Spatial and temporal variability characterize submerged aquatic vegetation (SAV) assemblages, but understanding the complex interactions of environmental drivers of SAV assemblages remains elusive. We documented SAV composition and biomass across a salinity gradient in a coastal estuary over 12 mo. Ten macrophyte species were identified. The dominant species, Ceratophyllum demersum and Myriophyllum spicatum, accounted for over 40% of total biomass. Only Ruppia maritima occurred across the salinity gradient. Salinity, water depth and clarity delineated 3 assemblages: a saline assemblage, and 2 groups of fresher-water species, one associated with deeper water and lower water clarity and the other associated with shallow water and higher water clarity. These assemblages exhibited intra-annual variation, with at least 5 times more biomass in late spring/mid-summer compared to early winter. This pattern was consistent across the estuary, although the difference between peak and low biomass varied by habitat type; brackish exhibited the greatest magnitude. This variation is likely due to higher variation in salinity and the species composition of this habitat. As climate change and coastal restoration impact timing and range of salinity, water depth and clarity in this region, these data can be used to help inform predictive models and management decisions.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/ab00719","usgsCitation":"Hillmann, E.R., DeMarco, K., and La Peyre, M., 2019, Salinity and water clarity dictate seasonal variability in coastal submerged aquatic vegetation in subtropical estuarine environments: Aquatic Biology, v. 28, p. 175-186, https://doi.org/10.3354/ab00719.","productDescription":"12 p.","startPage":"175","endPage":"186","ipdsId":"IP-105293","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":459093,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/ab00719","text":"Publisher Index Page"},{"id":388877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.483154296875,\n 28.748396571187406\n ],\n [\n -88.956298828125,\n 28.748396571187406\n ],\n [\n -88.956298828125,\n 30.330212685432734\n ],\n [\n -91.483154296875,\n 30.330212685432734\n ],\n [\n -91.483154296875,\n 28.748396571187406\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hillmann, Eva R.","contributorId":200686,"corporation":false,"usgs":false,"family":"Hillmann","given":"Eva","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":822573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeMarco, Kristin","contributorId":200003,"corporation":false,"usgs":false,"family":"DeMarco","given":"Kristin","email":"","affiliations":[],"preferred":false,"id":822574,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":822576,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215317,"text":"70215317 - 2019 - Potential threats facing a globally important population of the magnificent frigatebird Fregata magnificens","interactions":[],"lastModifiedDate":"2020-10-16T14:15:55.277198","indexId":"70215317","displayToPublicDate":"2019-11-27T12:10:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7163,"text":"Tropical Zoology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Potential threats facing a globally important population of the magnificent frigatebird Fregata magnificens","title":"Potential threats facing a globally important population of the magnificent frigatebird Fregata magnificens","docAbstract":"Tracking of seabirds has been used to identify foraging hotspots, migratory routes and to assess at-sea threats facing populations. One such threat is the potential negative interaction between seabirds and fisheries through incidental by-catch. In 2012, 60 magnificent frigatebirds Fregata magnificens were found dead, entangled in fishing line, at the globally important breeding site in the British Virgin Islands (BVI). To assess the potential relationship between foraging behaviour and fishing activity, data loggers were deployed on breeding magnificent frigatebirds to record foraging movements. In addition, a survey of local fishers was conducted to assess the scale of incidental by-catch. We recorded 28 complete foraging trips from GPS and GPS-GSM loggers, and 1758 PTT locations. Birds travelled up to 3.3–1067 km from their breeding colony and entered the waters of 10 neighbouring territories. A high percentage of fishers (93% n = 28) reported catching at least one seabird annually, of which the most common were magnificent frigatebirds and brown boobies Sula leucogaster. There are estimated to be at least 1112 vessels in the recreational and artisanal fishing fleets of BVI and its neighbouring islands. Thus, this substantial fishery may have potentially profound effects on seabird populations in the region.
Jewel Cave National Monument in the Black Hills of southwestern South Dakota has more than 200 miles of mapped cave passages and several subterranean lakes that have been discovered since 2015. Jewel Cave is one of the world’s longest known caves and its natural beauty and unique natural cave features led U.S. President Theodore Roosevelt to designate the cave as a national monument in 1908. Jewel Cave was naturally formed in the regionally extensive Madison Limestone, which is characterized as a carbonate karst environment (containing caves and sinkholes) with extensive subterranean cave networks and losing streams at the land surface. Preserving and protecting the cave is an important element of the National Park Service mission, and understanding the hydrogeologic connection between the surface and the subsurface is essential for ensuring the preservation and protection of the cave for future generations. A component in preserving and protecting the park includes the improved understanding of groundwater flow and vulnerability of the subsurface, which allows scientists, park managers, the visiting public, and the surrounding communities to better manage, protect, and preserve the site and its unique natural features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193072","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Valder, J.F., Carter, J.M., Wiles, M.E., and Heimel, S.M., 2019, Groundwater characterization of the Madison aquifer near Jewel Cave National Monument, South Dakota: U.S. Geological Survey Fact Sheet 2019–3072, 6 p., https://doi.org/10.3133/fs20193072.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-112578","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":369683,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20195098","text":"SIR 2019–5098","size":"5.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5098","linkHelpText":"– Generalized Potentiometric-Surface Map and Groundwater Flow Directions in the Madison Aquifer Near Jewel Cave National Monument, South Dakota"},{"id":369681,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3072/coverthb.jpg"},{"id":369682,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3072/fs20193072.pdf","text":"Report","size":"3.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019–3072"}],"country":"United States","state":"South Dakota","otherGeospatial":"Jewel Cave National Monument, Madison Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.01443481445311,\n 43.51917817047661\n ],\n [\n -103.55781555175781,\n 43.51917817047661\n ],\n [\n -103.55781555175781,\n 43.9058083561574\n ],\n [\n -104.01443481445311,\n 43.9058083561574\n ],\n [\n -104.01443481445311,\n 43.51917817047661\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
The city of Sioux Falls, in southeastern South Dakota, is the largest city in South Dakota. The U.S. Geological Survey (USGS), in cooperation with the city of Sioux Falls, completed a groundwater-flow model to use for improving the understanding of groundwater-flow processes, estimating hydrogeologic properties, and analyzing groundwater and surface-water interactions for the Big Sioux aquifer in the model area.
The model area includes the Big Sioux aquifer and the underlying hydrogeologic units from Dell Rapids, South Dakota, to the confluence of the Big Sioux River and the outlet of the Sioux Falls Diversion Channel in eastern Sioux Falls, S. Dak. The Big Sioux aquifer is the primary aquifer in the model area and the focus of the groundwater-flow model. The Big Sioux River is the largest stream in the model area and is in hydraulic connection with the Big Sioux aquifer.
A conceptual model for the area was constructed and includes a characterization of the hydrogeologic framework, analysis and construction of potentiometric surfaces, and summary of estimated water budget components in the model area. The primary hydrogeologic units in the model area consist of (1) the Big Sioux aquifer, (2) a glacial till confining unit, and (3) bedrock aquifers (Split Rock Creek and Sioux Quartzite aquifers). Sources of groundwater recharge included infiltration of precipitation, stream seepage, and groundwater exchanges among the hydraulically connected Big Sioux aquifer, glacial till confining unit, and bedrock aquifers. Groundwater losses included evapotranspiration, groundwater discharge to streams, and groundwater withdrawal to supply water-use needs.
A numerical groundwater-flow model (numerical model) was constructed and was used to simulate all aspects of the conceptual model for predevelopment (steady-state) and time-varying (transient) monthly conditions for 1950–2017. The numerical model was constructed using the USGS modular hydrologic simulation program, MODFLOW–6, and was calibrated using the Parameter ESTimation software, PEST++.
The transient numerical model was calibrated for steady-state and transient monthly conditions for 1950–2017. Calibration targets were observations of hydraulic head, changes in hydraulic head, monthly mean streamflow (as a rate), and cumulative monthly stream discharge (as a volume). Parameters adjusted during model calibration were horizontal and vertical hydraulic conductivity, specific storage, specific yield, recharge and evapotranspiration multipliers, and streambed hydraulic conductivity. Horizontal and vertical hydraulic conductivity were estimated at pilot points distributed within the model area; specific storage and specific yield were assigned to uniform values in each layer in the model area; recharge and evapotranspiration multipliers were assigned uniformly for every stress period in the numerical model; and streambed hydraulic conductivity values were assigned uniformly between stream confluences.
The final calibrated parameter values of horizontal and vertical hydraulic conductivity, specific yield, specific storage, streambed hydraulic conductivity, recharge, and evapotranspiration were considered reasonable for the hydrogeologic materials and conditions in the model area for 1950–2017.
Overall, simulated hydraulic head altitudes had a linear regression coefficient of determination (R2) of 0.48. Hydraulic head altitude residuals for the glacial till confining unit and bedrock aquifers were typically greater in magnitude when compared to residuals in the Big Sioux aquifer, but simulated hydraulic head altitudes in the Big Sioux aquifer compared favorably with mean observed hydraulic head altitudes and had a linear regression R2 of 0.93.
Simulated streamflow hydrographs matched the general trends of observed increases and decreases in streamflow for USGS streamgages 06482000 (Big Sioux River at Sioux Falls, S. Dak.) and 06482020 (Big Sioux River at North Cliff Avenue at Sioux Falls, S. Dak.), but larger streamflows were overestimated at the first streamgage and underestimated at the second streamgage. The numerical model reasonably estimated cumulative monthly stream discharge for the first 10–15 years of available streamflow records at both USGS streamgages. After the first 10–15 years of available streamflow record, cumulative monthly stream discharge was closely estimated for USGS streamgage 06482000 and underestimated at USGS streamgage 06482020.
Composite sensitivities without regularization were calculated by PEST++ for the calibrated numerical model parameters and were averaged by parameter group. The parameter group with the highest mean composite sensitivity was the recharge multiplier parameter group.
Model simplifications, assumptions, and limitations were necessary for construction of the conceptual and numerical models and for calibration efficiency. Spatial simplification of hydraulic properties could cause the numerical model to misrepresent reactions to changes in localized stresses, such as additional demands for groundwater withdrawal. The numerical model was temporally discretized into monthly periods and required scaling daily rates into representative monthly rates for model input and calibration targets. Based on the comparison between the observed and simulated groundwater levels, monthly mean streamflow and cumulative monthly stream discharge, and general groundwater distribution and flow, the numerical model favorably simulated the flow in the Big Sioux aquifer.
Eventual capture was calculated in the model area using a steady-state numerical groundwater-flow model. The eventual capture map shows areas of higher streamflow capture adjacent to the Big Sioux River north of the city of Sioux Falls and along the lower part of the Sioux Falls Diversion Channel, and areas of lower streamflow capture along aquifer boundaries and near the southern Sioux Quartzite barrier.
The timing of capture was determined using a transient numerical groundwater-flow model to determine the likely captured water sources for 30 years of groundwater withdrawal at three hypothetical wells using three continuous withdrawal rates (112.5, 450.0, and 900.0 gallons per minute). Supply for all three hypothetical wells became capture-dominated after only a short period of continuous withdrawal. Capture stabilized after about 10–15 years for well A, and after 20–25 years for well B, and after about 10–15 years for well C.
The groundwater-flow model is a suitable tool to use for improving the understanding of groundwater-flow processes, estimating hydrogeologic properties, and analyzing groundwater and surface-water interactions for the Big Sioux aquifer near Sioux Falls, S. Dak. The numerical model can be used to simulate hydrologic scenarios, advance understanding of groundwater budgets, compute system response to stress, and determine likely sources of water supplied to wells.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195117","collaboration":"Prepared in cooperation with the city of Sioux Falls","usgsCitation":"Davis, K.W., Eldridge, W.G., Valder, J.F., and Valseth, K.J., 2019, Groundwater-flow model and analysis of groundwater and surface-water interactions for the Big Sioux aquifer, Sioux Falls, South Dakota: U.S. Geological Survey Scientific Investigations Report 2019–5117, 86 p., https://doi.org/10.3133/sir20195117.","productDescription":"Report: xi, 86 p.; Data Release","numberOfPages":"102","onlineOnly":"Y","ipdsId":"IP-105956","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":369602,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20195013","text":"SIR 2019–5013","linkHelpText":"– Hydraulic conductivity estimates from slug tests in the Big Sioux aquifer near Sioux Falls, South Dakota"},{"id":369600,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim3393","text":"SIM 3393","linkHelpText":"– Delineation of the hydrogeologic framework of the Big Sioux aquifer near Sioux Falls, South Dakota, using airborne electromagnetic data"},{"id":369601,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/F79885XC","text":"USGS data release for SIM 3393","linkHelpText":"– Airborne electromagnetic and magnetic survey data, Big Sioux aquifer, October 2015, Sioux Falls, South Dakota"},{"id":369603,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/P9LUB44J","text":"USGS data release for SIR 2019–5013","linkHelpText":"– Water-level data and AQTESOLV Pro analysis results for slug tests in the Big Sioux Aquifer, Sioux Falls, South Dakota, 2017"},{"id":369535,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5117/coverthb.jpg"},{"id":369536,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5117/sir20195117.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5117"},{"id":369537,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O59RO0","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-6 model of the Big Sioux aquifer, Sioux Falls, South Dakota"}],"country":"United States","state":"South Dakota","city":"Sioux Falls","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.06146240234375,\n 43.29919735147067\n ],\n [\n -96.42425537109375,\n 43.29919735147067\n ],\n [\n -96.42425537109375,\n 43.757208878849376\n ],\n [\n -97.06146240234375,\n 43.757208878849376\n ],\n [\n -97.06146240234375,\n 43.29919735147067\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
A Decree of the Supreme Court of the United States, entered June 7, 1954, established the position of Delaware River Master within the U.S. Geological Survey. In addition, the Decree authorizes diversion of water from the Delaware River Basin and requires compensating releases from certain reservoirs, owned by New York City, to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master will furnish reports to the Court, not less frequently than annually. This report is the 57th Annual Report of the River Master of the Delaware River. It covers the 2010 River Master report year, the period from December 1, 2009, to November 30, 2010.
During the report year, precipitation in the upper Delaware River Basin was 49.38 inches or 112 percent of the long-term average. Combined storage in Pepacton, Cannonsville, and Neversink Reservoirs remained high much of the year and did not decline below 80 percent of combined capacity until September 2010. A lower basin drought warning was issued by the Delaware River Basin Commission on September 24, 2010. It automatically ended on October 31, 2010, when the reservoir contents rose above drought levels, due in large part to heavy rainfall during the last week of September. River Master operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Program.
Diversions from the Delaware River Basin by New York City and New Jersey were in full compliance with the Decree. Reservoir releases were made as directed by the River Master at rates designed to meet the flow objective for the Delaware River at Montague, New Jersey, on 81 days during the report year. Interim Excess Release Quantity and conservation releases, designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs, were made during the report year.
The quality of water in the Delaware Estuary between Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at various locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191093","usgsCitation":"Russell, K.L., Ockerman, D., Krejmas, B.E., Paulachok, G.N., and Mason, R.R., Jr., 2019, Report of the River Master of the Delaware River for the period December 1, 2009–November 30, 2010: U.S. Geological Survey Open-File Report 2019–1093, 128 p., https://doi.org/10.3133/ofr20191093.","productDescription":"x, 128 p.","numberOfPages":"142","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-099205","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":369615,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1093/ofr20191093.pdf","text":"Report","size":"3.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1093"},{"id":368735,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1093/coverthb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.278076171875,\n 39.32579941789298\n ],\n [\n -74.608154296875,\n 39.32579941789298\n ],\n [\n -74.608154296875,\n 42.68243539838623\n ],\n [\n -76.278076171875,\n 42.68243539838623\n ],\n [\n -76.278076171875,\n 39.32579941789298\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Deputy Delaware River Master
Office of the Delaware River Master
U.S. Geological Survey
120 Route 209 South
Milford, PA 18337
The main purpose of this study was to demonstrate the utility of the sediment fingerprinting approach to apportion surface-derived sediment, and then age date that portion using short-lived fallout radionuclides. In systems where a large mass of mobile sediment is in channel storage, age dating provides an understanding of the transfer of sediment through the watershed and the time scales over which management actions to reduce sediment loadings may be effective.
In the agricultural Walnut Creek watershed, Iowa, the sediment-fingerprinting approach with elemental analysis was used to apportion the sources of fine-grained sediment (croplands, prairie, unpaved roads, and channel banks). Fallout radionuclides (7Be, 210Pbex) were used to age the portion of suspended sediment that was derived from agricultural topsoil. Age dating was performed at two different scales: 210Pbex which can date sediment to ~ 85 years and 7Be to ~ 1 year.
Sediment fingerprinting results indicated that the majority of suspended sediment is derived from cropland (62%) with streambanks contributing 36%, and prairie, pasture, and unpaved roads each contributing ≤ 1%. The topsoil–derived portion of sediment (primarily agriculture) dated using 210Pbex has ages ranging from 1 to 58 years, and using 7Be, a component of much younger sediment that yields ages ranging from 44 to 205 days. The occurrence of 7Be indicates that some portion of the sediment is young, on the order of months, whereas the dating based on 210Pbex indicates that some of the surface-derived sediment has been in channel storage for decades. Published studies in Walnut Creek indicate that a large component of sediment is stored in the channel bed.
We conclude that the 210Pbex-based ages are a reasonable estimate for the mean age of the surface-derived fraction and that 7Be activities are evidence that there is a smaller fraction of very young sediment in the stream. We propose a geomorphic model where agricultural soil is delivered to the channel and conveyed to the watershed outlet at three time scales: a geologic-millennial time scale, decades, and a young time scale (< 1 year).
","language":"English","publisher":"Springer","doi":"10.1007/s11368-018-2168-z","usgsCitation":"Gellis, A.C., Fuller, C.C., Van Metre, P.C., Filstrup, C.T., Cole, K., and Sabitov, T., 2019, Combining sediment fingerprinting with age-dating sediment using fallout radionuclides for an agricultural stream, Walnut Creek, Iowa, USA: Journal of Soils and Sediments, v. 19, p. 3374-3396, https://doi.org/10.1007/s11368-018-2168-z.","productDescription":"23 p.","startPage":"3374","endPage":"3396","ipdsId":"IP-090014","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":377887,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","county":"Jasper County","otherGeospatial":"Walnut Creek","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-93.234,41.8622],[-93.1187,41.8624],[-93.0035,41.8624],[-92.8845,41.8619],[-92.7674,41.8618],[-92.7683,41.776],[-92.768,41.6879],[-92.7683,41.6007],[-92.7567,41.6011],[-92.7564,41.509],[-92.8729,41.5082],[-92.9894,41.5083],[-93.1047,41.5078],[-93.2181,41.5076],[-93.3304,41.5074],[-93.3314,41.6004],[-93.3504,41.6004],[-93.3496,41.688],[-93.3494,41.7757],[-93.3492,41.8624],[-93.234,41.8622]]]},\"properties\":{\"name\":\"Jasper\",\"state\":\"IA\"}}]}","volume":"19","noUsgsAuthors":false,"publicationDate":"2018-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":797341,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Metre, Peter C. 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":211144,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Filstrup, Christopher T.","contributorId":169032,"corporation":false,"usgs":false,"family":"Filstrup","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":797343,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cole, Kevin","contributorId":208183,"corporation":false,"usgs":false,"family":"Cole","given":"Kevin","email":"","affiliations":[{"id":37761,"text":"USDA-ARS, National Laboratory for Agriculture and the Environment, 1015 N. University Blvd, Ames. IA 50011","active":true,"usgs":false}],"preferred":false,"id":797344,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sabitov, Timur","contributorId":236885,"corporation":false,"usgs":false,"family":"Sabitov","given":"Timur","email":"","affiliations":[{"id":47559,"text":"Geology and Geophysics, Academy of Science of Uzbekistan","active":true,"usgs":false}],"preferred":false,"id":797345,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70209462,"text":"70209462 - 2019 - Watershed geomorphology modifies the sensitivity of aquatic ecosystem metabolism to temperature","interactions":[],"lastModifiedDate":"2020-05-04T17:57:42.379102","indexId":"70209462","displayToPublicDate":"2019-11-26T07:58:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Watershed geomorphology modifies the sensitivity of aquatic ecosystem metabolism to temperature","docAbstract":"How carbon cycles are regulated by environmental temperature remains a substantial uncertainty in our understanding of how watersheds will respond to ongoing climate change. Aquatic ecosystems are important components of carbon flux to the atmosphere and ocean, yet we have limited understanding of how temperature modifies ecosystem metabolic processes and, therefore, aquatic contributions to carbon cycles at watershed to global scales. We propose that geomorphology controls the landscape-scale distribution and quality of organic material that forms the metabolic base of aquatic ecosystems and, therefore, how aquatic ecosystem metabolism responds to changes in temperature. Across 23 streams and four years in a boreal river basin, we estimated how temperature sensitivity of ecosystem respiration (ER) varied among streams draining watersheds with different geomorphic characteristics. We found that geomorphic conditions imposed strong ultimate controls on temperature sensitivity; ER in streams draining flat watersheds was up to six times more sensitive to temperature than streams draining steeper watersheds. Further, we show that the link between watershed geomorphology and temperature sensitivity of ER was related to the quality of carbon substrates that changes systematically across the gradient in geomorphic conditions. These results suggest that geomorphology will ultimately control how carbon is transported, stored, and incorporated into river food webs as climate warms.","language":"English","publisher":"Nature","doi":"10.1038/s41598-019-53703-3","collaboration":"","usgsCitation":"Jankowski, K.J., and Schindler, D., 2019, Watershed geomorphology modifies the sensitivity of aquatic ecosystem metabolism to temperature: Scientific Reports, v. 9, 17619, 10 p., https://doi.org/10.1038/s41598-019-53703-3.","productDescription":"17619, 10 p.","ipdsId":"IP-102157","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":459115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-019-53703-3","text":"Publisher Index Page"},{"id":373857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2019-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Jankowski, Kathi Jo 0000-0002-3292-4182","orcid":"https://orcid.org/0000-0002-3292-4182","contributorId":207429,"corporation":false,"usgs":true,"family":"Jankowski","given":"Kathi","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":786569,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schindler, Daniel E.","contributorId":223885,"corporation":false,"usgs":false,"family":"Schindler","given":"Daniel E.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":786570,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204598,"text":"sir20195071 - 2019 - Pecos River Basin salinity assessment, Santa Rosa Lake, New Mexico, to the confluence of the Pecos River and the Rio Grande, Texas, 2015","interactions":[],"lastModifiedDate":"2019-11-26T06:25:41","indexId":"sir20195071","displayToPublicDate":"2019-11-25T16:39:51","publicationYear":"2019","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":"2019-5071","displayTitle":"Pecos River Basin Salinity Assessment, Santa Rosa Lake, New Mexico, to the Confluence of the Pecos River and the Rio Grande, Texas, 2015","title":"Pecos River Basin salinity assessment, Santa Rosa Lake, New Mexico, to the confluence of the Pecos River and the Rio Grande, Texas, 2015","docAbstract":"The elevated salinity of the Pecos River throughout much of its length is of paramount concern to water users and water managers. Dissolved-solids concentrations in the Pecos River exceed 3,000 milligrams per liter in many of its reaches in the study area, from Santa Rosa Lake, New Mexico, to the confluence of the Pecos River with the Rio Grande, Texas. The salinity of the Pecos River increases downstream and affects the availability of useable water in the Pecos River Basin. In this report, “salinity” and “dissolved-solids concentration” are considered synonymous; both terms are used to refer to the total ionic concentration of dissolved minerals in water. The sources of salinity in the Pecos River Basin are natural (geologic) and anthropogenic, including but not limited to groundwater discharge, springs, and irrigation return flows. Previous studies in the Pecos River Basin were project specific and designed to address salinity issues in specific parts of the basin; therefore, in 2015, the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers, New Mexico Interstate Stream Commission, Texas Commission on Environmental Quality, and Texas Water Development Board assessed the major sources of salinity throughout the extent of the basin where elevated salinity in the Pecos River is well documented (that is, in the drainage area of the Pecos River from Santa Rosa Lake to the confluence of the Pecos River and the Rio Grande). The goal was to gain a better understanding of how specific areas might be contributing to the elevated salinity in the Pecos River and how salinity of the Pecos River has changed over time. This assessment includes a literature review and compilation of previously published salinity-related data, which guided the collection of additional water-quality samples and streamflow gain-loss measurements. Differences in water quality of surface-water and groundwater samples, streamflow measurements, and geophysical data were assessed to gain new insights regarding sources of salinity in the Pecos River Basin and a more detailed assessment of potential areas of elevated salinity in the basin. The datasets compiled for this assessment are available in a companion data release.
The literature review identified several potential sources of salinity inputs to the Pecos River in New Mexico and Texas. In New Mexico, sources of salinity inputs included sinkhole springs discharging into El Rito Creek, the Bitter Lake National Wildlife Refuge inflow to the Pecos River, inflow from the Rio Hondo, including the main channel and a restored channel at the Bitter Lake National Wildlife Refuge referred to as the “Rio Hondo spring channel,” the outflow from Lea Lake at Bottomless Lakes State Park, and the Malaga Bend region of the Pecos River. In Texas, sources of salinity inputs included Salt Creek downstream from Red Bluff Reservoir and the area near the Horsehead Crossing ford on the Pecos River.
The compilation of historical water-quality data revealed a lack of consistent sampling of the same constituents at the same sites along the main stem of the Pecos River, which results in data gaps that hinder the ability to effectively analyze long-term changes in water quality that may help with the understanding of how salinity in the Pecos River has changed over time and identifying the sources of salinity in the Pecos River Basin. To help fill these data gaps, water-quality and streamflow data were collected in the study area in February 2015 by the U.S. Geological Survey. Historical water-quality data and newly collected data from February 2015 were evaluated for selected major-ion concentrations, dissolved-solids concentrations, and deuterium, oxygen, and strontium isotopes. Analysis of the data indicated several areas of increasing salinity in the Pecos River. Most notable increases were in two subreaches of the river, between Acme, N. Mex., and Artesia, N. Mex., and between Orla, Tex., and Grandfalls, Tex. Increasing sodium and chloride concentrations from Acme to Artesia coincided with changes in isotopic ratios within the Pecos River Basin. Changes in isotopic ratios in this reach indicate a likely inflow from an isotopically different source of water compared to the water in the main stem of the Pecos River, such as groundwater inflow, inflow from surface-water features distinct from the main stem of the Pecos River, or both. In the subreach between Orla and Grandfalls, an increase in dissolved-solids concentrations was observed along with a shift in isotope values, indicating that neither evaporative processes in Red Bluff Reservoir nor inflow from Salt Creek likely solely influences the salinity of the Pecos River in this subreach. The highest dissolved-solids concentrations in the Pecos River Basin were measured downstream from Grandfalls, where dissolved-solids concentrations are greater than 16,000 milligrams per liter near Iraan, Tex. Changes in isotopic values (deuterium, oxygen, and strontium) indicate mixing of different waters at several areas along the main stem of the Pecos River. The spatial distribution of the areas of interest from the literature review and the water-quality data are available in the companion data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195071","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, New Mexico Interstate Stream Commission, Texas Commission on Environmental Quality, and Texas Water Development Board","usgsCitation":"Houston, N.A., Thomas, J.V., Ging, P.B., Teeple, A.P., Pedraza, D.E., and Wallace, D.S., 2019, Pecos River Basin salinity assessment, Santa Rosa Lake, New Mexico, to the confluence of the Pecos River and the Rio Grande, Texas, 2015: U.S. Geological Survey Scientific Investigations Report 2019–5071, 75 p., https://doi.org/10.3133/sir20195071.","productDescription":"Report: xi, 75 p.; Data Release","numberOfPages":"91","onlineOnly":"Y","ipdsId":"IP-083306","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":369530,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DB800T","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water Quality, Streamflow Gain Loss, Geologic, and Geospatial Data Used in the Pecos River Basin Salinity Assessment from Santa Rosa Lake, New Mexico to the Confluence of the Pecos River and the Rio Grande, Texas, 1900–2015"},{"id":369528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5071/coverthb.jpg"},{"id":369529,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5071/sir20195071.pdf","text":"Report","size":"9.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5071"}],"country":"United States","state":"Texas, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.39257812499999,\n 29.916852233070173\n ],\n [\n -101.162109375,\n 29.305561325527698\n ],\n [\n -100.1513671875,\n 30.826780904779774\n ],\n [\n -99.97558593749999,\n 32.32427558887655\n ],\n [\n -101.9970703125,\n 33.797408767572485\n ],\n [\n -103.5791015625,\n 34.74161249883172\n ],\n [\n -105.0732421875,\n 35.567980458012094\n ],\n [\n -106.787109375,\n 36.38591277287651\n ],\n [\n -107.22656249999999,\n 35.53222622770337\n ],\n [\n -107.6220703125,\n 34.34343606848294\n ],\n [\n -105.908203125,\n 32.62087018318113\n ],\n [\n -102.39257812499999,\n 29.916852233070173\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
From 2015 through 2017, the U.S. Geological Survey in cooperation with the New Hampshire Department of Health and Human Services and the New Hampshire Department of Environmental Services studied occurrences of high levels of Escherichia coli (E. coli) bacteria at the Pawtuckaway State Park Beach in Nottingham, New Hampshire. Historic data collected by the New Hampshire Department of Environmental Services indicated that E. coli concentrations in the water typically increased through the beach season to levels considered potentially harmful to beachgoers. During the three beach seasons that were studied, E. coli samples were collected three to four times per week, and water-quality and meteorological data were collected continuously. The Virtual Beach software was used to generate a predictive model for each year of the study (2015–2017), and the model for each of these years was tested with data from the other two. Additionally, data from all study years were combined to generate a comprehensive model to help identify independent variables that might characterize environmental conditions relative to E. coli levels during multiple seasons. The accuracy of the models in predicting the occurrence of high E. coli levels was marginal, but the models did provide insights into the likely mechanisms for increased E. coli levels during the seasons. Variables most important in explaining high E. coli levels were the presence of geese at the beach, the progression of the season, the number of visitors at the beach, and wind vectors relative to beach orientation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195111","collaboration":"Prepared in cooperation with the New Hampshire Department of Health and Human Services and the New Hampshire Department of Environmental Services","usgsCitation":"Coles, J.F., and Bush, K.F., 2019, Evaluating associations between environmental variables and Escherichia coli levels for predictive modeling at Pawtuckaway Beach in Nottingham, New Hampshire, from 2015 to 2017: U.S. Geological Survey Scientific Investigations Report 2019–5111, 28 p., https://doi.org/10.3133/sir20195111.","productDescription":"Report: vii, 28 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101776","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":369290,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5111/coverthb.jpg"},{"id":369288,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5cc70bf4e4b09b8c0b77e5b7","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Data collected at Pawtuckaway Beach in Nottingham, New Hampshire, 2015–2017"},{"id":369409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5111/sir20195111.pdf","text":"Report","size":"4.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5111"}],"country":"United States","state":"New Hampshire","city":"Nottingham","otherGeospatial":"Pawtuckaway Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.1595630645752,\n 43.08080002811761\n ],\n [\n -71.14797592163086,\n 43.08080002811761\n ],\n [\n -71.14797592163086,\n 43.08650455068649\n ],\n [\n -71.1595630645752,\n 43.08650455068649\n ],\n [\n -71.1595630645752,\n 43.08080002811761\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
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331 Commerce Way, Suite 2
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As much as 22 inches of rain fell in Oklahoma in May 2019, resulting in historic flooding along the Arkansas River in Oklahoma and Arkansas. The flooding along the Arkansas River and its tributaries that began in May continued into June 2019. Peaks of record were measured at 12 U.S. Geological Survey (USGS) streamgages on various streams in eastern and northeastern Oklahoma. This report documents the peak streamflows and stages for seven selected streamgages along the Arkansas River in Oklahoma and Arkansas. Most of the flood peaks occurred from May 26 to June 4, 2019. The historic flooding caused homes to fall into the river as a result of bank erosion, forced some towns to be evacuated, and resulted in the highest flood depths in Tulsa, Oklahoma, since 1986. Along the Arkansas River, peak streamflows were recorded at six of the seven selected USGS streamgages, with the seventh streamgage on the Arkansas River having the second highest peak of record at that site since regulation began.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191129","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency and the U.S. Army Corps of Engineers","usgsCitation":"Lewis, J.M., and Trevisan, A.R., 2019, Peak streamflow and stages at selected streamgages on the Arkansas River in Oklahoma and Arkansas, May to June 2019: U.S. Geological Survey Open-File Report 2019–1129, 10 p., https://doi.org/10.3133/ofr20191129.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-112483","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":369335,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1129/ofr20191129.pdf","text":"Report","size":"4.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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\"}}]}","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
Red tree corals (Primnoa pacifica) are abundant in the eastern Gulf of Alaska, from the glacial fjords of Southeast Alaska where they emerge to as shallow as 6 m, to the continental shelf edge and seamounts where they are more commonly found at depths greater than 150 – 500 m. This keystone species forms large thickets, creating habitat for many associated species, including economically valuable fishes and crabs, and so are important benthic suspension feeders in this region. Though the reproductive periodicity of this species was reported in 2014 from a shallow fjord (Tracy Arm), this study examined reproductive ecologies from 8 sites – two within Glacier Bay National Park and Preserve, three on the continental shelf edge, one within Endicott Arm (Holkham Bay) and two time points from the Tracy Arm (Holkham Bay) study. Male reproductive traits were similar at all sites but there were distinct differences in oogenesis. Though per polyp fecundity mostly showed no significant difference between sites, there was a non-significant trend of increasing number of oocytes with depth. In addition, the average oocyte size from Tracy Arm (the shallowest site) was 105 μm, whereas from Shutter Ridge (one of the deepest sites) the average size was 309 μm. Moreover, the maximum oocyte size at Endicott Arm was 221 μm and at Tracy Arm was 802 μm (both shallow sites), whereas at Dixon Entrance (a deep site) it was 2120 μm, a difference not usually observed within a single species. We propose two theories to explain the observed differences, (a) this species shows great phenotypic plasticity in reproductive ecology, adjusting to different environmental variables based on energetic need and potentially demonstrating micro-evolution; or (b) the fjord sites are at a reproductive dead end, with the stress of shallow-water conditions effectively preventing gametogenesis reaching full potential and likely limiting successful reproductive events from occurring, at least on a regular basis.
Large-scale assessments of rangeland runoff and erosion require methods to extend plot-scale parameterizations to large areas. In this study, Rangeland Hydrology and Erosion Model (RHEM) parameters were developed from plot-scale foliar and ground-cover transect data for an arid, grass-shrub rangeland in southern New Mexico, and a method was assessed to upscale transect-plot parameters to a large landscape. The transect-plot data compared favorably to corresponding cell data generated from publicly available geospatial data for total foliar cover but less favorably for litter cover and poorly for rock cover. The RHEM effective hydraulic conductivity (Ke) parameter was comparable between transect-plot and geospatial-cell methods, but the splash and sheet erosion factor (Kss) had poor agreement between the two methods. Simulated runoff and erosion reflected differences in transect-plot and geospatial-cell-based RHEM parameterizations, with low error and very good agreement for runoff but high error and poor agreement for soil loss. These results demonstrate that Ke parameters developed using geospatial data calibrated to plot data can be extrapolated to large spatial areas and provide reasonable simulation of runoff using RHEM. However, these same geospatial methods do not provide reasonable estimation of Kss or simulation of soil loss. Poor representation of litter and rock cover variables, which are highly spatially heterogeneous at the plot scale, was inadequate to accurately represent Kss or soil loss using RHEM. High resolution ground cover data, such as from unmanned aerial systems, may improve parameterization of Kss, and, ultimately, arid rangeland soil erosion simulation.
","language":"English","publisher":"American Society of Agricultural and Biological Engineers","doi":"10.13031/aea.13275","usgsCitation":"Ball, G., and Douglas-Mankin, K., 2019, Geospatial scaling of runoff and erosion modeling in the Chihuahuan Desert: Applied Engineering in Agriculture, v. 5, no. 35, p. 733-743, https://doi.org/10.13031/aea.13275.","productDescription":"11 p.","startPage":"733","endPage":"743","ipdsId":"IP-104120","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":369346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Chihuahuan Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.732421875,\n 34.88593094075317\n ],\n [\n -105.13916015625,\n 33.60546961227188\n ],\n [\n -105.2490234375,\n 32.861132322810946\n ],\n [\n -105.75439453125,\n 32.491230287947594\n ],\n [\n -106.9189453125,\n 34.34343606848294\n ],\n [\n -107.1826171875,\n 33.970697997361626\n ],\n [\n -107.698974609375,\n 32.80574473290688\n ],\n [\n -109.09423828125,\n 33.19273094190692\n ],\n [\n -109.10522460937499,\n 31.325486676506983\n ],\n [\n -108.226318359375,\n 31.325486676506983\n ],\n [\n -108.204345703125,\n 31.774877618507386\n ],\n [\n -106.578369140625,\n 31.765537409484374\n ],\n [\n -106.644287109375,\n 31.970803930433096\n ],\n [\n -103.11767578124999,\n 32.01739159980399\n ],\n [\n -103.084716796875,\n 34.994003757575776\n ],\n [\n -105.732421875,\n 34.88593094075317\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"35","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ball, Grady 0000-0003-3030-055X","orcid":"https://orcid.org/0000-0003-3030-055X","contributorId":220746,"corporation":false,"usgs":true,"family":"Ball","given":"Grady","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":775597,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Douglas-Mankin, Kyle R. 0000-0002-3155-3666","orcid":"https://orcid.org/0000-0002-3155-3666","contributorId":200849,"corporation":false,"usgs":false,"family":"Douglas-Mankin","given":"Kyle R.","affiliations":[],"preferred":false,"id":775598,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206053,"text":"sim3444 - 2019 - Potentiometric surface of groundwater-level altitudes near the planned Highway 270 bypass, east of Hot Springs, Arkansas, July–August 2017","interactions":[],"lastModifiedDate":"2019-11-19T17:19:14","indexId":"sim3444","displayToPublicDate":"2019-11-19T13:49:10","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3444","displayTitle":"Potentiometric Surface of Groundwater-Level Altitudes Near the Planned Highway 270 Bypass, East of Hot Springs, Arkansas, July–August 2017","title":"Potentiometric surface of groundwater-level altitudes near the planned Highway 270 bypass, east of Hot Springs, Arkansas, July–August 2017","docAbstract":"The Ouachita Mountains aquifer system potentiometric-surface map is one component of the Hot Springs Bypass Groundwater Monitoring Project. The potentiometric-surface map provides a baseline assessment of shallow groundwater levels and flow directions before the construction of the Arkansas Department of Transportation planned extension of the Highway 270 bypass, east of Hot Springs, Arkansas. The map provides data regarding status of groundwater levels and potential effects on the recharge area in the Hot Springs National Park and to groundwater that supplies water to domestic users near the Highway 270 bypass.
Groundwater levels from 66 wells were measured in July–August 2017. Fifty nine of the 66 groundwater-level altitudes measured, along with select surface-water features and springs, were used to construct the Ouachita Mountains aquifer system potentiometric-surface map. The potentiometric surface, a two-dimensional representation, shows groundwater-level altitudes ranging from a maximum of 766 ft above the North American Vertical Datum of 1988 (NAVD 88) to a minimum of 443 ft NAVD 88. The spring altitudes on the potentiometric-surface map range from 534 ft to 927 ft above NAVD 88. The study area, located in the Ouachita Mountains physiographic section of the Ouachita physiographic province, comprises narrow valleys and high ridges of Stanley Shale, Hot Springs Sandstone, Arkansas Novaculite, Missouri Mountain-Polk Creek Shale, and Bigfork Chert. The highest groundwater-level altitudes observed were in the Hot Springs Sandstone, Arkansas Novaculite, and Missouri Mountain-Polk Creek Shale. The springs discharge in outcrop areas of the Stanley Shale, Bigfork Chert, and Arkansas novaculite. The planned Highway 270 bypass will cut across ridges and valleys comprising these formations and, very importantly, across areas with elevations above 660 ft above NAVD 88 that define the hot springs recharge zone.
This potentiometric-surface map defines the status of the shallow groundwater potentiometric surface near the Highway 270 bypass prior to initiation of construction activities. A post-construction potentiometric map is planned. It must be noted that shallow groundwater levels are also subject to climatic effects including changes in amount and timing of precipitation and changes in temperature.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3444","collaboration":"Prepared in cooperation with the Arkansas Department of Transportation and the National Park Service","usgsCitation":"Nottmeier, A.M., and Hays, P.D., 2019, Potentiometric surface of groundwater-level altitudes near the planned Highway 270 bypass, east of Hot Springs, Arkansas, July–August 2017: U.S. Geological Survey Scientific Investigations Map 3444, 13 p., 1 sheet, https://doi.org/10.3133/sim3444.","productDescription":"Pamphlet: v, 13 p.; Sheet: 22 x 28 inches; Data Release","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092242","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":369331,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TD9WK0","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"Datasets of the Potentiometric Surface of Groundwater-Level Altitudes Near the Planned Highway 270 Bypass, East of Hot Springs, Arkansas, July–August 2017"},{"id":369328,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3444/coverthb.jpg"},{"id":369329,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3444/sim3444.pdf","text":"Sheet ","size":"2.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3444 ","linkHelpText":"– Potentiometric-surface map for the Ouachita Mountains aquifer, July–August 2017"},{"id":369330,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3444/sim3444_pamphlet.pdf","text":"Pamphlet","size":"3.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3444 Pamphlet"}],"country":"United States","state":"Arkansas","county":"Garland County","city":"Hot Springs","otherGeospatial":"Highway 270 Bypass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.01935195922852,\n 34.50542493789137\n ],\n [\n -92.94931411743164,\n 34.50542493789137\n ],\n [\n -92.94931411743164,\n 34.5710371883746\n ],\n [\n -93.01935195922852,\n 34.5710371883746\n ],\n [\n -93.01935195922852,\n 34.50542493789137\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
This field guide explores volcanic effusions, sediments, and landforms at Mount St. Helens in Washington. A detailed synopsis outlines the eruptive history of Mount St. Helens from about 300,000 years ago through 1980 and beyond.
The five days in the field include about 28 stops and 12 potential stops. Exposures in valleys surrounding Mount St. Helens reveal records of diverse Pleistocene and Holocene processes including debris avalanche, lahar, huge water wave on a nearby lake, pyroclastic density currents (surge and flow), tephra fall, lava flow, the growth of domes, and Pleistocene glaciation. Many of the stops explore effects of the several catastrophes that constituted the 18 May 1980 eruption and made Mount St. Helens famous.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175022E","usgsCitation":"Waitt, R.B., Major, J.J., Hoblitt, R.P., Van Eaton, A.R., and Clynne, M.A., 2019, Field trip guide to Mount St. Helens, Washington—Recent and ancient volcaniclastic processes and deposits: U.S. Geological Survey Scientific Investigations Report 2017–5022–E, 68 p., https://doi.org/10.3133/sir20175022E.","productDescription":"xii, 68 p.","numberOfPages":"84","onlineOnly":"Y","ipdsId":"IP-076026","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":369261,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5022/e/coverthb.jpg"},{"id":369262,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5022/e/sir20175022E.pdf","text":"Report","size":"53.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5022–E"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.38494873046875,\n 46.12274903582433\n ],\n [\n -122.01141357421875,\n 46.12274903582433\n ],\n [\n -122.01141357421875,\n 46.3886223381617\n ],\n [\n -122.38494873046875,\n 46.3886223381617\n ],\n [\n -122.38494873046875,\n 46.12274903582433\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025