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Research about Minnesota

Source-linked reports with geographic coverage including Minnesota.

At least 73 records · Page 4Linked to original sources

How machine learning can improve predictions and provide insight into fluvial sediment transport in Minnesota

Understanding fluvial sediment transport is critical to addressing many environmental concerns such as exacerbated flooding, degradation of aquatic habitat, excess nutrients, and the economic challenges of restoring aquatic systems. However, fluvial sediment transport is difficult to understand because of the multitude of factors controlling the potential sources, delivery, mechanics, and storage of sediment in aquatic systems. While physical fluvial sediment samples are an integral part of developing solutions for these environmental concerns, samples cannot be collected at every river and time of interest. Therefore, accurate and cost-effective estimates of sediment loading are needed to manage riverine sediment transport at a multitude of scales (Ellison et al. 2016); also needed are methods to estimate sediment transport at sites where little or no physical samples have been collected (Gray & Simes 2008). The application of machine learning (ML) approaches to estimate sediment transport has grown over the past two decades (Afan et al. 2016). ML used in sediment transport research has shown multiple benefits over traditional approaches, such as increased prediction accuracy, the ability to learn complex linear and non-linear relations amongst the dataset and providing the ability to interpret these complex relations with important features used in the model (Cisty et al. 2021; Francke et al. 2008; Khan et al. 2021; Zounemat-Kermani et al. 2020; Cutler et al. 2007).

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Geophysical architecture of the Neoarchean Mentor anorthosite intrusive complex, northwestern Minnesota

The ca. 2737 Ma (Souders, 2023) Mentor anorthosite intrusive complex (MAIC) lies near the northern margin of the Wawa subprovince of the Archean Superior Province, in an area of northwestern Minnesota where the Wawa, Quetico, and Wabigoon subprovinces are juxtaposed in close proximity (Fig. 1). The rocks of interest are entirely concealed by 10s to >100 m of unconsolidated Quaternary sediments and localized Cretaceous strata and saprolite. The MAIC comprises a large volume of megacrystic anorthosite, with a lesser volume of oxide-rich gabbros. The gabbros are known, from a single borehole intersection at ~70 m depth, to be enriched in vanadium (see http://minarchive.dnr.state.mn.us), and have further potential for chromium and titanium mineralization. New interpretations are based on data from an Earth Mapping Resources Initiative (MRI)-sponsored aeromagnetic survey flown in 2021 and pre-existing ground gravity data, constrained by approximately ten boreholes in the area.

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Examining landowners’ preferences for a chronic wasting disease management program

Private landowners are key partners in chronic wasting disease (CWD) management, especially in landscapes where there is limited public ownership. In this study, we evaluated landowners' preferences for alternative hypothetical CWD management programs using a stated choice experiment. We were particularly interested in understanding preferences for the use of financial incentives to motivate white-tailed deer harvest and facilitate hunter access to private lands as potential CWD management tools. We used latent class analysis to characterize preference heterogeneity among landowners stemming from patterns of choice. We compared means and distributions of auxiliary variables related to landowners' perceived risks, trust, attitudes toward management, and sociodemographics across latent classes stemming from choice model results. The pooled model demonstrated that reducing deer population density, providing payments to landowners for CWD-positive deer taken from their property, the form of incentives for public access, and banning recreational deer feeding had a small positive effect on respondents' choice of CWD management program. However, providing financial payments to hunters for harvesting CWD-positive deer and the use of targeted culling had the opposite effect on choice. Latent class models revealed that a majority of respondents exhibited a pattern of preference where all forms of incentives exerted a negative effect on choice, but smaller subsets of landowners positively evaluate the use of some incentives. Post-hoc contrasts revealed relationships between patterns of preferences and trust, risk, and attitudes toward CWD management with small to medium effects. Results demonstrated limited support for the use of financial incentives as a tool to manage access and harvest in the southeast Minnesota CWD management zone

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Regional-scale mapping of landscape response to extreme precipitation using repeat lidar and object-based image analysis

Extreme precipitation events may cause flooding, slope failure, erosion, deposition, and damage to infrastructure over a regional scale, but the impacts of these events are often difficult to fully characterize. Regional-scale landscape change occurred during an extreme rain event in June 2012 in northeastern Minnesota. Landscape change was documented by 8,000 km 2 of airborne lidar data collected before and after the event. Following improved alignment of the lidar point data and reducing error using insight from analysis of extensive stable areas, elevation differences were classified into map objects representing geomorphic change in relation to process and landscape position using object-based image analysis. This remote mapping compares favorably to field and imagery-based mapping and provides the basis for volumetric sediment budgeting. Elevation differences in these objects indicate that 4.5 × 10 6 ± 1.0 × 10 6 m 3 of sediment was eroded in the study area. Of this, 2.5 × 10 6 ± 3.3 × 10 5 m 3 was deposited in deposits on hillslopes and valley floors, and 2.0 × 10 6 ± 4.6 × 10 5 m 3 were removed from watersheds and exported to the Saint Louis River Estuary and Lake Superior. Multivariate logistic regression analysis emphasized that topographic slope and presence of glaciolacustrine clay lithology are the primary control on landslide occurrence, and landslides occur most frequently on slopes within tens of meters of stream channels. These results provide the basis to anticipate the impacts of similar future storm events. Because precipitation events are forecast to continue to increase in frequency and intensity owing to climate change, characterizing and anticipating their effects may support hazard planning.

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Divergent responses of butterflies and bees to burning and grazing management in tallgrass prairies

Butterflies and bees contribute significantly to grassland biodiversity and play important roles as pollinators and herbivores. Grassland conservation and management must be seen through the lens of insect conservation and management if these species are to thrive. In North America, grasslands are a product of climate and natural disturbances such as fire and grazing. These natural disturbances have changed considerably since European colonization and subsequent landscape fragmentation. The aim of this study was to better understand the impacts of fire and grazing management on butterfly and bee communities in tallgrass prairie, enabling land managers and conservationists to better protect and manage remnant prairie. We examined butterfly and bee abundance, species richness, and diversity in Minnesota tallgrass prairies managed by grazing or fire. In 2016 and 2017, we surveyed butterflies, bees, vegetation, and surrounding land use at 20 remnant prairies (10 burned and 10 grazed) with known management histories. Butterfly and bee abundance at our study sites were significantly negatively correlated. Butterfly abundance, but not species richness, was higher in burned than grazed prairies, and prairie-associated grass-feeding butterflies were more abundant at sites with higher plant species richness. Bee abundance was unrelated to management type but was higher at sites with sandier soils; bee species richness was positively associated with forb frequency. These findings highlight the challenges of designing management plans tailored to wide groups of pollinators and the potential pitfalls of using one group of pollinators as indicators for another. They also point to the importance of a mosaic of management practices across the prairie landscape.

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The not-so-dead of winter: Underwater light climate and primary productivity under snow and ice cover in inland lakes

As global surface temperatures continue to rise as a result of anthropogenic climate change, effects in temperate lakes are likely to be more pronounced than in other ecosystems. Decreases in snow and ice cover extent and duration, as well as extended periods of summer stratification have been observed in temperate lake systems throughout the Anthropocene. However, the effects of changing snow and ice cover upon lacustrine communities remain largely uninvestigated. Here, we examined underwater light climate and associated primary productivity patterns under snow-covered and clear lake ice in 6 inland lakes in Minnesota, USA, spanning gradients of water column optical properties (blue, green, brown) associated with trophic status and organic material content. In all lakes, snow cover influenced not only the intensity, but also the spectral signature of light penetrating into the water column. Specifically, the wavelength of maximum penetration was shifted towards longer wavelengths under snow cover in green (eutrophic) lakes, while it was shifted towards shorter wavelengths in blue and brown lakes. Volumetric primary productivity was often higher than anticipated (e.g. ∼1200 mg · m -3 · d -1 ; L. Minnetonka, snow-covered ice). Carbon assimilation rates were lower under snow-covered ice throughout the water column in all lake types, except immediately under cleared ice in eutrophic lakes, where it is likely that phytoplankton were photo-inhibited due to penetration of intense, short-wavelength light. These findings suggest that changing patterns of snow and ice cover under ongoing climate change scenarios can affect patterns of phytoplankton primary productivity in sensitive aquatic ecosystems.

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Water-surface profile maps for the Mississippi River near Prairie Island, Minnesota, 2019

Digital water-surface profile maps for a 14-mile reach of the Mississippi River near Prairie Island, Minnesota, from the confluence of the St. Croix River at Prescott, Wisconsin, to upstream from the U.S. Army Corps of Engineers Lock and Dam No. 3 (U.S. Army Corps of Engineers National Inventory of Dams number MN00595) in Welch, Minnesota, were created by the U.S. Geological Survey (USGS) in cooperation with the Prairie Island Indian Community in the State of Minnesota. The water-surface profile maps depict estimates of the areal extent and depth of water inundation corresponding to selected water levels (stages) at the USGS streamgage Mississippi River at Prescott, Wisconsin (USGS station number 05344500). Current conditions for estimating near-real-time areas of inundation by use of USGS streamgage information may be obtained from the National Water Information System on the internet at https://doi.org/10.5066/F7P55KJN . In this study, water-surface profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the most current stage-discharge relations at the USGS streamgage Mississippi River at Prescott, Wisconsin (USGS station number 05344500). The hydraulic model was then used to determine four water-surface profiles for stream stages at 37.00, 39.00, 40.00, and 41.00 feet (ft) referenced to the streamgage datum and ranging from bankfull to approximately 2 ft below the highest recorded stage at the streamgage, which is 43.11 ft. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.35-ft vertical and 1.97-ft root mean square error horizontal resolution) in order to delineate the area inundated at each stage. The combination of maps provided in this report and real-time stage data from the upstream USGS streamgage provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post flood recovery efforts.

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Restoration of Gavia immer (common loon) in Minnesota—2021 annual report

The Deepwater Horizon oil spill caused extensive injury to natural resources in the Gulf of Mexico, and Gavia immer (common loon) were negatively affected from the spill. The Open Ocean Trustee Implementation Group funded the project Restoration of Common Loons in Minnesota to restore common loons lost to the spill. In 2020–21, priority lakes in an eight-county region in north-central Minnesota were identified to focus project activities. In 2021, surveys on these lakes were started to monitor common loon territory occupancy, nest success, and chick survival. We surveyed 62 lakes and identified 110 common loon territories that will be included in the project. At least 1 nest attempt was observed in 78 of 110 territories, and a second nest attempt was observed in 23 territories. A third nest attempt was observed in one territory. Successful nesting was observed in 32 of 110 territories. We present no formal data analysis and plan to analyze the data after the collection of all field data in subsequent years.

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Comparison of the results of enzyme-linked immunosorbent assay (ELISA) to mass-spectrometry based analytical methods for six unregulated contaminants in source water and finished drinking-water samples

Regulatory entities, such as the Minnesota Department of Health, monitor public water systems for conformance with Federal and State monitoring requirements and water-quality standards. Although some contaminants have Federal and (or) State regulations and guidance values, many contaminants, such as pesticides and pharmaceuticals, are unregulated in that only non-enforceable health-based guidance values have been assigned to them. Furthermore, because these contaminants are not regulated, commonly only limited resources are available to public water systems or regulatory entities to monitor them in drinking water. Focused screening efforts on contaminants that are frequently detected in the environment can provide information to help monitoring entities prioritize their sampling efforts. Here we assess the use of enzyme-linked immunosorbent assay (ELISA) method, a rapid, inexpensive screening method, as an alternative to more expensive methods to analyze source and finished drinking-water samples collected from public water systems throughout Minnesota for three commonly detected pesticides (atrazine, imidacloprid, and pyrethroids) and three commonly detected pharmaceuticals (caffeine, carbamazepine, and sulfamethoxazole). The ELISA results were compared to results provided by more advanced mass-spectrometry analytical methods at the U.S. Geological Survey National Water Quality Laboratory (NWQL) and SGS AXYS Analytical Services Ltd. (AXYS). Overall, these datasets are highly censored (>80 percent) and contain multiple reporting limits within and between laboratories. To discern agreement between paired contaminant group results (target contaminant plus immunologically similar contaminants) by ELISA and the advanced analytical methods at NWQL and AXYS, presence-absence agreement analysis was coupled with false negative and false positive analysis. Analysis of presence-absence agreement shows that ELISA has generally good agreement (77.9 to 100 percent) with both NWQL and AXYS for all unregulated contaminant groups. Imidicloprid, pyrethroids, and caffeine contaminant groups have relatively low false positivity rates (16, 6, and 5 percent, respectively) when analyzed by ELISA, which indicates the ELISA method, for these contaminant groups, could be experiencing low-level interference attributed to the detection of immunologically similar contaminants. Similarly, sulfamethoxazole has a low false positivity rate (0.8 percent), which indicates ELISA is likely not overestimating results for this contaminant group. Analyses for carbamazepine and sulfamethoxazole by ELISA resulted in low false negativity rates (1.6 and 0.8 percent, respectively), which indicates the ELISA method is likely not underestimating the results for this contaminant group. Conversely, the atrazine contaminant group has a high false negativity rate (84 percent), which indicates the method has a strong negative bias and that ELISA underestimates results for this contaminant. These qualitative results indicate that the ELISA method could potentially serve as a reliable and cost-effective screening method to help drinking water monitoring entities prioritize sampling efforts for analyzing carbamazepine and sulfamethoxazole in source and finished drinking-water samples collected from public water systems. At the same time, although ELISA did not prove to be a good screening method for atrazine, evaluation of ELISA results indicated that its use for screening imidacloprid, pyrethroids, and caffeine could be beneficial for water testing.

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Using machine learning to improve predictions and provide insight into fluvial sediment transport

A thorough understanding of fluvial sediment transport is critical to addressing many environmental concerns such as exacerbated flooding, degradation of aquatic habitat, excess nutrients, and the economic challenges of restoring aquatic systems. Fluvial sediment samples are integral for addressing these environmental concerns but cannot be collected at every river and time of interest. Therefore, to gain a better understanding for rivers where direct measurements have not been made, extreme gradient boosting machine learning (ML) models were developed and trained to predict suspended sediment and bedload from sampling data collected in Minnesota, United States (U.S.), by the U.S. Geological Survey. Approximately 400 watershed (full upstream area), catchment (nearby landscape), near-channel, channel, and streamflow features were retrieved or developed from multiple sources, reduced to approximately 30 uncorrelated features, and used in the final ML models. The results indicate suspended sediment and bedload ML models explain approximately 70% of the variance in the datasets. Important features used in the models were interpreted with Shapley additive explanation (SHAP) plots, which provided insight into sediment transport processes. The most important features in the models were developed to normalize streamflow by the 2-year recurrence interval and quantify the rate of change in streamflow (slope), which helped account for sediment hysteresis. Generally, this study also showed a combination of mostly watershed and catchment geospatial features were important in ML models that predict sediment transport from physical samples. This study is a promising step forward in making fluvial sediment transport predictions using machine learning models trained by physically collected samples. The approach developed here can be used wherever similar datasets exists and will be useful for landscape and water management.

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Understanding the evolution of groundwater-contaminant plume chemistry emanating from legacy contaminant sources: An example from a long-term crude oil spill

Understanding the evolution of plumes emanating from residual hydrocarbon contaminant sources requires evaluating how changes in source compositions over time cause changes in dissolved plume chemistry as residual sources age. This study investigates such changes at the site of a 1979 crude-oil pipeline spill and is the first comprehensive look at groundwater chemistry associated with a residual hydrocarbon source zones in different stages of aging. The data show a direct relationship between concentrations of benzene and naphthalene in the residual oil and those measured in water samples collected below the oil. Groundwater associated with oil near the spill site had different chemical composition compared with water associated with oil that had spread downgradient from the spill zone, indicating a shift in biodegradation reactions. These results emphasize that source zone processes are spatially and temporally heterogeneous and should be accounted for in natural attenuation studies where residual source zones persist.

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Characterization of the partial oxidation products of crude oil contaminating groundwater at the U.S. Geological Survey Bemidji research site in Minnesota by elemental analysis, radiocarbon dating, nuclear magnetic resonance spectroscopy, and Fourier transform ion cyclotron resonance mass spectrometry

In oil spill research, a topic of increasing attention during the last decade has been the environmental impact of the partial oxidation products that result from transformation of the petroleum in freshwater, marine, and terrestrial ecosystems. This report describes the isolation and characterization of the partial oxidation products from crude oil contaminating groundwater at the long-term U.S. Geological Survey Bemidji research site in Minnesota. As the result of a pipeline burst in August 1979, a body of light aliphatic crude oil is present from the land surface to 2 meters below the water table in a shallow sand and gravel aquifer in a remote area outside Bemidji, Minnesota, United States. Biodegradation has resulted in the formation of a plume of dissolved organic carbon (DOC) downgradient from the oil body. Groundwater has also been contaminated in an area known as the spray zone, from vertical infiltration of DOC resulting from biodegradation of oil in the soil column, and possibly from photooxidation of oil at the soil surface. The majority of DOC in the contaminated groundwater is in the form of nonvolatile organic acids (NVOAs) which represent the partial oxidation products of the crude oil constituents. The NVOAs have been classified into three fractions according to their isolation on XAD resins: hydrophobic neutrals (HPON), hydrophobic acids (HPOA), and hydrophilic acids (HPIA). These fractions of NVOAs were isolated from wells downgradient from the oil body (sampling well numbers 533, 532, 530, 515), in the spray zone (603), and from an uncontaminated well upgradient of the oil body (310) between the years 1986 and 1989, and again from wells 530 and 603 in 1998. The samples have been characterized by elemental analysis, radiocarbon dating, carbon-13 nuclear magnetic resonance spectroscopy ( 13 C NMR), and negative-mode (-) electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FTICR-MS), with a particular focus on fractions from wells 310, 530, and 603. All the characterization data indicate that the NVOAs from contaminated wells are distinguishable from the background DOC. Carbon-14 ( 14 C) ages of NVOAs from contaminated wells ranged from 3,615 to 18,985 years before the present, whereas the background DOC from the aquifer was post-bomb (post 1950). By elemental analysis, NVOAs from contaminated wells had higher sulfur but lower nitrogen contents than the background. By electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry, number average molecular weights determined from assigned molecular formulas ranged from 416 to 486 daltons for the HPOA and HPIA fractions from both background and contaminant wells. NVOAs from contaminated wells had significantly greater numbers of assigned molecular formulas containing sulfur, with elevated concentrations of the S 1 O 4-10 species in particular. Compared to the background, HPOA and HPIA fractions from contaminant wells had a broader range of double bond equivalents (DBEs) within O n compound classes (n is number of atoms). Additionally, within O n compound classes, contaminant well HPOA fractions had a greater abundance of lower n (less than eight) than the background. Contaminant well double bond equivalents versus carbon number (C # ) plots of oxygen compound classes suggest oil-derived aliphatic compounds in the range from C 12 to C 22 in HPOA and HPIA fractions and oil-derived compounds containing aromatic or saturated rings in the approximate range from C 20 to C 30 are present in HPOA fractions. The data suggest the NVOAs originate from biodegradation of several classes of C 12 and greater crude oil constituents: sulfur-containing constituents, including possibly the resins and asphaltenes; constituents containing aromatic rings substituted with methyl groups, including alkylaromatic and naph- thenoaromatic compounds, and C 12 to C 22 alkyl constituents. The overall similarities of the carbon-13 nuclear magnetic resonance spectra for the well 603 and 530 samples from the two sampling dates suggest that a steady state in the composition of the partial oxidation products in each of the two wells had been reached between 1986–1989 and 1998.

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On the multiple identities of stakeholders in wolf management in Minnesota, United States

Social identity theory offers a means to understand attitudes about wolves, with consequences for management support. Using data from a mail survey about wolves, we explored relationships among seven identities (i.e., wolf advocate, hunter, environmentalist, nature enthusiast, farmer, trapper, conservationist) using multidimensional scaling (MDS) and principal components analysis (PCA). We examined how identities correlated with political ideology, trust in a wildlife management agency, wildlife value orientations (WVOs) and attitudes about wolves, and we evaluated whether WVOs mediated the relationship between identities and attitudes. PCA suggested two factors in identifying relationships among stakeholders, while MDS and correlations found diversity among stakeholders beyond these factors. Hunter identity was most strongly associated with a domination WVO and conservative political ideology. Farmer identity was most strongly associated with agency distrust and negative wolf attitudes. Wolf advocate was most strongly associated with a mutualism WVO (i.e., beliefs that humans are meant to coexist in harmonious relationships with wildlife), agency trust, and positive wolf attitudes. Conservationist identity was positively correlated with all other identities. WVOs partially mediated the relationship between identities and attitudes.

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Quantifying relations between altered hydrology and fish community responses for streams in Minnesota

Altered hydrology is a stressor on aquatic life for several streams in Minnesota, but quantitative relations between specific aspects of streamflow alteration and biological responses have not been developed on a statewide scale in Minnesota. Best subsets regression analysis was used to develop linear regression models that quantify relations among five categories of hydrologic explanatory metrics (i.e., duration, frequency, magnitude, rate-of-change, and timing) computed from streamgage records and six categories of biological response metrics (i.e., composition, habitat, life history, reproductive, tolerance, trophic) computed from fish community samples, as well as fish-based indices of biotic integrity (FIBI) scores and FIBI scores normalized to the an impairment threshold of the corresponding stream class (FIBI_BCG4). Three hydrologic datasets were used to examine rRelations between altered hydrology and fish community responses were examined at three different temporal scalesusing three hydrologic datasets that represented periods of record, long-term changes, and short-term changes to flow regimes in streams of Minnesota.

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Experience preferences and place attachment of Minnesota wildlife management area hunters

Hunters in the United States are motivated to obtain and benefit from diverse experiences or experience preferences. Using a mail survey conducted during the 2015–2016 hunting season, we examined goal-oriented, introspective, and leadership experiences among hunters on Minnesota Department of Natural Resources’ Wildlife Management Area (WMAs). We used k-means cluster analysis to identify six clusters based on experience preferences. We defined these clusters using their ranked experience preferences and segregated them into categories of either participants or enthusiasts. These clusters showed differences in demographic characteristics, as well as support for management actions on WMAs. Hunters in clusters with lower importance ratings of experience preferences also reported less attachment to WMAs. High levels of support for management actions were closely related to high levels of place attachment. Using information gained from describing the heterogeneity of desired experiences, managers may be better able to understand their constituents and prioritize management goals to provide a variety of hunting experiences.

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Statewide quantitative microbial risk assessment for waterborne viruses, bacteria, and protozoa in public water supply wells in Minnesota

Infection risk from waterborne pathogens can be estimated via quantitative microbial risk assessment (QMRA) and forms an important consideration in the management of public groundwater systems. However, few groundwater QMRAs use site-specific hazard identification and exposure assessment, so prevailing risks in these systems remain poorly defined. We estimated the infection risk for 9 waterborne pathogens based on a 2-year pathogen occurrence study in which 964 water samples were collected from 145 public wells throughout Minnesota, USA. Annual risk across all nine pathogens combined was 3.3 × 10 –1 (95% CI: 2.3 × 10 –1 to 4.2 × 10 –1 ), 3.9 × 10 –2 (2.3 × 10 –2 to 5.4 × 10 –2 ), and 1.2 × 10 –1 (2.6 × 10 –2 to 2.7 × 10 –1 ) infections person –1 year –1 for noncommunity, nondisinfecting community, and disinfecting community wells, respectively. Risk estimates exceeded the U.S. benchmark of 10 –4 infections person –1 year –1 in 59% of well-years, indicating that the risk was widespread. While the annual risk for all pathogens combined was relatively high, the average daily doses for individual pathogens were low, indicating that significant risk results from sporadic pathogen exposure. Cryptosporidium dominated annual risk, so improved identification of wells susceptible to Cryptosporidium contamination may be important for risk mitigation.

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