On the evening of 15 January 2022, the Hunga Tonga-Hunga Ha’apai volcano1 unleashed a violent underwater eruption, blanketing the surrounding land masses in ash and debris. The eruption generated tsunamis observed around the world. An event of this type last occurred in 1883 during the eruption of Krakatau, and thus we have the first observations of a tsunami from a large emergent volcanic eruption captured with modern instrumentation. Here we show that the explosive eruption generated waves through multiple mechanisms, including: (1) air–sea coupling with the initial and powerful shock wave radiating out from the explosion in the immediate vicinity of the eruption; (2) collapse of the water cavity created by the underwater explosion; and (3) air–sea coupling with the air-pressure pulse that circled the Earth several times, leading to a global tsunami. In the near field, tsunami impacts are strongly controlled by the water-cavity source whereas the far-field tsunami, which was unusually persistent, can be largely described by the air-pressure pulse mechanism. Catastrophic damage in some harbours in the far field was averted by just tens of centimetres, implying that a modest sea level rise combined with a future, similar event would lead to a step-function increase in impacts on infrastructure. Piecing together the complexity of this event has broad implications for coastal hazards in similar geophysical settings, suggesting a currently neglected source of global tsunamis.
In the United States, high-resolution, century-long, hydroclimate projection datasets have been developed for water resources planning, focusing on the contiguous United States (CONUS) domain. However, there are few statewide hydroclimate projection datasets available for Alaska and Hawaiʻi. The limited information on hydroclimatic change motivates developing hydrologic scenarios from 1950 to 2099 using climate-hydrology impact modeling chains consisting of multiple statistically downscaled climate projections as input to hydrologic model simulations for both states. We adopt an approach similar to the previous CONUS hydrologic assessments where: 1) we select the outputs from ten global climate models (GCM) from the Coupled Model Intercomparison Project Phase 5 with Representative Concentration Pathways 4.5 and 8.5; 2) we perform statistical downscaling to generate climate input data for hydrologic models (12-km grid-spacing for Alaska and 1-km for Hawaiʻi); and 3) we perform process-based hydrologic model simulations. For Alaska, we have advanced the hydrologic model configuration from CONUS by using the full water-energy balance computation, frozen soils and a simple glacier model. The simulations show that robust warming and increases in precipitation produce runoff increases for most of Alaska, with runoff reductions in the currently glacierized areas in Southeast Alaska. For Hawaiʻi, we produce the projections at high resolution (1 km) which highlight high spatial variability of climate variables across the state, and a large spread of runoff across the GCMs is driven by a large precipitation spread across the GCMs. Our new ensemble datasets assist with state-wide climate adaptation and other water planning.
Surface and subsurface moored buoy, ship-based, remotely sensed, and reanalysis datasets are used to investigate thermal variability of northern Gulf of Alaska (NGA) nearshore, coastal, and offshore waters over synoptic to century-long time scales. NGA sea surface temperature (SST) showed a larger positive trend of 0.22 ± 0.10 °C per decade over 1970–2021 compared to 0.10 ± 0.03 °C per decade over 1900–2021. Over synoptic time scales, SST covariance between two stations is small (<10%) when separation exceeds 100 km, while stations separated by 500 km retain 50% of their co-variability for seasonal and longer fluctuations. Relative to in situ sensor data, remotely sensed SST data has limited accuracy in some NGA settings, capturing 60–70% of the daily SST anomaly in coastal and offshore waters, but often <25% nearshore. North Pacific and NGA leading modes of SST variability leave 25–50% of monthly variance unresolved. Analysis of the 2014–2016 Pacific marine heatwave shows that NGA coastal surface temperatures warmed contemporaneously with offshore waters through 2013, but deep inner shelf waters (200–250 m) exhibited delayed warming. Offshore surface waters cooled from 2014 to 2016, while shelf waters continued to warm from the combined effects of local air-sea and advective heat fluxes. We find that annually averaged Sitka air temperature is a leading predictor (r2 = 0.37, p < 0.05) for following-year NGA coastal water column temperature. Our results can inform future environmental monitoring designs, assist forward-looking projections of marine conditions, and show the importance of in situ measurements for nearshore studies that require knowledge of thermal conditions over time scales of days and weeks.
Coastal wetlands provide key ecosystem services, including substantial long-term storage of atmospheric CO2 in soil organic carbon pools. This accumulation of soil organic matter is a vital component of elevation gain in coastal wetlands responding to sea-level rise. Anthropogenic activities that alter coastal wetland function through disruption of tidal exchange and wetland water levels are ubiquitous. This study assesses soil vertical accretion and organic carbon accretion across five coastal wetlands that experienced over a century of impounded hydrology, followed by restoration of tidal exchange 5 to 14 years prior to sampling. Nearby marshes that never experienced tidal impoundment served as controls with natural hydrology to assess the impact of impoundment and restoration. Dated soil cores indicate that elevation gain and carbon storage were suppressed 30–70 % during impoundment, accounting for the majority of elevation deficit between impacted and natural sites. Only one site had substantial subsidence, likely due to oxidation of soil organic matter. Vertical and carbon accretion gains were achieved at all restored sites, with carbon burial increasing from 96 ± 33 to 197 ± 64 g C m−2 y−1. The site with subsidence was able to accrete at double the rate (13 ± 5.6 mm y−1) of the natural complement, due predominantly to organic matter accumulation rather than mineral deposition, indicating these ecosystems are capable of large dynamic responses to restoration when conditions are optimized for vegetation growth. Hydrologic restoration enhanced elevation resilience and climate benefits of these coastal wetlands.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2022.157682","usgsCitation":"Eagle, M.J., Kroeger, K.D., Spivak, A.C., Wang, F., Tang, J., Abdul-Aziz, O.I., Ishtiaq, K.S., O’Keefe Suttles, J.A., and Mann, A.G., 2022, Soil carbon consequences of historic hydrologic impairment and recent restoration in coastal wetlands: Science of the Total Environment, v. 848, 157682, 12 p., https://doi.org/10.1016/j.scitotenv.2022.157682.","productDescription":"157682, 12 p.","ipdsId":"IP-140249","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446890,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2022.157682","text":"Publisher Index Page"},{"id":405111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.56655883789062,\n 41.693424216151314\n ],\n [\n -69.96231079101562,\n 41.693424216151314\n ],\n [\n -69.96231079101562,\n 41.87262868373214\n ],\n [\n -70.56655883789062,\n 41.87262868373214\n ],\n [\n -70.56655883789062,\n 41.693424216151314\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"848","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eagle, Meagan J. 0000-0001-5072-2755 meagle@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":242890,"corporation":false,"usgs":true,"family":"Eagle","given":"Meagan","email":"meagle@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":848842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":848843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spivak, Amanda C.","contributorId":191376,"corporation":false,"usgs":false,"family":"Spivak","given":"Amanda","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":848844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wang, Faming","contributorId":216959,"corporation":false,"usgs":false,"family":"Wang","given":"Faming","email":"","affiliations":[{"id":39553,"text":"The Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA","active":true,"usgs":false}],"preferred":false,"id":848845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tang, Jianwu","contributorId":174890,"corporation":false,"usgs":false,"family":"Tang","given":"Jianwu","email":"","affiliations":[{"id":27818,"text":"The Ecosystems Center, Marine Biological Laboratory. Woods Hole, MA 02543.","active":true,"usgs":false}],"preferred":false,"id":848846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Abdul-Aziz, Omar I.","contributorId":192386,"corporation":false,"usgs":false,"family":"Abdul-Aziz","given":"Omar","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":848847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ishtiaq, Khandker S.","contributorId":211669,"corporation":false,"usgs":false,"family":"Ishtiaq","given":"Khandker","email":"","middleInitial":"S.","affiliations":[{"id":38311,"text":"Department of Civil and Environmental Engineering, West Virginia University, PO Box 6103, Morgantown, WV 26506","active":true,"usgs":false}],"preferred":false,"id":848848,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"O’Keefe Suttles, Jennifer A. 0000-0003-2345-5633","orcid":"https://orcid.org/0000-0003-2345-5633","contributorId":202609,"corporation":false,"usgs":true,"family":"O’Keefe Suttles","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":848849,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mann, Adrian G. 0000-0003-1689-8524 adriangreen@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-8524","contributorId":4328,"corporation":false,"usgs":true,"family":"Mann","given":"Adrian","email":"adriangreen@usgs.gov","middleInitial":"G.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":848850,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70234258,"text":"70234258 - 2022 - Understanding impacts of sea-level rise and land management on critical coastal marsh habitat","interactions":[],"lastModifiedDate":"2022-10-21T15:45:16.955892","indexId":"70234258","displayToPublicDate":"2022-08-05T10:39:33","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"title":"Understanding impacts of sea-level rise and land management on critical coastal marsh habitat","docAbstract":"Coastal wetlands in the Louisiana Mississippi River Deltaic Plain (MRDP) experience some of the highest rates of relative sea-level rise (SLR) in the world, leading to elevated surface water salinity and prolonged flooding. Elevated salinity causes a shift toward more salt-tolerant vegetation communities, associated with changes in ecosystem function and services. As sea level continues to rise, even salt-tolerant plant communities succumb to impacts of excessive flooding through submergence and conversion to open water. To better characterize the impacts of SLR on coastal wetland health and sustainability, we focused on two key landscape transitions in this project: 1) freshwater marsh transition to saltwater marsh, and 2) saltwater marsh transition to open water. We investigated these transitions using data with greater spatial and temporal resolution than previous studies in this region, allowing us to identify the mechanisms underlying widely observed landscape changes.
","language":"English","publisher":"South Central Climate Adaptation Science Center","usgsCitation":"Stagg, C., 2022, Understanding impacts of sea-level rise and land management on critical coastal marsh habitat: Final Report, 20 p.","productDescription":"20 p.","ipdsId":"IP-143747","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":408614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":404866,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f8c652fe4b0546c0c397b4a/5f315e4482ceae4cb3ca5195"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mississippi River deltaic plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.50590005310218,\n 29.42101094649145\n ],\n [\n -89.50590005310218,\n 30.0568363860655\n ],\n [\n -90.26633984845733,\n 30.0568363860655\n ],\n [\n -90.26633984845733,\n 29.42101094649145\n ],\n [\n -89.50590005310218,\n 29.42101094649145\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":222386,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":848355,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70234253,"text":"70234253 - 2022 - Microbial community response to a bioaugmentation test to degrade trichloroethylene in a fractured rock aquifer, Trenton, N.J","interactions":[],"lastModifiedDate":"2022-08-05T14:00:18.164559","indexId":"70234253","displayToPublicDate":"2022-08-05T08:46:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2729,"text":"Microbial Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Microbial community response to a bioaugmentation test to degrade trichloroethylene in a fractured rock aquifer, Trenton, N.J","docAbstract":"Bioaugmentation is a promising strategy for enhancing trichloroethylene (TCE) degradation in fractured rock. However, slow or incomplete biodegradation can lead to stalling at degradation byproducts such as 1,2-dichloroethene (cis-DCE) and vinyl chloride (VC). Over the course of 7 years, we examined the response of groundwater microbial populations in a bioaugmentation test where an emulsified vegetable oil solution (EOS®) and a dechlorinating consortium (KB-1®), containing the established dechlorinator Dehalococcoides (DHC), were injected into a TCE-contaminated fractured rock aquifer. Indigenous microbial communities responded within 2 days to added substrate and outcompeted KB-1®, and over the years of monitoring, several other notable turnover events were observed. Concentrations of ethene, the end product in reductive dechlorination, had the strongest correlations (P< .05) with members of Candidatus Colwellbacteria but their involvement in reductive dechlorination is unknown and warrants further investigation.DHC never exceeded 0.6% relative abundance of groundwater microbial communities, despite its previously presumed importance at the site. Increased concentrations of carbon dioxide, acetic acid, and methane were positively correlated with increasing ethene concentrations; however, concentrations of cis-DCE and VC remained high by the end of the monitoring period suggesting preferential enrichment of indigenous partial dechlorinators over bioaugmented complete dechlorinators. This study highlights the importance of characterizing in situ microbial populations to understand how they can potentially enhance or inhibit augmented TCE degradation.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/femsec/fiac077","usgsCitation":"Underwood, J.C., Akob, D., Lorah, M.M., Imbrigiotta, T.E., Harvey, R.W., and Tiedeman, C.R., 2022, Microbial community response to a bioaugmentation test to degrade trichloroethylene in a fractured rock aquifer, Trenton, N.J: Microbial Ecology, v. 98, no. 7, fiac077, 16 p., https://doi.org/10.1093/femsec/fiac077.","productDescription":"fiac077, 16 p.","ipdsId":"IP-136036","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":446899,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/femsec/fiac077","text":"Publisher Index Page"},{"id":435740,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RCWZPH","text":"USGS data release","linkHelpText":"Microbial community analyses of groundwater collected during an enhanced bioremediation experiment of trichlorethylene in a fractured rock aquifer, West Trenton, NJ (2008-2015)"},{"id":404875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","city":"Trenton","otherGeospatial":"Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.81015682220459,\n 40.26737800407964\n ],\n [\n -74.80513572692871,\n 40.27612061363972\n ],\n [\n -74.80620861053467,\n 40.27726656481315\n ],\n [\n -74.80620861053467,\n 40.277855903568465\n ],\n [\n -74.80582237243652,\n 40.27903456566876\n ],\n [\n -74.80449199676514,\n 40.28001676838985\n ],\n [\n -74.80384826660156,\n 40.28093347805573\n ],\n [\n -74.80393409729004,\n 40.28227578049736\n ],\n [\n -74.80462074279785,\n 40.28315972120923\n ],\n [\n -74.80582237243652,\n 40.283847222661024\n ],\n [\n -74.80753898620605,\n 40.28407638825784\n ],\n [\n -74.80955600738525,\n 40.28437102859794\n ],\n [\n -74.81015682220459,\n 40.28391269862511\n ],\n [\n -74.8119592666626,\n 40.28355258003785\n ],\n [\n -74.81316089630127,\n 40.28342162734864\n ],\n [\n -74.81380462646484,\n 40.283749008596\n ],\n [\n -74.81393337249756,\n 40.28443650405466\n ],\n [\n -74.81462001800536,\n 40.28515672989297\n ],\n [\n -74.81569290161133,\n 40.285385891050446\n ],\n [\n -74.81676578521729,\n 40.2853531537898\n ],\n [\n -74.81959819793701,\n 40.283847222661024\n ],\n [\n -74.8218297958374,\n 40.28122813209425\n ],\n [\n -74.82221603393555,\n 40.28057334359796\n ],\n [\n -74.82208728790283,\n 40.27978758903121\n ],\n [\n -74.82079982757568,\n 40.278641680585025\n ],\n [\n -74.82058525085449,\n 40.277757680799304\n ],\n [\n -74.82191562652588,\n 40.273304765410735\n ],\n [\n -74.82174396514893,\n 40.272813617082406\n ],\n [\n -74.82213020324707,\n 40.271765822059926\n ],\n [\n -74.82414722442626,\n 40.27058703325471\n ],\n [\n -74.82354640960693,\n 40.269735673006274\n ],\n [\n -74.8218297958374,\n 40.26858959420978\n ],\n [\n -74.8192548751831,\n 40.26580617913769\n ],\n [\n -74.81462001800536,\n 40.268098411637695\n ],\n [\n -74.81015682220459,\n 40.26737800407964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"98","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-06-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Underwood, Jennifer C. 0000-0002-2702-0410 jcunder@usgs.gov","orcid":"https://orcid.org/0000-0002-2702-0410","contributorId":294555,"corporation":false,"usgs":true,"family":"Underwood","given":"Jennifer","email":"jcunder@usgs.gov","middleInitial":"C.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":848344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Akob, Denise M. 0000-0003-1534-3025","orcid":"https://orcid.org/0000-0003-1534-3025","contributorId":204701,"corporation":false,"usgs":true,"family":"Akob","given":"Denise M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":848345,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorah, Michelle M. 0000-0002-9236-587X","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":224040,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","middleInitial":"M.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":848346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Imbrigiotta, Thomas E. 0000-0003-1716-4768 timbrig@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-4768","contributorId":152114,"corporation":false,"usgs":true,"family":"Imbrigiotta","given":"Thomas","email":"timbrig@usgs.gov","middleInitial":"E.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":848347,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harvey, Ronald W. 0000-0002-2791-8503","orcid":"https://orcid.org/0000-0002-2791-8503","contributorId":294558,"corporation":false,"usgs":false,"family":"Harvey","given":"Ronald","email":"","middleInitial":"W.","affiliations":[{"id":63603,"text":"U.S. Geological Survey, Water Mission Area, ESPD","active":true,"usgs":false}],"preferred":false,"id":848349,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tiedeman, Claire R. 0000-0002-0128-3685 tiedeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0128-3685","contributorId":196777,"corporation":false,"usgs":true,"family":"Tiedeman","given":"Claire","email":"tiedeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":848348,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70234246,"text":"70234246 - 2022 - Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams","interactions":[],"lastModifiedDate":"2022-08-05T13:15:34.056536","indexId":"70234246","displayToPublicDate":"2022-08-05T08:08:29","publicationYear":"2022","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":"Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams","docAbstract":"In mountain headwater streams, the quality and resilience of summer cold-water habitat is generally regulated by stream discharge, longitudinal stream channel connectivity and groundwater exchange. These critical hydrologic processes are thought to be influenced by the stream corridor bedrock contact depth (sediment thickness), a parameter often inferred from sparse hillslope borehole information, piezometer refusal and remotely sensed data. To investigate how local bedrock depth might control summer stream temperature and channel disconnection (dewatering) patterns, we measured stream corridor bedrock depth by collecting and interpreting 191 passive seismic datasets along eight headwater streams in Shenandoah National Park (Virginia, USA). In addition, we used multi-year stream temperature and streamflow records to calculate several baseflow-related metrics along and among the study streams. Finally, comprehensive visual surveys of stream channel dewatering were conducted in 2016, 2019 and 2021 during summer low flow conditions (124 total km of stream length). We found that measured bedrock depths along the study streams were not well-characterized by soils maps or an existing global-scale geologic dataset where the latter overpredicted measured depths by 12.2 m (mean) or approximately four times the average bedrock depth of 2.9 m. Half of the eight study stream corridors had an average bedrock depth of less than 2 m. Of the eight study streams, Staunton River had the deepest average bedrock depth (3.4 m), the coldest summer temperature profiles and substantially higher summer baseflow indices compared to the other study steams. Staunton River also exhibited paired air and water annual temperature signals suggesting deeper groundwater influence, and the stream channel did not dewater in lower sections during any baseflow survey. In contrast, Paine Run and Piney River did show pronounced, patchy channel dewatering, with Paine Run having dozens of discrete dry channel sections ranging from 1 to greater than 300 m in length. Stream dewatering patterns were apparently influenced by a combination of discrete deep bedrock (20+ m) features and more subtle sediment thickness variation (1–4 m) depending on local stream valley hydrogeology. In combination, these unique datasets show the first large-scale empirical support for existing conceptual models of headwater stream disconnection based on spatially variable underflow capacity and shallow groundwater supply.","language":"English","publisher":"Copernicus","doi":"10.5194/hess-26-3989-2022","usgsCitation":"Briggs, M., Goodling, P.J., Johnson, Z., Rogers, K., Hitt, N.P., Fair, J.H., and Snyder, C.D., 2022, Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams: Hydrology and Earth System Sciences, v. 26, no. 15, p. 3989-4011, https://doi.org/10.5194/hess-26-3989-2022.","productDescription":"23 p.","startPage":"3989","endPage":"4011","ipdsId":"IP-132407","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - 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2022 - Status of water-level altitudes and long-term water-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021","interactions":[],"lastModifiedDate":"2022-08-19T14:18:51.913895","indexId":"sir20225065","displayToPublicDate":"2022-08-05T07:27:23","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5065","displayTitle":"Status of Water-Level Altitudes and Long-Term Water-Level Changes in the Chicot and Evangeline (Undifferentiated) and Jasper Aquifers, Greater Houston Area, Texas, 2021","title":"Status of water-level altitudes and long-term water-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021","docAbstract":"Since the early 1900s, groundwater withdrawn from the primary aquifers that compose the Gulf Coast aquifer system—the Chicot and Evangeline (undifferentiated) and Jasper aquifers—has been the primary source of water in the greater Houston area, Texas. This report, prepared by the U.S. Geological Survey in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District, is one in an annual series of reports depicting the status of water-level altitudes and water-level changes in aquifers in the greater Houston area.
In contrast to previous reports, the Chicot and Evangeline aquifers are treated as a single hydrogeologic unit in this report. In 2021, shaded depictions of water-level altitudes for the Chicot and Evangeline aquifers (undifferentiated) ranged from 300 feet (ft) below the North American Vertical Datum of 1988 (NAVD 88) to 300 ft above NAVD 88. The largest decline in water-level altitudes indicated by the 1977–2021 long-term water-level-change map for the Chicot and Evangeline aquifers (undifferentiated) was in the north-central part of The Woodlands, Tex., whereas the 1990–2021 long-term water-level-change map for the Chicot and Evangeline aquifers (undifferentiated) depicts a large area of decline in water-level altitudes in northwestern Harris County, northwest of Jersey Village, Tex. The largest rise in water-level altitudes in the Chicot and Evangeline aquifers (undifferentiated) was observed in a relatively large area in southeastern Harris County for 1977–2021, whereas the largest rise in water-level altitudes for 1990–2021 was in a relatively large area in central Harris County.
In 2021, shaded depictions of water-level altitudes for the Jasper aquifer ranged from 250 ft below NAVD 88 to 300 ft above NAVD 88. The 2000–21 long-term water-level-change map for the Jasper aquifer depicts water-level declines throughout most of the study area where water-level-altitude data from the Jasper aquifer were collected, with the largest decline in northern Harris County southwest of The Woodlands.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225065","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District","usgsCitation":"Braun, C.L., and Ramage, J.K., 2022, Status of water-level altitudes and long-term water-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021 (ver. 1.1, August 19, 2022): U.S. Geological Survey Scientific Investigations Report 2022–5065, 25 p., https://doi.org/10.3133/sir20225065.","productDescription":"Report: iv, 25 p.; Data Releases; Dataset","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-127697","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":405340,"rank":9,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2022/5065/versionHist.txt","text":"Version History","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":405339,"rank":8,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5065/sir20225065.pdf","text":"Report","size":"13.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5065"},{"id":405338,"rank":7,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5065/coverthb2.jpg"},{"id":404816,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T8FJWO","text":"USGS data release","linkHelpText":"Groundwater-level altitudes and long-term groundwater-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021"},{"id":404817,"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":404815,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R6CX2T","text":"USGS data release","linkHelpText":"Depth to groundwater measured from wells completed in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021"},{"id":404813,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5065/images"},{"id":404812,"rank":1,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5065/sir20225065.XML"},{"id":404820,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225064","text":"Scientific Investigations Report 2022–5064","linkHelpText":"—Treatment of the Chicot and Evangeline aquifers as a single hydrogeologic unit and use of geostatistical interpolation methods to develop gridded surfaces of water-level altitudes and water-level changes in the Chicot and Evangeline aquifers (undifferentiated) and Jasper aquifer, greater Houston area, Texas, 2021"}],"country":"United States","state":"Texas","otherGeospatial":"Greater Houston area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.185302734375,\n 28.82061274169944\n ],\n [\n -94.757080078125,\n 28.82061274169944\n ],\n [\n -94.757080078125,\n 30.590637026892917\n ],\n [\n -96.185302734375,\n 30.590637026892917\n ],\n [\n -96.185302734375,\n 28.82061274169944\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: August 5, 2022; Version 1.1: August 19, 2022","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
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The greater Houston area of Texas includes approximately 11,000 square miles and encompasses all or part of 11 counties (Harris, Galveston, Fort Bend, Montgomery, Brazoria, Chambers, Grimes, Liberty, San Jacinto, Walker, and Waller). From the early 1900s until the mid-1970s, groundwater withdrawn from the three primary aquifers that compose the Gulf Coast aquifer system—the Chicot, Evangeline, and Jasper aquifers—had been the primary source of water for the greater Houston area. The withdrawal of groundwater was unregulated prior to 1975, resulting in land-surface subsidence caused by large water-level declines in the greater Houston area.
This report, prepared by the U.S. Geological Survey in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District, describes updates to the ways in which water-level altitudes and water-level changes in the greater Houston area are presented relative to previous U.S. Geological Survey reports. The first update involves presenting water-level altitudes and water-level changes as a combined (undifferentiated) representation of the Chicot and Evangeline aquifers. The second update concerns the methods used to depict water-level altitudes and water-level changes in the greater Houston area in interpretive reports, with geostatistical interpolation methods replacing manual contouring methods.
The Chicot and Evangeline aquifers have historically been described as distinct hydrogeologic units for the purpose of water-level mapping. A confining unit does not separate these two aquifers in the study area, and water-level data from colocated wells screened in these aquifers indicate that there is likely a substantial degree of hydrogeologic connection. From a groundwater-flow perspective, these two aquifer units predominantly function as a single unit. Hence, the decision was made to combine the Chicot and Evangeline aquifers into a single, undifferentiated hydrogeologic unit for the purposes of assessing water-level altitudes and water-level changes over time. The 2020 water-level altitudes for the Chicot, Evangeline, and Jasper aquifers were re-created in this report from computer algorithms of the contoured datasets as gridded surfaces to demonstrate the similarity of results from geostatistical interpolation methods to those from manual contouring methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225064","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District","usgsCitation":"Ramage, J.K., Braun, C.L., and Ellis, J.H., 2022, Treatment of the Chicot and Evangeline aquifers as a single hydrogeologic unit and use of geostatistical interpolation methods to develop gridded surfaces of water-level altitudes and water-level changes in the Chicot and Evangeline aquifers (undifferentiated) and Jasper aquifer, greater Houston area, Texas, 2021: U.S. Geological Survey Scientific Investigations Report 2022–5064, 51 p., https://doi.org/10.3133/sir20225064.","productDescription":"Report: vi, 51 p.; Data Release; Dataset","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-134432","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":404777,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":404775,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5064/images"},{"id":404774,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5064/sir20225064.XML"},{"id":404821,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20225065","text":"Scientific Investigations Report 2022–5065","linkHelpText":"—Status of water-level altitudes and long-term water-level changes in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021"},{"id":404776,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R6CX2T","text":"USGS data release","linkHelpText":"Depth to groundwater measured from wells completed in the Chicot and Evangeline (undifferentiated) and Jasper aquifers, greater Houston area, Texas, 2021"},{"id":404771,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5064/coverthb.jpg"},{"id":404772,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5064/sir20225064.pdf","text":"Report","size":"23.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5064"}],"country":"United States","state":"Texas","otherGeospatial":"Greater Houston area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.185302734375,\n 28.82061274169944\n ],\n [\n -94.757080078125,\n 28.82061274169944\n ],\n [\n -94.757080078125,\n 30.590637026892917\n ],\n [\n -96.185302734375,\n 30.590637026892917\n ],\n [\n -96.185302734375,\n 28.82061274169944\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
As marine ecosystems respond to climate change and other stressors, it is necessary to evaluate current and past hybridization events to gain insight on the outcomes and drivers of such events. Ancestral introgression within the gadids has been suggested to allow cod to inhabit a variety of habitats. Little attention has been given to contemporary hybridization, especially within cold-water-adapted cod (Boreogadus saida Lepechin, 1774 and Arctogadus glacialis Peters, 1872). We used whole-genome, restriction-site associated, and mitochondrial sequence data to explore the degree and direction of hybridization between these species where previous hybridization had not been reported. Although nearly identical morphologically at certain life stages, we detected very distinct nuclear and mitochondrial lineages. We detected one potential hybrid with a Arctogadus mitochondrial haplotype and Boreogadus nuclear genotype, but no early generational hybrids. The presence of a late generation hybrid suggests that at least some hybrids survive to maturity and reproduce. However, a historical introgression event could not be excluded. Contemporary gene flow appears asymmetrical from Arctogadus into Boreogadus, which may be due to overlap in timing of spawning, environmental heterogeneity, or differences in population size. This study provides important baseline information for the degree of potential hybridization between these species within Alaska marine environments.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/as-2021-0030","usgsCitation":"Wilson, R.E., Sonsthagen, S.A., Lavretsky, P., Majewski, A., Arnason, E., Halldorsdottir, K., Einarsson, A., Wedemeyr, K., and Talbot, S.L., 2022, Low levels of hybridization between sympatric cold-water-adapted Arctic cod and Polar cod in the Beaufort Sea confirm genetic distinctiveness: Arctic Science, v. 8, no. 4, p. 1082-1093, https://doi.org/10.1139/as-2021-0030.","productDescription":"12 p.","startPage":"1082","endPage":"1093","ipdsId":"IP-130423","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446914,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/as-2021-0030","text":"Publisher Index Page"},{"id":433449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Beaufort Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -174.72007918044827,\n 75.06986491260304\n ],\n [\n -174.76506022895288,\n 69.14800723197729\n ],\n [\n -166.15259714556063,\n 69.52600683358969\n ],\n [\n -156.95456159243057,\n 71.39604084905038\n ],\n [\n -136.81825817727585,\n 69.54036567664357\n ],\n [\n -129.58194373827234,\n 70.33510131179872\n ],\n [\n -126.37318701117965,\n 74.99060622515827\n ],\n [\n -174.72007918044827,\n 75.06986491260304\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Robert E.","contributorId":293234,"corporation":false,"usgs":false,"family":"Wilson","given":"Robert","email":"","middleInitial":"E.","affiliations":[{"id":63255,"text":"Nebraska State Museum","active":true,"usgs":false}],"preferred":false,"id":908846,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sonsthagen, Sarah A. 0000-0001-6215-5874 ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":908847,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lavretsky, P.","contributorId":341733,"corporation":false,"usgs":false,"family":"Lavretsky","given":"P.","affiliations":[{"id":36422,"text":"University of Texas","active":true,"usgs":false}],"preferred":false,"id":908848,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Majewski, A.","contributorId":341734,"corporation":false,"usgs":false,"family":"Majewski","given":"A.","email":"","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":908849,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arnason, E.","contributorId":341736,"corporation":false,"usgs":false,"family":"Arnason","given":"E.","email":"","affiliations":[{"id":36649,"text":"University of Iceland","active":true,"usgs":false}],"preferred":false,"id":908850,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Halldorsdottir, K.","contributorId":341738,"corporation":false,"usgs":false,"family":"Halldorsdottir","given":"K.","email":"","affiliations":[{"id":36649,"text":"University of Iceland","active":true,"usgs":false}],"preferred":false,"id":908851,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Einarsson, A.W.","contributorId":341742,"corporation":false,"usgs":false,"family":"Einarsson","given":"A.W.","email":"","affiliations":[{"id":36649,"text":"University of Iceland","active":true,"usgs":false}],"preferred":false,"id":908852,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wedemeyr, K.","contributorId":341745,"corporation":false,"usgs":false,"family":"Wedemeyr","given":"K.","email":"","affiliations":[{"id":20318,"text":"Bureau of Ocean Energy Management","active":true,"usgs":false}],"preferred":false,"id":908853,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":908854,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70234228,"text":"70234228 - 2022 - Distribution and trends of endemic Hawaiian waterbirds","interactions":[],"lastModifiedDate":"2022-08-04T14:39:59.491066","indexId":"70234228","displayToPublicDate":"2022-08-04T09:34:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Distribution and trends of endemic Hawaiian waterbirds","docAbstract":"Four endemic species of wetland-dependent waterbirds occur on the main Hawaiian Islands, all of which have experienced sharp population declines and are listed as endangered species. Twice per year, state-wide surveys are conducted to count waterbirds, but these surveys are evaluated only infrequently. We used a state-space approach to evaluate long-term (1986–2016) and short-term (2006–2016) trends and current distribution and abundance of endemic Hawaiian waterbirds. The most numerous species was the Ae‘o, or Hawaiian Stilt (Himantopus mexicanus knudseni), with a 5-year estimated average abundance of 1,932 individuals, followed by ‘Alae Ke‘oke‘o, or Hawaiian Coot (Fulica alai), with 1,815 individuals, Alae ‘Ula, or Hawaiian Common Gallinule (Gallinula galeata sandvicensis) with 927 individuals, and the Koloa Maoli, or Hawaiian Duck (Anas wyvilliana) with 931 individuals. All four species had positive trends over the long-term, but short-term and island specific trends were more variable, and in some cases negative. These results provide valuable information to help guide management of Hawaii’s threatened and endangered endemic waterbirds.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.044.0404","usgsCitation":"Paxton, E.H., Brinck, K., Henry, A., Siddiqi, A., Rounds, R.A., and Chutz, J., 2022, Distribution and trends of endemic Hawaiian waterbirds: Waterbirds, v. 44, no. 4, p. 425-437, https://doi.org/10.1675/063.044.0404.","productDescription":"13 p.","startPage":"425","endPage":"437","ipdsId":"IP-124419","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":404825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"44","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Paxton, Eben H. 0000-0001-5578-7689","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":19640,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben","email":"","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":848245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":3847,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","email":"kbrinck@usgs.gov","affiliations":[],"preferred":false,"id":848246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henry, Adonia","contributorId":294527,"corporation":false,"usgs":false,"family":"Henry","given":"Adonia","email":"","affiliations":[{"id":63590,"text":"Scaup & Willet LLC","active":true,"usgs":false}],"preferred":false,"id":848247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siddiqi, Afsheen","contributorId":294528,"corporation":false,"usgs":false,"family":"Siddiqi","given":"Afsheen","email":"","affiliations":[{"id":56397,"text":"State of Hawai‘i, Division of Forestry and Wildlife","active":true,"usgs":false}],"preferred":false,"id":848248,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rounds, Rachel A.","contributorId":290249,"corporation":false,"usgs":false,"family":"Rounds","given":"Rachel","email":"","middleInitial":"A.","affiliations":[{"id":62393,"text":"U.S. Fish and Wildlife Service, Pacific Islands Refuges and Monuments Office","active":true,"usgs":false}],"preferred":false,"id":848249,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chutz, Jennifer","contributorId":294529,"corporation":false,"usgs":false,"family":"Chutz","given":"Jennifer","email":"","affiliations":[{"id":63592,"text":"DCI West Biological Consulting LLC","active":true,"usgs":false}],"preferred":false,"id":848250,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70234234,"text":"70234234 - 2022 - Freshwater unionid mussels threatened by predation of Round Goby (Neogobius melanostomus)","interactions":[],"lastModifiedDate":"2022-08-04T14:05:53.114941","indexId":"70234234","displayToPublicDate":"2022-08-04T08:57:15","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Freshwater unionid mussels threatened by predation of Round Goby (Neogobius melanostomus)","title":"Freshwater unionid mussels threatened by predation of Round Goby (Neogobius melanostomus)","docAbstract":"Indigenous freshwater mussels (Unionidae) are integral to riverine ecosystems, playing a pivotal role in aquatic food webs and providing ecological services. With populations on the decline worldwide, freshwater mussels are of conservation concern. In this study, we explore the propensity of the invasive Round Goby (Neogobius melanostomus) fish to prey upon indigenous freshwater mussels. First, we conducted lab experiments where Round Gobies were given the opportunity to feed on juvenile unionid mussels and macroinvertebrates, revealing rates and preferences of consumption. Several Round Gobies consumed whole freshwater mussels during these experiments, as confirmed by mussel counts and x-ray images of the fishes. Next, we investigated Round Gobies collected from stream habitats of the French Creek watershed, which is renowned for its unique and rich aquatic biodiversity. We developed a novel DNA metabarcoding method to identify the specific species of mussels consumed by Round Goby and provide a new database of DNA gene sequences for 25 indigenous unionid mussel species. Several of the fishes sampled had consumed indigenous mussels, including the Elktoe (non-endangered), Creeper (non-endangered), Long Solid (state endangered), and Rayed Bean (federally endangered) species. The invasive Round Goby poses a growing threat to unionid mussels, including species of conservation concern. The introduction of the invasive Round Goby to freshwaters of North America is shaping ecosystem transitions within the aquatic critical zone having widespread implications for conservation and management.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-022-16385-y","usgsCitation":"Clark, K., Iwanowicz, D.D., Iwanowicz, L., Mueller, S., Wisor, J., Bradshaw-Wilson, C., Schill, W., Stauffer, J.R., and Boyer, E.W., 2022, Freshwater unionid mussels threatened by predation of Round Goby (Neogobius melanostomus): Scientific Reports, v. 12, 12859, 11 p., https://doi.org/10.1038/s41598-022-16385-y.","productDescription":"12859, 11 p.","ipdsId":"IP-137170","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446924,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-022-16385-y","text":"Publisher Index Page"},{"id":404822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, New York, Pennsylvania, West Virginia","otherGeospatial":"Allegheny River Basin, Monongahela River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.815673828125,\n 38.37611542403604\n ],\n [\n -79.70581054687499,\n 38.634036452919226\n ],\n [\n -78.99169921875,\n 39.01064750994083\n ],\n [\n -78.607177734375,\n 39.47860556892209\n ],\n [\n -78.64013671875,\n 39.985538414809746\n ],\n [\n -78.2666015625,\n 40.64730356252251\n ],\n [\n -77.34374999999999,\n 41.21998578493921\n ],\n [\n -77.2119140625,\n 42.27730877423709\n ],\n [\n -77.662353515625,\n 42.771211138625894\n ],\n [\n -78.914794921875,\n 42.78733853171998\n ],\n [\n -80.518798828125,\n 41.9921602333763\n ],\n [\n -80.13427734374999,\n 41.15384235711447\n ],\n [\n -80.628662109375,\n 38.77978137804918\n ],\n [\n -80.035400390625,\n 38.40194908237822\n ],\n [\n -79.815673828125,\n 38.37611542403604\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2022-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Clark, Kyle","contributorId":294537,"corporation":false,"usgs":false,"family":"Clark","given":"Kyle","email":"","affiliations":[{"id":63593,"text":"Penn State University, Pennsylvania Fish & Boat Commission","active":true,"usgs":false}],"preferred":false,"id":848276,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594 diwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":2253,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah","email":"diwanowicz@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":848278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":79382,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":848277,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mueller, Sara","contributorId":294538,"corporation":false,"usgs":false,"family":"Mueller","given":"Sara","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":848279,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wisor, Joshua","contributorId":294539,"corporation":false,"usgs":false,"family":"Wisor","given":"Joshua","email":"","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":848280,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bradshaw-Wilson, Casey","contributorId":294540,"corporation":false,"usgs":false,"family":"Bradshaw-Wilson","given":"Casey","email":"","affiliations":[{"id":63066,"text":"Allegheny College","active":true,"usgs":false}],"preferred":false,"id":848281,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schill, W. Bane 0000-0002-9217-984X","orcid":"https://orcid.org/0000-0002-9217-984X","contributorId":213903,"corporation":false,"usgs":true,"family":"Schill","given":"W. Bane","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":848282,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stauffer, Jay R. Jr.","contributorId":119700,"corporation":false,"usgs":false,"family":"Stauffer","given":"Jay","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":848283,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":848284,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70234221,"text":"sir20225030 - 2022 - Sediment and nutrient retention on a reconnected floodplain of an Upper Mississippi River tributary, 2013–2018","interactions":[],"lastModifiedDate":"2026-04-09T17:11:54.43681","indexId":"sir20225030","displayToPublicDate":"2022-08-04T07:15:52","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5030","displayTitle":"Sediment and Nutrient Retention on a Reconnected Floodplain of an Upper Mississippi River Tributary, 2013–2018","title":"Sediment and nutrient retention on a reconnected floodplain of an Upper Mississippi River tributary, 2013–2018","docAbstract":"The connection of rivers with their floodplains has been greatly reduced in agricultural drainage basins, especially in the Upper Mississippi River Basin. The restriction of the Mississippi River from its floodplain has reduced the sediment trapping and nutrient deposition capabilities of the floodplain, exacerbating water quality problems in the river and in downstream waterbodies. A small part of the Maquoketa River, a tributary to the Upper Mississippi River, was permanently reconnected to its floodplain in 2010 when a levee failure resulted in breaches in two locations. This study quantified the water quality benefits of that reconnection from October 2013 through September 2018. As part of the study, data from groundwater monitoring wells were used to determined hydraulic connectivity and surface-water/groundwater mixing; soil samples were collected in the floodplain to quantify floodplain sediment and nutrient retention potential during postflood and dry, interflood periods; and sensors were placed in the Maquoketa River to quantify total suspended solids, nitrogen, and phosphorus concentrations and loads.
The floodplain aquifer in the study area had low hydraulic gradients toward the Maquoketa (mean of 0.017) and Mississippi Rivers (mean of 0.0029) and reducing water-quality conditions (dissolved oxygen less than 1.0 milligram per liter [mg/L] and nitrate less than 0.04 mg/L as nitrogen) capable of denitrification. A specific conductance-based mixing indicated precipitation was the predominate source of groundwater; however, specific conductance-based mixing analysis was unable to distinguish between the river or direct precipitation as the source.
The floodplain was fully inundated five times during the study: in June–July 2014, March 2015, January 2017, February 2018, and September 2018. During the March 2015 flood (the only inundation event with sufficient duration to leave quantifiable sediment deposition in the study area), the equivalent of 0.91 percent of the nitrate load and 3.8 percent of the phosphorus load was deposited as sediment on the floodplain. Potential nitrogen losses on the floodplain because of denitrification ranged from 250 kilograms per day (kg/d) as nitrogen in March 2015 to 668 kg/d as nitrogen in October 2014. Potential denitrification rates indicate that when the soil is inundated, inorganic nitrogen present in the soil and in the water column is rapidly denitrified. Soil phosphorus measurements indicated that floodplain soils contain a mean of 365 milligrams per kilogram as phosphorus but still have the capacity to remove phosphorus from flood waters of the Maquoketa River depending on the surface water phosphorus concentration. Results from this study indicate that restoration of even small river-floodplain connections can improve water quality in the Upper Mississippi River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225030","collaboration":"Prepared in cooperation with the Eastern Tallgrass Prairie & Big Rivers Landscape Conservation Cooperative","usgsCitation":"Bartsch, L.A., Kreiling, R.M., Gruhn, L.R., Garrett, J.D., Richardson, W.B., and Nalley, G.M., 2022, Sediment and nutrient retention on a reconnected floodplain of an Upper Mississippi River Tributary, 2013–2018: U.S. Geological Survey Scientific Investigations Report 2022–5030, 27 p., https://doi.org/10.3133/sir20225030.","productDescription":"Report: viii, 27 p.; Data Releases; Datasets","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-121775","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":608,"text":"Upper Mississippi Science Center","active":false,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":404760,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9A12PVX","text":"USGS data release","linkHelpText":"Maquoketa River floodplain-river connectivity 2014-2016 data"},{"id":404761,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":404762,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://www.umesc.usgs.gov/data_library/water_quality/water_quality_data_page.html","text":"USGS Long Term Resource Monitoring Program database","linkHelpText":"—Long Term Resource Monitoring Program—Water Quality"},{"id":404757,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5030/coverthb.jpg"},{"id":502387,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113356.htm","linkFileType":{"id":5,"text":"html"}},{"id":404758,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5030/sir20225030.pdf","text":"Report","size":"7.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5030"}],"country":"United States","state":"Iowa","otherGeospatial":"Maquoketa River, Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.35,\n 42.1333\n ],\n [\n -90.2667,\n 42.1333\n ],\n [\n -90.2667,\n 42.1833\n ],\n [\n -90.35,\n 42.1833\n ],\n [\n -90.35,\n 42.1333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54602
In response to increasing groundwater demand and declining groundwater levels in the Harney Basin of southeastern Oregon, the U.S. Geological Survey and the Oregon Water Resources Department conducted a cooperative groundwater-availability study during 2016–22. This Fact Sheet summarizes the results of this study. Full details of the study are provided in Gingerich and others (2022a, 2022b), Garcia and others (2022), and the other supporting documents listed on the last page of this Fact Sheet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223052","collaboration":"Prepared in cooperation with the Oregon Water Resources Department","usgsCitation":"Gingerich, S.B., Garcia, C.A., and Johnson, H.M., 2022, Groundwater resources of the Harney Basin, southeastern Oregon (ver. 1.1, June 2025): U.S. Geological Survey Fact Sheet 2022–3052, 6 p., https://doi.org/10.3133/fs20223052.","productDescription":"Report: 6 p.; Data Release","ipdsId":"IP-140289","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":494145,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113361.htm","linkFileType":{"id":5,"text":"html"}},{"id":404793,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20215103","text":"Scientific Investigations Report 2021–5103","description":"SIR 2021–5103","linkHelpText":"- Groundwater resources of the Harney Basin, Oregon"},{"id":404792,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20215128","text":"Scientific Investigations Report 2021–5128","description":"SIR 2021–5128","linkHelpText":"- Hydrologic budget of the Harney Basin groundwater system, Oregon"},{"id":404791,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J0FE5M","text":"USGS data release","description":"USGS data release","linkHelpText":"Location information, discharge, and water-quality data for selected wells, springs, and streams in the Harney Basin, Oregon"},{"id":490440,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2022/3052/versionHistory.txt","description":"FS 2022-3052 version history"},{"id":404790,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3052/fs20223052.pdf","text":"Report","size":"5.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3052"},{"id":404789,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3052/coverthb2.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Harney Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.2783203125,\n 42.39912215986002\n ],\n [\n -117.94921874999999,\n 42.39912215986002\n ],\n [\n -117.94921874999999,\n 44.276671273775186\n ],\n [\n -120.2783203125,\n 44.276671273775186\n ],\n [\n -120.2783203125,\n 42.39912215986002\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: August 3, 2022; Version 1.1: June 11, 2025","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
911 NE 11th Avenue
Portland, Oregon 97232
Building continental-scale hydrologic models in data-sparse regions requires an understanding of spatial variation in hydrologic processes. Extending these models to ungaged locations requires techniques to group ungaged locations with gaged ones to make process importance and model parameter transfer decisions to ungaged locations. This analysis (1) tested the utility of fundamental streamflow statistics (FDSS) in defining hydrologic regions across Alaska, USA; (2) evaluated if the hydrologic regions represented different hydrologic processes; and (3) tested the ability of random forest and direct assignment techniques, informed by statistically estimated FDSS (FDSSest) and basin characteristics (BCs), to correctly assign ungaged locations to hydrologic regions. Six hydrologic regions were identified across the domain using FDSS. Differences in mean flow, phase shift of the seasonal cycle, and skewness were the primary characteristics defining each region. Two regions represented arctic and continental climates, generally in the northern portion of the domain; four regions represented the southern, maritime portion of the domain. Random forest modeling with BCs (67% success rate) outperformed FDSSest (58% success rate) suggesting that no statistically estimated streamflow was needed to assign ungaged locations to a region. For regions with many sites, most region assignment techniques performed similarly. Random forest modeling performance declined when BCs and FDSSest were both used to predict region membership, suggesting FDSSest had little information in addition to BCs. This analysis demonstrated that FDSS-based hydrologic regions discern process differences across a data-sparse and hydrologically diverse landscape. Process importance rankings from random forest-derived BCs provided model-independent information for making modeling decisions.
As sustainable development practitioners have worked to “ensure healthy lives and promote well-being for all” and “conserve life on land and below water”, what progress has been made with win–win interventions that reduce human infectious disease burdens while advancing conservation goals? Using a systematic literature review, we identified 46 proposed solutions, which we then investigated individually using targeted literature reviews. The proposed solutions addressed diverse conservation threats and human infectious diseases, and thus, the proposed interventions varied in scale, costs, and impacts. Some potential solutions had medium-quality to high-quality evidence for previous success in achieving proposed impacts in one or both sectors. However, there were notable evidence gaps within and among solutions, highlighting opportunities for further research and adaptive implementation. Stakeholders seeking win–win interventions can explore this Review and an online database to find and tailor a relevant solution or brainstorm new solutions.
Widespread stream network fragmentation from dams and culverts has altered habitat connectivity in river ecosystems and presents an acute threat to migratory fish. To support watershed management for an iconic migratory fish group, we assessed juvenile salmon growth outcomes across habitat use strategies and characterized how these life histories may be impacted by stream connectivity loss. Juvenile coho salmon (Oncorhynchus kisutch) in the Big Lake drainage, Alaska, USA, were individually tracked over 2012–2013 and categorized into habitat use behaviors, with fish either remaining in streams throughout freshwater residency or migrating seasonally to overwinter in lake habitats. Size, growth rate, and body condition of smolts (n = 1113) were compared across habitat use strategies. Juvenile coho salmon that moved seasonally to lake overwintering habitats, the most frequently observed strategy, grew faster and were significantly larger as smolts compared to their counterparts who remained in streams exclusively (spring Age 1 fish: 18% larger by weight, 9% faster growth rate; spring Age 2+ fish: 26% heavier, 11% faster growth). Environmental data from a subset of overwinter lakes indicate that greater foraging opportunity and lower energy costs may be implicated in growth advantages conferred by lentic overwintering strategies. Habitat use strategies requiring seasonal migrations, however, increased exposure to stream connectivity loss, and fish blocked from accessing a potential overwinter headwater lake by a culvert and dam had lowest body condition among study groups. Stream network fragmentation restricts access to preferred overwinter habitats, and our findings suggest this may constrain freshwater rearing strategies associated with strong juvenile coho salmon growth. As size at smolt has been implicated as a driver of salmon survival through ocean residency, reduced freshwater habitat connectivity during juvenile stages may have deleterious impacts on later marine life stages. Consequently, conservation of stream connectivity across lentic and lotic habitats represents an important watershed management priority for juvenile salmon.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4192","usgsCitation":"Sethi, S., Carey, M.P., Gerken, J., Harris, B., Wolf, N., Cunningham, C., Restrepo, F., and Ashline, J., 2022, Juvenile salmon habitat use drives variation in growth and highlights vulnerability to river fragmentation: Ecosphere, v. 13, no. 8, e4192, 14 p., https://doi.org/10.1002/ecs2.4192.","productDescription":"e4192, 14 p.","ipdsId":"IP-132334","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":489905,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4192","text":"Publisher Index Page"},{"id":481452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Big Lake watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -149.98177488959556,\n 61.59244437152677\n ],\n [\n -149.98177488959556,\n 61.46764452271171\n ],\n [\n -149.59522554516565,\n 61.46764452271171\n ],\n [\n -149.59522554516565,\n 61.59244437152677\n ],\n [\n -149.98177488959556,\n 61.59244437152677\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-08-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Sethi, Suresh 0000-0002-0053-1827 ssethi@usgs.gov","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":191424,"corporation":false,"usgs":true,"family":"Sethi","given":"Suresh","email":"ssethi@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":925435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":117,"text":"Alaska Science Center Biology WTEB","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":925436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerken, Jonathon","contributorId":350130,"corporation":false,"usgs":false,"family":"Gerken","given":"Jonathon","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":925437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, Bradley P.","contributorId":350131,"corporation":false,"usgs":false,"family":"Harris","given":"Bradley P.","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":925438,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolf, Nathan","contributorId":350132,"corporation":false,"usgs":false,"family":"Wolf","given":"Nathan","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":925439,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cunningham, Curry","contributorId":350133,"corporation":false,"usgs":false,"family":"Cunningham","given":"Curry","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":925440,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Restrepo, Felipe","contributorId":350134,"corporation":false,"usgs":false,"family":"Restrepo","given":"Felipe","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":925441,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ashline, Josh","contributorId":350135,"corporation":false,"usgs":false,"family":"Ashline","given":"Josh","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":925442,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70234174,"text":"sir20225063 - 2022 - Longitudinal water-temperature profiles in Mill Creek, Mason County, Washington","interactions":[],"lastModifiedDate":"2022-08-03T11:00:43.649803","indexId":"sir20225063","displayToPublicDate":"2022-08-02T13:27:36","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5063","displayTitle":"Longitudinal Water-Temperature Profiles in Mill Creek, Mason County, Washington","title":"Longitudinal water-temperature profiles in Mill Creek, Mason County, Washington","docAbstract":"In streams supporting Pacific salmon (Oncorhynchus spp.) within the southern Puget Lowland, high water temperatures during late summer are a primary water-quality concern. The metabolic rates of fish and other ectothermic (in other words, cold-blooded) species are regulated by water temperature; salmon and other cold-water fish have specific thermal tolerances outside of which they are susceptible to infection, disease, increased predation, and decreased reproductive success. Mill and Gosnell Creeks, which collectively drain a 30-square mile area of the Puget Lowland in Mason County, Washington, support several species of anadromous salmonids. Whereas previous studies documented relatively cool water temperatures in Gosnell Creek, which drains the watershed upstream from Lake Isabella, water temperatures in Mill Creek, which heads at the outlet of Lake Isabella, regularly exceed thermal tolerances for cold-water fish. The occurrence and distribution of cold-water anomalies in less-than-ambient water temperatures in Mill Creek, however, have not been assessed. In this report, we present spatially and temporally continuous measurements of near-streambed water temperature measured using fiber-optic distributed temperature sensing for three reaches of Mill Creek during August–September 2020 when the water temperatures of streams in western Washington were near their annual maximum. Water temperature was collected every hour and averaged spatially over 1.015-meter sections of the fiber-optic cable deployed at the streambed of Mill Creek. The lengths of the fiber-optic cables deployed in Reaches A, B, and C were 883, 270, and 1,014 meters, respectively. Daily maximum water temperature and daily temperature variability, as measured by standard deviation of water temperature during the deployment, progressively decreased downstream as distance from Lake Isabella increased. However, no abrupt decreases in daily maximum or standard deviation of water temperature were detected in longitudinal temperature profiles of any of the three reaches. Collectively, these results suggest that warm water discharged from Lake Isabella was progressively buffered downstream as it equilibrated with downstream heat fluxes mediated by physical processes including riparian shading and diffuse groundwater input. Although parts of the surveyed reaches associated with deep pools were cooler than other locations, no large (less than 2 °C) water-temperature anomalies characteristic of discrete sources of cold groundwater or surface-water inputs were measured in any of the three surveyed reaches.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225063","collaboration":"Prepared in cooperation with Squaxin Island Tribe","usgsCitation":"Gendaszek, A.S., Sheibley, R.W., Marbet, E., Puhn, J., and Seguin, C., 2022, Longitudinal water-temperature profiles in Mill Creek, Mason County, Washington: U.S. Geological Survey Scientific Investigations Report 2022–5063, 11 p., https://doi.org/10.3133/sir20225063.","productDescription":"Report: v, 11 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-132795","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":404673,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RP12RQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Longitudinal profiles of water temperature in Mill Creek, Mason County, Washington, measured using fiber-optic distributed temperature sensing (FO-DTS)"},{"id":404671,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5063/sir20225063.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5063"},{"id":404675,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5063/sir20225063.XML"},{"id":404674,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5063/images"},{"id":404670,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5063/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mill Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.29750061035155,\n 47.09490289688982\n ],\n [\n -122.9425048828125,\n 47.09490289688982\n ],\n [\n -122.9425048828125,\n 47.22656309922327\n ],\n [\n -123.29750061035155,\n 47.22656309922327\n ],\n [\n -123.29750061035155,\n 47.09490289688982\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
In 2019, the U.S. Geological Survey conducted a reconnaissance survey of concentrations of 41 trace elements present in bed sediment in the reservoir on the Similkameen River upstream from Enloe Dam, near Oroville, Washington. The Similkameen River drains a watershed containing highly mineralized geologic deposits with current (2019) and historical mining activity. Results of this survey indicated that surface and subsurface sediment are substantially enriched in element concentrations of silver (Ag), arsenic (As), gold (Au), bismuth (Bi), cadmium (Cd), copper (Cu), manganese (Mn), antimony (Sb), selenium (Se), tin (Sn), and tellurium (Te) relative to average concentrations found in upper continental-crustal material. Conversely, concentrations of mercury (Hg) and lead (Pb) in sediment above Enloe Dam (Enloe Reservoir) were generally less than average concentrations in upper continental-crustal material (Hg = 0.05 milligrams per kilogram [mg/kg]; Pb =17 mg/kg). Concentrations of most trace elements were higher in the less than 63-micrometer fraction (silt) and tended to be higher in subsurface than in surface sediment. The concentrations of trace elements were compared to consensus-based aquatic toxicity reference concentrations, Washington State Department of Ecology sediment management standards, and average concentrations of upper continental-crustal material. Arsenic concentrations were consistently elevated above these criteria among samples and often exceeded sediment management standards and aquatic toxicity reference values (both threshold effects and probable effects concentrations). High concentrations of As were measured in sediment with proportionally more material in the less than 63-micrometer size fraction; this result may be related to the presence of ore-processing waste material that has entered the aquatic system from approximately 125 years of mining operations in the basin. Elevated concentrations of chromium and copper that exceed the same criteria as arsenic (As) were measured less consistently and predominantly in the fine-grain size fraction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225073","collaboration":"Prepared in cooperation with Grant County Public Utility District","usgsCitation":"Cox, S.E., Curran, C.A., Spanjer, A.R., Opatz, C.C., Takesue, R.K., and Bell, J.L., 2022, Element concentrations and grain size of sediment from the Similkameen River above Enloe Dam (Enloe Reservoir) near Oroville, Washington, 2019: U.S. Geological Survey Scientific Investigations Report 2022–5073, 47 p., https://doi.org/10.3133/sir20225073.","productDescription":"Report: x, 47 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-120573","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":404705,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225073/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5073"},{"id":404708,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5073/sir20225073.XML"},{"id":404707,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5073/images"},{"id":404704,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5073/sir20225073.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5073"},{"id":404703,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5073/coverthb.jpg"},{"id":404706,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9593V04","text":"USGS data release","description":"USGS data release","linkHelpText":"Sediment chemistry and characteristics of samples collected in 2019 from the Similkameen River above Enloe Dam, Okanogan County, Washington (ver. 3.0, March 2022):"}],"country":"United States","state":"Washington","otherGeospatial":"Enloe Dam, Enloe Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.520263671875,\n 48.96218736991556\n ],\n [\n -119.49554443359376,\n 48.96218736991556\n ],\n [\n -119.49554443359376,\n 48.98652581047831\n ],\n [\n -119.520263671875,\n 48.98652581047831\n ],\n [\n -119.520263671875,\n 48.96218736991556\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Land subsidence is a settling, sinking, or collapse of the land surface. In the southeastern United States, subsidence is frequently observed as sinkhole collapse in karst environments, wetland degradation and loss in coastal and other low-lying areas, and inundation of coastal urban communities. Human activities such as fluid extraction, mining, and overburden alteration can cause or exacerbate subsidence, which can result in damage to infrastructure and resources. Subsidence is a hazard that takes place throughout the United States; however, a systematic approach to recognize and develop informed responses to the drivers of subsidence has not yet been fully established. To address this problem, the U.S. Geological Survey (USGS) Southeast Region (SER) funded the gathering of a team of interdisciplinary USGS scientists to promote scientific collaboration. Southeast Region scientists welcomed scientists from other regions (see table 1.1 in Appendix 1) in September 2018 at the St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida for the first workshop of the Subsidence Flex Team (SFT) (see Appendix 2 for agenda). The SFT set out to review subsidence-related research and technology and develop a unifying framework for describing the processes and hazards associated with land subsidence. A more comprehensive understanding of subsidence hazards could help to inform regional vulnerability assessments that would prove invaluable to the public, community developers, policy makers, and resource managers in both inland and coastal states. The SFT analyzed USGS strengths and weaknesses to identify existing infrastructure and capabilities that could be leveraged to create a comprehensive and far-reaching subsidence-monitoring and mitigation program. Over the course of the 2-day workshop, interdisciplinary understandings of the processes and hazards related to subsidence were explored through individual presentations and group discussion. With all perspectives considered, the SFT recommended that subsidence-related research develop scientific approaches and metrics by which the subsidence component can be isolated and quantified in order to protect both the environment and human infrastructure from harm.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221064","usgsCitation":"Flocks, J., McGraw, E., Barras, J., Bernier, J., Bradley, M., Galloway, D., Landmeyer, J., McBride, W.S., Smith, C., Smith, K., Swarzenski, C., and Toth, L., 2022, Documenting the multiple facets of a subsiding landscape from coastal cities and wetlands to the continental shelf: U.S. Geological Survey Open-File Report 2022–1064, 22 p., https://doi.org/10.3133/ofr20221064.","productDescription":"viii, 22 p.","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-106940","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":501871,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113357.htm","linkFileType":{"id":5,"text":"html"}},{"id":404582,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1064/covrthb.jpg"},{"id":404583,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1064/ofr20221064.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1064"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.603515625,\n 24.5271348225978\n ],\n [\n -79.7607421875,\n 24.5271348225978\n ],\n [\n -79.7607421875,\n 31.16580958786196\n ],\n [\n -93.603515625,\n 31.16580958786196\n ],\n [\n -93.603515625,\n 24.5271348225978\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
The Pacific Arctic region has experienced, and is projected to continue experiencing, rapid climate change. Large uncertainties exist in our understanding of the impact these physical changes have on the region’s ecology. This is, in part, due to the lack of long-term data. Here we investigate bivalve mollusc growth increment width chronologies (sclerochronologies) to develop a long-term biological data series in an Arctic species and address the hypothesis that benthic production in the Pacific Arctic region is in decline with implications for predators (e.g., walrus, whales, seals, and sea ducks). Growth increments formed in the shells of two bivalve mollusc species, Astarte borealis and Liocyma fluctuosa, were examined using conventional sclerochronological techniques. The A. borealis and L. fluctuosa samples exhibited measured longevities of >148 and >18 years, respectively, in the coastal waters of Alaska’s Chukchi Sea. Dendrochronology crossdating techniques facilitated the development of two robust (expressed population signal >0.85) independent growth increment width chronologies. These chronologies provide evidence of the growth conditions through time for each species (1985-2015 for A. borealis and 1997-2014 for L. fluctuosa). Linear regression analyses identified that both species grew more rapidly in years with warmer sea surface temperature and lower sea ice concentration. The results provide evidence that benthic ecosystems are benefiting from the warmer conditions and reduced sea ice that have accompanied recent Arctic climate trends. This result is encouraging for benthic predators in the eastern Chukchi Sea as it alleviates the concern that their benthic prey has already become food limited by weakened pelagic-benthic coupling. More broadly, this initial A. borealis chronology is among the longest biological data series for any Arctic species and highlights the feasibility of multicentennial biological data for the Arctic.
The 2018 eruption of Mount Veniaminof occurred from September 3–4 to December 27, lasting about 114 days. This report summarizes the types of volcanic unrest that accompanied the eruption and provides a chronology of events and observations. Information about the 2018 eruption was derived from geophysical instrumentation on or near the volcano that included an eight-station seismic network and regional infrasound sensors. Other observations came from frequent satellite images of the eruption, occasional aerial photographs and videos contributed by passing pilots, and web-camera views of the volcano from Perryville, Alaska, about 35 kilometers (km) south of the volcano. Eruptive activity involved small vents on the upper south flank of a cinder cone (cone A) within the ice-filled caldera that characterizes Mount Veniaminof. The 2018 eruption consisted of occasional explosive emissions of ash and gas (reaching up to 6,000 meters above sea level), episodes of low-level lava fountaining, Strombolian explosive activity, and effusion of lava flows. By the end of the eruption, lava covered an area of about 600,000 square meters (m2) on the lower south flank of cone A. The lava flows melted into ice and snow, slowly creating melt depressions around the flow margins. No unusual outflows of water were observed exiting the caldera through the main drainage northwest of the cone. Minor ash emissions were generated throughout the eruptive period, and trace amounts of ash fell on Perryville on October 25 and November 21–22. There were no reports of aircraft encounters with ash clouds. The amount of lava and ash erupted from early September to late December 2018 resulted in the generation of about 1,200,000 cubic meters (m3) of lava and 20,000–30,000 m3 of ash, which would characterize the 2018 activity as having an eruption magnitude of 1–2 on the Volcanic Explosivity Index (VEI) scale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225075","usgsCitation":"Waythomas, C.F., Dietterich, H.R., Tepp, G.M., Lopez, T.M., and Loewen, M.W., 2022, The 2018 eruption of Mount Veniaminof, Alaska: U.S. Geological Survey Scientific Investigations Report 2022-5075, 32 p., https://doi.org/10.3133/sir20225075.","productDescription":"vii, 32 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-120282","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":404574,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5075/covrthb.jpg"},{"id":404575,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5075/sir20225075.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Alaska","otherGeospatial":"Mount Veniaminof","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160.3399658203125,\n 55.83522882231773\n ],\n [\n -158.1866455078125,\n 55.83522882231773\n ],\n [\n -158.1866455078125,\n 56.48676175249086\n ],\n [\n -160.3399658203125,\n 56.48676175249086\n ],\n [\n -160.3399658203125,\n 55.83522882231773\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
This paper proposes a graph-based meta learning approach to separately predict water quantity and quality variables for river segments in stream networks. Given the heterogeneous water dynamic patterns in large-scale basins, we introduce an additional meta-learning condition based on physical characteristics of stream segments, which allows learning different sets of initial parameters for different stream segments. Specifically, we develop a representation learning method that leverages physical simulations to embed the physical characteristics of each segment. The obtained embeddings are then used to cluster river segments and add the condition for the meta-learning process. We have tested the performance of the proposed method for predicting daily water temperature and streamflow for the Delaware River Basin (DRB) over a 14 year period. The results confirm the effectiveness of our method in predicting target variables even using sparse training samples. We also show that our method can achieve robust performance with different numbers of clusterings.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and data mining","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","conferenceDate":"August 14-18, 2022","conferenceLocation":"Washington DC","language":"English","publisher":"ACM Digital Library","doi":"10.1145/3534678.3539115","usgsCitation":"Chen, S., Zwart, J.A., and Jia, X., 2022, Physics-guided graph meta learning for predicting water temperature and streamflow in stream networks, in Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and data mining, Washington DC, August 14-18, 2022, p. 2752-2761, https://doi.org/10.1145/3534678.3539115.","productDescription":"10 p.","startPage":"2752","endPage":"2761","ipdsId":"IP-138051","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":420911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Chen, Shengyu","contributorId":297452,"corporation":false,"usgs":false,"family":"Chen","given":"Shengyu","email":"","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":883313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":883314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":883315,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70237270,"text":"70237270 - 2022 - Floodplains and climate change","interactions":[],"lastModifiedDate":"2022-10-06T15:00:23.931708","indexId":"70237270","displayToPublicDate":"2022-08-01T11:35:37","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":12617,"text":"IEP Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"99","chapter":"4","title":"Floodplains and climate change","docAbstract":"Floodplains are landscape features that are periodically inundated by water from adjacent rivers (Opperman et al. 2010). Ecologically, functional floodplains are characterized by three primary elements: connectivity, flow regime, and spatial scale. Water quantity flowing over floodplains can vary greatly. Based on a flood’s effects on the floodplain, three flood categories have been defined: floodplain-activation floods, floodplain-maintenance floods, and floodplainresetting floods (Box 1). Several physical parameters determine the types of ecosystems on floodplains and the species they will support; these include temperature, water depth, water velocity, and hydrologic connectivity (Opperman et al. 2010). Natural ecosystems commonly found on floodplains include annual vegetation, forests, seasonal wetlands, and permanent ponds or wetlands (Whipple et al. 2012). Floodplains provide many valuable ecosystem services: attenuation of flood flows which reduces flood risk, filtration of surface water, recreation, fisheries, agriculture, biodiversity, food availability, and groundwater recharge, which contributes to more-sustained and cooler dry-season flows (Opperman et al. 2010).
--------------------------------------------------------------------------------------------------------------
Box 1
Floodplain-activation flood
A small magnitude flood that occurs relatively frequently and produces characteristic ecological benefits such as food-web productivity and habitat creation for native fish spawning and rearing.
Floodplain-maintenance flood
A higher magnitude flood that, in addition to providing ecological benefits, results in geomorphic changes including bank erosion and deposition on the floodplain.
Floodplain-resetting flood
A very high-magnitude flood that occurs rarely and results in extensive geomorphic changes, such as the scouring of floodplain surfaces and changes in channel location due to avulsion.
----------------------------------------------------------------------------
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Synthesis of data and studies related to the effect of climate change on the ecosystems and biota of the Upper San Francisco Estuary Year 2022","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"Interagency Ecological Program","usgsCitation":"Keeley, A., Khanna, S., Kwan, N., Matthias, B.G., Pien, C., and Wulff, M.L., 2022, Floodplains and climate change: IEP Technical Report 99, 51 p.","productDescription":"51 p.","startPage":"188","endPage":"238","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":408038,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":407971,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://iep.ca.gov/Publications/Library","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Cosumnes River floodplain, Yolo Bypass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.9317626953125,\n 37.709899354855125\n ],\n [\n -120.3936767578125,\n 37.709899354855125\n ],\n [\n -120.3936767578125,\n 39.21523130910491\n ],\n [\n -121.9317626953125,\n 39.21523130910491\n ],\n [\n -121.9317626953125,\n 37.709899354855125\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Bashevkin, Samuel M.","contributorId":288941,"corporation":false,"usgs":false,"family":"Bashevkin","given":"Samuel M.","affiliations":[{"id":61910,"text":"Delta Science Program, Delta Stewardship Council","active":true,"usgs":false}],"preferred":false,"id":854020,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854021,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Bush, Eva","contributorId":297190,"corporation":false,"usgs":false,"family":"Bush","given":"Eva","email":"","affiliations":[{"id":64315,"text":"Delta Stewardship Council Delta Science Program","active":true,"usgs":false}],"preferred":false,"id":854022,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Castillo, Gonzalo","contributorId":269408,"corporation":false,"usgs":false,"family":"Castillo","given":"Gonzalo","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":854023,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Colombano, Denise","contributorId":297365,"corporation":false,"usgs":false,"family":"Colombano","given":"Denise","affiliations":[],"preferred":false,"id":854024,"contributorType":{"id":2,"text":"Editors"},"rank":5},{"text":"Hartman, Rosemary","contributorId":200388,"corporation":false,"usgs":false,"family":"Hartman","given":"Rosemary","email":"","affiliations":[],"preferred":false,"id":854025,"contributorType":{"id":2,"text":"Editors"},"rank":6},{"text":"Herbold, Bruce","contributorId":51223,"corporation":false,"usgs":false,"family":"Herbold","given":"Bruce","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":854026,"contributorType":{"id":2,"text":"Editors"},"rank":7},{"text":"Khanna, 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