Between the 1950s and 1980s, wastewater generated at the Idaho National Laboratory contained Iodine-129 (129I); this wastewater was discharged directly into the eastern Snake River Plain (ESRP) aquifer through a deep disposal well, unlined infiltration ponds, or leaked from distribution systems below industrial facilities. During 2021–22, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy and the Idaho Department of Environmental Quality Idaho National Laboratory Oversight Program, collected groundwater samples from 64 monitoring wells in the ESRP aquifer, 6 of which are part of a multilevel monitoring system, to determine the concentration of 129I in the groundwater. These samples were analyzed by accelerator mass spectrometry as part of a long-term ongoing study to track trends and occurrences of this carcinogenic, long-lived radionuclide in the environment. Concentrations ranged from slightly above the locally determined background concentration of 5.4×10−6 picocuries per liter, to just below the U.S. Environmental Protection Agency’s maximum contaminant level of 1 picocurie per liter. Discharge of wastewater containing 129I has been discontinued to the aquifer, and long-term trends from a subset (n=15) of sampled wells show decreasing 129I concentrations over the last three decades. Concentrations of 129I in groundwater from monitoring wells near facilities at the Idaho National Laboratory are affected by episodic recharge from an ephemeral surface-water source and by the fracture-flow dominated hydrologic regime in the ESRP aquifer. The spatially focused sampling effort has also identified a low-level 129I plume that affects long-term water quality near and downgradient from the Advanced Test Reactor Complex in the southwestern part of the facility that had not been clearly defined in previous sampling efforts, although the definition of the plume is somewhat limited by available data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245124","collaboration":"Prepared in cooperation with the U.S. Department of Energy","programNote":"DOE/ID-22262","usgsCitation":"Treinen, K.C., Trcka, A.R., Krohe, N., and Lehotsky, G., 2024, Iodine-129 in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 2021–22: U.S. Geological Survey Scientific Investigations Report 2024–5124 (DOE/ID 22262), 27 p., https://doi.org/10.3133/sir20245124.","productDescription":"Report: vii, 27 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-150514","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":494219,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118236.htm","linkFileType":{"id":5,"text":"html"}},{"id":465410,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245124/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5124"},{"id":465409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5124/sir20245124.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5124"},{"id":465413,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5124/sir20245124.XML"},{"id":465412,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5124/images"},{"id":465411,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UWRYR4","text":"USGS data release","description":"USGS data release","linkHelpText":"Datasets for the U.S. Geological Survey—Idaho National Laboratory groundwater and surface-water monitoring networks, v1.1"},{"id":465408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5124/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Eastern Snake River Plain aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.973611,\n 43.591667\n ],\n [\n -112.916667,\n 43.591667\n ],\n [\n -112.916667,\n 43.540278\n ],\n [\n -112.973611,\n 43.540278\n ],\n [\n -112.973611,\n 43.591667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4250
Great Salt Lake is a critical habitat for migratory birds that is threatened by elevated metal concentrations, including mercury (Hg) and lead (Pb), and is subject to severe hydrologic changes, such as declining lake level. When assessing metal profiles recorded in Great Salt Lake sediment, a large data gap exists regarding the sources of metals within the system, which is complicated by various source inputs to the lake and complex biogeochemistry. Here, we leverage Hg and Pb stable isotopes to track relative changes in metal source contributions to Great Salt Lake over time. Mercury and Pb concentrations increase in sediments deposited after 1920 and peak between 1965 and 1995, following closure of several local smelters and the onset of increased emission controls. The nominal associations above are confirmed via Hg stable isotopes in pre-1920 background sediments, which reflect atmospheric inputs from regional and global origin, whereas Hg and Pb stable isotopes together indicate that elevated metal concentrations in mid-late 20th century sediments reflect increased mining/smelting inputs. The observed minimal rebound towards pre-1920 Pb isotope signatures in 21st century sediments indicates that mining/smelting inputs, though reduced, remain a primary source of Pb to Great Salt Lake. In contrast, the more pronounced rebound of Hg stable isotope signatures to pre-1920 values indicate a greater contribution of atmospheric inputs of regional/global origin to current Hg inputs, though Hg concentrations are ∼10 times greater than pre-1920 background values due to global increases in atmospheric Hg concentrations or possibly slow recovery from local contamination. The importance of regional/global Hg sources to the system suggests that reductions in Hg bioaccumulation in the open water food webs of Great Salt Lake are more dependent on national and global reductions in Hg emissions and management strategies to limit methylmercury production within system. This work highlights the utility of using coupled Hg and Pb stable isotope values to assess trace metal pollution sources and pathways in aquatic systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2024.177374","usgsCitation":"Lopez, S.F., Janssen, S., Tate, M., Fernandez, D.P., Anderson, C.R., Armstrong, G.J., Wang, T.C., and Johnson, W.P., 2024, Using mercury and lead stable isotopes to assess mercury, lead, and trace metal source contributions to Great Salt Lake, Utah, USA: Science of the Total Environment, v. 957, 177374, 14 p., https://doi.org/10.1016/j.scitotenv.2024.177374.","productDescription":"177374, 14 p.","ipdsId":"IP-170245","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":488066,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2024.177374","text":"Publisher Index Page"},{"id":464466,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Great Salt Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.27532189699335,\n 41.764305005205784\n ],\n [\n -113.27532189699335,\n 40.550910675427446\n ],\n [\n -111.82239945429947,\n 40.550910675427446\n ],\n [\n -111.82239945429947,\n 41.764305005205784\n ],\n [\n -113.27532189699335,\n 41.764305005205784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"957","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lopez, Samuel Francisco 0000-0002-3544-7465","orcid":"https://orcid.org/0000-0002-3544-7465","contributorId":344607,"corporation":false,"usgs":true,"family":"Lopez","given":"Samuel","email":"","middleInitial":"Francisco","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919347,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fernandez, Diego P.","contributorId":138701,"corporation":false,"usgs":false,"family":"Fernandez","given":"Diego","email":"","middleInitial":"P.","affiliations":[{"id":12499,"text":"Univ. of Utah","active":true,"usgs":false}],"preferred":false,"id":919348,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Christopher R.","contributorId":346496,"corporation":false,"usgs":false,"family":"Anderson","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":919349,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Armstrong, Grace Jane 0009-0009-8132-9011","orcid":"https://orcid.org/0009-0009-8132-9011","contributorId":332127,"corporation":false,"usgs":true,"family":"Armstrong","given":"Grace","email":"","middleInitial":"Jane","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919350,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wang, Thomas Charng-Shuen 0009-0001-2214-4721","orcid":"https://orcid.org/0009-0001-2214-4721","contributorId":331024,"corporation":false,"usgs":true,"family":"Wang","given":"Thomas","email":"","middleInitial":"Charng-Shuen","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":919351,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, William P.","contributorId":107288,"corporation":false,"usgs":false,"family":"Johnson","given":"William","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":919352,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70261721,"text":"sir20245117 - 2024 - Hydrologic and hydraulic analyses of Silver Creek and selected tributaries associated with Scott Air Force Base, Illinois, 2022–24","interactions":[],"lastModifiedDate":"2025-08-15T16:14:31.530381","indexId":"sir20245117","displayToPublicDate":"2024-12-20T08:15:47","publicationYear":"2024","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":"2024-5117","displayTitle":"Hydrologic and Hydraulic Analyses of Silver Creek and Selected Tributaries Associated with Scott Air Force Base, Illinois, 2022–24","title":"Hydrologic and hydraulic analyses of Silver Creek and selected tributaries associated with Scott Air Force Base, Illinois, 2022–24","docAbstract":"A hydrologic model of the Silver Creek Basin in southwest Illinois, and a hydraulic model of a selected reach of Silver Creek and local tributaries on and near Scott Air Force Base, Illinois, were developed to assess the effects of temporal land-use development in the Silver Creek Basin, the potential effects of projected changes based on future precipitation, and the effects of added detention storage in selected tributaries near Scott Air Force Base. The hydrologic model consists of a total of 52 scenarios—24 scenarios for an assessment of basin-wide changes in hydrology, and 28 scenarios for the hydraulic analysis of a focus area of Silver Creek and tributaries on and near Scott Air Force Base. Scenarios were run for precipitation events of 2-year through 500-year recurrence intervals (50-percent through 0.2-percent annual exceedance probability) and 24-hour durations.
The effects of detention structures added to Silver Creek tributaries throughout Scott Air Force Base were greater on water-level profiles (about 1 to 3 feet) than the effects of projected (2050) changes in precipitation (about 1 foot or less) in these basins. The results indicated that despite the increases in water-surface elevations resulting from projected increases in precipitation, the detention structures could provide a net reduction in water-surface elevations in the flood-prone western tributaries on the base. The effects of detention structures and projected precipitation also were assessed using the mapped extent of inundation for the simulated probabilistic precipitation scenarios. As an example, limited inundation of a residential area along Ash Creek was evident in the 5-year recurrence interval event for the scenarios without detention storage, whereas the first indications of flooding in the residential area from the scenario with detention storage were in the 50-year recurrence interval event.
Changes in hydrologic conditions followed a spatial pattern similar to that of the changes in land-cover development, with the greatest changes in the downstream one-half of the Silver Creek Basin and most pronounced in subbasins on and surrounding Scott Air Force Base. There was up to an estimated 54.6-percent increase in peak streamflows in subbasins on or near Scott Air Force Base from historical (1992) to current (2019) conditions, but changes in peak streamflows of as much as 144 percent are anticipated under the planned (to about 2050) land cover plus projected (2050) precipitation. The changes in the timing of peak streamflows were towards earlier peaks, with cumulative changes between historical and projected conditions approaching 0.75 hour (45 minutes) for a 2-year recurrence interval event. Results of the percentage change in cumulative event volume were similar to those of percentage change in peak streamflows in terms of magnitude of change and temporal and spatial distribution of changes. The greatest magnitude of percentage change in the assessed hydrologic properties was associated with the 2-year recurrence interval event, and the magnitude of the percentage change decreased with increasing probabilistic event recurrence interval. Subbasins with a substantial change in runoff yield between historical and current conditions were primarily in the downstream one-half of the Silver Creek Basin and most were within or adjacent to Scott Air Force Base. The magnitude of runoff yield changes increased with recurrence interval, and maximum changes were associated with subbasins on base and with the changes between the historical and current conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245117","collaboration":"Prepared in cooperation with Scott Air Force Base","usgsCitation":"Cigrand, C.V., Heimann, D.C., and Rydlund, P.H., Jr., 2024, Hydrologic and hydraulic analyses of Silver Creek and selected tributaries associated with Scott Air Force Base, Illinois, 2022–24: U.S. Geological Survey Scientific Investigations Report 2024–5117, 87 p., https://doi.org/10.3133/sir20245117.","productDescription":"Report: x, 87 p.; Data Release; 2 Datasets","numberOfPages":"102","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135331","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":494220,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118090.htm","linkFileType":{"id":5,"text":"html"}},{"id":465320,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GBYP2K","text":"USGS data release","linkHelpText":"Archive of hydrologic and hydraulic models used in the analyses of Silver Creek Basin and selected tributaries associated with Scott Air Force Base, Illinois, 1992–2050"},{"id":465321,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://datagateway.nrcs.usda.gov/GDGOrder.aspx","text":"U.S. Department of Agriculture, Natural Resources Conservation Service database","linkHelpText":"- GeoSpatial data gateway"},{"id":465322,"rank":8,"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":465316,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5117/sir20245117.pdf","text":"Report","size":"97.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5117"},{"id":465317,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5117/sir20245117.XML"},{"id":465318,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5117/images/"},{"id":465315,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5117/coverthb.jpg"},{"id":465319,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245117/full"}],"country":"United States","state":"Illinois","otherGeospatial":"Scott Air Force Base, Silver Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.8831289278596,\n 38.57664573726461\n ],\n [\n -89.8831289278596,\n 38.50342611477362\n ],\n [\n -89.77601466850366,\n 38.50342611477362\n ],\n [\n -89.77601466850366,\n 38.57664573726461\n ],\n [\n -89.8831289278596,\n 38.57664573726461\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
The Russian River watershed is in northern Sonoma County and southern Mendocino County, California, in the northern part of the California Coast Ranges. The Russian River serves as a supply for agricultural irrigation and for municipal, domestic, and commercial uses. Through a cooperative agreement with the California State Water Resources Control Board and Sonoma County Water Agency, the U.S. Geological Survey has completed studies to better understand the hydrogeologic system and develop numerical hydrologic modeling tools to evaluate and aid in managing groundwater resources. This report focuses on the development of a digital three-dimensional hydrogeologic framework model of the Russian River watershed for use in groundwater resource assessment and numerical models.
The digital three-dimensional hydrogeologic framework model of the Russian River watershed portrays the altitude, thickness, and extent of five hydrogeologic units. These five hydrogeologic units include (1) a basement unit, (2) the Sonoma Volcanics, (3) a consolidated sedimentary rock unit, (4) an unconsolidated sediment unit, and (5) channel alluvium. Model input data were compiled from published geologic maps, interpreted well data, and a model of the top of basement derived from gravity data. These data were used to construct surfaces that represent the upper and lower subsurface boundaries of each hydrogeologic unit. Top surfaces were created for the five hydrogeologic units and then stacked in three dimensions to create a solid-volume digital model.
The digital three-dimensional hydrogeologic framework model described in this report and the corresponding data represent the generalized geometry of the subsurface geologic units; the model reproduces the input geologic data with reasonable accuracy and is consistent with previously published subsurface conceptualizations of the region. The model indicates the overall geometry of the basement within the watershed and the spatial extent, altitude, and thickness of the basin-filling units. The hydrogeologic framework model is at a scale and resolution appropriate for use as the foundation for a numerical hydrologic model of the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245083","collaboration":"Prepared in cooperation with the California State Water Resources Control Board and Sonoma County Water Agency","programNote":"Water Availability and Use Science Program—Water Resources Mission Area","usgsCitation":"Cromwell, G., Sweetkind, D.S., Langenheim, V.E., and Ely, C.P., 2024, Three-dimensional hydrogeologic framework model of the Russian River watershed, California: U.S. Geological Survey Scientific Investigations Report 2024–5083, 25 p., https://doi.org/10.3133/sir20245083.","productDescription":"Report: viii, 25 p.; Data Release","numberOfPages":"25","onlineOnly":"Y","ipdsId":"IP-122963","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":465343,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GPH5FW","text":"USGS Data Release","description":"Fenton, N.C., Cromwell, G., Sweetkind, D.S., Langenheim, V.E., Ely, C.P., Kohel, C.A., Martin, A.J., Morita, A.Y., Peterson, M.F., and Roberts, M.A., 2022, Hydrogeologic data of the Russian River watershed, Sonoma and Mendocino Counties, California (ver. 1.1, July 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P9GPH5FW.","linkHelpText":"Hydrogeologic data of the Russian River watershed, Sonoma and Mendocino Counties, California (ver. 1.1, July 2023)"},{"id":465348,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5083/images"},{"id":465346,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5083/sir20245083.xml","linkFileType":{"id":8,"text":"xml"}},{"id":465347,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245083/full"},{"id":494221,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118084.htm"},{"id":465345,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5083/sir20245083.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":465344,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5083/covrthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Russian River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.25,\n 39.25\n ],\n [\n -123.25,\n 38.333\n ],\n [\n -122.667,\n 38.333\n ],\n [\n -122.667,\n 39.25\n ],\n [\n -123.25,\n 39.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The U.S. Geological Survey, in cooperation with the Upper Gunnison River Water Conservancy District, studied historical streamflow in a reach of the East River, Colorado, to gain a preliminary understanding of return flow dynamics. Return flow is agricultural irrigation water that is not consumed by evapotranspiration and instead reaches streams by surface and subsurface flow paths. The study reach had a contributing area of 50 square miles and contained 5.23 square miles of pastures irrigated with water diverted from the East River and its tributaries. By comparing upstream inflows to downstream outflows, the net water balance of the study reach from 1994 to 2023 was assessed.
Two general hydrologic conditions for the study reach were identified. One hydrologic condition was characterized by a net loss or consumption of water, termed here as general deficit. This general deficit condition extended about 16 years, from 1997 to 2012. During general deficit years, there was usually a notable net loss of streamflow from April through July, and a small net gain, possibly related to return flows, occurred in August about 75 days after the minimums for losses. The second hydrologic condition was characterized by a net gain of water, termed here as general surplus. This second condition extended about 10 years, from 2014 to 2023. During general surplus years, two separate transitions from net loss to net gain commonly occurred during June through August. Losses during general surplus years were smaller than losses during general deficit years, the respective gains were larger, and times between losses and gains were about 18 and 22 days.
Differences between the two hydrologic conditions could reflect interactions among irrigation water, available capacity to store additional shallow groundwater, and streamflow. However, deciphering the causes for the shifts between the two general hydrologic conditions was beyond the scope of this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20241075","collaboration":"Prepared in cooperation with Upper Gunnison River Water Conservancy District","usgsCitation":"Bern, C.R., and Gidley, R.G., 2024, Agricultural return flow dynamics on a reach of the East River, Colorado, as assessed by mass balance: U.S. Geological Survey Open-File Report 2024–1075, 10 p., https://doi.org/10.3133/ofr20241075.","productDescription":"Report: iv, 10 p.; Database","onlineOnly":"Y","ipdsId":"IP-170543","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":494235,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118077.htm","linkFileType":{"id":5,"text":"html"}},{"id":465116,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241075/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1075"},{"id":465073,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1075/ofr20241075.xml"},{"id":465072,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1075/images"},{"id":464952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1075/ofr20241075.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1075"},{"id":464954,"rank":3,"type":{"id":9,"text":"Database"},"url":"http://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation","linkHelpText":"U.S. Geological Survey National Water Information System database, accessed June 15, 2024"},{"id":464951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1075/coverthb.jpg"}],"country":"United states","state":"Colorado","otherGeospatial":"East River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.966667,\n 38.8333\n ],\n [\n -106.966667,\n 38.6333\n ],\n [\n -106.766667,\n 38.6333\n ],\n [\n -106.766667,\n 38.8333\n ],\n [\n -106.966667,\n 38.8333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
No abstract available.
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The purpose of the inventory was to provide information about water bottling facilities needed to assess and improve understanding of local-, regional-, and national-scale hydrologic and socioeconomic effects resulting from water extraction for bottling. Beverage types coded in the North American Industry Classification System under subsector 312 (Beverage and Tobacco Product Manufacturing) were compiled; however, facility information was often not publicly available, time intensive to search manually, and difficult to verify because there are no nationally available facility lists. A separate evaluation of facilities in the Great Lakes region identified some facilities that were missing and some with incorrect information. Ancillary facility attributes were primarily available from a proprietary business dataset and water-use data could only be acquired for a small subset of facilities. These limitations and deficiencies may affect the types of analyses that can be done using the inventory information. Therefore, the following data-quality aspects are used to describe the information compiled in the facility and water-use tables: completeness, uniqueness, validity, timeliness, accuracy, consistency, and accessibility. The resulting implications of the data and knowledge gaps are that users of the data may need to make additional evaluations of the inventory information for some analyses.
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U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Geochemical and hydrologic models of pit lakes are commonly used in environmental regulatory decisions to predict future water quality and hydrologic conditions and to understand existing pit lakes. Models may be used to quantify sulfide oxidation, predict thermal/chemical stratification and mixing, and better understand connections between pit lakes and aquifers. One concern related to the hydrologic character of pit lakes is if they are terminal (a groundwater sink with no outflow) or flowthrough (both receiving groundwater inflow and discharging to groundwater). This question was pertinent to the Liberty pit lake, a small acidic pit lake formed in a former Cu deposit in south-central Nevada where potentiometric and geochemical data potentially indicate pit-lake outflow. Potential discharge to groundwater from the pit lake was evaluated using a water-balance model, but uncertainty in hydraulic parameters led to ambiguity in the hydrologic character. Stable isotopes of water were then sampled from the pit lake and adjacent groundwater wells, which unambiguously indicated the lack of an evaporative signature in downgradient groundwater because the groundwater did not plot on a hypothetical mixing line between evaporated pit lake water and observed meteoric recharge. This methodology provided a more effective and more data-driven approach for understanding pit-lake hydrology. Although predictive models are required to quantify reasonable bounds on future conditions, many models contain substantial uncertainty and are not well suited in some environments. Datasets that provide more clear lines of evidence could be collected from existing pit lakes whenever possible to inform water-rock interaction, limnological behavior, and connectivity to adjacent groundwater.
","conferenceTitle":"International Conference on Acid Rock Drainage","conferenceDate":"September 16-20, 2024","conferenceLocation":"Halifax, Nova Scotia, Canada","language":"English","publisher":"Canadian Institute of Mining, Metallurgy and Petroleum","usgsCitation":"Newman, C.P., 2024, Models no not provide proof: An example of model ambiguity and application of isotopic data in a mine pit lake, International Conference on Acid Rock Drainage, Halifax, Nova Scotia, Canada, September 16-20, 2024, p. 1345-1356.","productDescription":"12 p.","startPage":"1345","endPage":"1356","ipdsId":"IP-164239","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":499757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Liberty pit lake","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Newman, Connor P. 0000-0002-6978-3440","orcid":"https://orcid.org/0000-0002-6978-3440","contributorId":222596,"corporation":false,"usgs":true,"family":"Newman","given":"Connor","email":"","middleInitial":"P.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931595,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70260864,"text":"fs20243042 - 2024 - Using citizen scientists to collect oxygen and hydrogen isotope data in southern Nevada","interactions":[],"lastModifiedDate":"2025-12-22T21:14:16.959755","indexId":"fs20243042","displayToPublicDate":"2024-11-25T12:47:51","publicationYear":"2024","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":"2024-3042","displayTitle":"Using Citizen Scientists to Collect Oxygen and Hydrogen Isotope Data in Southern Nevada","title":"Using citizen scientists to collect oxygen and hydrogen isotope data in southern Nevada","docAbstract":"Citizen science programs provide a means for Federal and non-Federal government agencies to make science more engaging, transparent, and accessible by partnering with the public for the purpose of problem solving, data collection, and monitoring. Public volunteers become directly involved in local research, thereby engaging in scientific projects. The public has already been included in existing citizen science programs that cover a broad range of disciplines, such as ecology, hydrology, and tectonics. Citizen science advances research while simultaneously fostering a sense of involvement and interest from the public.
Beginning in 2017, the U.S. Geological Survey (USGS), U.S. Forest Service, Bureau of Land Management, U.S. Fish and Wildlife Service, and National Park Service collaborated with private, non-profit partners to inventory, survey, and rehabilitate springs in Clark County, Nevada. The USGS maintains the National Water Information System (NWIS), a publicly available online database of water-resources data for the Nation, and the agency is interested in using citizen science to add geochemical data from springs in southern Nevada.
From 2021 to 2023, the USGS directly worked with citizen science partners, including the Springs Stewardship Institute and the Friends of Nevada Wilderness, to collect stable isotope and tritium samples from southern Nevada springs. The citizen science volunteers were provided the training and supplies for proper sample collection by USGS staff. As the citizen science partners traveled and hiked to the remote spring sites to complete spring surveys and perform restoration activities, they collected stable isotope and tritium samples for the USGS. Samples were shipped to national USGS laboratories for analysis, and the results were uploaded to the NWIS database (U.S. Geological Survey, 2024).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243042","collaboration":"Prepared in cooperation with the U.S. Forest Service, Bureau of Land Management, U.S. Fish and Wildlife Service, and National Park Service","usgsCitation":"Gonzales, J.M., Earp, K.J., and Cromratie Clemons, S.K., 2024, Using citizen scientists to collect oxygen and hydrogen isotope data in southern Nevada: U.S. Geological Survey Fact Sheet 2024–3042, 2 p., https://doi.org/10.3133/fs20243042.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-168597","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":497907,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118053.htm"},{"id":464448,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243042/full"},{"id":463892,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3042/images"},{"id":463891,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3042/fs20243042.xml"},{"id":463890,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3042/fs20243042.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":463889,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3042/covrthb.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 -114.6448726815736,\n 35.0569367782968\n ],\n [\n -114.58859270961553,\n 35.54700274401317\n ],\n [\n -114.6343675607446,\n 36.05085213875432\n ],\n [\n -114.05419193738352,\n 35.97188063994203\n ],\n [\n -114.05603111683918,\n 37\n ],\n [\n -117.13811636232018,\n 37\n ],\n [\n -114.6448726815736,\n 35.0569367782968\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 89701
Carbon fluxes in tidal brackish marshes play a critical role in determining coastal wetland carbon sequestration and storage, thus affecting carbon crediting of coastal wetland restoration. In this study, a process-driven wetland biogeochemistry model, Wetland Carbon Assessment Tool DeNitrification-DeComposition was applied to nine brackish marsh sites in Mississippi River (MR) Deltaic Plain to examine the responses of gross primary productivity (GPP), ecosystem respiration (ER), net ecosystem exchange (NEE), and emissions of methane (CH4) and nitrous oxide (N2O) to climate change. Simulations of a normal hydrologic year (2013), dry year (2011) and wet year (2021), and a hypothetical sea level rise (SLR) case were conducted as climate change scenarios. These climate change scenarios were determined by the Palmer Drought Severity Index (PDSI) for the Northeast Division of Coastal Louisiana during 2001–2021. Model results showed that GPP, ER, NEE, CH4, and N2O vary with site, and these brackish marshes lost carbon (net CO2 emission) due to large reduction in primary productivity under the climate scenarios, as well as even during the normal hydrologic year. Average cross-site NEE were 148, 140 and 132 g C m−2 yr−1 in the dry, wet, and normal years (all net loss of wetland C). Under the hypothetical SLR, NEE were reduced by -25% compared to the normal year, but GPP and NPP were declined by -40% and -70%, respectively. These results suggest that climate change induced changes in soil salinity and water table depth will exacerbate carbon loss from tidal brackish marshes.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-024-01881-w","usgsCitation":"Wang, H., Krauss, K., Dai, Z., Noe, G.E., and Trettin, C.C., 2024, Modeling the responses of blue carbon fluxes in Mississippi River Deltaic Plain brackish marshes to climate change induced hydrologic conditions: Wetlands, v. 44, no. 8, 122, 19 p., https://doi.org/10.1007/s13157-024-01881-w.","productDescription":"122, 19 p.","ipdsId":"IP-168330","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":489083,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.mtu.edu/michigantech-p2/1205","text":"External Repository"},{"id":465027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":" Mississippi River Deltaic Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.15,\n 29.6667\n ],\n [\n -91.7,\n 29.6667\n ],\n [\n -91.7,\n 29.15\n ],\n [\n -90.15,\n 29.15\n ],\n [\n -90.15,\n 29.6667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Hongqing 0000-0002-2977-7732 wangh@usgs.gov","orcid":"https://orcid.org/0000-0002-2977-7732","contributorId":215079,"corporation":false,"usgs":true,"family":"Wang","given":"Hongqing","email":"wangh@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":920660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken 0000-0003-2195-0729","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":219804,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":920661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dai, Zhaohua 0000-0002-0941-8345","orcid":"https://orcid.org/0000-0002-0941-8345","contributorId":290409,"corporation":false,"usgs":false,"family":"Dai","given":"Zhaohua","email":"","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":920662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":920663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trettin, Carl C. 0000-0003-0279-7191","orcid":"https://orcid.org/0000-0003-0279-7191","contributorId":293476,"corporation":false,"usgs":false,"family":"Trettin","given":"Carl","email":"","middleInitial":"C.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":920664,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261071,"text":"sir20245089 - 2024 - Mapping karst groundwater flow paths and delineating recharge areas for springs in the Little Sequatchie and Pryor Cove watersheds, Tennessee","interactions":[],"lastModifiedDate":"2025-12-22T20:39:12.793493","indexId":"sir20245089","displayToPublicDate":"2024-11-22T16:23:22","publicationYear":"2024","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":"2024-5089","displayTitle":"Mapping Karst Groundwater Flow Paths and Delineating Recharge Areas for Springs in the Little Sequatchie and Pryor Cove Watersheds, Tennessee","title":"Mapping karst groundwater flow paths and delineating recharge areas for springs in the Little Sequatchie and Pryor Cove watersheds, Tennessee","docAbstract":"The Little Sequatchie River and Pryor Cove Branch, in southern Tennessee, drain the eastern escarpment of the Cumberland Plateau to the Sequatchie River near the southern end of the Sequatchie Valley. The Little Sequatchie River is the largest tributary to the Sequatchie River by drainage area, covering over 120 square miles. The hydrology of the two drainage areas has been largely altered by karst processes, which has caused the majority of the streams to sink at the contact between the Mississippian Pennington Formation and the underlying Mississippian Bangor Limestone. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service and Tennessee Department of Environment and Conservation, initiated a study in 2021 to map the karst groundwater pathways in both watersheds in order to delineate recharge areas for several springs. One of these springs, Sequatchie Cave, represents a significant habitat for two Species of Greatest Conservation Need, the Glyphopsyche sequatchie (Sequatchie caddisfly) and the federally endangered Marstonia ogmorhaphe (royal marstonia). Springs and springflow-dominated streams in the Little Sequatchie River valley and Pryor Cove also provide water for agricultural practices and serve as a drinking water source for nearby communities. During the study, a total of 25 dye injections were conducted over eight rounds from January 2022 through March 2023. Dye traces from these injections helped to delineate recharge areas for six major springs, ranging from 7.3 to 65.2 square miles in area. The majority of the dye traces remained subsurface (from sinkpoint to recovery site) for long distances, with karst groundwater travelling nearly 8 miles before resurfacing. The dye traces also had rapid traveltimes, often travelling hundreds to thousands of feet per hour. The goal of this project was to provide scientific data related to karst groundwater pathways and spring recharge areas to aid State and Federal agencies in making informed decisions to protect and preserve this unique and vulnerable karst system.
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Contact Us- USGS Publications Warehouse
","tableOfContents":"Soil moisture maps provide quantitative information that, along with climate and energy balance, is critical to integrate with hydrologic processes for characterizing landscape conditions. However, soil moisture maps are difficult to produce for natural landscapes because of vegetation cover and complex topography. Satellite-based L-band microwave sensors are commonly used to develop spatial soil moisture data products, but most existing L-band satellites provide only coarse scale (one to tens of kilometers grid size), information that is unsuitable for measuring soil moisture variation at hillslope or watershed-scales. L-band sensors are typically deployed on satellite platforms and aircraft but have been too large to deploy on small uncrewed aircraft systems (UAS). There is a need for greater spatial resolution and development of effective measures of soil moisture across a variety of natural vegetation types. To address these challenges, a novel UAS-based L-band radiometer system was evaluated that has recently been tested in agricultural settings. In this study, L-band UAS was used to map soil moisture at 3–50-m (m) resolution in a 13 square kilometer (km2) mixed grassland-forested landscape in Sonoma County, California. The results represent the first application of this technology in a natural landscape with complex topography and vegetation. The L-band inversion of the radiative transfer model produced soil moisture maps with an average unbiased root mean squared error (ubRMSE) of 0.07 m3/m3 and a bias of 0.02 m3/m3. Improved fine-scale soil moisture maps developed using UAS-based systems may be used to help inform wildfire risk, improve hydrologic models, streamflow forecasting, and early detection of landslides.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/frsen.2024.1337953","usgsCitation":"Stern, M.A., Ferrell, R., Flint, L.E., Kozanitas, M., Ackerly, D., Elston, J., Stachura, M., Dai, E., and Thorne, J.H., 2024, Fine-scale surficial soil moisture mapping using UAS-based L-band remote sensing in a mixed oak-grassland landscape: Frontiers in Remote Sensing, v. 5, 1337953, 12 p., https://doi.org/10.3389/frsen.2024.1337953.","productDescription":"1337953, 12 p.","ipdsId":"IP-159618","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499941,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frsen.2024.1337953","text":"Publisher Index Page"},{"id":499713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Sonoma County","city":"Santa Rosa","otherGeospatial":"Mayacamas Mountains, Pepperwood Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.71354880264356,\n 38.57616137564548\n ],\n [\n -122.71354880264356,\n 38.565372954642044\n ],\n [\n -122.68982536456959,\n 38.565372954642044\n ],\n [\n -122.68982536456959,\n 38.57616137564548\n ],\n [\n -122.71354880264356,\n 38.57616137564548\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","noUsgsAuthors":false,"publicationDate":"2024-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":955319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferrell, Ryan","contributorId":366124,"corporation":false,"usgs":false,"family":"Ferrell","given":"Ryan","affiliations":[{"id":37798,"text":"Pepperwood Preserve","active":true,"usgs":false}],"preferred":false,"id":955320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Lorraine E. 0000-0002-7868-441X","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":306090,"corporation":false,"usgs":false,"family":"Flint","given":"Lorraine","email":"","middleInitial":"E.","affiliations":[{"id":66369,"text":"Earth Knowledge, Inc.","active":true,"usgs":false}],"preferred":false,"id":955321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kozanitas, Melina","contributorId":366125,"corporation":false,"usgs":false,"family":"Kozanitas","given":"Melina","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":955322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ackerly, David","contributorId":139541,"corporation":false,"usgs":false,"family":"Ackerly","given":"David","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":955323,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elston, Jack","contributorId":334719,"corporation":false,"usgs":false,"family":"Elston","given":"Jack","affiliations":[{"id":80215,"text":"Black Swift Technologies","active":true,"usgs":false}],"preferred":false,"id":955324,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stachura, Maciej","contributorId":334720,"corporation":false,"usgs":false,"family":"Stachura","given":"Maciej","affiliations":[{"id":80215,"text":"Black Swift Technologies","active":true,"usgs":false}],"preferred":false,"id":955325,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dai, Eryan","contributorId":366129,"corporation":false,"usgs":false,"family":"Dai","given":"Eryan","affiliations":[{"id":87362,"text":"Weather Stream Inc.","active":true,"usgs":false}],"preferred":false,"id":955326,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thorne, James H.","contributorId":173762,"corporation":false,"usgs":false,"family":"Thorne","given":"James","email":"","middleInitial":"H.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":955327,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70260977,"text":"70260977 - 2024 - Advancing sustainable groundwater management with a hydro-economic system model: Investigations in the Harney Basin, Oregon","interactions":[],"lastModifiedDate":"2024-11-19T19:40:18.336461","indexId":"70260977","displayToPublicDate":"2024-11-14T13:32:20","publicationYear":"2024","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":"Advancing sustainable groundwater management with a hydro-economic system model: Investigations in the Harney Basin, Oregon","docAbstract":"Groundwater resources frequently trend toward unsustainable levels because, absent effective institutions, individual water users generally act independently without considering the impacts on other users. Hydro-economic models (HEMs) of human-natural systems can play a positive role toward successful groundwater management by yielding valuable knowledge and insight. The current study explores how an HEM that captures essential physical and economic characteristics of a system can shed light on the system's processes and dynamics to benefit stakeholders, managers, and also researchers. These propositions are illustrated using the Harney Basin, Oregon, which has seen large groundwater declines in the past 20 years. The HEM shows that: (a) although current groundwater pumping rates will gradually raise costs and reduce well yields, irrigators gain the highest aggregate economic return by continuing current pumping; (b) lowland areas of the basin are hydrologically connected, which limits the efficacy of remedies focused on regulations only in some portions of the basin; (c) community expectations regarding the efficacy of several proposed solutions are overly optimistic; and (d) the study's scenarios identify interventions that would stabilize the groundwater system and prevent additional adverse impacts on residential and livestock wells and groundwater-dependent ecosystems. These interventions would require limiting groundwater pumping by nearly half and reducing annual profits by $7.5–$9.0M. The HEM also demonstrated its value to researchers: its insights shifted attention toward questions about Oregon's existing groundwater institutions and their inability to adaptively manage the transition from abundant groundwater to scarce groundwater in a timely manner.","language":"English","publisher":"Wiley","doi":"10.1029/2023WR036972","usgsCitation":"Jaeger, W.K., Antle, J.M., Gingerich, S.B., and Bigelow, D., 2024, Advancing sustainable groundwater management with a hydro-economic system model: Investigations in the Harney Basin, Oregon: Water Resources Research, v. 60, e2023WR036972, 26 p., https://doi.org/10.1029/2023WR036972.","productDescription":"e2023WR036972, 26 p.","ipdsId":"IP-159409","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":466765,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr036972","text":"Publisher Index Page"},{"id":464300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","county":"Harney","otherGeospatial":"Harney Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.44430319880412,\n 44.965776942074626\n ],\n [\n -121.44430319880412,\n 42.262073209475204\n ],\n [\n -117.31344382380401,\n 42.262073209475204\n ],\n [\n -117.31344382380401,\n 44.965776942074626\n ],\n [\n -121.44430319880412,\n 44.965776942074626\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","noUsgsAuthors":false,"publicationDate":"2024-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Jaeger, William K.","contributorId":338398,"corporation":false,"usgs":false,"family":"Jaeger","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":918781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Antle, John M.","contributorId":197804,"corporation":false,"usgs":false,"family":"Antle","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":918782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gingerich, Stephen B. 0000-0002-4381-0746 sbginger@usgs.gov","orcid":"https://orcid.org/0000-0002-4381-0746","contributorId":1426,"corporation":false,"usgs":true,"family":"Gingerich","given":"Stephen","email":"sbginger@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bigelow, Daniel 0000-0002-1154-2302","orcid":"https://orcid.org/0000-0002-1154-2302","contributorId":346353,"corporation":false,"usgs":false,"family":"Bigelow","given":"Daniel","email":"","affiliations":[{"id":82838,"text":"Oregon State University Applied Economics Department","active":true,"usgs":false}],"preferred":false,"id":918784,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262249,"text":"70262249 - 2024 - A synthesis of the characteristics and drivers of introduced fishes in prairie streams: Can we manage introduced harmful fishes in these dynamic environments?","interactions":[],"lastModifiedDate":"2025-01-17T16:45:52.438011","indexId":"70262249","displayToPublicDate":"2024-11-14T09:36:50","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"A synthesis of the characteristics and drivers of introduced fishes in prairie streams: Can we manage introduced harmful fishes in these dynamic environments?","docAbstract":"Prairie streams of North America support native fishes that are adapted to the dynamic environment that characterizes these ecologically and economically important ecosystems. However, prairie streams have been altered by landscape changes that may affect the proportions of native and introduced species in fish communities. Herein, we investigate drivers of introduced fish in prairie streams, detail common introduced species and their traits and effects, investigate how climate change may alter the balance between native and introduced species, and summarize management options. Commonly introduced fishes are those with the ability to tolerate extreme variations in temperature, hydrology, and salinity and, as a result, most of the introduced fishes were native to other prairie streams within the Great Plains ecoregion. This suggests environmental extremes may act as a filter for establishment or that short-distance translocations are more common than introductions from other ecoregions. The mechanisms or extent to which introduced species affect native fishes is often assumed or understudied. Climate change may amplify environmental disturbances in ways that may favor native or introduced fishes depending on species traits and biotic interactions. Actions such as habitat modifications or disturbances may favor introduced fishes over native fishes. Research to understand the relative roles of trait preadaptation and spatial proximity of source populations in introduced species establishment could benefit future management. Moreover, patterns observed in other ecosystems may not be transferrable to prairie streams, highlighting the need to understand the context dependency of effects of introduced species.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10530-024-03450-y","usgsCitation":"Coulter, A., Moore, M.J., Golcher-Benavides, J., Rahel, F.J., Walters, A.W., Brewer, S., and Wildhaber, M.L., 2024, A synthesis of the characteristics and drivers of introduced fishes in prairie streams: Can we manage introduced harmful fishes in these dynamic environments?: Biological Invasions, v. 26, p. 4011-4033, https://doi.org/10.1007/s10530-024-03450-y.","productDescription":"23 p.","startPage":"4011","endPage":"4033","ipdsId":"IP-160187","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-024-03450-y","text":"Publisher Index Page"},{"id":480749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"North American Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.30865918818435,\n 51.00019043175968\n ],\n [\n -108.8244372572745,\n 47.17125929409586\n ],\n [\n -106.13072410712726,\n 42.33953855703288\n ],\n [\n -104.22086600055933,\n 40.10613156257109\n ],\n [\n -104.39837770581909,\n 36.40878493463546\n ],\n [\n -104.26570852411,\n 33.836825487233355\n ],\n [\n -102.59989428051855,\n 31.991484684655916\n ],\n [\n -98.85669537584786,\n 31.98987602981056\n ],\n [\n -94.06006847133565,\n 38.705570253107695\n ],\n [\n -94.4212804260574,\n 43.37128007692609\n ],\n [\n -96.14739688752542,\n 48.2616932328075\n ],\n [\n -96.41979434976253,\n 50.75373398643449\n ],\n [\n -96.92898991711421,\n 51.5227386971378\n ],\n [\n -99.57727818526257,\n 52.66077258131\n ],\n [\n -107.3372532002433,\n 51.958499229615185\n ],\n [\n -111.30865918818435,\n 51.00019043175968\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","noUsgsAuthors":false,"publicationDate":"2024-11-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Coulter, A. 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A.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":923644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":923645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golcher-Benavides, Jimena","contributorId":348598,"corporation":false,"usgs":false,"family":"Golcher-Benavides","given":"Jimena","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":923646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rahel, Frank J.","contributorId":171824,"corporation":false,"usgs":false,"family":"Rahel","given":"Frank","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":923647,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":923648,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brewer, Shannon K. 0000-0002-1537-3921","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":340552,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":923649,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":923650,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70260228,"text":"sir20245088 - 2024 - Inset groundwater-flow models for the Cache and Grand Prairie Critical Groundwater Areas, northeastern Arkansas","interactions":[],"lastModifiedDate":"2025-12-22T21:29:22.991335","indexId":"sir20245088","displayToPublicDate":"2024-11-08T12:11:54","publicationYear":"2024","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":"2024-5088","displayTitle":"Inset Groundwater-Flow Models for the Cache and Grand Prairie Critical Groundwater Areas, Northeastern Arkansas","title":"Inset groundwater-flow models for the Cache and Grand Prairie Critical Groundwater Areas, northeastern Arkansas","docAbstract":"The water resources in the Mississippi alluvial plain, located in parts of Missouri, Kentucky, Tennessee, Mississippi, Louisiana, and Arkansas, supports a multibillion-dollar agricultural industry that relies heavily on pumping of groundwater for irrigation of crops and aquaculture. The primary source of groundwater for agricultural-related pumping is the Mississippi River Valley alluvial aquifer, which has declined in storage for decades; secondary groundwater sources include the middle Claiborne aquifer and Wilcox aquifer system. Two areas in northeastern Arkansas that lie within the Mississippi alluvial plain, part of the Cache and Grand Prairie regions, have been designated as Critical Groundwater Areas owing to decades of groundwater declines that resulted from past and current water use. The multidisciplinary Mississippi Alluvial Plain project, led by the U.S. Geological Survey, and funded by their Water Availability and Use Science Program, included objectives to develop numerical groundwater models in focus regions, including the part of the Cache and Grand Prairie regions of northeastern Arkansas. Two inset models were developed using the child model capabilities of MODFLOW 6, the U.S. Geological Survey’s Modular Hydrologic Model simulation software. Both models, called the Cache model and Grand Prairie model, simulated the groundwater system and surface-water/groundwater interactions for the Mississippi River Valley alluvial aquifer and underlying Tertiary-age aquifers and confining units to the Midway confining unit. Each model was spatially discretized into 500-meter x 500-meter orthogonal cells on a grid with 5-meter constant-thickness vertical layers that represented the Mississippi River Valley alluvial aquifer and increasing thickness layers for the aquifers and confining units below the alluvial aquifer. The Cache and Grand Prairie models were calibrated with the PEST++ iterative ensemble smoother Version 5 and employed high dimensional parameterization schemes of 13,740 and 30,436 parameters, respectively. The Cache mean absolute residual for groundwater-level observations within each model domain for the priority well was 1.58 meters. Grand Prairie mean absolute residuals for the alluvial aquifer and middle Claiborne aquifer groundwater-level observations were 2.71 and 10.78 meters, respectively. The groundwater budgets for the Cache and Grand Prairie models were characterized by substantial outflows to irrigation wells, which constituted about 52 and 54 percent of all outflows, with the primary source of water to those wells being releases from unconfined aquifer storage.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245088","programNote":"Water Availability and Use Science Program","usgsCitation":"Traylor, J.P., Duncan, L.L., Leaf, A.T., Weisser, A.R., Dietsch, B.J., and Guira, M., 2024, Inset groundwater-flow models for the Cache and Grand Prairie Critical Groundwater Areas, northeastern Arkansas: U.S. Geological Survey Scientific Investigations Report 2024–5088, 152 p., https://doi.org/10.3133/sir20245088.","productDescription":"Report: xi, 152 p.; 13 Figures: 8.50 x 11.00 inches; Data Release; Dataset","numberOfPages":"168","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-155030","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497914,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117774.htm","linkFileType":{"id":5,"text":"html"}},{"id":463425,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HZWI8S","text":"USGS data release","linkHelpText":"Simulations of the groundwater-flow system in the Cache and Grand Prairie Critical Groundwater Areas, northeastern Arkansas"},{"id":463426,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245088/full"},{"id":463424,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":463419,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5088/coverthb.jpg"},{"id":463422,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5088/images/"},{"id":463420,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5088/sir20245088.pdf","text":"Report","size":"22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5088"},{"id":463421,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5088/sir20245088.XML"},{"id":463423,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2024/5088/downloads/","text":"Layered figures","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arkansas","otherGeospatial":"Cache and Grand Prairie Critical Groundwater Areas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.4216070279204,\n 35.763468234275166\n ],\n [\n -92.62077527136867,\n 35.763468234275166\n ],\n [\n -92.62077527136867,\n 33.579387250010626\n ],\n [\n -90.4216070279204,\n 33.579387250010626\n ],\n [\n -90.4216070279204,\n 35.763468234275166\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
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Hydrologic connectivity, the network of water pathways linking aquatic habitats, is vital for the exchange of organisms and abiotic materials between rivers and adjacent waterbodies. This study quantified hydrologic connectivity for 1,283 lakes in the Lower Mississippi River floodplain using satellite imagery, streamgauge data, and geospatial information. We aimed to assess connection frequency patterns between lakes and streams. Eight metrics describing temporal aspects of hydrologic connectivity were estimated, identifying trends by lake features and by stream size. Each lake exhibited a distinct pattern of connection, with specific months of connectivity followed by disconnection, likely influenced by lake characteristics and seasonal precipitation. Larger lakes showed increased connectivity, likely due to their surface area and volume, while smaller lakes were more prone to isolation, especially during dry periods. Lakes connected to large streams exhibited more prolonged and recurring connections, with less seasonal variation. In contrast, lakes near agricultural areas experienced reduced connectivity. However, local factors such as levees and artificial channels often disrupted these general trends. This hydrologic connectivity analysis can provide insight to support floodplain management, facilitate development of frameworks that restore connectivity, promote preservation of ecological integrity, and support management of invasive species spread in agricultural floodplains.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2024.112808","usgsCitation":"Ahmad, H., Miranda, L.E., Dunn, C.G., Boudreau, M., and Colvin, M.E., 2024, Connectivity patterns between floodplain lakes and neighboring streams in the historical floodplain of the Lower Mississippi River: Ecological Indicators, v. 169, 112808, 12 p., https://doi.org/10.1016/j.ecolind.2024.112808.","productDescription":"112808, 12 p.","ipdsId":"IP-168197","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490657,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2024.112808","text":"Publisher Index Page"},{"id":490406,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1QIH9NJ","text":"USGS data release","linkHelpText":"Code for Connectivity patterns between floodplain lakes and neighboring streams in the historical floodplain of the Lower Mississippi River"},{"id":489294,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lower Mississippi River floodplain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.30878420635052,\n 38.86158462464857\n ],\n [\n -92.32018351048195,\n 38.86158462464857\n ],\n [\n -92.32018351048195,\n 28.20085112656909\n ],\n [\n -88.30878420635052,\n 28.20085112656909\n ],\n [\n -88.30878420635052,\n 38.86158462464857\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"169","noUsgsAuthors":false,"publicationDate":"2024-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Ahmad, Hafez","contributorId":353774,"corporation":false,"usgs":false,"family":"Ahmad","given":"Hafez","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":938775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":938776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":938777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boudreau, Melanie R.","contributorId":353778,"corporation":false,"usgs":false,"family":"Boudreau","given":"Melanie R.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":938778,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":331490,"corporation":false,"usgs":true,"family":"Colvin","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":938779,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260707,"text":"sir20235064I - 2024 - Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020","interactions":[{"subject":{"id":70260707,"text":"sir20235064I - 2024 - Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020","indexId":"sir20235064I","publicationYear":"2024","noYear":false,"chapter":"I","displayTitle":"Peak Streamflow Trends in South Dakota and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020"},"predicate":"IS_PART_OF","object":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"id":1}],"isPartOf":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"lastModifiedDate":"2025-12-22T21:31:08.991933","indexId":"sir20235064I","displayToPublicDate":"2024-11-08T10:53:13","publicationYear":"2024","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":"2023-5064","chapter":"I","displayTitle":"Peak Streamflow Trends in South Dakota and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020","docAbstract":"Peak-flow (flood) frequency analysis is essential to water-resources management applications, including the design of critical infrastructure such as bridges and culverts, and floodplain mapping. Federal guidelines for performing peak-flow flood frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C, which documents the guidelines for determining annual peak streamflow frequency, is that, for basins without major hydrologic alterations (for example, regulation, diversion, and urbanization), statistical properties of the distribution of annual peak streamflows are stationary; that is, the mean, variance, and skew are constant through time. Nonstationarity is a statistical property of a peak-flow series such that the long-term (on the order of decades) distributional properties change one or more times either gradually or abruptly through time. Individual nonstationarities may be attributed to one source such as flow regulation, land-use change, or climate but are often the result of a combination of sources, making detection and attribution of nonstationarities challenging.
In response to a growing concern regarding nonstationarity in peak streamflows in the region, the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, assessed the potential nonstationarity in peak streamflows in the north-central United States. This chapter characterizes the effects of natural hydroclimatic shifts and potential climate change on annual peak streamflows in the State of South Dakota. Annual peak and daily streamflow as well as model-simulated gridded climatic data were examined for temporal monotonic trends, change points, and other statistical properties indicative of changing climatic and environmental conditions.
Changes in annual peak and daily flows were evaluated among 13, 35, and 81 qualifying U.S. Geological Survey streamgages for the 75-, 50-, and 30-year trend periods through water year 2020 (the period from October 1, 2019, to September 30, 2020) in South Dakota, respectively. No qualifying streamgages were in the 100-year trend period in the State. Statistical tests for autocorrelation (independent and identically distributed assumption), monotonic trends, and change points in the median and scale are analyzed to evaluate potential stationarity violations (nonstationarity) for performing at-site peak-flow flood-frequency analysis. The trends are reported using a likelihood approach as an alternative to simply reporting significant trends with an arbitrary p-value cutoff point.
A distinct east-west spatial pattern of likely upward and downward monotonic trends and change points, respectively, was detected in 75- and 50-year trend periods, but an inconsistent spatial pattern was detected in the 30-year trend period. Additionally, change points in the median annual peak streamflows were detected in the late 1970s and early 1980s in the western part of the State, but in the east, the change point was more commonly detected in 1992–93. A similar east-west spatial pattern of likely upward and downward trends was detected in the annual peak-flow timing, the day of the year of the annal peak streamflow. In the western part of the State, the annual peak streamflows are arriving earlier, but in the east, the annual peak streamflows are arriving later. A peaks-over-threshold (POT) analysis where, on average, there are two events per year (POT2) and four events per year (POT4) was also used to evaluate changes in the frequency (count) of daily streamflows exceeding the threshold. Similar to detected changes in the annual peak streamflow, an east-west likely upward or downward change corresponding to an increase or decrease, respectively, in the frequency of daily streamflow greater than a POT2 and POT4 threshold was detected.
A monthly water-balance model was used to evaluate hydroclimatic variation in annual and seasonal precipitation, snowfall, potential evapotranspiration, and soil moisture storage for all qualifying streamgages in the 75-, 50-, and 30-year trend periods. Detected trends in the annual hydroclimatic metrics for the 75- and 50-year trend periods indicate a spatially consistent statewide increase in precipitation, decrease in snowfall, increase in potential evapotranspiration, and increase in soil moisture storage. Furthermore, detected trends in seasonal precipitation in the 75- and 50-year trend periods highlight a pronounced change in precipitation in winter and later into the summer season, especially in the 50-year trend period in the eastern part of the State. Statewide increases in seasonal soil moisture storage were also detected, highlighting year-round increasing flood magnitudes, particularly in the eastern part of the State.
Based on the results of these stationarity tests for the qualifying streamgages in South Dakota among the 75-, 50-, and 30-year trend periods, consistent temporal and spatial patterns of nonstationarity were detected among the 75- and 50-year trend periods. Furthermore, when nonstationarity is detected in daily streamflow, increased streamflow and volume (increasing frequency in POT), as well as potentially bridge scour, may have implications on culvert and highway design in the eastern part of South Dakota. Thus, when performing at-site peak-flow flood-frequency analyses in South Dakota, potential nonstationarities and alternative approaches are important considerations.
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U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
The production and uptake of toxic methylmercury (MeHg) impacts aquatic ecosystems globally. Rivers can be dynamic and difficult systems to study for MeHg production and bioaccumulation, hence identifying sources of MeHg to these systems is both challenging and important for resource management within rivers and main-stem reservoirs. Riparian zones, which are known biogeochemical hotspots for MeHg production, are understudied as potential sources of MeHg to rivers. Here, we present a comprehensive quantification of the hydrologic and biogeochemical processes governing MeHg concentrations, loads, and bioaccumulation at 16 locations along 164 km of the agriculturally intensive Snake River (Idaho, Oregon USA) during summer baseflow conditions, with emphasis on riparian production of MeHg. Approximately one-third of the MeHg load of the Snake River could not be attributed to inflowing waters (upgradient, tributaries, or irrigation drains). Across the study reach, increases in MeHg loads in surface waters were significantly correlated with MeHg concentrations in riparian porewaters, suggesting riparian zones were likely an important source of MeHg to the Snake River. Across all locations, MeHg concentrations in surface waters positively correlated with MeHg concentrations in benthic snails and clams, supporting that riparian produced MeHg was assimilated into local aquatic food webs. This study contributes new insights into riparian MeHg production within rivers which can inform mitigation efforts to reduce MeHg bioaccumulation in fish.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.4c08585","usgsCitation":"Krause, V., Baldwin, A.K., Peterson, B.D., Krabbenhoft, D.P., Janssen, S., Willacker, J., Eagles-Smith, C., and Poulin, B., 2024, Riparian methylmercury production increases riverine mercury flux and food web concentrations: Environmental Science & Technology, v. 58, no. 46, p. 20490-20501, https://doi.org/10.1021/acs.est.4c08585.","productDescription":"12 p.","startPage":"20490","endPage":"20501","ipdsId":"IP-168495","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":463875,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466774,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.4c08585","text":"Publisher Index Page"}],"country":"United States","state":"Idaho, Oregon","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.76519965515584,\n 44.99304074681157\n ],\n [\n -117.75863076747619,\n 42.94336107731144\n ],\n [\n -116.17776769472738,\n 42.9364463608284\n ],\n [\n -116.25927931073849,\n 44.985691191051046\n ],\n [\n -117.76519965515584,\n 44.99304074681157\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","issue":"46","noUsgsAuthors":false,"publicationDate":"2024-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Krause, Virginia","contributorId":346163,"corporation":false,"usgs":false,"family":"Krause","given":"Virginia","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":918280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Benjamin D.","contributorId":328487,"corporation":false,"usgs":false,"family":"Peterson","given":"Benjamin","email":"","middleInitial":"D.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":918282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - 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2024 - Upper Mississippi River System hydrogeomorphic change conceptual model and hierarchical classification","interactions":[],"lastModifiedDate":"2025-12-22T21:33:00.464442","indexId":"ofr20241051","displayToPublicDate":"2024-11-07T14:56:42","publicationYear":"2024","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":"2024-1051","displayTitle":"Upper Mississippi River System Hydrogeomorphic Change Conceptual Model and Hierarchical Classification","title":"Upper Mississippi River System hydrogeomorphic change conceptual model and hierarchical classification","docAbstract":"Understanding the geomorphic processes and causes for long-term hydrogeomorphic changes along the Upper Mississippi River System (UMRS) is necessary for scientific studies ranging from habitat needs assessments, sediment transport, and nutrient processing, and making sound management decisions and prioritizing ecological restoration activities. From 2018 through 2020 the U.S. Geological Survey and U.S. Army Corps of Engineers led a series of calls and meetings, and a workshop to develop a draft UMRS hydrogeomorphic change conceptual model and hierarchical classification scheme. This project was funded through an Upper Mississippi River Restoration 2018 science in support of restoration proposal entitled, “Conceptual Model and Hierarchical Classification of Hydrogeomorphic Settings in the Upper Mississippi River System.” This report documents the background leading up to and the major findings from the workshop. The resulting conceptual model focuses on the drivers and boundary conditions that affect the major hydrogeomorphic processes along the valley corridor using a continuum of spatial and temporal scales and resolutions. The draft hierarchical classification was based on three existing and three new nested geospatial datasets that ultimately can be used to characterize hydrogeomorphic settings that span the UMRS valley corridor. The conceptual model and hierarchical classification will help characterize recent (mid-1990s through mid-2010s) decadal-scale processes and sources for potential hydrogeomorphic change that span a range of spatial scales from watershed hydrology and sediment sources to channel hydraulics and sediment transport.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241051","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Fitzpatrick, F.A., Rogala, J.T., Hendrickson, J.S., Sawyer, L., Stone, J., Erwin, S., Brauer, E.J., and Vaughan, A.A., 2024, Upper Mississippi River System hydrogeomorphic change conceptual model and hierarchical classification: U.S. Geological Survey Open-File Report 2024–1051, 24 p., https://doi.org/10.3133/ofr20241051.","productDescription":"vi, 24 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154820","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":463608,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1051/ofr20241051.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1051"},{"id":463607,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1051/coverthb.jpg"},{"id":463611,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241051/full"},{"id":463609,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1051/ofr20241051.XML"},{"id":463610,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1051/images/"},{"id":497918,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117772.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois, Indiana, Iowa, Minnesota, Missouri, South Dakota, Wisconsin","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.50342683246095,\n 40.74721296729754\n ],\n [\n -86.22485822523954,\n 41.12212957640983\n ],\n [\n -86.47633619015835,\n 41.49085772032035\n ],\n [\n -87.70997806528162,\n 41.54161184649007\n ],\n [\n -87.96780499446993,\n 42.13710516972478\n ],\n [\n -88.45256695171824,\n 43.2601947483673\n ],\n [\n -88.90796053029793,\n 43.953704040844826\n ],\n [\n -89.31966888436784,\n 43.88619768580165\n ],\n [\n -88.82098034404291,\n 45.84620970391856\n ],\n [\n -89.77751644898966,\n 46.14284357021026\n ],\n [\n -92.3836871160787,\n 46.36717699384113\n ],\n [\n -93.57654031001726,\n 47.5843117955113\n ],\n [\n -96.69363739805445,\n 47.520997934475815\n ],\n [\n -96.5298693029927,\n 46.26717241479707\n ],\n [\n -97.88294379082475,\n 46.288663271101996\n ],\n [\n -96.96809715353103,\n 45.32804185048016\n ],\n [\n -95.79932895452089,\n 43.51835880034011\n ],\n [\n -93.73471399415848,\n 39.80187490699902\n ],\n [\n -90.99752932951242,\n 36.93622008574626\n ],\n [\n -89.6631770431625,\n 36.64968232220457\n ],\n [\n -89.28540446277691,\n 37.166100746132656\n ],\n [\n -87.50342683246095,\n 40.74721296729754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"VegDischarge v1 is a comprehensive river discharge across Africa (2000–2021), produced by coupling the agro-hydrologic VegET model and the mizuRoute routing framework. Using remote sensing data and hydrological modeling, the 1-km runoff field simulated by VegET, and routed with mizuRoute, covers over 64,000 river segments in Africa. The VegET model simulates runoff based on vegetation and soil moisture dynamics, while mizuRoute processes this runoff through a detailed river network. Performance metrics show strong model reliability, with R² ranging from 0.5 to 0.9, NSE between 0.6 and 0.9, and KGE from 0.5 to 0.8. The total annual average discharge for Africa is quantified at 3238.1 km³.year-1, with contributions to various oceanic basins: 989.9 km³.year-1 to the North Atlantic, primarily from West African rivers like the Senegal, Gambia, Volta, and Niger; 1313.7 km³.year-1 to the South Atlantic, largely from the Congo River; 212.5 km³.year-1 to the Mediterranean Sea, predominantly from the Nile River; and 722.0 km³.year-1 to the Indian Ocean, with substantial inputs from rivers such as the Zambezi. This VegDischarge v1 is valuable for policymakers, stakeholders, and researchers to better understand water availability, its temporal and spatial variations, that impact water-related infrastructure planning, sustainable resource allocation, and the development of climate resilience mitigation strategies.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41597-024-04034-0","usgsCitation":"Akpoti, K., Velpuri, N., Mizukami, N., Kagone, S., Leh, M., Mekonnen, K., Owusu, A., Tinonetsana, P., Phiri, M., Madushanka, L., Perera, T., Prabhath, P.T., Parrish, G.E., Senay, G.B., and Seid, A., 2024, Advancing water security in Africa with new high-resolution discharge data: Scientific Data, v. 11, 1195, 23 p., https://doi.org/10.1038/s41597-024-04034-0.","productDescription":"1195, 23 p.","ipdsId":"IP-163078","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":466784,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-024-04034-0","text":"Publisher Index Page"},{"id":464460,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": 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Inc., Contractor to the USGS EROS Center","active":true,"usgs":false}],"preferred":false,"id":919338,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":919339,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Seid, Abdulkarim","contributorId":335567,"corporation":false,"usgs":false,"family":"Seid","given":"Abdulkarim","email":"","affiliations":[{"id":80437,"text":"IWMI","active":true,"usgs":false}],"preferred":false,"id":919340,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70260475,"text":"70260475 - 2024 - Benthic community metrics track hydrologically stressed mangrove systems","interactions":[],"lastModifiedDate":"2024-11-04T17:40:22.765316","indexId":"70260475","displayToPublicDate":"2024-10-25T11:33:28","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Benthic community metrics track hydrologically stressed mangrove systems","docAbstract":"Mangrove restoration efforts have increased in order to help combat their decline globally. While restoration efforts often focus on planting seedlings, underlying chronic issues, including disrupted hydrological regimes, can hinder restoration success. While improving hydrology may be more cost-effective and have higher success rates than planting seedlings alone, hydrological restoration success in this form is poorly understood. Restoration assessments can employ a functional equivalency approach, comparing restoration areas over time with natural, reference forests in order to quantify the relative effectiveness of different restoration approaches. Here, we employ the use of baseline community ecology metrics along with stable isotopes to track changes in the community and trophic structure and enable time estimates for establishing mangrove functional equivalency. We examined a mangrove system impacted by road construction and recently targeted for hydrological restoration within the Rookery Bay National Estuarine Research Reserve, Florida, USA. Samples were collected along a gradient of degradation, from a heavily degraded zone, with mostly dead trees, to a transition zone, with a high number of saplings, to a full canopy zone, with mature trees, and into a reference zone with dense, mature mangrove trees. The transition, full canopy, and reference zones were dominated by annelids, gastropods, isopods, and fiddler crabs. Diversity was lower in the dead zone; these taxa were enriched in 13C relative to those found in all the other zones, indicating a shift in the dominant carbon source from mangrove detritus (reference zone) to algae (dead zone). Community-wide isotope niche metrics also distinguished zones, likely reflecting dominant primary food resources (baseline organic matter) present. Our results suggest that stable isotope niche metrics provide a useful tool for tracking mangrove degradation gradients. These baseline data provide critical information on the ecosystem functioning in mangrove habitats following hydrological restoration.
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In this Review, we discuss changes in urban hydrology and approaches to stormwater management. Roughly 90% of rainfall on impervious surfaces and drainage infrastructure becomes run-off, enhancing rainfall export away from cities and leading to local water scarcity and downstream flooding and pollution. Projected increases in urban populations (68% in cities by 2050) and rainfall intensity (~12% in the 10-year and 50-year recurrence interval intensity, under 1.5 °C warming) will exacerbate these issues. Transforming stormwater systems is thus urgently needed, to mitigate flood risk and also to address community desires for environmental protection and enhanced water security. Opportunities include rain gardens and other nature-based stormwater control measures (which restore natural flows and offer other ecosystem services), smart sensor monitoring networks and real-time management (which sustain natural flow regimes, mitigate flood risk and protect ecosystem services) and stormwater harvesting (to avoid local water scarcity). Community acceptance of stormwater harvesting is as high as 96% and stormwater is a substantial resource, with volumes often exceeding demand in some parts of the world. Delivering additional transformations globally requires research into strategies to incentivize engagement and investment, and policies to guide governance of decentralized networks.
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However, there is little consensus about how to evaluate the performance of these models, especially as hydrologic modeling moves toward larger spatial domains. This paper presents a comprehensive multi-objective approach to systematically evaluating the critical features in streamflow drought simulations performed by two widely used hydrological models. The evaluation approach captures how well a model classifies observed periods of drought and non-drought, quantifies error components during periods of drought, and assesses the models’ simulations of drought severity, duration, and intensity. We apply this approach at 4662 U.S. Geological Survey streamflow gages covering a wide range of hydrologic conditions across the conterminous U.S. from 1985 to 2016 to evaluate streamflow drought using two national-scale hydrologic models: the National Water Model (NWM) and the National Hydrologic Model (NHM); therefore, a benchmark against which to evaluate additional models is provided. Using this approach, we find that generally the NWM better simulates the timing of flows during drought, while the NHM better simulates the magnitude of flows during drought. Both models performed better in wetter eastern regions than in drier western regions. Finally, each model showed increased error when simulating the most severe drought events.
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0000-0003-0962-5130","orcid":"https://orcid.org/0000-0003-0962-5130","contributorId":78634,"corporation":false,"usgs":true,"family":"Hodson","given":"Timothy","email":"","middleInitial":"O.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Over, Thomas M. 0000-0001-8280-4368","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":204650,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918274,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70264051,"text":"70264051 - 2024 - Transfer learning with convolutional neural networks for hydrological streamline delineation","interactions":[],"lastModifiedDate":"2025-03-05T15:33:15.616325","indexId":"70264051","displayToPublicDate":"2024-10-21T08:29:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Transfer learning with convolutional neural networks for hydrological streamline delineation","docAbstract":"Hydrological streamline delineation is critical for effective environmental management, influencing agriculture sustainability, river dynamics, watershed planning, and more. This study develops a novel approach to combining transfer learning with convolutional neural networks that capitalize on image-based pre-trained models to improve the accuracy and transferability of streamline delineation. We evaluate the performance of eleven image-based pre-trained models and a baseline model using datasets from Rowan County, North Carolina, and Covington River, Virginia in the USA. Our results demonstrate that when models are adapted to a new area, the fine-tuned ImageNet pre-trained model exhibits superior predictive accuracy, markedly higher than the models trained from scratch or those only fine-tuned on the same area. Moreover, the pre-trained model achieves better smoothness and connectivity between classified streamline channels. These findings underline the effectiveness of transfer learning in enhancing the delineation of hydrological streamlines across varied geographies, offering a scalable solution for accurate and efficient environmental modelling.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2024.106165","usgsCitation":"Jaroenchai, N., Wang, S., Stanislawski, L., Shavers, E.J., Jiang, Z., Sagan, V., and Usery, E., 2024, Transfer learning with convolutional neural networks for hydrological streamline delineation: Environmental Modelling and Software, v. 181, 106165, 13 p., https://doi.org/10.1016/j.envsoft.2024.106165.","productDescription":"106165, 13 p.","ipdsId":"IP-147899","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":487400,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2024.106165","text":"Publisher Index Page"},{"id":482900,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, 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However, less is understood about how these sources affect downgradient hydrological systems and food webs. Here, we report paired PFAS measurements in water, sediment, and aquatic biota along a hydrological gradient away from source zones contaminated by the use of legacy aqueous film-forming foam (AFFF) manufactured using electrochemical fluorination. Clustering analysis indicates that the PFAS composition characteristic of AFFF is detectable in water and fishes >8 km from the source. Concentrations of 38 targeted PFAS and extractable organofluorine (EOF) decreased in fishes downgradient of the AFFF-contaminated source zones. However, PFAS concentrations remained above consumption limits at all locations within the affected watershed. Perfluoroalkyl sulfonamide precursors accounted for approximately half of targeted PFAS in fish tissues, which explain >90% of EOF across all sampling locations. Suspect screening analyses revealed the presence of a polyfluoroketone pharmaceutical in fish species, and a fluorinated agrochemical in water that likely does not accumulate in biological tissues, suggesting the presence of diffuse sources such as septic system and agrochemical inputs throughout the watershed in addition to AFFF contamination. Based on these results, monitoring programs that consider all hydrologically connected regions within watersheds affected by large PFAS sources would help ensure public health protection.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.4c07016","usgsCitation":"Pickard, H.M., Ruyle, B.J., Haque, F., Logan, J.M., LeBlanc, D.R., Vojta, S., and Sunderland, E.M., 2024, Characterizing the areal extent of PFAS contamination in fish species downgradient of AFFF source zones: Environmental Science & Technology, v. 58, no. 43, p. 19440-19453, https://doi.org/10.1021/acs.est.4c07016.","productDescription":"14 p.","startPage":"19440","endPage":"19453","ipdsId":"IP-168224","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":498694,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11526379","text":"External Repository"},{"id":498583,"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 -70.54,\n 41.71\n ],\n [\n -70.54,\n 41.56\n ],\n [\n -70.44,\n 41.56\n ],\n [\n -70.44,\n 41.71\n ],\n [\n -70.54,\n 41.71\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","issue":"43","noUsgsAuthors":false,"publicationDate":"2024-10-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Pickard, Heidi M.","contributorId":365051,"corporation":false,"usgs":false,"family":"Pickard","given":"Heidi","middleInitial":"M.","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":953641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruyle, Bridger J.","contributorId":365053,"corporation":false,"usgs":false,"family":"Ruyle","given":"Bridger","middleInitial":"J.","affiliations":[{"id":53026,"text":"Carnegie Institute for Science","active":true,"usgs":false}],"preferred":false,"id":953642,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haque, Faiz","contributorId":365056,"corporation":false,"usgs":false,"family":"Haque","given":"Faiz","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":953643,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Logan, John M.","contributorId":365058,"corporation":false,"usgs":false,"family":"Logan","given":"John","middleInitial":"M.","affiliations":[{"id":39892,"text":"Massachusetts Division of Marine Fisheries","active":true,"usgs":false}],"preferred":false,"id":953644,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":953645,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vojta, Simon","contributorId":304335,"corporation":false,"usgs":false,"family":"Vojta","given":"Simon","email":"","affiliations":[{"id":66031,"text":"University of Rhode Island, Narragansett, RI, USA","active":true,"usgs":false}],"preferred":false,"id":953646,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sunderland, Elsie M.","contributorId":365063,"corporation":false,"usgs":false,"family":"Sunderland","given":"Elsie","middleInitial":"M.","affiliations":[{"id":16811,"text":"Harvard University","active":true,"usgs":false}],"preferred":false,"id":953647,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}