Hydrologic units provide a convenient but problematic nationwide set of geographic polygons based on subjectively determined subdivisions of land surface areas at several hierarchical levels. The problem is that it is impossible to map watersheds, basins, or catchments of relatively equal size and cover the whole country. The hydrologic unit framework is in fact composed mostly of watersheds and pieces of watersheds. The pieces include units that drain to segments of streams, remnant areas, noncontributing areas, and coastal or frontal units that can include multiple watersheds draining to an ocean or large lake. Hence, half or more of the hydrologic units are not watersheds as the name of the framework “Watershed Boundary Dataset” implies. Nonetheless, hydrologic units and watersheds are commonly treated as synonymous, and this misapplication and misunderstanding can have some serious scientific and management consequences. We discuss some of the strengths and limitations of watersheds and hydrologic units as spatial frameworks. Using examples from the Northwest and Southeast United States, we explain how the misapplication of the hydrologic unit framework has altered the meaning of watersheds and can impair understanding associations between spatial geographic characteristics and surface water conditions.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-017-0854-z","usgsCitation":"Omernik, J.M., Griffith, G.E., Hughes, R.M., Glover, J.B., and Weber, M.H., 2017, How misapplication of the hydrologic unit framework diminishes the meaning of watersheds: Environmental Management, v. 60, no. 1, p. 1-11, https://doi.org/10.1007/s00267-017-0854-z.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-067027","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469773,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6145848","text":"External Repository"},{"id":342118,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-04","publicationStatus":"PW","scienceBaseUri":"59366da7e4b0f6c2d0d7d603","contributors":{"authors":[{"text":"Omernik, James M.","contributorId":169740,"corporation":false,"usgs":false,"family":"Omernik","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":25578,"text":"USGS -Volunteer","active":true,"usgs":false}],"preferred":false,"id":697136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffith, Glenn E. 0000-0001-7966-4720 ggriffith@usgs.gov","orcid":"https://orcid.org/0000-0001-7966-4720","contributorId":4053,"corporation":false,"usgs":true,"family":"Griffith","given":"Glenn","email":"ggriffith@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":697135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hughes, Robert M.","contributorId":113579,"corporation":false,"usgs":true,"family":"Hughes","given":"Robert","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":697137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glover, James B.","contributorId":192631,"corporation":false,"usgs":false,"family":"Glover","given":"James","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":697139,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weber, Marc H.","contributorId":169742,"corporation":false,"usgs":false,"family":"Weber","given":"Marc","email":"","middleInitial":"H.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":697138,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188184,"text":"70188184 - 2017 - Snow and ice","interactions":[],"lastModifiedDate":"2020-08-20T19:26:43.019871","indexId":"70188184","displayToPublicDate":"2017-06-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":32,"text":"General Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"PNW-GTR-950","chapter":"3","title":"Snow and ice","docAbstract":"An evaluation of trends in hydrologic and water quality conditions and estimation of water budgets through 2013 was done by the U.S. Geological Survey in cooperation with the Chester County Water Resources Authority. Long-term hydrologic, meteorologic, and biologic data collected in Chester County, Pennsylvania, which included streamflow, groundwater levels, surface-water quality, biotic integrity, precipitation, and air temperature were analyzed to determine possible trends or changes in hydrologic conditions. Statistically significant trends were determined by applying the Kendall rank correlation test; the magnitudes of the trends were determined using the Sen slope estimator. Water budgets for eight selected watersheds were updated and a new water budget was developed for the Marsh Creek watershed. An average water budget for Chester County was developed using the eight selected watersheds and the new Marsh Creek water budget.
Annual and monthly mean streamflow, base flow, and runoff were analyzed for trends at 10 streamgages. The periods of record at the 10 streamgages ranged from 1961‒2013 to 1988‒2013. The only statistically significant trend for annual mean streamflow was for West Branch Brandywine Creek near Honey Brook, Pa. (01480300) where annual mean streamflow increased 1.6 cubic feet per second (ft3/s) per decade. The greatest increase in monthly mean streamflow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 47 ft3/s per decade. No statistically significant trends in annual mean base flow or runoff were determined for the 10 streamgages. The greatest increase in monthly mean base flow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 26 ft3/s per decade.
The magnitude of peaks greater than a base streamflow was analyzed for trends for 12 streamgages. The period of record at the 12 stream gages ranged from 1912‒2012 to 2004–11. Fifty percent of the streamgages showed a small statistically significant increase in peaks greater than the base streamflow. The greatest increase was for Brandywine Creek at Chadds Ford, Pa. (01481000) during 1962‒2012; the increase was 1.8 ft3/s per decade. There were no statistically significant trends in the number of floods equal to or greater than the 2-year recurrence interval flood flow.
Twenty‒one monitoring wells were evaluated for statistically significant trends in annual mean water level, minimum annual water level, maximum annual water level, and annual range in water-level fluctuations. For four wells, a small statistically significant increase in annual mean water level was determined that ranged from 0.16 to 0.7 feet per decade. There was poor or no correlation between annual mean groundwater levels and annual mean streamflow and base flow. No correlation was determined between annual mean groundwater level and annual precipitation. Despite rapid population growth and land-use change since 1950, there appears to have been little or no detrimental effects on groundwater levels in 21 monitoring wells.
Long-term precipitation and temperature data were available from the West Chester (1893‒2013) and Phoenixville, Pa. (1915‒2013) National Oceanic and Atmospheric Administration (NOAA) weather stations. No statistically significant trends in annual mean precipitation or annual mean temperature were determined for either station. Both weather stations had a significant decrease in the number of days per year with precipitation greater than or equal to 0.1 inch. Annual mean minimum and maximum temperatures from the NOAA Southeastern Piedmont Climate Division increased 0.2 degrees Fahrenheit (F) per decade between 1896 and 2014. The number of days with a maximum temperature equal to or greater than 90 degrees F increased at West Chester and decreased at Phoenixville. No statistically significant trend was determined for annual snowfall amounts.
Data from 1974 to 2013 for three stream water-quality monitors in the Brandywine Creek watershed were evaluated. The monitors are on the West Branch Brandywine Creek at Modena, Pa. (01480617), East Branch Brandywine Creek below Downingtown, Pa. (01480870), and Brandywine Creek at Chadds Ford, Pa. (01481000). Statistically significant upward trends were determined for annual mean specific conductance at all three stations, indicating the total dissolved solids load has been increasing. If the current trend continues, the annual mean specific conductance could almost double from 1974 to 2050. The increase in specific conductance likely is due to increases in chloride concentrations, which have been increasing steadily over time at all three stations. No correlation was found between monthly mean specific conductance and monthly mean streamflow or base flow. Statistically significant upward trends in pH were determined for all three stations. Statistically significant upward trends in stream temperature were determined for East Branch Brandywine Creek below Downingtown, Pa. (01480870) and Brandywine Creek at Chadds Ford, Pa. (01481000). The stream water-quality data indicate substantial increases in the minimum daily dissolved oxygen concentrations in the Brandywine Creek over time.
The Chester County Index of Biotic Integrity (CC-IBI) determined for 1998‒2013 was evaluated for the five biological sampling sites collocated with streamgages. CC-IBI scores are based on a 0‒100 scale with higher scores indicating better stream quality. Statistically significant upward trends in the CC-IBI were determined for West Branch Brandywine Creek at Modena, Pa. (01480617) and East Branch Brandywine Creek below Downingtown, Pa. (01480870). No correlation was found between the CC-IBI and streamflow, precipitation, or stream specific conductance, pH, temperature, or dissolved oxygen concentration.
A Chester County average water budget was developed using the nine estimated watershed water budgets. Average precipitation was 48.4 inches, and average streamflow was 21.4 inches. Average runoff and base flow were 8.3 and 13.1 inches, respectively, and average evapotranspiration and estimation of errors was 27.2 inches.\"
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175025","collaboration":"Prepared in cooperation with the Chester County Water Resources Authority","usgsCitation":"Sloto, R.A., and Reif, A.G., 2017, Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania (ver.1.1, July 2017): U.S. Geological Survey Scientific Investigations Report 2017–5025, 59 p., https://doi.org/10.3133/sir20175025.","productDescription":"vii, 59 p.","numberOfPages":"71","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064731","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":341981,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5025/sir20175025.pdf","text":"Report","size":"8.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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1.0: Originally posted June 2,2017; Version 1.1: July 10, 2017","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Rich fens are common boreal ecosystems with distinct hydrology, biogeochemistry and ecology that influence their carbon (C) balance. We present growing season soil chamber methane emission (FCH4), ecosystem respiration (ER), net ecosystem exchange (NEE) and gross primary production (GPP) fluxes from a 9-years water table manipulation experiment in an Alaskan rich fen. The study included major flood and drought years, where wetting and drying treatments further modified the severity of droughts. Results support previous findings from peatlands that drought causes reduced magnitude of growing season FCH4, GPP and NEE, thus reducing or reversing their C sink function. Experimentally exacerbated droughts further reduced the capacity for the fen to act as a C sink by causing shifts in vegetation and thus reducing magnitude of maximum growing season GPP in subsequent flood years by ~15% compared to control plots. Conversely, water table position had only a weak influence on ER, but dominant contribution to ER switched from autotrophic respiration in wet years to heterotrophic in dry years. Droughts did not cause inter-annual lag effects on ER in this rich fen, as has been observed in several nutrient-poor peatlands. While ER was dependent on soil temperatures at 2 cm depth, FCH4 was linked to soil temperatures at 25 cm. Inter-annual variability of deep soil temperatures was in turn dependent on wetness rather than air temperature, and higher FCH4 in flooded years was thus equally due to increased methane production at depth and decreased methane oxidation near the surface. Short-term fluctuations in wetness caused significant lag effects on FCH4, but droughts caused no inter-annual lag effects on FCH4. Our results show that frequency and severity of droughts and floods can have characteristic effects on the exchange of greenhouse gases, and emphasize the need to project future hydrological regimes in rich fens.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13612","usgsCitation":"Olefeldt, D., Euskirchen, E., Harden, J.W., Kane, E.S., McGuire, A.D., Waldrop, M.P., and Turetsky, M.R., 2017, A decade of boreal rich fen greenhouse gas fluxes in response to natural and experimental water table variability: Global Change Biology, v. 23, no. 6, p. 2428-2440, https://doi.org/10.1111/gcb.13612.","productDescription":"13 p.","startPage":"2428","endPage":"2440","ipdsId":"IP-075210","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-31","publicationStatus":"PW","scienceBaseUri":"5a0425b8e4b0dc0b45b45367","contributors":{"authors":[{"text":"Olefeldt, David","contributorId":169408,"corporation":false,"usgs":false,"family":"Olefeldt","given":"David","affiliations":[{"id":32365,"text":"Department of Renewable Resources, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":721161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Euskirchen, Eugénie S.","contributorId":83378,"corporation":false,"usgs":false,"family":"Euskirchen","given":"Eugénie S.","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":721162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":721163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kane, Evan S.","contributorId":11903,"corporation":false,"usgs":true,"family":"Kane","given":"Evan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":721164,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGuire, A. David 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":166708,"corporation":false,"usgs":true,"family":"McGuire","given":"A.","email":"ffadm@usgs.gov","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":716795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waldrop, Mark P. 0000-0003-1829-7140 mwaldrop@usgs.gov","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":1599,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","email":"mwaldrop@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":721165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Turetsky, Merritt R.","contributorId":169398,"corporation":false,"usgs":false,"family":"Turetsky","given":"Merritt","email":"","middleInitial":"R.","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":721166,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70187214,"text":"sir20175035 - 2017 - Nutrient and sediment concentrations and loads in the Steele Bayou Basin, northwestern Mississippi, 2010–14","interactions":[],"lastModifiedDate":"2017-06-01T10:56:06","indexId":"sir20175035","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","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":"2017-5035","title":"Nutrient and sediment concentrations and loads in the Steele Bayou Basin, northwestern Mississippi, 2010–14","docAbstract":"The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers-Vicksburg District, monitored streamflow, water quality, and sediment at two stations on the Steele Bayou in northwestern Mississippi from October 2010 through September 2014 to characterize nutrient and sediment concentrations and loads in areas where substantial implementation of conservation efforts have been implemented. The motivation for this effort was to quantify improvements, or lack thereof, in water quality in the Steele Bayou watershed as a result of implementing large- and small-scale best-management practices aimed at reducing nutrient and sediment concentrations and loads. The results of this study document the hydrologic, water-quality, and sedimentation status of these basins following over two decades of ongoing implementation of conservation practices.
Results from this study indicate the two Steele Bayou stations have comparable loads and yields of total nitrogen, phosphorus, and suspended sediment when compared to other agricultural basins in the southeastern and central United States. However, nitrate plus nitrite yields from basins in the Mississippi River alluvial plain, including the Steele Bayou Basin, are generally lower than other agricultural basins in the southeastern and central United States.
Seasonal variation in nutrient and sediment loads was observed at both stations and for most constituents. About 50 percent of the total annual nutrient and sediment load was observed during the spring (February through May) and between 25 and 50 percent was observed during late fall and winter (October through January). These seasonal patterns probably reflect a combination of seasonal patterns in precipitation, runoff, streamflow, and in the timing of fertilizer application.
Median concentrations of total nitrogen, nitrate plus nitrite, total phosphorus, orthophosphate, and suspended sediment were slightly higher at the upstream station, Steele Bayou near Glen Allan, than at the downstream station, Steele Bayou at Grace Road at Hopedale, MS, although the differences typically were not statistically significant. Mean annual loads of nitrate plus nitrite and suspended sediment were also larger at the upstream station, although the annual loads at both stations were generally within the 95-percent confidence intervals of each other.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175035","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Vicksburg District","usgsCitation":"Hicks, M.B., Murphy, J.C., and Stocks, S.J., 2017, Nutrient and sediment concentrations and loads in the Steele Bayou Basin, northwestern Mississippi, 2010–14: U.S. Geological Survey Scientific Investigations Report 2017–5035, 32 p., https://doi.org/10.3133/sir20175035.","productDescription":"viii, 32 p.","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-072526","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":341906,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5035/sir20175035.pdf","text":"Report","size":"1.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5035"},{"id":341905,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5035/coverthb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Steele Bayou Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.25,\n 32.4\n ],\n [\n -90.6,\n 32.4\n ],\n [\n -90.6,\n 33.7\n ],\n [\n -91.25,\n 33.7\n ],\n [\n -91.25,\n 32.4\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi Gulf Water Science Center
U.S. Geological Survey
308 Airport Rd.
Jackson MS 39208
Decreases in the abundance and diversity of stream fishes in the North American Great Plains have been attributed to habitat fragmentation, altered hydrological and temperature regimes, and elevated levels of total dissolved solids and total suspended solids. Pelagic-broadcast spawning cyprinids, such as the Arkansas River Shiner Notropis girardi, may be particularly vulnerable to these changing conditions because of their reproductive strategy. Our objectives were to assess the effects of temperature, total dissolved solids, and total suspended solids on the developmental and survival rates of Arkansas River Shiner larvae. Results suggest temperature had the greatest influence on the developmental rate of Arkansas River Shiner larvae. However, embryos exposed to the higher levels of total dissolved solids and total suspended solids reached developmental stages earlier than counterparts at equivalent temperatures. Although this rapid development may be beneficial in fragmented waters, our data suggest it may be associated with lower survival rates. Furthermore, those embryos incubating at high temperatures, or in high levels of total dissolved solids and total suspended solids resulted in less viable embryos and larvae than those incubating in all other temperature, total dissolved solid, and total suspended solid treatment groups. As the Great Plains ecoregion continues to change, these results may assist in understanding reasons for past extirpations and future extirpation threats as well as predict stream reaches capable of sustaining Arkansas River Shiners and other species with similar early life-history strategies.
","language":"English","publisher":"Scientific Journals","doi":"10.3996/112015-JFWM-111","usgsCitation":"Mueller, J.S., Grabowski, T.B., Brewer, S.K., and Worthington, T.A., 2017, Effects of temperature, total dissolved solids, and total suspended solids on survival and development rate of larval Arkansas River Shiner: Journal of Fish and Wildlife Management, v. 8, no. 1, p. 79-88, https://doi.org/10.3996/112015-JFWM-111.","productDescription":"10 p.","startPage":"79","endPage":"88","ipdsId":"IP-052617","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469796,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.repository.cam.ac.uk/handle/1810/290516","text":"External Repository"},{"id":347437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-01","publicationStatus":"PW","scienceBaseUri":"5a07e8dee4b09af898c8cbcd","contributors":{"authors":[{"text":"Mueller, Julia S.","contributorId":176241,"corporation":false,"usgs":false,"family":"Mueller","given":"Julia","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":716099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":716093,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":716094,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Worthington, Thomas A.","contributorId":140662,"corporation":false,"usgs":false,"family":"Worthington","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":716100,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191688,"text":"70191688 - 2017 - Evaluating species-specific changes in hydrologic regimes: an iterative approach for salmonids in the Greater Yellowstone Area (USA)","interactions":[],"lastModifiedDate":"2017-10-24T13:44:30","indexId":"70191688","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating species-specific changes in hydrologic regimes: an iterative approach for salmonids in the Greater Yellowstone Area (USA)","docAbstract":"Despite the importance of hydrologic regimes to the phenology, demography, and abundance of fishes such as salmonids, there have been surprisingly few syntheses that holistically assess regional, species-specific trends in hydrologic regimes within a framework of climate change. Here, we consider hydrologic regimes within the Greater Yellowstone Area in the Rocky Mountains of western North America to evaluate changes in hydrologic metrics anticipated to affect salmonids, a group of fishes with high regional ecological and socioeconomic value. Our analyses assessed trends across different sites and time periods (1930–, 1950–, and 1970–2015) as means to evaluate spatial and temporal shifts. Consistent patterns emerged from our analyses indicating substantial shifts to (1) earlier peak discharge events; (2) reductions of summer minimum streamflows; (3) declines in the duration of river ice; and (4) decreases in total volume of water. We found accelerated trends in hydrologic change for the 1970–2015 period, with an average peak discharge 7.5 days earlier, 27.5% decline in summer minimum streamflows, and a 15.6% decline in the annual total volume of water (1 October–September 30) across sites. We did observe considerable variability in magnitude of change across sites, suggesting different levels of vulnerability to a changing climate. Our analyses provide an iterative means for assessing climate predictions and an important step in identifying the climate resilience of landscapes.
","language":"English","publisher":"Springer","doi":"10.1007/s11160-017-9472-3","usgsCitation":"Al-Chokhachy, R.K., Sepulveda, A.J., Ray, A.M., Thoma, D.P., and Tercek, M.T., 2017, Evaluating species-specific changes in hydrologic regimes: an iterative approach for salmonids in the Greater Yellowstone Area (USA): Reviews in Fish Biology and Fisheries, v. 27, no. 2, p. 425-441, https://doi.org/10.1007/s11160-017-9472-3.","productDescription":"17 p.","startPage":"425","endPage":"441","ipdsId":"IP-079638","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":347243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Greater Yellowstone Area","volume":"27","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-17","publicationStatus":"PW","scienceBaseUri":"59f05122e4b0220bbd9a1d94","contributors":{"authors":[{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":713063,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":713064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ray, Andrew M.","contributorId":167601,"corporation":false,"usgs":false,"family":"Ray","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":713065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thoma, David P.","contributorId":197256,"corporation":false,"usgs":false,"family":"Thoma","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":713066,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tercek, Michael T.","contributorId":197257,"corporation":false,"usgs":false,"family":"Tercek","given":"Michael","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":713067,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70185018,"text":"sir20175020 - 2017 - Hydrogeologic framework and selected components of the groundwater budget for the upper Umatilla River Basin, Oregon","interactions":[],"lastModifiedDate":"2017-06-01T08:28:44","indexId":"sir20175020","displayToPublicDate":"2017-05-31T00:00:00","publicationYear":"2017","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":"2017-5020","title":"Hydrogeologic framework and selected components of the groundwater budget for the upper Umatilla River Basin, Oregon","docAbstract":"This report presents a summary of the hydrogeology of the upper Umatilla River Basin, Oregon, based on characterization of the hydrogeologic framework, horizontal and vertical directions of groundwater flow, trends in groundwater levels, and components of the groundwater budget. The conceptual model of the groundwater flow system integrates available data and information on the groundwater resources of the upper Umatilla River Basin and provides insights regarding key hydrologic processes, such as the interaction between the groundwater and surface water systems and the hydrologic budget.
The conceptual groundwater model developed for the study area divides the groundwater flow system into five hydrogeologic units: a sedimentary unit, three Columbia River basalt units, and a basement rock unit. The sedimentary unit, which is not widely used as a source of groundwater in the upper basin, is present primarily in the lowlands and consists of conglomerate, loess, silt and sand deposits, and recent alluvium. The Columbia River Basalt Group is a series of Miocene flood basalts that are present throughout the study area. The basalt is uplifted in the southeastern half of the study area, and either underlies the sedimentary unit, or is exposed at the surface. The interflow zones of the flood basalts are the primary aquifers in the study area. Beneath the flood basalts are basement rocks composed of Paleogene to Pre-Tertiary sedimentary, volcanic, igneous, and metamorphic rocks that are not used as a source of groundwater in the upper Umatilla River Basin.
The major components of the groundwater budget in the upper Umatilla River Basin are (1) groundwater recharge, (2) groundwater discharge to surface water and wells, (3) subsurface flow into and out of the basin, and (4) changes in groundwater storage.
Recharge from precipitation occurs primarily in the upland areas of the Blue Mountains. Mean annual recharge from infiltration of precipitation for the upper Umatilla River Basin during 1951–2010 is about 9.6 inches per year (in/yr). Annual recharge from precipitation for water year 2010 ranged from 3 in. in the lowland area to about 30 in. in the Blue Mountains. Using Kahle and others (2011) data and methods from the Columbia Plateau regional model, average annual recharge from irrigation is estimated to be about 2.2 in/yr for the 13 square miles of irrigated land in the upper Umatilla River Basin.
Groundwater discharges to streams throughout the year and is a large component of annual streamflow in the upper Umatilla River Basin. Upward vertical hydraulic gradients near the Umatilla River indicate the potential for groundwater discharge. Groundwater discharge to the Umatilla River generally occurs in the upper part of the basin, upstream from the main stem.
Groundwater development in the upper Umatilla River Basin began sometime after 1950 (Davies-Smith and others, 1988; Gonthier and Bolke, 1991). By water year 2010, groundwater use in the upper Umatilla River Basin was approximately 11,214 acre-feet (acre-ft). Total groundwater withdrawals for the study area were estimated at 7,575 acre-ft for irrigation, 3,173 acre-ft for municipal use, and 466 acre-ft for domestic use.
Total groundwater flow into or from the study area depends locally on geology and hydraulic head distribution. Estimates of subsurface flow were calculated using the U.S. Geological Survey Columbia Plateau regional groundwater flow model. Net flux values range from 25,000 to 27,700 acre-ft per year and indicate that groundwater is moving out of the upper Umatilla River Basin into the lower Umatilla River Basin.
Water level changes depend on storage changes within an aquifer, and storage changes depend on the storage properties of the aquifer, as well as recharge to or discharge from the aquifer. Groundwater level data in the upper Umatilla River Basin are mostly available from wells in Columbia River basalt units, which indicate areas of long-term water level declines in the Grande Ronde basalt unit near Pendleton and Athena, Oregon. Groundwater levels in the Wanapum basalt unit do not show long-term declines in the upper Umatilla River Basin. Because of pumping, some areas in the upper Umatilla River Basin have shown a decrease, or reversal, in the upward vertical head gradient.
Key data needs are improvement of the spatial and temporal distribution of water-level data collection and continued monitoring of streamflow gaging sites. Additionally, refinement of recharge estimates would enhance understanding of the processes that provide the groundwater resources in the upper Umatilla River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175020","collaboration":"Prepared in cooperation with Confederated Tribes of the Umatilla Indian Reservation","usgsCitation":"Herrera, N.B., Ely, Kate, Mehta, Smita, Stonewall, A.J., Risley, J.C., Hinkle, S.R., and Conlon, T.D., 2017, Hydrogeologic framework and selected components of the groundwater budget for the upper Umatilla River Basin, Oregon: U.S. Geological Survey Scientific Investigations Report 2017–5020, 57 p., https://doi.org/10.3133/sir20175020.","productDescription":"vi, 57 p.","onlineOnly":"Y","ipdsId":"IP-049734","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":341899,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5020/coverthb.jpg"},{"id":341900,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5020/sir20175020.pdf","text":"Report","size":"16.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5020"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Umatilla River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.9,\n 45.35\n ],\n [\n -118,\n 45.35\n ],\n [\n -118,\n 45.93\n ],\n [\n -118.9,\n 45.93\n ],\n [\n -118.9,\n 45.35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Managers making decisions may benefit from a well-informed understanding of a species' population size and trends. Given the cryptic nature and habitat characteristics of the western pond turtle (Emys marmorata), however, imperfect detection may be high and population estimates are frequently varied and unreliable. As a case study to investigate this issue, we used temperature dataloggers to examine turtle behavior at 2 long-term monitoring sites with different hydrological characteristics in Sequoia National Park, California, to determine if common stream-survey techniques are consistent with site-specific turtle behavior. Sycamore Creek is an intermittent stream that dries up every summer while the North Fork Kaweah River flows year-round. We found that while turtles spent most of the recorded time in the water (55% in Sycamore Creek and 82% in the North Fork Kaweah River), the timing of traditional surveys only coincided with the turtles' aquatic activity in the North Fork Kaweah River. At Sycamore Creek, turtles were most likely to be in the water at night. In contrast, failure to detect turtles in North Fork Kaweah River is likely owing to the larger size and complexity of the underwater habitat. In both streams, turtles were also more likely to be in the water in the weeks leading up to important changes in hydroperiods. Our findings illustrate the effects that differences in water permanence can have on turtle behavior within the same watershed and how phenotypic plasticity may then affect detection during surveys. Our study highlights the importance of tailoring survey practices to the site-specific behavioral traits of the target species.
","language":"English","publisher":"Chelonian Research Foundation","doi":"10.2744/CCB-1240.1","usgsCitation":"Ruso, G., Meyer, E., and Das, A., 2017, Seasonal and diel environmental conditions predict western pond turtle (Emys marmorata) behavior at a perennial and an ephemeral stream in Sequoia National Park, California: Chelonian Conservation and Biology, v. 16, no. 1, p. 20-28, https://doi.org/10.2744/CCB-1240.1.","productDescription":"9 p.","startPage":"20","endPage":"28","ipdsId":"IP-082015","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":495027,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2744/ccb-1240.1","text":"Publisher Index Page"},{"id":341947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sequoia National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.69010925292969,\n 36.41078375301565\n ],\n [\n -118.4271240234375,\n 36.41078375301565\n ],\n [\n -118.4271240234375,\n 36.563151553545985\n ],\n [\n -118.69010925292969,\n 36.563151553545985\n ],\n [\n -118.69010925292969,\n 36.41078375301565\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"1","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592fd633e4b0e9bd0ea896a1","contributors":{"authors":[{"text":"Ruso, Gabrielle gruso@usgs.gov","contributorId":192549,"corporation":false,"usgs":true,"family":"Ruso","given":"Gabrielle","email":"gruso@usgs.gov","affiliations":[],"preferred":true,"id":696773,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer, Erik","contributorId":192550,"corporation":false,"usgs":false,"family":"Meyer","given":"Erik","email":"","affiliations":[],"preferred":false,"id":696774,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Das, Adrian J. 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":3842,"corporation":false,"usgs":true,"family":"Das","given":"Adrian J.","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":696772,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187992,"text":"70187992 - 2017 - Deleterious effects of net clogging on the quantification of stream drift","interactions":[],"lastModifiedDate":"2017-06-27T13:18:18","indexId":"70187992","displayToPublicDate":"2017-05-26T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Deleterious effects of net clogging on the quantification of stream drift","docAbstract":"Drift studies are central to stream and river ecological research. However, a fundamental aspect of quantifying drift — how net clogging affects the accuracy of results — has been widely ignored. Utilizing approaches from plankton and suspended sediment studies in oceanography and hydrology, we examined the rate and dynamics of net clogging across a range of conditions. We found that nets clog nonlinearly over time and that suspended solid concentrations and net mesh size exerted a strong effect on clogging rates. Critically, net clogging introduced unpredictable biases in resultant data due to the inaccuracies in water volume estimates introduced by progressive clogging. This renders the widespread approach to linearly “correct” for clogging inadequate. Using a meta-analysis of 77 drift studies spanning 25 years, we demonstrate that the detrimental effects of net clogging are routinely unappreciated, even though the results of most of these studies were likely affected by clogging. We close by describing an approach for avoiding net clogging, which will increase the accuracy and reproducibility of results in future freshwater, lotic drift studies.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2016-0365","usgsCitation":"Muehlbauer, J.D., Kennedy, T., Copp, A.J., and Sabol, T.A., 2017, Deleterious effects of net clogging on the quantification of stream drift: Canadian Journal of Fisheries and Aquatic Sciences, v. 74, no. 7, p. 1041-1048, https://doi.org/10.1139/cjfas-2016-0365.","productDescription":"8 p.","startPage":"1041","endPage":"1048","ipdsId":"IP-078467","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469823,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2016-0365","text":"External Repository"},{"id":438329,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71J97WD","text":"USGS data release","linkHelpText":"Stream Drift Sampling in Arizona, 2014Data"},{"id":341792,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59293e92e4b016f7a94076de","contributors":{"authors":[{"text":"Muehlbauer, Jeffrey D. 0000-0003-1808-580X jmuehlbauer@usgs.gov","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":5045,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","email":"jmuehlbauer@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":696164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Theodore A. tkennedy@usgs.gov","contributorId":140027,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore A.","email":"tkennedy@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":696165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Copp, Adam J. 0000-0001-7385-0055 acopp@usgs.gov","orcid":"https://orcid.org/0000-0001-7385-0055","contributorId":5194,"corporation":false,"usgs":true,"family":"Copp","given":"Adam","email":"acopp@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":696166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sabol, Thomas A. 0000-0002-4299-2285 tsabol@usgs.gov","orcid":"https://orcid.org/0000-0002-4299-2285","contributorId":3403,"corporation":false,"usgs":true,"family":"Sabol","given":"Thomas","email":"tsabol@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":696167,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187875,"text":"70187875 - 2017 - Variation in species-level plant functional traits over wetland indicator status categories","interactions":[],"lastModifiedDate":"2017-06-14T11:56:48","indexId":"70187875","displayToPublicDate":"2017-05-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Variation in species-level plant functional traits over wetland indicator status categories","docAbstract":"Wetland indicator status (WIS) describes the habitat affinity of plant species and is used in wetland delineations and resource inventories. Understanding how species-level functional traits vary across WIS categories may improve designations, elucidate mechanisms of adaptation, and explain habitat optima and niche. We investigated differences in species-level traits of riparian flora across WIS categories, extending their application to indicate hydrologic habitat. We measured or compiled data on specific leaf area (SLA), stem specific gravity (SSG), seed mass, and mature height of 110 plant species that occur along the Colorado River in Grand Canyon, Arizona. Additionally, we measured leaf δ13C, δ15N, % carbon, % nitrogen, and C/N ratio of 56 species with C3 photosynthesis. We asked the following: (i) How do species-level traits vary over WIS categories? (ii) Does the pattern differ between herbaceous and woody species? (iii) How well do multivariate traits define WIS categories? (iv) Which traits are correlated? The largest trait differences among WIS categories for herbaceous species occurred for SSG, seed mass, % leaf carbon and height, and for woody species occurred for height, SSG, and δ13C. SSG increased and height decreased with habitat aridity for both woody and herbaceous species. The δ13C and hence water use efficiency of woody species increased with habitat aridity. Water use efficiency of herbaceous species increased with habitat aridity via greater occurrence of C4 grasses. Multivariate trait assemblages differed among WIS categories. Over all species, SLA was correlated with height, δ13C, % leaf N, and C/N; height was correlated with SSG and % leaf C; SSG was correlated with % leaf C. Adaptations of both herbaceous and woody riparian species to wet, frequently inundated habitats include low-density stem tissue. Adaptations to drier habitats in the riparian zone include short, high-density cavitation-resistant stem tissue, and high water use efficiency. The results enhance understanding about using traits to describe plant habitat in riparian systems.
","language":"English","publisher":"Blackwell Pub. Ltd","doi":"10.1002/ece3.2975","usgsCitation":"McCoy-Sulentic, M.E., Kolb, T.E., Merritt, D.M., Palmquist, E.C., Ralston, B.E., and Sarr, D.A., 2017, Variation in species-level plant functional traits over wetland indicator status categories: Ecology and Evolution, v. 7, no. 11, p. 3732-3744, https://doi.org/10.1002/ece3.2975.","productDescription":"13 p.","startPage":"3732","endPage":"3744","ipdsId":"IP-083993","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469833,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2975","text":"Publisher Index Page"},{"id":438333,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BV7DTQ","text":"USGS data release","linkHelpText":"Plant functional traits, Colorado River, Grand Canyon, 2012-2014Data"},{"id":341617,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon, Marble Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.4503173828125,\n 35.73090666520053\n ],\n [\n -111.53045654296874,\n 35.73090666520053\n ],\n [\n -111.53045654296874,\n 36.90597988519294\n ],\n [\n -113.4503173828125,\n 36.90597988519294\n ],\n [\n -113.4503173828125,\n 35.73090666520053\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-17","publicationStatus":"PW","scienceBaseUri":"59269bb5e4b0b7ff9fb48963","contributors":{"authors":[{"text":"McCoy-Sulentic, Miles E.","contributorId":192228,"corporation":false,"usgs":false,"family":"McCoy-Sulentic","given":"Miles","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":695858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolb, Thomas E.","contributorId":189073,"corporation":false,"usgs":false,"family":"Kolb","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":695859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merritt, David M.","contributorId":192229,"corporation":false,"usgs":false,"family":"Merritt","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":24595,"text":"USDA Forest Service, Fort Collins CO","active":true,"usgs":false}],"preferred":false,"id":695860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":695857,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ralston, Barbara E. 0000-0001-9991-8994 bralston@usgs.gov","orcid":"https://orcid.org/0000-0001-9991-8994","contributorId":606,"corporation":false,"usgs":true,"family":"Ralston","given":"Barbara","email":"bralston@usgs.gov","middleInitial":"E.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":false,"id":695861,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sarr, Daniel A. dsarr@usgs.gov","contributorId":191593,"corporation":false,"usgs":false,"family":"Sarr","given":"Daniel","email":"dsarr@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":695862,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187170,"text":"ofr20171045 - 2017 - Oregon OCS seafloor mapping: Selected lease blocks relevant to renewable energy","interactions":[],"lastModifiedDate":"2017-06-23T12:33:29","indexId":"ofr20171045","displayToPublicDate":"2017-05-23T00:00:00","publicationYear":"2017","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":"2017-1045","title":"Oregon OCS seafloor mapping: Selected lease blocks relevant to renewable energy","docAbstract":"In 2014 the U.S. Geological Survey (USGS) and the Bureau of Ocean Energy Management (BOEM) entered into Intra-agency agreement M13PG00037 to map an area of the Oregon Outer Continental Shelf (OCS) off of Coos Bay, Oregon, under consideration for development of a floating wind energy farm. The BOEM requires seafloor mapping and site characterization studies in order to evaluate the impact of seafloor and sub-seafloor conditions on the installation, operation, and structural integrity of proposed renewable energy projects, as well as to assess the potential effects of construction and operations on archaeological resources. The mission of the USGS is to provide geologic, topographic, and hydrologic information that contributes to the wise management of the Nation's natural resources and that promotes the health, safety, and well being of the people. This information consists of maps, databases, and descriptions and analyses of the water, energy, and mineral resources, land surface, underlying geologic structure, and dynamic processes of the earth.
For the Oregon OCS study, the USGS acquired multibeam echo sounder and seafloor video data surrounding the proposed development site, which is 95 km2 in area and 15 miles offshore from Coos Bay. The development site had been surveyed by Solmar Hydro Inc. in 2013 under a contract with WindFloat Pacific. The USGS subsequently produced a bathymetry digital elevation model and a backscatter intensity grid that were merged with existing data collected by the contractor. The merged grids were published along with visual observations of benthic geo-habitat from the video data in an associated USGS data release (Cochrane and others, 2015).
This report includes the results of analysis of the video data conducted by Oregon State University and the geo-habitat interpretation of the multibeam echo sounder (MBES) data conducted by the USGS. MBES data was published in Cochrane and others (2015). Interpretive data associated with this publication is published in Cochrane (2017). All the data is provided as geographic information system (GIS) files that contain both Esri ArcGIS geotiffs or shapefiles. For those who do not own the full suite of Esri GIS and mapping software, the data can be read using Esri ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed August 29, 2016). Web services, which consist of standard implementations of ArcGIS representational state transfer (REST) Service and Open Geospatial Consortium (OGC) GIS web map service (WMS), also are available for all published GIS data. Web services were created using an ArcGIS service definition file, resulting in data layers that are symbolized as shown on the associated report figures. Both the ArcGIS REST Service and OGC WMS Service include all the individual GIS layers. Data layers are bundled together in a map-area web service; however, each layer can be symbolized and accessed individually after the web service is ingested into a desktop application or web map. Web services enable users to download and view data, as well as to easily add data to their own workflows, using any browser-enabled, standalone or mobile device.
Though the surficial substrate is dominated by combinations of mud and sand substrate, a diverse assortment of geomorphologic features are related to geologic processes—one anticlinal ridge where bedrock is exposed, a slump and associated scarps, and pockmarks. Pockmarks are seen in the form of fields of small pockmarks, a lineation of large pockmarks with methanogenic carbonates, and areas of large pockmarks that have merged into larger variously shaped depressions. The slump appears to have originated at the pockmark lineation. Video-supervised numerical analysis of the MBES backscatter intensity data and vector ruggedness derived from the MBES bathymetry data was used to produce a substrate model called a seafloor character raster for the study area. The seafloor character raster consists of three substrate classes: soft-flat areas, hard-flat areas, and hard-rugged areas. A Coastal and Marine Ecological Classification Standard (CMECS) geoform and substrate map was also produced using depth, slope, and benthic position index classes to delineate geoform boundaries. Seven geoforms were identified in this process, including ridges, slump scars, slump deposits, basins, and pockmarks.
Statistical analysis of the video data for correlations between substrate, depth, and invertebrate assemblages resulted in the identification of seven biomes: three hard-bottom biomes and four softbottom biomes. A similar analysis of vertebrate observations produces a similar set of biomes. The biome between-group dissimilarity was very high or high. Invertebrates alone represent most of the structure of the whole benthic community into different assemblages. A biotope map was generated using the seafloor character raster and the substrate and depth values of the biomes. Hard substrate biotopes were small in size and were located primarily on the ridge and in pockmarks along the pockmark lineation. The soft-bottom bitopes consisted of large contiguous areas delimited by isobaths.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171045","collaboration":"Prepared in cooperation with the Bureau of Ocean Energy Management","usgsCitation":"Cochrane, G.R., Hemery, L.G., and Henkel, S.K., 2017, Oregon OCS seafloor mapping: Selected lease blocks relevant to renewable energy: U.S. Geological Survey Open-File Report 2017-1045 and Bureau of Ocean Energy Management OCS Study BOEM 2017-018, 51 p., https://doi.org/10.3133/ofr20171045.","productDescription":"v, 51 p.","numberOfPages":"57","onlineOnly":"Y","ipdsId":"IP-080496","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438336,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7000069","text":"USGS data release","linkHelpText":"Interpretive data release for Oregon OCS Seafloor Mapping: Selected Lease Blocks Relevant to Renewable Energy"},{"id":341588,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1045/ofr20171045.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1045"},{"id":341585,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1045/coverthb.jpg"}],"contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species’ evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. We developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperature as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. Additionally, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Furthermore, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. Our results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0177467","usgsCitation":"Huntsman, B.M., Falke, J.A., Savereide, J.W., and Bennett, K.E., 2017, The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape: PLoS ONE, v. 12, no. 5, p. 1-21, https://doi.org/10.1371/journal.pone.0177467.","productDescription":"e0177467; 21 p.","startPage":"1","endPage":"21","ipdsId":"IP-077611","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":461565,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0177467","text":"Publisher Index Page"},{"id":353885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Chena River Basin","volume":"12","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-22","publicationStatus":"PW","scienceBaseUri":"5afee879e4b0da30c1bfc457","contributors":{"authors":[{"text":"Huntsman, Brock M. 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":166748,"corporation":false,"usgs":false,"family":"Huntsman","given":"Brock","email":"","middleInitial":"M.","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":734441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":734396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Savereide, James W.","contributorId":204591,"corporation":false,"usgs":false,"family":"Savereide","given":"James","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":734442,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bennett, Katrina E.","contributorId":204592,"corporation":false,"usgs":false,"family":"Bennett","given":"Katrina","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":734443,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70269685,"text":"70269685 - 2017 - Satellite-based water use dynamics using historical Landsat data (1984–2014) in the southwestern United States","interactions":[],"lastModifiedDate":"2025-07-31T13:22:08.551955","indexId":"70269685","displayToPublicDate":"2017-05-18T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Satellite-based water use dynamics using historical Landsat data (1984–2014) in the southwestern United States","docAbstract":"Remote sensing-based field-scale evapotranspiration (ET) maps are useful for characterizing water use patterns and assessing crop performance. The relative impact of climate variability and water management decisions are better studied and quantified using historical data that are derived using a set of consistent datasets and methodology. Historical (1984–2014) Landsat-based ET maps were generated for major irrigation districts in California, i.e., Palo Verde and eight other sub-basins in parts of the middle and lower Central Valley. A total of 3396 Landsat images were processed using the Operational Simplified Surface Energy Balance (SSEBop) model that integrates weather and remotely sensed images to estimate monthly and annual ET within the study sites over the 31 years. Model output evaluation and validation using gridded-flux data and water balance ET approaches indicated relatively good correspondence (R2 up to 0.88, root mean square error as low as 14 mm/month) between SSEBop ET and validation datasets. In a pairwise comparison, annual variability of agro-hydrologic parameters of actual evapotranspiration (ETa), land surface temperature (Ts), and runoff (Q) were found to be more variable than their corresponding climatic counterparts of atmospheric water demand (ETo), air temperature (Ta), and precipitation (P), revealing process differences between regional climatic drivers and localized agro-hydrologic responses. However, only Ta showed a consistent increase (up to 1.2 K) over study sites during the 31 years, whereas other climate variables such as ETo and P showed a generally neutral trend. This study demonstrates a useful application of “Big Data” science where large volumes of historical Landsat and weather datasets were used to quantify and understand the relative importance of water management and climate variability in crop water use dynamics in regards to the linkages among water management decisions, hydrologic processes and economic transactions. Irrigation district-wide ETa estimates were used to compute historical crop water use volumes and monetary equivalents of water savings for the Palo Verde Irrigation District (PVID). During the peak crop fallowing year in PVID, the water saved reached a maximum of ~ 107,200 acre-feet in 2011 with an estimated monetary payout value of $20.5 million. A significant decreasing trend in actual ET despite an increasing atmospheric demand in PVID highlights the role of management decisions in affecting local hydrologic processes. This study has importance for planning water resource allocation, managing water rights, sustaining agricultural production, and quantifying impacts of climate and land use/land cover changes on water resources. With increased computational efficiency, similar studies can be conducted in other parts of the world to help policy and decision makers understand and quantify various aspects of water resources management.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.05.005","usgsCitation":"Senay, G.B., Schauer, M., Friedrichs, M., Velpuri, N., and Singh, R., 2017, Satellite-based water use dynamics using historical Landsat data (1984–2014) in the southwestern United States: Remote Sensing of Environment, v. 202, p. 98-112, https://doi.org/10.1016/j.rse.2017.05.005.","productDescription":"15 p.","startPage":"98","endPage":"112","ipdsId":"IP-084512","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":493296,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2017.05.005","text":"Publisher Index Page"},{"id":493191,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.40977836532282,\n 42.04933677309765\n ],\n [\n -123.16675091874134,\n 36.46673710104686\n ],\n [\n -118.58307879273526,\n 32.705501119947826\n ],\n [\n -113.73717874196483,\n 32.12914120007623\n ],\n [\n -113.88408063137007,\n 35.268837865873046\n ],\n [\n -114.8258516238531,\n 35.43740401775197\n ],\n [\n -117.48081678552326,\n 37.20400442230724\n ],\n [\n -120.03564230020528,\n 39.18700095919894\n ],\n [\n -120.18220374157768,\n 41.98136883976758\n ],\n [\n -125.40977836532282,\n 42.04933677309765\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"202","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":944425,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schauer, Matthew 0000-0002-4198-3379","orcid":"https://orcid.org/0000-0002-4198-3379","contributorId":216909,"corporation":false,"usgs":true,"family":"Schauer","given":"Matthew","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":944426,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedrichs, MacKenzie 0000-0002-9602-321X mfriedrichs@usgs.gov","orcid":"https://orcid.org/0000-0002-9602-321X","contributorId":5847,"corporation":false,"usgs":true,"family":"Friedrichs","given":"MacKenzie","email":"mfriedrichs@usgs.gov","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":944427,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Velpuri, Naga Manohar 0000-0002-6370-1926","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":216911,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga Manohar ","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":944428,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singh, Ramesh 0000-0002-8164-3483","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":210983,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":944429,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187709,"text":"70187709 - 2017 - Predicting wading bird and aquatic faunal responses to ecosystem restoration scenarios","interactions":[],"lastModifiedDate":"2017-11-10T14:27:56","indexId":"70187709","displayToPublicDate":"2017-05-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting wading bird and aquatic faunal responses to ecosystem restoration scenarios","docAbstract":"In large-scale conservation decisions, scenario planning identifies key uncertainties of ecosystem function linked to ecological drivers affected by management, incorporates ecological feedbacks, and scales up to answer questions robust to alternative futures. Wetland restoration planning requires an understanding of how proposed changes in surface hydrology, water storage, and landscape connectivity affect aquatic animal composition, productivity, and food-web function. In the Florida Everglades, reintroduction of historical hydrologic patterns is expected to increase productivity of all trophic levels. Highly mobile indicator species such as wading birds integrate secondary productivity from aquatic prey (small fishes and crayfish) over the landscape. To evaluate how fish, crayfish, and wading birds may respond to alternative hydrologic restoration plans, we compared predicted small fish density, crayfish density and biomass, and wading bird occurrence for existing conditions to four restoration scenarios that varied water storage and removal of levees and canals (i.e. decompartmentalization). Densities of small fish and occurrence of wading birds are predicted to increase throughout most of the Everglades under all restoration options because of increased flows and connectivity. Full decompartmentalization goes furthest toward recreating hypothesized historical patterns of fish density by draining excess water ponded by levees and hydrating areas that are currently drier than in the past. In contrast, crayfish density declined and species composition shifted under all restoration options because of lengthened hydroperiods (i.e. time of inundation). Under full decompartmentalization, the distribution of increased prey available for wading birds shifted south, closer to historical locations of nesting activity in Everglades National Park.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.12518","usgsCitation":"Beerens, J.M., Trexler, J.C., and Catano, C.P., 2017, Predicting wading bird and aquatic faunal responses to ecosystem restoration scenarios: Restoration Ecology, v. 25, no. S1, p. S86-S98, https://doi.org/10.1111/rec.12518.","productDescription":"13 p.","startPage":"S86","endPage":"S98","ipdsId":"IP-070475","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469841,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://onlinelibrary.wiley.com/doi/10.1111/rec.12518/abstract","text":"External Repository"},{"id":341344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"S1","publicComments":"Special Issue: Synthesis of Everglades research and ecosystem services (SERES) project","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-10","publicationStatus":"PW","scienceBaseUri":"591c0fc8e4b0a7fdb43ddeec","contributors":{"authors":[{"text":"Beerens, James M. 0000-0001-8143-916X jbeerens@usgs.gov","orcid":"https://orcid.org/0000-0001-8143-916X","contributorId":143722,"corporation":false,"usgs":true,"family":"Beerens","given":"James","email":"jbeerens@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":695201,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trexler, Joel C.","contributorId":36267,"corporation":false,"usgs":false,"family":"Trexler","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":695202,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catano, Christopher P.","contributorId":138935,"corporation":false,"usgs":false,"family":"Catano","given":"Christopher","email":"","middleInitial":"P.","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":695203,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187134,"text":"sir20175023 - 2017 - U.S. Geological Survey Karst Interest Group Proceedings, San Antonio, Texas, May 16–18, 2017","interactions":[],"lastModifiedDate":"2025-03-06T13:23:23.159237","indexId":"sir20175023","displayToPublicDate":"2017-05-15T09:15:00","publicationYear":"2017","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":"2017-5023","title":"U.S. Geological Survey Karst Interest Group Proceedings, San Antonio, Texas, May 16–18, 2017","docAbstract":"Karst aquifer systems are present throughout parts of the United States and some of its territories, and have developed in carbonate rocks (primarily limestone and dolomite) and evaporites (gypsum, anhydrite, and halite) that span an interval of time encompassing more than 550 million years. The depositional environments, diagenetic processes, post-depositional tectonic events, and geochemical weathering processes that form karst aquifers are varied and complex. These factors involve biological, chemical, and physical changes that when combined with the diverse climatic regimes in which karst development has taken place, result in the unique dual- or triple-porosity nature of karst aquifers. These complex hydrogeologic systems typically represent challenging and unique conditions to scientists attempting to study groundwater flow and contaminant transport in these terrains.
The dissolution of carbonate rocks and the subsequent development of distinct and beautiful landscapes, caverns, and springs have resulted in the most exceptional karst areas being designated as national or state parks. Tens of thousands of similar areas in the United States have been developed into commercial caverns and known privately owned caves. Both public and private properties provide access for scientists to study the flow of groundwater in situ. Likewise, the range and complexity of landforms and groundwater flow systems associated with karst terrains are enormous, perhaps more than for any other aquifer type. Karst aquifers and landscapes that form in tropical areas, such as the cockpit karst along the north coast of Puerto Rico, differ greatly from karst landforms in more arid climates, such as the Edwards Plateau in west-central Texas or the Guadalupe Mountains near Carlsbad, New Mexico, where hypogenic processes have played a major role in speleogenesis. Many of these public and private lands also contain unique flora and fauna associated with these karst hydrogeologic systems. As a result, numerous federal, state, and local agencies have a strong interest in the study of karst terrains.
Many of the major springs and aquifers in the United States have developed in carbonate rocks, such as the Floridan aquifer system in Florida and parts of Alabama, Georgia, and South Carolina; the Ozark Plateaus aquifer system in parts of Arkansas, Kansas, Missouri, and Oklahoma; and the Edwards-Trinity aquifer system in west-central Texas. These aquifers, and the springs that discharge from them, serve as major water-supply sources and form unique ecological habitats. Competition for the water resources of karst aquifers is common, and urban development and the lack of attenuation of contaminants in karst areas due to dissolution features that form direct pathways into karst aquifers can impact the ecosystem and water quality associated with these aquifers.
The concept for developing a platform for interaction among scientists within the U.S. Geological Survey (USGS) working on karst-related studies evolved from the November 1999 National Groundwater Meeting of the USGS. As a result, the Karst Interest Group (KIG) was formed in 2000. The KIG is a loose-knit, grass-roots organization of USGS and non-USGS scientists and researchers devoted to fostering better communication among scientists working on, or interested in, karst science. The primary mission of the KIG is to encourage and support interdisciplinary collaboration and technology transfer among scientists working in karst areas. Additionally, the KIG encourages collaborative studies between the different mission areas of the USGS as well as with other federal and state agencies, and with researchers from academia and institutes.
To accomplish its mission, the KIG has organized a series of workshops that have been held near nationally important karst areas. To date (2017) seven KIG workshops, including the workshop documented in this report, have been held. The workshops typically include oral and poster sessions on selected karst-related topics and research, as well as field trips to local karst areas. To increase non-USGS participation an effort was made for the workshops to be held at a university or institute beginning with the fourth workshop. Proceedings of the workshops are published by the USGS and are available online at the USGS publications warehouse https://pubs.er.usgs.gov/ by using the search term “karst interest group.”
The first KIG workshop was held in St. Petersburg, Florida, in 2001, in the vicinity of the large springs and other karst features of the Floridan aquifer system. The second KIG workshop was held in 2002, in Shepherdstown, West Virginia, in proximity to the carbonate aquifers of the northern Shenandoah Valley, and highlighted an invited presentation on karst literature by the late Barry F. Beck of P.E. LaMoreaux and Associates. The third KIG workshop was held in 2005, in Rapid City, South Dakota, near evaporite karst features in limestones of the Madison Group in the Black Hills of South Dakota. The Rapid City KIG workshop included field trips to Wind Cave National Park and Jewel Cave National Monument, and featured a presentation by Thomas Casadevall, then USGS Central Region Director, on the status of Earth science at the USGS.
The fourth KIG workshop in 2008 was hosted by the Hoffman Environmental Research Institute and Center for Cave and Karst Studies at Western Kentucky University in Bowling Green, Kentucky, near Mammoth Cave National Park and karst features of the Chester Upland and Pennyroyal Plateau. The workshop featured a late-night field trip into Mammoth Cave led by Rickard Toomey and Rick Olsen, National Park Service. The fifth KIG workshop in 2011 was a joint meeting of the USGS KIG and University of Arkansas HydroDays, hosted by the Department of Geosciences at the University of Arkansas in Fayetteville. The workshop featured an outstanding field trip to the unique karst terrain along the Buffalo National River in the southern Ozarks, and a keynote presentation on paleokarst in the United States was delivered by Art and Peggy Palmer. The sixth KIG workshop was hosted by the National Cave and Karst Research Institute (NCKRI) in 2014, in Carlsbad, New Mexico. George Veni, Director of the NCKRI, served as a co-chair of the workshop with Eve Kuniansky of the USGS. The workshop featured speaker Dr. Penelope Boston, Director of Cave and Karst Studies at New Mexico Tech, Socorro, and Academic Director at the NCKRI, who addressed the future of karst research. The field trip on evaporite karst of the lower Pecos Valley was led by Lewis Land (NCKRI karst hydrologist), and the field trip on the geology of Carlsbad Caverns National Park was led by George Veni.
This current seventh KIG workshop is being held in San Antonio at the University of Texas at San Antonio (UTSA). This 2017 workshop is being hosted by the Department of Geological Sciences’ Student Geological Society (SGS), and student chapters of the American Association of Petroleum Geologists (AAPG) and Association of Engineering Geologists (AEG), with support by the UTSA Department of Geological Sciences and Center for Water Research. The UTSA student chapter presidents, Jose Silvestre (SGS), John Cooper (AAPG), and Tyler Mead (AEG) serve as co-chairs of the 2017 workshop with Eve Kuniansky of the USGS. The technical session committee is chaired by Eve Kuniansky, USGS, and includes Michael Bradley, Tom Byl, Rebecca Lambert, John Lane, and James Kaufmann, all USGS, and Patrick Tucci, retired USGS. The logistics committee includes Amy Clark, Yongli Gao, and Lance Lambert (Department Chair), UTSA Department of Geological Sciences; and Ryan Banta and Allan Clark, USGS, San Antonio, Texas. The field trip committee is chaired by Allan Clark and includes Amy Clark, Yongli Gao, and Keith Muehlestein, UTSA; Marcus Gary, Edwards Aquifer Authority and University of Texas at Austin; Ron Green, Southwest Research Institute; Geary Schindel, Edwards Aquifer Authority; and George Veni, NCKRI. Additionally, two organizations have assisted the UTSA student chapters in hosting the meeting by donating funds to the chapters: the Edwards Aquifer Authority, San Antonio, Texas, and the Barton Springs Edwards Aquifer Authority, Austin, Texas. Additionally, Yongli Gao, Center for Water Research and Department of Geological Sciences, UTSA, helped develop sessions on cave and karst research in China for this workshop. These proceedings could not have been accomplished without the assistance of Lawrence E. Spangler as co-editor who not only has subject matter expertise, but also serves as an editor with the USGS Science Publishing Network. We sincerely hope that this workshop continues to promote future collaboration among scientists of varied and diverse backgrounds, and improves our understanding of karst aquifer systems in the United States and its territories.
The extended abstracts of USGS authors were peer reviewed and approved for publication by the USGS. Articles submitted by university researchers and other federal and state agencies did not go through the formal USGS peer review and approval process, and therefore may not adhere to USGS editorial standards or stratigraphic nomenclature. However, all articles had a minimum of two peer reviews and were edited for consistency of appearance in the proceedings. The use of trade, firm or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The USGS Water Availability and Use Science Program funded the publication costs of the proceedings.
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]\n}","volume":"25","issue":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-05","publicationStatus":"PW","scienceBaseUri":"591abe34e4b0a7fdb43c8bed","contributors":{"authors":[{"text":"Knierim, Katherine J. 0000-0002-5361-4132 kknierim@usgs.gov","orcid":"https://orcid.org/0000-0002-5361-4132","contributorId":191788,"corporation":false,"usgs":true,"family":"Knierim","given":"Katherine","email":"kknierim@usgs.gov","middleInitial":"J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nottmeier, Anna M. 0000-0002-0205-0955 anottmeier@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-0955","contributorId":5283,"corporation":false,"usgs":true,"family":"Nottmeier","given":"Anna","email":"anottmeier@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Worland, Scott C. 0000-0001-6384-2457 scworland@usgs.gov","orcid":"https://orcid.org/0000-0001-6384-2457","contributorId":5802,"corporation":false,"usgs":true,"family":"Worland","given":"Scott","email":"scworland@usgs.gov","middleInitial":"C.","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}],"preferred":true,"id":695086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Westerman, Drew A. 0000-0002-8522-776X dawester@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-776X","contributorId":4526,"corporation":false,"usgs":true,"family":"Westerman","given":"Drew","email":"dawester@usgs.gov","middleInitial":"A.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695087,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Brian R. 0000-0001-6611-3807 brclark@usgs.gov","orcid":"https://orcid.org/0000-0001-6611-3807","contributorId":1502,"corporation":false,"usgs":true,"family":"Clark","given":"Brian","email":"brclark@usgs.gov","middleInitial":"R.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":695088,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187690,"text":"70187690 - 2017 - Carbon cycling in the mantled karst of the Ozark Plateaus, central United States","interactions":[],"lastModifiedDate":"2017-05-24T10:05:54","indexId":"70187690","displayToPublicDate":"2017-05-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5397,"text":"Geoderma Regional","active":true,"publicationSubtype":{"id":10}},"title":"Carbon cycling in the mantled karst of the Ozark Plateaus, central United States","docAbstract":"The nature of carbon (C) cycling in the unsaturated zone where groundwater is in contact with abundant gas-filled voids is poorly understood. The objective of this study was to trace inorganic-C cycling in a karst landscape using stable-C isotopes, with emphasis on a shallow groundwater flow path through the soil, to an underlying cave, and to the spring outlet of a cave stream in the Ozark Plateaus of northwestern Arkansas. Carbon dioxide (CO2) concentration and isotopic composition (δ13C-CO2) in gas and dissolved inorganic carbon (DIC) concentration and isotopic composition (δ13C-DIC) in water were measured in samples collected from two suction-cup soil samplers above the cave, three sites in the cave, and at the spring outlet of the cave stream. Soil-gas CO2 concentration (median 2,578 ppm) and δ13C-CO2 (median − 21.5‰) were seasonally variable, reflecting the effects of surface temperature changes on soil-CO2 production via respiration and organic-matter decomposition. Cave-air CO2 (median 1,026 ppm) was sourced from the soil zone and the surface atmosphere, with seasonally changing proportions of each source controlled by surface temperature-driven air density gradients. Soil-DIC concentration (median 1.7 mg L− 1) was lower and soil-δ13C-DIC (median − 19.5‰) was lighter compared to the cave (median 23.3 mg L− 1 and − 14.3‰, respectively) because carbonate-bedrock dissolution provided an inorganic source of C to the cave. Carbon species in the soil had a unique, light stable-C isotopic signature compared to the cave. Discrimination of soil-C sources to karst groundwater was achieved, which is critical for developing hydrologic budgets using environmental tracers such as C.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geodrs.2017.05.004","usgsCitation":"Knierim, K.J., Pollock, E.D., Covington, M.D., Hays, P.D., and Brye, K.R., 2017, Carbon cycling in the mantled karst of the Ozark Plateaus, central United States: Geoderma Regional, v. 10, p. 64-76, https://doi.org/10.1016/j.geodrs.2017.05.004.","productDescription":"13 p.","startPage":"64","endPage":"76","ipdsId":"IP-066344","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":469852,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geodrs.2017.05.004","text":"Publisher Index Page"},{"id":438344,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7610XJ5","text":"USGS data release","linkHelpText":"Carbonate geochemistry dataset of the soil and an underlying cave in the Ozark Plateaus, central United States"},{"id":341306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"10","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591abe34e4b0a7fdb43c8beb","contributors":{"authors":[{"text":"Knierim, Katherine J. 0000-0002-5361-4132 kknierim@usgs.gov","orcid":"https://orcid.org/0000-0002-5361-4132","contributorId":191788,"corporation":false,"usgs":true,"family":"Knierim","given":"Katherine","email":"kknierim@usgs.gov","middleInitial":"J.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pollock, Erik D.","contributorId":192014,"corporation":false,"usgs":false,"family":"Pollock","given":"Erik","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":695090,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Covington, Matthew D.","contributorId":192015,"corporation":false,"usgs":false,"family":"Covington","given":"Matthew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":695091,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hays, Phillip D. 0000-0001-5491-9272 pdhays@usgs.gov","orcid":"https://orcid.org/0000-0001-5491-9272","contributorId":4145,"corporation":false,"usgs":true,"family":"Hays","given":"Phillip","email":"pdhays@usgs.gov","middleInitial":"D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brye, Kristofor R.","contributorId":192016,"corporation":false,"usgs":false,"family":"Brye","given":"Kristofor","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":695161,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187644,"text":"70187644 - 2017 - Noble gas signatures in the Island of Maui, Hawaii: Characterizing groundwater sources in fractured systems","interactions":[],"lastModifiedDate":"2017-06-20T13:16:14","indexId":"70187644","displayToPublicDate":"2017-05-12T00:00:00","publicationYear":"2017","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":"Noble gas signatures in the Island of Maui, Hawaii: Characterizing groundwater sources in fractured systems","docAbstract":"Uneven distribution of rainfall and freshwater scarcity in populated areas in the Island of Maui, Hawaii, renders water resources management a challenge in this complex and ill-defined hydrological system. A previous study in the Galapagos Islands suggests that noble gas temperatures (NGTs) record seasonality in that fractured, rapid infiltration groundwater system rather than the commonly observed mean annual air temperature (MAAT) in sedimentary systems where infiltration is slower thus, providing information on recharge sources and potential flow paths. Here we report noble gas results from the basal aquifer, springs, and rainwater in Maui to explore the potential for noble gases in characterizing this type of complex fractured hydrologic systems. Most samples display a mass-dependent depletion pattern with respect to surface conditions consistent with previous observations both in the Galapagos Islands and Michigan rainwater. Basal aquifer and rainwater noble gas patterns are similar and suggest direct, fast recharge from precipitation to the basal aquifer. In contrast, multiple springs, representative of perched aquifers, display highly variable noble gas concentrations suggesting recharge from a variety of sources. The distinct noble gas patterns for the basal aquifer and springs suggest that basal and perched aquifers are separate entities. Maui rainwater displays high apparent NGTs, incompatible with surface conditions, pointing either to an origin at high altitudes with the presence of ice or an ice-like source of undetermined origin. Overall, noble gas signatures in Maui reflect the source of recharge rather than the expected altitude/temperature relationship commonly observed in sedimentary systems.
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In the arid southwestern USA, this combination of stressors has caused widespread declines of native aquatic and semi-aquatic species. Achieving resilience to drought and other effects of climate change may depend upon continued management, so understanding the combined effects of stressors is important. We used Bayesian hierarchical models fitted with 10-years of pond-based monitoring surveys for the federally-endangered Sonoran Tiger Salamander (Ambystoma mavortium stebbinsi) and invasive predators (fishes and American Bullfrogs, Lithobates catesbeianus) that threaten native species. We estimated trends in occupancy of salamanders and invasive predators while accounting for hydrological dynamics of ponds, then used a two-species interaction model to directly estimate how invasive predators affected salamander occupancy. We also tested a conceptual model that predicted that drought, by limiting the distribution of invasive predators, could ultimately benefit native species. Even though occupancy of invasive predators was stationary and their presence in a pond reduced the probability of salamander presence by 23%, occupancy of Sonoran Tiger Salamanders increased, annually, by 2.2%. Occupancy of salamanders and invasive predators both declined dramatically following the 5th consecutive year of drought. Salamander occupancy recovered quickly after return to non-drought conditions, while occupancy of invasive predators remained suppressed. Models that incorporated three time-lagged periods (1 to 4 years) of local moisture conditions confirmed that salamanders and invasive predators responded differently to drought, reflecting how life-history strategies shape responses to disturbances. The positive 10-year trend in salamander occupancy and their rapid recovery after drought provided partial support for the hypothesis of drought-mediated coexistence with invasive predators. These results also suggest management opportunities for conservation of the Sonoran Tiger Salamander and other imperiled organisms in human-transformed landscapes.
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Flood magnitudes were determined for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEPs at 220 streamgages, 125 of which are in Massachusetts and 95 are in the adjacent States of Connecticut, New Hampshire, New York, Rhode Island, and Vermont. AEP flood flows were computed for streamgages using the expected moments algorithm weighted with a recently computed regional skewness coefficient for New England.
Regional regression equations were developed to estimate the magnitude of floods for selected AEP flows at ungaged sites from 199 selected streamgages and for 60 potential explanatory basin characteristics. AEP flows for 21 of the 125 streamgages in Massachusetts were not used in the final regional regression analysis, primarily because of regulation or redundancy. The final regression equations used generalized least squares methods to account for streamgage record length and correlation. Drainage area, mean basin elevation, and basin storage explained 86 to 93 percent of the variance in flood magnitude from the 50- to 0.2-percent AEPs, respectively. The estimates of AEP flows at streamgages can be improved by using a weighted estimate that is based on the magnitude of the flood and associated uncertainty from the at-site analysis and the regional regression equations. Weighting procedures for estimating AEP flows at an ungaged site on a gaged stream also are provided that improve estimates of flood flows at the ungaged site when hydrologic characteristics do not abruptly change.
Urbanization expressed as the percentage of imperviousness provided some explanatory power in the regional regression; however, it was not statistically significant at the 95-percent confidence level for any of the AEPs examined. The effect of urbanization on flood flows indicates a complex interaction with other basin characteristics. Another complicating factor is the assumption of stationarity, that is, the assumption that annual peak flows exhibit no significant trend over time. The results of the analysis show that stationarity does not prevail at all of the streamgages. About 27 percent of streamgages in Massachusetts and about 42 percent of streamgages in adjacent States with 20 or more years of systematic record used in the study show a significant positive trend at the 95-percent confidence level. The remaining streamgages had both positive and negative trends, but the trends were not statistically significant. Trends were shown to vary over time. In particular, during the past decade (2004–2013), peak flows were persistently above normal, which may give the impression of positive trends. Only continued monitoring will provide the information needed to determine whether recent increases in annual peak flows are a normal oscillation or a true trend.
The analysis used 37 years of additional data obtained since the last comprehensive study of flood flows in Massachusetts. In addition, new methods for computing flood flows at streamgages and regionalization improved estimates of flood magnitudes at gaged and ungaged locations and better defined the uncertainty of the estimates of AEP floods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165156","collaboration":"Prepared in cooperation with the Massachusetts Department of Transportation","usgsCitation":"Zarriello, P.J., 2017, Magnitude of flood flows at selected annual exceedance probabilities for streams in Massachusetts: U.S. Geological Survey Scientific Investigations Report 2016–5156, 54 p., https://doi.org/10.3133/sir20165156.","productDescription":"Report: ix, 54 p.; Tables; 1 Appendix","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065274","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":341058,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_table11.csv","text":"Table 11","size":"47.9 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Magnitude and variance of selected flood 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studies"},{"id":341060,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_table13.csv","text":"Table 13","size":"28.6 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Comparison of newly estimated flood flows to prior studies"},{"id":341047,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_table03.csv","text":"Table 3 ","size":"85.5 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Flood flows for Massachusetts and adjacent States through water year 2013"},{"id":340865,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5156/coverthb.jpg"},{"id":340867,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_appendix03.xlsx","text":"Appendix 3 ","size":"92.5 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5156 Appendix 3","linkHelpText":"- Workbook for estimating flood flows at gaged and ungaged sites in Massachusetts "},{"id":340870,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_table04.xlsx","text":"Table 4","size":"71.6 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5156 Table 4","linkHelpText":"- Streamgage and basin characteristics"},{"id":341059,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156_table04.csv","text":"Table 4 ","size":"30.1 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Streamgage and basin characteristics"},{"id":340866,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5156/sir20165156.pdf","text":"Report","size":"5.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5156"}],"country":"United 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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
The current (2015) streamgage network in Pennsylvania and the Susquehanna River Basin in Pennsylvania and New York was evaluated in order to design a network that would meet the hydrologic needs of many partners and serve a variety of purposes and interests, including estimation of streamflow statistics at ungaged sites. This study was done by the U.S. Geological Survey, in cooperation with the Pennsylvania Department of Environmental Protection and the Susquehanna River Basin Commission. The study area includes the Commonwealth of Pennsylvania and the Susquehanna River Basin in Pennsylvania and New York. For this study, 229 streamgages were identified as reference streamgages that could be used to represent ungaged watersheds. Criteria for a reference streamgage are a minimum of 10 years of continuous record, minimally altered streamflow, and a drainage area less than 1,500 square miles. Some of the reference streamgages have been discontinued but provide historical hydrologic information valuable in the determination of streamflow characteristics of ungaged watersheds. Watersheds in the study area not adequately represented by a reference streamgage were identified by examining a range of basin characteristics, the extent of geographic coverage, and the strength of estimated streamflow correlations between gaged and ungaged sites.
Basin characteristics were determined for the reference streamgage watersheds and the 1,662 12-digit hydrologic unit code (HUC12) subwatersheds in Pennsylvania and the Susquehanna River Basin using a geographic information system (GIS) spatial analysis and nationally available GIS datasets. Basin characteristics selected for this study include drainage area, mean basin elevation, mean basin slope, percentage of urbanized area, percentage of forested area, percentage of carbonate bedrock, mean annual precipitation, and soil thickness. A GIS spatial analysis was used to identify HUC12 subwatersheds outside the range of basin characteristics of the reference streamgages. There were 320 HUC12 subwatersheds, or 19 percent of the study area, with basin characteristics outside the range represented by the reference streamgage watersheds.
A GIS spatial analysis was used to identify geographic gaps in the streamgage network. For each streamgage, a watershed area, called the gage statistical area (GSA), was delineated. The GSA shows the drainage area within a specific drainage-area ratio of the streamgage for transfer of streamflow statistics from that streamgage to ungaged sites on the valid statistical reach of the GSA for a streamgage. In Pennsylvania, a drainage-area ratio of 0.33–3 times the drainage area of the ungaged site was found to perform as well as, if not better than, more traditional ratios such as 0.5–1.5 (or 2) for transfer of selected streamflow statistics. A total of 1,102 HUC12 subwatersheds, or 66 percent of the study area, are outside the GSA for a reference streamgage.
The USGS Baseline Streamflow Estimator (BaSE) program was used to determine how well HUC12 subwatersheds outside the streamgage GSAs are represented by the reference streamgage network in Pennsylvania, based on estimated streamflow correlation. The centroid of each HUC12 subwatershed was run through the BaSE program to determine the reference streamgage with the highest estimated streamflow correlation. There were 929 HUC12 subwatersheds in Pennsylvania, or 56 percent of the State, with an estimated correlation coefficient less than 0.96.
The results from the basin characteristic, geographic, and streamflow correlation analyses were combined to identify 1,405 HUC12 subwatersheds in Pennsylvania and the Susquehanna River Basin in Pennsylvania and New York that lack a representative reference, based on at least one identified gap. Of the 1,405 HUC12 subwatersheds, 139 exhibited all three gaps, indicating a 8-percent gap in the reference streamgage network.
Streamgages in areas with similar hydrologic characteristics and in close proximity to one another can potentially provide similar information (termed streamgages with high substitution potential). Streamgages were considered to have a high substitution potential with a nearby streamgage(s) if (1) the streamflow correlation coefficient was equal to or greater than 0.96, (2) the streamgages had 10 years of concurrent record, and (3) the streamgages are in the same watershed within the GSA of the streamgage. Seventy-four current (2015) streamgages with high substitution potential with at least one other streamgage were identified in the study area. Although these identified streamgages have a high substitution potential, they provide valuable streamflow information to a stakeholder. Selected primary uses of these streamgages were identified to determine the overall need for an individual streamgage.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165149","collaboration":"Prepared in cooperation with the Pennsylvania Department of Environmental Protection and the Susquehanna River Basin Commission ","usgsCitation":"Sloto, R.A., Stuckey, M.H., and Hoffman, S.A., 2017, Evaluation of the streamgage network for estimating streamflow statistics at ungaged sites in Pennsylvania and the Susquehanna River Basin in Pennsylvania and New York: U.S. Geological Survey Scientific Investigations Report 2016–5149, 102 p., https://doi.org/10.3133/sir20165149.","productDescription":"vi, 102 p.","numberOfPages":"112","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069147","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":340754,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5149//sir20165149.pdf","text":"Report","size":"85.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5149"},{"id":340753,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5149/coverthb.jpg"}],"country":"United States","state":"New York, Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.77197265625,\n 39.70718665682654\n ],\n [\n -74.805908203125,\n 39.70718665682654\n ],\n [\n -74.805908203125,\n 42.97250158602597\n ],\n [\n -78.77197265625,\n 42.97250158602597\n ],\n [\n -78.77197265625,\n 39.70718665682654\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Geophysical methods were used to monitor infiltration during a water release, referred to as a “pulse flow,” in the Colorado River delta in March and April 2014. The pulse flow was enabled by Minute 319 of the 1944 United States–Mexico Treaty concerning water of the Colorado River. Fieldwork was carried out by the U.S. Geological Survey and the Centro de Investigación Científica y de Educación Superior de Ensenada as part of a binational effort to monitor the hydrologic effects of the pulse flow along the limitrophe (border) reach of the Colorado River and into Mexico. Repeat microgravity measurements were made at 25 locations in the southern limitrophe reach to quantify aquifer storage change during the pulse flow. Observed increases in storage along the river were greater with distance to the south, and the amount of storage change decreased away from the river channel. Gravity data at four monitoring well sites indicate specific yield equal to 0.32±0.05. Electromagnetic induction methods were used at 12 transects in the limitrophe reach of the river along the United States– Mexico border, and farther south into Mexico. These data, which are sensitive to variation in soil texture and water content, suggest relatively homogeneous conditions. Repeat direct-current resistivity measurements were collected at two locations to monitor groundwater elevation. Results indicate rapid groundwater-level rise during the pulse flow in the limitrophe reach and smaller variation at a more southern transect. Together, these data are useful for hydrogeologic characterization and hydrologic model development. Electronic data files are provided in the accompanying data release (Kennedy and others, 2016a).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171050","collaboration":"Prepared in Cooperation with Universidad Autónoma de Baja California and Centro de Investigación Científica y de Educación Superior de Ensenada","usgsCitation":"Kennedy, J.R., Callegary, J.B., Macy, J.P., Reyes-Lopez, J., Pérez-Flores, M., 2017, Geophysical data collected during the 2014 minute 319 pulse flow on the Colorado River below Morelos Dam, United States and Mexico: U.S. Geological Survey Open-File Report 2017–1050, 48 p., https://doi.org/10.3133/ofr20171050.","productDescription":"Report: vii, 48 Pp.; Data Release","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-067382","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":438349,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K935M8","text":"USGS data release","linkHelpText":"Geophysical Data Collected during the 2014 Minute 319 Pulse Flow"},{"id":341001,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1050/ofr20171050.pdf","text":"Report","size":"8.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1050"},{"id":341000,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1050/coverthb.jpg"},{"id":341002,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7K935M8","text":"Data Release"}],"country":"Mexico, United States","state":"Arizona, Baja California, California","otherGeospatial":"Colorado River, Morelos Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115,\n 32.33333\n ],\n [\n -114.5,\n 32.33333\n ],\n [\n -114.5,\n 32.75\n ],\n [\n -115,\n 32.75\n ],\n [\n -115,\n 32.33333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
A critical aspect of the uniqueness of coastal drought is the effects on the salinity dynamics of creeks, rivers, and estuaries. The location of the freshwater–saltwater interface along the coast is an important factor in the ecological and socioeconomic dynamics of coastal communities. Salinity is a critical response variable that integrates hydrologic and coastal dynamics including sea level, tides, winds, precipitation, streamflow, and tropical storms. The position of the interface determines the composition of freshwater and saltwater aquatic communities as well as the freshwater availability for water intakes. Many definitions of drought have been proposed, with most describing a decline in precipitation having negative impacts on the water supply. Indices have been developed incorporating data such as rainfall, streamflow, soil moisture, and groundwater levels. These water-availability drought indices were developed for upland areas and may not be ideal for characterizing coastal drought. The availability of real-time and historical salinity datasets provides an opportunity for the development of a salinity-based coastal drought index. An approach similar to the standardized precipitation index (SPI) was modified and applied to salinity data obtained from sites in South Carolina and Georgia. Using the SPI approach, the index becomes a coastal salinity index (CSI) that characterizes coastal salinity conditions with respect to drought periods of higher-saline conditions and wet periods of higher-freshwater conditions. Evaluation of the CSI indicates that it provides additional coastal response information as compared to the SPI and the Palmer hydrologic drought index, and the CSI can be used for different estuary types and for comparison of conditions along coastlines.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-15-00171.1","usgsCitation":"Conrads, P., and Darby, L.S., 2017, Development of a coastal drought index using salinity data: Bulletin of the American Meteorological Society, v. 98, no. 4, p. 753-766, https://doi.org/10.1175/BAMS-D-15-00171.1.","productDescription":"14 p.","startPage":"753","endPage":"766","ipdsId":"IP-067018","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":340993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-24","publicationStatus":"PW","scienceBaseUri":"5912d536e4b0e541a03d451b","contributors":{"authors":[{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":694571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Darby, Lisa S.","contributorId":191873,"corporation":false,"usgs":false,"family":"Darby","given":"Lisa","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":694572,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185687,"text":"ofr20161212 - 2017 - The U.S. Geological Survey Monthly Water Balance Model Futures Portal","interactions":[],"lastModifiedDate":"2017-05-03T14:33:53","indexId":"ofr20161212","displayToPublicDate":"2017-05-03T12:15:00","publicationYear":"2017","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":"2016-1212","title":"The U.S. Geological Survey Monthly Water Balance Model Futures Portal","docAbstract":"The U.S. Geological Survey Monthly Water Balance Model Futures Portal (https://my.usgs.gov/mows/) is a user-friendly interface that summarizes monthly historical and simulated future conditions for seven hydrologic and meteorological variables (actual evapotranspiration, potential evapotranspiration, precipitation, runoff, snow water equivalent, atmospheric temperature, and streamflow) at locations across the conterminous United States (CONUS).
The estimates of these hydrologic and meteorological variables were derived using a Monthly Water Balance Model (MWBM), a modular system that simulates monthly estimates of components of the hydrologic cycle using monthly precipitation and atmospheric temperature inputs. Precipitation and atmospheric temperature from 222 climate datasets spanning historical conditions (1952 through 2005) and simulated future conditions (2020 through 2099) were summarized for hydrographic features and used to drive the MWBM for the CONUS. The MWBM input and output variables were organized into an open-access database. An Open Geospatial Consortium, Inc., Web Feature Service allows the querying and identification of hydrographic features across the CONUS. To connect the Web Feature Service to the open-access database, a user interface—the Monthly Water Balance Model Futures Portal—was developed to allow the dynamic generation of summary files and plots based on plot type, geographic location, specific climate datasets, period of record, MWBM variable, and other options. Both the plots and the data files are made available to the user for download
Director, USGS Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225