{"pageNumber":"30","pageRowStart":"725","pageSize":"25","recordCount":16495,"records":[{"id":70242001,"text":"ofr20231025 - 2023 - User needs assessment for postfire debris-flow inundation hazard products","interactions":[],"lastModifiedDate":"2023-09-21T15:17:22.443946","indexId":"ofr20231025","displayToPublicDate":"2023-04-06T09:10:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1025","displayTitle":"User Needs Assessment for Postfire Debris-Flow Inundation Hazard Products","title":"User needs assessment for postfire debris-flow inundation hazard products","docAbstract":"Debris flows are a type of mass movement that is more likely after wildfires, and while existing hazard assessments evaluate the rainfall intensities that are likely to trigger debris flows, no operational hazard assessment exists for identifying the areas where they will run out after initiation. Fifteen participants who work in a wide range of job functions associated with southern California postfire hazards were selected using purposive sampling for unstructured interviews about useful characteristics and needs for postfire debris-flow inundation hazard assessments. The interview guide was developed by a team of social and physical scientists following best practices for engaging with users. The guide focused on target information that could influence ongoing or not-yet-initiated research on debris-flow physics and hazard assessment methodology. Following standard methods for user needs assessment, the audio from the unstructured interviews was recorded, transcribed, and analyzed using a thematic coding scheme. Participants reported engaging with postfire debris-flow inundation as one of multiple postfire hazards and their information needs reflect this breadth. Most participants were from organizations with life and property mandates, and this focused their concerns on where debris-flow inundation could impact people’s physical safety, the ability of populations to egress, and damage to property. Common comments included, (1) the need to interpret inundation hazard assessments in the context of forecast rainfall—which are typically associated with different timeframes, 15 and 60 minutes, respectively; (2) the need to provide multiple scenarios in a hazard assessment to show how the hazard changes under different external factors such as varying rainfall intensity; and (3) the tension between fully reflecting all sources of uncertainty in identifying impacted areas and a high level of precision needed to determine evacuation zones in order to reduce evacuation fatigue. Participants saw utility in both low-resolution hazard assessments over large areas and fine-resolution targeted assessments over small areas, noting that the identification of target areas could pose an ethical challenge because some areas might be prioritized over others. Participants were concerned about the hazard posed by the continuum of postfire hydrologic hazards, including hyperconcentrated flows. Finally, participants recognized that the shrinking time window between the end of fire season and the start of the wet season in southern California makes the production, interpretation, and use of rapid postfire debris-flow inundation hazard assessments both important and challenging.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231025","programNote":"Landslide Hazards Program","usgsCitation":"Barnhart, K.R., Romero, V.Y., and Clifford, K.R., 2023, User needs assessment for postfire debris-flow inundation hazard products: U.S. Geological Survey Open-File Report 2023–1025, 25 p., https://doi.org/10.3133/ofr20231025.","productDescription":"vi, 25 p.","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-140742","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":415140,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1025/coverthb.jpg"},{"id":415144,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1025/images/"},{"id":415143,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1025/ofr20231025.XML"},{"id":421028,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231025/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1025"},{"id":415141,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1025/ofr20231025.pdf","text":"Report","size":"1.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1025"}],"country":"United States","state":"California","city":"Montecito","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.70234862012427,\n              34.497719835273585\n            ],\n            [\n              -119.70234862012427,\n              34.41216398408224\n            ],\n            [\n              -119.52439809003698,\n              34.41216398408224\n            ],\n            [\n              -119.52439809003698,\n              34.497719835273585\n            ],\n            [\n              -119.70234862012427,\n              34.497719835273585\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/geologic-hazards-science-center\" data-mce-href=\"https://www.usgs.gov/centers/geologic-hazards-science-center\">Geologic Hazards Science Center</a><br>U.S. Geological Survey<br>1711 Illinois Street<br>Golden, Colorado 80401</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgements</li><li>Abstract</li><li>Introduction and Motivation</li><li>Elements of Postfire Debris-Flow Hazards</li><li>Connection with the USGS Risk Plan</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-04-06","noUsgsAuthors":false,"publicationDate":"2023-04-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":868489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romero, Veronica 0000-0002-8124-4386","orcid":"https://orcid.org/0000-0002-8124-4386","contributorId":302660,"corporation":false,"usgs":true,"family":"Romero","given":"Veronica","email":"","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clifford, Katherine R. 0000-0002-1385-8765","orcid":"https://orcid.org/0000-0002-1385-8765","contributorId":303904,"corporation":false,"usgs":false,"family":"Clifford","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":38977,"text":"University of Colorado at Boulder","active":true,"usgs":false}],"preferred":false,"id":868491,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70241874,"text":"fs20233012 - 2023 - U.S. Geological Survey and Blackfeet Water Department Hydrologic Assessment of the Blackfeet Indian Reservation, Montana","interactions":[],"lastModifiedDate":"2026-02-06T21:58:06.716158","indexId":"fs20233012","displayToPublicDate":"2023-04-03T15:12:20","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3012","displayTitle":"U.S. Geological Survey and Blackfeet Water Department Hydrologic Assessment of the Blackfeet Indian Reservation, Montana","title":"U.S. Geological Survey and Blackfeet Water Department Hydrologic Assessment of the Blackfeet Indian Reservation, Montana","docAbstract":"<p>The Blackfeet Nation seeks an increased scientific understanding of the water resources within the Blackfeet Indian Reservation of northwestern Montana. Hydrologic information is needed to better inform water-management decisions as the Blackfeet Nation implements the Blackfeet Water Rights Compact, initiates new water-use projects, and improves the Blackfeet Irrigation Project.</p><p>The U.S. Geological Survey and the Blackfeet Water Department began cooperating in 2019 to design and implement a hydrologic data-collection program. The program is being implemented in phases that include discrete and continuous discharge measurements of streams and canals, installation, operation of streamgages, groundwater-level monitoring, and database management. Data collected will be used to characterize current hydrologic conditions on the reservation and will act as a baseline for comparison as Blackfeet Nation water projects are implemented.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233012","collaboration":"Prepared in cooperation with the Blackfeet Water Department","usgsCitation":"Lawlor, S.M., Caldwell, R.R., Bartos, T.T., and Price, B., 2023, U.S. Geological Survey and Blackfeet Water Department Hydrologic Assessment of the Blackfeet Indian Reservation, Montana: U.S. Geological Survey Fact Sheet 2023–3012, 4 p., https://doi.org/10.3133/fs20233012.","productDescription":"Report: 4 p.; Dataset","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-141394","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":414914,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3012/coverthb2.jpg"},{"id":414918,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3012/images"},{"id":414919,"rank":5,"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":415102,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20233012/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":499662,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114650.htm","linkFileType":{"id":5,"text":"html"}},{"id":414917,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3012/fs20233012.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":414916,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3012/fs20233012.pdf","text":"Report","size":"2.78 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023–3012"}],"country":"United States","state":"Montana","otherGeospatial":"Blackfeet Indian Reservation","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -113.92382337824559,\n              49.00115786005651\n            ],\n            [\n              -113.92382337824559,\n              47.9492225969058\n            ],\n            [\n              -111.72750252269083,\n              47.9492225969058\n            ],\n            [\n              -111.72750252269083,\n              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0000-0001-5988-7548 slawlor@usgs.gov","orcid":"https://orcid.org/0000-0001-5988-7548","contributorId":1895,"corporation":false,"usgs":true,"family":"Lawlor","given":"Sean","email":"slawlor@usgs.gov","middleInitial":"M.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":868028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Caldwell, Rodney R. 0000-0002-2588-715X caldwell@usgs.gov","orcid":"https://orcid.org/0000-0002-2588-715X","contributorId":2577,"corporation":false,"usgs":true,"family":"Caldwell","given":"Rodney","email":"caldwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":868029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartos, Timothy T. 0000-0003-1803-4375 ttbartos@usgs.gov","orcid":"https://orcid.org/0000-0003-1803-4375","contributorId":1826,"corporation":false,"usgs":true,"family":"Bartos","given":"Timothy","email":"ttbartos@usgs.gov","middleInitial":"T.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":868030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Price, Brett baprice@usgs.gov","contributorId":303758,"corporation":false,"usgs":true,"family":"Price","given":"Brett","email":"baprice@usgs.gov","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":868031,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70246314,"text":"70246314 - 2023 - Flood-frequency analysis in the Midwest: Addressing potential nonstationarity of annual peak-flow records","interactions":[],"lastModifiedDate":"2023-07-19T15:37:03.166943","indexId":"70246314","displayToPublicDate":"2023-04-01T10:32:41","publicationYear":"2023","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":16356,"text":"AASHTO Hydrolink","active":true,"publicationSubtype":{"id":30}},"title":"Flood-frequency analysis in the Midwest: Addressing potential nonstationarity of annual peak-flow records","docAbstract":"Flood-frequency analysis is essential in numerous water-resource management applications, including critical structure design and flood-plain mapping. A basic assumption within Bulletin 17C [1], the standardized guidelines for conducting flood-frequency analysis, is that basins without major hydrologic alterations, such as regulation or urbanization, exhibit stationary statistical properties of the distribution of annual peak streamflow. That is, the mean, variance, and skew are constant over time and  the peak-flow record is a representative sample of the population of future floods [1]. In recent decades, better understanding of long-term climatic persistence and concerns about climate and land-use change have caused the assumption of stationarity in peak-flow records to be reexamined [2, 3, 4, 5]. Under nonstationary conditions, the long-term distributional properties (mean, variance, and/or skew) of peak-flow series change one or more times, either gradually or abruptly. Nonstationarities may be attributed to one source, but are often a result of a mixture of drivers, making detection and attribution of nonstationarities challenging [6, 7, 8]. Failure to incorporate observed trends and abrupt changes into flood-frequency analysis may result in a poor representation of the true flood risk. Bulletin 17C currently offers no guidance on how to account for nonstationarities when estimating floods and acknowledges the benefit additional flood frequency studies that incorporate changing climate or basin characteristics into the analysis would provide[1].","language":"English","publisher":"American Association of State Highway and Transportation Officials","usgsCitation":"Marti, M.K., Ryberg, K.R., and Levin, S., 2023, Flood-frequency analysis in the Midwest: Addressing potential nonstationarity of annual peak-flow records: AASHTO Hydrolink, no. 22, p. 9-11.","productDescription":"3 p.","startPage":"9","endPage":"11","ipdsId":"IP-146874","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":419153,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419152,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://transportation.org/design/technical-committees/hydrology-and-hydraulics/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Midwest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.63079880812552,\n              39.981338894898926\n            ],\n            [\n              -80.305088787779,\n              42.407786545262155\n            ],\n            [\n              -82.78313999112669,\n              41.8642895150752\n            ],\n            [\n              -81.94361722979289,\n              43.7411297751668\n            ],\n            [\n              -84.57946169161875,\n              46.783497345807575\n            ],\n            [\n              -88.02687384801146,\n              48.18911170131872\n            ],\n            [\n              -90.78141289084317,\n              48.05054435475736\n            ],\n            [\n              -94.73142386151744,\n              48.96813415136279\n            ],\n            [\n              -96.0701137437052,\n              49.34965225487991\n            ],\n            [\n              -118.36279683132679,\n              49.044880788818546\n            ],\n            [\n              -114.80117084034327,\n              34.5056159266112\n            ],\n            [\n              -106.83709671015015,\n              33.4475379407086\n            ],\n            [\n              -89.0414291409545,\n              33.06253925797563\n            ],\n            [\n              -81.8240905040015,\n              37.13731159053141\n            ],\n            [\n              -80.63079880812552,\n              39.981338894898926\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","issue":"22","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marti, Mackenzie K. 0000-0001-8817-4969 mmarti@usgs.gov","orcid":"https://orcid.org/0000-0001-8817-4969","contributorId":289738,"corporation":false,"usgs":true,"family":"Marti","given":"Mackenzie","email":"mmarti@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876791,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Levin, Sara B. 0000-0002-2448-3129","orcid":"https://orcid.org/0000-0002-2448-3129","contributorId":209947,"corporation":false,"usgs":true,"family":"Levin","given":"Sara B.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876792,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70242968,"text":"70242968 - 2023 - Dynamics of streamflow permanence in a headwater network: Insights from catchment-scale model simulations","interactions":[],"lastModifiedDate":"2023-04-25T11:53:37.989298","indexId":"70242968","displayToPublicDate":"2023-04-01T06:47:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics of streamflow permanence in a headwater network: Insights from catchment-scale model simulations","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab010\" class=\"abstract author\"><div id=\"as010\"><p id=\"sp0010\">The hillslope and channel dynamics that govern streamflow permanence in headwater systems have important implications for ecosystem functioning and downstream water quality. Recent advancements in process-based, semi-distributed hydrologic models that build upon empirical studies of streamflow permanence in well-monitored headwater catchments show promise for characterizing the dynamics of streamflow permanence in headwater systems. However, few process-based models consider the continuum of hillslope-stream network connectivity as a control on streamflow permanence in headwater systems. The objective of this study was to expand a process-based, catchment-scale hydrologic model to better understand the spatiotemporal dynamics of headwater streamflow permanence and to identify controls of streamflow expansion and contraction in a headwater network. Further, we aimed to develop an approach that enhanced the fidelity of model simulations, yet required little additional data, with the intent that the model might be later transferred to catchments with limited long-term and spatially explicit measurements. This approach facilitated network-scale estimates of the controls of streamflow expansion and contraction, albeit with higher degrees of uncertainty in individual reaches due to data constraints. Our model simulated that streamflow permanence was highly dynamic in first-order reaches with steep slopes and variable contributing areas. The simulated stream network length ranged from nearly 98±2% of the geomorphic channel extent during wet periods to nearly 50±10% during dry periods. The model identified a discharge threshold of approximately 1&nbsp;mm d<sup>−1</sup>, above which the rate of streamflow expansion decreases by nearly an order of magnitude, indicating a lack of sensitivity of streamflow expansion to hydrologic forcing during high-flow periods. Overall, we demonstrate that process-based, catchment-scale models offer important insights on the controls of streamflow permanence, despite uncertainties and limitations of the model. We encourage researchers to increase data collection efforts and develop benchmarks to better evaluate such models.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2023.129422","usgsCitation":"Mahoney, D.T., Christensen, J., Golden, H., Lane, C., Evenson, G., White, E., Fritz, K., D’Amico, E., Barton, C.D., Williamson, T.N., Sena, K., and Agouridis, C., 2023, Dynamics of streamflow permanence in a headwater network: Insights from catchment-scale model simulations: Journal of Hydrology, v. 620, no. Part A, 129422, 18 p., https://doi.org/10.1016/j.jhydrol.2023.129422.","productDescription":"129422, 18 p.","ipdsId":"IP-147290","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":443989,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/2000172","text":"Publisher Index Page"},{"id":416228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kentucky","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.15893416383679,\n              38.87506403800879\n            ],\n            [\n              -84.15893416383679,\n              36.582419250743726\n            ],\n            [\n              -81.83083405694916,\n              36.582419250743726\n            ],\n            [\n              -81.83083405694916,\n              38.87506403800879\n            ],\n            [\n              -84.15893416383679,\n              38.87506403800879\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"620","issue":"Part A","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mahoney, D. 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,{"id":70242842,"text":"70242842 - 2023 - Diverse portfolios: Investing in tributaries for restoration of large river fishes in the Anthropocene","interactions":[],"lastModifiedDate":"2023-04-20T11:38:15.653135","indexId":"70242842","displayToPublicDate":"2023-03-28T06:36:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Diverse portfolios: Investing in tributaries for restoration of large river fishes in the Anthropocene","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb15\">Rehabilitation of large Anthropocene rivers requires engagement of diverse stakeholders across a broad range of sociopolitical boundaries. Competing objectives often constrain options for ecological restoration of large rivers whereas fewer competing objectives may exist in a subset of tributaries. Further, tributaries contribute toward building a “portfolio” of river ecosystem assets through physical and biological processes that may present opportunities to enhance the resilience of large river fishes. Our goal is to review roles of tributaries in enhancing mainstem large river fish populations. We present case histories from two greatly altered and distinct large-river tributary systems that highlight how tributaries contribute four portfolio assets to support large-river fish populations: 1) habitat diversity, 2) connectivity, 3) ecological asynchrony, and 4) density-dependent processes. Finally, we identify future research directions to advance our understanding of tributary roles and inform conservation actions. In the Missouri River United States, we focus on conservation efforts for the state endangered lake sturgeon, which inhabits large rivers and tributaries in the Midwest and Eastern United States. In the Colorado River, Grand Canyon United States, we focus on conservation efforts for recovery of the federally threatened humpback chub. In the Missouri River, habitat diversity focused on physical habitats such as substrate for reproduction, and deep-water habitats for refuge, whereas augmenting habitat diversity for Colorado River fishes focused on managing populations in tributaries with minimally impaired thermal and flow regimes. Connectivity enhancements in the Missouri River focused on increasing habitat accessibility that may require removal of physical structures like low-head dams; whereas in the Colorado River, the lack of connectivity may benefit native fishes as the disconnection provides refuge from non-native fish predation. Hydrologic variability among tributaries was present in both systems, likely underscoring ecological asynchrony. These case studies also described density dependent processes that could influence success of restoration actions. Although actions to restore populations varied by river system, these examples show that these four portfolio assets can help guide restoration activities across a diverse range of mainstem rivers and their tributaries. Using these assets as a guide, we suggest these can be transferable to other large river-tributary systems.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fenvs.2023.1151315","usgsCitation":"Bouska, K.L., Healy, B.D., Moore, M.J., Dunn, C.G., Spurgeon, J.J., and Paukert, C.P., 2023, Diverse portfolios: Investing in tributaries for restoration of large river fishes in the Anthropocene: Frontiers in Environmental Science, v. 11, 1151315, 18 p., https://doi.org/10.3389/fenvs.2023.1151315.","productDescription":"1151315, 18 p.","ipdsId":"IP-149017","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444048,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2023.1151315","text":"Publisher Index Page"},{"id":416046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":869951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Healy, Brian D. 0000-0002-4402-638X","orcid":"https://orcid.org/0000-0002-4402-638X","contributorId":304257,"corporation":false,"usgs":true,"family":"Healy","given":"Brian","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":869952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Michael J. 0000-0002-5495-7049","orcid":"https://orcid.org/0000-0002-5495-7049","contributorId":304258,"corporation":false,"usgs":true,"family":"Moore","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":869953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunn, Corey Garland 0000-0002-7102-2165","orcid":"https://orcid.org/0000-0002-7102-2165","contributorId":288691,"corporation":false,"usgs":true,"family":"Dunn","given":"Corey","email":"","middleInitial":"Garland","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":869954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spurgeon, Jonathan J. 0000-0002-6888-5867","orcid":"https://orcid.org/0000-0002-6888-5867","contributorId":304259,"corporation":false,"usgs":true,"family":"Spurgeon","given":"Jonathan","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":869955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":869956,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70251080,"text":"70251080 - 2023 - A framework for estimating global river discharge from the Surface Water and Ocean Topography satellite mission","interactions":[],"lastModifiedDate":"2024-01-21T22:20:07.018816","indexId":"70251080","displayToPublicDate":"2023-03-27T16:18:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"A framework for estimating global river discharge from the Surface Water and Ocean Topography satellite mission","docAbstract":"<div class=\"article-section__content en main\"><p>The Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new data sets for both gaged and ungaged basins. SWOT discharge products (available approximately 1&nbsp;year after launch) will provide discharge for all river that reaches wider than 100&nbsp;m. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present for the first time a complete estimate of the SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge time series. We expect that discharge uncertainty will be less than 30% for two-thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these “gage-constrained” discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge time series will be dominated by random error and are expected to be estimated within 15% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021WR031614","usgsCitation":"Durand, M., Gleason, C., Pavelsky, T., Frasson, R., Turmon, M., David, C., Altenau, E., Tebaldi, N., Larnier, K., Monnier, J., Malaterre, P., Oubanas, H., Allen, G.H., Astifan, B., Brinkerhoff, C., Bates, P., Bjerklie, D.M., Coss, S., Dudley, R., Fengolio, L., Garambois, P., Getirana, A., Lin, P., Margulis, S.A., Matte, P., Minear, J., Muhebwa, A., Pan, M., Peters, D.L., Riggs, R., Sikder, S., Simmons, T., Stuurman, C., Taneja, J., Tarpanelli, A., Schulze, K., Tourian, M., and Wang, J., 2023, A framework for estimating global river discharge from the Surface Water and Ocean Topography satellite mission: Water Resources Research, v. 59, no. 4, e2021WR031614, 31 p., https://doi.org/10.1029/2021WR031614.","productDescription":"e2021WR031614, 31 p.","ipdsId":"IP-142706","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":444055,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021wr031614","text":"Publisher Index Page"},{"id":424667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Durand, Michael","contributorId":331079,"corporation":false,"usgs":false,"family":"Durand","given":"Michael","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":892993,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gleason, Colin","contributorId":213715,"corporation":false,"usgs":false,"family":"Gleason","given":"Colin","affiliations":[],"preferred":false,"id":892994,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pavelsky, Tamlin","contributorId":149629,"corporation":false,"usgs":false,"family":"Pavelsky","given":"Tamlin","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":892995,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frasson, Renato 0000-0003-4299-1730","orcid":"https://orcid.org/0000-0003-4299-1730","contributorId":258827,"corporation":false,"usgs":false,"family":"Frasson","given":"Renato","email":"","affiliations":[{"id":39742,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.","active":true,"usgs":false}],"preferred":false,"id":892996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Turmon, Michael","contributorId":225055,"corporation":false,"usgs":false,"family":"Turmon","given":"Michael","email":"","affiliations":[{"id":41027,"text":"NASA JPL/CalTech","active":true,"usgs":false}],"preferred":false,"id":892997,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"David, Cedric H.","contributorId":258841,"corporation":false,"usgs":false,"family":"David","given":"Cedric H.","affiliations":[{"id":27151,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA","active":true,"usgs":false}],"preferred":false,"id":892998,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Altenau, Elizabeth","contributorId":333510,"corporation":false,"usgs":false,"family":"Altenau","given":"Elizabeth","email":"","affiliations":[{"id":24532,"text":"Department of Geological Sciences, University of North Carolina, Chapel Hill, NC 27599, USA","active":true,"usgs":false}],"preferred":false,"id":892999,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Tebaldi, Nikki","contributorId":333511,"corporation":false,"usgs":false,"family":"Tebaldi","given":"Nikki","email":"","affiliations":[{"id":79905,"text":"Department of Civil and Environmental Engineering, University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":893000,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Larnier, Kevin","contributorId":333512,"corporation":false,"usgs":false,"family":"Larnier","given":"Kevin","email":"","affiliations":[{"id":79906,"text":"Space Department, CS Corporation, Toulouse, France","active":true,"usgs":false}],"preferred":false,"id":893001,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Monnier, Jerome","contributorId":258839,"corporation":false,"usgs":false,"family":"Monnier","given":"Jerome","email":"","affiliations":[{"id":52305,"text":"INSA Toulouse - Math. 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Canada","active":true,"usgs":false}],"preferred":false,"id":893017,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Minear, J.Toby","contributorId":333521,"corporation":false,"usgs":false,"family":"Minear","given":"J.Toby","email":"","affiliations":[{"id":79913,"text":"Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA","active":true,"usgs":false}],"preferred":false,"id":893018,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Muhebwa, Aggrey","contributorId":333522,"corporation":false,"usgs":false,"family":"Muhebwa","given":"Aggrey","email":"","affiliations":[{"id":79914,"text":"Department of Electrical and Computer Engineering, University of Massachusetts, Amherst , USA","active":true,"usgs":false}],"preferred":false,"id":893019,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Pan, Ming","contributorId":333523,"corporation":false,"usgs":false,"family":"Pan","given":"Ming","email":"","affiliations":[{"id":79915,"text":"Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA","active":true,"usgs":false}],"preferred":false,"id":893020,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Peters, Daniel L.","contributorId":315429,"corporation":false,"usgs":false,"family":"Peters","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":893021,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Riggs, Ryan","contributorId":333524,"corporation":false,"usgs":false,"family":"Riggs","given":"Ryan","email":"","affiliations":[{"id":79916,"text":"Department of Geography, Texas A&M University, College Station, TX, 77843, USA","active":true,"usgs":false}],"preferred":false,"id":893022,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Sikder, Safat","contributorId":333525,"corporation":false,"usgs":false,"family":"Sikder","given":"Safat","email":"","affiliations":[{"id":79917,"text":"Department of Geography and Geospatial Sciences, Kansas State University, Manhattan, KS, USA.","active":true,"usgs":false}],"preferred":false,"id":893023,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Simmons, Travis","contributorId":333526,"corporation":false,"usgs":false,"family":"Simmons","given":"Travis","email":"","affiliations":[{"id":79905,"text":"Department of Civil and Environmental Engineering, University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":893024,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Stuurman, Cassie","contributorId":239994,"corporation":false,"usgs":false,"family":"Stuurman","given":"Cassie","email":"","affiliations":[{"id":36276,"text":"JPL","active":true,"usgs":false}],"preferred":false,"id":893025,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Taneja, Jay","contributorId":333527,"corporation":false,"usgs":false,"family":"Taneja","given":"Jay","email":"","affiliations":[{"id":79914,"text":"Department of Electrical and Computer Engineering, University of Massachusetts, Amherst , USA","active":true,"usgs":false}],"preferred":false,"id":893026,"contributorType":{"id":1,"text":"Authors"},"rank":34},{"text":"Tarpanelli, Angelica","contributorId":333528,"corporation":false,"usgs":false,"family":"Tarpanelli","given":"Angelica","email":"","affiliations":[{"id":79918,"text":"Research Institute for Geo-Hydrological protection, National Research Council, Via Madonna Alta 126, Perugia, Italy","active":true,"usgs":false}],"preferred":false,"id":893027,"contributorType":{"id":1,"text":"Authors"},"rank":35},{"text":"Schulze, Kerstin","contributorId":333529,"corporation":false,"usgs":false,"family":"Schulze","given":"Kerstin","email":"","affiliations":[{"id":79911,"text":"Department of Geodesy and Geoinformation, University of Bonn, Bonn, Germany","active":true,"usgs":false}],"preferred":false,"id":893028,"contributorType":{"id":1,"text":"Authors"},"rank":36},{"text":"Tourian, Mohammad","contributorId":333530,"corporation":false,"usgs":false,"family":"Tourian","given":"Mohammad","email":"","affiliations":[{"id":79919,"text":"Institute of Geodesy, University of Stuttgart, Germany","active":true,"usgs":false}],"preferred":false,"id":893029,"contributorType":{"id":1,"text":"Authors"},"rank":37},{"text":"Wang, Jida","contributorId":333531,"corporation":false,"usgs":false,"family":"Wang","given":"Jida","email":"","affiliations":[{"id":79917,"text":"Department of Geography and Geospatial Sciences, Kansas State University, Manhattan, KS, USA.","active":true,"usgs":false}],"preferred":false,"id":893030,"contributorType":{"id":1,"text":"Authors"},"rank":38}]}}
,{"id":70242725,"text":"70242725 - 2023 - Uptake of per- and polyfluoroalkyl substances by fish, mussel, and passive samplers in mobile laboratory exposures using groundwater from a contamination plume at a historical fire training area, Cape Cod, Massachusetts","interactions":[],"lastModifiedDate":"2023-04-14T11:55:48.98417","indexId":"70242725","displayToPublicDate":"2023-03-27T06:49:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Uptake of per- and polyfluoroalkyl substances by fish, mussel, and passive samplers in mobile laboratory exposures using groundwater from a contamination plume at a historical fire training area, Cape Cod, Massachusetts","docAbstract":"<div class=\"container container_scaled-down\"><div class=\"row\"><div class=\"col-xs-12\"><div id=\"abstractBox\" class=\"article_abstract-content hlFld-Abstract\"><p class=\"articleBody_abstractText\">Aqueous film-forming foams historically were used during fire training activities on Joint Base Cape Cod, Massachusetts, and created an extensive per- and polyfluoroalkyl substances (PFAS) groundwater contamination plume. The potential for PFAS bioconcentration from exposure to the contaminated groundwater, which discharges to surface water bodies, was assessed with mobile-laboratory experiments using groundwater from the contamination plume and a nearby reference location. The on-site continuous-flow 21-day exposures used male and female fathead minnows, freshwater mussels, polar organic chemical integrative samplers (POCIS), and polyethylene tube samplers (PETS) to evaluate biotic and abiotic uptake. The composition of the PFAS-contaminated groundwater was complex and 9 PFAS were detected in the reference groundwater and 17 PFAS were detected in the contaminated groundwater. The summed PFAS concentrations ranged from 120 to 140 ng L<sup>–1</sup><span>&nbsp;</span>in reference groundwater and 6100 to 15,000 ng L<sup>–1</sup><span>&nbsp;</span>in contaminated groundwater. Biotic concentration factors (CF<sub>b</sub>) for individual PFAS were species, sex, source, and compound-specific and ranged from 2.9 to 1000 L kg<sup>–1</sup><span>&nbsp;</span>in whole-body male fish exposed to contaminated groundwater for 21 days. The fish and mussel CF<sub>b</sub><span>&nbsp;</span>generally increased with increasing fluorocarbon chain length and were greater for sulfonates than for carboxylates. The exception was perfluorohexane sulfonate, which deviated from the linear trend and had a 10-fold difference in CF<sub>b</sub><span>&nbsp;</span>between sites, possibly because of biotransformation of precursors such as perfluorohexane sulfonamide. Uptake for most PFAS in male fish was linear over time, whereas female fish had bilinear uptake indicated by an initial increase in tissue concentrations followed by a decrease. Uptake of PFAS was less for mussels (maximum CF<sub>b</sub><span>&nbsp;</span>= 200) than for fish, and mussel uptake of most PFAS also was bilinear. Although abiotic concentration factors were greater than CF<sub>b</sub>, and values for POCIS were greater than for PETS, passive samplers were useful for assessing PFAS that potentially bioconcentrate in fish but are present at concentrations below method quantitation limits in water. Passive samplers also accumulate short-chain PFAS that are not bioconcentrated.</p></div></div></div></div>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.2c06500","usgsCitation":"Barber, L., Pickard, H.M., Alvarez, D.A., Becanova, J., Keefe, S.H., LeBlanc, D.R., Lohmann, R., Steevens, J.A., and Vajda, A.M., 2023, Uptake of per- and polyfluoroalkyl substances by fish, mussel, and passive samplers in mobile laboratory exposures using groundwater from a contamination plume at a historical fire training area, Cape Cod, Massachusetts: Environmental Science and Technology, v. 57, no. 14, p. 5544-5557, https://doi.org/10.1021/acs.est.2c06500.","productDescription":"14 p.","startPage":"5544","endPage":"5557","ipdsId":"IP-121897","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":444066,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10116195","text":"External Repository"},{"id":435404,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LCN0EF","text":"USGS data release","linkHelpText":"Uptake of Per- and Polyfluoroalkyl Substances by Fish, Mussel, and Passive Samplers in Mobile Laboratory Exposures using Groundwater from a Contamination Plume at a Historical Fire Training Area, Cape Cod, Massachusetts - Chemical and Biological Data from August to September 2018"},{"id":415771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -70.68647141190323,\n              42.211476864603554\n            ],\n            [\n              -70.68647141190323,\n              41.50810472445593\n            ],\n            [\n              -69.8326516793067,\n              41.50810472445593\n            ],\n            [\n              -69.8326516793067,\n              42.211476864603554\n            ],\n            [\n              -70.68647141190323,\n              42.211476864603554\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"57","issue":"14","noUsgsAuthors":false,"publicationDate":"2023-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Barber, Larry B. 0000-0002-0561-0831","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":218953,"corporation":false,"usgs":true,"family":"Barber","given":"Larry B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":869505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pickard, Heidi M. 0000-0001-8312-7522","orcid":"https://orcid.org/0000-0001-8312-7522","contributorId":261821,"corporation":false,"usgs":false,"family":"Pickard","given":"Heidi","email":"","middleInitial":"M.","affiliations":[{"id":53027,"text":"Harvard John A. Paulson School of Engineering and Applied Sciences","active":true,"usgs":false}],"preferred":false,"id":869506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alvarez, David A. 0000-0002-6918-2709","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":220763,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":869507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Becanova, Jitka 0000-0002-3091-1054","orcid":"https://orcid.org/0000-0002-3091-1054","contributorId":304148,"corporation":false,"usgs":false,"family":"Becanova","given":"Jitka","email":"","affiliations":[{"id":37391,"text":"University of Rhode Island, Graduate School of Oceanography","active":true,"usgs":false}],"preferred":false,"id":869508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keefe, Steffanie H. 0000-0002-3805-6101 shkeefe@usgs.gov","orcid":"https://orcid.org/0000-0002-3805-6101","contributorId":2843,"corporation":false,"usgs":true,"family":"Keefe","given":"Steffanie","email":"shkeefe@usgs.gov","middleInitial":"H.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":869509,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LeBlanc, Denis R. 0000-0002-4646-2628","orcid":"https://orcid.org/0000-0002-4646-2628","contributorId":219907,"corporation":false,"usgs":true,"family":"LeBlanc","given":"Denis","email":"","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":869510,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lohmann, Rainer 0000-0001-8796-3229","orcid":"https://orcid.org/0000-0001-8796-3229","contributorId":304150,"corporation":false,"usgs":false,"family":"Lohmann","given":"Rainer","email":"","affiliations":[{"id":37391,"text":"University of Rhode Island, Graduate School of Oceanography","active":true,"usgs":false}],"preferred":false,"id":869511,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":869512,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vajda, Alan M.","contributorId":156301,"corporation":false,"usgs":false,"family":"Vajda","given":"Alan","email":"","middleInitial":"M.","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":869513,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70241125,"text":"sir20225132 - 2023 - Evaluation of potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, southern Nevada","interactions":[],"lastModifiedDate":"2026-02-24T18:04:17.753698","indexId":"sir20225132","displayToPublicDate":"2023-03-22T14:27:54","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":"2022-5132","displayTitle":"Evaluation of Potential Stresses and Hydrologic Conditions Driving Water-Level Fluctuations in Well ER-5-3-2, Frenchman Flat, Southern Nevada","title":"Evaluation of potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, southern Nevada","docAbstract":"<p>Well ER-5-3-2 is part of a well network designed to monitor long-term water levels and radionuclide concentrations downgradient from underground nuclear tests that occurred in Frenchman Flat, an area of the U.S. Department of Energy Nevada National Security Site in southern Nevada. Interpretation of monitoring records for well ER-5-3-2 was confounded by previously unexplained water-level fluctuations in the well hydrograph. This study integrated geologic, hydrologic, and water-chemistry data to evaluate potential stresses and hydrologic conditions that likely affected the well ER-5-3-2 hydrograph. Numerical groundwater models were applied to evaluate four model scenarios: (1) wellbore leakage without recharge, (2) wellbore leakage with recharge, (3) equilibration to vertical heterogeneities between shallow (low transmissivity) and deep (higher transmissivity) carbonate zones, and (4) equilibration to lateral heterogeneities in carbonate rocks.</p><p>Meteoric recharge was not the cause of the 21-foot (ft) water-level rise in well ER-5-3-2 from 2001 to 2011 or the 4-ft decline from 2012 to 2016. Based on observed water-level fluctuations in nearby wells, the water-level rise and decline from recharge for these periods was less than 3 and 1 ft, respectively. The lateral-heterogeneity scenario is based on the assumption that the 21-ft water-level rise from 2001 to 2011 was a natural water-level reequilibration following the pumping-induced depressurization of a large volume of high transmissivity and low-storage carbonate rock that is surrounded by low transmissivity and high-storage carbonate rock. The lateral-heterogeneity scenario was discounted because simulated water levels cannot match the well ER-5-3-2 hydrograph. Underground nuclear testing and temperature effects were discounted based on hydraulic connections and water-temperature data.</p><p>Wellbore-leakage scenarios are based on the assumption that the water-level rise was sustained from leakage rates required to cause a localized mounding in the carbonate system near well ER-5-3-2, where the carbonate transmissivity is 530 square feet per day. Even though simulated and measured water levels compare favorably for scenarios of wellbore leakage with and without recharge, large volumes (178–184 million gallons) of groundwater from volcanic rocks would be required to leak into the carbonate system, which is not supported by water-chemistry data.</p><p>An alternative conceptualization of wellbore leakage is based on the assumption that the 21-ft water-level rise from 2001 to 2011 was sustained by the hydraulic disconnection of well ER-5-3-2 from the carbonate system. The disconnection occurred several months after a constant-rate test in well ER-5-3-2 when carbonate rocks were hydraulically disconnected from the well by either (1) the shifting of sloughed fill in the open hole or (2) the encrusting of carbonate precipitate in the well screen. The hydraulic disconnection effectively sealed the well and caused a 21-ft water-level rise from wellbore leakage during 2001–11. In this case, total wellbore leakage from 2001 to 2011 was about 50 gallons. The 4-ft water-level decline from 2012 to 2016 was conceptualized to have occurred from the slow breaking of the seal and reconnection of the well to the carbonate system. This alternative conceptualization of wellbore leakage was consistent with water-chemistry analyses because the computed wellbore leakage (50 gallons) was small relative to purged volumes (30,000–40,000 gallons) for sampling, and the water chemistry would not be expected to change.</p><p>The shallow-deep carbonate scenario provided another explanation for the well ER-5-3-2 hydrograph. This scenario is based on the assumption that well-construction effects and vertical heterogeneity of the carbonate system explain the ER-5-3-2 water-level trend. Well-construction effects are attributed to a temporary clogging of the open interval below the well screen that was opened during pumping events, which affected the hydraulic connection of deep transmissive carbonate rocks to the wellbore. The 21-ft water-level rise from 2001 to 2011 was a natural equilibration to shallow, low-transmissivity carbonate rocks during a period when the lower open interval was clogged. The 4-ft decline from 2012 to 2016 represents equilibration between the shallow and deep intervals, because of a partial unclogging of the connection between the two intervals. The low water levels from 2016 to 2021 resulted from pumping for sampling and an unclogging of the open interval so that the low head in the deep carbonate dominated the water level. Despite potential well-construction effects, from either a wellbore leakage or shallow-deep carbonate scenario, samples collected from well ER-5-3-2 are representative of the carbonate system.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225132","collaboration":"Prepared in cooperation with the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office, Office of Environmental Management under Interagency Agreement, DE-EM0004969","usgsCitation":"Jackson, T.R., and Frus, R.J., 2023, Evaluation of potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, southern Nevada: U.S. Geological Survey Scientific Investigations Report 2022–5132, 35 p., https://doi.org/10.3133/sir20225132.","productDescription":"Report: viii, 35 p.; Data Release","numberOfPages":"35","onlineOnly":"Y","ipdsId":"IP-139917","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":413963,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95C0NG5","text":"MODFLOW 6 models used to evaluate potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, southern Nevada","description":"Jackson, T.R., and Frus, R.J., 2023, MODFLOW 6 models used to evaluate potential stresses and hydrologic conditions driving water-level fluctuations in well ER-5-3-2, Frenchman Flat, southern Nevada: U.S. Geological Survey data release, available at https://doi.org/10.5066/P95C0NG5."},{"id":500485,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114613.htm","linkFileType":{"id":5,"text":"html"}},{"id":413973,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225132/full"},{"id":413962,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5132/images"},{"id":413961,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5132/sir20225132.xml"},{"id":413960,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5132/sir20225132.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":413959,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5132/covrthb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Frenchman Flat","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -116.05668643871044,\n              36.549912612507626\n            ],\n            [\n              -116.05668643871044,\n              35.84481987187543\n            ],\n            [\n              -115.27945901304658,\n              35.84481987187543\n            ],\n            [\n              -115.27945901304658,\n              36.549912612507626\n            ],\n            [\n              -116.05668643871044,\n              36.549912612507626\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nv@usgs.gov\" data-mce-href=\"mailto:dc_nv@usgs.gov\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/nv-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/nv-water\">Nevada Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>2730 N. Deer Run Road<br>Carson City, Nevada 89701</p>","tableOfContents":"<ul><li>Acknowledgments <br></li><li>Abstract <br></li><li>Introduction <br></li><li>Well ER-5-3-2 History <br></li><li>Methods <br></li><li>Summary <br></li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2023-03-22","noUsgsAuthors":false,"publicationDate":"2023-03-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Jackson, Tracie R. 0000-0001-8553-0323","orcid":"https://orcid.org/0000-0001-8553-0323","contributorId":215365,"corporation":false,"usgs":true,"family":"Jackson","given":"Tracie R.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frus, Rebecca J. 0000-0002-2435-7202","orcid":"https://orcid.org/0000-0002-2435-7202","contributorId":206261,"corporation":false,"usgs":true,"family":"Frus","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866170,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70255298,"text":"70255298 - 2023 - Understanding the spatiotemporal distribution of snow refugia in the rain-snow transition zone of north-central Idaho","interactions":[],"lastModifiedDate":"2024-06-14T12:24:56.984299","indexId":"70255298","displayToPublicDate":"2023-03-21T07:19:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the spatiotemporal distribution of snow refugia in the rain-snow transition zone of north-central Idaho","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Knowledge of snow cover distribution and disappearance dates over a wide range of scales is imperative for understanding hydrological dynamics and for habitat management of wildlife species that rely on snow cover. Identification of snow refugia, or places with relatively late snow disappearance dates (SDDs) compared to surrounding areas, is especially important as climate change alters snow cover timing and duration. The purpose of this study was to increase understanding of snow refugia in complex terrain spanning the rain-snow transition zone at fine spatial and temporal scales. To accomplish this objective, we used remote cameras to provide relatively high temporal and spatial resolution measurements on snowpack conditions. We built linear models to relate SDDs at the monitoring sites to topoclimatic and canopy cover metrics. One model to quantify SDDs included elevation, aspect, and an interaction between canopy cover and cold-air pooling potential. High-elevation, north-facing sites in cold-air pools (CAPs) had the latest SDDs, but isolated lower-elevation points also exhibited relatively late potential SDDs. Importantly, canopy cover had a much stronger effect on SDDs in CAPs than in non-CAPs, indicating that best practices in forest management for snow refugia could vary across microtopography. A second model that included<span>&nbsp;</span><i>in situ</i><span>&nbsp;</span>hydroclimate observations (December<i>–</i>February (DJF) temperature and March 1 snow depth) indicated that March 1 snow depth had little impact on SDD at the coldest winter temperatures, and that DJF temperatures had a stronger effect on SDD at lower snow depths, implying that the relative importance of snowfall and temperature could vary across hydroclimatic contexts in their impact on snow refugia. This new understanding of factors influencing snow refugia can guide forest management actions to increase snow retention and inform management of snow-dependent wildlife species in complex terrain.</p></div>","language":"English","publisher":"IOPScience","doi":"10.1088/1748-9326/acbb90","usgsCitation":"Strickfaden, K.M., Marshall, A.M., Svancara, L.K., Dugger, K., and Link, T.E., 2023, Understanding the spatiotemporal distribution of snow refugia in the rain-snow transition zone of north-central Idaho: Environmental Research Letters, v. 18, 044014, 11 p., https://doi.org/10.1088/1748-9326/acbb90.","productDescription":"044014, 11 p.","ipdsId":"IP-147918","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":444142,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/acbb90","text":"Publisher Index Page"},{"id":430200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","noUsgsAuthors":false,"publicationDate":"2023-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Strickfaden, Kaitlyn M.","contributorId":339386,"corporation":false,"usgs":false,"family":"Strickfaden","given":"Kaitlyn","email":"","middleInitial":"M.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":904127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Adrienne M.","contributorId":339387,"corporation":false,"usgs":false,"family":"Marshall","given":"Adrienne","email":"","middleInitial":"M.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":904128,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Svancara, Leona K.","contributorId":339389,"corporation":false,"usgs":false,"family":"Svancara","given":"Leona","email":"","middleInitial":"K.","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":904129,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":904130,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Link, Timothy E.","contributorId":339393,"corporation":false,"usgs":false,"family":"Link","given":"Timothy","email":"","middleInitial":"E.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":904131,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70241616,"text":"70241616 - 2023 - Integrating terrestrial and aquatic ecosystems to constrain estimates of land-atmosphere carbon exchange","interactions":[],"lastModifiedDate":"2023-03-24T11:57:44.122655","indexId":"70241616","displayToPublicDate":"2023-03-21T06:53:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Integrating terrestrial and aquatic ecosystems to constrain estimates of land-atmosphere carbon exchange","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>In this Perspective, we put forward an integrative framework to improve estimates of land-atmosphere carbon exchange based on the accumulation of carbon in the landscape as constrained by its lateral export through rivers. The framework uses the watershed as the fundamental spatial unit and integrates all terrestrial and aquatic ecosystems as well as their hydrologic carbon exchanges. Application of the framework should help bridge the existing gap between land and atmosphere-based approaches and offers a platform to increase communication and synergy among the terrestrial, aquatic, and atmospheric research communities that is paramount to advance landscape carbon budget assessments.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41467-023-37232-2","usgsCitation":"Casas-Ruiz, J., Bodmer, P., Bona, K.A., Butman, D., Couturier, M., Emilson, E.J., Finlay, K., Genet, H., Hayes, D., Karlsson, J., Pare, D., Peng, C., Striegl, R.G., Webb, J., Wei, X., Ziegler, S., and Del Giorgio, P., 2023, Integrating terrestrial and aquatic ecosystems to constrain estimates of land-atmosphere carbon exchange: Nature Communications, v. 14, 1571, 17 p., https://doi.org/10.1038/s41467-023-37232-2.","productDescription":"1571, 17 p.","ipdsId":"IP-146296","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":444145,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-023-37232-2","text":"Publisher Index Page"},{"id":414690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2023-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Casas-Ruiz, Joan","contributorId":303397,"corporation":false,"usgs":false,"family":"Casas-Ruiz","given":"Joan","email":"","affiliations":[{"id":65789,"text":"Research Group on Ecology of Inland Waters, Institute of Aquatic Ecology, University of Girona, Girona, Spain","active":true,"usgs":false}],"preferred":false,"id":867499,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bodmer, Pascal","contributorId":303398,"corporation":false,"usgs":false,"family":"Bodmer","given":"Pascal","email":"","affiliations":[{"id":65790,"text":"Groupe de Recherche Interuniversitaire en Limnologie (GRIL), Département des sciences biologiques,  Université du Québec à Montréal, Montréal, Québec, Canada","active":true,"usgs":false}],"preferred":false,"id":867500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bona, Kelly Ann","contributorId":303399,"corporation":false,"usgs":false,"family":"Bona","given":"Kelly","email":"","middleInitial":"Ann","affiliations":[{"id":65791,"text":"Environment and Climate Change Canada, Gatineau, Quebec, Canada","active":true,"usgs":false}],"preferred":false,"id":867501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Butman, David","contributorId":224754,"corporation":false,"usgs":false,"family":"Butman","given":"David","affiliations":[{"id":16962,"text":"U. Washington","active":true,"usgs":false}],"preferred":false,"id":867502,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Couturier, Mathilde","contributorId":303400,"corporation":false,"usgs":false,"family":"Couturier","given":"Mathilde","email":"","affiliations":[{"id":65790,"text":"Groupe de Recherche Interuniversitaire en Limnologie (GRIL), Département des sciences biologiques,  Université du Québec à Montréal, Montréal, Québec, Canada","active":true,"usgs":false}],"preferred":false,"id":867503,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Emilson, Erik J.S.","contributorId":245463,"corporation":false,"usgs":false,"family":"Emilson","given":"Erik","email":"","middleInitial":"J.S.","affiliations":[{"id":49199,"text":"Natural Resources Canada, Canadian Forest ServiceGreat Lakes Forestry Centre, Sault Ste. Marie, Canada","active":true,"usgs":false}],"preferred":false,"id":867504,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Finlay, Kerri","contributorId":289777,"corporation":false,"usgs":false,"family":"Finlay","given":"Kerri","email":"","affiliations":[{"id":27547,"text":"University of Regina","active":true,"usgs":false}],"preferred":false,"id":867505,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Genet, Helene","contributorId":198686,"corporation":false,"usgs":false,"family":"Genet","given":"Helene","email":"","affiliations":[],"preferred":false,"id":867506,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hayes, Daniel B.","contributorId":248252,"corporation":false,"usgs":false,"family":"Hayes","given":"Daniel B.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":867507,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Karlsson, Jan","contributorId":139660,"corporation":false,"usgs":false,"family":"Karlsson","given":"Jan","email":"","affiliations":[{"id":12869,"text":"Dept. of Ecology and Environmental Science, Umeå University, Umeå, Sweden.","active":true,"usgs":false}],"preferred":false,"id":867508,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pare, David","contributorId":303401,"corporation":false,"usgs":false,"family":"Pare","given":"David","email":"","affiliations":[{"id":65793,"text":"Natural Resources Canada, Québec, Québec, Canada","active":true,"usgs":false}],"preferred":false,"id":867509,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Peng, Changhui","contributorId":197932,"corporation":false,"usgs":false,"family":"Peng","given":"Changhui","email":"","affiliations":[{"id":6613,"text":"Center of CEF/ESCER, Department of Biological Science, University of Quebec at Montreal, Montreal H3C 3P8, Canada","active":true,"usgs":false},{"id":6612,"text":"State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China","active":true,"usgs":false}],"preferred":false,"id":867510,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":867511,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Webb, Jackie","contributorId":293904,"corporation":false,"usgs":false,"family":"Webb","given":"Jackie","email":"","affiliations":[],"preferred":false,"id":867512,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wei, Xinyuan","contributorId":303402,"corporation":false,"usgs":false,"family":"Wei","given":"Xinyuan","email":"","affiliations":[{"id":65794,"text":"Center for Research on Sustainable Forests, University of Maine, Orono, Maine, USA","active":true,"usgs":false}],"preferred":false,"id":867513,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Ziegler, Sue","contributorId":303403,"corporation":false,"usgs":false,"family":"Ziegler","given":"Sue","email":"","affiliations":[{"id":65796,"text":"Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador, Canada","active":true,"usgs":false}],"preferred":false,"id":867514,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Del Giorgio, Paul","contributorId":211167,"corporation":false,"usgs":false,"family":"Del Giorgio","given":"Paul","email":"","affiliations":[{"id":38187,"text":"Université du Québec à Montréal, Quebec, Montreal, Canada","active":true,"usgs":false}],"preferred":false,"id":867515,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70248233,"text":"70248233 - 2023 - Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses","interactions":[],"lastModifiedDate":"2023-09-05T12:11:07.324945","indexId":"70248233","displayToPublicDate":"2023-03-19T07:06:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16697,"text":"Transportation Research Record, Journal of the Transportation Research Board.","active":true,"publicationSubtype":{"id":10}},"title":"Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses","docAbstract":"<div id=\"abstracts\" data-extent=\"frontmatter\"><div class=\"core-container\"><div>Transportation agencies need information about the potential effects of climate change on the volume, quality, and treatment of stormwater to mitigate potential effects of runoff on receiving waters. To address these concerns, the U.S. Geological Survey and the Federal Highway Administration used the Coupled Model Intercomparison Project tool and the Stochastic Empirical Loading and Dilution Model to perform space-for-time stormwater quality analyses. This study indicated that spatial variations in precipitation statistics within and adjacent to southern New England are greater than projected climate-related changes for the centroid of this region. A dilution-factor analysis indicated that highway runoff would become a greater proportion of downstream flows if average event volumes or time between event midpoints increase and would become a smaller proportion of downstream flows if event durations increase. Highway-runoff yield analyses for total phosphorus (TP) indicate that uncertainty in water quality statistics results in variations in long-term average yields from about 1.69 to 7.96 times higher than the lowest TP values simulated. In comparison, variations in precipitation statistics cause yield variations that ranged from 1.41 to 1.76 for the different simulated concentrations. An analysis of stormwater treatment indicated that uncertainties in runoff treatment variables are also larger than the magnitude of climate variations. This study does not question the potentially large climate-related changes in hydrologic and hydraulic variables expected to occur in the foreseeable future. It does indicate that uncertainties in the current data and potential effects of land use change on stormwater quality and treatment variables are larger than the projected effects of climate change.</div></div></div>","language":"English","publisher":"Sage","doi":"10.1177/03611981231155183","usgsCitation":"Jeznach, L.C., Granato, G., Sharar-Salgado, D., Jones, S.C., and Imig, D., 2023, Assessing potential effects of climate change on highway-runoff flows and loads in southern New England by using planning-level space-for-time analyses: Transportation Research Record, Journal of the Transportation Research Board., v. 2677, no. 7, p. 570-581, https://doi.org/10.1177/03611981231155183.","productDescription":"12 p.","startPage":"570","endPage":"581","ipdsId":"IP-143447","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":444172,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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0000-0001-7251-1537","orcid":"https://orcid.org/0000-0001-7251-1537","contributorId":305388,"corporation":false,"usgs":false,"family":"Sharar-Salgado","given":"Daniel","email":"","affiliations":[{"id":54843,"text":"Federal Highway Administration","active":true,"usgs":false}],"preferred":false,"id":882054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Susan C. 0000-0002-5891-5209","orcid":"https://orcid.org/0000-0002-5891-5209","contributorId":64716,"corporation":false,"usgs":false,"family":"Jones","given":"Susan","email":"","middleInitial":"C.","affiliations":[{"id":34302,"text":"Federal Highway Administration (United States)","active":true,"usgs":false}],"preferred":false,"id":882055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Imig, Daniel 0000-0002-5099-1266","orcid":"https://orcid.org/0000-0002-5099-1266","contributorId":329356,"corporation":false,"usgs":false,"family":"Imig","given":"Daniel","email":"","affiliations":[{"id":78575,"text":"Connecticut Department of Transportation","active":true,"usgs":false}],"preferred":false,"id":882056,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70241200,"text":"fs20233006 - 2023 - Application of geophysical methods to enhance aquifer characterization and groundwater-flow model development, Des Moines River alluvial aquifer, Des Moines, Iowa, 2022","interactions":[],"lastModifiedDate":"2026-02-04T20:37:47.514644","indexId":"fs20233006","displayToPublicDate":"2023-03-14T16:03:33","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3006","displayTitle":"Application of Geophysical Methods to Enhance Aquifer Characterization and Groundwater-Flow Model Development, Des Moines River Alluvial Aquifer, Des Moines, Iowa, 2022","title":"Application of geophysical methods to enhance aquifer characterization and groundwater-flow model development, Des Moines River alluvial aquifer, Des Moines, Iowa, 2022","docAbstract":"<p>Des Moines Water Works (DMWW) is one of the largest water providers in Iowa and as population growth continues, demand for drinking water is increasing. DMWW uses groundwater and surface water as raw water sources to supply the City of Des Moines and surrounding communities. In response to current and future demands, DMWW is in need of a thorough understanding of local groundwater resources, specifically the Des Moines River alluvial aquifer. The Des Moines River alluvial aquifer is hydraulically connected to the Des Moines River and consists of alluvial deposits and glacial outwash sands and gravels. To ensure a sustainable groundwater supply, additional information to better understand and manage groundwater availability within the Des Moines River alluvial aquifer would be beneficial. Beginning in 2018, DMWW partnered with the U.S. Geological Survey to construct a groundwater-flow model to increase understanding of the hydrologic system in the Des Moines area. The model hydrogeologic framework will be enhanced by using multiple geophysical methods of data collection in the Des Moines River, Beaver Creek, and the Des Moines River alluvial aquifer that could provide a better understanding of the geology in the model area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233006","usgsCitation":"Thomas, J.C., Spring, M.A., Gruhn, L.R., and Bristow, E.L., 2023, Application of geophysical methods to enhance aquifer characterization and groundwater-flow model development, Des Moines River alluvial aquifer, Des Moines, Iowa, 2022: U.S. Geological Survey Fact Sheet 2023–3006, 4 p., https://doi.org/10.3133/fs20233006.","productDescription":"Report: 4 p.; 2 Data Releases; Dataset","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-136349","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":414104,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3006/fs20233006.pdf","text":"Report","size":"2.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023–3006"},{"id":414105,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3006/fs20233006.XML","description":"FS 2023–3006"},{"id":414103,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3006/coverthb2.jpg"},{"id":414112,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://www.usgs.gov/national-hydrography/access-national-hydrography-products","text":"USGS dataset","linkHelpText":"—National Hydrography Dataset— USGS National Hydrography Dataset Best Resolution for Hydrologic Unit 4 – 2001"},{"id":414109,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B9AVKJ","text":"USGS data release","linkHelpText":"Geophysical data collected in the Des Moines River, Beaver Creek, and the Des Moines River floodplain, Des Moines, Iowa, 2018"},{"id":414110,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F3CKLC","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate groundwater levels in the Des Moines River alluvial aquifer near Des Moines, Iowa"},{"id":499566,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114475.htm","linkFileType":{"id":5,"text":"html"}},{"id":414138,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20233006/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":414113,"rank":7,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3006/images"}],"country":"United States","state":"Iowa","city":"Des Moines","otherGeospatial":"Des Moines River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -93.69895287733283,\n              41.66093681949087\n            ],\n            [\n              -93.69895287733283,\n              41.52388190639587\n            ],\n            [\n              -93.51363729010005,\n              41.52388190639587\n            ],\n            [\n              -93.51363729010005,\n              41.66093681949087\n            ],\n            [\n              -93.69895287733283,\n              41.66093681949087\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/cm-water\" data-mce-href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>405 North Goodwin <br>Urbana, IL 61801</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Study Objectives</li><li>Groundwater-Flow Model Background</li><li>Geophysical Methods Approach</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-03-14","noUsgsAuthors":false,"publicationDate":"2023-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Judith C. 0000-0001-7883-1419 juthomas@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-1419","contributorId":1468,"corporation":false,"usgs":true,"family":"Thomas","given":"Judith","email":"juthomas@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866417,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spring, Morgan A. 0000-0002-8781-604X mspring@usgs.gov","orcid":"https://orcid.org/0000-0002-8781-604X","contributorId":303050,"corporation":false,"usgs":true,"family":"Spring","given":"Morgan","email":"mspring@usgs.gov","middleInitial":"A.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866418,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gruhn, Lance R. 0000-0002-7120-3003 lgruhn@usgs.gov","orcid":"https://orcid.org/0000-0002-7120-3003","contributorId":219710,"corporation":false,"usgs":true,"family":"Gruhn","given":"Lance","email":"lgruhn@usgs.gov","middleInitial":"R.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866419,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bristow, Emilia L. 0000-0002-7939-166X ebristow@usgs.gov","orcid":"https://orcid.org/0000-0002-7939-166X","contributorId":214538,"corporation":false,"usgs":true,"family":"Bristow","given":"Emilia L.","email":"ebristow@usgs.gov","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866420,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70241433,"text":"70241433 - 2023 - Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis","interactions":[],"lastModifiedDate":"2023-03-17T12:05:34.434371","indexId":"70241433","displayToPublicDate":"2023-03-14T07:01:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"abs0002\" class=\"abstract author\"><div id=\"abss0002\"><p id=\"spara026\">Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. Finally, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2023.102693","usgsCitation":"Smith, C.M., Faulds, J., Brown, S.C., Coolbaugh, M., DeAngelo, J., Glen, J.M., Burns, E.R., Siler, D.L., Treitel, S., Mlawsky, E., Fehler, M., Gu, C., and Ayling, B.F., 2023, Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis: Geothermics, v. 111, 102693, 21 p., https://doi.org/10.1016/j.geothermics.2023.102693.","productDescription":"102693, 21 p.","ipdsId":"IP-145803","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":444214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1999607","text":"Publisher Index Page"},{"id":414334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.08429216037908,\n              42.0233321964142\n            ],\n            [\n              -120.08429216037908,\n              38.470780571367555\n            ],\n            [\n              -114.02241339577863,\n              38.470780571367555\n            ],\n            [\n              -114.02241339577863,\n              42.0233321964142\n            ],\n            [\n              -120.08429216037908,\n              42.0233321964142\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"111","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Connor M.","contributorId":237894,"corporation":false,"usgs":false,"family":"Smith","given":"Connor","email":"","middleInitial":"M.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":866828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faulds, James E.","contributorId":252834,"corporation":false,"usgs":false,"family":"Faulds","given":"James E.","affiliations":[{"id":50442,"text":"Great Basin Center for Geothermal Energy, Nevada Bureau of Mines and Geology, University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":866829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Stephen C.","contributorId":38457,"corporation":false,"usgs":false,"family":"Brown","given":"Stephen","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":866830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coolbaugh, Mark","contributorId":260754,"corporation":false,"usgs":false,"family":"Coolbaugh","given":"Mark","affiliations":[{"id":52671,"text":"University of Nevada, Reno, ATLAS Geosciences","active":true,"usgs":false}],"preferred":false,"id":866831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":866832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":866833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burns, Erick R. 0000-0002-1747-0506 eburns@usgs.gov","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":192154,"corporation":false,"usgs":true,"family":"Burns","given":"Erick","email":"eburns@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":866834,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Siler, Drew Lorenz 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":303226,"corporation":false,"usgs":false,"family":"Siler","given":"Drew","email":"","middleInitial":"Lorenz","affiliations":[{"id":65720,"text":"Geologica Geothermal Group, LLC.","active":true,"usgs":false}],"preferred":false,"id":866835,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Treitel, Sven","contributorId":237884,"corporation":false,"usgs":false,"family":"Treitel","given":"Sven","email":"","affiliations":[{"id":47634,"text":"Hi-Q Geophysical, Inc.","active":true,"usgs":false}],"preferred":false,"id":866836,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mlawsky, Eli","contributorId":237889,"corporation":false,"usgs":false,"family":"Mlawsky","given":"Eli","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":866837,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Fehler, Michael","contributorId":237888,"corporation":false,"usgs":false,"family":"Fehler","given":"Michael","email":"","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":866838,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gu, Chen","contributorId":237896,"corporation":false,"usgs":false,"family":"Gu","given":"Chen","email":"","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":866839,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Ayling, Bridget F.","contributorId":237899,"corporation":false,"usgs":false,"family":"Ayling","given":"Bridget","email":"","middleInitial":"F.","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":866840,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70241179,"text":"70241179 - 2023 - A call for strategic water-quality monitoring to advance assessment and prediction of wildfire impacts on water supplies","interactions":[],"lastModifiedDate":"2023-03-16T15:08:56.24279","indexId":"70241179","displayToPublicDate":"2023-03-13T06:50:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7170,"text":"Frontiers in Water","active":true,"publicationSubtype":{"id":10}},"title":"A call for strategic water-quality monitoring to advance assessment and prediction of wildfire impacts on water supplies","docAbstract":"<div class=\"JournalAbstract\"><p><span>Wildfires pose a risk to water supplies in the western U.S. and many other parts of the world, due to the potential for degradation of water quality. However, a lack of adequate data hinders prediction and assessment of post-wildfire impacts and recovery. The dearth of such data is related to lack of funding for monitoring extreme events and the challenge of measuring the outsized hydrologic and erosive response after wildfire. Assessment and prediction of post-wildfire surface water quality would be strengthened by the strategic monitoring of key parameters, and the selection of sampling locations based on the following criteria: (1) streamgage with pre-wildfire data; (2) ability to install equipment that can measure water quality at high temporal resolution, with a focus on storm sampling; (3) minimum of 10% drainage area burned at moderate to high severity; (4) lack of major water management; (5) high-frequency precipitation; and (6) availability of pre-wildfire water-quality data and (or) water-quality data from a comparable unburned basin. Water-quality data focused on parameters that are critical to human and (or) ecosystem health, relevant to water-treatment processes and drinking-water quality, and (or) inform the role of precipitation and discharge on flow paths and water quality are most useful. We discuss strategic post-wildfire water-quality monitoring and identify opportunities for advancing assessment and prediction. Improved estimates of the magnitude, timing, and duration of post-wildfire effects on water quality would aid the water resources community prepare for and mitigate against impacts to water supplies.</span></p></div>","language":"English","publisher":"Frontiers Media","doi":"10.3389/frwa.2023.1144225","usgsCitation":"Murphy, S.F., Alpers, C.N., Anderson, C.W., Banta, J.R., Blake, J., Carpenter, K.D., Clark, G.D., Clow, D.W., Hempel, L.A., Martin, D., Meador, M.R., Mendez, G., Mueller-Solger, A., Stewart, M.A., Payne, S.E., Peterman-Phipps, C.L., and Ebel, B., 2023, A call for strategic water-quality monitoring to advance assessment and prediction of wildfire impacts on water supplies: Frontiers in Water, v. 5, 1144225, 9 p., https://doi.org/10.3389/frwa.2023.1144225.","productDescription":"1144225, 9 p.","ipdsId":"IP-147614","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":444230,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frwa.2023.1144225","text":"Publisher Index Page"},{"id":414084,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2023-03-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":866351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":140160,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banta, John R. 0000-0002-2226-7270","orcid":"https://orcid.org/0000-0002-2226-7270","contributorId":222710,"corporation":false,"usgs":true,"family":"Banta","given":"John","email":"","middleInitial":"R.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blake, Johanna 0000-0003-4667-0096","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":217272,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866355,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carpenter, Kurt D. 0000-0002-6231-8335 kdcar@usgs.gov","orcid":"https://orcid.org/0000-0002-6231-8335","contributorId":127442,"corporation":false,"usgs":true,"family":"Carpenter","given":"Kurt","email":"kdcar@usgs.gov","middleInitial":"D.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866356,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Clark, Gregory D. 0000-0003-0066-8193 gmclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0066-8193","contributorId":224364,"corporation":false,"usgs":true,"family":"Clark","given":"Gregory","email":"gmclark@usgs.gov","middleInitial":"D.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866357,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866358,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hempel, Laura A. 0000-0001-5020-6056","orcid":"https://orcid.org/0000-0001-5020-6056","contributorId":224286,"corporation":false,"usgs":true,"family":"Hempel","given":"Laura","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866359,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Martin, Deborah A. 0000-0001-8237-0838","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":244709,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":866360,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Meador, Michael R. 0000-0001-5956-3340 mrmeador@usgs.gov","orcid":"https://orcid.org/0000-0001-5956-3340","contributorId":219878,"corporation":false,"usgs":true,"family":"Meador","given":"Michael","email":"mrmeador@usgs.gov","middleInitial":"R.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":866361,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mendez, Gregory 0000-0002-9955-3726 gomendez@usgs.gov","orcid":"https://orcid.org/0000-0002-9955-3726","contributorId":139098,"corporation":false,"usgs":true,"family":"Mendez","given":"Gregory","email":"gomendez@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866362,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mueller-Solger, Anke 0000-0002-2469-4284 amueller-solger@usgs.gov","orcid":"https://orcid.org/0000-0002-2469-4284","contributorId":178275,"corporation":false,"usgs":true,"family":"Mueller-Solger","given":"Anke","email":"amueller-solger@usgs.gov","affiliations":[],"preferred":true,"id":866363,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stewart, Marc A. 0000-0003-1140-6316 mastewar@usgs.gov","orcid":"https://orcid.org/0000-0003-1140-6316","contributorId":2277,"corporation":false,"usgs":true,"family":"Stewart","given":"Marc","email":"mastewar@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866364,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Payne, Sean E. 0000-0003-1836-1886 spayne@usgs.gov","orcid":"https://orcid.org/0000-0003-1836-1886","contributorId":292581,"corporation":false,"usgs":true,"family":"Payne","given":"Sean","email":"spayne@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866365,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Peterman-Phipps, Cara L. 0000-0003-1822-2552","orcid":"https://orcid.org/0000-0003-1822-2552","contributorId":259166,"corporation":false,"usgs":true,"family":"Peterman-Phipps","given":"Cara","email":"","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":866366,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":866367,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70241154,"text":"70241154 - 2023 - Adjusting design floods for urbanization across groundwater-dominated watersheds of Long Island, NY","interactions":[],"lastModifiedDate":"2023-03-14T11:38:49.467965","indexId":"70241154","displayToPublicDate":"2023-03-12T06:36:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Adjusting design floods for urbanization across groundwater-dominated watersheds of Long Island, NY","docAbstract":"<div id=\"ab015\" class=\"abstract author\"><div id=\"as015\"><p id=\"sp0015\">The magnitude and variability of floods have increased for many nontidal streams on Long Island (LI), NY since the mid-20th century. One of the most densely populated regions of the United States, LI has experienced amplified floods in step with increases in impervious land cover, storm, and sanitary sewers that have accompanied urban development. To better understand the drivers of observed flood trends and effects of urbanization, a nonstationary flood frequency analysis is conducted, using historical annual peak flow records from 17 gaged watersheds on LI using conditional moments based on physical covariates from a two-stage sequential robust linear regression procedure. Regression results indicate that urban development and precipitation are significant co-predictors of peak flows for LI watersheds that have undergone rapid development during the available peak flow record. In watersheds with less intense urbanization or that were fully developed before the peak flow record began, precipitation alone was a significant explanatory variable. Long-term baseflow patterns identified using a nonparametric smoother explained some patterns of decreasing peak flows and heteroskedasticity in the peak flow records. Fitting a log-Pearson III distribution with these conditional moments, floods corresponding to a 20% annual exceedance probability (AEP) are up to 80% higher under a nonstationary framework compared with stationary under current watershed conditions, and differ significantly (95% confidence) from stationary estimates for 6 out of 17 watersheds. Larger floods corresponding to 1% AEPs do not differ significantly between nonstationary and stationary estimates at a 95% confidence level. Nonmonotonic trends observed in two watersheds indicate that recent stormwater management practices, such as rerouting stormwater outfalls away from the channel, substantially reduce flood frequency. Reduced nonstationary flood quantile estimates at these two watersheds are 20 to 40% lower than stationary estimates when accounting for changing watershed conditions over time. Across LI, stormwater management and water-table fluctuations have increased peak flow variability, characteristic of a late phase urban adjustment period on LI. Results of this study demonstrate that a nonstationary framework is a necessary step forward toward a regional flood-frequency analysis for LI. This nonstationary framework will allow flood managers to update flood discharge estimates to current conditions that reflect altered relationships between urban cover and climate for more targeted planning of flood control, transportation infrastructure, and management of floodplain ecosystems.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2023.129194","usgsCitation":"Glas, R.L., Hecht, J.S., Simonson, A.E., Gazoorian, C.L., and Schubert, C., 2023, Adjusting design floods for urbanization across groundwater-dominated watersheds of Long Island, NY: Journal of Hydrology, v. 618, 129194, 18 p., https://doi.org/10.1016/j.jhydrol.2023.129194.","productDescription":"129194, 18 p.","ipdsId":"IP-141042","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":444235,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2023.129194","text":"Publisher Index Page"},{"id":414082,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -74.05858047106763,\n              40.53935289454654\n            ],\n            [\n              -73.5589147395655,\n              40.53100675208171\n            ],\n            [\n              -72.9988498537052,\n              40.622757129246565\n            ],\n            [\n              -72.21915167927318,\n              40.85158231156032\n            ],\n            [\n              -71.88970174641427,\n              41.046499814971185\n            ],\n            [\n              -71.84577508869982,\n              41.12099665045869\n            ],\n            [\n              -72.05442671284345,\n              41.191277217075765\n            ],\n            [\n              -72.26307833698762,\n              41.21193363017932\n            ],\n            [\n              -72.65292742420364,\n              41.129268863301746\n            ],\n            [\n              -73.23495563892061,\n              41.067201851192294\n            ],\n            [\n              -73.70167637713746,\n              40.980209521445886\n            ],\n            [\n              -73.99269048449594,\n              40.83081255180315\n            ],\n            [\n              -74.11348879321068,\n              40.63525879433698\n            ],\n            [\n              -74.05858047106763,\n              40.53935289454654\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"618","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glas, Robin L. 0000-0002-7394-1667","orcid":"https://orcid.org/0000-0002-7394-1667","contributorId":300625,"corporation":false,"usgs":true,"family":"Glas","given":"Robin","email":"","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hecht, Jory Seth 0000-0002-9485-3332","orcid":"https://orcid.org/0000-0002-9485-3332","contributorId":257771,"corporation":false,"usgs":true,"family":"Hecht","given":"Jory","email":"","middleInitial":"Seth","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":866290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simonson, Amy E. 0000-0001-8468-5382","orcid":"https://orcid.org/0000-0001-8468-5382","contributorId":217671,"corporation":false,"usgs":true,"family":"Simonson","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866291,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866292,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schubert, Christopher 0000-0002-5137-1229 schubert@usgs.gov","orcid":"https://orcid.org/0000-0002-5137-1229","contributorId":138826,"corporation":false,"usgs":true,"family":"Schubert","given":"Christopher","email":"schubert@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":866293,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70242934,"text":"70242934 - 2023 - Investigating hydrologic alteration in the Pearl and Pascagoula River basins using rule-based model trees","interactions":[],"lastModifiedDate":"2023-04-24T12:07:47.445858","indexId":"70242934","displayToPublicDate":"2023-03-09T07:04:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14255,"text":"Environmental Software and Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Investigating hydrologic alteration in the Pearl and Pascagoula River basins using rule-based model trees","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\"><span>Anthropogenic hydrologic alteration threatens the health of riverine ecosystems.&nbsp;Machine learning algorithms&nbsp;that employ the use of model trees to predict hydrologic alteration are underrepresented in related literature. This study assesses hydrologic alteration in the Pearl and Pascagoula River basins using modeled daily&nbsp;</span>streamflow<span>. Hydrologic alteration was determined by hypothesis testing and the computation of the net change across 60 years. Cubist models were developed for both basins to predict hydrologic alteration and to identify important basin characteristics. Results from net change and the hypothesis test indicated the basins were essentially identical with respect to the amount of hydrologic alteration. Cubist models for the basins successfully made accurate predictions of hydrologic alteration and demonstrated that the importance of basin&nbsp;geomorphology&nbsp;and land cover on alteration differed in both basins. The results of the study demonstrate the feasibility of model trees in assessing hydrologic alteration.</span></p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2023.105667","usgsCitation":"Roland, V.L., Crowley-Ornelas, E., and Rodgers, K., 2023, Investigating hydrologic alteration in the Pearl and Pascagoula River basins using rule-based model trees: Environmental Software and Modelling, v. 163, 105667, 10 p., https://doi.org/10.1016/j.envsoft.2023.105667.","productDescription":"105667, 10 p.","ipdsId":"IP-116276","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":444260,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2023.105667","text":"Publisher Index Page"},{"id":435420,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PUMMTV","text":"USGS data release","linkHelpText":"Supporting data and model outputs for hydrologic alteration modeling in the Pearl and Pascagoula river basins"},{"id":416172,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Pascagoula River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -89.80875982614708,\n              32.61000614560781\n            ],\n            [\n              -89.80875982614708,\n              30.154023040111667\n            ],\n            [\n              -88.27367909529212,\n              30.154023040111667\n            ],\n            [\n              -88.27367909529212,\n              32.61000614560781\n            ],\n            [\n              -89.80875982614708,\n              32.61000614560781\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"163","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roland, Victor L. II 0000-0002-6260-9351 vroland@usgs.gov","orcid":"https://orcid.org/0000-0002-6260-9351","contributorId":212248,"corporation":false,"usgs":true,"family":"Roland","given":"Victor","suffix":"II","email":"vroland@usgs.gov","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":870238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crowley-Ornelas, Elena 0000-0002-1823-8485","orcid":"https://orcid.org/0000-0002-1823-8485","contributorId":211970,"corporation":false,"usgs":true,"family":"Crowley-Ornelas","given":"Elena","email":"","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":870239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodgers, Kirk D. 0000-0003-4322-2781","orcid":"https://orcid.org/0000-0003-4322-2781","contributorId":203438,"corporation":false,"usgs":true,"family":"Rodgers","given":"Kirk D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":870334,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70240876,"text":"sir20235016 - 2023 - 2022 drought in New England","interactions":[],"lastModifiedDate":"2026-03-02T22:03:43.63376","indexId":"sir20235016","displayToPublicDate":"2023-03-08T15:50:00","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":"2023-5016","displayTitle":"2022 Drought in New England","title":"2022 drought in New England","docAbstract":"<h1>Introduction&nbsp;</h1><p>During April through September 2022, much of New England experienced a short but extreme hydrologic drought that was similar to the drought of 2020. By August 2022, Providence, Rhode Island, was declared a Federal disaster area, and New London and Windham counties in Connecticut were declared natural disaster areas. Mandatory water use restrictions were put in place in communities in Connecticut, Massachusetts, New Hampshire, and Rhode Island (Mecray and Borisoff, 2022). Precipitation in many areas of New England fell below normal levels in November 2021 and continued to decline until September 2022, contributing to low streamflows and groundwater levels in the region. U.S. Geological Survey (USGS) streamflow and groundwater conditions from April to September 2022 were used to characterize the hydrologic component of this short-duration drought. Several record low streamflows and groundwater levels were observed across New England, even falling below 2020 levels in parts of southern New England. The severity of this drought varied across New England, and regional and statewide perspectives are presented in this report.</p><p><strong>Highlights</strong></p><ul><li>May through August in 2022 ranked as the driest for those 4 months in 138 years of record at Boston, Massachusetts, with only 5.74 inches of rain (average of 13.26 inches).</li><li>Water levels at 95 USGS groundwater monitoring wells across New England were below normal in August; 16 of these wells recorded their lowest August water level in 25 years.</li><li>Flows at 54 USGS streamgages across New England were below normal in August, and 10 of those streamgages recorded their lowest August flows in 30 years.</li><li>Two USGS streamgages in Massachusetts (stations 01105600 and 01171500 with 56 and 83 years of record, respectively) had record 7-day average low flows on August 21, 2022, and August 22, 2022, respectively.</li></ul>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235016","usgsCitation":"McCarthy, D.E., LeNoir, J.M., and Lombard, P.J., 2023, 2022 drought in New England: U.S. Geological Survey Scientific Investigations Report 2023–5016, 34 p., https://doi.org/10.3133/sir20235016.","productDescription":"Report: vii, 34 p.; 6 Appendixes; 2 Tables; Dataset","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-146872","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":413478,"rank":4,"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":413479,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5016/sir20235016.XML"},{"id":413480,"rank":6,"type":{"id":34,"text":"Image 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2023-5016"},{"id":413873,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5016/sir20235016_appendix4.pdf","text":"Appendix 4","size":"0.99 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Drought in New Hampshire in 2022"},{"id":413872,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5016/sir20235016_appendix3.pdf","text":"Appendix 3","size":"0.98 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Drought in Massachusetts in 2022"},{"id":413871,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5016/sir20235016_appendix2.pdf","text":"Appendix 2","size":"1.26 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Drought in Maine in 2022"},{"id":413870,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5016/sir20235016_appendix1.pdf","text":"Appendix 1","size":"1.13 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Drought in Connecticut in 2022"},{"id":413482,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2023/5016/sir20235016_table7.2.txt","text":"Table 7.2","size":"9.11 KB","linkFileType":{"id":2,"text":"txt"},"linkHelpText":"- Groundwater monitoring stations used in a drought analysis for New England in 2022"},{"id":500710,"rank":15,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114472.htm","linkFileType":{"id":5,"text":"html"}},{"id":413875,"rank":14,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5016/sir20235016_appendix6.pdf","text":"Appendix 6","size":"0.98 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Drought in Vermont in 2022"},{"id":413874,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5016/sir20235016_appendix5.pdf","text":"Appendix 5","size":"1.00 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Drought in Rhode Island in 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 \"}}]}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Introduction</li><li>Highlights</li><li>Study Area</li><li>Drought Definition</li><li>Drought Severity</li><li>Meteorological Drought</li><li>U.S. Geological Survey Streamflow and Groundwater Level Monitoring Networks in New England</li><li>Data Analysis</li><li>Hydrologic Drought of 2022</li><li>Provisional Nature of the Data</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Drought in Connecticut in 2022</li><li>Appendix 2. Drought in Maine in 2022</li><li>Appendix 3. Drought in Massachusetts in 2022</li><li>Appendix 4. Drought in New Hampshire in 2022</li><li>Appendix 5. Drought in Rhode Island in 2022</li><li>Appendix 6. Drought in Vermont in 2022</li><li>Appendix 7. Streamgages and Groundwater Monitoring Stations in New England</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-03-08","noUsgsAuthors":false,"publicationDate":"2023-03-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Crozier, Dee-Ann E. 0000-0003-0526-3013","orcid":"https://orcid.org/0000-0003-0526-3013","contributorId":245837,"corporation":false,"usgs":true,"family":"Crozier","given":"Dee-Ann","email":"","middleInitial":"E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lenoir, Jonathan","contributorId":167876,"corporation":false,"usgs":false,"family":"Lenoir","given":"Jonathan","email":"","affiliations":[{"id":24849,"text":"Université de Picardie Jules Verne","active":true,"usgs":false}],"preferred":false,"id":865133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lombard, Pamela J. 0000-0002-0983-1906","orcid":"https://orcid.org/0000-0002-0983-1906","contributorId":205225,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela","email":"","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865134,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70240929,"text":"sir20235002 - 2023 - Hydrologic effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey","interactions":[],"lastModifiedDate":"2026-02-24T18:09:00.975169","indexId":"sir20235002","displayToPublicDate":"2023-03-07T14:25:00","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":"2023-5002","displayTitle":"Hydrologic Effects of Possible Changes in Water-Supply Withdrawals from, and Effluent Recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey","title":"Hydrologic effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey","docAbstract":"<p>Winslow Township and the Camden County Municipal Utility Authority (CCMUA) developed a plan to shut down the Winslow sewage-treatment facility and associated effluent infiltration facility and transfer the effluent to the CCMUA sewage-treatment facility on the Delaware River in Camden, New Jersey. Winslow Township reduced groundwater withdrawals from the Kirkwood-Cohansey aquifer system to offset groundwater recharge lost with the cessation of effluent infiltration. The U.S. Geological Survey, in cooperation with Winslow Township and the CCMUA, collected data to evaluate conditions prior to cessation of effluent infiltration and installed two continuous-record streamflow-gaging stations. Streamflow measurements also were made at two low-flow partial-record sites, and groundwater levels were measured in 17 wells at high and low water-level periods (May and September 2010). A groundwater-flow model provides estimated changes in base flow of the Great Egg Harbor River under several groundwater-withdrawal and effluent infiltration scenarios.</p><p>Water levels were measured in an observation well 480 feet (ft) from the infiltration lagoons during 1971–2010. A downward trend in water levels in the well prior to 1985 is attributed in part to increased impervious surfaces and groundwater withdrawals associated with development in the area that began in the early 1970s. From late 1985 to 2010, there was an upward trend in water levels in the well that is attributed to the construction of nearby effluent infiltration lagoons in 1985 and the increasing rate of effluent infiltration during the period. Recent and historical measurements made at the four surface-water sites were correlated with same-day discharges measured at three nearby index stations to estimate continuous low-flow record at the sites. Effects on base flow caused by reductions in groundwater withdrawals or the cessation of effluent infiltration in Winslow Township could not be ascertained from the available data with the statistical and analysis methods used.</p><p>Groundwater discharge to streams (base flow) was simulated with a groundwater-flow model of the Great Egg Harbor and Mullica River Basins. Simulated monthly base flows using 2008–10 withdrawal rates and effluent recharge (Scenario 1) are generally about 1.5 million gallons per day (Mgal/d) greater than simulated base flows using 2003–07 withdrawal rates (Baseline Scenario) because of the 1.57 Mgal/d reduction in average withdrawals by Winslow Township from the Kirkwood-Cohansey aquifer system from 2003–07 to 2008–10. Simulated monthly base flows using 2008–10 withdrawals but without effluent infiltration (Scenario 2) are very similar to, but typically slightly lower than, Baseline Scenario base flows.</p><p>Three hypothetical future distributions of groundwater withdrawals from existing Winslow Township wells are simulated, each without effluent infiltration and using the same groundwater withdrawal rate as Scenario 2, but with different hypothetical distributions of withdrawals among existing Winslow Township wells. The Scenario 3 and 4 base flows are greater than the Baseline Scenario base flows in all months, and the Scenario 5 base flows are less than the Baseline Scenario base flows in all months. The simulation results indicate that a reduction in average withdrawals from the Kirkwood-Cohansey aquifer system by 1.57 Mgal/d offsets the reduction of effluent infiltration by about the same rate, resulting in nearly unchanged base flows in the Great Egg Harbor River near Blue Anchor (01410820).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235002","collaboration":"Prepared in cooperation with the Township of Winslow and the Camden County Municipal Utilities Authority","usgsCitation":"Carleton, G.B., and Pope, D.A., 2023, Hydrologic effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey: U.S. Geological Survey Scientific Investigations Report 2023–5002, 16 p., https://doi.org/10.3133/sir20235002.","productDescription":"Report: vii, 16 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057410","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":413542,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7154G0Z","text":"USGS data release","linkHelpText":"MODFLOW-2000 model used to evaluate the effects of possible changes in water-supply withdrawals from, and effluent recharge to, the Kirkwood-Cohansey aquifer system, Winslow Township, Camden County, New Jersey"},{"id":500487,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114441.htm","linkFileType":{"id":5,"text":"html"}},{"id":413541,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5002/images/"},{"id":413538,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5002/sir20235002.pdf","text":"Report","size":"1.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5002"},{"id":413537,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5002/coverthb.jpg"},{"id":413539,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235002/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5002"},{"id":413540,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5002/sir20235002.XML"}],"country":"United States","state":"New Jersey","county":"Camden County","otherGeospatial":"Winslow Township","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -75,\n              39.833\n            ],\n            [\n              -75,\n              39.5833\n            ],\n            [\n              -74.833,\n              39.5833\n            ],\n            [\n              -74.833,\n              39.833\n            ],\n            [\n              -75,\n              39.833\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/new-jersey-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/new-jersey-water-science-center\">New Jersey Water Science Center</a><br>U.S. Geological Survey<br>3450 Princeton Pike, Suite 110<br>Lawrenceville, NJ, 08648</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Analysis of Groundwater Levels and Surface-Water Flow</li><li>Simulated Base Flow in the Great Egg Harbor River</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-03-07","noUsgsAuthors":false,"publicationDate":"2023-03-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Carleton, Glen B. 0000-0002-7666-4407","orcid":"https://orcid.org/0000-0002-7666-4407","contributorId":208415,"corporation":false,"usgs":true,"family":"Carleton","given":"Glen B.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865337,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, Daryll A. 0000-0002-6777-8285 dpope@usgs.gov","orcid":"https://orcid.org/0000-0002-6777-8285","contributorId":208416,"corporation":false,"usgs":true,"family":"Pope","given":"Daryll","email":"dpope@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":865338,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70243327,"text":"70243327 - 2023 - Hydrologic modeling and river corridor applications of HY_Features concepts","interactions":[],"lastModifiedDate":"2023-05-09T13:35:13.643633","indexId":"70243327","displayToPublicDate":"2023-03-06T08:26:24","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":14271,"text":"OGC Public Engineering Report","active":true,"publicationSubtype":{"id":3}},"title":"Hydrologic modeling and river corridor applications of HY_Features concepts","docAbstract":"<div class=\"paragraph\"><p>The WaterML2: Part 3 - Surface Hydrology Features (HY_Features) Conceptual Model was published by OGC in 2018. This report documents the use of HY_Features concepts in support of two key tasks: (1) local to continental hydrologic modeling; and (2) referencing river corridor data to hydrographic networks. The presented use cases are applicable in hydroscience research and assessments, water resources engineering practices, and drought and flood responses.</p></div><div class=\"paragraph\"><p>Before the HY_Features conceptual model there was no internationally recognized standard for the design of software and data for the hydroscience and engineering community. This report presents progress towards a logical data model that interprets the abstract HY_Features concepts for use in geospatial workflows, modeling applications, and web data systems that integrate hydrologic data.</p></div><div class=\"paragraph\"><p>The use cases addressed include: (1) hydrologic model control volume definition; (2) hydrologic network connectivity; (3) characterization of catchments with landscape and atmospheric data; (4) river corridor characterization; (5) hydrologic location; and (6) flow network location. Each use case is described briefly along with an analysis of the information requirements. This report presents a summary of the logical model designed to satisfy the needs of these use cases and a summary of updates and changes proposed for HY_Features.</p></div><div class=\"paragraph\"><p>Changes for consideration by the HY_Features Standards Working Group include the following.</p></div><div class=\"olist arabic\"><ol class=\"arabic\"><li><p>Provide more clarity on the inherited properties and associations of features that \"realize\" the catchment and nexus concepts from HY_Features.</p></li><li><p>Add nexus realization feature types to represent the outlet of catchments that are \"frontal\" (terminate to the ocean or a large waterbody) or \"inland sinks.\"</p></li><li><p>Add a \"HY_Flowline\" feature as a superclass of HY_Flowpath providing linear referencing on waterbodies that are not catchment realizations.</p></li><li><p>Add an association or interface to support connection between surface catchments and hydrogeologic units.</p></li></ol></div>","language":"English","publisher":"Open Geospatial Consortium","usgsCitation":"Blodgett, D.L., Johnson, J., Bock, A.R., LeRoy, J.Z., and Wernimont, M.R., 2023, Hydrologic modeling and river corridor applications of HY_Features concepts: OGC Public Engineering Report, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-145176","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":416858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":416834,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.opengis.net/doc/PER/Hydrofabric-er"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":872050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, J. Michael","contributorId":304963,"corporation":false,"usgs":false,"family":"Johnson","given":"J. Michael","affiliations":[{"id":66193,"text":"NOAA-NWS-OWP","active":true,"usgs":false}],"preferred":false,"id":872051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeRoy, Jessica Z. 0000-0003-4035-6872 jzinger@usgs.gov","orcid":"https://orcid.org/0000-0003-4035-6872","contributorId":174534,"corporation":false,"usgs":true,"family":"LeRoy","given":"Jessica","email":"jzinger@usgs.gov","middleInitial":"Z.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":872052,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wernimont, Martin R 0000-0002-2127-8568 mwernimont@usgs.gov","orcid":"https://orcid.org/0000-0002-2127-8568","contributorId":5662,"corporation":false,"usgs":true,"family":"Wernimont","given":"Martin","email":"mwernimont@usgs.gov","middleInitial":"R","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":872054,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70241187,"text":"70241187 - 2023 - A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management","interactions":[],"lastModifiedDate":"2023-03-14T12:19:36.295822","indexId":"70241187","displayToPublicDate":"2023-03-03T07:18:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13457,"text":"The Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management","docAbstract":"<div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Ecological condition continues to decline in arid and semi-arid river basins globally due to hydrological over-abstraction combined with changing climatic conditions. Whilst provision of water for the environment has been a primary approach to alleviate ecological decline, how to accurately monitor changes in riverine trees at fine spatial and temporal scales, remains a substantial challenge. This is further complicated by constantly changing water availability across expansive river basins with varying climatic zones. Within, we combine rare, fine-scale, high frequency temporal<span>&nbsp;</span><i>in-situ</i><span>&nbsp;</span>field collected data with machine learning and remote sensing, to provide a robust model that enables broadscale monitoring of physiological tree water stress response to environmental changes via actual evapotranspiration (ET). Physiological variation of<span>&nbsp;</span><i>Eucalyptus camaldulensis</i><span>&nbsp;</span>(River Red Gum) and<span>&nbsp;</span><i>E. largiflorens</i><span>&nbsp;</span>(Black Box) trees across 10 study locations in the southern Murray-Darling Basin, Australia, was captured instantaneously using sap flow sensors, substantially reducing tree response lags encountered by monitoring visual canopy changes. Actual ET measurement of both species was used to bias correct a national spatial ET product where a Random Forest model was trained using continuous timeseries of<span>&nbsp;</span><i>in-situ</i><span>&nbsp;</span>data of up to four years. Precise monthly AMLETT (<strong><u>A</u></strong>ustralia-wide<span>&nbsp;</span><strong><u>M</u></strong>achine<span>&nbsp;</span><strong><u>L</u></strong>earning<span>&nbsp;</span><strong><u>ET</u></strong><span>&nbsp;</span>for<span>&nbsp;</span><strong><u>T</u></strong>rees) ET outputs in 30&nbsp;m pixel resolution from 2012 to 2021, were derived by incorporating additional remote sensing layers such as soil moisture, land surface temperature, radiation and EVI and NDVI in the Random Forest model. Landsat and Sentinal-2 correlation results between<span>&nbsp;</span><i>in-situ</i><span>&nbsp;</span>ET and AMLETT ET returned R<sup>2</sup><span>&nbsp;</span>of 0.94 (RMSE 6.63&nbsp;mm period<sup>−1</sup>) and 0.92 (RMSE 6.89&nbsp;mm period<sup>−1</sup>), respectively. In comparison, correlation between<span>&nbsp;</span><i>in-situ</i><span>&nbsp;</span>ET and a national ET product returned R<sup>2</sup><span>&nbsp;</span>of 0.44 (RMSE 34.08&nbsp;mm period<sup>−1</sup>) highlighting the need for bias correction to generate accurate absolute ET values. The AMLETT method presented here, enhances environmental management in river basins worldwide. Such robust broadscale monitoring can inform water accounting and importantly, assist decisions on where to prioritize water for the environment to restore and protect key ecological assets and preserve floodplain and riparian ecological function.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2023.117393","usgsCitation":"Doody, T.M., Gao, S., Vervoot, W., Pritchard, J., Davies, M., Nolan, M., and Nagler, P.L., 2023, A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management: The Journal of Environmental Management, v. 332, 117393, 14 p., https://doi.org/10.1016/j.jenvman.2023.117393.","productDescription":"117393, 14 p.","ipdsId":"IP-144919","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":444303,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2023.117393","text":"Publisher Index Page"},{"id":414089,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              140.07757319376452,\n              -34.95139605233576\n            ],\n            [\n              144.51416562293036,\n              -34.95139605233576\n            ],\n            [\n              144.51416562293036,\n              -32.46697218892208\n            ],\n            [\n              140.07757319376452,\n              -32.46697218892208\n            ],\n            [\n              140.07757319376452,\n              -34.95139605233576\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"332","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Doody, Tanya M.","contributorId":138691,"corporation":false,"usgs":false,"family":"Doody","given":"Tanya","email":"","middleInitial":"M.","affiliations":[{"id":12494,"text":"CSIRO Land and Water, Australia","active":true,"usgs":false}],"preferred":false,"id":866383,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gao, Sicong","contributorId":303040,"corporation":false,"usgs":false,"family":"Gao","given":"Sicong","email":"","affiliations":[{"id":65623,"text":"CSIRO, Land and Water, Waite Campus, Adelaide, South Australia, Australia; University of Canberra, Canberra, Australian Capital Territory, Australia","active":true,"usgs":false}],"preferred":false,"id":866384,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vervoot, Willem","contributorId":303041,"corporation":false,"usgs":false,"family":"Vervoot","given":"Willem","email":"","affiliations":[{"id":65624,"text":"School of Life and Environmental Sciences, The University of Sydney, Sydney, Australia","active":true,"usgs":false}],"preferred":false,"id":866385,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pritchard, Jodie","contributorId":303042,"corporation":false,"usgs":false,"family":"Pritchard","given":"Jodie","email":"","affiliations":[{"id":65625,"text":"CSIRO, Land and Water, Waite Campus, Adelaide, South Australia, Australia","active":true,"usgs":false}],"preferred":false,"id":866386,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davies, Michah","contributorId":303043,"corporation":false,"usgs":false,"family":"Davies","given":"Michah","email":"","affiliations":[{"id":65627,"text":"CSIRO, Land and Water, Canberra, Australian Capital Territory, Australia","active":true,"usgs":false}],"preferred":false,"id":866387,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nolan, Martin","contributorId":303044,"corporation":false,"usgs":false,"family":"Nolan","given":"Martin","email":"","affiliations":[{"id":65625,"text":"CSIRO, Land and Water, Waite Campus, Adelaide, South Australia, Australia","active":true,"usgs":false}],"preferred":false,"id":866388,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866389,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70244090,"text":"70244090 - 2023 - Unravelling the influence of landscape alteration from flow alteration on benthic macroinvertebrate assemblage response in the Delaware River Basin","interactions":[],"lastModifiedDate":"2023-06-01T14:08:40.055086","indexId":"70244090","displayToPublicDate":"2023-03-01T08:44:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Unravelling the influence of landscape alteration from flow alteration on benthic macroinvertebrate assemblage response in the Delaware River Basin","docAbstract":"Quantifying the effects of streamflow alteration on assemblage response is central to understanding the role humans play in shaping aquatic environments. These changes represent a level of complexity that impedes developing quantitative links between flow and ecological response because stream hydrology is strongly intertwined with natural and anthropogenic factors. Better management outcomes require disentangling these linkages. Benthic macroinvertebrate data were combined with GIS-derived natural and anthropogenic basin characteristics to identify factors associated with changes in flow processes and assemblage characteristics. Models linking streamflow metrics and macroinvertebrate response at basin and subregion scales were developed using boosted regression tree (BRT) analysis. Basin-scale BRT analyses revealed that links between macroinvertebrate response and flow metrics were often obscured, whereas more homogeneous subregions were better able to discern relations with flow. Urban land cover was the primary factor accounting for changes in flow characteristics. Elevation, land cover, and high flow frequency were the principal variables driving changes in assemblage structure within subregions. Assemblage metrics and traits were equally useful for building response models and were affected similarly by streamflow alteration. Results indicate that response models should be developed based on upland and coastal subregions. However, when defining subregions, care should be taken to maintain data sufficiency. Developing practical flow-protection standards that support a balance between human water requirements and ecological integrity requires models that reduce uncertainty and identify management-relevant drivers. However, effective management often differs by location and models developed at the subregion level may be more applicable to management and stakeholder interests.","language":"English","publisher":"Wiley","doi":"10.1002/eco.2508","usgsCitation":"Kennen, J., and Cuffney, T.F., 2023, Unravelling the influence of landscape alteration from flow alteration on benthic macroinvertebrate assemblage response in the Delaware River Basin: Ecohydrology, v. 16, no. 2, e2508, 41 p., https://doi.org/10.1002/eco.2508.","productDescription":"e2508, 41 p.","ipdsId":"IP-128360","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":498861,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eco.2508","text":"Publisher Index Page"},{"id":417646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -75.07997541667648,\n              38.70906787639316\n            ],\n            [\n              -74.80531721355018,\n              39.00778043156808\n            ],\n            [\n              -74.33839826823872,\n              40.4450386444411\n            ],\n            [\n              -73.72865705730113,\n              40.994591290300974\n            ],\n            [\n              -73.7835886979261,\n              42.478350475454334\n            ],\n            [\n              -75.40956526042564,\n              42.295772510663625\n            ],\n            [\n              -75.42055158855078,\n              41.8349594674406\n            ],\n            [\n              -76.34340315105082,\n              40.43667721449637\n            ],\n            [\n              -75.78859358073888,\n              39.713504216020766\n            ],\n            [\n              -75.76662092448927,\n              39.578152174338356\n            ],\n            [\n              -75.66225080730156,\n              39.41283383409595\n            ],\n            [\n              -75.50294904948888,\n              39.22584914314203\n            ],\n            [\n              -75.47548322917642,\n              39.042631522344635\n            ],\n            [\n              -75.33266096355176,\n              38.846103881559685\n            ],\n            [\n              -75.07997541667648,\n              38.70906787639316\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"16","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cuffney, Thomas F. 0000-0003-1164-5560 tcuffney@usgs.gov","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":517,"corporation":false,"usgs":true,"family":"Cuffney","given":"Thomas","email":"tcuffney@usgs.gov","middleInitial":"F.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":874462,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70241112,"text":"70241112 - 2023 - Large increases in methane emissions expected from North America’s largest wetland complex","interactions":[],"lastModifiedDate":"2023-03-10T15:10:35.729452","indexId":"70241112","displayToPublicDate":"2023-03-01T08:33:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Large increases in methane emissions expected from North America’s largest wetland complex","docAbstract":"<p><span>Natural methane (CH</span><sub>4</sub><span>) emissions from aquatic ecosystems may rise because of human-induced climate warming, although the magnitude of increase is highly uncertain. Using an exceptionally large CH</span><sub>4</sub><span>&nbsp;flux dataset (~19,000 chamber measurements) and remotely sensed information, we modeled plot- and landscape-scale wetland CH</span><sub>4</sub><span>&nbsp;emissions from the Prairie Pothole Region (PPR), North America’s largest wetland complex. Plot-scale CH</span><sub>4</sub><span>&nbsp;emissions were driven by hydrology, temperature, vegetation, and wetland size. Historically, landscape-scale PPR wetland CH</span><sub>4</sub><span>&nbsp;emissions were largely dependent on total wetland extent. However, regardless of future wetland extent, PPR CH</span><sub>4</sub><span>&nbsp;emissions are predicted to increase by two- or threefold by 2100 under moderate or severe warming scenarios, respectively. Our findings suggest that international efforts to decrease atmospheric CH</span><sub>4</sub><span>&nbsp;concentrations should jointly account for anthropogenic and natural emissions to maintain climate mitigation targets to the end of the century.</span></p>","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.ade1112","usgsCitation":"Bansal, S., Post van der Burg, M., Fern, R., Jones, J., Lo, R., McKenna, O.P., Tangen, B., Zhang, Z., and Gleason, R.A., 2023, Large increases in methane emissions expected from North America’s largest wetland complex: Science Advances, v. 9, no. 9, eade1112, 14 p., https://doi.org/10.1126/sciadv.ade1112.","productDescription":"eade1112, 14 p.","ipdsId":"IP-137112","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":444325,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.ade1112","text":"Publisher Index Page"},{"id":435429,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PKI29C","text":"USGS data release","linkHelpText":"Methane flux model for wetlands of the Prairie Pothole Region of North America: Model input data and programming code"},{"id":413952,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -99.103,\n              47.104\n            ],\n            [\n              -99.103,\n              47.096\n            ],\n            [\n              -99.091,\n              47.096\n            ],\n            [\n              -99.091,\n              47.104\n            ],\n            [\n              -99.103,\n              47.104\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"9","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":866116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Post van der Burg, Max 0000-0002-3943-4194","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":219400,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":866117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fern, Rachel","contributorId":302984,"corporation":false,"usgs":false,"family":"Fern","given":"Rachel","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":866118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, John W. 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","middleInitial":"W.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":866119,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lo, Rachel 0000-0003-1014-7076","orcid":"https://orcid.org/0000-0003-1014-7076","contributorId":303000,"corporation":false,"usgs":true,"family":"Lo","given":"Rachel","email":"","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":866151,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKenna, Owen P. 0000-0002-5937-9436 omckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-5937-9436","contributorId":198598,"corporation":false,"usgs":true,"family":"McKenna","given":"Owen","email":"omckenna@usgs.gov","middleInitial":"P.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":866121,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":866122,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zhang, Zhen 0000-0003-0899-1139","orcid":"https://orcid.org/0000-0003-0899-1139","contributorId":149173,"corporation":false,"usgs":false,"family":"Zhang","given":"Zhen","email":"","affiliations":[],"preferred":false,"id":866123,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gleason, Robert A. 0000-0001-5308-8657 rgleason@usgs.gov","orcid":"https://orcid.org/0000-0001-5308-8657","contributorId":2402,"corporation":false,"usgs":true,"family":"Gleason","given":"Robert","email":"rgleason@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":866124,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70248778,"text":"70248778 - 2023 - Indicators of the effects of climate change on freshwater ecosystems","interactions":[],"lastModifiedDate":"2023-09-21T12:06:36.333278","indexId":"70248778","displayToPublicDate":"2023-03-01T07:03:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1246,"text":"Climate Change","onlineIssn":"1573-1480","printIssn":"0165-0009","active":true,"publicationSubtype":{"id":10}},"title":"Indicators of the effects of climate change on freshwater ecosystems","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Freshwater ecosystems, including lakes, streams, and wetlands, are responsive to climate change and other natural and anthropogenic stresses. These ecosystems are frequently hydrologically and ecologically connected with one another and their surrounding landscapes, thereby integrating changes throughout their watersheds. The responses of any given freshwater ecosystem to climate change depend on the magnitude of climate forcing, interactions with other anthropogenic and natural changes, and the characteristics of the ecosystem itself. Therefore, the magnitude and manner in which freshwater ecosystems respond to climate change are difficult to predict a priori. We present a conceptual model to elucidate how freshwater ecosystems are altered by climate change. We identify eleven indicators that describe the response of freshwater ecosystems to climate change, discuss their potential value and limitations, and describe supporting measurements. Indicators are organized in three interrelated categories: hydrologic, water quality, and ecosystem structure and function. The indicators are supported by data sets with a wide range of temporal and spatial coverage, and they inform important scientific and management needs. Together, these indicators improve the understanding and management of the effects of climate change on freshwater ecosystems.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10584-022-03457-1","usgsCitation":"Rose, K.C., Bierwagen, B., Bridgham, S.D., Carlisle, D.M., Hawkins, C., Poff, N.L., Read, J., Rohr, J., Saros, J.E., and Williamson, C.E., 2023, Indicators of the effects of climate change on freshwater ecosystems: Climate Change, v. 176, 23, 20 p., https://doi.org/10.1007/s10584-022-03457-1.","productDescription":"23, 20 p.","ipdsId":"IP-087945","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":444327,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11254324","text":"External Repository"},{"id":421018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"176","noUsgsAuthors":false,"publicationDate":"2023-03-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Rose, Kevin C.","contributorId":174809,"corporation":false,"usgs":false,"family":"Rose","given":"Kevin","email":"","middleInitial":"C.","affiliations":[{"id":12656,"text":"Rensselaer Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":883564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bierwagen, Britta","contributorId":201420,"corporation":false,"usgs":false,"family":"Bierwagen","given":"Britta","email":"","affiliations":[],"preferred":false,"id":883565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bridgham, Scott D.","contributorId":177413,"corporation":false,"usgs":false,"family":"Bridgham","given":"Scott","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":883566,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":883567,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hawkins, Charles P.","contributorId":173015,"corporation":false,"usgs":false,"family":"Hawkins","given":"Charles P.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":883568,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Poff, N. LeRoy","contributorId":261271,"corporation":false,"usgs":false,"family":"Poff","given":"N.","email":"","middleInitial":"LeRoy","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":883569,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":883570,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rohr, Jason","contributorId":214630,"corporation":false,"usgs":false,"family":"Rohr","given":"Jason","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":883571,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Saros, Jasmine E.","contributorId":302770,"corporation":false,"usgs":false,"family":"Saros","given":"Jasmine","email":"","middleInitial":"E.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":883572,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Williamson, Craig E.","contributorId":146436,"corporation":false,"usgs":false,"family":"Williamson","given":"Craig","email":"","middleInitial":"E.","affiliations":[{"id":16608,"text":"Miami University","active":true,"usgs":false}],"preferred":false,"id":883573,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70243279,"text":"70243279 - 2023 - Wildfire-induced shifts in groundwater discharge to streams identified with paired air and stream water temperature analyses","interactions":[],"lastModifiedDate":"2023-05-05T12:02:31.291377","indexId":"70243279","displayToPublicDate":"2023-03-01T06:59:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Wildfire-induced shifts in groundwater discharge to streams identified with paired air and stream water temperature analyses","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab010\" class=\"abstract author\"><div id=\"as010\"><p id=\"sp0010\">Within the western United States, increasingly severe and frequent wildfires may alter the magnitude, timing, and quality of water exported from burned areas by streams. Post-fire hydrologic studies often focus on peak stream flow responses to shifts in runoff generation or on annual streamflow yield response to changes in evapotranspiration following fire. However, the magnitude and duration of wildfire effects on groundwater recharge, changes in subsurface routing, and consequences for stream low flows sourced predominately by baseflow are poorly understood. Here, we demonstrate an approach using the amplitude and phase of paired annual air and stream water temperature signals to broadly identify changes in watershed subsurface flow contributions after fire. Watersheds were classified using pre-fire temperature data, as having air-coupled (i.e., reduced apparent groundwater signature), deep groundwater, or shallow groundwater stream temperature signals. Changes in pre- and post-fire paired air and stream water temperature metrics were compared for locations (n&nbsp;=&nbsp;17) spanning a large range of physiographic and climatic conditions across the western United States. Pre- and post-fire comparisons were computed by quantile using bootstrapped confidence intervals (ci&nbsp;=&nbsp;95), as well as in aggregate using Kruskal-Wallis and post-hoc Dunn tests. Statistical comparisons of pre- and post-fire temperature metrics suggest that overall, watersheds classified as having minimal groundwater influence are the most likely to experience fire-induced subsurface hydrologic change. More specifically, watersheds classified as having air-coupled or shallow groundwater signals experienced increases in the magnitude of groundwater discharge, with more stable annual thermal regimes post-fire that are less-coupled to ambient air temperature. These findings form the basis of a conceptual framework for watershed resistance to subsurface hydrologic change following fire that can be broadly applied as a first approximation for water management, impacts on aquatic habitat, and post-wildfire response planning.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2023.129272","usgsCitation":"Rey, D., Briggs, M., Walvoord, M.A., and Ebel, B., 2023, Wildfire-induced shifts in groundwater discharge to streams identified with paired air and stream water temperature analyses: Journal of Hydrology, v. 619, 129272, 10 p., https://doi.org/10.1016/j.jhydrol.2023.129272.","productDescription":"129272, 10 p.","ipdsId":"IP-148738","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":444329,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2023.129272","text":"Publisher Index Page"},{"id":416753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Oregon, 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,{"id":70240728,"text":"sir20225125 - 2023 - Modeling flow and water quality in reservoir and river reaches of the Mahoning River Basin, Ohio","interactions":[],"lastModifiedDate":"2026-02-23T20:55:47.151064","indexId":"sir20225125","displayToPublicDate":"2023-02-27T16:09:05","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":"2022-5125","displayTitle":"Modeling Flow and Water Quality in Reservoir and River Reaches of the Mahoning River Basin, Ohio","title":"Modeling flow and water quality in reservoir and river reaches of the Mahoning River Basin, Ohio","docAbstract":"<h1>Executive Summary</h1><p>The U.S. Army Corps of Engineers (USACE) is considering changes to the management of water surface elevation in four lakes in the Mahoning River Basin. These changes would affect the timing and amounts of water released to the Mahoning River and could affect the water quality of those releases. To provide information on possible water-quality effects from these operational changes, flow and water-quality models were constructed for Berlin Lake, Lake Milton, Michael J Kirwan Reservoir, Mosquito Creek Lake, Mosquito Creek, and the Mahoning River from the dams downstream to Lowellville, Ohio.</p><p>The models were calibrated for two calendar years each, with model years selected depending on the availability of water-quality data. Models were developed with CE-QUAL-W2 version 4.2 (Wells, S.A., 2020, CE-QUAL-W2—A two-dimensional, laterally averaged, hydrodynamic and water quality model [version 4.2]: Portland State University, variously paged), a two-dimensional, laterally averaged hydrodynamic and water-quality model. Modeled constituents included flow, velocity, ice cover, water temperature, total dissolved solids (TDS), sulfate, chloride, inorganic suspended sediment, nitrate, ammonia, total Kjeldahl nitrogen, orthophosphate, total phosphorus, dissolved and particulate organic matter, algae, and dissolved oxygen. Iron was included for the lake models, but not the river.</p><p>A whole-basin model, with the four lake models and river model, was used to run model scenarios to examine the effects of altered lake water surface elevations on flow and water quality in the lakes, the lake outflows, and the Mahoning River. The initial whole-basin model, with calendar year 2013 hydrology and measured or typical water quality, was designated as scenario 0. Mahoning River flows for calendar year 2013 were close to a 20-year median flow. Four additional scenarios were constructed based on reservoir operations model (RES-SIM) model water surface elevations for the four lakes as provided by USACE. Scenario 1 was the RES-SIM base case, scenario 2 kept Berlin Lake water surface elevations higher in summer, scenario 3 allowed 25 percent of summer flood storage to extend the guide curve, and scenario 4 allowed more flexibility in lake management by removing any downstream Mahoning River minimum flow requirements. The Mahoning River model was not changed in any scenarios but received altered flows from the lakes. Significant findings from this study include the following:</p><ul><li>In two of the four lakes (Berlin and Mosquito Creek Lakes), development of lake model grids using recent bathymetric surveys suggests that sedimentation in these lakes has occurred since they were constructed, altering volume-elevation curves.</li><li>Tests of model parameter sensitivity showed that modeled water temperature, TDS, and dissolved oxygen were relatively insensitive to model parameter values. Modeled chlorophyll <i>a</i>, a measure of algal concentration, was most sensitive to parameter values; nitrate and total phosphorus concentrations were affected by a few of the parameters tested. As a group, the lake model results were more sensitive to model parameter values compared to the Mahoning River model.</li><li>Data gaps were identified for inflows, both for water quantity and water quality, that could be filled through future sampling programs. Ample data were available from within the waterbodies for model calibration.</li><li>The model simulated the general spatial and temporal patterns of water temperature, TDS, chloride, sulfate, nutrients, suspended sediment, organic matter, chlorophyll <i>a</i>, and dissolved oxygen in the lakes and Mahoning River.</li><li>From late spring to autumn in the years modeled (2006, 2013, 2017–19 depending on the lake), all lakes developed thermal stratification and periods of anoxia in bottom waters. Stratification was most stable in Michael J Kirwan Reservoir and least stable in Mosquito Creek Lake. The stratification and anoxia in Berlin Lake, Lake Milton, and Mosquito Creek Lake could be interrupted by high-flow inputs moving through those lakes.</li><li>The model predicted the release of ammonia and iron during anoxic periods in the lake hypolimnions.</li><li>Concentrations of TDS, nitrate, orthophosphate, and total phosphorus increased in the Mahoning River down to Lowellville, the end of the river model, in the years modeled. These concentrations were greater than those in upstream lake releases.</li><li>Chloride and sulfate concentrations were underpredicted in the Mahoning River, suggesting the presence of unreported chloride and sulfate inputs to the river, at least in the years modeled.</li><li>Model scenario 4 kept water surface elevations the highest in all lakes in the April to mid-December period, compared to scenarios 1–3. Model scenario 2 kept water surface elevations in Berlin Lake higher in summer and late autumn, compared to scenarios 1 and 3, but to satisfy downstream minimum flow requirements, water surface elevations in the other lakes had periods of lower water surface elevation.</li><li>As a group, scenarios 1–3 had largely similar effects on flow and water surface elevation in the Mahoning River because the lake releases in those scenarios still met downstream Mahoning River flow targets.</li><li>Modeling the removal of downstream flow targets, scenario 4 had periods of lower flow in the Mahoning River from April to mid-September as water was held in the lakes, and periods of higher Mahoning River flow from mid-September through November as the lakes were drawn down to prepare for winter flood-risk management.</li><li>In the four scenarios, all the lakes and lake outflows had generally similar seasonal cycles of water quality, though some differences were predicted. For instance, higher concentrations of iron and ammonia in the Lake Milton hypolimnion were modeled during a period of both low inflows from Berlin Lake and low outflows at Lake Milton dam. It is possible that those changes could be minimized by maintaining more flow or pulses of higher flow through the lake.</li><li>Compared to the scenario 1 base case, changes to Mahoning River water quality were relatively minor for scenarios 2 and 3, which maintained downstream flows but shifted the flow source among the upstream lakes.</li><li>The largest changes in Mahoning River water quality were predicted between Leavittsburg and Lowellville for scenario 4. The periods of lower lake outflows between April and mid-September led to correspondingly higher concentrations of TDS, orthophosphate, total phosphorus, and nitrate in the river, compared to the base case scenario 1. Conversely, the overall greater lake outflows from mid-September through November in scenario 4 led to periods of lower concentrations of TDS and nutrients in that portion of the river, at that time of year.</li></ul>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225125","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Sullivan, A.B., Georgetson, G.M., Urbanczyk, C.E., Gordon, G.W., Wherry, S.A., and Long, W.B., 2023, Modeling flow and water quality in reservoir and river reaches of the Mahoning River Basin, Ohio: U.S. Geological Survey Scientific Investigations Report 2022–5125, 101 p., https://doi.org/10.3133/sir20225125.","productDescription":"Report: xi, 101 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-124907","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":413149,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5125/images"},{"id":413146,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5125/sir20225125.pdf","text":"Report","size":"38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5125"},{"id":413145,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5125/coverthb.jpg"},{"id":500467,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114425.htm","linkFileType":{"id":5,"text":"html"}},{"id":413150,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5125/sir20225125.XML"},{"id":413148,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IRZL8S","text":"USGS data release","description":"USGS data release","linkHelpText":"CE-QUAL-W2 water-quality model and data for Berlin Lake, Lake Milton, Michael J Kirwan Reservoir, Mosquito Creek Lake, and the Mahoning River, Ohio"}],"country":"United States","state":"Ohio","otherGeospatial":"Mahoning River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -81.09848920357355,\n              40.83548711669414\n            ],\n            [\n              -80.46047172680031,\n              40.83548711669414\n            ],\n            [\n              -80.46047172680031,\n              41.777477506089326\n            ],\n            [\n              -81.09848920357355,\n              41.777477506089326\n            ],\n            [\n              -81.09848920357355,\n              40.83548711669414\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_or@usgs.gov\" data-mce-href=\"mailto:dc_or@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/or-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/or-water\">Oregon Water Science Center</a><br>U.S. Geological Survey<br>601 SW 2nd Avenue, Suite 1950<br>Portland, OR 97204</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Methods and Data</li><li>Model Development</li><li>Model Water Quality</li><li>Model Application</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2023-02-27","noUsgsAuthors":false,"publicationDate":"2023-02-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":79821,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett B.","email":"annett@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":864550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Georgetson, Gabrielle M.","contributorId":302498,"corporation":false,"usgs":false,"family":"Georgetson","given":"Gabrielle","email":"","middleInitial":"M.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":864551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Urbanczyk, Christina E.","contributorId":302499,"corporation":false,"usgs":false,"family":"Urbanczyk","given":"Christina","email":"","middleInitial":"E.","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":864552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gordon, Gabriel W. 0000-0001-6866-0302 ggordon@usgs.gov","orcid":"https://orcid.org/0000-0001-6866-0302","contributorId":269773,"corporation":false,"usgs":true,"family":"Gordon","given":"Gabriel W.","email":"ggordon@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wherry, Susan A. 0000-0002-6749-8697 swherry@usgs.gov","orcid":"https://orcid.org/0000-0002-6749-8697","contributorId":4952,"corporation":false,"usgs":true,"family":"Wherry","given":"Susan","email":"swherry@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":864554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, William B. 0000-0002-9097-0603 wlong@usgs.gov","orcid":"https://orcid.org/0000-0002-9097-0603","contributorId":302501,"corporation":false,"usgs":true,"family":"Long","given":"William","email":"wlong@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science 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