Beginning in the 1970s, Alameda County Water District began infiltrating imported water through ponds in repurposed gravel quarries at the Quarry Lakes Regional Park, in the Niles Cone groundwater subbasin, to recharge groundwater and to minimize intrusion of saline, San Francisco Bay water into freshwater aquifers. Hydraulic connection between distinct aquifers underlying Quarry Lakes allows water to recharge the upper aquifer system to depths of 400 feet below land surface, and the Deep aquifer to depths of more than 650 feet. Previous studies of the Niles Cone and southern East Bay Plain groundwater subbasins suggested that these two subbasins may be hydraulically connected. Characterization of storage capacities and hydraulic properties of the complex aquifers and the structural and stratigraphic controls on groundwater movement aids in optimal storage and recovery of recharged water and provides information on the ability of aquifers shared by different water management agencies to fulfill competing storage and extraction demands. The movement of recharge water through the Niles Cone groundwater subbasin from Quarry Lakes and the possible hydraulic connection between the Niles Cone and the southern East Bay Plain groundwater subbasins were investigated using interferometric synthetic aperture radar (InSAR), water-chemistry, and isotopic data, including tritium/helium-3, helium-4, and carbon-14 age-dating techniques.
InSAR data collected during refilling of the Quarry Lakes recharge ponds show corresponding ground-surface displacement. Maximum uplift was about 0.8 inches, reasonable for elastic expansion of sedimentary materials experiencing an increase in hydraulic head that resulted from pond refilling. Sodium concentrations increase while calcium and magnesium concentrations in groundwater decrease along groundwater flowpaths from the Niles Cone groundwater subbasin through the Deep aquifer to the northwest toward the southern East Bay Plain groundwater subbasin. Residual effects of pre-1970s intrusion of saline water from San Francisco Bay, including high chloride concentrations in groundwater, are evident in parts of the Niles Cone subbasin. Noble gas recharge temperatures indicate two primary recharge sources (Quarry Lakes and Alameda Creek) in the Niles Cone groundwater subbasin. Although recharge at Quarry Lakes affects hydraulic heads as far as the transition zone between the Niles Cone and East Bay Plain groundwater subbasins (about 5 miles), the effect of recharged water on water quality is only apparent in wells near (less than 2 miles) recharge sources. Groundwater chemistry from upper aquifer system wells near Quarry Lakes showed an evaporated signal (less negative oxygen and hydrogen isotopic values) relative to surrounding groundwater and a tritium concentration (2 tritium units) consistent with recently recharged water from a surface-water impoundment.
Uncorrected carbon-14 activities measured in water sampled from wells in the Niles Cone groundwater subbasin range from 16 to 100 percent modern carbon (pmC). The geochemical reaction modeling software NETPATH was used to interpret carbon-14 ages along a flowpath from Quarry Lakes toward the East Bay Plain groundwater subbasin. Model results indicate that changes in groundwater chemistry are controlled by cation exchange on clay minerals and weathering of primary silicate minerals. Old groundwater (lower carbon-14 activities) is characterized by high dissolved silica and pH. Interpreted carbon-14 ages ranged from 830 to more than 7,000 years before present and are less than helium-4 ages that range from 2,000 to greater than 11,000 years before present. The average horizontal groundwater velocity along the studied flowpath, as calculated using interpreted carbon-14 ages, through the Deep aquifer of the Niles Cone groundwater subbasin is between 3 and 12 feet per year. The groundwater velocity decreases near the boundary of the transition zone to the southern East Bay Plain groundwater subbasin to about 0.5 feet per year. These changes may result from water recharged from different sources converging in flowpaths north of the transition zone, or a boundary to flow between the Niles Cone and southern East Bay Plain groundwater subbasins, likely owing to changes in lithology caused by depositional patterns.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185003","collaboration":"Prepared in cooperation with the East Bay Municipal Utility District, City of Hayward, and Alameda County Water District","usgsCitation":"Teague, Nick, Izbicki, John, Borchers, Jim, Kulongoski, Justin, and Jurgens, Bryant, 2018, Hydrogeologic controls and geochemical indicators of groundwater movement in the Niles Cone and southern East Bay Plain groundwater subbasins, Alameda County, California (ver. 1.1, February 2019): U.S. Geological Survey Scientific Investigations Report 2018–5003, 62 p., https://doi.org/10.3133/sir20185003.","productDescription":"x, 62 p.","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-043410","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":360934,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5003/versionHist.txt"},{"id":351228,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5003/coverthb.jpg"},{"id":351229,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5003/sir20185003_v1.1.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5003"}],"country":"United States","state":"California","county":"Alameda County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.3333,\n 37.5\n ],\n [\n -121.9167,\n 37.5\n ],\n [\n -121.9167,\n 37.8333\n ],\n [\n -122.3333,\n 37.8333\n ],\n [\n -122.3333,\n 37.5\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Ver. 1.0: February 2018; Ver. 1.1: February 2019","contact":"Director,
California Water Science Center
6000 J Street, Placer Hall
Sacramento, CA 95819
The quality of stormwater runoff from bridge decks (hereafter referred to as “bridge-deck runoff”) was characterized in a field study from August 2014 through August 2016 in which concentrations of suspended sediment (SS) and total nutrients were monitored. These new data were collected to supplement existing highway-runoff data collected in Massachusetts which were deficient in bridge-deck runoff concentration data. Monitoring stations were installed at three bridges maintained by the Massachusetts Department of Transportation in eastern Massachusetts (State Route 2A in the city of Boston, Interstate 90 in the town of Weston, and State Route 20 near Quinsigamond Village in the city of Worcester). The bridges had annual average daily traffic volumes from 21,200 to 124,000 vehicles per day; the land use surrounding the monitoring stations was 25 to 67 percent impervious.
Automatic-monitoring techniques were used to collect more than 160 flow-proportional composite samples of bridge-deck runoff. Samples were analyzed for concentrations of SS, loss on ignition of suspended solids (LOI), particulate carbon (PC), total phosphorus (TP), total dissolved nitrogen (DN), and particulate nitrogen (PN). The distribution of particle size of SS also was determined for composite samples. Samples of bridge-deck runoff were collected year round during rain, mixed precipitation, and snowmelt runoff and with different dry antecedent periods throughout the 2-year sampling period.
At the three bridge-deck-monitoring stations, median concentrations of SS in composite samples of bridge-deck runoff ranged from 1,490 to 2,020 milligrams per liter (mg/L); however, the range of SS in individual composites was vast at 44 to 142,000 mg/L. Median concentrations of SS were similar in composite samples collected from the State Route 2A and Interstate 90 bridge (2,010 and 2,020 mg/L, respectively), and lowest at the State Route 20 bridge (1,490 mg/L). Concentrations of coarse sediment (greater than 0.25 millimeters in diameter) dominated the SS matrix by more than an order of magnitude. Concentrations of LOI and PC in composite samples ranged from 15 to 1,740 mg/L and 6.68 to 1,360 mg/L, respectively, and generally represented less than 10 and 3 percent of the median mass of SS, respectively. Concentrations of TP in composite samples ranged from 0.09 to 7.02 mg/L; median concentrations of TP ranged from 0.505 to 0.69 mg/L and were highest on the bridge on State Route 2A in Boston. Concentrations of total nitrogen (TN) (sum DN and PN) in composite samples were variable (0.36 to 29 mg/L). Median DN (0.64 to 0.90 mg/L) concentrations generally represented about 40 percent of the TN concentration at each bridge and were similar to annual volume-weighted mean concentrations of nitrogen in precipitation in Massachusetts.
Nonparametric statistical methods were used to test for differences between sample constituent concentrations among the three bridges. These results indicated that there are no statistically significant differences for concentrations of SS, LOI, PC, and TP among the three bridges (one-way analysis of variance test on rank-transformed data, 95-percent confidence level). Test results for concentrations of TN in composite samples indicated that concentrations of TN collected on State Route 20 near Quinsigamond Village were significantly higher than those concentrations collected on State Route 2A in Boston and Interstate 90 near Weston. Median concentrations of TN were about 93 and 55 percent lower at State Route 2A and at Interstate 90, respectively, compared to the median concentrations of TN at State Route 20.
Samples of sediment were collected from five fixed locations on each bridge on three occasions during dry weather to calculate semiquantitative distributions of sediment yields on the bridge surface relative to the monitoring location. Mean yields of bridge-deck sediment during this study for State Route 2A in Boston, Interstate 90 near Weston, and State Route 20 near Quinsigamond Village were 1,500, 250, and 5,700 pounds per curb-mile, respectively. Sediment yields at each sampling location varied widely (26 to 25,000 pounds per curb-mile) but were similar to yields reported elsewhere in Massachusetts and the United States. Yields calculated for each sampling location indicated that the sediment was not evenly distributed across each bridge in this study for plausible reasons such as bridge slope, vehicular tracking, and bridge deterioration.
Bridge-deck sediment quality was largely affected by the distribution of sediment particle size. Concentrations of TP in the fine sediment-size fraction (less than 0.0625 millimeter in diameter) of samples of bridge-deck sediment were about 6 times greater than in the coarse size fraction. Concentrations for many total-recoverable metals were 2 to 17 times greater in the fine size fraction compared to concentrations in the coarse size fraction (greater than or equal to 0.25 millimeter in diameter), and concentrations of total-recoverable copper and lead in the fine size fraction were 2 to 65 times higher compared to concentrations in the intermediate (greater than or equal to 0.0625 to 0.25 millimeter in diameter) or the coarse size fraction. However, the proportion of sediment particles less than 0.0625 millimeter in diameter in composite samples of bridge-deck runoff was small (median values range from 4 to 8 percent at each bridge) compared to the larger sediment particle-size mass. As a result, more than 50 percent of the sediment-associated TP, aluminum, chromium, manganese, and nickel was estimated to be associated with the coarse size fraction of the SS load. In contrast, about 95 percent of the estimated sediment-associated copper concentration was associated with the fine size fraction of the SS load.
Version 1.0.2 of the Stochastic Empirical Loading and Dilution Model was used to simulate long-term (29–30-year) concentrations and annual yields of SS, TP, and TN in bridge-deck runoff and in discharges from a hypothetical stormwater treatment best-management practice structure. Three methods (traditional statistics, robust statistics, and L-moments) were used to calculate statistics for stochastic simulations because the high variability in measured concentration values during the field study resulted in extreme simulated concentrations. Statistics of each dataset, including the average, standard deviation, and skew of the common (base 10) logarithms, for each of the three bridges, and for a lumped dataset, were calculated and used for simulations; statistics representing the median of statistics calculated for the three bridges also were used for simulations. These median statistics were selected for the interpretive simulations so that the simulations could be used to estimate concentrations and yields from other, unmonitored bridges in Massachusetts. Comparisons of the standard and robust statistics indicated that simulation results with either method would be similar, which indicated that the large variability in simulated results was not caused by a few outliers. Comparison to statistics calculated by the L-moments methods indicated that L-moments do not produce extreme concentrations; however, they also do not produce results that represent the bulk of concentration data.
The runoff-quality risk analysis indicated that bridge-deck runoff would exceed discharge standards commonly used for large, advanced wastewater treatment plants, but that commonly used stormwater best-management practices may reduce the percentage of exceedances by one-half. Results of simulations indicated that long-term average yields of TN, TP, and SS may be about 21.4, 6.44, and 40,600 pounds per acre per year, respectively. These yields are about 1.3, 3.4, and 16 times simulated ultra-urban highway yields in Massachusetts; however, simulations indicated that use of a best-management practice structure to treat bridge-deck runoff may reduce discharge yields to about 10, 2.8, and 4,300, pounds per acre per year, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185033","isbn":"978-1-4113-4222-4","usgsCitation":"Smith, K.P., Sorenson, J.R., and Granato, G.E., 2018, Characterization of stormwater runoff from bridge decks in eastern Massachusetts, 2014–16: U.S. Geological Survey Scientific Investigations Report 2018–5033, 73 p., https://doi.org/10.3133/sir20185033.","productDescription":"xiii, 73 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088034","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":374915,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5033/sir20185033.pdf","text":"Report","size":"4.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5033"},{"id":353906,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5033/coverthb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.98516845703125,\n 41.97582726102573\n ],\n [\n -70.7904052734375,\n 41.97582726102573\n ],\n [\n -70.7904052734375,\n 42.827638636242284\n ],\n [\n -71.98516845703125,\n 42.827638636242284\n ],\n [\n -71.98516845703125,\n 41.97582726102573\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Lake trout stocking began in the 1970s as part of a binational effort to restore a self-sustaining population of lake trout in Lake Ontario. Despite 48 years of restoration stocking, lake trout in Lake Ontario have not reestablished a self-sustaining population. Spawning surveys done at Stony Island Reef (SIR) in eastern Lake Ontario in 1987 and 1989 documented lake trout egg deposition and swim-up fry. Bottom trawls in the early 1990s found naturally-reproduced juvenile lake trout in this region of the lake. More recently, naturally-reproduced juveniles have been found in western Lake Ontario, but few have been found near SIR in the eastern basin. In 2017 and 2018, we examined SIR spawning habitat and lake trout egg deposition rates and compared them to historical values. The average interstitial depth observed in 2018 was less than 4 cm, and the maximum depth observed was 15 cm. These interstitial depths are greatly reduced from depths up to 45 cm reported in the 1980s. Only one egg was captured in 95 egg nets deployed during the spawning period, which resulted in a CPUE of 0.00035 eggs/net/day, markedly lower than the egg densities measured at SIR in 1987 and 1989 of (1.27 eggs/net/day and 0.27 eggs/net/day respectively). Observations of the cobble spawning habitat suggested interstitial spaces were more infilled relative to conditions observed in the 1980s. Infill material was heavily comprised of dreissenid mussels shells and shell fragments. These findings indicate that changes in lake trout spawning habitat may be inhibiting lake trout reproduction at SIR.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"NYSDEC Lake Ontario annual report 2018","largerWorkSubtype":{"id":2,"text":"State or Local Government Series"},"language":"English","publisher":"New York State Department of Environmental Conservation (NYSDEC)","usgsCitation":"Furgal, S., Lantry, B.F., Weidel, B., Farrell, J.M., Gorsky, D., and Biesinger, Z., 2018, Lake trout spawning and habitat assessment at Stony Island Reef, chap. 20 of NYSDEC Lake Ontario annual report 2018, p. 20-1-20-6.","productDescription":"6 p.","startPage":"20-1","endPage":"20-6","ipdsId":"IP-106482","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":369862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":369861,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.dec.ny.gov/docs/fish_marine_pdf/lourpt18.pdf"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario, Stony Island Reef","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.3065719604492,\n 43.906055713100805\n ],\n [\n -76.27035140991211,\n 43.906055713100805\n ],\n [\n -76.27035140991211,\n 43.92707729641145\n ],\n [\n -76.3065719604492,\n 43.92707729641145\n ],\n [\n -76.3065719604492,\n 43.906055713100805\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Furgal, Stacy 0000-0001-8828-6290","orcid":"https://orcid.org/0000-0001-8828-6290","contributorId":216791,"corporation":false,"usgs":true,"family":"Furgal","given":"Stacy","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":765537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lantry, Brian F. 0000-0001-8797-3910 bflantry@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-3910","contributorId":3435,"corporation":false,"usgs":true,"family":"Lantry","given":"Brian","email":"bflantry@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":765538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":765539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farrell, John M.","contributorId":172505,"corporation":false,"usgs":false,"family":"Farrell","given":"John","email":"","middleInitial":"M.","affiliations":[{"id":27058,"text":"State University of New York, College of Environmental Science and Forestry, Department of Environmental and Forest Biology, 250 Illick Hall, 1 Forestry Drive, Syracuse, NY 13210, USA","active":true,"usgs":false}],"preferred":false,"id":765540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gorsky, Dimitry","contributorId":169691,"corporation":false,"usgs":false,"family":"Gorsky","given":"Dimitry","affiliations":[],"preferred":false,"id":765541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Biesinger, Zy","contributorId":197993,"corporation":false,"usgs":false,"family":"Biesinger","given":"Zy","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":765542,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199464,"text":"ofr20181150 - 2018 - Batrachochytrium salamandriovrans (Bsal) in Appalachia—Using scenario building to proactively prepare for a wildlife disease outbreak caused by an invasive amphibian chytrid fungus","interactions":[],"lastModifiedDate":"2019-11-08T09:16:34","indexId":"ofr20181150","displayToPublicDate":"2019-11-08T10:35:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1150","displayTitle":"Batrachochytrium salamandrivorans (Bsal) in Appalachia: Using Scenario Building to Proactively Prepare for a Wildlife Disease Outbreak Caused by an Invasive Amphibian Chytrid Fungus","title":"Batrachochytrium salamandriovrans (Bsal) in Appalachia—Using scenario building to proactively prepare for a wildlife disease outbreak caused by an invasive amphibian chytrid fungus","docAbstract":"Batrachochytrium salamandrivorans (Bsal), a pathogenic chytrid fungus, is nonnative to the United States and poses a disease threat to vulnerable amphibian hosts. The Bsal fungus may lead to increases in threatened, endangered, and sensitive status listings at State, Tribal, and Federal levels, resulting in financial costs associated with implementing the Endangered Species Act of 1973. The United States is a global biodiversity hotspot for salamanders, an order of amphibians that is particularly vulnerable to developing a disease called chytridiomycosis when exposed to Bsal. Published Bsal risk assessments for North America have suggested that salamanders within the Appalachian region of the United States are at a high risk. In May 2017, a workshop was facilitated by the Department of the Interior’s Strategic Sciences Group. During the workshop, a discussion-based incident-response exercise focused on a hypothetical Bsal disease outbreak in Appalachia was led by U.S. Geological Survey staff members. Participants included representatives of the Eastern Band of the Cherokee Indians, U.S. Fish and Wildlife Service, National Park Service, Appalachian Landscape Conservation Cooperative, Tennessee Wildlife Resources Agency, and U.S. Department of Agriculture’s U.S. Forest Service. Scenario building was used to brainstorm cascading consequences (social, economic, and ecological) of a Bsal disease outbreak in the Appalachian region. This report highlights the management and science actions that could be undertaken to ensure an effective, rapid response to a Bsal introduction into the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181150","usgsCitation":"Hopkins, M.C., Adams, M.J., Super, P.E., Olson, D.H., Hickman, C.R., English, P., Sprague, L., Maska, I.B., Pennaz, A.B., and Ludwig, K.A., 2018, Batrachochytrium salamandriovrans (Bsal) in Appalachia—Using scenario building to proactively prepare for a wildlife disease outbreak caused by an invasive amphibian chytrid fungus: U.S. Geological Survey Open-File Report 2018–1150, 31 p., https://doi.org/10.3133/ofr20181150.","productDescription":"Report: v, 9 p.; Appendixes","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092683","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":359122,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1150/coverthb.jpg"},{"id":359123,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1150/ofr20181150.pdf","text":"Report","size":"7.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2018-1150"}],"contact":"Associate Director, Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive, Suite 300
Reston, VA 20192
Sediment pulses can cause widespread, complex changes to rivers and coastal regions. Quantifying landscape response to sediment-supply changes is a long-standing problem in geomorphology, but the unanticipated nature of most sediment pulses rarely allows for detailed measurement of associated landscape processes and evolution. The intentional removal of two large dams on the Elwha River (Washington, USA) exposed ~30 Mt of impounded sediment to fluvial erosion, presenting a unique opportunity to quantify source-to-sink river and coastal responses to a massive sediment-source perturbation. Here we evaluate geomorphic evolution during and after the sediment pulse, presenting a 5-year sediment budget and morphodynamic analysis of the Elwha River and its delta. Approximately 65% of the sediment was eroded, of which only ~10% was deposited in the fluvial system. This restored fluvial supply of sand, gravel, and wood substantially changed the channel morphology. The remaining ~90% of the released sediment was transported to the coast, causing ~60 ha of delta growth. Although metrics of geomorphic change did not follow simple time-coherent paths, many signals peaked 1–2 years after the start of dam removal, indicating combined impulse and step-change disturbance responses.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-018-30817-8","usgsCitation":"Ritchie, A.C., Warrick, J.A., East, A.E., Magirl, C.S., Stevens, A.W., Bountry, J.A., Randle, T.J., Curran, C.A., Hilldale, R.C., Duda, J.J., Miller, I.M., Pess, G.R., Eidam, E., Foley, M.M., McCoy, R., and Ogston, A.S., 2018, Morphodynamic evolution following sediment release from the world’s largest dam removal: Scientific Reports, v. 8, 13279, 13 p., https://doi.org/10.1038/s41598-018-30817-8.","productDescription":"13279, 13 p.","ipdsId":"IP-093205","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":468150,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-30817-8","text":"Publisher Index Page"},{"id":366979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha Dam, Elwha River, Olympic National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.61679077148438,\n 47.96050238891509\n ],\n [\n -123.61679077148438,\n 48.15600899174947\n ],\n [\n -123.475341796875,\n 48.15600899174947\n ],\n [\n -123.475341796875,\n 47.96050238891509\n ],\n [\n -123.61679077148438,\n 47.96050238891509\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2018-09-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Ritchie, Andrew C. 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Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":769408,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Curran, Christopher A. 0000-0001-8933-416X ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769409,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hilldale, Robert C.","contributorId":139315,"corporation":false,"usgs":false,"family":"Hilldale","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":769410,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 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Randall","contributorId":194430,"corporation":false,"usgs":false,"family":"McCoy","given":"Randall","affiliations":[],"preferred":false,"id":769416,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Ogston, Andrea S.","contributorId":12119,"corporation":false,"usgs":true,"family":"Ogston","given":"Andrea","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":769417,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70205455,"text":"70205455 - 2018 - Thresholds of lake and reservoir connectivity in river networks control nitrogen removal","interactions":[],"lastModifiedDate":"2020-09-01T14:05:16.435219","indexId":"70205455","displayToPublicDate":"2019-07-17T18:32:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Thresholds of lake and reservoir connectivity in river networks control nitrogen removal","docAbstract":"Lakes, reservoirs, and other ponded waters are ubiquitous features of the aquatic landscape, yet their cumulative role in nitrogen removal in large river basins is often unclear. Here we use predictive modeling, together with comprehensive river water quality, land use, and hydrography datasets, to examine and explain the influences of more than 18,000 ponded waters on nitrogen removal through river networks of the Northeastern United States. Thresholds in pond density where ponded waters become important features to regional nitrogen removal are identified and shown to vary according to a ponded waters’ relative size, network position, and degree of connectivity to the river network, which suggests worldwide importance of these new metrics. Consideration of the interacting physical and biological factors, along with thresholds in connectivity, reveal where, why, and how much ponded waters function differently than streams in removing nitrogen, what regional water quality outcomes may result, and in what capacity management strategies could most effectively achieve desired nitrogen loading reduction.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-018-05156-x","usgsCitation":"Schmadel, N.M., Harvey, J., Alexander, R., Schwarz, G., Moore, R., Eng, K., Gomez-Velez, J., Boyer, E.W., and Scott, D., 2018, Thresholds of lake and reservoir connectivity in river networks control nitrogen removal: Nature Communications, v. 9, 2779, 10 p., https://doi.org/10.1038/s41467-018-05156-x.","productDescription":"2779, 10 p.","ipdsId":"IP-093046","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":468151,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-018-05156-x","text":"Publisher Index Page"},{"id":367536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Delaware, District of Columbia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode island, Vermont, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.884765625,\n 44.37098696297173\n ],\n [\n -66.884765625,\n 44.99588261816546\n ],\n [\n -67.67578124999999,\n 45.82879925192134\n ],\n [\n -67.8515625,\n 47.368594345213374\n ],\n [\n -69.2138671875,\n 47.517200697839414\n ],\n [\n -71.19140625,\n 45.398449976304086\n ],\n [\n -71.8505859375,\n 44.99588261816546\n ],\n [\n -74.3994140625,\n 45.182036837015886\n ],\n [\n -76.81640625,\n 42.74701217318067\n ],\n [\n -77.6953125,\n 40.81380923056958\n ],\n [\n -79.40917968749999,\n 39.40224434029275\n ],\n [\n -79.27734374999999,\n 37.50972584293751\n ],\n [\n -78.9697265625,\n 36.914764288955936\n ],\n [\n -75.234375,\n 36.38591277287651\n ],\n [\n -73.125,\n 40.111688665595956\n ],\n [\n -69.2578125,\n 41.11246878918088\n ],\n [\n -66.884765625,\n 44.37098696297173\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmadel, Noah M.","contributorId":219098,"corporation":false,"usgs":false,"family":"Schmadel","given":"Noah","email":"","middleInitial":"M.","affiliations":[{"id":39961,"text":"USGS Post-Doc","active":true,"usgs":false}],"preferred":false,"id":771257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harvey, Judson","contributorId":219097,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":436,"text":"National Research Program - 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Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":771261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gomez-Velez, Jesus D.","contributorId":219103,"corporation":false,"usgs":false,"family":"Gomez-Velez","given":"Jesus D.","affiliations":[{"id":39962,"text":"Department of Earth & Environmental Science, New Mexico Institute of Mining and Technology, Socorro, New Mexico, USA","active":true,"usgs":false}],"preferred":false,"id":771262,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":771263,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Scott, Durelle","contributorId":219088,"corporation":false,"usgs":false,"family":"Scott","given":"Durelle","affiliations":[{"id":39959,"text":"Virginia Tech.","active":true,"usgs":false}],"preferred":false,"id":771264,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70201558,"text":"sim3402 - 2018 - Surficial materials of Massachusetts—A 1:24,000-scale geologic map database","interactions":[],"lastModifiedDate":"2022-02-03T15:37:52.987287","indexId":"sim3402","displayToPublicDate":"2019-03-01T11:30:00","publicationYear":"2018","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":"3402","displayTitle":"Surficial Materials of Massachusetts—A 1:24,000-Scale Geologic Map Database","title":"Surficial materials of Massachusetts—A 1:24,000-scale geologic map database","docAbstract":"The surficial materials geologic map database defines the distribution of nonlithified earth materials at the land surface in the 189 7.5-minute, 1:24,000-scale quadrangles that cover the Commonwealth of Massachusetts (index map). Across the State, these materials range in thickness from a few feet to more than 500 feet (ft). In some places, surficial materials are absent where bedrock is at the land surface. The geologic map database differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. The mapped distribution of surficial materials defines the areas of exposed bedrock and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits at a 1:24,000-scale level of accuracy.
Most of the surficial materials in Massachusetts are deposits of the last two continental ice sheets that covered all of New England in the latter part of the Pleistocene ice age. The glacial deposits are divided into two broad categories, glacial till and moraine deposits, and glacial stratified deposits. Widespread till deposits were laid down directly on bedrock or on semi-consolidated coastal plain strata by glacier ice. Tills in thick-till (>15 ft thick) drumlin landforms are found in all parts of the State. Areas of shallow bedrock contain thin discontinuous till deposits and numerous bedrock outcrops, and are located chiefly in rocky upland areas. Moraine deposits related to glacial ice lobes of the last ice sheet are located mostly in southeastern Massachusetts. Glacial stratified deposits are concentrated in valleys and lowland areas and were laid down by glacial meltwater in streams, lakes, and the sea in front of the retreating ice margin during the last deglaciation. Postglacial deposits, primarily flood-plain alluvium and swamp deposits, make up a lesser proportion of the unconsolidated materials.
The geodatabase included with this report contains MapUnitPolys, MapUnitOverlayPolys, and OverlayPolys, which show the distribution of geologic units that cover the entire map area and are intended for use at quadrangle scale (1:24,000). These data layers can be clipped by quadrangle or by town boundary. Unlike the units in conventional geologic maps, the digitally defined MapUnitOverlayPolys are arranged in order according to superposition. The polygons for till and bedrock are on the bottom and are overlain by the succeeding stratified deposits; these materials are shown everywhere they occur, including beneath postglacial deposits such as swamp deposits, and also beneath water bodies. The postglacial deposits are on top because these materials overlie the other, older deposits. Instructions for using the digital files are included in the README file. A series of map figures in the pamphlet illustrates the stacking of geologic units in a portion of the Mount Toby quadrangle. The BaseMaps folder contains the 1:24,000-scale topographic base map images (1944–1977 editions) used for this compilation.
This report supersedes U.S. Geological Survey Open-File Reports 2006-1260-A, -B, -C, -D, -E, -F, -G, and -I.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3402","collaboration":"Prepared in cooperation with the Commonwealth of Massachusetts, Massachusetts Geological Survey and Executive Office for Administration and Finance","usgsCitation":"Stone, J.R., Stone, B.D., DiGiacomo-Cohen, M.L., and Mabee, S.B., comps., 2018, Surficial materials of Massachusetts—A 1:24,000-scale geologic map database: U.S. Geological Survey Scientific Investigations Map 3402, 189 sheets, scale 1:24,000; index map, scale 1:250,000; 58-p. pamphlet; and geodatabase files, https://doi.org/10.3133/sim3402.","productDescription":"Pamphlet: iv, 58 p.; Index Map; Quandrangle Map Sheets; Metadata; Read Me; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066389","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":361110,"rank":9,"type":{"id":23,"text":"Spatial 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\"}}]}","contact":"Florence Bascom Geoscience Center
(Formerly Eastern Geology and Paleoclimate Science Center)
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Near Moku‘āweoweo, Mauna Loa’s summit caldera, there are three fans of explosive deposits. The fans, located to the west, northwest, and east, are strongly arcuate in map view. Along ‘Āinapō Trail, 2.8–3.5 km southeast of the caldera, there are several small kīpuka that expose a fourth explosive deposit. Although these explosive deposits have been known for some time, no study bearing on the nature of the explosive activity that formed them has been done. By analyzing cosmogenic exposure age data and the physical properties of the debris fans—lithology, size distributions, and clast dispersal—we conclude that the lithic deposits are the result of five separate phreatic events. The lithic ejecta consist of fragments of ponded lavas, pāhoehoe, gabbroic xenoliths, and “bread-crust” fragments. The exposure ages indicate that the explosive deposit on the west caldera rim was erupted 868 ± 57 yr B.P.; for the northwest fan, the age determination is 829 ± 51 yr B.P.; and on the east rim, ejecta deposits are younger, with ages of 150 ± 20 and 220 ± 20 yr B.P. Lavas underlying these deposits have exposure ages of 960–1020 yr B.P., consistent with the stratigraphy. Near ‘Āinapō Trail, the explosive deposit is much older, overlain by flows dated with a pooled mean age of 1507 ± 19 yr B.P. From the cosmogenic dating, we have three reliable and unambiguous dates. At a much earlier time, a fourth explosive eruption created the ‘Āinapō Trail deposit. We conclude there were at least five explosive episodes around the summit caldera. These deposits, along with recent work done on Kīlauea’s explosive activity, further discredit the notion that Hawaiian volcanoes are strictly effusive in nature. The evidence from the summit of Mauna Loa indicates that it, too, has erupted explosively in recent history.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Field volcanology: A tribute to the distinguished career of Don Swanson","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2018.2538(15)","usgsCitation":"Trusdell, F., Hungerford, J., Stone, J., Fifield, K., McCann, K., Wershow, H., Zaarur, S., and Dimeo Boyd, M., 2018, Explosive eruptions at the summit of Mauna Loa: Lithology, modeling, and dating, chap. of Field volcanology: A tribute to the distinguished career of Don Swanson, v. 538, p. 325-349, https://doi.org/10.1130/2018.2538(15).","productDescription":"25 p.","startPage":"325","endPage":"349","ipdsId":"IP-089763","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":395128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.6297492980957,\n 19.42013505603468\n ],\n [\n -155.55353164672852,\n 19.42013505603468\n ],\n [\n -155.55353164672852,\n 19.502842244396035\n ],\n [\n -155.6297492980957,\n 19.502842244396035\n ],\n [\n -155.6297492980957,\n 19.42013505603468\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"538","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Trusdell, Frank A. 0000-0002-0681-0528 trusdell@usgs.gov","orcid":"https://orcid.org/0000-0002-0681-0528","contributorId":754,"corporation":false,"usgs":true,"family":"Trusdell","given":"Frank A.","email":"trusdell@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":832274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hungerford, Jefferson","contributorId":243584,"corporation":false,"usgs":false,"family":"Hungerford","given":"Jefferson","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":832275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stone, John","contributorId":199224,"corporation":false,"usgs":false,"family":"Stone","given":"John","email":"","affiliations":[],"preferred":false,"id":832276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fifield, Keith","contributorId":272639,"corporation":false,"usgs":false,"family":"Fifield","given":"Keith","email":"","affiliations":[{"id":37791,"text":"Australia National University, Canberra","active":true,"usgs":false}],"preferred":false,"id":832277,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCann, Kaitlin","contributorId":272640,"corporation":false,"usgs":false,"family":"McCann","given":"Kaitlin","email":"","affiliations":[{"id":37174,"text":"Volunteer","active":true,"usgs":false}],"preferred":false,"id":832278,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wershow, Harold","contributorId":272641,"corporation":false,"usgs":false,"family":"Wershow","given":"Harold","email":"","affiliations":[{"id":56394,"text":"Everett Community College, Everett, WA","active":true,"usgs":false}],"preferred":false,"id":832279,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zaarur, Shikma","contributorId":272642,"corporation":false,"usgs":false,"family":"Zaarur","given":"Shikma","email":"","affiliations":[{"id":56395,"text":"Hebrew University Insitute of Earh Sciences, Jerusalem","active":true,"usgs":false}],"preferred":false,"id":832280,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dimeo Boyd, Melissa","contributorId":272643,"corporation":false,"usgs":false,"family":"Dimeo Boyd","given":"Melissa","email":"","affiliations":[{"id":56396,"text":"Yeh and Associates, Denver CO","active":true,"usgs":false}],"preferred":false,"id":832281,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70201868,"text":"70201868 - 2018 - Water","interactions":[],"lastModifiedDate":"2019-02-01T13:34:43","indexId":"70201868","displayToPublicDate":"2019-01-01T13:34:38","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Water","docAbstract":"Ensuring a reliable supply of clean freshwater to individuals, communities, and ecosystems, together with effective management of floods and droughts, is the foundation of human and ecological health. The water sector is also central to the economy and contributes significantly to the resilience of many other sectors, including agriculture, energy, urban environments, and industry.
Water systems face considerable risk, even without anticipated future climate changes. Limited surface water storage, as well as a limited ability to make use of long-term drought forecasts and to trade water across uses and basins, has led to a significant depletion of aquifers in many regions in the United States. Across the Nation, much of the critical water and wastewater infrastructure is nearing the end of its useful life. To date, no comprehensive assessment exists of the climate-related vulnerability of U.S. water infrastructure (including dams, levees, aqueducts, sewers, and water and wastewater distribution and treatment systems), the potential resulting damages, or the cost of reconstruction and recovery. Paleoclimate information (reconstructions of past climate derived from ice cores or tree rings) shows that over the last 500 years, North America has experienced pronounced wet/dry regime shifts that sometimes persisted for decades. Because such protracted exposures to extreme floods or droughts in different parts of the country are extraordinary compared to events experienced in the 20th century, they are not yet incorporated in water management principles and practice. Anticipated future climate change will exacerbate this risk in many regions.
A central challenge to water planning and management is learning to plan for plausible future climate conditions that are wider in range than those experienced in the 20th century. Doing so requires approaches that evaluate plans over many possible futures instead of just one, incorporate real-time monitoring and forecast products to better manage extremes when they occur, and update policies and engineering principles with the best available geoscience-based understanding of planetary change. While this represents a break from historical practice, recent examples of adaptation responses undertaken by large water management agencies, including major metropolitan water utilities and the U.S. Army Corps of Engineers, are promising.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/NCA4.2018.CH3","usgsCitation":"Lall, U., Johnson, T.M., Colohan, P., AghaKouchak, A., Brown, C., McCabe, G.J., Pulwarty, R., and Arumugam, S., 2018, Water, 29 p., https://doi.org/10.7930/NCA4.2018.CH3.","productDescription":"29 p.","startPage":"145","endPage":"173","ipdsId":"IP-103820","costCenters":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true}],"links":[{"id":360919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Reidmiller, David 0000-0001-9321-7548","orcid":"https://orcid.org/0000-0001-9321-7548","contributorId":212241,"corporation":false,"usgs":true,"family":"Reidmiller","given":"David","email":"","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":755874,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Avery, C. 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This Coastal Effects chapter of the Fourth National Climate Assessment updates those themes, with a focus on integrating the socioeconomic and environmental impacts and consequences of a changing climate. Specifically, the chapter builds on the threat of rising sea levels exacerbating tidal and storm surge flooding, the state of coastal ecosystems, and the treatment of social vulnerability by introducing the implications for social equity.
U.S. coasts are dynamic environments and economically vibrant places to live and work. As of 2013, coastal shoreline counties were home to 133.2 million people, or 42% of the population. The coasts are economic engines that support jobs in defense, fishing, transportation, and tourism industries; contribute substantially to the U.S. gross domestic product; and serve as hubs of commerce, with seaports connecting the country with global trading partners. Coasts are home to diverse ecosystems such as beaches, intertidal zones, reefs, seagrasses, salt marshes, estuaries, and deltas that support a range of important services including fisheries, recreation, and coastal storm protection. U.S. coasts span three oceans, as well as the Gulf of Mexico, the Great Lakes, and Pacific and Caribbean islands.
The social, economic, and environmental systems along the coasts are being affected by climate change. Threats from sea level rise (SLR) are exacerbated by dynamic processes such as high tide and storm surge flooding (Ch. 19: Southeast, KM 2), erosion (Ch. 26: Alaska, KM 2), waves and their effects, saltwater intrusion into coastal aquifers and elevated groundwater tables (Ch. 27: Hawaiʻi & Pacific Islands, KM 1; Ch. 3: Water, KM 1), local rainfall (Ch. 3: Water, KM 1), river runoff (Ch. 3: Water, KM 1), increasing water and surface air temperatures (Ch. 9: Oceans, KM 3), and ocean acidification (see Ch. 2: Climate, KM 3 and Ch. 9: Oceans, KM 1, 2, and 3 for more information on ocean acidification, hypoxia, and ocean warming).
Although storms, floods, and erosion have always been hazards, in combination with rising sea levels they now threaten approximately $1 trillion in national wealth held in coastal real estate and the continued viability of coastal communities that depend on coastal water, land, and other resources for economic health and cultural integrity (Ch. 15: Tribes, KM 1 and 2).
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/NCA4.2018.CH8","usgsCitation":"Fleming, E., Payne, J., Sweet, W.V., Craghan, M., Haines, J.W., Finzi Hart, J., Stiller, H., and Sutton-Grier, A., 2018, Coastal effects, 31 p., https://doi.org/10.7930/NCA4.2018.CH8.","productDescription":"31 p.","startPage":"322","endPage":"352","ipdsId":"IP-103835","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":360918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Reidmiller, David 0000-0001-9321-7548","orcid":"https://orcid.org/0000-0001-9321-7548","contributorId":212241,"corporation":false,"usgs":true,"family":"Reidmiller","given":"David","email":"","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":755867,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Avery, C. 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Alaska is often identified as being on the front lines of climate change since it is warming faster than any other state and faces a myriad of issues associated with a changing climate. The cost of infrastructure damage from a warming climate is projected to be very large, potentially ranging from $110 to $270 million per year, assuming timely repair and maintenance. Although climate change does and will continue to dramatically transform the climate and environment of the Arctic, proactive adaptation in Alaska has the potential to reduce costs associated with these impacts. This includes the dissemination of several tools, such as guidebooks to support adaptation planning, some of which focus on Indigenous communities. While many opportunities exist with a changing climate, economic prospects are not well captured in the literature at this time.
As the climate continues to warm, there is likely to be a nearly sea ice-free Arctic during the summer by mid-century. Ocean acidification is an emerging global problem that will intensify with continued carbon dioxide (CO2) emissions and negatively affects organisms. Climate change will likely affect management actions and economic drivers, including fisheries, in complex ways. The use of multiple alternative models to appropriately characterize uncertainty in future fisheries biomass trajectories and harvests could help manage these challenges. As temperature and precipitation increase across the Alaska landscape, physical and biological changes are also occurring throughout Alaska’s terrestrial ecosystems. Degradation of permafrost is expected to continue, with associated impacts to infrastructure, river and stream discharge, water quality, and fish and wildlife habitat.
Longer sea ice-free seasons, higher ground temperatures, and relative sea level rise are expected to exacerbate flooding and accelerate erosion in many regions, leading to the loss of terrestrial habitat in the future and in some cases requiring entire communities or portions of communities to relocate to safer terrain. The influence of climate change on human health in Alaska can be traced to three sources: direct exposures, indirect effects, and social or psychological disruption. Each of these will have different manifestations for Alaskans when compared to residents elsewhere in the United States. Climate change exerts indirect effects on human health in Alaska through changes to water, air, and soil and through ecosystem changes affecting disease ecology and food security, especially in rural communities.
Alaska’s rural communities are predominantly inhabited by Indigenous peoples who may be disproportionately vulnerable to socioeconomic and environmental change; however, they also have rich cultural traditions of resilience and adaptation. The impacts of climate change will likely affect all aspects of Alaska Native societies, from nutrition, infrastructure, economics, and health consequences to language, education, and the communities themselves.
The profound and diverse climate-driven changes in Alaska’s physical environment and ecosystems generate economic impacts through their effects on environmental services. These services include positive benefits directly from ecosystems (for example, food, water, and other resources), as well as services provided directly from the physical environment (for example, temperature moderation, stable ground for supporting infrastructure, and smooth surface for overland transportation). Some of these effects are relatively assured and in some cases are already occurring. Other impacts are highly uncertain, due to their dependence on the structure of global and regional economies and future human alterations to the environment decades into the future, but they could be large.
In Alaska, a range of adaptations to changing climate and related environmental conditions are underway and others have been proposed as potential actions, including measures to reduce vulnerability and risk, as well as more systemic institutional transformation.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/NCA4.2018.CH26","usgsCitation":"Markon, C., Gray, S., Berman, M., Eerkes-Medrano, L., Hennessy, T., Huntington, H.P., Littell, J., McCammon, M., Thoman, R., and Trainor, S., 2018, Alaska, 57 p., https://doi.org/10.7930/NCA4.2018.CH26.","productDescription":"57 p.","startPage":"1185","endPage":"1241","ipdsId":"IP-103840","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":360915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Reidmiller, David 0000-0001-9321-7548","orcid":"https://orcid.org/0000-0001-9321-7548","contributorId":212241,"corporation":false,"usgs":true,"family":"Reidmiller","given":"David","email":"","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":755845,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Avery, C. 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A forest, for instance, would likely include tree cover but could also include areas of recent tree removals currently covered by open grass areas. Land cover and use are inherently coupled: changes in land-use practices can change land cover, and land cover enables specific land uses. Understanding how land cover, use, condition, and management vary in space and time is challenging.
Changes in land cover can occur in response to both human and climate drivers. For example, demand for new settlements often results in the permanent loss of natural and working lands, which can result in localized changes in weather patterns, temperature, and precipitation. Aggregated over large areas, these changes have the potential to influence Earth’s climate by altering regional and global circulation patterns, changing the albedo (reflectivity) of Earth’s surface, and changing the amount of carbon dioxide (CO2) in the atmosphere. Conversely, climate change can also influence land cover, resulting in a loss of forest cover from climate-related increases in disturbances, the expansion of woody vegetation into grasslands, and the loss of beaches due to coastal erosion amplified by rises in sea level.
Land use is also changed by both human and climate drivers. Land-use decisions are traditionally based on short-term economic factors. Land-use changes are increasingly being influenced by distant forces due to the globalization of many markets. Land use can also change due to local, state, and national policies, such as programs designed to remove cultivation from highly erodible land to mitigate degradation, legislation to address sea level rise in local comprehensive plans, or policies that reduce the rate of timber harvest on federal lands. Technological innovation has also influenced land-use change, with the expansion of cultivated lands from the development of irrigation technologies and, more recently, decreases in demand for agricultural land due to increases in crop productivity. The recent expansion of oil and gas extraction activities throughout large areas of the United States demonstrates how policy, economics, and technology can collectively influence and change land use and land cover.
Decisions about land use, cover, and management can help determine society’s ability to mitigate and adapt to climate change.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/NCA4.2018.CH5","usgsCitation":"Sleeter, B.M., Loveland, T., Domke, G., Herold, N., Wickham, J., and Wood, N.J., 2018, Land cover and land use change, 30 p., https://doi.org/10.7930/NCA4.2018.CH5.","productDescription":"30 p.","startPage":"202","endPage":"231","ipdsId":"IP-103826","costCenters":[{"id":505,"text":"Office of the AD Climate and Land-Use Change","active":true,"usgs":true}],"links":[{"id":360914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Reidmiller, David 0000-0001-9321-7548","orcid":"https://orcid.org/0000-0001-9321-7548","contributorId":212241,"corporation":false,"usgs":true,"family":"Reidmiller","given":"David","email":"","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":755838,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Avery, C. 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This natural landscape provides the economic and cultural foundation for many rural communities, which are largely supported by a diverse range of agricultural, tourism, and natural resource-dependent industries (see Ch. 10: Ag & Rural, Key Message 4). The recent dominant trend in precipitation throughout the Northeast has been towards increases in rainfall intensity, with increases in intensity exceeding those in other regions of the contiguous United States. Further increases in rainfall intensity are expected, with increases in total precipitation expected during the winter and spring but with little change in the summer. Monthly precipitation in the Northeast is projected to be about 1 inch greater for December through April by end of century (2070–2100) under the higher scenario (RCP8.5).
Ocean and coastal ecosystems are being affected by large changes in a variety of climate-related environmental conditions. These ecosystems support fishing and aquaculture, tourism and recreation, and coastal communities. Observed and projected increases in temperature, acidification, storm frequency and intensity, and sea levels are of particular concern for coastal and ocean ecosystems, as well as local communities and their interconnected social and economic systems. Increasing temperatures and changing seasonality on the Northeast Continental Shelf have affected marine organisms and the ecosystem in various ways. The warming trend experienced in the Northeast Continental Shelf has been associated with many fish and invertebrate species moving northward and to greater depths. Because of the diversity of the Northeast’s coastal landscape, the impacts from storms and sea level rise will vary at different locations along the coast.
Northeastern cities, with their abundance of concrete and asphalt and relative lack of vegetation, tend to have higher temperatures than surrounding regions due to the urban heat island effect. During extreme heat events, nighttime temperatures in the region’s big cities are generally several degrees higher than surrounding regions, leading to higher risk of heat-related death. Urban areas are at risk for large numbers of evacuated and displaced populations and damaged infrastructure due to both extreme precipitation events and recurrent flooding, potentially requiring significant emergency response efforts and consideration of a long-term commitment to rebuilding and adaptation, and/or support for relocation where needed. Much of the infrastructure in the Northeast, including drainage and sewer systems, flood and storm protection assets, transportation systems, and power supply, is nearing the end of its planned life expectancy. Climate-related disruptions will only exacerbate existing issues with aging infrastructure. Sea level rise has amplified storm impacts in the Northeast (Key Message 2), contributing to higher surges that extend farther inland, as demonstrated in New York City in the aftermath of Superstorm Sandy in 2012. Service and resource supply infrastructure in the Northeast is at increasing risk of disruption, resulting in lower quality of life, economic declines, and increased social inequality. Loss of public services affects the capacity of communities to function as administrative and economic centers and triggers disruptions of interconnected supply chains (Ch. 16: International, Key Message 1).
Increases in annual average temperatures across the Northeast range from less than 1°F (0.6°C) in West Virginia to about 3°F (1.7°C) or more in New England since 1901. Although the relative risk of death on very hot days is lower today than it was a few decades ago, heat-related illness and death remain significant public health problems in the Northeast. For example, a study in New York City estimated that in 2013 there were 133 excess deaths due to extreme heat. These projected increases in temperature are expected to lead to substantially more premature deaths, hospital admissions, and emergency department visits across the Northeast. For example, in the Northeast we can expect approximately 650 additional premature deaths per year from extreme heat by the year 2050 under either a lower (RCP4.5) or higher (RCP8.5) scenario and from 960 (under RCP4.5) to 2,300 (under RCP8.5) more premature deaths per year by 2090.
Communities, towns, cities, counties, states, and tribes across the Northeast are engaged in efforts to build resilience to environmental challenges and adapt to a changing climate. Developing and implementing climate adaptation strategies in daily practice often occur in collaboration with state and federal agencies (e.g., New Jersey Climate Adaptation Alliance 2017, New York Climate Clearinghouse 2017, Rhode Island STORMTOOLS 2017, EPA 2017, CDC 2015). Advances in rural towns, cities, and suburban areas include low-cost adjustments of existing building codes and standards. In coastal areas, partnerships among local communities and federal and state agencies leverage federal adaptation tools and decision support frameworks (for example, NOAA’s Digital Coast, USGS’s Coastal Change Hazards Portal, and New Jersey’s Getting to Resilience). Increasingly, cities and towns across the Northeast are developing or implementing plans for adaptation and resilience in the face of changing climate (e.g., EPA 2017). The approaches are designed to maintain and enhance the everyday lives of residents and promote economic development. In some cities, adaptation planning has been used to respond to present and future challenges in the built environment. Regional efforts have recommended changes in design standards when building, replacing, or retrofitting infrastructure to account for a changing climate.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/NCA4.2018.CH18","usgsCitation":"Dupigny-Giroux, L.L., Mecray, E.L., Lemcke-Stampone, M.D., Hodgkins, G.A., Lentz, E.E., Mills, K.E., Lane, E.D., Miller, R., Hollinger, D.Y., Solecki, W.D., Wellenius, G.A., Sheffield, P.E., McDonald, A.B., and Caldwell, C., 2018, Northeast, 74 p., https://doi.org/10.7930/NCA4.2018.CH18.","productDescription":"74 p.","startPage":"669","endPage":"742","ipdsId":"IP-103836","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":468162,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7930/nca4.2018.ch18","text":"Publisher Index Page"},{"id":360913,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Reidmiller, David 0000-0001-9321-7548","orcid":"https://orcid.org/0000-0001-9321-7548","contributorId":212241,"corporation":false,"usgs":true,"family":"Reidmiller","given":"David","email":"","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":755831,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Avery, C. 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0000-0001-9156-1193","orcid":"https://orcid.org/0000-0001-9156-1193","contributorId":212167,"corporation":false,"usgs":false,"family":"Sheffield","given":"Perry","email":"","middleInitial":"E.","affiliations":[{"id":38444,"text":"Icahn School of Medicine at Mount Sinai","active":true,"usgs":false}],"preferred":false,"id":755662,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"McDonald, Anthony B.","contributorId":212168,"corporation":false,"usgs":false,"family":"McDonald","given":"Anthony","email":"","middleInitial":"B.","affiliations":[{"id":38445,"text":"Monmouth University","active":true,"usgs":false}],"preferred":false,"id":755663,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Caldwell, Christopher","contributorId":212169,"corporation":false,"usgs":false,"family":"Caldwell","given":"Christopher","email":"","affiliations":[{"id":38446,"text":"College of Menominee Nations","active":true,"usgs":false}],"preferred":false,"id":755664,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70201873,"text":"70201873 - 2018 - Hawai‘i and U.S.-Affiliated Pacific Islands","interactions":[],"lastModifiedDate":"2019-02-01T11:53:35","indexId":"70201873","displayToPublicDate":"2019-01-01T11:53:29","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Hawai‘i and U.S.-Affiliated Pacific Islands","docAbstract":"The U.S. Pacific Islands are culturally and environmentally diverse, treasured by the 1.9 million people who call them home. Pacific islands are particularly vulnerable to climate change impacts due to their exposure and isolation, small size, low elevation (in the case of atolls), and concentration of infrastructure and economy along the coasts.
A prevalent cause of year-to-year changes in climate patterns around the globe and in the Pacific Islands region is the El Niño–Southern Oscillation (ENSO). The El Niño and La Niña phases of ENSO can dramatically affect precipitation, air and ocean temperature, sea surface height, storminess, wave size, and trade winds. It is unknown exactly how the timing and intensity of ENSO will continue to change in the coming decades, but recent climate model results suggest a doubling in frequency of both El Niño and La Niña extremes in this century as compared to the 20th century under scenarios with more warming, including the higher scenario (RCP8.5).
On islands, all natural sources of freshwater come from rainfall received within their limited land areas. Severe droughts are common, making water shortage one of the most important climate-related risks in the region. As temperature continues to rise and cloud cover decreases in some areas, evaporation is expected to increase, causing both reduced water supply and higher water demand. Streamflow in Hawai‘i has declined over approximately the past 100 years, consistent with observed decreases in rainfall.
The impacts of sea level rise in the Pacific include coastal erosion, episodic flooding, permanent inundation, heightened exposure to marine hazards, and saltwater intrusion to surface water and groundwater systems. Sea level rise will disproportionately affect the tropical Pacific and potentially exceed the global average.
Invasive species, landscape change, habitat alteration, and reduced resilience have resulted in extinctions and diminished ecosystem function. Inundation of atolls in the coming decades is projected to impact existing on-island ecosystems. Wildlife that relies on coastal habitats will likely also be severely impacted. In Hawaiʻi, coral reefs contribute an estimated $477 million to the local economy every year. Under projected warming of approximately 0.5°F per decade, all nearshore coral reefs in the Hawai‘i and Pacific Islands region will experience annual bleaching before 2050. An ecosystem-based approach to international management of open ocean fisheries in the Pacific that incorporates climate-informed catch limits is expected to produce more realistic future harvest levels and enhance ecosystem resilience.
Indigenous communities of the Pacific derive their sense of identity from the islands. Emerging issues for Indigenous communities of the Pacific include the resilience of marine-managed areas and climate-induced human migration from their traditional lands. The rich body of traditional knowledge is place-based and localized and is useful in adaptation planning because it builds on intergenerational sharing of observations. Documenting the kinds of governance structures or decision-making hierarchies created for management of these lands and waters is also important as a learning tool that can be shared with other island communities.
Across the region, groups are coming together to minimize damage and disruption from coastal flooding and inundation as well as other climate-related impacts. Social cohesion is already strong in many communities, making it possible to work together to take action. Early intervention can lower economic, environmental, social, and cultural costs and reduce or prevent conflict and displacement from ancestral land and resources.
Biodiversity—the variety of life on Earth—provides vital services that support and improve human health and well-being. Ecosystems, which are composed of living things that interact with the physical environment, provide numerous essential benefits to people. These benefits, termed ecosystem services, encompass four primary functions: provisioning materials, such as food and fiber; regulating critical parts of the environment, such as water quality and erosion control; providing cultural services, such as recreational opportunities and aesthetic value; and providing supporting services, such as nutrient cycling. Climate change poses many threats and potential disruptions to ecosystems and biodiversity, as well as to the ecosystem services on which people depend.
Building on the findings of the Third National Climate Assessment (NCA3), this chapter provides additional evidence that climate change is significantly impacting ecosystems and biodiversity in the United States. Mounting evidence also demonstrates that climate change is increasingly compromising the ecosystem services that sustain human communities, economies, and well-being. Both human and natural systems respond to change, but their ability to respond and thrive under new conditions is determined by their adaptive capacity, which may be inadequate to keep pace with rapid change. Our understanding of climate change impacts and the responses of biodiversity and ecosystems has improved since NCA3. The expected consequences of climate change will vary by region, species, and ecosystem type. Management responses are evolving as new tools and approaches are developed and implemented; however, they may not be able to overcome the negative impacts of climate change. Although efforts have been made since NCA3 to incorporate climate adaptation strategies into natural resource management, significant work remains to comprehensively implement climate-informed planning. This chapter presents additional evidence for climate change impacts to biodiversity, ecosystems, and ecosystem services, reflecting increased confidence in the findings reported in NCA3. The chapter also illustrates the complex and interrelated nature of climate change impacts to biodiversity, ecosystems, and the services they provide.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/NCA4.2018.CH7","usgsCitation":"Lipton, D., Rubenstein, M.A., Weiskopf, S.R., Carter, S.L., Peterson, J., Crozier, L., Fogarty, M., Gaichas, S., Hyde, K., Morelli, T.L., Morisette, J., Moustahfid, H., Munoz, R., Poudel, R., Staudinger, M., Stock, C., Thompson, L., Waples, R.S., and Weltzin, J., 2018, Ecosystems, Ecosystem Services, and Biodiversity, 54 p., https://doi.org/10.7930/NCA4.2018.CH7.","productDescription":"54 p.","startPage":"268","endPage":"321","ipdsId":"IP-103827","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":360911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Reidmiller, David 0000-0001-9321-7548","orcid":"https://orcid.org/0000-0001-9321-7548","contributorId":212241,"corporation":false,"usgs":true,"family":"Reidmiller","given":"David","email":"","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":755817,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Avery, C. 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These beaches and bayous, fields and forests, and cities and small towns are all at risk from a changing climate. While some climate change impacts, such as sea level rise and extreme downpours, are being acutely felt now, others, like increasing exposure to dangerous high temperatures, humidity, and new local diseases, are expected to become more significant in the coming decades. While all regional residents and communities are potentially at risk for some impacts, some communities or populations are at greater risk due to their locations, services available to them, and economic situations.
Observed warming since the mid-20th century has been uneven in the Southeast region, with average daily minimum temperatures increasing three times faster than average daily maximum temperatures. The number of extreme rainfall events is increasing. Climate model simulations of future conditions project increases in both temperature and extreme precipitation.
Trends towards a more urbanized and denser Southeast are expected to continue, creating new climate vulnerabilities. Cities across the Southeast are experiencing more and longer summer heat waves. Vector-borne diseases pose a greater risk in cities than in rural areas because of higher population densities and other human factors, and the major urban centers in the Southeast are already impacted by poor air quality during warmer months. Increasing precipitation and extreme weather events will likely impact roads, freight rail, and passenger rail, which will likely have cascading effects across the region. Infrastructure related to drinking water and wastewater treatment also has the potential to be compromised by climate-related events. Increases in extreme rainfall events and high tide coastal floods due to future climate change will impact the quality of life of permanent residents as well as tourists visiting the low-lying and coastal regions of the Southeast. Sea level rise is contributing to increased coastal flooding in the Southeast, and high tide flooding already poses daily risks to businesses, neighborhoods, infrastructure, transportation, and ecosystems in the region. There have been numerous instances of intense rainfall events that have had devastating impacts on inland communities in recent years.
The ecological resources that people depend on for livelihoods, protection, and well-being are increasingly at risk from the impacts of climate change. Sea level rise will result in the rapid conversion of coastal, terrestrial, and freshwater ecosystems to tidal saline habitats. Reductions in the frequency and intensity of cold winter temperature extremes are already allowing tropical and subtropical species to move northward and replace more temperate species. Warmer winter temperatures are also expected to facilitate the northward movement of problematic invasive species, which could transform natural systems north of their current distribution. In the future, rising temperatures and increases in the duration and intensity of drought are expected to increase wildfire occurrence and also reduce the effectiveness of prescribed fire practices.
Many in rural communities are maintaining connections to traditional livelihoods and relying on natural resources that are inherently vulnerable to climate changes. Climate trends and possible climate futures show patterns that are already impacting—and are projected to further impact—rural sectors, from agriculture and forestry to human health and labor productivity. Future temperature increases are projected to pose challenges to human health. Increases in temperatures, water stress, freeze-free days, drought, and wildfire risks, together with changing conditions for invasive species and the movement of diseases, create a number of potential risks for existing agricultural systems. Rural communities tend to be more vulnerable to these changes due to factors such as demography, occupations, earnings, literacy, and poverty incidence. In fact, a recent economic study using a higher scenario (RCP8.5) suggests that the southern and midwestern populations are likely to suffer the largest losses from future climate changes in the United States. Climate change tends to compound existing vulnerabilities and exacerbate existing inequities. Already poor regions, including those found in the Southeast, are expected to continue incurring greater losses than elsewhere in the United States.
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However, the Caribbean climate is changing and is projected to be increasingly variable as levels of greenhouse gases in the atmosphere increase.
The high percentage of coastal area relative to the total island land area in the U.S. Caribbean means that a large proportion of the region’s people, infrastructure, and economic activity are vulnerable to sea level rise, more frequent intense rainfall events and associated coastal flooding, and saltwater intrusion. High levels of exposure and sensitivity to risk in the U.S. Caribbean region are compounded by a low level of adaptive capacity, due in part to the high costs of mitigation and adaptation measures relative to the region’s gross domestic product, particularly when compared to continental U.S. coastal areas. The limited geographic and economic scale of Caribbean islands means that disruptions from extreme climate-related events, such as droughts and hurricanes, can devastate large portions of local economies and cause widespread damage to crops, water supplies, infrastructure, and other critical resources and services.
The U.S. Caribbean territories of Puerto Rico and the U.S. Virgin Islands (USVI) have distinct differences in topography, language, population size, governance, natural and human resources, and economic capacity. However, both are highly dependent on natural and built coastal assets; service-related industries account for more than 60% of the USVI economy. Beaches, affected by sea level rise and erosion, are among the main tourist attractions. In Puerto Rico, critical infrastructure (for example, drinking water pipelines and pump stations, sanitary pipelines and pump stations, wastewater treatment plants, and power plants) is vulnerable to the effects of sea level rise, storm surge, and flooding. In the USVI, infrastructure and historical buildings in the inundation zone for sea level rise include the power plants on both St. Thomas and St. Croix; schools; housing communities; the towns of Charlotte Amalie, Christiansted, and Frederiksted; and pipelines for water and sewage.
Climate change will likely result in water shortages due to an overall decrease in annual rainfall, a reduction in ecosystem services, and increased risks for agriculture, human health, wildlife, and socioeconomic development in the U.S. Caribbean. These shortages would result from some locations within the Caribbean experiencing longer dry seasons and shorter, but wetter, wet seasons in the future. Extended dry seasons are projected to increase fire likelihood. Excessive rainfall, coupled with poor construction practices, unpaved roads, and steep slopes, can exacerbate erosion rates and have adverse effects on reservoir capacity, water quality, and nearshore marine habitats.
Ocean warming poses a significant threat to the survival of corals and will likely also cause shifts in associated habitats that compose the coral reef ecosystem. Severe, repeated, or prolonged periods of high temperatures leading to extended coral bleaching can result in colony death. Ocean acidification also is likely to diminish the structural integrity of coral habitats. Studies show that major shifts in fisheries distribution and changes to the structure and composition of marine habitats adversely affect food security, shoreline protection, and economies throughout the Caribbean.
In Puerto Rico, the annual number of days with temperatures above 90°F has increased over the last four and a half decades. During that period, stroke and cardiovascular disease, which are influenced by such elevated temperatures, became the primary causes of death. Increases in average temperature and in extreme heat events will likely have detrimental effects on agricultural operations throughout the U.S. Caribbean region. Many farmers in the tropics, including the U.S. Caribbean, are considered small-holding, limited resource farmers and often lack the resources and/or capital to adapt to changing conditions.
Most Caribbean countries and territories share the need to assess risks, enable actions across scales, and assess changes in ecosystemsto inform decision-making on habitat protection under a changing climate. U.S. Caribbean islands have the potential to improve adaptation and mitigation actions by fostering stronger collaborations with Caribbean initiatives on climate change and disaster risk reduction.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/NCA4.2018.CH20","usgsCitation":"Gould, W.A., Diaz, E.L., Alvarez-Berrios, N.L., Aponte-Gonzalez, F., Archibald, W., Bowden, J.H., Carrubba, L., Crespo, W., Fain, S.J., Gonzalez, G., Goulbourne, A., Harmsen, E., Holupchinski, E., Khalyani, A.H., Kossin, J.P., Leinberger, A.J., Marrero-Santiago, V.I., Martinez-Sanchez, O., McGinley, K., Mendez-Lazaro, P., Morrell, J., Melendez Oyola, M., Pares-Ramos, I.K., Pulwarty, R., Sweet, W.V., Terando, A.J., and Torres-González, S., 2018, U.S. Caribbean, 63 p., https://doi.org/10.7930/NCA4.2018.CH20.","productDescription":"63 p.","startPage":"809","endPage":"871","ipdsId":"IP-103838","costCenters":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"links":[{"id":468165,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7930/nca4.2018.ch20","text":"Publisher Index Page"},{"id":360909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Reidmiller, David 0000-0001-9321-7548","orcid":"https://orcid.org/0000-0001-9321-7548","contributorId":212241,"corporation":false,"usgs":true,"family":"Reidmiller","given":"David","email":"","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":755803,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Avery, C. 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Overall, climate projections suggest that the number of heavy precipitation events (events with greater than 1 inch per day of rainfall) is projected to increase. Moving forward, the magnitude of year-to-year variability overshadows the small projected average decrease in streamflow. Changes in extreme events are likely to overwhelm average changes in both the eastern and western regions of the Northern Great Plains. Major flooding across the basin in 2011 was followed by severe drought in 2012, representing new and unprecedented variability that is likely to become more common in a warmer world.
The Northern Great Plains region plays a critical role in national food security. Among other anticipated changes, projected warmer and generally wetter conditions with elevated atmospheric carbon dioxide concentrations are expected to increase the abundance and competitive ability of weeds and invasive species, increase livestock production and efficiency of production, and result in longer growing seasons at mid- and high latitudes. Net primary productivity, including crop yields and forage production, is also likely to increase, although an increasing number of extreme temperature events during critical pollination and grain fill periods is likely to reduce crop yields.
Ecosystems across the Northern Great Plains provide recreational opportunities and other valuable goods and services that are ingrained in the region’s cultures. Higher temperatures, reduced snow cover, and more variable precipitation will make it increasingly challenging to manage the region’s valuable wetlands, rivers, and snow-dependent ecosystems. In the mountains of western Wyoming and western Montana, the fraction of total water in precipitation that falls as snow is expected to decline by 25% to 40% by 2100 under a higher scenario (RCP8.5), which would negatively affect the region’s winter recreation industry. At lower-elevation areas of the Northern Great Plains, climate-induced land-use changes in agriculture can have cascading effects on closely entwined natural ecosystems, such as wetlands, and the diverse species and recreational opportunities they support.
Energy resources in the Northern Great Plains include abundant crude oil, natural gas, coal, wind, and stored water, and to a lesser extent, corn-based ethanol, solar energy, and uranium. The infrastructure associated with the extraction, distribution, and energy produced from these resources is vulnerable to the impacts of climate change. Railroads and pipelines are vulnerable to damage or disruption from increasing heavy precipitation events and associated flooding and erosion. Declining water availability in the summer would likely increase costs for oil production operations, which require freshwater resources. These cost increases will either lead to lower production or be passed on to consumers. Finally, higher maximum temperatures, longer and more severe heat waves, and higher overnight lows are expected to increase electricity demand for cooling in the summer, further stressing the power grid.
Indigenous peoples in the region are observing changes to climate, many of which are impacting livelihoods as well as traditional subsistence and wild foods, wildlife, plants and water for ceremonies, medicines, and health and well-being. Because some tribes and Indigenous peoples are among those in the region with the highest rates of poverty and unemployment, and because many are still directly reliant on natural resources, they are among the most at risk to climate change (e.g., Gamble et al. 2016, Cozzetto et al. 2013, Espey et al. 2014, Wong et al. 2014, Kornfeld 2016, Paul and Caplins 2016, Maynard 2014, USGCRP 2017)
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2018 - Shrimp U-Pb zircon and opal geochronology, isotope geochemistry, and genesis of the super large Be deposit at Spor Mountain, Utah, USA","interactions":[],"lastModifiedDate":"2019-12-04T18:50:48","indexId":"70202804","displayToPublicDate":"2018-12-31T18:49:43","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Shrimp U-Pb zircon and opal geochronology, isotope geochemistry, and genesis of the super large Be deposit at Spor Mountain, Utah, USA","docAbstract":"Ongoing studies of the Spor Mountain beryllium (Be) deposit are focused on (1) characterizing the role of igneous rocks in the genesis of the ore zones, (2) determining the timing and duration of magmatic-hydrothermal events, and (3) establishing processes related to beryllium transport and accumulation. The Spor Mountain Formation (SMF) hosts the deposit, which is the largest known volcanic rock-related Be deposit in the world. Discovery of the Be deposit at Spor Mountain in the 1960s displaced beryl as the main commercial source of beryllium in the global supply chain. Technological advances in mineral processing enabled bertrandite (Be4Si2O7(OH)2) ore of variable grade and composition from Spor Mountain to compete with beryl ore derived from pegmatite. The deposit currently accounts for approximately 85% of the global beryllium mine production.\nThe Be deposit is in the Basin and Range province of North America, which is characterized by Oligocene and Eocene calderas, extensive alkalic rhyolitic lava and ash flow tuffs, widespread uranium and fluorite occurrences, and Precambrian to Paleozoic sedimentary rocks. The SMF consists of a hydrothermally-altered, fluorite-bearing, lithic-rich (clasts of carbonate, quartzite, and older volcanic rocks) pyroclastic tuff (informal name: Be tuff member) that is overlain by altered, porphyritic, and topaz-rich rhyolite (alkali rhyolite member). The tuff encloses elongate mineralized layers containing numerous nodules that consist of calcite, chalcedony, opal, fluorite, and bertrandite (Be4Si2O7(OH)2, the main ore mineral.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Magmatism of the Earth and related Strategic Metal Deposits","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"International Conference on Magmatism of the Earth and Related Strategic Metal Deposits","conferenceDate":"September 3-7, 2018","conferenceLocation":"Moscow, Russia","language":"English","usgsCitation":"Foley, N.K., and Ayuso, R.A., 2018, Shrimp U-Pb zircon and opal geochronology, isotope geochemistry, and genesis of the super large Be deposit at Spor Mountain, Utah, USA, in Magmatism of the Earth and related Strategic Metal Deposits, Moscow, Russia, September 3-7, 2018, p. 90-94.","productDescription":"5 p.","startPage":"90","endPage":"94","ipdsId":"IP-096788","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":369941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":369940,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://magmas-and-metals.ru"}],"country":"United States","state":"Utah","otherGeospatial":"Spor Mountain Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.22200775146483,\n 39.69463958513244\n ],\n [\n -113.14922332763672,\n 39.69463958513244\n ],\n [\n -113.14922332763672,\n 39.76738084178371\n ],\n [\n -113.22200775146483,\n 39.76738084178371\n ],\n [\n -113.22200775146483,\n 39.69463958513244\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Foley, Nora K. 0000-0003-0124-3509 nfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-0124-3509","contributorId":4010,"corporation":false,"usgs":true,"family":"Foley","given":"Nora","email":"nfoley@usgs.gov","middleInitial":"K.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":760095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":760096,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70197879,"text":"70197879 - 2018 - Preliminary 2018 national seismic hazard model for the conterminous United States","interactions":[],"lastModifiedDate":"2019-06-27T16:19:28","indexId":"70197879","displayToPublicDate":"2018-12-31T15:51:06","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Preliminary 2018 national seismic hazard model for the conterminous United States","docAbstract":"The 2014 U.S. Geological Survey national seismic hazard model for the conterminous U.S. will be updated in 2018 and 2020 to coincide with the Building Seismic Safety Council’s Project 17 timeline for development of new building code design criteria. The two closely timed updates are planned to allow more time for the Provisions Update Committee to analyze the consequences of the hazard model changes in the design criteria. To prepare the 2018 update we held a workshop (March 7-8, 2018) with scientists and engineers to solicit feedback on the model. The 2018 model will be available for public comment during the summer of 2018. The purpose of this paper is to solicit feedback on the modeling choices and results. The 2018 NSHM considers an updated seismicity catalog and certain key changes in the way ground motions are calculated. First, we implemented new Next Generation Attenuation Relationships for the Central and Eastern North America Region and other published models that allow for the calculation of ground motions at additional periods and site classes in the central and eastern U.S. (CEUS). Second, basin depth terms were implemented in the ground motion models in select regions of the western U.S. (WUS) to account for enhanced long-period ground motions at softer soil sites overlying sedimentary basins. Preliminary results indicate higher ground motions for all periods in parts of the CEUS and for long-periods and soft soils in urban areas overlying sedimentary basins in the WUS.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Earthquake Engineering. National Conference. 11TH 2018. 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groundwater flow, particularly in tectonically and topographically complex mountainous terrain, can be difficult to quantify without a detailed understanding of the regional subsurface geologic structure. This structure can influence the magnitude of groundwater flow through the mountain block, which in turn impacts groundwater composition and the flux of metals and nutrients to the near-surface ecosystem. In support of several ongoing studies in the upper East River and surrounding watersheds in central Colorado, regional-scale airborne electromagnetic, magnetic, and radiometric surveyswereconductedin late 2017. These data give a view of the geologic structure underlying the region that is unprecedented in both resolution and spatial coverage.
","conferenceTitle":"7th International Workshop on Airborne Electromagnetics","conferenceDate":"June 17-20, 2018","conferenceLocation":"Kolding, Denmark","language":"English","publisher":"Aarhus University","usgsCitation":"Minsley, B.J., and Ball, L.B., 2018, Airborne geophysical characterizationof geologic structure in a mountain headwater system, upper East River, Colorado, 7th International Workshop on Airborne Electromagnetics, Kolding, Denmark, June 17-20, 2018, 2 p.","productDescription":"2 p.","ipdsId":"IP-095926","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":383156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383155,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.conferencemanager.dk/aem2018"}],"country":"United States","state":"Colorado","otherGeospatial":"East River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.94641113281249,\n 38.930837791482\n ],\n [\n -106.99275970458983,\n 38.981563413747686\n ],\n [\n -107.03361511230469,\n 39.012514887438684\n ],\n [\n -107.04597473144531,\n 39.0055786653419\n ],\n [\n -107.01335906982422,\n 38.97222194853654\n ],\n [\n -106.99413299560547,\n 38.93991767539353\n ],\n [\n -106.97181701660156,\n 38.925763232374514\n ],\n [\n -106.9632339477539,\n 38.912674536257356\n ],\n [\n -106.94641113281249,\n 38.930837791482\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":809256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":809257,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211536,"text":"70211536 - 2018 - Crisis remote sensing during the 2018 lower East Rift Zone eruption of Kīlauea Volcano","interactions":[],"lastModifiedDate":"2020-07-30T15:35:05.351897","indexId":"70211536","displayToPublicDate":"2018-12-30T10:32:03","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5987,"text":"Photogrammetric Engineering & Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Crisis remote sensing during the 2018 lower East Rift Zone eruption of Kīlauea Volcano","docAbstract":"Kīlauea Volcano, Hawai‘i, is renowned as one of the most active and closely monitored volcanoes on Earth. Scores of seismometers and deformation sensors form an array across the volcano to detect subsurface magmatic activity, and ground observers track eruptions on the surface. In addition to this dense ground-based monitoring, remote sensing – both airborne and spaceborne – has become a backbone tool at the U.S. Geological Survey’s (USGS) Hawaiian Volcano Observatory (HVO) for mapping activity and forecasting volcanic hazards. Remote observations were critical components of HVO’s response to the historically unprecedented 2018 eruption from Kīlauea’s lower East Rift Zone (ERZ); here we describe some of the many types of remote sensing tools that were utilized, and the specific monitoring roles they filled.","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing (ASPRS)","doi":"10.14358/PERS.84.12.749","usgsCitation":"Zoeller, M., Patrick, M.R., and Neal, C.A., 2018, Crisis remote sensing during the 2018 lower East Rift Zone eruption of Kīlauea Volcano: Photogrammetric Engineering & Remote Sensing, v. 84, no. 12, p. 749-751, https://doi.org/10.14358/PERS.84.12.749.","productDescription":"3 p.","startPage":"749","endPage":"751","ipdsId":"IP-101942","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468170,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.84.12.749","text":"Publisher Index Page"},{"id":376898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea volcano, Lower East Rift Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.42358398437497,\n 19.141276144722184\n ],\n [\n -155.1214599609375,\n 19.21391262405755\n ],\n [\n -155.0006103515625,\n 19.298182590865377\n ],\n [\n -154.99099731445312,\n 19.46141299683288\n ],\n [\n -155.42358398437497,\n 19.454938719968585\n ],\n [\n -155.42358398437497,\n 19.141276144722184\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zoeller, Michael H. 0000-0003-4716-8567","orcid":"https://orcid.org/0000-0003-4716-8567","contributorId":195428,"corporation":false,"usgs":false,"family":"Zoeller","given":"Michael H.","affiliations":[],"preferred":false,"id":794563,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":794564,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neal, Christina A. 0000-0002-7697-7825 tneal@usgs.gov","orcid":"https://orcid.org/0000-0002-7697-7825","contributorId":131135,"corporation":false,"usgs":true,"family":"Neal","given":"Christina","email":"tneal@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":794565,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}