Many studies investigate river floods by analyzing annual maximum series that record the largest flow of each year, including many within-bank events inconsequential for human communities. Fewer focus on larger floods, especially at the continental scale. Using 473 streamgages across the conterminous United States with near-natural flow from 1966 to 2015, we characterized the seasonality, occurrence, and climatic associations of the 10 largest and 2 largest floods at each site. These are often overbank events that have ecosystem functions and pose risks to humans. We grouped sites into 14 clusters corresponding to climatic and physiographic regions and characterized their flood seasonality at a monthly resolution using a probabilistic method. We then evaluated annual occurrence regionally and nationally, and seasonal occurrence regionally, by complementing a traditional approach to trend analyses with a novel method based on expected occurrence. Relationships between flood occurrence and climate indices were also investigated. Large floods have strong seasonality in some regions, but in areas with numerous flood-generating mechanisms, seasonality is more complex. There is little evidence nationally that large riverine floods are more or less frequent than expected in recent years and only two regions show significant trends in annual counts; few show seasonal trends. We found some regional relationships between flood counts and climate indices, annually and seasonally; nationally the Pacific North American pattern is related to annual counts of the 2 largest floods. Large-flood occurrence was generally stable across the United States in the last five decades; this may or may not continue with projected warming.
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MA","active":true,"usgs":false}],"preferred":false,"id":839063,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":839064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":839065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":839066,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70264967,"text":"70264967 - 2022 - Evaluation of electrical and electromagnetic geophysical techniques to inspect earthen dam and levee structures in Arkansas","interactions":[],"lastModifiedDate":"2025-03-27T15:34:18.439831","indexId":"70264967","displayToPublicDate":"2022-02-03T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9128,"text":"Journal of Environmental and Engineering Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of electrical and electromagnetic geophysical techniques to inspect earthen dam and levee structures in Arkansas","docAbstract":"Within the state of Arkansas there is an increasing number of aging dams and levees that have little to no documentation concerning their construction or composition. Surface geophysical surveys offer a non-intrusive method for investigating these structures: To describe their lithologic makeup, to evaluate the materials that they were constructed upon, and to identify potential flow paths through them. Techniques such as electrical resistivity tomography, seismic refraction, and electromagnetic induction have all been used to image dams and levees and require additional information from geologic outcrops, geotechnical borings, or drill cores in order to make informed geologic interpretations of the geophysical models. These geologic models then allow the owners of these structures to make more informed decisions about their operation and maintenance. Between 2011 and 2018, the U.S. Geological Survey conducted geophysical and geotechnical investigations of three earthen structures within the state of Arkansas. Electrical and electromagnetic geophysical data were used to develop lithologic models of these structures and the underlying geology. Self-potential surveys were utilized to detect the movement of water through these structures indicating possible seepage pathways. Geotechnical methods such as electric and hydraulic direct-push well logs and cores acted as both a control on the geophysical interpretations and a confirmation of anomalies. This integrated approach detected the lack of an impermeable core within a levee, imaged a change in lithology of the bedrock forming the seal beneath a gravity dam, and identified a potential seepage feature within the core of an earthen dam. These results further support that this method of extending known lithologic features via surface and borehole geophysics is a useful approach for characterizing earthen water control structures.","language":"English","publisher":"GeoScienceWorld","doi":"10.32389/JEEG20-063","usgsCitation":"Adams, R.F., Miller, B., Kress, W., Ikard, S., Payne, J.D., and Killion, W., 2022, Evaluation of electrical and electromagnetic geophysical techniques to inspect earthen dam and levee structures in Arkansas: Journal of Environmental and Engineering Geophysics, v. 26, no. 4, p. 287-303, https://doi.org/10.32389/JEEG20-063.","productDescription":"17 p.","startPage":"287","endPage":"303","ipdsId":"IP-116502","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":483950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"26","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Ryan F. 0000-0001-7299-329X rfadams@usgs.gov","orcid":"https://orcid.org/0000-0001-7299-329X","contributorId":5499,"corporation":false,"usgs":true,"family":"Adams","given":"Ryan","email":"rfadams@usgs.gov","middleInitial":"F.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":932118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Benjamin 0000-0003-4795-3442 bvmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-4795-3442","contributorId":197345,"corporation":false,"usgs":true,"family":"Miller","given":"Benjamin","email":"bvmiller@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kress, Wade 0000-0002-6833-028X","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":203539,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ikard, Scott 0000-0002-8304-4935","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":212256,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932121,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Payne, Jason D. 0000-0003-4294-7924","orcid":"https://orcid.org/0000-0003-4294-7924","contributorId":257453,"corporation":false,"usgs":true,"family":"Payne","given":"Jason","email":"","middleInitial":"D.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932122,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Killion, Walter 0000-0002-5653-8489","orcid":"https://orcid.org/0000-0002-5653-8489","contributorId":214713,"corporation":false,"usgs":true,"family":"Killion","given":"Walter","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932123,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70241895,"text":"70241895 - 2022 - Quantifying streamflow depletion from groundwater pumping: A practical review of past and emerging approaches for water management","interactions":[],"lastModifiedDate":"2023-03-30T11:53:25.809423","indexId":"70241895","displayToPublicDate":"2022-02-02T06:51:42","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying streamflow depletion from groundwater pumping: A practical review of past and emerging approaches for water management","docAbstract":"Groundwater pumping can cause reductions in streamflow (“streamflow depletion”) that must be quantified for conjunctive management of groundwater and surface water resources. However, streamflow depletion cannot be measured directly and is challenging to estimate because pumping impacts are masked by streamflow variability due to other factors. Here, we conduct a management-focused review of analytical, numerical, and statistical models for estimating streamflow depletion and highlight promising emerging approaches. Analytical models are easy to implement, but include many assumptions about the stream and aquifer. Numerical models are widely used for streamflow depletion assessment and can represent many processes affecting streamflow, but have high data, expertise, and computational needs. Statistical approaches are a historically underutilized tool due to difficulty in attributing causality, but emerging causal inference techniques merit future research and development. We propose that streamflow depletion-related management questions can be divided into three broad categories (attribution, impacts, and mitigation) that influence which methodology is most appropriate. We then develop decision criteria for method selection based on suitability for local conditions and the management goal, actionability with current or obtainable data and resources, transparency with respect to process and uncertainties, and reproducibility.
In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources that might be produced by using current carbon dioxide enhanced oil recovery (CO2-EOR) technologies in amenable conventional oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes estimates of the mass of CO2 that could be stored (retained) in the assessed oil reservoirs following the application of the CO2-EOR process. The USGS assessment team evaluated more than 3,500 oil reservoirs that were miscible to injected CO2. The assessed reservoirs are in 185 previously defined USGS plays in 33 petroleum provinces of 7 national regions. The team estimated that the total technically recoverable oil resulting from the application of the CO2-EOR process ranges from approximately 25,000 million barrels (MMbbl) at the P5 percentile to as much as 32,000 MMbbl at the P95 percentile, with a mean of 29,000 MMbbl. The associated CO2 retention ranges from approximately 7,400 million metric tons (Mt) at the P5 percentile to as much as 9,500 Mt at the P95 percentile, with a mean of 8,400 Mt. The results are summarized in this fact sheet and are provided in more detail in the companion data release and circular.
The West Texas and Eastern New Mexico region (primarily its Permian Basin) and the Gulf Coast region together contain 60 percent of the mean assessed CO2-EOR oil potential and 61 percent of the mean assessed CO2 retention. Other regions with significant resource potential include the Midcontinent region and the Rocky Mountains and Northern Great Plains region.
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12201 Sunrise Valley Drive
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Telephone: 703–648–6470
In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources available if current carbon dioxide enhanced oil recovery (CO2-EOR) technologies were applied to amenable oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes estimates of the mass of CO2 that could be stored (retained) as a result of CO2-EOR activities. The USGS assessment team evaluated more than 3,500 oil reservoirs that were miscible to injected CO2. The assessed reservoirs are in 185 previously defined USGS plays in 33 petroleum provinces of 7 national regions. The assessment team estimated that the technically recoverable oil associated with CO2-EOR ranges from approximately 25,000 million barrels (MMbbl) at the P5 percentile to as much as 32,000 MMbbl at the P95 percentile, with a mean of 29,000 MMbbl. The associated CO2 retention ranges from approximately 7,400 million metric tons (Mt) at the P5 percentile to as much as 9,500 Mt at the P95 percentile, with a mean of 8,400 Mt. The West Texas and Eastern New Mexico region and the Gulf Coast region together contain 60 percent of the mean assessed CO2-EOR oil potential and 61 percent of the mean assessed CO2 retention. Other regions with significant resource potential include the Midcontinent region and Rocky Mountains and Northern Great Plains region.
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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Telephone: 703–648–6470
The Living Shoreline Demonstration Project (PO-148) used five bio-engineered reef technologies (Reef Balls in two configurations; Figure 1) acting as breakwaters to protect vulnerable shorelines. While the primary goal is to attenuate wave energy, the sustainability and success of these products as “living” shorelines are based on their ability to enhance oyster habitat, enabling the reef to maintain elevation within the rapidly changing environment (i.e., sea level rise, subsidence). This report documents the recruitment, survival, and growth of the living components of the reef – oysters and other encrusting organisms (e.g. mussels, barnacles). This final technical report provides data from five years of monitoring (November 2017 – December 2021) of reefs located along the western side of Eloi Bay in Pontchartrain Basin (Figure 2). Monitoring goals included assessment of (1) annual oyster densities and population dynamics on the reefs, (2) annual density and diversity of other encrusting organisms, and (3) comparisons of outcomes by reef technology, exposure, and water quality. Detailed information on technologies used, construction design, as-built elevations are available in Coast & Harbor Engineering (2016) Design Memorandum dated March 25, 2016, submitted to Louisiana Coastal Protection and Restoration Authority.
","language":"English","publisher":"U.S. Fish & Wildlife Service","doi":"10.3996/css70529922","usgsCitation":"Swam, L.M., Marshall, D.A., and La Peyre, M., 2022, Five years of monitoring a bio-engineered living shoreline: Comparison of oyster population development by reef technology.: Cooperator Science Series 139-2022, ii, 19 p., https://doi.org/10.3996/css70529922.","productDescription":"ii, 19 p.","ipdsId":"IP-137095","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.38780223527601,\n 29.790840321829222\n ],\n [\n -89.42069143656458,\n 29.790840321829222\n ],\n [\n -89.42069143656458,\n 29.750906524072846\n ],\n [\n -89.38780223527601,\n 29.750906524072846\n ],\n [\n -89.38780223527601,\n 29.790840321829222\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2022-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Swam, Lauren M.","contributorId":341585,"corporation":false,"usgs":false,"family":"Swam","given":"Lauren","email":"","middleInitial":"M.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Danielle Aguilar","contributorId":341509,"corporation":false,"usgs":false,"family":"Marshall","given":"Danielle","email":"","middleInitial":"Aguilar","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908646,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228376,"text":"70228376 - 2022 - Integrating urban planning and water management through green infrastructure in the United States-Mexico border","interactions":[],"lastModifiedDate":"2022-02-09T15:53:52.635912","indexId":"70228376","displayToPublicDate":"2022-02-01T09:49:30","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7170,"text":"Frontiers in Water","active":true,"publicationSubtype":{"id":10}},"title":"Integrating urban planning and water management through green infrastructure in the United States-Mexico border","docAbstract":"Creating sustainable, resilient, and livable cities calls for integrative approaches and collaborative practices across temporal and spatial scales. However, practicability is challenged by institutional, social, and technical complexities and the need to build collective understanding of integrated approaches. Rapid urbanization along the United States-Mexico border, fueled by industrialization, trade, and migration, has resulted in cities confronted with recurrent flooding risk, extended drought, water pollution, habitat destruction and systemic vulnerabilities. The international border, which separates natural and built ecosystems, is both a challenge and an opportunity, making a unique social and institutional setting ideal for testing the integration of urban planning and water management. Our research focuses on fusing multi-functional and multi-scalar green infrastructure to restore ecosystem services through a strategic binational planning process. This paper describes this planning process, including the development and application of both a land suitability analysis and a hydrological model to optimally site green infrastructure in the Nogales, Arizona, United States—Nogales, Sonora, Mexico, cross border region. We draw lessons from this process and stakeholder feedback focused on the potential for urban green infrastructure, to allow for adaptation and even transformation in the face of current and future challenges such as limited resources, underdeveloped governance, bordering, and climate change. In sum, a cross border network of green infrastructure can provide a backbone to connect this transboundary watershed while providing both hydrological and social benefits.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/frwa.2022.782922","usgsCitation":"Lara-Valencia, F., Garcia, M., Norman, L., Anides Morales, A., and Castellanos-Rubio, E.E., 2022, Integrating urban planning and water management through green infrastructure in the United States-Mexico border: Frontiers in Water, v. 4, 782922, 17 p., https://doi.org/10.3389/frwa.2022.782922.","productDescription":"782922, 17 p.","ipdsId":"IP-132393","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":448941,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frwa.2022.782922","text":"Publisher Index Page"},{"id":395668,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.0772705078125,\n 31.23159167205059\n ],\n [\n -110.8685302734375,\n 31.23159167205059\n ],\n [\n -110.8685302734375,\n 31.423975737976697\n ],\n [\n -111.0772705078125,\n 31.423975737976697\n ],\n [\n -111.0772705078125,\n 31.23159167205059\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","noUsgsAuthors":false,"publicationDate":"2022-02-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Lara-Valencia, Francisco","contributorId":275344,"corporation":false,"usgs":false,"family":"Lara-Valencia","given":"Francisco","affiliations":[{"id":56763,"text":"Arizona State University, Phoenix, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":834019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Margaret","contributorId":275345,"corporation":false,"usgs":false,"family":"Garcia","given":"Margaret","email":"","affiliations":[{"id":56763,"text":"Arizona State University, Phoenix, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":834020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":834021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anides Morales, Alma","contributorId":275346,"corporation":false,"usgs":false,"family":"Anides Morales","given":"Alma","email":"","affiliations":[{"id":50057,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":834022,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castellanos-Rubio, Edgar E.","contributorId":275347,"corporation":false,"usgs":false,"family":"Castellanos-Rubio","given":"Edgar","email":"","middleInitial":"E.","affiliations":[{"id":56764,"text":"Instituto Municipal de Investigación y Planeación de Nogales Sonora","active":true,"usgs":false}],"preferred":false,"id":834023,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70231295,"text":"70231295 - 2022 - Thermodynamic insights into the production of methane hydrate reservoirs from depressurization of pressure cores","interactions":[],"lastModifiedDate":"2022-05-06T13:59:17.797111","indexId":"70231295","displayToPublicDate":"2022-02-01T09:46:43","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Thermodynamic insights into the production of methane hydrate reservoirs from depressurization of pressure cores","docAbstract":"We present results of slow (multiple day) depressurization experiments of pressure cores recovered from Green Canyon Block 955 in the northern Gulf of Mexico during The University of Texas at Austin Hydrate Pressure Coring Expedition (UT-GOM2-1). These stepwise depressurization experiments monitored the pressure and temperature within the core storage chamber during each pressure step, or “shut-in” period to better understand dissociation behavior and to provide insight on the thermodynamic state of gas hydrate reservoirs during production. The pressure rebound that occurs in response to a depressurization step occurs more slowly during later dissociation steps, likely reflecting a slower heat transfer rate, decreasing salinity gradient, and increased compressibility of the pore and surrounding fluids with progressive dissociation. We demonstrate that displacement of water by gas within the core storage chamber during successive dissociations both insulates the core and increases the compressibility of the pore and chamber fluid. The increased compressibility requires that a larger hydrate volume dissociates per unit of pressure recovery. Pressures observed during progressive dissociation steps are lower than predicted by the sample’s average salinity, with pressures approaching the freshwater phase boundary during frequent dissociation steps, suggesting that local pore-water freshening strongly influences dissociation behavior. To avoid underestimating the magnitude of pressure drawdown required to sustain dissociation in the reservoir, we suggest that hydrate production models use the freshwater phase boundary rather than a phase boundary determined from bulk salinity.
","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/08182120216","usgsCitation":"Phillips, S.C., Flemings, P., You, K., and Waite, W., 2022, Thermodynamic insights into the production of methane hydrate reservoirs from depressurization of pressure cores: AAPG Bulletin, v. 106, no. 5, p. 1025-1049, https://doi.org/10.1306/08182120216.","productDescription":"25 p.","startPage":"1025","endPage":"1049","ipdsId":"IP-125570","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":400207,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Green Canyon Block 955 (GC 955) study area, northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96,\n 25\n ],\n [\n -88,\n 25\n ],\n [\n -88,\n 30\n ],\n [\n -96,\n 30\n ],\n [\n -96,\n 25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":842257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flemings, Peter B.","contributorId":242641,"corporation":false,"usgs":false,"family":"Flemings","given":"Peter B.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":842258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"You, Kehua","contributorId":239915,"corporation":false,"usgs":false,"family":"You","given":"Kehua","email":"","affiliations":[{"id":48038,"text":"Institute for Geophysics and Department of Geological Sciences, Jackson School of Geosciences, University of Texas","active":true,"usgs":false}],"preferred":false,"id":842259,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waite, William F. 0000-0002-9436-4109 wwaite@usgs.gov","orcid":"https://orcid.org/0000-0002-9436-4109","contributorId":625,"corporation":false,"usgs":true,"family":"Waite","given":"William F.","email":"wwaite@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":842260,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236587,"text":"70236587 - 2022 - Predicting flood damage probability across the conterminous United States","interactions":[],"lastModifiedDate":"2022-09-12T14:44:05.940487","indexId":"70236587","displayToPublicDate":"2022-02-01T09:26:20","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Predicting flood damage probability across the conterminous United States","docAbstract":"Floods are the leading cause of natural disaster damages in the United States, with billions of dollars incurred every year in the form of government payouts, property damages, and agricultural losses. The Federal Emergency Management Agency oversees the delineation of floodplains to mitigate damages, but disparities exist between locations designated as high risk and where flood damages occur due to land use and climate changes and incomplete floodplain mapping. We harnessed publicly available geospatial datasets and random forest algorithms to analyze the spatial distribution and underlying drivers of flood damage probability caused by excessive rainfall and overflowing water bodies across the conterminous United States. From this, we produced the first spatially complete map of flood damage probability for the nation, along with spatially explicit standard errors for four selected cities. We trained models using the locations of historical reported flood damage events (n = 71,434) and a suite of geospatial predictors (e.g., flood severity, climate, socio-economic exposure, topographic variables, soil properties, and hydrologic characteristics). We developed independent models for each hydrologic unit code level 2 watershed and generated a flood damage probability for each 100-m pixel. Our model classified damage or no damage with an average area under the curve accuracy of 0.75; however, model performance varied by environmental conditions, with certain land cover classes (e.g., forest) resulting in higher error rates than others (e.g., wetlands). Our results identified flood damage probability hotspots across multiple spatial and regional scales, with high probabilities common in both inland and coastal regions. The highest flood damage probabilities tended to be in areas of low elevation, in close proximity to streams, with extreme precipitation, and with high urban road density. Given rapid environmental changes, our study demonstrates an efficient approach for updating flood damage probability estimates across the nation.
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State University","active":true,"usgs":false}],"preferred":false,"id":851453,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sebastian, Antonia 0000-0002-4309-2561","orcid":"https://orcid.org/0000-0002-4309-2561","contributorId":296417,"corporation":false,"usgs":false,"family":"Sebastian","given":"Antonia","email":"","affiliations":[{"id":7043,"text":"University of North Carolina","active":true,"usgs":false}],"preferred":false,"id":851454,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meentemeyer, Ross K.","contributorId":179341,"corporation":false,"usgs":false,"family":"Meentemeyer","given":"Ross","email":"","middleInitial":"K.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":851455,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70229242,"text":"70229242 - 2022 - Action plan for restoration of coral reef coastal protection services: Case study example and workbook","interactions":[],"lastModifiedDate":"2022-03-03T14:52:52.979222","indexId":"70229242","displayToPublicDate":"2022-02-01T08:44:16","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":8915,"text":"EPA Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"EPA/600/R-21/306","title":"Action plan for restoration of coral reef coastal protection services: Case study example and workbook","docAbstract":"This report was prepared by the U.S. Environmental Protection Agency (USEPA), Office of Research and Development, as part of the Air, Climate and Energy (ACE) research program, with support from Tetra Tech, Inc., and in collaboration with the National Oceanic and Atmospheric Administration, the U.S. Geological Survey, and The Nature Conservancy. The ACE research program provides scientific information and tools to support USEPA’s commitment to clean air, clean water and sustainable natural resources, even as environmental conditions change. A key component of this is the development of sound science to support adaptation. Adaptation involves preparing for and adjusting to the effects of climate change and its interactions with other global and local stressors. Because these effects are diverse, interactive, and difficult to predict, adapting management of natural resources in this context can be very challenging.
Coral reefs—which provide valued ecosystem services such as fisheries, coastal protection, and tourism—are threatened by the effects of increased sea surface temperatures, sea level rise, and intensifying storms. These large-scale stressors are interacting with local stressors such as pollution, overfishing, and recreational misuse to drive ongoing and accelerating declines in coral reef ecosystems. Thus, there is a rising urgency to design and implement climate change adaptation measures that will enable reef resilience in the face of these changes. This includes accounting for, and adjusting to, the combined effects of climate change and local stressors in coral reef protection and restoration efforts.
The action plan, example case study, and workbook found in this report demonstrate a structured process for integrating climate-smart design considerations into restoration planning using A Manager’s Guide to Coral Reef Restoration Planning and Design. The focus is a hypothetical coral reef restoration project that has a goal of recovering nature-based coastal protection services using restoration interventions. The intent is to provide readers with a completed example of how to use the Guide workbook to inform a draft action plan, centering on the topic of coastal protection as a burgeoning area of interest in coral reef science and management communities. The information in this hypothetical case study is not intended for direct use; rather, it provides a starting point for more detailed planning that would occur in specific places. And while a full review of the current literature on reef restoration methods is outside the scope of this report, readers are encouraged to use the examples herein as well as in the Guide as a jumping-off point for exploring the rapidly growing body of information on methods, techniques, successes, failures, monitoring challenges and future directions of coral reef restoration in a changing world. The workbook, together with the action plan, can serve as a valuable record of the planning thought process as well as a living document for adaptive management, to be updated through time as improved information becomes available.
","language":"English","publisher":"Environmental Protection Agency","usgsCitation":"Courtney, C.A., West, J.M., Storlazzi, C.D., Viehman, T.S., Czaplinski, R., Hague, E., and Shaver, E.C., 2022, Action plan for restoration of coral reef coastal protection services: Case study example and workbook: EPA Report EPA/600/R-21/306, 73 p.","productDescription":"73 p.","ipdsId":"IP-130997","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":396697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396695,"type":{"id":11,"text":"Document"},"url":"https://cfpub.epa.gov/si/si_public_file_download.cfm?p_download_id=544353&Lab=CPHEA"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Courtney, Catherine A.","contributorId":287687,"corporation":false,"usgs":false,"family":"Courtney","given":"Catherine","email":"","middleInitial":"A.","affiliations":[{"id":61627,"text":"TetraTech, Inc.","active":true,"usgs":false}],"preferred":false,"id":837024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"West, Jordon M.","contributorId":287688,"corporation":false,"usgs":false,"family":"West","given":"Jordon","email":"","middleInitial":"M.","affiliations":[{"id":37230,"text":"EPA","active":true,"usgs":false}],"preferred":false,"id":837025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":837026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Viehman, T. Shay","contributorId":259297,"corporation":false,"usgs":false,"family":"Viehman","given":"T.","email":"","middleInitial":"Shay","affiliations":[{"id":16685,"text":"National Oceanic and Atmopheric Administration","active":true,"usgs":false}],"preferred":true,"id":837027,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Czaplinski, Richard","contributorId":287689,"corporation":false,"usgs":false,"family":"Czaplinski","given":"Richard","email":"","affiliations":[{"id":39152,"text":"TetraTech","active":true,"usgs":false}],"preferred":false,"id":837028,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hague, Erin","contributorId":287690,"corporation":false,"usgs":false,"family":"Hague","given":"Erin","email":"","affiliations":[{"id":39152,"text":"TetraTech","active":true,"usgs":false}],"preferred":false,"id":837029,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shaver, Elizabeth C.","contributorId":287691,"corporation":false,"usgs":false,"family":"Shaver","given":"Elizabeth","email":"","middleInitial":"C.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":837030,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70227733,"text":"sir20215139 - 2022 - Simulation of groundwater and surface-water resources of the San Antonio Creek Valley watershed, Santa Barbara County, California","interactions":[],"lastModifiedDate":"2026-04-08T16:30:38.872221","indexId":"sir20215139","displayToPublicDate":"2022-02-01T08:15:45","publicationYear":"2022","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":"2021-5139","displayTitle":"Simulation of Groundwater and Surface-Water Resources of the San Antonio Creek Valley Watershed, Santa Barbara County, California","title":"Simulation of groundwater and surface-water resources of the San Antonio Creek Valley watershed, Santa Barbara County, California","docAbstract":"In the San Antonio Creek Valley watershed (SACVW), western Santa Barbara County, California, groundwater is the primary source of water for agricultural irrigation, the town of Los Alamos, and supplemental water to Vandenberg Space Force Base (VSFB). Groundwater pumpage has increased since the 1970s as non-irrigated agricultural land has been converted to irrigated land and as local pumping for municipal use has increased. This increase in groundwater use has resulted in declining groundwater levels, adjustments in surface-water flows and species habitats, and changes in water quality. Water managers are addressing the challenges of meeting this increased demand while maintaining sustainable groundwater supplies. To address these challenges, Santa Barbara County Water Agency, Vandenberg Space Force Base (VSFB), and the U.S. Geological Survey (USGS) undertook a cooperative study to characterize the integrated hydrologic system of the SACVW and develop tools to better understand and manage the groundwater system. The objectives of this study were to improve the understanding of the integrated hydrologic system and incorporate the understanding into an integrated groundwater and surface-water flow model that can be used to help manage the water resources in the SACVW.
The San Antonio Creek integrated model (SACIM) was developed using the USGS coupled groundwater and surface-water flow model to simulate the hydrologic system of the SACVW and provide annual and average water budgets for 1948–2018 water years. Results from the SACIM indicated that between 1948 and 2018, total groundwater from storage (storage depletion) for the period was 453,300 acre-feet (acre-ft). Agricultural pumpage was the largest discharge and accounted for a total of 1,020,000 acre-ft of groundwater. Increased pumpage since the mid-1980s (of which agricultural pumpage is the primary component) is tied to an increased rate of storage depletion and reduced rates of groundwater evapotranspiration and surface leakage (groundwater discharge to the surface and soil zone). The increased pumpage also reduced subsurface inflow to Barka Slough, resulting in a decline in upward flow through the underlying hydrogeologic units and surface leakage. In addition to quantifying historical changes in the integrated hydrologic system, the SACIM is a tool than can be used by water managers to evaluate the effects of different climatic and hydrologic conditions and management strategies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215139","collaboration":"Prepared in cooperation with Santa Barbara County Water Agency and Vandenberg Space Force Base","programNote":"Groundwater Availability and Use Assessments","usgsCitation":"Woolfenden, L.R., Engott, J.A., Larsen, J.D., and Cromwell, G., 2022, Simulation of groundwater and surface-water resources of the San Antonio Creek Valley Watershed, Santa Barbara County, California: U.S. Geological Survey Scientific Investigations Report 2021–5139, 76 p., https://doi.org/10.3133/sir20215139.","productDescription":"Report: xii, 76 p.; Data Release","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-108916","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":502284,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112321.htm","linkFileType":{"id":5,"text":"html"}},{"id":394985,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5139/covrthb.png"},{"id":394986,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5139/sir20215139.pdf","text":"Report","size":"11 Mb","linkFileType":{"id":1,"text":"pdf"}},{"id":394989,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225001","text":"Scientific Investigations Report 2022–5001","linkHelpText":"- Hydrogeologic characterization of the San Antonio Creek Valley watershed, Santa Barbara County, California"},{"id":394984,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P960EOK8","linkHelpText":"GSFLOW model used to evaluate the groundwater and surface-water resources of the San Antonio Creek Valley watershed, Santa Barbara County, California"}],"country":"United States","state":"California","county":"Santa Barbara County","otherGeospatial":"San Antonio Creek Valley watershed,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.61889648437501,\n 34.37517887533528\n ],\n [\n -119.75,\n 34.37517887533528\n ],\n [\n -119.75,\n 35\n ],\n [\n -120.61889648437501,\n 35\n ],\n [\n -120.61889648437501,\n 34.37517887533528\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Predicting baseflow dynamics, protecting aquatic habitat, and managing legacy contaminants requires explicit characterization and prediction of groundwater discharge patterns throughout river networks. Using handheld thermal infrared (TIR) cameras, we surveyed 47 km of stream length across the Farmington River watershed (1,570 km2; CT and MA, USA), mapping locations of bank and waterline groundwater discharges based on their thermal signature. Using the observed groundwater discharge locations and predicted groundwater discharge rates from 6 variations of a numerical groundwater-flow model (MODFLOW-NWT), we compared 1) predicted groundwater-discharge rates in areas with and without observed groundwater discharge, 2) spatial patterns of observed and predicted groundwater discharge locations, and 3) density of observed groundwater discharge locations with predicted discharge rates. Five of six models reasonably predicted the spatial patterns of discharge locations along the 5th order mainstem, but fewer models predicted groundwater discharge patterns in smaller streams. Our results highlight 1) the feasibility of using TIR observations to evaluate groundwater models, 2) model parameters that influence discharge prediction accuracy (riverbed sediment and bedrock hydraulic conductivity and river-aquifer connections), and 3) current strengths and future opportunities for improved modeling of groundwater-discharge patterns.
Habitat alteration and destruction are primary drivers of biodiversity loss. However, the evolutionary dimensions of biodiversity loss remain largely unexplored in many systems. For example, little is known about how habitat alteration/loss can lead to phylogenetic deconstruction of ecological assemblages at the local level. That is, while species loss is evident, are some lineages favored over others? Using a long-term dataset of a globally, ecologically important guild of invertebrate consumers, stream leaf “shredders,” we created a phylogenetic tree of the taxa in the regional species pool, calculated mean phylogenetic distinctiveness for >1000 communities spanning >10 year period, and related species richness, phylogenetic diversity, and distinctiveness to watershed-scale impervious cover. Using a combination of changepoint and compositional analyses, we learned that increasing impervious cover produced marked reductions in all three measures of diversity. These results aid in understanding both phylogenetic diversity and mean assemblage phylogenetic distinctiveness. Our findings indicate that, not only are species lost when there is an increase in watershed urbanization, as other studies have demonstrated, but that those lost are members of more distinct lineages relative to the community as a whole.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.153595","usgsCitation":"Swan, C.M., Baker, M., Borowy, D., Johnson, A., Shcheglovitova, M., Sparkman, A., Neto, F.V., Van Appledorn, M., and Voelker, N., 2022, Loss of phylogenetic diversity under landscape change: Science of the Total Environment, v. 822, 153595, 8 p., https://doi.org/10.1016/j.scitotenv.2022.153595.","productDescription":"153595, 8 p.","ipdsId":"IP-123163","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":448976,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11603/24929","text":"External Repository"},{"id":396713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"822","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swan, Christopher M.","contributorId":265549,"corporation":false,"usgs":false,"family":"Swan","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":836946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baker, Matthew","contributorId":196362,"corporation":false,"usgs":false,"family":"Baker","given":"Matthew","affiliations":[],"preferred":false,"id":836947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borowy, Dorothy 0000-0002-2569-9757","orcid":"https://orcid.org/0000-0002-2569-9757","contributorId":287610,"corporation":false,"usgs":false,"family":"Borowy","given":"Dorothy","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":836948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Anna","contributorId":287611,"corporation":false,"usgs":false,"family":"Johnson","given":"Anna","email":"","affiliations":[{"id":52650,"text":"Pennsylvania Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":836949,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shcheglovitova, Mariya","contributorId":287612,"corporation":false,"usgs":false,"family":"Shcheglovitova","given":"Mariya","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":836950,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sparkman, April","contributorId":287614,"corporation":false,"usgs":false,"family":"Sparkman","given":"April","email":"","affiliations":[{"id":38069,"text":"University of Maryland, Baltimore County","active":true,"usgs":false}],"preferred":false,"id":836951,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neto, Francisco V.","contributorId":287617,"corporation":false,"usgs":false,"family":"Neto","given":"Francisco","email":"","middleInitial":"V.","affiliations":[{"id":61620,"text":"Laboratório de Ecologia, Instituto de Biociências","active":true,"usgs":false}],"preferred":false,"id":836952,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":836953,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Voelker, Nicole","contributorId":287619,"corporation":false,"usgs":false,"family":"Voelker","given":"Nicole","email":"","affiliations":[{"id":38069,"text":"University of Maryland, Baltimore County","active":true,"usgs":false}],"preferred":false,"id":836954,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70227800,"text":"sir20225001 - 2022 - Hydrogeologic characterization of the San Antonio Creek Valley watershed, Santa Barbara County, California","interactions":[],"lastModifiedDate":"2026-04-08T17:04:17.61002","indexId":"sir20225001","displayToPublicDate":"2022-01-31T11:06:53","publicationYear":"2022","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":"2022-5001","displayTitle":"Hydrogeologic Characterization of the San Antonio Creek Valley Watershed, Santa Barbara County, California","title":"Hydrogeologic characterization of the San Antonio Creek Valley watershed, Santa Barbara County, California","docAbstract":"The San Antonio Creek Valley watershed (SACVW) is located in western Santa Barbara County, about 15 miles south of Santa Maria and 55 miles north of Santa Barbara, California. The SACVW is about 135 square miles and encompasses the San Antonio Creek Valley groundwater basin; the SACVW is separated from adjacent groundwater basins by the Casmalia and Solomon Hills to the north, and the Purisima Hills to the south. At the western, downstream part of the valley, uplifted, consolidated rocks cause groundwater to discharge at land surface at Barka Slough. Since the late 1800s, groundwater has been the primary source of water for agricultural, military, municipal, and domestic uses. Groundwater withdrawal by pumping exceeded the amount of water replenishing the aquifer system during water years 1948–2018, causing groundwater-level declines of more than 150 feet in parts of the valley and reducing base flow at Barka Slough. Reliance on groundwater for agricultural water use (primarily for the irrigation and frost protection of vineyards, and fruit and berry crops) continues to strain the sustainability of the groundwater system.
Through a cooperative agreement, the Santa Barbara County Water Agency and Vandenberg Space Force Base invited the U.S. Geological Survey to address declines in groundwater levels, develop a better understanding of the hydrogeologic system, and provide tools to help evaluate and manage the effects of future development of the San Antonio Creek Valley groundwater basin within the encompassing San Antonio Creek Valley watershed (SACVW). The objectives of this study were to (1) refine the hydrogeologic framework of the San Antonio Creek Valley watershed, (2) quantify the hydrologic budget of the valley, and (3) develop hydrologic modeling tools to evaluate and aid in managing the groundwater resource. This report focuses on the first and second objectives to construct a hydrogeologic framework and characterize the historical and present-day hydrologic conditions of the SACVW during water years 1948–2018. As part of the second objective, work included quantifying the hydrologic budget and evaluating the hydrogeologic system using a combination of existing data and geologic and hydrologic data collected for this study.
The groundwater-flow system in the SACVW consists of five hydrogeologic units. These separate water-bearing units were identified based on hydrogeologic properties, such as sediment grain size, vertical-head differences in multiple-depth, monitoring-well sites, long-term groundwater level responses to pumping and climate, and the chemical character of groundwater and groundwater age in the mostly semi-consolidated to unconsolidated basin-fill sediments. The hydrogeologic units that comprise the different aquifers vary in their lithologic composition. The upper and lower aquifers (upper Paso Robles Formation, and lower Paso Robles Formation and Careaga Sandstone, respectively) are relatively coarse grained and are comprised of sand, gravel, and clay; the middle confining unit (the middle Paso Robles Formation) is relatively fine grained and is comprised of primarily clay, silt, and sand. The Pezzoni-Casmalia and Los Alamos faults, which are inferred to transect the SACVW between the western and eastern areas of the valley floor, do not appear to substantially affect the groundwater system.
Present-day recharge to the study area occurs primarily as infiltration from precipitation and streams in the upland areas of the Casmalia Hills and Solomon Hills, and along the main channel of San Antonio Creek. Reported estimates of annual natural recharge during water years 1948–2018 generally ranged from about 5,000 acre-feet to more than about 30,000 acre-feet. Stable and radioactive isotopes show that groundwater from the lower aquifer is old and probably was recharged as infiltration from precipitation and streams in the eastern upland areas of the Solomon Hills; however, the infiltration and recharge from these sources probably does not occur under present-day climatic conditions. Anthropogenic recharge, from sources such as return flow from agricultural irrigation, municipal water systems, and wastewater effluent, was estimated to range from about 600 acre-feet in 1948 to about 6,600 acre-feet in 2018. The average annual amount of groundwater removed from the SACVW by pumping during 1948–2018 was estimated to be about 17,200 acre-feet per year, increasing from about 3,000 acre-feet in 1948 to about 32,600 acre-feet in 2018. Estimates of annual pumpage generally exceeded estimates of annual recharge beginning in the mid-1970s and continuing through 2018. The predominant direction of groundwater flow under historical and present-day conditions was from the eastern uplands in the Solomon Hills to the west along San Antonio Creek to the discharge area in Barka Slough, and from the northern uplands in the Casmalia Hills south to San Antonio Creek.
Pumpage since the early 1900s and the subsequent groundwater-level declines have substantially reduced the amount of natural groundwater discharge at Barka Slough. Estimates of base flow to San Antonio Creek at the western, downstream extent of the SACVW have varied over time in response to changes in groundwater pumpage and climate; however, there was an overall decline in base flow during water years 1956–2018, decreasing from an average of about 1,700 acre-feet per year during 1956–69, to about 300 acre-feet per year during 2016–18. The long-term extraction of groundwater correlates with a decrease in groundwater levels by more than about 150 feet since the early 1940s in the eastern part of the basin near Los Alamos, and as much as about 50 feet in the upland areas and in the western part of the basin. At Barka Slough, groundwater levels have declined below land surface in some places, altering native riparian vegetation in and around the slough.
Surface-water quality in the SACVW varied depending on location and the time of year the samples were collected and on the amount of annual precipitation Most groundwater in the SACVW was calcium-bicarbonate-type water with total dissolved-solids concentrations of about 500–800 milligrams per liter generally representing water naturally recharged as infiltration from precipitation and streams. Total dissolved-solids concentrations in some wells ranged from 800 to 8,000 milligrams per liter, suggesting mixing of naturally recharged infiltrated water with water associated with oil-bearing geologic formations, agricultural products, or the evaporation of shallow groundwater. Concentrations of total dissolved solids and the chemical constituents chloride, nitrate plus nitrite (as nitrogen), calcium, and magnesium at selected wells generally increased during water years 1980–2018; increasing concentrations of these constituents may be associated with the expansion of agriculture in the watershed over time and the corresponding increase in the use of nitrates and calcium- and magnesium-based fertilizers and soil additives in modern agricultural practices.
The predominant direction of groundwater flow during historical and present-day conditions was from the eastern uplands in the Solomon Hills to the west along San Antonio Creek toward Barka Slough, and from the western uplands in the Casmalia Hills south to San Antonio Creek. The age of groundwater in the SACVW was evaluated using radioactive isotopes, and the flow of groundwater within the SACVW was evaluated using radioactive and stable isotopes. Modern groundwater (recharged after 1952) was generally found adjacent to San Antonio Creek and its tributaries in wells with perforated depths that averaged about 270 feet below land surface. Pre-modern groundwater (recharged before 1952) was found in wells that had average perforation depths of about 540 ft below land surface. Pre-modern groundwater identified in wells in the eastern upland area is interpreted to have had long, slow travel times to the western part of the SACVW where it was eventually discharged as base flow at Barka Slough or extracted as groundwater pumpage.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225001","collaboration":"Prepared in cooperation with Santa Barbara County Water Agency and Vandenberg Space Force Base","programNote":"Groundwater Availability and Use Assessments","usgsCitation":"Cromwell, G., Sweetkind, D.S., Densmore, J.N., Engott, J.A., Seymour, W.A., Larsen, J.D., Ely, C.P., Stamos, C.L., and Faunt, C.C., 2022, Hydrogeologic characterization of the San Antonio Creek Valley watershed, Santa Barbara County, California: U.S. Geological Survey Scientific Investigations Report 2022–5001, 124 p., https://doi.org/10.3133/sir20225001.","productDescription":"Report: xiv, 124 p.; Data Release","numberOfPages":"124","onlineOnly":"Y","ipdsId":"IP-106483","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":395163,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5001/images"},{"id":395162,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5001/sir20225001.xml"},{"id":502288,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112320.htm","linkFileType":{"id":5,"text":"html"}},{"id":395158,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AD7DL8","linkHelpText":"Data release of hydrogeologic data from the San Antonio Creek Valley watershed, Santa Barbara County, California"},{"id":395161,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5001/sir20225001.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":395160,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5001/covrthb.jpg"}],"country":"United States","state":"California","county":"Santa Barbara County","otherGeospatial":"San Antonio Creek Valley watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.50079345703125,\n 34.71113805795655\n ],\n [\n -120.09292602539062,\n 34.71113805795655\n ],\n [\n -120.09292602539062,\n 34.854382885097905\n ],\n [\n -120.50079345703125,\n 34.854382885097905\n ],\n [\n -120.50079345703125,\n 34.71113805795655\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The objectives of the study are to (1) develop an updated assessment of the hydrogeology and geochemistry of the Petaluma valley watershed (PVW) and (2) develop an integrated hydrologic model for the PVW. The purpose of this report is to describe the conceptual model of the hydrologic, hydrogeologic, and water-quality characteristics of the PVW and a numerical groundwater-flow model of PVW.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225009","collaboration":"Prepared in cooperation with the Sonoma County Water Agency and the City of Petaluma","programNote":"Water Availability and Use Science Program","usgsCitation":"Traum, J.A., Teague, N.F., Sweetkind, D.S., and Nishikawa, T., 2022, Hydrologic and geochemical characterization of the Petaluma River watershed, Sonoma County, California: U.S. Geological Survey Scientific Investigations Report 2022–5009, 217 p., https://doi.org/10.3133/sir20225009.","productDescription":"Report: xviii, 217 p.; Executive Summmary: 5 p.; 4 Data Releases","numberOfPages":"217","onlineOnly":"Y","ipdsId":"IP-081057","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":395150,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IRYFMB","linkHelpText":"Selected chemical and physical properties and inorganic constituents and time-series nitrate in samples from selected wells and/or springs, Petaluma Valley watershed, Sonoma County, California, 1959–2015"},{"id":395149,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NL90P8","linkHelpText":"Data release of three-dimensional hydrogeologic framework model of the Petaluma Valley watershed, Sonoma County, California"},{"id":395146,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IQDHIT","linkHelpText":"Petaluma Model GIS Data"},{"id":395147,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P965IDQZ","linkHelpText":"MODFLOW-OWHM used to characterize the flow system of the Petaluma River watershed, Sonoma County, California"},{"id":395154,"rank":8,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5009/images"},{"id":395153,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5009/sir20225009.xml"},{"id":395166,"rank":9,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5009/sir20225009_execSummary.pdf","text":"Executive Summary","size":"200 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Full Executive Summary from this report"},{"id":395151,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5009/covrthb.png"},{"id":395152,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5009/sir20225009.pdf","text":"Report","size":"130 MB"},{"id":502296,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112319.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","county":"Sonoma County","otherGeospatial":"Petaluma River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.44674682617188,\n 38.11943249695316\n ],\n [\n -122.61428833007814,\n 38.37503882134334\n ],\n [\n -122.74887084960936,\n 38.361041528596026\n ],\n [\n -122.77359008789062,\n 38.293170153420135\n ],\n [\n -122.728271484375,\n 38.19718009396176\n ],\n [\n -122.48382568359374,\n 38.07187927827001\n ],\n [\n -122.44674682617188,\n 38.11943249695316\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Climate change is transforming ecosystems and affecting ecosystem goods and services. Along the Gulf of Mexico and Atlantic coasts of the southeastern United States, the frequency and intensity of extreme freeze events greatly influences whether coastal wetlands are dominated by freeze-sensitive woody plants (mangrove forests) or freeze-tolerant grass-like plants (salt marshes). In response to warming winters, mangroves have been expanding and displacing salt marshes at varying degrees of severity in parts of north Florida, Louisiana, and Texas. As winter warming accelerates, mangrove range expansion is expected to increasingly modify wetland ecosystem structure and function. Because there are differences in the ecological and societal benefits that salt marshes and mangroves provide, coastal environmental managers are challenged to anticipate effects of mangrove expansion on critical wetland ecosystem services, including those related to carbon sequestration, wildlife habitat, storm protection, erosion reduction, water purification, fisheries support, and recreation. Mangrove range expansion may also affect wetland stability in the face of extreme climatic events and rising sea levels. Here, we review current understanding of the effects of mangrove range expansion and displacement of salt marshes on wetland ecosystem services in the southeastern United States. We also identify critical knowledge gaps and emerging research needs regarding the ecological and societal implications of salt marsh displacement by expanding mangrove forests. One consistent theme throughout our review is that there are ecological trade-offs for consideration by coastal managers. Mangrove expansion and marsh displacement can produce beneficial changes in some ecosystem services, while simultaneously producing detrimental changes in other services. Thus, there can be local-scale differences in perceptions of the impacts of mangrove expansion into salt marshes. For very specific local reasons, some individuals may see mangrove expansion as a positive change to be embraced, while others may see mangrove expansion as a negative change to be constrained.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16111","usgsCitation":"Osland, M., Hughes, A.R., Armitage, A.R., Scyphers, S.B., Cebrian, J., Swinea, S.H., Shepard, C., Allen, M.S., Feher, L., Nelson, J., O’Brien, C.L., Sanspree, C.R., Smee, D.L., Snyder, C.M., Stetter, A.P., Stevens, P.W., Swanson, K., Williams, L.H., Brush, J.M., Marchionno, J., and Bardou, R., 2022, The impacts of mangrove range expansion on wetland ecosystem services in the southeastern United States: Current understanding, knowledge gaps, and emerging research needs: Global Change Biology, v. 28, no. 10, p. 3163-3187, https://doi.org/10.1111/gcb.16111.","productDescription":"25 p.","startPage":"3163","endPage":"3187","ipdsId":"IP-132601","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":467202,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/43126","text":"External Repository"},{"id":395545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.12890625,\n 17.14079039331665\n ],\n [\n -79.1015625,\n 17.14079039331665\n ],\n [\n -79.1015625,\n 33.284619968887675\n ],\n [\n -102.12890625,\n 33.284619968887675\n ],\n [\n -102.12890625,\n 17.14079039331665\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Osland, Michael 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":219805,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":833324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hughes, A. 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Louisiana at Lafayette, Lafayette, LA USA","active":true,"usgs":false}],"preferred":false,"id":833333,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"O’Brien, Cherie L.","contributorId":274815,"corporation":false,"usgs":false,"family":"O’Brien","given":"Cherie","email":"","middleInitial":"L.","affiliations":[{"id":56660,"text":"Texas Parks and Wildlife Department, Dickinson, TX USA, 9U.S. Fish and Wildlife Service, Austwell, TX USA","active":true,"usgs":false}],"preferred":false,"id":833334,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sanspree, Colt R.","contributorId":274816,"corporation":false,"usgs":false,"family":"Sanspree","given":"Colt","email":"","middleInitial":"R.","affiliations":[{"id":56661,"text":"U.S. Fish and Wildlife Service, Austwell, TX USA","active":true,"usgs":false}],"preferred":false,"id":833335,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Smee, Delbert L.","contributorId":274817,"corporation":false,"usgs":false,"family":"Smee","given":"Delbert","email":"","middleInitial":"L.","affiliations":[{"id":39936,"text":"Dauphin Island Sea Lab, Dauphin Island, AL USA","active":true,"usgs":false}],"preferred":false,"id":833336,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Snyder, Caitlin M.","contributorId":218921,"corporation":false,"usgs":false,"family":"Snyder","given":"Caitlin","email":"","middleInitial":"M.","affiliations":[{"id":39940,"text":"Apalachicola National Estuarine Research Reserve, Eastpoint, FL USA","active":true,"usgs":false}],"preferred":false,"id":833337,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Stetter, Andrew P.","contributorId":274818,"corporation":false,"usgs":false,"family":"Stetter","given":"Andrew","email":"","middleInitial":"P.","affiliations":[{"id":56661,"text":"U.S. Fish and Wildlife Service, Austwell, TX 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USA","active":true,"usgs":false}],"preferred":false,"id":833344,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70227735,"text":"sir20215098 - 2022 - Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, August 2019, August 2020, and October 2020","interactions":[],"lastModifiedDate":"2026-04-02T19:39:16.740242","indexId":"sir20215098","displayToPublicDate":"2022-01-31T10:11:35","publicationYear":"2022","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":"2021-5098","displayTitle":"Bathymetric and Velocimetric Surveys at Highway Bridges Crossing the Missouri River near Kansas City, Missouri, August 2019, August 2020, and October 2020","title":"Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, August 2019, August 2020, and October 2020","docAbstract":"Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, near 9 bridges at 8 highway crossings of the Missouri River near Kansas City, Missouri, on August 13–14, 2019. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches about 1,550 to 1,660 feet longitudinally and generally extending laterally across the active channel from bank to bank during moderate flood-flow conditions. These surveys indicated the channel conditions at the time of the surveys and provided characteristics of scour holes that may be useful in developing predictive guidelines or equations for scour holes. These data also may be useful to the Missouri Department of Transportation as a low to moderate flood-flow assessment of the bridges for stability and integrity issues with respect to bridge scour during floods.
Bathymetric data were collected around every pier that was in water, except around the nose of one pier that was surrounded by a persistent debris raft. Scour holes were present at most piers for which bathymetry could be obtained, except those on banks or surrounded by riprap. The observed scour holes at the surveyed bridges generally were examined with respect to shape and depth.
Comparisons between bathymetric surfaces from previous surveys and this study do not indicate any consistent correlation in channel-bed elevations with streamflow conditions at the times of the surveys. The predominant overall scour observed between the various surveys implies the channel bed in the 2019 surveys might have been rebounding from more substantial scour caused by the high streamflow earlier in March and June 2019, which was the highest streamflow since 1993. Pier size and nose shape had a substantial effect on the size of the scour hole observed at a given pier. Many of the piers at the Kansas City area bridges have wide or blunt noses caused by exposed footings, seal courses, or caissons, which resulted in large, deep scour holes at most piers. Several of the structures had piers that were skewed to primary approach flow; and, at most of the structures, the scour hole was deeper and longer on the side of the pier with impinging flow than the leeward side, with some amount of deposition on the leeward side, as typically has been observed at piers skewed to approach flow.
Limited additional bathymetric data were collected by the U.S. Geological Survey, in cooperation with Clarkson Construction, near the main channel piers of the U.S. Highway 169 (Broadway) and the Interstate 435 (Randolph) bridges on August 17 and October 23, 2020, to determine the channel-bed conditions before and after installation of scour countermeasures near those piers. Survey results from before and after installation of these countermeasures show these features had a substantial effect on mitigating the observed scour at these piers, particularly when compared to piers at other sites without such features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215098","collaboration":"Prepared in cooperation with the Missouri Department of Transportation and Clarkson Construction","usgsCitation":"Huizinga, R.J., 2022, Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, August 2019, August 2020, and October 2020: U.S. Geological Survey Scientific Investigations Report 2021–5098, 112 p., https://doi.org/10.3133/sir20215098.","productDescription":"Report: xii, 112 p.; Data Release; Dataset","numberOfPages":"128","onlineOnly":"Y","ipdsId":"IP-124626","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":395010,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96TX8AE","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Bathymetry and velocity data from surveys at highway bridges crossing the Missouri River in Kansas City, Missouri, in August 2019, August 2020, and October 2020"},{"id":395008,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5098/coverthb.jpg"},{"id":395013,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5098/images"},{"id":395012,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5098/sir20215098.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2021–5098 XML"},{"id":395011,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":395009,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5098/sir20215098.pdf","text":"Report","size":"38.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5098"},{"id":502114,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112326.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Missouri","city":"Kansas City","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.68086242675781,\n 39.102357437817595\n ],\n [\n -94.48722839355467,\n 39.102357437817595\n ],\n [\n -94.48722839355467,\n 39.193948213963665\n ],\n [\n -94.68086242675781,\n 39.193948213963665\n ],\n [\n -94.68086242675781,\n 39.102357437817595\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Tidal wetlands provide myriad ecosystem services across local to global scales. With their uncertain vulnerability or resilience to rising sea levels, there is a need for mapping flooding drivers and vulnerability proxies for these ecosystems at a national scale. However, tidal wetlands in the conterminous USA are diverse with differing elevation gradients, and tidal amplitudes, making broad geographic comparisons difficult. To address this, a national-scale map of relative tidal elevation (Z*MHW), a physical metric that normalizes elevation to tidal amplitude at mean high water (MHW), was constructed for the first time at 30 × 30-m resolution spanning the conterminous USA. Contrary to two study hypotheses, watershed-level median Z*MHW and its variability generally increased from north to south as a function of tidal amplitude and relative sea-level rise. These trends were also observed in a reanalysis of ground elevation data from the Pacific Coast by Janousek et al. (Estuaries and Coasts 42 (1): 85–98, 2019). Supporting a third hypothesis, propagated uncertainty in Z*MHW increased from north to south as light detection and ranging (LiDAR) errors had an outsized effect under narrowing tidal amplitudes. The drivers of Z*MHW and its variability are difficult to determine because several potential causal variables are correlated with latitude, but future studies could investigate highest astronomical tide and diurnal high tide inequality as drivers of median Z*MHW and Z*MHW variability, respectively. Watersheds of the Gulf Coast often had propagated Z*MHW uncertainty greater than the tidal amplitude itself emphasizing the diminished practicality of applying Z*MHW as a flooding proxy to microtidal wetlands. Future studies could focus on validating and improving these physical map products and using them for synoptic modeling of tidal wetland carbon dynamics and sea-level rise vulnerability analyses.
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The purpose of the IOOC is to advise, assist, and make recommendations to the SOST on matters related to ocean observations via task teams such as the Biology - Integrating Core to Essential Variables (Bio-ICE) task team. The goal of the Bio-ICE task team is to advance the integration of biological observations from local, regional, and federal sources using best practices to inform national needs and ultimately feed seamlessly into the Global Ocean Observing System (GOOS), as appropriate. To accomplish this goal, and for the first time at the U.S. federal government level, a subgroup of the Bio-ICE task team focused on tropical, shallow-water (0-30 m) hard corals to identify commonalities between the U.S. Integrated Ocean Observing System (IOOS) core biological variable1 of “coral species and abundance,” the GOOS Essential Ocean Variable2 (EOV) “hard coral cover and composition,” the Group on Earth Observations Biological Observation Network (GEO BON) Essential Biodiversity Variables3 (EBVs), and the Global Climate Observing System (GCOS) Essential Climate Variables4 (ECVs) (Figure 1). The EOV data allows production of EBVs such as time series of maps of genetic composition, species populations, etc. Recognizing the complementarity of the different essential variable frameworks helps to promote best practices in observing and information management to facilitate data interoperability (Figure 1). The task team was charged with identifying where there are synergies in terms of spatial and temporal observing requirements and existing observation infrastructure and data delivery, including best practices and standard operating procedures. The task team also made suggestions to improve pathways for data flow for observations of these variables from Regional Associations of the U.S. IOOS, other nonfederal partners, and federal sources. The focus of the task team was on identifying and implementing best practices surrounding standardized data collection and data delivery to make continued progress toward adhering to the Findability, Accessibility, Interoperability, and Reuse (FAIR) and Collective benefit, Authority to control, Responsibility, and Ethics (CARE) data principles.
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- Typology development of earthquake displays in free-choice learning environments, to inform earthquake early warning education in the United States","interactions":[],"lastModifiedDate":"2022-04-05T14:48:51.971088","indexId":"70230236","displayToPublicDate":"2022-01-29T09:46:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"Typology development of earthquake displays in free-choice learning environments, to inform earthquake early warning education in the United States","docAbstract":"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.
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2022 - Condition of macroinvertebrate communities in the Buffalo River Area of Concern following sediment remediation","interactions":[],"lastModifiedDate":"2022-02-01T17:43:25.670538","indexId":"70227859","displayToPublicDate":"2022-01-28T11:37:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Condition of macroinvertebrate communities in the Buffalo River Area of Concern following sediment remediation","docAbstract":"The lower 10 km of the Buffalo River, a tributary to Lake Erie, was designated as an Area of Concern (AOC) in 1987 through the Great Lakes Water Quality Agreement because sediment contamination and habitat alteration from past industrialization caused several Beneficial Use Impairments (BUIs). Extensive remediation efforts conducted between 2011 and 2015 removed approximately 688,100 cubic meters of contaminated sediment from the Buffalo River AOC, and subsequent chemical analysis of sediments indicated that most remedial goals had been achieved. Benthic macroinvertebrate communities and sediment toxicity were evaluated in the AOC and an upstream reference area in 2017 and 2020 to determine whether remediation has improved benthic conditions sufficiently that the benthos BUI designation can be removed. Community condition was characterized using the New York State multi-metric index of biological integrity and bed sediments were used for 10-day toxicity tests with Chironomus dilutus and Hyalella azteca. Macroinvertebrate communities were classified as moderately to slightly impacted at most AOC sites compared to slightly impacted at most reference sites, but toxicity tests did not identify any evidence of toxicity in sediments from the AOC. A linear mixed effects model indicated that total organic carbon concentration in sediments, distance upstream from the river mouth, and the relative dominance of zebra mussels Dreissena polymorpha were the primary predictors of macroinvertebrate community condition. These findings are consistent with those from other AOCs in New York which indicate that contemporary benthic communities are generally shaped by legacy habitat alterations rather than AOC-specific sediment contamination and toxicity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.11.002","usgsCitation":"George, S.D., Duffy, B.T., Baldigo, B., Skaros, D., and Smith, A., 2022, Condition of macroinvertebrate communities in the Buffalo River Area of Concern following sediment remediation: Journal of Great Lakes Research, v. 48, no. 1, p. 183-194, https://doi.org/10.1016/j.jglr.2021.11.002.","productDescription":"12 p.","startPage":"183","endPage":"194","ipdsId":"IP-129186","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":449003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2021.11.002","text":"Publisher Index Page"},{"id":395221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Buffalo River area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.87908935546874,\n 42.83015652099459\n ],\n [\n -78.74862670898438,\n 42.83015652099459\n ],\n [\n -78.74862670898438,\n 42.895585521720584\n ],\n [\n -78.87908935546874,\n 42.895585521720584\n ],\n [\n -78.87908935546874,\n 42.83015652099459\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"48","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"George, Scott D. 0000-0002-8197-1866 sgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-8197-1866","contributorId":3014,"corporation":false,"usgs":true,"family":"George","given":"Scott","email":"sgeorge@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duffy, Brian T.","contributorId":272971,"corporation":false,"usgs":false,"family":"Duffy","given":"Brian","email":"","middleInitial":"T.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":832427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldigo, Barry P. 0000-0002-9862-9119","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":25174,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":832428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skaros, Damianos","contributorId":272972,"corporation":false,"usgs":false,"family":"Skaros","given":"Damianos","email":"","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":832429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Alexander J.","contributorId":140345,"corporation":false,"usgs":false,"family":"Smith","given":"Alexander J.","affiliations":[{"id":13464,"text":"Environmental Analyst, NY State Dept of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":832430,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228048,"text":"70228048 - 2022 - Assessing effects of sediment delivery to coral reefs: A Caribbean watershed perspective","interactions":[],"lastModifiedDate":"2022-02-03T14:36:45.836573","indexId":"70228048","displayToPublicDate":"2022-01-28T08:33:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Assessing effects of sediment delivery to coral reefs: A Caribbean watershed perspective","docAbstract":"Coral reefs in the western Atlantic and Caribbean are deteriorating primarily from disease outbreaks, increasing seawater temperatures, and stress due to land-based sources of pollutants including sediments associated with land use and dredging. Sediments affect corals in numerous ways including smothering, abrasion, shading, and inhibition of coral recruitment. Sediment delivery resulting in deposition and water quality deterioration can cause degradation at the spatial scale of corals or entire reefs. We still lack rigorous long-term studies of coral cover and community composition before, during and after major sediment stress, and evidence of recovery after watershed management actions. Here we present an overview of the effects of terrestrial sediments on corals and coral reefs, with recent advances in approaches to watershed assessment relevant to the delivery of sediments to these ecosystems. We present case studies of northeastern Caribbean watersheds to illustrate challenges and possible solutions and to draw conclusions about the current state of knowledge of sediment effects on coral reefs. With a better understanding of erosion and the pathways of sediment discharge to nearshore reefs, there is the increased potential for management interventions.
","language":"English","publisher":"Frontiers Media S.A.","doi":"10.3389/fmars.2021.773968","usgsCitation":"Rogers, C., and Ramos-Scharron, C.E., 2022, Assessing effects of sediment delivery to coral reefs: A Caribbean watershed perspective: Frontiers in Marine Science, v. 8, 773968, 23 p., https://doi.org/10.3389/fmars.2021.773968.","productDescription":"773968, 23 p.","ipdsId":"IP-127009","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":449009,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2021.773968","text":"Publisher Index Page"},{"id":395343,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2022-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Rogers, Caroline 0000-0001-9056-6961","orcid":"https://orcid.org/0000-0001-9056-6961","contributorId":223023,"corporation":false,"usgs":true,"family":"Rogers","given":"Caroline","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":832964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramos-Scharron, Carlos E.","contributorId":274400,"corporation":false,"usgs":false,"family":"Ramos-Scharron","given":"Carlos","email":"","middleInitial":"E.","affiliations":[{"id":36422,"text":"University of Texas","active":true,"usgs":false}],"preferred":false,"id":832965,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70239879,"text":"70239879 - 2022 - Loss of street trees causes 10,000 L/tree increase in leaf-on stormwater runoff for Great Lakes urban sewershed","interactions":[],"lastModifiedDate":"2023-01-26T17:09:03.944568","indexId":"70239879","displayToPublicDate":"2022-01-28T07:17:13","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Loss of street trees causes 10,000 L/tree increase in leaf-on stormwater runoff for Great Lakes urban sewershed","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"UDM 2022","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th Urban Drainage Modeling Conference","conferenceDate":"January 10-12, 2022","conferenceLocation":"Costa Mesa, California","language":"English","publisher":"Urban Drainage Modeling Conference Committee","usgsCitation":"Coville, R.C., Kruegler, J., Selbig, W.R., Hirabayashi, S., Loheide, S.P., Avery, W., Schuster, W., Haefner, R.J., Scharenbroch, B.C., Endreny, T.A., and Nowak, D., 2022, Loss of street trees causes 10,000 L/tree increase in leaf-on stormwater runoff for Great Lakes urban sewershed, in UDM 2022, Costa Mesa, California, January 10-12, 2022, 3 p.","productDescription":"3 p.","ipdsId":"IP-132935","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":412371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412370,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://udm2022.org/published-abstracts/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wisconsin","city":"Fond du Lac","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.52025425737595,\n 43.813053208246004\n ],\n [\n -88.52025425737595,\n 43.69340679691314\n ],\n [\n -88.39255354403629,\n 43.69340679691314\n ],\n [\n -88.39255354403629,\n 43.813053208246004\n ],\n [\n -88.52025425737595,\n 43.813053208246004\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coville, Robert C. 0000-0002-6895-2564","orcid":"https://orcid.org/0000-0002-6895-2564","contributorId":269851,"corporation":false,"usgs":false,"family":"Coville","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":40823,"text":"Davey Institute","active":true,"usgs":false}],"preferred":false,"id":862557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kruegler, James 0000-0002-2671-0807","orcid":"https://orcid.org/0000-0002-2671-0807","contributorId":269853,"corporation":false,"usgs":false,"family":"Kruegler","given":"James","email":"","affiliations":[{"id":40823,"text":"Davey Institute","active":true,"usgs":false}],"preferred":false,"id":862558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862257,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hirabayashi, Satoshi","contributorId":301162,"corporation":false,"usgs":false,"family":"Hirabayashi","given":"Satoshi","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":862559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loheide, Steven P. II","contributorId":62377,"corporation":false,"usgs":false,"family":"Loheide","given":"Steven","suffix":"II","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":862560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Avery, William 0000-0002-2651-9906","orcid":"https://orcid.org/0000-0002-2651-9906","contributorId":269858,"corporation":false,"usgs":false,"family":"Avery","given":"William","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":862561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schuster, William","contributorId":117899,"corporation":false,"usgs":true,"family":"Schuster","given":"William","email":"","affiliations":[],"preferred":false,"id":862562,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haefner, Ralph J. 0000-0002-4363-9010 rhaefner@usgs.gov","orcid":"https://orcid.org/0000-0002-4363-9010","contributorId":1793,"corporation":false,"usgs":true,"family":"Haefner","given":"Ralph","email":"rhaefner@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862563,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scharenbroch, Bryant C. 0000-0002-9342-7550","orcid":"https://orcid.org/0000-0002-9342-7550","contributorId":269849,"corporation":false,"usgs":false,"family":"Scharenbroch","given":"Bryant","email":"","middleInitial":"C.","affiliations":[{"id":17613,"text":"University of Wisconsin - Stevens Point","active":true,"usgs":false}],"preferred":false,"id":862564,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Endreny, Theodore A.","contributorId":195489,"corporation":false,"usgs":false,"family":"Endreny","given":"Theodore","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":862565,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Nowak, David J.","contributorId":171616,"corporation":false,"usgs":false,"family":"Nowak","given":"David J.","affiliations":[],"preferred":false,"id":862566,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70227702,"text":"ofr20211123 - 2022 - Optimization of salt marsh management at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex, Maine, through use of structured decision making","interactions":[],"lastModifiedDate":"2026-03-25T17:53:23.031994","indexId":"ofr20211123","displayToPublicDate":"2022-01-27T12:50:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1123","displayTitle":"Optimization of Salt Marsh Management at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex, Maine, Through Use of Structured Decision Making","title":"Optimization of salt marsh management at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex, Maine, through use of structured decision making","docAbstract":"Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex in Maine. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of two marsh management units within the refuge complex, totaling about 47 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to $9,545, and may continue to increase at a lower rate with further expenditures. Potential management actions in optimal portfolios at total costs less than or equal to $9,545 included removing dikes to restore tidal flow in the Gouldsboro Bay management unit and installing runnels to improve surface-water drainage in the Sawyers Marsh management unit. The potential management benefits were derived from expected increases in the numbers of tidal marsh obligate breeding birds and density of spiders (as an indicator of trophic health), reduced duration of flooding, and increased capacity of marsh elevation to keep pace with sea-level rise. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Maine Coastal Islands National Wildlife Refuge Complex that can be updated for implementation as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge complex.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211123","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., and Williams, S., 2022, Optimization of salt marsh management at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex, Maine, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1123, 27 p., https://doi.org/10.3133/ofr20211123.","productDescription":"Report: vi, 27 p.; Database","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135555","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501535,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112158.htm","linkFileType":{"id":5,"text":"html"}},{"id":394950,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://ecos.fws.gov/ServCat/Reference/Profile/121918","text":"U.S. Fish and Wildlife Service database","linkHelpText":"- Salt marsh integrity and Hurricane Sandy vegetation, bird and nekton data"},{"id":394949,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1123/images/"},{"id":394948,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1123/ofr20211123.XML"},{"id":394947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1123/ofr20211123.pdf","text":"Report","size":"3.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1123"},{"id":394946,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1123/coverthb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Petit Manan National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.0438232421875,\n 44.36902359940364\n ],\n [\n -67.64556884765625,\n 44.36902359940364\n ],\n [\n -67.64556884765625,\n 44.570415145955515\n ],\n [\n -68.0438232421875,\n 44.570415145955515\n ],\n [\n -68.0438232421875,\n 44.36902359940364\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey in cooperation with the Providence Water Supply Board collected streamflow and water-quality data at the Scituate Reservoir and tributaries. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance were used to calculate loads of chloride and sodium during water year 2019 (October 1, 2018, through September 30, 2019) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected by the Providence Water Supply Board at 37 sampling stations, which also include the 14 continuous-record streamgages maintained by the U.S. Geological Survey, during water year 2019 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for water year 2019.
The largest tributary to the reservoir, the Ponaganset River, which was monitored by the U.S. Geological Survey, contributed a mean streamflow of 40 cubic feet per second to the reservoir during water year 2019. For the same period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.55 to about 26 cubic feet per second. Together, tributaries equipped with instrumentation capable of continuously monitoring specific conductance transported about 3,500 metric tons of chloride and 2,100 metric tons of sodium to the Scituate Reservoir during water year 2019; annual chloride yields for the tributaries ranged from 20 to 180 metric tons per square mile, and annual sodium yields ranged from 14 to 100 metric tons per square mile.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the medians of the median concentrations were 25.1 milligrams per liter for chloride, 0.001 milligram per liter as nitrogen for nitrite, 0.08 milligram per liter as nitrogen for nitrate, 0.03 milligram per liter as phosphate for orthophosphate, 1,000 colony forming units per 100 milliliters for total coliform bacteria, and 10 colony forming units per 100 milliliters for Escherichia coli (E. coli). The medians of the median daily loads of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were 340 kilograms per day, 18 grams per day, 1,000 grams per day, 410 grams per day, 81,000 million colony forming units per day, and less than 1,800 million colony forming units per day, respectively. The medians of the median yields of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were 140 kilograms per day per square mile, 6.8 grams per day per square mile, 440 grams per day per square mile, 140 grams per day per square mile, 32,000 million colony forming units per day per square mile, and 660 million colony forming units per day per square mile, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1145","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2022, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2019: U.S. Geological Survey Data Report 1145, 35 p., https://doi.org/10.3133/dr1145.","productDescription":"Report: v, 35 p.; Data release; Dataset","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125608","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":394951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1145/coverthb.jpg"},{"id":501201,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112157.htm","linkFileType":{"id":5,"text":"html"}},{"id":394956,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":394955,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WK8N0F","text":"USGS data release","linkHelpText":"Water quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir, water year 2018–19"},{"id":394954,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1145/dr1145.XML"},{"id":394953,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1145/images/"},{"id":394952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1145/dr1145.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1145"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir Drainage Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.78192138671875,\n 41.71187978193456\n ],\n [\n -71.50177001953125,\n 41.71187978193456\n ],\n [\n -71.50177001953125,\n 41.947234477977766\n ],\n [\n -71.78192138671875,\n 41.947234477977766\n ],\n [\n -71.78192138671875,\n 41.71187978193456\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532