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
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Ecological restoration is critical for recovering degraded ecosystems but is challenged by variable success and low predictability. Understanding which outcomes are more predictable and less variable following restoration can improve restoration effectiveness. Recent theory asserts that the predictability of outcomes would follow an order from most to least predictable from coarse to fine community properties (physical structure > taxonomic diversity > functional composition > taxonomic composition) and that predictability would increase with more severe environmental conditions constraining species establishment. We tested this “hierarchy of predictability” hypothesis by synthesizing outcomes along an aridity gradient with 11 grassland restoration projects across the United States. We used 1829 vegetation monitoring plots from 227 restoration treatments, spread across 52 sites. We fit generalized linear mixed-effects models to predict six indicators of restoration outcomes as a function of restoration characteristics (i.e., seed mixes, disturbance, management actions, time since restoration) and used variance explained by models and model residuals as proxies for restoration predictability. We did not find consistent support for our hypotheses. Physical structure was among the most predictable outcomes when the response variable was relative abundance of grasses, but unpredictable for total canopy cover. Similarly, one dimension of taxonomic composition related to species identities was unpredictable, but another dimension of taxonomic composition indicating whether exotic or native species dominated the community was highly predictable. Taxonomic diversity (i.e., species richness) and functional composition (i.e., mean trait values) were intermittently predictable. Predictability also did not increase consistently with aridity. The dimension of taxonomic composition related to the identity of species in restored communities was more predictable (i.e., smaller residuals) in more arid sites, but functional composition was less predictable (i.e., larger residuals), and other outcomes showed no significant trend. Restoration outcomes were most predictable when they related to variation in dominant species, while those responding to rare species were harder to predict, indicating a potential role of scale in restoration predictability. Overall, our results highlight additional factors that might influence restoration predictability and add support to the importance of continuous monitoring and active management beyond one-time seed addition for successful grassland restoration in the United States.
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Canada","active":true,"usgs":false}],"preferred":false,"id":898925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ladouceur, Emma","contributorId":270938,"corporation":false,"usgs":false,"family":"Ladouceur","given":"Emma","email":"","affiliations":[{"id":56222,"text":"German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Biodiversity Synthesis & Physiological Diversity","active":true,"usgs":false}],"preferred":false,"id":898926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brudvig, Lars A.","contributorId":335644,"corporation":false,"usgs":false,"family":"Brudvig","given":"Lars","email":"","middleInitial":"A.","affiliations":[{"id":80453,"text":"Department of Plant Biology and Program in Ecology, Evolution, and Behavior, Michigan State University, Lansing, MI, USA","active":true,"usgs":false}],"preferred":false,"id":898927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laughlin, Daniel 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University Avenue, Laramie, WY, USA 82071","active":true,"usgs":false}],"preferred":false,"id":898930,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davies, Kirk W.","contributorId":255108,"corporation":false,"usgs":false,"family":"Davies","given":"Kirk","email":"","middleInitial":"W.","affiliations":[{"id":51433,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR 97720 USA","active":true,"usgs":false}],"preferred":false,"id":898931,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Svejcar, Lauren N.","contributorId":127492,"corporation":false,"usgs":false,"family":"Svejcar","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":898932,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shackelford, Nancy","contributorId":261567,"corporation":false,"usgs":false,"family":"Shackelford","given":"Nancy","email":"","affiliations":[{"id":52880,"text":"Ecology and Evolutionary Biology, University of Colorado Boulder, 1900 Pleasant St, Boulder, Colorado 80309, USA","active":true,"usgs":false}],"preferred":false,"id":898933,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70249184,"text":"sir20235107 - 2023 - Assessing the effects of chloride deicer applications on groundwater near the Siskiyou Pass, southwestern Oregon, July 2018–February 2021","interactions":[],"lastModifiedDate":"2025-07-28T13:13:06.240353","indexId":"sir20235107","displayToPublicDate":"2023-09-29T09:18:15","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5107","displayTitle":"Assessing the Effects of Chloride Deicer Applications on Groundwater near the Siskiyou Pass, Southwestern Oregon, July 2018–February 2021","title":"Assessing the effects of chloride deicer applications on groundwater near the Siskiyou Pass, southwestern Oregon, July 2018–February 2021","docAbstract":"The U.S. Geological Survey, in cooperation with the Oregon Department of Transportation (ODOT), evaluated the effects of cold-weather chloride deicers (road deicing chemicals) on groundwater quality, with a focus on chloride, near the Siskiyou Pass in southwestern Oregon. The study covered the period during July 2018 through February 2021. Between the years 2016 and 2020 ODOT applied up to 16,000 gallons per mile of chloride deicer and 143,000 pounds per mile of road salt along an 11-mile stretch of Interstate 5 (I-5) through the Siskiyou Pass. Despite the benefit of safer driving conditions, there are potentially negative environmental effects associated with the use of chloride-based deicers (such as magnesium chloride and sodium chloride). The results from this study are intended to help ODOT assess the water-quality effects from the application of chloride deicers at the Siskiyou Pass and inform decisions on how those chemicals are used.
Dissolved chloride concentrations tended to be greater in groundwater downgradient from I-5 compared to groundwater upgradient from the interstate. Specific conductance was a good predictor of dissolved chloride concentration (R2 = 0.905). Continuous monitoring showed that specific conductance measurements were greater at four downgradient spring-fed sites at the end of the study period compared with measurements at the beginning of the study. The study results indicate that chloride levels in shallow groundwater downgradient from I-5 are increasing, but dissolved chloride concentrations in domestic wells are not above the U.S. Environmental Protection Agency drinking water recommendations. The approach and methods used in this study, with modifications as site conditions warrant, can be applied in other areas of chloride deicer application to determine if groundwater is affected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235107","collaboration":"Prepared in cooperation with Oregon Department of Transportation","usgsCitation":"Gingerich, S.B., Wise, D.R., and Stonewall, A.J., 2023, Assessing the effects of chloride deicer applications on groundwater near the Siskiyou Pass, southwestern Oregon, July 2018–February 2021 (ver. 1.1, July 2025): U.S. Geological Survey Scientific Investigations Report 2023–5107, 39 p., https://doi.org/10.3133/sir20235107.","productDescription":"Report: viii, 39 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-140151","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":492943,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2023/5107/versionHistory.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version history"},{"id":421408,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D6XDIJ","text":"USGS data release","description":"USGS data release","linkHelpText":"Specific conductance and other groundwater quality data, Siskiyou Pass area, southwestern Oregon, 2018 to 2021"},{"id":421403,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5107/coverthb2.jpg"},{"id":421404,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5107/sir20235107.pdf","text":"Report","size":"7.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5107"},{"id":421405,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235107/full","text":"Report","description":"SIR 2023-5107"},{"id":421406,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5107/images"},{"id":421407,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5107/sir20235107.XML"},{"id":421409,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5107/sir20235107_appendix1.xlsx","text":"Appendix 1","size":"45 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2023-5107 Appendix 1"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.79414603940278,\n 42.22368397834566\n ],\n [\n -122.79414603940278,\n 41.9878942723297\n ],\n [\n -122.42473672058753,\n 41.9878942723297\n ],\n [\n -122.42473672058753,\n 42.22368397834566\n ],\n [\n -122.79414603940278,\n 42.22368397834566\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: September 29, 2023; Version 1.1: July 25, 2025","contact":"Director, Oregon Water Science Center
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Introduction: Large dam removals provide a restoration opportunity for shrinking coastal wetland habitats. Dam removal can increase sediment delivery to sediment-starved river deltas and estuaries by restoring natural sediment transport and mobilizing reservoir-impounded sediment. However, rapid mobilization of massive quantities of sediment stored behind large dams also constitutes a major ecological perturbation. Information is lacking on coastal habitat responses to sediment pulses of this magnitude.
Methods: Removal of two large dams along the Elwha River (Washington, USA) in 2011–2014 released ~20.5 Mt of impounded sediment, ~5.4 Mt of which were deposited in the delta and estuary (hereafter, delta). We used time series of aerial imagery, digital elevation models, and vegetation field sampling to examine plant community responses to this sediment pulse across seven years during and after dam removal.
Results: Between 2011 and 2018, the Elwha River delta increased by ~26.8 ha. Vegetation colonized ~16.4 ha of new surfaces, with mixed pioneer vegetation on supratidal beach, river bars, and river mouth bars and emergent marsh vegetation in intertidal aquatic habitats. Colonization occurred on surfaces that were higher and more stable in elevation and farther from the shoreline. Compared to established delta plant communities, vegetation on new surfaces had lower cover of dominant species and functional groups, with very low woody cover, and lower graminoid cover than dunegrass and emergent marsh communities. Over time following surface stabilization, however, vegetation on new surfaces increased in species richness, cover, and similarity to established communities. By 2018, ~1.0 ha of vegetation on new surfaces had developed into dunegrass or willow–alder communities and ~5.9 ha had developed into emergent marsh. At the same time, dam removal had few discernible effects on established delta plant communities.
Discussion: Together, these results suggest that rapid sediment mobilization during large dam removal has potential to expand coastal wetland habitat without negatively affecting established plant communities. However, as sediment loads declined in 2016–2018, new delta surfaces decreased by ~4.5 ha, and ~1.6 ha of new vegetation reverted to no vegetation. Long-term persistence of the expanded coastal habitat will depend on ongoing erosional and depositional processes under the restored natural sediment regime.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2023.1233903","usgsCitation":"Perry, L.G., Shafroth, P., Alfieri, S.J., and Miller, I.M., 2023, Coastal vegetation responses to large dam removal on the Elwha River: Frontiers in Ecology and Evolution, v. 11, 1233903, 21 p., https://doi.org/10.3389/fevo.2023.1233903.","productDescription":"1233903, 21 p.","ipdsId":"IP-153758","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":442000,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1233903","text":"Publisher Index Page"},{"id":435165,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O6NML1","text":"USGS data release","linkHelpText":"Vegetation and geomorphic surfaces in the Elwha River delta, Washington, after dam removal, derived from 2016 and 2018 aerial imagery and 2007, 2014, and 2018 field surveys"},{"id":422399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.8042115532547,\n 48.18296274689851\n ],\n [\n -123.8042115532547,\n 47.722552996994835\n ],\n [\n -123.34685932477454,\n 47.722552996994835\n ],\n [\n -123.34685932477454,\n 48.18296274689851\n ],\n [\n -123.8042115532547,\n 48.18296274689851\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Perry, Laura G.","contributorId":220048,"corporation":false,"usgs":false,"family":"Perry","given":"Laura","email":"","middleInitial":"G.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":887673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":887674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alfieri, Samuel J.","contributorId":329742,"corporation":false,"usgs":false,"family":"Alfieri","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":78705,"text":"self","active":true,"usgs":false}],"preferred":false,"id":887675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Ian M. 0000-0002-3289-6337","orcid":"https://orcid.org/0000-0002-3289-6337","contributorId":41951,"corporation":false,"usgs":false,"family":"Miller","given":"Ian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":887676,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249968,"text":"70249968 - 2023 - Biocrusts indicators of livestock grazing effects on soil stability in sagebrush steppe: A case study from a long-term experiment in the northern Great Basin","interactions":[],"lastModifiedDate":"2024-07-17T21:34:54.964345","indexId":"70249968","displayToPublicDate":"2023-09-29T07:00:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6002,"text":"Rangeland Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Biocrusts indicators of livestock grazing effects on soil stability in sagebrush steppe: A case study from a long-term experiment in the northern Great Basin","docAbstract":"Biocrusts are sensitive to changes in livestock grazing intensity in arid rangelands and may be useful indicators of ecosystem functions, particularly soil properties like soil stability, which may suggest the potential for soil erosion. We compared biocrust community composition and surface soil stability in a big sagebrush (Artemisia tridentata) steppe rangeland in the northwestern Great Basin in several paired sites, with or without long-term cattle grazing exclusion, and similar soils (mostly sandy loams), climate, and vegetation composition. We found that livestock grazing was associated with both lower surface soil stability and cover of several biocrust morphogroups, especially lichens, compared with sites with long-term livestock exclusion. Surface soil stability did not modify the effects of grazing on most biocrust components via interactive effects. Livestock grazing effects on total biocrust cover were partially mediated by changes in surface soil stability. Though lichens were more sensitive to grazing disturbance, our results suggest that moss (mostly Tortula ruralis in this site) might be a more readily observable indicator of grazing-related soil stability change in this area due to their relatively higher abundance compared with lichens (moss: mean, 8.5% cover, maximum, 96.1%, lichens: mean, 1.0% cover, maximum, 14.1%). These results highlight the potential for biocrust components as sensitive indicators of change in soil-related ecosystem functions in sagebrush steppe rangelands. However, further research is needed to identify relevant indicator groups across the wide range of biocrust community composition associated with site environmental characteristics, variable grazing systems, other rangeland health metrics, and other disturbance types such as wildfire.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2023.09.001","usgsCitation":"Copeland, S., Condon, L.A., Rosentreter, R., Miller, J., and Kahn-Abrams, M., 2023, Biocrusts indicators of livestock grazing effects on soil stability in sagebrush steppe: A case study from a long-term experiment in the northern Great Basin: Rangeland Ecology & Management, v. 91, p. 82-86, https://doi.org/10.1016/j.rama.2023.09.001.","productDescription":"5 p.","startPage":"82","endPage":"86","ipdsId":"IP-147342","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442004,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2023.09.001","text":"Publisher Index Page"},{"id":422476,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Great Basin","volume":"91","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Copeland, Stella M.","contributorId":196218,"corporation":false,"usgs":false,"family":"Copeland","given":"Stella M.","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":887850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Condon, Lea A. 0000-0002-9357-3881","orcid":"https://orcid.org/0000-0002-9357-3881","contributorId":202908,"corporation":false,"usgs":true,"family":"Condon","given":"Lea","email":"","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":887851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosentreter, Roger","contributorId":257441,"corporation":false,"usgs":false,"family":"Rosentreter","given":"Roger","affiliations":[{"id":52018,"text":"Biology Department, Boise State University, Boise, Idaho","active":true,"usgs":false}],"preferred":false,"id":887852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Jesse","contributorId":147734,"corporation":false,"usgs":false,"family":"Miller","given":"Jesse","email":"","affiliations":[{"id":16916,"text":"Dept. of Zoology, University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":887853,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kahn-Abrams, Maya","contributorId":331492,"corporation":false,"usgs":false,"family":"Kahn-Abrams","given":"Maya","email":"","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":887854,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248979,"text":"sir20235022 - 2023 - Identifying the relative importance of water-budget information needed to quantify how land-cover change affects recharge, Hawaiian Islands","interactions":[],"lastModifiedDate":"2026-03-06T20:41:42.483451","indexId":"sir20235022","displayToPublicDate":"2023-09-28T12:49:58","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5022","displayTitle":"Identifying the Relative Importance of Water-Budget Information Needed to Quantify How Land-Cover Change Affects Recharge, Hawaiian Islands","title":"Identifying the relative importance of water-budget information needed to quantify how land-cover change affects recharge, Hawaiian Islands","docAbstract":"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
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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
Compound earthquakes involving simultaneous ruptures along multiple faults often define a region’s upper threshold of maximum magnitude. Yet, the potential for linked faulting remains poorly understood given the infrequency of these events in the historic era. Geological records provide longer perspectives, although temporal uncertainties are too broad to clearly pinpoint single multifault events. Here, we use dendrochronological dating and a cosmogenic radiation pulse to constrain the death dates of earthquake-killed trees along two adjacent fault zones near Seattle, Washington to within a 6-month period between the 923 and 924 CE growing seasons. Our narrow constraints conclusively show linked rupturing that occurred either as a single composite earthquake of estimated magnitude 7.8 or as a closely spaced double earthquake sequence with estimated magnitudes of 7.5 and 7.3. These scenarios, which are not recognized in current hazard models, increase the maximum earthquake size needed for seismic preparedness and engineering design within the Puget Sound region of >4 million residents.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.adh4973","usgsCitation":"Black, B., Pearl, J., Pearson, C., Pringle, P., Frank, D., Page, M.T., Buckley, B., Cook, E.R., Harley, G.L., King, K., Hughes, J.F., Reynolds, D.J., and Sherrod, B.L., 2023, A multifault earthquake threat for the Seattle metropolitan region revealed by mass tree mortality: Science Advances, v. 9, no. 39, eadh4973, 9 p., https://doi.org/10.1126/sciadv.adh4973.","productDescription":"eadh4973, 9 p.","ipdsId":"IP-143345","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":489961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adh4973","text":"Publisher Index Page"},{"id":482643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","city":"Seattle","geographicExtents":"{\n \"type\": 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Texas, 2021","title":"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","docAbstract":"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 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, and Season Graphical Output at station 07144100"},{"id":421186,"rank":25,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_appendix9.zip","text":"Appendix 9","size":"35 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season Graphical Output at station 07143672"},{"id":421177,"rank":24,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_appendix6.zip","text":"Appendix 6","size":"2.6 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Surrogate Regression Model Archive Summaries for the Little Arkansas River upstream of ASR Facility near Sedgwick, Kansas"},{"id":421176,"rank":23,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_appendix5.zip","text":"Appendix 5","size":"2.7 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Surrogate Regression Model Archive Summaries for the Little Arkansas River near 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1995–2021"},{"id":421179,"rank":13,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table7.1.csv","text":"Table 7.1","size":"12 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season estimated mean, flow-normalized, and generalized mean concentrations for primary ions at the Little Arkansas River at Highway 50 near Halstead, Kansas, and Little Arkansas River near Sedgwick, Kans., 1995–2021"},{"id":421178,"rank":12,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_tables7.1-7.3.xlsx","text":"Tables 7.1–7.3","size":"108 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":421174,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table3.1.csv","text":"Table 3.1","size":"6.3 KB","linkFileType":{"id":7,"text":"csv"}},{"id":421173,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table3.1.xlsx","text":"Table 3.1","size":"27 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Relative percentage differences for discrete replicate pairs and detection percentages for blank discrete water-quality samples for the Little Arkansas River sites near Sedgwick, Kansas, 1995–2021"},{"id":421171,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table2.1.csv","text":"Table 2.1","size":"2.2 KB","linkFileType":{"id":7,"text":"csv"}},{"id":421172,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table2.1.xlsx","text":"Table 2.1","size":"20 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Summary statistics for continuously (hourly) measured turbidity data measured with different sensors at the Little Arkansas River at Highway 50 near Halstead, Kansas; Little Arkansas River near Sedgwick, Kans.; and Little Arkansas River upstream of ASR Facility near Sedgwick, Kans., 2004–19"},{"id":421170,"rank":7,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_fig1.1.PDF","text":"Figure 1.1","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Relations between turbidity sensors, 2004–19. A, YSI 6026 (YSI6026) and YSI 6136 (YSI6136) at the Little Arkansas River at Highway 50 near Halstead, Kansas"},{"id":421190,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":421169,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5102/images/"},{"id":421168,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102.XML","linkFileType":{"id":8,"text":"xml"}},{"id":501150,"rank":27,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115440.htm","linkFileType":{"id":5,"text":"html"}},{"id":421182,"rank":16,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_tables8.1-8.3.xlsx","text":"Tables 8.1–8.3","size":"112 KB","linkFileType":{"id":3,"text":"xlsx"}},{"id":421167,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102.pdf","text":"Report","size":"5.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5102"},{"id":421188,"rank":20,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table11.1.xlsx","text":"Table 11.1","size":"51 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Weighted Regressions on Time, Discharge, and Season estimated yearly water-quality constituent loads at the Little Arkansas River at Highway 50 near Halstead, Kansas and near Sedgwick, Kans., 1998–2021"},{"id":421166,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5102/coverthb.jpg"},{"id":421189,"rank":21,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5102/sir20235102_table11.1.csv","text":"Table 11.1","size":"14 KB","linkFileType":{"id":7,"text":"csv"}},{"id":421201,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235102/full","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.1667,\n 38.6\n ],\n [\n -98.1667,\n 37.5\n ],\n [\n -97.25,\n 37.5\n ],\n [\n -97.25,\n 38.6\n ],\n [\n -98.1667,\n 38.6\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
PyLith, a community, open-source code for modelling quasi-static and dynamic crustal deformation with an emphasis on earthquake faulting, has recently been updated with a flexible multiphysics implementation. We demonstrate the versatility of the multiphysics implementation by extending the code to model fully coupled continuum poromechanics. We verify the newly incorporated physics using standard benchmarks for a porous medium saturated with a slightly compressible fluid. The benchmarks include the 1-D consolidation problem as outlined by Terzaghi, Mandel’s problem for the 2-D case, and Cryer’s problem for the 3-D case. All three benchmarks have been added to the PyLith continuous integration test suite. We compare the closed form analytical solution for each benchmark against solutions generated by our updated code, and lastly, demonstrate that the poroelastic material formulation may be used alongside the existing fault implementation in PyLith.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggad370","usgsCitation":"Walker, R.L., Knepley, M.G., Aagaard, B.T., and Williams, C.A., 2023, Multiphysics modelling in PyLith: Poroelasticity: Geophysical Journal International, v. 235, no. 3, p. 2442-2475, https://doi.org/10.1093/gji/ggad370.","productDescription":"34 p.","startPage":"2442","endPage":"2475","ipdsId":"IP-146478","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":424189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"235","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Walker, Robert L.","contributorId":333017,"corporation":false,"usgs":false,"family":"Walker","given":"Robert","email":"","middleInitial":"L.","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":891663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knepley, Matthew G.","contributorId":333018,"corporation":false,"usgs":false,"family":"Knepley","given":"Matthew","email":"","middleInitial":"G.","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":891664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":891665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Charles A.","contributorId":333019,"corporation":false,"usgs":false,"family":"Williams","given":"Charles","email":"","middleInitial":"A.","affiliations":[{"id":36277,"text":"GNS Science","active":true,"usgs":false}],"preferred":false,"id":891666,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250550,"text":"70250550 - 2023 - Vegetation change over 140 years in a sagebrush landscape of the Rio Grande del Norte National Monument, New Mexico, USA","interactions":[],"lastModifiedDate":"2023-12-15T13:11:04.845576","indexId":"70250550","displayToPublicDate":"2023-09-26T06:58:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation change over 140 years in a sagebrush landscape of the Rio Grande del Norte National Monument, New Mexico, USA","docAbstract":"Big sagebrush (Artemisia tridentata) ecosystems across the western United States have experienced many changes in ecosystem dynamics and vegetation composition over the last century due to livestock grazing, non-native species, and changing climate and fire regimes. We conducted the first systematic investigation of historical vegetation composition and vegetation change in a sagebrush landscape in the southwestern United States, asking whether sagebrush or grass dominated the landscape historically?
The Rio Grande del Norte National Monument (RGDN), northern New Mexico, USA.
We combined General Land Office (GLO) surveys from 1881 with modern vegetation maps, field vegetation surveys, and sagebrush ages from growth ring analysis to test for changes in vegetation in the RGDN over the last 140 years.
We found that big sagebrush presence across the study area increased significantly, from being present on 16% of section lines in 1881 to 79% in 2019, and only three section lines lost sagebrush presence during that period. Concurrently, the number of section lines with low grass index more than doubled since 1881, while moderate and high grass index declined. Grass declined equally in areas where sagebrush increased and areas with no change in sagebrush, suggesting that changes in both vegetation types were catalyzed by external factors, likely including overgrazing. The growth ring analysis of 93 sagebrush revealed a maximum age of 87 years and establishment in every decade since the 1930s, consistent with the GLO results.
The significant vegetation changes in the RGDN over the last century, including an increase of sagebrush, provide important context about the shifting mosaic of grasslands and shrublands relevant to current and future management and ecosystem dynamics.
","language":"English","publisher":"Wiley","doi":"10.1111/jvs.13202","usgsCitation":"Fox, K., Margolis, E.Q., Lopez, M.K., Kasten, E., and Stevens, J., 2023, Vegetation change over 140 years in a sagebrush landscape of the Rio Grande del Norte National Monument, New Mexico, USA: Journal of Vegetation Science, v. 34, no. 5, e13202, 17 p., https://doi.org/10.1111/jvs.13202.","productDescription":"e13202, 17 p.","ipdsId":"IP-151212","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":423620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Rio Grande del Norte National Monument","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.5540076425751,\n 37.026637990156544\n ],\n [\n -106.5540076425751,\n 36.224664603824266\n ],\n [\n -105.13109401921486,\n 36.224664603824266\n ],\n [\n -105.13109401921486,\n 37.026637990156544\n ],\n [\n -106.5540076425751,\n 37.026637990156544\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"34","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Fox, Kara","contributorId":261706,"corporation":false,"usgs":false,"family":"Fox","given":"Kara","email":"","affiliations":[],"preferred":false,"id":890344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Margolis, Ellis Q. 0000-0002-0595-9005 emargolis@usgs.gov","orcid":"https://orcid.org/0000-0002-0595-9005","contributorId":173538,"corporation":false,"usgs":true,"family":"Margolis","given":"Ellis","email":"emargolis@usgs.gov","middleInitial":"Q.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":890345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lopez, Manuel K.","contributorId":298167,"corporation":false,"usgs":false,"family":"Lopez","given":"Manuel","email":"","middleInitial":"K.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":890346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kasten, Ella","contributorId":332521,"corporation":false,"usgs":false,"family":"Kasten","given":"Ella","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":890347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stevens, J.T.","contributorId":332522,"corporation":false,"usgs":false,"family":"Stevens","given":"J.T.","email":"","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":890348,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256445,"text":"70256445 - 2023 - Lessons learned in applying decision analysis to natural resource management for high stakes issues surrounded by uncertainty","interactions":[],"lastModifiedDate":"2024-08-02T15:54:38.642442","indexId":"70256445","displayToPublicDate":"2023-09-25T10:49:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14243,"text":"Decision Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Lessons learned in applying decision analysis to natural resource management for high stakes issues surrounded by uncertainty","docAbstract":"Management agencies are tasked with difficult decisions for conservation and management of natural resources. These decisions are difficult because of ecological and social uncertainties, the potential for multiple decision makers from multiple jurisdictions, and the need to account for the diverse values of stakeholders. Decision analysis provides a framework for accounting for these difficulties when making conservation and management decisions. We discuss the benefits of the application of decision analysis for these types of issues and provide insights from three case studies from the Laurentian Great Lakes. These case studies describe applications of decision analysis for decisions within an agency (management of double-crested cormorant), among agencies (response to invasive grass carp), and among agencies and stakeholders (sustainable fisheries harvest management). These case studies provide insight into the ways that decision analysis can be useful for conservation and management of natural resources, but we also highlight future needs for decision making for these resources. In particular, applications of decision analysis for conservation and management would benefit from enhanced integration of both ecological and social science, inclusion of a broader base of stakeholders and rightsholders, and better educational opportunities surrounding decision analysis for undergraduates and graduate students of natural resources management programs. Specific lessons from our experiences include the importance of establishing trust and transparency early through the formation of a working group, collaboratively defining objectives and evaluating uncertainties, risks, and tradeoffs, and implementing participatory modeling processes with an independent facilitator with appropriate quantitative skills.
","language":"English","publisher":"Informs","doi":"10.1287/deca.2023.0015","usgsCitation":"Robinson, K.F., Dufour, M.R., Fischer, J., Herbst, S.J., Jones, M., Nathan, L.R., and Newcomb, T.J., 2023, Lessons learned in applying decision analysis to natural resource management for high stakes issues surrounded by uncertainty: Decision Analysis, v. 20, no. 4, p. 326-342, https://doi.org/10.1287/deca.2023.0015.","productDescription":"17 p.","startPage":"326","endPage":"342","ipdsId":"IP-149566","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":442032,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://osf.io/3bgt9","text":"External Repository"},{"id":432151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Kelly Filer 0000-0001-8109-9492","orcid":"https://orcid.org/0000-0001-8109-9492","contributorId":340631,"corporation":false,"usgs":true,"family":"Robinson","given":"Kelly","email":"","middleInitial":"Filer","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":907415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischer, Jason L.","contributorId":241112,"corporation":false,"usgs":false,"family":"Fischer","given":"Jason L.","affiliations":[],"preferred":false,"id":907416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herbst, Seth J.","contributorId":11102,"corporation":false,"usgs":true,"family":"Herbst","given":"Seth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":907417,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jones, Michael L.","contributorId":126763,"corporation":false,"usgs":false,"family":"Jones","given":"Michael L.","affiliations":[{"id":6600,"text":"Qauntitative Fisheries Center, Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":907418,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nathan, Lucas R.","contributorId":340047,"corporation":false,"usgs":false,"family":"Nathan","given":"Lucas","email":"","middleInitial":"R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":907419,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Newcomb, Tammy J.","contributorId":13908,"corporation":false,"usgs":true,"family":"Newcomb","given":"Tammy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":907420,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70248995,"text":"70248995 - 2023 - Crop water use dynamics over arid and semi-arid croplands in the lower Colorado River Basin","interactions":[],"lastModifiedDate":"2025-12-11T22:25:34.900135","indexId":"70248995","displayToPublicDate":"2023-09-25T06:49:56","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16883,"text":"European Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Crop water use dynamics over arid and semi-arid croplands in the lower Colorado River Basin","docAbstract":"Numerous studies have evaluated the application of Remote Sensing (RS) techniques for mapping actual evapotranspiration (ETa) using Vegetation-Index-based (VI-based) and surface energy balance methods (SEB). SEB models computationally require a large effort for application. VI-based methods are fast and easy to apply and could therefore potentially be applied at high resolution; however, the accuracy of VI-based methods in comparison to SEB-based models remains unclear. We tested the ETa computed with the modified 2-band Enhanced Vegetation Index (METEVI2) implemented in the Google Earth Engine – for mapping croplands’ water use dynamics in the Lower Colorado River Basin. We compared METEVI2 with the well-established RS-based products of OpenET (Ensemble, eeMETRIC, SSEBop, SIMS, PT_JPL, DisALEXI and geeSEBAL). METEVI2 was then evaluated with measured ETa from four wheat fields (2017–2018). Results indicated that the monthly ETa variations for METEVI2 and OpenET models were comparable, though of varying magnitudes. On average, METEVI2 had the lowest difference rate from the average observed ETa with 17 mm underestimation, while SIMS had the highest difference rate (82 mm). Findings show that METEVI2 is a cost-effective ETa mapping tool in drylands to track crop water use. Future studies should test METEVI2’s applicability to croplands in more humid regions.
Lunar red spots are small spectrally red features that have been proposed to be the result of non-mare volcanism. Studies have shown that a number of red spots are silicic, and are spectrally distinct from both highlands and mare compositions. In this work, we use data from LRO Diviner, Mini-RF, and Arecibo to investigate the material properties of 10 red spots. We create albedo maps using Diviner daytime solar reflectance data to use as an input to our improved thermophysical model, and calculate the rock abundance (RA) and H-parameter values that best fit Diviner nighttime thermal infrared radiance measurements. The H-parameter can be considered analogous to the thermal inertia of the regolith, with a high H-parameter corresponding to low thermal inertia. We find that the red spots generally have low RA, and do not have a uniform H-parameter but contain localized regions of high H-parameter. We additionally find that the red spots have a low circular polarization ratio (CPR) in many of the same locations that show a low RA and high H-parameter. Low RA, high H-parameter, and low CPR indicate a relative lack of rocks larger than ∼10 cm, which is consistent with previous findings of a mantling of fine-grained pyroclastic material for at least three red spots. Areas with high H-parameter but that do not show clear signs of pyroclastics in other data sets may be evidence of previously undiscovered pyroclastics, or could be due to the unique physical properties (e.g., porosity, rock strength/breakdown resistance) of the rocks that make up the red spots.
","language":"English","publisher":"American Astronomical Society","doi":"10.3847/PSJ/acf134","usgsCitation":"Byron, B., Elder, C., Glotch, T., Hayne, P., Pigue, L.M., and Cahill, J.T., 2023, Evidence for fine-grained material at lunar red spots: Insights from thermal infrared and radar data sets: Planetary Science Journal, v. 4, no. 9, 182, 24 p., https://doi.org/10.3847/PSJ/acf134.","productDescription":"182, 24 p.","ipdsId":"IP-152412","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":442043,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/psj/acf134","text":"Publisher Index Page"},{"id":422001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Moon","volume":"4","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-09-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Byron, Benjamin","contributorId":331016,"corporation":false,"usgs":false,"family":"Byron","given":"Benjamin","email":"","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":886491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elder, Catherine","contributorId":331017,"corporation":false,"usgs":false,"family":"Elder","given":"Catherine","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":886492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glotch, Timothy","contributorId":331018,"corporation":false,"usgs":false,"family":"Glotch","given":"Timothy","affiliations":[{"id":25401,"text":"Stony Brook University, Stony Brook, NY","active":true,"usgs":false}],"preferred":false,"id":886493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayne, Paul O.","contributorId":331019,"corporation":false,"usgs":false,"family":"Hayne","given":"Paul","middleInitial":"O.","affiliations":[{"id":79091,"text":"Laboratory for Atmospheric and Space Physics, University of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":886494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pigue, Lori M. 0000-0002-6675-6877","orcid":"https://orcid.org/0000-0002-6675-6877","contributorId":330994,"corporation":false,"usgs":true,"family":"Pigue","given":"Lori","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":886495,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cahill, Joshua T. S.","contributorId":331020,"corporation":false,"usgs":false,"family":"Cahill","given":"Joshua","email":"","middleInitial":"T. S.","affiliations":[{"id":7166,"text":"Johns Hopkins University Applied Physics Laboratory","active":true,"usgs":false}],"preferred":false,"id":886496,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70249313,"text":"70249313 - 2023 - Eruption of stagnant lava from an inactive perched lava lake","interactions":[],"lastModifiedDate":"2023-10-04T11:40:20.695469","indexId":"70249313","displayToPublicDate":"2023-09-23T06:37:37","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":"Eruption of stagnant lava from an inactive perched lava lake","docAbstract":"Lava flow hazards are usually thought to end when the erupting vent becomes inactive, but this is not always the case. At Kīlauea in August 2014, a spiny ʻaʻā flow erupted from the levee of a crusted perched lava lake that had been inactive for a month, and the surface of the lava lake subsided as the flow advanced downslope over the following few days. Topography constructed from oblique aerial photographs using structure-from-motion (SfM) software shows that the volume of the flow (∼68,000 m3) closely matches the volume of subsidence of the crusted lava lake (∼64,000 m3). The similarity of these volumes, along with the textural characteristics of the lava, shows that the lava that fed the flow had been stored beneath the surface of the perched lava lake, and that the flow was not generated by reactivation of the vent. This extends the duration of the local lava flow hazard presented by perched lava lakes and similar flow field structures that store lava, such as rootless shields. The flow probably occurred because the density of the lava beneath the crusted surface of the perched lava lake increased through loss of gas bubbles until it was able to penetrate the less-dense levee, which was composed of relatively vesicular overflows. The flow is thus equivalent to the lava seeps described previously at Kīlauea and elsewhere. We present a simple physical model for the pressure change at the base of a densifying body of lava, which we apply to this case study, and which could be applied to similar scenarios elsewhere.
Amphibians are among the most sensitive taxa to climate change, and species inhabiting arid and semiarid landscapes at the extremes of their range are especially vulnerable to drought. The Jack Creek, Oregon, USA, population of Oregon spotted frogs (Rana pretiosa) faces unique challenges because it occupies the highest elevation site in the species' extant range and one that has been transformed by loss of American beavers (Castor canadensis), which historically maintained open water. We evaluated the effects of drought mitigation (addition of excavated ponds) on relationships between local and regional water availability, inactive legacy beaver dams, and Oregon spotted frog population dynamics in the Jack Creek system. We conducted egg mass surveys and capture-mark-recapture sampling at a treatment reach with excavated ponds and 3 reference reaches over 13 years; surveys spanned a period before and after pond excavation at the treatment and 1 primary comparison reference reach. We analyzed data using a combination of robust design capture-mark-recapture estimators and generalized linear mixed models to characterize population dynamics. Adult Oregon spotted frog survival was approximately 19.5% higher at the treatment reach than the primary reference reach during the study period. Annual survival was most strongly associated with late summer vegetation greenness, a proxy for water availability, and males had higher survival than females. Among the 4 study reaches, the treatment reach consistently had higher late summer vegetation greenness, and the hydrology functioned more independently of regional precipitation patterns relative to the reference reaches; however, these dynamics were not linked to pond excavation. Breeding was concentrated in 2 legacy beaver ponds that were deepened by excavation during the study compared to an unexcavated beaver pond, 2 excavated ponds without legacy beaver dams, and 9 reference ponds. These results point to the benefit of enhancing existing beaver structures and indicate that management actions aimed at maintaining surface water for breeding in spring and saturated soils and ponded water for adults in late summer would benefit this unique population of Oregon spotted frogs in the face of drought.
Introduction: Declining hunter populations across North America present wildlife management agencies with the prospect of declining revenues for wildlife conservation and management and the need for new tools to evaluate management strategies and predict future status of game species and hunters.
Methods: Here we present a modeling framework and potential decision support tool for managers to link future hunter population dynamics to regulatory restrictiveness, prey abundance, and harvest success. Our hunter model is parameterized based on the authors’ judgment and can be used for demonstration purposes. We simulated three scenarios of restricted harvest, moderate harvest and liberal harvest.
Results: Our simulations show that even though liberal harvest predicts higher cumulative license sales revenue, it corresponds with a slight decline in buck abundance over 10 years. In contrast, highly restrictive harvest corresponds with deer population growth, but a near collapse of hunter populations. Our model demonstrates that managers might face tradeoffs between managing for deer population abundance and hunting revenue and clarifies how these factors might affect decision making.
Discussion: The utility of our tool would be dependent on accessing data on hunter retention and recruitment, however, the strength of our paper is in highlighting a new way of thinking about and potentially addressing these potential tradeoffs. Further, these simulations demonstrate that these tools could be used to evaluate management strategies but also highlight uncertainties, establish research priorities, and potentially design an adaptive management framework.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fcosc.2023.1265806","usgsCitation":"McGowan, C., Price Tack, J., Silvano, A., and Grand, J.B., 2023, Models for linking hunter retention and recruitment to regulations and game populations: Frontiers in Conservation Science, v. 4, 126506, 9 p., https://doi.org/10.3389/fcosc.2023.1265806.","productDescription":"126506, 9 p.","ipdsId":"IP-140942","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":442050,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2023.1265806","text":"Publisher Index Page"},{"id":432487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"4","noUsgsAuthors":false,"publicationDate":"2023-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":3381,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":907711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price Tack, Jennifer L.","contributorId":340942,"corporation":false,"usgs":false,"family":"Price Tack","given":"Jennifer L.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":907712,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silvano, Amy","contributorId":340943,"corporation":false,"usgs":false,"family":"Silvano","given":"Amy","affiliations":[{"id":35940,"text":"Alabama Division of Wildlife and Freshwater Fisheries","active":true,"usgs":false}],"preferred":false,"id":907713,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907714,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248851,"text":"70248851 - 2023 - Salinity trends in a groundwater system supplemented by 50 years of imported Colorado River water","interactions":[],"lastModifiedDate":"2023-10-23T16:09:01.925637","indexId":"70248851","displayToPublicDate":"2023-09-21T09:12:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16870,"text":"Environmental Science & Technology Water","active":true,"publicationSubtype":{"id":10}},"title":"Salinity trends in a groundwater system supplemented by 50 years of imported Colorado River water","docAbstract":"The Indio subbasin of the Coachella Valley is a desert area of southern California where a growing population depends primarily on groundwater for drinking and agricultural uses. The aquifer system has been supplemented with Colorado River water through managed recharge and widespread irrigation since the mid-20th century. We use a combination of geochemical modeling and trend analysis to identify changes in total dissolved solids through time, elucidate the sources of dissolved solids, and quantify the extent of contributions from those sources throughout the Indio subbasin. We conclude that recharged Colorado River water is the primary source and driver of increasing salinity, particularly in areas immediately downgradient from the recharge locations and in the eastern part of the subbasin away from the recharge ponds due to irrigation using imported water. Other contributions of dissolved solids to groundwater resources include geothermal waters, wastewater effluent, and agricultural return flow, although their effects are more localized. This study presents a broadly applicable framework for identifying sources of dissolved solids in groundwater wells and salinity trends at a regional scale in a large data set.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acsestwater.3c00239","usgsCitation":"Harkness, J.S., McCarthy, P.M., Jurgens, B., and Levy, Z., 2023, Salinity trends in a groundwater system supplemented by 50 years of imported Colorado River water: Environmental Science & Technology Water, v. 3, no. 10, p. 3253-3264, https://doi.org/10.1021/acsestwater.3c00239.","productDescription":"12 p.","startPage":"3253","endPage":"3264","ipdsId":"IP-148329","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":442051,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acsestwater.3c00239","text":"Publisher Index Page"},{"id":435173,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KUBQKM","text":"USGS data release","linkHelpText":"Inverse Model Data for: Salinity trends in a groundwater system supplemented by 50 years of imported Colorado River water"},{"id":421073,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Coachella Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.13573439891272,\n 33.44388210065128\n ],\n [\n -115.83959902010358,\n 33.47539980820645\n ],\n [\n -116.10770512437531,\n 33.77373918192059\n ],\n [\n -116.49280298323828,\n 33.977110302145775\n ],\n [\n -116.5817654632921,\n 33.996309353196736\n ],\n [\n -116.645135997029,\n 33.92049840312886\n ],\n [\n -116.51108294489313,\n 33.79298404948595\n ],\n [\n -116.29781672558602,\n 33.66122225831866\n ],\n [\n -116.21372890197347,\n 33.55363612855925\n ],\n [\n -116.13573439891272,\n 33.44388210065128\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","issue":"10","noUsgsAuthors":false,"publicationDate":"2023-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Harkness, Jennifer S. 0000-0001-9050-2570 jharkness@usgs.gov","orcid":"https://orcid.org/0000-0001-9050-2570","contributorId":224299,"corporation":false,"usgs":true,"family":"Harkness","given":"Jennifer","email":"jharkness@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCarthy, Patrick Michael 0000-0002-5492-1409","orcid":"https://orcid.org/0000-0002-5492-1409","contributorId":330033,"corporation":false,"usgs":true,"family":"McCarthy","given":"Patrick","email":"","middleInitial":"Michael","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883885,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203409,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Levy, Zeno F. 0000-0003-4580-2309","orcid":"https://orcid.org/0000-0003-4580-2309","contributorId":222340,"corporation":false,"usgs":true,"family":"Levy","given":"Zeno","middleInitial":"F.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883887,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248843,"text":"70248843 - 2023 - Relating absolute abundance of an estuarine fish to habitat area in an urbanizing environment","interactions":[],"lastModifiedDate":"2023-09-22T12:22:47.101959","indexId":"70248843","displayToPublicDate":"2023-09-21T07:20:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16867,"text":"Marine Ecologly Progressive Series","active":true,"publicationSubtype":{"id":10}},"title":"Relating absolute abundance of an estuarine fish to habitat area in an urbanizing environment","docAbstract":"Organisms that rely on salt marsh habitat are an important trophic link, helping to maintain estuarine ecosystem productivity. We used GIS to quantify intertidal (assumed salt marsh) area from aerial photographs taken in 1939 and from software-supplied satellite imagery taken in 2021 for tidal creeks in North Carolina (USA) that have experienced minor (<20%), moderate (20-60%), or substantial (>60%) losses of intertidal habitat over the 8 decades. The current (2022) absolute abundance of adult Fundulus heteroclitus, a trophically important resident fish in US Atlantic estuaries, was estimated over each season in each creek by fitting a Lincoln-Petersen model to tag-recapture data. Current abundances of F. heteroclitus were lowest in creeks with the lowest intertidal area. The median and 2.5/97.5 credible intervals of the posterior probability distribution for the slope of a regression model relating current fish abundance to current intertidal area were positive, demonstrating that intertidal area was a meaningful covariate of abundance. Loss of intertidal area in the creeks between 1939 and 2021 ranged from 8 to 93%. The correlation between current intertidal area and historical loss of this habitat was negative and significant (Pearson r = -0.91, p = 0.012). Parameters from the regression relating current abundance to intertidal area were used to estimate historic F. heteroclitus abundances in each creek using GIS-derived estimates of historic intertidal area. Historic abundances were predicted to have been on average (across study creeks) 7.5 times greater in 1939 than in 2022. Reduced abundances, and thus reduced trophic relay by F. heteroclitus to higher-order consumers, can be expected in estuaries that have lost salt marsh due to inter-decadal development.
","language":"English","publisher":"MDPI","doi":"10.3354/meps14387","usgsCitation":"Rudershausen, P.J., Lombardo, S.M., Stilson, G.R., and O'Donnell, M.J., 2023, Relating absolute abundance of an estuarine fish to habitat area in an urbanizing environment: Marine Ecologly Progressive Series, v. 719, https://doi.org/10.3354/meps14387.","productDescription":"16 p.","startPage":"92","ipdsId":"IP-146609","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":421066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"719","edition":"77","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rudershausen, Paul J.","contributorId":330010,"corporation":false,"usgs":false,"family":"Rudershausen","given":"Paul","email":"","middleInitial":"J.","affiliations":[{"id":78765,"text":"Department of Applied Ecology, North Carolina State University, Center for Marine Sciences and Technology","active":true,"usgs":false}],"preferred":false,"id":883852,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lombardo, Steven M.","contributorId":330011,"corporation":false,"usgs":false,"family":"Lombardo","given":"Steven","email":"","middleInitial":"M.","affiliations":[{"id":78766,"text":"Bonefish and Tarpon Trust","active":true,"usgs":false}],"preferred":false,"id":883853,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stilson, George R.","contributorId":330012,"corporation":false,"usgs":false,"family":"Stilson","given":"George","email":"","middleInitial":"R.","affiliations":[{"id":78767,"text":"North Carolina Department of the Environment and Natural Resources, Division of Marine Fisheries","active":true,"usgs":false}],"preferred":false,"id":883854,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O'Donnell, Matthew J. 0000-0002-9089-2377","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":295467,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Matthew","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":883855,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249300,"text":"70249300 - 2023 - Future marsh evolution due to tidal changes induced by human adaptation to sea level rise","interactions":[],"lastModifiedDate":"2023-10-04T12:07:02.06102","indexId":"70249300","displayToPublicDate":"2023-09-21T07:00:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5053,"text":"Earth's Future","active":true,"publicationSubtype":{"id":10}},"title":"Future marsh evolution due to tidal changes induced by human adaptation to sea level rise","docAbstract":"With sea level rise threatening coastal development, decision-makers are beginning to act by modifying shorelines. Previous research has shown that hardening or softening shorelines may change the tidal range under future sea level rise. Tidal range can also be changed by natural factors. Coastal marshes, which humans increasingly depend on for shoreline protection, are ecologically sensitive to tidal range. Therefore, it is critical to examine how changes in tidal range could influence marsh processes. A marsh accretion model was used to investigate the ecological response of a San Francisco Bay, California, USA marsh to multiple tidal range scenarios and sea level rise from 2010 to 2100. The scenarios include a baseline scenario with no shoreline modifications in the estuary, a shoreline hardening scenario that amplifies the tidal range, and 14 tidal range scenarios as a sensitivity analysis that span tidal amplification and reduction of the baseline scenario. The modeling results expose key tradeoffs to consider when planning for sea level rise. Compared to the baseline, the hardening scenario shows minor differences. However, further tidal amplification prolongs marsh survival but decreases Sarcocornia pacifica cover, an important species for certain threatened wildlife and an effective attenuator of wave energy. Conversely, tidal reduction precipitates marsh drowning but shows gains in Sarcocornia pacifica cover. These mixed impacts of tidal amplification and reduction shown by the model indicate potential tradeoffs in relation to marsh survival, habitat characteristics, and shoreline protection. This study suggests the need for a cross-sectoral, regional approach to sea level rise adaptation.
The soil and groundwater at the Central Chemical facility, Hagerstown, Maryland, are contaminated due to the blending and production of pesticides and fertilizers during much of the 20th century. Remedial investigations focus on two operable units (OU) consisting of the surface soils and waste disposal lagoon (OU-1) and the groundwater (OU-2). The contaminants of concern (COC) for groundwater include 41 compounds categorized within the subgroups of volatile organic compounds (VOCs), semi-volatile organic compounds (SVOCs), pesticides, and metals. The purpose of this report is to provide a conceptual site model of the hydrogeology and groundwater contaminant transport at and near the Central Chemical facility. The conceptual model was developed through review, synthesis, and interpretation of the results of hydrogeologic, soil, and other environmental investigations conducted at and in the vicinity of the facility in recent decades and is intended to support plans for environmental remediation of the groundwater in OU-2.
The extent and nature of the groundwater contaminant plume associated with the bedrock was characterized for OU-2 of the site. Lithologic and structural comparisons between shallow soil, weathered rock, and epikarst and deeper competent but bedded, dipping, fractured, and karstic limestones illustrate two connected flow systems—a surficial flow system consisting of the unconsolidated overburden and epikarst and a structurally dominant bedrock flow system below the epikarst. Uncertainties exist regarding the nature and transport of contaminants within the epikarst system particularly within voids and perched epikarst water tables. Karst dissolution features are observed within the site including sinkholes and dissolution voids within wells at the site. Of interest, one well in the northern part of the study area (MW-J-71) appears to have a dissolution void connected to an offsite well (OW-2-115) farther to the north. This connection is supported by groundwater level data and elevated concentrations of total suspended solids (TSS) and chlorobenzene in both wells. The high level of TSS supports the possibility of offsite transport of particle-bound contaminants within the conduit system. Episodically elevated concentrations of COC from different groups also were observed within select wells in the epikarst near the waste disposal lagoon (particularly MW-A-51). The variability observed between different COC within the same well may be the result of additional contaminated source materials unrelated to the disposal lagoon. Storage and episodic transport of contaminated material within the epikarst system has the potential to hinder remediation efforts if not considered in the remedial action.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225011","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Needham, T.P., Fiore, A.R., Ator, S.W., Raffensperger, J.P., Smith, M.B., Bellmyer, N.M., Dugan, C.M., and Morel, C.J., 2023, Geology, hydrology, and groundwater contamination in the vicinity of Central Chemical facility, Hagerstown, Maryland: U.S. Geological Survey Scientific Investigations Report 2022–5011, 62 p., https://doi.org/10.3133/sir20225011.","productDescription":"ix, 62 p.","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127106","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":500691,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115410.htm","linkFileType":{"id":5,"text":"html"}},{"id":420978,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5011/images/"},{"id":420977,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5011/sir20225011.XML"},{"id":420976,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225011/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5011"},{"id":420975,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5011/sir20225011.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5011"},{"id":420974,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5011/coverthb.jpg"}],"country":"United States","state":"Maryland","city":"Hagerstown","otherGeospatial":"Central Chemical Facility","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.7208,\n 39.6542\n ],\n [\n -77.7208,\n 39.6597\n ],\n [\n -77.726,\n 39.6597\n ],\n [\n -77.726,\n 39.6542\n ],\n [\n -77.7208,\n 39.6542\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Maryland-Delaware-D.C. Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228
Sea lamprey (Petromyzon marinus) is an invasive species that is a significant source of mortality for populations of valued fish species across the North American Great Lakes. Large annual control programs are needed to reduce the species' impacts; however, the number of successfully spawning adults cannot currently be accurately assessed. In this study, effective breeding size (Nb) and the minimum number of spawning adults (Ns) were estimated for larval cohorts from 17 tributaries across all five Great Lakes using single nucleotide polymorphisms (SNP) genotyped via RAD-capture sequencing. Reconstructed larval pedigrees showed substantial variability in the size and number of full- and half-sibling groups, Nb (<1–367), and Ns (5–545) among streams. Generalized linear models examining the effects of stream environmental characteristics and aspects of sampling regimes on Nb and Ns estimates identified sample size, the number of sampling sites, and drainage area as important factors predicting Nb and Ns. Correlations between Nb, Ns, and capture–mark–recapture estimates of adult census size (Nc) increased when streams with small sample sizes (n < 50) were removed. Results collectively indicate that parameters estimated from genetic data can provide valuable information on spawning adults in a river system, especially if sampling regimes are standardized and physical stream covariates are included.