{"pageNumber":"623","pageRowStart":"15550","pageSize":"25","recordCount":46677,"records":[{"id":70039098,"text":"70039098 - 2012 - Evaluating the ability of regional models to predict local avian abundance","interactions":[],"lastModifiedDate":"2012-08-02T17:16:17","indexId":"70039098","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the ability of regional models to predict local avian abundance","docAbstract":"Spatial modeling over broad scales can potentially direct conservation efforts to areas with high species-specific abundances. We examined the performance of regional models for predicting bird abundance at spatial scales typically addressed in conservation planning. Specifically, we used point count data on wood thrush (Hylocichla mustelina) and blue-winged warbler (Vermivora cyanoptera) from 2 time periods (1995-1998 and 2006-2007) to evaluate the ability of regional models derived via Bayesian hierarchical techniques to predict bird abundance. We developed models for each species within Bird Conservation Region (BCR) 23 in the upper midwestern United States at 800-ha, 8,000-ha, and approximately 80,000-ha scales. We obtained count data from the Breeding Bird Survey and land cover data from the National Land Cover Dataset (1992). We evaluated predictions from the best models, as defined by an information-theoretic criterion, using point count data collected within an ecological subregion of BCR 23 at 131 count stations in the 1990s and again in 2006-2007. Competing (Deviance Information Criteria <5) blue-winged warbler models accounted for 67% of the variability and suggested positive associations with forest edge and proportion of forest at the 8,000-ha scale, and negative associations with forest patch area (800 ha) and wetness (800 ha and 80,000 ha). The regional model performed best for blue-winged warbler predicted abundances from point counts conducted in Iowa during 1995-1996 (rs = 0.57; P = 0.14), the survey period that most closely aligned with the time period of data used for regional model construction. Wood thrush models exhibited positive correlations with point count data for all survey areas and years combined (rs = 0.58, P ≤ 0.001). In comparison, blue-winged warbler models performed worse as time increased between the point count surveys and vintage of the model building data (rs = 0.03, P = 0.92 for Iowa and rs = 0.13, P = 0.51 for all areas, 2006-2007), likely related to the ephemeral nature of their preferred early successional habitat. Species abundance and sensitivity to changing habitat conditions seems to be an important factor in determining the predictive ability of regional models. Hierarchical models can be a useful tool for concentrating efforts at the scale of management units and should be one of many tools used by land managers, but we caution that the utility of such models may decrease over time for species preferring relatively ephemeral habitats if model inputs are not updated accordingly.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Wildlife Society","publisherLocation":"Bethesda, MD","doi":"10.1002/jwmg.374","usgsCitation":"LeBrun, J.J., Thogmartin, W.E., and Miller, J.R., 2012, Evaluating the ability of regional models to predict local avian abundance: Journal of Wildlife Management, v. 76, no. 6, p. 1177-1187, https://doi.org/10.1002/jwmg.374.","productDescription":"11 p.","startPage":"1177","endPage":"1187","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":258998,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258991,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.374","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"76","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-05-21","publicationStatus":"PW","scienceBaseUri":"505a0bf5e4b0c8380cd5297a","contributors":{"authors":[{"text":"LeBrun, Jaymi J.","contributorId":7959,"corporation":false,"usgs":true,"family":"LeBrun","given":"Jaymi","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":465614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":465612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, James R.","contributorId":6706,"corporation":false,"usgs":true,"family":"Miller","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":465613,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188563,"text":"70188563 - 2012 - Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment","interactions":[],"lastModifiedDate":"2017-06-15T12:38:38","indexId":"70188563","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment","docAbstract":"

Debris flows can dramatically increase their volume, and hence their destructive potential, by entraining sediment. Yet quantitative constraints on rates and mechanics of sediment entrainment by debris flows are limited. Using an in situ sensor network in the headwaters of a natural catchment we measured flow and bed properties during six erosive debris-flow events. Despite similar flow properties and thicknesses of bed sediment entrained across all events, time-averaged entrainment rates were significantly faster for bed sediment that was saturated prior to flow arrival compared with rates for sediment that was dry. Bed sediment was entrained from the sediment-surface downward in a progressive fashion and occurred during passage of dense granular fronts as well as water-rich, inter-surge flow.En massefailure of bed sediment along the sediment-bedrock interface was never observed. Large-magnitude, high-frequency fluctuations in total normal basal stress were dissipated within the upper 5 cm of bed sediment. Within this near surface layer, concomitant fluctuations in Coulomb frictional resistance are expected, irrespective of the influence of pore fluid pressure or fluctuations in shear stress. If the near-surface sediment was wet as it was overridden by a flow, additional large-magnitude, high-frequency pore pressure fluctuations were measured in the near-surface bed sediment. These pore pressure fluctuations propagated to depth at subsonic rates and in a diffusive manner. The depth to which large excess pore pressures propagated was typically less than 10 cm, but scaled as (D/fi)0.5, in which D is the hydraulic diffusivity and fi is the frequency of a particular pore pressure fluctuation. Shallow penetration depths of granular-normal-stress fluctuations and excess pore pressures demonstrate that only near-surface bed sediment experiences the full dynamic range of effective-stress fluctuations, and as a result, can be more easily entrained than deeper sediment. These data provide robust tests for mechanical models of entrainment and demonstrate that a debris flow over wet bed sediment will be larger than the same flow over dry bed sediment.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2011JF002278","usgsCitation":"McCoy, S., Kean, J.W., Coe, J.A., Tucker, G., Staley, D.M., and Wasklewicz, T., 2012, Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment: Journal of Geophysical Research F: Earth Surface, v. 117, no. F3, 25 p., https://doi.org/10.1029/2011JF002278.","productDescription":"25 p.","ipdsId":"IP-037498","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":474410,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011jf002278","text":"Publisher Index Page"},{"id":342549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Chalk Cliffs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.45820617675781,\n 38.493369048060764\n ],\n [\n -106.0400390625,\n 38.493369048060764\n ],\n [\n -106.0400390625,\n 38.79690830348427\n ],\n [\n -106.45820617675781,\n 38.79690830348427\n ],\n [\n -106.45820617675781,\n 38.493369048060764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"117","issue":"F3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-08-10","publicationStatus":"PW","scienceBaseUri":"59439c95e4b062508e31a9d5","contributors":{"authors":[{"text":"McCoy, S.W.","contributorId":192978,"corporation":false,"usgs":false,"family":"McCoy","given":"S.W.","email":"","affiliations":[],"preferred":false,"id":698350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tucker, G.E.","contributorId":150423,"corporation":false,"usgs":false,"family":"Tucker","given":"G.E.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":698351,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698347,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wasklewicz, T.A.","contributorId":64922,"corporation":false,"usgs":true,"family":"Wasklewicz","given":"T.A.","affiliations":[],"preferred":false,"id":698352,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70039081,"text":"70039081 - 2012 - Processes affecting geochemistry and contaminant movement in the middle Claiborne aquifer of the Mississippi embayment aquifer system","interactions":[],"lastModifiedDate":"2013-01-17T21:12:53","indexId":"70039081","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1534,"text":"Environmental Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Processes affecting geochemistry and contaminant movement in the middle Claiborne aquifer of the Mississippi embayment aquifer system","docAbstract":"Groundwater chemistry and tracer-based age data were used to assess contaminant movement and geochemical processes in the middle Claiborne aquifer (MCA) of the Mississippi embayment aquifer system. Water samples were collected from 30 drinking-water wells (mostly domestic and public supply) and analyzed for nutrients, major ions, pesticides, volatile organic compounds (VOCs), and transient age tracers (chlorofluorocarbons, tritium and helium-3, and sulfur hexafluoride). Redox conditions are highly variable throughout the MCA. However, mostly oxic groundwater with low dissolved solids is more vulnerable to nitrate contamination in the outcrop areas east of the Mississippi River in Mississippi and west Tennessee than in mostly anoxic groundwater in downgradient areas in western parts of the study area. Groundwater in the outcrop area was relatively young (apparent age of less than 40 years) with significantly (p < 0.05) higher dissolved oxygen and nitrate–N concentrations and higher detections of pesticides and VOCs compared to water samples from wells in downgradient areas. Oxygen reduction and denitrification rates were low compared to other aquifers in the United States (zero order rate constants for oxygen reduction and denitrification were 4.7 and 5–10 μmol/L/year, respectively). Elevated concentrations of nitrate–N, and detections of pesticides and VOCs in some deep public supply wells (>50 m depth) indicated contaminant movement from shallow parts of the aquifer into deeper oxic zones. Given the persistence of nitrate in young oxic groundwater that was recharged several decades ago, and the lack of a confining unit, the downward movement of young contaminated water may result in higher nitrate concentrations over time in deeper parts of the aquifer containing older oxic water.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Earth Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s12665-011-1157-y","usgsCitation":"Katz, B.G., Kingsbury, J.A., Welch, H.L., and Tollett, R.W., 2012, Processes affecting geochemistry and contaminant movement in the middle Claiborne aquifer of the Mississippi embayment aquifer system: Environmental Earth Sciences, v. 65, no. 6, p. 1759-1780, https://doi.org/10.1007/s12665-011-1157-y.","productDescription":"22 p.","startPage":"1759","endPage":"1780","costCenters":[{"id":288,"text":"Florida Water Science Center-Tallahassee","active":false,"usgs":true}],"links":[{"id":259003,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258990,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12665-011-1157-y","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Claiborne Aquifer;Mississippi Embayment","volume":"65","issue":"6","noUsgsAuthors":false,"publicationDate":"2011-08-17","publicationStatus":"PW","scienceBaseUri":"505a8da7e4b0c8380cd7ed47","contributors":{"authors":[{"text":"Katz, Brian G. bkatz@usgs.gov","contributorId":1093,"corporation":false,"usgs":true,"family":"Katz","given":"Brian","email":"bkatz@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":465596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kingsbury, James A. 0000-0003-4985-275X jakingsb@usgs.gov","orcid":"https://orcid.org/0000-0003-4985-275X","contributorId":883,"corporation":false,"usgs":true,"family":"Kingsbury","given":"James","email":"jakingsb@usgs.gov","middleInitial":"A.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":465595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welch, Heather L. 0000-0001-8370-7711 hllott@usgs.gov","orcid":"https://orcid.org/0000-0001-8370-7711","contributorId":552,"corporation":false,"usgs":true,"family":"Welch","given":"Heather","email":"hllott@usgs.gov","middleInitial":"L.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tollett, Roland W. 0000-0002-4726-5845 rtollett@usgs.gov","orcid":"https://orcid.org/0000-0002-4726-5845","contributorId":1896,"corporation":false,"usgs":true,"family":"Tollett","given":"Roland","email":"rtollett@usgs.gov","middleInitial":"W.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465597,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70039089,"text":"70039089 - 2012 - Floods in Central Texas, September 7-14, 2010","interactions":[],"lastModifiedDate":"2012-07-19T01:01:49","indexId":"70039089","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3536,"text":"Texas Water Journal","active":true,"publicationSubtype":{"id":10}},"title":"Floods in Central Texas, September 7-14, 2010","docAbstract":"Severe flooding occurred near the Austin metropolitan area in central Texas September 7–14, 2010, because of heavy rainfall associated with Tropical Storm Hermine. The U.S. Geological Survey, in cooperation with the Upper Brushy Creek Water Control and Improvement District, determined rainfall amounts and annual exceedance probabilities for rainfall resulting in flooding in Bell, Williamson, and Travis counties in central Texas during September 2010. We documented peak streamflows and the annual exceedance probabilities for peak streamflows recorded at several streamflow-gaging stations in the study area. The 24-hour rainfall total exceeded 12 inches at some locations, with one report of 14.57 inches at Lake Georgetown. Rainfall probabilities were estimated using previously published depth-duration frequency maps for Texas. At 4 sites in Williamson County, the 24-hour rainfall had an annual exceedance probability of 0.002. Streamflow measurement data and flood-peak data from U.S. Geological Survey surface-water monitoring stations (streamflow and reservoir gaging stations) are presented, along with a comparison of September 2010 flood peaks to previous known maximums in the periods of record. Annual exceedance probabilities for peak streamflow were computed for 20 streamflow-gaging stations based on an analysis of streamflow-gaging station records. The annual exceedance probability was 0.03 for the September 2010 peak streamflow at the Geological Survey's streamflow-gaging stations 08104700 North Fork San Gabriel River near Georgetown, Texas, and 08154700 Bull Creek at Loop 360 near Austin, Texas. The annual exceedance probability was 0.02 for the peak streamflow for Geological Survey's streamflow-gaging station 08104500 Little River near Little River, Texas. The lack of similarity in the annual exceedance probabilities computed for precipitation and streamflow might be attributed to the small areal extent of the heaviest rainfall over these and the other gaged watersheds.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Texas Water Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Texas Water Resources Institute","publisherLocation":"Austin, TX","usgsCitation":"Winters, K.E., 2012, Floods in Central Texas, September 7-14, 2010: Texas Water Journal, v. 3, no. 1, HTML Document.","productDescription":"HTML Document","numberOfPages":"12","temporalStart":"2010-09-07","temporalEnd":"2010-09-14","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":259000,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258986,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://journals.tdl.org/twj/article/view/3292","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Texas","volume":"3","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a119ee4b0c8380cd5405b","contributors":{"authors":[{"text":"Winters, Karl E. kwinters@usgs.gov","contributorId":3554,"corporation":false,"usgs":true,"family":"Winters","given":"Karl","email":"kwinters@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":465598,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70039093,"text":"sir20125103 - 2012 - Effects of urban best management practices on streamflow and phosphorus and suspended-sediment transport on Englesby Brook in Burlington, Vermont, 2000-2010","interactions":[],"lastModifiedDate":"2012-07-19T01:01:49","indexId":"sir20125103","displayToPublicDate":"2012-07-18T00:00:00","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":"2012-5103","title":"Effects of urban best management practices on streamflow and phosphorus and suspended-sediment transport on Englesby Brook in Burlington, Vermont, 2000-2010","docAbstract":"An assessment of the effectiveness of several urban best management practice structures, including a wet extended detention facility and a shallow marsh wetland (together the \"wet extended detention ponds\"), was made using data collected from 2000 through 2010 at Englesby Brook in Burlington, Vermont. The purpose of the best management practices was to reduce high streamflows and phosphorus and suspended-sediment loads and concentrations and to increase low streamflows. Englesby Brook was monitored for streamflow, phosphorus, and suspended-sediment concentrations at a streamgage downstream of the best management practice structures for 5 years before the wet extended detention ponds were constructed in 2005 and for 4 years (phosphorus and suspended-sediment concentrations) or 5 years (streamflow) after they were constructed. The period after construction of the best management practice structures was wetter and had higher discharges than the period before construction. Despite the wetter conditions, streamflow duration curves provided evidence that the streamflow regime appeared to have shifted so that the percentages of low streamflows have increased and those of high streamflows may have slightly decreased. Two other hydrologic measures showed improvements in the years following construction of the best management practices: the percentage of annual discharge transported during the 3 days with highest discharges and the number of days with zero streamflow have both decreased. Evidence was mixed for the effectiveness of the best management practices in reducing phosphorus and suspended-sediment concentrations and loads. Annual phosphorus and suspended-sediment loads, monthly loads, low-streamflow concentrations, storm-averaged streamflow-adjusted concentrations, and total storm loads either did not change significantly or increased in the period after construction. These results likely were because of the wetter conditions in the period after construction. For example, monthly loads assessed using analysis of covariance, which compensated for the effects of streamflow on loads, suggested no difference in phosphorus or suspended-sediment loads between the two periods, whereas the comparison of monthly loads without factoring in streamflow showed an increase. This result could be viewed as evidence that the ponds may have mitigated the effect of greater discharges in the period after construction by preventing a corresponding increase in loads. In another analysis used to adjust for the difference in discharge between the two comparison periods, annual and monthly load results were grouped into dry and wet years. Large (50 percent) reductions in annual loads were observed when data from dry (or wet) years before construction were compared with data from dry (or wet) years after construction. When paired monthly loads of each constituent were grouped into dry and wet years, approximately the same number of months had increases as did decreases with the magnitudes of the decreases generally larger than the magnitudes of the increases. These differences in magnitude explain the decrease in annual loads for dry and wet years. The close association of phosphorus with suspended-sediment data suggested that most of the phosphorus was in the particulate form and was controlled by suspended-sediment dynamics.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125103","collaboration":"Prepared in cooperation with the Vermont Department of Environmental Conservation","usgsCitation":"Medalie, L., 2012, Effects of urban best management practices on streamflow and phosphorus and suspended-sediment transport on Englesby Brook in Burlington, Vermont, 2000-2010: U.S. Geological Survey Scientific Investigations Report 2012-5103, vii, 26 p., https://doi.org/10.3133/sir20125103.","productDescription":"vii, 26 p.","onlineOnly":"Y","temporalStart":"2000-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":468,"text":"New Hampshire-Vermont Water Science Center","active":false,"usgs":true}],"links":[{"id":258993,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5103.JPG"},{"id":258982,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5103/pdf/sir2012-5103_report_508.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258981,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5103/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","datum":"North American Datum 1983","country":"United States","state":"Vermont","county":"Burlington","otherGeospatial":"Englesby Brook Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.33333333333333,44 ], [ -73.33333333333333,44.833333333333336 ], [ -72.66666666666667,44.833333333333336 ], [ -72.66666666666667,44 ], [ -73.33333333333333,44 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a081fe4b0c8380cd519b2","contributors":{"authors":[{"text":"Medalie, Laura 0000-0002-2440-2149 lmedalie@usgs.gov","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":3657,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","email":"lmedalie@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465609,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70039045,"text":"70039045 - 2012 - Cyclic biogeochemical processes and nitrogen fate beneath a subtropical stormwater infiltration basin","interactions":[],"lastModifiedDate":"2012-07-19T01:01:49","indexId":"70039045","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Cyclic biogeochemical processes and nitrogen fate beneath a subtropical stormwater infiltration basin","docAbstract":"A stormwater infiltration basin in north–central Florida, USA, was monitored from 2007 through 2008 to identify subsurface biogeochemical processes, with emphasis on N cycling, under the highly variable hydrologic conditions common in humid, subtropical climates. Cyclic variations in biogeochemical processes generally coincided with wet and dry hydrologic conditions. Oxidizing conditions in the subsurface persisted for about one month or less at the beginning of wet periods with dissolved O2 and NO3- showing similar temporal patterns. Reducing conditions in the subsurface evolved during prolonged flooding of the basin. At about the same time O2 and NO3- reduction concluded, Mn, Fe and SO42- reduction began, with the onset of methanogenesis one month later. Reducing conditions persisted up to six months, continuing into subsequent dry periods until the next major oxidizing infiltration event. Evidence of denitrification in shallow groundwater at the site is supported by median NO3-–N less than 0.016 mg L-1, excess N2 up to 3 mg L-1 progressively enriched in δ15N during prolonged basin flooding, and isotopically heavy δ15N and δ18O of NO3- (up to 25‰ and 15‰, respectively). Isotopic enrichment of newly infiltrated stormwater suggests denitrification was partially completed within two days. Soil and water chemistry data suggest that a biogeochemically active zone exists in the upper 1.4 m of soil, where organic carbon was the likely electron donor supplied by organic matter in soil solids or dissolved in infiltrating stormwater. The cyclic nature of reducing conditions effectively controlled the N cycle, switching N fate beneath the basin from NO3- leaching to reduction in the shallow saturated zone. Results can inform design of functionalized soil amendments that could replace the native soil in a stormwater infiltration basin and mitigate potential NO3- leaching to groundwater by replicating the biogeochemical conditions under the observed basin.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Contaminant Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jconhyd.2012.03.005","usgsCitation":"O’Reilly, A.M., Chang, N., and Wanielista, M.P., 2012, Cyclic biogeochemical processes and nitrogen fate beneath a subtropical stormwater infiltration basin: Journal of Contaminant Hydrology, v. 133, p. 53-75, https://doi.org/10.1016/j.jconhyd.2012.03.005.","productDescription":"23 p.","startPage":"53","endPage":"75","costCenters":[{"id":287,"text":"Florida Water Science Center-Orlando","active":false,"usgs":true}],"links":[{"id":501645,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://stars.library.ucf.edu/facultybib2010/3101","text":"External Repository"},{"id":258996,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258987,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jconhyd.2012.03.005","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","volume":"133","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fd22e4b0c8380cd4e655","contributors":{"authors":[{"text":"O’Reilly, Andrew M. 0000-0003-3220-1248 aoreilly@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-1248","contributorId":2184,"corporation":false,"usgs":true,"family":"O’Reilly","given":"Andrew","email":"aoreilly@usgs.gov","middleInitial":"M.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":465515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chang, Ni-Bin","contributorId":20205,"corporation":false,"usgs":false,"family":"Chang","given":"Ni-Bin","email":"","affiliations":[{"id":12564,"text":"Department of Biology, University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":465516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wanielista, Martin P.","contributorId":62069,"corporation":false,"usgs":false,"family":"Wanielista","given":"Martin","email":"","middleInitial":"P.","affiliations":[{"id":12564,"text":"Department of Biology, University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":465517,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70039055,"text":"sim3185 - 2012 - Flood-Inundation Maps for a 1.6-Mile Reach of Salt Creek, Wood Dale, Illinois","interactions":[],"lastModifiedDate":"2012-07-18T01:01:44","indexId":"sim3185","displayToPublicDate":"2012-07-17T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3185","title":"Flood-Inundation Maps for a 1.6-Mile Reach of Salt Creek, Wood Dale, Illinois","docAbstract":"Digital flood-inundation maps for a 1.6-mile reach of Salt Creek from upstream of the Chicago, Milwaukee, St. Paul & Pacific Railroad to Elizabeth Drive, Wood Dale, Illinois, were created by the U.S. Geological Survey (USGS) in cooperation with the DuPage County Stormwater Management Division. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent of flooding corresponding to selected water levels (gage heights) at the USGS streamgage on Salt Creek at Wood Dale, Illinois (station number 05531175). Current conditions at the USGS streamgage may be obtained on the Internet at http://waterdata.usgs.gov/usa/nwis/uv?05531175. In this study, flood profiles were computed for the stream reach by means of a one-dimensional unsteady flow Full EQuations (FEQ) model. The unsteady flow model was verified by comparing the rating curve output for a September 2008 flood event to discharge measurements collected at the Salt Creek at Wood Dale gage. The hydraulic model was then used to determine 14 water-surface profiles for gage heights at 0.5-ft intervals referenced to the streamgage datum and ranging from less than bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a Geographic Information System (GIS) Digital Elevation Model (DEM) (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The areal extent of the inundation was verified with high-water marks from a flood in July 2010 with a peak gage height of 14.08 ft recorded at the Salt Creek at Wood Dale gage. The availability of these maps along with Internet information regarding current gage height from USGS streamgages provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3185","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Division","usgsCitation":"Soong, D., Murphy, E., and Sharpe, J.B., 2012, Flood-Inundation Maps for a 1.6-Mile Reach of Salt Creek, Wood Dale, Illinois: U.S. Geological Survey Scientific Investigations Map 3185, v, 8 p.; Downloads Directory; PDF Downloads of Sheets 1-14: 18x 22 inches; ZIP Downloads of All 14 Map Sheets, https://doi.org/10.3133/sim3185.","productDescription":"v, 8 p.; Downloads Directory; PDF Downloads of Sheets 1-14: 18x 22 inches; ZIP Downloads of All 14 Map Sheets","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":258953,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3185.gif"},{"id":258949,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3185/","linkFileType":{"id":5,"text":"html"}},{"id":258950,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3185/contents/SIM3185_pamphlet.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"6500","projection":"Transverse Mercator","datum":"NAD 83","country":"United States","state":"Illinois","county":"Dupage County","city":"Wood Dale","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.98444444444445,41.95 ], [ -87.98444444444445,41.967222222222226 ], [ -87.96777777777778,41.967222222222226 ], [ -87.96777777777778,41.95 ], [ -87.98444444444445,41.95 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1158e4b0c8380cd53f7a","contributors":{"authors":[{"text":"Soong, David T.","contributorId":87487,"corporation":false,"usgs":true,"family":"Soong","given":"David T.","affiliations":[],"preferred":false,"id":465532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Elizabeth A.","contributorId":69660,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth A.","affiliations":[],"preferred":false,"id":465531,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharpe, Jennifer B. 0000-0002-5192-7848 jbsharpe@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-7848","contributorId":2825,"corporation":false,"usgs":true,"family":"Sharpe","given":"Jennifer","email":"jbsharpe@usgs.gov","middleInitial":"B.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465530,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70039065,"text":"sir20125052 - 2012 - Status of groundwater quality in the Upper Santa Ana Watershed, November 2006--March 2007--California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2012-07-18T01:01:44","indexId":"sir20125052","displayToPublicDate":"2012-07-17T00:00:00","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":"2012-5052","title":"Status of groundwater quality in the Upper Santa Ana Watershed, November 2006--March 2007--California GAMA Priority Basin Project","docAbstract":"Groundwater quality in the approximately 1,000-square-mile (2,590-square-kilometer) Upper Santa Ana Watershed (USAW) study unit was investigated as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is located in southern California in Riverside and San Bernardino Counties. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey and the Lawrence Livermore National Laboratory. The GAMA USAW study was designed to provide a spatially unbiased assessment of untreated groundwater quality within the primary aquifer systems in the study unit. The primary aquifer systems (hereinafter, primary aquifers) are defined as the perforation interval of wells listed in the California Department of Public Health (CDPH) database for the USAW study unit. The quality of groundwater in shallower or deeper water-bearing zones may differ from that in the primary aquifers; shallower groundwater may be more vulnerable to surficial contamination. The assessment is based on water-quality and ancillary data collected by the U.S. Geological Survey (USGS) from 90 wells during November 2006 through March 2007, and water-quality data from the CDPH database. The status of the current quality of the groundwater resource was assessed based on data from samples analyzed for volatile organic compounds (VOCs), pesticides, and naturally occurring inorganic constituents, such as major ions and trace elements. The status assessment is intended to characterize the quality of groundwater resources within the primary aquifers of the USAW study unit, not the treated drinking water delivered to consumers by water purveyors. Relative-concentrations (sample concentration divided by the health- or aesthetic-based benchmark concentration) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or non-regulatory benchmarks for drinking-water quality. A relative-concentration greater than (>) 1.0 indicates a concentration above a benchmark, and a relative-concentration less than or equal to (≤) 1.0 indicates a concentration equal to or less than a benchmark. Organic and special-interest constituent relative-concentrations were classified as \"high\" (> 1.0), \"moderate\" (0.1 < relative-concentration ≤ 1.0), or \"low\" (≤ 0.1). Inorganic constituent relative-concentrations were classified as \"high\" (> 1.0), \"moderate\" (0.5 < relative-concentration ≤ 1.0), or \"low\" ( ≤ 0.5). Aquifer-scale proportion was used as the primary metric in the status assessment for evaluating regional-scale groundwater quality. Aquifer-scale proportions are defined as the percentage of the area of the primary aquifer system with concentrations above or below specified thresholds relative to regulatory or aesthetic benchmarks. High aquifer-scale proportion is defined as the percentage of the area of the primary aquifers with a relative-concentration greater than 1.0 for a particular constituent or class of constituents; percentage is based on an areal, rather than a volumetric basis. Moderate and low aquifer-scale proportions were defined as the percentage of the primary aquifers with moderate and low relative-concentrations, respectively. Two statistical approaches—grid-based and spatially weighted—were used to evaluate aquifer-scale proportions for individual constituents and classes of constituents. Grid-based and spatially weighted estimates were comparable in the USAW study unit (within 90-percent confidence intervals). Inorganic constituents with human-health benchmarks had relative-concentrations that were high in 32.9 percent of the primary aquifers, moderate in 29.3 percent, and low in 37.8 percent. The high aquifer-scale proportion of these inorganic constituents primarily reflected high aquifer-scale proportions of nitrate (high relative-concentration in 25.3 percent of the aquifer), although seven other inorganic constituents with human-health benchmarks also were detected at high relative-concentrations in some percentage of the aquifer: arsenic, boron, fluoride, gross alpha activity, molybdenum, uranium, and vanadium. Perchlorate, as a constituent of special interest, was evaluated separately from other inorganic constituents, and had high relative-concentrations in 11.1 percent, moderate in 53.3 percent, and low or not detected in 35.6 percent of the primary aquifers. In contrast to the inorganic constituents, relative-concentrations of organic constituents (one or more) were high in 6.7 percent, moderate in 11.1 percent, and low or not detected in 82.2 percent of the primary aquifers. Of the 237 organic and special-interest constituents analyzed for, 39 constituents were detected (21 VOCs, 13 pesticides, 3 pharmaceuticals, and 2 constituents of special interest). All of the detected VOCs had health-based benchmarks, and five of these—1,1-dichloroethene, 1,2-dibromo-3-chloropropane (DBCP), tetrachloroethene (PCE), carbon tetrachloride, and trichloroethene (TCE)—were detected in at least one sample at a concentration above a benchmark (high relative-concentration). Seven of the 13 pesticides had health-based benchmarks, and none were detected above these benchmarks (no high relative-concentrations). Pharmaceuticals do not have health-based benchmarks. Thirteen organic constituents were frequently detected (detected in at least 10 percent of samples without regard to relative-concentrations): bromodichloromethane, chloroform, cis-1,2-dichloroethene, 1,1-dichloroethene, dichlorodifluoromethane (CFC-12), methyl tert-butyl ether (MTBE), PCE, TCE, trichlorofluoromethane (CFC-11), atrazine, bromacil, diuron, and simazine.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125052","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Kent, R., and Belitz, K., 2012, Status of groundwater quality in the Upper Santa Ana Watershed, November 2006--March 2007--California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2012-5052, viii, 88 p., https://doi.org/10.3133/sir20125052.","productDescription":"viii, 88 p.","numberOfPages":"100","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2006-11-01","temporalEnd":"2007-03-31","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":258970,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5052.jpg"},{"id":258955,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5052/","linkFileType":{"id":5,"text":"html"}},{"id":258956,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5052/pdf/sir20125052.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Upper Santa Ana Watershed","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b97cee4b08c986b31bc90","contributors":{"authors":[{"text":"Kent, Robert 0000-0003-4174-9467","orcid":"https://orcid.org/0000-0003-4174-9467","contributorId":20005,"corporation":false,"usgs":true,"family":"Kent","given":"Robert","affiliations":[],"preferred":false,"id":465551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":465550,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70039040,"text":"sir20125100 - 2012 - Geohydrology of Big Bear Valley, California: phase 1--geologic framework, recharge, and preliminary assessment of the source and age of groundwater","interactions":[],"lastModifiedDate":"2012-07-17T01:01:41","indexId":"sir20125100","displayToPublicDate":"2012-07-16T00:00:00","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":"2012-5100","title":"Geohydrology of Big Bear Valley, California: phase 1--geologic framework, recharge, and preliminary assessment of the source and age of groundwater","docAbstract":"The Big Bear Valley, located in the San Bernardino Mountains of southern California, has increased in population in recent years. Most of the water supply for the area is pumped from the alluvial deposits that form the Big Bear Valley groundwater basin. This study was conducted to better understand the thickness and structure of the groundwater basin in order to estimate the quantity and distribution of natural recharge to Big Bear Valley. A gravity survey was used to estimate the thickness of the alluvial deposits that form the Big Bear Valley groundwater basin. This determined that the alluvial deposits reach a maximum thickness of 1,500 to 2,000 feet beneath the center of Big Bear Lake and the area between Big Bear and Baldwin Lakes, and decrease to less than 500 feet thick beneath the eastern end of Big Bear Lake. Interferometric Synthetic Aperture Radar (InSAR) was used to measure pumping-induced land subsidence and to locate structures, such as faults, that could affect groundwater movement. The measurements indicated small amounts of land deformation (uplift and subsidence) in the area between Big Bear Lake and Baldwin Lake, the area near the city of Big Bear Lake, and the area near Sugarloaf, California. Both the gravity and InSAR measurements indicated the possible presence of subsurface faults in subbasins between Big Bear and Baldwin Lakes, but additional data are required for confirmation. The distribution and quantity of groundwater recharge in the area were evaluated by using a regional water-balance model (Basin Characterization Model, or BCM) and a daily rainfall-runoff model (INFILv3). The BCM calculated spatially distributed potential recharge in the study area of approximately 12,700 acre-feet per year (acre-ft/yr) of potential in-place recharge and 30,800 acre-ft/yr of potential runoff. Using the assumption that only 10 percent of the runoff becomes recharge, this approach indicated there is approximately 15,800 acre-ft/yr of total recharge in Big Bear Valley. The INFILv3 model was modified for this study to include a perched zone beneath the root zone to better simulate lateral seepage and recharge in the shallow subsurface in mountainous terrain. The climate input used in the INFILv3 model was developed by using daily climate data from 84 National Climatic Data Center stations and published Parameter Regression on Independent Slopes Model (PRISM) average monthly precipitation maps to match the drier average monthly precipitation measured in the Baldwin Lake drainage basin. This model resulted in a good representation of localized rain-shadow effects and calibrated well to measured lake volumes at Big Bear and Baldwin Lakes. The simulated average annual recharge was about 5,480 acre-ft/yr in the Big Bear study area, with about 2,800 acre-ft/yr in the Big Bear Lake surface-water drainage basin and about 2,680 acre-ft/yr in the Baldwin Lake surface-water drainage basin. One spring and eight wells were sampled and analyzed for chemical and isotopic data in 2005 and 2006 to determine if isotopic techniques could be used to assess the sources and ages of groundwater in the Big Bear Valley. This approach showed that the predominant source of recharge to the Big Bear Valley is winter precipitation falling on the surrounding mountains. The tritium and uncorrected carbon-14 ages of samples collected from wells for this study indicated that the groundwater basin contains water of different ages, ranging from modern to about 17,200-years old.The results of these investigations provide an understanding of the lateral and vertical extent of the groundwater basin, the spatial distribution of groundwater recharge, the processes responsible for the recharge, and the source and age of groundwater in the groundwater basin. Although the studies do not provide an understanding of the detailed water-bearing properties necessary to determine the groundwater availability of the basin, they do provide a framework for the future development of a groundwater model that would help to improve the understanding of the potential hydrologic effects of water-management alternatives in Big Bear Valley.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125100","collaboration":"Prepared in cooperation with Big Bear City Community Services District","usgsCitation":"Flint, L.E., Brandt, J., Christensen, A.H., Flint, A.L., Hevesi, J.A., Jachens, R., Kulongoski, J., Martin, P., and Sneed, M., 2012, Geohydrology of Big Bear Valley, California: phase 1--geologic framework, recharge, and preliminary assessment of the source and age of groundwater: U.S. Geological Survey Scientific Investigations Report 2012-5100, xiv, 112 p., https://doi.org/10.3133/sir20125100.","productDescription":"xiv, 112 p.","startPage":"i","endPage":"112","numberOfPages":"130","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":258929,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5100.jpg"},{"id":258920,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5100/pdf/sir20125100.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258917,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5100/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Big Bear Valley","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1802e4b0c8380cd55665","contributors":{"authors":[{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Justin 0000-0002-9397-6824","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":75798,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","affiliations":[],"preferred":false,"id":465507,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christensen, Allen H. 0000-0002-7061-5591 ahchrist@usgs.gov","orcid":"https://orcid.org/0000-0002-7061-5591","contributorId":1510,"corporation":false,"usgs":true,"family":"Christensen","given":"Allen","email":"ahchrist@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465505,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":465503,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hevesi, Joseph A. 0000-0003-2898-1800 jhevesi@usgs.gov","orcid":"https://orcid.org/0000-0003-2898-1800","contributorId":1507,"corporation":false,"usgs":true,"family":"Hevesi","given":"Joseph","email":"jhevesi@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465504,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jachens, Robert","contributorId":54660,"corporation":false,"usgs":true,"family":"Jachens","given":"Robert","affiliations":[],"preferred":false,"id":465506,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":94750,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin T.","affiliations":[],"preferred":false,"id":465508,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Martin, Peter pmmartin@usgs.gov","contributorId":799,"corporation":false,"usgs":true,"family":"Martin","given":"Peter","email":"pmmartin@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465501,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465500,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70039043,"text":"sir20125117 - 2012 - Water-quality characteristics and trend analyses for the Tongue, Powder, Cheyenne, and Belle Fourche River drainage basins, Wyoming and Montana, for selected periods, water years 1991 through 2010","interactions":[],"lastModifiedDate":"2012-07-17T01:01:41","indexId":"sir20125117","displayToPublicDate":"2012-07-16T00:00:00","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":"2012-5117","title":"Water-quality characteristics and trend analyses for the Tongue, Powder, Cheyenne, and Belle Fourche River drainage basins, Wyoming and Montana, for selected periods, water years 1991 through 2010","docAbstract":"The Powder River structural basin in northeastern Wyoming and southeastern Montana is an area of ongoing coalbed natural gas (CBNG) development. Waters produced during CBNG development are managed with a variety of techniques, including surface impoundments and discharges into stream drainages. The interaction of CBNG-produced waters with the atmosphere and the semiarid soils of the Powder River structural basin can affect water chemistry in several ways. Specific conductance and sodium adsorption ratios (SAR) of CBNG-produced waters that are discharged to streams have been of particular concern because they have the potential to affect the use of the water for irrigation. Water-quality monitoring has been conducted since 2001 at main-stem and tributary sites in the Tongue, Powder, Cheyenne, and Belle Fourche River drainage basins in response to concerns about CBNG effects. A study was conducted to summarize characteristics of stream-water quality for water years 2001–10 (October 1, 2000, to September 30, 2010) and examine trends in specific conductance, SAR, and primary constituents that contribute to specific conductance and SAR for changes through time (water years 1991–2010) that may have occurred as a result of CBNG development. Specific conductance and SAR are the focus characteristics of this report. Dissolved calcium, magnesium, and sodium, which are primary contributors to specific conductance and SAR, as well as dissolved alkalinity, chloride, and sulfate, which are other primary contributors to specific conductance, also are described. Stream-water quality in the Tongue, Powder, Cheyenne, and Belle Fourche River drainage basins was variable during water years 2001–10, in part because of variations in streamflow. In general, annual runoff was less than average during water years 2001–06 and near or above average during water years 2007–10. Stream water of the Tongue River had the smallest specific conductance values, sodium adsorption ratios, and major ion concentrations of the main-stem streams. Sites in the Tongue River drainage basin typically had the smallest range of specific conductance and SAR values. The water chemistry of sites in the Powder River drainage basin generally was the most variable as a result of diverse characteristics of that basin. Plains tributaries in the Powder River drainage basin had the largest range of specific conductance and SAR values, in part due to the many tributaries that receive CBNG-produced waters. Trends were analyzed using the seasonal Kendall test with flow-adjusted concentrations to determine changes to water quality through time at sites in the Tongue, Powder, Cheyenne, and Belle Fourche River drainage basins. Trends were evaluated for water years 2001–10 for 17 sites, which generally were on the main-stem streams and primary tributaries. Trends were evaluated for water years 2005–10 for 26 sites to increase the spatial coverage of sites. Trends were evaluated for water years 1991–2010 for eight sites to include water-quality data collected prior to widespread CBNG development and expand the temporal context of trends. Consistent patterns were not observed in trend results for water years 2001–10 for flow-adjusted specific conductance and SAR values in the Tongue, Powder, and Belle Fourche River drainage basins. Significant (p-values less than 0.05) upward trends in flow-adjusted specific conductance values were determined for 3 sites, a downward trend was determined for 1 site, and no significant (p-value greater than 0.05) trends were determined for 13 sites. One of the sites with a significant upward trend was the Tongue River at the Wyoming-Montana State line. No trend in flow-adjusted specific conductance values was determined for the Powder River at Moorhead, Mont. Significant upward trends in flow-adjusted SAR values were determined for 2 sites and no significant trends were determined for 15 sites. No trends in flow-adjusted SAR values were determined for the Tongue River at the Wyoming-Montana State line or for the Powder River at Moorhead, Mont. One of the sites with a significant upward trend in flow-adjusted SAR values was the Powder River at Arvada, Wyo. For water years 2005–10, significant upward trends in flow-adjusted specific conductance values were determined no significant trends were determined for 13 sites. A significant upward trend was determined for flow-adjusted specific conductance values for the Tongue River at the Wyoming-Montana State line. No trend in flow-adjusted specific conductance values was determined for the Powder River at Moorhead, Mont. Significant upward trends in flow-adjusted SAR values were determined for 4 sites, downward trends were determined for 5 sites, and no significant trend was determined for 17 sites. No trends in flow-adjusted SAR values were determined for the Tongue River at the Wyoming-Montana State line or for the Powder River at Moorhead, Mont. Results of the seasonal Kendall test applied to flow-adjusted specific conductance values for water years 1991–2010 indicated no significant trend for eight sites in the Tongue, Powder, and Belle Fourche River drainage basins. No significant trend in flow-adjusted specific conductance was determined for the Tongue River at the Wyoming-Montana State line or the Powder River at Moorhead, Mont. Results of the seasonal Kendall test applied to flow-adjusted SAR values for water years 1991–2010 indicated an upward trend for one site and no significant trend for four sites in the Powder and Belle Fourche River drainage basins. The significant upward trend in flow-adjusted SAR values was determined for the Powder River at Arvada, Wyo., for water years 1991–2010. Results indicate that CBNG development in the Powder River structural basin may have contributed to some trends, such as the upward trend in flow-adjusted SAR for the Powder River at Arvada, Wyo., for water years 1991–2010. An upward trend in flow-adjusted alkalinity concentrations for water years 2001–10 also was determined for the Powder River at Arvada, Wyo. Trend results are consistent with changes that can occur from the addition of sodium and bicarbonate associated with CBNG-produced waters to the Powder River. Upward trends in constituents at other sites, including the Belle Fourche River, may be the result of declining CBNG development, indicating that CBNG-produced waters may have had a dilution effect on some streams. The factors affecting other trends could not be determined because multiple factors could have been affecting the stream-water quality or because trends were observed at sites upstream from CBNG development that may have affected water-quality trends at sites downstream.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125117","collaboration":"Prepared in cooperation with the Wyoming Department of Environmental Quality","usgsCitation":"Clark, M.L., 2012, Water-quality characteristics and trend analyses for the Tongue, Powder, Cheyenne, and Belle Fourche River drainage basins, Wyoming and Montana, for selected periods, water years 1991 through 2010: U.S. Geological Survey Scientific Investigations Report 2012-5117, vii, 70 p.; Appendices, https://doi.org/10.3133/sir20125117.","productDescription":"vii, 70 p.; Appendices","startPage":"i","endPage":"70","numberOfPages":"82","additionalOnlineFiles":"N","temporalStart":"1990-10-01","temporalEnd":"2010-09-30","costCenters":[{"id":684,"text":"Wyoming Water Science Center","active":false,"usgs":true}],"links":[{"id":258930,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5117.gif"},{"id":258922,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5117/sir2012-5117.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258921,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5117/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming;Montana","otherGeospatial":"Tongue River Drainage Basin;Powder River Drainage Basin;Cheyenne River Drainage Basin;Belle Fourche River Drainage Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bcdd8e4b08c986b32e0ff","contributors":{"authors":[{"text":"Clark, Melanie L. mlclark@usgs.gov","contributorId":1827,"corporation":false,"usgs":true,"family":"Clark","given":"Melanie","email":"mlclark@usgs.gov","middleInitial":"L.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465509,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70039023,"text":"70039023 - 2012 - Housing arrangement and location determine the likelihood of housing loss due to wildfire","interactions":[],"lastModifiedDate":"2014-09-11T14:33:46","indexId":"70039023","displayToPublicDate":"2012-07-14T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Housing arrangement and location determine the likelihood of housing loss due to wildfire","docAbstract":"Surging wildfires across the globe are contributing to escalating residential losses and have major social, economic, and ecological consequences. The highest losses in the U.S. occur in southern California, where nearly 1000 homes per year have been destroyed by wildfires since 2000. Wildfire risk reduction efforts focus primarily on fuel reduction and, to a lesser degree, on house characteristics and homeowner responsibility. However, the extent to which land use planning could alleviate wildfire risk has been largely missing from the debate despite large numbers of homes being placed in the most hazardous parts of the landscape. Our goal was to examine how housing location and arrangement affects the likelihood that a home will be lost when a wildfire occurs. We developed an extensive geographic dataset of structure locations, including more than 5500 structures that were destroyed or damaged by wildfire since 2001, and identified the main contributors to property loss in two extensive, fire-prone regions in southern California. The arrangement and location of structures strongly affected their susceptibility to wildfire, with property loss most likely at low to intermediate structure densities and in areas with a history of frequent fire. Rates of structure loss were higher when structures were surrounded by wildland vegetation, but were generally higher in herbaceous fuel types than in higher fuel-volume woody types. Empirically based maps developed using housing pattern and location performed better in distinguishing hazardous from non-hazardous areas than maps based on fuel distribution. The strong importance of housing arrangement and location indicate that land use planning may be a critical tool for reducing fire risk, but it will require reliable delineations of the most hazardous locations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0033954","usgsCitation":"Syphard, A.D., Keeley, J.E., Massada, A.B., Brennan, T.J., and Radeloff, V., 2012, Housing arrangement and location determine the likelihood of housing loss due to wildfire: PLoS ONE, v. 7, no. 3, 13 p.; e33954, https://doi.org/10.1371/journal.pone.0033954.","productDescription":"13 p.; e33954","numberOfPages":"13","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":474413,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0033954","text":"Publisher Index Page"},{"id":258898,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258896,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0033954","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.5,32.5342 ], [ -119.5,34.5 ], [ -116.0809,34.5 ], [ -116.0809,32.5342 ], [ -119.5,32.5342 ] ] ] } } ] }","volume":"7","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-03-28","publicationStatus":"PW","scienceBaseUri":"505a3240e4b0c8380cd5e64b","contributors":{"authors":[{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":465467,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":465465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Massada, Avi Bar","contributorId":93744,"corporation":false,"usgs":true,"family":"Massada","given":"Avi","email":"","middleInitial":"Bar","affiliations":[],"preferred":false,"id":465469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brennan, Teresa J. 0000-0002-0646-3298 tjbrennan@usgs.gov","orcid":"https://orcid.org/0000-0002-0646-3298","contributorId":4323,"corporation":false,"usgs":true,"family":"Brennan","given":"Teresa","email":"tjbrennan@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":465466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Radeloff, Volker C.","contributorId":76169,"corporation":false,"usgs":true,"family":"Radeloff","given":"Volker C.","affiliations":[],"preferred":false,"id":465468,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70039004,"text":"sir20125136 - 2012 - Simulation of streamflow, evapotranspiration, and groundwater recharge in the middle Nueces River watershed, south Texas, 1961-2008","interactions":[],"lastModifiedDate":"2016-08-08T08:53:15","indexId":"sir20125136","displayToPublicDate":"2012-07-13T00:00:00","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":"2012-5136","title":"Simulation of streamflow, evapotranspiration, and groundwater recharge in the middle Nueces River watershed, south Texas, 1961-2008","docAbstract":"

The U.S. Geological Survey—in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe–Blanco River Authority; San Antonio River Authority; and San Antonio Water System— configured, calibrated, and tested a watershed model for a study area consisting of about 7,726 square miles of the middle Nueces River watershed in south Texas. The purpose of the model is to contribute to the understanding of watershed processes and hydrologic conditions in the middle Nueces River watershed. The model simulates streamflow, evapotranspiration, and groundwater recharge by using a numerical representation of physical characteristics of the landscape and meteorological and streamflow data.

\n

Model simulations of streamflow, evapotranspiration, and groundwater recharge were performed for various periods of record depending upon available gaged data for input and comparison, starting as early as 1961. Because of the large size of the study area, the middle Nueces River watershed was divided into eight subwatersheds, and separate Hydrological Simulation Program—FORTRAN models were developed for each subwatershed. Simulation of the overall study area involved running simulations in downstream order. Output from the model was summarized by subwatershed, point locations, stream and reservoir reaches, and the Carrizo– Wilcox aquifer outcrop area. Four long-term U.S. Geological Survey streamflow-gaging stations were used for streamflow model calibration and testing with data from 1990 to 2008. Monthly evaporation estimates from 2001 to 2008 and waterlevel data from 1961 to 2008 at Lake Corpus Christi also were used for model calibration. Additionally, evapotranspiration data for 2006–8 from a U.S. Geological Survey meteorological station in Medina County were used for calibration.

\n

Streamflow calibrations were considered poor to very good. The 2000–8 calibration results were characterized as good to very good for total flow volumes and for the volume of the highest 10 percent of daily flows. Calibration results for streamflow volumes of the lowest 50 percent of daily flows were considered poor. The daily streamflow calibration at U.S. Geological Survey streamflow-gaging station 08210000 Nueces River near Three Rivers, Tex., had the lowest (best) root mean square error, and U.S. Geological Survey streamflow-gaging station 08194500 Nueces River near Tilden, Tex., had the highest root mean square error expressed as a percentage of the mean flow rate. The mean daily reservoir volume during 1961–2008 was 182,000 acre-feet. Simulated mean daily reservoir volume was within 9 percent of this computed volume.

\n

Selected results of the model include streamflow yields for the subwatersheds and water-balance information for the Carrizo–Wilcox aquifer outcrop area. For the entire model domain, the area-weighted mean streamflow yield from 1961 to 2008 was 1.12 inches/year. The mean annual rainfall on the outcrop area during the 1961–2008 simulation period was 21.7 inches. Of this rainfall, an annual mean of 20.1 inches (about 93 percent) was simulated as evapotranspiration, 1.2 inches (about 6 percent) was simulated as groundwater recharge, and 0.5 inches (about 2 percent) was simulated as surface runoff.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125136","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe-Blanco River Authority; San Antonio River Authority; and San Antonio Water System","usgsCitation":"Dietsch, B.J., and Wehmeyer, L.L., 2012, Simulation of streamflow, evapotranspiration, and groundwater recharge in the middle Nueces River watershed, south Texas, 1961-2008: U.S. Geological Survey Scientific Investigations Report 2012-5136, vi, 37 p., https://doi.org/10.3133/sir20125136.","productDescription":"vi, 37 p.","numberOfPages":"37","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":258887,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5136.JPG"},{"id":258871,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5136/pdf/sir2012-5136.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258870,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5136/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Universal Transverse Mercator","datum":"North American Datum","country":"United States","state":"Texas","otherGeospatial":"Nueces River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.5,27.5 ], [ -100.5,30.000833333333333 ], [ -97.5,30.000833333333333 ], [ -97.5,27.5 ], [ -100.5,27.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9096e4b08c986b3195b4","contributors":{"authors":[{"text":"Dietsch, Benjamin J. 0000-0003-1090-409X bdietsch@usgs.gov","orcid":"https://orcid.org/0000-0003-1090-409X","contributorId":1346,"corporation":false,"usgs":true,"family":"Dietsch","given":"Benjamin","email":"bdietsch@usgs.gov","middleInitial":"J.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wehmeyer, Loren L.","contributorId":90412,"corporation":false,"usgs":true,"family":"Wehmeyer","given":"Loren","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":465397,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70039008,"text":"70039008 - 2012 - Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions","interactions":[],"lastModifiedDate":"2012-07-13T01:01:54","indexId":"70039008","displayToPublicDate":"2012-07-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions","docAbstract":"1. Understanding the factors affecting species occurrence is a pre-eminent focus of applied ecological research. However, direct information about species occurrence is lacking for many species. Instead, researchers sometimes have to rely on so-called presence-only data (i.e. when no direct information about absences is available), which often results from opportunistic, unstructured sampling. MAXENT is a widely used software program designed to model and map species distribution using presence-only data. 2. We provide a critical review of MAXENT as applied to species distribution modelling and discuss how it can lead to inferential errors. A chief concern is that MAXENT produces a number of poorly defined indices that are not directly related to the actual parameter of interest – the probability of occurrence (ψ). This focus on an index was motivated by the belief that it is not possible to estimate ψ from presence-only data; however, we demonstrate that ψ is identifiable using conventional likelihood methods under the assumptions of random sampling and constant probability of species detection. 3. The model is implemented in a convenient r package which we use to apply the model to simulated data and data from the North American Breeding Bird Survey. We demonstrate that MAXENT produces extreme under-predictions when compared to estimates produced by logistic regression which uses the full (presence/absence) data set. We note that MAXENT predictions are extremely sensitive to specification of the background prevalence, which is not objectively estimated using the MAXENT method. 4. As with MAXENT, formal model-based inference requires a random sample of presence locations. Many presence-only data sets, such as those based on museum records and herbarium collections, may not satisfy this assumption. However, when sampling is random, we believe that inference should be based on formal methods that facilitate inference about interpretable ecological quantities instead of vaguely defined indices.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Methods in Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.2041-210X.2011.00182.x","usgsCitation":"Royle, J., Chandler, R.B., Yackulic, C., and Nichols, J., 2012, Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions: Methods in Ecology and Evolution, v. 3, no. 3, p. 545-554, https://doi.org/10.1111/j.2041-210X.2011.00182.x.","productDescription":"10 p.","startPage":"545","endPage":"554","numberOfPages":"10","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474417,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.2041-210x.2011.00182.x","text":"Publisher Index Page"},{"id":258435,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258431,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.2041-210X.2011.00182.x","linkFileType":{"id":5,"text":"html"}}],"volume":"3","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-01-31","publicationStatus":"PW","scienceBaseUri":"505a477fe4b0c8380cd67895","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":465405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandler, Richard B. rchandler@usgs.gov","contributorId":63524,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":465404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles","contributorId":21831,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","affiliations":[],"preferred":false,"id":465403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":465402,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70039005,"text":"70039005 - 2012 - Assessment of bias in US waterfowl harvest estimates","interactions":[],"lastModifiedDate":"2012-07-13T01:01:54","indexId":"70039005","displayToPublicDate":"2012-07-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of bias in US waterfowl harvest estimates","docAbstract":"Context. North American waterfowl managers have long suspected that waterfowl harvest estimates derived from national harvest surveys in the USA are biased high. Survey bias can be evaluated by comparing survey results with like estimates from independent sources. Aims. We used band-recovery data to assess the magnitude of apparent bias in duck and goose harvest estimates, using mallards (Anas platyrhynchos) and Canada geese (Branta canadensis) as representatives of ducks and geese, respectively. Methods. We compared the number of reported mallard and Canada goose band recoveries, adjusted for band reporting rates, with the estimated harvests of banded mallards and Canada geese from the national harvest surveys. Weused the results of those comparisons to develop correction factors that can be applied to annual duck and goose harvest estimates of the national harvest survey. Key results. National harvest survey estimates of banded mallards harvested annually averaged 1.37 times greater than those calculated from band-recovery data, whereas Canada goose harvest estimates averaged 1.50 or 1.63 times greater than comparable band-recovery estimates, depending on the harvest survey methodology used. Conclusions. Duck harvest estimates produced by the national harvest survey from 1971 to 2010 should be reduced by a factor of 0.73 (95% CI = 0.71–0.75) to correct for apparent bias. Survey-specific correction factors of 0.67 (95% CI = 0.65–0.69) and 0.61 (95% CI = 0.59–0.64) should be applied to the goose harvest estimates for 1971–2001 (duck stamp-based survey) and 1999–2010 (HIP-based survey), respectively. Implications. Although this apparent bias likely has not influenced waterfowl harvest management policy in the USA, it does have negative impacts on some applications of harvest estimates, such as indirect estimation of population size. For those types of analyses, we recommend applying the appropriate correction factor to harvest estimates.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wildlife Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"CSIRO Publishing","publisherLocation":"Collingwood, Australia","doi":"10.1071/WR11105","usgsCitation":"Padding, P.I., and Royle, J., 2012, Assessment of bias in US waterfowl harvest estimates: Wildlife Research, v. 39, no. 4, p. 336-342, https://doi.org/10.1071/WR11105.","productDescription":"7 p.","startPage":"336","endPage":"342","numberOfPages":"7","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":258432,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258428,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1071/WR11105","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"39","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ee21e4b0c8380cd49bae","contributors":{"authors":[{"text":"Padding, Paul I.","contributorId":38411,"corporation":false,"usgs":true,"family":"Padding","given":"Paul","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":465398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":465399,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045452,"text":"70045452 - 2012 - Concentrations and annual fluxes of sediment-associated chemical constituents from conterminous US coastal rivers using bed sediment data","interactions":[],"lastModifiedDate":"2013-05-09T15:44:32","indexId":"70045452","displayToPublicDate":"2012-07-12T00:00:00","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":"Concentrations and annual fluxes of sediment-associated chemical constituents from conterminous US coastal rivers using bed sediment data","docAbstract":"Coastal rivers represent a significant pathway for the delivery of natural and anthropogenic sediment-associated chemical constituents to the Atlantic, Pacific and Gulf of Mexico coasts of the conterminous USA. This study entails an accounting segment using published average annual suspended sediment fluxes with published sediment-associated chemical constituent concentrations for (1) baseline, (2) land-use distributions, (3) population density, and (4) worldwide means to estimate concentrations/annual fluxes for trace/major elements and total phosphorus, total organic and inorganic carbon, total nitrogen, and sulphur, for 131 coastal river basins. In addition, it entails a sampling and subsequent chemical analysis segment that provides a level of ‘ground truth’ for the calculated values, as well as generating baselines for sediment-associated concentrations/fluxes against which future changes can be evaluated. Currently, between 260 and 270 Mt of suspended sediment are discharged annually from the conterminous USA; about 69% is discharged from Gulf rivers (n = 36), about 24% from Pacific rivers (n = 42), and about 7% from Atlantic rivers (n = 54). Elevated sediment-associated chemical concentrations relative to baseline levels occur in the reverse order of sediment discharges:Atlantic rivers (49%)>Pacific rivers (40%)>Gulf rivers (23%). Elevated trace element concentrations (e.g. Cu, Hg, Pb, Zn) frequently occur in association with present/former industrial areas and/or urban centres, particularly along the northeast Atlantic coast. Elevated carbon and nutrient concentrations occur along both the Atlantic and Gulf coasts but are dominated by rivers in the urban northeast and by southeastern and Gulf coast (Florida) ‘blackwater’ streams. Elevated Ca, Mg, K, and Na distributions tend to reflect local petrology, whereas elevated Ti, S, Fe, and Al concentrations are ubiquitous, possibly because they have substantial natural as well as anthropogenic sources. Almost all the elevated sediment-associated chemical concentrations found in conterminous US coastal rivers are lower than worldwide averages.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrological Processes","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/hyp.8437","usgsCitation":"Horowitz, A.J., Stephens, V.C., Elrick, K.A., and Smith, J.J., 2012, Concentrations and annual fluxes of sediment-associated chemical constituents from conterminous US coastal rivers using bed sediment data: Hydrological Processes, v. 26, p. 1090-1114, https://doi.org/10.1002/hyp.8437.","startPage":"1090","endPage":"1114","numberOfPages":"25","ipdsId":"IP-033553","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"links":[{"id":272162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272161,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/hyp.8437"}],"country":"United States","volume":"26","noUsgsAuthors":false,"publicationDate":"2012-02-08","publicationStatus":"PW","scienceBaseUri":"518cc560e4b05ebc8f7cc100","contributors":{"authors":[{"text":"Horowitz, Arthur J. 0000-0002-3296-730X horowitz@usgs.gov","orcid":"https://orcid.org/0000-0002-3296-730X","contributorId":1400,"corporation":false,"usgs":true,"family":"Horowitz","given":"Arthur","email":"horowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephens, Verlin C.","contributorId":34479,"corporation":false,"usgs":true,"family":"Stephens","given":"Verlin","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":477516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elrick, Kent A.","contributorId":78415,"corporation":false,"usgs":true,"family":"Elrick","given":"Kent","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":477518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, James J.","contributorId":74086,"corporation":false,"usgs":true,"family":"Smith","given":"James","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":477517,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189053,"text":"70189053 - 2012 - Imaging with cross-hole seismoelectric tomography","interactions":[],"lastModifiedDate":"2017-06-30T09:40:56","indexId":"70189053","displayToPublicDate":"2012-07-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Imaging with cross-hole seismoelectric tomography","docAbstract":"

We propose a cross-hole imaging approach based on seismoelectric conversions (SC) associated with the transmission of seismic waves from seismic sources located in a borehole to receivers (electrodes) located in a second borehole. The seismoelectric (seismic-to-electric) problem is solved using Biot theory coupled with a generalized Ohm's law with an electrokinetic streaming current contribution. The components of the displacement of the solid phase, the fluid pressure, and the electrical potential are solved using a finite element approach with Perfect Match Layer (PML) boundary conditions for the seismic waves and boundary conditions mimicking an infinite material for the electrostatic problem. We develop an inversion algorithm using the electrical disturbances recorded in the second borehole to localize the position of the heterogeneities responsible for the SC. Because of the ill-posed nature of the inverse problem (inherent to all potential-field problems), regularization is used to constrain the solution at each time in the SC-time window comprised between the time of the seismic shot and the time of the first arrival of the seismic waves in the second borehole. All the inverted volumetric current source densities are aggregated together to produce an image of the position of the heterogeneities between the two boreholes. Two simple synthetic case studies are presented to test this concept. The first case study corresponds to a vertical discontinuity between two homogeneous sub-domains. The second case study corresponds to a poroelastic inclusion (partially saturated by oil) embedded into an homogenous poroelastic formation. In both cases, the position of the heterogeneity is recovered using only the electrical disturbances associated with the SC. That said, a joint inversion of the seismic and seismoelectric data could improve these results.

","language":"English","publisher":"Royal Astronomical Society","doi":"10.1111/j.1365-246X.2011.05325.x","usgsCitation":"Araji, A., Revil, A., Jardani, A., Minsley, B.J., and Karaoulis, M., 2012, Imaging with cross-hole seismoelectric tomography: Geophysical Journal International, v. 188, no. 3, p. 1285-1302, https://doi.org/10.1111/j.1365-246X.2011.05325.x.","productDescription":"18 p.","startPage":"1285","endPage":"1302","ipdsId":"IP-026821","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":474418,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-246x.2011.05325.x","text":"Publisher Index Page"},{"id":343211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"188","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-01-25","publicationStatus":"PW","scienceBaseUri":"59576339e4b0d1f9f051b553","contributors":{"authors":[{"text":"Araji, A.H.","contributorId":37988,"corporation":false,"usgs":true,"family":"Araji","given":"A.H.","email":"","affiliations":[],"preferred":false,"id":702658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Revil, A.","contributorId":49627,"corporation":false,"usgs":true,"family":"Revil","given":"A.","affiliations":[],"preferred":false,"id":702657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jardani, A.","contributorId":74599,"corporation":false,"usgs":true,"family":"Jardani","given":"A.","email":"","affiliations":[],"preferred":false,"id":703000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karaoulis, M.","contributorId":77762,"corporation":false,"usgs":true,"family":"Karaoulis","given":"M.","email":"","affiliations":[],"preferred":false,"id":702659,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70190225,"text":"70190225 - 2012 - An algal model for predicting attainment of tiered biological criteria of Maine's streams and rivers","interactions":[],"lastModifiedDate":"2017-08-20T09:49:53","indexId":"70190225","displayToPublicDate":"2012-07-11T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"An algal model for predicting attainment of tiered biological criteria of Maine's streams and rivers","docAbstract":"

State water-quality professionals developing new biological assessment methods often have difficulty relating assessment results to narrative criteria in water-quality standards. An alternative to selecting index thresholds arbitrarily is to include the Biological Condition Gradient (BCG) in the development of the assessment method. The BCG describes tiers of biological community condition to help identify and communicate the position of a water body along a gradient of water quality ranging from natural to degraded. Although originally developed for fish and macroinvertebrate communities of streams and rivers, the BCG is easily adapted to other habitats and taxonomic groups. We developed a discriminant analysis model with stream algal data to predict attainment of tiered aquatic-life uses in Maine's water-quality standards. We modified the BCG framework for Maine stream algae, related the BCG tiers to Maine's tiered aquatic-life uses, and identified appropriate algal metrics for describing BCG tiers. Using a modified Delphi method, 5 aquatic biologists independently evaluated algal community metrics for 230 samples from streams and rivers across the state and assigned a BCG tier (1–6) and Maine water quality class (AA/A, B, C, nonattainment of any class) to each sample. We used minimally disturbed reference sites to approximate natural conditions (Tier 1). Biologist class assignments were unanimous for 53% of samples, and 42% of samples differed by 1 class. The biologists debated and developed consensus class assignments. A linear discriminant model built to replicate a priori class assignments correctly classified 95% of 150 samples in the model training set and 91% of 80 samples in the model validation set. Locally derived metrics based on BCG taxon tolerance groupings (e.g., sensitive, intermediate, tolerant) were more effective than were metrics developed in other regions. Adding the algal discriminant model to Maine's existing macroinvertebrate discriminant model will broaden detection of biological impairment and further diagnose sources of impairment. The algal discriminant model is specific to Maine, but our approach of explicitly tying an assessment tool to tiered aquatic-life goals is widely transferrable to other regions, taxonomic groups, and waterbody types.

","language":"English","publisher":"Society for Freshwater Science","doi":"10.1899/11-061.1","usgsCitation":"Danielson, T.J., Loftin, C., Tsomides, L., DiFranco, J.L., Connors, B., Courtemanch, D.L., Drummond, F., and Davies, S., 2012, An algal model for predicting attainment of tiered biological criteria of Maine's streams and rivers: Freshwater Science, v. 31, no. 2, p. 318-340, https://doi.org/10.1899/11-061.1.","productDescription":"23 p.","startPage":"318","endPage":"340","ipdsId":"IP-029126","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":344973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"599a9fb7e4b0b589267d58bd","contributors":{"authors":[{"text":"Danielson, Thomas J.","contributorId":195761,"corporation":false,"usgs":false,"family":"Danielson","given":"Thomas","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":708075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":708027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tsomides, Leonidas","contributorId":195762,"corporation":false,"usgs":false,"family":"Tsomides","given":"Leonidas","email":"","affiliations":[],"preferred":false,"id":708076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DiFranco, Jeanne L.","contributorId":195763,"corporation":false,"usgs":false,"family":"DiFranco","given":"Jeanne","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":708077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Connors, Beth","contributorId":195764,"corporation":false,"usgs":false,"family":"Connors","given":"Beth","email":"","affiliations":[],"preferred":false,"id":708078,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Courtemanch, David L.","contributorId":70639,"corporation":false,"usgs":true,"family":"Courtemanch","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":708079,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Drummond, Francis","contributorId":195765,"corporation":false,"usgs":false,"family":"Drummond","given":"Francis","affiliations":[],"preferred":false,"id":708080,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Davies, Susan","contributorId":63249,"corporation":false,"usgs":true,"family":"Davies","given":"Susan","email":"","affiliations":[],"preferred":false,"id":708081,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70038969,"text":"ofr20121141 - 2012 - Relative abundance and distribution of fishes and crayfish at Ash Meadows National Wildlife Refuge, Nye County, Nevada, 2010-11","interactions":[],"lastModifiedDate":"2016-05-04T11:43:09","indexId":"ofr20121141","displayToPublicDate":"2012-07-09T00:00:00","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":"2012-1141","title":"Relative abundance and distribution of fishes and crayfish at Ash Meadows National Wildlife Refuge, Nye County, Nevada, 2010-11","docAbstract":"

Introduction

\n

Ash Meadows National Wildlife Refuge (AMNWR) was established by the U.S. Fish and Wildlife Service (with the assistance of The Nature Conservancy) in 1984 to protect one of the highest concentrations of endemic flora and fauna in North America (Pister, 1985; Sada, 1990). Prior to federal acquisition, Ash Meadows had been anthropogenically altered, and non-native species had been introduced to the detriment of native species; reports and published literature document the negative effects to the Ash Meadows flora and fauna (Deacon and others, 1964; U.S. Department of the Interior, 1971; Landye, 1973; Pister, 1974; Soltz and Naiman, 1978; Taylor, 1980; Williams and others, 1985; Williams and Sada, 1985; Baugh and others, 1986; Hershler and Sada, 1987; Knight and Clemmer, 1987; Sada, 1990; Deacon and Williams, 1991; Scoppettone and others, 2005; Kennedy and others, 2006). Such activities led to the extinction of the endemic Ash Meadows poolfish (Empetrichthyes merriami) (Miller, 1961; Soltz and Naiman, 1978), and subsequently the federal government listed three local endemic fish as endangered pursuant to the Endangered Species Act (U.S. Fish and Wildlife Service, 1989)—Warm springs pupfish (Cyprinodon nevadensis pectoralis), Ash Meadows Amargosa pupfish (Cyprinodon nevadensis mionectes), and Ash Meadows speckled dace (Rhinichthys osculus nevadensis).

\n

Public ownership of a large portion of Ash Meadows provided the opportunity to restore the landscape to some semblance of its historical condition. Elimination of invasive aquatic species may be more difficult than landscape restoration, and their persistence can cause additional native fish decline or extirpation (Taylor and others, 1984; Moyle and others, 1986; Miller and others, 1989; Minckley and Deacon, 1991; Olden and Poff, 2005). Chemical treatment to remove invasive fishes is often unsuccessful (Meffe, 1983; Rinne and Turner, 1991; Meronek and others, 1996). In Ash Meadows, there has been some success in chemical eradication of localized populations of largemouth bass (Micropterus salmoides) and black bullhead (Ameiurus melas) (St. George, 1998, 1999; Weissenfluh, 2008b), as well as convict cichlid (Archocentrus nigrofasciatus) and sailfin molly (Poecilia latipinna) (Weissenfluh,2008a). However, there has been less success in removing western mosquitofish (Gambusia affinis) from Ash Meadows’s larger spring systems, and sailfin molly maintains strongholds in several spring systems (Scoppettone and others, 2011b). Perhaps the more destructive invasive species are two invertebrates: red swamp crayfish (Procambarus clarkii) and red-rim melania (Melanoides tuberculata). Following the appearance of red swamp crayfish within the Warm Springs Complex, Warm Springs pupfish was believed to be extirpated from one spring system (St. George, 2000) and near extirpation in two others (Darrick Weissenfluh, Ash Meadows National Wildlife Refuge, oral commun., 2008, 2011). Crayfish also were demonstrated to greatly suppress the Bradford Springs population of Ash Meadows speckled dace population (McShane and others, 2004). Red-rim melania is known to displace native snail populations (Mitchell and others, 2007), and has been implicated as an agent of extinction of native Ash Meadows spring-snails (Donald Sada, Desert Research Institute, oral commun., 2011). Both invasive invertebrates are difficult to control or eradicate (Mitchell and others, 2007; Freeman and others, 2010).

\n

Habitat restoration that favors native species can help control non-native species (McShane and others, 2004; Scoppettone and others, 2005; Kennedy and others, 2006). Restoration of Carson Slough and its tributaries present an opportunity to promote habitat types that favor native species over non-natives. Historically, the majority of Ash Meadows spring systems were tributaries to Carson Slough. In 2007 and 2008, a survey of Ash Meadows spring systems was conducted to generate baseline information on the distribution of fishes throughout AMNWR (Scoppettone and others, 2011b). In this study, we conducted a follow-up survey with emphasis on upper Carson Slough. This permitted us to gauge the early effects of spring system restoration on fish populations and to generate further baseline data relevant to future restoration efforts. 

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121141","usgsCitation":"Scoppettone, G., Johnson, D., Hereford, M., Rissler, P., Fabes, M., Salgado, A., and Shea, S., 2012, Relative abundance and distribution of fishes and crayfish at Ash Meadows National Wildlife Refuge, Nye County, Nevada, 2010-11: U.S. Geological Survey Open-File Report 2012-1141, iv, 44 p., https://doi.org/10.3133/ofr20121141.","productDescription":"iv, 44 p.","startPage":"i","endPage":"44","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2010-01-01","temporalEnd":"2011-12-31","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":258310,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1141.jpg"},{"id":258305,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1141/","linkFileType":{"id":5,"text":"html"}},{"id":258306,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1141/pdf/ofr20121141.pdf","text":"Report","size":"8.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Nevada","county":"Nye County","otherGeospatial":"Ash Meadows National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.4111328125,\n 36.54384614538856\n ],\n [\n -116.37954711914062,\n 36.54329449143642\n ],\n [\n -116.25938415527344,\n 36.50301312197295\n ],\n [\n -116.22230529785156,\n 36.47375460532763\n ],\n [\n -116.20239257812499,\n 36.448903794892864\n ],\n [\n -116.17835998535156,\n 36.4052575563742\n ],\n [\n -116.17973327636719,\n 36.36490441440569\n ],\n [\n -116.18591308593749,\n 36.32397712011264\n ],\n [\n -116.23329162597655,\n 36.296864779193506\n ],\n [\n -116.27037048339844,\n 36.29741818650811\n ],\n [\n -116.31912231445312,\n 36.330062268112485\n ],\n [\n -116.42074584960936,\n 36.4113363510602\n ],\n [\n -116.44958496093749,\n 36.49086941889727\n ],\n [\n -116.4502716064453,\n 36.52288052805137\n ],\n [\n -116.4111328125,\n 36.54384614538856\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505aa669e4b0c8380cd84e2d","contributors":{"authors":[{"text":"Scoppettone, G.G.","contributorId":22793,"corporation":false,"usgs":true,"family":"Scoppettone","given":"G.G.","email":"","affiliations":[],"preferred":false,"id":465328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, D.M.","contributorId":58266,"corporation":false,"usgs":true,"family":"Johnson","given":"D.M.","email":"","affiliations":[],"preferred":false,"id":465330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hereford, M.E.","contributorId":88203,"corporation":false,"usgs":true,"family":"Hereford","given":"M.E.","email":"","affiliations":[],"preferred":false,"id":465333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rissler, Peter","contributorId":83647,"corporation":false,"usgs":true,"family":"Rissler","given":"Peter","affiliations":[],"preferred":false,"id":465332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fabes, Mark","contributorId":39639,"corporation":false,"usgs":true,"family":"Fabes","given":"Mark","affiliations":[],"preferred":false,"id":465329,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Salgado, Antonio","contributorId":20595,"corporation":false,"usgs":true,"family":"Salgado","given":"Antonio","email":"","affiliations":[],"preferred":false,"id":465327,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shea, Sean","contributorId":60491,"corporation":false,"usgs":true,"family":"Shea","given":"Sean","affiliations":[],"preferred":false,"id":465331,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70038965,"text":"ofr20121133 - 2012 - An environmental streamflow assessment for the Santiam River basin, Oregon","interactions":[],"lastModifiedDate":"2012-07-10T01:01:44","indexId":"ofr20121133","displayToPublicDate":"2012-07-09T00:00:00","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":"2012-1133","title":"An environmental streamflow assessment for the Santiam River basin, Oregon","docAbstract":"The Santiam River is a tributary of the Willamette River in northwestern Oregon and drains an area of 1,810 square miles. The U.S. Army Corps of Engineers (USACE) operates four dams in the basin, which are used primarily for flood control, hydropower production, recreation, and water-quality improvement. The Detroit and Big Cliff Dams were constructed in 1953 on the North Santiam River. The Green Peter and Foster Dams were completed in 1967 on the South Santiam River. The impacts of the structures have included a decrease in the frequency and magnitude of floods and an increase in low flows. For three North Santiam River reaches, the median of annual 1-day maximum streamflows decreased 42–50 percent because of regulated streamflow conditions. Likewise, for three reaches in the South Santiam River basin, the median of annual 1-day maximum streamflows decreased 39–52 percent because of regulation. In contrast to their effect on high flows, the dams increased low flows. The median of annual 7-day minimum flows in six of the seven study reaches increased under regulated streamflow conditions between 60 and 334 percent. On a seasonal basis, median monthly streamflows decreased from February to May and increased from September to January in all the reaches. However, the magnitude of these impacts usually decreased farther downstream from dams because of cumulative inflow from unregulated tributaries and groundwater entering the North, South, and main-stem Santiam Rivers below the dams. A Wilcox rank-sum test of monthly precipitation data from Salem, Oregon, and Waterloo, Oregon, found no significant difference between the pre-and post-dam periods, which suggests that the construction and operation of the dams since the 1950s and 1960s are a primary cause of alterations to the Santiam River basin streamflow regime. In addition to the streamflow analysis, this report provides a geomorphic characterization of the Santiam River basin and the associated conceptual framework for assessing possible geomorphic and ecological changes in response to river-flow modifications. Suggestions for future biomonitoring and investigations are also provided. This study was one in a series of similar tributary streamflow and geomorphic studies conducted for the Willamette Sustainable Rivers Project. The Sustainable Rivers Project is a national effort by the USACE and The Nature Conservancy to develop environmental flow requirements in regulated river systems.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121133","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Risley, J.C., Wallick, J., Mangano, J.F., and Jones, K.L., 2012, An environmental streamflow assessment for the Santiam River basin, Oregon: U.S. Geological Survey Open-File Report 2012-1133, vi, 66 p.; Appendices; ZIP Downloads of Appendices A and C; XLSX Download of Appendix D, https://doi.org/10.3133/ofr20121133.","productDescription":"vi, 66 p.; Appendices; ZIP Downloads of Appendices A and C; XLSX Download of Appendix D","startPage":"i","endPage":"66","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":258277,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1133.jpg"},{"id":258272,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1133/","linkFileType":{"id":5,"text":"html"}},{"id":258273,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1133/pdf/ofr20121133.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon","otherGeospatial":"Santiam River Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ea3ee4b0c8380cd4871d","contributors":{"authors":[{"text":"Risley, John C. 0000-0002-8206-5443 jrisley@usgs.gov","orcid":"https://orcid.org/0000-0002-8206-5443","contributorId":2698,"corporation":false,"usgs":true,"family":"Risley","given":"John","email":"jrisley@usgs.gov","middleInitial":"C.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wallick, J. Rose 0000-0002-9392-272X rosewall@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-272X","contributorId":3583,"corporation":false,"usgs":true,"family":"Wallick","given":"J. 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These standard attributes are typically embedded into the default attribute table, which is directly linked to the geospatial features. However, it is impractical to embed too much information because it can create a complex, inflexible, and hard to maintain geospatial dataset. Many scientists prefer to create a modular, or relational, data design where the information about the features is stored and maintained separately, then linked to the geospatial data. For example, information about the water chemistry of a lake can be maintained in a separate file and linked to the lake. A Geographic Information System (GIS) can then relate the water chemistry to the lake and analyze it as one piece of information. For example, the GIS can select all lakes more than 50 acres, with turbidity greater than 1.5 milligrams per liter.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123068","collaboration":"National Geospatial Program","usgsCitation":"Simley, J., and Doumbouya, A., 2012, National hydrography dataset--linear referencing: U.S. Geological Survey Fact Sheet 2012-3068, 2 p., https://doi.org/10.3133/fs20123068.","productDescription":"2 p.","numberOfPages":"2","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":258276,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3068.gif"},{"id":258270,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3068/","linkFileType":{"id":5,"text":"html"}},{"id":258271,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3068/FS12-3068.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6271e4b0c8380cd71ef6","contributors":{"authors":[{"text":"Simley, Jeffrey","contributorId":31246,"corporation":false,"usgs":true,"family":"Simley","given":"Jeffrey","affiliations":[],"preferred":false,"id":465318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doumbouya, Ariel","contributorId":44025,"corporation":false,"usgs":true,"family":"Doumbouya","given":"Ariel","affiliations":[],"preferred":false,"id":465319,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70101102,"text":"70101102 - 2012 - Initial assessment of the intensity distribution of the 2011 Mw5.8 Mineral, Virginia, earthquake","interactions":[],"lastModifiedDate":"2014-04-10T13:26:52","indexId":"70101102","displayToPublicDate":"2012-07-07T13:19:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Initial assessment of the intensity distribution of the 2011 Mw5.8 Mineral, Virginia, earthquake","docAbstract":"The intensity data collected by the U.S. Geological Survey (USGS) \"Did You Feel It?\" (DYFI) Website (USGS, DYFI; http://earthquake.usgs.gov/earthquakes/dyfi/events/se/082311a/us/index.html, last accessed Sept 2011) for the Mw5.8 Mineral, Virginia, earthquake, are unprecedented in their spatial richness and geographical extent. More than 133,000 responses were received during the first week following the earthquake. Although intensity data have traditionally been regarded as imprecise and generally suspect (e.g., Hough 2000), there is a growing appreciation for the potential utility of spatially rich, systematically determined DYFI data to address key questions in earthquake ground-motions science (Atkinson and Wald, 2007; Hauksson et al., 2008).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Seismological Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SRL","doi":"10.1785/0220110140","usgsCitation":"Hough, S.E., 2012, Initial assessment of the intensity distribution of the 2011 Mw5.8 Mineral, Virginia, earthquake: Seismological Research Letters, v. 83, no. 4, 9 p., https://doi.org/10.1785/0220110140.","productDescription":"9 p.","ipdsId":"IP-034418","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":286198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286197,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0220110140"}],"country":"United States","state":"Virginia","city":"Mineral","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.0,32.0 ], [ -88.0,46.0 ], [ -70.0,46.0 ], [ -70.0,32.0 ], [ -88.0,32.0 ] ] ] } } ] }","volume":"83","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-07-26","publicationStatus":"PW","scienceBaseUri":"5355947ce4b0120853e8c028","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":492602,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70038943,"text":"70038943 - 2012 - Ecosystem performance monitoring of rangelands by integrating modeling and remote sensing","interactions":[],"lastModifiedDate":"2013-02-19T23:45:06","indexId":"70038943","displayToPublicDate":"2012-07-06T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem performance monitoring of rangelands by integrating modeling and remote sensing","docAbstract":"Monitoring rangeland ecosystem dynamics, production, and performance is valuable for researchers and land managers. However, ecosystem monitoring studies can be difficult to interpret and apply appropriately if management decisions and disturbances are inseparable from the ecosystem's climate signal. This study separates seasonal weather influences from influences caused by disturbances and management decisions, making interannual time-series analysis more consistent and interpretable. We compared the actual ecosystem performance (AEP) of five rangeland vegetation types in the Owyhee Uplands for 9 yr to their expected ecosystem performance (EEP). Integrated growing season Normalized Difference Vegetation Index data for each of the nine growing seasons served as a proxy for annual AEP. Regression-tree models used long-term site potential, seasonal weather, and land cover data sets to generate annual EEP, an estimate of ecosystem performance incorporating annual weather variations. The difference between AEP and EEP provided a performance measure for each pixel in the study area. Ecosystem performance anomalies occurred when the ecosystem performed significantly better or worse than the model predicted. About 14% of the Owyhee Uplands showed a trend of significant underperformance or overperformance (P<0.10). Land managers can use results from weather-based rangeland ecosystem performance models to help support adaptive management strategies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Rangeland Ecology and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Society for Range Management","publisherLocation":"Wheat Ridge, CO","doi":"10.2111/REM-D-11-00058.1","usgsCitation":"Wylie, B.K., Boyte, S., and Major, D.J., 2012, Ecosystem performance monitoring of rangelands by integrating modeling and remote sensing: Rangeland Ecology and Management, v. 65, no. 3, p. 241-252, https://doi.org/10.2111/REM-D-11-00058.1.","productDescription":"12 p.","startPage":"241","endPage":"252","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474423,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/642631","text":"External Repository"},{"id":258235,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258225,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2111/REM-D-11-00058.1","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon;Idaho","otherGeospatial":"Owyhee Uplands","volume":"65","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a059fe4b0c8380cd50e99","contributors":{"authors":[{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":465278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyte, Stephen P. 0000-0002-5462-3225","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":103539,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen P.","affiliations":[],"preferred":false,"id":465280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Major, Donald J.","contributorId":83405,"corporation":false,"usgs":false,"family":"Major","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":465279,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038915,"text":"70038915 - 2012 - Interannual variability of snowmelt in the Sierra Nevada and Rocky Mountains, United States: examples from two alpine watersheds","interactions":[],"lastModifiedDate":"2012-07-06T01:01:41","indexId":"70038915","displayToPublicDate":"2012-07-05T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Interannual variability of snowmelt in the Sierra Nevada and Rocky Mountains, United States: examples from two alpine watersheds","docAbstract":"The distribution of snow and the energy flux components of snowmelt are intrinsic characteristics of the alpine water cycle controlling the location of source waters and the effect of climate on streamflow. Interannual variability of these characteristics is relevant to the effect of climate change on alpine hydrology. Our objective is to characterize the interannual variability in the spatial distribution of snow and energy fluxes of snowmelt in watersheds of a maritime setting, Tokopah Basin (TOK) in California's southern Sierra Nevada, and a continental setting, Green Lake 4 Valley (GLV4) in Colorado's Front Range, using a 12 year database (1996–2007) of hydrometeorological observations and satellite-derived snow cover. Snowpacks observed in GLV4 exhibit substantially greater spatial variability than in TOK (0.75 versus 0.28 spatial coefficient of variation). In addition, modeling results indicate that the net turbulent energy flux contribution to snowmelt in GLV4 is, on average, 3 times greater in magnitude (mean 29% versus 10%) and interannual variability (standard deviation 17% versus 6%) than in TOK. These energy flux values exhibit strong seasonality, increasing as the melt season progresses to times later in the year (R2 = 0.54–0.77). This seasonality of energy flux appears to be associated with snowmelt rates that generally increase with onset date of melt (0.02 cm d-2). This seasonality in snowmelt rate, coupled to differences in hydrogeology, may account for the observed differences in correspondence between the timing of snowmelt and timing of streamflow in these watersheds.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2011WR011006","usgsCitation":"Jepsen, S.M., Molotch, N., Williams, M.W., Rittger, K.E., and Sickman, J.O., 2012, Interannual variability of snowmelt in the Sierra Nevada and Rocky Mountains, United States: examples from two alpine watersheds: Water Resources Research, v. 48, 15 p.; W02529, https://doi.org/10.1029/2011WR011006.","productDescription":"15 p.; W02529","numberOfPages":"15","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":474424,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011wr011006","text":"Publisher Index Page"},{"id":258177,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258169,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2011WR011006","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Sierra Nevada;Rocky Mountains","volume":"48","noUsgsAuthors":false,"publicationDate":"2012-02-23","publicationStatus":"PW","scienceBaseUri":"505a3ce9e4b0c8380cd63143","contributors":{"authors":[{"text":"Jepsen, Steven M. sjepsen@usgs.gov","contributorId":3892,"corporation":false,"usgs":true,"family":"Jepsen","given":"Steven","email":"sjepsen@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":465223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Molotch, Noah P.","contributorId":79741,"corporation":false,"usgs":true,"family":"Molotch","given":"Noah P.","affiliations":[],"preferred":false,"id":465227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Mark W.","contributorId":43046,"corporation":false,"usgs":true,"family":"Williams","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":465226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rittger, Karl E.","contributorId":13850,"corporation":false,"usgs":true,"family":"Rittger","given":"Karl","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":465224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sickman, James O.","contributorId":30741,"corporation":false,"usgs":true,"family":"Sickman","given":"James","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":465225,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70038871,"text":"sir20125125 - 2012 - Streamflow gains and losses and selected water-quality observations in five subreaches of the Rio Grande/Rio Bravo del Norte from near Presidio to Langtry, Texas, Big Bend area, United States and Mexico, 2006","interactions":[],"lastModifiedDate":"2016-08-08T08:55:35","indexId":"sir20125125","displayToPublicDate":"2012-07-05T00:00:00","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":"2012-5125","title":"Streamflow gains and losses and selected water-quality observations in five subreaches of the Rio Grande/Rio Bravo del Norte from near Presidio to Langtry, Texas, Big Bend area, United States and Mexico, 2006","docAbstract":"

Few historical streamflow and water-quality data are available to characterize the segment of the Rio Grande/Rio Bravo del Norte (hereinafter Rio Grande) extending from near Presidio to near Langtry, Texas. The U.S. Geological Survey, in cooperation with the National Park Service and the Texas Commission on Environmental Quality, collected water-quality and streamflow data from the Rio Grande from near Presidio to near Langtry, Texas, to characterize the streamflow gain and loss and selected constituent concentrations in a 336.3-mile reach of the Rio Grande from near Presidio to near Langtry, Texas. Streamflow was measured at 38 sites and water-quality samples were collected at 20 sites along the Rio Grande in February, March, and June 2006. Streamflow gains and losses over the course of the stream were measured indirectly by computing the differences in measured streamflow between sites along the stream. Water-quality data were collected and analyzed for salinity, dissolved solids, major ions, nutrients, trace elements, and stable isotopes. Selected properties and constituents were compared to available Texas Commission on Environmental Quality general use protection criteria or screening levels. Summary statistics of selected water-quality data were computed for each of the five designated subreaches. Streamflow gain and loss and water-quality constituent concentration were compared for each subreach, rather than the entire segment because of the temporal variation in sample collection caused by controlled releases upstream. Subreach A was determined to be a losing reach, and subreaches B, C, D, and E were determined to be gaining reaches. Compared to concentrations measured in upstream subreaches, downstream subreaches exhibited evidence of dilution of selected constituent concentrations. Subreaches A and B had measured total dissolved solids, chloride, and sulfate exceeding the Texas Commission on Environmental Quality general use protection criteria. Subreaches C, D, and E did not exceed the general use protection criteria for any constituent concentration criteria, but dissolved oxygen concentrations did not meet the general use criteria in these subreaches.

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Ecosystem service models are increasingly in demand for decision making. However, the data required to run these models are often patchy, missing, outdated, or untrustworthy. Further, communication of data and model uncertainty to decision makers is often either absent or unintuitive. In this work, we introduce a systematic approach to addressing both the data gap and the difficulty in communicating uncertainty through a stochastic adaptation of the Service Path Attribution Networks (SPAN) framework. The SPAN formalism assesses ecosystem services through a set of up to 16 maps, which characterize the services in a study area in terms of flow pathways between ecosystems and human beneficiaries. Although the SPAN algorithms were originally defined deterministically, we present them here in a stochastic framework which combines probabilistic input data with a stochastic transport model in order to generate probabilistic spatial outputs. This enables a novel feature among ecosystem service models: the ability to spatially visualize uncertainty in the model results. The stochastic SPAN model can analyze areas where data limitations are prohibitive for deterministic models. Greater uncertainty in the model inputs (including missing data) should lead to greater uncertainty expressed in the model’s output distributions. By using Bayesian belief networks to fill data gaps and expert-provided trust assignments to augment untrustworthy or outdated information, we can account for uncertainty in input data, producing a model that is still able to run and provide information where strictly deterministic models could not. Taken together, these attributes enable more robust and intuitive modelling of ecosystem services under uncertainty.

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