In this study, the revised Remote Sensing-Penman Monteith model (RS-PM) was used to scale up evapotranspiration (ET) over the entire Yukon River Basin (YRB) from three eddy covariance (EC) towers covering major vegetation types. We determined model parameters and uncertainty using a Bayesian-based method in the three EC sites. The 95 % confidence interval for the aggregate ecosystem ET ranged from 233 to 396 mm yr−1 with an average of 319 mm yr−1. The mean difference between precipitation and evapotranspiration (W) was 171 mm yr−1 with a 95 % confidence interval of 94–257 mm yr−1. The YRB region showed a slight increasing trend in annual precipitation for the 1982–2009 time period, while ET showed a significant increasing trend of 6.6 mm decade−1. As a whole, annual W showed a drying trend over YRB region.
","language":"English","publisher":"Springer","doi":"10.1007/s11269-012-0007-3","usgsCitation":"Yuan, W., Liu, S., Liang, S., Tan, Z., Liu, H., and Young, C., 2012, Estimations of evapotranspiration and water balance with uncertainty over the Yukon River Basin: Water Resources Management, v. 26, no. 8, p. 2147-2157, https://doi.org/10.1007/s11269-012-0007-3.","productDescription":"11 p.","startPage":"2147","endPage":"2157","ipdsId":"IP-022996","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":342158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska","otherGeospatial":"Yukon River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.76171875,\n 60.56537850464181\n ],\n [\n -134.5166015625,\n 60.56537850464181\n ],\n [\n -134.5166015625,\n 68.67254350285471\n ],\n [\n -165.76171875,\n 68.67254350285471\n ],\n [\n -165.76171875,\n 60.56537850464181\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-03-14","publicationStatus":"PW","scienceBaseUri":"5937bf30e4b0f6c2d0d9c7a6","contributors":{"authors":[{"text":"Yuan, Wenping","contributorId":83435,"corporation":false,"usgs":true,"family":"Yuan","given":"Wenping","email":"","affiliations":[],"preferred":false,"id":697304,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":697305,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liang, Shunlin","contributorId":192428,"corporation":false,"usgs":false,"family":"Liang","given":"Shunlin","email":"","affiliations":[],"preferred":false,"id":697306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tan, Zhengxi 0000-0002-4136-0921 ztan@usgs.gov","orcid":"https://orcid.org/0000-0002-4136-0921","contributorId":2945,"corporation":false,"usgs":true,"family":"Tan","given":"Zhengxi","email":"ztan@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":697307,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liu, Heping","contributorId":117909,"corporation":false,"usgs":true,"family":"Liu","given":"Heping","affiliations":[],"preferred":false,"id":697308,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Young, Claudia 0000-0002-0859-7206 claudia.young.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-0859-7206","contributorId":192026,"corporation":false,"usgs":true,"family":"Young","given":"Claudia","email":"claudia.young.ctr@usgs.gov","affiliations":[],"preferred":false,"id":697309,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187335,"text":"70187335 - 2012 - Geophysical study of the San Juan Mountains batholith complex, southwestern Colorado","interactions":[],"lastModifiedDate":"2019-12-17T09:16:06","indexId":"70187335","displayToPublicDate":"2012-06-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Geophysical study of the San Juan Mountains batholith complex, southwestern Colorado","docAbstract":"One of the largest and most pronounced gravity lows over North America is over the rugged San Juan Mountains of southwestern Colorado (USA). The mountain range is coincident with the San Juan volcanic field (SJVF), the largest erosional remnant of a widespread mid-Cenozoic volcanic field that spanned much of the southern Rocky Mountains. A buried, low-density silicic batholith complex related to the volcanic field has been the accepted interpretation of the source of the gravity low since the 1970s. However, this interpretation was based on gravity data processed with standard techniques that are problematic in the SJVF region. The combination of high-relief topography, topography with low densities, and the use of a common reduction density of 2670 kg/m3produces spurious large-amplitude gravity lows that may distort the geophysical signature of deeper features such as a batholith complex. We applied an unconventional processing procedure that uses geologically appropriate densities for the uppermost crust and digital topography to mostly remove the effect of the low-density units that underlie the topography associated with the SJVF. This approach resulted in a gravity map that provides an improved representation of deeper sources, including reducing the amplitude of the anomaly attributed to a batholith complex. We also reinterpreted vintage seismic refraction data that indicate the presence of low-velocity zones under the SJVF. Assuming that the source of the gravity low on the improved gravity anomaly map is the same as the source of the low seismic velocities, integrated modeling corroborates the interpretation of a batholith complex and then defines the dimensions and overall density contrast of the complex. Models show that the thickness of the batholith complex varies laterally to a significant degree, with the greatest thickness (∼20 km) under the western SJVF, and lesser thicknesses (<10 km) under the eastern SJVF. The largest group of nested calderas on the surface of the SJVF, the central caldera cluster, is not correlated with the thickest part of the batholith complex. This result is consistent with petrologic interpretations from recent studies that the batholith complex continued to be modified after cessation of volcanism and therefore is not necessarily representative of synvolcanic magma chambers. The total volume of the batholith complex is estimated to be 82,000–130,000 km3. The formation of such a large felsic batholith complex would inevitably involve production of a considerably greater volume of residuum, which could be present in the lower crust or uppermost mantle. The interpreted vertically averaged density contrast (–60 to –110 kg/m3), density (2590–2640 kg/m3), and seismic expression of the batholith complex are consistent with results of geophysical studies of other large batholiths in the western United States.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES00723.1","usgsCitation":"Drenth, B.J., Keller, G.R., and Thompson, R.A., 2012, Geophysical study of the San Juan Mountains batholith complex, southwestern Colorado: Geosphere, v. 8, no. 3, p. 669-684, https://doi.org/10.1130/GES00723.1.","productDescription":"16 p.","startPage":"669","endPage":"684","ipdsId":"IP-026514","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":474496,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00723.1","text":"Publisher Index Page"},{"id":340695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"San Juan Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.05029296875,\n 36.99377838872517\n ],\n [\n -105.97412109375,\n 36.99377838872517\n ],\n [\n -105.97412109375,\n 38.48369476951686\n ],\n [\n -109.05029296875,\n 38.48369476951686\n ],\n [\n -109.05029296875,\n 36.99377838872517\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59084936e4b0fc4e448ffda2","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":693511,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keller, G. Randy","contributorId":40602,"corporation":false,"usgs":true,"family":"Keller","given":"G.","email":"","middleInitial":"Randy","affiliations":[],"preferred":false,"id":693513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Ren A. 0000-0002-3044-3043 rathomps@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":1265,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren","email":"rathomps@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693512,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70037976,"text":"70037976 - 2012 - Modeling radium distribution in coastal aquifers during sea level changes: The Dead Sea case","interactions":[],"lastModifiedDate":"2012-06-06T01:01:36","indexId":"70037976","displayToPublicDate":"2012-05-31T12:13:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Modeling radium distribution in coastal aquifers during sea level changes: The Dead Sea case","docAbstract":"We present a new approach to studying the behavior of radium isotopes in a coastal aquifer. In order to simulate radium isotope distributions in the dynamic flow field of the Dead Sea aquifer, a multi-species density dependent flow model (SUTRA-MS) was used. Field data show that the activity of 226Ra decreases from 140 to 60 dpm/L upon entering the aquifer from the Dead Sea, and then further decreases linearly due to mixing with Ra-poor fresh water. On the other hand, an increase is observed in the activity of the shorter-lived isotopes (up to 52 dpm/L 224Ra and 31 dpm/L 223Ra), which are relatively low in Dead Sea water (up to 2.5 dpm/L 224Ra and 0.5 dpm/L 223Ra). The activities of the short lived radium isotopes also decrease with decreasing salinity, which is due to the effect of salinity on the adsorption of radium. The relationship between 224Ra and salinity suggests that the adsorption partition coefficient (K) is linearly related to salinity. Simulations of the steady-state conditions, show that the distance where equilibrium activity is attained for each radium isotope is affected by the isotope half-life, K and the groundwater velocity, resulting in a longer distance for the long-lived radium isotopes. K affects the radium distribution in transient conditions, especially that of the long-lived radium isotopes. The transient conditions in the Dead Sea system, with a 1 m/yr lake level drop, together with the radium field data, constrains K to be relatively low (<10). Thus, the sharp decrease in 226Ra cannot be explained by adsorption, and it is better explained by removal via coprecipitation, probably with barite or celestine.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochimica et Cosmochimica Acta","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.gca.2012.03.022","usgsCitation":"Kiro, Y., Yechieli, Y., Voss, C.I., Starinsky, A., and Weinstein, Y., 2012, Modeling radium distribution in coastal aquifers during sea level changes: The Dead Sea case: Geochimica et Cosmochimica Acta, v. 88, p. 237-254, https://doi.org/10.1016/j.gca.2012.03.022.","productDescription":"18 p.","startPage":"237","endPage":"254","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true}],"links":[{"id":257213,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.gca.2012.03.022","linkFileType":{"id":5,"text":"html"}},{"id":257226,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Isreal","otherGeospatial":"Dead Sea","volume":"88","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5c20e4b0c8380cd6fa5f","contributors":{"authors":[{"text":"Kiro, Yael","contributorId":88996,"corporation":false,"usgs":true,"family":"Kiro","given":"Yael","email":"","affiliations":[],"preferred":false,"id":463191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yechieli, Yoseph","contributorId":95320,"corporation":false,"usgs":true,"family":"Yechieli","given":"Yoseph","email":"","affiliations":[],"preferred":false,"id":463192,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":463189,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Starinsky, Abraham","contributorId":98988,"corporation":false,"usgs":true,"family":"Starinsky","given":"Abraham","email":"","affiliations":[],"preferred":false,"id":463193,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weinstein, Yishai","contributorId":44404,"corporation":false,"usgs":true,"family":"Weinstein","given":"Yishai","email":"","affiliations":[],"preferred":false,"id":463190,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037930,"text":"70037930 - 2012 - Mercury and other element exposure in tree swallows nesting at low pH and neutral pH lakes in northern Wisconsin USA","interactions":[],"lastModifiedDate":"2012-06-06T01:01:36","indexId":"70037930","displayToPublicDate":"2012-05-31T10:37:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Mercury and other element exposure in tree swallows nesting at low pH and neutral pH lakes in northern Wisconsin USA","docAbstract":"The primary objective of this study was to determine whether tree swallows (Tachycineta bicolor) demonstrate similar responses to lake pH and mercury (Hg) contamination in northern Wisconsin as do common loons (Gavia immer). Similar to common loons, Hg concentrations in the blood of tree swallow nestlings were higher, Hg concentrations in eggs tended to be higher, and egg size tended to be smaller at low (<6.2) pH lakes. In contrast to common loons, tree swallow nestling production was not lower at low pH lakes. Based on modeling associations, Hg concentrations in tree swallow eggs and nestling blood can be used to predict Hg concentrations in common loons without the invasive or destructive sampling of loons. Mean concentrations of cadmium, manganese, and mercury in nestling livers were higher at low pH lakes than neutral pH lakes. Concentrations of cadmium, chromium, mercury, selenium, and zinc were not at toxic levels.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Pollution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.envpol.2011.12.017","usgsCitation":"Custer, T.W., Custer, C.M., Thogmartin, W.E., Dummer, P.M., Rossmann, R., Kenow, K.P., and Meyer, M., 2012, Mercury and other element exposure in tree swallows nesting at low pH and neutral pH lakes in northern Wisconsin USA: Environmental Pollution, v. 163, p. 68-76, https://doi.org/10.1016/j.envpol.2011.12.017.","productDescription":"9 p.","startPage":"68","endPage":"76","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":257227,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257202,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.envpol.2011.12.017","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wisconsin","volume":"163","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a53dee4b0c8380cd6cd8c","contributors":{"authors":[{"text":"Custer, Thomas W. 0000-0003-3170-6519 tcuster@usgs.gov","orcid":"https://orcid.org/0000-0003-3170-6519","contributorId":2835,"corporation":false,"usgs":true,"family":"Custer","given":"Thomas","email":"tcuster@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":463071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Custer, Christine M. 0000-0003-0500-1582 ccuster@usgs.gov","orcid":"https://orcid.org/0000-0003-0500-1582","contributorId":1143,"corporation":false,"usgs":true,"family":"Custer","given":"Christine","email":"ccuster@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":463069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":463070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dummer, Paul M. 0000-0002-2055-9480","orcid":"https://orcid.org/0000-0002-2055-9480","contributorId":90665,"corporation":false,"usgs":true,"family":"Dummer","given":"Paul","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":463075,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rossmann, Ronald","contributorId":65982,"corporation":false,"usgs":true,"family":"Rossmann","given":"Ronald","affiliations":[],"preferred":false,"id":463074,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kenow, Kevin P. 0000-0002-3062-5197 kkenow@usgs.gov","orcid":"https://orcid.org/0000-0002-3062-5197","contributorId":3339,"corporation":false,"usgs":true,"family":"Kenow","given":"Kevin","email":"kkenow@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":463072,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meyer, Michael W.","contributorId":38943,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael W.","affiliations":[],"preferred":false,"id":463073,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70007202,"text":"70007202 - 2012 - Mapping socio-environmentally vulnerable populations access and exposure to ecosystem services at the U.S.-Mexico borderlands","interactions":[],"lastModifiedDate":"2012-06-06T01:01:36","indexId":"70007202","displayToPublicDate":"2012-05-31T09:59:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":836,"text":"Applied Geography","active":true,"publicationSubtype":{"id":10}},"title":"Mapping socio-environmentally vulnerable populations access and exposure to ecosystem services at the U.S.-Mexico borderlands","docAbstract":"Socio-environmental vulnerable populations are often unrepresented in land-use planning yet have great potential for loss when exposed to changes in ecosystem services. Administrative boundaries, cultural differences, and language barriers increase the disassociation between land-use management and marginalized populations living in the U.S.–Mexico borderlands. This paper describes the development of a Modified Socio-Environmental Vulnerability Index (M-SEVI), using determinants from binational census and neighborhood data that describe levels of education, access to resources, migratory status, housing, and number of dependents, to provide a simplified snapshot of the region's populace that can be used in binational planning efforts. We apply this index at the SCW, located on the border between Arizona, USA and Sonora, Mexico. For comparison, the Soil and Water Assessment Tool is concurrently applied to assess the provision of erosion- and flood control services over a 9-year period. We describe how this coupling of data can form the base for an ecosystem services assessment across political boundaries that can be used by land-use planners. Results reveal potential disparities in environmental risks and burdens throughout the binational watershed in residential districts surrounding and between urban centers. The M-SEVI can be used as an important first step in addressing environmental justice for binational decision-making.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Geography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.apgeog.2012.01.006","usgsCitation":"Norman, L.M., Villarreal, M., Lara-Valencia, F., Yuan, Y., Nie, W., Wilson, S., Amaya, G., and Sleeter, R., 2012, Mapping socio-environmentally vulnerable populations access and exposure to ecosystem services at the U.S.-Mexico borderlands: Applied Geography, v. 34, p. 413-424, https://doi.org/10.1016/j.apgeog.2012.01.006.","productDescription":"12 p.","startPage":"413","endPage":"424","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":257198,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.apgeog.2012.01.006","linkFileType":{"id":5,"text":"html"}},{"id":257224,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States;Mexico","state":"Arizona","otherGeospatial":"Sonora","volume":"34","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5074e4b0c8380cd6b6ce","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":356052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L.","contributorId":107012,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel L.","affiliations":[],"preferred":false,"id":356058,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lara-Valencia, Francisco","contributorId":77409,"corporation":false,"usgs":true,"family":"Lara-Valencia","given":"Francisco","email":"","affiliations":[],"preferred":false,"id":356055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yuan, Yongping","contributorId":75799,"corporation":false,"usgs":true,"family":"Yuan","given":"Yongping","email":"","affiliations":[],"preferred":false,"id":356054,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nie, Wenming","contributorId":7126,"corporation":false,"usgs":true,"family":"Nie","given":"Wenming","email":"","affiliations":[],"preferred":false,"id":356053,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, Sylvia","contributorId":105160,"corporation":false,"usgs":true,"family":"Wilson","given":"Sylvia","email":"","affiliations":[],"preferred":false,"id":356057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Amaya, Gladys","contributorId":86212,"corporation":false,"usgs":true,"family":"Amaya","given":"Gladys","email":"","affiliations":[],"preferred":false,"id":356056,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sleeter, Rachel 0000-0003-3477-0436 rsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-0436","contributorId":666,"corporation":false,"usgs":true,"family":"Sleeter","given":"Rachel","email":"rsleeter@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":356051,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70005708,"text":"70005708 - 2012 - Preferential flow occurs in unsaturated conditions","interactions":[],"lastModifiedDate":"2012-06-01T01:01:40","indexId":"70005708","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Preferential flow occurs in unsaturated conditions","docAbstract":"Because it commonly generates high-speed, high-volume flow with minimal exposure to solid earth materials, preferential flow in the unsaturated zone is a dominant influence in many problems of infiltration, recharge, contaminant transport, and ecohydrology. By definition, preferential flow occurs in a portion of a medium – that is, a preferred part, whether a pathway, pore, or macroscopic subvolume. There are many possible classification schemes, but usual consideration of preferential flow includes macropore or fracture flow, funneled flow determined by macroscale heterogeneities, and fingered flow determined by hydraulic instability rather than intrinsic heterogeneity. That preferential flow is spatially concentrated associates it with other characteristics that are typical, although not defining: it tends to be unusually fast, to transport high fluxes, and to occur with hydraulic disequilibrium within the medium. It also has a tendency to occur in association with large conduits and high water content, although these are less universal than is commonly assumed. Predictive unsaturated-zone flow models in common use employ several different criteria for when and where preferential flow occurs, almost always requiring a nearly saturated medium. A threshold to be exceeded may be specified in terms of the following (i) water content; (ii) matric potential, typically a value high enough to cause capillary filling in a macropore of minimum size; (iii) infiltration capacity or other indication of incipient surface ponding; or (iv) other conditions related to total filling of certain pores. Yet preferential flow does occur without meeting these criteria. My purpose in this commentary is to point out important exceptions and implications of ignoring them. Some of these pertain mainly to macropore flow, others to fingered or funneled flow, and others to combined or undifferentiated flow modes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrological Processes","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/hyp.8380","usgsCitation":"Nimmo, J.R., 2012, Preferential flow occurs in unsaturated conditions: Hydrological Processes, v. 26, no. 5, p. 786-789, https://doi.org/10.1002/hyp.8380.","productDescription":"4 p.","startPage":"786","endPage":"789","costCenters":[{"id":148,"text":"Branch of Regional Research-Western Region","active":false,"usgs":true}],"links":[{"id":257090,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257084,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/hyp.8380","linkFileType":{"id":5,"text":"html"}}],"volume":"26","issue":"5","noUsgsAuthors":false,"publicationDate":"2011-12-12","publicationStatus":"PW","scienceBaseUri":"505a821fe4b0c8380cd7b905","contributors":{"authors":[{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":353098,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70038442,"text":"ofr20121101 - 2012 - Dissolved oxygen analysis, TMDL model comparison, and particulate matter shunting—Preliminary results from three model scenarios for the Klamath River upstream of Keno Dam, Oregon","interactions":[],"lastModifiedDate":"2012-06-01T01:01:40","indexId":"ofr20121101","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","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":"2012-1101","title":"Dissolved oxygen analysis, TMDL model comparison, and particulate matter shunting—Preliminary results from three model scenarios for the Klamath River upstream of Keno Dam, Oregon","docAbstract":"Efforts are underway to identify actions that would improve water quality in the Link River to Keno Dam reach of the Upper Klamath River in south-central Oregon. To provide further insight into water-quality improvement options, three scenarios were developed, run, and analyzed using previously calibrated CE-QUAL-W2 hydrodynamic and water-quality models. Additional scenarios are under development as part of this ongoing study. Most of these scenarios evaluate changes relative to a \"current conditions\" model, but in some cases a \"natural conditions\" model was used that simulated the reach without the effect of point and nonpoint sources and set Upper Klamath Lake at its Total Maximum Daily Load (TMDL) targets. These scenarios were simulated using a model developed by the U.S. Geological Survey (USGS) and Watercourse Engineering, Inc. for the years 2006–09, referred to here as the \"USGS model.\" Another model of the reach was developed by Tetra Tech, Inc. for years 2000 and 2002 to support the Klamath River TMDL process; that model is referred to here as the \"TMDL model.\" The three scenarios described in this report included (1) an analysis of whether this reach of the Upper Klamath River would be in compliance with dissolved oxygen standards if sources met TMDL allocations, (2) an application of more recent datasets to the TMDL model with comparison to results from the USGS model, and (3) an examination of the effect on dissolved oxygen in the Klamath River if particulate material were stopped from entering Klamath Project diversion canals. Updates and modifications to the USGS model are in progress, so in the future these scenarios will be reanalyzed with the updated model and the interim results presented here will be superseded. Significant findings from this phase of the investigation include: * The TMDL analysis used depth-averaged dissolved oxygen concentrations from model output for comparison with dissolved oxygen standards. The Oregon dissolved oxygen standards do not specify whether the numeric criteria are based on depth-averaged dissolved oxygen concentration; this was an interpretation of the standards rule by the Oregon Department of Environmental Quality (ODEQ). In this study, both depth-averaged and volume-averaged dissolved oxygen concentrations were calculated from model output. Results showed that modeled depth-averaged concentrations typically were lower than volume-averaged dissolved oxygen concentrations because depth-averaging gives a higher weight to small volume areas near the channel bottom that often have lower dissolved oxygen concentrations. Results from model scenarios in this study are reported using volume-averaged dissolved oxygen concentrations. * Under all scenarios analyzed, violations of the dissolved oxygen standard occurred most often in summer. Of the three dissolved oxygen criteria that must be met, the 30-day standard was violated most frequently. Under the base case (current conditions), fewer violations occurred in the upstream part of the reach. More violations occurred in the down-stream direction, due in part to oxygen demand from the decay of algae and organic matter from Link River and other inflows. * A condition in which Upper Klamath Lake and its Link River outflow achieved Upper Klamath Lake TMDL water-quality targets was most effective in reducing the number of violations of the dissolved oxygen standard in the Link River to Keno Dam reach of the Klamath River. The condition in which point and nonpoint sources within the Link River to Keno Dam reach met Klamath River TMDL allocations had no effect on dissolved oxygen compliance in some locations and a small effect in others under current conditions. On the other hand, meeting TMDL allocations for nonpoint and point sources was predicted to be important in meeting dissolved oxygen criteria when Upper Klamath Lake and Link River also met Upper Klamath TMDL water-quality targets. * The location of greatest dissolved oxygen improvement from nutrient and organic matter reductions was downstream from point and nonpoint source inflows because time and distance are required for decay to occur and for oxygen demand to be exerted. * After assessing compliance with dissolved oxygen standards at all 102 model segments in the Link River to Keno Dam reach, it was determined that the seven locations used by ODEQ appear to be a representative subset of the reach for dissolved oxygen analysis. * The USGS and TMDL models were qualitatively compared by running both models for the 2006–09 period but preserving the essential characteristics of each, such as organic matter partitioning, bathymetric representation, and parameter rates. The analysis revealed that some constituents were not greatly affected by the differing algorithms, rates, and assumptions in the two models. Conversely, other constituents, especially organic matter, were simulated differently by the two models. Organic matter in this river system is best represented by a mixture of relatively labile particulate material and a substantial concentration of refractory dissolved material. In addition, the use of a first-order sediment oxygen demand, as in the USGS model, helps to capture the seasonal and dynamic effect of settled organic and algal material. * Simulation of shunting (diverting) particulate material away from the intake of four Klamath Project diversion canals, so that the material stayed in the river and out of the Project area, caused higher concentrations of particulate material to occur in the river. In all cases modeled, the increase in in-river particulate material also produced decreased dissolved oxygen concentrations and an increase in the number of days when dissolved oxygen standards were violated. * If particulate material were shunted back into the river at the Klamath Project diversion canals, less organic matter and nutrients would be taken into the Klamath Project area and the Lost River basin, resulting in return flows to the Klamath River via Lost River Diversion Channel that may have reduced nutrient concentrations. Model scenarios bracketing potential end-member nutrient concentrations showed that the composition of the return flows had little to no effect on dissolved oxygen compliance under simulated conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121101","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Sullivan, A.B., Rounds, S.A., Deas, M., and Sogutlugil, I.E., 2012, Dissolved oxygen analysis, TMDL model comparison, and particulate matter shunting—Preliminary results from three model scenarios for the Klamath River upstream of Keno Dam, Oregon: U.S. Geological Survey Open-File Report 2012-1101, v, 28; Appendix, https://doi.org/10.3133/ofr20121101.","productDescription":"v, 28; Appendix","startPage":"i","endPage":"30","numberOfPages":"35","additionalOnlineFiles":"N","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":257075,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1101.bmp"},{"id":257060,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1101/","linkFileType":{"id":5,"text":"html"}},{"id":257061,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1101/pdf/ofr20121101.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon","otherGeospatial":"Klamath River;Keno Dam","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a023be4b0c8380cd4ff67","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":56317,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett","email":"annett@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":464149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deas, Michael L.","contributorId":98830,"corporation":false,"usgs":true,"family":"Deas","given":"Michael L.","affiliations":[],"preferred":false,"id":464150,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sogutlugil, I. Ertugrul","contributorId":50277,"corporation":false,"usgs":true,"family":"Sogutlugil","given":"I.","email":"","middleInitial":"Ertugrul","affiliations":[],"preferred":false,"id":464148,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70038439,"text":"sir20125070 - 2012 - Representation of regional urban development conditions using a watershed-based gradient study design","interactions":[],"lastModifiedDate":"2018-04-02T16:30:50","indexId":"sir20125070","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5070","title":"Representation of regional urban development conditions using a watershed-based gradient study design","docAbstract":"As part of the U.S. Geological Survey National Water-Quality Assessment Program, the effects of urbanization on stream ecosystems (EUSE) have been intensively investigated in nine metropolitan areas in the United States, including Boston, Massachusetts; Atlanta, Georgia; Birmingham, Alabama; Raleigh, North Carolina; Salt Lake City, Utah; Denver, Colorado; Dallas–Fort Worth, Texas; Portland, Oregon; and Milwaukee–Green Bay, Wisconsin. Each of the EUSE study area watersheds was associated with one ecological region of the United States. This report evaluates whether each metropolitan area can be generalized across the ecological regions (ecoregions) within which the EUSE study watersheds are located. Seven characteristics of the EUSE watersheds that affect stream ecosystems were examined to determine the similarities in the same seven characteristics of the watersheds in the entire ecoregion. Land cover (percentage developed, forest and shrubland, and herbaceous and cultivated classes), average annual temperature, average annual precipitation, average surface elevation, and average percentage slope were selected as human-influenced, climate, and topography characteristics. Three findings emerged from this comparison that have implications for the use of EUSE data in models used to predict stream ecosystem condition. One is that the predominant or \"background\" land-cover type (either forested or agricultural land) in each ecoregion also is the predominant land-cover type within the associated EUSE study watersheds. The second finding is that in all EUSE study areas, the watersheds account for the range of developed land conditions that exist in the corresponding ecoregion watersheds. However, six of the nine EUSE study area watersheds have significantly different distributions of developed land from the ecoregion watersheds. Finally, in seven of the nine EUSE/ecoregion comparisons, the distributions of the values of climate variables in the EUSE watersheds are different from the distributions for watersheds in the corresponding ecoregions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125070","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Terziotti, S., McMahon, G., and Bell, A.H., 2012, Representation of regional urban development conditions using a watershed-based gradient study design: U.S. Geological Survey Scientific Investigations Report 2012-5070, viii, 91 p.; Appendix, https://doi.org/10.3133/sir20125070.","productDescription":"viii, 91 p.; Appendix","startPage":"i","endPage":"109","numberOfPages":"117","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":13634,"text":"South Atlantic Water Science 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Science Center","active":true,"usgs":true}],"preferred":true,"id":464138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Amanda H. 0000-0002-7199-2145 ahbell@usgs.gov","orcid":"https://orcid.org/0000-0002-7199-2145","contributorId":1752,"corporation":false,"usgs":true,"family":"Bell","given":"Amanda","email":"ahbell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464140,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038440,"text":"sir20125091 - 2012 - Reconnaissance of land-use sources of pesticides in drinking water, McKenzie River, Oregon","interactions":[],"lastModifiedDate":"2012-06-05T01:01:48","indexId":"sir20125091","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5091","title":"Reconnaissance of land-use sources of pesticides in drinking water, McKenzie River, Oregon","docAbstract":"The Eugene Water and Electric Board (EWEB) provides water and electricity to the City of Eugene, Oregon, from the McKenzie River. In the spring of 2002, EWEB initiated a pesticide monitoring program in cooperation with the U.S. Geological Survey as part of their Drinking Water Source Protection Plan. Approximately twice yearly pesticide samples were collected from 2002 to 2010 at a suite of sampling sites representing varying land uses in the lower McKenzie River basin. A total of 117 ambient samples were collected from 28 tributary and mainstem sites, including those dominated by forestry, urban, and agricultural activities, as well as the mouths of major tributaries characterized by a mixture of upstream land use. Constituents tested included 175 compounds in filtered water (72 herbicides, 43 insecticides, 10 fungicides, and 36 of their degradation products, as well as 14 pharmaceutical compounds). No attempt was made to sample different site types equivalently; sampling was instead designed primarily to characterize representative storm events during spring and fall runoff conditions in order to assess or confirm the perceived importance of the different site types as sources for pesticides. Sampling was especially limited for agricultural sites, which were only sampled during two spring storm surveys. A total of 43 compounds were detected at least once, with many of these detected only at low concentrations (<0.1 micrograms per liter). Nine compounds were detected at the drinking- water intake, and most of these were reported as estimates less than the laboratory reporting level. Human-health benchmark concentrations were consistently several orders of magnitude higher than detected concentrations at the intake, indicating that pesticide concentrations present a negligible threat to human health. The largest number of pesticide detections occurred during spring storm surveys and primarily were associated with urban stormwater drains. Urban sites also were associated with the highest concentrations, occasionally exceeding 1 microgram per liter. Many of the compounds detected at urban sites were relatively hydrophobic (do not mix easily with water), persistent, and suspected of endocrine disruption. In contrast, forestry compounds were rarely detectable in the McKenzie River, even though forest land predominates in the basin and forestry pesticide use was detected in small tributaries draining forested lands following application. Agricultural pesticide runoff was not well characterized by the limited data available, although a large number of compounds was estimated to be used in the basin and concentrations were moderately high in the few samples collected from small tributaries draining agricultural lands. Results from this analysis indicate that urban pesticide use is potentially an important source for pesticides of concern for drinking water, not limited exclusively to storm conditions. Forestry pesticide use is not considered a likely threat to drinking water quality at the present time (2012). A more complete understanding of agricultural chemicals in runoff in the McKenzie River basin requires further investigation. In addition to evaluating the data collected in this study, a conceptual model describing pesticide contamination in the McKenzie River basin is provided, based on current scientific understanding that is consistent with the data analysis presented in this report. This model is intended to provide a foundation for future monitoring in the basin.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125091","collaboration":"Prepared in cooperation with Eugene Water and Electric Board","usgsCitation":"Kelly, V.J., Anderson, C., and Morgenstern, K., 2012, Reconnaissance of land-use sources of pesticides in drinking water, McKenzie River, Oregon: U.S. Geological Survey Scientific Investigations Report 2012-5091, vi, 38 p.; Appendices; PDF Download of Appendix B, https://doi.org/10.3133/sir20125091.","productDescription":"vi, 38 p.; Appendices; PDF Download of Appendix B","startPage":"i","endPage":"46","numberOfPages":"52","additionalOnlineFiles":"N","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":257054,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5091.jpg"},{"id":257049,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5091/","linkFileType":{"id":5,"text":"html"}},{"id":257050,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5091/pdf/sir20125091.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon","otherGeospatial":"Mckenzie River Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a98ade4b0c8380cd82b45","contributors":{"authors":[{"text":"Kelly, Valerie J. vjkelly@usgs.gov","contributorId":4161,"corporation":false,"usgs":true,"family":"Kelly","given":"Valerie","email":"vjkelly@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":1151,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey W.","email":"chauncey@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":464141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morgenstern, Karl","contributorId":57716,"corporation":false,"usgs":true,"family":"Morgenstern","given":"Karl","email":"","affiliations":[],"preferred":false,"id":464143,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038441,"text":"ofr20121090 - 2012 - Aquatic organism passage at road-stream crossings—synthesis and guidelines for effectiveness monitoring","interactions":[],"lastModifiedDate":"2012-06-01T01:01:40","indexId":"ofr20121090","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","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":"2012-1090","title":"Aquatic organism passage at road-stream crossings—synthesis and guidelines for effectiveness monitoring","docAbstract":"Restoration and maintenance of passage for aquatic organisms at road-stream crossings represents a major management priority, involving an investment of hundreds of millions of dollars (for example, U.S. Government Accounting Office, 2001). In recent years, passage at hundreds of crossings has been restored, primarily by replacing barrier road culverts with bridges or stream simulation culverts designed to pass all species and all life stages of aquatic life and simulate natural hydro-geomorphic processes (U.S. Forest Service, 2008). The current situation has motivated two general questions: 1. Are current design standards for stream simulation culverts adequately re-establishing passage for aquatic biota? and 2. How do we monitor and evaluate effectiveness of passage restoration? To address the latter question, a national workshop was held in March 2010, in Portland, Oregon. The workshop included experts on aquatic organism passage from across the nation (see table of participants, APPENDIX) who addressed four classes of methods for monitoring effectiveness of aquatic organism passage—individual movement, occupancy, demography, and genetics. This report has been written, in part, for field biologists who will be undertaking and evaluating the effectiveness of aquatic organism passage restoration projects at road-stream crossings. The report outlines basic methods for evaluating road-stream crossing passage impairment and restoration and discusses under what circumstances and conditions each method will be useful; what questions each method can potentially answer; how to design and implement an evaluation study; and points out the fundamental reality that most evaluation projects will require special funding and partnerships among researchers and resource managers. The report is organized into the following sections, which can be read independently: 1. Historical context: In this section, we provide a brief history of events leading up to the present situation involving aquatic organism passage as a useful context for the issues covered herein. 2. Importance of connectivity for aquatic organisms: In this section, we provide background information regarding the movement characteristics of aquatic organisms and their vulnerability to passage impairment, and the importance of connectivity for a broad diversity of aquatic vertebrates and invertebrates. This section should be useful for practitioners in selecting what species to monitor in relation to aquatic organism passage. 3. Methods for evaluating aquatic organism passage: In this section, we present a range of perspectives on alternatives for assessing and monitoring aquatic organism passage impairment and the effectiveness of passage restoration actions, including the following methods: Individual Movement, Occupancy Models, Abundance (Demography), and Molecular Genetic Markers. 4. Relevance, strengths, and limitations of the four methods: In this section, we discuss the utility of each of the methods as a tool for assessing and quantifying passage impairment and restoration effectiveness. 5. Guidelines for selecting a method: In this section, we review some fundamental criteria and guidelines to consider when selecting a method for monitoring in the context of answering three important questions that should be addressed when developing a plan for evaluating aquatic organism passage. 6. Study and monitoring design considerations: In this section, we discuss four key design elements that need to be considered when developing a monitoring design for assessing passage impairment and restoration. The basic objectives of the report are to: 1. Review the movement characteristics of five groups of aquatic organisms that inhabit streams and to assess their general vulnerability to passage impairment at road-stream crossings; 2. Review four methods for monitoring aquatic organism passage impairment and the effectiveness of actions to restore passage at road-stream crossing structures; 3. Assess the relevance, strengths, and limitations of each method as a monitoring tool; 4. Identify and discuss guidelines that will be useful for selecting a monitoring method; and 5. Discuss what we have identified as the four key elements that need to be considered when developing a monitoring design for assessing passage impairment and restoration at road-stream crossings.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121090","collaboration":"Prepared for USDA Forest Service, San Dimas Technology & Development Center, San Dimas, CA 91773; Interagency Agreement No. 09-IA-11138150-041","usgsCitation":"Hoffman, R.L., Dunham, J., and Hansen, B.P., 2012, Aquatic organism passage at road-stream crossings—synthesis and guidelines for effectiveness monitoring: U.S. Geological Survey Open-File Report 2012-1090, vi, 48 p.; Appendix, https://doi.org/10.3133/ofr20121090.","productDescription":"vi, 48 p.; Appendix","startPage":"i","endPage":"64","numberOfPages":"70","additionalOnlineFiles":"N","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":257076,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1090.bmp"},{"id":257057,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1090/","linkFileType":{"id":5,"text":"html"}},{"id":257058,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1090/pdf/ofr20121090.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ed12e4b0c8380cd495e6","contributors":{"authors":[{"text":"Hoffman, Robert L.","contributorId":52931,"corporation":false,"usgs":true,"family":"Hoffman","given":"Robert","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":464144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B.","contributorId":64791,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason B.","affiliations":[],"preferred":false,"id":464145,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Bruce P.","contributorId":90727,"corporation":false,"usgs":true,"family":"Hansen","given":"Bruce","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":464146,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038445,"text":"ofr20121108 - 2012 - Monitoring of stream restoration habitat on the main stem of the Methow River, Washington, during the pre-treatment phase (October 2008-May 2012) with a progress report for activities from March 2011 to November 2011","interactions":[],"lastModifiedDate":"2016-05-04T12:00:42","indexId":"ofr20121108","displayToPublicDate":"2012-05-31T00:00:00","publicationYear":"2012","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":"2012-1108","title":"Monitoring of stream restoration habitat on the main stem of the Methow River, Washington, during the pre-treatment phase (October 2008-May 2012) with a progress report for activities from March 2011 to November 2011","docAbstract":"The coupled ocean-atmosphere-wave-sediment transport modeling system (COAWST) enables simulations that integrate oceanic, atmospheric, wave and morphological processes in the coastal ocean. Within the modeling system, the three-dimensional ocean circulation module (ROMS) is coupled with the wave generation and propagation model (SWAN) to allow full integration of the effect of waves on circulation and vice versa. The existing wave-current coupling component utilizes a depth dependent radiation stress approach. In here we present a new approach that uses the vortex force formalism. The formulation adopted and the various parameterizations used in the model as well as their numerical implementation are presented in detail. The performance of the new system is examined through the presentation of four test cases. These include obliquely incident waves on a synthetic planar beach and a natural barred beach (DUCK' 94); normal incident waves on a nearshore barred morphology with rip channels; and wave-induced mean flows outside the surf zone at the Martha's Vineyard Coastal Observatory (MVCO).
\nModel results from the planar beach case show good agreement with depth-averaged analytical solutions and with theoretical flow structures. Simulation results for the DUCK' 94 experiment agree closely with measured profiles of cross-shore and longshore velocity data from and . Diagnostic simulations showed that the nonlinear processes of wave roller generation and wave-induced mixing are important for the accurate simulation of surf zone flows. It is further recommended that a more realistic approach for determining the contribution of wave rollers and breaking induced turbulent mixing can be formulated using non-dimensional parameters which are functions of local wave parameters and the beach slope. Dominant terms in the cross-shore momentum balance are found to be the quasi-static pressure gradient and breaking acceleration. In the alongshore direction, bottom stress, breaking acceleration, horizontal advection and horizontal vortex forces dominate the momentum balance. The simulation results for the bar/rip channel morphology case clearly show the ability of the modeling system to reproduce horizontal and vertical circulation patterns similar to those found in laboratory studies and to numerical simulations using the radiation stress representation. The vortex force term is found to be more important at locations where strong flow vorticity interacts with the wave-induced Stokes flow field. Outside the surf zone, the three-dimensional model simulations of wave-induced flows for non-breaking waves closely agree with flow observations from MVCO, with the vertical structure of the simulated flow varying as a function of the vertical viscosity as demonstrated by Lentz et al. (2008).
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ocean Modelling","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ocemod.2012.01.003","usgsCitation":"Kumar, N., Voulgaris, G., Warner, J., and Olabarrieta, M., 2012, Implementation of the vortex force formalism in the coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system for inner shelf and surf zone applications: Ocean Modelling, v. 47, p. 65-95, https://doi.org/10.1016/j.ocemod.2012.01.003.","productDescription":"31 p.","startPage":"65","endPage":"95","numberOfPages":"71","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474502,"rank":101,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/5231","text":"External Repository"},{"id":257004,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":256998,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.ocemod.2012.01.003","linkFileType":{"id":5,"text":"html"}}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3911e4b0c8380cd617b5","contributors":{"authors":[{"text":"Kumar, Nirnimesh","contributorId":102308,"corporation":false,"usgs":false,"family":"Kumar","given":"Nirnimesh","affiliations":[{"id":27143,"text":"University of South Carolina, Columbia, SC","active":true,"usgs":false}],"preferred":false,"id":462820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voulgaris, George","contributorId":26377,"corporation":false,"usgs":false,"family":"Voulgaris","given":"George","email":"","affiliations":[{"id":27143,"text":"University of South Carolina, Columbia, SC","active":true,"usgs":false}],"preferred":false,"id":462818,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":462817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":81631,"corporation":false,"usgs":true,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":462819,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70038144,"text":"70038144 - 2012 - Environmental conditions associated with bat white-nose syndrome in the north-eastern United States","interactions":[],"lastModifiedDate":"2012-10-30T16:17:44","indexId":"70038144","displayToPublicDate":"2012-05-25T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Environmental conditions associated with bat white-nose syndrome in the north-eastern United States","docAbstract":"1. White-nose syndrome (WNS) is an emerging disease of hibernating North American bats that is caused by the cold-growing fungus Geomyces destructans. Since first observed in the winter of 2007, WNS has led to unprecedented mortality in several species of bats and may threaten more than 15 additional hibernating bat species if it continues across the continent. Although the exact means by which fungal infection causes mortality are undetermined, available evidence suggests a strong role of winter environmental conditions in disease mortality.\n2. By 2010, the fungus G. destructans was detected in new areas of North America far from the area it was first observed, as well as in eight European bat species in different countries, yet mortality was not observed in many of these new areas of North America or in any part of Europe. This could be because of the differences in the fungus, rates of disease progression and/or in life-history or physiological traits of the affected bat species between different regions. Infection of bats by G. destructans without associated mortality might also suggest that certain environmental conditions might have to co-occur with fungal infection to cause mortality. 3. We tested the environmental conditions hypothesis using Maxent to map and model landscape surface conditions associated with WNS mortality. This approach was unique in that we modelled possible requisite environmental conditions for disease mortality and not simply the presence of the causative agent. 4. The top predictors of WNS mortality were land use/land cover types, mean air temperature of wettest quarter, elevation, frequency of precipitation and annual temperature range. Model results suggest that WNS mortality is most likely to occur in landscapes that are higher in elevation and topographically heterogeneous, drier and colder during winter, and more seasonally variable than surrounding landscapes. 5. Synthesis and applications. This study mapped the most likely environmental surface conditions associated with bat mortality owing to WNS in the north-eastern United Sates; maps can be used for selection of priority monitoring sites. Our results provide a starting point from which to investigate and predict the potential spread and population impacts of this catastrophic emerging disease.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1365-2664.2012.02129.x","usgsCitation":"Flory, A.R., Kumar, S., Stohlgren, T.J., and Cryan, P., 2012, Environmental conditions associated with bat white-nose syndrome in the north-eastern United States: Journal of Applied Ecology, v. 49, no. 3, p. 680-689, https://doi.org/10.1111/j.1365-2664.2012.02129.x.","productDescription":"10 p.","startPage":"680","endPage":"689","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":474503,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-2664.2012.02129.x","text":"Publisher Index Page"},{"id":256973,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":256971,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-2664.2012.02129.x","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"49","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-04-20","publicationStatus":"PW","scienceBaseUri":"505a09a7e4b0c8380cd51fe3","contributors":{"authors":[{"text":"Flory, Abigail R.","contributorId":80151,"corporation":false,"usgs":true,"family":"Flory","given":"Abigail","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":463512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kumar, Sunil","contributorId":84992,"corporation":false,"usgs":true,"family":"Kumar","given":"Sunil","affiliations":[],"preferred":false,"id":463513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stohlgren, Thomas J. 0000-0001-9696-4450 stohlgrent@usgs.gov","orcid":"https://orcid.org/0000-0001-9696-4450","contributorId":2902,"corporation":false,"usgs":true,"family":"Stohlgren","given":"Thomas","email":"stohlgrent@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":463511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cryan, Paul M. 0000-0002-2915-8894","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":99685,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":463514,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156907,"text":"70156907 - 2012 - Warming experiments underpredict plant phenological responses to climate change","interactions":[],"lastModifiedDate":"2021-10-26T16:55:14.565652","indexId":"70156907","displayToPublicDate":"2012-05-24T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Warming experiments underpredict plant phenological responses to climate change","docAbstract":"Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.
","language":"English","publisher":"Nature","doi":"10.1038/nature11014","usgsCitation":"Wolkovich, E., Cook, B., Allen, J.M., Crimmins, T., Betancourt, J.L., Travers, S.E., Pau, S., Regetz, J., Davies, T., Kraft, N., Ault, T., Bolmgren, K., Mazer, S., McCabe, G., McGill, B.J., Parmesan, C., Salamin, N., Schwartz, M., and Cleland, E., 2012, Warming experiments underpredict plant phenological responses to climate change: Nature, p. 494-497, https://doi.org/10.1038/nature11014.","productDescription":"4 p.","startPage":"494","endPage":"497","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-031445","costCenters":[{"id":144,"text":"Branch of Regional Research","active":false,"usgs":true}],"links":[{"id":307798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2012-05-02","publicationStatus":"PW","scienceBaseUri":"560bb71de4b058f706e53f8c","contributors":{"authors":[{"text":"Wolkovich, Elizabeth M.","contributorId":69288,"corporation":false,"usgs":true,"family":"Wolkovich","given":"Elizabeth M.","affiliations":[],"preferred":false,"id":571089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, Benjamin I.","contributorId":81237,"corporation":false,"usgs":true,"family":"Cook","given":"Benjamin I.","affiliations":[],"preferred":false,"id":571090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Jenica M.","contributorId":146420,"corporation":false,"usgs":false,"family":"Allen","given":"Jenica","email":"","middleInitial":"M.","affiliations":[{"id":13006,"text":"Department of Ecology and Evolutionary Biology, University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":571091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crimmins, Theresa","contributorId":103579,"corporation":false,"usgs":false,"family":"Crimmins","given":"Theresa","affiliations":[],"preferred":false,"id":571092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":571093,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Travers, Steven E.","contributorId":146419,"corporation":false,"usgs":false,"family":"Travers","given":"Steven","email":"","middleInitial":"E.","affiliations":[{"id":16604,"text":"Department of Biological Sciences, North Dakota State University, Fargo, ND","active":true,"usgs":false}],"preferred":false,"id":571094,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pau, Stephanie","contributorId":86094,"corporation":false,"usgs":true,"family":"Pau","given":"Stephanie","affiliations":[],"preferred":false,"id":571095,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Regetz, James","contributorId":20596,"corporation":false,"usgs":true,"family":"Regetz","given":"James","email":"","affiliations":[],"preferred":false,"id":571096,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Davies, T. Jonathan","contributorId":84062,"corporation":false,"usgs":true,"family":"Davies","given":"T. Jonathan","affiliations":[],"preferred":false,"id":571097,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kraft, Nathan J. B.","contributorId":86471,"corporation":false,"usgs":true,"family":"Kraft","given":"Nathan J. B.","affiliations":[],"preferred":false,"id":571098,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ault, Toby R.","contributorId":48852,"corporation":false,"usgs":true,"family":"Ault","given":"Toby R.","affiliations":[],"preferred":false,"id":571099,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bolmgren, Kjell","contributorId":80001,"corporation":false,"usgs":true,"family":"Bolmgren","given":"Kjell","affiliations":[],"preferred":false,"id":571100,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mazer, Susan J.","contributorId":96564,"corporation":false,"usgs":true,"family":"Mazer","given":"Susan J.","affiliations":[],"preferred":false,"id":571101,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":1453,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":571102,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"McGill, Brian J.","contributorId":146422,"corporation":false,"usgs":false,"family":"McGill","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":571103,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Parmesan, Camille","contributorId":146423,"corporation":false,"usgs":false,"family":"Parmesan","given":"Camille","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":571104,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Salamin, Nicolas","contributorId":146424,"corporation":false,"usgs":false,"family":"Salamin","given":"Nicolas","email":"","affiliations":[],"preferred":false,"id":571105,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Schwartz, Mark D.","contributorId":11092,"corporation":false,"usgs":true,"family":"Schwartz","given":"Mark D.","affiliations":[],"preferred":false,"id":571106,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Cleland, Elsa E.","contributorId":92790,"corporation":false,"usgs":true,"family":"Cleland","given":"Elsa E.","affiliations":[],"preferred":false,"id":571107,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70159147,"text":"70159147 - 2012 - Bayesian WLS/GLS regression for regional skewness analysis for regions with large crest stage gage networks","interactions":[],"lastModifiedDate":"2021-10-27T16:14:13.779152","indexId":"70159147","displayToPublicDate":"2012-05-24T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Bayesian WLS/GLS regression for regional skewness analysis for regions with large crest stage gage networks","docAbstract":"This paper summarizes methodological advances in regional log-space skewness analyses that support flood-frequency analysis with the log Pearson Type III (LP3) distribution. A Bayesian Weighted Least Squares/Generalized Least Squares (B-WLS/B-GLS) methodology that relates observed skewness coefficient estimators to basin characteristics in conjunction with diagnostic statistics represents an extension of the previously developed B-GLS methodology. B-WLS/B-GLS has been shown to be effective in two California studies. B-WLS/B-GLS uses B-WLS to generate stable estimators of model parameters and B-GLS to estimate the precision of those B-WLS regression parameters, as well as the precision of the model. The study described here employs this methodology to develop a regional skewness model for the State of Iowa. To provide cost effective peak-flow data for smaller drainage basins in Iowa, the U.S. Geological Survey operates a large network of crest stage gages (CSGs) that only record flow values above an identified recording threshold (thus producing a censored data record). CSGs are different from continuous-record gages, which record almost all flow values and have been used in previous B-GLS and B-WLS/B-GLS regional skewness studies. The complexity of analyzing a large CSG network is addressed by using the B-WLS/B-GLS framework along with the Expected Moments Algorithm (EMA). Because EMA allows for the censoring of low outliers, as well as the use of estimated interval discharges for missing, censored, and historic data, it complicates the calculations of effective record length (and effective concurrent record length) used to describe the precision of sample estimators because the peak discharges are no longer solely represented by single values. Thus new record length calculations were developed. The regional skewness analysis for the State of Iowa illustrates the value of the new B-WLS/BGLS methodology with these new extensions.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World environmental and water resources congress 2012: Crossing boundaries","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"World Environmental and Water Resources Congress 2012: Crossing Boundaries","conferenceDate":"May 20-24 2012","conferenceLocation":"Albuquerque, New Mexico","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/9780784412312.227","usgsCitation":"Veilleux, A.G., Stedinger, J.R., and Eash, D.A., 2012, Bayesian WLS/GLS regression for regional skewness analysis for regions with large crest stage gage networks, in World environmental and water resources congress 2012: Crossing boundaries, Albuquerque, New Mexico, May 20-24 2012, p. 2253-2263, https://doi.org/10.1061/9780784412312.227.","productDescription":"11 p.","startPage":"2253","endPage":"2263","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-034624","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":309969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2012-07-11","publicationStatus":"PW","scienceBaseUri":"5620ce4fe4b06217fc478ac3","contributors":{"authors":[{"text":"Veilleux, Andrea G. aveilleux@usgs.gov","contributorId":4404,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":577702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stedinger, Jery R.","contributorId":76198,"corporation":false,"usgs":true,"family":"Stedinger","given":"Jery","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":577703,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eash, David A. 0000-0002-2749-8959 daeash@usgs.gov","orcid":"https://orcid.org/0000-0002-2749-8959","contributorId":1887,"corporation":false,"usgs":true,"family":"Eash","given":"David","email":"daeash@usgs.gov","middleInitial":"A.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":577704,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038389,"text":"sir20125078 - 2012 - Analysis of low flows and selected methods for estimating low-flow characteristics at partial-record and ungaged stream sites in western Washington","interactions":[],"lastModifiedDate":"2012-05-22T01:01:41","indexId":"sir20125078","displayToPublicDate":"2012-05-21T09:42:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5078","title":"Analysis of low flows and selected methods for estimating low-flow characteristics at partial-record and ungaged stream sites in western Washington","docAbstract":"A regional low-flow survey of small, perennial streams in western Washington was initiated by the Northwest Indian Fisheries Commission (NWIFC), NWIFC-member tribes, and Point-No-Point Treaty Council in cooperation with the U.S. Geological Survey in 2007 and repeated by the tribes during the low-flow seasons of 2008–09. Low-flow measurements at 63 partial-record and miscellaneous streamflow-measurement sites during surveys in 2007–09 are used with concurrent flows at continuous streamflow-gaging stations (index sites) within the U.S. Geological Survey network to estimate the low-flow metric Q7,10 at each measurement site (Q7,10 is defined as the lowest average streamflow for a consecutive 7-day period that recurs on average once every 10 years). Index-site correlation methods for estimating low-flow characteristics at partial-record sites are reviewed and an empirical Monte Carlo technique is used with the daily streamflow record at 43 index sites to determine the error and bias associated with estimating the Q7,10 at synthetic partial-record sites using three methods: Q-ratio, MOVE.1, and Base-Flow Correlation. The Q-ratio method generally has the lowest error and least amount of bias for 170 scenarios, with each scenario defined by the number of concurrent flow measurements between the partial-record and index sites (ranging from 4 to 20) and the combination of basin attributes used to select the index site. The root-mean square error for the Q-ratio method ranged from 70 to 118 percent, depending on the scenario. The scenario with the smallest root-mean square error used four concurrent flow measurements and the basin attributes: basin area, mean annual precipitation, and base-flow recession time constant, also referred to as tau (τ).
\nRegional low-flow regression models for estimating Q7,10 at ungaged stream sites are developed from the records of daily discharge at 65 continuous gaging stations (including 22 discontinued gaging stations) for the purpose of evaluating explanatory variables. By incorporating the base-flow recession time constant τ as an explanatory variable in the regression model, the root-mean square error for estimating Q7,10 at ungaged sites can be lowered to 72 percent (for known values of τ), which is 42 percent less than if only basin area and mean annual precipitation are used as explanatory variables. If partial-record sites are included in the regression data set, τ must be estimated from pairs of discharge measurements made during continuous periods of declining low flows. Eight measurement pairs are optimal for estimating τ at partial-record sites, and result in a lowering of the root-mean square error by 25 percent. A low-flow survey strategy that includes paired measurements at partial-record sites requires additional effort and planning beyond a standard strategy, but could be used to enhance regional estimates of τ and potentially reduce the error of regional regression models for estimating low-flow characteristics at ungaged sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125078","collaboration":"Prepared in cooperation with the Northwest Indian Fisheries Commission","usgsCitation":"Curran, C.A., Eng, K., and Konrad, C.P., 2012, Analysis of low flows and selected methods for estimating low-flow characteristics at partial-record and ungaged stream sites in western Washington: U.S. Geological Survey Scientific Investigations Report 2012-5078, vi, 36 p.; Appendix, https://doi.org/10.3133/sir20125078.","productDescription":"vi, 36 p.; Appendix","temporalStart":"2007-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":256902,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5078.jpg"},{"id":256899,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5078/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.83333333333333,49.25 ], [ -124.83333333333333,49 ], [ -121,49 ], [ -121,49.25 ], [ -124.83333333333333,49.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059eb1fe4b0c8380cd48c2c","contributors":{"authors":[{"text":"Curran, Christopher A. 0000-0001-8933-416X ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eng, Ken","contributorId":89480,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","affiliations":[],"preferred":false,"id":464040,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Konrad, Christopher P. 0000-0002-7354-547X cpkonrad@usgs.gov","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":1716,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","email":"cpkonrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464039,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038388,"text":"ofr20121098 - 2012 - Distribution and condition of young-of-year Lost River and shortnose suckers in the Williamson River Delta restoration project and Upper Klamath Lake, Oregon, 2008-10--Final Report","interactions":[],"lastModifiedDate":"2012-05-22T01:01:41","indexId":"ofr20121098","displayToPublicDate":"2012-05-21T09:17:00","publicationYear":"2012","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":"2012-1098","title":"Distribution and condition of young-of-year Lost River and shortnose suckers in the Williamson River Delta restoration project and Upper Klamath Lake, Oregon, 2008-10--Final Report","docAbstract":"The Nature Conservancy undertook restoration of the Williamson River Delta Preserve with a primary goal \"to restore and maintain the diversity of habitats that are essential to the endangered [Lost River sucker (Deltistes luxatus) and shortnose sucker (Chasmistes brevirostris)] while, at the same time, minimizing disturbance and adverse impacts\" (David Evans and Associates, 2005). The Western Fisheries Research Center of the U.S. Geological Survey was asked by the Bureau of Reclamation to assist The Nature Conservancy in assessing the use of the restoration by larval and juvenile suckers. We identified five obtainable objectives to gauge the habitat suitability for young-of-year suckers in the permanently flooded portions of the two most recently restored sections (Goose Bay and Tulana) of the Williamson River Delta Preserve (hereafter referred to as the Preserve) and its effects on the distribution and health of larval and juvenile suckers. Several of these objectives were met through collaborations with The Nature Conservancy, Oregon State University, Oregon Water Science Center, and Leetown Science Center.
\nOur findings were in concurrence with those of The Nature Conservancy, who found that the Preserve supported young-of-year suckers at least as well as adjacent lake habitats (Erdman and others, 2011) despite the prevalence of non-native and piscivorous species in the system. The Preserve was recolonized by all fishes in the regional species pool, both native and non-native, between the time each portion of the Preserve (Goose Bay and Tulana) was inundated in autumn and the following spring. A large number of fish capable of preying on endangered larval suckers and a few fish that could prey on juvenile suckers were captured in the Preserve, but these species were no more abundant in the Preserve than in adjacent lakes.
\nLarvae and age-0, age-1, and age-2 juvenile Lost River and shortnose suckers were captured in the Preserve, Upper Klamath Lake, and Agency Lake, indicating that these species reared in restored and unaltered lake habitats. We captured too few larval suckers to examine patterns in spatial or temporal distribution. Once endangered suckers transitioned into juveniles, as defined by morphological development, they continued to disperse from shallow to deep water throughout the Preserve and into adjacent lakes. Age-1 and age-2 suckers captured throughout the Preserve and in adjacent lake habitats, especially in spring, show continued use of restored habitat by these species.
\nQuantitative examination of habitat use by age-0 juvenile suckers that accounted for imperfect detection indicated the portion of habitat used increased throughout July and August each year until the entire study area was used by one or more age-0 juvenile suckers by the end of August. Our rigorous evaluation showed both restored Preserve and unaltered lake habitats were equally used by age-0 juvenile suckers. Although all sampled habitats were used, multi-state occupancy models indicated that more age-0 suckers occupied shallow rather than deep habitats within the range of depths we sampled (0.5–4.3 m).
\nWe were unable to compare health and condition of juvenile suckers among habitats, due to their movement among habitats. However, documentation of length-weight relationships, afflictions and deformities, and histology indicated juvenile suckers captured in all habitats maintained a similar level of health among the 3 years of our study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121098","collaboration":"Prepared in cooperation with The Nature Conservancy and the Bureau of Reclamation","usgsCitation":"Burdick, S.M., and Hewitt, D.A., 2012, Distribution and condition of young-of-year Lost River and shortnose suckers in the Williamson River Delta restoration project and Upper Klamath Lake, Oregon, 2008-10--Final Report: U.S. Geological Survey Open-File Report 2012-1098, vi, 24 p.; Figures; Tables; Appendix, https://doi.org/10.3133/ofr20121098.","productDescription":"vi, 24 p.; Figures; Tables; Appendix","temporalStart":"2008-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":256901,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":256898,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1098/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake;Williamson River Delta Restoration Project","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.11749999999999,42.21666666666667 ], [ -122.11749999999999,42.58416666666667 ], [ -121.73333333333333,42.58416666666667 ], [ -121.73333333333333,42.21666666666667 ], [ -122.11749999999999,42.21666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0283e4b0c8380cd5009c","contributors":{"authors":[{"text":"Burdick, Summer M. 0000-0002-3480-5793 sburdick@usgs.gov","orcid":"https://orcid.org/0000-0002-3480-5793","contributorId":3448,"corporation":false,"usgs":true,"family":"Burdick","given":"Summer","email":"sburdick@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":464036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":464037,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70038377,"text":"sir20125079 - 2012 - Well network installation and hydrogeologic data collection, Assateague Island National Seashore, Worcester County, Maryland, 2010","interactions":[],"lastModifiedDate":"2023-03-09T20:19:02.55174","indexId":"sir20125079","displayToPublicDate":"2012-05-17T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5079","title":"Well network installation and hydrogeologic data collection, Assateague Island National Seashore, Worcester County, Maryland, 2010","docAbstract":"The U.S. Geological Survey, as part of its Climate and Land Use Change Research and Development Program, is conducting a multi-year investigation to assess potential impacts on the natural resources of Assateague Island National Seashore, Maryland that may result from changes in the hydrologic system in response to projected sea-level rise. As part of this effort, 26 monitoring wells were installed in pairs along five east-west trending transects. Each of the five transects has between two and four pairs of wells, consisting of a shallow well and a deeper well. The shallow well typically was installed several feet below the water table—usually in freshwater about 10 feet below land surface (ft bls)—to measure water-level changes in the shallow groundwater system. The deeper well was installed below the anticipated depth to the freshwater-saltwater interface—usually in saltwater about 45 to 55 ft bls—for the purpose of borehole geophysical logging to characterize local differences in lithology and salinity and to monitor tidal influences on groundwater. Four of the 13 shallow wells and 5 of the 13 deeper wells were instrumented with water-level recorders that collected water-level data at 15-minute intervals from August 12 through September 28, 2010. Data collected from these instrumented wells were compared with tide data collected north of Assateague Island at the Ocean City Inlet tide gage, and precipitation data collected by National Park Service staff on Assateague Island. These data indicate that precipitation events coupled with changes in ambient sea level had the largest effect on groundwater levels in all monitoring wells near the Atlantic Ocean and Chincoteague and Sinepuxent Bays, whereas precipitation events alone had the greatest impact on shallow groundwater levels near the center of the island. Daily and bi-monthly tidal cycles appeared to have minimal influence on groundwater levels throughout the island and the water-level changes that were observed appeared to vary among well sites, indicating that changes in lithology and salinity also may affect the response of water levels in the shallow and deeper groundwater systems throughout the island. Borehole geophysical logs were collected at each of the 13 deeper wells along the 5 transects. Electromagnetic induction logs were collected to identify changes in lithology; determine the approximate location of the freshwater-saltwater interface; and characterize the distribution of fresh and brackish water in the shallow aquifer, and the geometry of the fresh groundwater lens beneath the island. Natural gamma logs were collected to provide information on the geologic framework of the island including the presence and thickness of finer-grained deposits found in the subsurface throughout the island during previous investigations. Results of this investigation show the need for collection of continuous water-level data in both the shallow and deeper parts of the flow system and electromagnetic induction and natural gamma geophysical logging data to better understand the response of this groundwater system to changes in precipitation and tidal forcing. Hydrologic data collected as part of this investigation will serve as the foundation for the development of numerical flow models to assess the potential effects of climate change on the coastal groundwater system of Assateague Island.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125079","collaboration":"USGS Climate and Land Use Change Research and Development Program","usgsCitation":"Banks, W.S., Masterson, J., and Johnson, C.D., 2012, Well network installation and hydrogeologic data collection, Assateague Island National Seashore, Worcester County, Maryland, 2010: U.S. Geological Survey Scientific Investigations Report 2012-5079, v, 20 p., https://doi.org/10.3133/sir20125079.","productDescription":"v, 20 p.","startPage":"i","endPage":"20","numberOfPages":"25","additionalOnlineFiles":"N","temporalStart":"2010-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":256886,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5079.gif"},{"id":256878,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5079/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Maryl","county":"Worcester County","otherGeospatial":"Assateague Island National Seashore","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bcfd9e4b08c986b32eb3d","contributors":{"authors":[{"text":"Banks, William S.L.","contributorId":35281,"corporation":false,"usgs":true,"family":"Banks","given":"William","email":"","middleInitial":"S.L.","affiliations":[],"preferred":false,"id":464015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Masterson, John P. 0000-0003-3202-4413 jpmaster@usgs.gov","orcid":"https://orcid.org/0000-0003-3202-4413","contributorId":1865,"corporation":false,"usgs":true,"family":"Masterson","given":"John P.","email":"jpmaster@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":false,"id":464013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Carole D. 0000-0001-6941-1578 cjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":1891,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole","email":"cjohnson@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":464014,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70157098,"text":"70157098 - 2012 - Fuel treatment impacts on estimated wildfire carbon loss from forests in Montana, Oregon, California, and Arizona","interactions":[],"lastModifiedDate":"2015-10-05T15:50:31","indexId":"70157098","displayToPublicDate":"2012-05-16T10:30:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Fuel treatment impacts on estimated wildfire carbon loss from forests in Montana, Oregon, California, and Arizona","docAbstract":"