{"pageNumber":"55","pageRowStart":"1350","pageSize":"25","recordCount":16446,"records":[{"id":70216470,"text":"70216470 - 2020 - Exploring the potential of ground-penetrating radar (GPR) to measure the extent of chronic disturbance in peatlands: Examples from acid mine drainage and peat fire","interactions":[],"lastModifiedDate":"2020-11-23T14:39:05.647854","indexId":"70216470","displayToPublicDate":"2020-08-31T09:38:40","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Exploring the potential of ground-penetrating radar (GPR) to measure the extent of chronic disturbance in peatlands: Examples from acid mine drainage and peat fire","docAbstract":"

Peatlands are accumulations of partially decayed organic soil that cover approximately 3% of Earth’s surface and have been shown to serve essential environmental and ecological functions such as sequestering carbon, purifying water, and providing habitat for organisms. However, peatlands are threatened by pressures from agriculture, urban development, mining, and climate change. Geophysical methods have been used in peatlands to determine peat volume and carbon stocks (e.g., Comas et al., 2017), observe differences in humification and water content (e.g., Ulriksen, 1982), guide engineering projects (e.g., Jol and Smith, 1995), learn about subsurface greenhouse gas dynamics (Wright and Comas, 2016), observe seasonal variations in pore water salinity (Walter et al., 2018), and assess hydrological processes (Hare et al., 2017). Among various geophysical methods, ground penetrating radar (GPR) is arguably the most popular for studying peat properties given the method’s sensitivity to variations in water content and ability to resolve major structural properties within the peat at high spatial resolution. Though less widely applied, frequency-domain analysis of GPR may also yield useful information.

","conferenceTitle":"18th International Conference on Ground Penetrating Radar","conferenceDate":"June 14-19, 2020","conferenceLocation":"Golden, Colorado","language":"English","publisher":"Society of Exploration Geologists","doi":"10.1190/gpr2020-015.1","usgsCitation":"Terry, N., Runkel, R.L., Werkema, D.D., Rutila, E., Comas, X., Warren, M., Kristiyono, A., and Murdiyarso, D., 2020, Exploring the potential of ground-penetrating radar (GPR) to measure the extent of chronic disturbance in peatlands: Examples from acid mine drainage and peat fire, 18th International Conference on Ground Penetrating Radar, Golden, Colorado, June 14-19, 2020, p. 53-56, https://doi.org/10.1190/gpr2020-015.1.","productDescription":"4 p.","startPage":"53","endPage":"56","ipdsId":"IP-117032","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":380686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Terry, Neil 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":805218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":805220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":805219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rutila, Elizabeth 0000-0003-0288-9678","orcid":"https://orcid.org/0000-0003-0288-9678","contributorId":224637,"corporation":false,"usgs":false,"family":"Rutila","given":"Elizabeth","email":"","affiliations":[{"id":40900,"text":"Oakridge Institute for Science and Education","active":true,"usgs":false}],"preferred":false,"id":805371,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Comas, Xavier","contributorId":176879,"corporation":false,"usgs":false,"family":"Comas","given":"Xavier","affiliations":[],"preferred":false,"id":805221,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Warren, Matthew","contributorId":245034,"corporation":false,"usgs":false,"family":"Warren","given":"Matthew","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":805222,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kristiyono, Agus 0000-0001-6433-3902","orcid":"https://orcid.org/0000-0001-6433-3902","contributorId":245036,"corporation":false,"usgs":false,"family":"Kristiyono","given":"Agus","email":"","affiliations":[{"id":49058,"text":"Indonesian Agency for Assessment and Application of Technology (BPPT)","active":true,"usgs":false}],"preferred":false,"id":805223,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Murdiyarso, Daniel","contributorId":243962,"corporation":false,"usgs":false,"family":"Murdiyarso","given":"Daniel","email":"","affiliations":[{"id":48776,"text":"cifor","active":true,"usgs":false}],"preferred":false,"id":805224,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70218497,"text":"70218497 - 2020 - Coarse sediment dynamics in a large glaciated river system: Holocene history and storage dynamics dictate contemporary climate sensitivity","interactions":[],"lastModifiedDate":"2021-03-08T12:38:47.66941","indexId":"70218497","displayToPublicDate":"2020-08-31T07:06:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Coarse sediment dynamics in a large glaciated river system: Holocene history and storage dynamics dictate contemporary climate sensitivity","docAbstract":"

The gravel-bedded White River drains a 1279 km2 basin in Washington State, with lowlands sculpted by continental glaciation and headwaters on an actively glaciated stratovolcano. Chronic aggradation along an alluvial fan near the river’s mouth has progressively reduced flood conveyance. In order to better understand how forecasted climate change may influence coarse sediment delivery and aggradation rates in this lowland depositional setting, we assessed the contemporary delivery and routing of coarse sediment through the watershed; this assessment was based on a rich set of topographic, sedimentologic, and hydrologic data from the past century, with a focus on repeat high-resolution topographic surveys from the past decade.

We found that most of the lower river’s contemporary bed-load flux originates from persistent erosion of alluvial deposits in the lower watershed. This erosion is a response to a drop in local base level caused by a major avulsion across the fan in 1906 and then augmented by subsequent dredging. The 1906 avulsion and modern disequilibrium valley profiles reflect landscape conditioning by continental glaciation and a massive mid-Holocene lahar. In the proglacial headwaters, infrequent large sediment pulses have accomplished most of the observed coarse sediment export, with exported material blanketing downstream valley floors; during typical floods, transported bed material is largely sourced from erosion of these valley floor deposits. Throughout the watershed, we observe decadal-scale coarse sediment dynamics strongly related to the filling or emptying of valley-scale sediment storage over 102−104 yr time scales, often in response to major disturbances that either emplace large deposits or influence their redistribution. Paraglacial responses in large watersheds are suggested to be inherently complicated and punctuated as a result of internal landform interactions and stochastic/threshold-dependent events. We argue, in combination, that Holocene disturbance, storage dynamics, and human flow modification make coarse sediment fluxes in the lower White River relatively insensitive to decadal climate variability. Results highlight the degree to which river sensitivity to contemporary disturbance, climatic or otherwise, may be contingent on local and idiosyncratic watershed histories, underscoring the need to unpack those histories while demonstrating the utility of watershed-scale high-resolution topography toward that end.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35530.1","usgsCitation":"Anderson, S.W., and Jaeger, K.L., 2020, Coarse sediment dynamics in a large glaciated river system: Holocene history and storage dynamics dictate contemporary climate sensitivity: Geological Society of America Bulletin, 24 p., https://doi.org/10.1130/B35530.1.","productDescription":"24 p.","ipdsId":"IP-106664","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":436809,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HT46KB","text":"USGS data release","linkHelpText":"Supporting Data for Sediment Studies in the White River Watershed"},{"id":383708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"White River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.68981933593749,\n 46.72856582519053\n ],\n [\n -121.58843994140625,\n 46.72856582519053\n ],\n [\n -121.58843994140625,\n 47.31648293428332\n ],\n [\n -122.68981933593749,\n 47.31648293428332\n ],\n [\n -122.68981933593749,\n 46.72856582519053\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-08-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":811210,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216697,"text":"70216697 - 2020 - Permafrost hydrogeology","interactions":[],"lastModifiedDate":"2020-12-01T13:39:38.019573","indexId":"70216697","displayToPublicDate":"2020-08-29T07:38:34","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Permafrost hydrogeology","docAbstract":"

Groundwater processes are often overlooked in permafrost environments, but subsurface storage and routing can strongly influence water and biogeochemical cycling in northern catchments. Groundwater flow in permafrost regions is controlled by the temporal and spatial distribution of frozen ground, causing the hydrogeologic framework to be temperature-dependent. Most flow occurs in geologic units above the permafrost table (supra-permafrost aquifers) or below the permafrost base (sub-permafrost aquifers). In the context of climate change, thawing permafrost is altering groundwater flowpaths and thereby inducing positive trends in river baseflow in many discontinuous permafrost basins. Activated groundwater systems can provide new conduits for flushing Arctic basins and transporting nutrients to basin outlets. The thermal and hydraulic physics that govern groundwater flow in permafrost regions are strongly coupled and more complex than those in non-permafrost settings. Recent research activity in permafrost hydrogeological modeling has resulted in several mainstream groundwater models (e.g., SUTRA, FEFLOW, HYDRUS) offering users advanced capabilities for simulating processes in aquifers that experience dynamic freeze-thaw. This chapter relies on field examples to review key processes and conditions that control groundwater dynamics in permafrost settings and presents an up-to-date synthesis of the mathematical representation of heat transfer and groundwater flow in northern landscapes.


","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Arctic hydrology, permafrost and ecosystems","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-50930-9_17","usgsCitation":"Kurylyk, B.L., and Walvoord, M.A., 2020, Permafrost hydrogeology, chap. of Arctic hydrology, permafrost and ecosystems, p. 493-523, https://doi.org/10.1007/978-3-030-50930-9_17.","productDescription":"31 p.","startPage":"493","endPage":"523","ipdsId":"IP-095432","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":380908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Kurylyk, Barret L.","contributorId":176296,"corporation":false,"usgs":false,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":805914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":805915,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206398,"text":"sir20195130 - 2020 - Use of boosted regression trees to quantify cumulative instream flow resulting from curtailment of irrigation in the Sprague River basin, Oregon","interactions":[],"lastModifiedDate":"2020-08-31T12:30:21.007926","indexId":"sir20195130","displayToPublicDate":"2020-08-28T09:28:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5130","displayTitle":"Use of Boosted Regression Trees to Quantify Cumulative Instream Flow Resulting from Curtailment of Irrigation in the Sprague River Basin, Oregon","title":"Use of boosted regression trees to quantify cumulative instream flow resulting from curtailment of irrigation in the Sprague River basin, Oregon","docAbstract":"A boosted regression trees (BRT) approach was used to estimate the amount by which streamflow is increased when irrigation is regulated (curtailed) upstream of a streamgage on the Sprague River in southern-central Oregon. The BRT approach differs from most other approaches that require baseline conditions for comparison, where those baseline conditions are determined from past observations by searching for hydrologically similar years when irrigation was not regulated. Such baseline conditions are always imperfect estimates of the true baseline conditions. The BRT approach instead estimates unique baseline conditions for any year in which irrigation is regulated by calculating the baseline condition based on measurements of precipitation and weather observations that determine evapotranspiration, and other measurements that are proxies for the effects of climate and regional groundwater pumping on water-table elevation, using a model that has been trained in years of no regulation. The amount by which streamflow is increased by regulation is then calculated by subtracting the estimated baseline conditions from the measured streamflow. The approach is challenged by the fact that the streamflow increase may be a small fraction of the total streamflow; nonetheless, during 2 years in which regulation was started early and was implemented consistently through the season, the increased flow made up about one third of the flow past the streamgage during the regulation period. An advantage of this approach is that with rigorous model testing with holdout data, the threshold for detecting streamflow increase and intervals around the estimates of increase at a desired level of confidence can be quantified. The model relies on datasets that are readily available and updated continuously and therefore can be used operationally to inform resource management.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195130","collaboration":"Prepared in cooperation with the Bureau of Reclamation
(Interagency Agreement R16PG00120)","usgsCitation":"Wood, T.M., 2019, Use of boosted regression trees to quantify cumulative instream flow resulting from curtailment of irrigation in the Sprague River basin, Oregon: U.S. Geological Survey Scientific Investigations Report 2019-5130, 25 p., https://doi.org/10.3133/sir20195130.","productDescription":"vi, 25 p.","onlineOnly":"Y","ipdsId":"IP-100543","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":377906,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5130/sir20195130.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5130"},{"id":377905,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5130/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Sprague River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.04687499999999,\n 42.00032514831621\n ],\n [\n -118.69628906249999,\n 42.00032514831621\n ],\n [\n -118.69628906249999,\n 44.008620115415354\n ],\n [\n -123.04687499999999,\n 44.008620115415354\n ],\n [\n -123.04687499999999,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2020-08-28","noUsgsAuthors":false,"publicationDate":"2020-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Tamara M. 0000-0001-6057-8080 tmwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6057-8080","contributorId":1164,"corporation":false,"usgs":true,"family":"Wood","given":"Tamara","email":"tmwood@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":774399,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70212472,"text":"sir20205065 - 2020 - Flood-frequency estimation for very low annual exceedance probabilities using historical, paleoflood, and regional information with consideration of nonstationarity","interactions":[],"lastModifiedDate":"2020-08-26T12:58:26.704616","indexId":"sir20205065","displayToPublicDate":"2020-08-25T14:37:00","publicationYear":"2020","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":"2020-5065","displayTitle":"Flood-Frequency Estimation for Very Low Annual Exceedance Probabilities Using Historical, Paleoflood, and Regional Information with Consideration of Nonstationarity","title":"Flood-frequency estimation for very low annual exceedance probabilities using historical, paleoflood, and regional information with consideration of nonstationarity","docAbstract":"

Streamflow estimates for floods with an annual exceedance probability of 0.001 or lower are needed to accurately portray risks to critical infrastructure, such as nuclear powerplants and large dams. However, extrapolating flood-frequency curves developed from at-site systematic streamflow records to very low annual exceedance probabilities (less than 0.001) results in large uncertainties in the streamflow estimates. Traditionally, methods for statistically estimating flood frequency have relied on the systematic streamflow record, which provides a time series of annual maximum flood peaks, often including some historical peaks. However, most peak-flow records are less than 100 years, and uncertainties are large when trying to extrapolate magnitudes of very low annual exceedance probability events.

Other data may be available that extend the record beyond the systematic dataset. Historical data are defined as data from outside the period of systematic records but within the period of human records. Examples of historical information include flood estimates from other agencies and newspaper accounts that can be translated to flood magnitude point estimates, interval estimates, or perception thresholds (such as a statement that an 1880 flood was the largest since 1869). Paleoflood data, which may also extend the dataset, include a broad range of information about flood occurrence or magnitude from sources like sediment deposits or tree rings.

Several assumptions are made in flood-frequency analysis, and an understanding of whether the data conform to these assumptions is desired. A particularly difficult assumption to evaluate for flood-frequency analysis is the underlying assumption that the flood series is stationary—the assumption that a time series of peak flow varies around a constant mean within a particular range of values (constant variance). As the hydrologic community’s understanding of natural systems and anthropogenic effects on streamflows has evolved, the community has come to understand that many surface-water systems exhibit one or more forms of nonstationarity, and thus the stationarity assumption is often violated to some degree. However, there is currently (2020) no consensus among hydrologists regarding the most appropriate flood-frequency-analysis methods for nonstationary systems, and this topic remains an active area of research.

A literature review was completed to summarize the state of the science of flood frequency. The literature review highlights tools available to detect nonstationarities and identifies approaches that include external information to inform flood-frequency analysis. To demonstrate methods for initial data analysis and for incorporating historical and paleoflood information in flood-frequency analysis, five sites were selected: the Red River of the North at James Avenue Pumping Station, Winnipeg, Manitoba, Canada; lower reach, Rapid Creek, South Dakota; Spring Creek, South Dakota; Cherry Creek near Melvin, Colorado; and Escalante River near Escalante, Utah. The sites were chosen for the availability of published historical and paleoflood data and for their geographic diversity and unique characteristics, which highlighted issues such as autocorrelation, change points, trends, outlier peaks, or short periods of record.

An initial data analysis that involved examining records for autocorrelation, change points, and trends was completed for all sites. The flood-frequency analysis completed for this study used version 7.2 of the U.S. Geological Survey PeakFQ program. Multiple analyses were done on each site documenting the change in the flood-frequency curve when additional historical or paleoflood data were added. When other flood-frequency studies were available, their results were compared to the results here. The comparisons in some cases simply show the effect of additional years of data, whereas other comparisons show results from probability distributions or fitting methods other than those used in PeakFQ.

For the Red River of the North, flood-frequency analysis shows that paleoflood data appear necessary to reasonably estimate very low annual exceedance probabilities. For the analysis of the lower reach of Rapid Creek and Spring Creek, paleoflood information helped put a high outlier from the systematic period in context; however, very low annual exceedance probabilities at these sites still had extraordinarily large confidence bounds. These sites also showed that paleoflood information might be transferred from one site to another, with the caveat that this is a case where we had existing paleoflood data to test the transfer of paleoflood information—this is not the case at many sites, and transferring paleoflood information requires assumptions about the comparability of floods at the sites. The Cherry Creek analysis affirmed the result of an earlier study that showed that the generalized Pareto distribution was not a good distribution for estimating very low annual exceedance probabilities. The Escalante River analysis showed that adding paleoflood information might increase uncertainty for very low annual exceedance probabilities, compared to analysis with the systematic period of record information only, when the paleoflood peaks are of much larger magnitudes than the systematic record.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205065","collaboration":"Prepared in cooperation with the U.S. Nuclear Regulatory Commission","usgsCitation":"Ryberg, K.R., Kolars, K.A., Kiang, J.E., and Carr, M.L., 2020, Flood-frequency estimation for very low annual exceedance probabilities using historical, paleoflood, and regional information with consideration of nonstationarity: U.S. Geological Survey Scientific Investigations Report 2020–5065, 89 p., https://doi.org/10.3133/sir20205065.","productDescription":"Report: xii, 89 p.; 5 Tables; Appendix; Dataset","numberOfPages":"105","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088812","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":377559,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5065/sir20205065_appendix.zip","text":"Appendix 1. Data, Settings, and Output for Each Site and Scenario","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2020–5065 Appendix 1","linkHelpText":"— Each zipped file represents the analysis for a particular site and scenario"},{"id":377557,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5065/sir20205065_table_7.pdf","text":"Table 7","size":"114 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5065 Table 7","linkHelpText":"— Streamflow estimates (fit) for selected annual exceedance probabilities and associated confidence intervals (lower and upper) and variance estimates for flood-frequency analysis under two different scenarios using U.S. Geological Survey PeakFQ software (Veilleux and others, 2014) version 7.2 for streamgage station 06712500 Cherry Creek near Melvin, Colorado, with comparisons to other distributions and fitting methods."},{"id":377553,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5065/sir20205065.pdf","text":"Report","size":"5.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5065"},{"id":377554,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5065/sir20205065_table_4.pdf","text":"Table 4","size":"139 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5065 Table 4","linkHelpText":"— Streamflow estimates (fit) for selected annual exceedance probabilities and associated confidence intervals (lower and upper) and variance estimates for flood-frequency analysis under 10 different scenarios using U.S. Geological Survey PeakFQ software (Veilleux and others, 2014) version 7.2 for streamgage station 05OJ015 Red River of the North at James Avenue Pumping Station, Winnipeg, Manitoba, Canada, as well as results from flood-frequency studies by Burn and Goel (2001) and Harden (1999)."},{"id":377697,"rank":9,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":377555,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5065/sir20205065_table_5.pdf","text":"Table 5","size":"122 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5065 Table 5","linkHelpText":"— Streamflow estimates (fit) for selected annual exceedance probabilities and associated confidence intervals (lower and upper) and variance estimates for flood-frequency analysis under three different scenarios using U.S. Geological Survey PeakFQ software (Veilleux and others, 2014) version 7.2 for the lower reach of Rapid Creek, South Dakota, with comparisons to Harden and others (2011)."},{"id":377556,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5065/sir20205065_table_6.pdf","text":"Table 6","size":"112 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5065 Table 6","linkHelpText":"— Streamflow estimates (fit) for selected annual exceedance probabilities and associated confidence intervals (lower and upper) and variance estimates for flood-frequency analysis under three different scenarios using U.S. Geological Survey PeakFQ software (Veilleux and others, 2014) version 7.2 for Spring Creek, South Dakota, with comparisons to Harden and others (2011)."},{"id":377552,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5065/coverthb.jpg"},{"id":377558,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5065/sir20205065_table_8.pdf","text":"Table 8","size":"116 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5065 Table 8","linkHelpText":"— Streamflow estimates (fit) for selected annual exceedance probabilities and associated confidence intervals (lower and upper) and variance estimates for flood-frequency analysis under three different scenarios using U.S. Geological Survey PeakFQ software (Veilleux and others, 2014) version 7.2 for streamgage station 09337500 Escalante River near Escalante, Utah, with comparisons to Webb and others (1988), Webb and Rathburn (1988), and Kenney and others (2008)."}],"contact":"

Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-08-25","noUsgsAuthors":false,"publicationDate":"2020-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Ryberg, Karen R. 0000-0002-9834-2046 kryberg@usgs.gov","orcid":"https://orcid.org/0000-0002-9834-2046","contributorId":1172,"corporation":false,"usgs":true,"family":"Ryberg","given":"Karen","email":"kryberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":796398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kolars, Kelsey A. 0000-0002-0540-3285 kkolars@usgs.gov","orcid":"https://orcid.org/0000-0002-0540-3285","contributorId":152116,"corporation":false,"usgs":true,"family":"Kolars","given":"Kelsey","email":"kkolars@usgs.gov","middleInitial":"A.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":796399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":796400,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carr, Meredith L. 0000-0003-1970-8511","orcid":"https://orcid.org/0000-0003-1970-8511","contributorId":238712,"corporation":false,"usgs":false,"family":"Carr","given":"Meredith","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":796401,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70212674,"text":"sir20205073 - 2020 - Development of regional skew coefficients for selected flood durations in the Columbia River Basin, northwestern United States and British Columbia, Canada","interactions":[],"lastModifiedDate":"2020-10-15T14:35:08.197052","indexId":"sir20205073","displayToPublicDate":"2020-08-25T12:25:45","publicationYear":"2020","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":"2020-5073","displayTitle":"Development of Regional Skew Coefficients for Selected Flood Durations in the Columbia River Basin, Northwestern United States and British Columbia, Canada","title":"Development of regional skew coefficients for selected flood durations in the Columbia River Basin, northwestern United States and British Columbia, Canada","docAbstract":"

Flood-frequency (hereinafter frequency) estimates provide information used to design, operate, and maintain hydraulic structures such as bridges and dams. Failures of these structures could cause catastrophic loss of property, life, or both. In addition to frequency estimates that use annual peak streamflow, frequency estimates of flood durations are required to safely and effectively operate the numerous dams in the Columbia River Basin of the northwestern United States, and British Columbia, Canada. Frequency studies rely on U.S. Geological Survey Guidelines for Determining Flood Flow Frequency (Bulletin 17C, published in 2018). A major consideration in estimating frequencies is the use of skew coefficients, which measure the asymmetry of flood flow distributions. Large uncertainties are associated with estimating the at-site skew coefficients directly from streamflow records, which are limited in length. Skew also is sensitive to extreme events for limited record lengths. Bulletin 17C recommends using regional skew coefficients to weight with the at-site skew estimate for more reliable frequency estimates. In this study, streamflow records from 313 unregulated U.S. Geological Survey streamgage sites and 97 regulated sites with naturalized streamflow records provided by the U.S. Army Corps of Engineers were used to develop regional skew models for the Columbia River Basin. The naturalized streamflow records were synthesized by removing regulatory components such as withdrawals and reservoir storage. Skew models were developed for 1-, 3-, 7-, 10-, 15-, 30-, and 60-day flood durations and used to estimate regional skew coefficients for the Columbia River Basin.

This report used Bayesian statistical regression methods to develop and analyze regional skew models based on hydrologically important basin characteristics. After examining a suite of available basin characteristics, mean annual precipitation had the strongest correlation to skew across the flood durations. Regional skew regression models were fit using mean annual precipitation for selected subbasins in the Columbia River Basin.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205073","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Lind, G.D., Lamontagne, J.R., and Stonewall, A.J., 2020, Development of regional skew coefficients for selected flood durations in the Columbia River Basin, northwestern United States and British Columbia, Canada (ver. 1.1, October 2020): U.S. Geological Survey Scientific Investigations Report 2020–5073, 48 p., https://doi.org/10.3133/sir20205073.","productDescription":"Report: viii, 48 p.; 8 Tables; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-109443","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":377840,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5073/sir20205073_table1.csv","text":"Table 1","size":"26 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020-5073 Table 1"},{"id":377846,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5073/sir20205073_table2.4.csv","text":"Table 2.4","size":"22 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020-5073 Table 2.4"},{"id":377838,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5073/coverthb2.jpg"},{"id":377848,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7P55KJN","text":"USGS data release","description":"USGS Data Release","linkHelpText":"National Water Information System: Web Interface"},{"id":377847,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5073/sir20205073_table2.5.csv","text":"Table 2.5","size":"20 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020-5073 Table 2.5"},{"id":377845,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5073/sir20205073_table2.2.csv","text":"Table 2.2","size":"10 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020-5073 Table 2.2"},{"id":377844,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5073/sir20205073_table2.1.csv","text":"Table 2.1","size":"4 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020-5073 Table 2.1"},{"id":377843,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5073/sir20205073_table1.3.csv","text":"Table 1.3","size":"6 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020-5073 Table 1.3"},{"id":377842,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5073/sir20205073_table1.2.csv","text":"Table 1.2","size":"64 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020-5073 Table 1.2"},{"id":377841,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5073/sir20205073_table1.1.csv","text":"Table 1.1","size":"66 KB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020-5073 Table 1.1"},{"id":377839,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5073/sir20205073.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5073"},{"id":379386,"rank":12,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2020/5073/versionhist.txt","size":"724 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2020-5073 Version History"}],"country":"United States, Canada","otherGeospatial":"Columbia River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.92578125,\n 46.5739667965278\n ],\n [\n -124.25537109375,\n 46.24824991289166\n ],\n [\n -124.04663085937499,\n 45.82879925192134\n ],\n [\n -123.53027343749999,\n 45.460130637921004\n ],\n [\n -122.9150390625,\n 45.27488643704891\n ],\n [\n -122.32177734375,\n 45.13555516012536\n ],\n [\n -121.39892578125,\n 44.809121700077355\n ],\n [\n -120.32226562500001,\n 44.22158376545796\n ],\n [\n -119.28955078124999,\n 43.95328204198018\n ],\n [\n -118.61938476562499,\n 43.01268088642034\n ],\n [\n -117.894287109375,\n 42.32606244456202\n ],\n [\n -117.50976562499999,\n 41.86956082699455\n ],\n [\n -117.42187500000001,\n 42.17968819665961\n ],\n [\n -117.0703125,\n 41.582579601430346\n ],\n [\n -116.334228515625,\n 40.95501133048621\n ],\n [\n -115.323486328125,\n 40.538851525354666\n ],\n [\n -114.27978515625,\n 41.46742831254425\n ],\n [\n -113.763427734375,\n 41.983994270935625\n ],\n [\n -113.35693359375,\n 42.05745022024682\n ],\n [\n -112.291259765625,\n 42.3016903282445\n ],\n [\n -110.74218749999999,\n 42.342305278572816\n ],\n [\n -109.58862304687499,\n 41.97582726102573\n ],\n [\n -108.709716796875,\n 42.46399280017058\n ],\n [\n -109.248046875,\n 43.197167282501276\n ],\n [\n -109.5556640625,\n 43.739352079154706\n ],\n [\n -110.478515625,\n 44.08758502824516\n ],\n [\n -111.005859375,\n 44.11914151643737\n ],\n [\n -111.22558593749999,\n 45.182036837015886\n ],\n [\n -111.70898437499999,\n 46.164614496897094\n ],\n [\n -112.4560546875,\n 47.249406957888446\n ],\n [\n -113.48876953125,\n 48.40003249610685\n ],\n [\n -114.697265625,\n 49.26780455063753\n ],\n [\n -114.93896484374999,\n 50.44351305245805\n ],\n [\n -116.91650390625,\n 51.57706953722565\n ],\n [\n -118.63037109375,\n 52.45600939264076\n ],\n [\n -120.30029296875,\n 53.891391285752874\n ],\n [\n -121.79443359375,\n 54.316523240258256\n ],\n [\n -122.6513671875,\n 54.25238930276849\n ],\n [\n -122.76123046875,\n 53.80065082633023\n ],\n [\n -122.71728515624999,\n 53.225768435790194\n ],\n [\n -122.32177734375,\n 52.36218321674427\n ],\n [\n -122.32177734375,\n 51.998410382390325\n ],\n [\n -121.59667968749999,\n 50.233151832472245\n ],\n [\n -121.4208984375,\n 49.15296965617042\n ],\n [\n -121.09130859375,\n 48.04870994288686\n ],\n [\n -121.2451171875,\n 47.040182144806664\n ],\n [\n -122.62939453125001,\n 46.36209301204985\n ],\n [\n -123.92578125,\n 46.5739667965278\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: August 2020; Version 1.1: October 2020","contact":"

Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2020-08-25","revisedDate":"2020-10-14","noUsgsAuthors":false,"publicationDate":"2020-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Lind, Greg D. 0000-0001-5385-2117 glind@usgs.gov","orcid":"https://orcid.org/0000-0001-5385-2117","contributorId":5514,"corporation":false,"usgs":true,"family":"Lind","given":"Greg","email":"glind@usgs.gov","middleInitial":"D.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamontagne, Jonathan R. 0000-0003-3976-1678","orcid":"https://orcid.org/0000-0003-3976-1678","contributorId":31640,"corporation":false,"usgs":true,"family":"Lamontagne","given":"Jonathan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":797263,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stonewall, Adam J. 0000-0002-3277-8736 stonewal@usgs.gov","orcid":"https://orcid.org/0000-0002-3277-8736","contributorId":2699,"corporation":false,"usgs":true,"family":"Stonewall","given":"Adam J.","email":"stonewal@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":797264,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70212768,"text":"70212768 - 2020 - Reducing water scarcity by improving water productivity in the United States","interactions":[],"lastModifiedDate":"2020-08-27T16:59:15.03136","indexId":"70212768","displayToPublicDate":"2020-08-25T11:55:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Reducing water scarcity by improving water productivity in the United States","docAbstract":"

Nearly one-sixth of U.S. river basins are unable to consistently meet societal water demands while also providing sufficient water for the environment. Water scarcity is expected to intensify and spread as populations increase, new water demands emerge, and climate changes. Improving water productivity by meeting realistic benchmarks for all water users could allow U.S. communities to expand economic activity and improve environmental flows. Here we utilize a spatially detailed database of water productivity to set realistic benchmarks for over 400 industries and products. We assess unrealized water savings achievable by each industry in each river basin within the conterminous U.S. by bringing all water users up to industry- and region-specific water productivity benchmarks. Some of the most water stressed areas throughout the U.S. West and South have the greatest potential for water savings, with around half of these water savings obtained by improving water productivity in the production of corn, cotton, and alfalfa. By incorporating benchmark-meeting water savings within a national hydrological model (WaSSI), we demonstrate that depletion of river flows across Western U.S. regions can be reduced on average by 6.2–23.2%, without reducing economic production. Lastly, we employ an environmentally extended input-output model to identify the U.S. industries and locations that can make the biggest impact by working with their suppliers to reduce water use 'upstream' in their supply chain. The agriculture and manufacturing sectors have the largest indirect water footprint due to their reliance on water-intensive inputs but these sectors also show the greatest capacity to reduce water consumption throughout their supply chains.

","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ab9d39","usgsCitation":"Marston, L., Lamsal, G., Ancona, Z.H., Caldwell, P.V., Richter, B., Ruddell, B., Rushforth, R., and Davis, K.F., 2020, Reducing water scarcity by improving water productivity in the United States: Environmental Research Letters, v. 15, no. 9, 094033, 13 p., https://doi.org/10.1088/1748-9326/ab9d39.","productDescription":"094033, 13 p.","ipdsId":"IP-114542","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":455531,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ab9d39","text":"Publisher Index Page"},{"id":377942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Conterminous United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n -83.61613,\n 46.11693\n ],\n [\n -83.46955,\n 45.99469\n ],\n [\n -83.59285,\n 45.81689\n ],\n [\n -82.55092,\n 45.34752\n ],\n [\n -82.33776,\n 44.44\n ],\n [\n -82.13764,\n 43.57109\n ],\n [\n -82.43,\n 42.98\n ],\n [\n -82.9,\n 42.43\n ],\n [\n -83.12,\n 42.08\n ],\n [\n -83.142,\n 41.97568\n ],\n [\n -83.02981,\n 41.8328\n ],\n [\n -82.69009,\n 41.67511\n ],\n [\n -82.43928,\n 41.67511\n ],\n [\n -81.27775,\n 42.20903\n ],\n [\n -80.24745,\n 42.3662\n ],\n [\n -78.93936,\n 42.86361\n ],\n [\n -78.92,\n 42.965\n ],\n [\n -79.01,\n 43.27\n ],\n [\n -79.17167,\n 43.46634\n ],\n [\n -78.72028,\n 43.62509\n ],\n [\n -77.73789,\n 43.62906\n ],\n [\n -76.82003,\n 43.62878\n ],\n [\n -76.5,\n 44.01846\n ],\n [\n -76.375,\n 44.09631\n ],\n [\n -75.31821,\n 44.81645\n ],\n [\n -74.867,\n 45.00048\n ],\n [\n -73.34783,\n 45.00738\n ],\n [\n -71.50506,\n 45.0082\n ],\n [\n -71.405,\n 45.255\n ],\n [\n -71.08482,\n 45.30524\n ],\n [\n -70.66,\n 45.46\n ],\n [\n -70.305,\n 45.915\n ],\n [\n -69.99997,\n 46.69307\n ],\n [\n -69.23722,\n 47.44778\n ],\n [\n -68.905,\n 47.185\n ],\n [\n -68.23444,\n 47.35486\n ],\n [\n -67.79046,\n 47.06636\n ],\n [\n -67.79134,\n 45.70281\n ],\n [\n -67.13741,\n 45.13753\n ],\n [\n -66.96466,\n 44.8097\n ],\n [\n -68.03252,\n 44.3252\n ],\n [\n -69.06,\n 43.98\n ],\n [\n -70.11617,\n 43.68405\n ],\n [\n -70.64548,\n 43.09024\n ],\n [\n -70.81489,\n 42.8653\n ],\n [\n -70.825,\n 42.335\n ],\n [\n -70.495,\n 41.805\n ],\n [\n -70.08,\n 41.78\n ],\n [\n -70.185,\n 42.145\n ],\n [\n -69.88497,\n 41.92283\n ],\n [\n -69.96503,\n 41.63717\n ],\n [\n -70.64,\n 41.475\n ],\n [\n -71.12039,\n 41.49445\n ],\n [\n -71.86,\n 41.32\n ],\n [\n -72.295,\n 41.27\n ],\n [\n -72.87643,\n 41.22065\n ],\n [\n -73.71,\n 40.9311\n ],\n [\n -72.24126,\n 41.11948\n ],\n [\n -71.945,\n 40.93\n ],\n [\n -73.345,\n 40.63\n ],\n [\n -73.982,\n 40.628\n ],\n [\n -73.95232,\n 40.75075\n ],\n [\n -74.25671,\n 40.47351\n ],\n [\n -73.96244,\n 40.42763\n ],\n [\n -74.17838,\n 39.70926\n ],\n [\n -74.90604,\n 38.93954\n ],\n [\n -74.98041,\n 39.1964\n ],\n [\n -75.20002,\n 39.24845\n ],\n [\n -75.52805,\n 39.4985\n ],\n [\n -75.32,\n 38.96\n ],\n [\n -75.07183,\n 38.78203\n ],\n [\n -75.05673,\n 38.40412\n ],\n [\n -75.37747,\n 38.01551\n ],\n [\n -75.94023,\n 37.21689\n ],\n [\n -76.03127,\n 37.2566\n ],\n [\n -75.72205,\n 37.93705\n ],\n [\n -76.23287,\n 38.31921\n ],\n [\n -76.35,\n 39.15\n ],\n [\n -76.54272,\n 38.71762\n ],\n [\n -76.32933,\n 38.08326\n ],\n [\n -76.99,\n 38.23999\n ],\n [\n -76.30162,\n 37.91794\n ],\n [\n -76.25874,\n 36.9664\n ],\n [\n -75.9718,\n 36.89726\n ],\n [\n -75.86804,\n 36.55125\n ],\n [\n -75.72749,\n 35.55074\n ],\n [\n -76.36318,\n 34.80854\n ],\n [\n -77.39763,\n 34.51201\n ],\n [\n -78.05496,\n 33.92547\n ],\n [\n -78.55435,\n 33.86133\n ],\n [\n -79.06067,\n 33.49395\n ],\n [\n -79.20357,\n 33.15839\n ],\n [\n -80.30132,\n 32.50935\n ],\n [\n -80.86498,\n 32.0333\n ],\n [\n -81.33629,\n 31.44049\n ],\n [\n -81.49042,\n 30.72999\n ],\n [\n -81.31371,\n 30.03552\n ],\n [\n -80.98,\n 29.18\n ],\n [\n -80.53558,\n 28.47213\n ],\n [\n -80.53,\n 28.04\n ],\n [\n -80.05654,\n 26.88\n ],\n [\n -80.08801,\n 26.20576\n ],\n [\n -80.13156,\n 25.81677\n ],\n [\n -80.38103,\n 25.20616\n ],\n [\n -80.68,\n 25.08\n ],\n [\n -81.17213,\n 25.20126\n ],\n [\n -81.33,\n 25.64\n ],\n [\n -81.71,\n 25.87\n ],\n [\n -82.24,\n 26.73\n ],\n [\n -82.70515,\n 27.49504\n ],\n [\n -82.85526,\n 27.88624\n ],\n [\n -82.65,\n 28.55\n ],\n [\n -82.93,\n 29.1\n ],\n [\n -83.70959,\n 29.93656\n ],\n [\n -84.1,\n 30.09\n ],\n [\n -85.10882,\n 29.63615\n ],\n [\n -85.28784,\n 29.68612\n ],\n [\n -85.7731,\n 30.15261\n ],\n [\n -86.4,\n 30.4\n ],\n [\n -87.53036,\n 30.27433\n ],\n [\n -88.41782,\n 30.3849\n ],\n [\n -89.18049,\n 30.31598\n ],\n [\n -89.59383,\n 30.15999\n ],\n [\n -89.41373,\n 29.89419\n ],\n [\n -89.43,\n 29.48864\n ],\n [\n -89.21767,\n 29.29108\n ],\n [\n -89.40823,\n 29.15961\n ],\n [\n -89.77928,\n 29.30714\n ],\n [\n -90.15463,\n 29.11743\n ],\n [\n -90.88022,\n 29.14854\n ],\n [\n -91.62678,\n 29.677\n ],\n [\n -92.49906,\n 29.5523\n ],\n [\n -93.22637,\n 29.78375\n ],\n [\n -93.84842,\n 29.71363\n ],\n [\n -94.69,\n 29.48\n ],\n [\n -95.60026,\n 28.73863\n ],\n [\n -96.59404,\n 28.30748\n ],\n [\n -97.14,\n 27.83\n ],\n [\n -97.37,\n 27.38\n ],\n [\n -97.38,\n 26.69\n ],\n [\n -97.33,\n 26.21\n ],\n [\n -97.14,\n 25.87\n ],\n [\n -97.53,\n 25.84\n ],\n [\n -98.24,\n 26.06\n ],\n [\n -99.02,\n 26.37\n ],\n [\n -99.3,\n 26.84\n ],\n [\n -99.52,\n 27.54\n ],\n [\n -100.11,\n 28.11\n ],\n [\n -100.45584,\n 28.69612\n ],\n [\n -100.9576,\n 29.38071\n ],\n [\n -101.6624,\n 29.7793\n ],\n [\n -102.48,\n 29.76\n ],\n [\n -103.11,\n 28.97\n ],\n [\n -103.94,\n 29.27\n ],\n [\n -104.45697,\n 29.57196\n ],\n [\n -104.70575,\n 30.12173\n ],\n [\n -105.03737,\n 30.64402\n ],\n [\n -105.63159,\n 31.08383\n ],\n [\n -106.1429,\n 31.39995\n ],\n [\n -106.50759,\n 31.75452\n ],\n [\n -108.24,\n 31.75485\n ],\n [\n -108.24194,\n 31.34222\n ],\n [\n -109.035,\n 31.34194\n ],\n [\n -111.02361,\n 31.33472\n ],\n [\n -113.30498,\n 32.03914\n ],\n [\n -114.815,\n 32.52528\n ],\n [\n -114.72139,\n 32.72083\n ],\n [\n -115.99135,\n 32.61239\n ],\n [\n -117.12776,\n 32.53534\n ],\n [\n -117.29594,\n 33.04622\n ],\n [\n -117.944,\n 33.62124\n ],\n [\n -118.4106,\n 33.74091\n ],\n [\n -118.51989,\n 34.02778\n ],\n [\n -119.081,\n 34.078\n ],\n [\n -119.43884,\n 34.34848\n ],\n [\n -120.36778,\n 34.44711\n ],\n [\n -120.62286,\n 34.60855\n ],\n [\n -120.74433,\n 35.15686\n ],\n [\n -121.71457,\n 36.16153\n ],\n [\n -122.54747,\n 37.55176\n ],\n [\n -122.51201,\n 37.78339\n ],\n [\n -122.95319,\n 38.11371\n ],\n [\n -123.7272,\n 38.95166\n ],\n [\n -123.86517,\n 39.76699\n ],\n [\n -124.39807,\n 40.3132\n ],\n [\n -124.17886,\n 41.14202\n ],\n [\n -124.2137,\n 41.99964\n ],\n [\n -124.53284,\n 42.76599\n ],\n [\n -124.14214,\n 43.70838\n ],\n [\n -124.02053,\n 44.6159\n ],\n [\n -123.89893,\n 45.52341\n ],\n [\n -124.07963,\n 46.86475\n ],\n [\n -124.39567,\n 47.72017\n ],\n [\n -124.68721,\n 48.18443\n ],\n [\n -124.5661,\n 48.37971\n ],\n [\n -123.12,\n 48.04\n ],\n [\n -122.58736,\n 47.096\n ],\n [\n -122.34,\n 47.36\n ],\n [\n -122.5,\n 48.18\n ],\n [\n -122.84,\n 49\n ],\n [\n -120,\n 49\n ],\n [\n -117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"15","issue":"9","noUsgsAuthors":false,"publicationDate":"2020-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Marston, Landon 0000-0001-9116-1691","orcid":"https://orcid.org/0000-0001-9116-1691","contributorId":239626,"corporation":false,"usgs":false,"family":"Marston","given":"Landon","email":"","affiliations":[{"id":47941,"text":"Department of Civil Engineering, Kansas State University","active":true,"usgs":false}],"preferred":false,"id":797428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamsal, Gambhir","contributorId":239627,"corporation":false,"usgs":false,"family":"Lamsal","given":"Gambhir","email":"","affiliations":[{"id":47941,"text":"Department of Civil Engineering, Kansas State University","active":true,"usgs":false}],"preferred":false,"id":797429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ancona, Zachary H. 0000-0001-5430-0218 zancona@usgs.gov","orcid":"https://orcid.org/0000-0001-5430-0218","contributorId":5578,"corporation":false,"usgs":true,"family":"Ancona","given":"Zachary","email":"zancona@usgs.gov","middleInitial":"H.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":797430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caldwell, Peter V","contributorId":145892,"corporation":false,"usgs":false,"family":"Caldwell","given":"Peter","email":"","middleInitial":"V","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":797431,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richter, Brian","contributorId":239628,"corporation":false,"usgs":false,"family":"Richter","given":"Brian","email":"","affiliations":[],"preferred":false,"id":797432,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ruddell, Benjamin 0000-0003-2967-9339","orcid":"https://orcid.org/0000-0003-2967-9339","contributorId":239629,"corporation":false,"usgs":false,"family":"Ruddell","given":"Benjamin","email":"","affiliations":[{"id":47944,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University","active":true,"usgs":false}],"preferred":false,"id":797433,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rushforth, Richard","contributorId":239630,"corporation":false,"usgs":false,"family":"Rushforth","given":"Richard","email":"","affiliations":[],"preferred":false,"id":797434,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Davis, Kyle F. 0000-0003-4504-1407","orcid":"https://orcid.org/0000-0003-4504-1407","contributorId":239631,"corporation":false,"usgs":false,"family":"Davis","given":"Kyle","email":"","middleInitial":"F.","affiliations":[{"id":47945,"text":"Department of Geography and Spatial Sciences & Department of Plant and Soil Sciences, University of Delaware","active":true,"usgs":false}],"preferred":false,"id":797435,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70212621,"text":"sim3459 - 2020 - Stratigraphic units of shallow unconsolidated deposits in Deadwood, South Dakota, delineated by real-time kinematic surveys","interactions":[],"lastModifiedDate":"2020-08-26T13:05:12.542236","indexId":"sim3459","displayToPublicDate":"2020-08-25T11:11:39","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3459","displayTitle":"Stratigraphic Units of Shallow Unconsolidated Deposits in Deadwood, South Dakota, Delineated by Real-Time Kinematic Surveys","title":"Stratigraphic units of shallow unconsolidated deposits in Deadwood, South Dakota, delineated by real-time kinematic surveys","docAbstract":"

The City of Deadwood, South Dakota, has been working on a new archeological investigation in preparation for economic growth and expansion within the city limits, through the Deadwood Historic Preservation Office. During the excavation process, buried artifacts and historical features from the late 1800s have been uncovered. The stratigraphy of shallow unconsolidated deposits in the city of Deadwood, S. Dak., was surveyed on January 29, 2020, using real-time kinematic survey methods and described to identify variations in geologic material, thickness, and depth from the land surface in support of archeological studies by the city. The findings of the study will provide city managers and the public with reliable and impartial information for their use by advancing field or analytical methodology and understanding of hydrologic processes in the study area. The primary excavation site was surveyed, and stratigraphic units were delineated from changes in material properties or depositional environment. The primary excavation site consisted of nine stratigraphic units; however, some units were not consistent along the length of the excavation and pinched out along the cross section. Survey data points also were collected for artifacts and other sites of interest. The shallow surficial geology in the study area was affected by human construction, fires, and flooding.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3459","collaboration":"Prepared in cooperation with the City of Deadwood, South Dakota","usgsCitation":"Tatge, W.S., Medler, C.J., Eldridge, W.G., and Valder, J.F., 2020, Stratigraphic units of shallow unconsolidated deposits in Deadwood, South Dakota, delineated by real-time kinematic surveys: U.S. Geological Survey Scientific Investigations Map 3459, pamphlet 7 p., 1 sheet, https://dx.doi.org/10.3133/sim3459.","productDescription":"Pamphlet: vi, 7 p.; 1 Sheet: 42.75 x 35.40 inches; 1 Table","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-119064","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":377805,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/3459/sim3459_table1.csv","text":"Table 1","size":"32.7 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIM 3459 Table 1","linkHelpText":"— Survey points collected for delineation of selected stratigraphic units."},{"id":377804,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3459/sim3459_pamphlet.pdf","text":"Pamphlet","size":"2.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3459 Pamphlet"},{"id":377803,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3459/sim3459.pdf","text":"Sheet 1","size":"5.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3459","linkHelpText":"— Stratigraphic Units of Shallow Unconsolidated Deposits in Deadwood, South Dakota, Delineated by Real-Time Kinematic Surveys"},{"id":377802,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3459/coverthb.jpg"}],"country":"United States","state":"South Dakota","city":"Deadwood","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.74698638916016,\n 44.364237624976326\n ],\n [\n -103.71814727783202,\n 44.364237624976326\n ],\n [\n -103.71814727783202,\n 44.38558741441454\n ],\n [\n -103.74698638916016,\n 44.38558741441454\n ],\n [\n -103.74698638916016,\n 44.364237624976326\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue, Bismarck, ND 58503
1608 Mountain View Road, Rapid City, SD 57702

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-08-25","noUsgsAuthors":false,"publicationDate":"2020-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Tatge, Wyatt S. 0000-0003-4414-2492","orcid":"https://orcid.org/0000-0003-4414-2492","contributorId":239544,"corporation":false,"usgs":true,"family":"Tatge","given":"Wyatt","email":"","middleInitial":"S.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797151,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medler, Colton J. 0000-0001-6119-5065","orcid":"https://orcid.org/0000-0001-6119-5065","contributorId":201463,"corporation":false,"usgs":true,"family":"Medler","given":"Colton","email":"","middleInitial":"J.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797152,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eldridge, William G. 0000-0002-3562-728X","orcid":"https://orcid.org/0000-0002-3562-728X","contributorId":208529,"corporation":false,"usgs":true,"family":"Eldridge","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797153,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valder, Joshua F. 0000-0003-3733-8868","orcid":"https://orcid.org/0000-0003-3733-8868","contributorId":220912,"corporation":false,"usgs":true,"family":"Valder","given":"Joshua F.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797154,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70215537,"text":"70215537 - 2020 - Holocene paleoclimate change in the western US: The importance of chronology in discerning patterns and drivers","interactions":[],"lastModifiedDate":"2020-10-22T14:56:39.511724","indexId":"70215537","displayToPublicDate":"2020-08-25T09:52:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Holocene paleoclimate change in the western US: The importance of chronology in discerning patterns and drivers","docAbstract":"

Sediment in lakes and meadows forms a powerful archive that can be used to reconstruct environmental change through time. Reconstructions of lake level, of chemical, biological, and hydrological conditions, and of surrounding vegetation provide detailed information about past climate conditions, both locally and regionally. Indeed, most of our current knowledge of centennial- to millennial-scale climate variability in the arid western United States, where information about past hydroclimate is particularly important, comes from such sediment-based reconstructions. The pressing need for robust, precise predictions of future conditions is a significant motivation for paleoclimate science, and current research questions frequently require Holocene reconstructions to be resolved at sub-centennial timescales. Increasingly, regional syntheses seek to identify synoptic-scale patterns similar to those defined from modern observations (seasonal, interannual, multi-decadal, etc.) or to compare with the output of climate model simulations. However, the age control on existing records, especially those more than about 20 years old, is often sufficient only for millennial-scale interpretation. Here we assess the age control for 84 published and unpublished records from lakes and meadows in the Great Basin, California, and desert southwest, and use Bayesian modeling to evaluate the 95% uncertainty ranges for the 42 best-dated records. In the Late Holocene, about half of the 42 records have <400-year mean uncertainty ranges; however, high-precision age control is especially critical for young records, used to develop an accurate understanding of a proxy’s response to known climate variations. In the Middle Holocene, records vary from 400 to >800-year mean uncertainty and records of the Early Holocene have 600- to >1400-year mean uncertainty ranges. We find that the largest control on modeled uncertainties is dating density, with at least 2 dates/kyr being optimal and suggest obtaining “range-finder” dates at the onset of a study to better predict the total number of dates needed for an adequate age model. Such a density avoids a commonly observed phenomenon of significant peaks in uncertainty arising in gaps between age control points. Analysis of the uncertainties associated with proxy shifts reveal that more than half are >400 years. Although such large uncertainties currently prevent sub-centennial interpretations in most cases, increased dating density, strategic use of limited funds (including budgeting for a 2 date/kyr minimum at the proposal stage), construction of age-depth models with Bayesian methods, and critical evaluation of chronological uncertainty will shed light on past climate variability at finer timescales, enhancing our understanding of global and regional drivers of western U.S. climate.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2020.106487","usgsCitation":"Zimmerman, S., and Wahl, D., 2020, Holocene paleoclimate change in the western US: The importance of chronology in discerning patterns and drivers: Quaternary Science Reviews, v. 246, 106487, 26 p., https://doi.org/10.1016/j.quascirev.2020.106487.","productDescription":"106487, 26 p.","ipdsId":"IP-117485","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":455535,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1901504","text":"Publisher Index Page"},{"id":379657,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.78271484375,\n 32.69486597787505\n ],\n [\n -111.005859375,\n 32.69486597787505\n ],\n [\n -111.005859375,\n 43.97700467496408\n ],\n [\n -124.78271484375,\n 43.97700467496408\n ],\n [\n -124.78271484375,\n 32.69486597787505\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"246","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zimmerman, Susan 0000-0002-1320-1878","orcid":"https://orcid.org/0000-0002-1320-1878","contributorId":243580,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Susan","email":"","affiliations":[{"id":48737,"text":"CAMS, LLNL","active":true,"usgs":false}],"preferred":false,"id":802616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wahl, David 0000-0002-0451-3554","orcid":"https://orcid.org/0000-0002-0451-3554","contributorId":206113,"corporation":false,"usgs":true,"family":"Wahl","given":"David","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":802617,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70209320,"text":"sir20205033 - 2020 - Temporal and spatial variability of water quality in the San Antonio segment of the Edwards aquifer recharge zone, Texas, with an emphasis on periods of groundwater recharge, September 2017–July 2019","interactions":[],"lastModifiedDate":"2020-08-24T17:39:27.590296","indexId":"sir20205033","displayToPublicDate":"2020-08-24T09:57:00","publicationYear":"2020","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":"2020-5033","displayTitle":"Temporal and Spatial Variability of Water Quality in the San Antonio Segment of the Edwards Aquifer Recharge Zone, Texas, With an Emphasis on Periods of Groundwater Recharge, September 2017–July 2019","title":"Temporal and spatial variability of water quality in the San Antonio segment of the Edwards aquifer recharge zone, Texas, with an emphasis on periods of groundwater recharge, September 2017–July 2019","docAbstract":"

Ongoing urbanization on the Edwards aquifer recharge zone in the greater San Antonio area raises concern about the potential adverse effects on the public water supply from development. To address this concern, the U.S. Geological Survey, in cooperation with the City of San Antonio, studied patterns of temporal and spatial changes in water quality at selected surface-water and groundwater sites in the Edwards aquifer recharge zone, with an emphasis on changes during periods of groundwater recharge. Water-quality characteristics were continuously monitored and discrete water samples were collected at two sets of paired surface-water (stream) and groundwater (well) sites during a 2-year period (2017–19) that included relatively dry conditions and a large recharge event in September 2018 when as much as 16 inches of rain fell in parts of the study area.

Continuous monitoring of water-level altitude, specific conductance, and concentrations of nitrate in two wells completed in the Edwards aquifer provided high-resolution data showing detailed changes in water quality across a broad range of hydrologic conditions. Water levels in the wells responded rapidly (within hours to days) to recharge from both small and large rainfall and runoff events; changes in groundwater quality as a consequence of the influx of surface-derived recharge were indicated by changes in values of the monitored characteristics. A broad range in measured values of the stable isotopes of water expressed as delta deuterium and delta oxygen-18 in the water samples collected from two streams (Salado and West Elm Creeks), in comparison to the tight clustering of the values of these isotopes in groundwater samples, indicates that source waters (surface waters) of widely varying chemical characteristics become homogenized within the aquifer system.

Concentrations of major ions, trace ions, and nutrient concentrations in stormwater runoff indicate a combination of land-derived and rainfall-derived constituents. The distribution of concentrations of nitrogen species (nitrite, nitrate, and nitrogen in ammonia) among sampling sites transitions from a more variable distribution in stormwater runoff to a more uniform distribution in groundwater in which the dominant form is nitrate. Differences in nitrate isotopic composition and concentration in groundwater across the study area are likely controlled by the relative contributions of natural and anthropogenic nitrogen (with the anthropogenic nitrogen component including a wastewater source) and by the process of nitrification. Among all measured constituents, pesticides detected in discrete stormwater-runoff samples provided the clearest indication that urbanization was adversely affecting water quality; specifically, the more urbanized surface-water site had a greater number of detections and greater variety of detected pesticides. Though temporal variability in the numbers and types of pesticides was evident, the overall proportion of pesticides was dominated by triazine herbicides including atrazine, atrazine degradates, and simazine. The observed hydrologic responses to rainfall and corresponding changes in water quality in wells are thought to result from the direct hydrologic connectivity of surface water and unconfined groundwater; however, patterns of groundwater-quality change indicate mixing from multiple sources such as ambient groundwater, recent surface-derived recharge, and possibly inflow from other aquifers. Therefore, understanding the connection between urbanization and groundwater quality cannot be inferred from the input of stormwater runoff alone as changes related to local and regional hydrologic conditions also need to be considered. It should be noted that a single study comparing the results from two site pairs is not able to support definitive conclusions about the full effect of urbanization on surface water/groundwater quality; however, this study does provide useful insights about the spatial and temporal variability of both stormwater runoff and unconfined groundwater that are consistent with expectations based on the current conceptual model that depicts the Edwards aquifer surface-water/groundwater system as a single water resource.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205033","collaboration":"Prepared in cooperation with the City of San Antonio","usgsCitation":"Opsahl, S.P., Musgrove, M., and Mecum, K.E., 2020, Temporal and spatial variability of water quality in the San Antonio segment of the Edwards aquifer recharge zone, Texas, with an emphasis on periods of groundwater recharge, September 2017–July 2019: U.S. Geological Survey Scientific Investigations Report 2020–5033, 37 p., https://doi.org/10.3133/sir20205033.","productDescription":"Report: x, 37 p.; Companion Report","numberOfPages":"51","onlineOnly":"Y","ipdsId":"IP-112400","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":376131,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5033/sir20205033.pdf","text":"Report","size":"1.84 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5033"},{"id":376132,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/fs20203028","text":"FS 2020-3028","size":"852 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–5028","linkHelpText":"— Effects of urbanization on water quality in the Edwards aquifer, San Antonio and Bexar County"},{"id":376130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5033/coverthb.jpg"}],"country":"United States","state":"Texas","city":"San Antonio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.909912109375,\n 28.613459424004414\n ],\n [\n -97.05322265625,\n 29.635545914466675\n ],\n [\n -98.02001953125,\n 30.472348632640834\n ],\n [\n -99.744873046875,\n 29.49698759653577\n ],\n [\n -98.909912109375,\n 28.613459424004414\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
Director, Oklahoma-Texas Water Science Center 
U.S. Geological Survey 
1505 Ferguson Lane 
Austin, TX 78754 
gs-w-txpublicinfo@usgs.gov 
","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-08-24","noUsgsAuthors":false,"publicationDate":"2020-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Opsahl, Stephen P. 0000-0002-4774-0415 sopsahl@usgs.gov","orcid":"https://orcid.org/0000-0002-4774-0415","contributorId":4713,"corporation":false,"usgs":true,"family":"Opsahl","given":"Stephen","email":"sopsahl@usgs.gov","middleInitial":"P.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786042,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":1316,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":786043,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mecum, Keith E. 0000-0002-5617-3504","orcid":"https://orcid.org/0000-0002-5617-3504","contributorId":223711,"corporation":false,"usgs":true,"family":"Mecum","given":"Keith","email":"","middleInitial":"E.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786044,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70212487,"text":"sir20205074 - 2020 - Flood-inundation maps for the Little Calumet River from Lansing to South Holland, Illinois, 2020","interactions":[],"lastModifiedDate":"2022-10-25T13:58:13.629382","indexId":"sir20205074","displayToPublicDate":"2020-08-19T12:20:30","publicationYear":"2020","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":"2020-5074","displayTitle":"Flood-Inundation Maps for the Little Calumet River from Lansing to South Holland, Illinois, 2020","title":"Flood-inundation maps for the Little Calumet River from Lansing to South Holland, Illinois, 2020","docAbstract":"

Digital flood-inundation maps for about an 8-mile reach of the Little Calumet River, Illinois, were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at three USGS streamgages: Little Calumet River at South Holland, Ill. (USGS station 05536290); Little Calumet River at Munster, Indiana (USGS station 05536195); and Thorn Creek at Thornton, Ill. (USGS station 05536275). Near-real-time stages at these streamgages may be obtained on the internet from the USGS National Water Information System at https://doi.org/10.5066/F7P55KJN or the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/, which also forecasts flood hydrographs at these sites.

Flood profiles were computed for the stream reaches using a one-dimensional unsteady flow step-backwater hydraulic model. The model performance was evaluated using historical streamflow measurements and the most current stage-discharge relations at the USGS streamgages at Little Calumet River at South Holland, Ill.; Little Calumet River at Munster, Ind.; and Thorn Creek at Thornton, Ill. The model was used to compute 24 water-surface profiles at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to about the 0.2-percent annual-exceedance probability flood (500-year recurrence interval flood). The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.6-foot vertical accuracy and a 2-foot horizontal resolution) to delineate the area flooded at each water level.

The availability of these maps, along with internet information regarding current stage from USGS streamgages and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205074","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Dunn, A.P., Straub, T.D., and Manaster, A.E., 2020, Flood-inundation maps for the Little Calumet River from Lansing to South Holland, Illinois, 2020: U.S. Geological Survey Scientific Investigations Report 2020–5074, 10 p., https://doi.org/10.3133/sir20205074.","productDescription":"Report: vi, 10 p.; Data Release; Dataset","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-097182","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":377581,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99L14DN","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial datasets for the flood-inundation study of Little Calumet River from Lansing to South Holland, Illinois, 2020, 2020"},{"id":377582,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":377580,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5074/sir20205074.pdf","text":"Report","size":"2.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5074"},{"id":377579,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5074/coverthb.jpg"}],"country":"United States","state":"Illinois","city":"Lansing, South Holland","otherGeospatial":"Little Calumet River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.6295280456543,\n 41.54404730359805\n ],\n [\n -87.52584457397461,\n 41.54404730359805\n ],\n [\n -87.52584457397461,\n 41.62339874820646\n ],\n [\n -87.6295280456543,\n 41.62339874820646\n ],\n [\n -87.6295280456543,\n 41.54404730359805\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-08-19","noUsgsAuthors":false,"publicationDate":"2020-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Dunn, Andrew P.","contributorId":238780,"corporation":false,"usgs":false,"family":"Dunn","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":796524,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Straub, Timothy D. 0000-0002-5896-0851 tdstraub@usgs.gov","orcid":"https://orcid.org/0000-0002-5896-0851","contributorId":2273,"corporation":false,"usgs":true,"family":"Straub","given":"Timothy D.","email":"tdstraub@usgs.gov","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":false,"id":796525,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manaster, Adam E. 0000-0001-8183-4274","orcid":"https://orcid.org/0000-0001-8183-4274","contributorId":238781,"corporation":false,"usgs":false,"family":"Manaster","given":"Adam","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":796526,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209129,"text":"sir20205024 - 2020 - Hydrology of Haskell Lake and investigation of a groundwater contamination plume, Lac du Flambeau Reservation, Wisconsin","interactions":[],"lastModifiedDate":"2020-08-24T20:46:47.699056","indexId":"sir20205024","displayToPublicDate":"2020-08-18T15:30:18","publicationYear":"2020","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":"2020-5024","displayTitle":"Hydrology of Haskell Lake and Investigation of a Groundwater Contamination Plume, Lac du Flambeau Reservation, Wisconsin","title":"Hydrology of Haskell Lake and investigation of a groundwater contamination plume, Lac du Flambeau Reservation, Wisconsin","docAbstract":"

Haskell Lake is a shallow, 89-acre drainage lake in the headwaters of the Squirrel River, on the Lac du Flambeau Reservation in northern Wisconsin. The lake has long been valued by the Lac du Flambeau Band of Lake Superior Chippewa Indians (LDF Tribe) for abundant wild rice and game fish. In recent decades, however, wild rice has mostly disappeared from the lake and the fishery has declined. A petroleum contamination plume discovered in the 1990s in the shallow aquifer upgradient from the northern end of the lake poses a threat to the ecological health of the lake and the aquifer, which is the sole drinking water source for nearby residents and businesses. Understanding of the lake’s hydrology is important to the LDF Tribe as they seek to restore wild rice and maintain the ecological health of the Haskell Lake/Tower Creek watershed. An improved understanding of lithology in the area of the contamination plume, documentation of a contamination pathway from groundwater in the plume source area to Haskell Lake, and an understanding of the plume extent beneath the lake are needed to advance remediation efforts. Evaluation of the fraction of groundwater discharge that is contaminated relative to the overall lake water budget is desired as a first step towards determining the extent of ecological effects from the plume.

A cooperative study between the U.S. Geological Survey and the LDF Tribe was initiated to quantify the lake water budget and the sources of water to the lake, to provide a rough estimate of the maximum quantity of groundwater discharge to the lake that may be contaminated, and to improve the conceptual understanding of the plume extent and subsurface materials in the area of contamination. The results of this study can help inform natural resource management of the Haskell Lake/Tower Creek watershed, including planned wild rice restoration and cleanup of the contaminant plume.

During 2016–17, field data on lake and groundwater levels, gradients, fluxes, and subsurface lithology were collected using a variety of techniques that ranged from basic measurement of water levels and streamflows to distributed temperature sensing, vertical temperature profiling, and several shallow geophysical methods. The data were used to inform a MODFLOW–NWT model that simulated the contributing groundwatershed, including the water budget for Haskell Lake and Tower Creek using the Lake, Streamflow-Routing, and Unsaturated Zone-Flow Packages. Particle tracking with the MODFLOW solution (using MODPATH 6) was used to improve understanding of the downgradient extent of the contamination plume, estimate groundwater flux through the plume area, and delineate the groundwater contributing area (groundwatershed) for the lake/creek system. Linear uncertainty estimates for model results were computed during model parameter estimation using the software package PEST++.

Results indicate groundwater discharge along the perimeter of Haskell Lake, with groundwater accounting for about 22 (± 11.5) percent of the lake water budget. Field data and particle tracking results indicate discharge of the entire contamination plume to Haskell Lake. Although the exact locations where contaminated groundwater enters the lake are unknown, the downgradient extent of the plume beneath Haskell Lake is likely limited to within about 700 feet from the shore. Groundwater flux through the plume accounts for at most about 1.4 percent of total groundwater discharge to Haskell Lake, or about 0.3 percent of the lake water budget. Most groundwater discharging to Haskell Lake and Tower Creek originates as terrestrial recharge. A lesser amount originates in or passes through neighboring lakes, including Buckskin, Crawling Stone, Broken Bow, Tippecanoe, and Jerms Lakes, as well as several unnamed kettles. The average age of simulated groundwater discharge to the lake is about 20 years.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205024","collaboration":"Prepared in cooperation with the Lac du Flambeau Band of Lake Superior Chippewa Indians","usgsCitation":"Leaf, A.T., and Haserodt, M.J., 2020, Hydrology of Haskell Lake and investigation of a groundwater contamination plume, Lac du Flambeau Reservation, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2020–5024, 79 p., https://doi.org/10.3133/sir20205024.","productDescription":"Report: x, 70 p.; Appendices: 1.1-10.3; Data Release; Companion Report","numberOfPages":"92","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098814","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":377617,"rank":14,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZQGGHY","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW–NWT and MODPATH models, data from aquifer tests and temperature profilers, and groundwater flux estimates used to assess groundwater/surface-water interactions in Haskell Lake, Wisconsin"},{"id":377616,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5024/sir20205024_appendix_table10.1_10.3.xlsx","text":"Appendix Tables 10.1 to 10.3","size":"19.4 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5024 Appendix Tables 10.1 to 10.3"},{"id":377615,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5024/sir20205024_appendix_table_9.1.xlsx","text":"Appendix Table 9.1","size":"12.8 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5024 Appendix Table 9.1"},{"id":377614,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5024/sir20205024_appendix_table_8.1.xlsx","text":"Appendix Table 8.1","size":"17.2 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5024 Appendix Table 8.1"},{"id":377611,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5024/sir20205024_appendix_table_5.1.xlsx","text":"Appendix Table 5.1","size":"12.3 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5024 Appendix Table 5.1"},{"id":377607,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5024/sir20205024_appendix_table1.1_1.12.xlsx","text":"Appendix Tables 1.1 to 1.12","size":"35.5 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5024 Appendix Tables 1.1 to 1.12"},{"id":377606,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20205005","text":"SIR 2020–5005","size":"3.67 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"— A distributed temperature sensing investigation of groundwater discharge to Haskell Lake, Lac du Flambeau Reservation, Wisconsin, July 27–August 1, 2016"},{"id":377610,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5024/sir20205024_appendix_table_4.1.xlsx","text":"Appendix Table 4.1","size":"10.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5024 Appendix Table 4.1"},{"id":377608,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5024/sir20205024_appendix_table_2.1.xlsx","text":"Appendix Table 2.1","size":"12.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5024 Appendix Table 2.1"},{"id":377609,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5024/sir20205024_appendix_table_3.1_3.6.xlsx","text":"Appendix Tables 3.1 to 3.6","size":"24.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5024 Appendix Tables 3.1 to 3.6"},{"id":377604,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5024/coverthb.jpg"},{"id":377801,"rank":15,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5024/downloads","text":"Appendix Tables","size":"47.8 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5024 Appendix Tables"},{"id":377612,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5024/sir20205024_appendix_table_6.1_6.2.xlsx","text":"Appendix Tables 6.1 to 6.2","size":"13.9 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5024 Appendix Tables 6.1 to 6.2"},{"id":377613,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5024/sir20205024_appendix_table_7.1.xlsx","text":"Appendix Table 7.1","size":"13.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5024 Appendix Table 7.1"},{"id":377605,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5024/sir20205024.pdf","text":"Report","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5024"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Haskell Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.93322372436523,\n 45.89717666670996\n ],\n [\n -89.89992141723633,\n 45.89717666670996\n ],\n [\n -89.89992141723633,\n 45.920467927558576\n ],\n [\n -89.93322372436523,\n 45.920467927558576\n ],\n [\n -89.93322372436523,\n 45.89717666670996\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562 

","tableOfContents":"","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2020-08-18","noUsgsAuthors":false,"publicationDate":"2020-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haserodt, Megan J. 0000-0002-8304-090X mhaserodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8304-090X","contributorId":174791,"corporation":false,"usgs":true,"family":"Haserodt","given":"Megan","email":"mhaserodt@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":785039,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215055,"text":"70215055 - 2020 - Hillslopes in humid-tropical climates aren’t always wet: Implications for hydrologic response and landslide initiation in Puerto Rico, USA","interactions":[],"lastModifiedDate":"2020-10-07T12:14:54.550159","indexId":"70215055","displayToPublicDate":"2020-08-17T17:11:58","publicationYear":"2020","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":"Hillslopes in humid-tropical climates aren’t always wet: Implications for hydrologic response and landslide initiation in Puerto Rico, USA","docAbstract":"

The devastating impacts of the widespread flooding and landsliding in Puerto Rico following the September 2017 landfall of Hurricane Maria highlight the increasingly extreme atmospheric disturbances and enhanced hazard potential in mountainous humid‐tropical climate zones. Long‐standing conceptual models for hydrologically driven hazards in Puerto Rico posit that hillslope soils remain wet throughout the year, and therefore, that antecedent soil wetness imposes a negligible effect on hazard potential. Our post‐Maria in situ hillslope hydrologic observations, however, indicate that while some slopes remain wet throughout the year, others exhibit appreciable seasonal and intra‐storm subsurface drainage. Therefore, we evaluated the performance of hydro‐meteorological (soil wetness and rainfall) versus intensity‐duration (rainfall only) hillslope hydrologic response thresholds that identify the onset of positive pore‐water pressure, a predisposing factor for widespread slope instability in this region. Our analyses also consider the role of soil‐water storage and infiltration rates on runoff generation, which are relevant factors for flooding hazards. We found that the hydro‐meteorological thresholds outperformed intensity‐duration thresholds for a seasonally wet, coarse‐grained soil, although they did not outperform intensity‐duration thresholds for a perennially wet, fine‐grained soil. These end‐member soils types may also produce radically different stormflow responses, with subsurface flow being more common for the coarse‐grained soils underlain by intrusive rocks versus infiltration excess and/or saturation excess for the fine‐grained soils underlain by volcaniclastic rocks. We conclude that variability in soil‐hydraulic properties, as opposed to climate zone, is the dominant factor that controls runoff generation mechanisms and modulates the relative importance of antecedent soil wetness for our hillslope hydrologic response thresholds.

","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13885","usgsCitation":"Thomas, M.A., Mirus, B.B., and Smith, J., 2020, Hillslopes in humid-tropical climates aren’t always wet: Implications for hydrologic response and landslide initiation in Puerto Rico, USA: Hydrological Processes, v. 34, no. 22, p. 4307-4318, https://doi.org/10.1002/hyp.13885.","productDescription":"Article: 12 p.; Data Release","startPage":"4307","endPage":"4318","ipdsId":"IP-120135","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":455618,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.13885","text":"Publisher Index Page"},{"id":379147,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9548YK2"},{"id":379148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto Rico","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-65.3277,18.295843],[-65.337451,18.308308],[-65.327318,18.323666],[-65.342068,18.34529],[-65.335701,18.349535],[-65.329334,18.341955],[-65.321754,18.338316],[-65.309833,18.337973],[-65.304409,18.332054],[-65.298328,18.330529],[-65.255933,18.342117],[-65.221568,18.320959],[-65.222853,18.310464],[-65.249857,18.296691],[-65.260282,18.290823],[-65.283269,18.280214],[-65.3277,18.295843]]],[[[-67.89174,18.11397],[-67.887099,18.112574],[-67.87643,18.114157],[-67.869804,18.118851],[-67.861548,18.122144],[-67.848245,18.10832],[-67.843202,18.094858],[-67.843615,18.085099],[-67.845293,18.081938],[-67.853098,18.078195],[-67.865598,18.06544],[-67.871462,18.0578],[-67.895921,18.052342],[-67.904431,18.05913],[-67.918778,18.063116],[-67.927841,18.068572],[-67.940799,18.079716],[-67.934479,18.111306],[-67.932185,18.113221],[-67.91088,18.119668],[-67.89174,18.11397]]],[[[-65.308717,18.145172],[-65.302295,18.141089],[-65.294896,18.14283],[-65.287962,18.148097],[-65.275165,18.13443],[-65.276214,18.131936],[-65.283248,18.132999],[-65.296036,18.12799],[-65.322794,18.126589],[-65.327184,18.124106],[-65.338506,18.112439],[-65.342037,18.11138],[-65.350493,18.111914],[-65.364733,18.120377],[-65.397837,18.110873],[-65.399791,18.108832],[-65.411767,18.106211],[-65.423765,18.097764],[-65.426311,18.093749],[-65.45138,18.086096],[-65.45681,18.087778],[-65.465849,18.087715],[-65.468768,18.092643],[-65.47979,18.096352],[-65.507265,18.091646],[-65.524209,18.081977],[-65.542087,18.081177],[-65.558646,18.08566],[-65.569305,18.091616],[-65.570628,18.097325],[-65.57686,18.103224],[-65.575579,18.115669],[-65.546199,18.119329],[-65.511712,18.13284],[-65.489829,18.135912],[-65.46791,18.143767],[-65.437058,18.15766],[-65.399517,18.161935],[-65.371373,18.157517],[-65.334289,18.147761],[-65.313476,18.144296],[-65.308717,18.145172]]],[[[-66.438813,18.485713],[-66.420921,18.488639],[-66.410344,18.489886],[-66.394287,18.489748],[-66.377286,18.488044],[-66.37282,18.487726],[-66.349647,18.486335],[-66.337728,18.48562],[-66.315477,18.474724],[-66.31503,18.47468],[-66.291225,18.472347],[-66.283675,18.472203],[-66.276599,18.478129],[-66.269799,18.480281],[-66.258015,18.476906],[-66.251547,18.472464],[-66.241797,18.46874],[-66.220148,18.466],[-66.199032,18.466163],[-66.192664,18.466212],[-66.183886,18.460506],[-66.179218,18.455305],[-66.172315,18.451462],[-66.159796,18.451706],[-66.153037,18.454457],[-66.14395,18.459761],[-66.139572,18.462317],[-66.139451,18.462387],[-66.139443,18.462315],[-66.138532,18.453305],[-66.133085,18.445881],[-66.127938,18.444632],[-66.125198,18.451209],[-66.124284,18.456324],[-66.123188,18.45943],[-66.123343,18.460363],[-66.125015,18.470435],[-66.118338,18.469581],[-66.092098,18.466535],[-66.083254,18.462022],[-66.073987,18.4581],[-66.043272,18.453655],[-66.03944,18.454441],[-66.036559,18.450216],[-66.036491,18.450117],[-66.023221,18.443875],[-66.006523,18.444347],[-65.99718,18.449895],[-65.992935,18.457489],[-65.992793,18.458102],[-65.992349,18.460024],[-65.99079,18.460419],[-65.958492,18.451354],[-65.92567,18.444881],[-65.916843,18.444619],[-65.907756,18.446893],[-65.904988,18.450926],[-65.878683,18.438322],[-65.838825,18.431865],[-65.831476,18.426849],[-65.828457,18.423543],[-65.816691,18.410663],[-65.794556,18.402845],[-65.787666,18.402544],[-65.774937,18.413951],[-65.77053,18.41294],[-65.769749,18.409473],[-65.771695,18.406277],[-65.750455,18.385208],[-65.750179,18.38505],[-65.742154,18.380459],[-65.733567,18.382211],[-65.699069,18.368156],[-65.669636,18.362102],[-65.668845,18.361939],[-65.634431,18.369835],[-65.627246,18.376436],[-65.626527,18.381728],[-65.624975,18.386553],[-65.622761,18.387771],[-65.618229,18.386496],[-65.614891,18.382473],[-65.619068,18.367755],[-65.628198,18.353711],[-65.63419,18.338965],[-65.628047,18.328252],[-65.626456,18.298982],[-65.634389,18.292349],[-65.635826,18.288271],[-65.634893,18.283923],[-65.630833,18.264989],[-65.623111,18.248012],[-65.597618,18.234289],[-65.589947,18.228225],[-65.593795,18.224059],[-65.615981,18.227389],[-65.626731,18.235484],[-65.638181,18.229121],[-65.637565,18.224444],[-65.628414,18.205149],[-65.635281,18.199975],[-65.639688,18.205656],[-65.662185,18.207018],[-65.664127,18.207136],[-65.690749,18.19499],[-65.694515,18.187011],[-65.691021,18.178998],[-65.695856,18.179324],[-65.710895,18.186963],[-65.712533,18.189146],[-65.717999,18.190176],[-65.728471,18.185588],[-65.734664,18.180368],[-65.738834,18.174066],[-65.739125,18.173453],[-65.743632,18.163957],[-65.758728,18.156601],[-65.766919,18.148424],[-65.777584,18.129239],[-65.796711,18.083746],[-65.796289,18.079835],[-65.794686,18.078607],[-65.795028,18.073561],[-65.796711,18.069842],[-65.801831,18.058527],[-65.809174,18.056818],[-65.817107,18.063378],[-65.825848,18.057482],[-65.83109,18.050664],[-65.834274,18.038988],[-65.832429,18.014916],[-65.839591,18.015077],[-65.850913,18.011954],[-65.870335,18.006597],[-65.875122,18.002826],[-65.884937,17.988521],[-65.896102,17.99026],[-65.905319,17.983974],[-65.910537,17.981855],[-65.924738,17.976087],[-65.976611,17.967669],[-65.98455,17.969411],[-65.985358,17.971854],[-65.995185,17.978989],[-66.007731,17.980541],[-66.017308,17.979583],[-66.019539,17.978354],[-66.024,17.975896],[-66.046585,17.954853],[-66.049033,17.954561],[-66.058217,17.959238],[-66.068678,17.966335],[-66.069979,17.966357],[-66.08141,17.966552],[-66.116194,17.949141],[-66.127009,17.946953],[-66.140661,17.94102],[-66.147912,17.933963],[-66.155387,17.929406],[-66.159742,17.928613],[-66.161232,17.931747],[-66.175626,17.933565],[-66.186914,17.935363],[-66.189726,17.933936],[-66.200174,17.929515],[-66.206961,17.932268],[-66.213374,17.944614],[-66.202655,17.944753],[-66.185554,17.940997],[-66.179548,17.943727],[-66.174839,17.948214],[-66.176814,17.950438],[-66.206207,17.96305],[-66.206807,17.963307],[-66.215355,17.959376],[-66.218081,17.95729],[-66.231519,17.943912],[-66.229181,17.934651],[-66.232013,17.931154],[-66.252737,17.934574],[-66.260684,17.936083],[-66.270905,17.947098],[-66.275651,17.94826],[-66.290782,17.946491],[-66.297679,17.959148],[-66.31695,17.976683],[-66.323659,17.978536],[-66.338152,17.976492],[-66.33839,17.976458],[-66.362511,17.968231],[-66.365098,17.964832],[-66.368777,17.957717],[-66.371591,17.951469],[-66.385059,17.939004],[-66.391227,17.945819],[-66.398945,17.950925],[-66.412131,17.957286],[-66.445481,17.979379],[-66.450368,17.983226],[-66.454888,17.986784],[-66.461342,17.990273],[-66.491396,17.990262],[-66.510143,17.985618],[-66.540537,17.975476],[-66.583233,17.961229],[-66.589658,17.969386],[-66.594392,17.970682],[-66.605035,17.969015],[-66.623788,17.98105],[-66.631944,17.982746],[-66.645651,17.98026],[-66.657797,17.974605],[-66.664391,17.968259],[-66.672819,17.966451],[-66.699115,17.977568],[-66.709856,17.982109],[-66.713394,17.987763],[-66.716957,17.990344],[-66.731118,17.991658],[-66.746248,17.990349],[-66.750427,17.995443],[-66.753964,17.99959],[-66.755341,18.001203],[-66.764491,18.006317],[-66.770307,18.005955],[-66.799656,17.99245],[-66.806866,17.983786],[-66.807924,17.979606],[-66.806903,17.976046],[-66.805683,17.975052],[-66.795106,17.977438],[-66.789302,17.980793],[-66.784953,17.978326],[-66.787245,17.972914],[-66.80827,17.965635],[-66.8224,17.954499],[-66.838584,17.949931],[-66.852288,17.955004],[-66.856474,17.956553],[-66.859471,17.954316],[-66.862545,17.952022],[-66.871697,17.952707],[-66.88344,17.952526],[-66.899639,17.948298],[-66.904585,17.950527],[-66.906532,17.955356],[-66.906276,17.963368],[-66.924529,17.972808],[-66.928651,17.970204],[-66.930414,17.963127],[-66.916127,17.959102],[-66.909483,17.952559],[-66.909359,17.94988],[-66.912522,17.947446],[-66.930313,17.943389],[-66.932636,17.939998],[-66.931581,17.9369],[-66.919298,17.932062],[-66.923826,17.926923],[-66.927261,17.926875],[-66.959998,17.940216],[-66.980516,17.951648],[-66.98105,17.952505],[-66.982669,17.9551],[-66.982206,17.961192],[-66.987287,17.970663],[-66.996738,17.972899],[-67.003972,17.970799],[-67.014744,17.968468],[-67.024522,17.970722],[-67.062478,17.973819],[-67.076534,17.967759],[-67.089827,17.951418],[-67.101468,17.946621],[-67.109985,17.945806],[-67.109986,17.945806],[-67.128251,17.948153],[-67.133733,17.951919],[-67.167031,17.963073],[-67.178566,17.964792],[-67.183508,17.962706],[-67.188717,17.950989],[-67.187474,17.946252],[-67.183694,17.937982],[-67.183457,17.931135],[-67.194785,17.932826],[-67.196924,17.935651],[-67.197273,17.937461],[-67.197517,17.941514],[-67.197668,17.943549],[-67.198988,17.94782],[-67.200973,17.949896],[-67.210034,17.953595],[-67.212101,17.956027],[-67.21433,17.962436],[-67.215271,17.983464],[-67.211973,17.992993],[-67.207694,17.998019],[-67.177893,18.008882],[-67.174299,18.011149],[-67.172397,18.014906],[-67.172138,18.021422],[-67.173761,18.024548],[-67.193269,18.03185],[-67.209887,18.035439],[-67.196694,18.066491],[-67.190656,18.064269],[-67.184589,18.06775],[-67.183938,18.069914],[-67.186465,18.074195],[-67.192999,18.076877],[-67.198212,18.076828],[-67.199314,18.091135],[-67.19529,18.096149],[-67.183921,18.103683],[-67.182182,18.108507],[-67.176554,18.151046],[-67.178618,18.159318],[-67.180822,18.168055],[-67.180701,18.168182],[-67.155185,18.195001],[-67.152665,18.203493],[-67.158001,18.216719],[-67.173,18.230666],[-67.175429,18.248008],[-67.187843,18.266671],[-67.187873,18.266874],[-67.189971,18.281015],[-67.196056,18.290443],[-67.209963,18.294974],[-67.225403,18.296648],[-67.226081,18.296722],[-67.235137,18.299935],[-67.267484,18.353149],[-67.27135,18.362329],[-67.268259,18.366989],[-67.260671,18.370197],[-67.23909,18.375318],[-67.226744,18.378247],[-67.216998,18.382078],[-67.202167,18.389908],[-67.160144,18.415587],[-67.159608,18.415915],[-67.156599,18.418983],[-67.155245,18.424401],[-67.156619,18.439562],[-67.161746,18.453462],[-67.169011,18.466352],[-67.169016,18.478488],[-67.164144,18.487396],[-67.14283,18.505485],[-67.138249,18.507776],[-67.125655,18.511706],[-67.103468,18.514523],[-67.093752,18.515757],[-67.07929,18.513256],[-67.020276,18.510603],[-66.988958,18.497724],[-66.95954,18.489878],[-66.957733,18.489129],[-66.957517,18.489171],[-66.944636,18.491693],[-66.906872,18.483556],[-66.90143,18.484552],[-66.867386,18.490785],[-66.849673,18.490745],[-66.83694,18.487659],[-66.836635,18.487701],[-66.79932,18.492775],[-66.780311,18.491411],[-66.764893,18.484097],[-66.749301,18.476701],[-66.742067,18.474681],[-66.733986,18.473457],[-66.710743,18.472611],[-66.683719,18.481367],[-66.679876,18.484944],[-66.664364,18.487809],[-66.645839,18.488777],[-66.624618,18.494199],[-66.586778,18.484948],[-66.584074,18.484287],[-66.565241,18.485523],[-66.562916,18.48845],[-66.563485,18.490512],[-66.558503,18.489987],[-66.53484,18.481253],[-66.533487,18.481663],[-66.529476,18.482877],[-66.511609,18.476848],[-66.470292,18.46907],[-66.456486,18.46892],[-66.449184,18.470991],[-66.441852,18.479751],[-66.439961,18.485525],[-66.438813,18.485713]]]]},\"properties\":{\"name\":\"Puerto Rico\",\"nation\":\"USA \"}}]}","volume":"34","issue":"22","noUsgsAuthors":false,"publicationDate":"2020-09-04","publicationStatus":"PW","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":800660,"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":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":800661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Joel B. 0000-0001-7219-7875","orcid":"https://orcid.org/0000-0001-7219-7875","contributorId":242670,"corporation":false,"usgs":false,"family":"Smith","given":"Joel B.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":800662,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211862,"text":"sir20205060 - 2020 - Flood-inundation maps for Dardenne Creek in St. Charles County, Missouri, 2019","interactions":[],"lastModifiedDate":"2020-08-12T23:31:17.152064","indexId":"sir20205060","displayToPublicDate":"2020-08-12T14:12:35","publicationYear":"2020","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":"2020-5060","displayTitle":"Flood-Inundation Maps for Dardenne Creek in St. Charles County, Missouri, 2019","title":"Flood-inundation maps for Dardenne Creek in St. Charles County, Missouri, 2019","docAbstract":"

Digital flood-inundation maps for a 9.9-mile reach of Dardenne Creek, St. Charles County, Missouri, were created by the U.S. Geological Survey (USGS), in cooperation with the Missouri Department of Transportation, St. Charles County, and the Cities of O’Fallon and St. Peters, Mo. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/​mission-​areas/​water-​resources/​science/​flood-​inundation-​mapping-​fim-​program, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgages 05514860 Dardenne Creek at Old Town St. Peters, Mo., and 05587450 Mississippi River at Grafton, Illinois. Near-real-time stages at these streamgages may be obtained from the USGS National Water Information System at https://doi.org/​10.5066/​F7P55KJN or the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ ahps2/ hydrograph.php? wfo= lsx&gage= drcm7 and https://water.weather.gov/ ahps2/ hydrograph.php? wfo= lsx&gage= grfi2, which also forecasts flood hydrographs at these sites (sites DRCM7 and GRFI2).

Flood profiles were computed for the Dardenne Creek stream reach by means of a one-dimensional model for simulating water-surface profiles with steady-state flow computations. The model was calibrated by using the current stage-streamflow relation at the USGS streamgages 05514840 Dardenne Creek at O’Fallon, Mo., and 05514860 Dardenne Creek at Old Town St. Peters, Mo., and the documented high-water marks from the flood of December 2015.

The hydraulic model was then used to compute 17 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from 16 ft, or near bankfull, to 32 ft at the reference streamgage 05514860. Stages in the lower Dardenne Creek can be affected by backwater from the Mississippi River; therefore, several sets of water-surface profiles were developed representing the extent of varying levels of backwater as referenced to the USGS streamgage 05587450 on the Mississippi River at Grafton, Ill. The upper stage for each map library exceeds the stage corresponding to the estimated 0.2-percent annual exceedance probability flood (500-year recurrence interval flood) at the streamgage location. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.26-ft vertical accuracy and 0.71-ft horizontal resolution) to delineate the area flooded at each water level.

The availability of these maps, along with real-time information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood mitigation, preparedness and planning, flood-response activities such as evacuations and road closures, and postflood recovery efforts.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205060","collaboration":"Prepared in cooperation with Missouri Department of Transportation, St. Charles County, and the Cities of O’Fallon and St. Peters, Missouri","usgsCitation":"Heimann, D.C., Voss, J.D., and Rydlund, P.H., Jr., 2020, Flood-inundation maps for Dardenne Creek in St. Charles County, Missouri, 2019: U.S. Geological Survey Scientific Investigations Report 2020–5060, 14 p., https://doi.org/10.3133/sir20205060.","productDescription":"Report: vii, 14 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-117593","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":377288,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5060/coverthb.jpg"},{"id":377289,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5060/sir20205060.pdf","text":"Report","size":"3.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5060"},{"id":377290,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QPY9MI","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial datasets for the flood-inundation study of Dardenne Creek, St. Charles County, Missouri, 2019"}],"country":"United States","state":"Missouri","county":"St. Charles County","otherGeospatial":"Dardenne Creek","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-90.4493,38.9685],[-90.4476,38.9688],[-90.4448,38.9685],[-90.4423,38.9682],[-90.4369,38.9679],[-90.4322,38.967],[-90.4264,38.9661],[-90.4181,38.9655],[-90.4073,38.9649],[-90.3992,38.9634],[-90.3916,38.9615],[-90.3828,38.9595],[-90.3746,38.9561],[-90.3652,38.9524],[-90.3574,38.948],[-90.3448,38.9425],[-90.3366,38.9382],[-90.3297,38.9346],[-90.3235,38.9315],[-90.315,38.9293],[-90.3079,38.9272],[-90.3009,38.9262],[-90.295,38.9262],[-90.2903,38.9263],[-90.2897,38.9263],[-90.2826,38.9259],[-90.2773,38.9255],[-90.2767,38.9254],[-90.269,38.9249],[-90.2607,38.9237],[-90.2554,38.9224],[-90.2488,38.9197],[-90.2438,38.9181],[-90.238,38.9152],[-90.2257,38.9099],[-90.2185,38.9054],[-90.2114,38.9005],[-90.2054,38.8965],[-90.2002,38.8928],[-90.1956,38.8891],[-90.1888,38.8861],[-90.1839,38.8843],[-90.1793,38.8824],[-90.1733,38.8803],[-90.1682,38.8781],[-90.1623,38.8753],[-90.1555,38.8722],[-90.1437,38.8659],[-90.1336,38.8605],[-90.1234,38.8555],[-90.1181,38.8534],[-90.1141,38.8508],[-90.1118,38.8471],[-90.1096,38.8426],[-90.1086,38.838],[-90.1091,38.8335],[-90.1101,38.8285],[-90.1121,38.8218],[-90.1146,38.8154],[-90.116,38.8105],[-90.1185,38.806],[-90.1212,38.812],[-90.1263,38.8207],[-90.1413,38.8296],[-90.1443,38.8296],[-90.1461,38.8297],[-90.1585,38.829],[-90.1835,38.8218],[-90.2006,38.8239],[-90.2198,38.8342],[-90.2349,38.8426],[-90.2361,38.8431],[-90.2524,38.8511],[-90.2588,38.854],[-90.2599,38.8544],[-90.2697,38.8632],[-90.2708,38.8651],[-90.2714,38.8669],[-90.2731,38.8692],[-90.276,38.872],[-90.2788,38.8747],[-90.2834,38.8811],[-90.2839,38.8816],[-90.2857,38.8835],[-90.2868,38.8848],[-90.288,38.8853],[-90.2886,38.8853],[-90.2909,38.8872],[-90.2926,38.8881],[-90.2932,38.889],[-90.2943,38.8895],[-90.2949,38.8895],[-90.2955,38.89],[-90.2978,38.8909],[-90.2996,38.8919],[-90.3002,38.8923],[-90.3025,38.8928],[-90.3031,38.8928],[-90.3049,38.8933],[-90.3061,38.8933],[-90.309,38.8939],[-90.3107,38.8948],[-90.3119,38.8953],[-90.3137,38.8953],[-90.3143,38.8953],[-90.316,38.8953],[-90.3202,38.895],[-90.3208,38.895],[-90.3214,38.8945],[-90.3226,38.8945],[-90.3238,38.8941],[-90.3244,38.8941],[-90.3255,38.8941],[-90.3267,38.8937],[-90.3273,38.8933],[-90.3279,38.8928],[-90.3291,38.8924],[-90.3303,38.892],[-90.331,38.8911],[-90.3322,38.8902],[-90.3334,38.8893],[-90.334,38.8884],[-90.3352,38.8871],[-90.3358,38.8866],[-90.3364,38.8853],[-90.3371,38.8848],[-90.3384,38.8799],[-90.3391,38.8772],[-90.3397,38.8763],[-90.3397,38.8749],[-90.341,38.8727],[-90.341,38.8717],[-90.341,38.8708],[-90.3429,38.8668],[-90.3425,38.8613],[-90.3426,38.8582],[-90.3451,38.851],[-90.3452,38.8501],[-90.3533,38.8366],[-90.3606,38.829],[-90.3726,38.8229],[-90.3868,38.8222],[-90.4062,38.8257],[-90.4226,38.8292],[-90.4232,38.8292],[-90.425,38.8292],[-90.4309,38.8293],[-90.4338,38.8293],[-90.4404,38.8272],[-90.4476,38.8219],[-90.45,38.8196],[-90.4611,38.8058],[-90.4617,38.8049],[-90.4684,38.7973],[-90.4739,38.7897],[-90.4759,38.7834],[-90.4765,38.7825],[-90.4815,38.7712],[-90.4821,38.7703],[-90.4852,38.7654],[-90.4858,38.7645],[-90.4943,38.7556],[-90.5034,38.7475],[-90.5076,38.7453],[-90.5154,38.74],[-90.522,38.7365],[-90.5292,38.7334],[-90.5335,38.7267],[-90.533,38.7213],[-90.5304,38.709],[-90.5307,38.6972],[-90.5338,38.6936],[-90.5374,38.6914],[-90.5463,38.6884],[-90.5558,38.6863],[-90.5641,38.6846],[-90.6018,38.6852],[-90.616,38.6854],[-90.6265,38.6896],[-90.637,38.6916],[-90.6459,38.6913],[-90.6554,38.6882],[-90.6625,38.6874],[-90.6762,38.6804],[-90.6775,38.6763],[-90.6817,38.6719],[-90.6848,38.666],[-90.6961,38.6639],[-90.7045,38.6595],[-90.7069,38.6577],[-90.7093,38.655],[-90.7158,38.6533],[-90.726,38.648],[-90.7319,38.6449],[-90.7349,38.6432],[-90.7373,38.6414],[-90.738,38.6396],[-90.7386,38.6387],[-90.7398,38.6373],[-90.741,38.6365],[-90.7422,38.6328],[-90.7453,38.6288],[-90.7459,38.627],[-90.7507,38.6221],[-90.7525,38.6203],[-90.7532,38.6189],[-90.7538,38.6176],[-90.755,38.6158],[-90.755,38.6144],[-90.7551,38.6122],[-90.7563,38.6108],[-90.7575,38.6086],[-90.7599,38.6063],[-90.7618,38.6041],[-90.763,38.6023],[-90.7636,38.601],[-90.763,38.6001],[-90.7763,38.5866],[-90.7769,38.5848],[-90.7781,38.5849],[-90.7787,38.5844],[-90.7793,38.583],[-90.7818,38.5804],[-90.783,38.5786],[-90.7836,38.5772],[-90.7854,38.5759],[-90.7889,38.5755],[-90.7907,38.5764],[-90.7954,38.5769],[-90.8,38.5824],[-90.8069,38.5866],[-90.8075,38.5866],[-90.8128,38.5867],[-90.8175,38.5863],[-90.8223,38.5832],[-90.8265,38.5819],[-90.8282,38.5815],[-90.83,38.581],[-90.8324,38.5815],[-90.8347,38.5811],[-90.8359,38.5811],[-90.8383,38.5811],[-90.8412,38.5807],[-90.8442,38.5799],[-90.8465,38.5794],[-90.8513,38.5772],[-90.8525,38.575],[-90.8538,38.5732],[-90.8538,38.5723],[-90.855,38.5705],[-90.8568,38.5687],[-90.858,38.5673],[-90.8598,38.5656],[-90.8604,38.5647],[-90.8729,38.5576],[-90.8873,38.5473],[-90.8938,38.5438],[-90.9022,38.5403],[-90.9093,38.5381],[-90.9181,38.5382],[-90.9263,38.5374],[-90.9363,38.5385],[-90.9481,38.5404],[-90.9539,38.5414],[-90.9557,38.5423],[-90.9586,38.5442],[-90.9609,38.5451],[-90.9626,38.546],[-90.9632,38.5465],[-90.9644,38.5474],[-90.9563,38.875],[-90.957,38.8986],[-90.9499,38.8981],[-90.944,38.8957],[-90.94,38.8925],[-90.9376,38.8911],[-90.9347,38.8911],[-90.9324,38.8888],[-90.9294,38.8901],[-90.9264,38.8914],[-90.9216,38.8914],[-90.9169,38.8922],[-90.9121,38.894],[-90.9085,38.8957],[-90.9021,38.8952],[-90.8986,38.8929],[-90.8951,38.8915],[-90.8892,38.8905],[-90.8838,38.8909],[-90.8767,38.8931],[-90.8719,38.8935],[-90.8678,38.8934],[-90.8625,38.892],[-90.8608,38.8897],[-90.8591,38.8874],[-90.8579,38.8869],[-90.8549,38.8878],[-90.8519,38.8896],[-90.8478,38.8877],[-90.8431,38.8867],[-90.8384,38.888],[-90.836,38.8889],[-90.8331,38.887],[-90.8308,38.8838],[-90.829,38.8825],[-90.8202,38.881],[-90.8166,38.8814],[-90.8142,38.8827],[-90.8124,38.8836],[-90.8065,38.8831],[-90.8053,38.8844],[-90.8047,38.8871],[-90.8076,38.8894],[-90.8087,38.8913],[-90.8074,38.898],[-90.8078,38.9062],[-90.8054,38.9062],[-90.8013,38.9052],[-90.7989,38.907],[-90.7976,38.9106],[-90.8005,38.9142],[-90.8016,38.917],[-90.7986,38.9197],[-90.7915,38.9209],[-90.7849,38.9222],[-90.7795,38.9258],[-90.7753,38.9275],[-90.7689,38.9265],[-90.7653,38.9255],[-90.7612,38.9241],[-90.7571,38.9254],[-90.7523,38.9272],[-90.7475,38.9303],[-90.7433,38.9329],[-90.7385,38.9338],[-90.7332,38.9337],[-90.7285,38.9323],[-90.725,38.9309],[-90.7245,38.9268],[-90.7269,38.925],[-90.7287,38.9241],[-90.7311,38.9224],[-90.7329,38.9201],[-90.7324,38.9183],[-90.7312,38.9178],[-90.7294,38.9173],[-90.7264,38.9191],[-90.7241,38.9195],[-90.7247,38.9155],[-90.723,38.9132],[-90.7183,38.9145],[-90.7165,38.9149],[-90.7135,38.9139],[-90.7113,38.9107],[-90.7089,38.9098],[-90.7066,38.9075],[-90.7037,38.9079],[-90.7001,38.9097],[-90.6988,38.9119],[-90.7017,38.9151],[-90.7082,38.9152],[-90.7123,38.9162],[-90.7146,38.9185],[-90.714,38.9207],[-90.7122,38.923],[-90.7086,38.9243],[-90.7038,38.9238],[-90.6992,38.9214],[-90.6962,38.9209],[-90.6897,38.9204],[-90.6856,38.9208],[-90.6844,38.9226],[-90.6902,38.9263],[-90.6937,38.9286],[-90.6972,38.9309],[-90.6983,38.9341],[-90.6928,38.939],[-90.6637,38.9369],[-90.6622,38.9322],[-90.6611,38.9281],[-90.6582,38.9238],[-90.656,38.9208],[-90.6528,38.9184],[-90.6508,38.9162],[-90.6468,38.9135],[-90.6432,38.9108],[-90.6393,38.9082],[-90.6372,38.9059],[-90.6346,38.9037],[-90.6329,38.9001],[-90.6312,38.8973],[-90.6269,38.8924],[-90.6225,38.889],[-90.6156,38.8857],[-90.6085,38.882],[-90.5983,38.8768],[-90.5904,38.874],[-90.5846,38.8724],[-90.5781,38.8702],[-90.5728,38.8692],[-90.5663,38.87],[-90.5592,38.8712],[-90.5532,38.873],[-90.5466,38.8765],[-90.5422,38.8791],[-90.5375,38.8828],[-90.5321,38.8872],[-90.5273,38.8916],[-90.5212,38.8965],[-90.5165,38.9006],[-90.5104,38.9031],[-90.5062,38.9053],[-90.5036,38.908],[-90.4977,38.9134],[-90.4946,38.9183],[-90.4885,38.925],[-90.4838,38.9317],[-90.4821,38.9362],[-90.4815,38.9399],[-90.4804,38.9444],[-90.4789,38.9493],[-90.477,38.9521],[-90.4766,38.9526],[-90.4734,38.9569],[-90.4697,38.9614],[-90.4653,38.964],[-90.46,38.9663],[-90.4548,38.9675],[-90.4493,38.9685]]]},\"properties\":{\"name\":\"Saint Charles\",\"state\":\"MO\"}}]}","contact":"

Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-08-12","noUsgsAuthors":false,"publicationDate":"2020-08-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":795454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voss, Jonathon D. 0000-0001-8219-7887","orcid":"https://orcid.org/0000-0001-8219-7887","contributorId":237843,"corporation":false,"usgs":false,"family":"Voss","given":"Jonathon D.","affiliations":[],"preferred":false,"id":795455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rydlund, Paul H. Jr. 0000-0001-9461-9944 prydlund@usgs.gov","orcid":"https://orcid.org/0000-0001-9461-9944","contributorId":3840,"corporation":false,"usgs":true,"family":"Rydlund","given":"Paul","suffix":"Jr.","email":"prydlund@usgs.gov","middleInitial":"H.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":795456,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211582,"text":"sir20205059 - 2020 - Hydrology and geomorphology of the Taiya River near the West Creek Tributary, southeast Alaska","interactions":[],"lastModifiedDate":"2020-08-12T14:26:37.531465","indexId":"sir20205059","displayToPublicDate":"2020-08-11T14:15:21","publicationYear":"2020","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":"2020-5059","displayTitle":"Hydrology and Geomorphology of the Taiya River Near the West Creek Tributary, Southeast Alaska","title":"Hydrology and geomorphology of the Taiya River near the West Creek Tributary, southeast Alaska","docAbstract":"

The Taiya River flows through the Chilkoot Trail Unit of Klondike Gold Rush National Historical Park in southeast Alaska, which was founded to preserve cultural and historical resources and further understanding of natural processes active in the surrounding coastal-to-subarctic basin. Riverine processes exert an important influence on ecologically important boreal toad (Anaxryus boreas boreas), salmon [chum salmon (Oncorhynchus keta), pink salmon (O. gorbushca), and coho salmon (O. kisutch)], and eulachon (Thaleichthys pacificus) habitats, erosion of the historic ghost town of Dyea and other cultural and historical artifacts, and recreational opportunities in the lower 7.5 kilometers (km) of the Taiya River valley bottom. Recurrent consideration of hydroelectric development in West Creek upstream of the park since the 1980s has included proposals for damming and diverting West Creek, which could alter the delivery of water and sediment to this section of the Taiya River. To improve understanding of the hydrologic dependence of park resources for the purposes of guiding effective monitoring and conservation, this study, conducted by the U.S. Geological Survey in cooperation with the National Park Service, used a review of hydrologic data, collection of discrete suspended sediment data, geomorphic mapping, and analysis of historical aerial and ground photographs in a reconnaissance of formative geomorphic processes and hydrologic conditions in the lower 7.5 km of the Taiya River valley bottom.

Streamflow and suspended sediment data collected at the U.S. Geological Survey streamgages on the Taiya River and West Creek, combined with historical data, document conditions consistent with streams draining strongly glacierized basins in Alaska. Suspended sediment concentrations from samples collected concurrently over six varying flow levels during 2017–18 ranged from 6 to 284 milligrams per liter (mg/L) for the Taiya River and 13 to 162 mg/L for West Creek, which are similar to or slightly higher than historical values. For the common period of record (1970–77), correlation of daily mean discharge between the two streams was strongest (Pearson’s r = 0.97) during the prolonged May–October high-flow season and weakest (r = 0.90) during the November–April low-flow season, when West Creek daily mean discharge was proportionally higher. For the Taiya River, streamflow data compared between the available periods of record (1970–77 and 2004–17) showed no decadal-scale patterns in mean annual discharge but did show a shift toward an earlier spring snowmelt pulse. Notable flooding in the Taiya River Basin includes glacial lake outburst floods from the Nourse River valley prior to and during the 1897–98 Gold Rush, a 2002 glacial lake outburst flood from the West Creek valley, and a 1967 rainfall-generated flood.

Geomorphic mapping identified four categories of surfaces in the valley bottom—active main stem, abandoned main stem, alluvial fans, and emergent tidal surfaces. Using the maps, main-stem surfaces were subdivided into age categories to identify channel migration patterns from prior to 1940s to 2018. The valley bottom is dominated by active or abandoned channels of the Taiya River except at the extensive low-angle West Creek fan. The active main stem presently supports a mostly single-thread channel with bars and a few sloughs, but the channel actively moved and sometimes was braided within multiple, wider unvegetated corridors in 1894 and earlier. An inventory of 29 off-main-stem channels identified for the study indicates that abandoned main stem channels provide local topographic lows that can intercept groundwater or sustain tributary flow, facilitating the formation of most nonestuarine wetlands in the valley and sustaining important boreal toad breeding habitat.

Within the active main stem corridor, the channel has episodically built and reworked meanders and bars, eroding more than one-half of the historic Dyea townsite, in response to glacially controlled delivery of water and sediment, flooding, inputs from West Creek, local features including large woody debris and beaver dams, and rapid uplift from isostatic rebound. West Creek has constructed a large, persistent fan, provoked kilometer-scale Taiya River channel change near the confluence, constructively added to high-season streamflow that affects Taiya River channel migration capacity, disproportionately contributed early-season streamflow, and possibly contributed to groundwater levels in the valley bottom. The progressive narrowing and stability of the main stem corridor, possibly a result of reduction in the magnitude or frequency of glacial lake outburst floods or glacial sediment delivery to streams, indicates less active future reworking of abandoned main-stem surfaces or regeneration of wetland features. The fluvial history of the Taiya River valley bottom collectively indicates continued channel change within a limited corridor, relative stability in wetland locations but uncertainty in stability of groundwater supply to them, and channel incision and extension in response to uplift.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205059","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Curran, J.H., 2020, Hydrology and geomorphology of the Taiya River near the West Creek Tributary, southeast Alaska: U.S. Geological Survey Scientific Investigations Report 2020–5059, 57 p., https://doi.org/10.3133/sir20205059.","productDescription":"Report: viii, 57 p.; Data Release","numberOfPages":"57","onlineOnly":"Y","ipdsId":"IP-102183","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":376975,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5059/covrthb.jpg"},{"id":376976,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5059/sir20205059.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":376977,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XP1SE7","linkHelpText":"Geomorphic surface and channel boundaries for the lower 7.5 kilometers of the Taiya River Valley, southeast Alaska, 2018"}],"country":"United States","state":"Alaska","otherGeospatial":"Taiya River Near the West Creek Tributary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -137.5927734375,\n 57.71588512774503\n ],\n [\n -135,\n 57.657157596582984\n ],\n [\n -132.64892578125,\n 57.621875380195455\n ],\n [\n -132.64892578125,\n 59.877911874831156\n ],\n [\n -137.61474609375,\n 59.877911874831156\n ],\n [\n -137.5927734375,\n 57.71588512774503\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508

","tableOfContents":"","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"publishedDate":"2020-07-31","noUsgsAuthors":false,"publicationDate":"2020-07-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Curran, Janet H. 0000-0002-3899-6275 jcurran@usgs.gov","orcid":"https://orcid.org/0000-0002-3899-6275","contributorId":690,"corporation":false,"usgs":true,"family":"Curran","given":"Janet","email":"jcurran@usgs.gov","middleInitial":"H.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":794702,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70211866,"text":"ofr20201098 - 2020 - Understanding and documenting the scientific basis of selenium ecological protection in support of site-specific guidelines development for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada","interactions":[],"lastModifiedDate":"2020-08-12T14:23:02.871456","indexId":"ofr20201098","displayToPublicDate":"2020-08-11T13:57:34","publicationYear":"2020","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":"2020-1098","displayTitle":"Understanding and Documenting the Scientific Basis of Selenium Ecological Protection in Support of Site-Specific Guidelines Development for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada","title":"Understanding and documenting the scientific basis of selenium ecological protection in support of site-specific guidelines development for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada","docAbstract":"

Modeling of ecosystems is a part of the U.S. Environmental Protection Agency’s protocol for developing site-specific selenium guidelines for protection of aquatic life. Selenium as an environmental contaminant is known to bioaccumulate and cause reproductive effects in fish and wildlife. Here we apply a modeling methodology—ecosystem-scale selenium modeling—to understand and document the scientific basis for predicting and validating ecological protection for Lake Koocanusa, a transboundary reservoir between Montana and British Columbia. A comprehensive set of site-specific data compiled from public databases (Federal, State, and Provincial) and reports by Teck Coal Ltd., is available in a companion U.S. Geological Survey data release. The tissue guideline used within modeling here to assess protection is the U.S. Environmental Protection Agency’s national selenium guideline for whole-body fish (dry weight); however, other numeric values for a whole-body guideline or other tissue types may be assumed if applicable tissue-to-tissue conversion factors are available. 

We consider the report assembled here as a working document that presents a model that can effectively address and structure the needs of (1) scientific understanding in representing the lake’s ecosystem and selenium biodynamics and (2) policy and management development during a decision-making process, but it is open to modification and updating as more ecologically detailed data become available. The approach brings together the main concerns involved in selenium toxicity: likelihood of high exposure, inherent species sensitivity, and close connectivity of ecosystem characteristics and behavioral ecology of predators. Detailed site-specific modeling equations are provided to document the linked factors that determine the responses of ecosystems to selenium. A series of scenarios quantifies the implications of choices of site-specific variables including food-web species, bioavailability of particulate material, and partitioning between the dissolved and particulate phases at the base of food webs. A gradient mapping tool applied to Lake Koocanusa provides a precedent for ecosystem-scale modeling of lakes by recognizing the importance of lake strata and hydrodynamics as components of modeling. 

Data requirements for ecosystem modeling, including ecological and hydrological process information fundamental to the dietary biodynamics of selenium in site-specific food webs, were assessed as a precursor to model validation for Lake Koocanusa. Understanding these relationships is necessary to connect modeling outcomes to reproductive effects and establish boundaries, in the case of Lake Koocanusa, for the influences of dam operation, fish-community viability, and its Clean Water Act impaired 303(d)-listing status on ecosystem function. 

We find that an assemblage of conditions affects the representation of Lake Koocanusa’s ecosystem within modeling scenarios but that the constructed gradient maps, mechanistic model, and associated bioaccumulation potentials portray and quantify the variables that are determinative to protection of predator species. Ecological and hydrological sorting of compiled individual data points on a site- and species-specific basis helps identify and address model uncertainties. Sources of uncertainty include (1) the scarcity of data for some environmental media compartments across time and locations, (2) the complexity of hydrodynamic conditions that can lead to seasonal ecological disconnects such as in selenium partitioning from water into particulates, and (3) the functional status of Lake Koocanusa’s ecosystem because of cumulative effects of various environmental stresses (for example, fish-community changes, flow regime changes, parasites, gonadal dysfunction, and increasing mining input-selenium concentrations since 1984). To this last point, it is important to determine where Lake Koocanusa is in an impairment-restoration cycle so as not to base protection on survivor bias, the maintenance of a currently degraded ecosystem, or normalized toxicity. In a broader context, one of the overall consequences of revised selenium regulations is that their derivation is now dependent on being able to define and understand the status of the ecosystem on which protection is based.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201098","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality","usgsCitation":"Presser, T.S., and Naftz, D.L., 2020, Understanding and documenting the scientific basis of selenium ecological protection in support of site-specific guidelines development for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada: U.S. Geological Survey Open-File Report 2020–1098, 40 p., https://doi.org/10.3133/ofr20201098.","productDescription":"Report: viii, 40 p.; 3 Tables; Data Releases","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-120031","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":436823,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99LM27E","text":"USGS data release","linkHelpText":"Results of Ecosystem Scale Selenium Modeling in Support of Site-Specific Guidelines Development for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada, 2020"},{"id":377297,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HB5S5F","text":"USGS data release","description":"USGS Data Release","linkHelpText":"USGS measurements of dissolved and suspended particulate material selenium in Lake Koocanusa in the vicinity of Libby Dam (MT), 2015–2017 (update)"},{"id":377296,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VXYSNZ","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Selenium concentrations in food webs of Lake Koocanusa in the vicinity of Libby Dam (MT) and the Elk River (BC) as the basis for applying ecosystem-scale modeling, 2008–2018"},{"id":377295,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1098/ofr20201098.pdf","text":"Report","size":"19.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1098"},{"id":377294,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1098/coverthb.jpg"},{"id":377363,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2020/1098/ofr20201098_tables_1_and_3_to_10.xlsx","text":"Tables 1 and 3–10","size":"91.5 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2020–1098 Tables"}],"country":"United States, Canada","state":"Montana, British Columbia","otherGeospatial":"Lake Koocanusa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.72998046875,\n 48.33251726168281\n ],\n [\n -114.90600585937499,\n 48.33251726168281\n ],\n [\n -114.90600585937499,\n 49.457413352792216\n ],\n [\n -115.72998046875,\n 49.457413352792216\n ],\n [\n -115.72998046875,\n 48.33251726168281\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Water Mission Area
U.S. Geological Survey
345 Middlefield Rd.
Menlo Park, CA 94025

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2020-08-11","noUsgsAuthors":false,"publicationDate":"2020-08-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Presser, Theresa S. 0000-0001-5643-0147 tpresser@usgs.gov","orcid":"https://orcid.org/0000-0001-5643-0147","contributorId":2467,"corporation":false,"usgs":true,"family":"Presser","given":"Theresa","email":"tpresser@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":795464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Naftz, David L. 0000-0003-1130-6892 dlnaftz@usgs.gov","orcid":"https://orcid.org/0000-0003-1130-6892","contributorId":1041,"corporation":false,"usgs":true,"family":"Naftz","given":"David","email":"dlnaftz@usgs.gov","middleInitial":"L.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":795465,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211854,"text":"70211854 - 2020 - Improving early warning of drought-driven food insecurity in Southern Africa using operational hydrological monitoring and forecasting products","interactions":[],"lastModifiedDate":"2020-08-12T14:30:08.809626","indexId":"70211854","displayToPublicDate":"2020-08-11T11:59:29","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Improving early warning of drought-driven food insecurity in Southern Africa using operational hydrological monitoring and forecasting products","docAbstract":"The region of southern Africa (SA) has a fragile food economy and is vulnerable to frequent droughts. Interventions to mitigate food insecurity impacts require early warning of droughts —preferably as early as possible before the harvest season (typically, starting in April) and lean season (typically, starting in November). Hydrologic monitoring and forecasting systems provide a unique opportunity to support early warning efforts, since they can provide regular updates on available rootzone soil moisture (RZSM), a critical variable for crop yield, and provide forecasts of RZSM by combining the estimates of antecedent soil moisture conditions with climate forecasts. For SA, this study documents the predictive capabilities of RZSM products from a recently developed NASA Hydrological Forecasting and Analysis System (NHyFAS). Results show that the NHyFAS products would have identified the regional severe drought event—which peaked during December-February of 2015/2016—at least as early as November 1, 2015. Next, it is shown that during 1982-2016, February RZSM forecasts [monitoring product] available in early November [early March] have a correlation of 0.49 [0.79] with the detrended regional crop yield. It is also found that when the February RZSM forecast [monitoring product] available in early November [early March] is indicated to be in the lowest tercile, the detrended regional crop yield is below normal about two-thirds of the time [always], at least over the sample years considered. Additionally, it is shown that February RZSM forecast [monitoring product] can provide “out-of-sample” crop yield forecasts with comparable [substantially better with 40% reduction in mean error] skill to December-February ENSO. These results indicate that the NHyFAS products can effectively support food insecurity early warning in the SA region. Finally, since a framework similar to NHyFAS can be used to provide RZSM monitoring and forecasting products over other regions of the globe, this case study also demonstrates potential for supporting food insecurity early warning globally.","language":"English","publisher":"Copernicus","doi":"10.5194/nhess-20-1187-2020","usgsCitation":"Shukla, S., Arsenault, K., Hazra, A., Peters-Lidard, C., Davenport, F., Magadzire, T., and Funk, C., 2020, Improving early warning of drought-driven food insecurity in Southern Africa using operational hydrological monitoring and forecasting products: Hydrology and Earth System Sciences, v. 20, p. 1187-1201, https://doi.org/10.5194/nhess-20-1187-2020.","productDescription":"15 p.","startPage":"1187","endPage":"1201","ipdsId":"IP-111564","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":455657,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-20-1187-2020","text":"Publisher Index Page"},{"id":377344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Southern Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 40.166015625,\n -10.746969318459989\n ],\n [\n 26.455078125,\n -14.604847155053898\n ],\n [\n 12.83203125,\n -17.14079039331664\n ],\n [\n 11.513671874999998,\n -17.72775860985227\n ],\n [\n 18.896484375,\n -36.17335693522159\n ],\n [\n 30.322265625000004,\n -34.161818161230386\n ],\n [\n 40.78125,\n -17.811456088564473\n ],\n [\n 40.166015625,\n -10.746969318459989\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","noUsgsAuthors":false,"publicationDate":"2020-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Shukla, Shraddhanand","contributorId":224784,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":13549,"text":"UC Santa Barbara Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":795403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arsenault, Kristi","contributorId":198836,"corporation":false,"usgs":false,"family":"Arsenault","given":"Kristi","affiliations":[],"preferred":false,"id":795404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hazra, Abda","contributorId":237825,"corporation":false,"usgs":false,"family":"Hazra","given":"Abda","email":"","affiliations":[],"preferred":false,"id":795405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters-Lidard, Christa","contributorId":198839,"corporation":false,"usgs":false,"family":"Peters-Lidard","given":"Christa","email":"","affiliations":[],"preferred":false,"id":795406,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davenport, Frank","contributorId":145816,"corporation":false,"usgs":false,"family":"Davenport","given":"Frank","email":"","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":795407,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Magadzire, Tamuka","contributorId":145822,"corporation":false,"usgs":false,"family":"Magadzire","given":"Tamuka","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":795408,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":795409,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70212473,"text":"70212473 - 2020 - Boreal blazes: Biomass burning and vegetation types archived in the Juneau Icefield","interactions":[],"lastModifiedDate":"2020-09-09T14:53:31.855594","indexId":"70212473","displayToPublicDate":"2020-08-11T08:35:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Boreal blazes: Biomass burning and vegetation types archived in the Juneau Icefield","docAbstract":"

The past decade includes some of the most extensive boreal forest fires in the historical record. Warming temperatures, changing precipitation patterns, the desiccation of thick organic soil layers, and increased ignition from lightning all contribute to a combustive combination. Smoke aerosols travel thousands of kilometers, before blanketing the surfaces on which they fall, such as the Juneau Icefield. However, many aerosols found in smoke plumes are also produced by other processes and therefore can be ambiguous indicators of fire activity. Here, we use the monosaccharide anhydrides levoglucosan, mannosan, and galactosan as specific indicators of biomass burning to unambiguously demonstrate that fire aerosols reach the Juneau Icefield and are integrated into the snowpack. Back trajectories and satellite observations demonstrate that smoke plumes originating in central Alaska and eastern Siberia affect the Juneau Icefield. These regional sources of fire differ from other combustion aerosols deposited on the Juneau Icefield, such as black carbon, that originate from local fossil fuel burning. Ratios of levoglucosan/mannosan (L/M) and levoglucosan/(mannosan + galactosan) (L/(M + G)) demonstrate that while the majority of fire aerosols reaching the Juneau Icefield originate from softwood burning, grasslands and hardwood forests are also sources. The presence of these hardwoods suggests that fire aerosols may reach the Juneau Icefield from locations as far away as East Asia.

","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ab8fd2","usgsCitation":"Kehrwald, N., Jasmann, J.R., Dunham, M.E., Ferris, D.G., Osterburg, E.C., Kennedy, J., Havens, J.C., Fortner, S.K., and Barber, L., 2020, Boreal blazes: Biomass burning and vegetation types archived in the Juneau Icefield: Environmental Research Letters, v. 15, no. 8, 085005, 15 p., https://doi.org/10.1088/1748-9326/ab8fd2.","productDescription":"085005, 15 p.","ipdsId":"IP-111615","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":455677,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ab8fd2","text":"Publisher Index Page"},{"id":377596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Juneau icefield","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -136.51611328125,\n 58.00809779306888\n ],\n [\n -133.6376953125,\n 58.00809779306888\n ],\n [\n -133.6376953125,\n 59.7563950493563\n ],\n [\n -136.51611328125,\n 59.7563950493563\n ],\n [\n -136.51611328125,\n 58.00809779306888\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"15","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Kehrwald, Natalie 0000-0002-9160-2239","orcid":"https://orcid.org/0000-0002-9160-2239","contributorId":220636,"corporation":false,"usgs":true,"family":"Kehrwald","given":"Natalie","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":796402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jasmann, Jeramy Roland 0000-0002-5251-6987","orcid":"https://orcid.org/0000-0002-5251-6987","contributorId":238713,"corporation":false,"usgs":true,"family":"Jasmann","given":"Jeramy","email":"","middleInitial":"Roland","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":796403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Melissa E.","contributorId":238714,"corporation":false,"usgs":false,"family":"Dunham","given":"Melissa","email":"","middleInitial":"E.","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":796404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ferris, David G.","contributorId":238715,"corporation":false,"usgs":false,"family":"Ferris","given":"David","email":"","middleInitial":"G.","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":796405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Osterburg, Erich C.","contributorId":238716,"corporation":false,"usgs":false,"family":"Osterburg","given":"Erich","email":"","middleInitial":"C.","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":796406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kennedy, Joshua","contributorId":238717,"corporation":false,"usgs":false,"family":"Kennedy","given":"Joshua","email":"","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":796407,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Havens, Jeremy C. 0000-0002-8685-2823","orcid":"https://orcid.org/0000-0002-8685-2823","contributorId":238719,"corporation":false,"usgs":false,"family":"Havens","given":"Jeremy","email":"","middleInitial":"C.","affiliations":[{"id":37768,"text":"USGS Contractor","active":true,"usgs":false}],"preferred":false,"id":796628,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Barber, Larry B. 0000-0002-0561-0831","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":218953,"corporation":false,"usgs":true,"family":"Barber","given":"Larry B.","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":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":796408,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fortner, Sarah K.","contributorId":238718,"corporation":false,"usgs":false,"family":"Fortner","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":47748,"text":"Wittenberg University","active":true,"usgs":false}],"preferred":false,"id":796409,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70209319,"text":"ofr20201010 - 2020 - Repurposing a hindcast simulation of the 1926 Great Miami Hurricane, south Florida","interactions":[],"lastModifiedDate":"2020-08-11T12:26:13.109316","indexId":"ofr20201010","displayToPublicDate":"2020-08-10T13:45:24","publicationYear":"2020","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":"2020-1010","displayTitle":"Repurposing a Hindcast Simulation of the 1926 Great Miami Hurricane, South Florida","title":"Repurposing a hindcast simulation of the 1926 Great Miami Hurricane, south Florida","docAbstract":"

Hydrodynamic model hindcasts of the surface water and groundwater of the Everglades and the greater Miami, Florida, area were used to simulate hydrology using estimated storm surge height, wind field, and rainfall for the Great Miami Hurricane (GMH), which struck on September 18, 1926. Ranked estimates of losses from hurricanes in inflation-adjusted dollars indicate that the GMH was one of the most damaging tropical cyclones to make landfall in the United States, but little hydrologic data were collected because many types of field stations did not exist at the time. Several techniques were used to estimate previously unknown critical storm variables for model input, demonstrating the value of reanalyzing historical storm events using modern hydrodynamic modeling. This representation of the 1926 GMH was then used to develop a hypothetical simulation of the hydrologic effects of a similar hurricane occurring in contemporary (1996) times. Results indicate that the 18-centimeter sea-level rise between 1926 and 1996 had a greater effect on salinity intrusion than climatic differences or the development of modern canal-based infrastructure. Moreover, the post-1926 canal infrastructure does not seem to substantially mitigate the deleterious effects of sea-level rise.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201010","usgsCitation":"Krohn, M.D., Swain, E.D., Langtimm, C.A., and Obeysekera, J., 2020, Repurposing a hindcast simulation of the 1926 Great Miami Hurricane, south Florida: U.S. Geological Survey Open-File Report 2020–1010, 9 p., https://doi.org/10.3133/ofr20201010.","productDescription":"Report: iv, 9 p.; Data Release","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-073595","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":375607,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C681IV","text":"USGS data release","linkHelpText":"FTLOADDS (combined SWIFT2D surface-water model and SEAWAT groundwater model) simulator used to repurpose a hindcast simulation of the 1926 Great Miami Hurricane using the south Florida peninsula for the Biscayne and Southern Everglades Coastal Transport (BISECT) model"},{"id":375605,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1010/coverthb.jpg"},{"id":375606,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1010/ofr20201010.pdf","text":"Report","size":"2.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1010"}],"country":"United States","state":"Florida","city":"Miami","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.55999755859375,\n 25.209911213827688\n ],\n [\n -80.28533935546875,\n 25.199970890386023\n ],\n [\n -80.04638671875,\n 25.403584973186703\n ],\n [\n -80.04638671875,\n 26.23430203240673\n ],\n [\n -80.52978515625,\n 26.23430203240673\n ],\n [\n -80.55999755859375,\n 25.209911213827688\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Caribbean-Florida Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, Florida 33559

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-08-10","noUsgsAuthors":false,"publicationDate":"2020-08-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Krohn, M. Dennis","contributorId":223706,"corporation":false,"usgs":false,"family":"Krohn","given":"M.","email":"","middleInitial":"Dennis","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":false,"id":786039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langtimm, Catherine A. 0000-0001-8499-5743","orcid":"https://orcid.org/0000-0001-8499-5743","contributorId":223707,"corporation":false,"usgs":true,"family":"Langtimm","given":"Catherine","email":"","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":786040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Obeysekera, Jayantha 0000-0002-9261-1268","orcid":"https://orcid.org/0000-0002-9261-1268","contributorId":223708,"corporation":false,"usgs":false,"family":"Obeysekera","given":"Jayantha","affiliations":[{"id":40755,"text":"South Florida WMD West Palm Beach, FL","active":true,"usgs":false}],"preferred":false,"id":786041,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70211848,"text":"sir20205079 - 2020 - Water-quality trends for selected sites and constituents in the international Red River of the North Basin, Minnesota and North Dakota, United States, and Manitoba, Canada, 1970–2017","interactions":[],"lastModifiedDate":"2020-08-11T12:18:59.556966","indexId":"sir20205079","displayToPublicDate":"2020-08-10T12:46:54","publicationYear":"2020","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":"2020-5079","displayTitle":"Water-Quality Trends for Selected Sites and Constituents in the International Red River of the North Basin, Minnesota and North Dakota, United States, and Manitoba, Canada, 1970–2017","title":"Water-quality trends for selected sites and constituents in the international Red River of the North Basin, Minnesota and North Dakota, United States, and Manitoba, Canada, 1970–2017","docAbstract":"

A comprehensive study to evaluate water-quality trends, while considering natural hydroclimatic variability, in the Red River of the North Basin and assess water-quality conditions for the Red River of the North crossing the international boundary near Emerson, Manitoba, Canada (the binational site), was completed by the U.S. Geological Survey in cooperation with the International Joint Commission, North Dakota Department of Environmental Quality, and Minnesota Pollution Control Agency and in collaboration with Manitoba Sustainable Development and Environment and Climate Change Canada. The international Red River of the North Basin encompasses 3 U.S. States (South Dakota, North Dakota, and Minnesota) and 1 Canadian Province (Manitoba). Water quality in the Red River of the North Basin is of concern for both Federal governments and State and Provincial governments. Water-quality objectives have been previously established for selected dissolved ions and recently (2019) proposed for selected nutrients for the binational site.

In the current (2020) study, water-quality data from State, Provincial, and Federal agencies in the United States and Canada for sites in the Red River of the North Basin from 1970 to 2017 were compiled and used for trend analysis. Trend analysis using a water-quality dataset from multiple agencies that collect water-quality data for various objectives presented multiple challenges. The trend-analysis approach was able to accommodate differences in water-quality data caused by field-collection and laboratory-analytical method differences, disparities in sampling frequencies, and spatial and temporal gaps in data. Most of these challenges were overcome by the statistical tool, R–QWTREND, which identifies trends in concentration unrelated to variability in streamflow.

The integrated basin approach used in the current study, combined with comparing current data trends with historical trends, provided valuable insights into understanding how water quality is changing spatially (34 sites analyzed for a recent period, 2000–15) and temporally (5 sites analyzed for a 45-year historical period, 1970–2015) within the Red River of the North Basin. One of the most consistent spatial and temporal changes observed in the current study was increasing concentrations of sulfate among tributary and main-stem sites since 2000. For some sites, increases were detected starting as early as 1985. Total dissolved solids and chloride concentrations had spatial and temporal patterns like sulfate. Although R–QWTREND removes the variability in constituent concentration caused by natural streamflow variability, all variability in sulfate caused by hydroclimatic variability may not be captured because of changes in hydrologic pathways and changes in the contributions of sulfate from various natural sources.

Nutrient concentrations demonstrated less consistent spatial and temporal changes than sulfate, and changes in nutrient concentrations were assumed to be more closely tied to human-induced rather than natural changes. Nitrate-plus-nitrite concentrations were mostly increasing in the upper Red River of the North subbasin, and for nitrate plus nitrite and total nitrogen, the Sheyenne River subbasin had consistent decreasing concentrations. Since 2000, total phosphorus has decreased in the upper Red River of the North subbasin, but total phosphorus concentration has increased for sites in the lower Red River of the North subbasin, and for some main-stem sites, concentrations have been increasing since 1985. Unlike sulfate, the pattern in historical trends for total phosphorus for the main-stem sites differed from tributary sites, indicating that human-induced changes affected tributaries and main-stem sites differently.

The more detailed evaluation of flow-averaged water-quality conditions for the binational site provided an understanding of how loads have changed over time and what proportion of the year and season concentrations are expected to exceed water-quality objectives. In a basin with highly variable streamflow like the Red River of the North, the trend in flow-averaged load (assuming streamflow conditions are the same year after year) provided a robust measure of change over time. Increasing concentrations of sulfate, chloride, total dissolved solids, and total phosphorus since 1985 for the binational site resulted in longer periods of exceedance of water-quality objectives per year occurring over time. For total nitrogen, decreasing concentrations resulted in shorter periods of exceedance per year during 1980 to 2015, but concentrations were still expected to exceed the water-quality objective about half the year. Periods of when exceedances were likely to occur during the year were affected by the source and transport mechanisms of the constituent.

Trend results from this effort identified how water quality has changed across the basin, and further investigation would help to identify causes for the trends observed here. Information from the current study provides a basis for future trend attribution studies, evaluation of water-quality objectives, and development of comprehensive strategies for reducing nutrients to desired targets and establishes a baseline for tracking future progress in the Red River of the North Basin.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205079","collaboration":"Prepared in cooperation with the International Joint Commission, North Dakota Department of Environmental Quality, and Minnesota Pollution Control Agency and in collaboration with Manitoba Sustainable Development and Environment and Climate Change Canada","usgsCitation":"Nustad, R.A., and Vecchia, A.V., 2020, Water-quality trends for selected sites and constituents in the international Red River of the North Basin, Minnesota and North Dakota, United States, and Manitoba, Canada, 1970–2017: U.S. Geological Survey Scientific Investigations Report 2020–5079, 75 p., https://doi.org/10.3133/sir20205079.","productDescription":"Report: ix, 75 p.; 2 Tables; Data Release; Dataset","numberOfPages":"90","onlineOnly":"Y","ipdsId":"IP-113881","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":377257,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5079/coverthb.jpg"},{"id":377260,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C9JAMY","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water-quality and streamflow data for United States and Canadian sites in the Red River Basin and scripts for trend analysis—Data supporting water-quality trend analysis in the Red River of the North basin, 1970–2017"},{"id":377258,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5079/sir20205079.pdf","text":"Report","size":"11.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5079"},{"id":377259,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2020/5079/sir20205079_tables_2_and_3.xlsx","text":"Tables 2 and 3","size":"60.3 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5079 Tables 2 and 3"},{"id":377261,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation","description":"USGS Data Release","linkHelpText":"— U.S. Geological Survey National Water Information System database"}],"country":"United States, Canada","state":"Minnesota, North Dakota, South Dakota, Manitoba","otherGeospatial":"Red River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.27294921875,\n 50.14874640066278\n ],\n [\n -98.85498046875,\n 49.710272582105695\n ],\n [\n -100.81054687499999,\n 49.38237278700955\n ],\n [\n -100.7666015625,\n 48.58932584966975\n ],\n [\n -99.86572265625,\n 47.040182144806664\n ],\n [\n -98.525390625,\n 46.7248003746672\n ],\n [\n -98.76708984374999,\n 46.37725420510028\n ],\n [\n -98.63525390624999,\n 45.96642454131025\n ],\n [\n -97.91015624999999,\n 45.55252525134013\n ],\n [\n -97.14111328125,\n 45.321254361171476\n ],\n [\n -95.77880859375,\n 45.89000815866184\n ],\n [\n -95.2294921875,\n 46.28622391806706\n ],\n [\n -95.1416015625,\n 46.73986059969267\n ],\n [\n -95.0537109375,\n 47.68018294648414\n ],\n [\n -94.59228515625,\n 47.79839667295524\n ],\n [\n -94.306640625,\n 48.07807894349862\n ],\n [\n -94.54833984375,\n 48.29781249243716\n ],\n [\n -95.1416015625,\n 48.23930899024907\n ],\n [\n -95.2734375,\n 48.850258199721495\n ],\n [\n -95.42724609375,\n 49.1242192485914\n ],\n [\n -96.7236328125,\n 50.02185841773444\n ],\n [\n -97.27294921875,\n 50.14874640066278\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503 1608
Mountain View Road,
Rapid City, SD 57702

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2020-08-10","noUsgsAuthors":false,"publicationDate":"2020-08-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Nustad, Rochelle A. 0000-0002-4713-5944 ranustad@usgs.gov","orcid":"https://orcid.org/0000-0002-4713-5944","contributorId":1811,"corporation":false,"usgs":true,"family":"Nustad","given":"Rochelle","email":"ranustad@usgs.gov","middleInitial":"A.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":795353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401 avecchia@usgs.gov","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":1173,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"avecchia@usgs.gov","middleInitial":"V.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":795354,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216776,"text":"70216776 - 2020 - Integrating airborne remote sensing and field campaigns for ecology and Earth system science","interactions":[],"lastModifiedDate":"2020-12-07T16:36:45.211204","indexId":"70216776","displayToPublicDate":"2020-08-08T10:08:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Integrating airborne remote sensing and field campaigns for ecology and Earth system science","docAbstract":"
  1. In recent years, the availability of airborne imaging spectroscopy (hyperspectral) data has expanded dramatically. The high spatial and spectral resolution of these data uniquely enable spatially explicit ecological studies including species mapping, assessment of drought mortality and foliar trait distributions. However, we have barely begun to unlock the potential of these data to use direct mapping of vegetation characteristics to infer subsurface properties of the critical zone. To assess their utility for Earth systems research, imaging spectroscopy data acquisitions require integration with large, coincident ground‐based datasets collected by experts in ecology and environmental and Earth science. Without coordinated, well‐planned field campaigns, potential knowledge leveraged from advanced airborne data collections could be lost. Despite the growing importance of this field, documented methods to couple such a wide variety of disciplines remain sparse.
  2. We coordinated the first National Ecological Observatory Network Airborne Observation Platform (AOP) survey performed outside of their core sites, which took place in the Upper East River watershed, Colorado. Extensive planning for sample tracking and organization allowed field and flight teams to update the ground‐based sampling strategy daily. This enabled collection of an extensive set of physical samples to support a wide range of ecological, microbiological, biogeochemical and hydrological studies.
  3. We present a framework for integrating airborne and field campaigns to obtain high‐quality data for foliar trait prediction and document an archive of coincident physical samples collected to support a systems approach to ecological research in the critical zone. This detailed methodological account provides an example of how a multi‐disciplinary and multi‐institutional team can coordinate to maximize knowledge gained from an airborne survey, an approach that could be extended to other studies.
  4. The coordination of imaging spectroscopy surveys with appropriately timed and extensive field surveys, along with high‐quality processing of these data, presents a unique opportunity to reveal new insights into the structure and dynamics of the critical zone. To our knowledge, this level of co‐aligned sampling has never been undertaken in tandem with AOP surveys and subsequent studies utilizing this archive will shed considerable light on the breadth of applications for which imaging spectroscopy data can be leveraged.
","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.13463","usgsCitation":"Chadwick, K.D., Brodrick, P.G., Grant, K., Goulden, T., Henderson, A., Falco, N., Wainwright, H., Williams, K., Bill, M., Breckheimer, I., Brodie, E., Steltzer, H., Williams, C.F., Blonder, B., Chen, J., Dafflon, B., Damerow, J., Hancher, M., Khurram, A., Lamb, J., Lawrence, C.R., McCormick, M., Musinsky, J., Pierce, S., Polussa, A., Hastings Porro, M., Scott, A., Wu Singh, H., Sorensen, P., Varadharajan, C., Whitney, B., and Maher, K., 2020, Integrating airborne remote sensing and field campaigns for ecology and Earth system science: Methods in Ecology and Evolution, v. 11, no. 11, p. 1492-1508, https://doi.org/10.1111/2041-210X.13463.","productDescription":"17 p.","startPage":"1492","endPage":"1508","ipdsId":"IP-118938","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":455710,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.13463","text":"Publisher Index Page"},{"id":381039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Upper East River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.01129913330078,\n 38.68443777679761\n ],\n [\n -106.80255889892578,\n 38.68443777679761\n ],\n [\n -106.80255889892578,\n 38.89717867392901\n ],\n [\n -107.01129913330078,\n 38.89717867392901\n ],\n [\n -107.01129913330078,\n 38.68443777679761\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Chadwick, K. Dana","contributorId":245426,"corporation":false,"usgs":false,"family":"Chadwick","given":"K.","email":"","middleInitial":"Dana","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brodrick, Philip G.","contributorId":245427,"corporation":false,"usgs":false,"family":"Brodrick","given":"Philip","email":"","middleInitial":"G.","affiliations":[{"id":27365,"text":"NASA Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":806185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grant, Kathleen","contributorId":245428,"corporation":false,"usgs":false,"family":"Grant","given":"Kathleen","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goulden, Tristan","contributorId":245429,"corporation":false,"usgs":false,"family":"Goulden","given":"Tristan","email":"","affiliations":[{"id":49194,"text":"National Ecological Observation Network","active":true,"usgs":false}],"preferred":false,"id":806187,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henderson, Amanda","contributorId":245430,"corporation":false,"usgs":false,"family":"Henderson","given":"Amanda","affiliations":[{"id":49195,"text":"Rocky Mountain Biological Laboratory","active":true,"usgs":false}],"preferred":false,"id":806188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Falco, Nicola","contributorId":245431,"corporation":false,"usgs":false,"family":"Falco","given":"Nicola","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806189,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wainwright, Haruko","contributorId":245432,"corporation":false,"usgs":false,"family":"Wainwright","given":"Haruko","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806190,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Kenneth","contributorId":245433,"corporation":false,"usgs":false,"family":"Williams","given":"Kenneth","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806191,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bill, Markus","contributorId":245434,"corporation":false,"usgs":false,"family":"Bill","given":"Markus","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806192,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Breckheimer, Ian","contributorId":245435,"corporation":false,"usgs":false,"family":"Breckheimer","given":"Ian","affiliations":[{"id":49195,"text":"Rocky Mountain Biological Laboratory","active":true,"usgs":false}],"preferred":false,"id":806193,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Brodie, Eoin","contributorId":245436,"corporation":false,"usgs":false,"family":"Brodie","given":"Eoin","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806194,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Steltzer, Heidi","contributorId":245437,"corporation":false,"usgs":false,"family":"Steltzer","given":"Heidi","affiliations":[{"id":49196,"text":"Fort Lewis College","active":true,"usgs":false}],"preferred":false,"id":806195,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Williams, C. F. Rick","contributorId":245438,"corporation":false,"usgs":false,"family":"Williams","given":"C.","email":"","middleInitial":"F. Rick","affiliations":[{"id":49195,"text":"Rocky Mountain Biological Laboratory","active":true,"usgs":false}],"preferred":false,"id":806196,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Blonder, Benjamin","contributorId":245439,"corporation":false,"usgs":false,"family":"Blonder","given":"Benjamin","email":"","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":806197,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Chen, Jiancong","contributorId":245440,"corporation":false,"usgs":false,"family":"Chen","given":"Jiancong","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806198,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Dafflon, Baptiste","contributorId":245441,"corporation":false,"usgs":false,"family":"Dafflon","given":"Baptiste","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806199,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Damerow, Joan","contributorId":245442,"corporation":false,"usgs":false,"family":"Damerow","given":"Joan","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806200,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Hancher, Matt","contributorId":245443,"corporation":false,"usgs":false,"family":"Hancher","given":"Matt","email":"","affiliations":[{"id":12484,"text":"Google","active":true,"usgs":false}],"preferred":false,"id":806201,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Khurram, Aizah","contributorId":245444,"corporation":false,"usgs":false,"family":"Khurram","given":"Aizah","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806202,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Lamb, Jack","contributorId":245445,"corporation":false,"usgs":false,"family":"Lamb","given":"Jack","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806203,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Lawrence, Corey R. 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202390,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":806204,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"McCormick, Maeve","contributorId":245446,"corporation":false,"usgs":false,"family":"McCormick","given":"Maeve","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806205,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Musinsky, John","contributorId":245447,"corporation":false,"usgs":false,"family":"Musinsky","given":"John","affiliations":[{"id":49194,"text":"National Ecological Observation Network","active":true,"usgs":false}],"preferred":false,"id":806206,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Pierce, Samuel","contributorId":245448,"corporation":false,"usgs":false,"family":"Pierce","given":"Samuel","email":"","affiliations":[{"id":36408,"text":"SLAC National Accelerator Laboratory","active":true,"usgs":false}],"preferred":false,"id":806207,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Polussa, Alexander","contributorId":245449,"corporation":false,"usgs":false,"family":"Polussa","given":"Alexander","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806208,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Hastings Porro, Maceo","contributorId":245450,"corporation":false,"usgs":false,"family":"Hastings Porro","given":"Maceo","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806209,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Scott, Andea","contributorId":245451,"corporation":false,"usgs":false,"family":"Scott","given":"Andea","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806210,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Wu Singh, Hans","contributorId":245452,"corporation":false,"usgs":false,"family":"Wu Singh","given":"Hans","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806211,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Sorensen, Patrick O.","contributorId":245453,"corporation":false,"usgs":false,"family":"Sorensen","given":"Patrick O.","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806212,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Varadharajan, Charuleka","contributorId":245454,"corporation":false,"usgs":false,"family":"Varadharajan","given":"Charuleka","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806213,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Whitney, Bizuayehu","contributorId":245455,"corporation":false,"usgs":false,"family":"Whitney","given":"Bizuayehu","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":806214,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Maher, Katharine","contributorId":245456,"corporation":false,"usgs":false,"family":"Maher","given":"Katharine","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806215,"contributorType":{"id":1,"text":"Authors"},"rank":32}]}} ,{"id":70212497,"text":"70212497 - 2020 - Ecosystem services of riparian restoration: A review of rock detention structures in the Madrean Archipelago Ecoregion","interactions":[],"lastModifiedDate":"2020-08-18T14:46:14.015324","indexId":"70212497","displayToPublicDate":"2020-08-07T09:40:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":686,"text":"Air, Soil and Water Research","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem services of riparian restoration: A review of rock detention structures in the Madrean Archipelago Ecoregion","docAbstract":"In northwestern Mexico and the southwestern United States, limited water supplies and fragile landscapes jeopardize world-renowned biological diversity. Simple rock detention structures have been used to manage agricultural water for over a thousand years and are now being installed to restore ecohydrological functionality but with little scientific evidence of their success. The impacts, design, and construction of such structures has been debated among local restoration practitioners, management, and permitting agencies. This article presents archeological documentation, local contentions, and examples of available research assessments of rock detention structures in the Madrean Archipelago Ecoregion. A US Geological Survey study to quantify impacts of rock detention structures using remote-sensing analyses, hydrologic monitoring, vegetation surveys, and watershed modeling is discussed, and results rendered in terms of the critical restoration ecosystem services provided. This framework provides a means for comparing management actions that might directly or indirectly impact human populations and assessing tradeoffs between them.","language":"English","publisher":"Sage Journals","doi":"10.1177/1178622120946337","usgsCitation":"Norman, L., 2020, Ecosystem services of riparian restoration: A review of rock detention structures in the Madrean Archipelago Ecoregion: Air, Soil and Water Research, v. 13, 13 p., https://doi.org/10.1177/1178622120946337.","productDescription":"13 p.","ipdsId":"IP-114137","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":455722,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1177/1178622120946337","text":"Publisher Index Page"},{"id":377603,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","state":"Arizona, Chihuahua, New Mexico, Sonora","otherGeospatial":"Madrean Archipelago Ecoregion","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.610107421875,\n 29.372601506681402\n ],\n [\n -108.00659179687499,\n 29.372601506681402\n ],\n [\n -108.00659179687499,\n 33.486435450999885\n ],\n [\n -111.610107421875,\n 33.486435450999885\n ],\n [\n -111.610107421875,\n 29.372601506681402\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2020-08-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":203300,"corporation":false,"usgs":true,"family":"Norman","given":"Laura M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":796583,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70211604,"text":"ds1129 - 2020 - Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2019","interactions":[],"lastModifiedDate":"2020-08-04T21:34:42.312972","indexId":"ds1129","displayToPublicDate":"2020-08-04T14:33:20","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1129","displayTitle":"Water-Level Data for the Albuquerque Basin and Adjacent Areas, Central New Mexico, Period of Record Through September 30, 2019","title":"Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2019","docAbstract":"

The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is hydrologically defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift between San Acacia to the south and Cochiti Lake to the north. A 20-percent population increase in the basin from 1990 to 2000 and a 22-percent population increase from 2000 to 2010 resulted in an increased demand for water in areas within the basin. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when the Albuquerque Bernalillo County Water Utility Authority (ABCWUA) began treatment and distribution of surface water from the Rio Grande through the San Juan-Chama Drinking Water Project.

An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the Albuquerque Basin. In 1983, this network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly. As of 2019, the network consisted of 120 wells and piezometers. (A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers screened at different depths.) The USGS, in cooperation with the ABCWUA, the New Mexico Office of the State Engineer, and Bernalillo County, measures water levels from the 120 wells and piezometers in the network; this report, prepared in cooperation with the ABCWUA, presents water-level data collected by USGS personnel at those 120 sites through water year 2019 (October 1, 2018, through September 30, 2019). Water levels that were collected from those discontinued wells in previous water years were published in previous USGS reports.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1129","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Beman, J.E., 2020, Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2019: U.S. Geological Survey Data Series 1129, 40 p., https://doi.org/10.3133/ds1129.","productDescription":"iii, 40 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-120239","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":377000,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1129/coverthb.jpg"},{"id":377001,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1129/ds1129.pdf","text":"Report","size":"5.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1129"}],"country":"United States","state":"New Mexico","city":"Albuquerque","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.611083984375,\n 33.797408767572485\n ],\n [\n -105.941162109375,\n 33.797408767572485\n ],\n [\n -105.941162109375,\n 36.06686213257888\n ],\n [\n -107.611083984375,\n 36.06686213257888\n ],\n [\n -107.611083984375,\n 33.797408767572485\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-08-04","noUsgsAuthors":false,"publicationDate":"2020-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Beman, Joseph E. 0000-0002-0689-029X jebeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0689-029X","contributorId":2619,"corporation":false,"usgs":true,"family":"Beman","given":"Joseph","email":"jebeman@usgs.gov","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":794774,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70211645,"text":"70211645 - 2020 - Macroinvertebrate oviposition habitat selectivity and egg-mass desiccation tolerances: Implications for population dynamics in large regulated rivers","interactions":[],"lastModifiedDate":"2020-09-10T20:22:24.200583","indexId":"70211645","displayToPublicDate":"2020-08-04T09:13:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Macroinvertebrate oviposition habitat selectivity and egg-mass desiccation tolerances: Implications for population dynamics in large regulated rivers","docAbstract":"

Aquatic insects exhibit complex life cycles that include egg, larval, adult, and, in some instances, pupal stages. Disturbances at any of these life stages can affect overall population dynamics. Yet, efforts to understand the effects of disturbances, such as hydrologic alterations, overwhelmingly focus on the larval life stage of aquatic insects. We evaluated the potential for load-following flows associated with hydroelectric power production to act as a population bottleneck for aquatic insects via reductions in the availability and temporal persistence of optimal oviposition habitats. Specifically, we quantified the oviposition habitat selectivity of Baetis spp. (Baetidae), Brachycentrus occidentalis (Brachycentridae), Chironomidae (Diptera), and Hydropsyche occidentalis (Hydropsychidae) downstream of Flaming Gorge Dam, Utah, USA. We found that all taxa except H. occidentalis preferentially laid eggs on large emergent substrates located along the river edge. Peak discharge associated with load-following flows substantially reduced the number of emergent substrates available for oviposition, and daily low flows exposed eggs in these habitats to desiccation and drying. When subjected to experimental drying, both Baetis and H. occidentalis eggs experienced nearly 100% mortality after 2 h, whereas most B. occidentalis remained viable after 8 h. Our paired field and experimental results are consistent with the hypothesis that load-following flows from hydroelectric dams produce a population bottleneck for aquatic insects by short circuiting recruitment processes. Environmental flows that seek to improve the health of tailwater aquatic insect populations would benefit from consideration of habitat requirements for all life stages of aquatic insects.

","language":"English","publisher":"University of Chicago Press Journals","doi":"10.1086/710237","usgsCitation":"Miller, S.W., Schroer, M., Fleri, J.R., and Kennedy, T.A., 2020, Macroinvertebrate oviposition habitat selectivity and egg-mass desiccation tolerances: Implications for population dynamics in large regulated rivers: Freshwater Science, v. 39, no. 3, p. 584-599, https://doi.org/10.1086/710237.","productDescription":"16 p.","startPage":"584","endPage":"599","onlineOnly":"N","ipdsId":"IP-112469","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":455768,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1086/710237","text":"Publisher Index Page"},{"id":377107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Green River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.52407836914062,\n 40.84706035607122\n ],\n [\n -109.10659790039062,\n 40.84706035607122\n ],\n [\n -109.10659790039062,\n 40.93841495689795\n ],\n [\n -109.52407836914062,\n 40.93841495689795\n ],\n [\n -109.52407836914062,\n 40.84706035607122\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, Scott W.","contributorId":237002,"corporation":false,"usgs":false,"family":"Miller","given":"Scott","email":"","middleInitial":"W.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":794962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schroer, Matt","contributorId":237003,"corporation":false,"usgs":false,"family":"Schroer","given":"Matt","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":794963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fleri, Jesse R.","contributorId":237004,"corporation":false,"usgs":false,"family":"Fleri","given":"Jesse","email":"","middleInitial":"R.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":794964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kennedy, Theodore A. 0000-0003-3477-3629 tkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":167537,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","email":"tkennedy@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":794965,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70213241,"text":"70213241 - 2020 - The pervasive and multifaceted influence of biocrusts on water in the world’s drylands","interactions":[],"lastModifiedDate":"2020-09-24T16:21:19.257777","indexId":"70213241","displayToPublicDate":"2020-07-30T10:45:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"The pervasive and multifaceted influence of biocrusts on water in the world’s drylands","docAbstract":"

The capture and use of water are critically important in drylands, which collectively constitute Earth's largest biome. Drylands will likely experience lower and more unreliable rainfall as climatic conditions change over the next century. Dryland soils support a rich community of microphytic organisms (biocrusts), which are critically important because they regulate the delivery and retention of water. Yet despite their hydrological significance, a global synthesis of their effects on hydrology is lacking. We synthesized 2,997 observations from 109 publications to explore how biocrusts affected five hydrological processes (times to ponding and runoff, early [sorptivity] and final [infiltration] stages of water flow into soil, and the rate or volume of runoff) and two hydrological outcomes (moisture storage, sediment production). We found that increasing biocrust cover reduced the time for water to pond on the surface (−40%) and commence runoff (−33%), and reduced infiltration (−34%) and sediment production (−68%). Greater biocrust cover had no significant effect on sorptivity or runoff rate/amount, but increased moisture storage (+14%). Infiltration declined most (−56%) at fine scales, and moisture storage was greatest (+36%) at large scales. Effects of biocrust type (cyanobacteria, lichen, moss, mixed), soil texture (sand, loam, clay), and climatic zone (arid, semiarid, dry subhumid) were nuanced. Our synthesis provides novel insights into the magnitude, processes, and contexts of biocrust effects in drylands. This information is critical to improve our capacity to manage dwindling dryland water supplies as Earth becomes hotter and drier.

","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15232","usgsCitation":"Eldridge, D., Reed, S., Travers, S.K., Bowker, M.A., Maestre, F.T., Ding, J., Havrilla, C.A., Rodriguez-Caballero, E., Barger, N.N., Weber, B., Antoninka, A., Belnap, J., Chaudhary, B.V., Faist, A.M., Ferrenberg, S., Huber-Sannwald, E., Issa, O., and Zhao, Y., 2020, The pervasive and multifaceted influence of biocrusts on water in the world’s drylands: Global Change Biology, v. 26, no. 10, p. 6003-6014, https://doi.org/10.1111/gcb.15232.","productDescription":"12 p.","startPage":"6003","endPage":"6014","ipdsId":"IP-117232","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":490068,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1644140","text":"External Repository"},{"id":378433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-07-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Eldridge, David J. 0000-0002-2191-486X","orcid":"https://orcid.org/0000-0002-2191-486X","contributorId":66535,"corporation":false,"usgs":false,"family":"Eldridge","given":"David J.","affiliations":[{"id":27407,"text":"Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia","active":true,"usgs":false}],"preferred":false,"id":798740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":798723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Travers, Samantha K.","contributorId":240682,"corporation":false,"usgs":false,"family":"Travers","given":"Samantha","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":798741,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bowker, Matthew A. mbowker@usgs.gov","contributorId":2875,"corporation":false,"usgs":true,"family":"Bowker","given":"Matthew","email":"mbowker@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":798742,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maestre, Fernando T.","contributorId":62450,"corporation":false,"usgs":true,"family":"Maestre","given":"Fernando","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":798743,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ding, Jingyi","contributorId":240684,"corporation":false,"usgs":false,"family":"Ding","given":"Jingyi","email":"","affiliations":[],"preferred":false,"id":798744,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Havrilla, Caroline Ann 0000-0003-3913-0980","orcid":"https://orcid.org/0000-0003-3913-0980","contributorId":228882,"corporation":false,"usgs":true,"family":"Havrilla","given":"Caroline","email":"","middleInitial":"Ann","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":798745,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rodriguez-Caballero, Emilio 0000-0002-5934-3214","orcid":"https://orcid.org/0000-0002-5934-3214","contributorId":205639,"corporation":false,"usgs":false,"family":"Rodriguez-Caballero","given":"Emilio","email":"","affiliations":[{"id":37132,"text":"Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":798746,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barger, Nichole N.","contributorId":193039,"corporation":false,"usgs":false,"family":"Barger","given":"Nichole","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":798747,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Weber, Bettina","contributorId":196800,"corporation":false,"usgs":false,"family":"Weber","given":"Bettina","email":"","affiliations":[],"preferred":false,"id":798748,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Antoninka, Anita","contributorId":166769,"corporation":false,"usgs":false,"family":"Antoninka","given":"Anita","affiliations":[{"id":24503,"text":"Northern Arizona University, School of Forestry, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":798749,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"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":798750,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Chaudhary, Bala V.","contributorId":52718,"corporation":false,"usgs":true,"family":"Chaudhary","given":"Bala","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":798751,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Faist, Akasha M.","contributorId":193038,"corporation":false,"usgs":false,"family":"Faist","given":"Akasha","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":798752,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Ferrenberg, Scott 0000-0002-3542-0334 sferrenberg@usgs.gov","orcid":"https://orcid.org/0000-0002-3542-0334","contributorId":147684,"corporation":false,"usgs":true,"family":"Ferrenberg","given":"Scott","email":"sferrenberg@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":798753,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Huber-Sannwald, Elisabeth","contributorId":88700,"corporation":false,"usgs":false,"family":"Huber-Sannwald","given":"Elisabeth","email":"","affiliations":[],"preferred":false,"id":798754,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Issa, Oumarou M","contributorId":174266,"corporation":false,"usgs":false,"family":"Issa","given":"Oumarou M","affiliations":[{"id":27408,"text":"URCA, GEGENAA EA 3795, 51100 Reims – France / UMR 242 IEES-Paris, IRD representation au Niger BP11416 Niamey, Niger","active":true,"usgs":false}],"preferred":false,"id":798755,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Zhao, Y.","contributorId":81705,"corporation":false,"usgs":true,"family":"Zhao","given":"Y.","email":"","affiliations":[],"preferred":false,"id":798756,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ]}