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A diverse array of natural and human-engineered systems experience temporally variable inundation whereby they fluctuate between inundated and non-inundated states. Variable inundation spans extreme events to predictable sub-daily cycles. Variably inundated ecosystems (VIEs) include hillslopes, non-perennial streams, wetlands, floodplains, temporary ponds, tidal systems, storm-impacted coastal zones, and human-engineered systems. VIEs are diverse in terms of inundation regimes, water chemistry and flow velocity, soil and sediment properties, vegetation, and many other properties. The spatial and temporal scales of variable inundation are vast, ranging from sub-meter to whole landscapes and from sub-hourly to multi-decadal. The broad range of system types and scales makes it challenging to predict the hydrology, biogeochemistry, ecology, and physical evolution of VIEs. Despite all experiencing the loss and gain of an overlying water column, VIEs are rarely considered together in conceptual, theoretical, modeling, or measurement frameworks and approaches. Studying VIEs together has the potential to generate mechanistic understanding that is transferable across a much broader range of environmental conditions, relative to knowledge generated by studying any one VIE type. We postulate that enhanced transferability will be important for predicting changes in VIE function in response to global change. Here we aim to catalyze cross-VIE science that studies drivers and impacts of variable inundation across Earth's VIEs. To this end, we complement expert mini-reviews of eight major VIE systems with overviews of VIE-relevant methods and challenges associated with scale. We conclude with perspectives on how cross-VIE science can derive transferable understanding via unifying conceptual models in which the impacts of variable inundation are studied across multi-dimensional environmental space.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/bg-22-995-2025","usgsCitation":"Stegen, J., Burgin, A.J., Busch, M., Fisher, J.B., Ladau, J., Abrahamson, J., Kinsman-Costello, L., Li, L., Chen, X., Datry, T., McDowell, N., Tatariw, C., Braswell, A., Deines, J.M., Guimond, J., Regier, P., Rod, K., Bam, E., Fluet-Chouinard, E., Forbrich, I., Jaeger, K.L., O'Meara, T., Scheibe, T.D., Seybold, E., Sweetman, J.N., Zheng, J., Allen, D.C., Herndon, E., Middleton, B., Painter, S., Roche, K., Scamardo, J., Vander Vorste, R., Boye, K., Wohl, E., Zimmer, M., Hondula, K., Laan, M., Marshall, A., and Patel, K., 2025, Reviews and syntheses: Variable inundation across Earth's terrestrial ecosystems: Biogeosciences, v. 22, no. 4, p. 995-1034, https://doi.org/10.5194/bg-22-995-2025.","productDescription":"30 p.","startPage":"995","endPage":"1034","ipdsId":"IP-159303","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488342,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-22-995-2025","text":"Publisher Index Page"},{"id":483581,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Stegen, James","contributorId":242792,"corporation":false,"usgs":false,"family":"Stegen","given":"James","affiliations":[{"id":48525,"text":"Earth and Biological Sciences Division, Pacific Northwest National 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,{"id":70263964,"text":"70263964 - 2025 - Hydroclimate projections and effects on runoff at National Wildlife Refuges in the semi-arid western U.S.","interactions":[],"lastModifiedDate":"2026-02-10T13:52:37.210978","indexId":"70263964","displayToPublicDate":"2025-02-24T09:03:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20192,"text":"JAWRA Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Hydroclimate projections and effects on runoff at National Wildlife Refuges in the semi-arid western U.S.","docAbstract":"<p><span>This study evaluated hydroclimate projections and effects on runoff at National Wildlife Refuges in a semiarid region of the western United States (U.S. Fish and Wildlife Service Region 6) using mean air temperature (TAVE) and precipitation (PPT) inputs and runoff (RO) output from a national application of a Monthly Water Balance Model (MWBM). An ensemble of statistically downscaled global circulation models for two future emissions scenarios from Coupled Model Intercomparison Project 3 and 5 (CMIP3 and 5) were assessed at the refuges for the years 1950–2099. TAVE, PPT, and RO and departures from mean baseline conditions were analyzed from MWBM hydrologic response units within refuge boundaries. Seasonal results were evaluated across four periods: historical (1951–1969), baseline (1981–1999), 2050 (2041–2059), and 2080 (2071–2089). Projected TAVE increases for all refuges and time periods, whereas PPT and RO are much more variable across ecoregions. Using the high emission scenario, summer mean monthly TAVE increases range from 4.8°C to 5.5°C by 2080. Summer mean monthly PPT departures vary from −5.7 to 3.9 mm (up to 14% decrease), with decreases at 41% of refuges. Summer RO departures range from −16.7 to 0.2 mm (up to 60% decrease), with decreases at 71% of refuges. Under the same emission scenario, winter PPT and RO increase at most refuges by 2080. These variable departures will create substantial challenges for future conservation management in the region.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.13251","usgsCitation":"Caruso, B., Eng, L., Bock, A.R., and Hall, N.G., 2025, Hydroclimate projections and effects on runoff at National Wildlife Refuges in the semi-arid western U.S.: JAWRA Journal of the American Water Resources Association, v. 61, no. 1, e13251, https://doi.org/10.1111/1752-1688.13251.","productDescription":"e13251","ipdsId":"IP-159661","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":482792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Caruso, Brian S. 0000-0002-2184-4961","orcid":"https://orcid.org/0000-0002-2184-4961","contributorId":257039,"corporation":false,"usgs":false,"family":"Caruso","given":"Brian S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":929370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eng, Lauren Ellissa 0009-0003-9808-4184","orcid":"https://orcid.org/0009-0003-9808-4184","contributorId":332901,"corporation":false,"usgs":true,"family":"Eng","given":"Lauren Ellissa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929371,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bock, Andrew R. 0000-0001-7222-6613 abock@usgs.gov","orcid":"https://orcid.org/0000-0001-7222-6613","contributorId":4580,"corporation":false,"usgs":true,"family":"Bock","given":"Andrew","email":"abock@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929372,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hall, Nicholas Graff 0000-0002-7331-8947","orcid":"https://orcid.org/0000-0002-7331-8947","contributorId":315497,"corporation":false,"usgs":true,"family":"Hall","given":"Nicholas","email":"","middleInitial":"Graff","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929373,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70264627,"text":"70264627 - 2025 - James Buttle review: The characteristics of baseflow resilience across diverse ecohydrological terrains","interactions":[],"lastModifiedDate":"2025-03-19T13:12:59.597752","indexId":"70264627","displayToPublicDate":"2025-02-23T08:21:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"James Buttle review: The characteristics of baseflow resilience across diverse ecohydrological terrains","docAbstract":"The dynamic storage of aquifers is the portion of groundwater that can potentially drain to any given point along a stream to create baseflow. Baseflow typically occurs year-round in perennial streams, though the characteristics and stability of dynamic storage are often most important to instream processes during extended dry periods (without precipitation and snowmelt) when runoff and quickflows are minimised. The term ‘baseflow resilience’ is defined for this review as the tendency of baseflow in streams to maintain a consistent volume and water quality year to year while under stress from climate variability and extremes, along with anthropogenic stressors such as water withdrawals, land use change, and water quality degradation. ‘Baseflow resilience’ has, in part, a user-defined meaning spanning water supply and water quality variables of primary interest. Watershed characteristics that directly impact resilience can often produce non-intuitive feedbacks that enhance some attributes of baseflow while simultaneously impairing others. For example, permeable stream corridor geology creates strong stream-groundwater hydrologic connectivity, yet fast groundwater drainage via preferential high-permeability flowpaths can lead to streamflow not being sustained during extended dry periods. Also, shallow groundwater sources are generally more immediately vulnerable to extreme events, warming, salinization, transpiration, and precipitation drought, compared to deeper groundwater. Yet baseflow drought in streams influenced by deeper groundwater can lag precipitation drought by years, and contaminant legacies may propagate through deep groundwater flowpaths to receiving waters for decades to centuries. Finally, irrigation withdrawals can intercept groundwater that would have drained to streams, and the application of irrigation may leach contaminants from the soil zone by unnaturally raising water tables, yet irrigation return flows can sustain baseflow and groundwater-dependent habitats in semiarid areas. This review covers the concept of hydrologic resilience in the context of stream baseflow processes and summarises the common hydrogeological controls on, and multiscale stressors of, dynamic groundwater storage. Further, we present several quantitative metrics to assess a range of water supply to water quality baseflow characteristics using both broadly available and boutique data types, a subset of which are demonstrated using data from the Delaware River Basin, USA.","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70101","usgsCitation":"Briggs, M., Newman, C.P., Benton, J., Rey, D., Konrad, C., Ouellet, V., Torgersen, C.E., Gruhn, L.R., Fleming, B.J., Gazoorian, C.L., and Doctor, D.H., 2025, James Buttle review: The characteristics of baseflow resilience across diverse ecohydrological terrains: Hydrological Processes, v. 39, e70101, 21 p., https://doi.org/10.1002/hyp.70101.","productDescription":"e70101, 21 p.","ipdsId":"IP-172740","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":488334,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70101","text":"Publisher Index Page"},{"id":483482,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Delaware, New Jersey, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -75.72740040176602,\n              40.21569215354026\n            ],\n            [\n              -75.72740040176602,\n              39.17926830473752\n            ],\n            [\n              -74.59478267456883,\n              39.17926830473752\n            ],\n            [\n              -74.59478267456883,\n              40.21569215354026\n            ],\n            [\n              -75.72740040176602,\n              40.21569215354026\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"39","noUsgsAuthors":false,"publicationDate":"2025-03-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222759,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":930998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":930999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benton, Joshua Robert 0000-0002-1698-6455","orcid":"https://orcid.org/0000-0002-1698-6455","contributorId":304604,"corporation":false,"usgs":true,"family":"Benton","given":"Joshua Robert","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":931000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rey, David M. 0000-0003-2629-365X","orcid":"https://orcid.org/0000-0003-2629-365X","contributorId":211848,"corporation":false,"usgs":true,"family":"Rey","given":"David M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":931001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Konrad, Christopher 0000-0002-7354-547X","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":220231,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931002,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ouellet, Valerie","contributorId":316799,"corporation":false,"usgs":false,"family":"Ouellet","given":"Valerie","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":931003,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":146935,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":931004,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gruhn, Lance R. 0000-0002-7120-3003 lgruhn@usgs.gov","orcid":"https://orcid.org/0000-0002-7120-3003","contributorId":219710,"corporation":false,"usgs":true,"family":"Gruhn","given":"Lance","email":"lgruhn@usgs.gov","middleInitial":"R.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931005,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931006,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gazoorian, Christopher L. 0000-0002-5408-6212 cgazoori@usgs.gov","orcid":"https://orcid.org/0000-0002-5408-6212","contributorId":2929,"corporation":false,"usgs":true,"family":"Gazoorian","given":"Christopher","email":"cgazoori@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931007,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":931008,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70266342,"text":"70266342 - 2025 - A new groundwater energy transport model for the MODFLOW hydrologic simulator","interactions":[],"lastModifiedDate":"2025-05-05T14:11:27.139592","indexId":"70266342","displayToPublicDate":"2025-02-14T09:08:16","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"A new groundwater energy transport model for the MODFLOW hydrologic simulator","docAbstract":"<p><span>Heat transport in the subsurface is an important aspect of research related to the effects of a warming climate on ecological services (i.e., cold-water refugia); the development of geothermal resources for energy banking schemes (i.e., aquifer thermal energy storage [ATES]); and the effects of temperature on other aspects of groundwater quality, such as nutrient cycling. Historically, simulation of heat transport using the MODFLOW groundwater simulator and related codes was performed by scaling the input parameters of a solute-transport model to emulate heat transport. However, that approach required additional pre- and post-processing of input and output and could not account for the variation in effective thermal storage and transport properties during transient, unsaturated flow, for example. True heat-transport capabilities in the context of MODFLOW were first introduced in a variant called USG-Transport. More recently, a new groundwater energy-transport (GWE) model type has been added to MODFLOW 6, the core version of the MODFLOW hydrologic simulator. GWE supports the simulation of heat transport on structured or unstructured grids as well as within and between features of advanced packages that represent streams, lakes, multi-aquifer wells, and the unsaturated zone. GWE is integrated within MODFLOW 6 and is accessible through the FloPy Python package and the MODFLOW 6 application programming interface (API). An example simulation demonstrates conduction between grid cells through both the water and the solid aquifer material, including thermal bleeding from saturated overburden cells into a groundwater flow field.</span></p>","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.13470","usgsCitation":"Morway, E.D., Provost, A.M., Langevin, C.D., Hughes, J.D., Russcher, M.J., Chen, C., and Lin, Y., 2025, A new groundwater energy transport model for the MODFLOW hydrologic simulator: Groundwater, v. 63, no. 3, p. 409-421, https://doi.org/10.1111/gwat.13470.","productDescription":"13 p.","startPage":"409","endPage":"421","ipdsId":"IP-172581","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":487945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gwat.13470","text":"Publisher Index Page"},{"id":485372,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"63","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":935684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Provost, Alden M. 0000-0002-4443-1107 aprovost@usgs.gov","orcid":"https://orcid.org/0000-0002-4443-1107","contributorId":2830,"corporation":false,"usgs":true,"family":"Provost","given":"Alden","email":"aprovost@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":935685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":935686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":935687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Russcher, Martijn J. 0000-0001-8799-6514","orcid":"https://orcid.org/0000-0001-8799-6514","contributorId":272524,"corporation":false,"usgs":false,"family":"Russcher","given":"Martijn","email":"","middleInitial":"J.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":935688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chen, Chieh-Ying","contributorId":354439,"corporation":false,"usgs":false,"family":"Chen","given":"Chieh-Ying","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":935689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lin, Yu-Feng 0000-0001-6454-0901","orcid":"https://orcid.org/0000-0001-6454-0901","contributorId":302351,"corporation":false,"usgs":false,"family":"Lin","given":"Yu-Feng","email":"","affiliations":[{"id":65462,"text":"Illinois Water Resources Center, University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":935690,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70266054,"text":"70266054 - 2025 - Confluence of time and space: An innovation for quantifying dynamics of hydrologic floodplain connectivity with remote sensing and GIS","interactions":[],"lastModifiedDate":"2025-06-12T15:39:19.215206","indexId":"70266054","displayToPublicDate":"2025-02-06T08:46:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Confluence of time and space: An innovation for quantifying dynamics of hydrologic floodplain connectivity with remote sensing and GIS","docAbstract":"Hydrologic connectivity is a crucial determinant of aquatic ecosystem services, governing the exchange of nutrients, sediments, chemicals, and biota. Various indices and metrics exist for quantifying hydrologic connectivity across diverse environments and scales. However, existing methodologies often fail to adequately capture lateral connectivity between floodplain lakes and streams across vast, low-relief, multi-lake floodplain systems. This study introduces a novel approach for quantifying lateral hydrologic connectivity specifically tailored for floodplain lakes connecting to streams within the expansive floodplain of the Lower Mississippi River. This approach centers on the spatial and temporal intersection of lakes and streams, leveraging remote sensing and GIS data to estimate nine distinct metrics of hydrologic connectivity. To assess the reliability of the method, the study estimated connectivity metrics for 92 randomly selected floodplain lakes, comprising 53 lakes connected to large streams (Strahler order >7), 13 lakes connected to medium (order 4-6) streams, and 26 lakes connected to small (order 1-3) streams. As expected, there was significant variability in hydrologic connectivity across different stream size classes. The outlined approach contributes valuable insights into the hydrologic connectivity of floodplain lakes and offers a generalizable framework applicable to other floodplains. Its versatility makes it a practical tool for understanding connectivity requirements for biota and facilitating applications in conservation and water resources management. Thus, this work represents a meaningful step toward advancing our understanding of lateral hydrologic connectivity dynamics in complex aquatic ecosystems.\n ","language":"English","publisher":"Wiley","doi":"10.1002/rra.4426","usgsCitation":"Ahmad, H., Miranda, L.E., Dunn, C.G., Boudreau, M., Colvin, M., and Dash, P., 2025, Confluence of time and space: An innovation for quantifying dynamics of hydrologic floodplain connectivity with remote sensing and GIS: River Research and Applications, v. 41, no. 5, p. 1014-1029, https://doi.org/10.1002/rra.4426.","productDescription":"16 p.","startPage":"1014","endPage":"1029","ipdsId":"IP-166779","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":484990,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee","otherGeospatial":"Lower Mississippi River floodplain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.70569886340942,\n              35.378193533513624\n            ],\n            [\n              -91.48523796505039,\n              33.22134089549405\n            ],\n            [\n              -91.97295509476544,\n              30.945728873306038\n            ],\n            [\n              -91.04203402054121,\n              30.941053928057386\n            ],\n            [\n              -90.92591403794623,\n              31.351716726235846\n            ],\n            [\n              -90.60384187137875,\n              33.59410666110667\n            ],\n            [\n              -89.14760247281004,\n              36.80807080526803\n            ],\n            [\n              -90.70569886340942,\n              35.378193533513624\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"41","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-02-06","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":934467,"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":934468,"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":934469,"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":934470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colvin, Michael E.","contributorId":264842,"corporation":false,"usgs":false,"family":"Colvin","given":"Michael E.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":934471,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dash, Padmanava 0000-0003-3851-6830","orcid":"https://orcid.org/0000-0003-3851-6830","contributorId":297903,"corporation":false,"usgs":false,"family":"Dash","given":"Padmanava","email":"","affiliations":[{"id":64445,"text":"Department of Geosciences, Mississippi State University, Mississippi State, MS, US","active":true,"usgs":false}],"preferred":false,"id":934472,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70267521,"text":"70267521 - 2025 - Preprint: Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020","interactions":[],"lastModifiedDate":"2025-05-28T13:51:16.156231","indexId":"70267521","displayToPublicDate":"2025-02-05T08:48:40","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19891,"text":"ESS Open Archive","active":true,"publicationSubtype":{"id":32}},"title":"Preprint: Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020","docAbstract":"<p><span>The U.S. Geological Survey (USGS) and the Washington State Department of Ecology (Ecology) have developed watershed models of seasonal load estimates of total nitrogen (TN) and total phosphorus (TP) discharging into the Washington waters of the Salish Sea from 2005 through 2020. The modeling approach used was dynamic SPARROW (SPAtially Referenced Regressions On Watershed attributes), a statistical-physical watershed modeling technique, initially applied at large spatial scales to represent long-term average stream loads throughout a stream network, refined here to estimate seasonal TN and TP loads across watersheds to clarify upstream contributions from discernable point and nonpoint sources delivered to marine waters at surface water confluences along the shoreline and quantify when, where, and why they were high or low. Upstream contributing sources included permitted treated wastewater facilities, crop fertilizer, animal feeding operations, septic systems, urban land and stormwater, atmospheric deposition (TN only), nitrogen fixation by Red Alder Alnus rubra trees (TN only), and background geologic material (TP only). Instream load magnitudes and their source compositions varied widely across watersheds, and even within each watershed, yet the largest loads typically occurred in the large rivers during winter and fall when streamflow was highest. Likewise, instream loads were typically lowest in summer during low streamflow, yet the relative instream aquatic decay was highest. The seasonal storage lag component of those nonpoint sources was estimated to contribute a quarter of the seasonal instream load during winter and fall high streamflow and sometimes half of the instream load during summer low streamflow. A key aspect of Ecology’s current Puget Sound Nutrient Source Reduction Project is consideration of upstream watershed contributions of nutrients to their marine-water discharge points. Simulated seasonal loads carried by streams to 63 river mouth marine discharge points 9 ranged by several orders-of-magnitude for both TN and TP due to the spatial and seasonal differences in hydrologic flows, magnitude and timing of contributing sources, and in-stream decay. The Snohomish and Skagit Rivers discharged the largest TN and TP loads, yet the Samish River was shown to have some of the highest TN and TP yields and concentrations. Additionally, a reference scenario was developed to provide an estimate of the pre-industrial local and regional loads.</span></p>","language":"English","publisher":"ESS Open Archive","doi":"10.22541/essoar.173878059.92247480/v1","usgsCitation":"Schmadel, N., Figueroa-Kaminsky, C., Wise, D., Wasielewski, J., Johnson, Z., and Black, R.W., 2025, Preprint: Simulated seasonal loads of total nitrogen and total phosphorus by major source from watersheds draining to Washington waters of the Salish Sea, 2005 through 2020: ESS Open Archive, preprint posted February 05, 2025, https://doi.org/10.22541/essoar.173878059.92247480/v1.","productDescription":"110 p.","ipdsId":"IP-174989","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":486634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmadel, Noah 0000-0002-2046-1694","orcid":"https://orcid.org/0000-0002-2046-1694","contributorId":219105,"corporation":false,"usgs":true,"family":"Schmadel","given":"Noah","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":938477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Figueroa-Kaminsky, Cristiana","contributorId":350514,"corporation":false,"usgs":false,"family":"Figueroa-Kaminsky","given":"Cristiana","affiliations":[{"id":25353,"text":"Washington State Department of Ecology","active":true,"usgs":false}],"preferred":false,"id":938478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wise, Daniel 0000-0002-1215-9612","orcid":"https://orcid.org/0000-0002-1215-9612","contributorId":217259,"corporation":false,"usgs":true,"family":"Wise","given":"Daniel","email":"","affiliations":[],"preferred":true,"id":938479,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wasielewski, Jamie K. 0009-0005-7497-3344","orcid":"https://orcid.org/0009-0005-7497-3344","contributorId":344993,"corporation":false,"usgs":false,"family":"Wasielewski","given":"Jamie K.","affiliations":[{"id":82458,"text":"Washington Dept. of Ecology","active":true,"usgs":false}],"preferred":false,"id":938480,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Zachary 0000-0002-0149-5223 zjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-0149-5223","contributorId":190399,"corporation":false,"usgs":true,"family":"Johnson","given":"Zachary","email":"zjohnson@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":938481,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Black, Robert W. 0000-0002-4748-8213 rwblack@usgs.gov","orcid":"https://orcid.org/0000-0002-4748-8213","contributorId":1820,"corporation":false,"usgs":true,"family":"Black","given":"Robert","email":"rwblack@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":938482,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70263305,"text":"70263305 - 2025 - Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed","interactions":[],"lastModifiedDate":"2025-02-11T15:50:56.369579","indexId":"70263305","displayToPublicDate":"2025-02-03T07:53:49","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed","docAbstract":"Concentration-discharge (CQ) relations are commonly used to understand geochemical and hydrologic controls on the generation of solutes in watersheds. Despite the widespread application of CQ relations, this technique has been infrequently applied to acid mine drainage (AMD) sites, but the CQ framework may allow mechanistic understanding of remedial outcomes such as impoundment of water within underground mines. Results of CQ analyses and changes in metal loads in an AMD affected watershed in Colorado, USA indicate that dissolved loads increased at many individual locations following water impoundment within mine workings. Although increased loads were observed at most individual locations, these increases were offset by a large decrease in loading from the largest mine. A loading analysis that included data from an instream monitoring location showed a statistically significant decrease in Fe and Zn after bulkhead emplacement, indicating a net positive effect of bulkheads. Streams generally displayed dilution CQ patterns whereas mines and springs showed either flushing or chemostatic patterns prior to bulkheading, which transitioned to chemostatic patterns following bulkheading, indicating a transition from dynamic to equilibrium geochemical processes. Saturation indices for sulfide and secondary minerals indicated that mines and springs were near equilibrium for phases including schwertmannite, fluorite, and gypsum. Saturation indices vary through time for mines suggesting progressive leaching of sulfide minerals as the mass of available minerals in the mine workings decreases. Together, these diverse analyses provide an integrated understanding of the variability in solute generating processes in this watershed and may inform remediation plans for similarly affected sites by indicating the nature of mineralogic controls on water quality.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jconhyd.2025.104513","usgsCitation":"Newman, C.P., Navarre-Sitchler, A., Runkel, R.L., and Cowie, R.M., 2025, Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed: Journal of Contaminant Hydrology, v. 269, 104513, 19 p., https://doi.org/10.1016/j.jconhyd.2025.104513.","productDescription":"104513, 19 p.","ipdsId":"IP-159009","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":489934,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index 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 \"}}]}","volume":"269","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":926259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Navarre-Sitchler, Alexis","contributorId":190441,"corporation":false,"usgs":false,"family":"Navarre-Sitchler","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":926260,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":926261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cowie, Rory M.","contributorId":270098,"corporation":false,"usgs":false,"family":"Cowie","given":"Rory","email":"","middleInitial":"M.","affiliations":[{"id":56077,"text":"Alpine Water Resources","active":true,"usgs":false}],"preferred":false,"id":926262,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70262805,"text":"70262805 - 2025 - Determining the effects of reduced water availability on seed germination of five bottomland hardwood tree species","interactions":[],"lastModifiedDate":"2025-01-23T16:00:41.372934","indexId":"70262805","displayToPublicDate":"2025-02-01T08:56:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Determining the effects of reduced water availability on seed germination of five bottomland hardwood tree species","docAbstract":"<p><span>Globally, floodplain forests are experiencing shifts in species composition associated with drier conditions and disruptions of flood pulse hydrology. The specific processes behind these shifts in composition are not fully understood, but differential effects of drought on regeneration processes such as seed germination may be partially responsible. To determine how reduced water availability impacts seed germination of different floodplain tree species, a lab-controlled germination experiment was conducted. Seeds from tree species common to floodplain forests of the southeastern and southcentral United States whose abundance have been altered by drier hydrogeomorphic conditions were examined. These seeds included desiccation resistant, or orthodox, seeds of sugarberry (</span><i>Celtis laevigata</i><span>) and green ash (</span><i>Fraxinus pennsylvanica</i><span>), and desiccation sensitive, or recalcitrant, acorns of overcup oak (</span><i>Quercus lyrata</i><span>), water oak (</span><i>Quercus nigra</i><span>), and willow oak (</span><i>Quercus phellos</i><span>). Seeds of each species were incubated with one of eight osmotically adjusted water solutions ranging in water potential from 0.0 MPa to −1.4 MPa. This reduction in water potential decreases the water available to the seeds for germination. After four weeks, seed germination of all species decreased with reduced water potential; however, desiccation tolerance did not correspond with the ability to germinate under lower water potential. Orthodox seeds only germinated in higher water potential treatments. Sugarberry reached 30 % germination in only the control 0.0 MPa treatment while green ash reached 30 % germination in treatments as low as −0.4 MPa. In contrast, recalcitrant acorns continued to germinate under lower water potentials. Water oak maintained 30 % or greater germination under all treatments and willow oak reached 30 % down to −0.8 MPa. Overcup oak was the only species to not respond to water potential treatment. With respect to maximum germination, sugarberry and green ash reached maximum germination an average of 9 days sooner than the oak species. The results of this study agree with others that demonstrate that seed germination success is sensitive to environmental water conditions and that species specific differences in germination traits are linked to broader life history strategies that are adaptive to common environmental conditions in their range.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2024.122410","usgsCitation":"Pell, C., King, S.L., Hawkins, T.S., and Symmank, M., 2025, Determining the effects of reduced water availability on seed germination of five bottomland hardwood tree species: Forest Ecology and Management, v. 577, 122410, 7 p., https://doi.org/10.1016/j.foreco.2024.122410.","productDescription":"122410, 7 p.","ipdsId":"IP-162807","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":480998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"577","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pell, Charles J.","contributorId":349796,"corporation":false,"usgs":false,"family":"Pell","given":"Charles J.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":924825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":924826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawkins, Tracy S.","contributorId":341655,"corporation":false,"usgs":false,"family":"Hawkins","given":"Tracy","email":"","middleInitial":"S.","affiliations":[{"id":81773,"text":"Research Ecologist","active":true,"usgs":false}],"preferred":false,"id":924827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Symmank, Matt","contributorId":349797,"corporation":false,"usgs":false,"family":"Symmank","given":"Matt","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":924828,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70265497,"text":"70265497 - 2025 - Myiasis infection by the toad fly (Lucilia bufonivora; Calliphoidae) in amphibians in Montana, USA","interactions":[],"lastModifiedDate":"2025-04-08T15:30:56.957189","indexId":"70265497","displayToPublicDate":"2025-01-31T08:25:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Myiasis infection by the toad fly (Lucilia bufonivora; Calliphoidae) in amphibians in Montana, USA","docAbstract":"<p><span>Toad flies in the genus&nbsp;</span><i>Lucilia</i><span>&nbsp;(previously referred to as&nbsp;</span><i>Bufolucilia</i><span>&nbsp;spp.) parasitize and cause myiasis in several amphibian species in North America. From 2019 to 2022, we documented&nbsp;</span><i>Lucilia bufonivora</i><span>&nbsp;infections in post-metamorphic western toads&nbsp;</span><i>(Anaxyrus boreas</i><span>) during amphibian surveys in four wetlands in Glacier National Park, Montana, US. We found nine infected adult toads in 2019, seven infected adults in 2020, one infected juvenile in 2021, and five infected adults plus one infected juvenile in 2022. We also captured Columbia spotted frogs (</span><i>Rana luteiventris</i><span>) during these same surveys but detected no infections. Only one of the four wetlands had infected toads in 2019, despite their proximity and hydrologic connectivity, but two of these wetlands had infections in 2020, and a third had a single infection in 2021. The same three of four wetlands had infections in 2022. In 2008, a similar parasitic infection in one western toad had been noted at the same wetland as in 2019. That toad had been captured again two years later without signs of infection.</span></p>","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-24-00066","usgsCitation":"Fischer, L., and Hossack, B., 2025, Myiasis infection by the toad fly (Lucilia bufonivora; Calliphoidae) in amphibians in Montana, USA: Journal of Wildlife Diseases, v. 61, no. 1, p. 206-2011, https://doi.org/10.7589/JWD-D-24-00066.","productDescription":"6 p.","startPage":"206","endPage":"2011","ipdsId":"IP-165212","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":484332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.31542629184875,\n              48.99439796903869\n            ],\n            [\n              -114.31542629184875,\n              48.51117768811824\n            ],\n            [\n              -113.42667525702582,\n              48.51117768811824\n            ],\n            [\n              -113.42667525702582,\n              48.99439796903869\n            ],\n            [\n              -114.31542629184875,\n              48.99439796903869\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"61","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fischer, Leah M.","contributorId":353074,"corporation":false,"usgs":false,"family":"Fischer","given":"Leah M.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":932828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":932829,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70263339,"text":"70263339 - 2025 - Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning","interactions":[],"lastModifiedDate":"2025-02-06T15:53:28.669956","indexId":"70263339","displayToPublicDate":"2025-01-29T09:49:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning","docAbstract":"<p><span>Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km</span><sup>2</sup><span>&nbsp;(0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs17030457","usgsCitation":"Shastry, A.R., Cerovski-Darriau, C., Coltin, B., and Stock, J.D., 2025, Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning: Remote Sensing, v. 17, no. 3, 457, 11 p., https://doi.org/10.3390/rs17030457.","productDescription":"457, 11 p.","ipdsId":"IP-153917","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"links":[{"id":487628,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs17030457","text":"Publisher Index Page"},{"id":481746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.41245311245856,\n              35.20197552578807\n            ],\n            [\n              -117.96299074904582,\n              36.06858120494961\n            ],\n            [\n              -118.86530937366612,\n              37.63884023254646\n            ],\n            [\n              -119.85965473348287,\n              38.80651233617289\n            ],\n            [\n              -120.17114612624695,\n              40.23030133169971\n            ],\n            [\n              -120.73602418336918,\n              40.662012753561754\n            ],\n            [\n              -122.36739903137283,\n              40.400491599532984\n            ],\n            [\n              -120.74692405664294,\n              38.0147515126105\n            ],\n            [\n              -119.36615838296214,\n              35.979191454701876\n            ],\n            [\n              -118.41245311245856,\n              35.20197552578807\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Shastry, Apoorva Ramesh 0000-0002-3996-4857","orcid":"https://orcid.org/0000-0002-3996-4857","contributorId":317867,"corporation":false,"usgs":true,"family":"Shastry","given":"Apoorva","email":"","middleInitial":"Ramesh","affiliations":[{"id":227,"text":"Earth Surface Dynamics Program","active":true,"usgs":true}],"preferred":true,"id":926515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cerovski-Darriau, Corina 0000-0002-0543-0902","orcid":"https://orcid.org/0000-0002-0543-0902","contributorId":221159,"corporation":false,"usgs":true,"family":"Cerovski-Darriau","given":"Corina","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coltin, Brian","contributorId":350636,"corporation":false,"usgs":false,"family":"Coltin","given":"Brian","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":926517,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stock, Jonathan D. 0000-0001-8565-3577 jstock@usgs.gov","orcid":"https://orcid.org/0000-0001-8565-3577","contributorId":3648,"corporation":false,"usgs":true,"family":"Stock","given":"Jonathan","email":"jstock@usgs.gov","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":926518,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70262822,"text":"sir20245105 - 2025 - Groundwater hydrology, groundwater and surface-water interactions, water quality, and groundwater-flow simulations for the Wet Mountain Valley alluvial aquifer, Custer and Fremont Counties, Colorado, 2017–19","interactions":[],"lastModifiedDate":"2025-01-29T14:30:56.495951","indexId":"sir20245105","displayToPublicDate":"2025-01-28T12:40:00","publicationYear":"2025","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":"2024-5105","displayTitle":"Groundwater Hydrology, Groundwater and Surface-Water Interactions, Water Quality, and Groundwater-Flow Simulations for the Wet Mountain Valley Alluvial Aquifer, Custer and Fremont Counties, Colorado, 2017–19","title":"Groundwater hydrology, groundwater and surface-water interactions, water quality, and groundwater-flow simulations for the Wet Mountain Valley alluvial aquifer, Custer and Fremont Counties, Colorado, 2017–19","docAbstract":"<p>In 2017, the U.S. Geological Survey, in cooperation with the Upper Arkansas Water Conservancy District, began a study to provide a comprehensive analysis of the Wet Mountain Valley alluvial aquifer, Custer and Fremont Counties, Colorado. The study included collection of data pertaining to groundwater hydrology, groundwater and surface-water interactions, and water quality in the alluvial aquifer. In addition to providing foundational information on the hydrology of the alluvial aquifer, a numerical groundwater-flow model was developed to estimate the potential effects of additional storage of groundwater in the alluvial aquifer.</p><p>Groundwater-level elevation data from 30 wells were used to estimate groundwater-flow directions in the alluvial aquifer, which were generally from the southwest to northeast, away from the Sangre de Cristo Mountains and towards perennial streams in the center of the valley. Although some seasonal variation was apparent in groundwater-level elevation records, no statistically significant seasonal trends were indicated. Statistically significant long-term trends were indicated in groundwater-level elevation records for 8 of the 30 wells, and of these wells with statistically significant trends, all but 1 indicated a negative trend of groundwater-level elevations. Spatial evaluation of wells with statistically significant negative groundwater-level elevation trends showed many are in areas of denser well drilling for domestic or other uses, indicating increasing groundwater use could potentially be causing groundwater-level elevation declines. There were instances of wells with no statistically significant groundwater-level elevation trends also located in areas of greater density of well completions. Additional investigations may be necessary to more fully characterize the processes responsible for negative groundwater-level elevation trends.</p><p>Streamflow gain or loss calculations were completed for low flow in 2017–19 and for high flow in 2018 in nine reaches of streams within the study area. Stream reaches of the upper Texas Creek, upper Grape Creek, upper-middle Grape Creek, and Taylor Creek displayed consistent streamflow loss in each period from 2017 to 2019. These stream reaches represent long-term sources of recharge to the alluvial aquifer. Streamflow gain or loss varies through time in other stream reaches (lower Texas Creek, lower-middle Grape Creek, lower Grape Creek below Westcliffe, and lower Grape Creek above DeWeese Reservoir). The temporally variable behavior indicates these stream reaches may be sources of groundwater recharge or areas of groundwater discharge, likely depending on temporal dynamics between the elevation of the water table and the stream.</p><p>Water-quality samples were collected from 10 groundwater wells and 10 stream sites during September through November 2019. All groundwater and stream samples were analyzed for major and trace elements and stable isotopes of water. A subset of groundwater samples was also analyzed for the environmental tracers sulfur hexafluoride, tritium, and noble gases. Comparison of water-quality results to U.S. Environmental Protection Agency drinking water-quality standards indicated no constituents exceeded primary standards for human health. Spatial evaluation of water quality indicated the concentrations of various constituents are likely controlled by groundwater and surface-water interactions and by spatial variability in bedrock geology underlying the alluvial aquifer. Specifically, streams shown to gain from groundwater had water chemistry constituent compositions similar to groundwater, whereas streams exiting the Sangre de Cristo Mountains tended to have compositions consistent with snowmelt. Groundwater geochemistry appeared to be partially controlled by oxidation-reduction processes and by proximity to igneous rocks in the Wet Mountains. Environmental tracers used to estimate groundwater age indicated all sampled groundwater contained tracers representing modern recharge (approximately less than 65 years old) but mixing of premodern recharge (approximately more than 65 years old) also occurs. Spatial evaluation of environmental tracers indicated large faults may be conduits for upwelling of older groundwater. No trends were observed in groundwater age with well depth, indicating all sampled wells are located within the zone of active groundwater flow. The presence of modern groundwater in wells with statistically significant negative groundwater-level elevation trends indicates groundwater storage depletions may be partially offset by capture of modern recharge. Repeated sampling of groundwater age would be necessary, however, to determine if any trends in groundwater age exist, which may indicate changing groundwater recharge, storage, or discharge. Additional investigations could also consider quantifying groundwater age in deeper wells to more fully define the depth of active groundwater flow.</p><p>A numerical groundwater-flow model was developed to estimate components of the water budget, simulate groundwater and surface-water interactions, and evaluate the potential effects of aquifer storage and recovery. Simulated groundwater-level elevations from the calibrated groundwater-flow model are similar to the observed pattern of groundwater-level elevations with higher elevations in the western part of the study area along the Sangre de Cristo Mountains. Simulated water-budget components indicate most of the recharge to the alluvial aquifer is derived from streamflow losses, which is consistent with observations of losing streams along the mountain front. The largest groundwater discharge component of the alluvial aquifer was to streams in the center of the valley, where observations of stream gain or loss indicated the predominance of gaining conditions. Comparison of groundwater and surface-water interactions between the calibrated groundwater-flow model for 2000-19 (the base-case model) and a simulation including additional recharge, representing potential aquifer storage and recovery operations, indicated the additional recharge distributed throughout the area had minimal effects on streamflow in the nearby Grape Creek. An analysis of subregional groundwater budgets showed approximately 54 percent of the additional recharge flowed back to nearby Grape Creek, and the other 46 percent was distributed laterally into adjacent cells in the alluvial aquifer. The comparison of simulations and subregional water budget show the additional recharge did not substantially alter groundwater-level elevations or basin wide groundwater storage. Although the analysis of additional recharge provided in the numerical groundwater-flow model considers only one of many possible recharge scenarios, the model provides a useful tool that could be modified for various scenarios to understand potential effects of managed aquifer recharge.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20245105","collaboration":"Prepared in cooperation with the Upper Arkansas Water Conservancy District","usgsCitation":"Newman, C.P., Russell, C.A., Kisfalusi, Z.D., and Paschke, S.S., 2025, Groundwater hydrology, groundwater and surface-water interactions, water quality, and groundwater-flow simulations for the Wet Mountain Valley alluvial aquifer, Custer and Fremont Counties, Colorado, 2017–19: U.S. Geological Survey Scientific Investigations Report 2024–5105, 62 p., https://doi.org/10.3133/sir20245105.","productDescription":"Report: vii, 62 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-125470","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":481114,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5105/coverthb.jpg"},{"id":481115,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5105/sir20245105.pdf","text":"Report","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5105"},{"id":481144,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9342SSP","text":"USGS data release","linkHelpText":"Environmental tracer model for the Wet Mountain Valley alluvial aquifer, Custer and Fremont Counties, Colorado, 2019"},{"id":481145,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AAUGNY","text":"USGS data release","linkHelpText":"Groundwater-flow model of the Wet Mountain Valley alluvial aquifer, Custer and Fremont Counties, Colorado"},{"id":481407,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5105/images"},{"id":481408,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5105/sir20245105.xml"},{"id":481417,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245105/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5105"}],"country":"United States","state":"Colorado","county":"Custer County, Fremont County","otherGeospatial":"Upper Arkansas River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.1667,\n              38.5\n            ],\n            [\n              -105.1667,\n              37.9167\n            ],\n            [\n              -105.9167,\n              37.9167\n            ],\n            [\n              -105.9167,\n              38.5\n            ],\n            [\n              -105.1667,\n              38.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/colorado-water-science-center/\" data-mce-href=\"https://www.usgs.gov/centers/colorado-water-science-center/\">Colorado Water Science Center</a><br>U.S. Geological Survey<br>Box 25046, Mail Stop 415<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Study Methods</li><li>Groundwater Hydrology</li><li>Groundwater and Surface-Water Interactions</li><li>Water Quality</li><li>Groundwater-Flow Simulations </li><li>Model Limitations</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2025-01-28","noUsgsAuthors":false,"publicationDate":"2025-01-28","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":924930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Cory A. 0000-0001-6358-1605","orcid":"https://orcid.org/0000-0001-6358-1605","contributorId":223018,"corporation":false,"usgs":true,"family":"Russell","given":"Cory","email":"","middleInitial":"A.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kisfalusi, Zachary D. 0000-0001-6016-3213","orcid":"https://orcid.org/0000-0001-6016-3213","contributorId":222422,"corporation":false,"usgs":true,"family":"Kisfalusi","given":"Zachary","email":"","middleInitial":"D.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paschke, Suzanne S. 0000-0002-3471-4242 spaschke@usgs.gov","orcid":"https://orcid.org/0000-0002-3471-4242","contributorId":1347,"corporation":false,"usgs":true,"family":"Paschke","given":"Suzanne","email":"spaschke@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924933,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70262914,"text":"70262914 - 2025 - Hotter temperatures alter riparian plant outcomes under regulated river conditions","interactions":[],"lastModifiedDate":"2025-01-28T15:42:49.175773","indexId":"70262914","displayToPublicDate":"2025-01-27T09:39:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Hotter temperatures alter riparian plant outcomes under regulated river conditions","docAbstract":"<p><span>Climate change and river regulation alter environmental controls on riparian plant occurrence and cover worldwide. Simultaneous changes to river flow and air temperature could result in unanticipated plant responses to novel environmental conditions. Increasing temperature could alter riparian plant response to hydrology and other factors, while river regulation may exacerbate environmental stress through novel flows like those resulting from power generation. Further, plant establishment and growth may require differing conditions, which may be decoupled by novel conditions. Using a large dataset that spans a natural 5°C mean annual temperature (MAT) gradient and a Bayesian model that integrates plant occurrence and cover, we address four questions: (1) Does hotter MAT modify plant response to hydrology, substrate composition, topography, and cover of co-occurring plant species? (2) Does the timing of hydropower tides benefit some species over others? (3) Does dam-induced erosion hinder riparian species more than upland species? (4) Do occurrence and cover respond to different environmental variables, allowing for decoupling of life history processes? We addressed these questions with data collected along 364 km of the Colorado River downstream of Glen Canyon Dam, Arizona, United States of America. Occurrence and cover class were recorded in &gt;10,000 plots from 2016 to 2020, along with environmental covariates that repeat across the climate gradient. For 36 species, plant occurrence and cover were modeled with respect to MAT, hydrology, substrate, topography, other plant cover, and their interactions with MAT. There were four key results. (1) Increasing MAT will not only directly influence plants but will mediate their responses to the environment, including greater dependence on stable water supplies. (2) The timing of hydropower tides shapes plant community composition. (3) Dam-related erosion has an outsized effect on riparian species, which could lead to a loss of regionally unique plant species. (4) For all species, the most important covariates driving occurrence differed from those for cover, suggesting the potential for these life stages to be decoupled. Not only will climate change and river regulation independently alter plant distributions, interactions among hotter temperature, dam-controlled flow patterns, and limited fine sediments will determine which species flourish or perish under future conditions.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecm.1645","usgsCitation":"Palmquist, E.C., Ogle, K., Butterfield, B.J., Whitham, T.G., Allan, G.J., and Shafroth, P., 2025, Hotter temperatures alter riparian plant outcomes under regulated river conditions: Ecological Monographs, v. 95, no. 1, e1645, 21 p., https://doi.org/10.1002/ecm.1645.","productDescription":"e1645, 21 p.","ipdsId":"IP-159047","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":481415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River downstream of Glen Canyon Dam","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -111.21176601160529,\n              36.979125233919234\n            ],\n            [\n              -113.97825341279814,\n              36.979125233919234\n            ],\n            [\n              -113.97825341279814,\n              35.65153018969767\n            ],\n            [\n              -111.21176601160529,\n              35.65153018969767\n            ],\n            [\n              -111.21176601160529,\n              36.979125233919234\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"95","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":925281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ogle, Kiona","contributorId":248351,"corporation":false,"usgs":false,"family":"Ogle","given":"Kiona","email":"","affiliations":[],"preferred":false,"id":925282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":925283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitham, Thomas G.","contributorId":174327,"corporation":false,"usgs":false,"family":"Whitham","given":"Thomas","email":"","middleInitial":"G.","affiliations":[{"id":27416,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Nothern Arizona University, Flagstaff, AZ 86011 USA","active":true,"usgs":false}],"preferred":false,"id":925284,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allan, Gerard J.","contributorId":189075,"corporation":false,"usgs":false,"family":"Allan","given":"Gerard","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":925285,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":925286,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70264824,"text":"70264824 - 2025 - Decomposing the Tea Bag Index and finding slower organic matter loss rates at higher elevations and deeper soil horizons in a minerogenic salt marsh","interactions":[],"lastModifiedDate":"2025-03-26T15:03:35.464504","indexId":"70264824","displayToPublicDate":"2025-01-24T09:54:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Decomposing the Tea Bag Index and finding slower organic matter loss rates at higher elevations and deeper soil horizons in a minerogenic salt marsh","docAbstract":"<p><span>Environmental gradients can affect organic matter decay within and across wetlands and contribute to spatial heterogeneity in soil carbon stocks. We tested the sensitivity of decay rates to tidal flooding and soil depth in a minerogenic salt marsh using the Tea Bag Index (TBI). Tea bags were buried at 10 and 50 cm depths across an elevation gradient in a subtropical&nbsp;</span><i>Spartina alterniflora</i><span>&nbsp;marsh in Georgia (USA). Plant and animal communities and soil properties were characterized once, while replicate tea bags and porewaters were collected several times over 1 year. TBI decay rates were faster than prior litterbag studies in the same marsh, largely due to rapid green tea loss. Rooibos tea decay rates were more comparable to natural marsh litter, potentially suggesting that is more useful as a standardized organic matter proxy than green tea. Decay was slowest at higher marsh elevations and not consistently related to other biotic (e.g., plants, crab burrows) or abiotic factors (e.g., porewater chemistry), indicating that local hydrology strongly affected organic matter loss rates. TBI rates were 32 %–118 % faster in the 10 cm horizon than at 50 cm. Rates were fastest in the first 3 months and slowed 54 %–60 % at both depths between 3 and 6 months. Rates slowed further between 6 and 12 months, but this was more muted at 10 cm (17 %) compared to 50 cm (50 %). Slower rates at depth and with time were unlikely due to the TBI stabilization factor, which was similar across depths and decreased from 6 to 12 months. Slower decay at 50 cm demonstrates that rates were constrained by environmental conditions in the deeper horizon rather than the composition of this highly standardized litter. Overall, these patterns suggest that hydrological setting, which affects oxidant introduction and reactant removal and is often overlooked in marsh decomposition studies, may be a particularly important control on organic matter loss in the short term (3–12 months).</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/bg-22-435-2025","usgsCitation":"Reddy, S., Farrell, W., Wu, F., Pennings, S.C., Sanderman, J., Eagle, M.J., Craft, C., and Spivak, A.C., 2025, Decomposing the Tea Bag Index and finding slower organic matter loss rates at higher elevations and deeper soil horizons in a minerogenic salt marsh: Biogeosciences, v. 22, no. 2, p. 435-453, https://doi.org/10.5194/bg-22-435-2025.","productDescription":"19 p.","startPage":"435","endPage":"453","ipdsId":"IP-166089","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-22-435-2025","text":"Publisher Index Page"},{"id":483875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Altamaha River","volume":"22","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Reddy, Satyatejas G.","contributorId":352677,"corporation":false,"usgs":false,"family":"Reddy","given":"Satyatejas G.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":931981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Farrell, W. Reilly","contributorId":352678,"corporation":false,"usgs":false,"family":"Farrell","given":"W. Reilly","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":931982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wu, Fengrun","contributorId":352679,"corporation":false,"usgs":false,"family":"Wu","given":"Fengrun","affiliations":[{"id":84281,"text":"Xiamen University of Technology","active":true,"usgs":false}],"preferred":false,"id":931983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pennings, Steven C.","contributorId":177820,"corporation":false,"usgs":false,"family":"Pennings","given":"Steven","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":931984,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sanderman, Jonathan","contributorId":187477,"corporation":false,"usgs":false,"family":"Sanderman","given":"Jonathan","email":"","affiliations":[],"preferred":false,"id":931985,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Eagle, Meagan J. 0000-0001-5072-2755 meagle@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":242890,"corporation":false,"usgs":true,"family":"Eagle","given":"Meagan","email":"meagle@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":931986,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Craft, Christopher","contributorId":156398,"corporation":false,"usgs":false,"family":"Craft","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":931987,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Spivak, Amanda C.","contributorId":191376,"corporation":false,"usgs":false,"family":"Spivak","given":"Amanda","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":931988,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70263287,"text":"70263287 - 2025 - Biotic and abiotic drivers of ecosystem temporal stability in herbaceous wetlands in China","interactions":[],"lastModifiedDate":"2025-02-04T15:20:26.056947","indexId":"70263287","displayToPublicDate":"2025-01-24T08:15:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Biotic and abiotic drivers of ecosystem temporal stability in herbaceous wetlands in China","docAbstract":"Maintaining the stability of ecosystems is critical for supporting essential ecosystem services over time. However, our understanding of the contribution of the diverse biotic and abiotic factors to this stability in wetlands remains limited. Here, we combined data from a field vegetation survey of 725 herbaceous wetland sites in China with remote sensing information from the Enhanced Vegetation Index (EVI) from 2010 to 2020 to explore the contribution of biotic and abiotic factors to the temporal stability of primary productivity. We found that plant species richness directly contributed to stability on a national scale, but that this contribution differed among climate zones, hydrological regimes, and vegetation types. In addition, many abiotic factors, including soil properties, geographical location, and climate also contributed to stability. Piecewise structural equation modeling identified that soil properties, including soil pH, total nitrogen, and soil organic carbon, emerged as primary factors modulating ecosystem stability, both directly and indirectly by affecting species richness and vegetation type. Higher species richness and soil organic carbon were related to higher ecosystem stability in peatlands but less so in coastal and inland marshes. These findings enhance our ability to forecast how wetland ecosystems may respond to future environmental changes and biodiversity loss and can inform policy decisions related to ecosystem stability.","language":"English","publisher":"Wiley","doi":"10.1111/gcb.70056","usgsCitation":"Wang, G., Hu, N., Hautier, Y., Middleton, B., Wang, M., Zhao, M., Meng, J., Ma, Z., Liu, B., Liu, Y., and Jiang, M., 2025, Biotic and abiotic drivers of ecosystem temporal stability in herbaceous wetlands in China: Global Change Biology, v. 31, no. 1, e70056, 10 p., https://doi.org/10.1111/gcb.70056.","productDescription":"e70056, 10 p.","ipdsId":"IP-166071","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":499262,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.70056","text":"Publisher Index Page"},{"id":481667,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[110.33919,18.6784],[109.47521,18.1977],[108.65521,18.50768],[108.62622,19.36789],[109.11906,19.82104],[110.2116,20.10125],[110.78655,20.07753],[111.01005,19.69593],[110.57065,19.25588],[110.33919,18.6784]]],[[[127.65741,49.76027],[129.39782,49.4406],[130.58229,48.72969],[130.98728,47.79013],[132.50667,47.78897],[133.3736,48.18344],[135.02631,48.47823],[134.50081,47.57844],[134.11236,47.21247],[133.76964,46.11693],[133.09713,45.14407],[131.88345,45.32116],[131.02521,44.96795],[131.28856,44.11152],[131.14469,42.92999],[130.63387,42.90301],[130.64002,42.39501],[129.99427,42.98539],[129.59667,42.42498],[128.05222,41.99428],[128.20843,41.46677],[127.34378,41.50315],[126.86908,41.81657],[126.18205,41.10734],[125.07994,40.56982],[124.26562,39.92849],[122.86757,39.63779],[122.13139,39.17045],[121.05455,38.89747],[121.58599,39.36085],[121.37676,39.75026],[122.1686,40.42244],[121.64036,40.94639],[120.76863,40.59339],[119.6396,39.89806],[119.02346,39.25233],[118.04275,39.20427],[117.5327,38.73764],[118.0597,38.06148],[118.87815,37.89733],[118.91164,37.44846],[119.7028,37.15639],[120.82346,37.87043],[121.71126,37.48112],[122.35794,37.45448],[122.51999,36.93061],[121.10416,36.65133],[120.63701,36.11144],[119.66456,35.60979],[119.15121,34.90986],[120.22752,34.36033],[120.62037,33.37672],[121.22901,32.46032],[121.90815,31.69217],[121.89192,30.94935],[121.26426,30.67627],[121.50352,30.14291],[122.09211,29.83252],[121.93843,29.01802],[121.68444,28.22551],[121.12566,28.13567],[120.39547,27.05321],[119.5855,25.74078],[118.65687,24.54739],[117.28161,23.6245],[115.89074,22.78287],[114.76383,22.66807],[114.15255,22.22376],[113.80678,22.54834],[113.24108,22.05137],[111.84359,21.55049],[110.78547,21.39714],[110.44404,20.34103],[109.88986,20.28246],[109.62766,21.00823],[109.86449,21.39505],[108.52281,21.71521],[108.05018,21.55238],[107.04342,21.8119],[106.56727,22.2182],[106.7254,22.79427],[105.81125,22.97689],[105.32921,23.35206],[104.47686,22.81915],[103.50451,22.70376],[102.70699,22.7088],[102.17044,22.46475],[101.65202,22.3182],[101.80312,21.17437],[101.27003,21.20165],[101.18001,21.43657],[101.15003,21.84998],[100.41654,21.55884],[99.98349,21.74294],[99.2409,22.11831],[99.53199,22.94904],[98.89875,23.14272],[98.66026,24.06329],[97.60472,23.8974],[97.72461,25.08364],[98.67184,25.9187],[98.71209,26.74354],[98.68269,27.50881],[98.24623,27.74722],[97.91199,28.33595],[97.32711,28.26158],[96.24883,28.41103],[96.58659,28.83098],[96.11768,29.4528],[95.4048,29.03172],[94.56599,29.27744],[93.41335,28.64063],[92.50312,27.89688],[91.69666,27.77174],[91.25885,28.04061],[90.73051,28.06495],[90.01583,28.29644],[89.47581,28.04276],[88.81425,27.29932],[88.73033,28.08686],[88.12044,27.87654],[86.95452,27.97426],[85.82332,28.20358],[85.01164,28.64277],[84.23458,28.83989],[83.89899,29.32023],[83.33712,29.46373],[82.32751,30.11527],[81.5258,30.42272],[81.11126,30.18348],[79.72137,30.88271],[78.73889,31.51591],[78.45845,32.61816],[79.17613,32.48378],[79.20889,32.99439],[78.81109,33.5062],[78.91227,34.32194],[77.83745,35.49401],[76.19285,35.8984],[75.8969,36.66681],[75.15803,37.13303],[74.98,37.41999],[74.82999,37.99001],[74.86482,38.37885],[74.25751,38.60651],[73.92885,38.50582],[73.67538,39.43124],[73.96001,39.66001],[73.82224,39.89397],[74.77686,40.36643],[75.46783,40.56207],[76.52637,40.42795],[76.90448,41.06649],[78.1872,41.18532],[78.54366,41.58224],[80.11943,42.12394],[80.25999,42.35],[80.18015,42.92007],[80.86621,43.18036],[79.96611,44.91752],[81.94707,45.31703],[82.45893,45.53965],[83.18048,47.33003],[85.16429,47.00096],[85.72048,47.45297],[85.76823,48.45575],[86.59878,48.54918],[87.35997,49.21498],[87.75126,49.2972],[88.01383,48.59946],[88.8543,48.06908],[90.28083,47.69355],[90.97081,46.88815],[90.58577,45.71972],[90.94554,45.28607],[92.13389,45.11508],[93.48073,44.97547],[94.68893,44.35233],[95.30688,44.24133],[95.76245,43.31945],[96.3494,42.72564],[97.45176,42.74889],[99.51582,42.52469],[100.84587,42.6638],[101.83304,42.51487],[103.31228,41.90747],[104.52228,41.90835],[104.96499,41.59741],[106.12932,42.13433],[107.74477,42.48152],[109.2436,42.51945],[110.4121,42.87123],[111.12968,43.40683],[111.82959,43.74312],[111.66774,44.07318],[111.34838,44.45744],[111.87331,45.10208],[112.43606,45.01165],[113.46391,44.80889],[114.46033,45.33982],[115.9851,45.72724],[116.71787,46.3882],[117.4217,46.67273],[118.87433,46.80541],[119.66327,46.69268],[119.77282,47.04806],[118.86657,47.74706],[118.06414,48.06673],[117.29551,47.69771],[116.30895,47.85341],[115.74284,47.72654],[115.48528,48.13538],[116.1918,49.1346],[116.6788,49.88853],[117.87924,49.51098],[119.28846,50.14288],[119.27937,50.58291],[120.18205,51.64357],[120.73819,51.96412],[120.72579,52.51623],[120.17709,52.75389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Guodong","contributorId":350506,"corporation":false,"usgs":false,"family":"Wang","given":"Guodong","affiliations":[{"id":83757,"text":"Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun","active":true,"usgs":false}],"preferred":false,"id":926162,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hu, Nanlin","contributorId":350507,"corporation":false,"usgs":false,"family":"Hu","given":"Nanlin","affiliations":[{"id":83757,"text":"Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun","active":true,"usgs":false}],"preferred":false,"id":926163,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hautier, Yann","contributorId":271107,"corporation":false,"usgs":false,"family":"Hautier","given":"Yann","affiliations":[{"id":56284,"text":"Ecology and Biodiversity Group, Department of Biology, Utrecht University, Utrecht, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":926164,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":222689,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":926165,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Ming","contributorId":350508,"corporation":false,"usgs":false,"family":"Wang","given":"Ming","affiliations":[{"id":83758,"text":"State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, Institute for Peat and Mire Research, Northeast Normal University, Changchun, China","active":true,"usgs":false}],"preferred":false,"id":926166,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhao, Meiling","contributorId":350509,"corporation":false,"usgs":false,"family":"Zhao","given":"Meiling","affiliations":[{"id":83757,"text":"Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun","active":true,"usgs":false}],"preferred":false,"id":926167,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meng, Jingci","contributorId":350510,"corporation":false,"usgs":false,"family":"Meng","given":"Jingci","affiliations":[{"id":83757,"text":"Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun","active":true,"usgs":false}],"preferred":false,"id":926168,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ma, Zijun","contributorId":350511,"corporation":false,"usgs":false,"family":"Ma","given":"Zijun","affiliations":[{"id":83757,"text":"Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun","active":true,"usgs":false}],"preferred":false,"id":926169,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Liu, Bo","contributorId":338749,"corporation":false,"usgs":false,"family":"Liu","given":"Bo","email":"","affiliations":[],"preferred":false,"id":926170,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Liu, Yanjie","contributorId":350512,"corporation":false,"usgs":false,"family":"Liu","given":"Yanjie","affiliations":[{"id":83757,"text":"Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun","active":true,"usgs":false}],"preferred":false,"id":926171,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jiang, Mingkai","contributorId":245059,"corporation":false,"usgs":false,"family":"Jiang","given":"Mingkai","email":"","affiliations":[{"id":49069,"text":"Hawkesbury Institute for the Environment, Western Sydney University, Locked Bag 1797, Penrith, NSW, 2751 Australia","active":true,"usgs":false}],"preferred":false,"id":926172,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70264806,"text":"70264806 - 2025 - Effects of river floods and sedimentation on a naturally dynamic Great Lakes estuary","interactions":[],"lastModifiedDate":"2025-03-25T15:05:21.017701","indexId":"70264806","displayToPublicDate":"2025-01-22T09:58:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Effects of river floods and sedimentation on a naturally dynamic Great Lakes estuary","docAbstract":"<p><span>Some of the most biologically diverse coastal wetlands and estuaries are found along the Great Lakes, but the spatial extent and timing of river-related inundation and sedimentation vary greatly among natural and altered systems. We used hydrologic data, geomorphic change detection, and satellite imagery to study inundation and sedimentation patterns in the naturally dynamic estuary of the Bad River (</span><i>Mashkiiziibii</i><span>) that flows into Lake Superior (</span><i>Anishinaabeg-gichigami</i><span>), and the Kakagon River (</span><i>Ogaakaagaang-ziibii</i><span>) that flows into a sheltered bay (</span><i>Chi-Kaamigong</i><span>). In 2016, an extreme summer flood (annual exceedance probability&nbsp;&lt;&nbsp;0.2&nbsp;%) caused total inundation of the 46-km</span><sup>2</sup><span>&nbsp;estuary. Floods from the sediment-rich Bad River, with an annual exceedance probability of&nbsp;≤&nbsp;50&nbsp;%, have overflowed into the upper wetlands and channels of the Kakagon River about 60 times over the last 75&nbsp;years, including 20 floods during the most recent 10-year wet period. Sedimentation patterns were associated with proximity to river channels, shoreline erosion, and wind action. Early winter ice-up coupled with a storm surge and an early spring snowmelt into the iced-over bay changed inundation duration and sedimentation patterns. Climate-change projections for more intense rainfall and warmer temperatures will likely cause more frequent flooding and sedimentation; however, patterns may differ depending on the timing of the floods relative to storm surges and ice formation, or other factors. The approach of integrating readily available data helped give a broader temporal and spatial context to the possible causes for inundation and sedimentation, some expected and others not, in natural and restored estuaries of the Great Lakes.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2024.102458","usgsCitation":"Fitzpatrick, F., Vaughan, A., Dantoin, E.D., Sterner, S.P., Reneau, P., and Roland, C., 2025, Effects of river floods and sedimentation on a naturally dynamic Great Lakes estuary: Journal of Great Lakes Research, v. 51, no. 1, 102458, 19 p., https://doi.org/10.1016/j.jglr.2024.102458.","productDescription":"102458, 19 p.","ipdsId":"IP-163441","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":488275,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2024.102458","text":"Publisher Index Page"},{"id":483809,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Bad River, Chequamegon Bay, Lake Superior","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.86741881591443,\n              46.74517791310441\n            ],\n            [\n              -90.86741881591443,\n              46.59429411429369\n            ],\n            [\n              -90.55858891028036,\n              46.59429411429369\n            ],\n            [\n              -90.55858891028036,\n              46.74517791310441\n            ],\n            [\n              -90.86741881591443,\n              46.74517791310441\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"51","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fitzpatrick, Faith 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209191,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931769,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vaughan, Angus 0000-0001-9900-4658","orcid":"https://orcid.org/0000-0001-9900-4658","contributorId":302333,"corporation":false,"usgs":true,"family":"Vaughan","given":"Angus","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":931770,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dantoin, Eric D. 0000-0002-8561-2924 edantoin@usgs.gov","orcid":"https://orcid.org/0000-0002-8561-2924","contributorId":2278,"corporation":false,"usgs":true,"family":"Dantoin","given":"Eric","email":"edantoin@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931771,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sterner, Shelby P. 0000-0002-3103-7960","orcid":"https://orcid.org/0000-0002-3103-7960","contributorId":292246,"corporation":false,"usgs":true,"family":"Sterner","given":"Shelby","email":"","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931772,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reneau, Paul 0000-0002-1335-7573","orcid":"https://orcid.org/0000-0002-1335-7573","contributorId":217293,"corporation":false,"usgs":true,"family":"Reneau","given":"Paul","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931773,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roland, Collin 0000-0003-1004-0746","orcid":"https://orcid.org/0000-0003-1004-0746","contributorId":343660,"corporation":false,"usgs":true,"family":"Roland","given":"Collin","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931774,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70262454,"text":"70262454 - 2025 - Tracing metal sources and groundwater flow paths in the Upper Animas River watershed using rare earth elements and stable isotopes","interactions":[],"lastModifiedDate":"2025-02-11T15:45:16.210494","indexId":"70262454","displayToPublicDate":"2025-01-16T10:25:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1758,"text":"Geochemistry: Exploration, Environment, Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Tracing metal sources and groundwater flow paths in the Upper Animas River watershed using rare earth elements and stable isotopes","docAbstract":"<p><span>Groundwater flow paths and processes that govern metal mobility and transport are difficult to characterize in mountainous bedrock watersheds. Despite the difficulty in holistic characterization, conceptual understanding of subsurface hydrologic and geochemical processes is key to developing remediation plans for locations affected by acid mine drainage, such as the Upper Animas River watershed in southwestern Colorado, USA. Stable isotopes of water and rare earth elements were utilized to evaluate groundwater flow and metal sources within this complex catchment. Stable isotope samples collected from draining mine adits and springs display systematic spatial variation wherein sample sites at higher elevations have greater seasonal variability than sites at lower elevations. The Upper Cement Creek watershed, where multiple draining mines are present, displays the lowest seasonal variation in stable isotopic signatures, potentially indicating the presence of a large, well-mixed volume of groundwater storage or interbasin groundwater flow. Rare earth elements display statistically significant variation between different alteration styles in the catchment. Overprinting of regional propylitic alteration is evident based on enrichment of middle rare earth elements in acidic springs and mines that are not spatially associated with surficial exposures of acid generating alteration styles. Europium anomaly and middle rare earth enrichment signatures from two flooded mine tunnels on opposite sides of a watershed divide indicate connections to the same subsurface flooded mine workings.</span></p>","language":"English","publisher":"Geological Society of London","doi":"10.1144/geochem2024-023","usgsCitation":"Newman, C.P., Cowie, R.M., Wilkin, R., and Navarre-Sitchler, A., 2025, Tracing metal sources and groundwater flow paths in the Upper Animas River watershed using rare earth elements and stable isotopes: Geochemistry: Exploration, Environment, Analysis, v. 25, no. 1, geochem2024-023, 13 p., https://doi.org/10.1144/geochem2024-023.","productDescription":"geochem2024-023, 13 p.","ipdsId":"IP-165955","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":480747,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":481028,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1144/geochem2024-023","text":"Publisher Index Page"}],"country":"United States","state":"Colorado","otherGeospatial":"Upper Animas River watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -107.70,\n              37.93\n            ],\n            [\n              -107.70,\n              37.86\n            ],\n            [\n              -107.56,\n              37.86\n            ],\n            [\n              -107.56,\n              37.93\n            ],\n            [\n              -107.70,\n              37.93\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"25","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-02-07","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":924248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cowie, Rory M.","contributorId":270098,"corporation":false,"usgs":false,"family":"Cowie","given":"Rory","email":"","middleInitial":"M.","affiliations":[{"id":56077,"text":"Alpine Water Resources","active":true,"usgs":false}],"preferred":false,"id":924249,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilkin, Rick 0000-0002-8635-9545","orcid":"https://orcid.org/0000-0002-8635-9545","contributorId":345122,"corporation":false,"usgs":false,"family":"Wilkin","given":"Rick","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":924250,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Navarre-Sitchler, Alexis","contributorId":190441,"corporation":false,"usgs":false,"family":"Navarre-Sitchler","given":"Alexis","email":"","affiliations":[],"preferred":false,"id":924251,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70262495,"text":"70262495 - 2025 - Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA","interactions":[],"lastModifiedDate":"2025-01-17T16:06:37.26906","indexId":"70262495","displayToPublicDate":"2025-01-16T10:01:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA","docAbstract":"<p><span>Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2024.132195","usgsCitation":"Bassah, R., Corzo Perez, G.A., Bhattacharya, B., Haider, S., Swain, E.D., and Aumen, N., 2025, Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA: Journal of Hydrology, v. 652, 132195, 17 p., https://doi.org/10.1016/j.jhydrol.2024.132195.","productDescription":"132195, 17 p.","ipdsId":"IP-165910","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":489132,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2024.132195","text":"Publisher Index Page"},{"id":480739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.15272667125285,\n              26.85302740104224\n            ],\n            [\n              -81.52356680957865,\n              26.85302740104224\n            ],\n            [\n              -81.52356680957865,\n              25.136407133512265\n            ],\n            [\n              -80.15272667125285,\n              25.136407133512265\n            ],\n            [\n              -80.15272667125285,\n              26.85302740104224\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"652","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bassah, Raidan","contributorId":349546,"corporation":false,"usgs":false,"family":"Bassah","given":"Raidan","affiliations":[{"id":49677,"text":"IHE Delft Institute for Water Education","active":true,"usgs":false}],"preferred":false,"id":924376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corzo Perez, Gerald A.","contributorId":332614,"corporation":false,"usgs":false,"family":"Corzo Perez","given":"Gerald","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":924377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bhattacharya, Biswa 0000-0002-8046-589X","orcid":"https://orcid.org/0000-0002-8046-589X","contributorId":298961,"corporation":false,"usgs":false,"family":"Bhattacharya","given":"Biswa","email":"","affiliations":[{"id":49677,"text":"IHE Delft Institute for Water Education","active":true,"usgs":false}],"preferred":false,"id":924378,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haider, Saira M. 0000-0001-9306-3454","orcid":"https://orcid.org/0000-0001-9306-3454","contributorId":206253,"corporation":false,"usgs":true,"family":"Haider","given":"Saira","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":924379,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":924380,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aumen, Nicholas 0000-0002-5277-2630","orcid":"https://orcid.org/0000-0002-5277-2630","contributorId":223550,"corporation":false,"usgs":true,"family":"Aumen","given":"Nicholas","affiliations":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"preferred":true,"id":924381,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70264082,"text":"70264082 - 2025 - Ecohydrological response of a forested headwater catchment to a flash drought in the Southeastern U.S.","interactions":[],"lastModifiedDate":"2025-03-06T15:26:45.148976","indexId":"70264082","displayToPublicDate":"2025-01-16T09:06:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Ecohydrological response of a forested headwater catchment to a flash drought in the Southeastern U.S.","docAbstract":"<p><span>Flash droughts differ from traditionally defined droughts in their rapidity of intensification and often associated high vapor-pressure deficit. These droughts can lead to declines in streamflow and water table depth and induce water stress to vegetation at a greater rate than droughts that manifest over longer periods. However, little is known regarding the response of forested environments to flash drought because most studies of impacts have been conducted in agricultural settings. In this study we investigated water-use patterns of riparian trees using sap flow methods and examined the role of groundwater as a source of moisture over three periods that were delimited by antecedent soil moisture conditions. For a longer-term perspective we also examine monthly streamflow over the 35-year record. We observed that trees at only one monitoring plot showed a decrease in water use relative to evaporative demand during a flash drought. Total reverse sap flow (flow toward the roots rather than the canopy) greatly increased during the flash drought period, suggesting the likely occurrence of hydraulic redistribution to the excessively dry soils. Over the drought period groundwater became a more dominant source of moisture for sustaining forest water use. Monthly mean streamflow during the flash drought approached levels observed in past multiyear droughts. This is the first study, to our knowledge, to specifically investigate the response of multiple water budget components to flash drought in a humid forest. As more studies are conducted, a better understanding of the range of expected responses are likely to emerge.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2024.132658","usgsCitation":"Riley, J.W., Pangle, L., Forster, M., and Aulenbach, B.T., 2025, Ecohydrological response of a forested headwater catchment to a flash drought in the Southeastern U.S.: Journal of Hydrology, v. 652, 132658, 12 p., https://doi.org/10.1016/j.jhydrol.2024.132658.","productDescription":"132658, 12 p.","ipdsId":"IP-150167","costCenters":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":488037,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2024.132658","text":"Publisher Index Page"},{"id":482969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Panola Mountain Research Watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.18385537410896,\n              33.647487899040684\n            ],\n            [\n              -84.18385537410896,\n              33.62051112971396\n            ],\n            [\n              -84.13090752919243,\n              33.62051112971396\n            ],\n            [\n              -84.13090752919243,\n              33.647487899040684\n            ],\n            [\n              -84.18385537410896,\n              33.647487899040684\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"652","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Riley, Jeffrey W. 0000-0001-5525-3134 jriley@usgs.gov","orcid":"https://orcid.org/0000-0001-5525-3134","contributorId":3605,"corporation":false,"usgs":true,"family":"Riley","given":"Jeffrey","email":"jriley@usgs.gov","middleInitial":"W.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pangle, Luke A.","contributorId":351888,"corporation":false,"usgs":false,"family":"Pangle","given":"Luke A.","affiliations":[{"id":52554,"text":"Georgia State University","active":true,"usgs":false}],"preferred":false,"id":929714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forster, Michael","contributorId":351889,"corporation":false,"usgs":false,"family":"Forster","given":"Michael","affiliations":[{"id":84068,"text":"Edaphic Scientific Pty. and Griffith University","active":true,"usgs":false}],"preferred":false,"id":929715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":929716,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70262096,"text":"pp1894F - 2025 - Integrated water availability in the conterminous United States, 2010–20","interactions":[{"subject":{"id":70262096,"text":"pp1894F - 2025 - Integrated water availability in the conterminous United States, 2010–20","indexId":"pp1894F","publicationYear":"2025","noYear":false,"chapter":"F","displayTitle":"Integrated Water Availability in the Conterminous United States, 2010–20","title":"Integrated water availability in the conterminous United States, 2010–20"},"predicate":"IS_PART_OF","object":{"id":70262098,"text":"pp1894 - 2025 - U.S. Geological Survey Integrated Water Availability Assessment—2010–20","indexId":"pp1894","publicationYear":"2025","noYear":false,"title":"U.S. Geological Survey Integrated Water Availability Assessment—2010–20"},"id":1}],"isPartOf":{"id":70262098,"text":"pp1894 - 2025 - U.S. Geological Survey Integrated Water Availability Assessment—2010–20","indexId":"pp1894","publicationYear":"2025","noYear":false,"title":"U.S. Geological Survey Integrated Water Availability Assessment—2010–20"},"lastModifiedDate":"2025-07-10T15:46:09.741772","indexId":"pp1894F","displayToPublicDate":"2025-01-15T14:08:51","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1894","chapter":"F","displayTitle":"Integrated Water Availability in the Conterminous United States, 2010–20","title":"Integrated water availability in the conterminous United States, 2010–20","docAbstract":"<p>Water availability is defined as the spatial and temporal distribution of water quantity and quality as it relates to the needs of humans and ecosystems. Broad assessment of water availability requires the consideration of multiple indicators because water users have different sensitivities to the degradation of water conditions. This chapter draws upon estimates of water supply, water use, and water quality to develop an integrated assessment of water availability in the conterminous United States (CONUS) for water years 2010–2020. The surface water-supply and use index (SUI) was used to express limitation arising from high water consumption in relation to water supply. Ecological stress was also assessed using indicators of ecologically detrimental flow alteration. Benchmarks of human and ecological health were used to assess water quality in relation to several key uses nationwide. In all, we find that 10 of 18 hydrologic regions have severe water stress in at least 1 indicator. Furthermore, it was common for regions to have high or severe stress in more than one indicator, which emphasizes that limitations often co-occur. For example, regions with high SUIs may also have an increased tendency to experience water quality degradation or ecologically detrimental flow alteration. Furthermore, we compared the spatial distribution of water availability against the Centers for Disease Control Social Vulnerability Index (SVI) to examine the relative distribution of socially vulnerable populations in relation to limitations on water availability. We found a tendency for an increasing segment of the population exposed to elevated SUI or water-quality degradation to be from socially vulnerable groups, as defined by SVI. This finding is similar to other studies that have noted greater water-availability limitations among socially vulnerable groups. By considering multiple indicators of water availability as a whole, greater insight into the distribution of limitations affecting water availability was gained and contributed to a more comprehensive assessment. </p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1894F","programNote":"Water Availability and Use Science Program and National Water Quality Program","usgsCitation":"Stets, E.G., Cashman, M.J., Miller, O.L., and Powlen, K.A., 2025, Integrated water availability in the conterminous United States, 2010–20, chap. 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Availability</li><li>Integrated Water Availability</li><li>Socioeconomic Limitations Affecting Water Availability</li><li>Future Water-Availability Considerations</li><li>Conclusions</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix 1. Methods Supporting the Integrated Water Availability Assessment</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-01-15","noUsgsAuthors":false,"publicationDate":"2025-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Stets, Edward G. 0000-0001-5375-0196 estets@usgs.gov","orcid":"https://orcid.org/0000-0001-5375-0196","contributorId":194490,"corporation":false,"usgs":true,"family":"Stets","given":"Edward","email":"estets@usgs.gov","middleInitial":"G.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":923065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":923066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Olivia L. 0000-0002-8846-7048","orcid":"https://orcid.org/0000-0002-8846-7048","contributorId":216556,"corporation":false,"usgs":true,"family":"Miller","given":"Olivia","email":"","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923067,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powlen, Kathryn 0000-0002-9685-0063","orcid":"https://orcid.org/0000-0002-9685-0063","contributorId":328833,"corporation":false,"usgs":true,"family":"Powlen","given":"Kathryn","email":"","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923068,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70262099,"text":"pp1894D - 2025 - Water use across the conterminous United States, water years 2010–20","interactions":[{"subject":{"id":70262099,"text":"pp1894D - 2025 - Water use across the conterminous United States, water years 2010–20","indexId":"pp1894D","publicationYear":"2025","noYear":false,"chapter":"D","displayTitle":"Water Use Across the Conterminous United States, Water Years 2010–20","title":"Water use across the conterminous United States, water years 2010–20"},"predicate":"IS_PART_OF","object":{"id":70262098,"text":"pp1894 - 2025 - U.S. Geological Survey Integrated Water Availability Assessment—2010–20","indexId":"pp1894","publicationYear":"2025","noYear":false,"title":"U.S. Geological Survey Integrated Water Availability Assessment—2010–20"},"id":1}],"isPartOf":{"id":70262098,"text":"pp1894 - 2025 - U.S. Geological Survey Integrated Water Availability Assessment—2010–20","indexId":"pp1894","publicationYear":"2025","noYear":false,"title":"U.S. Geological Survey Integrated Water Availability Assessment—2010–20"},"lastModifiedDate":"2025-11-18T17:37:33.623919","indexId":"pp1894D","displayToPublicDate":"2025-01-15T14:06:28","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1894","chapter":"D","displayTitle":"Water Use Across the Conterminous United States, Water Years 2010–20","title":"Water use across the conterminous United States, water years 2010–20","docAbstract":"<p>Withdrawals of water for human use are fundamental to the evaluation of the Nation’s water availability. This chapter provides an analysis of public supply, crop irrigation, and thermoelectric power water use for the conterminous United States (CONUS) during water years 2010–20. These three categories account for about 90 percent of water withdrawals in the Nation. The values presented here are based on modeling approaches that estimate water use at temporal (monthly) and spatial scales (12-digit hydrologic unit code—small watersheds sized 50–100 square kilometers) compatible for integration into a broader national assessment of water availability. Models also provide an understanding of factors that influence water use.</p><p>An estimated 244,817 million gallons per day (Mgal/d; 28,677 million cubic meters per month [Mm<sup>3</sup>/mo]) were withdrawn on average within the CONUS during water years 2010–20 from fresh water and saline water for crop irrigation, public supply, and thermoelectric power, with shares of 43, 14.5, and 42.5 percent for each of these categories, respectively. In the same period, estimated withdrawals and consumptive use (1) for public supply were 35,400 and 4,219 Mgal/d (4,081 and 486 Mm<sup>3</sup>/mo), respectively; (2) for crop irrigation were 105,497 and 75,698 Mgal/d (12,147 and 8,716 Mm<sup>3</sup>/mo), respectively; and (3) for thermoelectric power from fresh water were 82,656 and 2,904 Mgal/d (9,952 and 345 Mm<sup>3</sup>/mo), respectively.</p><p>Withdrawals for these categories of water use are highly spatially variable, with western States dominated by crop irrigation and eastern States dominated by thermoelectric-power water use. Public supply accounts for the largest percentage of water use in several heavily populated northeastern States. Reliance on groundwater compared to surface water depends on the availability of water sources and the type of water use. For public supply, withdrawals from groundwater are greater than withdrawals from surface water in the Western aggregated hydrologic regions, whereas the balance shifts to more surface water for the rest of the CONUS. In all aggregated hydrologic regions, the predominant source of water for crop irrigation is groundwater. Most thermoelectric power facilities in the eastern half of the CONUS use surface water from freshwater and saline sources; most thermoelectric power facilities in the western half of the CONUS use groundwater.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1894D","programNote":"Water Availability and Use Science Program and National Water Quality Program","usgsCitation":"Medalie, L., Galanter, A.E., Martinez, A.J., Archer, A.A., Luukkonen, C.L., Harris, M.A., and Haynes, J.V., 2025, Water use across the conterminous United States, water years 2010–20, chap. 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             -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/iwaas\" data-mce-href=\"https://www.usgs.gov/iwaas\">Integrated Water Availability Assessment</a><br>Water Resources Mission Area<br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, Virginia 20192</p><p><a href=\"mailto:National_IWAAs%40usgs.gov?subject=\" data-mce-href=\"mailto:National_IWAAs%40usgs.gov?subject=\">Contact Integrated Water Availability Assessment Team</a></p>","tableOfContents":"<ul><li>Preface</li><li>Abstract</li><li>Key Points</li><li>Introduction</li><li>Estimated Water Use by Category</li><li>Water Use Estimated Using Modeling Approaches</li><li>Other Water-Use Topics</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>References Cited</li><li>Glossary</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-01-15","noUsgsAuthors":false,"publicationDate":"2025-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Medalie, Laura 0000-0002-2440-2149","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":258234,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":205393,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martinez, Anthony J. 0000-0002-4295-0261","orcid":"https://orcid.org/0000-0002-4295-0261","contributorId":343462,"corporation":false,"usgs":true,"family":"Martinez","given":"Anthony J.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":923083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Archer, Althea A. 0000-0003-1927-0783","orcid":"https://orcid.org/0000-0003-1927-0783","contributorId":302489,"corporation":false,"usgs":true,"family":"Archer","given":"Althea","email":"","middleInitial":"A.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":923084,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Luukkonen, Carol L. 0000-0001-7056-8599","orcid":"https://orcid.org/0000-0001-7056-8599","contributorId":208181,"corporation":false,"usgs":true,"family":"Luukkonen","given":"Carol","email":"","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923085,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harris, Melissa A. 0000-0003-2659-9763 mharris@usgs.gov","orcid":"https://orcid.org/0000-0003-2659-9763","contributorId":1903,"corporation":false,"usgs":true,"family":"Harris","given":"Melissa","email":"mharris@usgs.gov","middleInitial":"A.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923086,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haynes, Jonathan V. 0000-0001-6530-6252 jhaynes@usgs.gov","orcid":"https://orcid.org/0000-0001-6530-6252","contributorId":3113,"corporation":false,"usgs":true,"family":"Haynes","given":"Jonathan","email":"jhaynes@usgs.gov","middleInitial":"V.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923087,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70262128,"text":"pp1894B - 2025 - Water supply in the conterminous United States, Alaska, Hawaii, and Puerto Rico, water years 2010–20","interactions":[{"subject":{"id":70262128,"text":"pp1894B - 2025 - Water supply in the conterminous United States, Alaska, Hawaii, and Puerto Rico, water years 2010–20","indexId":"pp1894B","publicationYear":"2025","noYear":false,"chapter":"B","displayTitle":"Water Supply in the Conterminous United States, Alaska, Hawaii, and Puerto Rico, Water Years 2010–20","title":"Water supply in the conterminous United States, Alaska, Hawaii, and Puerto Rico, water years 2010–20"},"predicate":"IS_PART_OF","object":{"id":70262098,"text":"pp1894 - 2025 - U.S. Geological Survey Integrated Water Availability Assessment—2010–20","indexId":"pp1894","publicationYear":"2025","noYear":false,"title":"U.S. Geological Survey Integrated Water Availability Assessment—2010–20"},"id":1}],"isPartOf":{"id":70262098,"text":"pp1894 - 2025 - U.S. Geological Survey Integrated Water Availability Assessment—2010–20","indexId":"pp1894","publicationYear":"2025","noYear":false,"title":"U.S. Geological Survey Integrated Water Availability Assessment—2010–20"},"lastModifiedDate":"2026-01-26T19:04:04.062257","indexId":"pp1894B","displayToPublicDate":"2025-01-15T14:03:48","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1894","chapter":"B","displayTitle":"Water Supply in the Conterminous United States, Alaska, Hawaii, and Puerto Rico, Water Years 2010–20","title":"Water supply in the conterminous United States, Alaska, Hawaii, and Puerto Rico, water years 2010–20","docAbstract":"<p>We present an assessment of water supply across the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico covering water years 2010–20. Our analysis drew on two national hydrologic models, the National Hydrologic Model Precipitation-Runoff Modeling System and the Weather Research and Forecasting model hydrologic modeling system. Both models produced estimates of streamflow, evapotranspiration, soil moisture, snow water equivalent, and other hydrologic states and fluxes. The models were driven by the bias-adjusted 4-kilometer-resolution, long-term regional hydroclimate simulation over the conterminous United States dataset (CONUS404). We assessed spatial and temporal error distributions by comparing monthly simulations at the 12-digit hydrologic unit code and regional scale from both models against external benchmarking datasets. Results showed that average annual rainfall across the CONUS was 857 millimeters per year for the period of analysis, with water year 2012 the driest year (729 millimeters) and water year 2019 the wettest year (995 millimeters). Key interannual variability results included the following: (1) the California–Nevada hydrologic region had the highest variability in precipitation and snow accumulation, and (2) the Texas hydrologic region was among hydrologic regions with the highest variability in precipitation. We related interannual variability in precipitation to storage volumes in soil moisture, snow water equivalent, and lakes and reservoirs to highlight areas with little storage and large year-to-year variability in precipitation. These areas included the Southern High Plains, Central High Plains, Texas, Souris–Red–Rainy, Mississippi Embayment, and Midwest regions. Our analysis of groundwater-level data showed that several of these areas overlap aquifers where groundwater levels were considerably lower than historical averages, including the Colorado Plateaus aquifers, the Rio Grande aquifer system, and the Central and Southern regions of the High Plains aquifer. Many of these lowered groundwater levels are continuations of decades-long declines from overpumping that started well before the assessment period. The resulting water budgets and their analyses provide a high-resolution foundational assessment of the mean state and variability of the terrestrial hydrologic cycle across the CONUS and Alaska, Hawaii, and Puerto Rico to support a wide range of water resource management applications.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1894B","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","programNote":"Water Availability and Use Science Program and National Water Quality Program","usgsCitation":"Gorski, G., Stets, E.G., Scholl, M.A., Degnan, J.R., Mullaney, J.R., Galanter, A.E., Martinez, A.J., Padilla, J., LaFontaine, J.H., Corson-Dosch, H.R., and Shapiro, A., 2025, Water supply in the conterminous United States, Alaska, Hawaii, and Puerto Rico, water years 2010–20 (ver. 1.2, July 2025), chap. 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of Water-Storage Components and Fluxes</li><li>Synthesis and Discussion of Water Budgets</li><li>Uncertainty of Simulated Results</li><li>Summary</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. Comparison of Individual Hydrologic Budget Components to External Datasets</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-01-15","revisedDate":"2025-07-30","noUsgsAuthors":false,"publicationDate":"2025-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Gorski, Galen 0000-0003-0083-4251","orcid":"https://orcid.org/0000-0003-0083-4251","contributorId":329714,"corporation":false,"usgs":true,"family":"Gorski","given":"Galen","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":923202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stets, Edward G. 0000-0001-5375-0196 estets@usgs.gov","orcid":"https://orcid.org/0000-0001-5375-0196","contributorId":194490,"corporation":false,"usgs":true,"family":"Stets","given":"Edward","email":"estets@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":923203,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":923204,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Degnan, James R. 0000-0002-5665-9010","orcid":"https://orcid.org/0000-0002-5665-9010","contributorId":218796,"corporation":false,"usgs":true,"family":"Degnan","given":"James R.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mullaney, John R. 0000-0003-4936-5046","orcid":"https://orcid.org/0000-0003-4936-5046","contributorId":203254,"corporation":false,"usgs":true,"family":"Mullaney","given":"John R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923206,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":205393,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923207,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Martinez, Anthony J. 0000-0002-4295-0261","orcid":"https://orcid.org/0000-0002-4295-0261","contributorId":343462,"corporation":false,"usgs":true,"family":"Martinez","given":"Anthony J.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":923208,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Padilla, Julie 0000-0002-3366-2938","orcid":"https://orcid.org/0000-0002-3366-2938","contributorId":343464,"corporation":false,"usgs":false,"family":"Padilla","given":"Julie","affiliations":[{"id":79206,"text":"Washington Department of Ecology","active":true,"usgs":false}],"preferred":false,"id":923209,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923210,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Corson-Dosch, Hayley R. 0000-0001-8695-1584","orcid":"https://orcid.org/0000-0001-8695-1584","contributorId":244707,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Hayley","middleInitial":"R.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":923211,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Shapiro, Allen 0000-0002-6425-9607","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":348204,"corporation":false,"usgs":false,"family":"Shapiro","given":"Allen","affiliations":[{"id":83323,"text":"The Catholic University of America","active":true,"usgs":false}],"preferred":false,"id":923212,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
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Because of its central importance, the U.S. Congress tasked the U.S. Geological Survey (USGS) and other Federal agencies with conducting regular, comprehensive assessments of water availability in the United States through the requirements under the SECURE Water Act. In response to this mandate, the USGS has developed the U.S. Geological Survey Integrated Water Availability Assessment—2010–20, which addresses aspects of water supply, quality, and use related to water availability in the United States. This is the first chapter of that report. The major climatic factors affecting water availability are also described. Multiple aspects of water availability are integrated to produce a more comprehensive analysis of water availability in the United States. This chapter enumerates the development, organization, and tools used in the USGS Integrated Water Availability Assessment. SECURE Water Act reports, developed by the Department of Energy Hydropower Climate Change Assessment and the Bureau of Reclamation West-Wide Climate and Hydrology Assessment, are also described. A distilled list of key findings from the overall report is also provided, serving as an introduction to each topic along with the most important high-level information.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1894A","programNote":"Water Availability and Use Science Program and National Water Quality Program","usgsCitation":"Stets, E.G., Archer, A.A., Degnan, J.R., Erickson, M.L., Gorski, G., Medalie, L., and Scholl, M.A., 2025, The National integrated water availability assessment, water years 2010–20, chap. 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49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/iwaas\" data-mce-href=\"https://www.usgs.gov/iwaas\">Integrated Water Availability Assessment</a><br>Water Resources Mission Area<br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, Virginia 20192</p><p><a href=\"mailto:National_IWAAs%40usgs.gov?subject=\" data-mce-href=\"mailto:National_IWAAs%40usgs.gov?subject=\">Contact Integrated Water Availability Assessment Team</a></p>","tableOfContents":"<ul><li>Preface</li><li>Abstract</li><li>Development of a National Water Availability Assessment</li><li>Regional Studies in Support of Integrated Water Availability Assessments at the National Scale</li><li>Organization of the Assessment Report</li><li>Spatial Resolution of Water Availability Analyses</li><li>Key Findings for the Status of Water Availability in the United States, Water Years 2010–20</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-01-15","noUsgsAuthors":false,"publicationDate":"2025-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Stets, Edward G. 0000-0001-5375-0196 estets@usgs.gov","orcid":"https://orcid.org/0000-0001-5375-0196","contributorId":194490,"corporation":false,"usgs":true,"family":"Stets","given":"Edward","email":"estets@usgs.gov","middleInitial":"G.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":923088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Archer, Althea A. 0000-0003-1927-0783","orcid":"https://orcid.org/0000-0003-1927-0783","contributorId":302489,"corporation":false,"usgs":true,"family":"Archer","given":"Althea","email":"","middleInitial":"A.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":923089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Degnan, James R. 0000-0002-5665-9010","orcid":"https://orcid.org/0000-0002-5665-9010","contributorId":218796,"corporation":false,"usgs":true,"family":"Degnan","given":"James R.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923090,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Melinda L. 0000-0002-1117-2866 merickso@usgs.gov","orcid":"https://orcid.org/0000-0002-1117-2866","contributorId":3671,"corporation":false,"usgs":true,"family":"Erickson","given":"Melinda L.","email":"merickso@usgs.gov","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923091,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gorski, Galen 0000-0003-0083-4251","orcid":"https://orcid.org/0000-0003-0083-4251","contributorId":329714,"corporation":false,"usgs":true,"family":"Gorski","given":"Galen","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":923092,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Medalie, Laura 0000-0002-2440-2149","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":258234,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923093,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":923094,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70262135,"text":"70262135 - 2025 - Endemic and invasive species: A history of distributional trends in the fish fauna of the lower New River drainage","interactions":[],"lastModifiedDate":"2025-01-15T17:02:19.54134","indexId":"70262135","displayToPublicDate":"2025-01-15T09:54:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Endemic and invasive species: A history of distributional trends in the fish fauna of the lower New River drainage","docAbstract":"<p><span>Invasive species are often central to conservation efforts, particularly when concerns involve potential impacts on rare, endemic native species. The lower New River drainage of the eastern United States is a watershed that warrants conservation assessment, as the system is naturally depauperate of native fish species and it is nearly saturated with non-native fish species: there are 31 natives, including at least nine endemic taxa, and 63 non-natives. For endemic taxa, we examined temporal distribution shifts (range expansions or contractions) based on percent change in the occupied watershed area. We contrasted these findings with time series analyses on distribution trends of non-native minnows (Leuciscidae) and darters (Percidae) based on growth curve models of the cumulative sum of the total area of occupied 12-digit hydrologic unit codes. We documented range reductions for six of nine endemic taxa. We determined that 11 of 18 non-native minnows and 6 of 8 non-native darters were invasive based on range expansions and associated invasion curve models. The endemic taxa are of conservation concern given the limited distribution ranges and documented population declines. Although among-species comparisons of range shifts do not support causal inference, documentation of changes in distribution ranges of endemic and invasive species is critical to inform conservation efforts.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/w17020221","usgsCitation":"Welsh, S.A., Cincotta, D., Owens, N., and Stauffer, J.R., 2025, Endemic and invasive species: A history of distributional trends in the fish fauna of the lower New River drainage: Water, v. 17, no. 2, 221, 23 p., https://doi.org/10.3390/w17020221.","productDescription":"221, 23 p.","ipdsId":"IP-173053","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466652,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w17020221","text":"Publisher Index Page"},{"id":466432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina, Tennessee, Virginia, West Virginia","otherGeospatial":"New River drainage","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -82.06585576020927,\n              38.59746796567387\n            ],\n            [\n              -82.06585576020927,\n              35.986473012540856\n            ],\n            [\n              -80.05188055833794,\n              35.986473012540856\n            ],\n            [\n              -80.05188055833794,\n              38.59746796567387\n            ],\n            [\n              -82.06585576020927,\n              38.59746796567387\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"17","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-01-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Welsh, Stuart A. 0000-0003-0362-054X","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":217037,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"","middleInitial":"A.","affiliations":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":923241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cincotta, Daniel A.","contributorId":273118,"corporation":false,"usgs":false,"family":"Cincotta","given":"Daniel A.","affiliations":[{"id":56173,"text":"West Virginia DNR","active":true,"usgs":false}],"preferred":false,"id":923242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Owens, Nathaniel V.","contributorId":348205,"corporation":false,"usgs":false,"family":"Owens","given":"Nathaniel V.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":923243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stauffer, Jay R. Jr.","contributorId":119700,"corporation":false,"usgs":false,"family":"Stauffer","given":"Jay","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":923244,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70262233,"text":"70262233 - 2025 - Enhanced hydrologic monitoring and characterization of groundwater drainage features","interactions":[],"lastModifiedDate":"2025-01-27T16:47:24.222862","indexId":"70262233","displayToPublicDate":"2025-01-14T11:17:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17124,"text":"Nature Water","active":true,"publicationSubtype":{"id":10}},"title":"Enhanced hydrologic monitoring and characterization of groundwater drainage features","docAbstract":"<p><span>Groundwater drains to the land surface, generating the baseflow of streams, lakes, and wetlands. The hydrologic resilience of baseflow during prolonged dry periods and after disturbance can be assessed with evolving remote sensing analysis paired with localized monitoring of groundwater drainage features and creative model calibration strategies.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s44221-024-00376-6","usgsCitation":"Briggs, M., 2025, Enhanced hydrologic monitoring and characterization of groundwater drainage features: Nature Water, v. 3, p. 2-3, https://doi.org/10.1038/s44221-024-00376-6.","productDescription":"2 p.","startPage":"2","endPage":"3","ipdsId":"IP-172738","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":466645,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2025-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222759,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":923616,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70262124,"text":"70262124 - 2025 - Local water use and climate drive water stress over the conterminous United States with substantial impacts to fish species of conservation concern","interactions":[],"lastModifiedDate":"2025-01-14T15:12:43.565065","indexId":"70262124","displayToPublicDate":"2025-01-11T09:04:15","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19891,"text":"ESS Open Archive","active":true,"publicationSubtype":{"id":32}},"title":"Local water use and climate drive water stress over the conterminous United States with substantial impacts to fish species of conservation concern","docAbstract":"<p><span>There is a growing need for consistent, large-scale estimates of water availability to identify and avoid potential conflicts among human and ecosystem uses of water. We present an assessment of water limitation, defined as the monthly balance (difference) between water supply (</span><i>ws</i><span>) and human consumptive water use (</span><i>wc</i><span>), for the conterminous United States (CONUS) during water years 2010–2020.&nbsp; We estimate that 26.7 million Americans, 8% of CONUS population, live in areas with chronic high or severe water limitation. Although&nbsp;</span><i>ws</i><span>&nbsp;greatly exceeds&nbsp;</span><i>wc</i><span>&nbsp;at the CONUS scale, water is limited locally or regionally due to spatial and temporal patterns in climate and&nbsp;</span><i>wc</i><span>. Our water limitation metric, the monthly supply and use index (SUI), peaked in 2012 during a widespread drought when 38% of the CONUS land area experienced elevated water stress.&nbsp; The central and southwestern U.S. experienced the highest SUI due to the combination of low&nbsp;</span><i>ws</i><span>&nbsp;and high&nbsp;</span><i>wc</i><span>, especially for crop irrigation. Spatial overlays of SUI and habitat ranges for fish species, including those of conservation concern, revealed that several species had notable proportions of their habitat exposed to high or severe water limitation during spawning season over the modeled time period, especially the Arkansas River shiner. Water supply (</span><i>ws</i><span>) was calculated from two CONUS, physically based, hydrologic models while&nbsp;</span><i>wc</i><span>&nbsp;was calculated from three CONUS models of water use for crop irrigation, thermoelectric power generation, and public supply.&nbsp; The&nbsp;</span><i>ws</i><span>&nbsp;and&nbsp;</span><i>wc</i><span>&nbsp;values were routed through a stream network and used to calculate water limitation for human populations and fish species at the scale of 12-digit hydrologic unit codes (HUC12s, 50-100 km</span><sup>2</sup><span>&nbsp;catchments) and then analyzed using SUI.&nbsp; Evaluation of water availability at higher spatial and temporal resolution promotes more comprehensive analyses of the drivers of water availability and can be combined with complementary studies of water quality and water limiting thresholds to better understand the limitations on water availability.</span></p>","language":"English","publisher":"ESS Open Archive","doi":"10.22541/essoar.173655431.12049152/v1","usgsCitation":"Stets, E.G., Miller, O.L., Cashman, M.J., Powlen, K., Martinez, A., Archer, A.A., and Padilla, J., 2025, Local water use and climate drive water stress over the conterminous United States with substantial impacts to fish species of conservation concern: ESS Open Archive, https://doi.org/10.22541/essoar.173655431.12049152/v1.","productDescription":"29  p.","ipdsId":"IP-171942","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":466656,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.22541/essoar.173655431.12049152/v1","text":"External Repository"},{"id":466211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n 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