As the boundaries of urban land use continue to expand, environmental managers are looking for innovative ways to reduce export of nutrients from urban sources. Municipal services such as leaf collection and street cleaning have the potential to reduce nutrient pollution at its source while continuing to offer services valued by residents. This study characterized reductions of total and dissolved forms of phosphorus and nitrogen in stormwater runoff from paired catchments, testing the method and frequency of municipal leaf collection and street cleaning programs.
Overall, the performance of municipal programs was related to the frequency and not the form of treatment. Catchments receiving a weekly street cleaning by a regenerative-air street cleaner had the highest reduction in phosphorus load, ranging from 65 to 71 percent (probability value [p] is less than 0.05) for total phosphorus and 57 to 70 percent (p is less than 0.05) for dissolved phosphorus, regardless of leaf collection method or frequency. Reduction in nitrogen load was generally mixed, with many of the catchments showing no statistically significant changes after treatment. In general, nutrient concentrations, and subsequent percent reduction of nutrient loads, were positively correlated with street tree canopy. Collection of only leaf piles, leaving streets unswept, showed no significant reduction in loads of total or dissolved phosphorus and an 83 percent increase in load of total nitrogen. The majority of nutrient concentrations were in the dissolved fraction making source control through leaf collection and street cleaning more effective at reducing the amount of dissolved nutrients in stormwater runoff than structural practices such as wet detention ponds. Based on the results of this study, municipal leaf management programs would be most effective with weekly street cleaning in areas of high street tree canopy, whereas the method and frequency of leaf pile collection is of less importance to the mitigation of nutrients in stormwater runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205109","collaboration":"Prepared in cooperation with the Wisconsin Department of Natural Resources, the City of Madison, Fund for Lake Michigan, Yahara Watershed Improvement Network, Dane County Land and Water Resources, Clean Lakes Alliance, League of Wisconsin Municipalities, and DuPage River Salt Creek Workgroup","usgsCitation":"Selbig, W.R., Buer, N.H., Bannerman, R.T., and Gaebler, P., 2020, Reducing leaf litter contributions of phosphorus and nitrogen to urban stormwater through municipal leaf collection and street cleaning practices: U.S. Geological Survey Scientific Investigations Report 5109, 17 p., https://doi.org/10.3133/sir20205109.","productDescription":"Report: iv, 17 p.; Appendix; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-116819","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":380292,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93L2WM1","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Stormwater-quality data in the control and test catchments during the calibration and treatment phase of a leaf collection study in Madison, Fond du Lac, and Oshkosh, Wisconsin, from September 2016 through November 2019"},{"id":380291,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5109/sir20205109_appendix_1.pdf","text":"Appendix 1","size":"1.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5109 Appendix 1","linkHelpText":"— Paired-Basin Nutrient Loads in the Control and Test Catchments During Calibration and Treatment Phases"},{"id":380289,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5109/coverthb.jpg"},{"id":380290,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5109/sir20205109.pdf","text":"Report","size":"2.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5109"}],"country":"United States","state":"Wisconsin","city":"Fond du Lac, Madison, Oshkosh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.49462890625,\n 42.98154421882687\n ],\n [\n -89.27490234375,\n 42.98154421882687\n ],\n [\n -89.27490234375,\n 43.1405770781429\n ],\n [\n -89.49462890625,\n 43.1405770781429\n ],\n [\n -89.49462890625,\n 42.98154421882687\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.505859375,\n 43.71354951931429\n ],\n [\n -88.37814331054688,\n 43.71354951931429\n ],\n [\n -88.37814331054688,\n 43.804800966308385\n ],\n [\n -88.505859375,\n 43.804800966308385\n ],\n [\n -88.505859375,\n 43.71354951931429\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.61160278320312,\n 43.95822503841972\n ],\n [\n -88.50723266601562,\n 43.95822503841972\n ],\n [\n -88.50723266601562,\n 44.050089820756796\n ],\n [\n -88.61160278320312,\n 44.050089820756796\n ],\n [\n -88.61160278320312,\n 43.95822503841972\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
The U.S. Geological Survey, in cooperation with the Connecticut Department of Public Health, conducted a study to determine the presence of arsenic and uranium in private drinking water wells in Connecticut. Samples were collected during 2013–18 from wells completed in 115 geologic units, with 2,433 samples analyzed for arsenic and 2,191 samples analyzed for uranium. The study concluded four major findings.
Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Considerable effort and resources have been placed into conservation programs designed to reduce or alleviate negative environmental effects of crop production and into evaluation of the benefits of these programs. Wetlands are an important source of ecosystem services, but modeling wetland plants is an emerging science. To date, wetland plant growth has not been explicitly accounted for in ecosystem service models that quantify conservation program effects. As part of an effort to more accurately simulate wetland plants within process-based models, we expanded upon plant growth data collected in an earlier effort with additional sampling at two of four previously sampled areas, and included a fifth sampling site. We then used data from the five sites spanning five years as wetland plant parameters at both the species and functional group levels for the Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) model. In addition to individual species, modelers are interested in functional groups representing a collection of species because it is unrealistic to model every species occurring in an ecosystem. ALMANAC simulations were completed at three sites for both individual wetland plant species and functional groups. At each site, simulated plant yields were within 1 Mg ha–1 (±7%) of measured values (r2 = 0.99). Multisite species simulated yields were within 37% of measured values (r2 = 0.95). Functional groups performed as well as individual species simulations. Functional group simulated yields were within 1 Mg ha–1 (±5%) of measured yields. Plant growth is a major component of these wetland ecosystems, and ALMANAC verified wetland plant parameters support more accurate assessments of conservation programs and practices on the influence of wetland ecosystems embedded within agricultural fields. The improved plant parameters we provide here will be transferred to other process-based models that focus on other ecosystem components such as soil and water effects, facilitating wetland evaluations across the United States and elsewhere.
The relationship between people and wildfire has always been paradoxical: fire is an essential ecological process and management tool, but can also be detrimental to life and property. Consequently, fire regimes have been modified throughout history through both intentional burning to promote benefits and active suppression to reduce risks. Reintroducing fire and its benefits back into the Sky Island mountains of the United States-Mexico borderlands has the potential to reduce adverse effects of altered fire regimes and build resilient ecosystems and human communities. To help guide regional fire restoration, we describe the frequency and severity of recent fires over a 32-year period (1985-2017) across a vast binational region in the United States-Mexico borderlands and assess variation in fire frequency and severity across climate gradients and in relation to vegetation and land tenure classes. We synthesize relevant literature on historical fire regimes within 9 major vegetation types and assess how observed contemporary fire characteristics vary from expectations based on historical patterns. Less than 28% of the study area burned during the observation period, excluding vegetation types in warmer climates that are not adapted to fire (eg, Desertscrub and Thornscrub). Average severity of recent fires was low despite some extreme outliers in cooler, wetter environments. Midway along regional temperature and precipitation gradients, approximately 64% of Pine-Oak Forests burned at least once, with fire frequencies that mainly corresponded to historical expectations on private lands in Mexico but less so on communal lands, suggesting the influence of land management. Fire frequency was higher than historical expectations in extremely cool and wet environments that support forest types such as Spruce-Fir, indicating threats to these systems possibly attributable to drought and other factors. In contrast, fires were absent or infrequent across large areas of Woodlands (~73% unburned) and Grasslands (~88% unburned) due possibly to overgrazing, which reduces abundance and continuity of fine fuels needed to carry fire. Our findings provide a new depiction of fire regimes in the Sky Islands that can help inform fire management, restoration, and regional conservation planning, fostered by local and traditional knowledge and collaboration among landowners and managers.
","language":"English","publisher":"Sage Journals","doi":"10.1177/1178622120969191","usgsCitation":"Villarreal, M.L., Iniguez, J.M., Flesch, A.D., Sanderlin, J.S., Cortes Montano, C., Conrad, C.R., and Haire, S.L., 2020, Contemporary fire regimes provide a critical perspective on restoration needs in the Mexico-United States borderlands: Air, Soil and Water Research, v. 13, p. 1-18, https://doi.org/10.1177/1178622120969191.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-117669","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":454834,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/1178622120969191","text":"Publisher Index Page"},{"id":436720,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99S0I9W","text":"USGS data release","linkHelpText":"Differenced Normalized Burn Ratio (dNBR) data of wildfires in the Sky Island Mountains of the southwestern US and northern Mexico from 2011-2017"},{"id":380988,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, Sonora","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.796875,\n 29.036960648558267\n ],\n [\n -108.984375,\n 29.036960648558267\n ],\n [\n -108.984375,\n 33.54139466898275\n ],\n [\n -111.796875,\n 33.54139466898275\n ],\n [\n -111.796875,\n 29.036960648558267\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":806073,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iniguez, Jose M. 0000-0002-4566-1297","orcid":"https://orcid.org/0000-0002-4566-1297","contributorId":213972,"corporation":false,"usgs":false,"family":"Iniguez","given":"Jose","email":"","middleInitial":"M.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":806074,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flesch, Aaron D. 0000-0003-3434-0778","orcid":"https://orcid.org/0000-0003-3434-0778","contributorId":245372,"corporation":false,"usgs":false,"family":"Flesch","given":"Aaron","email":"","middleInitial":"D.","affiliations":[{"id":49169,"text":"School of Natural Resources and the Environment and The Desert Laboratory on Tumamoc Hill, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":806075,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanderlin, Jamie S. 0000-0001-8651-9804","orcid":"https://orcid.org/0000-0001-8651-9804","contributorId":245373,"corporation":false,"usgs":false,"family":"Sanderlin","given":"Jamie","email":"","middleInitial":"S.","affiliations":[{"id":49171,"text":"US Forest Service, Rocky Mountain Research Station, Flagstaff, Arizona","active":true,"usgs":false}],"preferred":false,"id":806076,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cortes Montano, Citlali 0000-0002-1916-1985","orcid":"https://orcid.org/0000-0002-1916-1985","contributorId":213973,"corporation":false,"usgs":false,"family":"Cortes Montano","given":"Citlali","email":"","affiliations":[{"id":38945,"text":"Universidad Juárez del Estado de Durango","active":true,"usgs":false}],"preferred":false,"id":806077,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Conrad, Caroline Rose 0000-0002-0496-8081","orcid":"https://orcid.org/0000-0002-0496-8081","contributorId":236945,"corporation":false,"usgs":true,"family":"Conrad","given":"Caroline","email":"","middleInitial":"Rose","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":806078,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haire, Sandra L. 0000-0002-5356-7567","orcid":"https://orcid.org/0000-0002-5356-7567","contributorId":213971,"corporation":false,"usgs":false,"family":"Haire","given":"Sandra","email":"","middleInitial":"L.","affiliations":[{"id":32362,"text":"Haire Laboratory for Landscape Ecology","active":true,"usgs":false}],"preferred":false,"id":806079,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216782,"text":"70216782 - 2020 - Recent and projected precipitation and temperature changes in the Grand Canyon area with implications for groundwater resources","interactions":[],"lastModifiedDate":"2020-12-10T13:27:13.701227","indexId":"70216782","displayToPublicDate":"2020-11-12T09:24:34","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Recent and projected precipitation and temperature changes in the Grand Canyon area with implications for groundwater resources","docAbstract":"Groundwater is a critical resource in the Grand Canyon region, supplying nearly all water needs for residents and millions of visitors. Additionally, groundwater discharging at hundreds of spring locations in and near Grand Canyon supports important ecosystems in this mostly arid environment. The security of groundwater supplies is of critical importance for both people and ecosystems in the region and the potential for changes to groundwater systems from projected climate change is a cause for concern. In this study, we analyze recent historical and projected precipitation and temperature data for the Grand Canyon region. Projected climate scenarios are then used in Soil Water Balance groundwater infiltration simulations to understand the state-of-the-science on projected changes to groundwater resources in the area. Historical climate data from 1896 through 2019 indicate multi-decadal cyclical patterns in both precipitation and temperature for most of the time period. Since the 1970s, however, a significant rising trend in temperature is observed in the area. All 10-year periods since 1993 are characterized by both below average precipitation and above average temperature. Downscaled and bias-corrected precipitation and temperature output from 97 CMIP5 global climate models for the water-year 2020–2099 time period indicate projected precipitation patterns similar to recent historical (water-year 1951–2015) data. Projected temperature for the Grand Canyon area, however, is expected to rise by as much as 3.4 °C by the end of the century, relative to the recent historical average. Integrating the effects of projected precipitation and temperature changes on groundwater infiltration, simulation results indicate that > 76% of future decades will experience average potential groundwater infiltration less than that of the recent historical period.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-020-76743-6","usgsCitation":"Tillman, F.D., Gangopadhyay, S., and Pruitt, T., 2020, Recent and projected precipitation and temperature changes in the Grand Canyon area with implications for groundwater resources: Scientific Reports, v. 10, 19740, 11 p., https://doi.org/10.1038/s41598-020-76743-6.","productDescription":"19740, 11 p.","ipdsId":"IP-117188","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":454837,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-76743-6","text":"Publisher Index Page"},{"id":381030,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Utah","otherGeospatial":"Colorado Plateau, Grand Canyon, Kaibab Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.97216796875,\n 35.60371874069731\n ],\n [\n -109.53369140625,\n 35.60371874069731\n ],\n [\n -109.53369140625,\n 38.35888785866677\n ],\n [\n -113.97216796875,\n 38.35888785866677\n ],\n [\n -113.97216796875,\n 35.60371874069731\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2020-11-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806235,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":806236,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pruitt, Tom 0000-0002-3543-1324","orcid":"https://orcid.org/0000-0002-3543-1324","contributorId":173440,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","email":"","affiliations":[{"id":27228,"text":"Reclamation","active":true,"usgs":false}],"preferred":false,"id":806237,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70216124,"text":"ofr20201085 - 2020 - Quality assurance/quality control procedure for New Jersey’s water-use data for the New Jersey Water Transfer Data System (NJWaTr)","interactions":[],"lastModifiedDate":"2020-11-10T22:12:04.805415","indexId":"ofr20201085","displayToPublicDate":"2020-11-10T11:25:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1085","displayTitle":"Quality Assurance/Quality Control Procedure for New Jersey’s Water-Use Data for the New Jersey Water Transfer Data System (NJWaTr)","title":"Quality assurance/quality control procedure for New Jersey’s water-use data for the New Jersey Water Transfer Data System (NJWaTr)","docAbstract":"This report is an instructional reference document that describes methods developed and used by the U.S. Geological Survey (USGS) New Jersey Water Science Center (NJWSC) to assure the quality and completeness of water-use data as provided by the New Jersey Department of Environmental Protection (NJDEP) Bureau of Water Allocation. These data are owned wholly by the State of New Jersey. The role of the USGS NJWSC is to assure the quality of these data by compiling, reviewing, and checking the datasets before uploading them into the New Jersey Water Transfer Data System (NJWaTr) database on an annual basis. The complete uploaded version of the NJWaTr database serves as the repository for New Jersey’s approved and published water-use data. The State of New Jersey maintains a public-facing version of the NJWaTr database (available online at https://www.nj.gov/dep/njgs/geodata/dgs10-3.htm) that contains monthly water-use data at the municipality and 14-digit Hydrologic Unit Code subwatershed level. The protected version of the NJWaTr database that contains monthly site-specific water-use data is available from the NJDEP upon request.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201085","collaboration":"Prepared in cooperation with New Jersey Department of Environmental Protection","usgsCitation":"Shourds, J.L., 2020, Quality assurance/quality control procedure for New Jersey’s water-use data for the New Jersey Water Transfer Data System (NJWaTr): U.S. Geological Survey Open-File Report 2020–1085, 26 p., https://doi.org/10.3133/ofr20201085.","productDescription":"viii, 26 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112307","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":380203,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1085/coverthb.jpg"},{"id":380204,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1085/ofr20201085.pdf","text":"Report","size":"2.09 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Jersey\",\"nation\":\"USA \"}}]}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Understanding recent historical and projected trends in precipitation and temperature in the Colorado River Basin, and estimating what the projected changes in these climate parameters may mean for groundwater resources in the region, is important for water managers and policymakers to sustainably manage water resources in the basin. Historical (1896–2019) precipitation and temperature data for the upper and lower Colorado River Basins were analyzed to better understand recent trends in climate data that may affect groundwater resources in the area. Historical data indicate multidecadal-scale cyclical patterns in precipitation in both the upper and lower basins. Although upper basin precipitation had no statistical trend over the recent historical period, the lower basin had a weak negative trend over this period. Multidecadal-scale cyclical patterns in temperature also are observed in historical climate data in both the upper and lower basins, at least until the early 1970s. Beginning at that time, both the upper and lower basins experienced strong, monotonic positive trends in temperature. Basic principles of hydrology indicate that periods of decreasing precipitation as well as increasing temperature would have a negative effect, that is, reduction in groundwater infiltration and hence, reduced recharge of aquifer systems.
Projected climate data from 97 Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble members across the full range of Representative Concentration Pathway (RCPs) from water years 1951 through 2099 were evaluated to understand what current global climate models are projecting about future conditions in the Colorado River Basin, and what this might mean for groundwater systems in the region. Precipitation in the upper basin is projected to increase throughout the rest of the century, rising to 6 percent above the 1951–2015 historical period by mid-century and to 9 percent above the historical period by the end of the century. Temperature in the upper basin also is projected to be above the recent historical median throughout the rest of the century, with steady warming in decadal average temperatures expected until the last quarter of this century. In contrast to projected precipitation in the upper basin, precipitation in the lower basin is projected to be the same as, or slightly less than, the historical period throughout most of the rest of this century. Like projected temperature in the upper basin, temperature in the lower basin also is projected to be above the recent historical median throughout the rest of the century. Comparing median projections for all future decades with median results from all historical decades, future precipitation is expected to be greater than that of the past in the upper basin, though no significant difference is projected for precipitation in the lower basin. Significant increases (p-value<0.05) are expected in temperature in both the upper and lower basins.
To estimate the effects of projected precipitation and temperature on groundwater systems in the region, results from the 97 member CMIP5 climate projection ensemble were used as input in a Soil-Water Balance (SWB) groundwater infiltration model for the Colorado River Basin. SWB simulation results indicate that the upper Colorado River Basin is expected to experience decades of above-historical-average groundwater infiltration through the end of the century. For the lower Colorado River Basin, simulated groundwater infiltration is projected to be consistently less than the recent (1951–2015) historical period for most of the remaining century. A comparison of the distribution of all median simulated groundwater infiltration results between recent historical and future periods indicates projected groundwater infiltration in the upper basin is significantly (p-value<0.05) greater over the combined 2020–2099 future period than the recent (1951–2015) historical period. Moreover, in 41 of 71 (58 percent) possible future decades in this century, groundwater infiltration is projected to be greater than the 75th percentile of historical simulated groundwater infiltration. Projected groundwater infiltration in the lower Colorado River Basin across all future decades is significantly less than in the historical period. Of the 71 future decades in the century, projected groundwater infiltration in the lower basin is expected to be less than the 25th percentile of historical infiltration in 55 (77 percent) of the 10-year periods. Important differences in projected precipitation between the upper (increasing precipitation) and lower (decreasing precipitation) basins largely drive the different responses of simulated groundwater infiltration in the upper (increasing infiltration) and lower (decreasing infiltration) basins. It will be useful to revisit projections in groundwater infiltration in the Colorado River Basin when more up-to-date projections of precipitation become available from the next Coupled Model Intercomparison Project phases or by using climate input developments through Regional Climate Modeling efforts and stochastic weather generators.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205107","collaboration":"Prepared in cooperation with Bureau of Reclamation","usgsCitation":"Tillman, F.D., Gangopadhyay, S., and Pruitt, T., 2020, Trends in recent historical and projected climate data for the Colorado River Basin and potential effects on groundwater availability: U.S. Geological Survey Scientific Investigations Report 2020–5107, 24 p., https://doi.org/10.3133/sir20205107.","productDescription":"Report: vii, 24 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-117191","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":380358,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5107/coverthb.jpg"},{"id":380361,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7ST7MX7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Soil-water balance groundwater recharge model results for the Upper Colorado River Basin (ver. 2.0, April 2017)"},{"id":380359,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5107/sir20205107.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5107"},{"id":380360,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VLU0O6","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Soil-water balance groundwater infiltration model results for the Lower Colorado River Basin"}],"country":"Mexico, United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Utah, Wyoming","otherGeospatial":"Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5,\n 30.088107753367257\n ],\n [\n -108.984375,\n 30.221101852485987\n ],\n [\n -108.21533203125,\n 31.39115752282472\n ],\n [\n -107.16064453125,\n 35.08395557927643\n ],\n [\n -105.35888671875,\n 36.12012758978146\n ],\n [\n -104.6337890625,\n 36.40359962073253\n ],\n [\n -104.96337890625,\n 37.735969208590504\n ],\n [\n -105.3369140625,\n 38.58252615935333\n ],\n [\n -104.83154296875,\n 39.027718840211605\n ],\n [\n -104.87548828125,\n 41.19518982948959\n ],\n [\n -105.05126953124999,\n 41.934976500546604\n ],\n [\n -106.3916015625,\n 43.16512263158296\n ],\n [\n -110.91796875,\n 43.100982876188546\n ],\n [\n -111.09374999999999,\n 40.64730356252251\n ],\n [\n -111.533203125,\n 39.07890809706475\n ],\n [\n -113.04931640625,\n 37.405073750176925\n ],\n [\n -114.14794921875,\n 37.10776507118514\n ],\n [\n -114.54345703125,\n 37.54457732085582\n ],\n [\n -115.46630859375,\n 38.839707613545144\n ],\n [\n -116.806640625,\n 38.805470223177466\n ],\n [\n -116.19140625,\n 37.3002752813443\n ],\n [\n -115.3564453125,\n 36.421282443649496\n ],\n [\n -116.1474609375,\n 35.55010533588552\n ],\n [\n -115.4443359375,\n 32.491230287947594\n ],\n [\n -114.93896484374999,\n 31.3348710339506\n ],\n [\n -114.2578125,\n 31.57853542647338\n ],\n [\n -113.291015625,\n 31.316101383495624\n ],\n [\n -113.04931640625,\n 30.732392734006083\n ],\n [\n -112.7197265625,\n 30.012030680358613\n ],\n [\n -112.47802734375,\n 30.012030680358613\n ],\n [\n -112.5,\n 30.088107753367257\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
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520 N. Park Avenue
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This report summarizes the primary characteristics of alkalic-type epithermal gold (Au) deposits and provides an updated descriptive model. These deposits, primarily of Mesozoic to Neogene age, are among the largest epithermal gold deposits in the world. Considered a subset of low-sulfidation epithermal deposits, they are spatially and genetically linked to small stocks or clusters of intrusions containing high alkali-element contents. Deposits occur as disseminations, breccia-fillings, and veins and may be spatially and genetically related to skarns and low-grade porphyry copper (Cu) or molybdenum (Mo) systems. Gold commonly occurs as native gold, precious metal tellurides, and as sub-micron gold in arsenian pyrite. Quartz, carbonate, fluorite, adularia, and vanadian muscovite/roscoelite are the most common gangue minerals. Alkalic-type gold deposits form in a variety of geological settings including continent-arc collision zones and back-arc or post-subduction rifts that are invariably characterized by a transition from convergent to extensional or transpressive tectonics.
The geochemical compositions of alkaline igneous rocks spatially linked with these deposits span the alkaline-subalkaline transition. Their alkali enrichment may be masked by potassic alteration, but the unaltered or least altered rocks (1) have chondrite normalized patterns that are commonly light rare earth element (LREE) enriched, (2) are heavy rare earth element (HREE) depleted, and (3) have high large ion lithophile contents and variable enrichment of high-field strength elements. Radiogenic isotopes suggest a mantle derivation for the alkalic magmas but allow crustal contamination.
Oxygen and hydrogen isotope compositions show that the fluids responsible for deposit formation are dominantly magmatic, although meteoric or other external fluids (seawater, evolved groundwater) also contributed to the ore-forming fluids responsible for these deposits. Carbon and sulfur isotope compositions in vein-hosted carbonates and sulfide gangue minerals, respectively, coincide with magmatic values, although a sedimentary source of carbon and sulfur is evident in several deposits.
Deep-seated structures are critical for the upwelling of hydrous alkalic magmas and for focusing magmatic-hydrothermal fluids to the site of precious metal deposition. The source of gold, silver (Ag), tellurium (Te), vanadium (V), and fluorine (F) was probably the alkalic igneous rocks themselves, and the coexistence of native gold, gold tellurides, and roscoelite in several deposits is primarily a function of similar physicochemical conditions during deposition (for example, overlapping pH and oxygen fugacity (fO2).
Potential environmental impacts related to the mining and processing of alkalic-type epithermal gold deposits include acid mine drainage with high levels of metals, especially zinc (Zn), copper, lead (Pb), and arsenic. However, because alkalic-type gold deposits typically contain carbonates, which contribute calcium and magnesium ions that increase water hardness, aquatic life may be afforded some protection. Impacts vary widely as a function of host rocks, climate, topography, and mining methods.
Geologic mapping to (1) highlight the distribution of potassic alteration; (2) define fault density and orientation of structures; (3) determine the distribution of alkaline rocks and hydrothermal breccias; and (4) identify uniquely colored gangue minerals, such as fluorite and roscoelite, will be critical to exploration and future discoveries. Geophysical techniques that identify potassium (K) anomalies (for example, radiometric and spectroscopic surveys), as well as magnetic, resistivity, aeromagnetic, and gravity surveys, may help locate zones of high-permeability that control advecting hydrothermal fluids. Geochemical surveys that include analyses for Au, Ag, barium, Te, K, F, V, Mo, and mercury, which are key elements in these deposits, should be undertaken along with the measurement of other pathfinder elements such as arsenic, bismuth, Cu, iron, nickel, Pb, antimony, selenium, and Zn.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070R","issn":"2328-0328","usgsCitation":"Kelley, K.D., Spry, P.G., McLemore, V.T., Fey, D.L., and Anderson, E.D., 2020, Alkalic-type epithermal gold deposit model: U.S. Geological Survey Scientific Investigations Report 2010–5070–R, 74 p., https://doi.org/ 10.3133/ sir20105070R.","productDescription":"x, 74 p.","onlineOnly":"Y","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":380198,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/r/sir20105070r.pdf","text":"Report","size":"11.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010–5070–R"},{"id":380197,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2010/5070/r/coverthb.jpg"}],"contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS–973
Denver, CO 80225
This study evaluated the spatial variability of trends in simulated snowpack properties across the Rio Grande headwaters of Colorado using the SnowModel snow evolution modeling system. SnowModel simulations were performed using a grid resolution of 100 m and 3-hourly time step over a 34-yr period (1984–2017). Atmospheric forcing was provided by phase 2 of the North American Land Data Assimilation System, and the simulations accounted for temporal changes in forest canopy from bark beetle and wildfire disturbances. Annual summary values of simulated snowpack properties [snow metrics; e.g., peak snow water equivalent (SWE), snowmelt rate and timing, and snow sublimation] were used to compute trends across the domain. Trends in simulated snow metrics varied depending on elevation, aspect, and land cover. Statistically significant trends did not occur evenly within the basin, and some areas were more sensitive than others. In addition, there were distinct trend differences between the different snow metrics. Upward trends in mean winter air temperature were 0.3°C decade−1, and downward trends in winter precipitation were −52 mm decade−1. Middle elevation zones, coincident with the greatest volumetric snow water storage, exhibited the greatest sensitivity to changes in peak SWE and snowmelt rate. Across the Rio Grande headwaters, snowmelt rates decreased by 20% decade−1, peak SWE decreased by 14% decade−1, and total snowmelt quantity decreased by 13% decade−1. These snow trends are in general agreement with widespread snow declines that have been reported for this region. This study further quantifies these snow declines and provides trend information for additional snow variables across a greater spatial coverage at finer spatial resolution.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-20-0077.1","usgsCitation":"Sexstone, G., Penn, C.A., Liston, G., Gleason, K., Moeser, C.D., and Clow, D.W., 2020, Spatial variability in seasonal snowpack trends across the Rio Grande headwaters (1984 - 2017): Journal of Hydrometeorology, v. 21, no. 11, p. 2713-2733, https://doi.org/10.1175/JHM-D-20-0077.1.","productDescription":"21 p.","startPage":"2713","endPage":"2733","ipdsId":"IP-114071","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":454846,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-20-0077.1","text":"Publisher Index Page"},{"id":436725,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q8PYX1","text":"USGS data release","linkHelpText":"SnowModel simulations and supporting observations for the Rio Grande Headwaters, southwestern Colorado, United States, 1984 - 2017"},{"id":380501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rio Grande headwaters","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.65777587890625,\n 37.267495764381856\n ],\n [\n -105.83404541015625,\n 37.267495764381856\n ],\n [\n -105.83404541015625,\n 37.91603433975963\n ],\n [\n -107.65777587890625,\n 37.91603433975963\n ],\n [\n -107.65777587890625,\n 37.267495764381856\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"21","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sexstone, Graham A. 0000-0001-8913-0546","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":203850,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":804851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Penn, Colin A. 0000-0002-5195-2744","orcid":"https://orcid.org/0000-0002-5195-2744","contributorId":203851,"corporation":false,"usgs":true,"family":"Penn","given":"Colin","email":"","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":804852,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liston, Glen","contributorId":244889,"corporation":false,"usgs":false,"family":"Liston","given":"Glen","affiliations":[{"id":36729,"text":"Cooperative Institute for Research in the Atmosphere","active":true,"usgs":false}],"preferred":false,"id":804853,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gleason, Kelly","contributorId":244890,"corporation":false,"usgs":false,"family":"Gleason","given":"Kelly","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":804854,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moeser, C. David 0000-0003-0154-9110","orcid":"https://orcid.org/0000-0003-0154-9110","contributorId":214563,"corporation":false,"usgs":true,"family":"Moeser","given":"C.","email":"","middleInitial":"David","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":804855,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":804856,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217232,"text":"70217232 - 2020 - A synthesis of patterns of environmental mercury inputs, exposure and effects in New York State","interactions":[],"lastModifiedDate":"2021-01-13T14:19:18.133975","indexId":"70217232","displayToPublicDate":"2020-11-10T08:16:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"A synthesis of patterns of environmental mercury inputs, exposure and effects in New York State","docAbstract":"Mercury (Hg) pollution is an environmental problem that adversely affects human and ecosystem health at local, regional, and global scales—including within New York State. More than two-thirds of the Hg currently released to the environment originates, either directly or indirectly, from human activities. Since the early 1800s, global atmospheric Hg concentrations have increased by three- to eight-fold over natural levels. In the U.S., atmospheric emissions and point-source releases to waterways increased following industrialization into the mid-1980s. Since then, water discharges have largely been curtailed. As a result, Hg emissions, atmospheric concentrations, and deposition over the past few decades have declined across the eastern U.S. Despite these decreases, Hg pollution persists. To inform policy efforts and to advance public understanding, the New York State Energy Research and Development Authority (NYSERDA) sponsored a scientific synthesis of information on Hg in New York State. This effort includes 23 papers focused on Hg in atmospheric deposition, water, fish, and wildlife published in Ecotoxicology. New York State experiences Hg contamination largely due to atmospheric deposition. Some landscapes are inherently sensitive to Hg inputs driven by the transport of inorganic Hg to zones of methylation, the conversion of inorganic Hg to methylmercury, and the bioaccumulation and biomagnification along food webs. Mercury concentrations exceed human and ecological risk thresholds in many areas of New York State, particularly the Adirondacks, Catskills, and parts of Long Island. Mercury concentrations in some biota have declined in the Eastern Great Lakes Lowlands and the Northeastern Highlands over the last four decades, concurrent with decreases in water releases and air emissions from regional and U.S. sources. However, widespread changes have not occurred in other ecoregions of New York State. While the timing and magnitude of the response of Hg levels in biota varies, policies expected to further diminish Hg emissions should continue to decrease Hg concentrations in food webs, yielding benefits to the fish, wildlife, and people of New York State. Anticipated improvements in the Hg status of aquatic ecosystems are likely to be greatest for inland surface waters and should be roughly proportional to declines in atmospheric Hg deposition. Efforts that advance recovery from Hg pollution in recent years have yielded significant progress, but Hg remains a pollutant of concern. Indeed, due to this extensive compilation of Hg observations in biota, it appears that the extent and intensity of the contamination on the New York landscape and waterscape is greater than previously recognized. Understanding the extent of Hg contamination and recovery following decreases in atmospheric Hg deposition will require further study, underscoring the need to continue existing monitoring efforts.
To meet drinking water regulations, rather than investing in costly treatment plant operations, managers can look for ways to improve source water quality; this requires understanding watershed sources and fates of constituents of concern. Trihalomethanes (THMs) are one of the major classes of regulated disinfection byproducts, formed when a specific fraction of the organic carbon pool—referred to as THM precursors—reacts with chorine and/or bromine during treatment. Understanding the source, fate, timing and duration of the organic compounds that react to form THMs will allow identification of targeted and effective management actions. In this study we evaluated THM precursor contributions from multiple land use categories and hydrologic contexts, including novel data for urban land uses that demonstrate strong potential to release water with high THM formation potential (THMFP; median 618 μg L−1): greater than storm runoff integrated across a mixed-use (1/3 natural, 2/3 agricultural) watershed (median 460 μg L−1), irrigation runoff from agricultural systems (357 μg L−1), or runoff from a natural forested (median 123 μg L−1) and shrubland/grassland (median 259 μg L−1) watersheds. While individual storm events released high THM precursor concentrations over short periods, dry season agricultural irrigation as well as urban landscapes have the potential to release water high in THM precursors for several months. Experimental bioassays and sampling along 333 miles of the California Aqueduct confirmed bioavailability and photooxidation potential of less than 10% for THM precursors, suggesting that rivers with residence times of days to weeks may act as THM precursor conduits, shuttling THM precursors from hundreds of miles away to drinking water intakes with minimal degradation. This finding has considerable implications for water managers, who may therefore consider THM precursor management strategies that target even sources located far upstream.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.140571","usgsCitation":"Eckard, R.S., Bergamaschi, B.A., Pellerin, B., Kraus, T.E., and Hernes, P.J., 2020, Trihalomethane precursors: Land use hot spots, persistence during transport, and management options: Science of the Total Environment, v. 742, 140571, 9 p., https://doi.org/10.1016/j.scitotenv.2020.140571.","productDescription":"140571, 9 p.","ipdsId":"IP-119566","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":420660,"type":{"id":24,"text":"Thumbnail"},"url":"http://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River, Willow Slough Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.17412069648752,\n 38.72735441792287\n ],\n [\n -122.17412069648752,\n 38.49482301341115\n ],\n [\n -121.67887201941832,\n 38.49482301341115\n ],\n [\n -121.67887201941832,\n 38.72735441792287\n ],\n [\n -122.17412069648752,\n 38.72735441792287\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"742","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eckard, Robert S.","contributorId":88863,"corporation":false,"usgs":true,"family":"Eckard","given":"Robert","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":882660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pellerin, Brian A. 0000-0003-3712-7884","orcid":"https://orcid.org/0000-0003-3712-7884","contributorId":204324,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian A.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":882662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kraus, Tamara E. C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":147560,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E. C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":882663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hernes, Peter J.","contributorId":139730,"corporation":false,"usgs":false,"family":"Hernes","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":12894,"text":"Department of Land, Air, and Water Resources, University of California, One Shields Avenue, Davis, CA, 95616, USA","active":true,"usgs":false}],"preferred":false,"id":882664,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216917,"text":"70216917 - 2020 - The INI North American Regional Nitrogen Center: 2011–2015 nitrogen activities in North America","interactions":[],"lastModifiedDate":"2020-12-16T13:53:06.921866","indexId":"70216917","displayToPublicDate":"2020-11-10T07:49:59","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"34","title":"The INI North American Regional Nitrogen Center: 2011–2015 nitrogen activities in North America","docAbstract":"The North American Nitrogen Center (NANC) carries out three main charges: (1) conducting assessments on nitrogen (N) flows within North America and the consequences for human health, water resources, biodiversity, and greenhouse gas emissions; (2) facilitating efforts to develop solutions to the problem of excess nitrogen in agricultural, institutional, and natural resource management sectors; and (3) presenting these results to policy makers. There are formidable challenges in reducing N loss from all parts of the North American food production and supply chain, including altering consumer behavior. The NANC is working with producers, trade groups, universities, and supply chains to develop effective practices for minimizing loss of reactive nitrogen (Nr) to the environment. The NANC is also helping public land management and regulatory agencies prepare effective policy approaches toward minimizing ecological damage from atmospheric Nr deposition.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Just enough nitrogen","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-58065-0_34","usgsCitation":"Baron, J., and Davidson, E., 2020, The INI North American Regional Nitrogen Center: 2011–2015 nitrogen activities in North America, chap. 34 of Just enough nitrogen, p. 489-497, https://doi.org/10.1007/978-3-030-58065-0_34.","productDescription":"9 p.","startPage":"489","endPage":"497","ipdsId":"IP-111809","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":381417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Baron, Jill S. 0000-0002-5902-6251","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":215101,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":806943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davidson, Eric A.","contributorId":245739,"corporation":false,"usgs":false,"family":"Davidson","given":"Eric A.","affiliations":[{"id":38802,"text":"University of Maryland Center for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":806944,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70228271,"text":"70228271 - 2020 - Diets of double-crested cormorants in the Winnebago System, Wisconsin","interactions":[],"lastModifiedDate":"2022-02-08T20:52:13.193412","indexId":"70228271","displayToPublicDate":"2020-11-09T14:38:40","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Diets of double-crested cormorants in the Winnebago System, Wisconsin","docAbstract":"Double-crested cormorant Phalacrocorox auritus Lesson (cormorant) populations have increased throughout the Great Lakes region of North America causing concern related to the impact of cormorant predation on fish communities. A recent decline in yellow perch Perca flavescens (Mitchill) abundance within the Lake Winnebago System, Wisconsin, USA, prompted an assessment of cormorant diets to evaluate potential effects of cormorant predation on the sportfish community. Diets were collected from 883 cormorants (417 from Lake Winnebago and 466 from Lake Butte des Morts) between 2015 and 2017. Cormorant diets on both waterbodies consisted mostly of freshwater drum Aplodinotus grunniens Rafinesque and gizzard shad Dorosoma cepedianum (Lesueur). Yellow perch and walleye Sander vitreus (Mitchill) observations were infrequent and represented < 5% of cormorant diets by weight each year. Under current conditions, cormorant predation likely has minimal impact on the Lake Winnebago sportfish community, but more research is needed to assess potential impacts on Lake Butte des Morts.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12466","usgsCitation":"Koenigs, R.P., Dembkowski, D., Lovell, C., Isermann, D.A., and Nickel, A., 2020, Diets of double-crested cormorants in the Winnebago System, Wisconsin: Fisheries Management and Ecology, v. 28, no. 2, p. 183-193, https://doi.org/10.1111/fme.12466.","productDescription":"11 p.","startPage":"183","endPage":"193","ipdsId":"IP-110241","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":488962,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.unl.edu/icwdm_usdanwrc/2436","text":"External Repository"},{"id":395654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Benedict's Island, Garlic Island, Fraction Islands Lake Butte des Morts ,Lake Winnebago, Long Point Island Monkey Island,,Terrell's Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.95492553710938,\n 43.78695837311561\n ],\n [\n -88.2366943359375,\n 43.78695837311561\n ],\n [\n -88.2366943359375,\n 44.24421523567905\n ],\n [\n -88.95492553710938,\n 44.24421523567905\n ],\n [\n -88.95492553710938,\n 43.78695837311561\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Koenigs, Ryan P.","contributorId":275008,"corporation":false,"usgs":false,"family":"Koenigs","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":56696,"text":"Wisconson Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":833573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dembkowski, Daniel J.","contributorId":275009,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":833574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovell, Charles D.","contributorId":275010,"corporation":false,"usgs":false,"family":"Lovell","given":"Charles D.","affiliations":[{"id":40821,"text":"U. 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Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":833575,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833572,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nickel, Adam","contributorId":275011,"corporation":false,"usgs":false,"family":"Nickel","given":"Adam","email":"","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":833576,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70216165,"text":"sim3450 - 2020 - Bedrock geologic map of the 15' Sleetmute A-2 quadrangle, southwestern Alaska","interactions":[],"lastModifiedDate":"2020-11-09T12:57:35.594614","indexId":"sim3450","displayToPublicDate":"2020-11-06T12:18:29","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3450","displayTitle":"Bedrock Geologic Map of the 15' Sleetmute A-2 Quadrangle, Southwestern Alaska","title":"Bedrock geologic map of the 15' Sleetmute A-2 quadrangle, southwestern Alaska","docAbstract":"Twelve unnamed, bedrock stratigraphic units are recognized within the Sleetmute A-2 1:63,360-scale quadrangle of southwestern Alaska. These units range in age from late(?) Proterozoic through Devonian and can be divided into two distinct facies belts: (1) a southern facies of dominantly shallow-water platform carbonate and minor siliciclastic rocks (including Early Ordovician–Early Devonian platform edge algal buildups) with subordinate transgressive tongues of deeper-water platy carbonates; and (2) a northern facies belt of approximately age equivalent deep-water carbonate and siliciclastic rocks deposited in slope and basinal environments. Both facies belts belong to the Farewell terrane of Decker and others (1994). Two structural provinces are also recognized, which correspond directly with these belts. The Farewell terrane is interpreted as a continental margin sequence that rifted from Siberia. Many of the bedrock units recognized in the Sleetmute A-2 quadrangle are equivalent to units previously recognized to the east and northeast in the Lime Hills, McGrath, and Medfra quadrangles. Shallow-water carbonate platform rocks make up the majority of the southern facies and occur primarily along the crest and north side (and to a lesser degree along the south side) of a prominent crescentic-shaped, east-west trending anticlinal axis exposed in the southern part of the Sleetmute A-2 quadrangle. Because of the relatively low thermal alteration indices of the rocks of this area and the presence of highly porous dolostone intervals of good reservoir quality in the platform facies, this region elicited interest for petroleum exploration in the 1980s. However, low total organic carbon (TOC) content of potential source rocks within the Ordovician–Silurian basinal facies belt indicates low petroleum resource potential for this area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3450","usgsCitation":"Blodgett, R.B., Wilson, F.H., Shew, N.B., and Clough, J.G., 2020, Bedrock geologic map of the 15' Sleetmute A-2 quadrangle, southwestern Alaska: U.S. Geological Survey Scientific Investigations Map 3450, 18 p., 1 map sheet, scale 1:63,360, https://doi.org/10.3133/sim3450.","productDescription":"Pamphlet: iv, 18 p.; 1 Sheet: 23.20 x 26.17 inches; Table; Spatial Data","onlineOnly":"Y","ipdsId":"IP-098211","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":380271,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3450/sim3450.pdf","text":"Sheet 1","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3450"},{"id":380272,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3450/sim3450_pamphlet.pdf","text":"Pamphlet","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3450 Pamphlet"},{"id":380270,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3450/coverthb.jpg"},{"id":380273,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3450/sim3450_table.csv","text":"Table 1","size":"10 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIM 3450 Table csv"},{"id":380274,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3450/sim3450_table.xls","text":"Table 1","size":"39 KB xls","description":"SIM 3450 Table xls"},{"id":380275,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3450/sim3450_spatial_data.zip","text":"SIM 3450 spatial data","size":"2.2 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3450 Spatial Data"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.45,\n 61.000\n ],\n [\n -156.2230,\n 61.000\n ],\n [\n -156.2230,\n 61.15\n ],\n [\n -156.45,\n 61.15\n ],\n [\n -156.45,\n 61.000\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
This report provides the best estimates of riparian area evapotranspiration (ET) on the rivers and streams of the Navajo Nation by (1) quantifying the natural riparian vegetation water use within the Little Colorado River watershed using a literature search for comparable riparian ET estimates, and (2) in conjunction with the given area of stream-side plant cover on the Navajo Nation, provides the best estimate of consumptive use, the total water requirement (in acre-feet). This report includes riparian water use information only from the literature for riparian areas that are in similar dryland ecosystems in the Southwest, and not specific to the perennial tributaries and springs on the Navajo Nation within the Little Colorado River watershed. The report also includes any information found regarding the location of Navajo Nation weather station variables, such as where we can derive required data inputs from the Navajo Nation to estimate actual ET rates (in millimeters per day or millimeters per year). We provide estimates of annual riparian plant water use and calculations that include reference ET (potential ET or ETo), precipitation (in millimeters), and the calculations of consumptive water requirements of riparian vegetation. We cite our data sources and provide references used to determine the consumptive water requirement (acre-feet).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201129","collaboration":"Prepared in cooperation with Fred Phillips Consulting","usgsCitation":"Nagler, P.L., 2020, Literature reviewed estimates of riparian consumptive water use in the drylands of Northeast Arizona, USA: U.S. Geological Survey Open-File Report 2020–1129, 9 p., https://doi.org/10.3133/ofr20201129.","productDescription":"v, 9 p.","onlineOnly":"Y","ipdsId":"IP-122975","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":380268,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1129/coverthb.jpg"},{"id":380269,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1129/ofr20201129.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1129"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.26855468749999,\n 32.30570601389429\n ],\n [\n -113.51074218749999,\n 32.30570601389429\n ],\n [\n -113.51074218749999,\n 35.71083783530009\n ],\n [\n -115.26855468749999,\n 35.71083783530009\n ],\n [\n -115.26855468749999,\n 32.30570601389429\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.90673828125,\n 34.45221847282654\n ],\n [\n -108.984375,\n 34.45221847282654\n ],\n [\n -108.984375,\n 36.96744946416934\n ],\n [\n -111.90673828125,\n 36.96744946416934\n ],\n [\n -111.90673828125,\n 34.45221847282654\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC Staff, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
Shorebirds—which include sandpipers, plovers, and oystercatchers—are perhaps best known by their presence on sandy beaches, running along the water’s edge while they probe for food. But they are probably less recognized for their impressive long-distance migrations. Millions of individuals travel from across the globe to breed throughout Alaska each spring, making these birds a familiar and important part of local wildlife communities and Alaska Native cultures. Unfortunately, many shorebird populations have steeply declined worldwide. Because shorebirds use the same coastal habitats as humans, anthropogenic development can lead to habitat loss that degrades the extent and quality of coastal sites important to these species. However, Alaska has an abundance of intact coastal ecosystems that provide important breeding and migratory stopover sites for shorebirds, making the State one of the world’s most critical sites for shorebirds. The focus of shorebird research at the U.S. Geological Survey Alaska Science Center is to help identify important breeding and migratory sites, and to investigate the causes of the declines in many shorebird populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203056","usgsCitation":"Ruthrauff, D.R., Tibbitts, T.L., and Pearce, J.M., 2020, Shorebird research at the U.S. Geological Survey Alaska Science Center: U.S. Geological Survey Fact Sheet 2020-3056, 4 p., https://doi.org/10.3133/fs20203056.","productDescription":"4 p.","onlineOnly":"Y","ipdsId":"IP-118225","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":380242,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3056/fs20203056.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3056"},{"id":380241,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3056/coverthb2.jpg"}],"contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Perennial snow, or firn, covers 80 % of the Greenland ice sheet and has the capacity to retain surface meltwater, influencing the ice sheet mass balance and contribution to sea-level rise. Multilayer firn models are traditionally used to simulate firn processes and estimate meltwater retention. We present, intercompare and evaluate outputs from nine firn models at four sites that represent the ice sheet's dry snow, percolation, ice slab and firn aquifer areas. The models are forced by mass and energy fluxes derived from automatic weather stations and compared to firn density, temperature and meltwater percolation depth observations. Models agree relatively well at the dry-snow site while elsewhere their meltwater infiltration schemes lead to marked differences in simulated firn characteristics. Models accounting for deep meltwater percolation overestimate percolation depth and firn temperature at the percolation and ice slab sites but accurately simulate recharge of the firn aquifer. Models using Darcy's law and bucket schemes compare favorably to observed firn temperature and meltwater percolation depth at the percolation site, but only the Darcy models accurately simulate firn temperature and percolation at the ice slab site. Despite good performance at certain locations, no single model currently simulates meltwater infiltration adequately at all sites. The model spread in estimated meltwater retention and runoff increases with increasing meltwater input. The highest runoff was calculated at the KAN_U site in 2012, when average total runoff across models (±2σ) was 353±610 mm w.e. (water equivalent), about 27±48 % of the surface meltwater input. We identify potential causes for the model spread and the mismatch with observations and provide recommendations for future model development and firn investigation.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/tc-14-3785-2020","usgsCitation":"Vandecrux, B., Mottram, R., Langen, P., Fausto, R., Olesen, M., Stevens, C.M., Verjans, V., Lee, A., Ligtenberg, S., Kuipers Munneke, P., Marchenko, S., van Pelt, W., Meyer, C.R., Simonsen, S.B., Heilig, A., Samimi, S., Marshall, S.J., Machguth, H., MacFerrin, M.J., Niwano, M., Miller, O.L., Voss, C.I., and Box, J.E., 2020, The firn meltwater Retention Model Intercomparison Project (RetMIP): Evaluation of nine firn models at four weather station sites on the Greenland ice sheet: The Cryosphere, v. 14, p. 3785-3810, https://doi.org/10.5194/tc-14-3785-2020.","productDescription":"26 p.","startPage":"3785","endPage":"3810","ipdsId":"IP-118335","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":454868,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-14-3785-2020","text":"Publisher Index Page"},{"id":380331,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -42.1875,\n 61.438767493682825\n ],\n [\n -22.8515625,\n 69.41124235697256\n ],\n [\n -18.984375,\n 76.01609366420995\n ],\n [\n -14.0625,\n 81.56996820323275\n ],\n [\n -66.796875,\n 80.70399666821143\n ],\n [\n -71.015625,\n 78.83606545333527\n ],\n [\n -70.3125,\n 76.9206135182968\n ],\n [\n -58.35937499999999,\n 73.92246884621463\n ],\n [\n -57.30468749999999,\n 69.16255790810501\n ],\n [\n -50.2734375,\n 60.23981116999893\n ],\n [\n -41.8359375,\n 59.17592824927136\n ],\n [\n -42.1875,\n 61.438767493682825\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2020-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Vandecrux, Baptiste","contributorId":244723,"corporation":false,"usgs":false,"family":"Vandecrux","given":"Baptiste","email":"","affiliations":[{"id":48961,"text":"Geological Survey of Denmark and Greenland, Copenhagen, Denmark.","active":true,"usgs":false}],"preferred":false,"id":804456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mottram, Ruth","contributorId":244738,"corporation":false,"usgs":false,"family":"Mottram","given":"Ruth","email":"","affiliations":[],"preferred":false,"id":804486,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langen, Peter","contributorId":244739,"corporation":false,"usgs":false,"family":"Langen","given":"Peter","email":"","affiliations":[],"preferred":false,"id":804487,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fausto, Robert","contributorId":220400,"corporation":false,"usgs":false,"family":"Fausto","given":"Robert","email":"","affiliations":[{"id":40164,"text":"Geological Survey of Denmark and Greenland","active":true,"usgs":false}],"preferred":false,"id":804488,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olesen, Martin","contributorId":244740,"corporation":false,"usgs":false,"family":"Olesen","given":"Martin","email":"","affiliations":[],"preferred":false,"id":804489,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stevens, C. 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Western Branch","active":true,"usgs":true}],"preferred":true,"id":804506,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Box, Jason E.","contributorId":198809,"corporation":false,"usgs":false,"family":"Box","given":"Jason","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":804507,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70217122,"text":"70217122 - 2020 - Phasing of millennial-scale climate variability in the Pacific and Atlantic Oceans","interactions":[],"lastModifiedDate":"2021-01-06T12:47:55.504011","indexId":"70217122","displayToPublicDate":"2020-11-06T06:40:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Phasing of millennial-scale climate variability in the Pacific and Atlantic Oceans","docAbstract":"New radiocarbon and sedimentological results from the Gulf of Alaska document recurrent millennial-scale episodes of reorganized Pacific Ocean ventilation synchronous with rapid Cordilleran Ice Sheet discharge, indicating close coupling of ice-ocean dynamics spanning the past 42,000 years. Ventilation of the intermediate-depth North Pacific tracks strength of the Asian monsoon, supporting a role for moisture and heat transport from low latitudes in North Pacific paleoclimate. Changes in carbon-14 age of intermediate waters are in phase with peaks in Cordilleran ice-rafted debris delivery, and both consistently precede ice discharge events from the Laurentide Ice Sheet, known as Heinrich events. This timing precludes an Atlantic trigger for Cordilleran Ice Sheet retreat and instead implicates the Pacific as an early part of a cascade of dynamic climate events with global impact.
","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.aba7096","usgsCitation":"Walczak, M., Mix, A., Cowan, E., Fallon, S., Fitfield, K., Alder, J.R., Du, J., Haley, B., Hobern, T., Padman, J., Praetorius, S.K., Schmittner, A., Stoner, J., and Zellers, S., 2020, Phasing of millennial-scale climate variability in the Pacific and Atlantic Oceans: Science, v. 370, no. 6517, p. 716-720, https://doi.org/10.1126/science.aba7096.","productDescription":"5 p.","startPage":"716","endPage":"720","ipdsId":"IP-120777","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":381934,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"370","issue":"6517","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Walczak, Maureen 0000-0002-4123-6998","orcid":"https://orcid.org/0000-0002-4123-6998","contributorId":206972,"corporation":false,"usgs":false,"family":"Walczak","given":"Maureen","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":807650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mix, Alan","contributorId":184163,"corporation":false,"usgs":false,"family":"Mix","given":"Alan","affiliations":[],"preferred":false,"id":807651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cowan, Ellen 0000-0001-6512-5769","orcid":"https://orcid.org/0000-0001-6512-5769","contributorId":247312,"corporation":false,"usgs":false,"family":"Cowan","given":"Ellen","email":"","affiliations":[{"id":36626,"text":"Appalachian State University","active":true,"usgs":false}],"preferred":false,"id":807652,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fallon, Stewart 0000-0002-8064-5903","orcid":"https://orcid.org/0000-0002-8064-5903","contributorId":152573,"corporation":false,"usgs":false,"family":"Fallon","given":"Stewart","email":"","affiliations":[],"preferred":false,"id":807653,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fitfield, Keith 0000-0003-2866-4944","orcid":"https://orcid.org/0000-0003-2866-4944","contributorId":247314,"corporation":false,"usgs":false,"family":"Fitfield","given":"Keith","email":"","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":807654,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - 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2020 - High prevalence of biliary neoplasia in white perch Morone americana: Potential roles of bile duct parasites and environmental contaminants","interactions":[],"lastModifiedDate":"2021-01-22T19:45:45.226167","indexId":"70211649","displayToPublicDate":"2020-11-05T08:56:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"displayTitle":"High prevalence of biliary neoplasia in white perch Morone americana: Potential roles of bile duct parasites and environmental contaminants","title":"High prevalence of biliary neoplasia in white perch Morone americana: Potential roles of bile duct parasites and environmental contaminants","docAbstract":"Recent surveys of white perch Morone americana from Chesapeake Bay, USA, revealed a high prevalence of hepatic and biliary lesions, including neoplasia, and bile duct parasites. Here, we describe lesions in the liver and gallbladder and evaluate for statistical associations among lesions, parasites, and biomarkers of chemical exposure in fish from 2 tributaries of Chesapeake Bay. Fish were collected from an estuarine site in the Choptank River (n = 122, ages 3-11), a tributary with extensive agriculture within the watershed, and the Severn River (n = 131, ages 2-16), a tributary with extensive urban development. Passive integrative samplers were deployed at the fish collection site and an upstream, non-tidal site in each river for 30 d. Intrahepatic biliary lesions observed in fish from both rivers included neoplasia (23.3%), dysplasia (16.2%), hyperplasia (46.6%), cholangitis (24.9%), and dilated ducts containing plasmodia of Myxidium sp. (24.9%). Hepatocellular lesions included foci of hepatocellular alteration (FHA, 15.8%) and neoplasia in 4 Severn River fish (2.3%). Age of fish and Myxidium sp. infections were significant risk factors for proliferative and neoplastic biliary lesions, age alone was a risk factor for FHA, and Goussia bayae infections were associated with cholangitis and cholecystitis. Lesion prevalence was higher in fish from the Severn River, which contained higher concentrations of PAHs, organochlorine pesticides, and brominated diphenyl ethers. Metabolite biomarkers indicated higher PAH exposures in Severn River fish. This study suggests Myxidium sp. as a promoter of bile duct tumors, but more data are needed to evaluate the biological effects of environmental contaminants in this species.
","language":"English","publisher":"Inter Research Science Publisher","doi":"10.3354/dao03510","usgsCitation":"Matsche, M.A., Blazer, V., Pulster, E., and Mazik, P.M., 2020, High prevalence of biliary neoplasia in white perch Morone americana: Potential roles of bile duct parasites and environmental contaminants: Diseases of Aquatic Organisms, v. 141, p. 195-224, https://doi.org/10.3354/dao03510.","productDescription":"20 p.","startPage":"195","endPage":"224","ipdsId":"IP-119255","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":377084,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.2666015625,\n 36.58024660149866\n ],\n [\n -74.92675781249999,\n 36.58024660149866\n ],\n [\n -74.92675781249999,\n 39.757879992021756\n ],\n [\n -78.2666015625,\n 39.757879992021756\n ],\n [\n -78.2666015625,\n 36.58024660149866\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"141","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Matsche, Mark A","contributorId":194275,"corporation":false,"usgs":false,"family":"Matsche","given":"Mark","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":794927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pulster, Erin","contributorId":236999,"corporation":false,"usgs":false,"family":"Pulster","given":"Erin","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":794929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":794930,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255619,"text":"70255619 - 2020 - Comparison of groundwater storage changes from GRACE satellites with monitoring and modeling of major U.S. aquifers","interactions":[],"lastModifiedDate":"2024-06-26T12:26:49.454901","indexId":"70255619","displayToPublicDate":"2020-11-05T07:20:17","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of groundwater storage changes from GRACE satellites with monitoring and modeling of major U.S. aquifers","docAbstract":"GRACE satellite data are widely used to estimate groundwater storage (GWS) changes in aquifers globally; however, comparisons with GW monitoring and modeling data are limited. Here we compared GWS changes from GRACE over 15 yr (2002–2017) in 14 major U.S. aquifers with groundwater-level (GWL) monitoring data in ~23,000 wells and with regional and global hydrologic and land surface models. Results show declining GWS trends from GRACE data in the six southwestern and south-central U.S. aquifers, totaling −90 km3 over 15 yr, related to long-term (5–15 yr) droughts, and exceeding Lake Mead volume by ~2.5×. GWS trends in most remaining aquifers were stable or slightly rising. GRACE-derived GWS changes agree with GWL monitoring data in most aquifers (correlation coefficients, R = 0.52–0.95), showing that GRACE satellites capture groundwater (GW) dynamics. Regional GW models (eight models) generally show similar or greater GWS trends than those from GRACE. Large discrepancies in the Mississippi Embayment aquifer, with modeled GWS decline approximately four times that of GRACE, may reflect uncertainties in model storage parameters, stream capture, pumpage, and/or recharge rates. Global hydrologic models (2003–2014), which include GW pumping, generally overestimate GRACE GWS depletion (total: approximately −172 to −186 km3) in heavily exploited aquifers in southwestern and south-central U.S. by ~2.4× (GRACE: −74 km3), underscoring needed modeling improvements relative to anthropogenic impacts. Global land surface models tend to track GRACE GWS dynamics better than global hydrologic models. Intercomparing remote sensing, monitoring, and modeling data underscores the importance of considering all data sources to constrain GWS uncertainties.
Assessing chemical loading from streams in remote, difficult-to-access watersheds is challenging. The Grand Canyon area in northern Arizona, an international tourist destination and sacred place for many Native Americans, is characterized by broad plateaus divided by canyons as much as two-thousand meters deep and hosts some of the highest-grade uranium deposits in the U.S. From 2015–2018 major surface waters in Grand Canyon were monitored for select elements associated with breccia-pipe uranium deposits in the area, including uranium, arsenic, cadmium, and lead. Dissolved constituents in the Colorado River were monitored upstream (Lees Ferry), in the middle (Phantom Ranch), and downstream (Diamond Creek) of uranium mining areas. Concentrations of uranium, arsenic, cadmium, and lead at these main-stem sites varied little during the study period and were all well below human health and aquatic life benchmark criteria (30, 10, 5, and 15 μg/L maximum contaminant levels and 15, 150, 0.8, and 3.1 μg/L aquatic life criteria, respectively). Additionally, dissolved and sediment-bound constituents were monitored during a wide range of streamflow conditions at Little Colorado River, Kanab Creek, and Havasu Creek tributaries, whose watersheds have experienced different levels of uranium mining activities over time. Samples from the tributary sites contained ≤3.8 μg/L of dissolved cadmium and lead, and ≤17 μg/L of dissolved uranium. Dissolved arsenic also was mostly below human and aquatic life criteria at Little Colorado River and Kanab Creek; however, 63% of water samples from Havasu Creek were above the maximum contaminant level for arsenic. Arsenic in suspended sediment was greater than sediment quality guidelines in 9%, 35%, and 35% of samples from Little Colorado River, Kanab Creek, and Havasu Creek, respectively. At the concentrations observed during this study, tributaries contributed on average only about 0.12 μg/L of arsenic and 0.03 μg/L of uranium to the main-stem river. This study demonstrates how chemical loading from mined watersheds may be reliably assessed across a wide range of flow conditions in challenging locations.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0241502","usgsCitation":"Tillman, F.D., Anderson, J.R., Unema, J., and Chapin, T., 2020, Assessing uranium and select trace elements associated with breccia pipe uranium deposits in the Colorado River and main tributaries in Grand Canyon, USA: PLoS ONE, v. 15, no. 11, e0241502, 32 p., https://doi.org/10.1371/journal.pone.0241502.","productDescription":"e0241502, 32 p.","ipdsId":"IP-109483","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":454877,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0241502","text":"Publisher Index Page"},{"id":381032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.08203125,\n 35.44277092585766\n ],\n [\n -110.54443359375,\n 35.44277092585766\n ],\n [\n -110.54443359375,\n 36.94989178681327\n ],\n [\n -114.08203125,\n 36.94989178681327\n ],\n [\n -114.08203125,\n 35.44277092585766\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Jessica R. 0000-0002-3286-7552 jranderson@usgs.gov","orcid":"https://orcid.org/0000-0002-3286-7552","contributorId":193158,"corporation":false,"usgs":true,"family":"Anderson","given":"Jessica","email":"jranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Unema, Joel A. 0000-0002-7428-219X","orcid":"https://orcid.org/0000-0002-7428-219X","contributorId":211449,"corporation":false,"usgs":true,"family":"Unema","given":"Joel A.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":806229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chapin, Thomas 0000-0001-6587-0734 tchapin@usgs.gov","orcid":"https://orcid.org/0000-0001-6587-0734","contributorId":758,"corporation":false,"usgs":true,"family":"Chapin","given":"Thomas","email":"tchapin@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":806230,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216761,"text":"70216761 - 2020 - An assessment of the thiamine status of Smallmouth Bass (Micropterus dolomieu) in the Susquehanna River watershed","interactions":[],"lastModifiedDate":"2020-12-04T14:50:36.985453","indexId":"70216761","displayToPublicDate":"2020-11-04T08:47:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"An assessment of the thiamine status of Smallmouth Bass (Micropterus dolomieu) in the Susquehanna River watershed","docAbstract":"Unpredictable recruitment and physical abnormalities (sores and lesions) have been observed in populations of Micropterus dolomieu (Smallmouth Bass) throughout the Susquehanna River basin. Malnutrition has been proposed as one of among several potential stressors, yet little to no information was available to critically assess its feasibility as a causal factor. We measured thiamine profiles of Smallmouth Bass (free thiamine [T], thiamine monophosphate [TP], and thiamine pyrophosphate [TPP]) for 3 tissues (egg, liver, and muscle) collected at 13 sites in the Susquehanna River and compared the values to those in 2 neighboring drainages (Allegheny River and Delaware River). Mass-specific thiamine concentrations in eggs were comparable to published values for Micropterus salmoides (Largemouth Bass), but higher than those found in Sander vitreus (Walleye), and Salvelinus namaycush (Lake Trout) known to consume Alosa pseudoharengus (Alewife), a thiaminase positive forage fish. In general, Smallmouth Bass collected from sites within the Susquehanna River basin had thiamine concentrations comparable to fish at the site in the Allegheny River, yet average thiamine concentrations in fish from the Susquehanna and Allegheny sites were each considerably lower than the average value collected from the Smallmouth Bass in the Delaware River. Future studies should consider a more balanced sampling design among watersheds to assess spatial variability among sites and basins. Average site-specific thiamine concentrations measured in Smallmouth Bass exceeded published minimum threshold values for Lake Trout. Given that Smallmouth Bass appear to have distinct thiamine profiles, concentrations, and timing of egg development, threshold thiamine concentrations parameterized for salmonids may not apply to Smallmouth Bass. As such, empirical studies that parameterize species-specific thiamine thresholds are needed to formally evaluate if thiamine deficiency is an issue for Smallmouth Bass in the Susquehanna River basin. To our knowledge, these are the first data on thiamine concentrations published for Smallmouth Bass.
The processes controlling advance and retreat of outlet glaciers in fjords draining the Greenland Ice Sheet remain poorly known, undermining assessments of their dynamics and associated sea-level rise in a warming climate. Mass loss of the Greenland Ice Sheet has increased six-fold over the last four decades, with discharge and melt from outlet glaciers comprising key components of this loss. Here we acquired oceanographic data and multibeam bathymetry in the previously uncharted Sherard Osborn Fjord in northwest Greenland where Ryder Glacier drains into the Arctic Ocean. Our data show that warmer subsurface water of Atlantic origin enters the fjord, but Ryder Glacier’s floating tongue at its present location is partly protected from the inflow by a bathymetric sill located in the innermost fjord. This reduces under-ice melting of the glacier, providing insight into Ryder Glacier’s dynamics and its vulnerability to inflow of Atlantic warmer water.
A crude-oil spill occurred in 1979 when a pipeline burst near Bemidji, Minnesota. More than 70 percent of the 1.7 million liters of spilled crude oil was removed shortly thereafter. In response to a requirement by the State regulatory agency to remove the remaining crude to a sheen in all wells, in 1998, the pipeline company installed a dual-pump recovery system at the site. This additional remediation from 1999 to 2003 resulted in removal of about 115,000 liters of crude oil, representing between 36 and 41 percent of the volume of oil (281,000–317,000 liters) estimated to be present in 1998. Effects of the 1999–2003 remediation on groundwater plumes and unsaturated-zone vapor concentrations were evaluated by the U.S. Geological Survey using several methods including measurements of oil thicknesses in wells; field water-quality properties of dissolved oxygen, specific conductance, temperature, and pH in groundwater; and vapor concentrations of methane, carbon dioxide, nitrogen, and oxygen in the unsaturated zone.
Although the recovery system decreased oil thicknesses near the remediation wells, average oil thicknesses measured in all wells at the site were not reduced substantially. Dissolved oxygen and specific conductance measurements indicate that a secondary plume was created during the remediation, caused by the disposal of pumped water from the remediation wells in an upgradient infiltration gallery. This plume expanded rapidly immediately after the start of the remediation in 1999, resulting in expansion of the anoxic zone of groundwater upgradient and beneath the existing natural attenuation plume. Beginning in 2000–1, for example, specific conductance concentrations noticeably increased in many wells at the north oil pool from about 400 to more than 700 microsiemens per centimeter. The rapid expansion of the anoxic and elevated specific conductance plume indicates that the remediation contributed substantial amounts of biodegradable dissolved organic carbon to groundwater through the infiltration gallery. The trends in vapor data collected before, during, and after the remediation generally support the research hypothesis that crude-oil removal would have an insignificant effect on vapor concentrations in the unsaturated zone. Although there were some small changes in the concentration of methane, carbon dioxide, nitrogen, and oxygen in the unsaturated zone, these changes were not coincident with the beginning or cessation of the remediation and are therefore thought to be the result of other factors affecting biodegradation rates. A decrease in methane concentrations in one representative well, for example, is thought to be the result of reduced rates of biodegradation and methane production from the increasingly more weathered crude oil. Oil-phase recovery at this site was determined to be challenging and resulted in considerable volumes of mobile and entrapped oil remaining in the subsurface despite remediation efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205111","collaboration":"Toxic Substances Hydrology Program","usgsCitation":"Delin, G.N., Herkelrath, W.N., and Trost, J.J., 2020, Effects of a crude-oil recovery remediation system operated 1999–2003 on groundwater plumes and unsaturated-zone vapor concentrations at a crude-oil spill site near Bemidji, Minnesota: U.S. Geological Survey Scientific Investigations Report 2020–5111, 31 p., https://doi.org/10.3133/sir20205111.","productDescription":"Report: vii, 31 p.; Data Releases","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-112190","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":380003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5111/coverthb.jpg"},{"id":380006,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","description":"USGS Data Release","linkHelpText":"USGS water data for the Nation"},{"id":380005,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FJ8I0P","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data sets from the National Crude Oil Spill Fate and Natural Attenuation Research site near Bemidji, Minnesota, USA (ver 3.0, April 2020)"},{"id":380004,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5111/sir20205111.pdf","text":"Report","size":"1.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5111"}],"country":"United States","state":"Minnesota","city":"Bemidji","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.98779296875,\n 47.416937456635445\n ],\n [\n -94.7900390625,\n 47.416937456635445\n ],\n [\n -94.7900390625,\n 47.537601245618134\n ],\n [\n -94.98779296875,\n 47.537601245618134\n ],\n [\n -94.98779296875,\n 47.416937456635445\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112