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At least 991 records · Page 55Linked to original sources

USGS2017

A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing

Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying cyanoHABs in multiple water bodies and across geo-political boundaries. An assessment method was developed using MEdium Resolution Imaging Spectrometer (MERIS) imagery to quantify cyanoHAB surface area extent, transferable to different spatial areas, in Florida, Ohio, and California for the test period of 2008 to 2012. Temporal assessment was used to evaluate changes in satellite resolvable inland waterbodies for each state of interest. To further assess cyanoHAB risk within the states, the World Health Organization’s (WHO) recreational guidance level thresholds were used to categorize surface area of cyanoHABs into three risk categories: low, moderate, and high-risk bloom area. Results showed that in Florida, the area of cyanoHABs increased largely due to observed increases in high-risk bloom area. California exhibited a slight decrease in cyanoHAB extent, primarily attributed to decreases in Northern California. In Ohio (excluding Lake Erie), little change in cyanoHAB surface area was observed. This study uses satellite remote sensing to quantify changes in inland cyanoHAB surface area across numerous water bodies within an entire state. The temporal assessment method developed here will be relevant into the future as it is transferable to the Ocean Land Colour Instrument (OLCI) on Sentinel-3A/3B missions.

California, Florida, Ohio↗

USGS2022

A validation of satellite derived cyanobacteria detections with state reported events and recreation advisories across U.S. lakes

Cyanobacteria harmful algal blooms (cyanoHABs) negatively affect ecological, human, and animal health. Traditional methods of validating satellite algorithms with data from water samples are often inhibited by the expense of quantifying cyanobacteria indicators in the field and the lack of public data. However, state recreation advisories and other recorded events of cyanoHAB occurrence reported by local authorities can serve as an independent and publicly available dataset for validation. State recreation advisories were defined as a period delimited by a start and end date where a warning was issued due to detections of cyanoHABs over a state's risk threshold. State reported events were defined as any event that was documented with a single date related to cyanoHABs. This study examined the presence-absence agreement between 160 state reported cyanoHAB advisories and 1,343 events and cyanobacteria biomass estimated by a satellite algorithm called the Cyanobacteria Index (CI cyano ). The true positive rate of agreement with state recreation advisories was 69% and 60% with state reported events. CI cyano detected a reduction or absence in cyanobacteria after 76% of the recreation advisories ended. CI cyano was used to quantify the magnitude, spatial extent, and temporal frequency of cyanoHABs; each of these three metrics were greater ( r > 0.2) during state recreation advisories compared to non-advisory times with effect sizes ranging from small to large. This is the first study to quantitatively evaluate satellite algorithm performance for detecting cyanoHABs with state reported events and advisories and supports informed management decisions with satellite technologies that complement traditional field observations.

Harmful Algae↗

USGS2020

Thicknesses of lava flows in satellite images: Comparison of layered mare units with terrestrial analogs

Recent advances in satellite imaging technology have greatly improved our observations of planetary surfaces. The Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) records images with resolutions on average of 0.5 m per pixel, resolving meter scale features on the surface of the Moon. NAC images have revealed layered deposits, interpreted to be sequences of mare basalt flows, in the walls of impact craters on the lunar nearside. However, caution must be exercised in the interpretation of surface processes from morphologies of features that are close to the limits of detectability. Our goal is to quantify where that limit is for lava flow stratigraphy. Here we report on a terrestrial analog study conduced to better constrain limitations in the measurements of thicknesses of lava flows observed in high-resolution satellite-collected images. Using WorldView-2 satellite images, we mapped layered basalt flows at three sites in the Wai'anae and Ko'olau Ranges of O'ahu, Hawai'i. Fieldwork conducted at these sites allowed for assessment of the accuracy of image interpretations. We found that flow thickness estimates made using WorldView-2 images overestimated thicknesses of individual lava flows measured in the field at all eight locations visited by a factor of 1.2 to 3.5. A primary reason for this overestimation by remote sensing analysis is that many outcropping “layers” within a transect contain more than one individual flow, a distinction that is not visible in satellite images. However, the mean thickness of the layers seen in the orbital data was 0.8 to 1.7 times the outcrop thickness measured in the field, suggesting that the remote measurements should be considered estimates of the outcrop thickness rather than the thickness of individual lava flows. Measurements of layered lunar mare lava units in LRO NAC images provided layer thicknesses that ranged from <1–6 times greater than those derived from images of the O'ahu study sites. It is reasonable to expect that many lunar outcrops similarly contain more than one individual flow and display similar outcropping patterns. This suggests that many current estimates of layer thicknesses derived by comparable methods actually correspond to outcrop thicknesses. Current interpretations of lava flow thicknesses derived from planetary images should be considered maximums for individual flow thicknesses with uncertainties that may be as high as a factor of 3 or more.

Hawaii↗

USGS2022

Typology development of earthquake displays in free-choice learning environments, to inform earthquake early warning education in the United States

Free-choice learning environments, such as museums, national parks, interpretive trails, and visitor centers, are trusted sources of information in their communities and support lifelong learning. Earthquake education in these spaces creates awareness of earthquake hazards and risk in areas where people live or visit and, in turn, may increase engagement in preparedness behavior. The ShakeAlert® Earthquake Early Warning System helps publics prepare by warning in advance of shaking from significant earthquakes along the West Coast of the United States. ShakeAlert can minimize earthquake damage by prompting automated actions (e.g., slowing trains, shutting off water valves) and prompting personal protective actions like “Drop, Cover, and Hold On” to significantly reduce damage, injury, and loss of life. Individuals and communities must have a basic understanding of earthquake hazards, as well as an awareness of ShakeAlert technology, to know how to respond if they feel shaking or receive an alert. Currently, there is a lack of contemporary scholarship on how free-choice learning environments approach earthquake education through exhibits and displays. We analyzed a sample of existing earthquake exhibits and their themes in the United States and explored how different display types are uniquely engaging. We found that most displays did not include information about how to prepare for an earthquake or associated protective actions. From this and the development of the typology, our research posits a foundational framework for how best to incorporate place-based learning on earthquakes and early warning into centers of free-choice learning which may apply to a range of other natural hazards and will enhance public awareness and safety.

International Journal of Disaster Risk Reduction↗

USGS2022

Great expectations for earthquake early warnings on the United States West Coast

In October 2019, California became the first state in the United States to fully activate a public earthquake early warning system—ShakeAlert®—managed by the U.S. Geological Survey. The system was subsequently rolled out in March 2021 in Oregon and May 2021 in Washington. Earthquake early warning (EEW) systems can provide seconds of notice to people and technological systems that shaking is imminent, but their effectiveness depends on recipients’ expectations and actions as well as technical performance. To better understand these dependencies, we surveyed representative samples of adults in California (N = 1219), Oregon (N = 1020), and Washington (N = 1037) in February 2021. Most respondents had experienced earthquakes, but few had lived through violent shaking; most had not followed protective action guidance to Drop, Cover, and Hold On (DCHO) in earthquakes; and most reported no personal or social harm from prior earthquakes. Nevertheless, expectations and perceived usefulness of EEW were high, and higher still for those who expected alerts to be accurate and easy to use, expressed tolerance of missed and erroneous warnings, and expected to be affected by a damaging earthquake in their lifetime. Results suggest opportunities to better align public preferences and expectations with ShakeAlert operations. For example, some respondents preferred lower alerting thresholds than those proposed by government and scientists. Moreover, reported tolerance of warning errors was widespread, but respondents wanted explanations quickly, suggesting a need to further develop post-alert messaging. Findings from this study should be informative for future research on the co-evolution of experiences and expectations with EEW systems.

California, Oregon, Washington↗

USGS2022

Multi-hazard risk analysis for the U.S. Department of the Interior: An integration of expert elicitation, planning priorities, and geospatial analysis

An integral part of disaster risk management is identifying and prioritizing hazards and their potential impacts in a meaningful way to support risk-reduction planning. There has been considerable use and subsequent criticism of threat prioritization efforts that simply compare likelihoods and consequences of plausible threats. This article summarizes a new mixed-methods and scalable approach for prioritizing risks in a multi-hazard, multi-objective, and multi-criteria organizational context. This approach integrates (1) hazard characterizations using subject-matter-expert (SME) elicitation, (2) expressed preferences in planning priorities provided by emergency managers, and (3) quantitative estimates of asset exposure to hazards using geospatial data and geographic-information-systems (GIS) software. We demonstrate this approach with a case study designed to support multi-hazard mitigation and response planning done by the U.S. Department of the Interior (DOI) Office of Emergency Management, which required a national understanding of the risks posed by 75 natural, technological, and adversarial hazards to DOI managed and administered lands, facilities, people, revenues, and resources. Results demonstrate that hazard priorities vary depending on the asset, scale, and risk-management context, thereby making the case that “one-size-fits-all” hazard rankings have limited utility or relevance to real-world, risk mitigation and response planning. Our results suggest that recognizing the risk-management context provides greater transparency, flexibility, and relevance in comparing threats than traditional likelihood-threat matrices or the use of hazard SMEs to decide for planners which hazard scenarios are emphasized in risk planning.

International Journal of Disaster Risk Reduction↗

USGS2023

Social vulnerability and geographic access barriers to earthquake early warning education in museums and other free choice learning environments

Given the earthquake risk on the West Coast of the United States, individuals and communities require a basic understanding of ShakeAlert earthquake early warning technology, which may provide crucial seconds of warning. Free choice learning environments (FCLEs), such as museums, public libraries, and national parks, are uniquely positioned to expand the reach of earthquake early warning through educational initiatives and resources. Earthquake education in these spaces creates awareness of earthquake hazards and risk in areas where people live or visit and may also increase engagement in preparedness behavior as they are trusted sources of information in their communities. However, population demographics within the ShakeAlert states has yet to be examined; audience segmentation theories require a better understanding of the demographics of the people the system seeks to serve. Here we build upon previous typology research that examined over 150 earthquake displays around the United States and found that most did not include information about earthquake preparedness or associated protective actions. This new research shifts to a hierarchical clustering analysis that identifies seven main population groups within the ShakeAlert states. We also find that the cost of admission and the geographic distance away from FCLEs, including the potential cost and time of transportation, may lead to an urban-rural divide in visitor access. Using audience segmentation theories as related to earthquakes, we can understand critical barriers to FCLEs and opportunities for ShakeAlert education. As earthquake early warning systems expand internationally, thoughtful and equitable education initiatives are beneficial to reach critical audiences.

International Journal of Disaster Risk Reduction↗

USGS2012

Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO2 injection experiment

A field experiment involving the release of carbon dioxide (CO 2 ) into a shallow aquifer was conducted near Bozeman, Montana, during the summer of 2008, to investigate the potential groundwater quality impacts in the case of leakage of CO 2 from deep geological storage. As an essential part of the Montana State University Zero Emission Research and Technology (MSU-ZERT) field program, food-grade CO 2 was injected over a 30 day period into a horizontal perforated pipe a few feet below the water table of a shallow aquifer. The impact of elevated CO 2 concentrations on groundwater quality was investigated by analyzing water samples taken before, during, and following CO 2 injection, from observation wells located in the vicinity of the injection pipe, and from two distant monitoring wells. Field measurements and laboratory analyses showed rapid and systematic changes in pH, alkalinity, and conductance, as well as increases in the aqueous concentrations of naturally occurring major and trace element species. The geochemical data were evaluated using principal component analysis (PCA) to (1) understand potential correlations between aqueous species, and (2) to identify minerals controlling the chemical composition of the groundwater prior to CO 2 injection. These evaluations were used to assess possible geochemical processes responsible for the observed increases in the concentrations of dissolved constituents, and to simulate these processes using a multicomponent reaction path model. Reasonable agreement between observed and modeled data suggests that (1) calcite dissolution was the primary pH buffer, yielding increased Ca +2 concentrations in the groundwater, (2) increases in the concentrations of most major and trace metal cations except Fe could be a result of Ca +2 -driven exchange reactions, (3) the release of anions from adsorption sites due to competitive adsorption of carbonate could explain the observed trends of most anions, and (4) the dissolution of reactive Fe minerals (presumed ferrihydrite and fougerite, from thermodynamic analyses) could explain increases in total Fe concentration. Highlights ► Because the possibility of CO 2 leakage cannot be completely ruled out, the potential impact of CO 2 intrusion on the quality of fresh water aquifers overlying CO 2 storage sites needs to be investigated. ► Geochemical data from a field experiment involving the release of carbon dioxide (CO 2 ) into a shallow aquifer were evaluated. ► Geochemical model used to assess possible geochemical processes responsible for the observed increases in the concentrations of dissolved constituents. ► Reasonable agreement between observed and modeled data suggests that increases in the concentrations of most major and trace metal cations except Fe could be a result of Ca +2 -driven exchange reactions and the release of anions from adsorption sites due to competitive adsorption of carbonate could explain the observed trends of most anions.

Montana↗

USGS2018

Museum metabarcoding: a novel method revealing gut helminth communities of small mammals across space and time

Natural history collections spanning multiple decades provide fundamental historical baselines to measure and understand changing biodiversity. New technologies such as next generation DNA sequencing (NGS) have considerably increased the potential of museum specimens to address significant questions regarding the impact of environmental changes on host and parasite/pathogen dynamics. We developed a new technique to identify intestinal helminth parasites and applied it to shrews (Eulipotyphla: Soricidae) because they are ubiquitous, occupy diverse habitats, and host a diverse and abundant parasite fauna. Notably, we included museum specimens preserved in various ways to explore the efficacy of using metabarcoding analyses that may enable identification of helminth symbiont communities from historical archives. We successfully sequenced the parasite communities (using 12S mtDNA, 16S mtDNA, 28S rDNA) of 23 whole gastrointestinal (GI) tracts. All GI tracts were obtained from the Museum of Southwestern Biology (MSB), USA, and from recent field collections, varying both in time since fixation (ranging from 4 months to 16 years) and preservation method (70% or 95% ethanol stored at room temperature, or flash frozen in liquid nitrogen and stored at -80°C). Our proof of concept demonstrates the feasibility of applying NGS techniques to authoritatively identify the parasite/pathogen communities within whole GI tracts from museum specimens of varying age and fixation, and the value of future preservation of host-associated whole GI tracts in public research archives. This powerful approach facilitates future comparative examinations of the distributions and interactions among multiple associated groups of organisms through time and space.

International Journal for Parasitology↗

USGS2013

Next generation of global land cover characterization, mapping, and monitoring

Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).

International Journal of Applied Earth Observation↗

USGS2018

Landsat time series analysis of fractional plant cover changes on abandoned energy development sites

Oil and natural gas development in the western United States has increased substantially in recent decades as technological advances like horizontal drilling and hydraulic fracturing have made extraction more commercially viable. Oil and gas pads are often developed for production, and then capped, reclaimed, and left to recover when no longer productive. Understanding the rates, controls, and degree of recovery of these reclaimed well sites to a state similar to pre-development conditions is critical for energy development and land management decision processes. Here we use a multi-decadal time series of satellite imagery (Landsat 5, 1984–2011) to assess vegetation regrowth on 365 abandoned well pads located across the Colorado Plateau in Utah, Colorado, and New Mexico. We developed high-frequency time series of the Soil-Adjusted Total Vegetation Index (SATVI) for each well pad using the Google Earth Engine cloud computing platform. BFAST time-series models were used to fit temporal trends, identifying when vegetation was cleared from the site and the magnitudes and rates of vegetation change after abandonment. The time series metrics are used to calculate the relative fractional vegetation cover (RFVC) of each pad, a measure of post-abandonment vegetation cover relative to pre-drilling condition. Mean and median RFVC were 36% (s.d. 33%) and 26%, respectively, five years after abandonment, with one third of well pads having RFVC greater than 50%. Statistical analyses suggest that much of the high vegetation cover is associated with weedy invasive annual species such as cheatgrass (Bromus tectorum) and Russian thistle (Salsola spp.). Climate conditions and the year of abandonment also play a role, with increased cover in later years associated with a wetter period. Non-linear change at many pads suggests longer recovery times than would be estimated by linear extrapolation. New techniques implemented here address a complex response of cover change to soils, management, and climate over time, and can be extended to the operational monitoring of energy development across large areas.

International Journal of Applied Earth Observation↗

USGS2017

Monitoring water content dynamics of biological soil crusts

Biological soil crusts (hereafter, “biocrusts”) dominate soil surfaces in nearly all dryland environments. To better understand the influence of water content on carbon (C) exchange, we assessed the ability of dual-probe heat-pulse (DPHP) sensors, installed vertically and angled, to measure changes in near-surface water content. Four DPHP sensors were installed in each of two research plots (eight sensors total) that differed by temperature treatment (control and heated). Responses were compared to horizontally installed water content measurements made with three frequency-domain reflectometry (FDR) sensors in each plot at 5-cm depth. The study was conducted near Moab, Utah, from April through September 2009. Results showed significant differences between sensor technologies: peak water content differences from the DPHP sensors were approximately three times higher than those from the FDR sensors; some of the differences can be explained by the targeted monitoring of biocrust material in the shorter DPHP sensor and by potential signal loss from horizontally installed FDR sensors, or by an oversampling of deeper soil. C-exchange estimates using the DPHP sensors showed a net C loss of 69 and 76 g C m −2 in control and heated plots, respectively. The study illustrates the potential for using the more sensitive data from shallow installations for estimating C exchange in biocrusts.

Journal of Arid Environments↗

USGS2017

Porosity and pore size distribution in a sedimentary rock: Implications for the distribution of chlorinated solvents

Characterizing properties of the rock matrix that control retention and release of chlorinated solvents is essential in evaluating the extent of contamination and the application of remediation technologies in fractured rock. Core samples from seven closely spaced boreholes in a mudstone subject to trichloroethene (TCE) contamination were analyzed using Mercury Intrusion Porosimetry to investigate porosity and pore size distribution as a function of mudstone characteristics, and depth and lateral extent in the aquifer; organic carbon content was also evaluated to identify the potential for adsorption. Porosity and retardation factor varied over two orders of magnitude, with the largest porosities and largest retardation factors associated with carbon-rich mudstone layers. Larger porosities were also measured in the shallow rock that has been subject to enhanced groundwater flow. Porosity also varied over more than an order of magnitude in spatially continuous mudstone layers. The analyses of the rock cores indicated that the largest pore diameters may be accessible to entry of the nonaqueous form of TCE. Although the porosity associated with the largest pore diameters is small (~ 0.1%), that volume of TCE can significantly affect the total TCE that is retained in the rock matrix. The dimensions of the largest pore diameters may also be accessible to microbes responsible for reductive dechlorination; however, the small percentage of the pore space that can accommodate microbes may limit the extent of reductive dechlorination in the rock matrix.

Journal of Contaminant Hydrology↗

USGS2008

Ocean forecasting in terrain-following coordinates: Formulation and skill assessment of the Regional Ocean Modeling System

Systematic improvements in algorithmic design of regional ocean circulation models have led to significant enhancement in simulation ability across a wide range of space/time scales and marine system types. As an example, we briefly review the Regional Ocean Modeling System, a member of a general class of three-dimensional, free-surface, terrain-following numerical models. Noteworthy characteristics of the ROMS computational kernel include: consistent temporal averaging of the barotropic mode to guarantee both exact conservation and constancy preservation properties for tracers; redefined barotropic pressure-gradient terms to account for local variations in the density field; vertical interpolation performed using conservative parabolic splines; and higher-order, quasi-monotone advection algorithms. Examples of quantitative skill assessment are shown for a tidally driven estuary, an ice-covered high-latitude sea, a wind- and buoyancy-forced continental shelf, and a mid-latitude ocean basin. The combination of moderate-order spatial approximations, enhanced conservation properties, and quasi-monotone advection produces both more robust and accurate, and less diffusive, solutions than those produced in earlier terrain-following ocean models. Together with advanced methods of data assimilation and novel observing system technologies, these capabilities constitute the necessary ingredients for multi-purpose regional ocean prediction systems.

Journal of Computational Physics↗

USGS2015

A comparison between boat-based and diver-based methods for quantifying coral bleaching

Recent increases in both the frequency and severity of coral bleaching events have spurred numerous surveys to quantify the immediate impacts and monitor the subsequent community response. Most of these efforts utilize conventional diver-based methods, which are inherently time-consuming, expensive, and limited in spatial scope unless they deploy large teams of scientifically-trained divers. In this study, we evaluated the effectiveness of the Along-Track Reef Imaging System (ATRIS), an automated image-acquisition technology, for assessing a moderate bleaching event that occurred in the summer of 2011 in the Florida Keys. More than 100,000 images were collected over 2.7 km of transects spanning four patch reefs in a 3-h period. In contrast, divers completed 18, 10-m long transects at nine patch reefs over a 5-day period. Corals were assigned to one of four categories: not bleached, pale, partially bleached, and bleached. The prevalence of bleaching estimated by ATRIS was comparable to the results obtained by divers, but only for corals > 41 cm in size. The coral size-threshold computed for ATRIS in this study was constrained by prevailing environmental conditions (turbidity and sea state) and, consequently, needs to be determined on a study-by-study basis. Both ATRIS and diver-based methods have innate strengths and weaknesses that must be weighed with respect to project goals.

Florida↗

USGS2015

Monitoring and modeling wetland chloride concentrations in relationship to oil and gas development

Extraction of oil and gas via unconventional methods is becoming an important aspect of energy production worldwide. Studying the effects of this development in countries where these technologies are being widely used may provide other countries, where development may be proposed, with some insight in terms of concerns associated with development. A fairly recent expansion of unconventional oil and gas development in North America provides such an opportunity. Rapid increases in energy development in North America have caught the attention of managers and scientists as a potential stressor for wildlife and their habitats. Of particular concern in the Northern Great Plains of the U.S. is the potential for chloride-rich produced water associated with unconventional oil and gas development to alter the water chemistry of wetlands. We describe a landscape scale modeling approach designed to examine the relationship between potential chloride contamination in wetlands and patterns of oil and gas development. We used a spatial Bayesian hierarchical modeling approach to assess multiple models explaining chloride concentrations in wetlands. These models included effects related to oil and gas wells (e.g. age of wells, number of wells) and surficial geology (e.g. glacial till, outwash). We found that the model containing the number of wells and the surficial geology surrounding a wetland best explained variation in chloride concentrations. Our spatial predictions showed regions of localized high chloride concentrations. Given the spatiotemporal variability of regional wetland water chemistry, we do not regard our results as predictions of contamination, but rather as a way to identify locations that may require more intensive sampling or further investigation. We suggest that an approach like the one outlined here could easily be extended to more of an adaptive monitoring approach to answer questions about chloride contamination risk that are of interest to managers.

Montana, North Dakota↗

USGS2016

Prototypic automated continuous recreational water quality monitoring of nine Chicago beaches

Predictive empirical modeling is used in many locations worldwide as a rapid, alternative recreational water quality management tool to eliminate delayed notifications associated with traditional fecal indicator bacteria (FIB) culturing (referred to as the persistence model, PM) and to prevent errors in releasing swimming advisories. The goal of this study was to develop a fully automated water quality management system for multiple beaches using predictive empirical models (EM) and state-of-the-art technology. Many recent EMs rely on samples or data collected manually, which adds to analysis time and increases the burden to the beach manager. In this study, data from water quality buoys and weather stations were transmitted through cellular telemetry to a web hosting service. An executable program simultaneously retrieved and aggregated data for regression equations and calculated EM results each morning at 9:30 AM; results were transferred through RSS feed to a website, mapped to each beach, and received by the lifeguards to be posted at the beach. Models were initially developed for five beaches, but by the third year, 21 beaches were managed using refined and validated modeling systems. The adjusted R 2 of the regressions relating Escherichia coli to hydrometeorological variables for the EMs were greater than those for the PMs, and ranged from 0.220 to 0.390 (2011) and 0.103 to 0.381 (2012). Validation results in 2013 revealed reduced predictive capabilities; however, three of the originally modeled beaches showed improvement in 2013 compared to 2012. The EMs generally showed higher accuracy and specificity than those of the PMs, and sensitivity was low for both approaches. In 2012 EM accuracy was 70–97%; specificity, 71–100%; and sensitivity, 0–64% and in 2013 accuracy was 68–97%; specificity, 73–100%; and sensitivity 0–36%. Factors that may have affected model capabilities include instrument malfunction, non-point source inputs, and sparse calibration data. The modeling system developed is the most extensive, fully-automated system for recreational water quality developed to date. Key insights for refining and improving large-scale empirical models for beach management have been developed through this multi-year effort.

Illinois↗

USGS2024

Reducing wastewater nitrogen loading by >90% with carbon-amended septic systems: A field demonstration in Barnstable (Cape Cod), Massachusetts

Onsite wastewater treatment systems (OWTS) are a major source of excess nutrients and co-pollutants in watersheds across the United States. In Barnstable County (Cape Cod), Massachusetts, effluent from septic systems and cesspools contributes approximately 80% of the controllable reactive nitrogen (N) load to numerous impaired estuaries and degrades water quality in the region's sole source aquifer, streams and ponds. In unsewered areas, wastewater N loads could be reduced substantially by Innovative/Alternative (I/A) septic systems designed for enhanced removal. Use, however, has been partly limited by the availability of high performing, cost effective options, while conventional septic systems continue to be installed in watersheds with well documented N impairments. This paper describes the strategic replacement of residential OWTS with two I/A models that incorporate woodchip bioreactors to enhance N removal. Systems were installed at 14 neighboring homes in Barnstable, MA, and monitored for field performance. Influent and effluent were sampled monthly and analyzed for N and phosphorus (P), among other water quality indicators. Flow to each system was continuously metered to estimate nutrient loads. Results from the first 25 months of monitoring for 13 systems with at least a full year of data are presented in terms of 1) reductions in nutrient concentrations and mass loads and 2) reliability of the systems for meeting a performance goal of total N (TN) < 10 mg/L. Discussion supports consideration of where and how these technologies may be successfully used to manage excess N in sensitive watersheds.

Massachusetts↗