Groundwater-flow models require the spatial distribution of the hydraulic conductivity parameter. One approach to defining this spatial distribution in groundwater-flow model grids is to map the electrical resistivity distribution by airborne electromagnetic (AEM) survey and establish a petrophysical relation between mean resistivity calculated as a nonlinear function of the resistivity layering and thicknesses of the layers and aquifer transmissivity compiled from historical aquifer tests completed within the AEM survey area. The petrophysical relation is used to transform AEM resistivity to transmissivity and to hydraulic conductivity over areas where the saturated thickness of the aquifer is known. The US Geological Survey applied this approach to a gain better understanding of the aquifer properties of the Mississippi River Valley alluvial aquifer. Alluvial-aquifer transmissivity data, compiled from 160 historical aquifer tests in the Mississippi Alluvial Plain (MAP), were correlated to mean resistivity calculated from 16,816 line-kilometers (km) of inverted resistivity soundings produced from a frequency-domain AEM survey of 95,000 km2 of the MAP. Correlated data were used to define petrophysical relations between transmissivity and mean resistivity by omitting from the correlations the aquifer-test and AEM sounding data that were separated by distances greater than 1 km and manually calibrating the relation coefficients to slug-test data. The petrophysical relation yielding the minimum residual error between simulated and slug-test data was applied to 2,364 line-km of AEM soundings in the 1,000-km2 Shellmound (Mississippi) study area to calculate hydraulic property distributions of the alluvial aquifer for use in future groundwater-flow models.
Big sagebrush ecosystems are widespread across drylands of western North America and provide numerous services, but the abundance of these ecosystems has declined substantially and the future of these ecosystems is uncertain. As a result, characterizing potential areas for expansion of these ecosystems is important. Species distribution models of the big sagebrush suggest areas of increasing climatic habitat suitability at northern latitudes under climate change scenarios. This implies the formation of a leading edge during a future big sagebrush range expansion. Such an expansion requires that current nearby range margin big sagebrush populations are stable and serve as future seed sources. Our goal was to quantify the impacts of future climate conditions on the plant community composition and biomass in the in range margin big sagebrush plant communities adjacent to the leading edge. We did this using an individual-based soil water and plant growth simulation model, STEPWAT2. We assessed community dynamics throughout the twenty-first century using 13 climate models under two representative concentration pathways to capture the variability among projections. Our results show minimal overall change in plant community composition and little change in biomass, suggesting that range margin big sagebrush plant communities adjacent to the leading edge will remain stable to serve as essential dispersal sources for future range expansion, assuming no other relevant changes such as changes in disturbance regimes. These assessments of plant community responses to shifts in climate and characterization of variability in future projections will help inform conservation planning and management of the big sagebrush ecosystem.
Poorly constructed road crossings block upstream movement of fish into stream reaches that provide critical habitat or connect isolated populations. Although removing these barriers is often a conservation priority, quantifying fish passage following removal has not been well studied, particularly in intermittent streams. In this study, we sought to understand how barriers influence the dispersal of fishes in intermittent prairie streams. We used passive integrated transponder tags and antenna stations to quantify fish movement of 3 prairie-stream fishes (Central Stoneroller Campostoma anomalum [Rafinesque, 1820], Southern Redbelly Dace Chrosomus erythrogaster [Rafinesque, 1820], and Creek Chub Semotilis atromaculatus [Mitchill, 1818]) through a road crossing in an intermittent prairie stream for 3 y before and 3 y after removing a perched culvert. We verified that no upstream fish movement occurred through the culvert, despite large aggregations of tagged fish in the intermittent reach below the culvert. In contrast, tagged individuals of all 3 species were detected above the road crossing in each of the 3 y following removal. We also tracked the recovery of these species, plus the Orangethroat Darter Etheostoma spectabile (Agassiz, 1854), following a severe drought in 2018 in 2 spring-fed tributary reaches, 1 without a downstream barrier and 1 with the removed downstream culvert. Surveys of the tributary reaches showed rapid recovery of fish densities following drought in the tributary without a downstream barrier. However, recovery at the site above the removed culvert appeared to be limited by a natural waterfall. Our observations suggest barrier removal allowed access to spawning habitat within the intermittent reach immediately upstream of the site, but other obstacles or shear distance to perennial spring-fed tributary reaches also limited recolonization following severe drought. Increased connectivity between perennial and intermittent reaches in prairie streams likely benefits fishes by increasing their resilience following disturbance and providing habitat during critical life stages.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/723046","usgsCitation":"Gido, K., Hedden, S.C., Bruckerhoff, L.A., Pennock, C.A., Hedden, C.K., Hopper, G.W., Renner, E.A., Johnson, E., and Postlethwait, B.J., 2023, A perched culvert and natural obstructions limit fish dispersal in an intermittent prairie stream: Freshwater Science, v. 42, no. 1, p. 33-43, https://doi.org/10.1086/723046.","productDescription":"11 p.","startPage":"33","endPage":"43","ipdsId":"IP-137178","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":499917,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.lsu.edu/agrnr_pubs/367","text":"External Repository"},{"id":433206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Kings Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.64135743121071,\n 39.14759412347976\n ],\n [\n -96.64135743121071,\n 39.00078060209594\n ],\n [\n -96.44964269955051,\n 39.00078060209594\n ],\n [\n -96.44964269955051,\n 39.14759412347976\n ],\n [\n -96.64135743121071,\n 39.14759412347976\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gido, Keith B.","contributorId":341429,"corporation":false,"usgs":false,"family":"Gido","given":"Keith B.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hedden, Skyler C.","contributorId":341430,"corporation":false,"usgs":false,"family":"Hedden","given":"Skyler","email":"","middleInitial":"C.","affiliations":[{"id":38831,"text":"Arizona Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":908405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bruckerhoff, Lindsey Ann 0000-0002-9523-4808","orcid":"https://orcid.org/0000-0002-9523-4808","contributorId":292594,"corporation":false,"usgs":true,"family":"Bruckerhoff","given":"Lindsey","email":"","middleInitial":"Ann","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pennock, Casey A.","contributorId":341431,"corporation":false,"usgs":false,"family":"Pennock","given":"Casey","email":"","middleInitial":"A.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":908407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hedden, Crosby K.","contributorId":341432,"corporation":false,"usgs":false,"family":"Hedden","given":"Crosby","email":"","middleInitial":"K.","affiliations":[{"id":38831,"text":"Arizona Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":908408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hopper, Garrett W.","contributorId":341433,"corporation":false,"usgs":false,"family":"Hopper","given":"Garrett","email":"","middleInitial":"W.","affiliations":[{"id":36730,"text":"University of Alabama","active":true,"usgs":false}],"preferred":false,"id":908409,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Renner, Elizabeth A.","contributorId":341434,"corporation":false,"usgs":false,"family":"Renner","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":908410,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Eric R.","contributorId":341435,"corporation":false,"usgs":false,"family":"Johnson","given":"Eric R.","affiliations":[{"id":81737,"text":"Wildlife and Avian Programs","active":true,"usgs":false}],"preferred":false,"id":908411,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Postlethwait, Ben J.","contributorId":341436,"corporation":false,"usgs":false,"family":"Postlethwait","given":"Ben","email":"","middleInitial":"J.","affiliations":[{"id":81737,"text":"Wildlife and Avian Programs","active":true,"usgs":false}],"preferred":false,"id":908412,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70239772,"text":"70239772 - 2023 - Incorporating temperature into seepage loss estimates for a large unlined irrigation canal","interactions":[],"lastModifiedDate":"2025-05-14T17:36:22.285243","indexId":"70239772","displayToPublicDate":"2023-01-18T06:52:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Incorporating temperature into seepage loss estimates for a large unlined irrigation canal","docAbstract":"Quantifying seepage losses from unlined irrigation canals is necessary to improve water use and conservation. The use of heat as a tracer is widely used in quantifying seepage rates across the sediment–water interface. In this study, field observations and two-dimensional numerical models were used to simulate seepage losses during the 2018 and 2019 irrigation season in the Truckee Canal system. Nineteen transects were instrumented with temperature probes and stage recording devices for inverse modeling to derive seepage flux and volumetric losses over the 39 km length of canal. The numerical models for each transect were calibrated and validated using the two-year dataset. Soil zones and observation data were used in each numerical model to help guide calibration of vertical and lateral heat and fluid fluxes. Model simulations were used to derive multivariable regression equations that consider stage, temperature, and hydraulic gradient. The results demonstrate the value of long-term datasets that illustrate the seasonality of groundwater levels, siltation, stage, and temperature on seepage rates. Seepage rates estimated by the numerical models range from 0.16 to 4.6 m3/d m−1. Total annual volumetric losses estimated for 2018 and 2019 were 1.6 × 10-2 to 1.2 × 10-2 km3, respectively. The seepage losses estimated by this study account for 32 % to 41 % of the inflow volumes. Regression models were able to reproduce seepage time-series simulated by the numerical models reasonably well. In arid environments, water diverted into irrigation canals may be influenced by seasonal variations in temperature sufficient to influence the water accounting of conveyed surface flows.
Here we determine how traditional morphometrics (TM) compares with geometric morphometrics (GM) in discriminating among morphologies of four forms of ciscoes of the Coregonus artedi complex collected from Lake Huron. One of the forms comprised two groups of the same deepwater cisco separated by capture depth, whereas the other three forms were shallow-water ciscoes. Our three groups of shallow-water ciscoes were better separated (3% versus 19% overlap) in Principle Component Analysis (PCA) with TM data than with GM data incorporating semilandmarks (evenly spaced nonhomologous landmarks used to bridge between widely separated homologous landmarks). Our two deepwater cisco groups, comprising a putatively single form collected from different depths, separated more in PCAs with GM data (33% overlap) than in PCAs with TM data (66% overlap), an anomaly caused by greater decompression of the swimbladder and deformation of the body wall in the group captured at greater depths. Separation of the two deepwater cisco groups captured at different depths was not affected by the removal of semilandmarks. Assignment of forms using canonical variate analysis (CVA) accurately assigned 86% of individuals using TM data, 98% of individuals using GM data incorporating semilandmarks, and 100% of individuals using GM data without semilandmarks. However, we considered assignments from the same form of deepwater cisco into separate groups as misassignments resulting from different capture depths, which reduced the accuracy of assignments with GM data to 66% with semilandmarks. Our study implies that TM will continue to have an important role in morphological discrimination within Coregonus and other fishes similarly shaped.
Information on velocity fields in rivers is critical for designing infrastructure, modeling contaminant transport, and assessing habitat. Although non-contact approaches to measuring flow velocity are well established, these methods assume a stationary imaging platform. This study eliminates this constraint by introducing a framework for moving aircraft river velocimetry (MARV). The workflow takes as input images acquired from an airplane and involves orthorectification, frame overlap analysis, image enhancement, particle image velocimetry (PIV), and aggregation of the resulting velocity vectors onto a prediction grid. We also use new metrics to quantify the agreement between image-derived and field-measured velocity vectors in terms of both orientation and magnitude. The potential of MARV was evaluated using data from two Alaskan rivers: a large, highly turbid channel and its smaller, clearer tributary. Sediment boil vortices on the mainstem provided natural features trackable via PIV and estimated velocities corresponded closely with field measurements (R2 up to 0.911). We compared an exhaustive approach that evaluates overlap for all frame combinations to a simpler rolling window implementation and found that the more efficient algorithm did not compromise accuracy. Sensitivity analysis suggested that the method was robust to window parameterization. Comparing PIV output from different flying heights and imaging systems indicated that larger pixels led to higher accuracy and that a more advanced dual-camera system provided superior performance. Results from the tributary were less encouraging, presumably due to a lack of trackable features in visible images. Testing across a range of rivers is needed to assess the generality of MARV.
Continued climate warming is reducing seasonal snowpacks in the western United States, where >50% of historical water supplies were snowmelt-derived. In the Upper Colorado River Basin, declining snow water equivalent (SWE) and altered surface water input (SWI, rainfall and snowmelt available to enter the soil) timing and magnitude affect streamflow generation and water availability. To adapt effectively to future conditions, we need to understand current spatiotemporal distributions of SWE and SWI and how they may change in future decades. We developed 100-m SnowModel simulations for water years 2001–2013 and two scenarios: control (CTL) and pseudo-global-warming (PGW). The PGW fraction of precipitation falling as snow was lower relative to CTL, except for November–April at high elevations. PGW peak SWE was lower for low (−45%) and mid elevations (−14%), while the date of peak SWE was uniformly earlier in the year for all elevations (17–23 days). Currently unmonitored high elevation snow represented a greater fraction of total PGW SWE. PGW peak daily SWI was higher for all elevations (30%–42%), while the dates of SWI peaks and centroids were earlier in the year for all elevations under PGW. PGW displayed elevated winter SWI, lower summer SWI, and changes in spring SWI timing were elevation-dependent. Although PGW peak SWI was elevated and earlier compared to CTL, SWI was more evenly distributed throughout the year for PGW. These simulated shifts in the timing and magnitude of SWE and SWI have broad implications for water management in dry, snow-dominated regions.
In the United States and globally, contaminant exposure in unregulated private-well point-of-use tapwater (TW) is a recognized public-health data gap and an obstacle to both risk-management and homeowner decision making. To help address the lack of data on broad contaminant exposures in private-well TW from hydrologically-vulnerable (alluvial, karst) aquifers in agriculturally-intensive landscapes, samples were collected in 2018–2019 from 47 northeast Iowa farms and analyzed for 35 inorganics, 437 unique organics, 5 in vitro bioassays, and 11 microbial assays. Twenty-six inorganics and 51 organics, dominated by pesticides and related transformation products (35 herbicide-, 5 insecticide-, and 2 fungicide-related), were observed in TW. Heterotrophic bacteria detections were near ubiquitous (94 % of the samples), with detection of total coliform bacteria in 28 % of the samples and growth on at least one putative-pathogen selective media across all TW samples. Health-based hazard index screening levels were exceeded frequently in private-well TW and attributed primarily to inorganics (nitrate, uranium). Results support incorporation of residential treatment systems to protect against contaminant exposure and the need for increased monitoring of rural private-well homes. Continued assessment of unmonitored and unregulated private-supply TW is needed to model contaminant exposures and human-health risks.
Land-based sources of groundwater pollution can be a critical threat to coral reefs, and a better understanding of “ridge-to-reef” water movement is required to advance management and coral survival in the Anthropocene. In this study a more complete understanding of the geological, atmospheric, and oceanic drivers behind coastal groundwater exchange on the Kalaupapa peninsula, on Moloka‘i, Hawai‘i, is obtained by analyzing high resolution geochemical and geophysical time-series data. In concert with multiyear water level analyses, a tidally and precipitation-driven groundwater connection between Kauhakō Crater lake and submarine groundwater discharge (SGD) fluxes are demonstrated. Results include an average discharge rate of 190 cm d−1 and the detection of water-flow pathways past cesspools that likely contribute to higher nutrient loading near the SGD sites. This underlines the importance of managing anthropogenic nutrients that enter the shallow freshwater lens such as through cesspools and are consequently discharged via SGD onto coral reef habitats.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2022.114509","usgsCitation":"Oberle, F.K., Cheriton, O.M., Swarzenski, P., Brown, E.K., and Storlazzi, C.D., 2023, Physicochemical coastal groundwater dynamics between Kauhakō Crater lake and Kalaupapa settlement, Moloka‘i, Hawai‘i: Marine Pollution Bulletin, v. 187, 114509, 12 p., https://doi.org/10.1016/j.marpolbul.2022.114509.","productDescription":"114509, 12 p.","ipdsId":"IP-146121","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":435502,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XQAMW8","text":"USGS data release","linkHelpText":"Physicochemical measurements of the coastal aquifer and coastal groundwater discharge on Kalaupapa, Moloka'i, Hawaii"},{"id":411967,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","city":"Kalaupapa","otherGeospatial":"Kauhakō Crater Lake, Kalaupapa Peninsula, Moloka'i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.9876032907954,\n 21.20057697124608\n ],\n [\n -156.9876032907954,\n 21.184169607286606\n ],\n [\n -156.9619419645661,\n 21.184169607286606\n ],\n [\n -156.9619419645661,\n 21.20057697124608\n ],\n [\n -156.9876032907954,\n 21.20057697124608\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"187","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Oberle, Ferdinand K.J. 0000-0001-8871-3619","orcid":"https://orcid.org/0000-0001-8871-3619","contributorId":214402,"corporation":false,"usgs":true,"family":"Oberle","given":"Ferdinand","middleInitial":"K.J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":204459,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarzenski, Peter W 0000-0003-0116-0578","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":225227,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter W","affiliations":[],"preferred":true,"id":861703,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Eric K.","contributorId":41956,"corporation":false,"usgs":true,"family":"Brown","given":"Eric","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":861727,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":861728,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239727,"text":"70239727 - 2023 - Subaqueous clinoforms created by sandy wave-supported gravity flows: Lessons from the central California shelf","interactions":[],"lastModifiedDate":"2023-01-16T19:30:15.171651","indexId":"70239727","displayToPublicDate":"2023-01-16T13:25:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Subaqueous clinoforms created by sandy wave-supported gravity flows: Lessons from the central California shelf","docAbstract":"Subaqueous clinoforms are an important yet underappreciated shelf feature. Their origins are typically associated with subaerial deltas but recent work has identified similar features in settings without a significant fluvial source. These other studies have shown that such subaqueous clinoforms, also known as infralittoral prograding wedges (IPWs), are created largely by wave-induced processes. This study uses geophysical, sedimentological, and radiocarbon data to determine the sedimentary characteristics and genesis of a shore-parallel subaqueous clinoform developed far from any significant river on the central California continental shelf; a feature known locally as the Cross Hosgri Slope. Sediment cores through the feature reveal that it is composed of beds with an erosive base, followed by a thin coarsening upward sequence of shelly fine sands transitioning to a fining upward sequence marked by alternating parallel and ripple cross laminated very fine sands. The deposit is often capped by fine silts that are commonly interbedded with thin very fine sand beds. Radiocarbon dating of shells within the cores paired with seismic profiles indicate the subaqueous clinoform initiated progradation ~7 ka, nucleating on an older Younger Dryas relict shoreface. We suggest the CHS was created by winter-storm waves mobilizing sands in water depths up to ~ 70 m that transitioned into wave-supported gravity flows. The wave-supported gravity flows traveled downslope to water depths of up to ~85 m, corresponding to the foot of the subaqueous clinoform. They did not travel beyond this depth as wave influence at these depths is negligible and the shelf slope is insufficient to maintain movement of the load alone. Our work suggests that wave-supported gravity flows can entrain very fine sands and silts and build subaqueous clinoforms, even in the absence of a significant river source. Furthermore, we provide a facies model for sandy wave-supported gravity flow deposits.","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2022.106977","usgsCitation":"Medri, E., Simms, A.R., Kluesner, J., Johnson, S., Nishenko, S., Greene, H.G., and Conrad, J.E., 2023, Subaqueous clinoforms created by sandy wave-supported gravity flows: Lessons from the central California shelf: Marine Geology, v. 456, 106977, 13 p., https://doi.org/10.1016/j.margeo.2022.106977.","productDescription":"106977, 13 p.","ipdsId":"IP-144443","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444808,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2022.106977","text":"Publisher Index Page"},{"id":411965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Pacific Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.56611710043825,\n 36.61947594158909\n ],\n [\n -123.56611710043825,\n 34.32371030361945\n ],\n [\n -119.09307635415979,\n 34.32371030361945\n ],\n [\n -119.09307635415979,\n 36.61947594158909\n ],\n [\n -123.56611710043825,\n 36.61947594158909\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"456","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Medri, Elisa","contributorId":300974,"corporation":false,"usgs":false,"family":"Medri","given":"Elisa","email":"","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":861657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simms, Alexander R.","contributorId":52887,"corporation":false,"usgs":true,"family":"Simms","given":"Alexander","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":861658,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kluesner, Jared W. 0000-0003-1701-8832","orcid":"https://orcid.org/0000-0003-1701-8832","contributorId":206367,"corporation":false,"usgs":true,"family":"Kluesner","given":"Jared W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Samuel Y. 0000-0001-7972-9977","orcid":"https://orcid.org/0000-0001-7972-9977","contributorId":221270,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel Y.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nishenko, Stuart P.","contributorId":82219,"corporation":false,"usgs":true,"family":"Nishenko","given":"Stuart P.","affiliations":[],"preferred":false,"id":861661,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greene, H. Gary","contributorId":139063,"corporation":false,"usgs":false,"family":"Greene","given":"H.","email":"","middleInitial":"Gary","affiliations":[{"id":12639,"text":"Moss Landing Marine Labs","active":true,"usgs":false}],"preferred":false,"id":861662,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":861663,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70239723,"text":"70239723 - 2023 - Hydrodynamics and habitat interact to structure fish communities within terminal channels of a tidal freshwater delta","interactions":[],"lastModifiedDate":"2023-01-16T18:55:39.202204","indexId":"70239723","displayToPublicDate":"2023-01-16T12:45:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Hydrodynamics and habitat interact to structure fish communities within terminal channels of a tidal freshwater delta","docAbstract":"Terminal channels were historically a common feature of tidal delta ecosystems but have become increasingly rare as landscapes have been modified. Tidal hydrodynamics are a defining feature in tidal terminal channel ecosystems from which native aquatic communities have evolved. However, few studies have explored the relationship between fish community structure and hydrodynamics in these tidal terminal channel ecosystems. We sampled fish communities throughout a network of terminal channels within the northeasternmost region of the San Francisco Estuary to determine the relationship between fish community structure and hydrodynamics within these environments. We collected two years (2017 and 2018) of fish community samples using gill nets and analyzed data using multivariate community analyses and count models. We found metrics of fish diversity and counts of native fishes to be greatest upstream (farthest from tidal influence) of the tidal excursion within terminal channels. Counts of non-native fishes were less affected by this hydrodynamic feature of terminal channels and more tightly correlated to local habitat conditions (e.g., water temperature, depth). Our results suggest that channel hydrodynamics plays a role in structuring fish communities within terminal channels, particularly native fishes. These results indicate that hydrodynamics in tidal delta ecosystems may be able to be altered in ways that benefit native fishes without the cost of water pumping.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4339","usgsCitation":"Huntsman, B., Young, M.J., Feyrer, F.V., Stumpner, P., Brown, L.R., and Burau, J.R., 2023, Hydrodynamics and habitat interact to structure fish communities within terminal channels of a tidal freshwater delta: Ecosphere, v. 14, no. 1, e4339, 18 p., https://doi.org/10.1002/ecs2.4339.","productDescription":"e4339, 18 p.","ipdsId":"IP-139147","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":444812,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4339","text":"Publisher Index Page"},{"id":411962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cache Slough Complex, San Francisco Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.69932887248329,\n 38.24856975517184\n ],\n [\n -121.67220637492461,\n 38.24776088323978\n ],\n [\n -121.71752497844034,\n 38.3229474560282\n ],\n [\n -121.80987879924118,\n 38.31217280176293\n ],\n [\n -121.77760646037407,\n 38.28495967449561\n ],\n [\n -121.72713801554991,\n 38.28064774752275\n ],\n [\n -121.69932887248329,\n 38.24856975517184\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Huntsman, Brock 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":223101,"corporation":false,"usgs":true,"family":"Huntsman","given":"Brock","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Matthew J. 0000-0001-9306-6866 mjyoung@usgs.gov","orcid":"https://orcid.org/0000-0001-9306-6866","contributorId":206255,"corporation":false,"usgs":true,"family":"Young","given":"Matthew","email":"mjyoung@usgs.gov","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":178379,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stumpner, Paul 0000-0002-0933-7895 pstump@usgs.gov","orcid":"https://orcid.org/0000-0002-0933-7895","contributorId":5667,"corporation":false,"usgs":true,"family":"Stumpner","given":"Paul","email":"pstump@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Larry R. 0000-0001-6702-4531","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":269405,"corporation":false,"usgs":false,"family":"Brown","given":"Larry","email":"","middleInitial":"R.","affiliations":[{"id":55970,"text":"USGS CAWSC (not in system - posthumous)","active":true,"usgs":false}],"preferred":false,"id":861639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":861640,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70239810,"text":"70239810 - 2023 - Watershed- and reach-scale drivers of phosphorus retention and release by streambed sediment in a western Lake Erie watershed during summer","interactions":[],"lastModifiedDate":"2023-01-20T13:09:14.687072","indexId":"70239810","displayToPublicDate":"2023-01-16T07:06:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Watershed- and reach-scale drivers of phosphorus retention and release by streambed sediment in a western Lake Erie watershed during summer","docAbstract":"Reducing phosphorus (P) concentrations in aquatic ecosystems, is necessary to improve water quality and reduce the occurrence of harmful cyanobacterial algal blooms. Managing P reduction requires information on the role rivers play in P transport from land to downstream water bodies, but we have a poor understanding of when and where river systems are P sources or sinks. During the summers of 2019 and 2021, we sampled streambed sediment at 78 sites throughout the Maumee River network (a major source of P loads to Lake Erie) focusing on the zero equilibrium P concentration (EPC0), the soluble reactive phosphorus (SRP) concentration at which sediment neither sorbs nor desorbs P. We used structural equation modeling to identify direct and indirect drivers of EPC0. Stream sediment was a P sink at 40 % and 67 % of sites in 2019 and 2021, respectively. During both years, spatial variation in EPC0 was shaped by stream water SRP concentrations, sediment P saturation, and sediment physicochemical characteristics. In turn, SRP concentrations and sediment P saturation (PSR) were influenced by agricultural land use and stream size. Effect of stream size differed among years with stream size having a greater effect on SRP in 2019 and on PSR in 2021. Streambed sediment is currently a net P sink across the sites sampled in the Maumee River network during summer, but sediment at these locations, especially sites in headwater streams, may become a P source if stream water SRP concentrations decrease. Our results improve the understanding of watershed- and reach-scale controls on EPC0 but also indicate the need for further research on how changes in SRP concentration as a result of conservation management implementation influences the role of streambed sediment in P transport to Lake Erie.
Rivers and streams export inorganic and organic carbon derived from contributing landscapes and so downstream carbon fluxes are important quantitative indicators of change in ecosystem function and for the full accounting of terrestrial carbon budgets. Carbon concentration-discharge (C-Q) relationships in rivers provide important information about carbon source and behavior in watersheds and are useful for estimating carbon export. However, C-Q relationships are complex in large river systems because of spatial and temporal heterogeneity in carbon dynamics across the watershed and river networks. We quantified dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) fluxes in the Upper Mississippi River basin and investigated their relationships with land cover and hydrology. The magnitude of dissolved carbon yields ranged widely among stations, 0.6–5.7 g DOC m−2 yr−1 and 2.9–11.8 g DIC m−2 yr−1. Spatial patterns in carbon fluxes were strongly related to land cover, with agricultural sites having high DIC/low DOC exports and forested and wetland areas having the opposite. DIC was always negatively related to discharge (Q), while the DOC-Q relationship varied with land cover. Differential behavior of carbon across the basin resulted in Q having a weak relationship with DOC and DIC at the basin outlet. Hence, there is a need to improve understanding of headwater terrestrial-to-aquatic carbon connections in order to improve basin-to-continental-scale carbon export estimates. Our results demonstrate that quantitative understanding of carbon export by large rivers can be improved by incorporating stream network information, such as the timing, location, and source of constituent flux, rather than relying solely upon relationships between constituent behavior and seasonality or discharge at the basin outlet.
In arid and Mediterranean regions, landscape-scale wetland conservation requires understanding how wildlife responds to dynamic freshwater availability and conservation actions to enhance wetland habitat. Taking advantage of Landsat satellite data and structured and community science bird survey data, we built species distribution models to describe how three duck species, the Northern Pintail (Anas acuta), Green-winged Teal (Anas crecca), and Northern Shoveler (Anas clypeata), respond to freshwater supply and food resources on different flooded land cover types in the Central Valley of California. Specifically, our models compared duck habitat suitability between the wettest and driest conditions in each month from September through April. Using abundance-weighted boosted regression trees, we created three sets of species occurrence models based on different covariates: (1) near real-time (hereafter “real-time”) covariates in which duck observations were matched to the water availability within the 16-day window of a Landsat observation, (2) a combination of real-time covariates and waterfowl food resource covariates describing annual corn and rice biomass and managed wetland moist soil seed yield estimates derived from Landsat data, and (3) long-term average covariates—the most common approach to species distribution modeling—in which long-term average surface water availability was used. We modeled the monthly occurrence of three duck species as a function of surface water availability, land cover type, road density, temperature, and bird data source. We found that dry conditions result in reduced habitat suitability, with the biggest reductions in November through January and in agricultural fields; in contrast, suitability of flooded wetland habitat was relatively robust to surface water availability. When models of habitat suitability based on long-term average climate conditions were compared to models based on real-time conditions, the highest long-term suitability values occurred in areas where suitability was high regardless of whether it was a wet or a dry year. While all models performed well, the inclusion of crop and wetland plant yield covariates resulted in slightly higher model performance. Overall, species distribution models created using data on the environmental conditions present at the time of bird observations can aid conservation efforts under extreme conditions over large spatial scales.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4367","usgsCitation":"Conlisk, E.E., Byrd, K.B., Matchett, E., Lorenz, A., Casazza, M.L., Golet, G.H., Reynolds, M.D., Sesser, K.A., and Reiter, M.E., 2023, Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California: Ecosphere, v. 14, e4367, 19 p., https://doi.org/10.1002/ecs2.4367.","productDescription":"e4367, 19 p.","ipdsId":"IP-144890","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":444827,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4367","text":"Publisher Index Page"},{"id":412024,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n 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E.","contributorId":301022,"corporation":false,"usgs":false,"family":"Conlisk","given":"Erin","email":"","middleInitial":"E.","affiliations":[{"id":17734,"text":"Point Blue Conservation Science","active":true,"usgs":false}],"preferred":false,"id":861775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrd, Kristin B. 0000-0002-5725-7486 kbyrd@usgs.gov","orcid":"https://orcid.org/0000-0002-5725-7486","contributorId":3814,"corporation":false,"usgs":true,"family":"Byrd","given":"Kristin","email":"kbyrd@usgs.gov","middleInitial":"B.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":861776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":861777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorenz, Austen 0000-0003-3657-5941","orcid":"https://orcid.org/0000-0003-3657-5941","contributorId":222610,"corporation":false,"usgs":true,"family":"Lorenz","given":"Austen","email":"","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":861778,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":861779,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Golet, Gregory H.","contributorId":89844,"corporation":false,"usgs":false,"family":"Golet","given":"Gregory","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":861780,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Reynolds, Mark D.","contributorId":301023,"corporation":false,"usgs":false,"family":"Reynolds","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":861781,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sesser, Kristin A.","contributorId":215294,"corporation":false,"usgs":false,"family":"Sesser","given":"Kristin","email":"","middleInitial":"A.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":861782,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reiter, Matthew E. 0000-0002-0587-786X","orcid":"https://orcid.org/0000-0002-0587-786X","contributorId":271031,"corporation":false,"usgs":false,"family":"Reiter","given":"Matthew","email":"","middleInitial":"E.","affiliations":[{"id":56258,"text":"Point Blue","active":true,"usgs":false}],"preferred":false,"id":861783,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70239935,"text":"70239935 - 2023 - Nest-site selection model for endangered Everglade snail kites to inform ecosystem restoration","interactions":[],"lastModifiedDate":"2023-03-28T14:38:56.423278","indexId":"70239935","displayToPublicDate":"2023-01-15T07:09:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Nest-site selection model for endangered Everglade snail kites to inform ecosystem restoration","docAbstract":"dictors of nesting for snail kites in south Florida. The results of our modeling indicate that hydrology, percent canopy cover, and proximity to recently burned areas were the most important factors associated with nest-site selection for snail kites. Water depths between 75 and 100 cm, water recession rates between 0 and 1.25 cm/day, percent canopy covers <20%, and areas <10 km from recently burned habitat were associated with the greatest likelihood of nest-site selection. KiteNest is applicable to natural resource management decisions in the Everglades and may be useful independently or in conjunction with other ecological models for restoration decision support.
Irregularly flooded wetlands are found above the mean high water tidal datum and are exposed to tides and saltwater less frequently than daily. These wetlands provide important ecosystem services, such as providing habitat for fish and wildlife, enhancing water quality, ameliorating flooding impacts, supporting coastal food webs, and protecting upslope areas from erosion. Mapping irregularly flooded wetlands is challenging given their expansive coverage and dynamic nature. Furthermore, coastal wetlands are expected to change over the coming century due to sea-level rise and changes in the frequency and intensity of extreme storms. Consequently, coastal managers need baseline information on the spatial distribution of wetlands along with efficient and repeatable methods for observing changes. In this study, we used coastal wetlands from existing land use land cover data, best available lidar-derived digital elevation models, and Monte Carlo simulations to incorporate elevation uncertainty to create a probabilistic map of irregularly flooded wetlands along the northern Gulf of Mexico coast (USA). Our approach integrated findings from a review of coastal wetland elevation error in lidar datasets and an analysis of spatial autocorrelations of wetland elevation. We found a positive correlation (r = 0.563, p < 0.0001) when comparing the probability estimated from a digital elevation model and in situ elevation observations. The differences in probability had a mean bias error of −0.04 (i.e., digital elevation model-based probability tends to be slightly lower), a mean absolute error of 0.20, and a root mean square error of 0.26. Beyond this overall validation, we explored error metrics for land cover classes and lidar collection details. To quantify areal coverage of the probabilistic output, we classified the probability values into equal bins using an interval of 0.33. The areal coverage of the lowest probability bin (“unlikely”; probability ≤0.33) was separated into the upper and lower portions of the irregularly flooded wetland zone. Of the coastal wetlands along the northern Gulf of Mexico coast about 38% were classified as unlikely and low with the greatest coverage in south Louisiana and the Everglades and around 33% were classified as unlikely and high with the greatest coverage in the Everglades and Texas. The relative coverage within the highest probability bin (“likely”; probability >0.66) covered around 13%, with the greatest coverage in south Florida, south Louisiana, and Texas. The framework developed in this study can be transferred to other coastal wetland areas and updated to observe changes with sea-level rise.
As a part of the Texas Water Development Board groundwater availability modeling program, the U.S. Geological Survey developed the Gulf Coast Land Subsidence and Groundwater-Flow model (hereinafter, the “GULF model”) and ensemble to simulate groundwater flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system (the study area) in Texas from predevelopment (1897) through 2018. Since the publication of a previous groundwater model for the greater Houston area in 2012, there have been changes to the distribution of groundwater withdrawals and advances in modeling tools. To reflect these changes and to simulate more recent conditions, the GULF model was developed in cooperation with the Harris-Galveston and Fort Bend Subsidence Districts to provide an updated Groundwater Availability Model.
Since the early 1900s, most of the groundwater withdrawals in the study area have been from three of the hydrogeologic units that compose the Gulf Coast aquifer system—the Chicot, Evangeline, and Jasper aquifers and, more recently, from the Catahoula confining unit. Withdrawals from these hydrogeologic units are used for municipal supply, commercial and industrial use, and irrigation purposes. Withdrawals of large quantities of groundwater in the greater Houston area have caused widespread groundwater-level declines in the Chicot, Evangeline, and Jasper aquifers of more than 300 feet (ft). Early development of the aquifer system, which began before 1900, resulted in nearly 50 percent of the eventual historical groundwater-level minimums having been reached as early as 1946 in some areas. These groundwater-level declines led to more than 9 ft of land-surface subsidence—historically in central and southeastern Harris County and Galveston County, but more recently in northern, northwestern, and western Harris County, Montgomery County, and northern Fort Bend County—from depressurization and compaction of clay and silt layers interbedded in the aquifer sediments.
In a generalized conceptual model of the Gulf Coast aquifer system, water enters the groundwater system in topographically high outcrops of the hydrogeologic units in the northwestern part of the aquifer system. Groundwater that does not discharge to streams flows to intermediate and deep zones of the aquifer system southeastward of the outcrop areas where it is discharged by wells and by upward leakage in topographically low areas near the coast. The uppermost parts of the aquifer system, which include outcrop areas, are under water-table (unconfined) conditions where the groundwater is not confined under pressure. As depth increases in the aquifer system and interbedded clay and silt layers accumulate, water-table conditions evolve into confined conditions where the groundwater is under pressure.
Groundwater flow and land-surface subsidence in the GULF model and ensemble were simulated by using MODFLOW 6 with the Skeletal Storage, Compaction, and Subsidence package. The model consists of six layers, one for each of the five hydrogeologic units in the northern part of the Gulf Coast aquifer system and a surficial top layer that includes part of each hydrogeologic unit. Transient groundwater flow was simulated during 1897–2018 by using a combination of multiyear, annual, and monthly stress periods. An initial steady-state stress period was configured to represent predevelopment mean annual inflows and outflows. The subsidence package used in the GULF model and ensemble uses a head-based subsidence formulation that simulates the delayed drainage response from clay and silt sediment to changes in groundwater levels.
The GULF model and ensemble were history matched to groundwater-level observations at selected wells, land-surface subsidence at benchmarks, aquifer compaction at borehole extensometers, and vertical displacement from Global Positioning System stations. A Bayesian framework was used to represent uncertainty in modeled parameters and simulated outputs of interest. History matching and uncertainty quantification were performed by using a Monte Carlo approach enabled through iterative ensemble smoother software to produce an ensemble of models fit to historical data. The iterative ensemble smoother substantially reduced the computational demand of parameter estimation by approximating the first-order relation between model inputs and outputs, thereby allowing 183,207 adjustable parameters to be used for history matching at a relatively low computational and time cost.
The history-matched parameter values are within the ranges of previously published values and agree with the current understanding of the spatial and temporal patterns of parameter uncertainty for the Gulf Coast aquifer system. A good agreement between the observed (or estimated) and simulated groundwater levels, land-surface subsidence, compaction, and vertical displacement was obtained across the modeled area based on qualitative and quantitative comparisons. Ensemble mean annual groundwater-flow rates to the Chicot, Evangeline, Jasper aquifers and Catahoula confining unit were 0.0–0.49 inch (in.), 0.09–0.33 in., 0.01–0.07 in., and 0.01–0.05 in., respectively. GULF model mean annual groundwater-flow rates to the Chicot, Evangeline, and Jasper aquifers and Catahoula confining unit were 0.31 in., 0.19 in., 0.03 in., and 0.03 in., respectively.
The GULF-model-simulated recharge to the outcrop area was the largest inflow (75 percent), and recharge to other areas was 25 percent of the model inflow. The simulated outflows included (1) net surface-water/groundwater exchange with study area streams (50 percent), (2) groundwater use (49 percent), and (3) net surface-water/groundwater exchange with the Gulf of Mexico (1 percent). The sum of the simulated values of the outflows (1,041,973 acre-feet per year [acre-ft/yr]) and the elastic expansion of the fine-grained sediment and numerical solver error (339 acre-ft/yr) minus the inflows (654,172 acre-ft/yr) represents the reduction of storage from the Gulf Coast aquifer system (388,140 acre-ft/yr). Most of the storage depletion is caused by the long-term groundwater-level declines that have resulted primarily in inelastic compaction.
The GULF model was used to estimate Jasper aquifer compaction at selected benchmarks in Montgomery County and northern Harris County, which are the primary locations of Jasper aquifer groundwater use. Simulated Jasper aquifer compaction in northern Harris County was between 0.2 and 0.5 ft, or between about 5 and 16 percent of simulated subsidence at the benchmark locations. Simulated Jasper aquifer compaction in Montgomery County was between 0.8 and 1.2 ft, or between about 33 and 57 percent of simulated subsidence at the benchmark locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1877","issn":"ISSN 2330-7102","collaboration":"Prepared in cooperation with the Harris-Galveston Subsidence District and the Fort Bend Subsidence District","usgsCitation":"Ellis, J.H., Knight, J.E., White, J.T., Sneed, M., Hughes, J.D., Ramage, J.K., Braun, C.L., Teeple, A., Foster, L., Rendon, S.H., and Brandt, J., 2023, Hydrogeology, land-surface subsidence, and documentation of the Gulf Coast Land Subsidence and Groundwater-Flow (GULF) model, southeast Texas, 1897–2018 (ver. 1.1, November 2023): U.S. Geological Survey Professional Paper 1877, 425 p., https://doi.org/10.3133/pp1877.","productDescription":"Report: xx, 425 p., 8 Appendixes; Data Release","numberOfPages":"450","onlineOnly":"Y","ipdsId":"IP-127938","costCenters":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":500160,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114230.htm","linkFileType":{"id":5,"text":"html"}},{"id":422702,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/pp/pp1877/versionHist.txt","linkFileType":{"id":2,"text":"txt"}},{"id":411889,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XM8A1P","text":"USGS Data Release","linkHelpText":"MODFLOW 6 model and ensemble used in the simulation of groundwater flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system, 1897–2018"},{"id":422705,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/pp1877/coverthb2.jpg"},{"id":411888,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/pp1877/pp1877.pdf","text":"Report","size":"184 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.54245107965883,\n 31.199747848944256\n ],\n [\n -96.33297842340923,\n 30.997489619299927\n ],\n [\n -96.79440420465926,\n 30.136679255787612\n ],\n [\n -96.02536123590899,\n 28.551820525825022\n ],\n [\n -95.36068838434645,\n 28.86498475853952\n ],\n [\n -94.72348135309639,\n 29.28746086219381\n ],\n [\n -94.65207022028405,\n 29.402380282489133\n ],\n [\n -94.23458975153387,\n 29.574516044800063\n ],\n [\n -93.82809561090883,\n 29.670020494605353\n ],\n [\n -93.89401357965892,\n 29.803574466610613\n ],\n [\n -93.6907665093464,\n 30.05113045792723\n ],\n [\n -93.67428701715903,\n 30.307554456695556\n ],\n [\n -93.6687938530968,\n 30.563309394138372\n ],\n [\n -93.49301260309677,\n 30.841976559030968\n ],\n [\n -93.4765331109094,\n 31.077503645282718\n ],\n [\n -93.54245107965883,\n 31.199747848944256\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: January 13, 2023; Version 1.1: November 28, 2023","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754-4501
Groundwater is the primary source of drinking water in the Coachella Valley in the desert region of southern California. Although most people in Coachella Valley are served by public drinking-water systems, about 20,000 people rely on private domestic or small-system wells (referred to herein as domestic wells). Recently, the U.S. Geological Survey (USGS) found that 39 percent of the groundwater resources used by domestic wells in Coachella Valley contained arsenic, fluoride, or both constituents at concentrations greater than the maximum contaminant levels established for public drinking-water systems. Uranium, chromium, nitrate, and perchlorate were detected at moderate concentrations below maximum contaminant levels. Elevated (above background) perchlorate concentrations in some areas indicate that domestic wells may receive recharge from Colorado River water used for irrigation or aquifer replenishment. Moderate total dissolved solids (TDS) concentrations throughout the study area and the co-occurrence of high concentrations of TDS and perchlorate indicates that Colorado River water is a source of recharge in the southeastern Indio groundwater subbasin. Four volatile organic compounds were detected at low concentrations, and pesticides and per- and polyfluoroalkyl substances were not detected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221122","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Soldavini, A.L., Harkness, J.S., Levy, Z.F., and Fram, M.S., 2023, Quality of groundwater used for domestic drinking-water supply in the Coachella Valley, 2020: U.S. Geological Survey Open-File Report 2022-1122, 6 p., https://doi.org/10.3133/ofr20221122.","productDescription":"Report: 6 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-127493","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":411823,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UYXI95","text":"USGS data release","description":"USGS data release","linkHelpText":"Groundwater-quality data in the Coachella Valley Domestic Supply Aquifer Study Unit, 2020: Results from the California GAMA Priority Basin Project (ver. 2.0, May 2022)"},{"id":411820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1122/coverthb.jpg"},{"id":411821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1122/ofr20221122.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1122"},{"id":411824,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1122/images"},{"id":411825,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1122/ofr20221122.XML"},{"id":411822,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221122/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1122"},{"id":499728,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114228.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United 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U.S. Geological Survey
California Water Science Center
6000 J Street, Placer Hall
Sacramento, CA 95819
Telephone number: (916) 278-3000
Unit Chief State Water Resources Control Board Division of Water Quality
P.O. Box 2231, Sacramento, CA 95812
Telephone number: (916) 341-5779
Snow Lake, a glacially dammed lake on the Snow Glacier near Seward, Alaska, drains rapidly every 14 months–3 years, causing flooding along the Snow River. Highway, railroad, and utility infrastructure on the lower Snow River floodplain is vulnerable to flood damage. Historical hydrology, geomorphology, and two-dimensional hydraulic and sediment transport modeling were used to assess the flood risks from Snow Lake outburst floods. Floods have become more frequent, peaked more rapidly, and have had generally higher peaks over the last 20 years as the Snow Glacier has thinned, translating to a greater potential for flood damage. Rapidly shifting channel locations and the occasional introduction of large volumes of debris to the river also threaten infrastructure on the floodplain and in the channel. An assessment of the historical channel planform between 1951 and 2019 showed that there have been more and less stable segments along the lower Snow River and that channel migration has generally been toward the east. An analysis of floodplain elevations using 2008 light detection and ranging (lidar) showed that the main channel is relatively high compared to floodplain channels that carry floodwaters along the railroad grade, so that once the main channel banks are overtopped water rapidly disperses throughout the floodplain. A two-dimensional flow and sediment transport model was developed, and its simulation results were compared to three past outburst floods from 2007, 2017, and 2019. Despite the complex floodplain and channel geometry, coarse resolution of the mesh, and sediment input data, the model successfully simulated areas of observed scour along the railroad grade and at the guidebank to the highway bridge. The modeled water-surface elevations generally replicated peak elevations recorded at a streamgage in the middle of the model domain and at pressure transducers installed on the floodplain and main channel, although there were discrepancies on the rising limb and some locations had a poorer fit than others. A model of a hypothetical check flood, approximately 150 percent of the largest recorded outburst flood, was developed to provide hydraulic variables to use when planning for infrastructure upgrades.
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
One of the most critical challenges we face today is access to clean water. Climate change, industrialization, high rates of urbanization, and population growth have resulted in many countries suffering from water crises, especially in the arid and semi-arid areas. Countries in different regions of the world have also been struggling over regional water availability and it is anticipated that these struggles may result in conflicts over shared water resources in these regions. Considering the adverse consequences of the water crisis, countries have been trying to increasingly cope with this problem of water availability by implementing sustainable water management plans and looking for alternative water supply sources.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2023.1132758","usgsCitation":"Bustos-Terrones, Y.A., Norman, L., Perez-Estrada, L., El Nemr, A., and Bandala, E.R., 2023, Editorial: Advanced physico-chemical technologies for water detoxification and disinfection: Frontiers in Environmental Science, v. 11, 1132758, 3 p., https://doi.org/10.3389/fenvs.2023.1132758.","productDescription":"1132758, 3 p.","ipdsId":"IP-147820","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":444843,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2023.1132758","text":"Publisher Index Page"},{"id":416549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-01-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Bustos-Terrones, Yaneth A.","contributorId":304606,"corporation":false,"usgs":false,"family":"Bustos-Terrones","given":"Yaneth","email":"","middleInitial":"A.","affiliations":[{"id":66127,"text":"CONACYT - Division of Postgraduate Studies and Research, Technological Institute of Culiacan, Culiacan, Sinaloa, Mexico.","active":true,"usgs":false}],"preferred":false,"id":871141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":871142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perez-Estrada, Leonidas","contributorId":304607,"corporation":false,"usgs":false,"family":"Perez-Estrada","given":"Leonidas","email":"","affiliations":[{"id":65218,"text":"EURECAT, Spain","active":true,"usgs":false}],"preferred":false,"id":871143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"El Nemr, Ahmed","contributorId":304608,"corporation":false,"usgs":false,"family":"El Nemr","given":"Ahmed","email":"","affiliations":[{"id":66129,"text":"Environment Division, National Institute of Oceanography and Fisheries (NIOF), Kayet Bey, Elanfoushy, Alexandria, Egypt. E-mail: ahmedmoustafaelnemr@yahoo.com","active":true,"usgs":false}],"preferred":false,"id":871144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bandala, Erick R.","contributorId":304605,"corporation":false,"usgs":false,"family":"Bandala","given":"Erick","email":"","middleInitial":"R.","affiliations":[{"id":66126,"text":"Division of Hydrologic Sciences. Desert Research Institute. 755 E. Flamingo Road, Las Vegas, Nevada 89119, USA, Tel: 702 862 5395, e-mail: erick.bandala@dri.edu","active":true,"usgs":false}],"preferred":false,"id":871140,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239357,"text":"fs20223088 - 2023 - Research needs identified for potential effects of energy development activities on environmental resources of the Williston Basin, United States","interactions":[],"lastModifiedDate":"2026-02-04T20:26:08.038844","indexId":"fs20223088","displayToPublicDate":"2023-01-11T09:22:49","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3088","displayTitle":"Research Needs Identified for Potential Effects of Energy Development Activities on Environmental Resources of the Williston Basin, United States","title":"Research needs identified for potential effects of energy development activities on environmental resources of the Williston Basin, United States","docAbstract":"Unconventional oil and gas development that uses horizontal drilling and hydraulic fracturing is rapidly changing the landscape and exponentially increasing oil production within the Williston Basin, especially in North Dakota and eastern Montana. The activities associated with unconventional oil and gas development are complex and wide reaching and include, in part, road and well-pad construction, leaks from pits or tanks, chemical spills, discharge of wastewater, drilling before casing installation, leaks during or after hydraulic fracturing, failed casing seals, pipeline breaks, abandoned wells, deep-well disposal of flowback or produced wastewater, and induced subsurface migration pathways that can potentially adversely affect the environmental resources within the Williston Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223088","usgsCitation":"Delzer, G.C., and Post van der Burg, M., 2023, Research needs identified for potential effects of energy development activities on environmental resources of the Williston Basin, United States: U.S. Geological Survey Fact Sheet 2022–3088, 6 p., https://doi.org/10.3133/fs20223088.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","ipdsId":"IP-142397","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":499561,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114229.htm","linkFileType":{"id":5,"text":"html"}},{"id":411643,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3088/images"},{"id":411641,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3088/fs20223088.pdf","text":"Report","size":"1.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022–3088"},{"id":411642,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3088/fs20223088.XML"},{"id":411640,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3088/coverthb.jpg"},{"id":411720,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223088/full","text":"Report","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Montana, North Dakota, South Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101.85992433948707,\n 44.748962924301054\n ],\n [\n -100.27178237770465,\n 45.62378897009327\n ],\n [\n -99.72386467913583,\n 47.01666497234379\n ],\n [\n -98.92422494544115,\n 48.99070414841606\n ],\n [\n -106.85334014872393,\n 49.00199336720374\n ],\n [\n -106.20557284548465,\n 47.60278245148987\n ],\n [\n -105.42666681945474,\n 46.15028300648845\n ],\n [\n -104.32046634105996,\n 45.350667945249626\n ],\n [\n -103.35976723012234,\n 45.170260895064786\n ],\n [\n -102.7400085664068,\n 44.590251713951545\n ],\n [\n -101.96303401243244,\n 44.60899148746665\n ],\n [\n -101.85992433948707,\n 44.748962924301054\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702
Wetlands are the largest natural source of methane (CH4) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH4, but interpreting its spatiotemporal variations is challenging due to the co-occurrence of CH4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data-model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data-constrained model—iPEACE—reasonably reproduced CH4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH4 production appeared to be the most important process, followed by oxidation in explaining inter-site variations in CH4 emissions. Based on a sensitivity analysis, CH4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant-mediated transport appeared to be the major pathway for CH4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH4 production and CH4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH4 production, plant-mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH4 emissions across biomes. These processes and associated parameters for CH4 emissions among and within the wetlands provide useful insights for interpreting observed net CH4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH4 fluxes.
The abundance of Culex restuans and Culex pipiens in relation to ecological predictors is poorly understood in regions of the United States where their ranges overlap. It is suspected that these species play different roles in spreading West Nile virus (WNV) in these regions, but few studies have modeled these species separately or accounted for spatial correlation using Bayesian methods. We used mosquito surveillance data collected by the Pennsylvania Department of Environmental Protection from 2002 to 2016 and integrated nested Laplace approximations with the stochastic partial differential equation approach to predict C. restuans and C. pipiens abundance in relation to several ecological predictors. We then made a predictive risk surface of abundance for each species at locations that were not sampled. Explanatory variables in the models included ecological variables previously described to be important predictors of the abundance of these mosquito species. Developed habitat, temperature, and precipitation were important predictor variables for the abundance of C. restuans, whereas developed habitat, snow water equivalent, and normalized difference water index were important predictor variables for the abundance of C. pipiens. The abundance of C. restuans had a negative relationship with developed habitat in contrast to C. pipiens abundance, which had a positive relationship with developed habitat. Julian date was modeled as a temporal trend for both species and showed C. restuans to be more abundant from late April through late June and C. pipiens to be more abundant from July through September. A seasonal crossover was observed between these two species on Julian day 185, 4 July. We observed different spatial patterns of abundance in the predictive risk maps of each of the species. Our results indicate that modeling the abundance of these species spatially and separately in regions where these two mosquito vectors coexist can help gain further insight into understanding the epidemiology of WNV in human and susceptible animal populations.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4346","usgsCitation":"Bondo, K., Montecino-Latorre, D., Williams, L., Helwig, M., Duren, K., Hutchinson, M., and Walter, W., 2023, Spatial modeling of two mosquito vectors of West Nile virus using integrated nested Laplace approximations: Ecosphere, v. 14, no. 1, e4346, 15 p., https://doi.org/10.1002/ecs2.4346.","productDescription":"e4346, 15 p.","ipdsId":"IP-138613","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467127,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4346","text":"Publisher Index Page"},{"id":466441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":41,\"properties\":{\"name\":\"Pennsylvania\",\"nation\":\"USA 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Matt","contributorId":348326,"corporation":false,"usgs":false,"family":"Helwig","given":"Matt","affiliations":[{"id":83334,"text":"Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":923365,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duren, Kenneth","contributorId":348327,"corporation":false,"usgs":false,"family":"Duren","given":"Kenneth","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":923366,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hutchinson, Mike","contributorId":348328,"corporation":false,"usgs":false,"family":"Hutchinson","given":"Mike","affiliations":[{"id":83334,"text":"Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":923367,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Walter, W. David 0000-0003-3068-1073","orcid":"https://orcid.org/0000-0003-3068-1073","contributorId":219540,"corporation":false,"usgs":true,"family":"Walter","given":"W. David","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923368,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70239961,"text":"70239961 - 2023 - Contaminant exposure and transport from three potential reuse waters within a single watershed","interactions":[],"lastModifiedDate":"2023-03-20T18:57:43.980108","indexId":"70239961","displayToPublicDate":"2023-01-10T06:47:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Contaminant exposure and transport from three potential reuse waters within a single watershed","docAbstract":"Global demand for safe and sustainable water supplies necessitates a better understanding of contaminant exposures in potential reuse waters. In this study, we compared exposures and load contributions to surface water from the discharge of three reuse waters (wastewater effluent, urban stormwater, and agricultural runoff). Results document substantial and varying organic-chemical contribution to surface water from effluent discharges (e.g., disinfection byproducts [DBP], prescription pharmaceuticals, industrial/household chemicals), urban stormwater (e.g., polycyclic aromatic hydrocarbons, pesticides, nonprescription pharmaceuticals), and agricultural runoff (e.g., pesticides). Excluding DBPs, episodic storm-event organic concentrations and loads from urban stormwater were comparable to and often exceeded those of daily wastewater-effluent discharges. We also assessed if wastewater-effluent irrigation to corn resulted in measurable effects on organic-chemical concentrations in rain-induced agricultural runoff and harvested feedstock. Overall, the target-organic load of 491 g from wastewater-effluent irrigation to the study corn field during the 2019 growing season did not produce substantial dissolved organic-contaminant contributions in subsequent rain-induced runoff events. Out of the 140 detected organics in source wastewater-effluent irrigation, only imidacloprid and estrone had concentrations that resulted in observable differences between rain-induced agricultural runoff from the effluent-irrigated and nonirrigated corn fields. Analyses of pharmaceuticals and per-/polyfluoroalkyl substances in at-harvest corn-plant samples detected two prescription antibiotics, norfloxacin and ciprofloxacin, at concentrations of 36 and 70 ng/g, respectively, in effluent-irrigated corn-plant samples; no contaminants were detected in noneffluent irrigated corn-plant samples.