Carbonate-sandstone geology in southeastern Minnesota creates a heterogeneous landscape of springs, seeps, and sinkholes that supply groundwater into streams. Air temperatures are effective predictors of water temperature in surface-water dominated streams. However, no published work investigates the relationship between air and water temperatures in groundwater-fed streams (GWFS) across watersheds. We used simple linear regressions to examine weekly air-water temperature relationships for 40 GWFS in southeastern Minnesota. A 40-stream, composite linear regression model has a slope of 0.38, an intercept of 6.63, and R2 of 0.83. The regression models for GWFS have lower slopes and higher intercepts in comparison to surface-water dominated streams. Regression models for streams with high R2 values offer promise for use as predictive tools for future climate conditions. Climate change is expected to alter the thermal regime of groundwater-fed systems, but will do so at a slower rate than surface-water dominated systems. A regression model of intercept vs. slope can be used to identify streams for which water temperatures are more meteorologically than groundwater controlled, and thus more vulnerable to climate change. Such relationships can be used to guide restoration vs. management strategies to protect trout streams.
","language":"English","publisher":"Wiley","doi":"10.1111/jawr.12046","usgsCitation":"Krider, L.A., Magner, J.A., Perry, J., Vondracek, B.C., and Ferrington, L.C., 2013, Air - water temperature relationships in the trout streams of southeastern Minnesota’s carbonate - sandstone landscape: Journal of the American Water Resources Association, v. 49, no. 4, p. 896-907, https://doi.org/10.1111/jawr.12046.","productDescription":"12 p.","startPage":"896","endPage":"907","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-036165","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.01599121093749,\n 44.38669150215206\n ],\n [\n -92.9718017578125,\n 44.35920579433503\n ],\n [\n -93.1585693359375,\n 44.24126379833979\n ],\n [\n -93.0706787109375,\n 43.93350594453702\n ],\n [\n -92.3895263671875,\n 43.91372326852401\n ],\n [\n -92.1478271484375,\n 43.69965122967144\n ],\n [\n -92.0379638671875,\n 43.492782808225\n ],\n [\n -91.241455078125,\n 43.492782808225\n ],\n [\n -91.263427734375,\n 43.74728909225906\n ],\n [\n -91.38427734374999,\n 43.96514454266273\n ],\n [\n -91.6644287109375,\n 44.071800467511565\n ],\n [\n -91.8841552734375,\n 44.22158376545796\n ],\n [\n -91.9500732421875,\n 44.37098696297173\n ],\n [\n -92.01599121093749,\n 44.38669150215206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5763cdace4b07657d19ba748","contributors":{"authors":[{"text":"Krider, Lori A.","contributorId":172050,"corporation":false,"usgs":false,"family":"Krider","given":"Lori","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":639450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magner, Joseph A.","contributorId":172051,"corporation":false,"usgs":false,"family":"Magner","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":639451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Jim","contributorId":111771,"corporation":false,"usgs":true,"family":"Perry","given":"Jim","affiliations":[],"preferred":false,"id":639452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vondracek, Bruce C. bcv@usgs.gov","contributorId":904,"corporation":false,"usgs":true,"family":"Vondracek","given":"Bruce","email":"bcv@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637177,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferrington, Leonard C. Jr.","contributorId":172049,"corporation":false,"usgs":false,"family":"Ferrington","given":"Leonard","suffix":"Jr.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":639453,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046371,"text":"70046371 - 2013 - Estimating age ratios and size of Pacific walrus herds on coastal haulouts using video imaging","interactions":[],"lastModifiedDate":"2018-06-16T17:48:39","indexId":"70046371","displayToPublicDate":"2013-07-31T21:52:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Estimating age ratios and size of Pacific walrus herds on coastal haulouts using video imaging","docAbstract":"During Arctic summers, sea ice provides resting habitat for Pacific walruses as it drifts over foraging areas in the eastern Chukchi Sea. Climate-driven reductions in sea ice have recently created ice-free conditions in the Chukchi Sea by late summer causing walruses to rest at coastal haulouts along the Chukotka and Alaska coasts, which provides an opportunity to study walruses at relatively accessible locations. Walrus age can be determined from the ratio of tusk length to snout dimensions. We evaluated use of images obtained from a gyro-stabilized video system mounted on a helicopter flying at high altitudes (to avoid disturbance) to classify the sex and age of walruses hauled out on Alaska beaches in 2010–2011. We were able to classify 95% of randomly selected individuals to either an 8- or 3-category age class, and we found measurement-based age classifications were more repeatable than visual classifications when using images presenting the correct head profile. Herd density at coastal haulouts averaged 0.88 walruses/m2 (std. err. = 0.02), herd size ranged from 8,300 to 19,400 (CV 0.03–0.06) and we documented ~30,000 animals along ~1 km of beach in 2011. Within the herds, dependent walruses (0–2 yr-olds) tended to be located closer to water, and this tendency became more pronounced as the herd spent more time on the beach. Therefore, unbiased estimation of herd age-ratios will require a sampling design that allows for spatial and temporal structuring. In addition, randomly sampling walruses available at the edge of the herd for other purposes (e.g., tagging, biopsying) will not sample walruses with an age structure representative of the herd. Sea ice losses are projected to continue, and population age structure data collected with aerial videography at coastal haulouts may provide demographic information vital to ongoing efforts to understand effects of climate change on this species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0069806","usgsCitation":"Monson, D., Udevitz, M.S., and Jay, C.V., 2013, Estimating age ratios and size of Pacific walrus herds on coastal haulouts using video imaging: PLoS ONE, v. 8, no. 7, https://doi.org/10.1371/journal.pone.0069806.","ipdsId":"IP-045689","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":473631,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0069806","text":"Publisher Index Page"},{"id":277155,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277133,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0069806"}],"country":"United States","volume":"8","issue":"7","noUsgsAuthors":false,"publicationDate":"2013-07-31","publicationStatus":"PW","scienceBaseUri":"52206d61e4b0645fc25e8c2d","contributors":{"authors":[{"text":"Monson, Daniel H. 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":140480,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel H.","email":"dmonson@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":false,"id":479564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":479562,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":479563,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047326,"text":"fs20133055 - 2013 - Reproductive health of yellow perch, Perca flavescens, in Chesapeake Bay Tributaries","interactions":[],"lastModifiedDate":"2024-03-04T18:00:14.444595","indexId":"fs20133055","displayToPublicDate":"2013-07-31T15:57:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3055","title":"Reproductive health of yellow perch, Perca flavescens, in Chesapeake Bay Tributaries","docAbstract":"Yellow perch live in creeks, rivers, ponds, lakes, and estuaries across the central and eastern United States and Canada. In Chesapeake Bay, they tolerate salinities up to one-third that of seawater. The adults reside in the brackish waters of the bay’s tributaries and migrate upstream to spawn. Yellow perch are eagerly sought by recreational fishermen for their excellent taste and, because their late winter spawning runs are the earliest of the year, they are regarded as a harbinger of spring. Yellow perch also support a small but valuable, tightly regulated commercial fishery in the part of Chesapeake Bay that lies in Maryland.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133055","usgsCitation":"Blazer, V., Pinkney, A., and Uphoff, J.H., 2013, Reproductive health of yellow perch, Perca flavescens, in Chesapeake Bay Tributaries: U.S. Geological Survey Fact Sheet 2013-3055, 2 p., https://doi.org/10.3133/fs20133055.","productDescription":"2 p.","numberOfPages":"2","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":275652,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133055.jpg"},{"id":275651,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3055/pdf/fs2013-3055.pdf"},{"id":275650,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3055/"}],"country":"United States","state":"Maryl","otherGeospatial":"Chesapeake Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.6224,37.3195 ], [ -77.6224,39.7196 ], [ -74.7564,39.7196 ], [ -74.7564,37.3195 ], [ -77.6224,37.3195 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51fa2c80e4b076c3a8d82627","contributors":{"authors":[{"text":"Blazer, Vicki 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":792,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":481713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pinkney, A.E.","contributorId":87501,"corporation":false,"usgs":true,"family":"Pinkney","given":"A.E.","affiliations":[],"preferred":false,"id":481715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Uphoff, James H.","contributorId":74656,"corporation":false,"usgs":true,"family":"Uphoff","given":"James","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":481714,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047254,"text":"ofr20131178 - 2013 - Significance of headwater streams and perennial springs in ecological monitoring in Shenandoah National Park","interactions":[],"lastModifiedDate":"2013-07-31T15:50:02","indexId":"ofr20131178","displayToPublicDate":"2013-07-31T15:43:00","publicationYear":"2013","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":"2013-1178","title":"Significance of headwater streams and perennial springs in ecological monitoring in Shenandoah National Park","docAbstract":"Shenandoah National Park has been monitoring water chemistry and benthic macroinvertebrates in stream ecosystems since 1979. These monitoring efforts were designed to assess the status and trends in stream condition associated with atmospheric deposition (acid rain) and changes in forest health due to gypsy moth infestations. The primary objective of the present research was to determine whether the current long-term macroinvertebrate and water-quality monitoring program in Shenandoah National Park was failing to capture important information on the status and trends in stream condition by not sufficiently representing smaller, headwater streams. The current benthic-macroinvertebrate and water-chemistry sampling designs do not include routine collection of data from streams with contributing watershed areas smaller than 100 hectares, even though these small streams represent the overwhelming proportion of total stream length in the park. In this study, we sampled headwater sites, including headwater stream reaches (contributing watershed area approximately 100 hectares (ha) and perennial springs, in the park for aquatic macroinvertebrates and water chemistry and compared the results with current and historical data collected at long-term ecological monitoring (LTEM) sites on larger streams routinely sampled as part of ongoing monitoring efforts. The larger purpose of the study was to inform ongoing efforts by park managers to evaluate the effectiveness and efficiency of the current aquatic monitoring program in light of other potential stressors (for example, climate change) and limited resources. Our results revealed several important findings that could influence management decisions regarding long-term monitoring of park streams. First, we found that biological indicators of stream condition at headwater sites and perennial springs generally were more indicative of lower habitat quality and were more spatially variable than those observed at sites on routinely monitored larger streams. We hypothesized that poorer stream condition observed in smaller streams was due to stream drying that occurs more frequently in headwater areas. We also found that biological and water-chemistry measures responded differently to landscape drivers. Variation in most biological endpoints was driven primarily by stream size and was only secondarily associated with bedrock geology. In contrast, water chemistry showed essentially the opposite pattern, with underlying geology explaining much of the variation and stream size being of secondary importance. Therefore, expanding the LTEM program to include headwater areas would yield substantially different biological information, whereas broad inferences regarding spatial patterns in water chemistry would probably not change. Although significant differences in community composition were observed among streams of different sizes, no taxa were unique to headwater sites. All taxa collected at the 45 headwater sites also had been collected at one or more LTEM sites during one or more years. This observation indicates that headwater sites in the park may be structured by biotic nestedness; consequently, focusing management efforts on preserving the species pool at the larger LTEM sites would likely result in the protection of most taxa parkwide. Finally, linkages (correlations) between water chemistry and biological measures of stream condition were signficantly stronger when assessed at the LTEM sites than when assessed at the springs or headwater sites, indicating that conditions at downstream sites may be better indicators of water-quality trends.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131178","collaboration":"Prepared in Cooperation with the National Park Service","usgsCitation":"Snyder, C.D., Webb, J., Young, J.A., and Johnson, Z.B., 2013, Significance of headwater streams and perennial springs in ecological monitoring in Shenandoah National Park: U.S. Geological Survey Open-File Report 2013-1178, v, 46 p., https://doi.org/10.3133/ofr20131178.","productDescription":"v, 46 p.","numberOfPages":"51","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-049033","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":275649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131178.gif"},{"id":275648,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1178/pdf/ofr2013-1178.pdf"},{"id":275647,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1178/"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79,8.333333333333334E-4 ], [ -79,8.333333333333334E-4 ], [ -78,8.333333333333334E-4 ], [ -78,8.333333333333334E-4 ], [ -79,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51fa2c80e4b076c3a8d8262f","contributors":{"authors":[{"text":"Snyder, Craig D. 0000-0002-3448-597X csnyder@usgs.gov","orcid":"https://orcid.org/0000-0002-3448-597X","contributorId":2568,"corporation":false,"usgs":true,"family":"Snyder","given":"Craig","email":"csnyder@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":481529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Webb, James R.","contributorId":74431,"corporation":false,"usgs":true,"family":"Webb","given":"James R.","affiliations":[],"preferred":false,"id":481532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":481530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Zane B.","contributorId":21441,"corporation":false,"usgs":true,"family":"Johnson","given":"Zane","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":481531,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199861,"text":"70199861 - 2013 - Fine-scale hydrologic modeling for regional landscape applications: the California Basin Characterization Model development and performance","interactions":[],"lastModifiedDate":"2018-10-01T15:22:10","indexId":"70199861","displayToPublicDate":"2013-07-31T15:22:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1460,"text":"Ecological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Fine-scale hydrologic modeling for regional landscape applications: the California Basin Characterization Model development and performance","docAbstract":"Introduction
Resource managers need spatially explicit models of hydrologic response to changes in key climatic drivers across variable landscape conditions. We demonstrate the utility of a Basin Characterization Model for California (CA-BCM) to integrate high-resolution data on physical watershed characteristics with historical or projected climate data to predict watershed-specific hydrologic responses.
Methods
The CA-BCM applies a monthly regional water-balance model to simulate hydrologic responses to climate at the spatial resolution of a 270-m grid. The model has been calibrated using a total of 159 relatively unimpaired watersheds for the California region.
Results
As a result of calibration, predicted basin discharge closely matches measured data for validation watersheds. The CA-BCM recharge and runoff estimates, combined with estimates of snowpack and timing of snowmelt, provide a basis for assessing variations in water availability. Another important output variable, climatic water deficit, integrates the combined effects of temperature and rainfall on site-specific soil moisture, a factor that plants may respond to more directly than air temperature and precipitation alone. Model outputs are calculated for each grid cell, allowing results to be summarized for a variety of planning units including hillslopes, watersheds, ecoregions, or political boundaries.
Conclusions
The ability to confidently calculate hydrologic outputs at fine spatial scales provides a new suite of hydrologic predictor variables that can be used for a variety of purposes, such as projections of changes in water availability, environmental demand, or distribution of plants and habitats. Here we present the framework of the CA-BCM model for the California hydrologic region, a test of model performance on 159 watersheds, summary results for the region for the 1981–2010 time period, and changes since the 1951–1980 time period.
Electrical conductivity (κ) measurements of natural waters are typically referenced to 25 °C (κ25) using standard temperature compensation factors (α). For acidic waters (pH < 4), this can result in a large κ25 error (δκ25). The more the sample temperature departs from 25 °C, the larger the potential δκ25. For pH < 4, the hydrogen ion transport number becomes substantial and its mode of transport is different from most other ions resulting in a different α. A new method for determining α as a function of pH and temperature is presented. Samples with varying amounts of H2SO4 and NaCl were used to develop the new α, which was then applied to 65 natural water samples including acid mine waters, geothermal waters, seawater, and stream waters. For each sample, the κ and pH were measured at several temperatures from 5 to 90 °C and κ25 was calculated. The δκ25 ranged from −11 to 9% for the new method as compared to −42 to 25% and −53 to 27% for the constant α (0.019) and ISO-7888 methods, respectively. The new method for determining α is a substantial improvement for acidic waters and performs as well as or better than the standard methods for circumneutral waters.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/es402188r","usgsCitation":"McCleskey, R.B., 2013, New Method for Electrical Conductivity Temperature Compensation: Environmental Science & Technology, v. 47, no. 17, p. 9874-9881, https://doi.org/10.1021/es402188r.","productDescription":"8 p.","startPage":"9874","endPage":"9881","ipdsId":"IP-046099","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"17","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-08-15","publicationStatus":"PW","scienceBaseUri":"5980419ce4b0a38ca2789369","contributors":{"authors":[{"text":"McCleskey, R. Blaine 0000-0002-2521-8052 rbmccles@usgs.gov","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":147399,"corporation":false,"usgs":true,"family":"McCleskey","given":"R.","email":"rbmccles@usgs.gov","middleInitial":"Blaine","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":706782,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70118398,"text":"70118398 - 2013 - A combined radio- and stable-isotopic study of a California coastal aquifer system","interactions":[],"lastModifiedDate":"2018-09-27T10:53:11","indexId":"70118398","displayToPublicDate":"2013-07-28T16:23:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A combined radio- and stable-isotopic study of a California coastal aquifer system","docAbstract":"Stable and radioactive tracers were utilized in concert to characterize geochemical processes in a complex coastal groundwater system and to provide constraints on the kinetics of rock/water interactions. Groundwater samples from wells within the Dominguez Gap region of Los Angeles County, California were analyzed for a suite of major cations (Na+, K+, Mg2+, Ca2+) and anions (Cl−, SO42−), silica, alkalinity, select trace elements (Ba, B, Sr), dissolved oxygen, stable isotopes of hydrogen (δD), oxygen (δ18O), dissolved inorganic carbon (δ13CDIC), and radioactive isotopes (3H, 222Rn and 223,224,226,228Ra). In the study area, groundwater may consist of a complex mixture of native groundwater, intruded seawater, non-native injected water, and oil-field brine water. In some wells, Cl− concentrations attained seawater-like values and in conjunction with isotopically heavier δ18O values, these tracers provide information on the extent of seawater intrusion and/or mixing with oil-field brines. Groundwater 3H above 1 tritium unit (TU) was observed only in a few select wells close to the Dominguez Gap area and most other well groundwater was aged pre-1952. Based on an initial 14C value for the study site of 90 percent modern carbon (pmc), groundwater age estimates likely extend beyond 20 kyr before present and confirm deep circulation of some native groundwater through multiple aquifers. Enriched values of groundwater δ13CDIC in the absence of SO42− imply enhanced anaerobic microbial methanogenesis. While secular equilibrium was observed for 234U/238U (activity ratios ~1) in host matrices, strong isotopic fractionation in these groundwater samples can be used to obtain information of adsorption/desorption kinetics. Calculated Ra residence times are short, and the associated desorption rate constant is about three orders of magnitude slower than that of the adsorption rate constant. Combined stable- and radio-isotopic results provide unique insights into aquifer characteristics, such as geochemical cycling, rock/water interactions, and subsurface transport and mixing.","language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/w5020480","usgsCitation":"Swarzenski, P.W., Baskaran, M., Rosenbauer, R.J., Edwards, B.D., and Land, M., 2013, A combined radio- and stable-isotopic study of a California coastal aquifer system: Water, v. 5, no. 2, p. 480-504, https://doi.org/10.3390/w5020480.","productDescription":"25 p.","startPage":"480","endPage":"504","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":473642,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w5020480","text":"Publisher Index Page"},{"id":291225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291224,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/w5020480"}],"country":"United States","state":"California","county":"Los Angeles County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.9449,32.7984 ], [ -118.9449,34.8232 ], [ -117.6456,34.8232 ], [ -117.6456,32.7984 ], [ -118.9449,32.7984 ] ] ] } } ] }","volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-04-19","publicationStatus":"PW","scienceBaseUri":"57f7f286e4b0bc0bec0a0424","contributors":{"authors":[{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":496878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baskaran, Mark","contributorId":87867,"corporation":false,"usgs":false,"family":"Baskaran","given":"Mark","email":"","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":496881,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenbauer, Robert J. brosenbauer@usgs.gov","contributorId":204,"corporation":false,"usgs":true,"family":"Rosenbauer","given":"Robert","email":"brosenbauer@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":496877,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, Brian D. bedwards@usgs.gov","contributorId":3161,"corporation":false,"usgs":true,"family":"Edwards","given":"Brian","email":"bedwards@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":496879,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Land, Michael 0000-0001-5141-0307","orcid":"https://orcid.org/0000-0001-5141-0307","contributorId":56613,"corporation":false,"usgs":true,"family":"Land","given":"Michael","affiliations":[],"preferred":false,"id":496880,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70118374,"text":"70118374 - 2013 - K-Ar dating and delta O-18-delta D characterization of nanometric illite from Ordovician K-bentonites of the Appalachians: illitization and the Acadian-Alleghenian tectonic activity","interactions":[],"lastModifiedDate":"2014-07-28T15:47:23","indexId":"70118374","displayToPublicDate":"2013-07-28T15:35:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"K-Ar dating and delta O-18-delta D characterization of nanometric illite from Ordovician K-bentonites of the Appalachians: illitization and the Acadian-Alleghenian tectonic activity","docAbstract":"Nanometric (<0.02, 0.02–0.05, 0.05–0.1, 0.1–0.2 μm) illite fractions were separated from K-bentonite samples from northwestern Georgia, and studied by X-ray diffraction, oxygen and hydrogen isotope geochemistry, and K-Ar dated to more tightly constrain the tectono-thermal history of the Appalachian orogeny. Their XRD patterns are very similar for a given sample with respect to the peak shapes and positions. They are ordered illite-smectite mixed layers with only small variations in the relative proportions of illite and smectite interlayers. The illite crystal thickness distributions also are very homogeneous across the various size fractions of the same sample, but crystallite thickness varies from sample to sample. It can be concluded from the α-β2 diagram that illitization occurred in all fractions by simultaneous nucleation and crystal growth, except for one sample. In that sample, a period of growth without nucleation was detected on top of the nucleation and growth episode.
\nThe K-Ar ages organize into two isochrons, the first at 319.9 ± 2.0 Ma with an initial 40Ar/36Ar ratio of 271 ± 66 Ma, and the second at 284.9 ± 1.2 Ma with an initial 40Ar/36Ar ratio of 310 ± 44. One data point above the older isochron and three between the two isochrons suggest a detrital contamination for the former separate and a possible further generation of nanoparticles for the three others. The samples with the older crystallization age consist of illite and illite-rich mixed-layers, and those with the younger age contain smectite-rich mixed-layers without illite, or illite-enriched illite-smectite mixed-layers. The K-Ar ages fit the age trends published previously for similar K-bentonites with regional age patterns between 240 and 270 Ma in the southwestern region, between 270 and 300 Ma in the central zone and the southern Appalachians, and between 315 and 370 Ma in the northernmost.
\nEach of the two generations of illite crystals yields very consistent δ18O (V-SMOW) values at 17 ± 1‰ for the older and at 21 ± 1‰ for the younger. If crystallization temperatures of the nanometric illite were between 100 and 200 °C, as suggested by microthermometric determinations, the hydrothermal fluids had δ18O values of 4 ± 1‰ in the Dalton district and of 8 ± 1‰ in the Lafayette, Trenton, and Dirtseller districts at 100 °C, and of 11 ± 1 and 15 ± 1‰ in the same locations at 200 °C, probably because the water-rock isotope exchanges at elevated temperature occurred in rock-dominated systems. The δ18O of the fluids remained unchanged during local crystal growth, but varied depending on the geographic location of the samples and timing of illitization. The δD (V-SMOW) values of the different size fractions do not provide consistent information; they range from −70 to −45‰ for most nanometric and micrometric fractions (V-SMOW), but with no apparent coherent pattern.
\nNanometric illite-rich crystals from K-bentonite that underwent tectono-thermal alteration yield constant ages, constant clay mineralogy, constant crystallite size distributions for all of the nucleating and growing illite-type crystals of each sample, as well as constant δ18O values implying constant fluid chemistry, all pointing to geologically sudden crystallization.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"American Mineralogist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am.2013.4510","usgsCitation":"Clauer, N., Fallick, A.E., Eberl, D.D., Honty, M., Huff, W.D., and Auberti, A., 2013, K-Ar dating and delta O-18-delta D characterization of nanometric illite from Ordovician K-bentonites of the Appalachians: illitization and the Acadian-Alleghenian tectonic activity: American Mineralogist, v. 98, no. 11-12, p. 2144-2154, https://doi.org/10.2138/am.2013.4510.","productDescription":"11 p.","startPage":"2144","endPage":"2154","costCenters":[],"links":[{"id":291211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291210,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2138/am.2013.4510"}],"country":"United States","state":"Georgia","city":"Dalton;Lafayette;Trenton","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.61,33.63 ], [ -85.61,35.0 ], [ -82.77,35.0 ], [ -82.77,33.63 ], [ -85.61,33.63 ] ] ] } } ] }","volume":"98","issue":"11-12","noUsgsAuthors":false,"publicationDate":"2013-11-18","publicationStatus":"PW","scienceBaseUri":"57f7f286e4b0bc0bec0a0426","contributors":{"authors":[{"text":"Clauer, Norbert","contributorId":9182,"corporation":false,"usgs":true,"family":"Clauer","given":"Norbert","affiliations":[],"preferred":false,"id":496849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fallick, Anthony E.","contributorId":107210,"corporation":false,"usgs":true,"family":"Fallick","given":"Anthony","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":496854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eberl, Dennis D.","contributorId":68388,"corporation":false,"usgs":true,"family":"Eberl","given":"Dennis","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":496851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Honty, Miroslav","contributorId":91034,"corporation":false,"usgs":true,"family":"Honty","given":"Miroslav","email":"","affiliations":[],"preferred":false,"id":496853,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huff, Warren D.","contributorId":90228,"corporation":false,"usgs":true,"family":"Huff","given":"Warren","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":496852,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Auberti, Amelie","contributorId":51220,"corporation":false,"usgs":true,"family":"Auberti","given":"Amelie","email":"","affiliations":[],"preferred":false,"id":496850,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70148415,"text":"70148415 - 2013 - Occurrence and mobility of mercury in groundwater: Chapter 5","interactions":[],"lastModifiedDate":"2016-04-12T19:06:45","indexId":"70148415","displayToPublicDate":"2013-07-27T11:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"title":"Occurrence and mobility of mercury in groundwater: Chapter 5","docAbstract":"1. Introduction
\n1.1. FORMS, TOXICITY, AND HEALTH EFFECTS
\nMercury (Hg) has long been identified as an element that is injurious, even lethal, to living organisms. Exposure to its inorganic form, mainly from elemental Hg (Hg(0)) vapor (Fitzgerald & Lamborg, 2007) can cause damage to respiratory, neural, and renal systems (Hutton, 1987; USEPA, 2012; WHO, 2012). The organic form, methylmercury (CH3Hg+; MeHg), is substantially more toxic than the inorganic form (Fitzgerald & Lamborg, 2007). Methylmercury attacks the nervous system and exposure can prove lethal, as demonstrated by well-known incidents such as those in 1956 in Minimata, Japan (Harada, 1995), and 1971 in rural Iraq (Bakir et al., 1973), where, in the former, industrial release of MeHg into coastal waters severely tainted the fish caught and eaten by the local population, and in the latter, grain seed treated with an organic mercurial fungicide was not planted, but eaten in bread instead. Resultant deaths are not known with certainty but have been estimated at about 100 and 500, respectively (Hutton, 1987). Absent such lethal accidents, human exposure to MeHg comes mainly from ingestion of piscivorous fish in which MeHg has accumulated, with potential fetal damage ascribed to high fish diets during their mothers’ pregnancies (USEPA, 2001). Lesser human exposure occurs through ingestion of drinking water (USEPA, 2001), where concentrations of total Hg (THg; inorganic plus organic forms) typically are in the low nanograms-per-liter range[1] - , particularly from many groundwater sources, and concentrations at the microgram-per-liter level are rare.
\n