected from the Allegheny Formation exceeded the SMCL of 300 μg/L for Fe and 50 μg/L for Mn. Forty-three and 62 percent of the groundwater samples collected from the Pottsville Formation exceeded the SMCL for iron and Mn, respectively. The highest Fe and Mn concentrations for surface waters were measured for tributaries draining the Pottsville Formation. The highest median Fe concentration for tributaries was in samples from streams draining the Allegheny Formation. During base-flow conditions, the streamflow per unit area along the main stem of Laurel Hill Creek was lowest in the upper parts of the basin [farthest upstream site 0.07 cubic foot per second per square mile (ft 3 /s/mi 2 )] and highest (two sites averaging about 0.20 (ft 3 /s/mi 2 ) immediately downstream from Laurel Hill Lake in the center of the basin. Tributaries with the highest streamflow per unit area were those subbasins that drain the western ridge of the Laurel Hill Creek Basin. The mean streamflow per unit area for tributaries draining areas that extend into the western ridge and draining eastern or central sections was 0.24 and 0.05 ft 3 /s/mi 2 , respectively. In general, as the drainage area increased for tributary basins, the streamflow per unit area increased. Criteria established by the Pennsylvania Department of Environmental Protection indicate that the safe yield of water withdrawals from the Laurel Hill Creek Basin is 1.43 million gallons per day (Mgal/d). Water-use data for 2009 indicate that net (water withdrawals subtracted by water discharges) water withdrawals from groundwater and surface-water sources in the basin were approximately 1.93 Mgal/d. Water withdrawals were concentrated in the upper part of the basin with approximately 80 percent of the withdrawals occurring in the upper 36 mi 2 of the basin. Three subbasins—Allen Creek, Kooser Run, and Shafer Run— in the upper part were affected the most by water withdrawals such that safe yields were exceeded by more than 1,000 percent in the first two and more than 500 percent in the other. In the subbasin of Shafer Run, intermittent streamflow characterizes sections that historically have been perennial. The GSFLOW model of the Laurel Hill Creek Basin is a simple one-layer representation of the groundwater flow system. The GSFLOW model was primarily calibrated to reduce the error term associated with base-flow periods. The total amount of observed streamflow at the Laurel Hill Creek at Ursina, Pa. streamflow-gaging station and the simulated streamflow were within 0.1 percent over the entire modeled period; however, annual differences between simulated and observed streamflow showed a range of -27 to 24 percent from 1992 to 2007 with nine of the years having less than a 10-percent difference. The primary source of simulated streamflow in the GSFLOW model was the subsurface (interflow; 62 percent), followed by groundwater (25 percent) and surface runoff (13 percent). Most of the simulated subsurface flow that reached the stream was in the form of slow flow as opposed to preferential (fast) interflow.

Pennsylvania↗
USGS2011

Demographics and run timing of adult Lost River ( Deltistes luxatus ) and short nose ( Chasmistes brevirostris ) suckers in Upper Klamath Lake, Oregon, 2009

Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers ( Deltistes luxatus ) and shortnose suckers ( Chasmistes brevirostris ) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were reencountered on remote underwater antennas deployed throughout the spawning areas. Captures and remote encounters during spring 2009 were used to describe the spawning migrations in that year and also were incorporated into capture-recapture analyses of population dynamics over the last decade. Cormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish was examined for any additional evidence of recruitment. Survival and recruitment estimates were combined to estimate changes in population size over time and to determine the status of the populations through 2007. Separate analyses were conducted for each species and also for each subpopulation of Lost River suckers (LRS). One subpopulation of LRS migrates into tributaries to spawn, similar to shortnose suckers (SNS), whereas the other subpopulation spawns at upwelling areas along the eastern shoreline of the lake. In 2009, we captured and tagged 781 LRS at four shoreline areas and recaptured an additional 638 individuals that had been tagged in previous years. Across all four areas, the remote antennas detected 6,056 individual LRS during the spawning season. Spawning activity peaked in April and most individuals were encountered at Sucker Springs and Cinder Flats. In the Williamson River, we captured and tagged 3,008 LRS and 287 SNS, and recaptured 271 LRS and 81 SNS that had been tagged in previous years. Remote antennas that spanned the river downstream of the tributary spawning areas detected a total of 12,509 LRS and 5,023 SNS. Most LRS passed upstream in mid-April when water temperatures were rising and near or greater than 10°C. In contrast, peaks in upstream passage of SNS occurred in late April and early May when water temperatures were rising and near or greater than 12°C. Finally, an additional 1,569 LRS and 1,794 SNS were captured in trammel net sampling at prespawn staging areas in the northeastern portion of the lake. Of these, 209 of the LRS and 452 of the SNS had been PIT-tagged in previous years. For LRS, encounter histories showed that nearly all of the fish captured at the staging areas were members of the subpopulation that spawns in the tributaries. Capture-recapture analyses for the LRS subpopulation that spawns at the shoreline areas included encounter histories for more than 9,000 individuals, and analyses for the subpopulation that spawns in the tributaries included more than 14,000 encounter histories. With a few exceptions, the survival of males and females in both subpopulations was high (>0.9) between 1999 and 2007. Notably lower survival occurred for both sexes from the tributaries in 2000, for males from the shoreline areas in 2002, and for males from the tributaries in 2006. Recruitment of new individuals into either spawning population was trivial in all years between 2002 and 2007. Over that period, the abundance of males in the lakeshore spawning subpopulation declined by 44–53 percent and the abundance of females declined by 25–38 percent. Similarly, the abundance of males in the tributary spawning subpopulation declined by as much as 39 percent and the abundance of females declined by as much as 33 percent. Capture-recapture analyses for SNS included encounter histories for more than 12,000 individuals. The majority of annual survival estimates between 2001 and 2007 were high (>0.8), but SNS experienced more years of low survival than either LRS subpopulation. The survival of both sexes was particularly low in both 2001 and 2004, and male survival also was somewhat low in 2002 and 2006. Similar to LRS, recruitment of new individuals into the spawning population was trivial in all years between 2001 and 2007. Over that period, the abundance of male SNS declined by 58–80 percent and the abundance of females declined by 52–73 percent. Despite relatively high survival in most years, both species have experienced substantial declines in the abundance of spawning fish because losses from mortality have not been balanced by recruitment of new individuals. Indeed, all populations appear to be largely comprised of fish that were present in the late 1990s and early 2000s. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains worrisome, and the situation is most dire for shortnose suckers. Survival analyses show that the two species do not necessarily experience poor survival in the same years and that poor survival on an annual scale is not predictable from fish die-offs observed in the summer and fall. Future analyses will explore the connections between annual sucker survival and environmental factors of interest, such as water quality and disease. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.

Oregon↗
USGS2010

Potential economic benefits of adapting agricultural production systems to future climate change

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960–2005) and future climate period (2006–2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO 2 emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.

Montana↗
USGS2016

Consequences of changes in vegetation and snow cover for climate feedbacks in Alaska and northwest Canada

Changes in vegetation and snow cover may lead to feedbacks to climate through changes in surface albedo and energy fluxes between the land and atmosphere. In addition to these biogeophysical feedbacks, biogeochemical feedbacks associated with changes in carbon (C) storage in the vegetation and soils may also influence climate. Here, using a transient biogeographic model (ALFRESCO) and an ecosystem model (DOS-TEM), we quantified the biogeophysical feedbacks due to changes in vegetation and snow cover across continuous permafrost to non-permafrost ecosystems in Alaska and northwest Canada. We also computed the changes in carbon storage in this region to provide a general assessment of the direction of the biogeochemical feedback. We considered four ecoregions, or Landscape Conservations Cooperatives (LCCs; including the Arctic, North Pacific, Western Alaska, and Northwest Boreal). We examined the 90 year period from 2010 to 2099 using one future emission scenario (A1B), under outputs from two general circulation models (MPI-ECHAM5 and CCCMA-CGCM3.1). We found that changes in snow cover duration, including both the timing of snowmelt in the spring and snow return in the fall, provided the dominant positive biogeophysical feedback to climate across all LCCs, and was greater for the ECHAM (+3.1 W m −2 decade −1 regionally) compared to the CCCMA (+1.3 W m −2 decade −1 regionally) scenario due to an increase in loss of snow cover in the ECHAM scenario. The greatest overall negative feedback to climate from changes in vegetation cover was due to fire in spruce forests in the Northwest Boreal LCC and fire in shrub tundra in the Western LCC (−0.2 to −0.3 W m −2 decade −1 ). With the larger positive feedbacks associated with reductions in snow cover compared to the smaller negative feedbacks associated with shifts in vegetation, the feedback to climate warming was positive (total feedback of +2.7 W m −2 decade regionally in the ECHAM scenario compared to +0.76 W m −2 decade regionally in the CCCMA scenario). Overall, increases in C storage in the vegetation and soils across the study region would act as a negative feedback to climate. By exploring these feedbacks to climate, we can reach a more integrated understanding of the manner in which climate change may impact interactions between high-latitude ecosystems and the global climate system.

Environmental Research Letters↗
USGS2008

A Vegetation Database for the Colorado River Ecosystem from Glen Canyon Dam to the Western Boundary of Grand Canyon National Park, Arizona

A vegetation database of the riparian vegetation located within the Colorado River ecosystem (CRE), a subsection of the Colorado River between Glen Canyon Dam and the western boundary of Grand Canyon National Park, was constructed using four-band image mosaics acquired in May 2002. A digital line scanner was flown over the Colorado River corridor in Arizona by ISTAR Americas, using a Leica ADS-40 digital camera to acquire a digital surface model and four-band image mosaics (blue, green, red, and near-infrared) for vegetation mapping. The primary objective of this mapping project was to develop a digital inventory map of vegetation to enable patch- and landscape-scale change detection, and to establish randomized sampling points for ground surveys of terrestrial fauna (principally, but not exclusively, birds). The vegetation base map was constructed through a combination of ground surveys to identify vegetation classes, image processing, and automated supervised classification procedures. Analysis of the imagery and subsequent supervised classification involved multiple steps to evaluate band quality, band ratios, and vegetation texture and density. Identification of vegetation classes involved collection of cover data throughout the river corridor and subsequent analysis using two-way indicator species analysis (TWINSPAN). Vegetation was classified into six vegetation classes, following the National Vegetation Classification Standard, based on cover dominance. This analysis indicated that total area covered by all vegetation within the CRE was 3,346 ha. Considering the six vegetation classes, the sparse shrub (SS) class accounted for the greatest amount of vegetation (627 ha) followed by Pluchea (PLSE) and Tamarix (TARA) at 494 and 366 ha, respectively. The wetland (WTLD) and Prosopis-Acacia (PRGL) classes both had similar areal cover values (227 and 213 ha, respectively). Baccharis-Salix (BAXX) was the least represented at 94 ha. Accuracy assessment of the supervised classification determined that accuracies varied among vegetation classes from 90% to 49%. Causes for low accuracies were similar spectral signatures among vegetation classes. Fuzzy accuracy assessment improved classification accuracies such that Federal mapping standards of 80% accuracies for all classes were met. The scale used to quantify vegetation adequately meets the needs of the stakeholder group. Increasing the scale to meet the U.S. Geological Survey (USGS)-National Park Service (NPS)National Mapping Program's minimum mapping unit of 0.5 ha is unwarranted because this scale would reduce the resolution of some classes (e.g., seep willow/coyote willow would likely be combined with tamarisk). While this would undoubtedly improve classification accuracies, it would not provide the community-level information about vegetation change that would benefit stakeholders. The identification of vegetation classes should follow NPS mapping approaches to complement the national effort and should incorporate the alternative analysis for community identification that is being incorporated into newer NPS mapping efforts. National Vegetation Classification is followed in this report for association- to formation-level categories. Accuracies could be improved by including more environmental variables such as stage elevation in the classification process and incorporating object-based classification methods. Another approach that may address the heterogeneous species issue and classification is to use spectral mixing analysis to estimate the fractional cover of species within each pixel and better quantify the cover of individual species that compose a cover class. Varying flights to capture vegetation at different times of the year might also help separate some vegetation classes, though the cost may be prohibitive. Lastly, photointerpretation instead of automated mapping could be tried. Photointerpretation would likely not improve accuracies in this case, howev

Open-File Report↗
USGS2014

Threshold-dependent sample sizes for selenium assessment with stream fish tissue

Natural resource managers are developing assessments of selenium (Se) contamination in freshwater ecosystems based on fish tissue concentrations. We evaluated the effects of sample size (i.e., number of fish per site) on the probability of correctly detecting mean whole-body Se values above a range of potential management thresholds. We modeled Se concentrations as gamma distributions with shape and scale parameters fitting an empirical mean-to-variance relationship in data from southwestern West Virginia, USA (63 collections, 382 individuals). We used parametric bootstrapping techniques to calculate statistical power as the probability of detecting true mean concentrations up to 3 mg Se/kg above management thresholds ranging from 4 to 8 mg Se/kg. Sample sizes required to achieve 80% power varied as a function of management thresholds and Type I error tolerance (α). Higher thresholds required more samples than lower thresholds because populations were more heterogeneous at higher mean Se levels. For instance, to assess a management threshold of 4 mg Se/kg, a sample of eight fish could detect an increase of approximately 1 mg Se/kg with 80% power (given α = 0.05), but this sample size would be unable to detect such an increase from a management threshold of 8 mg Se/kg with more than a coin-flip probability. Increasing α decreased sample size requirements to detect above-threshold mean Se concentrations with 80% power. For instance, at an α-level of 0.05, an 8-fish sample could detect an increase of approximately 2 units above a threshold of 8 mg Se/kg with 80% power, but when α was relaxed to 0.2, this sample size was more sensitive to increasing mean Se concentrations, allowing detection of an increase of approximately 1.2 units with equivalent power. Combining individuals into 2- and 4-fish composite samples for laboratory analysis did not decrease power because the reduced number of laboratory samples was compensated for by increased precision of composites for estimating mean conditions. However, low sample sizes (<5 fish) did not achieve 80% power to detect near-threshold values (i.e., <1 mg Se/kg) under any scenario we evaluated. This analysis can assist the sampling design and interpretation of Se assessments from fish tissue by accounting for natural variation in stream fish populations.

Integrated Environmental Assessment and Management↗
USGS2019

Understanding tidal marsh trajectories: Evaluation of multiple indicators of marsh persistence

Robust assessments of ecosystem stability are critical for informing conservation and management decisions. Tidal marsh ecosystems provide vital services, yet are globally threatened by anthropogenic alterations to physical and biological processes. A variety of monitoring and modeling approaches have been undertaken to determine which tidal marshes are likely to persist into the future. Here, we conduct the most robust comparison of marsh metrics to date, building on two foundational studies that had previously and independently developed metrics for marsh condition. We characterized pairs of marshes with contrasting trajectories (of marsh cover ) across six regions of the United States, using a combination of remote-sensing and field-based metrics. We also quantified decadal trends in marsh conversion to mudflat/open water at these twelve marshes. Our results suggest that metrics quantifying the distribution of vegetation across an elevational gradient represent the best indicators of marsh trajectories. The unvegetated to vegetated ratio and flood-ebb sediment differential also served as valuable indicators. No single metric universally predicted marsh trajectories, and therefore a more robust approach includes a suite of spatially integrated, landscape-scale metrics that are mostly obtainable from remote sensing. Data from surface elevation tables and marker horizons revealed that degrading marshes can have higher rates of vertical accretion and elevation gain than more intact counterparts, likely due to longer inundation times potentially combined with internal recycling of material. A high rate of elevation gain relative to local sea-level rise has been considered critical to marsh persistence, but our results suggest that it also may serve as a signature of degradation in marshes that have already begun to deteriorate. This investigation, with rigorous comparison and integration of metrics initially developed independently, tested at a broad geographic scale, provides a model for collaborative science to develop management tools for improving conservation outcomes.

Environmental Research Letters↗
USGS2025

Estimating daily public supply water use by drinking water service area in New Jersey

This report, prepared in cooperation with the New Jersey Department of Environmental Protection, presents a method for estimating daily public supply water use by drinking water service area systems for New Jersey. The ability to accurately estimate daily public supply water use could help water supply planners in New Jersey better understand and manage the state’s limited water resources and balance the competing needs for freshwater resources. Data sources for this work include daily public supply water-use data from 2016 through 2020 acquired from New Jersey American Water for 15 drinking water service areas and monthly data exported from the New Jersey Department of Environmental Protection’s online water transfer data model database (known as NJWaTr). The two datasets were compared by aggregating the daily data to a monthly timescale. Statistical regression analysis was applied to the daily data, along with climate data, to evaluate what factors are influential in estimating daily fluctuations and trends in daily public supply water use. Fifteen regression equations were developed, one for each of the 15 drinking water service area systems for which daily data were acquired. Regression equations for systems that had seasonal patterns performed better than equations for non-seasonal systems. For the test year (2020), the average adjusted coefficient of determination for the linear regression with autoregressive errors model among systems with seasonality was 0.78; the average adjusted coefficient of determination for the linear regression with autoregressive errors model among systems with little or no seasonality was 0.25. The effects of anomalous data in the regression analysis were examined by comparing adjusted coefficient of determination values when the atypical data points were removed versus when they were retained in the analysis. Overall, including the anomalous data did not have a large effect on the results, and thus the data were retained for this study. In addition to developing regression equations, all 589 unique drinking water service area systems in New Jersey were characterized based on socio-economic data and monthly water-use data from NJWaTr. Systems that are located near the New Jersey coast, serve populations larger than 1,970 people, or serve areas that have median property values over $256,250 tended to demonstrate seasonal water-use behaviors. Systems that have mostly urban residential land use tended to show little to no seasonal water-use behaviors. Finally, a method was developed to disaggregate monthly data to a daily timescale and was tested against systems for which daily data were not available. Two regression equation forms were developed to be applied to systems beyond the 15 systems from which the original equations were developed; one equation was developed for use when all drinking water service area systems showed little to no seasonality, and the other equation was developed for use when systems displayed seasonal behavior. To the extent possible, uncertainty and possible sources of error were identified and examined in relation to the regression model equations developed. Additional daily data from these 15 systems (over different years) and daily data from different systems could be used to further evaluate the results of the disaggregation through a comprehensive assessment of error. Further adjustments to the regression equations could be made, ultimately enhancing their accuracy.

New Jersey↗
USGS2024

Using the horizontal-to-vertical spectral ratio method to estimate thickness of the Barry Arm landslide, Prince William Sound, Alaska

Conducting detailed investigations of large landslides is difficult, especially in the subsurface, largely due to environmental factors such as steep slopes, difficult access, and numerous objective hazards. These factors have made it challenging to accurately estimate the depth to the failure surface of the Barry Arm landslide, a large (roughly 10 8 cubic meters), deep-seated bedrock landslide in Prince William Sound, Alaska, recognized in 2019. The landslide has exhibited accelerated movement in recent years and poses a potential tsunamigenic hazard if rapid failure occurs. Failure surface depth, equivalent to landslide thickness, is a necessary metric for landslide-volume calculations and associated tsunami wave models. In this report, we used seismic noise recorded by a seismometer located on the Barry Arm landslide in Alaska to calculate the horizontal-to-vertical spectral ratio (HVSR) to investigate the site fundamental frequency ( f 0 ) and depth of the failure surface. To ensure that observed peak frequencies in the spectral ratio were related to the underlying stratigraphy (and not caused by other noise sources like nearby glaciers, topographic resonance, weather, or human activities), we also calculated HVSRs using earthquake signals, HVSRs at other seismic stations within a 2.5-kilometer radius, and a standard spectral ratio between the landslide station and other sites. We observed multiple peaks in the landslide HVSR curves at 1.5 hertz (Hz), 4–5 Hz, and 7–11 Hz. The frequencies of these peaks were consistent at the landslide site through time and across methods and were dissimilar to those identified at other seismic stations in the area, making it unlikely the peaks were caused by local noise. Directional HVSRs calculated at 15-degree intervals showed amplification of the higher frequency peaks in the direction parallel to slip, indicating two-dimensional site effects. We used the distinct frequency peaks in the seismic record to develop a 4-layer conceptual model of the landslide wherein the top of the deepest layer represents the primary failure surface, or the boundary between damaged (mobile) and undamaged material. We inverted Rayleigh wave ellipticity curves within this 4-layer configuration with constraints on S-wave velocity and layer thickness based on analogous material properties identified in the literature. This was necessary absent any site-specific subsurface S-wave velocity data. The best-fitting models indicate a mean slope-normal depth to the failure surface of 188 (±9) meters (m), with additional stratigraphic boundaries at 4 and 20 m below ground surface, potentially representing layered motion. These results agree with and improve upon ranges estimated by previous studies and can support future modeling and assessment efforts at Barry Arm.

Alaska↗
USGS2019

In ovo exposure to brominated flame retardants Part II: Assessment of effects of TBBPA-BDBPE and BTBPE on hatching success, morphometric and physiological endpoints in American kestrels

Tetrabromobisphenol A bis(2,3-dibromopropyl ether) (TBBPA-BDBPE) and 1,2-bis(2,4,6-tribromophenoxy)ethane (BTPBE) are both brominated flame retardants (BFRs) that have been detected in birds; however, their potential biological effects are largely unknown. We assessed the effects of embryonic exposure to TBBPA-BDBPE and BTBPE in a model avian predator, the American kestrel ( Falco sparverius ). Fertile eggs from a captive population of kestrels were injected on embryonic day 5 (ED5) with a vehicle control or one of three doses within the range of concentrations that have been detected in biota (nominal concentrations of 0, 10, 50 or 100 ng/g egg; measured concentrations 0, 3.0, 13.7 or 33.5 ng TBBPA-BDBPE/g egg and 0, 5.3, 26.8 or 58.1 ng BTBPE/g egg). Eggs were artificially incubated until hatching (ED28), at which point blood and tissues were collected to measure morphological and physiological endpoints, including organ somatic indices, circulating and glandular thyroid hormone concentrations, thyroid gland histology, hepatic deiodinase activity, and markers of oxidative stress. Neither compound had any effects on embryo survival through 90% of the incubation period or on hatching success, body mass, organ size, or oxidative stress of hatchlings. There was evidence of sex-specific effects in the thyroid system responses to the BTBPE exposures, with type 2 deiodinase (D2) activity decreasing at higher doses in female, but not in male hatchlings, suggesting that females may be more sensitive to BTBPE. However, there were no effects of TBBPA-BDBPE on the thyroid system in kestrels. For the BTPBE study, a subset of high-dose eggs was collected throughout the incubation period to measure changes in BTBPE concentrations. There was no decrease in BTBPE over the incubation period, suggesting that BTBPE is slowly metabolized by kestrel embryos throughout their ∼28-d development. These two compounds, therefore, do not appear to be particularly toxic to embryos of the American kestrel.

Ecotoxicology and Environmental Safety↗
USGS2017

Assessing the global distribution of river fisheries harvest: A systematic map protocol

Background Although surface freshwater comprises < 0.01% of the total water volume of earth, freshwater inland capture fisheries and aquaculture represent 40% of the global reported finfish harvest. While the social, economic, and ecological importance of inland fish and fisheries is difficult to overstate, they are often undervalued and underappreciated. Accurate information about these highly dispersed fisheries is inherently difficult to acquire, often unreported, and not collected in a standardized format globally. A standardized river fishery database is needed for managing aquatic systems as well as for defining relevant development policies. Here, we describe our methodology to search, identify, and describe available river fisheries information to create a harmonized global database of river fisheries harvest. This database will provide the first global database of spatially and temporally explicit river fisheries data. The database can be used to identify locations, hotspots of data collection, and gaps in existing knowledge and will be especially important to inform studies and management at larger spatial scales (i.e., watershed, regional, or global scales). This database will also be critical for developing fish biomass models for rivers, which can provide managers with information critical for decision-making, such as improved valuation methods for river fish and fisheries. Methods This systematic map protocol describes the methodology to search, identify, and describe available information on river fish and fisheries across the globe. We define river fisheries as “both capture and aquaculture of river finfish species for food, income, or recreation”. River fish species are those finfish that live part, or all of their lives in rivers. The searches will be conducted for the period from 1950 to present using bibliographic databases and grey literature sources. To identify relevant evidence, pre-defined inclusion and exclusion criteria will be used to screen articles at title, abstract, and full text. A searchable database containing extracted meta-data from relevant included studies will be developed and presented as a geodatabase. The final systematic map will consist of a descriptive narrative report of the distribution and content of river fish literature including a geodatabase of available information.

Environmental Evidence↗
USGS2010

Biological pathways of exposure and ecotoxicity values for uranium and associated radionuclides: Chapter D in Hydrological, geological, and biological site characterization of breccia pipe uranium deposits in Northern Arizona

This chapter compiles available chemical and radiation toxicity information for plants and animals from the scientific literature on naturally occurring uranium and associated radionuclides. Specifically, chemical and radiation hazards associated with radionuclides in the uranium decay series including uranium, thallium, thorium, bismuth, radium, radon, protactinium, polonium, actinium, and francium were the focus of the literature compilation. In addition, exposure pathways and a food web specific to the segregation areas were developed. Major biological exposure pathways considered were ingestion, inhalation, absorption, and bioaccumulation, and biota categories included microbes, invertebrates, plants, fishes, amphibians, reptiles, birds, and mammals. These data were developed for incorporation into a risk assessment to be conducted as part of an environmental impact statement for the Bureau of Land Management, which would identify representative plants and animals and their relative sensitivities to exposure of uranium and associated radionuclides. This chapter provides pertinent information to aid in the development of such an ecological risk assessment but does not estimate or derive guidance thresholds for radionuclides associated with uranium. Previous studies have not attempted to quantify the risks to biota caused directly by the chemical or radiation releases at uranium mining sites, although some information is available for uranium mill tailings and uranium mine closure activities. Research into the biological impacts of uranium exposure is strongly biased towards human health and exposure related to enriched or depleted uranium associated with the nuclear energy industry rather than naturally occurring uranium associated with uranium mining. Nevertheless, studies have reported that uranium and other radionuclides can affect the survival, growth, and reproduction of plants and animals. Exposure to chemical and radiation hazards is influenced by a plant’s or an animal’s life history and surrounding environment. Various species of plants, invertebrates, fishes, amphibians, reptiles, birds, and mammals found in the segregation areas that are considered species of concern by State and Federal agencies were included in the development of the site-specific food web. The utilization of subterranean habitats (burrows in uranium-rich areas, burrows in waste rock piles or reclaimed mining areas, mine tunnels) in the seasonally variable but consistently hot, arid environment is of particular concern in the segregation areas. Certain species of reptiles, amphibians, birds, and mammals in the segregation areas spend significant amounts of time in burrows where they can inhale or ingest uranium and other radionuclides through digging, eating, preening, and hibernating. Herbivores may also be exposed though the ingestion of radionuclides that have been aerially deposited on vegetation. Measured tissues concentrations of uranium and other radionuclides are not available for any species of concern in the segregation areas. The sensitivity of these animals to uranium exposure is unknown based on the existing scientific literature, and species-specific uranium presumptive effects levels were only available for two endangered fish species known to inhabit the segregation areas. Overall, the chemical toxicity data available for biological receptors of concern were limited, although chemical and radiation toxicity guidance values are available from several sources. However, caution should be used when directly applying these values to northern Arizona given the unique habitat and life history strategies of biological receptors in the segregation areas and the fact that some guidance values are based on models rather than empirical (laboratory or field) data. No chemical toxicity information based on empirical data is available for reptiles, birds, or wild mammals; therefore, the risks associated with uranium and other radionuclides are unknown for these biota.

Arizona↗
USGS2009

Estimating Locations of Perennial Streams in Idaho Using a Generalized Least-Squares Regression Model of 7-Day, 2-Year Low Flows

Many State and Federal agencies use information regarding the locations of streams having intermittent or perennial flow when making management and regulatory decisions. For example, the application of some Idaho water quality standards depends on whether streams are intermittent. Idaho Administrative Code defines an intermittent stream as one having a 7-day, 2-year low flow (7Q2) less than 0.1 ft3/s. However, there is a general recognition that the cartographic representation of perennial/intermittent status of streams on U.S. Geological Survey (USGS) topographic maps is not as accurate or consistent as desirable from one map to another, which makes broad management and regulatory assessments difficult and inconsistent. To help resolve this problem, the USGS has developed a methodology for predicting the locations of perennial streams based on regional generalized least-squares (GLS) regression equations for Idaho streams for the 7Q2 low-flow statistic. Using these regression equations, the 7Q2 streamflow may be estimated for naturally flowing streams in most areas in Idaho. The use of these equations in conjunction with a geographic information system (GIS) technique known as weighted flow accumulation allows for an automated and continuous estimation of 7Q2 streamflow at all points along stream reaches. The USGS has developed a GIS-based map of the locations of streams in Idaho with perennial flow based on a 7Q2 of 0.1 ft3/s and a transition zone of plus or minus 1 standard error. Idaho State cooperators plan to use this information to make regulatory and water-quality management decisions. Originally, 7Q2 equations were developed for eight regions of similar hydrologic characteristics in the study area, using long-term data from 234 streamflow-gaging stations. Equations in five of the regions were revised based on spatial patterns observed in the initial perennial streams map and unrealistic behavior of the equations in extrapolation. The standard errors of prediction for the final equations ranged from a minimum of +75.0 to -42.9 percent in the central part of the study area to a maximum of +277 to -73.5 percent in the southern part of the study area. The equations are applicable only to unregulated, naturally-flowing streams and may produce unreliable results outside the range of explanatory variables used for equation development. Extrapolation outside the range of available data was necessary, however, to predict perennial flow initiation points and transition zones along stream reaches. The map of perennial streams was evaluated by comparing predicted stream classifications with four independent datasets, including field observations by other government agencies. Overall, 81 percent of the comparison data points agreed with the USGS perennial streams model. Regions with the highest number of disagreements had a high percentage of mountainous and forested area with potential mountain front recharge zones, and regions with the highest agreements had a high percentage of low gradient, low elevation area. As a whole, the USGS model predicted a higher number of perennial streams than predictions made with the independent datasets. Some disagreements were due to poor site location coordinates, timing of the comparison site visits during unusually wet or dry years, discrepancies in classification criteria, and variable ground water contributions to flow in some areas. The Idaho Department of Environmental Quality Beneficial Use Reconnaissance Program (BURP) dataset is considered the most representative dataset for comparison because it covered a range of climate conditions and the number of sites visited were consistent from year to year during the study period. Eighty-five percent of BURP comparison data points agreed with the USGS perennial streams model. Although site-specific flow data may be needed to correctly classify streams in some areas, this information rarely is available and is not always practical to o

Scientific Investigations Report↗
USGS2025

Physical habitat is more than a sediment issue: A multi-dimensional habitat assessment indicates new approaches for river management

Degraded physical habitat is a common stressor affecting river ecosystems and typically addressed in the United States (US) through a regulatory focus on sediment. However, a narrow regulatory focus on sediment may overlook other aspects of physical habitat and the processes for its creation, maintenance, and degradation. In addition, there exist few “ready-to-use” regional assessments of the multiple dimensions of physical habitat to better understand continuous patterns of condition and prioritize management efforts across a large spatial scale. In this study, we use rapid habitat monitoring data to train a machine-learning ( i.e., random forest) model to predict twelve physical habitat metrics for nearly 120,000 km of nontidal rivers and streams across the Chesapeake Bay watershed, US. We capture a range of habitat conditions driven by both natural variables and anthropogenic pressures. Covariation among habitat metrics indicated two major dimensions of habitat variation: 1) coarse bed substrate and hydromorphic heterogeneity and 2) bank stability and riparian condition. The model predicted localized changes from 2001 to 2019, and the predicted areas of deterioration roughly balanced improvements across the watershed, indicating little progress towards long-term watershed management goals. To evaluate connections to regulatory and management endpoints, we compared our physical habitat predictions to paired estimates of sediment and flow alteration across the region. Sediment concentrations were greater in reaches with less bank stability and lower riparian quality; however, the relation was weak for coarse bed condition metrics, including embeddedness, which is frequently used for establishing regulatory sediment restrictions. For flow alteration, most habitat metrics had lower scores with altered flow metrics, but metrics of instream habitat heterogeneity and coarse substrate condition were most strongly affected. Increased flashy, high flows negatively affected most metrics, but coarse substrate metrics were also negatively affected by greater low flow severity. This study highlights a potential disconnect between a narrow focus on regulatory sediment targets given the multiple dimensions and responses of physical habitat. A more holistic approach to physical habitat in management interventions – one that considers hydromorphic processes, diversity and variability in microhabitats, and explicit consideration of alterations to both low and high flows – may be warranted. By providing direct estimates of multiple aspects of physical habitat, this model can help support managers in the Chesapeake Bay watershed to better understand the range of habitat conditions, identify high-quality reaches for conservation, and target potential management actions tailored to localized conditions.

Delaware, Maryland, New York, Pennsylvania, Virgin↗