In 2006, the U.S. Geological Survey (USGS), in
cooperation with the Texas Department of Transportation,
began collecting annual and approximately quarterly series
peak-streamflow data at streamflow-gaging stations in smallto
medium-sized watersheds in central and western Texas
as part of a crest-stage gage (CSG) network, along with
selected flood-hydrograph data at a subset of these stations.
CSGs record the peak stage during storm events, which is
the maximum gage height (elevation of water surface above
a local vertical datum), at each CSG station. Established and
widely used indirect methods of peak streamflow estimation
and interpretation, such as culvert-flow, slope-area, and
flow-over-road methods, are used in conjunction with peak
gage height data to create the database of peak streamflow
described herein. The CSG network is focused on hydrology
of small- to medium-sized watersheds in central and western
Texas because additional streamflow data for this semiarid
to arid study area will eventually provide for more statistical
information and presumably reduced uncertainty in regional
regression equations or other regionalized statistical methods
for peak-streamflow frequency estimation at ungaged
locations. The database of annual and approximately quarterly
peak streamflow is published through USGS ScienceBase and
described in this report.
Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
Consistent relations between shallow landslide initiation and associated rainfall characteristics remain difficult to identify, due largely to the complex hydrological and geological processes causing slopes to be predisposed to failure and those processes that subsequently trigger failures. Considering the importance of hillslope hydrology for rainfall-induced landsliding, we develop and test a method for identifying hybrid hydro-meteorological thresholds to assess landslide initiation potential. We outline a series of steps for using a landslide inventory in combination with triggering rainfall and antecedent wetness to identify empirical thresholds that can inform landslide early warning systems. The method is semi-automated but remains flexible enough to allow threshold developers to consider data inputs and various performance metrics with different priorities for balancing failed versus false alarms. We demonstrate the utility of our approach for two monitoring sites near Seattle, Washington and in Portland, Oregon, USA, to develop daily bilinear thresholds within a two-dimensional parameter space, which rely on accurate 24 h forecasts, measured recent rainfall and in situ soil saturation. Although there were no prior landslide thresholds for Portland, our new hybrid threshold for the Seattle area outperforms established rainfall-only thresholds for the same region. Introducing subsurface hydrologic monitoring into landslide initiation thresholds has the potential to greatly improve early warning capabilities and help reduce losses.
","language":"English","publisher":"MDPI","doi":"10.3390/w10091274","usgsCitation":"Mirus, B.B., Morphew, M.D., and Smith, J.B., 2018, Developing hydro-meteorological thresholds for shallow landslide initiation and early warning: Water, v. 10, no. 9, p. 1-19, https://doi.org/10.3390/w10091274.","productDescription":"Article 1274; 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-101411","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468392,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w10091274","text":"Publisher Index Page"},{"id":357440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7367,\n 45.5217\n ],\n [\n -122.7333,\n 45.5217\n ],\n [\n -122.7333,\n 45.5233\n ],\n [\n -122.7367,\n 45.5233\n ],\n [\n -122.7367,\n 45.5217\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.34100341796875,\n 47.874907453605935\n ],\n [\n -122.31628417968749,\n 47.874907453605935\n ],\n [\n -122.31628417968749,\n 47.892866512069666\n ],\n [\n -122.34100341796875,\n 47.892866512069666\n ],\n [\n -122.34100341796875,\n 47.874907453605935\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-18","publicationStatus":"PW","scienceBaseUri":"5bc02f9ce4b0fc368eb538f7","contributors":{"authors":[{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":745347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morphew, Michael D. 0000-0003-0072-1652","orcid":"https://orcid.org/0000-0003-0072-1652","contributorId":207959,"corporation":false,"usgs":false,"family":"Morphew","given":"Michael","email":"","middleInitial":"D.","affiliations":[{"id":37668,"text":"USGS, Student- Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":745348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Joel B. 0000-0001-7219-7875 jbsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-7219-7875","contributorId":4925,"corporation":false,"usgs":true,"family":"Smith","given":"Joel","email":"jbsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":745349,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199446,"text":"70199446 - 2018 - Decadal topographic change in the McMurdo Dry Valleys of Antarctica: Thermokarst subsidence, glacier thinning, and transfer of water storage from the cryosphere to the hydrosphere","interactions":[],"lastModifiedDate":"2018-09-18T13:35:39","indexId":"70199446","displayToPublicDate":"2018-09-18T13:35:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Decadal topographic change in the McMurdo Dry Valleys of Antarctica: Thermokarst subsidence, glacier thinning, and transfer of water storage from the cryosphere to the hydrosphere","docAbstract":"Recent local-scale observations of glaciers, streams, and soil surfaces in the McMurdo Dry Valleys of Antarctica (MDV) have documented evidence for rapid ice loss, glacial thinning, and ground surface subsidence associated with melting of ground ice. To evaluate the extent, magnitude, and location of decadal-scale landscape change in the MDV, we collected airborne lidar elevation data in 2014–2015 and compared these data to a 2001–2002 airborne lidar campaign. This regional assessment of elevation change spans the recent acceleration of warming and melting observed by long-term meteorological and ecosystem response experiments, allowing us to assess the response of MDV surfaces to warming and potential thawing feedbacks. We find that locations of thermokarst subsidence are strongly associated with the presence of excess ground ice and with proximity to surface or shallow subsurface (active layer) water. Subsidence occurs across soil types and landforms, in low-lying, low-slope areas with impeded drainage and also high on steep valley walls. Glacier thinning is widespread and is associated with the growth of fine-scale roughness. Pond levels are rising in most closed-basin lakes in the MDV, across all microclimate zones. These observations highlight the continued importance of insolation-driven melting in the MDV. The regional melt pattern is consistent with an overall transition of water storage from the local cryosphere (glaciers, permafrost) to the hydrosphere (closed basin lakes and ponds as well as the Ross Sea). We interpret this regional melting pattern to reflect a transition to Arctic and alpine-style, hydrologically mediated permafrost and glacial melt.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2018.09.012","usgsCitation":"Levy, J., Fountain, A., Obryk, M., Telling, J., Glennie, C., Pettersson, R., Gooseff, M., and van Horn, D., 2018, Decadal topographic change in the McMurdo Dry Valleys of Antarctica: Thermokarst subsidence, glacier thinning, and transfer of water storage from the cryosphere to the hydrosphere: Geomorphology, v. 323, p. 80-97, https://doi.org/10.1016/j.geomorph.2018.09.012.","productDescription":"18 p.","startPage":"80","endPage":"97","ipdsId":"IP-098526","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468393,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2018.09.012","text":"Publisher Index Page"},{"id":357438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"McMurdo Dry Valleys, Antarctica","volume":"323","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f9ce4b0fc368eb538f9","contributors":{"authors":[{"text":"Levy, J.S.","contributorId":207960,"corporation":false,"usgs":false,"family":"Levy","given":"J.S.","email":"","affiliations":[{"id":37669,"text":"Colgate University","active":true,"usgs":false}],"preferred":false,"id":745351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fountain, A.G.","contributorId":207961,"corporation":false,"usgs":false,"family":"Fountain","given":"A.G.","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":745352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Obryk, Maciej K. 0000-0002-8182-8656","orcid":"https://orcid.org/0000-0002-8182-8656","contributorId":203477,"corporation":false,"usgs":true,"family":"Obryk","given":"Maciej","middleInitial":"K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":745350,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Telling, J.","contributorId":207962,"corporation":false,"usgs":false,"family":"Telling","given":"J.","email":"","affiliations":[{"id":37670,"text":"National Center for Airborne Laser Mapping","active":true,"usgs":false}],"preferred":false,"id":745353,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glennie, C.","contributorId":207963,"corporation":false,"usgs":false,"family":"Glennie","given":"C.","affiliations":[{"id":37670,"text":"National Center for Airborne Laser Mapping","active":true,"usgs":false}],"preferred":false,"id":745354,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pettersson, R.","contributorId":207964,"corporation":false,"usgs":false,"family":"Pettersson","given":"R.","email":"","affiliations":[{"id":37671,"text":"Uppsala University","active":true,"usgs":false}],"preferred":false,"id":745355,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gooseff, M.","contributorId":201026,"corporation":false,"usgs":false,"family":"Gooseff","given":"M.","email":"","affiliations":[],"preferred":false,"id":745356,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"van Horn, D.J.","contributorId":207965,"corporation":false,"usgs":false,"family":"van Horn","given":"D.J.","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":745357,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70199232,"text":"fs20183060 - 2018 - Hydrologic conditions in Kansas, water year 2017","interactions":[],"lastModifiedDate":"2018-09-18T14:06:38","indexId":"fs20183060","displayToPublicDate":"2018-09-18T08:37:23","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3060","title":"Hydrologic conditions in Kansas, water year 2017","docAbstract":"The U.S. Geological Survey, in cooperation with Federal, State, and local agencies, maintains a long-term network of hydrologic monitoring stations in Kansas. 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","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183060","usgsCitation":"Lukasz, B.S., 2018, Hydrologic conditions in Kansas, water year 2017: U.S. Geological Survey Fact Sheet 2018–3060, 6 p., https://doi.org/10.3133/fs20183060.","productDescription":"6 p.","onlineOnly":"N","ipdsId":"IP-092067","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":357374,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3060/fs20183060.pdf","text":"Report","size":"14.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3060"},{"id":357373,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3060/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Dr.
Lawrence, KS 66049
Quantifying and understanding the natural streamflow regime, defined as expected streamflow that would occur in the absence of anthropogenic modification to the hydrologic system, is critically important for the development of management strategies aimed at protecting aquatic ecosystems. Water balance models have been applied frequently to estimate natural flows, but are limited in the number of predictor variables that can be included. Here, a statistical machine learning technique — random forest modeling — was applied to estimate natural flows at a monthly time‐step from 1950 to 2015 for >2.5 million stream reaches in the conterminous United States (U.S.) using 200 potential predictor variables. We describe the development and documentation of this dataset and assess model performance. Model fit statistics (mean Nash–Sutcliffe efficiency = 0.85; observed/expected ratio = 0.94) indicate good correspondence between predicted and observed flows at nearly 2,000 streamgages. As an example application of the dataset, the observed streamflow record at a site prior to and after the construction of an upstream reservoir was compared with estimated natural flows to demonstrate the magnitude of seasonal depletions in streamflow due to the reservoir. This dataset can be applied to quantify natural and anthropogenic processes contributing to streamflow depletion or augmentation, and assess associated ecological effects.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12685","usgsCitation":"Miller, M.P., Carlisle, D.M., Wolock, D.M., and Wieczorek, M., 2018, A database of natural monthly streamflow estimates from 1950 to 2015 for the conterminous United States: Journal of the American Water Resources Association, v. 54, no. 6, p. 1258-1269, https://doi.org/10.1111/1752-1688.12685.","productDescription":"12 p.","startPage":"1258","endPage":"1269","ipdsId":"IP-094353","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468395,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12685","text":"Publisher Index Page"},{"id":437752,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CC0ZMG","text":"USGS data release","linkHelpText":"Natural Monthly Flow Estimates for the Conterminous United States, 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\"}}]}","volume":"54","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-17","publicationStatus":"PW","scienceBaseUri":"5bc02f9de4b0fc368eb53903","contributors":{"authors":[{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":745157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlisle, Daren M. 0000-0002-7367-348X dcarlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-7367-348X","contributorId":513,"corporation":false,"usgs":true,"family":"Carlisle","given":"Daren","email":"dcarlisle@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":745158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":745159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wieczorek, Michael 0000-0003-0999-5457","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":207911,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":745160,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199412,"text":"70199412 - 2018 - Identifying physics‐based thresholds for rainfall‐induced landsliding","interactions":[],"lastModifiedDate":"2018-10-23T16:50:13","indexId":"70199412","displayToPublicDate":"2018-09-17T13:45:04","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Identifying physics‐based thresholds for rainfall‐induced landsliding","docAbstract":"Most regional landslide warning systems utilize empirically derived rainfall thresholds that are difficult to improve without recalibration to additional landslide events. To address this limitation, we explored the use of synthetic rainfall to generate thousands of possible storm patterns and coupled them with a physics‐based hydrology and slope stability model for various antecedent soil saturation scenarios to analyze pore‐water pressure and factor of safety metrics. We used these metrics to generate two‐tiered alert thresholds that can be employed to assess shallow landslide potential for any given combination of storm and antecedent wetness. When applied to the San Francisco Bay region (California, USA), the results are consistent with events that caused widespread landsliding. Our deterministic modeling approach, which accounts for plausible ranges in soil hydraulic and mechanical properties, can inform the development of the next generation of warning systems for rainfall‐induced landsliding.
","language":"English","publisher":"AGU","doi":"10.1029/2018GL079662","usgsCitation":"Thomas, M.A., Mirus, B.B., and Collins, B.D., 2018, Identifying physics‐based thresholds for rainfall‐induced landsliding: Geophysical Research Letters, v. 45, no. 18, p. 9651-9661, https://doi.org/10.1029/2018GL079662.","productDescription":"11 p.","startPage":"9651","endPage":"9661","ipdsId":"IP-099617","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468396,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gl079662","text":"Publisher Index Page"},{"id":357398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"18","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-26","publicationStatus":"PW","scienceBaseUri":"5bc02f9de4b0fc368eb53905","contributors":{"authors":[{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":745169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":745170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":745171,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197184,"text":"cir1440 - 2018 - Continuing progress toward a national assessment of water availability and use","interactions":[],"lastModifiedDate":"2022-04-22T16:20:30.384084","indexId":"cir1440","displayToPublicDate":"2018-09-12T09:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1440","displayTitle":"Continuing Progress Toward a National Assessment of Water Availability and Use","title":"Continuing progress toward a national assessment of water availability and use","docAbstract":"The Omnibus Public Land Management Act of 2009 (Public Law 111—11) was passed into law on March 30, 2009. Subtitle F, also known as the SECURE Water Act, calls for the establishment of a “national water availability and use assessment program” within the U.S. Geological Survey (USGS). The USGS issued the first report on the program in 2013. Program progress over the period 2013–17 is reported herein to fulfill the requirement to inform Congress on implementation of the national water availability and use assessment program, also referred to as the USGS National Water Census (the Water Census).
Much work has been accomplished during 2013–17 on producing water budgets for the nation, a goal USGS outlined in its first report on program progress to Congress. The USGS has completed three geographic focus area studies and has begun three others. Work has advanced on nationwide efforts in streamflow analysis, groundwater assessment and research, evapotranspiration studies, water use, environmental water science, and drought science. The USGS works with Federal and non-Federal agencies, universities, and other organizations to ensure that the information can be aggregated with other types of water-availability and socioeconomic information, such as data on food and energy production. The USGS has also made great strides in measures for delivering data and information on the Water Census to stakeholders and the public.
Much work remains to be accomplished for the Nation to have a comprehensive, ongoing Water Census. In this report, the USGS lays out activities to be accomplished in the next 5 years (2017–22), based upon current funding levels. These include selecting new focus area studies, conducting hydrologic modeling to complete water budgets for the conterminous United States, expanding groundwater modeling efforts, mapping a national classification system for environmental water science, and developing an inventory of interbasin water transfers. All of these steps are necessary in order for the Water Census to achieve the goals outlined by Congress in the SECURE Water Act.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1440","usgsCitation":"Evenson, E.J., Jones, S.A., Barber, N.L., Barlow, P.M., Blodgett, D.L., Bruce, B.W., Douglas-Mankin, K., Farmer, W.H., Fischer, J.M., Hughes, W.B., Kennen, J.G., Kiang, J.E., Maupin, M.A., Reeves, H.W., Senay, G.B., Stanton, J.S., Wagner, C.R., and Wilson, J.T., 2018, Continuing progress toward a national assessment of water availability and use: U.S. Geological Survey Circular 1440, 64 p., https://doi.org/10.3133/cir1440.","productDescription":"viii, 64 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088874","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":354392,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1440/circ1440.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"CIRC 1440"},{"id":354391,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1440/coverthb.jpg"}],"contact":"Coordinator—Water Availability and Use Science Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
While many studies on tribal water resources of individual tribal lands in the United States (US) have been conducted, the importance of tribal water resources at a national scale has largely gone unrecognized because their combined totals have not been quantified. Thus, we sought to provide a numerical estimate of major water budget components on tribal lands within the conterminous US and on USGS hydrologic unit codes (HUC2) regions. Using existing national-scale data and models, we estimated mean annual precipitation, evapotranspiration, excess precipitation, streamflow, and water use for the period 1971–2000. Tribal lands represent about 3.4 percent of the total land area of the conterminous US and on average account for 1.9 percent of precipitation, 2.4 percent of actual evapotranspiration, 0.95 percent of excess precipitation, 1.6 percent of water use, and 0.43 percent of streamflow origination. Additionally, approximately 9.5 and 11.3 percent of US streamflow flows through or adjacent as boundaries to tribal lands, respectively. Streamflow through or adjacent to tribal lands accounts for 42 and 48 percent of streamflow in the Missouri region, respectively; and for 86 and 88 percent in the Lower Colorado region, respectively. On average, 5,600 million cubic meters of streamflow per year was produced on tribal lands in the Pacific Northwest region, nearly five times greater than tribal lands in any other region. Tribal lands in the Great Lakes, Missouri, Arkansas-White-Red, and California regions all produced between 1,000 and 1,400 million cubic meters per year.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0203872","usgsCitation":"Blasch, K.W., Hundt, S., Wurster, P., Sando, R., and Berthelote, A., 2018, Streamflow contributions from tribal lands to major river basins of the United States: PLoS ONE, v. 13, no. 9, p. 1-16, https://doi.org/10.1371/journal.pone.0203872.","productDescription":"e0203872; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-089346","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":468411,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0203872","text":"Publisher Index Page"},{"id":357234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"13","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-11","publicationStatus":"PW","scienceBaseUri":"5b98a25fe4b0702d0e842e3e","contributors":{"authors":[{"text":"Blasch, Kyle W. 0000-0002-0590-0724","orcid":"https://orcid.org/0000-0002-0590-0724","contributorId":203415,"corporation":false,"usgs":true,"family":"Blasch","given":"Kyle","email":"","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744764,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hundt, Stephen A. 0000-0002-6484-0637","orcid":"https://orcid.org/0000-0002-6484-0637","contributorId":204678,"corporation":false,"usgs":true,"family":"Hundt","given":"Stephen","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wurster, Patrick 0000-0003-2668-2014","orcid":"https://orcid.org/0000-0003-2668-2014","contributorId":207806,"corporation":false,"usgs":false,"family":"Wurster","given":"Patrick","email":"","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":false,"id":744766,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sando, Roy 0000-0003-0704-6258","orcid":"https://orcid.org/0000-0003-0704-6258","contributorId":3874,"corporation":false,"usgs":true,"family":"Sando","given":"Roy","email":"","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":744767,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Berthelote, Antony","contributorId":207807,"corporation":false,"usgs":false,"family":"Berthelote","given":"Antony","email":"","affiliations":[{"id":37636,"text":"Salish Kootenai College","active":true,"usgs":false}],"preferred":false,"id":744768,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70201135,"text":"70201135 - 2018 - Patterns of host-associated fecal indicators driven by hydrology, precipitation, and land use attributes in Great Lakes watersheds","interactions":[],"lastModifiedDate":"2018-12-03T10:40:21","indexId":"70201135","displayToPublicDate":"2018-09-07T10:40:14","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Patterns of host-associated fecal indicators driven by hydrology, precipitation, and land use attributes in Great Lakes watersheds","docAbstract":"Fecal contamination from sewage and agricultural runoff is a pervasive problem in Great Lakes watersheds. Most work examining fecal pollution loads relies on discrete samples of fecal indicators and modeling land use. In this study, we made empirical measurements of human and ruminant-associated fecal indicator bacteria and combined these with hydrological measurements in eight watersheds ranging from predominantly forested to highly urbanized. Flow composited river samples were collected over low-flow (n = 89) and rainfall or snowmelt runoff events (n = 130). Approximately 90% of samples had evidence of human fecal pollution, with highest loads from urban watersheds. Ruminant indicators were found in ∼60–100% of runoff-event samples in agricultural watersheds, with concentrations and loads related to cattle density. Rain depth, season, agricultural tile drainage, and human or cattle density explained variability in daily flux of human or ruminant indicators. Mapping host-associated indicator loads to watershed discharge points sheds light on the type, level, and possible health risk from fecal pollution entering the Great Lakes and can inform total maximum daily load implementation and other management practices to target specific fecal pollution sources.
","language":"English","publisher":"ACS","doi":"10.1021/acs.est.8b01945","usgsCitation":"Dila, D.K., Corsi, S., Lenaker, P.L., Baldwin, A.K., Bootsma, M.J., and McLellan, S.L., 2018, Patterns of host-associated fecal indicators driven by hydrology, precipitation, and land use attributes in Great Lakes watersheds: Environmental Science & Technology, v. 52, no. 20, p. 11500-11509, https://doi.org/10.1021/acs.est.8b01945.","productDescription":"10 p.","startPage":"11500","endPage":"11509","ipdsId":"IP-084279","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468430,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6437017","text":"External Repository"},{"id":437765,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7VX0DRH","text":"USGS data release","linkHelpText":"Regression models and associated data for describing variability of host specific bacteria fluxes in eight Great Lakes tributaries, 2011-2013"},{"id":359866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"20","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-27","publicationStatus":"PW","scienceBaseUri":"5c064ee3e4b0815414cecb0e","contributors":{"authors":[{"text":"Dila, Deborah K.","contributorId":210966,"corporation":false,"usgs":false,"family":"Dila","given":"Deborah","email":"","middleInitial":"K.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752862,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lenaker, Peter L. 0000-0002-9469-6285 plenaker@usgs.gov","orcid":"https://orcid.org/0000-0002-9469-6285","contributorId":5572,"corporation":false,"usgs":true,"family":"Lenaker","given":"Peter","email":"plenaker@usgs.gov","middleInitial":"L.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752864,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752867,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bootsma, Melinda J.","contributorId":210967,"corporation":false,"usgs":false,"family":"Bootsma","given":"Melinda","email":"","middleInitial":"J.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752865,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McLellan, Sandra L. 0000-0003-3283-1151","orcid":"https://orcid.org/0000-0003-3283-1151","contributorId":210968,"corporation":false,"usgs":false,"family":"McLellan","given":"Sandra","email":"","middleInitial":"L.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752866,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199125,"text":"70199125 - 2018 - Leveraging big data towards functionally-based, catchment scale restoration prioritization","interactions":[],"lastModifiedDate":"2018-11-21T15:06:36","indexId":"70199125","displayToPublicDate":"2018-09-05T10:19:29","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging big data towards functionally-based, catchment scale restoration prioritization","docAbstract":"The persistence of freshwater degradation has necessitated the growth of an expansive stream and wetland restoration industry, yet restoration prioritization at broad spatial extents is still limited and ad-hoc restoration prevails. The River Basin Restoration Prioritization tool has been developed to incorporate vetted, distributed data models into a catchment scale restoration prioritization framework. Catchment baseline condition and potential improvement with restoration activity is calculated for all National Hydrography Dataset stream reaches and catchments in North Carolina and compared to other catchments within the river subbasin to assess where restoration efforts may best be focused. Hydrologic, water quality, and aquatic habitat quality conditions are assessed with peak flood flow, nitrogen and phosphorus loading, and aquatic species distribution models. The modular nature of the tool leaves ample opportunity for future incorporation of novel and improved datasets to better represent the holistic health of a watershed, and the nature of the datasets used herein allow this framework to be applied at much broader scales than North Carolina.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-018-1100-z","usgsCitation":"Lovette, J.P., Duncan, J.M., Smart, L.S., Fay, J.P., Urban, D.L., Daly, N., Blackwell, J., Hoos, A.B., Garcia, A.M., and Band, L.E., 2018, Leveraging big data towards functionally-based, catchment scale restoration prioritization: Environmental Management, v. 62, no. 6, p. 1007-1024, https://doi.org/10.1007/s00267-018-1100-z.","productDescription":"18 p.","startPage":"1007","endPage":"1024","ipdsId":"IP-094881","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":357074,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-31","publicationStatus":"PW","scienceBaseUri":"5b98a268e4b0702d0e842e78","contributors":{"authors":[{"text":"Lovette, John P.","contributorId":207568,"corporation":false,"usgs":false,"family":"Lovette","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":37566,"text":"UNC","active":true,"usgs":false}],"preferred":false,"id":744230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duncan, Jonathan M.","contributorId":207569,"corporation":false,"usgs":false,"family":"Duncan","given":"Jonathan","email":"","middleInitial":"M.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":744231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smart, Lindsey S.","contributorId":207570,"corporation":false,"usgs":false,"family":"Smart","given":"Lindsey","email":"","middleInitial":"S.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":744232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fay, John P.","contributorId":207571,"corporation":false,"usgs":false,"family":"Fay","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":744233,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Urban, Dean L.","contributorId":207572,"corporation":false,"usgs":false,"family":"Urban","given":"Dean","email":"","middleInitial":"L.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":744234,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Daly, Nancy","contributorId":207573,"corporation":false,"usgs":false,"family":"Daly","given":"Nancy","email":"","affiliations":[{"id":37567,"text":"Wake County Department of Environmental Services","active":true,"usgs":false}],"preferred":false,"id":744235,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Blackwell, Jamie","contributorId":207574,"corporation":false,"usgs":false,"family":"Blackwell","given":"Jamie","email":"","affiliations":[{"id":24615,"text":"North Carolina Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":744236,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hoos, Anne B. 0000-0001-9845-7831","orcid":"https://orcid.org/0000-0001-9845-7831","contributorId":207575,"corporation":false,"usgs":true,"family":"Hoos","given":"Anne","email":"","middleInitial":"B.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744237,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Garcia, Ana M. 0000-0002-5388-1281 agarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-1281","contributorId":207567,"corporation":false,"usgs":true,"family":"Garcia","given":"Ana","email":"agarcia@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744229,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Band, Lawrence E.","contributorId":207576,"corporation":false,"usgs":false,"family":"Band","given":"Lawrence","email":"","middleInitial":"E.","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":744238,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70198077,"text":"sir20185096 - 2018 - Documentation of single-well aquifer tests and integrated borehole analyses, Pahute Mesa and Vicinity, Nevada","interactions":[],"lastModifiedDate":"2018-09-05T12:07:20","indexId":"sir20185096","displayToPublicDate":"2018-09-04T09:27:04","publicationYear":"2018","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":"2018-5096","title":"Documentation of single-well aquifer tests and integrated borehole analyses, Pahute Mesa and Vicinity, Nevada","docAbstract":"Director,
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
Groundwater systems are dynamic geologic environments in which water continuously flows from recharge areas to discharge areas at streams, springs, wetlands, coastal waters, and wells. Natural, predevelopment conditions within groundwater systems are changed by the introduction of wells and other human stresses that modify existing groundwater levels, flow paths, and hydrologic budgets. Groundwater serves the Nation as an important water supply, but in some instances such stresses can have adverse impacts that include excessive ground water-level declines, aquifer-storage reductions, and streamflow depletions. Many of the Nation’s aquifer systems extend over thousands of square miles and their hydrologic boundaries may be distant from jurisdictional boundaries that can be the focus of groundwater disputes. Effective interstate management of groundwater resources is benefited by an understanding of the regional-scale controls that affect groundwater conditions at the local scale. Numerical models are the most effective approach for accounting for all of the relevant hydrologic processes that affect groundwater systems and their response to natural and manmade stresses. This paper provides a brief background on some of the basic principles of groundwater hydrology that are relevant to interstate management of this important natural resource.
","conferenceTitle":"34th Water Law Conference","conferenceDate":"March 29-30, 2016","conferenceLocation":"Austin, TX","language":"English","publisher":"American Bar Association Section of Environment, Energy, and Resources","usgsCitation":"Barlow, P.M., 2018, Interstate water management of a “hidden” resource - Physical principles of groundwater hydrology, 34th Water Law Conference, Austin, TX, March 29-30, 2016, 9 p.","productDescription":"9 p.","ipdsId":"IP-072301","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":357022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a26ae4b0702d0e842e8c","contributors":{"authors":[{"text":"Barlow, Paul M. 0000-0003-4247-6456 pbarlow@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6456","contributorId":1200,"corporation":false,"usgs":true,"family":"Barlow","given":"Paul","email":"pbarlow@usgs.gov","middleInitial":"M.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":742190,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70199087,"text":"70199087 - 2018 - Thresholds and relations for soil‐hydraulic and soil‐physical properties as a function of burn severity 4 years after the 2011 Las Conchas Fire, New Mexico, USA","interactions":[],"lastModifiedDate":"2018-09-01T20:00:48","indexId":"70199087","displayToPublicDate":"2018-09-01T20:00:41","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Thresholds and relations for soil‐hydraulic and soil‐physical properties as a function of burn severity 4 years after the 2011 Las Conchas Fire, New Mexico, USA","docAbstract":"Wildfire effects on soil‐physical and ‐hydraulic properties as a function of burn severity are poorly characterized, especially several years after wildfire. A stratified random sampling approach was used in 2015 to sample seven sites representing a spectrum of remotely sensed burn severity in the area impacted by the 2011 Las Conchas Fire in New Mexico, USA. Replicate samples from each site were analysed in the laboratory. Linear and linear indicator regression were used to assess thresholds in soil‐physical and ‐hydraulic properties and functional relations with remotely sensed burn severity. Significant thresholds were present for initial soil‐water content (θi) at 0–6 cm depth between the change in the Normalized Burn Ratio (dNBR) equal to 618–802, for bulk density (ρb) at 3–6 cm between dNBR equal to 416–533, for gravel fraction at 0–1 cm between dNBR equal to 416–533, for fines (the silt + clay fraction) at 0–1 cm for dNBR equal to 416–533, and for fines at 3–6 cm for dNBR equal to 293–416. Significant linear relations with dNBR were present between ρb at 0–1 cm, loss on ignition (LOI) at 0–1 cm, gravel fraction at 0–1 cm, and the large organic fraction at 1–3 cm. No thresholds or effects on soil‐hydraulic properties of field‐saturated hydraulic conductivity or sorptivity were observed. These results suggest that ρb and LOI at 0–1 cm have residual direct impacts from the wildfire heat impulse. The θi threshold is most likely from delayed groundcover/vegetation recovery that increases evaporation at the highest burn severity sites. Gravel and silt + clay thresholds at 0–1 cm at the transition to high burn severity suggest surface gravel lag development from hydraulic erosion. Thresholds in ρb from 3 to 6 cm and in silt + clay fraction from 3 to 6 cm appear to be the result of soil variability between sites rather than wildfire impacts. This work suggests that gravel‐rich soils may have increased resilience to sustained surface runoff generation and erosion following wildfire, with implications for assessments of postwildfire hydrologic and erosion recovery potential.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13167","usgsCitation":"Ebel, B.A., Romero, O.C., and Martin, D.A., 2018, Thresholds and relations for soil‐hydraulic and soil‐physical properties as a function of burn severity 4 years after the 2011 Las Conchas Fire, New Mexico, USA: Hydrological Processes, v. 32, no. 14, p. 2263-2278, https://doi.org/10.1002/hyp.13167.","productDescription":"16 p.","startPage":"2263","endPage":"2278","ipdsId":"IP-089035","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":357011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","volume":"32","issue":"14","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-20","publicationStatus":"PW","scienceBaseUri":"5b98a26be4b0702d0e842e96","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":744007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romero, Orlando C. 0000-0003-0162-0239 ocromero@usgs.gov","orcid":"https://orcid.org/0000-0003-0162-0239","contributorId":5077,"corporation":false,"usgs":true,"family":"Romero","given":"Orlando","email":"ocromero@usgs.gov","middleInitial":"C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744008,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":168662,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":744009,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199088,"text":"70199088 - 2018 - Field and laboratory hydraulic characterization of landslide-prone soils in the Oregon Coast Range and implications for hydrologic simulation","interactions":[],"lastModifiedDate":"2020-10-22T19:48:10.063873","indexId":"70199088","displayToPublicDate":"2018-09-01T17:41:20","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Field and laboratory hydraulic characterization of landslide-prone soils in the Oregon Coast Range and implications for hydrologic simulation","docAbstract":"Unsaturated zone flow processes are an important focus of landslide hazard estimation. Differences in soil hydraulic behavior between wetting and drying conditions (i.e., hydraulic hysteresis) may be important in landslide triggering. Hydraulic hysteresis can complicate soil hydraulic parameter estimates and impact prediction capability. This investigation focused on hydraulic property estimation for soil in a landslide‐prone area where the relative importance of hysteresis is unclear. Laboratory measurements of soil‐water retention from field soils in the Oregon Coast Range during wetting and drying show that pronounced hydraulic hysteresis is present. In contrast, a 4‐yr field data record of pore‐water pressure and soil‐water content from multiple soil pits at the same landslide‐prone area shows relatively minor hydraulic hysteresis compared with the laboratory estimates. Simulated subsurface hydrologic response parameterized using estimates from field data more closely matched hydrologic observations relative to model parameterization based on laboratory analysis of repacked soil samples. Our results suggest that (i) unsaturated hydraulic parameter estimates based on in situ field data, as opposed to laboratory measurements alone, may lead to more accurate simulation of the hydrologic response to rainfall, (ii) in situ data of soil‐water retention may need to include values at both high suctions and near saturation to improve estimates of soil hydraulic parameters for slope failure applications, and (iii) laboratory measurements of soil‐water retention made under dynamic conditions may overestimate hydraulic hysteresis.
","language":"English","publisher":"ACSESS","doi":"10.2136/vzj2018.04.0078","usgsCitation":"Ebel, B.A., Godt, J.W., Lu, N., Coe, J.A., Smith, J.B., and Baum, R.L., 2018, Field and laboratory hydraulic characterization of landslide-prone soils in the Oregon Coast Range and implications for hydrologic simulation: Vadose Zone Journal, v. 17, 180078, 15 p., https://doi.org/10.2136/vzj2018.04.0078.","productDescription":"180078, 15 p.","ipdsId":"IP-098356","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468449,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/vzj2018.04.0078","text":"Publisher Index Page"},{"id":357010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":379661,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://acsess.onlinelibrary.wiley.com/doi/full/10.2136/vzj2018.04.0078"}],"country":"United States","state":"Oregon","otherGeospatial":"Oregon Coast Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.617919921875,\n 42.17968819665961\n ],\n [\n -122.67333984374999,\n 42.17968819665961\n ],\n [\n -122.67333984374999,\n 44.39454219215587\n ],\n [\n -124.617919921875,\n 44.39454219215587\n ],\n [\n -124.617919921875,\n 42.17968819665961\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-30","publicationStatus":"PW","scienceBaseUri":"5b98a26ce4b0702d0e842e98","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":744010,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":744011,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lu, Ning","contributorId":191360,"corporation":false,"usgs":false,"family":"Lu","given":"Ning","email":"","affiliations":[{"id":12620,"text":"U.S. Army Corp. of Engineers","active":true,"usgs":false}],"preferred":false,"id":744012,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":744013,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Joel B. 0000-0001-7219-7875 jbsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-7219-7875","contributorId":4925,"corporation":false,"usgs":true,"family":"Smith","given":"Joel","email":"jbsmith@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":744014,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":744015,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198528,"text":"ofr20181127 - 2018 - Southern Rockies Landscape Conservation Cooperative unit watershed erosion potential prioritization for check-dam installation","interactions":[],"lastModifiedDate":"2018-09-04T10:38:08","indexId":"ofr20181127","displayToPublicDate":"2018-08-31T09:15:57","publicationYear":"2018","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":"2018-1127","title":"Southern Rockies Landscape Conservation Cooperative unit watershed erosion potential prioritization for check-dam installation","docAbstract":"Changes in land-use practices and the extirpation (local extinction) of beaver populations in the early 20th century during European settlement are believed to have resulted in many changes in how streams in the Western United States function. Some of the negative changes that have resulted include stream channelization, soil erosion, changing vegetation, water turbidity, and a loss of overland flow. Efforts to restore streams and reduce soil erosion by water have included reintroductions of beaver, incorporating Native American traditional knowledge of dry-land farming techniques, and the installation of rigid check-dams. Many of these efforts have been successful in improving both intermittent and perennial stream function. Therefore, stakeholders in the Southern Rockies Landscape Conservation Cooperative (SRLCC) have identified a need to prioritize streams within their region of interest for the installation of check-dams to continue restoration and conservation efforts and to improve sediment catchment.
Using Natural Resource Conservation Service soil databases, topographic features derived from digital elevation models, stream networks, and regional climatic patterns, I developed a ranking system for watershed potential erosion rates and suitability for check-dam placement across the SRLCC. This ranking system serves as a first step for land managers to prioritize areas for check-dam installation based on relatively static factors (soil properties, topography, and hydrology) that can contribute to rates of soil erosion by water and the stability of check-dams. Many other relatively dynamic factors over time can contribute to rates of soil erosion by water, such as recent wildfire events, changes in weather patterns and extreme climate events, and changing land-use such as grazing, logging, mining, development, and cultivation. These factors that influence vegetative and biological soil crusts cover are also important elements to the potential erosion of soil by water. Because of this, SRLCC stakeholders might consider further evaluation of the watersheds identified here as high ranking. Final watershed prioritization among the high-ranking watersheds identified here should include current knowledge of land-use and land-cover estimates to identify areas at risk for soil erosion or degree of existing erosion problems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181127","usgsCitation":"Ironside, K.E., 2018, Southern Rockies Landscape Conservation Cooperative unit watershed erosion potential prioritization for check-dam installation: U.S. Geological Survey Open-File Report 2018–1127, 15 p., https://doi.org/10.3133/ofr20181127.","productDescription":"Report: v, 15 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-096570","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":356855,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SEUC93","text":"Data release","description":"USGS Data Release","linkHelpText":"Watershed potential erosion rate ranking system and check-dam placement suitability data within the Southern Rockies Landscape Conservation Cooperative (SRLCC)"},{"id":356853,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1127/coverthb.jpg"},{"id":356854,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1127/ofr20181127.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1127"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.173197,\n 32.416412\n ],\n [\n -103.499364,\n 32.416412\n ],\n [\n -103.499364,\n 43.335375\n ],\n [\n -116.173197,\n 43.335375\n ],\n [\n -116.173197,\n 32.416412\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC Staff,
Southwest Biological Science Center
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Flagstaff, AZ 86001
Numerous contaminants of emerging concern (CECs) typically occur in urban rivers. Wastewater effluents are a major source of many CECs. Urban runoff (stormwater) is a major urban water budget component and may constitute another major CEC pathway. Yet, stormwater-based CEC field studies are rare. This research investigated 384 CECs in 36 stormwater samples in Minneapolis-St. Paul, Minnesota, USA. Nine sampling sites included three large stormwater conveyances (pipes) and three paired iron-enhanced sand filters (IESFs; untreated inlets and treated outlets). The 123 detected compounds included commercial-consumer compounds, veterinary and human pharmaceuticals, lifestyle and personal care compounds, pesticides, and others. Thirty-one CECs were detected in ≥50% of samples. Individual samples contained a median of 35 targeted CECs (range: 18–54). Overall, median concentrations were ≥10 ng/L for 25 CECs and ≥100 ng/L for 9 CECs. Ranked, hierarchical linear modeling indicated significant seasonal- and site type-based concentration variability for 53 and 30 CECs, respectively, with observed patterns corresponding to CEC type, source, usage, and seasonal hydrology. A primarily warm-weather, diffuse, runoff-based profile included many herbicides. A second profile encompassed winter and/or late summer samples enriched with some recalcitrant, hydrophobic compounds (e.g., PAHs), especially at pipes, suggesting conservative, less runoff-dependent sources (e.g., sediments). A third profile, indicative of mixed conservative/non-runoff, runoff, and/or atmospheric sources and transport that collectively affect a variety of conditions, included various fungicides, lifestyle, non-prescription, and commercial-consumer CECs. Generally, pipe sites had large, diverse land-use catchments, and showed more frequent detections of diverse CECs, but often at lower concentrations; while untreated sites (with smaller, more residential-catchments) demonstrated greater detections of “pseudo-persistent” and other ubiquitous or residentially-associated CECs. Although untreated stormwater transports an array of CECs to receiving waters, IESF treatment significantly removed concentrations of 14 (29%) of the 48 most detected CECs; for these, median removal efficiencies were 26%–100%. Efficient removal of some hydrophobic (e.g., PAHs, bisphenol A) and polar-hydrophilic (e.g., caffeine, nicotine) compounds indicated particulate-bound contaminant filtration and for certain dissolved contaminants, sorption.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2018.08.020","usgsCitation":"Fairbairn, D.J., Elliott, S.M., Kiesling, R.L., Schoenfuss, H.L., Ferrey, M.L., and Westerhoff, B., 2018, Contaminants of emerging concern in urban stormwater: Spatiotemporal patterns and removal by iron-enhanced sand filters (IESFs): Water Research, v. 145, p. 332-345, https://doi.org/10.1016/j.watres.2018.08.020.","productDescription":"14 p.","startPage":"332","endPage":"345","ipdsId":"IP-094557","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":356946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","city":"Minneapolis, St. Paul","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.44696044921875,\n 44.859275967357476\n ],\n [\n -92.95944213867186,\n 44.859275967357476\n ],\n [\n -92.95944213867186,\n 45.08661163034925\n ],\n [\n -93.44696044921875,\n 45.08661163034925\n ],\n [\n -93.44696044921875,\n 44.859275967357476\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a26ee4b0702d0e842eb4","contributors":{"authors":[{"text":"Fairbairn, David J.","contributorId":207455,"corporation":false,"usgs":false,"family":"Fairbairn","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":743862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":743864,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferrey, Mark L.","contributorId":207457,"corporation":false,"usgs":false,"family":"Ferrey","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":13330,"text":"Minnesota Pollution Control Agency","active":true,"usgs":false}],"preferred":false,"id":743865,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Westerhoff, Benjamin J.","contributorId":207458,"corporation":false,"usgs":false,"family":"Westerhoff","given":"Benjamin J.","affiliations":[{"id":20306,"text":"St. Cloud State University","active":true,"usgs":false}],"preferred":false,"id":743866,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198999,"text":"70198999 - 2018 - Elevated aeolian sediment transport on the Colorado Plateau, USA: The role of grazing, vehicle disturbance, and increasing aridity","interactions":[],"lastModifiedDate":"2018-11-14T09:27:13","indexId":"70198999","displayToPublicDate":"2018-08-29T16:05:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Elevated aeolian sediment transport on the Colorado Plateau, USA: The role of grazing, vehicle disturbance, and increasing aridity","docAbstract":"Dryland wind transport of sediment can accelerate soil erosion, degrade air quality, mobilize dunes, decrease water supply, and damage infrastructure. We measured aeolian sediment horizontal mass flux (q) at 100 cm height using passive aspirated sediment traps to better understand q variability on the Colorado Plateau. Measured q‘hot spots’ rival the highest ever recorded including 7,460 g m−2 day−1 in an off‐highway vehicle (OHV) area, but were more commonly 50‐2,000 g m−2 day−1. Overall mean q on rangeland sites was 5.14 g m−2 day−1, considerably lower than areas with concentrated livestock use (9‐19 g m−2 day−1), OHV use (414 g m−2 day−1), and downwind of unpaved roads (13.14 g m−2 day−1), but were higher than areas with minimal soil disturbance (1.60 g m−2 day−1). Rangeland q increased with increasing annual temperature, increased winds, and decreasing precipitation. Spatial modeling suggests that ~92‐93% of regional q occurs in rangelands versus ~7‐8% along unpaved roads. Four of the five largest road qvalues (n=33) measured were along roads used primarily for oil or gas wells. Our findings indicate that predicted future mega‐droughts will increase q disproportionately in disturbed rangelands, and potentially further compromise air quality, hydrologic cycles, and other ecosystem services.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4457","usgsCitation":"Nauman, T.W., Duniway, M.C., Webb, N.P., and Belnap, J., 2018, Elevated aeolian sediment transport on the Colorado Plateau, USA: The role of grazing, vehicle disturbance, and increasing aridity: Earth Surface Processes and Landforms, v. 43, no. 14, p. 2897-2914, https://doi.org/10.1002/esp.4457.","productDescription":"18 p.","startPage":"2897","endPage":"2914","ipdsId":"IP-091070","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":356937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.23406982421875,\n 37.76202988573211\n ],\n [\n -109.05853271484374,\n 37.76202988573211\n ],\n [\n -109.05853271484374,\n 39.37889504706486\n ],\n [\n -110.23406982421875,\n 39.37889504706486\n ],\n [\n -110.23406982421875,\n 37.76202988573211\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"14","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-13","publicationStatus":"PW","scienceBaseUri":"5b98a26ee4b0702d0e842eb8","contributors":{"authors":[{"text":"Nauman, Travis W. 0000-0001-8004-0608 tnauman@usgs.gov","orcid":"https://orcid.org/0000-0001-8004-0608","contributorId":169241,"corporation":false,"usgs":true,"family":"Nauman","given":"Travis","email":"tnauman@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743714,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743715,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Nichloas P.","contributorId":207393,"corporation":false,"usgs":false,"family":"Webb","given":"Nichloas","email":"","middleInitial":"P.","affiliations":[{"id":37528,"text":"USDA-ARS Jornada Experimental Range, PO Box 30003, MSC 3JER, NMSU, Las Cruces, NM 88003, USA","active":true,"usgs":false}],"preferred":false,"id":743717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743716,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70224965,"text":"70224965 - 2018 - Exploring drivers of regional water-quality change using differential spatially referenced regression – A pilot study in the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2021-10-11T15:35:54.717764","indexId":"70224965","displayToPublicDate":"2018-08-29T10:32:27","publicationYear":"2018","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":"Exploring drivers of regional water-quality change using differential spatially referenced regression – A pilot study in the Chesapeake Bay watershed","docAbstract":"An understanding of riverine water-quality dynamics in regional mixed-land use watersheds is the foundation for advances in landscape biogeochemistry and informed land management. A differential implementation of the statistical/process-based model SPAtially Referenced Regressions on Watershed attributes (SPARROW; Smith et al., https://doi.org/10.1029/97wr02171) is proposed to empirically relate a regional pattern of changes in flow-normalized constituent flux, over a multiyear period, to contemporaneous changes in spatially referenced explanatory variables. In a pilot application, the differential model, called Spatiotemporal Watershed Accumulation of Net effects (SWAN), is used to explore factors influencing changes in flow-normalized flux of total nitrogen over the period 1990–2010 at 43 sites in the nontidal Chesapeake Bay watershed. A seven-parameter model explains 80% of the transformed variability in independently estimated flux changes, indicating that storage effects having characteristic time scales greater than 20 years had a small influence, relative to changes in inputs, on regional water-quality response. Results suggest that 1990–2010 changes in total-nitrogen flux are largely the outcome of increased nonpoint-source pollution associated with urban and suburban development, modulated to the point of negation by terrestrial losses stemming from widespread increases in air temperature and precipitation. The loss mechanism is qualitatively consistent with denitrification; however, increases in aboveground biomass, agricultural nitrogen exports, or hydrologic flushing are also plausible contributors. Although qualified by a small sample size and constraints on explanatory data availability, the pilot suggests that SWAN is a promising approach for broadening scientific understanding of factors driving regional water-quality change and for supporting evidence-based land-management decisions.
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0000-0001-5587-3683","orcid":"https://orcid.org/0000-0001-5587-3683","contributorId":267279,"corporation":false,"usgs":false,"family":"Yang","given":"Guoxiang","affiliations":[{"id":55459,"text":"NSA Contractor to USGS VA and WV WSC","active":true,"usgs":false}],"preferred":false,"id":824898,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198289,"text":"ofr20181120 - 2018 - Laboratory evaluation of the Sea-Bird Scientific HydroCycle-PO4 phosphate sensor","interactions":[],"lastModifiedDate":"2018-08-29T14:51:19","indexId":"ofr20181120","displayToPublicDate":"2018-08-29T00:00:00","publicationYear":"2018","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":"2018-1120","displayTitle":"Laboratory evaluation of the Sea-Bird Scientific HydroCycle-PO4 phosphate sensor","title":"Laboratory evaluation of the Sea-Bird Scientific HydroCycle-PO4 phosphate sensor","docAbstract":"Sea-Bird Scientific’s HydroCycle-PO4 phosphate sensor is a single-analyte wet-chemistry sensor designed for in situ environmental monitoring. The unit was evaluated at the U.S. Geological Survey Hydrologic Instrumentation Facility to assess the accuracy of the sensor in solutions with known phosphorous concentration and to test the effects of chromophoric (colored) dissolved organic matter (CDOM) and natural water matrixes on sensor accuracy. Accuracy was tested with three standards: 0.110, 0.174, and 0.260 milligram per liter, as phosphorous (mg/L as P). The 0.110- and 0.260-mg/L standards were made from a dilution of a National Institute of Standards and Technology-traceable phosphate-phosphorous standard with Type I deionized water (DIW). Average measured phosphate concentrations of the tested standards (0.110, 0.174, and 0.260 mg/L as P) in DIW were 0.132, 0.181, and 0.310 mg/L as P, for differences of 20, 4, and 19 percent, respectively.
Measured phosphate concentration of a tested standard was biased by the addition of tea water filtered through a 0.45-micrometer pore size filter (filtered tea water [FTW]) simulating the effect of CDOM. An aliquot of the filtered tea solution was sent to a certified environmental laboratory, which reported a less than reporting level (<0.004 mg/L as P) phosphate concentration. True color of the FTW was measured at 380 platinum-cobalt units by using Standard Methods 8025. For this FTW test, the measured phosphate concentration for the clear 0.260 mg/L as P standard averaged 0.366 mg/L as P. This concentration increased to an average of 0.653 mg/L as P with the addition of 10 percent FTW, and to an average of 0.859 mg/L as P with the addition of 20 percent FTW. These test results indicate a positive bias of up to 40 percent of the concentrations of the measured phosphate concentrations when CDOM is present and indicate a proportional increase in an apparent concentration of phosphorus instrument response as CDOM concentration increases.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181120","usgsCitation":"Snazelle, T.T., 2018, Laboratory evaluation of the Sea-Bird Scientific HydroCycle-PO4 phosphate sensor: U.S. Geological Survey Open-File Report 2018–1120, 10 p., https://doi.org/ofr20181120.","productDescription":"vi, 10 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-090916","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":356807,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1120/coverthb5.jpg"},{"id":356711,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1120/ofr20181120.pdf","text":"Report","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1120"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
Extreme climate events—such as hurricanes, droughts, extreme precipitation, and wildfires—have the potential to alter watershed processes and stream response. Yet due to the destructive and hazardous nature and unpredictability of such events, capturing their hydrochemical signal is challenging. A 5‐year postwildfire study of stream chemistry in the Fourmile Creek watershed, Colorado Front Range, USA, focused on high‐frequency storm sampling. During the study, the watershed was impacted by three additional extreme climate events—drought and two periods of extreme rainfall totals. These events altered concentration‐discharge relationships in ways that elucidate how hydrologic flow paths and source material availability affect stream water chemistry. Reduced infiltration after wildfire led to overland flow during thunderstorms, which conveyed ash and soil into streams. This resulted in elevated stream concentrations of constituents elevated in ash—Ca, K, Mg, alkalinity, and dissolved organic carbon—along with sediment and nitrate. Subsurface flow paths were bypassed, leading to low concentrations of Na and SiO2, which are bedrock derived and not elevated in ash. During drought conditions, when stream discharge was <20% of average, concentrations of sediment, dissolved organic carbon, and Ca fell below average concentrations, but SiO2 did not. Extreme rainfall totals saturated the subsurface and led to prolonged elevated stream discharge. Concentration‐discharge relationships for bedrock‐derived constituents, such as Ca and SiO2, were altered in that time period, while those for dissolved organic carbon were not. Previous disturbances, including historical mining, also affect stream chemistry, and water‐quality impairment can be exacerbated by extreme climate events.
","language":"English","publisher":"AGU","doi":"10.1029/2017JG004349","usgsCitation":"Murphy, S.F., McCleskey, R.B., Martin, D.A., Writer, J., and Ebel, B.A., 2018, Fire, flood, and drought: Extreme climate events alter flow paths and stream chemistry: Journal of Geophysical Research G: Biogeosciences, v. 123, no. 8, p. 2513-2526, https://doi.org/10.1029/2017JG004349.","productDescription":"14 p.","startPage":"2513","endPage":"2526","ipdsId":"IP-080472","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":468468,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jg004349","text":"Publisher Index Page"},{"id":356843,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Fourmile Creek Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.5833,\n 40\n ],\n [\n -105.33,\n 40\n ],\n [\n -105.33,\n 40.0667\n ],\n [\n -105.5833,\n 40.0667\n ],\n [\n -105.5833,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-24","publicationStatus":"PW","scienceBaseUri":"5b98a271e4b0702d0e842ed4","contributors":{"authors":[{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":743505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052 rbmccles@usgs.gov","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":147399,"corporation":false,"usgs":true,"family":"McCleskey","given":"R.","email":"rbmccles@usgs.gov","middleInitial":"Blaine","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":743508,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":168662,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":743506,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Writer, Jeffrey H.","contributorId":207308,"corporation":false,"usgs":false,"family":"Writer","given":"Jeffrey H.","affiliations":[{"id":29863,"text":"University of Colorado, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":743507,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":743509,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198946,"text":"70198946 - 2018 - Before the storm: Antecedent conditions as regulators of hydrologic and biogeochemical response to extreme climate events","interactions":[],"lastModifiedDate":"2018-12-05T14:19:32","indexId":"70198946","displayToPublicDate":"2018-08-28T13:29:10","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Before the storm: Antecedent conditions as regulators of hydrologic and biogeochemical response to extreme climate events","docAbstract":"While the influence of antecedent conditions on watershed function is widely recognized under typical hydrologic regimes, gaps remain in the context of extreme climate events (ECEs). ECEs are those events that far exceed seasonal norms of intensity, duration, or impact upon the physical environment or ecosystem. In this synthesis, we discuss the role of source availability and hydrologic connectivity on antecedent conditions and propose a conceptual framework to characterize system response to ECEs at the watershed scale. We present four case studies in detail that span a range of types of antecedent conditions and type of ECE to highlight important controls and feedbacks. Because ECEs have the potential to export large amounts of water and materials, their occurrence in sequence can disproportionately amplify the response. In fact, multiple events may not be considered extreme in isolation, but when they occur in close sequence they may lead to extreme responses in terms of both supply and transport capacity. Therefore, to advance our understanding of these complexities, we need continued development of a mechanistic understanding of how antecedent conditions set the stage for ECE response across multiple regions and climates, particularly since monitoring of these rare events is costly and difficult to obtain. Through focused monitoring of critical ecosystems during rare events we will also be able to extend and validate modeling studies. Cross-regional comparisons are also needed to define characteristics of resilient systems. These monitoring, modeling, and synthesis efforts are more critical than ever in light of changing climate regimes, intensification of human modifications of the landscape, and the disproportionate impact of ECEs in highly populated regions.
","language":"English","publisher":"Springer","doi":"10.1007/s10533-018-0482-6","usgsCitation":"McMillan, S.K., Wilson, H.F., Tague, C.L., Hanes, D.M., Inamdar, S., Karwan, D.L., Loecke, T., Morrison, J., Murphy, S.F., and Vidon, P., 2018, Before the storm: Antecedent conditions as regulators of hydrologic and biogeochemical response to extreme climate events: Biogeochemistry, v. 141, no. 3, p. 487-501, https://doi.org/10.1007/s10533-018-0482-6.","productDescription":"15 p.","startPage":"487","endPage":"501","ipdsId":"IP-092162","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":356841,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"141","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-16","publicationStatus":"PW","scienceBaseUri":"5b98a271e4b0702d0e842ed6","contributors":{"authors":[{"text":"McMillan, Sara K.","contributorId":207309,"corporation":false,"usgs":false,"family":"McMillan","given":"Sara","email":"","middleInitial":"K.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":743514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Henry F.","contributorId":207310,"corporation":false,"usgs":false,"family":"Wilson","given":"Henry","email":"","middleInitial":"F.","affiliations":[{"id":24491,"text":"Agriculture and Agri-Food Canada","active":true,"usgs":false}],"preferred":false,"id":743515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tague, Christina L.","contributorId":207311,"corporation":false,"usgs":false,"family":"Tague","given":"Christina","email":"","middleInitial":"L.","affiliations":[{"id":16936,"text":"University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":743516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanes, Daniel M.","contributorId":207312,"corporation":false,"usgs":false,"family":"Hanes","given":"Daniel","email":"","middleInitial":"M.","affiliations":[{"id":37518,"text":"St. Louis University","active":true,"usgs":false}],"preferred":false,"id":743517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Inamdar, Shreeram","contributorId":177337,"corporation":false,"usgs":false,"family":"Inamdar","given":"Shreeram","affiliations":[],"preferred":false,"id":743518,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karwan, Diana L.","contributorId":207315,"corporation":false,"usgs":false,"family":"Karwan","given":"Diana","email":"","middleInitial":"L.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":743522,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Loecke, Terry","contributorId":207313,"corporation":false,"usgs":false,"family":"Loecke","given":"Terry","email":"","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":743519,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morrison, Jonathan 0000-0002-1756-4609","orcid":"https://orcid.org/0000-0002-1756-4609","contributorId":203255,"corporation":false,"usgs":true,"family":"Morrison","given":"Jonathan","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743520,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":743513,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vidon, Philippe","contributorId":207314,"corporation":false,"usgs":false,"family":"Vidon","given":"Philippe","email":"","affiliations":[{"id":37519,"text":"SUNY College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":743521,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70198988,"text":"70198988 - 2018 - Input data processing tools for the integrated hydrologic model GSFLOW","interactions":[],"lastModifiedDate":"2018-08-28T13:25:31","indexId":"70198988","displayToPublicDate":"2018-08-28T13:25:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Input data processing tools for the integrated hydrologic model GSFLOW","docAbstract":"Integrated hydrologic modeling (IHM) encompasses a vast number of processes and specifications, variable in time and space, and development of models can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model grid-scale digital elevation model (DEM) is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorological data over the model domain is difficult in complex terrain at the model-grid scale, but is necessary for realistic simulations. As model development requires extensive GIS and computer programming expertise, the use of IHMs has mostly been limited to research groups with available financial, human, and technical resources. Here we present a series of open-source Python scripts that are combined with ESRI ArcGIS to provide a formalized technique for the parameterization and development of inputs for the readily available IHM called GSFLOW. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development, land coverages, and meteorological distribution over the model domain. The final products of the toolkit are PRMS ready Parameter Files, along with several input parameters for a MODFLOW model, including input for the Streamflow Routing Package. A demonstration of the toolkit is provided to illustrate its capabilities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2018.07.020","usgsCitation":"Gardner, M.A., Morton, C.G., Huntington, J., Niswonger, R., and Henson, W.R., 2018, Input data processing tools for the integrated hydrologic model GSFLOW: Environmental Modelling and Software, v. 109, p. 41-53, https://doi.org/10.1016/j.envsoft.2018.07.020.","productDescription":"13 p.","startPage":"41","endPage":"53","ipdsId":"IP-092325","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":468469,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2018.07.020","text":"Publisher Index Page"},{"id":356840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"109","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a272e4b0702d0e842ed8","contributors":{"authors":[{"text":"Gardner, Murphy A. 0000-0002-3951-6667","orcid":"https://orcid.org/0000-0002-3951-6667","contributorId":207374,"corporation":false,"usgs":true,"family":"Gardner","given":"Murphy","email":"","middleInitial":"A.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morton, Charles G.","contributorId":207375,"corporation":false,"usgs":false,"family":"Morton","given":"Charles","email":"","middleInitial":"G.","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":743652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huntington, Justin L.","contributorId":31279,"corporation":false,"usgs":true,"family":"Huntington","given":"Justin L.","affiliations":[],"preferred":false,"id":743653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":2833,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard G.","email":"rniswon@usgs.gov","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":743654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henson, Wesley R. 0000-0003-4962-5565 whenson@usgs.gov","orcid":"https://orcid.org/0000-0003-4962-5565","contributorId":384,"corporation":false,"usgs":true,"family":"Henson","given":"Wesley","email":"whenson@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":743655,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70198932,"text":"70198932 - 2018 - Biocrusts: The living skin of the Earth","interactions":[],"lastModifiedDate":"2018-08-27T16:16:52","indexId":"70198932","displayToPublicDate":"2018-08-27T16:16:48","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3089,"text":"Plant and Soil","active":true,"publicationSubtype":{"id":10}},"title":"Biocrusts: The living skin of the Earth","docAbstract":"Biological soil crusts (biocrusts) form a “living skin” at the soil surface in many low productivity ecosystems around the world including water- and cold-limited environments, and early successional seres (Belnap et al. 2003). They may be composed of any configuration of soil surface-dwelling cyanobacteria, eukaryotic algae, lichens, mosses or liverworts, and support assemblages of decomposers and a faunal food web (Belnap et al. 2003). These soil surface communities have global relevance, as it has been recently estimated that they cover about 12% of the terrestrial surface currently (Rodriguez-Caballero et al. 2018). Biocrust communities are perhaps an ideal subject for the journal Plant and Soil, because they are simultaneously plant-like, due to their dominance by autotrophs, yet biocrusts are also clearly a physical feature of the soil given that component organisms are enmeshed in, adherent to, or otherwise in direct contact with the soil surface. The activity of the organisms is what engineers the well-aggregated thin layer at the soil surface that we recognize as a biocrust (Belnap et al. 2003). The contributions of biocrusts to ecosystem function has fueled much research interest, initially in the observation of biocrusts’ soil aggregating and erosion-resisting nature, and later as a multifunctional, globally-relevant ecosystem element instrumental in: 1. building or otherwise altering soil nutrient stocks through N-fixation (Elbert et al. 2012), dust trapping (Reynolds et al. 2001) and nutrient cycling (Strauss et al. 2012), 2. influencing hydrological properties of soil such as the water balance (Chamizo et al. 2016), and 3. The thermal energy balance of the ecosystem (Coradeau et al. 2016, Rutherford et al. 2017).
","language":"English","publisher":"Springer","doi":"10.1007/s11104-018-3735-1","usgsCitation":"Bowker, M.A., Reed, S.C., Maestre, F.T., and Eldridge, D.J., 2018, Biocrusts: The living skin of the Earth: Plant and Soil, v. 429, no. 1-2, p. 1-7, https://doi.org/10.1007/s11104-018-3735-1.","productDescription":"7 p.","startPage":"1","endPage":"7","ipdsId":"IP-098860","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468475,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11104-018-3735-1","text":"Publisher Index Page"},{"id":356812,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"429","issue":"1-2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-03","publicationStatus":"PW","scienceBaseUri":"5b98a273e4b0702d0e842ee8","contributors":{"authors":[{"text":"Bowker, Matthew A.","contributorId":196428,"corporation":false,"usgs":false,"family":"Bowker","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":743475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maestre, Fernando T.","contributorId":207297,"corporation":false,"usgs":false,"family":"Maestre","given":"Fernando","email":"","middleInitial":"T.","affiliations":[{"id":37513,"text":"Departamento de Biología y Geología, Física y Química Inorgánica, ESCET, Universidad Rey Juan Carlos, c/ Tulipán s/n, 28933 Móstoles, Spain","active":true,"usgs":false}],"preferred":false,"id":743477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eldridge, David J. 0000-0002-2191-486X","orcid":"https://orcid.org/0000-0002-2191-486X","contributorId":207298,"corporation":false,"usgs":false,"family":"Eldridge","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":37514,"text":"Center for Ecosystem Science, University of New South Wales, Sydney, NSW 2052, Australia","active":true,"usgs":false}],"preferred":false,"id":743478,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197361,"text":"ofr20181089 - 2018 - Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey","interactions":[],"lastModifiedDate":"2018-08-24T12:37:46","indexId":"ofr20181089","displayToPublicDate":"2018-08-20T14:30:00","publicationYear":"2018","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":"2018-1089","title":"Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey","docAbstract":"The U.S. Geological Survey (USGS) uses Maintenance of Variance Extension Type 1 (MOVE.1) regression to transfer streamflows measured at long-term continuous-record streamgaging stations to partial-record (PR) streamgaging stations where intermittent base-flow measurements are available. MOVE.1 regression is used widely throughout the hydrologic community to extend historic low flows and low-flow statistics at continuous-record streamgaging stations to streamgaging stations that have access to only a partial record of low flows. The method correlates base-flow measurements at PR streamgaging stations with daily mean streamflows measured at index stations that exhibit similar streamflow characteristics.
Following changes in the computing platform for storing, processing, retrieving, and publishing National Water Information System (NWIS) hydrologic data, legacy Statistical Analysis System (SAS) code developed by the USGS to implement the MOVE.1 regression was no longer suitable for reading and processing NWIS streamflow data. To migrate the MOVE.1 program so that it could continue to read streamflow data using the new hydrologic data platform, the SAS code was re-written in R, an open source programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The work described in this report was performed in a study conducted by USGS in cooperation with the New Jersey Department of Environmental Protection.
During migration from SAS to R, graphical and tabular output generated by the R script was compared to output produced by the legacy SAS code to ensure that equations used to perform the MOVE.1 regression remained the same. An option to perform censored MOVE.1 regression was added to extend the MOVE.1 methodology to cases where one or more measured continuous-record or PR streamgaging station flows are zero valued. In addition to permitting censored regression, the new R script includes an option to perform piecewise MOVE.1 regression when the relation between PR station and index station low flows varies significantly across the range of index station streamflows.
Together with traditional MOVE.1 regression, censored, and piecewise MOVE.1 regression methods implemented by the R script offer less biased estimates than ordinary least squares regression for the annual 7-day 10-year and other low-flow statistics at PR stations for a range of base-flow conditions. The R script is used to implement the MOVE.1 regression methods across a variety of computing platforms.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181089","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Colarullo, S.J., Sullivan, S.L., and McHugh, A.R., 2018, Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey: U.S. Geological Survey Open-File Report 2018–1089, 20 p., https://doi.org/10.3133/ofr20181089.","productDescription":"v, 20 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-089567","costCenters":[{"id":470,"text":"New Jersey Water Science 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Jersey\",\"nation\":\"USA \"}}]}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648