We investigated the spatial and temporal distribution of Bighead Carp and Silver Carp (hereafter Carp) in the lower Red River basin of Arkansas. Our study objectives were: 1) determine the spatial and temporal extent of Bighead and Silver Carp in the Red River basin of Arkansas; 2) determine habitat associations of large river fish assemblages; and 3) summarize the demographics of Bighead and Silver Carp. We sampled 67 reaches in the lower Red River and its major tributaries for juvenile Carp and other small-bodied fishes (24 of the reaches were in the Arkansas portion of the Red River). We conducted repeated surveys in these reaches where the reaches were sampled 2-3 times over approximately 2 years representing 242 surveys (95 surveys in Arkansas). We completed adult Carp and native fish assemblage sampling across 61 reaches (22 reaches in Arkansas) where we also repeated surveys at these locations (245 total surveys, 100 surveys completed in Arkansas during the reporting period). We captured the most large-bodied fishes (including Carp) using gillnets and electrofishing, whereas fyke nets and seine hauls collected mainly smaller-bodied fishes. Hoop nets captured fewer fishes when compared to other gear types. We sampled 120,072 fishes, comprising 70 species and 41 genera, from the mainstem Red River in Arkansas. We used data associated with the entire catchment (including OK and TX data) to model the occupancy of adult fishes including both carp species. Carp tended to occupy reaches with the presence of slackwater habitat, that were deeper and narrower (lower habitat complexity), with higher discharge conditions, and were positively associated with chlorophyll-a concentrations. Adult and juvenile assemblage structure varied with reach scale attributes with notable differences among some taxonomically similar species. No carp under the age of 3 were sampled in the catchment. Bighead Carp and Silver Carp in the Red River catchment appear to live longer and grow larger than other populations. Silver Carp and Bighead Carp in the lower Red River had a theoretical maximum length (\uD835\uDC3F∞) of 920 and 1,348-mm TL, respectively. The oldest sampled Silver Carp and Bighead Carp were age 14 and 17, respectively. Bighead Carp growth was positively associated with warmer air temperatures and negatively associated with discharge variability. Similarly, Silver Carp growth was positively associated with warm air temperature and negatively associated with discharge variability. However, Silver Carp growth was also positively related to high discharge conditions and the variability of air temperature. Silver Carp annual mortality was relatively low and recruitment into the population appeared steady. It appears that Carp are likely coming from another catchment, have only limited or periodic successful reproduction in the study area, or spawn downriver in LA. Continued monitoring for reproductive success would be helpful. Moreover, if the goal is to greatly reduce or eliminate carp, then strategies that prevent further immigration before reproduction occurs or becomes more successful would be ideal. Targeted removal may then be useful for reducing numbers already in the catchment; however, there are also oxbow lakes that contain carp but appear only connected to the river during major floods (i.e., possible source locations).
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/css88134777","usgsCitation":"Brewer, S., Dattilo, J., Ramsey, P., and Birdsall, B., 2023, Evaluating the spatial and temporal distribution and ecology of Bighead and Silver Carp and native fishes of the lower Red River basin: Cooperator Science Series CSS-153-2023, ii, 193 p., https://doi.org/10.3996/css88134777.","productDescription":"ii, 193 p.","ipdsId":"IP-177588","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":495039,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3996/css88134777","text":"Publisher Index Page"},{"id":494522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Oklahoma, Texas","otherGeospatial":"lower Red River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.79873940117595,\n 34.31284035073031\n ],\n [\n -96.79873940117595,\n 33.02263338338369\n ],\n [\n -93.57412593043699,\n 33.02263338338369\n ],\n [\n -93.57412593043699,\n 34.31284035073031\n ],\n [\n -96.79873940117595,\n 34.31284035073031\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Brewer, Shannon K. 0000-0002-1537-3921","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":340552,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946819,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dattilo, John","contributorId":341000,"corporation":false,"usgs":false,"family":"Dattilo","given":"John","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":946821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsey, Paul","contributorId":341001,"corporation":false,"usgs":false,"family":"Ramsey","given":"Paul","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":946823,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birdsall, Ben","contributorId":341002,"corporation":false,"usgs":false,"family":"Birdsall","given":"Ben","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":946824,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250109,"text":"70250109 - 2023 - Effects of vehicle traffic on space use and road crossings of caribou in the Arctic","interactions":[],"lastModifiedDate":"2023-12-04T17:27:48.321119","indexId":"70250109","displayToPublicDate":"2023-10-03T09:30:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Effects of vehicle traffic on space use and road crossings of caribou in the Arctic","docAbstract":"Assessing the effects of industrial development on wildlife is a key objective of managers and conservation practitioners. However, wildlife responses are often only investigated with respect to the footprint of infrastructure, even though human activity can strongly mediate development impacts. In Arctic Alaska, there is substantial interest in expanding energy development, raising concerns about the potential effects on barren-ground caribou (Rangifer tarandus granti). While caribou generally avoid industrial infrastructure, little is known about the role of human activity in moderating their responses, and whether managing activity levels could minimize development effects. To address this uncertainty, we examined the influence of traffic volume on caribou summer space use and road crossings in the Central Arctic Herd within the Kuparuk and Milne Point oil fields on the North Slope of Alaska. We first modeled spatiotemporal variation in hourly traffic volumes across the road system from traffic counter data using gradient-boosted regression trees. We then used generalized additive models to estimate nonlinear step selection functions and road-crossing probabilities from collared female caribou during the post-calving and insect harassment seasons, when they primarily interact with roads. Step selection analyses revealed that caribou selected areas further from roads (~1–3 km) during the post-calving and mosquito seasons and selected areas with lower traffic volumes during all seasons, with selection probabilities peaking when traffic was <5 vehicles/h. Using road-crossing models, we found that caribou were less likely to cross roads during the insect seasons as traffic increased, but that response dissipated as insect harassment became more severe. Past studies suggested that caribou exhibit behavioral responses when traffic exceeds 15 vehicles/h, but our results demonstrate behavioral responses at much lower traffic levels. Our results illustrate that vehicle activity mediates caribou responses to road infrastructure, information that can be used in future land-use planning to minimize the behavioral responses of caribou to industrial development in sensitive Arctic landscapes.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2923","usgsCitation":"Severson, J.P., Johnson, H.E., and Vosburgh, T.C., 2023, Effects of vehicle traffic on space use and road crossings of caribou in the Arctic: Ecological Applications, v. 33, no. 8, e2923, 21 p., https://doi.org/10.1002/eap.2923.","productDescription":"e2923, 21 p.","ipdsId":"IP-145608","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":441958,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2923","text":"Publisher Index Page"},{"id":435163,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HXW3N5","text":"USGS data release","linkHelpText":"Hourly Vehicle Traffic Data Associated with Industrial Activity on the North Slope of Alaska During Summers 2019-2020"},{"id":422728,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -149.86133804316822,\n 70.5106570028494\n ],\n [\n -150.1022371487244,\n 70.43506564845134\n ],\n [\n -150.2251448556409,\n 70.43341923336993\n ],\n [\n -150.57911905156016,\n 70.3773618530881\n ],\n [\n -150.74135722468978,\n 70.32611628176022\n ],\n [\n -150.84459969849965,\n 70.2448529934669\n ],\n [\n -150.83476708194632,\n 70.20992730257379\n ],\n [\n -150.71677568330648,\n 70.143238146334\n ],\n [\n -151.12482927026898,\n 69.73513298795481\n ],\n [\n -150.58895166811348,\n 69.72322531382761\n ],\n [\n -150.42671349498383,\n 69.76237009655026\n ],\n [\n -150.24972639702415,\n 69.86563513788099\n ],\n [\n -150.16123284804445,\n 69.94084273688509\n ],\n [\n -149.85642173489157,\n 69.9705480654984\n ],\n [\n -149.4606589186207,\n 70.04604045538369\n ],\n [\n -149.24679950858615,\n 70.08973159573645\n ],\n [\n -148.97640255337,\n 70.26312377942679\n ],\n [\n -149.04031456096658,\n 70.34927534019323\n ],\n [\n -148.91740685405023,\n 70.41529987953601\n ],\n [\n -149.0501471775199,\n 70.48111126247821\n ],\n [\n -149.46311707275905,\n 70.52213540068598\n ],\n [\n -149.649936787272,\n 70.5106570028494\n ],\n [\n -149.86133804316822,\n 70.5106570028494\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"33","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Severson, John P. 0000-0002-1754-6689","orcid":"https://orcid.org/0000-0002-1754-6689","contributorId":213469,"corporation":false,"usgs":true,"family":"Severson","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":888389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Heather E. 0000-0001-5392-7676 hejohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5392-7676","contributorId":205919,"corporation":false,"usgs":true,"family":"Johnson","given":"Heather","email":"hejohnson@usgs.gov","middleInitial":"E.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vosburgh, Timothy C.","contributorId":331661,"corporation":false,"usgs":false,"family":"Vosburgh","given":"Timothy","email":"","middleInitial":"C.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":888391,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249375,"text":"70249375 - 2023 - How long do runoff-generated debris-flow hazards persist after wildfire?","interactions":[],"lastModifiedDate":"2023-10-05T12:25:34.339245","indexId":"70249375","displayToPublicDate":"2023-10-03T07:24:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"How long do runoff-generated debris-flow hazards persist after wildfire?","docAbstract":"Runoff-generated debris flows are a potentially destructive and deadly response to wildfire until sufficient vegetation and soil-hydraulic recovery have reduced susceptibility to the hazard. Elevated debris-flow susceptibility may persist for several years, but the controls on the timespan of the susceptible period are poorly understood. To evaluate the connection between vegetation recovery and debris-flow occurrence, we calculated recovery for 25 fires in the western United States using satellite-derived leaf area index (LAI) and compared recovery estimates to the timing of 536 debris flows from the same fires. We found that the majority (>98%) of flows occurred when LAI was less than 2/3 of typical prefire values. Our results show that total vegetation recovery is not necessary to inhibit runoff-generated flows in a wide variety of regions in the western United States. Satellite-derived vegetation data show promise for estimating the timespan of debris-flow susceptibility.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GL105101","usgsCitation":"Graber, A.P., Thomas, M.A., and Kean, J.W., 2023, How long do runoff-generated debris-flow hazards persist after wildfire?: Geophysical Research Letters, v. 50, no. 19, e2023GL105101, 10 p., https://doi.org/10.1029/2023GL105101.","productDescription":"e2023GL105101, 10 p.","ipdsId":"IP-153081","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":441961,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gl105101","text":"Publisher Index Page"},{"id":435164,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98Q4CDH","text":"USGS data release","linkHelpText":"Compilation of runoff-generated debris-flow inventories for 17 fires across Arizona, California, Colorado, New Mexico, and Washington, USA"},{"id":421673,"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 \"coordinates\": [\n [\n [\n -127.73580454866216,\n 50.89584069263282\n ],\n [\n -127.73580454866216,\n 30.13526525190572\n ],\n [\n -101.983851423662,\n 30.13526525190572\n ],\n [\n -101.983851423662,\n 50.89584069263282\n ],\n [\n -127.73580454866216,\n 50.89584069263282\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","issue":"19","noUsgsAuthors":false,"publicationDate":"2023-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Graber, Andrew Paul 0000-0003-4179-0291","orcid":"https://orcid.org/0000-0003-4179-0291","contributorId":304628,"corporation":false,"usgs":true,"family":"Graber","given":"Andrew","email":"","middleInitial":"Paul","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":885378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":885379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":885380,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70249272,"text":"70249272 - 2023 - Monitoring sediment transport pathways from an artificial nearshore berm, South Padre Island, Texas, USA, August 2018 to November 2019: Implications for coastal management","interactions":[],"lastModifiedDate":"2023-10-03T12:25:53.266857","indexId":"70249272","displayToPublicDate":"2023-10-03T07:10:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2449,"text":"Journal of Sea Research","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring sediment transport pathways from an artificial nearshore berm, South Padre Island, Texas, USA, August 2018 to November 2019: Implications for coastal management","docAbstract":"During August 2018 – November 2019, the transport pathways of dredge material from a specially constructed nearshore feeder berm were investigated as part of a collaborative study by the City of South Padre Island, U.S. Army Corps of Engineers–Galveston District, U.S. Geological Survey, Partrac GeoMarine Inc., and Texas A&M University, into the efficacy of beneficial use dredge material (BUDM) as a method of replenishing the beach profile and shoreface at South Padre Island, Texas with sediment. Dual-signature (fluorescent and ferrimagnetic) tracer particles, designed to be hydraulically equivalent to the dredge material, were placed on the berm, and a sampling program was initiated to monitor the spatiotemporal movement of tracer particles under the influence of the prevailing hydrodynamic regime. Wave and current data were collected and were used together with available metocean data to identify the forcing mechanisms of sediment transport; improved understanding garnered from the consideration of multiple datasets can be used to inform future coastal management decisions.
Tracer analysis results indicated low magnitude, shoreward transport of dredge material from the berm and along shore transport in both northerly and southerly directions. Small amounts of tracer detected in beach face samples demonstrated connectivity between the constructed feeder berm and the shoreface. However, the generally low tracer concentration within beach face samples indicated low rates of sediment transport for berm sediments, and a low magnitude sediment transport pathway from the berm directly to the beach face, with possible storage of sediment in the nearshore bar system.
Given that the berm was at or beyond the closure depth and considering the relatively weak prevailing near bottom hydrodynamic conditions, the potential for sediment to be mobilized and transported during the study period was generally low. Periods of higher energy waves, driven by north-northwest winds, were identified as a key driver of sediment transport but due to the infrequent nature of these events the sediment transport regime across the area of interest was temporally limited. Longshore movement of sediment was both north and south, mainly dependent on prevailing wind directions and resulting longshore currents.
We discuss implications for coastal zone management and the use of feeder berms as an artificial beach nourishment mechanism to replenish sediments lost by coastal erosional processes. The insight into nearshore emplacement of material can be used by local governments and coastal managers to optimize the efficacy of berm emplacement and implement such schemes as a cost-effective nourishment option, or when onshore placement of material is not feasible.
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Center","active":true,"usgs":true}],"preferred":true,"id":884955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poleykett, Jack","contributorId":272835,"corporation":false,"usgs":false,"family":"Poleykett","given":"Jack","email":"","affiliations":[{"id":56391,"text":"Partrec, Inc.","active":true,"usgs":false}],"preferred":false,"id":884956,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friend, Patrick L.","contributorId":272633,"corporation":false,"usgs":false,"family":"Friend","given":"Patrick","email":"","middleInitial":"L.","affiliations":[{"id":56391,"text":"Partrec, Inc.","active":true,"usgs":false}],"preferred":false,"id":884957,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maglio, Coraggio K.","contributorId":272632,"corporation":false,"usgs":false,"family":"Maglio","given":"Coraggio","email":"","middleInitial":"K.","affiliations":[{"id":56390,"text":"U.S. Army Corps of Engineers-Galveston District","active":true,"usgs":false}],"preferred":false,"id":884958,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boburka, Kristina","contributorId":272634,"corporation":false,"usgs":false,"family":"Boburka","given":"Kristina","email":"","affiliations":[{"id":56392,"text":"City of South Padre Island, Texas","active":true,"usgs":false}],"preferred":false,"id":884959,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70250350,"text":"70250350 - 2023 - Predatory impacts of invasive Blue Catfish in an Atlantic coast estuary","interactions":[],"lastModifiedDate":"2023-12-05T12:46:37.592725","indexId":"70250350","displayToPublicDate":"2023-10-03T06:43:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Predatory impacts of invasive Blue Catfish in an Atlantic coast estuary","docAbstract":"Predatory invasive fishes may consume species of management interest and alter food webs. Blue Catfish Ictalurus furcatus is a large-bodied, salinity-tolerant species that exhibits broad diet breadth and preys on species of both conservation concern and fisheries management interest. To better understand the ecological consequences of the establishment of Blue Catfish fisheries, estimates of predatory impacts are needed.
Using a Monte Carlo simulation, we integrated abundance estimates, diet information, and consumption-to-biomass ratios to estimate population-level Blue Catfish predation for a large Chesapeake Bay tributary along the mid-Atlantic coast of the United States, the James River.
Population-level annual predation estimates by Blue Catfish exceeded 100 metric tons for several species or taxa of interest, including an estimated 400.7 metric tons (95% CI = 272.6–613.2) of blue crab Callinectes sapidus. Prey species abundances were unknown and thus limited opportunities to evaluate prey population responses. For instance, effects of Blue Catfish on blue crab populations remain unknown without tributary-specific estimates of blue crab abundance, but comparisons to landings data suggests that Blue Catfish predation on blue crab in the James River may be low compared with harvest.
Estimation of Blue Catfish predatory effects may inform development of management goals and objectives that balance diverse stakeholder interests. This work provides beneficial information to assess trade-offs of Blue Catfish fisheries and their effects on coastal aquatic resources.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/mcf2.10261","usgsCitation":"Hilling, C.D., Schmitt, J., Jiao, Y., and Orth, D., 2023, Predatory impacts of invasive Blue Catfish in an Atlantic coast estuary: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 15, no. 5, e10261, 14 p., https://doi.org/10.1002/mcf2.10261.","productDescription":"e10261, 14 p.","ipdsId":"IP-149753","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":441964,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/mcf2.10261","text":"Publisher Index Page"},{"id":423232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.45655387490967,\n 36.550631310388894\n ],\n [\n -75.45655387490967,\n 38.29548758624807\n ],\n [\n -77.87354606241009,\n 38.29548758624807\n ],\n [\n -77.87354606241009,\n 36.550631310388894\n ],\n [\n -75.45655387490967,\n 36.550631310388894\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Hilling, Corbin David 0000-0003-4040-9516","orcid":"https://orcid.org/0000-0003-4040-9516","contributorId":298946,"corporation":false,"usgs":true,"family":"Hilling","given":"Corbin","email":"","middleInitial":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":889520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":889521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jiao, Yan","contributorId":204633,"corporation":false,"usgs":false,"family":"Jiao","given":"Yan","email":"","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":889522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orth, Donald J.","contributorId":279468,"corporation":false,"usgs":false,"family":"Orth","given":"Donald J.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":889523,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249514,"text":"70249514 - 2023 - Sound and sturgeon: Bioacoustics and anthropogenic sound","interactions":[],"lastModifiedDate":"2023-10-12T14:18:12.968347","indexId":"70249514","displayToPublicDate":"2023-10-02T09:16:30","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17057,"text":"The Journal of the Acoustical Society of America","active":true,"publicationSubtype":{"id":10}},"title":"Sound and sturgeon: Bioacoustics and anthropogenic sound","docAbstract":"Sturgeons are basal bony fishes, most species of which are considered threatened and/or endangered. Like all fishes, sturgeons use hearing to learn about their environment and perhaps communicate with conspecifics, as in mating. Thus, anything that impacts the ability of sturgeon to hear biologically important sounds could impact fitness and survival of individuals and populations. There is growing concern that the sounds produced by human activities (anthropogenic sound), such as from shipping, commercial barge navigation on rivers, offshore windfarms, and oil and gas exploration, could impact hearing by aquatic organisms. Thus, it is critical to understand how sturgeon hear, what they hear, and how they use sound. Such data are needed to set regulatory criteria for anthropogenic sound to protect these animals. However, very little is known about sturgeon behavioral responses to sound and their use of sound. To help understand the issues related to sturgeon and anthropogenic sound, this review first examines what is known about sturgeon bioacoustics. It then considers the potential effects of anthropogenic sound on sturgeon and, finally identifies areas of research that could substantially improve knowledge of sturgeon bioacoustics and effects of anthropogenic sound. Filling these gaps will help regulators establish appropriate protection for sturgeon.
","language":"English","publisher":"Acoustical Society of America","doi":"10.1121/10.0021166","usgsCitation":"Popper, A.N., and Calfee, R.D., 2023, Sound and sturgeon: Bioacoustics and anthropogenic sound: The Journal of the Acoustical Society of America, v. 154, no. 4, p. 2021-2035, https://doi.org/10.1121/10.0021166.","productDescription":"15 p.","startPage":"2021","endPage":"2035","ipdsId":"IP-151832","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":441969,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1121/10.0021166","text":"Publisher Index Page"},{"id":421890,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"154","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-10-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Popper, Arthur N.","contributorId":175351,"corporation":false,"usgs":false,"family":"Popper","given":"Arthur","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":886048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":886049,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70249363,"text":"70249363 - 2023 - Microgravity as a tool for eruption forecasting","interactions":[],"lastModifiedDate":"2023-10-04T20:16:28.295246","indexId":"70249363","displayToPublicDate":"2023-10-01T13:00:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Microgravity as a tool for eruption forecasting","docAbstract":"Detection of gravity change over time has been used to better understand magmatic activity at volcanoes for decades, but the technique is not commonly applied to forecasting eruptions. In contrast, other tools, notably seismic, deformation, and gas monitoring have made exceptional strides in the past several decades and form the foundation for eruption forecasting, especially during the final buildup to an eruption. Reasons for this gap include the high cost and fragile nature of gravity instruments, and the ambiguous nature of many results. But this is changing. Instrumentation is becoming more robust and accurate, expenses may soon diminish thanks to technological advances, and the record of success in tracking subsurface mass change (either from magma or hydrothermal fluids) in volcanic areas is growing. Here we review how gravity change can be applied to forecasting volcanic eruptions across a variety of spatial and temporal scales. We argue that microgravity has untapped potential as a forecasting tool in three specific ways: constraining probabilistic assessments, detecting long-term mass change that may occur prior to the onset of vigorous seismicity and deformation, and identifying transient activity that indicates magma ascent or other changes that immediately precede new eruptions or changes in ongoing eruptions. As with any volcano-monitoring method, microgravity has strengths and weaknesses, but the varied forms of data collection—for instance, campaign versus continuous, and relative versus absolute—offer the potential to record a broad range of signals at volcanoes with a diversity of magmatic systems. The technique is currently underutilized; additional attention, investment, and application at more volcanoes could help to realize its promise.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2023.107910","usgsCitation":"de Zeeuw-van Dalfsen, E., and Poland, M.P., 2023, Microgravity as a tool for eruption forecasting: Journal of Volcanology and Geothermal Research, v. 442, 107910, 14 p., https://doi.org/10.1016/j.jvolgeores.2023.107910.","productDescription":"107910, 14 p.","ipdsId":"IP-152507","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":421616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.28629797636563,\n 19.401938981737857\n ],\n [\n -155.28523227780258,\n 19.401603921708983\n ],\n [\n -155.2829232642494,\n 19.40171560846254\n ],\n [\n -155.27984457951175,\n 19.403390900554683\n ],\n [\n -155.27800920976435,\n 19.406183015701615\n ],\n [\n -155.27818682619153,\n 19.408472514355836\n ],\n [\n -155.2790157028517,\n 19.410091896380962\n ],\n [\n -155.28126551092907,\n 19.411599582390465\n ],\n [\n -155.28617956541413,\n 19.411376222382003\n ],\n [\n -155.28689003112277,\n 19.41065030023701\n ],\n [\n -155.28712685302565,\n 19.40970101254156\n ],\n [\n -155.28925825015176,\n 19.406294699311132\n ],\n [\n -155.28931745562747,\n 19.404898648686896\n ],\n [\n -155.28896222277308,\n 19.404451909956876\n ],\n [\n -155.2884293734916,\n 19.403446743327578\n ],\n [\n -155.28629797636563,\n 19.401938981737857\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"442","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"de Zeeuw-van Dalfsen, Elske 0000-0003-2527-4932","orcid":"https://orcid.org/0000-0003-2527-4932","contributorId":217967,"corporation":false,"usgs":false,"family":"de Zeeuw-van Dalfsen","given":"Elske","email":"","affiliations":[{"id":39727,"text":"KNMI","active":true,"usgs":false}],"preferred":false,"id":885329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":885330,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70250110,"text":"70250110 - 2023 - Stable isotope constraints on the source of ore fluids for the Hicks Dome REE+Y-HFSE-fluorspar deposit","interactions":[],"lastModifiedDate":"2023-11-20T16:11:18.374145","indexId":"70250110","displayToPublicDate":"2023-10-01T10:04:32","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Stable isotope constraints on the source of ore fluids for the Hicks Dome REE+Y-HFSE-fluorspar deposit","docAbstract":"Hicks Dome is comprised of coarse crystalline Mississippi Valley Type deposits at shallow levels and an enigmatic, fine-grained fluorite, rare earth elements, Y, high field strength elements, Be, and Ba rich deposit at deeper levels. Phyllosilicates from a lamprophyre dike and a breccia from two Hicks Dome drill cores were sampled to resolve the fluid history of the entire deposit using light stable isotopes. Silicate fluorination coupled with isotope ratio mass spectrometry give δ18O values from +6.9 to +16.0 ‰ (Vienna Standard Mean Ocean Water). Temperature conversion elemental analyzer and gas chromatography-isotope ratio mass spectrometry give δ2H values from -54 to -33 ‰ (Vienna Standard Mean Ocean Water). Muscovite from metasomatized dikes and breccias are relatively enriched in 18O compared to phlogopite from lamprophyre. Calculated isotopic compositions of the fluids from which the phyllosilicates precipitated indicate that phlogopite retained a magmatic composition while muscovite likely formed from magmatic fluids that exchanged with carbonate host rocks or from magmatic fluids that mixed with basinal brines. Enrichment of deuterium in fluids calculated from muscovite suggest that fluids were derived from hypothesized carbonatites or were acidic. These data demonstrate that the Hicks Dome critical mineral resource is magmatic hydrothermal in origin.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 17th SGA biennial meeting","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"17th SGA Biennial Meeting: Mineral Resources in a changing world","conferenceDate":"August 28-September 1, 2023","conferenceLocation":"Zurich, Switzerland","language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"McIntosh, J.A., Johnson, C.A., Andersen, A.K., and Hofstra, A.H., 2023, Stable isotope constraints on the source of ore fluids for the Hicks Dome REE+Y-HFSE-fluorspar deposit, in Proceedings of the 17th SGA biennial meeting, v. 3, Zurich, Switzerland, August 28-September 1, 2023, p. 225-228.","productDescription":"4 p.","startPage":"225","endPage":"228","ipdsId":"IP-151317","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":422730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":422729,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://sga2023.ch/programme/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois","otherGeospatial":"Hicks Dome","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.5,\n 37.633333\n ],\n [\n -88.5,\n 37.41\n ],\n [\n -88.25,\n 37.41\n ],\n [\n -88.25,\n 37.633333\n ],\n [\n -88.5,\n 37.633333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McIntosh, Julia A. 0000-0003-2819-8664","orcid":"https://orcid.org/0000-0003-2819-8664","contributorId":331662,"corporation":false,"usgs":true,"family":"McIntosh","given":"Julia","email":"","middleInitial":"A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":888392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":888393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andersen, Allen K. 0000-0002-6865-2561","orcid":"https://orcid.org/0000-0002-6865-2561","contributorId":217476,"corporation":false,"usgs":true,"family":"Andersen","given":"Allen","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":888394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":888395,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70260095,"text":"70260095 - 2023 - Petrology and geochronology of Cretaceous–Eocene plutonic rocks in northeastern Washington, USA: Crustal thickening, slab rollback, and origin of the Challis episode","interactions":[],"lastModifiedDate":"2024-10-28T12:02:39.587199","indexId":"70260095","displayToPublicDate":"2023-09-30T07:00:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Petrology and geochronology of Cretaceous–Eocene plutonic rocks in northeastern Washington, USA: Crustal thickening, slab rollback, and origin of the Challis episode","docAbstract":"Cretaceous through Eocene plutonic rocks in northeastern Washington, USA, document a 60 m.y. history of crustal thickening and subsequent collapse and extension in response to two terrane-accretion events. Rocks emplaced 113–53 Ma have increasing La/Yb ratios reflecting orogenic plateau development after arrival of the Insular terrane by 100 Ma. Plutons emplaced 52–45 Ma (the Challis episode) document collapse of this plateau and define a SW-younging age progression attributed to breakoff and rollback of the Farallon slab following accretion of the Siletzia terrane at ca. 50 Ma. All of the rocks have chemical traits of arc magmas, likely inherited from their lower-crustal sources, but low B/Be ratios and the lack of evidence for amphibole fractionation indicate the Eocene magmas formed under drier conditions than are typical of active subduction settings. These magmas also originated at greater depth (eclogitic vs. gabbroic source) and were emplaced more shallowly than the earlier ones. All rocks have overlapping Sr-Nd and O isotopic data, indicating significant contributions from older continental crust, and depleted mantle Nd model ages become older toward the east, defining three regions that correspond with previously inferred lower-crustal domains. Farallon slab rollback also drove extension (core complex formation, dike swarms) and crustal uplift, which, along with voluminous magmatism, define the Challis episode. This tectonic model is further supported by seismic tomography, which has identified remnants of a detached slab in the upper mantle beneath the region.
The lack of contemporary data on contaminants in resident fish prevents an analysis of temporal trends in contaminant concentrations and the present-day status of the “Restrictions on Fish and Wildlife Consumption” Beneficial Use Impairment (BUI) in the Niagara River Area of Concern (AOC). During 2018, concentrations of 260 contaminants in four groups of fish species from five areas in or near the upper Niagara River AOC were analyzed to determine the potential risks from fish consumption, responses to remediation in an adjacent AOC, and whether additional remedial actions were warranted in this AOC. The concentrations of most contaminants were generally undetectable or did not exceed established Federal, State, or European Union fish-consumption limits. Several contaminants without State or Federal limits exceeded European Union fish-consumption guidelines in some species and areas. High PCB residues in many bullhead from Scajaquada Creek, some bass from Hoyt Lake, and most common carp from all areas surpassed certain New York and Federal fish-consumption limits and indicate PCBs continue to restrict fish consumption at most study areas. High concentrations of several contaminants in resident fish, especially dioxins and furans in carp, from Cayuga Creek indicate that additional scrutiny of consumption advisories is warranted in this area. Because this study provides a snapshot in time of fish-contaminant data from five areas, additional data from other areas and times, and more detailed information on present-day pollutant sources may be needed before determining the status of the fish-consumption BUI in this AOC.
Current methods for determining the 1-percent annual exceedance probability (AEP) for a streamflow assume stationarity (the assumption that the statistical distribution of data from past observations does not contain trends and will continue unchanged in the future). This assumption allows the 1-percent AEP to be determined based on historical streamflow records. However, the assumption of stationarity is challenged by observed trends in streamflow records.
In response, the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, studied potential changes to the 1-percent AEP streamflows at streamgages in the Housatonic River watershed in Massachusetts, Connecticut, and New York. The study used the Precipitation-Runoff Modeling System—a deterministic hydrologic model. Climate inputs to the model of temperature and precipitation were scaled to anticipated changes based on global climate models that could occur in 2030, 2050, and 2100. The model outputs were used to characterize the 1-percent AEP streamflows for 2030, 2050, and 2100 and compare the results to baseline conditions for 1950 to 2015. Results indicated that the 1-percent AEP streamflow for unregulated streams and rivers may increase from the 1950–2015 baseline period by 7.4, 11.7, and 17.3 percent in 2030, 2050, and 2100, respectively, because of climate change.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235090","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Olson, S.A., 2023, Characterizing changes in the 1-percent annual exceedance probability streamflows for climate-change scenarios in the Housatonic River watershed of Massachusetts, Connecticut, and New York: U.S. Geological Survey Scientific Investigations Report 2023–5090, 16 p., https://doi.org/10.3133/sir20235090.","productDescription":"Report: iv, 16 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-149676","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501055,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115441.htm","linkFileType":{"id":5,"text":"html"}},{"id":421394,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91CSH0P","text":"USGS data release","linkHelpText":"Data for characterizing changes in the 1-percent annual exceedance probability streamflows for climate change scenarios in the Housatonic River watershed—Massachusetts, Connecticut, and New York"},{"id":421390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5090/coverthb.jpg"},{"id":421391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5090/sir20235090.pdf","text":"Report","size":"8.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5090"},{"id":421392,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5090/sir20235090.XML"},{"id":421393,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5090/images"},{"id":421395,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235090/full"}],"country":"United States","state":"Connecticut, Massachusetts, New York","otherGeospatial":"Housatonic River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.73443369971218,\n 41.34286607604693\n ],\n [\n -72.73443369971218,\n 42.92331687334064\n ],\n [\n -74.64605479346228,\n 42.92331687334064\n ],\n [\n -74.64605479346228,\n 41.34286607604693\n ],\n [\n -72.73443369971218,\n 41.34286607604693\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Integrating recent scientific knowledge into management decisions supports effective natural resource management and can lead to better resource outcomes. However, finding and accessing scientific knowledge can be time consuming and costly. To assist in this process, the U.S. Geological Survey is creating a series of annotated bibliographies on topics of management concern for western lands. Previously published reports introduced a methodology for preparing annotated bibliographies to facilitate the integration of recent, peer-reviewed science into resource management decisions. Therefore, relevant text from those efforts is reproduced here to frame the presentation. Centrocercus minimus (Gunnison sage-grouse; hereafter GUSG) has been a focus of scientific investigation since the early 2000s. The U.S. Fish and Wildlife Service listed GUSG as threatened under the Endangered Species Act in 2014 because of declining populations and increasing habitat loss. The U.S. Fish and Wildlife Service, Bureau of Land Management, and Colorado Parks and Wildlife have sought to increase the conservation of this species by adapting management and recovery plans to reduce threats and increase population resiliency. GUSG are studied less than the closely related Centrocercus urophasianus (greater sage-grouse); however, research efforts have recently increased to understand the life history, genetics, and habitat suitability of this sagebrush-obligate species. We compiled and summarized peer-reviewed journal articles, data products, and formal technical reports (such as U.S. Department of Agriculture Forest Service General Technical Reports and U.S. Geological Survey Open-File Reports) on GUSG, published between January 2005 and September 2022. We first systematically searched three reference databases and three government databases using the following search phrases: “Gunnison sage-grouse” or “lesser sage-grouse” or “Gunnison grouse” or “Gunnison sage grouse” or “lesser sage grouse” or “Centrocercus minimus.” We refined the initial list of products by removing (1) duplicates, (2) publications that were not published as research, data products, or scientific review articles in peer-reviewed journals or as formal technical reports, and (3) products that did not have GUSG as a research focus or products that did not present new data or findings about GUSG. We summarized each product using a consistent structure (background, objectives, methods, location, findings, and implications) and identified the management topics (for example, population estimates or targets, habitat, and management efforts) addressed by each product. We also noted which publications included new geospatial data. The review process for this annotated bibliography included two initial internal colleague reviews of each summary, requesting input on each summary from an author of the original publication, and a formal peer review. Our initial searches resulted in 80 total products, of which 63 met our criteria for inclusion of which 53 were products that had not been summarized before. Across products summarized in the annotated bibliography, broad-scale habitat characteristics; population estimates or targets; behavior or demographics; and genetics were the most commonly addressed management topics. The bibliographies are available on the Science for Resource Managers tool (https://apps.usgs.gov/science-for-resource-managers) and are searchable by topic, location, and year, and the search tool includes links to each original publication. The studies compiled and summarized in this annotated bibliography may inform planning and management actions that seek to maintain and restore sagebrush landscapes and GUSG populations across the GUSG range.
","publisher":"U S Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231079","usgsCitation":"Maxwell, L.M., Teige, E.C., Jordan, S.E., Rutherford, T.K., Samuel, E.M., Selby, L.B., Foster, A.C., Kleist, N.J., and Carter, S.K., 2023, Annotated bibliography of scientific research on Gunnison sage-grouse published from January 2005 to September 2022: U.S. Geological Survey Open-File Report 2023–1079, 52 p., https://doi.org/10.3133/ofr20231079.","productDescription":"vii, 52 p.","onlineOnly":"Y","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":421428,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231079/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1079"},{"id":421397,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1079/ofr20231079.xml"},{"id":421355,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1079/ofr20231079.pdf","text":"Report","size":"2.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1079"},{"id":421396,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1079/images"},{"id":421354,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1079/coverthb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.12083328575649,\n 39.47396881795231\n ],\n [\n -109.12083328575649,\n 36.98898041947241\n ],\n [\n -104.41868484825648,\n 36.98898041947241\n ],\n [\n -104.41868484825648,\n 39.47396881795231\n ],\n [\n -109.12083328575649,\n 39.47396881795231\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
Satellite remote sensing is becoming a widely used monitoring technique in coastal sciences. Yet, no benchmarking studies exist that compare the performance of popular satellite-derived shoreline mapping algorithms against standardized sets of inputs and validation data. Here we present a new benchmarking framework to evaluate the accuracy of shoreline change observations extracted from publicly available satellite imagery (Landsat and Sentinel-2). Accuracy and precision of five established shoreline mapping algorithms are evaluated at four sandy beaches with varying geologic and oceanographic conditions. Comparisons against long-term in situ beach surveys reveal that all algorithms provide horizontal accuracy on the order of 10 m at microtidal sites. However, accuracy deteriorates as the tidal range increases, to more than 20 m for a high-energy macrotidal beach (Truc Vert, France) with complex foreshore morphology. The goal of this open-source, collaborative benchmarking framework is to identify areas of improvement for present algorithms, while providing a stepping stone for testing future developments, and ensuring reproducibility of methods across various research groups and applications.
This report describes a sensitivity analysis of a water-budget model that was completed to identify the most important types of hydrologic information needed to reduce the uncertainty of model recharge estimates. The sensitivity of model recharge estimates for the Hawaiian Islands of Oʻahu and Maui was analyzed for seven model parameters potentially affected by land-cover changes within a watershed. The seven model parameters tested were canopy capacity, canopy-cover fraction, crop coefficient, fog-catch efficiency, root depth, stemflow, and trunk-storage capacity.
Results of the sensitivity analysis were used to (1) quantify the relative importance of the seven model parameters to recharge assessments for three moisture zones (dry, mesic, and wet) on Oʻahu and Maui and (2) prepare a list of critical information needs for each moisture zone. The list of critical information needs was developed for three general types of land cover (forest, shrubland, and grassland) that are assumed to be affected by watershed management in the Hawaiian Islands. Identified information needs included estimates or measurements of (1) evapotranspiration processes needed to determine crop coefficients for land-cover types in all moisture zones, (2) rooting depths for land-cover types in the dry and mesic moisture zones, (3) canopy-cover fraction for forests in the wet and mesic moisture zones, (4) ratios of fog interception to rainfall for forests and shrublands in the wet moisture zone, and (5) canopy capacity for forests in the wet and mesic moisture zones. The list of information needs can guide data-collection strategies of future projects. Collection and analysis of the identified hydrologic information may help model users develop a better parameterization scheme, reduce uncertainty of values that model users assign to land-cover dependent parameters, and therefore allow future applications of the water-budget model to more accurately quantify how recharge in the Hawaiian Islands might be affected by future land-cover changes within a watershed.
","language":"English","publisher":"U.S. Geological Center","publisherLocation":"Reston, VA","doi":"10.3133/sir20235022","collaboration":"Prepared in cooperation with the State of Hawai‘i Commission on Water Resource Management","usgsCitation":"Johnson, A.G., Mair, A., and Oki, D.S., 2023, Identifying the relative importance of water-budget information needed to quantify how land-cover change affects recharge, Hawaiian Islands: U.S. Geological Survey Scientific Investigations Report 2023–5022, 28 p., https://doi.org/10.3133/sir20235022.","productDescription":"Report: vi, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-129378","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":500874,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115438.htm","text":"Maui","linkFileType":{"id":5,"text":"html"}},{"id":500873,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115437.htm","text":"Oahu","linkFileType":{"id":5,"text":"html"}},{"id":421316,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X9ZEE3","text":"USGS Data Release","description":"Johnson, A.G., and Kāne, H.L., 2023, Model subareas and moisture zones used in a sensitivity analysis of a water-budget model completed in 2022 for the islands of Oahu and Maui, Hawaii: U.S. Geological Survey data release, https://doi.org/10.5066/P9X9ZEE3.","linkHelpText":"Model subareas and moisture zones used in a sensitivity analysis of a water-budget model completed in 2022 for the islands of Oahu and Maui, Hawaii"},{"id":421315,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5022/sir20235022.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":421314,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5022/covrthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui, O'ahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.75858532451014,\n 21.145379373074235\n ],\n [\n -156.75858532451014,\n 20.508739201099033\n ],\n [\n -155.89066540263516,\n 20.508739201099033\n ],\n [\n -155.89066540263516,\n 21.145379373074235\n ],\n [\n -156.75858532451014,\n 21.145379373074235\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -158.3516029026351,\n 21.83029675022702\n ],\n [\n -158.3516029026351,\n 21.17099365241016\n ],\n [\n -157.59354626201016,\n 21.17099365241016\n ],\n [\n -157.59354626201016,\n 21.83029675022702\n ],\n [\n -158.3516029026351,\n 21.83029675022702\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
Most of the population of the Treasure Valley and the surrounding area of southwestern Idaho and easternmost Oregon depends on groundwater for domestic supply, either from domestic or municipal-supply wells. Current and projected rapid population growth in the area has caused concern about the long-term sustainability of the groundwater resource. In 2016, the U.S. Geological Survey, in cooperation with the Idaho Water Resource Board and the Idaho Department of Water Resources, began a project to construct a numerical groundwater-flow model of the westernmost portion of the western Snake River Plain aquifer system, called the Treasure Valley.
The development of the model was guided by several objectives, including:
The model was constructed with a spatial scale and level of detail that aimed to meet these objectives while balancing the sometimes-competing goals of fast runtimes, numerical stability, usability, and parsimony.
The Treasure Valley Groundwater Flow Model (TVGWFM) is a three-dimensional finite-difference numerical model constructed using MODFLOW 6 (Langevin and others, 2017, Documentation for the MODFLOW 6 Groundwater Flow Model: U.S. Geological Survey Techniques and Methods, book 6, chap. A55, 197 p., https://doi.org/10.3133/tm6A55). The model covers the westernmost portion of the western Snake River Plain and is discretized into a regular grid of 64 by 65 cells with a side length of 1 mile and 6 layers of varying depth and active area. A historical model period was developed consisting of 360 month-long stress periods for 1986–2015. The model builds upon previous modeling efforts by adding a transient period, incorporating new head and discharge observations to constrain parameters, incorporating information from the hydrogeologic framework model (HFM) of Bartolino (2019, Hydrogeologic framework of the Treasure Valley and surrounding area, Idaho and Oregon: U.S. Geological Survey Scientific Investigations Report 2019–5138, https://doi.org/10.3133/sir20195138) and incorporating refined estimates of evapotranspiration and irrigation classification of lands in the study area.
The TVGWFM includes all significant components of recharge to and discharge from the aquifer. Inflows include canal seepage, irrigation and precipitation recharge, mountain-front recharge, rivers and stream seepage, and seepage from Lake Lowell. Outflows include discharge to agricultural drainage ditches, discharge to rivers and streams, pumping, and discharge to Lake Lowell. Each recharge or discharge component is represented separately using individual MODFLOW 6 packages.
Parameter values were derived with a combination of trial-and-error steps and automated parameter estimation using PEST software (Doherty, J.E., 2005, PEST, model-independent parameter estimation–User manual: Watermark Numerical Computing, https://pesthomepage.org/documentation). Parameter estimates were constrained with several types of observation data, including water levels, water level changes, vertical water level differences, drain discharges, change in drain discharges, river seepage, seepage from Lake Lowell, and change in seepage from Lake Lowell. Material properties from the hydrogeologic framework were also used to assign the minimum and maximum values of some parameters.
A final parameter realization was reached that minimized residuals between the observed and modelled values for the various observation groups. Mean residuals for the observation groups were 15.4 feet (ft) for water levels, 0.2 ft for water level changes, 19.4 ft for vertical water level differences, −3.9 cubic feet per second (ft3/s) for drain discharges, 0.0 ft3/s for changes in drain discharge, 45.0 ft3/s for river seepage, −40.1 ft3/s for Lake Lowell seepage, and 126.3 ft3/s for changes in Lake Lowell seepage. The quality of the model’s fit to observations varied spatially, with notable areas of under- or over-simulation of water levels present to the northwest and southwest of Lake Lowell, in the foothills along the eastern model boundary, and near the City of Eagle. Trends were observed in the residuals of many of the observation groups, indicating that the model is missing or not fully reproducing some phenomena that are observed in the system.
The TVGWFM can be used as a tool for water resource planning, for understanding the interactions of groundwater and surface water at a basin scale, and for facilitating conjunctive management, but may lack the precision needed for water rights administration at a local scale. Additional sources of uncertainty or limitations of the model are noted. The quantity and spatial distribution of canal seepage and infiltration of irrigation water recharge, the largest sources of recharge to the system, are unknown and approximated indirectly. There is poor understanding of how canal seepage and incidental recharge change as land is converted from agricultural (irrigated) to suburban (semi-irrigated). These uncertainties will affect any scenarios that investigate changes to land use or irrigation practices. Finally, the model has relatively high water-level residuals around and to the southwest of Lake Lowell and should not be used to estimate water level effects in that region.
The model was built with multiple, broadly expressed objectives and did not optimize performance for specific uses. However, the model and the tools included in an associated data release provide ample flexibility to improve the model for future uses. Adjustments and improvements could be made by refining the model in an area of interest, collecting additional calibration data, applying more rigorous boundary conditions, or re-estimating model parameters to optimize model performance for a specific model forecast.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235096","collaboration":"Prepared in cooperation with the Idaho Water Resource Board and the Idaho Department of Water Resources","usgsCitation":"Hundt, S.A., and Bartolino, J.R., 2023, Groundwater-flow model of the Treasure Valley, southwestern Idaho, 1986–2015: U.S. Geological Survey Scientific Investigations Report 2023–5096, 107 p., https://doi.org/10.3133/sir20235096.","productDescription":"Report: xii, 107 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-127901","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":501062,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115439.htm","linkFileType":{"id":5,"text":"html"}},{"id":421318,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5096/sir20235096.pdf","text":"Report","size":"30.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5096"},{"id":421321,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5096/images"},{"id":421317,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5096/coverthb.jpg"},{"id":421320,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U6OOPH","text":"USGS data release","description":"USGS data release","linkHelpText":"Data and archive for a groundwater flow model of the Treasure Valley aquifer system, southwestern Idaho"},{"id":421322,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5096/sir20235096.XML"}],"country":"United States","state":"Idaho","otherGeospatial":"Treasure Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.26392993194762,\n 44.27650517719664\n ],\n [\n -117.26392993194762,\n 42.71456173603502\n ],\n [\n -115.50611743194747,\n 42.71456173603502\n ],\n [\n -115.50611743194747,\n 44.27650517719664\n ],\n [\n -117.26392993194762,\n 44.27650517719664\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
The Sparta-Memphis aquifer, present across much of eastern Arkansas, is the second most used groundwater resource in the State, with the Mississippi River Valley alluvial aquifer being the primary groundwater resource. The U.S. Geological Survey, in cooperation with Arkansas Department of Agriculture-Natural Resources Division, Arkansas Geological Survey, Natural Resources Conservation Service, Union County Water Conservation Board, and the Union County Conservation District, collects groundwater data across the Sparta-Memphis aquifer extent in Arkansas. This report presents water-level data for measurements conducted during two time periods, January–May 2013 and January–June 2015, and discusses water-level altitude changes for the 2011–13 and 2013–15 periods in the Sparta-Memphis aquifer. Accompanying water-level data in this report include groundwater-quality data for the period 2010–15 in the Sparta-Memphis aquifer. Groundwater data can guide ongoing and future groundwater-monitoring efforts and inform management of the aquifers in Arkansas.
Water levels measured at 306 wells from January to May 2013 and 273 wells from January to June 2015 are graphically presented as potentiometric-surface maps. Measurements from 2011, 2013, and 2015 were used in the construction of 2011–13 and 2013–15 water-level change maps. Select long-term hydrographs are included in the report to illustrate water-level changes at the local scale.
Water-level data show the influence of climate, pumping, and conservation and management efforts on groundwater levels. With respect to climate, the study area experienced extreme drought conditions between January 2011 and December 2012. The proximate effects of drought—increased evapotranspiration, decreased recharge, and increased irrigation needs—resulted in water-level declines that were particularly notable in the northern and central portions of the study area.
Groundwater sampled in 2010–15 from 148 wells completed in the Sparta-Memphis aquifer was analyzed for specific conductance, pH, chloride (Cl) concentration, and bromide (Br) concentration. In 2015, groundwater-quality data from 103 wells completed in the Sparta-Memphis aquifer had a median specific conductance of 356 microsiemens per centimeter at 25 degrees Celsius and a median Cl concentration of 9.5 milligrams per liter (mg/L). The data show two areas of higher Cl (greater than 10 mg/L) and higher Br (greater than 0.5 mg/L) concentrations in Union, Calhoun, and Bradley Counties in southern Arkansas and Monroe and Phillips Counties in eastern-central Arkansas. A Cl and Br mixing model indicates the two regions of wells may have different sources of higher salinity. In the greater Union County area, water in most wells may be a mixture of recharge or precipitation and higher salinity groundwater from the Nacatoch aquifer. Water in wells in eastern-central Arkansas may be sourced from aquifers having a higher Cl concentration (and thus, also a higher Cl-to-Br ratio).
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Causes of population collapse and failed recovery often remain enigmatic in marine forage fish like Pacific herring (Clupea pallasii) that experience dramatic population oscillations. Diseases such as ichthyophoniasis are hypothesized to contribute to these declines, but lack of long-term datasets frequently prevents inference. Analysis of pathogen surveillance and population assessment datasets spanning 2007–2019 indicate that the age-based prevalence estimate of Ichthyophonus infection was, on average, 54% greater among a collapsed population of Pacific herring (Prince William Sound, Alaska, USA) as compared to a nearby population (Sitka Sound, Alaska, USA) that is relatively robust. During the study years, the age-based infection prevalence ranged from 14 to 44% in Prince William Sound and 5 to 33% in Sitka Sound. At both sites, the age-based infection prevalence declined over time, with an average decrease of 7% per year. Statistical analyses indicated that infection prevalence between the two populations was reduced by regional factors affecting both sites, and that these factors were independent of herring density. Infection prevalence in both populations was positively correlated with herring age and negatively correlated with the Pacific Decadal Oscillation. This study demonstrates how synthesis of environmental, stock assessment, and disease assessment data can be leveraged to elucidate epidemiological trends in diseases of wild fish.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/icesjms/fsad147","usgsCitation":"Groner, M., Bravo-Mendosa, E.D., MacKenzie, A., Gregg, J.L., Conway, C.M., Trochta, J.T., and Hershberger, P., 2023, Temporal, environmental, and demographic correlates of Ichthyophonus sp. infections in mature Pacific herring populations: ICES Journal of Marine Science, fsad147, 14 p., https://doi.org/10.1093/icesjms/fsad147.","productDescription":"fsad147, 14 p.","ipdsId":"IP-131654","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":442017,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/icesjms/fsad147","text":"Publisher Index Page"},{"id":421382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2023-09-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Groner, Maya L. 0000-0002-3381-6415","orcid":"https://orcid.org/0000-0002-3381-6415","contributorId":292708,"corporation":false,"usgs":false,"family":"Groner","given":"Maya","middleInitial":"L.","affiliations":[{"id":62985,"text":"Senior Research Scientist, Bigelow Laboratory for Ocean Sciences, 60 Bigelow Drive, East Boothbay, ME 04544","active":true,"usgs":false}],"preferred":false,"id":884529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bravo-Mendosa, Eliana D.","contributorId":330269,"corporation":false,"usgs":false,"family":"Bravo-Mendosa","given":"Eliana","email":"","middleInitial":"D.","affiliations":[{"id":78857,"text":"Previously a volunteer for the USGS Western Fisheries Research Center","active":true,"usgs":false}],"preferred":false,"id":884530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacKenzie, Ashley 0000-0002-7402-7877 amackenzie@usgs.gov","orcid":"https://orcid.org/0000-0002-7402-7877","contributorId":150817,"corporation":false,"usgs":true,"family":"MacKenzie","given":"Ashley","email":"amackenzie@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":884531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gregg, Jacob L. 0000-0001-5328-5482 jgregg@usgs.gov","orcid":"https://orcid.org/0000-0001-5328-5482","contributorId":203912,"corporation":false,"usgs":true,"family":"Gregg","given":"Jacob","email":"jgregg@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":884532,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Conway, Carla M. 0000-0002-3851-3616 cmconway@usgs.gov","orcid":"https://orcid.org/0000-0002-3851-3616","contributorId":2946,"corporation":false,"usgs":true,"family":"Conway","given":"Carla","email":"cmconway@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":884533,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Trochta, John T.","contributorId":279655,"corporation":false,"usgs":false,"family":"Trochta","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":57329,"text":"School of Aquatic and Fishery Sciences, Box 355020, University of Washington, Seattle WA, 98195, USA","active":true,"usgs":false}],"preferred":false,"id":884534,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":884535,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70248933,"text":"ofr20231069 - 2023 - Assessing the value and usage of data management planning and data management plans within the U.S. Geological Survey","interactions":[],"lastModifiedDate":"2023-10-26T20:09:51.762052","indexId":"ofr20231069","displayToPublicDate":"2023-09-27T14:00:00","publicationYear":"2023","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":"2023-1069","displayTitle":"Assessing the Value and Usage of Data Management Planning and Data Management Plans Within the U.S. Geological Survey","title":"Assessing the value and usage of data management planning and data management plans within the U.S. Geological Survey","docAbstract":"As of 2016, the U.S. Geological Survey (USGS) Fundamental Science Practices require data management plans (DMPs) for all USGS and USGS-funded research. The USGS Science Data Management Branch of the Science Analytics and Synthesis Program has been working to help the USGS (Bureau) meet this requirement. However, USGS researchers still encounter common data management-related challenges that may be reduced or eliminated by better planning. In 2021, USGS staff were given a series of surveys aimed to better understand current data management planning practices, perceptions, and needs. The survey results indicated that adoption and integration of data management planning and DMPs into USGS research project workflows are broad, if inconsistent, across USGS Science Centers and programs. The USGS Science Data Management Branch can help improve clarity and guidance on the purpose, intended audience, content, workflows, and evaluation processes for DMPs. It would also be beneficial to provide additional supporting cyberinfrastructure to support DMP activities. Survey responses indicated it would be beneficial for the Science Data Management Branch to develop a strategy, other than through DMPs, for teaching and encouraging good data management practices. Although these surveys were an opportunity for USGS staff to provide feedback on their experiences, the surveys may also have revealed the desire for more frequent evaluations, cross-disciplinary communication, and training on research data management and DMP development and integration, in the context of USGS policy, Fundamental Science Practices requirements, and overall Bureau expectations. Data management-related roles such as data manager or steward, information technologist, and repository manager may need to be formally recognized as skilled professional career positions within the Bureau. At a minimum, the best practice for USGS would be to create and maintain DMPs as living documents, integrated with existing systems that are broadly accessible to all stakeholders, and include quantitatively measurable benefits tied directly to a clearly defined purpose.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231069","programNote":"Science Synthesis, Analysis, and Research Program","usgsCitation":"Langseth, M.L., Sellers, E.A., Donovan, G.C., and Liford, A.N., 2023, Assessing the value and usage of data management planning and data management plans within the U.S. Geological Survey: U.S. Geological Survey Open-File Report 2023–1069, 44 p., https://doi.org/10.3133/ofr20231069.","productDescription":"Report: vi, 44 p.; 6 Appendixes; Data Release","onlineOnly":"Y","ipdsId":"IP-139788","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":421261,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91WKCA3","text":"USGS data release","description":"Data release associated with OFR 2023-1069","linkHelpText":"U.S. Geological Survey 2021 Data Management Planning Survey Results and Analyses"},{"id":422160,"rank":12,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231069/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1069"},{"id":421342,"rank":11,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069.xml"},{"id":421254,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix3.pdf","text":"Appendix 3","size":"180 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2023-1069 Appendix 3","linkHelpText":"- Data Management Planning Questionnaire for Center Directors"},{"id":421255,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix4.pdf","text":"Appendix 4","size":"168kB","description":"OFR 2023-1069 Appendix 4","linkHelpText":"- Data Management Planning Questionnaire for Program Coordinators and Bureau Approving Officials Appendix"},{"id":421257,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix6.pdf","text":"Appendix 6","size":"88 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 6","linkHelpText":"- Interview Questions for Data Managers"},{"id":421219,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix1.pdf","text":"Appendix 1","size":"184 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 1","linkHelpText":"- Data Management Planning Questionnaire for Researchers"},{"id":421253,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix2.pdf","text":"Appendix 2","size":"184 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 2","linkHelpText":"- Data Management Planning Questionnaire for Data Managers and Information Technologists"},{"id":421341,"rank":10,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1069/images"},{"id":421256,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069_appendix5.pdf","text":"Appendix 5","size":"108 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069 Appendix 5","linkHelpText":"- Interview Questions for Researchers"},{"id":421217,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1069/coverthb.jpg"},{"id":421218,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1069/ofr20231069.pdf","text":"Report","size":"1.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1069"}],"contact":"Director, Science Analytics and Synthesis Program
U.S. Geological Survey
P.O. Box 25046, Mail Stop 302
Denver, CO 80225
The U.S. Geological Survey and the Idaho Department of Water Resources measured groundwater levels during spring 2022 and autumn 2022 to create detailed potentiometric-surface maps for the alluvial aquifer in the Big Lost River Valley in south-central Idaho. Wells were assigned to shallow, intermediate, and deep water-bearing units based on well depth, groundwater potentiometric-surface altitude, and hydrogeologic unit. Potentiometric-surface contours were created for each of the three water-bearing units for spring 2022 and autumn 2022. Groundwater flow generally follows topography down valley to the south. The groundwater-level data also were used to calculate changes in groundwater levels from spring to autumn 2022 and from historical measurement events in 1968 and 1991 to 2022. Groundwater levels declined at most wells from spring 1968 to spring 2022 and from spring 1991 to spring 2022. Although groundwater-level changes are sensitive to interannual wet and dry periods, long-term groundwater-level declines suggest that recharge and down-valley groundwater flows are insufficient to fully recover groundwater-level declines from pumping in some parts of the alluvial aquifer in the Big Lost River Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3509","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Ducar, S.D., and Zinsser, L.M., 2023, Groundwater potentiometric-surface altitude in 2022 and groundwater-level changes between 1968, 1991, and 2022, in the alluvial aquifer in the Big Lost River Valley, south-central Idaho: U.S. Geological Survey Scientific Investigations Map 3509, 1 sheet, scale 1:150,000, 11-p. pamphlet, https://doi.org/10.3133/sim3509.","productDescription":"Pamphlet: viii, 11 p.; Map: 22.51 × 30.00 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-140355","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":500438,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115436.htm","linkFileType":{"id":5,"text":"html"}},{"id":421346,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93NQAP9","text":"USGS data release","description":"USGS data release","linkHelpText":"Groundwater potentiometric-surface contours and well numbers used to map groundwater potentiometric-surface altitude in 2022 and groundwater-level changes between 1968, 1991, and 2022 in the alluvial aquifer in the Big Lost River Valley, south-central Idaho"},{"id":421275,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sim/3509/sim3509_pamphlet.XML"},{"id":421274,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sim/3509/images"},{"id":421270,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3509/coverthb.jpg"},{"id":421271,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3509/sim3509.pdf","text":"Sheet","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3509"},{"id":421272,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sim/3509/sim3509_pamphlet.pdf","text":"Pamphlet","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3509 Pamphlet"},{"id":421273,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sim3509/full","text":"Pamphlet","linkFileType":{"id":5,"text":"html"},"description":"SIM 3509 Pamphlet"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Lost River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.0,\n 44.15\n ],\n [\n -114,\n 43.30\n ],\n [\n -113.15,\n 43.3\n ],\n [\n -113.15,\n 44.15\n ],\n [\n -114,\n 44.15\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520
Turtles are one of the most imperiled vertebrate groups in the world. With habitat destruction unabated in many places, urban and suburban greenspaces may serve as refugia for turtles, at least those species able to tolerate heavily altered landscapes. In south-central Louisiana, we have conducted a turtle capture–mark–recapture effort in two ponds in an urban greenspace for 13 yr to understand species composition, survival, and individual growth rates. We had 574 total captures of 251 individuals of five species from 2009–2021, with Trachemys scripta elegans (Red-Eared Sliders) and Sternotherus odoratus (Eastern Musk Turtles) being the most common. Apparent annual survival for T. scripta (0.79) was similar to estimates reported in other studies in altered habitats, whereas apparent annual survival for S. odoratus (0.89) was slightly or much higher than other published studies. Growth rates of T. scripta were comparable to other studies and showed both sexes have similar rates of growth until maturity, which is earlier and at a smaller size in males. The two ponds showed marked differences in captures by size, with significantly more juvenile T. scripta captured in the pond with more vegetation, depth, and a softer bottom. Most T. scripta (78.5%) that were recaptured came from the same pond from which they were originally captured. The basic demographic data gained in this study can serve as a starting point for broader questions on urbanization effects and as a comparison to more natural populations.
In 2021, the U.S. Geological Survey (USGS), in cooperation with the Bandera County River Authority and Groundwater District and the Texas Water Development Board, studied floods to produce a library of flood-inundation maps for the Sabinal River near Utopia, Texas. Digital flood-inundation maps were created for a 10-mile reach of the Sabinal River from USGS streamgage 08197936 Sabinal River below Mill Creek near Vanderpool, Tex., at the upstream boundary of the study reach, to USGS streamgage 08197970 Sabinal River at Utopia, Tex. (hereinafter referred to as the “Utopia gage”), at the downstream boundary of the study reach, and for a 7-mile reach of the West Sabinal River. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to selected gage heights (the water-surface elevation at a streamgage, commonly referred to as “stage”) at the Utopia gage. Water-surface elevations were computed for the stream reach by means of a two-dimensional unsteady-state diffusion wave model with the U.S. Army Corps of Engineers Hydrologic Engineering Center River Analysis System program. A synthetic stage-discharge rating curve at the Utopia gage was developed using a regional regression equation to construct the model boundary condition inputs, and the upper bound of the stage-discharge relation was matched to a major flood event in July 2002. The hydraulic model was used to compute water-surface elevations for 35 stages at 0.5-foot (ft) increments referenced to the Utopia gage datum and ranging from 11 ft (near bankfull) to 28 ft (estimated peak stage during the July 2002 flood event). These flood-inundation maps, in conjunction with the real-time stage data from the Utopia gage, are intended to help guide the public in taking individual safety precautions and provide emergency management personnel with a tool to efficiently manage emergency flood operations and postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235001","issn":"2328-0328 (online)","collaboration":"Prepared in cooperation with the Bandera County River Authority and Groundwater District and the Texas Water Development Board","usgsCitation":"Choi, N., 2023, Flood-inundation maps created using a synthetic rating curve for a 10-mile reach of the Sabinal River and a 7-mile reach of the West Sabinal River near Utopia, Texas, 2021 (ver. 2.0, September 2023): U.S. Geological Survey Scientific Investigations Report 2023–5001, 18 p., https://doi.org/10.3133/sir20235001.","productDescription":"Report: viii, 18 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-136311","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":435168,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CIK9ZF","text":"USGS data release","linkHelpText":"Geospatial and model dataset for flood-Inundation maps in a 10-mile reach of the Sabinal River and a 7-mile reach of the West Sabinal River near Utopia, Texas, 2021"},{"id":421129,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5001/coverthb.jpg"},{"id":500486,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114428.htm","linkFileType":{"id":5,"text":"html"}},{"id":421198,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20233001","text":"Fact Sheet 2023–3001","description":"USGS Fact Sheet 2023–3001","linkHelpText":"- Flood Warning Toolset for the Sabinal River Near Utopia, Texas"},{"id":421197,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2023/5001/versionHist.txt","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2023-5001 version history"},{"id":421196,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5001/sir20235001.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023-5001 XML"},{"id":421193,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5001/images"},{"id":421599,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235001/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5001 HTML"},{"id":421194,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5001/sir20235001.pdf","text":"Report","size":"2.52 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5001"}],"country":"United States","state":"Texas","city":"Utopia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.38878556700459,\n 29.515266260991964\n ],\n [\n -99.38878556700459,\n 29.797981198043047\n ],\n [\n -99.67156342604174,\n 29.797981198043047\n ],\n [\n -99.67156342604174,\n 29.515266260991964\n ],\n [\n -99.38878556700459,\n 29.515266260991964\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: February 2023; Version 2.0: September 2023","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 7–8 for quarter 2 (April–June) of 2023. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.
One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was a Landsat 8 Thermal Infrared Sensor (TIRS) Scene Select Mechanism (SSM) excursion anomaly. On April 21, 2023, a TIRS SSM excursion error flag was indicated in telemetry during a calibration activity when the SSM encoder was powered on and the mirror was between the nadir position and the deep space position. An initial recovery plan indicated the SSM was moving erratically, so the instrument was put into a safe state for additional troubleshooting. A second recovery plan was developed and successfully executed on April 23, 2023. Additional information about the Landsat 8 TIRS SSM excursion anomaly is available at https://www.usgs.gov/landsat-missions/news/landsat-8-level-1-product-processing-resumes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231075","usgsCitation":"Haque, M.O., Rengarajan, R., Lubke, M., Hasan, M.N., Shrestha, A., Tuli, F.T.Z., Shaw, J.L., Denevan, A., Franks, S., Ruslander, K., Micijevic, E., Choate, M.J., Anderson, C., Thome, K., Kaita, E., Barsi, J., Levy, R., Miller, J., and Ding, L., 2023, ECCOE Landsat quarterly Calibration and Validation report—Quarter 2, 2023: U.S. Geological Survey Open-File Report 2023–1075, 39 p., https://doi.org/10.3133/ofr20231075.","productDescription":"Report: vii, 39 p.; Dataset","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154779","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":421208,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":421207,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1075/images/"},{"id":421206,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1075/ofr20231075.XML","linkFileType":{"id":8,"text":"xml"}},{"id":421209,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231075/full","linkFileType":{"id":5,"text":"html"}},{"id":421204,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1075/coverthb.jpg"},{"id":421205,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1075/ofr20231075.pdf","text":"Report","size":"126 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1075"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The Equus Beds aquifer and Cheney Reservoir are primary sources for the city of Wichita’s current (2023) water supply. The Equus Beds aquifer storage and recovery (ASR) project was developed by the city of Wichita in the early 1990s to meet future water demands using the Little Arkansas River as an artificial aquifer recharge water source during above-base-flow conditions. Little Arkansas River water is removed from the river at an ASR Facility intake structure, treated using National Primary Drinking Water Regulations as a guideline, and is infiltrated into the Equus Beds aquifer through recharge basins or injected into the aquifer through recharge wells for later use. The U.S. Geological Survey, in cooperation with the city of Wichita, completed this study to quantify and characterize Little Arkansas River water-quality data. Data in this report can be used to evaluate changing conditions, provide science-based information for decision making, and help meet regulatory requirements.
Continuous (hourly) physicochemical properties were measured, and discrete water-quality samples were collected from three Little Arkansas River sites located along the easternmost extent of the Equus Beds aquifer during 1995 through 2021 over a range of streamflow conditions. The Little Arkansas River at Highway 50 near Halstead, Kansas, streamgage (U.S. Geological Survey station 07143672; hereafter referred to as the “Highway 50 site”) is located upstream from the other two sites, and the Little Arkansas River near Sedgwick, Kans., streamgage (U.S. Geological Survey station 07144100; hereafter referred to as the “Sedgwick site”) is located downstream from the other two sites; these two sites bracket most of the easternmost part of the Equus Beds aquifer. The Little Arkansas River upstream of ASR Facility near Sedgwick, Kans., streamgage (U.S. Geological Survey station 375350097262800; hereafter referred to as the “Upstream ASR site”) is located between the Highway 50 and Sedgwick sites, about 14.7 river miles (mi) downstream from the Highway 50 site, about 1.7 river mi upstream from the Sedgwick site, and immediately upstream from the ASR Facility intake structure. Surrogate models for water-quality constituents of interest (including bromide, dissolved organic carbon, 2-chloro-4-isopropylamino-6-amino-s-triazine [deethylatrazine], atrazine, and metolachlor) were updated or developed using continuously measured and concomitant discrete data. These surrogate models, along with previously developed regression models, were used to compute concentrations (at the Highway 50, Sedgwick, and Upstream ASR sites) and loads (at the Highway 50 and Sedgwick sites) during the study period. Federal criteria were used to evaluate water quality. Where applicable, water-quality data were compared to Federal national drinking-water regulations. Flow-normalized water-quality constituent trends were evaluated using Weighted Regressions on Time, Discharge, and Season (WRTDS) statistical models and water-quality trends were described using WRTDS bootstrap tests.
Continuously computed primary ion concentrations were generally larger at the Highway 50 site compared to the Sedgwick site. During the study period, the Federal secondary maximum contaminant level (SMCL) for dissolved solids was exceeded 57 percent of the time at the Highway 50 site and 38 percent of the time at the Sedgwick site. Computed bromide concentrations were larger at the Highway 50 site and exceeded the city of Wichita treatment threshold about 70, 21, and 19 percent of the time at the Highway 50, Sedgwick, and Upstream ASR sites, respectively. Chloride concentrations exceeded the Federal SMCL about 16 percent of the time at the Highway 50 site and did not exceed the SMCL at the Sedgwick site. Continuous arsenic concentrations exceeded the Federal Maximum Contaminant Level (MCL) 9 to 15 percent of the time at the Sedgwick and Highway 50 sites, respectively, during the study. Atrazine concentrations exceeded the Federal MCL 10 percent of the time at the Highway 50 and Sedgwick sites and 14 percent of the time at the Upstream ASR site during the study; computed glyphosate concentrations at the Sedgwick site never exceeded the MCL during the study.
Little Arkansas River flow-normalized primary ion concentrations during 1995 through 2021 generally had downward trends and decreases were generally larger at the Highway 50 site compared to the Sedgwick site. Dissolved solids and chloride concentrations decreased at the Highway 50 and Sedgwick sites. Bromide had no trend at the Highway 50 site and a downward trend at the Sedgwick site. Nitrate plus nitrite and total phosphorus concentrations had upward trends at the Highway 50 site but downward trends at the Sedgwick site, whereas total organic carbon had upward trends at both sites. Nitrate plus nitrite, total nitrogen, total phosphorus, and total organic carbon fluxes had upward trends at the Highway 50 and Sedgwick sites. Suspended-sediment concentrations had an upward trend at the Highway 50 site and had no trend at the Sedgwick site. Arsenic concentrations had downward trends at the Highway 50 and Sedgwick sites.
About one-quarter to one-half of the Little Arkansas River loads, including nutrients and sediment, were transported during 1 percent of the time during the study. Because streamflows are highly sensitive to climatic variation and an increase of extreme precipitation events in the Great Plains is expected, similar disproportionately large pollutant loading events may increase into the future. Continuous measurement of physicochemical properties in near-real time allowed characterization of Little Arkansas River surface water during conditions and time scales that would not have been possible otherwise and served as a complement to discrete water-quality sampling. Continuation of this water-quality monitoring will provide data to characterize changing conditions in the Little Arkansas River and possibly identify new and changing trends. Information in this report allows the city of Wichita to make informed municipal water-supply decisions using past and present water-quality conditions and trends in the watershed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235102","collaboration":"Prepared in cooperation with the city of Wichita, Kansas","usgsCitation":"Stone, M.L., and Klager, B.J., 2023, Long-term water-quality constituent trends in the Little Arkansas River, south-central Kansas, 1995–2021: U.S. Geological Survey Scientific Investigations Report 2023–5102, 103 p., https://doi.org/10.3133/sir20235102.","productDescription":"Report: ix, 103 p.; 1 Figure; 9 Tables; 5 Appendixes; Dataset","numberOfPages":"118","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-146544","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":421187,"rank":26,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_appendix10.zip","text":"Appendix 10","size":"46 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Weighted Regressions on Time, Discharge, 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