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Results for “Environmental Modeling & Assessment”

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At least 523 records · Page 29Linked to original sources
USGS2020

Reducing water scarcity by improving water productivity in the United States

Nearly one-sixth of U.S. river basins are unable to consistently meet societal water demands while also providing sufficient water for the environment. Water scarcity is expected to intensify and spread as populations increase, new water demands emerge, and climate changes. Improving water productivity by meeting realistic benchmarks for all water users could allow U.S. communities to expand economic activity and improve environmental flows. Here we utilize a spatially detailed database of water productivity to set realistic benchmarks for over 400 industries and products. We assess unrealized water savings achievable by each industry in each river basin within the conterminous U.S. by bringing all water users up to industry- and region-specific water productivity benchmarks. Some of the most water stressed areas throughout the U.S. West and South have the greatest potential for water savings, with around half of these water savings obtained by improving water productivity in the production of corn, cotton, and alfalfa. By incorporating benchmark-meeting water savings within a national hydrological model (WaSSI), we demonstrate that depletion of river flows across Western U.S. regions can be reduced on average by 6.2–23.2%, without reducing economic production. Lastly, we employ an environmentally extended input-output model to identify the U.S. industries and locations that can make the biggest impact by working with their suppliers to reduce water use 'upstream' in their supply chain. The agriculture and manufacturing sectors have the largest indirect water footprint due to their reliance on water-intensive inputs but these sectors also show the greatest capacity to reduce water consumption throughout their supply chains.

Conterminous United States↗
USGS2004

Assessing development pressure in the Chesapeake Bay watershed: An evaluation of two land-use change models

Natural resource lands in the Chesapeake Bay watershed are increasingly susceptible to conversion into developed land uses, particularly as the demand for residential development grows. We assessed development pressure in the Baltimore-Washington, DC region, one of the major urban and suburban centers in the watershed. We explored the utility of two modeling approaches for forecasting future development trends and patterns by comparing results from a cellular automata model, SLEUTH (slope, land use, excluded land, urban extent, transportation), and a supply/demand/allocation model, the Western Futures Model. SLEUTH can be classified as a land-cover change model and produces projections on the basis of historic trends of changes in the extent and patterns of developed land and future land protection scenarios. The Western Futures Model derives forecasts from historic trends in housing units, a U.S. Census variable, and exogenously supplied future population projections. Each approach has strengths and weaknesses, and combining the two has advantages and limitations. ?? 2004 Kluwer Academic Publishers.

Environmental Monitoring and Assessment↗
USGS2023

Cisco population characteristics in Wisconsin lakes in relation to lake- and landscape-level factors

Objective Declines in Cisco Coregonus artedi populations in some inland lakes have prompted assessments of Cisco occurrence and extirpation risk in relation to various stressors to identify refuge lakes and factors that promote Cisco persistence. However, most previous assessments have focused on presence–absence of Cisco rather than examining how population characteristics, such as relative abundance or growth, might change in relation to lake- and landscape-level environmental factors. Consequently, our specific objectives were to identify important environmental factors explaining variation in Cisco relative abundance and growth and to determine whether population metrics describing size and age distributions were related to relative abundance in Wisconsin inland lakes. Methods Cisco were collected from 48 inland Wisconsin lakes during 2011–2015 using vertical monofilament gill nets and population-specific relative abundance estimates (catch per unit effort [CPUE]) were quantified as the number of individuals per gill-net night. Sagittal otoliths were removed from a subsample of Cisco for age estimation and growth was indexed as mean total length (TL; mm) at age 2. Length and age data were used to develop a suite of metrics describing size and age distributions of each population. Random forest models were used to evaluate relationships between 10 biologically relevant predictor variables representing variation in physical, climatic, catchment, and limnological characteristics and Cisco CPUE and growth. Pearson correlations were used to determine whether population characteristics were related to CPUE. Result Cisco populations exhibited large variation in relative abundance, growth, and size and age distributions. Best-fit random forest models explained approximately 25% of the variation in Cisco CPUE and 46% of the variation in growth. Growing degree-days and variables associated with availability, quality, and quantity of suitable oxythermal conditions were identified as important predictors of both Cisco CPUE and growth; CPUE was also identified as an important predictor of growth. Mean TL and mean TL at age 2 were negatively related to Cisco CPUE, whereas mean age, number of age-classes present, and maximum observed age were positively related to CPUE. Conclusion Our results suggest that maintenance of suitable oxythermal habitat conditions may be critical to conserving abundant Cisco populations. Our assessment also provides insights on how Cisco populations may respond to environmental and anthropogenic stressors, which could aid ongoing and future conservation and management efforts in Wisconsin and elsewhere.

Wisconsin↗
USGS2015

Hydrogeochemistry and microbiology of mine drainage: An update

The extraction of mineral resources requires access through underground workings, or open pit operations, or through drillholes for solution mining. Additionally, mineral processing can generate large quantities of waste, including mill tailings, waste rock and refinery wastes, heap leach pads, and slag. Thus, through mining and mineral processing activities, large surface areas of sulfide minerals can be exposed to oxygen, water, and microbes, resulting in accelerated oxidation of sulfide and other minerals and the potential for the generation of low-quality drainage. The oxidation of sulfide minerals in mine wastes is accelerated by microbial catalysis of the oxidation of aqueous ferrous iron and sulfide. These reactions, particularly when combined with evaporation, can lead to extremely acidic drainage and very high concentrations of dissolved constituents. Although acid mine drainage is the most prevalent and damaging environmental concern associated with mining activities, generation of saline, basic and neutral drainage containing elevated concentrations of dissolved metals, non-metals, and metalloids has recently been recognized as a potential environmental concern. Acid neutralization reactions through the dissolution of carbonate, hydroxide, and silicate minerals and formation of secondary aluminum and ferric hydroxide phases can moderate the effects of acid generation and enhance the formation of secondary hydrated iron and aluminum minerals which may lessen the concentration of dissolved metals. Numerical models provide powerful tools for assessing impacts of these reactions on water quality.

Applied Geochemistry↗
USGS2017

Reconciling catch differences from multiple fishery independent gill net surveys

Fishery independent gill net surveys provide valuable demographic information for population assessment and resource management, but relative to net construction, the effects of ancillary species, and environmental variables on focal species catch rates are poorly understood. In response, we conducted comparative deployments with three unique, inter-agency, survey gill nets used to assess walleye Sander vitreus in Lake Erie. We used an information-theoretic approach with Akaike’s second-order information criterion (AIC c ) to evaluate linear mixed models of walleye catch as a function of net type (multifilament and two types of monofilament netting), mesh size (categorical), Secchi depth, temperature, water depth, catch of ancillary species, and interactions among selected variables. The model with the greatest weight of evidence showed that walleye catches were positively associated with potential prey and intra-guild predators and negatively associated with water depth and temperature. In addition, the multifilament net had higher average walleye catches than either of the two monofilament nets. Results from this study both help inform decisions about proposed gear changes to stock assessment surveys in Lake Erie, and advance our understanding of how multispecies associations explain variation in gill net catches. Of broader interest to fishery-independent gill net studies, effects of abiotic variables and ancillary species on focal specie’s catch rates were small in comparison with net characteristics of mesh size or twine type.

Lake Erie↗
USGS2009

Age-distribution estimation for karst groundwater: Issues of parameterization and complexity in inverse modeling by convolution

Convolution modeling is useful for investigating the temporal distribution of groundwater age based on environmental tracers. The framework of a quasi-transient convolution model that is applicable to two-domain flow in karst aquifers is presented. The model was designed to provide an acceptable level of statistical confidence in parameter estimates when only chlorofluorocarbon (CFC) and tritium ( 3 H) data are available. We show how inverse modeling and uncertainty assessment can be used to constrain model parameterization to a level warranted by available data while allowing major aspects of the flow system to be examined. As an example, the model was applied to water from a pumped well open to the Madison aquifer in central USA with input functions of CFC-11, CFC-12, CFC-113, and 3 H, and was calibrated to several samples collected during a 16-year period. A bimodal age distribution was modeled to represent quick and slow flow less than 50 years old. The effects of pumping and hydraulic head on the relative volumetric fractions of these domains were found to be influential factors for transient flow. Quick flow and slow flow were estimated to be distributed mainly within the age ranges of 0-2 and 26-41 years, respectively. The fraction of long-term flow (>50 years) was estimated but was not dateable. The different tracers had different degrees of influence on parameter estimation and uncertainty assessments, where 3 H was the most critical, and CFC-113 was least influential.

Journal of Hydrology↗
USGS2003

Quaternary vegetation and climate change in the western United States: Developments, perspectives, and prospects

This chapter explores the strengths and shortcomings of the major sources of data on Quaternary vegetation and climate change and discusses the use of models as a means to explore past and potential future environmental changes. The flora and major vegetation types of the western United States are present for several million years. Ongoing changes in atmospheric chemistry , climate, and human activities may lead to major vegetation changes over the coming decades to centuries. The combination of observations from the paleoenvironmental record, modern ecological studies, and modeling now permit assessments of the magnitude of potential future changes in the context of natural variability. They also provide opportunities for hypothesis testing and identification of the processes driving past changes in vegetation and climate. Understanding the dynamics of paleoenvironmental change can contribute to current conservation and natural resource management efforts and will help conservation and natural resource managers anticipate the potential rate, magnitude, and complexity of future vegetation change.

western United States↗
USGS2022

A framework for integrating inferred movement behavior into disease risk models

Movement behavior is an important contributor to habitat selection and its incorporation in disease risk models has been somewhat neglected. The habitat preferences of host individuals affect their probability of exposure to pathogens. If preference behavior can be incorporated in ecological niche models (ENMs) when data on pathogen distributions are available, then variation in such behavior may dramatically impact exposure risk. Here we use data from the anthrax endemic system of Etosha National Park, Namibia, to demonstrate how integrating inferred movement behavior alters the construction of disease risk maps. We used a Maximum Entropy (MaxEnt) model that associated soil, bioclimatic, and vegetation variables with the best available pathogen presence data collected at anthrax carcass sites to map areas of most likely Bacillus anthracis (the causative bacterium of anthrax) persistence. We then used a hidden Markov model (HMM) to distinguish foraging and non-foraging behavioral states along the movement tracks of nine zebra ( Equus quagga ) during the 2009 and 2010 anthrax seasons. The resulting tracks, decomposed on the basis of the inferred behavioral state, formed the basis of step-selection functions (SSFs) that used the MaxEnt output as a potential predictor variable. Our analyses revealed different risks of exposure during different zebra behavioral states, which were obscured when the full movement tracks were analyzed without consideration of the underlying behavioral states of individuals. Pathogen (or vector) distribution models may be misleading with regard to the actual risk faced by host animal populations when specific behavioral states are not explicitly accounted for in selection analyses. To more accurately evaluate exposure risk, especially in the case of environmentally transmitted pathogens, selection functions could be built for each identified behavioral state and then used to assess the comparative exposure risk across relevant states. The scale of data collection and analysis, however, introduces complexities and limitations for consideration when interpreting results.

Etosha National Park↗
USGS2012

Can arsenic occurrence rate in bedrock aquifers be predicted?

A high percentage (31%) of groundwater samples from bedrock aquifers in the greater Augusta area, Maine was found to contain greater than 10 μg L –1 of arsenic. Elevated arsenic concentrations are associated with bedrock geology, and more frequently observed in samples with high pH, low dissolved oxygen, and low nitrate. These associations were quantitatively compared by statistical analysis. Stepwise logistic regression models using bedrock geology and/or water chemistry parameters are developed and tested with external data sets to explore the feasibility of predicting groundwater arsenic occurrence rates (the percentages of arsenic concentrations higher than 10 μg L –1 ) in bedrock aquifers. Despite the under-prediction of high arsenic occurrence rates, models including groundwater geochemistry parameters predict arsenic occurrence rates better than those with bedrock geology only. Such simple models with very few parameters can be applied to obtain a preliminary arsenic risk assessment in bedrock aquifers at local to intermediate scales at other localities with similar geology.

Environmental Science & Technology↗
USGS2015

Empirical evaluation of the conceptual model underpinning a regional aquatic long-term monitoring program using causal modelling

Conceptual models are an integral facet of long-term monitoring programs. Proposed linkages between drivers, stressors, and ecological indicators are identified within the conceptual model of most mandated programs. We empirically evaluate a conceptual model developed for a regional aquatic and riparian monitoring program using causal models (i.e., Bayesian path analysis). We assess whether data gathered for regional status and trend estimation can also provide insights on why a stream may deviate from reference conditions. We target the hypothesized causal pathways for how anthropogenic drivers of road density, percent grazing, and percent forest within a catchment affect instream biological condition. We found instream temperature and fine sediments in arid sites and only fine sediments in mesic sites accounted for a significant portion of the maximum possible variation explainable in biological condition among managed sites. However, the biological significance of the direct effects of anthropogenic drivers on instream temperature and fine sediments were minimal or not detected. Consequently, there was weak to no biological support for causal pathways related to anthropogenic drivers’ impact on biological condition. With weak biological and statistical effect sizes, ignoring environmental contextual variables and covariates that explain natural heterogeneity would have resulted in no evidence of human impacts on biological integrity in some instances. For programs targeting the effects of anthropogenic activities, it is imperative to identify both land use practices and mechanisms that have led to degraded conditions (i.e., moving beyond simple status and trend estimation). Our empirical evaluation of the conceptual model underpinning the long-term monitoring program provided an opportunity for learning and, consequently, we discuss survey design elements that require modification to achieve question driven monitoring, a necessary step in the practice of adaptive monitoring. We suspect our situation is not unique and many programs may suffer from the same inferential disconnect. Commonly, the survey design is optimized for robust estimates of regional status and trend detection and not necessarily to provide statistical inferences on the causal mechanisms outlined in the conceptual model, even though these relationships are typically used to justify and promote the long-term monitoring of a chosen ecological indicator. Our application demonstrates a process for empirical evaluation of conceptual models and exemplifies the need for such interim assessments in order for programs to evolve and persist.

California, Colorado, Idaho, Montana, Nevada, Oreg↗
USGS2021

Demographic risk assessment for a harvested species threatened by climate change: Polar bears in the Chukchi Sea

Climate change threatens global biodiversity. Many species vulnerable to climate change are important to humans for nutritional, cultural, and economic reasons. Polar bears Ursus maritimus are threatened by sea-ice loss and represent a subsistence resource for Indigenous people. We applied a novel population modeling-management framework that is based on species life history and accounts for habitat loss to evaluate subsistence harvest for the Chukchi Sea (CS) polar bear subpopulation. Harvest strategies followed a state-dependent approach under which new data were used to update the harvest on a predetermined management interval. We found that a harvest strategy with a starting total harvest rate of 2.7% (˜85 bears/yr at current abundance), a 2:1 male-to-female ratio, and a 10-yr management interval would likely maintain subpopulation abundance above maximum net productivity level for the next 35 yr (approximately three polar bear generations), our primary criterion for sustainability. Plausible bounds on starting total harvest rate were 1.7–3.9%, where the range reflects uncertainty due to sampling variation, environmental variation, model selection, and differing levels of risk tolerance. The risk of undesired demographic outcomes (e.g., overharvest) was positively related to harvest rate, management interval, and projected declines in environmental carrying capacity; and negatively related to precision in population data. Results reflect several lines of evidence that the CS subpopulation has been productive in recent years, although it is uncertain how long this will last as sea-ice loss continues. Our methods provide a template for balancing trade-offs among protection, use, research investment, and other factors. Demographic risk assessment and state-dependent management will become increasingly important for harvested species, like polar bears, that exhibit spatiotemporal variation in their response to climate change.

Chukchi Sea↗
USGS2009

Remote sensing of global croplands for food security: Way forward

This book opens a new pathway for global mapping that is focused on a specific land use theme, such as irrigated or rain-fed croplands and classes within these themes. Since croplands use most of the water consumed by humans, specific knowledge of irrigated and rain-fed croplands will be critical for precise estimates of water use. At present and in the coming decades, irrigated and rain-fed cropland area mapping is crucial for food security studies. Throughout this book, various subjects pertaining to global croplands are discussed comprehensively.

Book chapter↗
USGS2007

Chinook salmon use of spawning patches: Relative roles of habitat quality, size, and connectivity

Declines in many native fish populations have led to reassessments of management goals and shifted priorities from consumptive uses to species preservation. As management has shifted, relevant environmental characteristics have evolved from traditional metrics that described local habitat quality to characterizations of habitat size and connectivity. Despite the implications this shift has for how habitats may be prioritized for conservation, it has been rare to assess the relative importance of these habitat components. We used an information-theoretic approach to select the best models from sets of logistic regressions that linked habitat quality, size, and connectivity to the occurrence of chinook salmon (Oncorhynchus tshawytscha) nests. Spawning distributions were censused annually from 1995 to 2004, and data were complemented with field measurements that described habitat quality in 43 suitable spawning patches across a stream network that drained 1150 km 2 in central Idaho. Results indicated that the most plausible models were dominated by measures of habitat size and connectivity, whereas habitat quality was of minor importance. Connectivity was the strongest predictor of nest occurrence, but connectivity interacted with habitat size, which became relatively more important when populations were reduced. Comparison of observed nest distributions to null model predictions confirmed that the habitat size association was driven by a biological mechanism when populations were small, but this association may have been an area-related sampling artifact at higher abundances. The implications for habitat management are that the size and connectivity of existing habitat networks should be maintained whenever possible. In situations where habitat restoration is occurring, expansion of existing areas or creation of new habitats in key areas that increase connectivity may be beneficial. Information about habitat size and connectivity also could be used to strategically prioritize areas for improvement of local habitat quality, with areas not meeting minimum thresholds being deemed inappropriate for pursuit of restoration activities. ?? 2007 by the Ecological Society of America.

Ecological Applications↗
USGS2015

California State Waters Map Series — Offshore of Point Reyes, California

This publication about the Offshore of Point Reyes map area includes ten map sheets that contain explanatory text, in addition to this descriptive pamphlet and a data catalog of geographic information system (GIS) files. Sheets 1, 2, and 3 combine data from four different sonar surveys to generate comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic features (highlighted in the perspective views on sheet 4) such as the flat, sediment-covered seafloor in Drakes Bay, as well as abundant “scour depressions” on the Bodega Head–Tomales Point shelf (see sheet 9) and local, tectonically controlled bedrock uplifts. To validate geological and biological interpretations of the sonar data shown in sheets 1, 2, and 3, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are summarized on sheet 6. Sheet 5 is a “seafloor character” map, which classifies the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. Sheet 7 is a map of “potential habitats,” which are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Sheet 8 compiles representative seismic-reflection profiles from the map area, providing information on the subsurface stratigraphy and structure of the map area. Sheet 9 shows the distribution and thickness of young sediment (deposited over the last about 21,000 years, during the most recent sea-level rise) in both the map area and the larger Salt Point to Drakes Bay region, interpreted on the basis of the seismic-reflection data, and it identifies the Offshore of Point Reyes map area as lying within the Bodega Head–Tomales Point shelf, Point Reyes bar, and Bolinas shelf domains. Sheet 10 is a geologic map that merges onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery (sheets 1, 2, 3), seafloor-sediment and rock samples (Reid and others, 2006), digital camera and video imagery (sheet 6), and high-resolution seismic-reflection profiles (sheet 8), as well as aerial-photographic interpretation of nearshore areas. The information provided by the map sheets, pamphlet, and data catalog have a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues.

California↗
USGS2020

Temporal and spatial changes in Myotis lucifugus acoustic activity before and after white-nose syndrome on Fort Drum Army Installation, New York, USA

Changes to bat distribution and habitat associations at the local to sub-landscape scale in the post white-nose syndrome (WNS) environment have received little attention to date despite being critical information for managers. To better understand the spatial nature of bat population declines, we modelled both activity patterns and occupancy from acoustic surveys for the Myotis lucifugus (little brown bat) on Fort Drum Military Installation in New York, USA over 15 summers (2003–2017) that span the pre-WNS, WNS-advent (2008) and post-WNS periods, using a set of generalized linear mixed models and geospatial analysis. Our best supported model indicated significant differences between years with significant declines in activity post-WNS. M. lucifugus activity was most closely associated with woody wetland habitats over the study period, however, the spatial patterns of high activity areas were variable over years, with the areal extent of these high activity areas decreasing post-WNS. Our best supported occupancy model varied by year. However, the null occupancy model [Ψ(.)] was either competing (within 2 ΔAIC units) or was the best supported model. Meaning that none of our environmental variables seemed to impact occupancy, and when they did, these differences were not significant. There was high disagreement between our relative activity models and predictions compared to our occupancy models, suggesting that geographic spatial scale and the resolution of the data impacts model outcome. Our results indicate that continued acoustic monitoring of bat species in the Northeast to assess ongoing temporal and spatial changes in habitat associations and to provide direction for future mist-netting studies should rely more on relative activity as the metric of choice rather than site occupancy.

New York↗
USGS2015

Synergistic and singular effects of river discharge and lunar illumination on dam passage of upstream migrant yellow-phase American eels

Monitoring of dam passage can be useful for management and conservation assessments of American eel, particularly if passage counts can be examined over multiple years. During a 7-year study (2007–2013) of upstream migration of American eels within the lower Shenandoah River (Potomac River drainage), we counted and measured American eels at the Millville Dam eel pass, where annual study periods were determined by the timing of the eel pass installation during spring or summer and removal during fall. Daily American eel counts were analysed with negative binomial regression models, with and without a year (YR) effect, and with the following time-varying environmental covariates: river discharge of the Shenandoah River at Millville (RDM) and of the Potomac River at Point of Rocks, lunar illumination (LI), water temperature, and cloud cover. A total of 17 161 yellow-phase American eels used the pass during the seven annual periods, and length measurements were obtained from 9213 individuals (mean = 294 mm TL, s.e. = 0.49, range 183–594 mm). Data on passage counts of American eels supported an additive-effects model (YR + LI + RDM) where parameter estimates were positive for river discharge (β = 7.3, s.e. = 0.01) and negative for LI (β = −1.9, s.e. = 0.34). Interestingly, RDM and LI acted synergistically and singularly as correlates of upstream migration of American eels, but the highest daily counts and multiple-day passage events were associated with increased RDM. Annual installation of the eel pass during late spring or summer prevented an early spring assessment, a period with higher RDM relative to those values obtained during sampling periods. Because increases in river discharge are climatically controlled events, upstream migration events of American eels within the Potomac River drainage are likely linked to the influence of climate variability on flow regime.

Potomac River drainage, Shenandoah River↗
USGS2025

Hydrogeologic mapping and three-dimensional geologic modeling of glacial deposits in a multicounty area of southeastern Michigan, northeastern Indiana, and northwestern Ohio

The glacial deposits underlying southeastern Michigan, northeastern Indiana, and northwestern Ohio are a substantial source of water to communities, agriculture, and industry in the region. Previous efforts to characterize aquifer materials in the area cited a need for additional information about the underlying hydrogeologic characteristics and related groundwater availability as well as improved mapping of the extent and properties of the glacial deposits. Recent U.S. Geological Survey multi-State compilations of water-well drilling records have greatly increased access to high-resolution geologic data, particularly in glacial depositional environments. This study by the U.S. Geological Survey, in cooperation with the Ohio Environmental Protection Agency, uses processed data from the State-managed collections of well records to characterize the glacial deposits in the study area using two methods. The first method creates two-dimensional maps of basic hydrogeologic information commonly required for assessments of groundwater availability, including (1) total thickness of glacial deposits, (2) total thickness of coarse-grained deposits, (3) specific-capacity-based transmissivity and hydraulic conductivity, and (4) texture-based estimated equivalent horizontal and vertical hydraulic conductivity and transmissivity. The second method builds a hydrogeologic framework of the complex glacial aquifer through construction of a volumetric geologic model by using three-dimensional kriging. Results of the volumetric model indicate that aquifer materials are primarily concentrated in the western parts of the study area near the Indiana-Ohio border. Coarse-grained sediments are also present as surficial deposits in the north of the study area where intermixing glacial advances created complex distributions of unconsolidated deposits. Two-dimensional maps of hydrogeologic properties support the volumetric model, showing thicknesses of coarse-grained deposits that reach up to 250 feet in the western sections of the study area and progressively thin to near absence in the east. Visualization of the aquifer materials with a volumetric model generally shows a highly discontinuous distribution of coarse- and fine-grained materials, with no clearly defined boundaries to delineate the extent of the aquifer. Comparisons of cross sections derived from the volumetric model with existing published maps support previous near-surface hydrogeologic interpretations while filling gaps where data are sparse, particularly in deeper parts of the aquifer. Both the two-dimensional maps and the volumetric model provide data that can directly inform assessments of groundwater availability, in addition to having future applications to studies of groundwater flow and transport.

Indiana, Michigan, Ohio↗
USGS2020

Predicting microcystin concentration action-level exceedances resulting from cyanobacterial blooms in selected lake sites in Ohio

Cyanobacterial harmful algal blooms and the toxins they produce are a global water-quality problem. Monitoring and prediction tools are needed to quickly predict cyanotoxin action-level exceedances in recreational and drinking waters used by the public. To address this need, data were collected at eight locations in Ohio, USA, to identify factors significantly related to observed concentrations of microcystins (a freshwater cyanotoxin) that could be used in two types of site-specific regression models. Real-time models include easily- or continuously-measured factors that do not require that a sample be collected; comprehensive models use a combination of discrete sample-based measurements and real-time factors. The study sites included two recreational sites and six water treatment plant sites. Real-time models commonly included variables such as phycocyanin, pH, specific conductance, and streamflow or gage height. Many real-time factors were averages over time periods antecedent to the time the microcystin sample was collected, including water-quality data compiled from continuous monitors. Comprehensive models were useful at some sites with lagged variables for cyanobacterial toxin genes, dissolved nutrients, and (or) nitrogen to phosphorus ratios. Because models can be used for management decisions, important measures of model performance were sensitivity, specificity, and accuracy of estimates above or below the microcystin concentration threshold standard or action level. Sensitivity is how well the predictive tool correctly predicts exceedance of a threshold, an important measure for water-resource managers. Sensitivities >90% at four Lake Erie water treatment plants indicated that models with continuous monitor data were especially promising. The planned next steps are to collect more data to build larger site-specific datasets and validate models before they can be used for management decisions.

Ohio↗