Rocky reefs provide important spawning and refuge habitats for lithophilic spawning fishes. However, many reefs have been lost or severely degraded through anthropogenic effects like dredging, channelization, or sedimentation. Constructed reefs have been used to mitigate these effects in some systems, but these reefs are also subject to degradation which may warrant custodial maintenance. Monitoring and maintenance of natural or constructed spawning reefs are not common practices; therefore, few methodologies have been created to test the effectiveness of such tools. We conducted a literature review to assess available information on maintenance of rocky spawning habitats used by lithophilic fishes. We identified 54 rocky spawning habitat maintenance projects, most of which aimed to improve fish spawning habitats through the addition of spawning substrate (n = 33) or cleaning of substrate (n = 23). In comparison to shallow riverine studies focused on salmonids, we found little information on deep-water reefs, marine reefs, or other fish species. We discuss the possible application of potential spawning habitat cleaning methods from other disciplines (e.g., treasure hunting; archeology) that may provide effective means of reef maintenance that can be used by restoration practitioners.
","language":"English","publisher":"MDPI","doi":"10.3390/w12092501","usgsCitation":"Baetz, A., Tucker, T., DeBruyne, R., Gatch, A., Hook, T., Fischer, J., and Roseman, E., 2020, Review of methods to repair and maintain lithophilic fish spawning habitat: Water, v. 12, 2501, 37 p., https://doi.org/10.3390/w12092501.","productDescription":"2501, 37 p.","ipdsId":"IP-121247","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":455380,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12092501","text":"Publisher Index Page"},{"id":378359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","noUsgsAuthors":false,"publicationDate":"2020-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Baetz, Audrey 0000-0003-4474-5656","orcid":"https://orcid.org/0000-0003-4474-5656","contributorId":240597,"corporation":false,"usgs":false,"family":"Baetz","given":"Audrey","email":"","affiliations":[{"id":48110,"text":"Nichols State University","active":true,"usgs":false}],"preferred":false,"id":798526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Taaja 0000-0003-1534-4677","orcid":"https://orcid.org/0000-0003-1534-4677","contributorId":217908,"corporation":false,"usgs":true,"family":"Tucker","given":"Taaja","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":798527,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeBruyne, Robin 0000-0002-9232-7937","orcid":"https://orcid.org/0000-0002-9232-7937","contributorId":240598,"corporation":false,"usgs":false,"family":"DeBruyne","given":"Robin","affiliations":[{"id":48111,"text":"Univ. Toledo","active":true,"usgs":false}],"preferred":false,"id":798528,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gatch, Alex","contributorId":222574,"corporation":false,"usgs":false,"family":"Gatch","given":"Alex","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":798529,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hook, T.","contributorId":222576,"corporation":false,"usgs":false,"family":"Hook","given":"T.","email":"","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":798530,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fischer, J. 0000-0001-7226-6500","orcid":"https://orcid.org/0000-0001-7226-6500","contributorId":240599,"corporation":false,"usgs":false,"family":"Fischer","given":"J.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":798531,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":798532,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70213252,"text":"70213252 - 2020 - Effects of water level alteration on carbon cycling in peatlands","interactions":[],"lastModifiedDate":"2020-09-16T13:51:41.744782","indexId":"70213252","displayToPublicDate":"2020-09-08T08:49:51","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5075,"text":"Ecosystem Health and Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Effects of water level alteration on carbon cycling in peatlands","docAbstract":"Globally, peatlands play an important role in the carbon (C) cycle. High water level is a key factor in maintaining C storage in peatlands, but water levels are vulnerable to climate change and anthropogenic disturbance. This review examines literature related to the effects of water level alteration on C cycling in peatlands to summarize new ideas and uncertainties emerging in this field. Peatland ecosystems maintain their function by altering plant community structure to adapt to changing water levels. Regarding primary production, woody plants are more productive in unflooded, well-aerated conditions, while Sphagnum mosses are more productive in wetter conditions. The responses of sedges to water level alteration are species-specific. While peat decomposition is faster in unflooded, well aerated conditions, increased plant production may counteract the C loss induced by increased ecosystem respiration (ER) for a period of time. In contrast, rising water table maintains anaerobic conditions and enhances the role of the peatland as a C sink. Nevertheless, changes in DOC flux during water level fluctuation is complicated and depends on the interactions of flooding with environment. Notably, vegetation also plays a role in C flux but particular species vary in their ability to sequester and transport C. Bog ecosystems have a greater resilience to water level alteration than fens, due to differences in biogeochemical responses to hydrology. The full understanding of the role of peatlands in global C cycling deserves much more study due to uncertainties of vegetation feedbacks, peat–water interactions, microbial mediation of vegetation, wildfire, and functional responses after hydrologic restoration.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/20964129.2020.1806113","usgsCitation":"Zhong, Y., Ming, J., and Middleton, B., 2020, Effects of water level alteration on carbon cycling in peatlands: Ecosystem Health and Sustainability, v. 6, no. 1, 1806113, 29 p., https://doi.org/10.1080/20964129.2020.1806113.","productDescription":"1806113, 29 p.","ipdsId":"IP-109966","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":455385,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/20964129.2020.1806113","text":"Publisher Index Page"},{"id":378449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhong, Yehui","contributorId":240734,"corporation":false,"usgs":false,"family":"Zhong","given":"Yehui","email":"","affiliations":[{"id":48133,"text":"Chinese Academy of Science (Beijing University)","active":true,"usgs":false}],"preferred":false,"id":798866,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ming, Jiang","contributorId":240735,"corporation":false,"usgs":false,"family":"Ming","given":"Jiang","email":"","affiliations":[{"id":48136,"text":"Chinese Academy of Science","active":true,"usgs":false}],"preferred":false,"id":798867,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":206609,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":798868,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215572,"text":"70215572 - 2020 - Endocrine disrupting activities and geochemistry of water resources associated with unconventional oil and gas activity","interactions":[],"lastModifiedDate":"2020-10-23T13:24:36.594397","indexId":"70215572","displayToPublicDate":"2020-09-08T08:20:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Endocrine disrupting activities and geochemistry of water resources associated with unconventional oil and gas activity","docAbstract":"The rise of hydraulic fracturing and unconventional oil and gas (UOG) exploration in the United States has increased public concerns for water contamination induced from hydraulic fracturing fluids and associated wastewater spills. Herein, we collected surface and groundwater samples across Garfield County, Colorado, a drilling-dense region, and measured endocrine bioactivities, geochemical tracers of UOG wastewater, UOG-related organic contaminants in surface water, and evaluated UOG drilling production (weighted well scores, nearby well count, reported spills) surrounding sites. Elevated antagonist activities for the estrogen, androgen, progesterone, and glucocorticoid receptors were detected in surface water and associated with nearby shale gas well counts and density. The elevated endocrine activities were observed in surface water associated with medium and high UOG production (weighted UOG well score-based groups). These bioactivities were generally not associated with reported spills nearby, and often did not exhibit geochemical profiles associated with UOG wastewater from this region. Our results suggest the potential for releases of low-saline hydraulic fracturing fluids or chemicals used in other aspects of UOG production, similar to the chemistry of the local water, and dissimilar from defined spills of post-injection wastewater. Notably, water collected from certain medium and high UOG production sites exhibited bioactivities well above the levels known to impact the health of aquatic organisms, suggesting that further research to assess potential endocrine activities of UOG operations is warranted.
Sacramento Pikeminnow Ptychocheilus grandis is a potamodromous species endemic to mid- and low-elevation streams and rivers of Central and Northern California. Adults are known to undertake substantial migrations, typically associated with spawning, though few data exist on the extent of these migrations. Six Sacramento Pikeminnow implanted with passive integrated transponder tags in the Sacramento–San Joaquin Delta were detected in Cottonwood and Mill creeks, tributaries to the Sacramento River in Northern California, between April 2018 and late February 2020. Total travel distances ranged from 354 to 432 km, the maximum of which exceeds the previously known record by at least 30 km. These observations add to a limited body of knowledge regarding the natural history of Sacramento Pikeminnow and highlight the importance of the river–estuary continuum as essential for this migratory species.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3996/JFWM-20-038","usgsCitation":"Valentine, D.A., Young, M.J., and Feyrer, F.V., 2020, Sacramento pikeminnow migration record: Journal of Fish and Wildlife Management, v. 11, no. 22, p. 588-592, https://doi.org/10.3996/JFWM-20-038.","productDescription":"5 p","startPage":"588","endPage":"592","ipdsId":"IP-119448","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":455388,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-20-038","text":"Publisher Index Page"},{"id":385630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Sacramento","otherGeospatial":"Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.76696777343749,\n 38.32226566803644\n ],\n [\n -121.39068603515625,\n 38.32226566803644\n ],\n [\n -121.39068603515625,\n 39.52522954427751\n ],\n [\n -121.76696777343749,\n 39.52522954427751\n ],\n [\n -121.76696777343749,\n 38.32226566803644\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"22","noUsgsAuthors":false,"publicationDate":"2020-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Valentine, Dennis A.","contributorId":258067,"corporation":false,"usgs":false,"family":"Valentine","given":"Dennis","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":815642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":815597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":178379,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":815598,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70214487,"text":"70214487 - 2020 - Fates and fingerprints of sulfur and carbon following wildfire in economically important croplands of California, U.S.","interactions":[],"lastModifiedDate":"2020-09-28T13:44:58.985652","indexId":"70214487","displayToPublicDate":"2020-09-07T08:42:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Fates and fingerprints of sulfur and carbon following wildfire in economically important croplands of California, U.S.","docAbstract":"Sulfur (S) is widely used in agriculture, yet little is known about its fates within upland watersheds, particularly in combination with disturbances like wildfire. Our study examined the effects of land use and wildfire on the biogeochemical “fingerprints,” or the quantity and chemical composition, of S and carbon (C). We conducted our research within the Napa River Watershed, California, U.S., where high S applications to vineyards are common, and ~ 20% of the watershed burned in October 2017, introducing a disturbance now common across the warmer, drier Western U.S. We used a laboratory rainfall experiment to compare unburned and low severity burned vineyard and grassland soils. We then sampled streams draining sub-catchments with differing land use and degrees of burn and burn severity to understand combined effects at broader spatial scales. Before the laboratory experiment, vineyard soils had 2–3.5 times more S than grassland soils, while burned soils—regardless of land use—had 1.5–2 times more C than unburned soils. During the laboratory experiment, vineyard soil leachates had 16–20 times more S than grassland leachates, whereas leachate C was more variable across land use and burn soil types. Unburned and burned vineyard soils leached S with δ34S values enriched 6–15‰ relative to grassland soils, likely due to microbial S processes within vineyard soils. Streams draining vineyards also had the fingerprint of agricultural S, with ~2–5 fold higher S concentrations and ~ 10‰ enriched δ34S-SO42− values relative to streams draining non-agricultural areas. However, streams draining a higher fraction of burned non-agricultural areas also had enriched δ34S values relative to unburned non-agricultural areas, which we attribute to loss of 32S during combustion. Our findings illustrate the interacting effects of wildfire and land use on watershed S and C cycling—a new consideration under a changing climate, with significant implications for ecosystem function and human health.
Improved understanding of the budget and retention of sediment in river deltas is becoming increasingly important to mitigate and plan for impacts expected with sea level rise. In this study, analyses of historical bathymetric change, sediment core stratigraphy, and modeling are used to evaluate the sediment budget and environmental response of the largest river delta in the U.S. Pacific Northwest to western land-use change beginning in ~1850. An estimated 142±28 M m3 of sediment accumulated offshore of the emergent Skagit River delta in Washington State between 1890 and 2014 and ~68% of which was found in sand deposits. The fraction of sediment retained in sand reservoirs represents 83% of the expected fluvial sand delivery over this time suggesting their potential utility to evaluate the relative contribution of different land uses to sediment runoff through time. A significantly higher ratio of sand retention to delivery during the period 1890–1939 coincided with extensive watershed denudation (clear-cut logging) and channel dredging, relative to the period 1940–2014, which was characterized by improved forest practices and sediment management to protect endangered species but also more extensive river channelization. Retention in the delta foreset of 78% of the sand delivered by the river between 1890 and 1939 was associated with extensive sediment bypassing and delta progradation that is shown to be 5–10x higher than rates over the Holocene. Comparable offshore sand retention over time and higher nearshore retention subsequent to 1940 after normalizing for the assumed reduction in sediment runoff with improved forest practices, suggests that channelization has continued to influence sediment export at a magnitude equivalent to the effects of early logging. Adverse impacts of the bypassing sediment regime to natural hazards risk and ecosystem management concerns are discussed, including the role of the lost sediment as a resource to mitigate subsiding coastal lands vulnerable to flood impacts. The sediment budget and coastal change analyses provide a framework for evaluating opportunities to achieve greater resilience across several sectors of coastal land use important in low-lying deltas worldwide.
Effective water resource management requires practical, data‐driven determination of instream flow needs. Newly developed, high‐resolution flow models and aquatic species databases provide enormous opportunity, but the volume of data can prove challenging to manage without automated tools. The objective of this study was to develop a framework of analytical methods and best practices to reduce costs of entry into flow–ecology analysis by integrating widely available hydrologic and ecological datasets. Ecological limit functions (ELFs) describing the relation between maximum species richness and stream size characteristics (streamflow or drainage area) were developed. Species richness is expected to increase with streamflow through a watershed up to a point where it either plateaus or transitions to a decreasing trend in larger streams. Our results show that identifying the location of this \"breakpoint\" is critical for producing optimal ELF model fit. We found that richness breakpoints can be estimated using automated low‐supervision methods, with high‐supervision providing negligible improvement in detection accuracy. Model fit (and predictive capability) was found to be superior in smaller hydrologic units. The ELF model (\"elfgen\" R package available on GitHub: https://github.com/HARPgroup/elfgen) can be used to generate ELFs using built‐in datasets for the conterminous United States, or applied anywhere else streamflow and biodiversity data inputs are available.
Bull trout (Salvelinus confluentus) are challenging to detect as a result of the species cryptic behavior and coloration, relatively low densities in complex habitats, and affinity for cold, high clarity, low conductivity waters. Bull trout are also closely associated with the stream bed, frequently conceal in substrate, and this concealment behavior is poorly understood. Consequently, population assessments are problematic and biologists and managers often lack quantitative information to accurately describe bull trout distributions, estimate abundance, and assess status and trends; particularly for stream-dwelling populations. During controlled laboratory trials, we recorded concealment, resting, and swimming behavior of juvenile wild bull trout in response to: (1) constant and fluctuating water temperature, (2) presence or absence of light, and (3) substrate size. Light level had the strongest influence on wild fish concealment and more fish concealed as light levels increased from darkness to daylight. Wild fish were 14.5 times less likely to conceal in constant darkness and 4.1 times more likely to conceal in 12 h light x 12 h darkness compared to constant light. Wild fish were 6.2 times less likely to conceal in small (26–51 mm) substrate compared to larger (52–102 mm) substrate. As water temperature increased, fewer wild fish concealed. Knowledge of wild bull trout concealment will improve field sampling protocols and increase detection efficiencies. These data also enhance knowledge of bull trout niche requirements which illuminates ecological differences among species and informs conservation and restoration efforts.
","language":"English","doi":"10.1371/journal.pone.0237716","usgsCitation":"Russell F. Thurow, Peterson, J., Chandler, G.L., Moffitt, C.M., and Bjornn, T.C., 2020, Concealment of juvenile bull trout in response to temperature, light, and substrate: Implications for detection: PLoS ONE, v. 15, no. 9, e0237716, 17 p., https://doi.org/10.1371/journal.pone.0237716.","productDescription":"e0237716, 17 p.","ipdsId":"IP-099310","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":455408,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0237716","text":"Publisher Index Page"},{"id":395306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Russell F. Thurow","contributorId":273112,"corporation":false,"usgs":false,"family":"Russell F. Thurow","affiliations":[{"id":56194,"text":"fs","active":true,"usgs":false}],"preferred":false,"id":832584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chandler, Gwynne L.","contributorId":273115,"corporation":false,"usgs":false,"family":"Chandler","given":"Gwynne","email":"","middleInitial":"L.","affiliations":[{"id":56194,"text":"fs","active":true,"usgs":false}],"preferred":false,"id":832587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moffitt, Christine M.","contributorId":273113,"corporation":false,"usgs":false,"family":"Moffitt","given":"Christine","email":"","middleInitial":"M.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":832585,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bjornn, Theodore C.","contributorId":273114,"corporation":false,"usgs":false,"family":"Bjornn","given":"Theodore","email":"","middleInitial":"C.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":832586,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70214121,"text":"70214121 - 2020 - Utilization of multiple microbial tools to evaluate efficacy of restoration strategies to improve recreational water quality at a Lake Michigan Beach (Racine, WI)","interactions":[],"lastModifiedDate":"2020-10-29T14:53:05.4625","indexId":"70214121","displayToPublicDate":"2020-09-04T09:51:23","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2390,"text":"Journal of Microbiological Methods","active":true,"publicationSubtype":{"id":10}},"title":"Utilization of multiple microbial tools to evaluate efficacy of restoration strategies to improve recreational water quality at a Lake Michigan Beach (Racine, WI)","docAbstract":"Hydro-meteorological conditions facilitate transport of fecal indicator bacteria (FIB) to the nearshore environment, affecting recreational water quality. North Beach (Racine, Wisconsin, United States), is an exemplar public beach site along Lake Michigan, where precipitation-mediated surface runoff, wave encroachment, stormwater and tributary outflow were demonstrated to contribute to beach advisories. Multiple restoration actions, including installation of a stormwater retention wetland, were successfully deployed to improve recreational water quality. Implementation of molecular methods (e.g. human microbial source tracking markers and Escherichia coli (E. coli) qPCR) assisted in identifying potential pollution sources and improving public health response time. However, periodic water quality failures still occur. As local beach managers reassess restoration measures in response to climatic changes, use of expanded microbial methods (including bacterial community profiling) may contribute to a better understanding of these dynamic environments. In this 2-year study (2015 and 2019), nearshore/offshore Lake Michigan, stormwater, and tributary samples were collected to determine if, 1) the constructed wetland (~50 m from the shoreline) continued to provide stormwater separation/retention and 2) mixing between onshore sources, Root River and Lake Michigan, was increasing due to rising precipitation/lake levels. Monthly rainfall totals were 1.5× higher in 2019 than 2015, coinciding with a 0.63 m lake-level rise. The prevalence of more intense, onshore winds also increased, facilitating interaction between potential reservoirs of FIB with nearshore water through wind driven waves and lake intrusion, e.g. beach sands and the adjacent Root River. While a strong relationship existed between wet weather wetland and North Beach nearshore E. coli concentrations (all sites), bacterial communities were strikingly different. Conversely, bacterial community overlap existed between the Root River mouth and nearshore/offshore sites. These results suggest the constructed wetland can accommodate the climate-related changes observed in this study. Future restoration activities could be directed towards upstream tributary sources in order to minimize microbial contaminants entering Lake Michigan.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.mimet.2020.106049","usgsCitation":"Kinzelman, J., Byappanahalli, M., Nevers, M., Shively, D., Kurdas, S., and Nakatsu, C.H., 2020, Utilization of multiple microbial tools to evaluate efficacy of restoration strategies to improve recreational water quality at a Lake Michigan Beach (Racine, WI): Journal of Microbiological Methods, v. 178, 106049, 12 p., https://doi.org/10.1016/j.mimet.2020.106049.","productDescription":"106049, 12 p.","ipdsId":"IP-118690","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":455414,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.mimet.2020.106049","text":"Publisher Index Page"},{"id":378693,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","city":"Racine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.83397674560547,\n 42.70312746128158\n ],\n [\n -87.76840209960938,\n 42.70312746128158\n ],\n [\n -87.76840209960938,\n 42.74524729560673\n ],\n [\n -87.83397674560547,\n 42.74524729560673\n ],\n [\n -87.83397674560547,\n 42.70312746128158\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"178","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kinzelman, Julie","contributorId":207713,"corporation":false,"usgs":false,"family":"Kinzelman","given":"Julie","affiliations":[{"id":37612,"text":"City of Racine Health Department","active":true,"usgs":false}],"preferred":false,"id":799508,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byappanahalli, Muruleedhara 0000-0001-5376-597X byappan@usgs.gov","orcid":"https://orcid.org/0000-0001-5376-597X","contributorId":147923,"corporation":false,"usgs":true,"family":"Byappanahalli","given":"Muruleedhara","email":"byappan@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":799509,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nevers, Meredith B. 0000-0001-6963-6734","orcid":"https://orcid.org/0000-0001-6963-6734","contributorId":201531,"corporation":false,"usgs":true,"family":"Nevers","given":"Meredith B.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":799510,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shively, Dawn 0000-0002-6119-924X dshively@usgs.gov","orcid":"https://orcid.org/0000-0002-6119-924X","contributorId":201533,"corporation":false,"usgs":true,"family":"Shively","given":"Dawn","email":"dshively@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":799511,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kurdas, Stephan","contributorId":241089,"corporation":false,"usgs":false,"family":"Kurdas","given":"Stephan","email":"","affiliations":[{"id":48200,"text":"City of Racine, Public Health Department Laboratory","active":true,"usgs":false}],"preferred":false,"id":799512,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nakatsu, Cindy H 0000-0003-0663-180X","orcid":"https://orcid.org/0000-0003-0663-180X","contributorId":215593,"corporation":false,"usgs":false,"family":"Nakatsu","given":"Cindy","email":"","middleInitial":"H","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":799513,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70261935,"text":"70261935 - 2020 - Effect of fluvial discharges and remote non-tidal residuals on compound flood forecasting in San Francisco Bay","interactions":[],"lastModifiedDate":"2025-01-06T15:08:00.207928","indexId":"70261935","displayToPublicDate":"2020-09-04T00:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Effect of fluvial discharges and remote non-tidal residuals on compound flood forecasting in San Francisco Bay","docAbstract":"Accurate and timely flood forecasts are critical for making emergency-response decisions regarding public safety, infrastructure operations, and resource allocation. One of the main challenges for coastal flood forecasting systems is a lack of reliable forecast data of large-scale oceanic and watershed processes and the combined effects of multiple hazards, such as compound flooding at river mouths. Offshore water level anomalies, known as remote Non-Tidal Residuals (NTRs), are caused by processes such as downwelling, offshore wind setup, and also driven by ocean-basin salinity and temperature changes, common along the west coast during El Niño events. Similarly, fluvial discharges can contribute to extreme water levels in the coastal area, while they are dominated by large-scale watershed hydraulics. However, with the recent emergence of reliable large-scale forecast systems, coastal models now import the essential input data to forecast extreme water levels in the nearshore. Accordingly, we have developed Hydro-CoSMoS, a new coastal forecast model based on the USGS Coastal Storm Modeling System (CoSMoS) powered by the Delft3D San Francisco Bay and Delta community model. In this work, we studied the role of fluvial discharges and remote NTRs on extreme water levels during a February 2019 storm by using Hydro-CoSMoS in hindcast mode. We simulated the storm with and without real-time fluvial discharge data to study their effect on coastal water levels and flooding extent, and highlight the importance of watershed forecast systems such as NOAA’s National Water Model (NWM). We also studied the effect of remote NTRs on coastal water levels in San Francisco Bay during the 2019 February storm by utilizing the data from a global ocean model (HYCOM). Our results showed that accurate forecasts of remote NTRs and fluvial discharges can play a significant role in predicting extreme water levels in San Francisco Bay. This pilot application in San Francisco Bay can serve as a basis for integrated coastal flood modeling systems in complex coastal settings worldwide.
","language":"English","publisher":"MDPI","doi":"10.3390/w12092481","usgsCitation":"Tehranirad, B., Herdman, L.M., Nederhoff, K., Erikson, L.H., Cifelli, R., Pratt, G., Leon, M., and Barnard, P.L., 2020, Effect of fluvial discharges and remote non-tidal residuals on compound flood forecasting in San Francisco Bay: Water, v. 12, no. 9, 2481, 15 p., https://doi.org/10.3390/w12092481.","productDescription":"2481, 15 p.","ipdsId":"IP-120224","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467278,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w12092481","text":"Publisher Index Page"},{"id":465668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.88353317906419,\n 38.09730105803703\n ],\n [\n -122.88353317906419,\n 37.39198937844094\n ],\n [\n -121.86759792175883,\n 37.39198937844094\n ],\n [\n -121.86759792175883,\n 38.09730105803703\n ],\n [\n -122.88353317906419,\n 38.09730105803703\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-09-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Tehranirad, Babak 0000-0002-1634-9165","orcid":"https://orcid.org/0000-0002-1634-9165","contributorId":299107,"corporation":false,"usgs":false,"family":"Tehranirad","given":"Babak","affiliations":[{"id":64774,"text":"contracted to USGS PCMSC","active":true,"usgs":false}],"preferred":false,"id":922342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herdman, Liv M. 0000-0002-5444-6441 lherdman@usgs.gov","orcid":"https://orcid.org/0000-0002-5444-6441","contributorId":149964,"corporation":false,"usgs":true,"family":"Herdman","given":"Liv","email":"lherdman@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nederhoff, Kees 0000-0003-0552-3428","orcid":"https://orcid.org/0000-0003-0552-3428","contributorId":334091,"corporation":false,"usgs":false,"family":"Nederhoff","given":"Kees","affiliations":[{"id":39963,"text":"Deltares-USA","active":true,"usgs":false}],"preferred":true,"id":922344,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":922345,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cifelli, Rob","contributorId":211532,"corporation":false,"usgs":false,"family":"Cifelli","given":"Rob","email":"","affiliations":[{"id":38261,"text":"NOAA/ESRL/Physical Sciences Division","active":true,"usgs":false}],"preferred":false,"id":922346,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pratt, Greg","contributorId":268885,"corporation":false,"usgs":false,"family":"Pratt","given":"Greg","email":"","affiliations":[{"id":55709,"text":"NOAA Global Systems Laboratory","active":true,"usgs":false}],"preferred":false,"id":922347,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Leon, Michael","contributorId":347739,"corporation":false,"usgs":false,"family":"Leon","given":"Michael","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":922348,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":922349,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70213003,"text":"sir20205093 - 2020 - Detection and measurement of land subsidence and uplift using Global Positioning System surveys and interferometric synthetic aperture radar, Coachella Valley, California, 2010–17","interactions":[],"lastModifiedDate":"2020-09-04T12:33:02.543434","indexId":"sir20205093","displayToPublicDate":"2020-09-03T09:24:30","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5093","displayTitle":"Detection and Measurement of Land Subsidence and Uplift Using Global Positioning System Surveys and Interferometric Synthetic Aperture Radar, Coachella Valley, California, 2010–17","title":"Detection and measurement of land subsidence and uplift using Global Positioning System surveys and interferometric synthetic aperture radar, Coachella Valley, California, 2010–17","docAbstract":"Groundwater has been a major source of agricultural, recreational, municipal, and domestic supply in the Coachella Valley of California since the early 1920s. Pumping of groundwater resulted in groundwater-level declines as large as 50 feet (ft) or 15 meters (m) by the late 1940s. Because of concerns that the declines could cause land subsidence, the Coachella Valley Water District (CVWD) and the U.S. Geological Survey (USGS) have cooperatively investigated subsidence in the Coachella Valley since 1996.
Importation of Colorado River water to the southern Coachella Valley began in 1949, resulting in a reduction in groundwater pumping and a recovery of groundwater levels during the 1950s through the 1970s. Since the late 1970s, the demand for water in the valley increased to the point that groundwater levels again declined in response to increased pumping and, consequently, increased the potential for land subsidence caused by aquifer-system compaction. Several management actions to increase recharge or to reduce reliance on groundwater have been implemented since as early as 1973 to address overdraft in the Coachella Valley. The implementation of three particular projects has markedly improved groundwater conditions in some of the historically most overdrafted areas of the valley: (1) groundwater substitution with surface-water imports since 2006 using Colorado River water through the Mid-Valley Pipeline project, which was expanded through 2017; (2) budget-based, tiered rates since 2009; and (3) managed aquifer recharge at the Thomas E. Levy Groundwater Replenishment Facility since 2009.
Global Positioning System (GPS) surveying and interferometric synthetic aperture radar (InSAR) methods were used to determine the location, extent, and magnitude of the vertical land-surface changes in the Coachella Valley during 2010–17, updating 1993–2010 information presented in previous USGS reports. The GPS measurements taken at 24 geodetic monuments in August 2010 and September 2015 indicated that the land-surface elevation was stable at 17 monuments but changed at seven monuments during the 5-year period. Subsidence ranged from 0.17 to 0.43 ±0.09 ft (52 to 132 ±28 millimeters, or mm) at three monuments, and uplift ranged from 0.11 to 0.18 ±0.09 ft (33 to 54 ±28 mm) at four monuments between 2010 and 2015. At two of the monuments that subsided, the subsidence rates decreased between 2010 and 2015 from those computed between 2005 and 2010. Data prior to 2010 were not available for the third monument that subsided; thus, the 2010–15 subsidence rate could not be compared to an earlier period. At three of the monuments that uplifted between 2010 and 2015, data collected in 2005 and 2010 indicated stability. Data prior to 2010 were not available for the fourth monument that uplifted; thus, the 2010–15 uplift rate could not be compared to an earlier period.
InSAR analyses for December 28, 2014–June 27, 2017, indicated that the land surface uplifted as much as about 0.20 ft (60 mm) near the Whitewater River Groundwater Replenishment Facility in the northern Coachella Valley and subsided as much as about 0.26 ft (80 mm) in the La Quinta area and less in Palm Desert, Indian Wells, and other localized areas in the southern Coachella Valley. These areas were identified as subsidence areas in previous reports covering periods during 1993–2010. The comparison of 2014–17 subsidence rates with those derived for 1995–2010 generally indicated a substantial slowing of subsidence, however. Analyses of deformation in the northern Coachella Valley were not included in the previous reports, so a comparison to deformation during the earlier period could not be made.
Water levels in wells near the subsiding geodetic monuments, in and near the three subsiding areas shown by InSAR, and throughout the valley generally indicated seasonal fluctuations and longer-term stability or rising groundwater levels since about 2010. These results mark a reversal in trends of groundwater-level declines during the preceding decades. This trend reversal provides new insights into aquifer-system mechanics. Although many areas have stopped subsiding, and a few have even uplifted, the few areas that did subside during 2010–17—albeit at a slower rate—indicate a mixed aquifer-system response. Subsidence when groundwater levels are stable or recovering indicates that residual compaction may have occurred. At the same time, coarse-grained materials and thin aquitards may have expanded as groundwater levels recovered. The continued valley-wide stabilization and recovery of groundwater levels since 2010 likely is a result of various projects designed to increase recharge or to reduce reliance on groundwater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205093","collaboration":"Water Availability and Use Science ProgramDirector, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Flooding, excessive sedimentation, and high bacteria counts are among the most challenging water resource issues affecting the Upper Roanoke River watershed. These issues threaten public safety, impair the watershed’s living resources, and threaten drinking water supplies, though mitigation is costly and difficult to manage.
Urban development, land disturbance, and changing climatic patterns continue to challenge watershed managers who are tasked with protecting and improving the water quality of the Upper Roanoke River watershed. The U.S. Geological Survey helps watershed managers meet these demands by providing high-quality data and analyses designed to inform watershed restoration activities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203040","usgsCitation":"Webber, J., and Jastram, J., 2020, Science to support water-resource management in the upper Roanoke River watershed: U.S. Geological Survey Fact Sheet 2020-3040, 2 p., https://doi.org/10.3133/fs20203040.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-117852","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":378117,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3040/coverthb.gif"},{"id":378118,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3040/fs20203040.pdf","text":"Report","size":"3.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3040"}],"country":"United States","state":"Virginia","otherGeospatial":"Upper Roanoke River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.88409423828125,\n 36.97622678464096\n ],\n [\n -79.62890625,\n 36.96525497589677\n ],\n [\n -79.61517333984375,\n 37.42906945530332\n ],\n [\n -80.39245605468749,\n 37.461778479617486\n ],\n [\n -80.88409423828125,\n 36.97622678464096\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
Successful river restoration requires understanding and integration of multiple disciplinary perspectives, including evaluations of past and ongoing watershed processes, local geomorphic response, and impacts unique to human activity. Nowhere is this more apparent than along the Merced River in Yosemite National Park, USA, where both an outstanding natural landscape and the consequences of over a century of human disturbances continue to interact. An intact upstream watershed highlights the importance here of local impacts on geomorphic response. Incision and the resulting decoupling of the channel from its adjacent late-Holocene floodplain are consequences of reduced channel roughness, likely from de-snagging the river, and instream gravel mining in the 19th and early 20th century. Riparian-zone disturbance by visitor use has damaged riparian vegetation and soils, inducing channel widening. Revetments and channel-spanning bridges, the latter being visible and oft-cited impacts to fluvial processes, have distorted the natural evolution of meanders and induced local channel narrowing. The historical rate of sediment export from Yosemite Valley has greatly exceeded replenishment from upstream and lateral sources, creating a deficit that now inhibits recovery via passive restoration of more natural channel form and function. Climate change may amplify now-diminished fluvial processes but also exacerbate the rate of sediment export. These conditions, reflecting a complex intersection of geologic history, modern geomorphic processes, and human interactions, demonstrate how a limited influx of sediment coupled with intensive human use can have long-term consequences for riverine conditions, restoration opportunities, and social engagement with the riverine landscape.
Freshwater mussels (order Unionida) are among the world’s most biodiverse but imperiled taxa. Recent unionid mass mortality events around the world threaten ecosystem services such as water filtration, nutrient cycling, habitat stabilization, and food web enhancement, but causes have remained elusive. To examine potential infectious causes of these declines, we studied mussels in Clinch River, Virginia and Tennessee, USA, where the endemic and once-predominant pheasantshell (Actinonaias pectorosa) has suffered precipitous declines since approximately 2016. Using metagenomics, we identified 17 novel viruses in Clinch River pheasantshells. However, only one virus, a novel densovirus (Parvoviridae; Densovirinae), was epidemiologically linked to morbidity. Clinch densovirus 1 was 11.2 times more likely to be found in cases (moribund mussels) than controls (apparently healthy mussels from the same or matched sites), and cases had 2.7 (log10) times higher viral loads than controls. Densoviruses cause lethal epidemic disease in invertebrates, including shrimp, cockroaches, crickets, moths, crayfish, and sea stars. Viral infection warrants consideration as a factor in unionid mass mortality events either as a direct cause, an indirect consequence of physiological compromise, or a factor interacting with other biological and ecological stressors to precipitate mortality.
The geographic information system tool, Social Values for Ecosystem Services (SolVES), was developed to incorporate quantified and spatially explicit measures of social values into ecosystem service assessments. SolVES 4.0 provides an open-source version of SolVES, which was designed to assess, map, and quantify the social values of ecosystem services. Social values—the perceived, nonmarket values the public ascribes to ecosystem services, particularly cultural services, such as aesthetics and recreation—can be evaluated for various stakeholder groups. These groups are distinguishable by factors such as their attitudes and preferences regarding public uses (for example, motorized recreation and logging). As with previous versions, SolVES 4.0 derives a quantitative 10-point, social-values metric—the value index—from a combination of spatial and nonspatial responses to public value and preference surveys. The tool also calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. SolVES 4.0 has been developed with Python using a QGIS user interface and a PostgreSQL database for required data. SolVES is integrated with Maxent maximum entropy modeling software to generate more complete social-value maps and offer robust statistical models describing the relation between the value index and explanatory environmental variables. A model’s goodness of fit to a primary study area and its potential performance in transferring social values to similar areas using value-transfer methods can be evaluated. SolVES 4.0 provides an improved open-source, public-domain tool for decision makers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among ecosystem services in a variety of biophysical and social contexts including mountain, forest, coastal, riparian, agricultural, and urban environments around the globe.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C25","usgsCitation":"Sherrouse, B.C., and Semmens, D.J., 2020, Social Values for Ecosystem Services, version 4.0 (SolVES 4.0)—Documentation and user manual: U.S. Geological Survey Techniques and Methods, book 7, chap. C25, 59 p., https://doi.org/ 10.3133/ tm7C25.","productDescription":"Report: ix, 59 p.; Application Site","onlineOnly":"Y","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":436802,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9URDZ4V","text":"USGS data release","linkHelpText":"SolVES"},{"id":377693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c25/coverthb.jpg"},{"id":377694,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c25/tm7C25.pdf","text":"Report","size":"13.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 7 C-25"},{"id":377695,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://doi.org/10.5066/P9URDZ4V","text":"Social Values for Ecosystem Services (SolVES) 4.0"}],"contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, Mail Stop 980
Denver, CO 80225
As part of a regional effort to characterize groundwater in rural areas of Pennsylvania, water samples from 47 domestic wells in Potter County were collected from May through September 2017. The sampled wells had depths ranging from 33 to 600 feet in sandstone, shale, or siltstone aquifers. Groundwater samples were analyzed for physicochemical properties that could be evaluated in relation to drinking-water health standards, geology, land use, and other environmental factors. Laboratory analyses included concentrations of major ions, nutrients, bacteria, trace elements, volatile organic compounds (VOCs), ethylene and propylene glycol, alcohols, gross-alpha/beta-particle activity, uranium, radon-222, and dissolved gases. A subset of samples was analyzed for radium isotopes (radium-226 and -228) and for the isotopic composition of methane.
Results of this 2017 study show that groundwater quality generally met most drinking-water standards that apply to public water supplies. However, a percentage of samples exceeded maximum contaminant levels (MCLs) for total coliform bacteria (69.6 percent), Escherichia coli (30.4 percent), arsenic, and barium; and secondary maximum contaminant levels (SMCLs) for field pH, manganese, sodium, iron, total dissolved solids, aluminum, and chloride. All of the analyzed VOCs were below limits of detection and associated drinking water criteria. Radon-222 activities exceeded the proposed drinking-water standard of 300 picocuries per liter in 80.9 percent of the samples.
The field pH of the groundwater ranged from 4.6 to 9.0. Generally, the lower pH samples had greater potential for elevated concentrations of dissolved metals, including beryllium, copper, lead, nickel, and zinc, whereas the higher pH samples had greater potential for elevated concentrations of total dissolved solids, sodium, fluoride, boron, and uranium. Near-neutral samples (pH 6.5 to 7.5) had greater hardness and alkalinity concentrations than other samples with pH values outside this range. Calcium/bicarbonate waters were the predominant hydrochemical type for the sampled aquifers, with mixed water types for many samples, including variable contributions from calcium, magnesium, and sodium combined with bicarbonate, sulfate, chloride, and nitrate.
Water from 45 wells had concentrations of methane greater than the 0.0002 milligrams per liter (mg/L) detection limit. One sample had the maximum value of 11 mg/L, which exceeds the Pennsylvania action level of 7 mg/L. Additionally, three other samples had concentrations of methane greater than 4 mg/L. Outgassing of such levels of methane from the water to air within a confined space can result in a potential hazard. The elevated concentrations of methane generally were associated with suboxic groundwater (dissolved oxygen less than 0.5 mg/L) that had near-neutral to alkaline pH with relatively elevated concentrations of iron, manganese, ammonia, lithium, fluoride, and boron. Other constituents, including barium, sodium, chloride, and bromide, commonly were elevated, but not limited to, those well-water samples with elevated methane. Low levels of ethane (as much as 1.2 mg/L) were present in eight samples with the highest methane concentrations. Five samples were analyzed for methane isotopes. The isotopic and hydrocarbon compositions in these five samples suggest the methane may be of microbial origin or a mixture of thermogenic and microbial gas, but differed from the compositions reported for mud-gas logging samples collected during drilling of gas wells.
The concentrations of sodium (median 8.2 mg/L), chloride (median 7.64 mg/L), and bromide (median 0.02 mg/L) for the 47 groundwater samples collected for this study ranged widely and were positively correlated with one another and with specific conductance and associated measures of ionic strength. Sixty percent of the Potter County well-water samples had chloride concentrations less than 10 mg/L. Samples with higher chloride concentrations had variable bromide concentrations and corresponding chloride/bromide ratios that are consistent with sources such as road-deicing salt and septic effluent (low bromide) or brine (high bromide). Brines are naturally present in deeper parts of the regional groundwater system and, in some cases, may be mobilized by gas drilling. It is also possible that valley wells were drilled close to or into the brine-freshwater interface, so brine signatures do not necessarily indicate contamination due to drilling. The chloride, bromide, and other constituents in road-deicing salt or brine solutions tend to be diluted by mixing with fresh groundwater in shallow aquifers used for water supply. Although 1 of 8 groundwater samples with the highest methane concentrations (greater than 0.2 mg/L) had concentrations of chloride and bromide with corresponding chloride/bromide ratios that indicated mixing with road-deicing salt, the other 7 of 8 samples with elevated methane had concentrations of chloride and bromide with corresponding chloride/bromide ratios that indicated mixing with a small amount of brine (0.02 percent or less) similar in composition to those reported for gas and oil well brines in Pennsylvania. In several eastern Pennsylvania counties where gas drilling is absent, groundwater with comparable chloride/bromide ratios and chloride concentrations have been reported. Approximately 50 percent of Potter County well-water samples, including two samples with the fourth (72.9 mg/L) and fifth (47.0 mg/L) highest chloride concentrations, have chloride/bromide ratios that indicate predominantly anthropogenic sources of chloride, such as road-deicing salt or septic effluent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205038","collaboration":"Prepared in cooperation with the County of Potter","usgsCitation":"Galeone, D.G., Cravotta, C.A., III, and Risser, D.W., 2020, Groundwater quality in relation to drinking water health standards and hydrogeologic and geochemical characteristics for 47 domestic wells in\nPotter County, Pennsylvania, 2017: U.S. Geological Survey Scientific Investigations Report 2020–5038, p.67, https://doi.org/10.3133/sir20205038.","productDescription":"Report: viii, 67 p.; 2 Appendixes, Data Release","numberOfPages":"67","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-111083","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":377852,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5038/coverthb.jpg"},{"id":377854,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5038/sir20205038.pdf","text":"Report","size":"8.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5038"},{"id":377855,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5038/sir20205038_appendix3.xlsx","text":"Appendix 3","size":"30.3 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Excel file"},{"id":377856,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5038/sir20205038_appendix3.csv","text":"Appendix 3","size":"9.00 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- CSV file"},{"id":377857,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EBORD5","text":"USGS data release","linkHelpText":"Compilation of wells sampled, physical characteristics of wells, links to water-quality data, and quality assurance and quality control data for domestic wells sampled by the U.S. Geological Survey in Potter County, Pennsylvania, April–September 2017"}],"country":"United States","state":"Pennsylvania","county":"Potter County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-77.7513,41.999],[-77.7031,41.9991],[-77.6884,41.9992],[-77.6096,41.9998],[-77.6077,41.9211],[-77.6076,41.9174],[-77.6076,41.9015],[-77.6063,41.8402],[-77.6057,41.8334],[-77.6056,41.8121],[-77.6056,41.8093],[-77.605,41.8007],[-77.605,41.7944],[-77.6043,41.7558],[-77.6043,41.7499],[-77.6043,41.7472],[-77.603,41.7186],[-77.603,41.6999],[-77.6017,41.6518],[-77.6017,41.6437],[-77.601,41.6128],[-77.601,41.5987],[-77.5997,41.5497],[-77.5991,41.5424],[-77.5991,41.5256],[-77.5991,41.5211],[-77.5984,41.5002],[-77.5978,41.4784],[-77.6155,41.4784],[-77.664,41.4784],[-77.6977,41.4779],[-77.6989,41.4779],[-77.7093,41.4778],[-77.7498,41.4778],[-77.7645,41.4777],[-77.7774,41.4772],[-77.8006,41.4772],[-77.8123,41.4772],[-77.8282,41.4767],[-77.8454,41.4766],[-77.8742,41.4761],[-77.903,41.476],[-77.922,41.4755],[-77.9514,41.4754],[-77.9796,41.4757],[-77.9876,41.4757],[-78.0513,41.4768],[-78.0643,41.4881],[-78.0773,41.5003],[-78.094,41.5157],[-78.0958,41.5175],[-78.0977,41.5193],[-78.1107,41.5315],[-78.1119,41.5328],[-78.1243,41.5437],[-78.1379,41.5568],[-78.1769,41.5933],[-78.1831,41.5992],[-78.1862,41.6019],[-78.1992,41.6136],[-78.2035,41.6177],[-78.2054,41.619],[-78.2048,41.625],[-78.2062,41.6967],[-78.2065,41.7875],[-78.2065,41.7925],[-78.2066,41.8029],[-78.2068,41.8197],[-78.2071,41.8479],[-78.2073,41.866],[-78.2067,41.8697],[-78.2068,41.881],[-78.2075,41.8865],[-78.2078,41.9196],[-78.2078,41.9786],[-78.2085,41.9859],[-78.2086,42],[-77.9943,41.999],[-77.9662,41.9988],[-77.8686,41.9989],[-77.7513,41.999]]]},\"properties\":{\"name\":\"Potter\",\"state\":\"PA\"}}]}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Many water quality and ecosystem functions performed by streams occur in the benthic biolayer, the biologically active upper (~5 cm) layer of the streambed. Solute transport through the benthic biolayer is facilitated by bedform pumping, a physical process in which dynamic and static pressure variations over the surface of stationary bedforms (e.g., ripples and dunes) drive flow across the sediment-water interface. In this paper we derive two predictive modeling frameworks, one advective and the other diffusive, for solute transport through the benthic biolayer by bedform pumping. Both frameworks closely reproduce patterns and rates of bedform pumping previously measured in the laboratory, provided that the diffusion model's dispersion coefficient declines exponentially with depth. They are also functionally equivalent, such that parameter sets inferred from the 2D advective model can be applied to the 1D diffusive model, and vice versa. The functional equivalence and complementary strengths of these two models expand the range of questions that can be answered, for example, by adopting the 2D advective model to study the effects of geomorphic processes (such as bedform adjustments to land use change) on flow-dependent processes and the 1D diffusive model to study problems where multiple transport mechanisms combine (such as bedform pumping and turbulent diffusion). By unifying 2D advective and 1D diffusive descriptions of bedform pumping, our analytical results provide a straightforward and computationally efficient approach for predicting, and better understanding, solute transport in the benthic biolayer of streams and coastal sediments.
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","language":"English","publisher":"Department of Energy","doi":"10.25584/09102020/1659275","usgsCitation":"Lesmes, D.P., Moerman, J., Torgeson, T., Vallario, B., Scheibe, T.D., Foufoula-Georgiou, E., Jenter, H.L., Bingner, R.L., Condon, L., Cosgrove, B., Del Castillo, C., Downer, C.W., Eylander, J., Fienen, M.N., Frazier, N., Gochis, D., Goodrich, D., Harvey, J., Hughes, J.D., Hyndman, D., Johnston, J., Melton, F., Moglen, G.E., Moulton, D., Lautz, L.K., Parmar, R., Rashleigh, B., Reed, P., Skalak, K., Varadharajan, C., Viger, R.J., Voisin, N., and Wahl, M., 2020, Integrated hydro-terrestrial modeling: Development of a national capability, 182 p., https://doi.org/10.25584/09102020/1659275.","productDescription":"182 p.","ipdsId":"IP-120302","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction 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Via, Jr. Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":800698,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Moulton, David","contributorId":242704,"corporation":false,"usgs":false,"family":"Moulton","given":"David","email":"","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":800699,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Lautz, Laura K.","contributorId":124523,"corporation":false,"usgs":false,"family":"Lautz","given":"Laura","email":"","middleInitial":"K.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":800700,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Parmar, Rajbir","contributorId":242706,"corporation":false,"usgs":false,"family":"Parmar","given":"Rajbir","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":800701,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Rashleigh, Brenda 0000-0002-0806-686X","orcid":"https://orcid.org/0000-0002-0806-686X","contributorId":242708,"corporation":false,"usgs":false,"family":"Rashleigh","given":"Brenda","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":800702,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Reed, Patrick","contributorId":242710,"corporation":false,"usgs":false,"family":"Reed","given":"Patrick","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":800703,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":800704,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Varadharajan, Charuleka","contributorId":242712,"corporation":false,"usgs":false,"family":"Varadharajan","given":"Charuleka","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":800705,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":800706,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Voisin, Nathalie","contributorId":242715,"corporation":false,"usgs":false,"family":"Voisin","given":"Nathalie","email":"","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":800707,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Wahl, Mark","contributorId":242718,"corporation":false,"usgs":false,"family":"Wahl","given":"Mark","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":800708,"contributorType":{"id":1,"text":"Authors"},"rank":33}]}} ,{"id":70216737,"text":"70216737 - 2020 - Rapid-assessment test strips: Effectiveness forcyanotoxin monitoring in a northern temperate lake","interactions":[],"lastModifiedDate":"2021-03-15T23:09:01.802048","indexId":"70216737","displayToPublicDate":"2020-09-01T08:03:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"Rapid-assessment test strips: Effectiveness forcyanotoxin monitoring in a northern temperate lake","docAbstract":"Precise and rapid methods of determining toxin levels are needed in lakes used for recreation and drinking water to facilitate a quick risk assessment during cyanobacteria blooms. Therefore, we evaluated rapid-assessment test strips, a newer technology for estimating the toxicity of cyanobacterial blooms, in Kabetogama Lake, a popular recreational area of Voyageurs National Park in northern Minnesota (USA). Sixty-seven percent of the test strip results matched results of enzyme-linked immunosorbent assays, with individual toxin results of 75% (anatoxin-a), 80% (cylindrospermopsin), and 64% (microcystin). These results provide some evidence that the test strips may be effective for rapid detection of toxins in northern temperate lakes, although improvements to the test strips may be beneficial. Despite the intensive processing required and uncertainty of some results, the availability of a rapid and inexpensive field method allowed us to sample opportunistically in the fall, when we documented dangerously high toxin concentrations at places where waterfowl-retrieving dogs may be at particular risk of exposure.
Linked hydrologic, hydraulic, and ecological models can facilitate planning and implementing water releases from reservoirs to achieve ecological objectives along rivers. We applied a flow‐ecology model, the Ecosystem Functions Model (HEC‐EFM), to the Bill Williams River in southwestern USA to estimate areas suitable for recruitment of riparian tree seedlings in the context of managing flow releases from a large dam for riparian restoration. Ecological variables in the model included timing of seed dispersal, tolerable rates of flow recession, and tolerable duration of inundation following germination and early seedling establishment for native Fremont cottonwood and Goodding's willow, and non‐native tamarisk. Hydrological variables included peak flow timing, rate of flow recession following the peak, and duration of inundation. A one‐dimensional hydraulic model was applied to estimate stage‐discharge relationships along ~58 river kilometres. We then used HEC‐EFM to apply relationships between seedling ecology and streamflow to link hydrological dynamics with ecological response. We developed and validated HEC‐EFM based on an examination of seedling recruitment following an experimental flow release from Alamo Dam in spring 2006. The model predicted the largest area of potential recruitment for cottonwood (280–481 ha), with smaller areas predicted for willow (174–188 ha) and tamarisk (59–60 ha). Correlations between observed and predicted patches with successful seedling recruitment for areas within 40 m of the main channel ranged from 0.66 to 0.94. Finally, we examined arrays of hydrographs to identify which are most conducive to seedling recruitment along the river, given different combinations of peak flow, recession rate, and water volume released. Similar application of this model could be useful for informing reservoir management in the context of riparian restoration along other rivers facing similar challenges.
Little is known about the underlying mechanisms governing the bioaccumulation of uranium (U) in aquatic insects. We experimentally parameterized conditional rate constants for aqueous U uptake, dietary U uptake, and U elimination for the aquatic baetid mayfly Neocloeon triangulifer. Results showed that this species accumulates U from both the surrounding water and diet, with waterborne uptake prevailing. Elevated dietary U concentrations decreased feeding rates, presumably by altering food palatability or impairing the mayfly’s digestive processes, or both. Nearly 90% of the accumulated U was eliminated within 24 h after the waterborne exposure ceased, reflecting the desorption of weakly bound U from the insect’s integument. To examine whether the experimentally derived rate constants for N. triangulifer could be generalized to baetid mayflies, mayfly U concentrations were predicted using the water chemistry and U measured in periphyton from springs in Grand Canyon (United States) and were compared to U concentrations in spring-dwelling mayflies. Predicted and observed mayfly U concentrations were in good agreement. Under the modeled site-specific conditions, waterborne U uptake accounted for 52–93% of the bioaccumulated U. U accumulation was limited in these wild populations due to a combination of factors including low concentrations of bioavailable dissolved U species, slow U uptake rates from food, and fast U elimination.