Managing water resources in semiarid watersheds is challenging due to limited supply and uncertain future climate conditions. This paper examines the impact of future climate changes on an urban watershed in southern California using an integrated hydrologic model. GSFLOW modeling software is used to simulate the nonlinear relationships between climate trends and precipitation partitioning into ET, runoff, and subsurface storage. Four global circulation models (GCMs), each with two greenhouse-gas scenarios, RCP45 and RCP85 are used to project future climate conditions. GCMs include the CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 models. The model's simulated hydrologic conditions are compared with historical data to assess changes in water budgets and groundwater supply. Results indicate decreased groundwater storage in most scenarios due to increased natural evapotranspiration, vegetation consumptive use, and streamflow out of the watershed. Only scenarios with substantially increased future precipitation show increased groundwater storage. The study also highlights increased future aridity despite the rise in precipitation and large precipitation events forecast by GCMs, which increase the risk of urban floods and decrease stream leakage and water available to vegetation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2025.102461","usgsCitation":"Ryter, D.W., Alzraiee, A.H., and Niswonger, R., 2025, Simulation of the impacts of projected climate change on groundwater resources in the urban, semiarid Yucaipa Valley watershed, southern California using an integrated hydrologic model: Journal of Hydrology, Regional Studies, v. 60, 102461, 16 p., https://doi.org/10.1016/j.ejrh.2025.102461.","productDescription":"102461, 16 p.","ipdsId":"IP-153865","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":493789,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2025.102461","text":"Publisher Index Page"},{"id":493644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yucaipa Valley watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.09271702186436,\n 34.0874203948469\n ],\n [\n -117.09271702186436,\n 33.9725594754417\n ],\n [\n -116.9002906646693,\n 33.9725594754417\n ],\n [\n -116.9002906646693,\n 34.0874203948469\n ],\n [\n -117.09271702186436,\n 34.0874203948469\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ryter, Derek W. 0000-0002-2488-626X dryter@usgs.gov","orcid":"https://orcid.org/0000-0002-2488-626X","contributorId":3395,"corporation":false,"usgs":true,"family":"Ryter","given":"Derek","email":"dryter@usgs.gov","middleInitial":"W.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alzraiee, Ayman H. 0000-0001-7576-3449","orcid":"https://orcid.org/0000-0001-7576-3449","contributorId":272120,"corporation":false,"usgs":true,"family":"Alzraiee","given":"Ayman","email":"","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":944910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niswonger, Richard G. rniswon@usgs.gov","contributorId":146547,"corporation":false,"usgs":false,"family":"Niswonger","given":"Richard G.","email":"rniswon@usgs.gov","affiliations":[],"preferred":false,"id":944911,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70267395,"text":"sir20245130 - 2025 - Estimating the magnitude and frequency of floods at ungaged locations on streams in Tennessee through the 2013 water year","interactions":[],"lastModifiedDate":"2025-05-29T15:06:41.309366","indexId":"sir20245130","displayToPublicDate":"2025-05-29T08:00:00","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":"2024-5130","displayTitle":"Estimating the Magnitude and Frequency of Floods at Ungaged Locations on Streams in Tennessee Through the 2013 Water Year","title":"Estimating the magnitude and frequency of floods at ungaged locations on streams in Tennessee through the 2013 water year","docAbstract":"To improve estimates of the frequency of annual peak flows for ungaged locations on non-urban, unregulated streams in Tennessee, generalized least-squares multiple linear-regression techniques were used to relate annual peak flows from streamgages operated by the U.S. Geological Survey to physical, climatic, and land-use characteristics of their drainage basins. Geospatial data acquired since the previous study in 2003, annual peak-streamflow data through the 2013 water year, and Bulletin 17C methods for frequency analysis of annual peak-streamflow data were used in the study. Generalized least-squares regression equations were developed for four hydrologic areas with distinct hydrologic, geologic, and topographic characteristics. Drainage area was used as an explanatory variable in equations developed for each hydrologic area. In addition to drainage area, a 2-year recurrence-interval climate factor was used for hydrologic area 1, a 10–85 channel slope was used for hydrologic area 2, and percent imperviousness was used for hydrologic area 4. The regression equations can be used to estimate annual exceedance probability streamflows for ungaged locations on non-urban, unregulated streams in Tennessee. The term “unregulated” indicates that streamflow is not appreciably influenced by regulation from reservoirs or other impoundments. Average standard errors of prediction for the regression equations ranged from 44.4 to 51.4 percent for hydrologic area 1; 30.4 to 42.9 percent for hydrologic area 2; 35.7 to 42.6 percent for hydrologic area 3; and 32.5 to 47.4 percent for hydrologic area 4.
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Contact Us- USGS Publications Warehouse
","tableOfContents":"Wildfires often occur in mountainous terrain, regions that pose substantial challenges to operational meteorological and hydrologic observing networks.
A mobile, post-fire hydrometeorological observatory comprising remote-sensing and in situ instrumentation was developed and deployed in a burnt area to provide unique insights into rainfall-induced post-fire hazards.
Mobile radar-based rainfall estimates were produced throughout the burn area at 75-m resolution and compared with rain gauge accumulations and basin response variables.
The mobile radar was capable of resolving details in intra-basin rain fields as well as detecting storms approaching the burn area with accuracy equivalent to rain gauges. Runoff responses were complex and dependent on spatiotemporal patterns and magnitude of rainfall intensity over the burn area.
The complement of the mobile radar with the near-field, non-contact instruments measuring the hydrologic response provided valuable information in regions that are difficult to access and are not routinely monitored by conventional observing networks.
Post-fire observatories equipped with mobile radars deployed on burn areas provide real-time data, early alerting capabilities and visualizations to potentially guide impact-based decision support for local authorities.
Montane meadows provide vital habitat that supports ecosystems, regulate hydrological processes, and offer valuable recreational opportunities. Meadows account for 3 % of Yosemite National Park's area, including Yosemite Valley, and are particularly susceptible to human impacts such as formation of informal trails. We collected observational data on visitor activity and quantified social trail disturbance to compare with resource monitoring datasets and through similar parameters to Walden-Schreiner and Leung (2013) who studied visitor use and behavior in three Yosemite Valley meadows in 2011. We documented change in number of visitors per hour and primary activity pursued. We also compared trends of meadow disturbance (informal trail length and disturbed area) from the early 2000s - 2023. Informal trail length at El Capitan Meadow decreased from 2004 to 2018, followed by recent increases. Disturbed area for Cooks A, Sentinel A, Slaughterhouse B, Stoneman A, and Stoneman B sub-meadows increased from 2006 to 2023. Between 2011 and 2023, the proportion of those engaged in active versus stationary pursuits showed that visitors engaged in more active pursuits in two of three meadows. Moreover, there were >3.5 times more visitors per hour in Cooks, El Capitan, and Leidig meadows in 2023 compared to 2011, yet, most visitors utilized designated trails. Meadow locational context was linked to activity preference and types of impacts. Management strategies, such as fencing and signage have been effective at minimizing impacts in several meadows. Parsing nuances of informal trail use and drivers of disturbance for various meadows is crucial for informed park management decisions and actions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jort.2025.100896","usgsCitation":"Shiflett, S., Jenkins, J., Mattos, R., Thiry, K., Ibsen, P.C., Booher, M., Tricomi, A., and Athearn, N.D., 2025, Monitoring visitor activity and informal trail disturbance in Yosemite Valley meadows to assess temporal changes in use and impacts: Journal of Outdoor Recreation and Tourism, v. 50, 100896, 13 p., https://doi.org/10.1016/j.jort.2025.100896.","productDescription":"100896, 13 p.","ipdsId":"IP-172211","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":490667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jort.2025.100896","text":"Publisher Index Page"},{"id":489476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.73284138722612,\n 37.993305694720945\n ],\n [\n -119.73284138722612,\n 37.66294383877451\n ],\n [\n -119.39779065426013,\n 37.66294383877451\n ],\n [\n -119.39779065426013,\n 37.993305694720945\n ],\n [\n -119.73284138722612,\n 37.993305694720945\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shiflett, Sheri A.","contributorId":347753,"corporation":false,"usgs":false,"family":"Shiflett","given":"Sheri A.","affiliations":[{"id":39509,"text":"National Park Service, Yosemite National Park","active":true,"usgs":false}],"preferred":false,"id":938991,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Jeffery S.","contributorId":347754,"corporation":false,"usgs":false,"family":"Jenkins","given":"Jeffery S.","affiliations":[{"id":38695,"text":"University of California Merced","active":true,"usgs":false}],"preferred":false,"id":938992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mattos, Rachel F.","contributorId":347755,"corporation":false,"usgs":false,"family":"Mattos","given":"Rachel F.","affiliations":[{"id":39509,"text":"National Park Service, Yosemite National Park","active":true,"usgs":false}],"preferred":false,"id":938993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thiry, Kai","contributorId":356273,"corporation":false,"usgs":false,"family":"Thiry","given":"Kai","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":938995,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Booher, Melissa","contributorId":356275,"corporation":false,"usgs":false,"family":"Booher","given":"Melissa","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938996,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tricomi, Angela","contributorId":356276,"corporation":false,"usgs":false,"family":"Tricomi","given":"Angela","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":938997,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Athearn, Nicole D","contributorId":221011,"corporation":false,"usgs":false,"family":"Athearn","given":"Nicole","email":"","middleInitial":"D","affiliations":[{"id":40310,"text":"NPS, Yosemite National Park, CA","active":true,"usgs":false}],"preferred":false,"id":938998,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70266892,"text":"sir20255032 - 2025 - Flood-inundation maps for 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, 2023","interactions":[],"lastModifiedDate":"2025-08-07T21:16:38.983416","indexId":"sir20255032","displayToPublicDate":"2025-05-21T08:56:33","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":"2025-5032","displayTitle":"Flood-Inundation Maps for 14.8 Miles of Little and Big Papillion Creeks in Omaha, Nebraska, 2023","title":"Flood-inundation maps for 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, 2023","docAbstract":"Digital flood-inundation map libraries for two reaches that constitute 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, were created by the U.S. Geological Survey (USGS) in cooperation with the Papio-Missouri River Natural Resource District. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at Little Papillion Creek at Irvington, Nebr. (USGS station 06610750), Little Papillion Creek at Ak-Sar-Ben at Omaha, Nebr. (USGS station 06610765), and Big Papillion Creek at Q Street at Omaha, Nebr. (USGS station 06610770) streamgages. Near-real-time stages at these streamgages may be obtained from the USGS National Water Information System database at https://doi.org/10.5066/F7P55KJN or from the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/.
Flood profiles were computed for two different reaches that constitute 14.8 miles of stream length in the study area by using hydraulic models. The models were calibrated by adjusting roughness coefficients to best represent the current (2022) stage-streamflow relation at the streamgages within the study reach.
The hydraulic models were then used to compute water-surface profiles at 1-foot stage intervals for selected stage ranges to represent various flooding scenarios at the streamgages in each reach. The simulated water-surface profiles then were combined with a digital elevation model using a geographic information system, which had a 10-foot grid spacing to delineate the flooding extents and water depths for each stage. The availability of these flood-inundation maps, along with information regarding current stage from the USGS streamgages, can provide emergency management personnel and residents with information that is critical for flood response activities and post flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255032","collaboration":"Prepared in cooperation with the Papio-Missouri River Natural Resource District","usgsCitation":"Strauch, K.R., and Hoefer, B.R., 2025, Flood-inundation maps for 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, 2023: U.S. Geological Survey Scientific Investigations Report 2025–5032, 14 p., https://doi.org/10.3133/sir20255032.","productDescription":"Report: vi, 14 p.; Data Release; Dataset","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-152753","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":493771,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118579.htm","linkFileType":{"id":5,"text":"html"}},{"id":485915,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5032/coverthb.jpg"},{"id":485916,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5032/sir20255032.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5032"},{"id":485920,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5032/sir20255032.XML"},{"id":485921,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5032/images/"},{"id":485922,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":485923,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OU7E42","text":"USGS data release","linkHelpText":"Flood-inundation geospatial datasets for 14.8 miles of the Little and Big Papillion Creeks in Omaha, Nebraska, 2023"},{"id":485924,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255032/full"}],"country":"United States","state":"Nebraska","city":"Omaha","otherGeospatial":"Little and Big Papillion Creeks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.15305796306968,\n 41.36725587936067\n ],\n [\n -96.15305796306968,\n 41.117996650104345\n ],\n [\n -95.92667071234595,\n 41.117996650104345\n ],\n [\n -95.92667071234595,\n 41.36725587936067\n ],\n [\n -96.15305796306968,\n 41.36725587936067\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Standard flood-frequency analysis methods rely on an assumption of stationarity, but because of growing understanding of climatic persistence and concern regarding the effects of climate change, the need for methods to detect and model nonstationary flood frequency has become widely recognized. In this study, a regional statistical method for estimating the effects of climate variations on annual maximum (peak) flows that allows for the effect to vary by quantile is presented and applied. The method uses a panel–quantile regression framework based on a location-scale model with two fixed effects per basin. The model was fitted to 330 selected gauged basins in the midwestern United States, filtered to remove basins affected by reservoir regulation and urbanization. Precipitation and discharge simulated using a water-balance model at daily and annual time scales were tested as climate variables. Annual maximum daily discharge was found to be the best predictor of peak flows, and the quantile regression coefficients were found to depend monotonically on annual exceedance probability. Application of the models to gauged basins is demonstrated by estimating the peak-flow distributions at the end of the study period (2018) and, using the panel model, to the study basins as-if-ungauged by using leave-one-out cross validation, estimating the fixed effects using static basin characteristics, and parameterizing the water-balance model discharge using median parameters. The errors of the quantiles predicted as-if-ungauged approximately doubled compared to the errors of the fitted panel model.
","language":"English","publisher":"MDPI","doi":"10.3390/hydrology12050119","usgsCitation":"Over, T.M., Marti, M.K., and Podzorski, H.L., 2025, Regional analysis of the dependence of peak-flow quantiles on climate with application to adjustment to climate trends: Hydrology, v. 12, no. 5, 119, 43 p., https://doi.org/10.3390/hydrology12050119.","productDescription":"119, 43 p.","ipdsId":"IP-167316","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":487957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/hydrology12050119","text":"Publisher Index Page"},{"id":486509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Over, Thomas M. 0000-0001-8280-4368","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":204650,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":938195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marti, Mackenzie K. 0000-0001-8817-4969 mmarti@usgs.gov","orcid":"https://orcid.org/0000-0001-8817-4969","contributorId":289738,"corporation":false,"usgs":true,"family":"Marti","given":"Mackenzie","email":"mmarti@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":938196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Podzorski, Hannah Lee 0000-0001-5204-2606 hpodzorski@usgs.gov","orcid":"https://orcid.org/0000-0001-5204-2606","contributorId":333626,"corporation":false,"usgs":true,"family":"Podzorski","given":"Hannah","email":"hpodzorski@usgs.gov","middleInitial":"Lee","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":938197,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70267387,"text":"70267387 - 2025 - Linking permafrost to the abundance, biomass, and energy density of fish in Arctic headwater streams","interactions":[],"lastModifiedDate":"2025-05-21T14:10:33.157869","indexId":"70267387","displayToPublicDate":"2025-05-13T08:59:33","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Linking permafrost to the abundance, biomass, and energy density of fish in Arctic headwater streams","docAbstract":"Permafrost thaw alters groundwater flow, river hydrology, stream-catchment interactions, and the availability of carbon and nutrients in headwater streams. The impact of permafrost on watershed hydrology and biogeochemistry of headwater streams has been demonstrated, but there is little understanding of how permafrost influences fish in these ecosystems. We examined relations among permafrost characteristics, the resulting changes in water temperature, stream hydrology (e.g., discharge flashiness), and macroinvertebrates, with the abundance, biomass, and energy density of juvenile Dolly Varden (Salvelinus malma) and Arctic Grayling (Thymallus arcticus) across 10 headwater streams in northwestern Alaska. Macroinvertebrate density was driven by concentrations of dissolved carbon and nutrients supporting stream food webs. Dolly Varden abundance was primarily related to water temperature with fewer fish in warmer streams, whereas Dolly Varden energy density decreased with the flashiness of the headwater streams. Dolly Varden biomass was related to both temperature and bottom-up food web effects. The energy density of Arctic Grayling decreased with warmer temperatures and discharge flashiness. These relations demonstrate the importance of terrestrial–aquatic connections in permafrost landscapes and indicate the complexity of landscape effects on fish. Because permafrost thaw is one of the most impactful changes occurring as the Arctic warms, an improved understanding of how stream temperature, hydrology, and bottom-up food web processes influence fish populations can aid forecasting of future conditions across the Arctic.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70270","usgsCitation":"Carey, M.P., Koch, J.C., O’Donnell, J.A., Poulin, B., and Zimmerman, C.E., 2025, Linking permafrost to the abundance, biomass, and energy density of fish in Arctic headwater streams: Ecosphere, v. 16, no. 5, e70270, 20 p., https://doi.org/10.1002/ecs2.70270.","productDescription":"e70270, 20 p.","ipdsId":"IP-168519","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":486925,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70270","text":"Publisher Index Page"},{"id":486281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Noatak National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -164,\n 69\n ],\n [\n -164,\n 66.7\n ],\n [\n -156,\n 66.7\n ],\n [\n -156,\n 69\n ],\n [\n -164,\n 69\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":938061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":938062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Jonathan A. 0000-0001-7031-9808","orcid":"https://orcid.org/0000-0001-7031-9808","contributorId":191423,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":938063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poulin, Brett 0000-0002-5555-7733","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":260893,"corporation":false,"usgs":false,"family":"Poulin","given":"Brett","affiliations":[{"id":52706,"text":"Department of Environmental Toxicology, University of California Davis, Davis, CA 95616, USA","active":true,"usgs":false}],"preferred":false,"id":938064,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":938065,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266760,"text":"sir20245133 - 2025 - Using the D-Claw software package to model lahars in the Middle Fork Nooksack River drainage and beyond, Mount Baker, Washington","interactions":[],"lastModifiedDate":"2025-07-03T14:16:54.133347","indexId":"sir20245133","displayToPublicDate":"2025-05-12T15:08:17","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":"2024-5133","displayTitle":"Using the D-Claw Software Package to Model Lahars in the Middle Fork Nooksack River Drainage and Beyond, Mount Baker, Washington","title":"Using the D-Claw software package to model lahars in the Middle Fork Nooksack River drainage and beyond, Mount Baker, Washington","docAbstract":"Lahars, or volcanic mudflows, are the most hazardous eruption-related phenomena that will affect communities living along rivers that originate on Mount Baker. In the past 15,000 years, the largest lahars from Mount Baker have affected the Middle Fork Nooksack River drainage and beyond. Here we use the physics-based D-Claw software package to model nine lahar scenarios that are initiated as water-saturated landslides between Sherman Crater and the Roman Wall on the Mount Baker edifice and flow down the Middle Fork Nooksack River. The scenarios range in volume from 1 to 260 million cubic meters and have an initial hydraulic permeability from 10−12 to 10−10 meters squared. Model output includes data such as flow depth, velocity, runout distance, area inundated, arrival time, and sediment concentration as well as information that allows scientists to calculate other important hydrologic characteristics such as lahar discharge. These data are important to officials who have the responsibility to plan for, or take mitigation measures against, future Mount Baker lahars. To check the validity of the D-Claw results, we compare the scenarios to known geologic information. We also compare D-Claw results with empirical models that have been used in the past to determine potential inundation areas, runout distances, and arrival times. These comparisons highlight similarities and differences between empirical and physics-based models. We also present D-Claw scenario-based animations to help scientists, officials, and lay people alike to visualize how future lahars could affect communities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245133","usgsCitation":"Gardner, C.A., Benage, M.C., Cannon, C., and George, D.L., 2025, Using the D-Claw software package to model lahars in the Middle Fork Nooksack River drainage and beyond, Mount Baker, Washington: U.S. Geological Survey Scientific Investigations Report 2024–5133, 47 p., https://doi.org/10.3133/sir20245133.","productDescription":"Report: vii, 47 p.; 9 Animation Videos; Data Release","numberOfPages":"47","ipdsId":"IP-151680","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":485743,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioC2.mp4","text":"Appendix 4 - Scenario C2","size":"35.9 MB","description":"Scenario C2","linkHelpText":"- Scenario C2"},{"id":485742,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioB3.mp4","text":"Appendix 4 - Scenario B3","size":"47 MB","description":"Scenario B3","linkHelpText":"- Scenario B3"},{"id":485741,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioB2.mp4","text":"Appendix 4 - Scenario B2","size":"37.6 MB","description":"Scenario B2","linkHelpText":"- Scenario B2"},{"id":485740,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioB1.mp4","text":"Appendix 4 - Scenario B1","size":"25.6 MB","description":"Scenario B1","linkHelpText":"- Scenario B1"},{"id":485739,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioA3.mp4","text":"Appendix 4 - Scenario A3","size":"50.4 MB","description":"Scenario A3","linkHelpText":"- Scenario A3"},{"id":485737,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioA1.mp4","text":"Appendix 4 - Scenario A1","size":"35.4 MB","description":"Scenario A1","linkHelpText":"- Scenario A1"},{"id":485736,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1PEX7FS","text":"USGS data release","description":"George, D.L., Cannon, C.M., Benage, M.C., and Gardner, C.A., 2025, Simulated lahar extents and dynamics in the Middle Fork Nooksack River drainage, resulting from hypothetical landslide sources on the western summit of Mount Baker, Washington: U.S. Geological Survey data release, https://doi.org/10.5066/P1PEX7FS.","linkHelpText":"Simulated lahar extents and dynamics in the Middle Fork Nooksack River drainage, resulting from hypothetical landslide sources on the western summit of Mount Baker, Washington"},{"id":485734,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5133/images"},{"id":485733,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133.XML","description":"SIR 2024-5133 XML"},{"id":485731,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5133 PDF"},{"id":485730,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5133/coverthb.jpg"},{"id":485745,"rank":15,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioE2.mp4","text":"Appendix 4 - Scenario E2","size":"22.1 MB","description":"Scenario E2","linkHelpText":"- Scenario E2"},{"id":485744,"rank":14,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioD2.mp4","text":"Appendix 4 - Scenario D2","size":"26.5 MB","description":"Scenario D2","linkHelpText":"- Scenario D2"},{"id":485732,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245133/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5133 HTML"},{"id":485738,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioA2.mp4","text":"Appendix 4 - Scenario A2","size":"41.7 MB","description":"Scenario A2","linkHelpText":"- Scenario A2"},{"id":485848,"rank":16,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118573.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Middle Fork Nooksack River, Mount Baker","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.667,\n 49\n ],\n [\n -122.667,\n 49\n ],\n [\n -122.667,\n 48.6667\n ],\n [\n -121.667,\n 48.6667\n ],\n [\n -121.667,\n 49\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"David A. Johnston Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Building 10, Suite 100
Vancouver, WA 98683
Email: askCVO@usgs.gov
","tableOfContents":"Managing species in a rapidly changing climate requires knowledge of how species will respond to climate change and other threats while simultaneously developing management actions to reduce threats. Amphibians are one of the most threatened taxa on earth and often serve as the ‘canary in the coalmine’ for the health of ecosystems that countless other species and humans rely on. To understand the status of and guide management for the boreal toad (Anaxyrus boreas boreas), an imperiled amphibian species in the North Central region, we coproduced several products with the Boreal Toad Conservation Team. These products included 1) reconstructed seasonal hydrology patterns for historical boreal toad breeding wetlands and high elevation watersheds in the Southern Rocky Mountain Region (SRMR) from remotely sensed data, 2) current and future predictions of drying rates for historical breeding wetlands, 3) current and future predictions on the status of the boreal toad in the SRMR, and 4) a web tool to guide management actions. While the boreal toad is considered a ‘data rich’ species given data collection efforts that span multiple decades, many amphibian species are considered ‘data poor’, meaning managers lack data on the biology, ecology, or status of the species needed to make sound decisions. To address this knowledge gap, we also quantified drying patterns across watersheds for two ‘data poor’ species in the North Central region at risk from climate change: the Great Basin spadefoot toad (Spea intermontana) and the wood frog (Lithobates sylvaticus). These new data can guide management decisions for these species by allowing managers to understand habitat changes with respect to water availability, a crucial element for amphibian survival and persistence. Together, these products demonstrate how cutting-edge technology and analytical methods can produce a range of useful information to support amphibian conservation.
","language":"English","publisher":"Nrrth Central Climate Adaptation Center","usgsCitation":"Kissel, A.M., Muths, E., Lacey, M., Popescu, V.D., Dyck, M., and Littlefield, C., 2025, A framework for guiding management decisions for amphibians in an uncertain future, 56 p.","productDescription":"56 p.","ipdsId":"IP-174467","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":486563,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f83509de4b0e84f60868124/6009c26fd34e162231fb2333","linkFileType":{"id":5,"text":"html"}},{"id":501210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico, Wyoming","otherGeospatial":"southern Rocky Mountain region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108,\n 41.25\n ],\n [\n -108,\n 36.5\n ],\n [\n -105,\n 36.5\n ],\n [\n -105,\n 41.25\n ],\n [\n -108,\n 41.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kissel, Amanda Marie 0000-0002-6346-7455","orcid":"https://orcid.org/0000-0002-6346-7455","contributorId":334356,"corporation":false,"usgs":true,"family":"Kissel","given":"Amanda","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":938369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245922,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":938370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lacey, Mae","contributorId":355913,"corporation":false,"usgs":false,"family":"Lacey","given":"Mae","affiliations":[{"id":13470,"text":"Conservation Science Partners","active":true,"usgs":false}],"preferred":false,"id":938371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Popescu, Viorel D.","contributorId":169697,"corporation":false,"usgs":false,"family":"Popescu","given":"Viorel","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":938372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dyck, Marissa","contributorId":355915,"corporation":false,"usgs":false,"family":"Dyck","given":"Marissa","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":938373,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Littlefield, Caitlin","contributorId":352216,"corporation":false,"usgs":false,"family":"Littlefield","given":"Caitlin","affiliations":[],"preferred":false,"id":938374,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267494,"text":"70267494 - 2025 - Small waterbodies of large conservation concern: Towards an integrated approach to more accurately measuring surface water dynamics","interactions":[],"lastModifiedDate":"2025-05-27T14:15:43.711544","indexId":"70267494","displayToPublicDate":"2025-05-09T09:04:33","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Small waterbodies of large conservation concern: Towards an integrated approach to more accurately measuring surface water dynamics","docAbstract":"Millions of small waterbodies are dispersed throughout the middle of the North American continent, and billions of dollars have been invested to conserve, restore, and manage these waterbodies in the 20th and 21st centuries. Small waterbody conservation has been supported by different stakeholders aiming at improving water quality, enhancing floodwater storage, and supporting migratory bird breeding habitat. Conservation agencies are using hydrological and biological monitoring, modeling, and mapping to adaptively manage small waterbodies in the face of stressors such as invasive species and climate change. As remote sensing estimates of small waterbody surface water extent have become easier to access, understanding the capabilities and limitations of using remote sensing, especially in areas lacking surface water monitoring, is important for conservation decision making. Here, we used in situ monitoring and process-based hydrological modeling to explore remote sensing accuracy, especially related to waterbody size, emergent aquatic vegetation cover, and climatic conditions. Overall, we found that the accuracy of satellite and aerial imagery surface water mapping approaches vastly decreased for waterbodies smaller than 2 ha. We also found emergent vegetation could be masking surface water in waterbodies larger than 2 ha and that accuracy of some remote sensing estimates may decrease during wetter climatic periods. These results indicate that sensors commonly used for surface water applications alone may not be able to accurately detect small waterbody surface water, which supports the need for combining monitoring and modeling to understand how small waterbodies may respond to future changes in climate and land use.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.113525","usgsCitation":"McKenna, O.P., Lothspeich, A., Vacek, S., MacDonald, D., Eash, J., Vanderhoof, M.K., McCulloch, E., Ross, C., Sabrina, S., and Knight, J., 2025, Small waterbodies of large conservation concern: Towards an integrated approach to more accurately measuring surface water dynamics: Ecological Indicators, v. 175, 113525, 13 p., https://doi.org/10.1016/j.ecolind.2025.113525.","productDescription":"113525, 13 p.","ipdsId":"IP-156979","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":488103,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.113525","text":"Publisher Index Page"},{"id":486573,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Nelson Lake Waterfowl Protection Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.298889,\n 45.492\n ],\n [\n -95.298889,\n 45.4889\n ],\n [\n -95.295,\n 45.4889\n ],\n [\n -95.295,\n 45.492\n ],\n [\n -95.298889,\n 45.492\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"175","noUsgsAuthors":false,"publicationDate":"2025-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"McKenna, Owen P. 0000-0002-5937-9436 omckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-5937-9436","contributorId":198598,"corporation":false,"usgs":true,"family":"McKenna","given":"Owen","email":"omckenna@usgs.gov","middleInitial":"P.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":938404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lothspeich, Audrey Claire 0000-0002-5460-6142","orcid":"https://orcid.org/0000-0002-5460-6142","contributorId":355935,"corporation":false,"usgs":true,"family":"Lothspeich","given":"Audrey Claire","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":938405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vacek, Sara","contributorId":178445,"corporation":false,"usgs":false,"family":"Vacek","given":"Sara","email":"","affiliations":[],"preferred":false,"id":938406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MacDonald, Dawn","contributorId":355936,"corporation":false,"usgs":false,"family":"MacDonald","given":"Dawn","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":938407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eash, Josh D.","contributorId":267175,"corporation":false,"usgs":false,"family":"Eash","given":"Josh D.","affiliations":[{"id":55428,"text":"U.S. Fish and Wildlife Service, 5600 American Blvd. W., Bloomington, MN","active":true,"usgs":false}],"preferred":false,"id":938408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":938409,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCulloch, Elyssa C.","contributorId":355940,"corporation":false,"usgs":false,"family":"McCulloch","given":"Elyssa C.","affiliations":[{"id":84869,"text":"Formerly - USGS NPWRC","active":true,"usgs":false}],"preferred":false,"id":938410,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ross, Caryn D.","contributorId":355942,"corporation":false,"usgs":false,"family":"Ross","given":"Caryn D.","affiliations":[{"id":84869,"text":"Formerly - USGS NPWRC","active":true,"usgs":false}],"preferred":false,"id":938411,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sabrina, Sadia","contributorId":355943,"corporation":false,"usgs":false,"family":"Sabrina","given":"Sadia","affiliations":[{"id":84869,"text":"Formerly - USGS NPWRC","active":true,"usgs":false}],"preferred":false,"id":938412,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Knight, Joseph F.","contributorId":355944,"corporation":false,"usgs":false,"family":"Knight","given":"Joseph F.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":938413,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70266306,"text":"70266306 - 2025 - Variability in hydrologic response to wildfire between snow zones in forested headwaters","interactions":[],"lastModifiedDate":"2025-05-15T15:08:04.001368","indexId":"70266306","displayToPublicDate":"2025-05-08T10:02:28","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":"Variability in hydrologic response to wildfire between snow zones in forested headwaters","docAbstract":"Rising temperatures and shifting fire regimes in the western United States are pushing fires upslope into areas of deep winter snowpack, where we have little knowledge of the likely hydrologic impacts of wildfire. We quantified differences in the timing and magnitude of stormflow responses to summer rainstorms among six catchments of varying levels of burn severity and seasonal snowpack cover for years 1–3 after the 2020 Cameron Peak fire. Our objectives were to (1) examine whether responsiveness, magnitude, and timing of stormflow responses to rainfall vary between burned and unburned catchments and between snow zones, and (2) identify the factors that affect these responses. We evaluated whether differences in storm hydrograph peak flow, total flow, stage rise, and lag to peak time differed by snow zone and burn category using generalised linear models. Additional predictors in these models are the maximum 60-min rainfall intensity for each storm, the cumulative potential water deficit prior to the storm, and the year post-fire. These models showed that the high snow zone (HSZ) has higher total stormflow than the low snow zone (LSZ), likely due to the higher soil moisture content in that area. In both snow zones, the biggest driver of the magnitude of the stormflow response was MI60. Burn category did not have a clear impact on stormflow response in the HSZ, but it did impact stage rise at the severely burned catchment in the LSZ. This was the only site that had widespread overland flow post-fire. These results demonstrate that the stormflow responses to fire vary between snow zones, indicating a need to account for elevation and snow persistence in post-fire risk assessments.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70151","usgsCitation":"Miller, Q., Barnard, D.M., Sears, M., Hammond, J., and Kampf, S., 2025, Variability in hydrologic response to wildfire between snow zones in forested headwaters: Hydrological Processes, v. 39, no. 5, e70151, 16 p., https://doi.org/10.1002/hyp.70151.","productDescription":"e70151, 16 p.","ipdsId":"IP-172047","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":490124,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.70151","text":"Publisher Index Page"},{"id":485996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106,\n 41\n ],\n [\n -106,\n 40.333\n ],\n [\n -105,\n 40.333\n ],\n [\n -105,\n 41\n ],\n [\n -106,\n 41\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Quinn","contributorId":354373,"corporation":false,"usgs":false,"family":"Miller","given":"Quinn","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, David M 0000-0003-1877-3151","orcid":"https://orcid.org/0000-0003-1877-3151","contributorId":222833,"corporation":false,"usgs":false,"family":"Barnard","given":"David","email":"","middleInitial":"M","affiliations":[{"id":18168,"text":"USDA ARS","active":true,"usgs":false}],"preferred":false,"id":935515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sears, Megan","contributorId":354374,"corporation":false,"usgs":false,"family":"Sears","given":"Megan","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hammond, John C. 0000-0002-4935-0736","orcid":"https://orcid.org/0000-0002-4935-0736","contributorId":223108,"corporation":false,"usgs":true,"family":"Hammond","given":"John C.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":935517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kampf, Stephanie","contributorId":346221,"corporation":false,"usgs":false,"family":"Kampf","given":"Stephanie","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":935518,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266883,"text":"70266883 - 2025 - Long-term patterns in growth of White Sturgeon in the Sacramento-San Joaquin River basin, California.","interactions":[],"lastModifiedDate":"2025-05-15T13:11:35.40062","indexId":"70266883","displayToPublicDate":"2025-05-06T09:26:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18328,"text":"Frontiers in Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Long-term patterns in growth of White Sturgeon in the Sacramento-San Joaquin River basin, California.","docAbstract":"Introduction: The Sacramento-San Joaquin River system (SSJ) of California includes both riverine, delta, and estuarine habitats and is among the most modified aquatic ecosystems in the United States. Water development projects in the system are associated with declines of many native species, including White Sturgeon Acipenser transmontanus.
Methods: We used White Sturgeon pectoral fin rays collected from 1983 to 2016 throughout the SSJ to assess long-term changes in growth and associations with thermal and hydrological conditions (i.e., temperature, discharge, salinity). Age and growth were estimated from 1,897 White Sturgeon varying in fork length from 25 to 210 cm and from age 0 to 33.
Results: Age structure varied through time with the oldest fish generally sampled during the mid-1980s. Growth of White Sturgeon in 1951–1970 was slower than growth of fish in 1971–1990 and 1991–2012. Growth of White Sturgeon during 1991–2012 was ~10% higher than during other time periods.
Discussion: Little variation in growth was explained by environmental covariates, suggesting that annual growth was likely influenced by factors not measured in our study. Alternatively, population structure and movement behavior of White Sturgeon in the SSJ may be such that the scale (i.e., spatial or temporal) of available habitat covariates was mismatched to the scale at which growth of White Sturgeon responds. Increased growth in recent times may be partly due to density-dependent processes in association with substantial declines in White Sturgeon population abundance over the last several decades. This research provides important information on long-term patterns in growth that contributes to the conservation and management of White Sturgeon in the SSJ and beyond.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffwsc.2025.1577065","usgsCitation":"Quist, M.C., Blackburn, S., Ulaski, M., and Jackson, Z., 2025, Long-term patterns in growth of White Sturgeon in the Sacramento-San Joaquin River basin, California.: Frontiers in Freshwater Science, v. 3, 1577065, 10 p., https://doi.org/10.3389/ffwsc.2025.1577065.","productDescription":"1577065, 10 p.","ipdsId":"IP-175717","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488907,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffwsc.2025.1577065","text":"Publisher Index Page"},{"id":485931,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.79850686101548,\n 38.755876798924476\n ],\n [\n -122.64621142922209,\n 38.755876798924476\n ],\n [\n -122.64621142922209,\n 37.31156292678925\n ],\n [\n -120.79850686101548,\n 37.31156292678925\n ],\n [\n -120.79850686101548,\n 38.755876798924476\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2025-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blackburn, Shannon","contributorId":338596,"corporation":false,"usgs":false,"family":"Blackburn","given":"Shannon","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ulaski, Marta","contributorId":280108,"corporation":false,"usgs":false,"family":"Ulaski","given":"Marta","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Zachary","contributorId":338597,"corporation":false,"usgs":false,"family":"Jackson","given":"Zachary","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":937033,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266471,"text":"70266471 - 2025 - Inferring snowpack contributions and the mean elevation of source water to streamflow in the Willamette River, Oregon using water stable isotopes","interactions":[],"lastModifiedDate":"2025-05-07T18:42:39.895388","indexId":"70266471","displayToPublicDate":"2025-05-04T13:38:57","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":"Inferring snowpack contributions and the mean elevation of source water to streamflow in the Willamette River, Oregon using water stable isotopes","docAbstract":"Snowpacks are an important water source for mountainous rivers, worldwide. The timing and volume of streamflow in systems reliant on snowmelt can be affected by changes in snow accumulation and melt time. In the Cascade Range (western USA), seasonal snowpacks are predicted to decrease by over 50% within the next century. During the last decade, Cascade Range snowpacks have varied between 17% and 150% of the median 1981–2023 peak snowpack values. To understand how snowpack variation could affect Willamette River streamflow, we monitored water stable isotopes over 13 years from two sites on the mainstem and 60 streams draining small catchments across the Willamette River Basin. Small catchment water stable isotope values integrated and dampened variation in precipitation isotopes and varied with elevation, providing a marker for determining the mean elevation from which streamflow in the Willamette River was derived. During winter, while snow accumulates in the mountains, most streamflow in the Willamette River originates from rainfall at lower elevations. During summer low-flow conditions, most streamflow in the river was derived from winter snow that accumulated at elevations above 1200 m, which represents < 12% of the Willamette River Basin area. Peak snow water equivalent from the previous winter was positively correlated with the proportion of Willamette River streamflow derived from > 1200 m during the summer low-flow period, but both high elevation (> 1200 m) precipitation and temperature trends explained nearly as much variance as snow water equivalent. However, after accounting for climate trends, the estimated amount of high-elevation streamflow in the Willamette River during summer low-flow has decreased over the past 13 years. Improved understanding of the origin of, and trends in, summer streamflow in the Willamette River will aid in reconciling human demands with biological instream requirements during periods of low snowpack.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.70136","usgsCitation":"Brooks, J.R., Johnson, H.M., Johnson, K., Cline, S., Comeleo, R., Rugh, W., and Trine, L., 2025, Inferring snowpack contributions and the mean elevation of source water to streamflow in the Willamette River, Oregon using water stable isotopes: Hydrological Processes, v. 39, no. 5, e70136, 16 p., https://doi.org/10.1002/hyp.70136.","productDescription":"e70136, 16 p.","ipdsId":"IP-172923","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":504383,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12181979/","text":"External Repository"},{"id":485517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.95523621449394,\n 45.86142450803834\n ],\n [\n -123.81476990715908,\n 44.89596823269312\n ],\n [\n -123.72977022633785,\n 43.74103690962323\n ],\n [\n -123.07197402264748,\n 42.915774707124\n ],\n [\n -122.07756499909124,\n 42.658344639098516\n ],\n [\n -121.39018022281371,\n 43.76496540434982\n ],\n [\n -121.33327288435316,\n 44.70946434908879\n ],\n [\n -121.72513456164276,\n 45.32271768048014\n ],\n [\n -122.32368441902653,\n 45.52334782078054\n ],\n [\n -122.66134858778295,\n 45.556744965138535\n ],\n [\n -122.95523621449394,\n 45.86142450803834\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Brooks, J. Renee","contributorId":176587,"corporation":false,"usgs":false,"family":"Brooks","given":"J.","email":"","middleInitial":"Renee","affiliations":[],"preferred":false,"id":936062,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Henry M. 0000-0002-7571-4994 hjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7571-4994","contributorId":869,"corporation":false,"usgs":true,"family":"Johnson","given":"Henry","email":"hjohnson@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":936063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Keira R.","contributorId":354644,"corporation":false,"usgs":false,"family":"Johnson","given":"Keira R.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":936064,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cline, Steven P.","contributorId":354645,"corporation":false,"usgs":false,"family":"Cline","given":"Steven P.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":936065,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Comeleo, Randy","contributorId":217974,"corporation":false,"usgs":false,"family":"Comeleo","given":"Randy","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":936066,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rugh, WIlliam","contributorId":354646,"corporation":false,"usgs":false,"family":"Rugh","given":"WIlliam","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":936067,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Trine, Lisandra","contributorId":354647,"corporation":false,"usgs":false,"family":"Trine","given":"Lisandra","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":936068,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70264061,"text":"70264061 - 2025 - Sources and risk factors for nitrate, pathogens, and fecal contamination of private wells in rural southwestern Wisconsin, USA","interactions":[],"lastModifiedDate":"2025-03-05T15:27:14.791487","indexId":"70264061","displayToPublicDate":"2025-05-02T08:20:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Sources and risk factors for nitrate, pathogens, and fecal contamination of private wells in rural southwestern Wisconsin, USA","docAbstract":"Household well water can be degraded by contaminants from the land's surface, but private well owners lack means to protect the source water from neighboring disturbances. Rural residents of southwestern Wisconsin, USA, rely on private well water, and the combination of land use and fractured carbonate bedrock makes groundwater vulnerable to contamination. To identify the extent, sources, and risk factors of private well contamination, randomly selected wells sampled during two-day periods in fall (n = 301) and spring (n = 529) were analyzed for nitrate and indicator bacteria, and a subset (n = 138) was sampled across four seasonal events for analysis of pathogens and microbial source tracking markers by quantitative polymerase chain reaction. Risk factors representing land use, hydrology, geology, and well construction were analyzed for associations with contamination in multivariable models. The importance of risk factors varied by contaminant, illustrating the multifaceted nature of rural groundwater quality. Nitrate contamination was associated with agricultural land use, and wells with casings that extended below a shale aquitard accessed less contaminated water than those drawing water from above it. Human fecal microbes were detected in 64 wells (46%), and rainfall was the key risk factor for contamination, indicating that wastewater from septic systems was available to contaminate wells when transport conditions were favorable. Manure microbes from cattle/ruminants and pigs were detected in 33 and 13 wells, respectively, and concentrations increased with the hectarage of cultivated land near wells. Pathogen genes for viruses, bacteria, and protozoa were detected in 66 wells (48%), including more detections of zoonotic than human-specific pathogens, and human Bacteroides, an indicator of wastewater, was an equivocal predictor of pathogen presence in private wells. Characterizing important elements of the setting, like geology, and identifying sources and risk factors for contaminants can inform landscape-level policies to protect groundwater quality.
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Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Alaskan hydrology in transition: Changing precipitation and evapotranspiration patterns are projected to reshape seasonal streamflow and water temperature by midcentury (2035-2064)","docAbstract":"High spatial and temporal resolution models are essential for understanding future climate impacts and developing effective climate resilience plans. However, existing regional and global river models often lack the resolution needed to accurately capture local conditions. This study uses a series of high-resolution models, including the Regional Arctic System Model, mizuRoute, and the river basin model, to analyze Arctic and sub-Arctic Alaskan hydrology. We compare a historical baseline (1991–2020) with six midcentury (2035–64) futures: two pseudo–global warming scenarios based on historical meteorology and four direct dynamically downscaled global climate models. The six futures reveal significant uncertainty in future annual discharge and peak flows, although a widespread increase in discharge during April (+63%) and October (+31%) is consistently shown across models. Projected increases in rain and shifting weather patterns lead to a transition from snow to rain in spring and autumn, reducing the fraction of snowmelt contributing to river discharge. Rising evapotranspiration moderates discharge changes, particularly in autumn, by offsetting precipitation increases. Average summer river temperatures are projected to increase by approximately 1.5°C, doubling the number of river segments that experience 18°C days, a critical threshold for salmon survival, and intensifying the heat flux to the ocean adding an average of 3.3 × 1012 MJ yr−1. These changes in the hydrologic cycle could profoundly impact riverine and oceanic ecosystems, posing substantial challenges to communities reliant on these environments.
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C. 0000-0001-6621-2717","orcid":"https://orcid.org/0000-0001-6621-2717","contributorId":211589,"corporation":false,"usgs":false,"family":"Newman","given":"A.","email":"","middleInitial":"C.","affiliations":[{"id":38269,"text":"Aarhus, Denmark","active":true,"usgs":false}],"preferred":false,"id":940068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":940069,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goseff, M","contributorId":356787,"corporation":false,"usgs":false,"family":"Goseff","given":"M","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":940070,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Musselman, K","contributorId":302756,"corporation":false,"usgs":false,"family":"Musselman","given":"K","email":"","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":940071,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267209,"text":"70267209 - 2025 - Effects of climate change on midwestern ecosystems: Appalachian – Interior – Northeast Mesic Forest","interactions":[],"lastModifiedDate":"2026-03-17T14:22:08.438751","indexId":"70267209","displayToPublicDate":"2025-05-01T09:13:46","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Effects of climate change on midwestern ecosystems: Appalachian – Interior – Northeast Mesic Forest","docAbstract":"The Appalachian-Interior-Northeast Mesic Forest ecosystem, historically buffered by cool, moist conditions, may experience significant stress under future climate change, particularly due to intensifying droughts and milder winters in the midwestern United States. Droughts are expected to intensify in frequency and severity, depleting soil moisture, increasing tree mortality, and reshaping species composition. Increasing aridity and disrupted hydrologic cycles will likely accelerate soil erosion, deplete nutrients, and heighten wildfire risk. Meanwhile, milder winters may reduce snowpack insulation, increase freeze-thaw cycles, and alter growing seasons, potentially amplifying cold stress, disrupting phenology, and contributing to shifts in habitat structure and community composition. While easing winter severity may temporarily boost plant productivity and facilitate species migration into and throughout the Midwest, it can also increase the risk of frost damage for early-leafing trees and disrupt ecological relationships, such as plant-pollinator interactions.
Together, these stressors may drive fundamental shifts in habitat structure and community composition, favoring drought-, fire-, and cold-tolerant species, while historically dominant, moisture-dependent species decline. Species with limited drought resistance, such as those with shallow roots or low water-use efficiency, may be especially vulnerable, while drought-adapted taxa could gain a competitive advantage. This shift could trigger a departure from over a century of mesophication in the Appalachian-Interior-Northeast Mesic Forest, which has favored shade-loving, moisture-dependent species in fire-suppressed landscapes. As a result, these forests may be particularly ill-equipped to withstand the novel environmental conditions imposed by intensifying droughts and milder winters. The Appalachian-Northeast Mesic Forest habitat group, dominated by eastern hemlock (Tsuga canadensis) and eastern white pine (Pinus strobus), is likely particularly vulnerable, as both dominant species are projected to decline due to increasing drought stress and shifting competitive dynamics. In the North-Central Beech - Maple - Basswood Forest, the Driftless Area of Wisconsin, Minnesota, and Iowa may be more vulnerable than more eastern portions of the habitat due to its already drier conditions, with climate change expected to push these communities beyond favorable conditions.
Species interactions, including invasive species, pests, and herbivory, are also likely to be reshaped by climate change, compounding stress on habitat groups throughout the Appalachian-Interior-Northeast Mesic Forest. Warmer winters and increased disturbance may facilitate the expansion of invasive species, which outcompete native vegetation and alter ecosystem dynamics. At the same time, pests and pathogens are likely to become more destructive, as milder winters enhance their survival and spread and drought weakens tree defenses. Additionally, rising white-tailed deer (Odocoileus virginianus) populations, supported by warmer winters, may shift forest regeneration patterns by selectively browsing on sensitive seedlings and saplings, limiting the recruitment of historically dominant tree species while favoring browse-resistant plants. Collectively, these pressures can drive significant and ongoing ecological transformation in the Appalachian-Interior-Northeast Mesic Forest, highlighting the need for adaptive management strategies to sustain biodiversity and ecosystem function.
","language":"English","publisher":"Midwest Climate Adaptation Science Center","usgsCitation":"Ratcliffe, H., Charton, K., Siddons, T., Lyons, M.P., and LeDee, O.E., 2025, Effects of climate change on midwestern ecosystems: Appalachian – Interior – Northeast Mesic Forest, 97 p.","productDescription":"97 p.","ipdsId":"IP-177855","costCenters":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":486042,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://mwcasc.umn.edu/research-publications"},{"id":501211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, Ohio, 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University","active":true,"usgs":false}],"preferred":false,"id":937287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lyons, Marta P. 0000-0002-8117-8710 mlyons@usgs.gov","orcid":"https://orcid.org/0000-0002-8117-8710","contributorId":270223,"corporation":false,"usgs":true,"family":"Lyons","given":"Marta","email":"mlyons@usgs.gov","middleInitial":"P.","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":937285,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"LeDee, Olivia E. 0000-0002-7791-5829 oledee@usgs.gov","orcid":"https://orcid.org/0000-0002-7791-5829","contributorId":242820,"corporation":false,"usgs":true,"family":"LeDee","given":"Olivia","email":"oledee@usgs.gov","middleInitial":"E.","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":937286,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70269031,"text":"70269031 - 2025 - Advancing broadscale spatial evapotranspiration modelling by incorporating sun-induced chlorophyll fluorescence measurements","interactions":[],"lastModifiedDate":"2025-07-14T14:48:30.146948","indexId":"70269031","displayToPublicDate":"2025-04-28T07:43:40","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":"Advancing broadscale spatial evapotranspiration modelling by incorporating sun-induced chlorophyll fluorescence measurements","docAbstract":"Evapotranspiration (ET) describes the sum of water transfer from the ground surface through soil evaporation and water loss from leaf stomata into the atmosphere − critical factors linking the global water and carbon cycles. Myriad ET models based on remote sensing data provide spatially continuous estimates of ET; however, leaf photosynthetic information is critical to ensure accurate ET estimates, which are difficult to measure from space. Remotely sensed sun-induced chlorophyll fluorescence (SIF) provides a proxy of stomatal conductance activity with high performance in predicting plant transpiration, which can account for a large proportion of terrestrial and riverine ET. This study aims to improve estimates of tree water use in semi-arid to arid environments. In this study, a fixed stomatal conductance model and three SIF-driven canopy conductance (gsc) models were applied to model potential ET (PET). The models estimated PET using the Penman-Monteith equation with: (1) a constant leaf stomatal conductance; (2) a transpiration-driven gsc model; (3) a gsc model based on electron-transfer rate and vapor pressure deficit, and a (4) Ball-Berry stomatal conductance model. A machine learning model was then applied to scale PET to actual ET (AET) using remote sensing and climate data. Accordingly, four AET models were cross-validated with in-situ measured AET at 52 sites, including 21 eddy covariance flux tower sites, and 31 sap-flow measurement sites (semi-arid and plantation area), for various plant functional types in Australia. This study demonstrated that SIF effectively captured seasonal variations of gsc, finding that AET models with SIF-driven gsc models correlated well with in-situ measured AET (R2 = 0.64). Modelled AET with dynamic variations of gsc generated lower prediction error (0.85 mm day−1), while the AET model with fixed stomatal conductance tended to overestimate AET in floodplains and underestimate it in evergreen broadleaf forests, indicating using fixed stomatal conductance results in unstable performance when modelling AET. This study demonstrated that SIF-driven AET models improved broadscale estimation of ET. Our findings provide vital broadscale hydrological data to assist catchment and regional water management, particularly over unmonitored areas at risk of future climate-driven reductions in rainfall.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2025.133404","usgsCitation":"Gao, S., Nagler, P.L., Woodgate, W., Huete, A., and Doody, T.M., 2025, Advancing broadscale spatial evapotranspiration modelling by incorporating sun-induced chlorophyll fluorescence measurements: Journal of Hydrology, v. 660, no. Part B, 133404, 16 p., https://doi.org/10.1016/j.jhydrol.2025.133404.","productDescription":"133404, 16 p.","ipdsId":"IP-172126","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":499843,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2025.133404","text":"Publisher Index Page"},{"id":492203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 123.28690979572599,\n -14.507783026538078\n ],\n [\n 113.28039887008524,\n -21.66065633263682\n ],\n [\n 112.17079996753354,\n -24.994521175001637\n ],\n [\n 115.10354300417447,\n -36.486501164702105\n ],\n [\n 122.24168422144697,\n -35.62034073401294\n ],\n [\n 131.93124828895753,\n -32.58906983701101\n ],\n [\n 141.10544225154464,\n -40.23302031896691\n ],\n [\n 152.81278701443853,\n -40.33448456027517\n ],\n [\n 155.92719705356842,\n -24.451431761649573\n ],\n [\n 144.11359477726128,\n -8.385497835754798\n ],\n [\n 130.88500806969773,\n -10.415819254694402\n ],\n [\n 123.28690979572599,\n -14.507783026538078\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"660","issue":"Part B","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gao, Sicong","contributorId":303040,"corporation":false,"usgs":false,"family":"Gao","given":"Sicong","email":"","affiliations":[{"id":65623,"text":"CSIRO, Land and Water, Waite Campus, Adelaide, South Australia, Australia; University of Canberra, Canberra, Australian Capital Territory, Australia","active":true,"usgs":false}],"preferred":false,"id":942957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":942958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodgate, William","contributorId":357983,"corporation":false,"usgs":false,"family":"Woodgate","given":"William","affiliations":[{"id":85572,"text":"Earth Observation Research Centre, School of the Environment, The University of Queensland, Brisbane, QLD 4072, Australia; CSIRO, Space and Astronomy, Kensington, 6151, WA, Australia","active":true,"usgs":false}],"preferred":false,"id":942959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huete, Alfredo 0000-0003-2809-2376","orcid":"https://orcid.org/0000-0003-2809-2376","contributorId":208294,"corporation":false,"usgs":false,"family":"Huete","given":"Alfredo","email":"","affiliations":[],"preferred":false,"id":942960,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doody, Tanya M.","contributorId":138691,"corporation":false,"usgs":false,"family":"Doody","given":"Tanya","email":"","middleInitial":"M.","affiliations":[{"id":12494,"text":"CSIRO Land and Water, Australia","active":true,"usgs":false}],"preferred":false,"id":942961,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70265923,"text":"70265923 - 2025 - Wet antecedent soil moisture increases atmospheric river streamflow magnitudes non-linearly","interactions":[],"lastModifiedDate":"2025-06-12T15:41:54.841369","indexId":"70265923","displayToPublicDate":"2025-04-24T10:26:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Wet antecedent soil moisture increases atmospheric river streamflow magnitudes non-linearly","docAbstract":"Atmospheric rivers (ARs) drive most riverine floods on the United States (U.S.) West Coast. However, estimating flood risk based solely on AR intensity and duration is challenging because precipitation phase, antecedent conditions, and physical watershed characteristics (e.g., slope and soil depth) can influence the magnitude of floods. Here, we analyze how antecedent soil moisture (ASM) conditions contribute to variability in streamflow during AR events and how that changes across climatic regimes and physiography in 122 U.S. West Coast watersheds. We identify a robust non-linear relationship between streamflow and ASM during ARs in 89% of watersheds. The inflection point in this relationship represents a watershed-specific critical ASM threshold, above which event maximum streamflow is, on average, two to four and a half times larger. Wet ASM conditions amplify the hydrologic impacts of more frequent but weaker, lower moisture transport AR events, while dry ASM conditions attenuate the hydrologic impacts that stronger, higher moisture transport AR events could otherwise cause. Our research shows that watersheds prone to ASM-amplified streamflows have higher evaporation ratios, lower cold-season precipitation, lower snow-to-rain ratios, and shallower, clay-rich soils. Higher evaporation and lower precipitation lead to greater ASM variability during the cold season, increasing streamflow during wet periods and buffering streamflow during dry periods. Lower snow fraction and shallower soils limit the antecedent water storage capacity of a watershed, contributing to greater sensitivity of streamflow peaks to ASM variability. Incorporating ASM thresholds into hydrologic models in these regions prone to AR-amplified streamflow could improve forecasts and decrease uncertainty.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-24-0078.1","collaboration":"Desert Research Institute, Reno, NV","usgsCitation":"Webb, M., Albano, C., Harpold, A., Wagner, D.M., and Wilson, A.M., 2025, Wet antecedent soil moisture increases atmospheric river streamflow magnitudes non-linearly: Journal of Hydrometeorology, v. 26, no. 6, p. 741-758, https://doi.org/10.1175/JHM-D-24-0078.1.","productDescription":"18 p.","startPage":"741","endPage":"758","ipdsId":"IP-166108","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":485998,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.92121191786663,\n 33.407810452030205\n ],\n [\n -116.523784768193,\n 36.41502072713284\n ],\n [\n -119.64994516515054,\n 39.88994270690637\n ],\n [\n -120.51138519071847,\n 42.20041323206641\n ],\n [\n -119.3720758190301,\n 48.777534854733574\n ],\n [\n -122.9287960859929,\n 48.977595241145025\n ],\n [\n -123.36076938971661,\n 48.210450784064506\n ],\n [\n -125.09530509112804,\n 48.5114622057049\n ],\n [\n -124.0899142321606,\n 45.77238715755897\n ],\n [\n -124.63673786495912,\n 42.844084204189784\n ],\n [\n -124.31096484013645,\n 41.342509106103535\n ],\n [\n -124.81776995325123,\n 40.42865225014583\n ],\n [\n -123.57485679616491,\n 38.65999426544576\n ],\n [\n -122.45718830306802,\n 37.1653556881036\n ],\n [\n -121.77165200602349,\n 35.90307547409293\n ],\n [\n -120.64970139084915,\n 34.560810038256434\n ],\n [\n -117.92121191786663,\n 33.407810452030205\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Webb, Mariana J. 0000-0003-0331-2635","orcid":"https://orcid.org/0000-0003-0331-2635","contributorId":353576,"corporation":false,"usgs":false,"family":"Webb","given":"Mariana J.","affiliations":[{"id":84438,"text":"Division of Hydrological Sciences, Desert Research Institute, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":933999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Albano, Christine M.","contributorId":17681,"corporation":false,"usgs":true,"family":"Albano","given":"Christine M.","affiliations":[],"preferred":false,"id":934000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harpold, Adrian A. 0000-0002-2566-9574","orcid":"https://orcid.org/0000-0002-2566-9574","contributorId":353577,"corporation":false,"usgs":false,"family":"Harpold","given":"Adrian A.","affiliations":[{"id":84439,"text":"Dept. of Natural Resources and Environmental Science, Univ. of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":934001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagner, Daniel M. 0000-0002-0432-450X dwagner@usgs.gov","orcid":"https://orcid.org/0000-0002-0432-450X","contributorId":4531,"corporation":false,"usgs":true,"family":"Wagner","given":"Daniel","email":"dwagner@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":934002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Anna M.","contributorId":211536,"corporation":false,"usgs":false,"family":"Wilson","given":"Anna","email":"","middleInitial":"M.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":934003,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70268481,"text":"70268481 - 2025 - A review of post-wildfire adaptations of surface-water-quality models: Synthesis, gaps, and opportunities","interactions":[],"lastModifiedDate":"2025-06-27T15:13:12.47879","indexId":"70268481","displayToPublicDate":"2025-04-24T08:09:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"A review of post-wildfire adaptations of surface-water-quality models: Synthesis, gaps, and opportunities","docAbstract":"As wildfires increasingly affect water-supply watersheds, the demand for models to predict water-quality responses is increasing. This work reviews and synthesizes existing post-wildfire applications of water-quality models in the context of geographic and ecohydrological distribution, hydrologic and water-quality response process representation, model parameterization, model and input data scales, model calibration data availability, as well as calibration and performance evaluation approaches. Emphasis is placed on models that simulate water-quality output, rather than sediment and erosional response as the primary focus. Here, identified gaps and opportunities to advance the post-wildfire application of water-quality models include: 1. applying models in under-represented geographic and ecohydrologic regions, 2. simulating multiple streamflow generation mechanisms, including groundwater, with an emphasis on shifting dominant flow pathways as the landscape recovers following wildfire, 3. adding studies that include the simulation of metals, 4. incorporating more biogeochemical and in-stream processes to model applications, 5. applying finer spatial and temporal resolution of precipitation data input as well as finer spatial resolution hydrologic response units, 6. implementing fully distributed grid or element models or finer resolution response units to capture burn severity heterogeneity, 7. collecting enhanced water-quality data for model calibration and validation, 8. conducting model-intercomparison studies, and 9. developing model parameter value guidance in post-wildfire applications. These identified gaps and opportunities may assist users in deciding on key processes and approaches to consider in modeling post-wildfire water-quality conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.179435","usgsCitation":"Shephard, Z.M., Partridge, T.F., Murphy, S.F., Walvoord, M.A., and Ebel, B., 2025, A review of post-wildfire adaptations of surface-water-quality models: Synthesis, gaps, and opportunities: Science of the Total Environment, v. 979, 179435, 15 p., https://doi.org/10.1016/j.scitotenv.2025.179435.","productDescription":"179435, 15 p.","ipdsId":"IP-165381","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":491530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"979","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shephard, Zachary M. 0000-0003-2994-3355","orcid":"https://orcid.org/0000-0003-2994-3355","contributorId":222581,"corporation":false,"usgs":true,"family":"Shephard","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Partridge, Trevor Fuess 0000-0003-1589-4783","orcid":"https://orcid.org/0000-0003-1589-4783","contributorId":302668,"corporation":false,"usgs":true,"family":"Partridge","given":"Trevor","email":"","middleInitial":"Fuess","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":941496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":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":941497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":941498,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":941499,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274641,"text":"70274641 - 2025 - Pluvial and potential compound flooding in a coupled coastal modeling framework: New York City during post-tropical Cyclone Ida (2021)","interactions":[],"lastModifiedDate":"2026-04-02T16:06:57.228299","indexId":"70274641","displayToPublicDate":"2025-04-23T11:03:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Pluvial and potential compound flooding in a coupled coastal modeling framework: New York City during post-tropical Cyclone Ida (2021)","docAbstract":"Many coastal urban areas are prone to extreme pluvial flooding due to limitations in stormwater system capacity, with the additional potential for flooding compounded by storm surge, tides, and waves. Understanding and simulating these processes can improve prediction and flood risk management. Here, we adapt the Coupled Ocean–Atmosphere–Wave–Sediment Transport modeling framework (COAWST) to simulate pluvial flooding from post-tropical Cyclone Ida (2021) in the Jamaica Bay watershed of New York City (NYC). We modify the model to capture the volumetric effects of rainfall and parameterize soil infiltration and a stormwater conveyance system as the drainage rate. We generate a spatially continuous flood map of Ida with a root-mean-square error (RMSE) of 20 cm when compared to high-water marks, useful for understanding Ida's impacts and subsequent mitigation planning. Results show that over 23 km2 and 4621 buildings were flooded deeper than 0.3 m during Ida. Sensitivity analyses are used to study the broader risk from events like Ida (pluvial flooding) as well as potential compound (pluvial–coastal) flooding. Spatial shifting of the storm track within a typical 12 h forecast uncertainty reveals a worst-case scenario that increases this flooded area to 62 km2 (5907 buildings). Shifting Ida's rainfall to coincide with high tide increases this flooded area by 1 km2, a relatively small change due to the lack of significant storm surge. The application of COAWST to this storm event addresses a broader goal of developing the capability to model compound pluvial–coastal flooding by simultaneously representing coastal storm processes such as rain, tide, waves, erosion, and atmosphere–wave–ocean interactions. The sensitivity analysis results underscore the need for detailed flood risk assessments, showing that Ida, already NYC's worst rain event, could have been even more devastating with slight shifts in the storm track.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-29-2043-2025","usgsCitation":"Kasaei, S., Orton, P.M., Ralston, D.K., and Warner, J., 2025, Pluvial and potential compound flooding in a coupled coastal modeling framework: New York City during post-tropical Cyclone Ida (2021): Hydrology and Earth System Sciences, v. 29, no. 8, p. 2043-2058, https://doi.org/10.5194/hess-29-2043-2025.","productDescription":"16 p.","startPage":"2043","endPage":"2058","ipdsId":"IP-168323","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":502086,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-29-2043-2025","text":"Publisher Index Page"},{"id":502009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","city":"New York City","otherGeospatial":"Jamaica Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.01902277171598,\n 40.81541595710692\n ],\n [\n -74.01902277171598,\n 40.5619948325492\n ],\n [\n -73.61280152477734,\n 40.5619948325492\n ],\n [\n -73.61280152477734,\n 40.81541595710692\n ],\n [\n -74.01902277171598,\n 40.81541595710692\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kasaei, Shima","contributorId":369142,"corporation":false,"usgs":false,"family":"Kasaei","given":"Shima","affiliations":[{"id":28243,"text":"Stevens Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":958528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orton, Phillip M.","contributorId":369143,"corporation":false,"usgs":false,"family":"Orton","given":"Phillip","middleInitial":"M.","affiliations":[{"id":28243,"text":"Stevens Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":958529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ralston, David K.","contributorId":369144,"corporation":false,"usgs":false,"family":"Ralston","given":"David","middleInitial":"K.","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":958530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":958531,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266396,"text":"70266396 - 2025 - Fisheries dependent and independent data inform a capture technique for an emerging invasive fish species in the mainstem Mississippi River; Black Carp Mylopharyngodon piceus","interactions":[],"lastModifiedDate":"2025-05-06T14:11:54.318665","indexId":"70266396","displayToPublicDate":"2025-04-23T09:02:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Fisheries dependent and independent data inform a capture technique for an emerging invasive fish species in the mainstem Mississippi River; Black Carp Mylopharyngodon piceus","title":"Fisheries dependent and independent data inform a capture technique for an emerging invasive fish species in the mainstem Mississippi River; Black Carp Mylopharyngodon piceus","docAbstract":"Black Carp Mylopharyngodon piceus were imported into the United States in the 1970s and 1980s for use in aquaculture; escape occurred and reported wild captures increased. Lacking species-specific capture methods, we assessed fisheries dependent incidental Black Carp catches for a common method, hoop nets, by kernel density analysis to identify an area of increased reporting and compare frequency of reports for water temperature, river stage, and capture date to identify seasonality. We then used fisheries independent effort to identify co-occurrence of species via non-metric multi-dimensional scaling and fit Black Carp catch and environmental covariates by generalized linear models to assess site-specific environmental covariates facilitating capture. The best approximating distribution was refitted for predictions and inference. The greatest density of fisheries dependent hoop net captures (39 %) was near the confluence of the Missouri and Mississippi rivers, primarily from July-September. Captures were characterized by median water temperature 26.7°C, river stage 5.02 m, and 223 day-of-year (DOY; mid-August). Ordination of fisheries independent catch identified similarity in environmental covariates of Smallmouth Buffalo Ictiobus bubalus and Black Carp. The probability of capturing ≥ 1 Black Carp increased with DOY, decreased with increasing current velocity, and increased with depth. Most captures occurred in outside bends (87 %) or side channels (12 %). Probability of Black Carp capture was low but increased in summer and early fall when stage is lower, facilitating reduced current velocity and access to deeper areas. Results may be validated beyond this river segment to test if site-specific hydrology or habitat characteristics facilitated increased commercial and biologist capture and for replication.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2025.107368","usgsCitation":"Kroboth, P., Colvin, M.E., and Broaddus, C., 2025, Fisheries dependent and independent data inform a capture technique for an emerging invasive fish species in the mainstem Mississippi River; Black Carp Mylopharyngodon piceus: Fisheries Research, v. 285, 107368, 12 p., https://doi.org/10.1016/j.fishres.2025.107368.","productDescription":"107368, 12 p.","ipdsId":"IP-167531","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":487576,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2025.107368","text":"Publisher Index Page"},{"id":485444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Missouri","otherGeospatial":"MIssissippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.22145042868262,\n 38.90746978465282\n ],\n [\n -90.22145042868262,\n 38.666188258783194\n ],\n [\n -90.1030809646113,\n 38.666188258783194\n ],\n [\n -90.1030809646113,\n 38.90746978465282\n ],\n [\n -90.22145042868262,\n 38.90746978465282\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"285","noUsgsAuthors":false,"publicationDate":"2025-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kroboth, Patrick 0000-0002-9447-4818","orcid":"https://orcid.org/0000-0002-9447-4818","contributorId":216578,"corporation":false,"usgs":true,"family":"Kroboth","given":"Patrick","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":935820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":331490,"corporation":false,"usgs":true,"family":"Colvin","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":935821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Broaddus, Courtney 0000-0003-3851-3584","orcid":"https://orcid.org/0000-0003-3851-3584","contributorId":354595,"corporation":false,"usgs":true,"family":"Broaddus","given":"Courtney","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":935822,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265982,"text":"sir20255029 - 2025 - Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington","interactions":[{"subject":{"id":70257569,"text":"70257569 - 2024 - Spatial variability of water temperature within the White River basin, Mount Rainier National Park Washington","indexId":"70257569","publicationYear":"2024","noYear":false,"title":"Spatial variability of water temperature within the White River basin, Mount Rainier National Park Washington"},"predicate":"SUPERSEDED_BY","object":{"id":70265982,"text":"sir20255029 - 2025 - Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington","indexId":"sir20255029","publicationYear":"2025","noYear":false,"title":"Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington"},"id":1}],"lastModifiedDate":"2025-08-07T21:05:21.759632","indexId":"sir20255029","displayToPublicDate":"2025-04-23T07:58:02","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":"2025-5029","displayTitle":"Spatial Stream Network Modeling of Water Temperature within the White River Basin, Mount Rainier National Park, Washington","title":"Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington","docAbstract":"Water temperature is a primary control on the occurrence and distribution of fish and other ectothermic aquatic species. In the Pacific Northwest, cold-water species such as Pacific salmon (Oncorhynchus spp.) and bull trout (Salvelinus confluentus) have specific temperature requirements during different life stages that must be met to ensure the viability of their populations. Rivers draining Mount Rainier in western Washington, including the White River along its northern flank, support a number of cold-water fish populations, but the spatial distribution of water temperatures, particularly during late-summer baseflow during August and September, and the climatic, hydrologic, and physical processes regulating it are not well constrained. Spatial stream network (SSN) models, which are generalized linear models that incorporate streamwise spatial autocovariance structures, were fit to mean and 7-day average daily maximum water temperature for August and September for the White River Basin. The SSN models were calibrated using water temperature measurements collected in 2010 through 2020. The extent of the models included the White River and its tributaries upstream from its confluence with Silver Creek in Mount Rainier National Park, Washington. SSN models incorporated covariates hypothesized to represent the climatic, hydrologic, and physical processes that influence water temperature. SSN models were fit to the measured data and compared to generalized linear models that lacked spatial autocovariance structures. Statistically significant covariates within the best-fit models included the proportion of ice cover and forest cover within the basin, mean August air temperature, the proportion of consolidated geologic units, and snow-water equivalent. Statistical models that included spatial autocovariance structures had better predictive performance than those that did not. Additionally, models of mean August and September water temperature had better predictive performance than those of 7-day average daily maximum temperature in August and September. Predictions of the spatial distribution of water temperature were similar between August and September with a general warming in the downstream part of the mainstem White River compared to cooler water temperatures in the high-elevation headwater streams. The proportion of ice cover emerged as an inversely related significant covariate to both mean August and September water temperature because streams that receive glacial meltwater are colder than non-glaciated streams. Water temperatures of the upper White River increased downstream and are attributed to warming of water temperature from accumulated solar radiation and inflow of non-glaciated tributaries. Estimated water temperatures for the upper White River model are 3–4 degrees Celsius (°C) warmer for tributaries, but 1–2 °C cooler for the mainstem compared to the regional-scale model. Differences between the upper White River SSN model and the regional-scale NorWeST model are attributed to the fact that the upper White River SSN included water temperature observations specific to the upper White River, whereas water temperature observations from lower elevation streams and downstream from the Mount Rainer National Park boundary were used in the regional scale model.
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U.S. Geological Survey
934 Broadway, Suite 300
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The hydrogeologic framework at closed-loop geothermal sites in the Erie-Ontario Lowlands and Allegheny Plateau of central and western New York is the result of the complex interaction of bedrock geology, glacial geology, and groundwater hydrology, and the occurrence of petroleum and gas. Considerations for closed-loop geothermal bore installation include the thickness and character of glacial deposits, bedrock solubility and depth to competent rock, karst development, the distribution of highly permeable zones and their hydraulic heads, and the presence of saline water, gas, and oil. The hydrogeology of the Erie-Ontario Lowlands and Allegheny Plateau poses challenges to closed-loop geothermal bore drilling and casing; managing drill cuttings, discharge water, and gas; and grouting. The potential to encounter severe challenges typically increases with bore depth. This report highlights hydrogeologic considerations for closed-loop geothermal bore installation in New York’s Erie-Ontario Lowlands and Allegheny Plateau to help guide the efficient and safe development of geothermal resources in the regions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251013","usgsCitation":"Williams, J.H., Kappel, W.M., and Woda, J.C., 2025, Hydrogeologic framework and considerations for drilling and grouting of closed-loop geothermal bores in the Erie-Ontario Lowlands and Allegheny Plateau of New York State: U.S. Geological Survey Open-File Report 2025–1013, 11 p., https://doi.org/10.3133/ofr20251013.","productDescription":"v, 11 p.","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-160254","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":484773,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1013/coverthb.jpg"},{"id":484774,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1013/ofr20251013.pdf","text":"Report","size":"3.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1013 PDF"},{"id":484776,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1013/ofr20251013.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1013 XML"},{"id":484775,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251013/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1013 HTML"},{"id":484777,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1013/images/"},{"id":493765,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118544.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Allegheny Plateau, Erie-Ontario Lowlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.81166805859044,\n 42.45817957611891\n ],\n [\n -79.70949328319377,\n 41.9887101346182\n ],\n [\n -75.25480564049155,\n 41.98783382644345\n ],\n [\n -74.87533808065217,\n 41.42844676638893\n ],\n [\n -74.68982238759088,\n 44.66640491894796\n ],\n [\n -75.55631580076837,\n 44.66459292990035\n ],\n [\n -76.3423531557645,\n 44.2288156067778\n ],\n [\n -76.41053068058827,\n 43.979744421465796\n ],\n [\n -76.30005176487545,\n 43.60034279040653\n ],\n [\n -76.88563948226266,\n 43.34164590639\n ],\n [\n -77.46843046198688,\n 43.34036285729903\n ],\n [\n -78.42846779801299,\n 43.474518439670874\n ],\n [\n -79.08970961322291,\n 43.31146453979213\n ],\n [\n -78.97892018115594,\n 42.958836576630915\n ],\n [\n -78.81395126277387,\n 42.855237313375795\n ],\n [\n -79.81166805859044,\n 42.45817957611891\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349