Much of the native prairie managed by the U.S. Fish and Wildlife Service (FWS) in the Prairie Pothole Region (PPR) of the northern Great Plains is extensively invaded by the introduced cool-season grasses, smooth brome (Bromus inermis) and Kentucky bluegrass (Poa pratensis). Management to suppress these invasive plants has had poor to inconsistent success. The central challenge to managers is selecting appropriate management actions in the face of biological and environmental uncertainties. In partnership with the FWS, the U.S. Geological Survey (USGS) developed an adaptive decision support framework to assist managers in selecting management actions under uncertainty and maximizing learning from management outcomes. This joint partnership is known as the Native Prairie Adaptive Management (NPAM) initiative. The NPAM decision framework is built around practical constraints faced by FWS refuge managers and includes identification of the management objective and strategies, analysis of uncertainty and construction of competing decision models, monitoring, and mechanisms for model feedback and decision selection. Nineteen FWS field stations, spanning four states of the PPR, have participated in the initiative. These FWS cooperators share a common management objective, available management strategies, and biological uncertainties. Though the scope is broad, the initiative interfaces with individual land managers who provide site-specific information and receive updated decision guidance that incorporates understanding gained from the collective experience of all cooperators. We describe the technical components of this approach, how the components integrate and inform each other, how data feedback from individual cooperators serves to reduce uncertainty across the whole region, and how a successful adaptive management project is coordinated and maintained on a large scale.
\nDuring an initial scoping workshop, FWS cooperators developed a consensus management objective: increase the composition of native grasses and forbs on native sod while minimizing cost. Cooperators agreed that decision guidance should be provided annually and should account for local, real-time vegetation conditions observed on the ground. Over the course of development, two prototypes of the decision framework were considered. The final framework recognized four alternative actions that managers could take in any given year: (1) Graze—targeted use of grazing ungulates to achieve defoliation, (2) Burn—application of prescribed fire as the single form of defoliation, (3) Burn/Graze—a combination treatment, and (4) Rest—no action. The study area included northern mixed-grass and tallgrass prairie. Native vegetation in mixed–grass prairie has a strong cool-season component and thus the dominant native species have a phenology similar to that of smooth brome and Kentucky bluegrass, making management of those species challenging. In contrast, tallgrass prairie has a strong warm-season native component, leading to an existence of cool-season windows, periods of time in the fall and spring when cool‐season invasive grass species are actively growing and vulnerable to damage via select management actions, but warm‐season grass species are not active and are thus less susceptible to damage via the same actions. This dichotomy between prairie types necessitated the development of separate but parallel decision support systems for mixed-grass and tallgrass biomes.
\nManagement units are parcels of native prairie that receive a single management treatment at any one time over their entire extent. At any particular time, the vegetation state of each management unit is characterized by the amount of cover of native grasses and forbs and the type of invasive grass that is dominant. In addition, each unit has a defoliation state which reflects the number of years since the last defoliation event and an index to how intensively the unit was managed during the previous 7 years. State-transition models are used to predict the state of a management unit in year t+1 from its state in year t and a prescribed management action that was applied between the two monitoring events. Alternative models are built around key uncertainties that make choice of a management action difficult. Three uncertainties revolve around whether the effect of management actions depends on (1) type of dominant invader, (2) past defoliation history, and (3) level of invasion. Two additional uncertainties are considered when choosing a management action for tallgrass units: (4) the effectiveness of grazing within the cool-season window as a surrogate for burning when smooth brome is the dominant invader, and (5) the differential effect of active management outside the window as compared to rest.
\nBecause data on the probability of transitioning from one state to another under the various models were lacking, expert opinion and elicitation were used to parameterize the models. In addition, cooperators participated in elicitation exercises to extract their beliefs regarding the value of having native prairie compared to the cost of achieving it. Quantifying the subjective expression of utility in this way allowed for mathematical representation of the management objective into an objective function. By maximizing the objective function, cumulative utility is maximized, leading to the identification of a sequence of decisions that will achieve the management objective.
\nThe NPAM system adopted a vegetation monitoring protocol that was rapid, inexpensive, and familiar to many of the cooperators. The monitoring protocol served three purposes: (1) determining current vegetation and defoliation states of each unit, (2) evaluating progress toward the management objective, and (3) assessing predictive performance of the alternative models. The management year runs from September 1 to August 31. Management can be applied anytime during that period and monitoring takes places from late June to mid-August. Cooperators enter vegetation data and management information into a centralized database by August 25 of each year. Given the current state of the system (vegetation and defoliation states) and the current understanding of the system (or the belief state), identifying the current best management decision is a matter of looking up the combination (that is, system state and belief state) in the appropriate (mixed-grass or tallgrass) optimal decision table. Given complete uncertainty at the outset of decision-making, initial assignment of equal belief weights to each model was believed reasonable. The decisions in the optimal decision table that correspond to the current belief state constitute the current optimal decision policy. By August 31 of each year, individual cooperators are provided with a recommended management action for each of their management units for the upcoming management year. Upon receiving the management recommendations for their units, managers consider the recommendation, along with other relevant information, and at some point during the year one of the management alternatives is carried out. This iterative cycle of making and implementing a management decision, predicting the response, monitoring the outcome, comparing predicted and observed outcomes, updating model weights, and recommending a management action for the next cycle is expected to result in an accumulation of weight on a representative model of system dynamics, thereby increasing understanding needed to effectively manage native prairies.
\nThe NPAM system is now entering its second full year of complete operation, and represents one of only a few fully implemented applications of adaptive management within the U.S. Fish and Wildlife Service. NPAM is truly unique in that it originated from the ground up as a result of the leadership and steadfastness of several refuge biologists and managers confronted with a common problem. These biologists recognized that working together across a large landscape presented perhaps the best opportunity for halting and reversing the invasion of native grasslands by non-native cool-season grasses. Importantly, the NPAM system encapsulates the collective thinking and experience of tens if not hundreds of individuals who have battled this vexing problem for much of their careers.
\nThe NPAM initiative is rooted in principles of adaptive management, thereby affording the opportunity for grassland managers to pursue management objectives while acquiring information to reduce uncertainty and improve future management. The project introduced a number of technical innovations that will serve as templates for conservation efforts throughout and beyond the U.S. Fish and Wildlife Service. First, NPAM is an on-the-ground implementation of active adaptive management—possibly the first of its kind in conservation management—in which recommended management actions result from a prospective analysis of future learning (Williams, 1996). Second, by the use of dynamic optimization, NPAM demonstrates how decisions can be made that take into account possible future transitions of the system. Third, NPAM demonstrates how models of partial controllability are an effective means of accommodating unpredictable circumstances that cause a manager to follow a different course than was intended. Finally, the database developed for NPAM is an unparalleled system that enables the rapid integration of data from the field for the generation of ‘just-in-time’ management recommendations. In all, NPAM provides an example of how a science-management partnership can be forged to achieve large-scale conservation objectives.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131279","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Gannon, J., Shaffer, T.L., and Moore, C., 2013, Native Prairie Adaptive Management: a multi region adaptive approach to invasive plant management on Fish and Wildlife Service owned native prairies: U.S. Geological Survey Open-File Report 2013-1279, Report: vii, 184 p.; Downloads Directory, https://doi.org/10.3133/ofr20131279.","productDescription":"Report: vii, 184 p.; Downloads Directory","numberOfPages":"190","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-043840","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":281449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131279.jpg"},{"id":280311,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1279/"},{"id":281447,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1279/pdf/of2013-1279.pdf"},{"id":281448,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1279/Downloads/"}],"country":"United States","state":"Minnesota;Montana;North Dakota;South Dakota","otherGeospatial":"Great Plains;Prairie Pothole Region","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.32,40.75 ], [ -116.32,50.04 ], [ -90.88,50.04 ], [ -90.88,40.75 ], [ -116.32,40.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd68a3e4b0b290851022f6","contributors":{"authors":[{"text":"Gannon, Jill J.","contributorId":12722,"corporation":false,"usgs":true,"family":"Gannon","given":"Jill J.","affiliations":[],"preferred":false,"id":487376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shaffer, Terry L. 0000-0001-6950-8951 tshaffer@usgs.gov","orcid":"https://orcid.org/0000-0001-6950-8951","contributorId":3192,"corporation":false,"usgs":true,"family":"Shaffer","given":"Terry","email":"tshaffer@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":487374,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Clinton T.","contributorId":9767,"corporation":false,"usgs":true,"family":"Moore","given":"Clinton T.","affiliations":[],"preferred":false,"id":487375,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70056154,"text":"ofr20121007 - 2013 - National assessment of shoreline change: historical shoreline change along the Pacific Northwest coast","interactions":[],"lastModifiedDate":"2013-12-06T11:40:13","indexId":"ofr20121007","displayToPublicDate":"2013-12-09T08:55:00","publicationYear":"2013","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":"2012-1007","title":"National assessment of shoreline change: historical shoreline change along the Pacific Northwest coast","docAbstract":"Beach erosion is a chronic problem along most open ocean shores of the United States. As coastal populations continue to increase and infrastructure is threatened by erosion, there is increased demand for accurate information regarding past and present trends and rates of shoreline movement. There is also a need for a comprehensive analysis of shoreline movement that is consistent from one coastal region to another. To meet these national needs, the U.S. Geological Survey (USGS) is conducting an analysis of historical shoreline changes along the open-ocean sandy shores of the conterminous United States and parts of Hawaii, Alaska, and the Great Lakes. One purpose of this work is to develop standard, repeatable methods for mapping and analyzing shoreline movement so that periodic, systematic, and internally consistent updates regarding coastal erosion and land loss can be made nationally. In the case of the analysis of shoreline change in the Pacific Northwest (PNW), the shoreline is the interpreted boundary between the ocean water surface and the sandy beach.
\nThis report on the PNW coasts of Oregon and Washington is the seventh in a series of regionally focused reports on historical shoreline change. Previous investigations include analyses and descriptive reports of the U.S. Gulf of Mexico (Morton and others, 2004), the southeastern Atlantic (Morton and Miller, 2005), the sandy shorelines (Hapke and others, 2006) and coastal cliffs (Hapke and Reid, 2007) of California, the New England and mid-Atlantic coasts (Hapke and others, 2011), and parts of the Hawaii coast (Fletcher and others, 2012). Like the earlier reports in this series, this report summarizes the methods of analysis, interprets the results of the analysis, provides explanations regarding long- and short-term trends and rates of shoreline change, and describes how different coastal communities are responding to coastal erosion. This report differs from the early USGS reports in the series in that those shoreline change analyses incorporated only four total shorelines to represent specific time periods. This assessment of the PNW incorporates all available shorelines that meet minimum quality standards for resolution and positional accuracy. Shoreline change evaluations are based on a comparison of historical shoreline positions digitized from maps or aerial photographic data sources with recent shorelines, at least one of which is derived from lidar surveys. The historical shorelines cover a variety of time periods ranging from the 1800s through the 1980s, whereas the lidar shoreline is from 2002. Long-term rates of change are calculated using all available shoreline data and short-term rates of change are calculated using the lidar shoreline and the historical shoreline that will produce an assessment for a 15- to 35-year period. The rates of change presented in this report represent conditions up to the date of only the most recent shoreline data and therefore are not intended for predicting future shoreline positions or rates of change.
\nThe PNW coast was subdivided into eight analysis regions for the purpose of graphically reporting regional trends in shoreline change rates. The average rate of long-term shoreline change for the entire PNW coast was 0.9 meter per year (m/yr) of progradation with an uncertainty of 0.07 m/yr. This rate is based on 8,823 individual transects, of which 36 percent was determined to be eroding. Long-term shoreline change was generally more progradational in Washington than in Oregon. This is primarily due to the influence of the Columbia River and human perturbations to the natural system, particularly the construction of jetties at both the mouth of the Columbia River and at Grays Harbor, Washington. The majority of the beaches in southwestern Washington have responded to these large-scale engineered structures by experiencing dramatic beach progradation during the past century. Although these beaches are still responding to the human effects, in several locations beaches that had been rapidly prograding are now either prograding at a slower rate or eroding.
\nThe average rate of short-term shoreline change in the PNW was also progradational at a rate of 0.9 m/yr with an uncertainty of 0.03 m/yr. This rate is based on 9,087 individual transects, of which 44 percent was determined to be eroding. Similar to the results of the long-term shoreline change analysis, the shorelines in Washington were typically more progradational than those in Oregon in the short term. However, many stretches of coast in Oregon are either less accretional, changed from accretional to erosional, or more erosional when comparing the long- and short-term rate calculations. In the long and short term, there are significantly different historical shoreline change trends for beaches deriving their modern sediments from the Columbia River in southwestern Washington and northwestern Oregon, and beaches elsewhere in the PNW. The majority of shorelines in Oregon and in Washington’s Olympic Peninsula are not influenced by the human effects to the Columbia River littoral cell and typically have not experienced the human-induced century-scale trends apparent in southwestern Washington and northwestern Oregon.
\nAn increase in erosion hazards in much of Oregon may be related to the effects of sea-level rise and increasing storm wave heights. Of importance, particularly in the short term, is the alongshore variability in land uplift rates due to tectonics, which results in an alongshore varying rate of relative sea level rise that appears to at least partially control the regional variability in short-term shoreline change rates. Other climate related processes, such as the occurrence of major El Niño events, also significantly affect the shoreline changes in the region. Major El Niño events elevate monthly mean sea levels by tens of centimeters throughout the winter and produce a shift in the storm tracks, resulting in alongshore redistributions in sand volumes on the beaches, leading to hotspot beach erosion and property losses north of headlands and tidal inlets to bays and estuaries. There are limited modern-day sources of sand to Oregon’s beaches, with much of the sand being relict in having arrived thousands of years ago at a time of lowered sea levels when headlands did not prevent the alongshore movement of the beach sediments, the result being that many beaches today are deficient in sand volumes and therefore do not provide sufficient buffer protection to backshore properties during winter storms.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121007","usgsCitation":"Ruggerio, P., Kratzmann, M., Himmelstoss, E., Reid, D., Allan, J., and Kaminsky, G., 2013, National assessment of shoreline change: historical shoreline change along the Pacific Northwest coast: U.S. Geological Survey Open-File Report 2012-1007, xi, 61 p., https://doi.org/10.3133/ofr20121007.","productDescription":"xi, 61 p.","numberOfPages":"76","ipdsId":"IP-034232","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":280213,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121007.jpg"},{"id":280211,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1007/"},{"id":280212,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1007/pdf/ofr2012-1007.pdf"}],"scale":"70000","datum":"North American Datum of 1983","country":"United States","state":"Oregon;Washington","otherGeospatial":"Columbia River;Olympic Peninsula;Pacific Northwest","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.97,41.87 ], [ -125.97,48.65 ], [ -121.2,48.65 ], [ -121.2,41.87 ], [ -125.97,41.87 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52a717f3e4b0de1a6d2d96f7","contributors":{"authors":[{"text":"Ruggerio, Peter","contributorId":67403,"corporation":false,"usgs":true,"family":"Ruggerio","given":"Peter","email":"","affiliations":[],"preferred":false,"id":486358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kratzmann, Meredith G.","contributorId":11565,"corporation":false,"usgs":true,"family":"Kratzmann","given":"Meredith G.","affiliations":[],"preferred":false,"id":486353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Himmelstoss, Emily A.","contributorId":24736,"corporation":false,"usgs":true,"family":"Himmelstoss","given":"Emily A.","affiliations":[],"preferred":false,"id":486354,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reid, David","contributorId":63888,"corporation":false,"usgs":true,"family":"Reid","given":"David","email":"","affiliations":[],"preferred":false,"id":486357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Allan, Jonathan","contributorId":46847,"corporation":false,"usgs":false,"family":"Allan","given":"Jonathan","affiliations":[{"id":7198,"text":"Oregon Department Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":486355,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kaminsky, George","contributorId":60262,"corporation":false,"usgs":true,"family":"Kaminsky","given":"George","affiliations":[],"preferred":false,"id":486356,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70048792,"text":"sir20135150 - 2013 - Estimating nitrate concentrations in groundwater at selected wells and springs in the surficial aquifer system and Upper Floridan aquifer, Dougherty Plain and Marianna Lowlands, Georgia, Florida, and Alabama, 2002-50","interactions":[],"lastModifiedDate":"2017-01-17T20:49:03","indexId":"sir20135150","displayToPublicDate":"2013-11-05T11:31:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5150","title":"Estimating nitrate concentrations in groundwater at selected wells and springs in the surficial aquifer system and Upper Floridan aquifer, Dougherty Plain and Marianna Lowlands, Georgia, Florida, and Alabama, 2002-50","docAbstract":"Groundwater from the surficial aquifer system and Upper Floridan aquifer in the Dougherty Plain and Marianna Lowlands in southwestern Georgia, northwestern Florida, and southeastern Alabama is affected by elevated nitrate concentrations as a result of the vulnerability of the aquifer, irrigation water-supply development, and intensive agricultural land use. The region relies primarily on groundwater from the Upper Floridan aquifer for drinking-water and irrigation supply. Elevated nitrate concentrations in drinking water are a concern because infants under 6 months of age who drink water containing nitrate concentrations above the U.S. Environmental Protection Agency maximum contaminant level of 10 milligrams per liter as nitrogen can become seriously ill with blue baby syndrome.\n\nIn response to concerns about water quality in domestic wells and in springs in the lower Apalachicola–Chattahoochee–Flint River Basin, the Florida Department of Environmental Protection funded a study in cooperation with the U.S. Geological Survey to examine water quality in groundwater and springs that provide base flow to the Chipola River. A three-dimensional, steady-state, regional-scale groundwater-flow model and two local-scale models were used in conjunction with particle tracking to identify travel times and areas contributing recharge to six groundwater sites—three long-term monitor wells (CP-18A, CP-21A, and RF-41) and three springs (Jackson Blue Spring, Baltzell Springs Group, and Sandbag Spring) in the lower Apalachicola–Chattahoochee–Flint River Basin. Estimated nitrate input to groundwater at land surface, based on previous studies of nitrogen fertilizer sales and atmospheric nitrate deposition data, were used in the advective transport models for the period 2002 to 2050. Nitrate concentrations in groundwater samples collected from the six sites during 1993 to 2007 and groundwater age tracer data were used to calibrate the transport aspect of the simulations.\n\nMeasured nitrate concentrations (as nitrogen) in wells and springs sampled during the study ranged from 0.37 to 12.73 milligrams per liter. Average apparent ages of groundwater calculated from measurements of chlorofluorocarbon, sulfur hexafluoride, and tritium from wells CP-18A, CP-21A,and RF-41 were about 23, 29, and 32 years, respectively. Average apparent ages of groundwater from Baltzell Springs Group, Sandbag Spring, and Jackson Blue Spring were about 16, 18, and 19 years, respectively. Simulated travel times of particles from the six selected sites ranged from less than 1 day to 511 years; both the minimum and maximum particle travel times were estimated for water from Jackson Blue Spring. Median simulated travel times of particles were about 30, 38, and 62 years for Jackson Blue Spring, Sandbag Spring, and Baltzell Springs Group, respectively. Study results indicated that travel times for approximately 50 percent of the particles from all spring sites were less than 50 years. The median simulated travel times of particles arriving at receptor wells CP-18A, CP-21A, and RF-41 were about 50, 35, and 36 years, respectively. All particle travel times were within the same order of magnitude as the tracer-derived average apparent ages for water, although slightly older than the measured ages. Travel time estimates were substantially greater than the measured age for groundwater reaching well CP-18A, as confirmed by the average apparent age of water determined from tracers.\n\nLocal-scale particle-tracking models were used to predict nitrate concentrations in the three monitor wells and three springs from 2002 to 2050 for three nitrogen management scenarios: (1) fixed input of nitrate at the 2001 level, (2) reduction of nitrate inputs of 4 percent per year (from the previous year) from 2002 to 2050, and (3) elimination of nitrate input after 2001. Simulated nitrate concentrations in well CP-21A peaked at 7.82 milligrams per liter in 2030, and concentrations in background well RF-41 peaked at 1.10 milligrams per liter in 2020. The simulated particle travel times were longer than indicated by age dating analysis for groundwater in well CP-18A; to account for the poor calibration fit at this well, nitrate concentrations were shifted 21 years. With the shift, simulated nitrate concentrations in groundwater at CP-18A peaked at 13.76 milligrams per liter in 2026. For groundwater in Baltzell Springs Group, Jackson Blue Spring, and Sandbag Spring, simulated nitrate concentrations peaked at 3.77 milligrams per liter in 2006, 3.51 milligrams per liter in 2011, and 0.81 milligram per liter in 2018, respectively, under the three management scenarios. In management scenario 3 (elimination of nitrate input after 2001), simulated nitrate concentrations in Baltzell Springs Group decreased to less than background concentrations (0.10 milligram per liter) by 2033, and in Sandbag Spring concentrations decreased to less than background by 2041. Simulations using nitrate management scenarios 1 (fixed input of nitrate at 2001 levels) and 2 (reduction of 4.0 percent per year) indicate that nitrate concentrations in groundwater may remain above background concentrations through 2050 at all sites.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135150","collaboration":"National Water-Quality Assessment Program; Prepared in cooperation with the Florida Department of Environmental Protection","usgsCitation":"Crandall, C.A., Katz, B.G., and Berndt, M., 2013, Estimating nitrate concentrations in groundwater at selected wells and springs in the surficial aquifer system and Upper Floridan aquifer, Dougherty Plain and Marianna Lowlands, Georgia, Florida, and Alabama, 2002-50: U.S. Geological Survey Scientific Investigations Report 2013-5150, ix, 65 p., https://doi.org/10.3133/sir20135150.","productDescription":"ix, 65 p.","numberOfPages":"80","onlineOnly":"Y","temporalStart":"2002-01-01","temporalEnd":"2050-12-31","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":278706,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5150/"},{"id":278707,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5150/pdf/sir2013-5150.pdf"},{"id":278708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135150.gif"}],"scale":"24000","projection":"Albers Equal-Area Conic Projection","country":"United States","state":"Alabama, Florida, Georgia","otherGeospatial":"Apalachicola River Basin, Chattahoochee River Basin, Flint River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.8626,29.8562 ], [ -85.8626,32.2922 ], [ -83.6061,32.2922 ], [ -83.6061,29.8562 ], [ -85.8626,29.8562 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527a1367e4b051792d014898","contributors":{"authors":[{"text":"Crandall, Christy A. crandall@usgs.gov","contributorId":1091,"corporation":false,"usgs":true,"family":"Crandall","given":"Christy","email":"crandall@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":485654,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katz, Brian G. bkatz@usgs.gov","contributorId":1093,"corporation":false,"usgs":true,"family":"Katz","given":"Brian","email":"bkatz@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":485655,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berndt, Marian P.","contributorId":45296,"corporation":false,"usgs":true,"family":"Berndt","given":"Marian P.","affiliations":[],"preferred":false,"id":485656,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70112523,"text":"70112523 - 2013 - Does centennial morphodynamic evolution lead to higher channel efficiency in San Pablo Bay, California?","interactions":[],"lastModifiedDate":"2020-06-05T14:44:42.854024","indexId":"70112523","displayToPublicDate":"2013-11-01T14:21:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Does centennial morphodynamic evolution lead to higher channel efficiency in San Pablo Bay, California?","docAbstract":"Measured bathymetries on 30 year interval over the past 150 years show that San Pablo Bay experienced periods of considerable deposition followed by periods of net erosion. However, the main channel in San Pablo Bay has continuously narrowed. The underlying mechanisms and consequences of this tidal channel evolution are not well understood.
\nThe central question of this study is whether tidal channels evolve towards a geometry that leads to more efficient hydraulic conveyance and sediment throughput. We applied a hydrodynamic process-based, numerical model (Delft3D), which was run on 5 San Pablo Bay bathymetries measured between 1856 and 1983.
\nModel results shows increasing energy dissipation levels for lower water flows leading to an approximately 15% lower efficiency in 1983 compared to 1856. During the same period the relative seaward sediment throughput through the San Pablo Bay main channel increased by 10%. A probable explanation is that San Pablo Bay is still affected by the excessive historic sediment supply. Sea level rise and Delta surface water area variations over 150 years have limited effect on the model results. With expected lower sediment concentrations in the watershed and less impact of wind waves due to erosion of the shallow flats, it is possible that energy dissipations levels will decrease again in future decades. Our study suggests that the morphodynamic adaptation time scale to excessive variations in sediment supply to estuaries may be on the order of centuries.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2013.06.020","usgsCitation":"van der Wegen, M., and Jaffe, B.E., 2013, Does centennial morphodynamic evolution lead to higher channel efficiency in San Pablo Bay, California?: Marine Geology, v. 345, p. 254-265, https://doi.org/10.1016/j.margeo.2013.06.020.","productDescription":"12 p.","startPage":"254","endPage":"265","numberOfPages":"12","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay, San Pablo Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.6229,37.333 ], [ -122.6229,38.2598 ], [ -121.1534,38.2598 ], [ -121.1534,37.333 ], [ -122.6229,37.333 ] ] ] } } ] }","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae768ae4b0abf75cf2bf93","contributors":{"editors":[{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":509889,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":509891,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":509890,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"van der Wegen, M.","contributorId":106720,"corporation":false,"usgs":true,"family":"van der Wegen","given":"M.","affiliations":[],"preferred":false,"id":494832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":494831,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70112504,"text":"70112504 - 2013 - The use of modeling and suspended sediment concentration measurements for quantifying net suspended sediment transport through a large tidally dominated inlet","interactions":[],"lastModifiedDate":"2020-06-05T14:52:04.442498","indexId":"70112504","displayToPublicDate":"2013-11-01T13:41:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"The use of modeling and suspended sediment concentration measurements for quantifying net suspended sediment transport through a large tidally dominated inlet","docAbstract":"Sediment exchange at large energetic inlets is often difficult to quantify due complex flows, massive amounts of water and sediment exchange, and environmental conditions limiting long-term data collection. In an effort to better quantify such exchange this study investigated the use of suspended sediment concentrations (SSC) measured at an offsite location as a surrogate for sediment exchange at the tidally dominated Golden Gate inlet in San Francisco, CA. A numerical model was calibrated and validated against water and suspended sediment flux measured during a spring–neap tide cycle across the Golden Gate. The model was then run for five months and net exchange was calculated on a tidal time-scale and compared to SSC measurements at the Alcatraz monitoring site located in Central San Francisco Bay ~ 5 km from the Golden Gate. Numerically modeled tide averaged flux across the Golden Gate compared well (r2 = 0.86, p-value < 0.05) with 25 h low-pass filtered (tide averaged) SSCs measured at Alcatraz over the five month simulation period (January through April 2008). This formed a basis for the development of a simple equation relating the advective flux at Alcatraz with suspended sediment flux across the Golden Gate. Utilization of the equation with all available Alcatraz SSC data resulted in an average export rate of 1.2 Mt/yr during water years 2004 through 2010. While the rate is comparable to estimated suspended sediment inflow rates from sources within the Bay over the same time period (McKee et al., 2013-this issue), there was little variation from year to year. Exports were computed to be greatest during the wettest water year analyzed but only marginally so.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2013.06.001","usgsCitation":"Erikson, L., Wright, S., Elias, E., Hanes, D.M., Schoellhamer, D., and Largier, J., 2013, The use of modeling and suspended sediment concentration measurements for quantifying net suspended sediment transport through a large tidally dominated inlet: Marine Geology, v. 345, p. 96-112, https://doi.org/10.1016/j.margeo.2013.06.001.","productDescription":"17 p.","startPage":"96","endPage":"112","numberOfPages":"17","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":288632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.559719,37.681583 ], [ -122.559719,37.994051 ], [ -122.249249,37.994051 ], [ -122.249249,37.681583 ], [ -122.559719,37.681583 ] ] ] } } ] }","volume":"345","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7871e4b0abf75cf2d559","contributors":{"editors":[{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":147147,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick L.","email":"pbarnard@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":509868,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":509870,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":509869,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Erikson, Li H.","contributorId":10880,"corporation":false,"usgs":true,"family":"Erikson","given":"Li H.","affiliations":[],"preferred":false,"id":494790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494789,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elias, Edwin","contributorId":50615,"corporation":false,"usgs":true,"family":"Elias","given":"Edwin","affiliations":[],"preferred":false,"id":494791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanes, Daniel M.","contributorId":96360,"corporation":false,"usgs":true,"family":"Hanes","given":"Daniel","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":494793,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494788,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Largier, John","contributorId":85257,"corporation":false,"usgs":true,"family":"Largier","given":"John","email":"","affiliations":[],"preferred":false,"id":494792,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70048712,"text":"sir20135051 - 2013 - Groundwater and surface-water interaction within the upper Smith River Watershed, Montana 2006-2010","interactions":[],"lastModifiedDate":"2014-01-30T14:30:20","indexId":"sir20135051","displayToPublicDate":"2013-10-31T08:34:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5051","title":"Groundwater and surface-water interaction within the upper Smith River Watershed, Montana 2006-2010","docAbstract":"The 125-mile long Smith River, a tributary of the Missouri River, is highly valued as an agricultural resource and for its many recreational uses. During a drought starting in about 1999, streamflow was insufficient to meet all of the irrigation demands, much less maintain streamflow needed for boating and viable fish habitat. In 2006, the U.S. Geological Survey, in cooperation with the Meagher County Conservation District, initiated a multi-year hydrologic investigation of the Smith River watershed. This investigation was designed to increase understanding of the water resources of the upper Smith River watershed and develop a detailed description of groundwater and surface-water interactions. A combination of methods, including miscellaneous and continuous groundwater-level, stream-stage, water-temperature, and streamflow monitoring was used to assess the hydrologic system and the spatial and temporal variability of groundwater and surface-water interactions. Collectively, data are in agreement and show: (1) the hydraulic connectedness of groundwater and surface water, (2) the presence of both losing and gaining stream reaches, (3) dynamic changes in direction and magnitude of water flow between the stream and groundwater with time, (4) the effects of local flood irrigation on groundwater levels and gradients in the watershed, and (5) evidence and timing of irrigation return flows to area streams.
\nGroundwater flow within the alluvium and older (Tertiary) basin-fill sediments generally followed land-surface topography from the uplands to the axis of alluvial valleys of the Smith River and its tributaries. Groundwater levels were typically highest in the monitoring wells located within and adjacent to streams in late spring or early summer, likely affected by recharge from snowmelt and local precipitation, leakage from losing streams and canals, and recharge from local flood irrigation. The effects of flood irrigation resulted in increased hydraulic gradients (increased groundwater levels relative to stream stage) or even reversed gradient direction at several monitoring sites coincident with the onset of nearby flood irrigation. Groundwater-level declines in mid-summer were due to groundwater withdrawals and reduced recharge from decreased precipitation, increased evapotranspiration, and reduced leakage in some area streams during periods of low flow. Groundwater levels typically rebounded in late summer, a result of decreased evapotranspiration, decreased groundwater use for irrigation, increased flow in losing streams, and the onset of late-season flood irrigation at some sites.
\nThe effect of groundwater and surface-water interactions is most apparent along the North and South Forks of the Smith River where the magnitude of streamflow losses and gains can be greater than the magnitude of flow within the stream. Net gains consistently occurred over the lower 15 miles of the South Fork Smith River. A monitoring site near the mouth of the South Fork Smith River gained (flow from the groundwater to the stream) during all seasons, with head gradients towards the stream. Two upstream sites on the South Fork Smith River exhibited variable conditions that ranged from gaining during the spring, losing (flowing from the stream to the groundwater) during most of the summer as groundwater levels declined, and then approached or returned to gaining conditions in late summer. Parts of the South Fork Smith River became dry during periods of losing conditions, thus classifying this tributary as intermittent. The North Fork Smith River is highly managed at times through reservoir releases. The North Fork Smith River was perennial throughout the study period although irrigation diversions removed a large percentage of streamflow at times and losing conditions persisted along a lower reach. The lowermost reach of the North Fork Smith River near its mouth transitioned from a losing reach to a gaining reach throughout the study period.
\nGroundwater and surface-water interactions occur downstream from the confluence of the North and South Fork Smith Rivers, but are less discernible compared to the overall magnitude of the main-stem streamflow. The Smith River was perennial throughout the study. Monitoring sites along the Smith River generally displayed small head gradients between the stream and the groundwater, while one site consistently showed strongly gaining conditions. Synoptic streamflow measurements during periods of limited irrigation diversion in 2007 and 2008 consistently showed gains over the upper 41.4 river miles of the main stem Smith River where net gains ranged from 13.0 to 28.9 cubic feet per second. Continuous streamflow data indicated net groundwater discharge and small-scale tributary inflow contributions of around 25 cubic feet per second along the upper 10-mile reach of the Smith River for most of the 2010 record. A period of intense irrigation withdrawal during the last two weeks in May was followed by a period (early June 2010 to mid-July 2010) with the largest net increase (an average of 71.1 cubic feet per second) in streamflow along this reach of the Smith River. This observation is likely due to increased groundwater discharge to the Smith River resulting from irrigation return flow. By late July, the apparent effects of return flows receded, and the net increase in streamflow returned to about 25 cubic feet per second.
\nTwo-dimensional heat and solute transport VS2DH models representing selected stream cross sections were used to constrain the hydraulic properties of the Quaternary alluvium and estimate temporal water-flux values through model boundaries. Hydraulic conductivity of the Quaternary alluvium of the modeled sections ranged from 3x10-6 to 4x10-5 feet per second. The models showed reasonable approximations of the streambed and shallow aquifer environment, and the dynamic changes in water flux between the stream and the groundwater through different model boundaries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135051","collaboration":"Prepared in cooperation with Meagher County Conservation District","usgsCitation":"Caldwell, R.R., and Eddy-Miller, C., 2013, Groundwater and surface-water interaction within the upper Smith River Watershed, Montana 2006-2010: U.S. Geological Survey Scientific Investigations Report 2013-5051, xi, 88 p., https://doi.org/10.3133/sir20135051.","productDescription":"xi, 88 p.","numberOfPages":"104","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":278592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135051.gif"},{"id":278591,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5051/pdf/sir2013-5051.pdf"},{"id":279219,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5051/"}],"scale":"100000","projection":"Lambert Conformal Conic Projection","datum":"North American Datum of 1983","country":"United States","state":"Montana","otherGeospatial":"Smith River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.0,46.0 ], [ -112.0,47.5 ], [ -110.5,47.5 ], [ -110.5,46.0 ], [ -112.0,46.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52736dfce4b097f32ac3dae0","contributors":{"authors":[{"text":"Caldwell, Rodney R. 0000-0002-2588-715X caldwell@usgs.gov","orcid":"https://orcid.org/0000-0002-2588-715X","contributorId":2577,"corporation":false,"usgs":true,"family":"Caldwell","given":"Rodney","email":"caldwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":485472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eddy-Miller, Cheryl A.","contributorId":86755,"corporation":false,"usgs":true,"family":"Eddy-Miller","given":"Cheryl A.","affiliations":[],"preferred":false,"id":485473,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047159,"text":"70047159 - 2013 - Updating the planetary time scale: focus on Mars","interactions":[],"lastModifiedDate":"2013-10-30T11:22:11","indexId":"70047159","displayToPublicDate":"2013-09-23T13:48:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1238,"text":"Ciencias Da Terra","active":true,"publicationSubtype":{"id":10}},"title":"Updating the planetary time scale: focus on Mars","docAbstract":"Formal stratigraphic systems have been developed for the surface materials of the Moon, Mars, Mercury, and the Galilean satellite Ganymede. These systems are based on geologic mapping, which establishes relative ages of surfaces delineated by superposition, morphology, impact crater densities, and other relations and features. Referent units selected from the mapping determine time-stratigraphic bases and/or representative materials characteristic of events and periods for definition of chronologic units. Absolute ages of these units in some cases can be estimated using crater size-frequency data. For the Moon, the chronologic units and cratering record are calibrated by radiometric ages measured from samples collected from the lunar surface. Model ages for other cratered planetary surfaces are constructed primarily by estimating cratering rates relative to that of the Moon. Other cratered bodies with estimated surface ages include Venus and the Galilean satellites of Jupiter. New global geologic mapping and crater dating studies of Mars are resulting in more accurate and detailed reconstructions of its geologic history.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ciencias Da Terra","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Department of Earth Sciences Lisbon University","usgsCitation":"Tanaka, K.L., and Quantin-Nataf, C., 2013, Updating the planetary time scale: focus on Mars: Ciencias Da Terra.","ipdsId":"IP-044682","costCenters":[],"links":[{"id":278011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278012,"type":{"id":11,"text":"Document"},"url":"https://www.cienciasdaterra.com/index.php/vol/article/view/278"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"524154fce4b0ec672f073ac7","contributors":{"authors":[{"text":"Tanaka, Kenneth L. ktanaka@usgs.gov","contributorId":610,"corporation":false,"usgs":true,"family":"Tanaka","given":"Kenneth","email":"ktanaka@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":481187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quantin-Nataf, Cathy","contributorId":26615,"corporation":false,"usgs":true,"family":"Quantin-Nataf","given":"Cathy","email":"","affiliations":[],"preferred":false,"id":481188,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70058716,"text":"70058716 - 2013 - Wind River watershed restoration. Annual report. November 2011 through October 2012","interactions":[],"lastModifiedDate":"2016-05-17T08:51:18","indexId":"70058716","displayToPublicDate":"2013-08-01T02:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Wind River watershed restoration. Annual report. November 2011 through October 2012","docAbstract":"This report summarizes work by U.S. Geological Survey’s Columbia River Research Laboratory (USGS-CRRL) in the Wind River subbasin, from November 2011 through October 2012. Funding was provided by Bonneville Power Administration (BPA) under contract 55275. The primary focus of USGS activities during this time was tagging of parr steelhead Oncorhynchus mykiss with Passive Integrated Transponder (PIT) tags, and establishing a network of instream PIT tag interrogation systems (PTIS). The PIT-tagged parr steelhead will provide movement and life history data through recapture events and detections at instream PTIS systems, will contribute to estimates of adult steelhead returning to the Wind River, and aid in the evaluation of the removal of Hemlock Dam on Trout Creek steelhead populations.
\nThe Wind River Watershed project (BPA Project Number 1998-019-00) is a collaborative effort to restore wild steelhead in the Wind River, WA. The four partner agencies are the U.S. Forest Service (USFS), Washington Department of Fish and Wildlife (WDFW), USGS-CRRL, and Underwood Conservation District (UCD). This partnership was established in the early 1990s with support from BPA, and has continued to conduct extensive habitat, research, monitoring, and coordination activities across the subbasin. The project works at multiple levels to identify and characterize key limiting habitat factors in the Wind River; restore degraded habitats and watershed processes; document fish populations, life histories, and interactions; investigate efficacy of restoration actions; and to share information across agency and non-agency boundaries. Long-term research in the Wind River has focused on assessments of steelhead/rainbow trout populations, relationships with introduced populations of spring Chinook salmon O. tshawytscha and brook trout Salvelinus fontinalis, and effects of habitat variables and habitat restoration on fish productivity.
\nDuring the period covered by this report, we PIT tagged steelhead parr in headwater sections of the subbasin (Figure 1), maintained a PTIS in Trout Creek, installed a PTIS in the Wind River, and installed smaller scale PTISs in Trapper Creek, Paradise Creek, and the Wind River upstream of Paradise Creek (Figure 2). Additionally we maintained thermologgers to collect water temperature data near the PIT tagging sites.
\nA statement of work (SOW) was submitted to BPA in October 2011 that outlined work to be performed by USGS-CRRL. The SOW was organized by Work Element (WE), with each describing a research task. This report summarizes the progress completed under each WE.
","language":"English","publisher":"Bonneville Power Administration","collaboration":"BPA Project Number: 1998-019-00. Report covers work performed under BPA contract number: 55275. Report was completed under BPA contract number: 59821.","usgsCitation":"Jezorek, I.G., and Connolly, P., 2013, Wind River watershed restoration. Annual report. November 2011 through October 2012, 40 p.","productDescription":"40 p.","numberOfPages":"41","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2011-11-01","temporalEnd":"2012-10-31","ipdsId":"IP-045885","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":287615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280261,"type":{"id":11,"text":"Document"},"url":"https://pisces.bpa.gov/release/documents/documentviewer.aspx?doc=P133526","text":"Report","size":"648.14 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Washington","otherGeospatial":"Wind River Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.982107,45.715023 ], [ -121.982107,45.88214 ], [ -121.787086,45.88214 ], [ -121.787086,45.715023 ], [ -121.982107,45.715023 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5385b408e4b09e18fc023ad9","contributors":{"authors":[{"text":"Jezorek, Ian G. 0000-0002-3842-3485 ijezorek@usgs.gov","orcid":"https://orcid.org/0000-0002-3842-3485","contributorId":3572,"corporation":false,"usgs":true,"family":"Jezorek","given":"Ian","email":"ijezorek@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connolly, Patrick J. 0000-0001-7365-7618 pconnolly@usgs.gov","orcid":"https://orcid.org/0000-0001-7365-7618","contributorId":2920,"corporation":false,"usgs":true,"family":"Connolly","given":"Patrick J.","email":"pconnolly@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":487296,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047262,"text":"ofr20131144 - 2013 - Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California, 2012","interactions":[],"lastModifiedDate":"2013-07-27T11:45:43","indexId":"ofr20131144","displayToPublicDate":"2013-07-27T11:32:00","publicationYear":"2013","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":"2013-1144","title":"Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California, 2012","docAbstract":"Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in South San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January to December 2012. These data serve as the basis for the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.\n\nFollowing significant reductions in the late 1980s, silver (Ag) and copper (Cu) concentrations in sediment and in M. petalum appear to have stabilized. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2012, concentrations of Ag and Cu in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported for previous time periods. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se were generally similar in timing and magnitude as those for Ag and Cu. In 2012, metal concentrations in both sediments and clam tissue were among the lowest concentrations on record. This record suggests that regional-scale factors now largely control sedimentary and bioavailable concentrations of Ag and Cu, as well as other elements of regulatory interest, at the Palo Alto site.\n\nAnalyses of the benthic community structure of a mudflat in South San Francisco Bay over a 39-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of the M. petalum community shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2012), with almost all animals initiating reproduction in the fall and spawning the following spring. The community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for those deep-dwelling animals like Macoma petalum. Animals immediately returned to the mudflat in 2008, which was the first indication that the disturbance was not due to a persistent toxin or to anoxia. The reproductive mode of most species present in 2012 is reflective of the species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2012 benthic community data, which show that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of animals that consume the sediment, filter feed, have pelagic larvae that must survive landing on the sediment, and brood their young. USGS scientists continue to observe the community’s response to the 2008 defaunation event because it allows them to examine the response of the community to a natural disturbance (possible causes include sediment accretion or freshwater inundation) and compare this recovery to the long-term recovery observed in the 1970s when the decline in sediment pollutants was the dominating factor.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131144","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Dyke, J., Thompson, J.K., Cain, D.J., Kleckner, A.E., Parcheso, F., Luoma, S.N., and Hornberger, M.I., 2013, Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California, 2012: U.S. Geological Survey Open-File Report 2013-1144, vi, 109 p.; Tables; Appendixes, https://doi.org/10.3133/ofr20131144.","productDescription":"vi, 109 p.; Tables; Appendixes","numberOfPages":"117","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":434,"text":"National Research Program","active":false,"usgs":true}],"links":[{"id":275491,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131144.gif"},{"id":275489,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1144/of2013-1144_tables.xlsx"},{"id":275490,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1144/of2013-1144_appendixes.xlsx"},{"id":275487,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1144/"},{"id":275488,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1144/of2013-1144_text.pdf"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.75,36.75 ], [ -122.75,38.5 ], [ -121.5,38.5 ], [ -121.5,36.75 ], [ -122.75,36.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f4ddd9e4b0838938b28033","contributors":{"authors":[{"text":"Dyke, Jessica jldyke@usgs.gov","contributorId":1035,"corporation":false,"usgs":true,"family":"Dyke","given":"Jessica","email":"jldyke@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":481556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Janet K. 0000-0002-1528-8452 jthompso@usgs.gov","orcid":"https://orcid.org/0000-0002-1528-8452","contributorId":1009,"corporation":false,"usgs":true,"family":"Thompson","given":"Janet","email":"jthompso@usgs.gov","middleInitial":"K.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":481555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cain, Daniel J. 0000-0002-3443-0493 djcain@usgs.gov","orcid":"https://orcid.org/0000-0002-3443-0493","contributorId":1784,"corporation":false,"usgs":true,"family":"Cain","given":"Daniel","email":"djcain@usgs.gov","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":481558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kleckner, Amy E. kleckner@usgs.gov","contributorId":4258,"corporation":false,"usgs":true,"family":"Kleckner","given":"Amy","email":"kleckner@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":481561,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parcheso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":2590,"corporation":false,"usgs":true,"family":"Parcheso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":481560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":481559,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hornberger, Michelle I. 0000-0002-7787-3446 mhornber@usgs.gov","orcid":"https://orcid.org/0000-0002-7787-3446","contributorId":1037,"corporation":false,"usgs":true,"family":"Hornberger","given":"Michelle","email":"mhornber@usgs.gov","middleInitial":"I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":481557,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70047150,"text":"70047150 - 2013 - Superimposed extension and shortening in the southern Salinas Basin and La Panza Range, California: A guide to Neogene deformation in the Salinian block of the central California Coast Ranges","interactions":[],"lastModifiedDate":"2013-07-23T11:48:11","indexId":"70047150","displayToPublicDate":"2013-07-23T11:25:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2626,"text":"Lithosphere","active":true,"publicationSubtype":{"id":10}},"title":"Superimposed extension and shortening in the southern Salinas Basin and La Panza Range, California: A guide to Neogene deformation in the Salinian block of the central California Coast Ranges","docAbstract":"We synthesized data from geologic maps, wells, seismic-reflection profiles, potential-field interpretations, and low-temperature thermochronology to refine our understanding of late Cenozoic extension and shortening in the Salinian block of the central California Coast Ranges. Data from the La Panza Range and southern Salinas Basin document early to middle Miocene extension, followed by Pliocene and younger shortening after a period of little deformation in the late Miocene. Extension took place on high-angle normal faults that accommodated ∼2% strain at the scale of the ∼50-km-wide Salinian block (oriented perpendicular to the San Andreas fault). Shortening was accommodated by new reverse faults, reactivation of older normal faults, and strike-slip faulting that resulted in a map-view change in the width of the Salinian block. The overall magnitude of shortening was ∼10% strain, roughly 4–5 times greater than the amount of extension. The timing and magnitude of deformation in our study area are comparable to that documented in other Salinian block basins, and we suggest that the entire block deformed in a similar manner over a similar time span. The timing and relative magnitude of extension and shortening may be understood in the context of central Coast Range tectonic boundary conditions linked to rotation of the western Transverse Ranges at the south end of the Salinian block. Older models for Coast Range shortening based on balanced fault-bend fold-style cross sections are a poor approximation of Salinian block deformation, and may lead to mechanically improbable fault geometries that overestimate the amount of shortening.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Lithosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/L208.1","usgsCitation":"Colgan, J.P., McPhee, D., McDougall, K., and Hourigan, J.K., 2013, Superimposed extension and shortening in the southern Salinas Basin and La Panza Range, California: A guide to Neogene deformation in the Salinian block of the central California Coast Ranges: Lithosphere, v. 4, no. 5, p. 29-48, https://doi.org/10.1130/L208.1.","startPage":"29","endPage":"48","ipdsId":"IP-038444","costCenters":[],"links":[{"id":473659,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/l208.1","text":"Publisher Index Page"},{"id":275282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275247,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/L208.1"},{"id":275248,"type":{"id":15,"text":"Index Page"},"url":"https://lithosphere.gsapubs.org/content/4/5/411.abstract"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.9867,34.3752 ], [ -121.9867,37.0815 ], [ -118.9874,37.0815 ], [ -118.9874,34.3752 ], [ -121.9867,34.3752 ] ] ] } } ] }","volume":"4","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ef97d9e4b0b09fbe58f171","contributors":{"authors":[{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":481174,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McPhee, Darcy 0000-0002-5177-3068 dmcphee@usgs.gov","orcid":"https://orcid.org/0000-0002-5177-3068","contributorId":2621,"corporation":false,"usgs":true,"family":"McPhee","given":"Darcy","email":"dmcphee@usgs.gov","affiliations":[{"id":412,"text":"National Cooperative Geologic Mapping Program","active":false,"usgs":true}],"preferred":true,"id":481175,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDougall, Kristin 0000-0002-8788-3664","orcid":"https://orcid.org/0000-0002-8788-3664","contributorId":85610,"corporation":false,"usgs":true,"family":"McDougall","given":"Kristin","affiliations":[],"preferred":false,"id":481176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hourigan, Jeremy K.","contributorId":99023,"corporation":false,"usgs":true,"family":"Hourigan","given":"Jeremy","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":481177,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193590,"text":"70193590 - 2013 - Merapi 2010 eruption—Chronology and extrusion rates monitored with satellite radar and used in eruption forecasting","interactions":[],"lastModifiedDate":"2017-11-02T12:05:26","indexId":"70193590","displayToPublicDate":"2013-07-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Merapi 2010 eruption—Chronology and extrusion rates monitored with satellite radar and used in eruption forecasting","docAbstract":"Despite dense cloud cover, satellite-borne commercial Synthetic Aperture Radar (SAR) enabled frequent monitoring of Merapi volcano's 2010 eruption. Near-real-time interpretation of images derived from the amplitude of the SAR signals and timely delivery of these interpretations to those responsible for warnings, allowed satellite remote sensing for the first time to play an equal role with in situ seismic, geodetic and gas monitoring in guiding life-saving decisions during a major volcanic crisis. Our remotely sensed data provide an observational chronology for the main phase of the 2010 eruption, which lasted 12 days (26 October–7 November, 2010). Unlike the prolonged low-rate and relatively low explosivity dome-forming and collapse eruptions of recent decades at Merapi, the eruption began with an explosive eruption that produced a new summit crater on 26 October and was accompanied by an ash column and pyroclastic flows that extended 8 km down the flanks. This initial explosive event was followed by smaller explosive eruptions on 29 October–1 November, then by a period of rapid dome growth on 1–4 November, which produced a summit lava dome with a volume of ~ 5 × 106 m3. A paroxysmal VEI 4 magmatic eruption (with ash column to 17 km altitude) destroyed this dome, greatly enlarged the new summit crater and produced extensive pyroclastic flows (to ~ 16 km radial distance in the Gendol drainage) and surges during the night of 4–5 November. The paroxysmal eruption was followed by a period of jetting of gas and tephra and by a second short period (12 h) of rapid dome growth on 6 November. The eruption ended with low-level ash and steam emissions that buried the 6 November dome with tephra and continued at low levels until seismicity decreased to background levels by about 23 November. Our near-real-time commercial SAR documented the explosive events on 26 October and 4–5 November and high rates of dome growth (> 25 m3 s− 1). An event tree analysis for the previous 2006 Merapi eruption indicated that for lava dome extrusion rates > 1.2 m3 s− 1, the probability of a large (1872-scale) eruption was ~ 10%. Consequently, the order-of-magnitude greater rates in 2010, along with the explosive start of the eruption on 26 October, the large volume of lava accumulating at the summit by 4 November, and the rapid and large increases in seismic energy release, deformation and gas emissions were the basis for warnings of an unusually large eruption by the Indonesian Geological Agency's Center for Volcanology and Geologic Hazard Mitigation (CVGHM) and their Volcano Research and Technology Development Center (BPPTK) in Yogyakarta — warnings that saved thousands of lives.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2012.07.012","usgsCitation":"Pallister, J.S., Schneider, D.J., Griswold, J.P., Keeler, R.H., Burton, W.C., Noyles, C., Newhall, C.G., and Ratdomopurbo, A., 2013, Merapi 2010 eruption—Chronology and extrusion rates monitored with satellite radar and used in eruption forecasting: Journal of Volcanology and Geothermal Research, v. 261, p. 144-152, https://doi.org/10.1016/j.jvolgeores.2012.07.012.","productDescription":"9 p.","startPage":"144","endPage":"152","ipdsId":"IP-039184","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":348081,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Merapi Volcano","volume":"261","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2eade4b0531197b27fc5","contributors":{"authors":[{"text":"Pallister, John S. 0000-0002-2041-2147 jpallist@usgs.gov","orcid":"https://orcid.org/0000-0002-2041-2147","contributorId":2024,"corporation":false,"usgs":true,"family":"Pallister","given":"John","email":"jpallist@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":719512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schneider, David J. 0000-0001-9092-1054 djschneider@usgs.gov","orcid":"https://orcid.org/0000-0001-9092-1054","contributorId":198601,"corporation":false,"usgs":true,"family":"Schneider","given":"David","email":"djschneider@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":719510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griswold, Julia P. griswold@usgs.gov","contributorId":4148,"corporation":false,"usgs":true,"family":"Griswold","given":"Julia","email":"griswold@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":719511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keeler, Ronald H.","contributorId":199596,"corporation":false,"usgs":false,"family":"Keeler","given":"Ronald","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":719541,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burton, William C. 0000-0001-7519-5787 bburton@usgs.gov","orcid":"https://orcid.org/0000-0001-7519-5787","contributorId":1293,"corporation":false,"usgs":true,"family":"Burton","given":"William","email":"bburton@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":719542,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noyles, Christopher","contributorId":199597,"corporation":false,"usgs":false,"family":"Noyles","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":719543,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Newhall, Christopher G.","contributorId":25557,"corporation":false,"usgs":true,"family":"Newhall","given":"Christopher","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":719544,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ratdomopurbo, Antonius","contributorId":22523,"corporation":false,"usgs":true,"family":"Ratdomopurbo","given":"Antonius","email":"","affiliations":[],"preferred":false,"id":719545,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70046655,"text":"ds746 - 2013 - Historical rock falls in Yosemite National Park, California (1857-2011)","interactions":[],"lastModifiedDate":"2023-06-05T15:11:43.627772","indexId":"ds746","displayToPublicDate":"2013-06-18T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"746","title":"Historical rock falls in Yosemite National Park, California (1857-2011)","docAbstract":"Inventories of rock falls and other types of landslides are valuable tools for improving understanding of these events. For example, detailed information on rock falls is critical for identifying mechanisms that trigger rock falls, for quantifying the susceptibility of different cliffs to rock falls, and for developing magnitude-frequency relations. Further, inventories can assist in quantifying the relative hazard and risk posed by these events over both short and long time scales.
\nThis report describes and presents the accompanying rock fall inventory database for Yosemite National Park, California. The inventory database documents 925 events spanning the period 1857–2011. Rock falls, rock slides, and other forms of slope movement represent a serious natural hazard in Yosemite National Park. Rock-fall hazard and risk are particularly relevant in Yosemite Valley, where glacially steepened granitic cliffs approach 1 km in height and where the majority of the approximately 4 million yearly visitors to the park congregate. In addition to damaging roads, trails, and other facilities, rock falls and other slope movement events have killed 15 people and injured at least 85 people in the park since the first documented rock fall in 1857.
\nThe accompanying report describes each of the organizational categories in the database, including event location, type of slope movement, date, volume, relative size, probable trigger, impact to humans, narrative description, references, and environmental conditions. The inventory database itself is contained in a Microsoft Excel spreadsheet (Yosemite_rock_fall_database_1857-2011.xlsx). Narrative descriptions of events are contained in the database, but are also provided in a more readable Adobe portable document format (pdf) file (Yosemite_rock_fall_database_narratives_1857-2011.pdf) available for download separate from the database.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds746","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Stock, G.M., Collins, B., Santaniello, D.J., Zimmer, V.L., Wieczorek, G.F., and Snyder, J.B., 2013, Historical rock falls in Yosemite National Park, California (1857-2011): U.S. Geological Survey Data Series 746, Report: iv, 17 p.; Database, https://doi.org/10.3133/ds746.","productDescription":"Report: iv, 17 p.; Database","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":273931,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds746.gif"},{"id":273927,"rank":4,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/746/","linkFileType":{"id":5,"text":"html"}},{"id":273929,"rank":2,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/ds/746/Yosemite_rock_fall_database_1857-2011.xlsx"},{"id":273930,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/746/Yosemite_rock_fall_database_narratives_1857-2011.pdf"},{"id":273928,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/746/ds746_text.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.8863,37.4948 ], [ -119.8863,38.1863 ], [ -119.1995,38.1863 ], [ -119.1995,37.4948 ], [ -119.8863,37.4948 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c17357e4b0dd0e00d92187","contributors":{"authors":[{"text":"Stock, Greg M.","contributorId":88593,"corporation":false,"usgs":true,"family":"Stock","given":"Greg","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":479939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collins, Brian D.","contributorId":71641,"corporation":false,"usgs":true,"family":"Collins","given":"Brian D.","affiliations":[],"preferred":false,"id":479936,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Santaniello, David J.","contributorId":85070,"corporation":false,"usgs":true,"family":"Santaniello","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":479938,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmer, Valerie L.","contributorId":22661,"corporation":false,"usgs":true,"family":"Zimmer","given":"Valerie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":479935,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wieczorek, Gerald F.","contributorId":81889,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Gerald","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":479937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Snyder, James B.","contributorId":102137,"corporation":false,"usgs":true,"family":"Snyder","given":"James","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":479940,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70046445,"text":"70046445 - 2013 - Disproportionation and thermochemical sulfate reduction reactions in S-H20-Ch4 and S-D2O-CH4 systems from 200 to 340 °C at elevated pressures","interactions":[],"lastModifiedDate":"2013-07-01T10:06:44","indexId":"70046445","displayToPublicDate":"2013-06-12T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Disproportionation and thermochemical sulfate reduction reactions in S-H20-Ch4 and S-D2O-CH4 systems from 200 to 340 °C at elevated pressures","docAbstract":"Elemental sulfur, as a transient intermediate compound, by-product, or catalyst, plays significant roles in thermochemical sulfate reduction (TSR) reactions. However, the mechanisms of the reactions in S-H2O-hydrocarbons systems are not clear. To improve our understanding of reaction mechanisms, we conducted a series of experiments between 200 and 340 °C for S-H2O-CH4, S-D2O-CH4, and S-CH4-1m ZnBr2 systems in fused silica capillary capsules (FSCC). After a heating period ranging from 24 to 2160 hours (hrs), the quenched samples were analyzed by Raman spectroscopy. Combined with the in situ Raman spectra collected at high temperatures and pressures in the S-H2O and S-H2O-CH4 systems, our results showed that (1) the disproportionation of sulfur in the S-H2O-CH4 system occurred at temperatures above 200 °C and produced H2S, SO42-, and possibly trace amount of HSO4-; (2) sulfate (and bisulfate), in the presence of sulfur, can be reduced by methane between 250 and 340 °C to produce CO2 and H2S, and these TSR temperatures are much closer to those of the natural system (<200 °C) than those of any previous experiments; (3) the disproportionation and TSR reactions in the S-H2O-CH4 system may take place simultaneously, with TSR being favored at higher temperatures; and (4) in the system S-D2O-CH4, both TSR and the competitive disproportionation reactions occurred simultaneously at temperatures above 300 °C, but these reactions were very slow at lower temperatures. Our observation of methane reaction at 250 °C in a laboratory time scale suggests that, in a geologic time scale, methane may be destroyed by TSR reactions at temperatures > 200 °C that can be reached by deep drilling for hydrocarbon resources.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochimica et Cosmochimica Acta","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2013.05.021","usgsCitation":"Yuan, S., Chou, I., and Burruss, R.A., 2013, Disproportionation and thermochemical sulfate reduction reactions in S-H20-Ch4 and S-D2O-CH4 systems from 200 to 340 °C at elevated pressures: Geochimica et Cosmochimica Acta, v. 118, p. 263-275, https://doi.org/10.1016/j.gca.2013.05.021.","productDescription":"13 p.","startPage":"263","endPage":"275","ipdsId":"IP-037502","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":273643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273642,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.gca.2013.05.021"}],"volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b98a5ce4b07b9df6070f22","contributors":{"authors":[{"text":"Yuan, Shunda","contributorId":26608,"corporation":false,"usgs":true,"family":"Yuan","given":"Shunda","affiliations":[],"preferred":false,"id":479660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chou, I-Ming 0000-0001-5233-6479 imchou@usgs.gov","orcid":"https://orcid.org/0000-0001-5233-6479","contributorId":882,"corporation":false,"usgs":true,"family":"Chou","given":"I-Ming","email":"imchou@usgs.gov","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":479659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burruss, Robert A. 0000-0001-6827-804X burruss@usgs.gov","orcid":"https://orcid.org/0000-0001-6827-804X","contributorId":558,"corporation":false,"usgs":true,"family":"Burruss","given":"Robert","email":"burruss@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":479658,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046064,"text":"70046064 - 2013 - Coal resources, reserves and peak coal production in the United States","interactions":[],"lastModifiedDate":"2013-05-23T15:10:11","indexId":"70046064","displayToPublicDate":"2013-05-23T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Coal resources, reserves and peak coal production in the United States","docAbstract":"In spite of its large endowment of coal resources, recent studies have indicated that United States coal production is destined to reach a maximum and begin an irreversible decline sometime during the middle of the current century. However, studies and assessments illustrating coal reserve data essential for making accurate forecasts of United States coal production have not been compiled on a national basis. As a result, there is a great deal of uncertainty in the accuracy of the production forecasts. A very large percentage of the coal mined in the United States comes from a few large-scale mines (mega-mines) in the Powder River Basin of Wyoming and Montana. Reported reserves at these mines do not account for future potential reserves or for future development of technology that may make coal classified currently as resources into reserves in the future. In order to maintain United States coal production at or near current levels for an extended period of time, existing mines will eventually have to increase their recoverable reserves and/or new large-scale mines will have to be opened elsewhere. Accordingly, in order to facilitate energy planning for the United States, this paper suggests that probabilistic assessments of the remaining coal reserves in the country would improve long range forecasts of coal production. As it is in United States coal assessment projects currently being conducted, a major priority of probabilistic assessments would be to identify the numbers and sizes of remaining large blocks of coal capable of supporting large-scale mining operations for extended periods of time and to conduct economic evaluations of those resources.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Coal Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2012.10.002","usgsCitation":"Milici, R.C., Flores, R.M., and Stricker, G.D., 2013, Coal resources, reserves and peak coal production in the United States: International Journal of Coal Geology, v. 113, p. 109-115, https://doi.org/10.1016/j.coal.2012.10.002.","productDescription":"7 p.","startPage":"109","endPage":"115","ipdsId":"IP-027301","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":272765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272764,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.coal.2012.10.002"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,19.0 ], [ 172.5,71.4 ], [ -67.0,71.4 ], [ -67.0,19.0 ], [ 172.5,19.0 ] ] ] } } ] }","volume":"113","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"519f2c5be4b0687ba0506b5a","contributors":{"authors":[{"text":"Milici, Robert C. rmilici@usgs.gov","contributorId":563,"corporation":false,"usgs":true,"family":"Milici","given":"Robert","email":"rmilici@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":478802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flores, Romeo M. rflores@usgs.gov","contributorId":71984,"corporation":false,"usgs":true,"family":"Flores","given":"Romeo","email":"rflores@usgs.gov","middleInitial":"M.","affiliations":[{"id":165,"text":"Central Energy Resources Team","active":false,"usgs":true}],"preferred":false,"id":478803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stricker, Gary D. gstricker@usgs.gov","contributorId":87163,"corporation":false,"usgs":true,"family":"Stricker","given":"Gary","email":"gstricker@usgs.gov","middleInitial":"D.","affiliations":[{"id":165,"text":"Central Energy Resources Team","active":false,"usgs":true}],"preferred":false,"id":478804,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045736,"text":"sir20135045 - 2013 - Investigations of groundwater system and simulation of regional groundwater flow for North Penn Area 7 Superfund site, Montgomery County, Pennsylvania","interactions":[],"lastModifiedDate":"2015-05-01T08:11:34","indexId":"sir20135045","displayToPublicDate":"2013-05-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5045","title":"Investigations of groundwater system and simulation of regional groundwater flow for North Penn Area 7 Superfund site, Montgomery County, Pennsylvania","docAbstract":"Groundwater in the vicinity of several industrial facilities in Upper Gwynedd Township and vicinity, Montgomery County, in southeast Pennsylvania has been shown to be contaminated with volatile organic compounds (VOCs), the most common of which is the solvent trichloroethylene (TCE). The 2-square-mile area was placed on the National Priorities List as the North Penn Area 7 Superfund site by the U.S. Environmental Protection Agency (USEPA) in 1989. The U.S. Geological Survey (USGS) conducted geophysical logging, aquifer testing, and water-level monitoring, and measured streamflows in and near North Penn Area 7 from fall 2000 through fall 2006 in a technical assistance study for the USEPA to develop an understanding of the hydrogeologic framework in the area as part of the USEPA Remedial Investigation. In addition, the USGS developed a groundwater-flow computer model based on the hydrogeologic framework to simulate regional groundwater flow and to estimate directions of groundwater flow and pathways of groundwater contaminants. The study area is underlain by Triassic- and Jurassic-age sandstones and shales of the Lockatong Formation and Brunswick Group in the Mesozoic Newark Basin. Regionally, these rocks strike northeast and dip to the northwest. The sequence of rocks form a fractured-sedimentary-rock aquifer that acts as a set of confined to partially confined layers of differing permeabilities. Depth to competent bedrock typically is less than 20 ft below land surface. The aquifer layers are recharged locally by precipitation and discharge locally to streams. The general configuration of the potentiometric surface in the aquifer is similar to topography, except in areas affected by pumping. The headwaters of Wissahickon Creek are nearby, and the stream flows southwest, parallel to strike, to bisect North Penn Area 7. Groundwater is pumped in the vicinity of North Penn Area 7 for industrial use, public supply, and residential supply. Results of field investigations by USGS at the site and results from other studies support, and are consistent with, a conceptual model of a layered leaky aquifer where the dip of the beds has a strong control on hydraulic connections in the groundwater system. Connections within and (or) parallel to bedding tend to be greater than across bedding. Transmissivities of aquifer intervals isolated by packers ranged over three orders of magnitude [from about 2.8 to 2,290 square feet per day (ft2/d) or 0.26 to 213 square meters per day (m2/d)], did not appear to differ much by mapped geologic unit, but showed some relation to depth being relatively smaller in the shallowest and deepest intervals (0 to 50 ft and more than 250 ft below land surface, respectively) compared to the intermediate depth intervals (50 to 250 ft below land surface) tested. Transmissivities estimated from multiple-observation well aquifer tests ranged from about 700 to 2,300 ft2/d (65 to 214 m2/d). Results of chemical analyses of water from isolated intervals or monitoring wells open to short sections of the aquifer show vertical differences in concentrations; chloride and silica concentrations generally were greater in shallow intervals than in deeper intervals. Chloride concentrations greater than 100 milligrams per liter (mg/L), combined with distinctive chloride/bromide ratios, indicate a different source of chloride in the western part of North Penn Area 7 than elsewhere in the site. Groundwater flow at a regional scale under steady-state conditions was simulated by use of a numerical model (MODFLOW-2000) for North Penn Area 7 with different layers representing saprolite/highly weathered rock near the surface and unweathered competent bedrock. The sedimentary formations that underlie the study area were modeled using dipping model layers for intermediate and deep zones of unweathered, fractured rock. Horizontal cell model size was 100 meters (m) by 100 meters (328 ft by 328 ft), and model layer thickness ranged from 6 m (19.7 ft) representing shallow weathered rock and saprolite up to 200 m (656 ft) representing deeper dipping bedrock. The model did not include detailed structure to account for local-scale differences in hydraulic properties, with the result that local-scale groundwater flow may not be well simulated. Additional detailed multi-well aquifer tests would be needed to establish the extent of interconnection between intervals at the local scale to address remediation of contamination at each source area. This regional groundwater-flow model was calibrated against measured groundwater levels (1996, 2000, and 2005) and base flow estimated from selected streamflow measurements by use of nonlinear-regression parameter-estimation algorithms to determine hydraulic conductivity and anisotropy of hydraulic conductivity, streambed hydraulic conductivity, and recharge during calibration periods. Results of the simulation using the calibrated regional model indicate that the aquifer appears to be anisotropic where hydraulic conductivity is greatest parallel to the orientation of bedding of the formations underlying the area and least in the cross-bed direction. The maximum hydraulic conductivity is aligned with the average regional strike of the formations, which is “subhorizontal” in the model because the altitudes of the beds and model cells vary in the strike, as well as dip, direction. Estimated subhorizontal hydraulic conductivities (in strike direction parallel to dipping beds) range from 0.001 to 1.67 meters per day (0.0032 to 5.5 feet per day). The ratio of minimum (dip direction) to maximum (strike direction) subhorizontal hydraulic conductivity ranges from 1/3.1 to 1/8.6, and the ratio of vertical to horizontal hydraulic conductivity ranges from 1/1 to 1/478. However, limited available field data precluded rigorous calibration of vertical anisotropy in the model. Estimated recharge rates corresponding to calibration periods in 1996, 2000, and 2005 are 150, 109, and 124 millimeters per year (5.9, 4.3, and 4.9 inches per year), respectively. The calibrated groundwater-flow model was used to simulate groundwater flow under steady-state conditions during periods of relatively high withdrawals (pumpage) (1990) and relatively low withdrawals (2000 and 2005). Groundwater-flow paths originating from recharge areas near known areas of soil contamination (sources) were simulated. Pumped industrial and production wells captured more groundwater from several of these sources during 1990 than after 1990 when pumping declined or ceased and greater amounts of contaminated groundwater moved away from North Penn Area 7 Superfund site to surrounding areas. Uncertainty in simulated groundwater-flow paths from contaminant sources and contributing areas, resulting from uncertainty in estimated hydraulic properties of the model, was illustrated through Monte Carlo simulations. The effect of uncertainty in the vertical anisotropy was not included in the Monte Carlo simulations. Contributing areas indicating the general configuration of groundwater flow towards production well MG-202 (L-22) in the study area also were simulated for the different time periods; as simulated, the flow paths do not pass through any identified contaminant source in North Penn Area 7. However, contributing areas to wells, such as MG-202, located near many pumped wells are particularly complex and, in some cases, include areas that contribute flow to streams that subsequently recharge the aquifer through stream loss. In these cases, water-quality constituents, including contaminants that are present in surface water may be drawn into the aquifer to nearby pumped wells. Results of a simulated shutdown of well MG-202 under steady-state 2005 conditions showed that the area contributing recharge for nearby production well MG-76 (L-17), when MG-202 is not pumping, shifts downstream and is similar to the area contributing recharge for MG-202 when both wells are pumping. Concentrations of constituents in groundwater samples collected in fall 2005 or spring 2006 were compared to simulated groundwater-flow paths for the year 2005 to provide a qualitative assessment of model results. The observed spatial distribution of selected constituents, including TCE, CFC-11, and CFC-113 in groundwater in 2005 and the chloride/bromide mass ratios in 2006, generally were consistent with the model results of the simulated 2005 groundwater-flow paths at North Penn Area 7, indicating the presence of several separate sources of contaminants within North Penn Area 7.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135045","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Senior, L.A., and Goode, D., 2013, Investigations of groundwater system and simulation of regional groundwater flow for North Penn Area 7 Superfund site, Montgomery County, Pennsylvania (Version 1: Originally posted April 30, 2013; Version 1.1: April 30, 2015): U.S. Geological Survey Scientific Investigations Report 2013-5045, xii, 95 p., https://doi.org/10.3133/sir20135045.","productDescription":"xii, 95 p.","numberOfPages":"112","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1990-01-01","temporalEnd":"2006-07-01","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":300001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135045.jpg"},{"id":271689,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5045/"},{"id":271690,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5045/support/sir2013-5045.pdf","text":"Report","size":"14.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"scale":"24000","projection":"Universal Transverse Mercator, Zone 18","datum":"North American Datum of 1927","country":"United States","state":"Pennsylvania","county":"Montgomery","city":"Upper Gwynedd","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.33050537109375,\n 40.17939793281656\n ],\n [\n -75.33050537109375,\n 40.23079086353824\n ],\n [\n -75.23162841796875,\n 40.23079086353824\n ],\n [\n -75.23162841796875,\n 40.17939793281656\n ],\n [\n -75.33050537109375,\n 40.17939793281656\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1: Originally posted April 30, 2013; Version 1.1: April 30, 2015","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5543522ee4b0a658d79414af","contributors":{"authors":[{"text":"Senior, Lisa A. 0000-0003-2629-1996 lasenior@usgs.gov","orcid":"https://orcid.org/0000-0003-2629-1996","contributorId":2150,"corporation":false,"usgs":true,"family":"Senior","given":"Lisa","email":"lasenior@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goode, Daniel J. 0000-0002-8527-2456 djgoode@usgs.gov","orcid":"https://orcid.org/0000-0002-8527-2456","contributorId":2433,"corporation":false,"usgs":true,"family":"Goode","given":"Daniel J.","email":"djgoode@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478214,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045697,"text":"sir20135042 - 2013 - Simulation of groundwater flow, effects of artificial recharge, and storage volume changes in the Equus Beds aquifer near the city of Wichita, Kansas well field, 1935–2008","interactions":[],"lastModifiedDate":"2013-04-30T10:39:05","indexId":"sir20135042","displayToPublicDate":"2013-04-30T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5042","title":"Simulation of groundwater flow, effects of artificial recharge, and storage volume changes in the Equus Beds aquifer near the city of Wichita, Kansas well field, 1935–2008","docAbstract":"The Equus Beds aquifer is a primary water-supply source for Wichita, Kansas and the surrounding area because of shallow depth to water, large saturated thickness, and generally good water quality. Substantial water-level declines in the Equus Beds aquifer have resulted from pumping groundwater for agricultural and municipal needs, as well as periodic drought conditions. In March 2006, the city of Wichita began construction of the Equus Beds Aquifer Storage and Recovery project to store and later recover groundwater, and to form a hydraulic barrier to the known chloride-brine plume near Burrton, Kansas. In October 2009, the U.S. Geological Survey, in cooperation with the city of Wichita, began a study to determine groundwater flow in the area of the Wichita well field, and chloride transport from the Arkansas River and Burrton oilfield to the Wichita well field. Groundwater flow was simulated for the Equus Beds aquifer using the three-dimensional finite-difference groundwater-flow model MODFLOW-2000. The model simulates steady-state and transient conditions. The groundwater-flow model was calibrated by adjusting model input data and model geometry until model results matched field observations within an acceptable level of accuracy. The root mean square (RMS) error for water-level observations for the steady-state calibration simulation is 9.82 feet. The ratio of the RMS error to the total head loss in the model area is 0.049 and the mean error for water-level observations is 3.86 feet. The difference between flow into the model and flow out of the model across all model boundaries is -0.08 percent of total flow for the steady-state calibration. The RMS error for water-level observations for the transient calibration simulation is 2.48 feet, the ratio of the RMS error to the total head loss in the model area is 0.0124, and the mean error for water-level observations is 0.03 feet. The RMS error calculated for observed and simulated base flow gains or losses for the Arkansas River for the transient simulation is 7,916,564 cubic feet per day (91.6 cubic feet per second) and the RMS error divided by (/) the total range in streamflow (7,916,564/37,461,669 cubic feet per day) is 22 percent. The RMS error calculated for observed and simulated streamflow gains or losses for the Little Arkansas River for the transient simulation is 5,610,089 cubic feet per day(64.9 cubic feet per second) and the RMS error divided by the total range in streamflow (5,612,918/41,791,091 cubic feet per day) is 13 percent. The mean error between observed and simulated base flow gains or losses was 29,999 cubic feet per day (0.34 cubic feet per second) for the Arkansas River and -1,369,250 cubic feet per day (-15.8 cubic feet per second) for the Little Arkansas River. Cumulative streamflow gain and loss observations are similar to the cumulative simulated equivalents. Average percent mass balance difference for individual stress periods ranged from -0.46 to 0.51 percent. The cumulative mass balance for the transient calibration was 0.01 percent. Composite scaled sensitivities indicate the simulations are most sensitive to parameters with a large areal distribution. For the steady-state calibration, these parameters include recharge, hydraulic conductivity, and vertical conductance. For the transient simulation, these parameters include evapotranspiration, recharge, and hydraulic conductivity. The ability of the calibrated model to account for the additional groundwater recharged to the Equus Beds aquifer as part of the Aquifer Storage and Recovery project was assessed by using the U.S. Geological Survey subregional water budget program ZONEBUDGET and comparing those results to metered recharge for 2007 and 2008 and previous estimates of artificial recharge. The change in storage between simulations is the volume of water that estimates the recharge credit for the aquifer storage and recovery system. The estimated increase in storage of 1,607 acre-ft in the basin storage area compared to metered recharge of 1,796 acre-ft indicates some loss of metered recharge. Increased storage outside of the basin storage area of 183 acre-ft accounts for all but 6 acre-ft or 0.33 percent of the total. Previously estimated recharge credits for 2007 and 2008 are 1,018 and 600 acre-ft, respectively, and a total estimated recharge credit of 1,618 acre-ft. Storage changes calculated for this study are 4.42 percent less for 2007 and 5.67 percent more for 2008 than previous estimates. Total storage change for 2007 and 2008 is 0.68 percent less than previous estimates. The small difference between the increase in storage from artificial recharge estimated with the groundwater-flow model and metered recharge indicates the groundwater model correctly accounts for the additional water recharged to the Equus Beds aquifer as part of the Aquifer Storage and Recovery project. Small percent differences between inflows and outflows for all stress periods and all index cells in the basin storage area, improved calibration compared to the previous model, and a reasonable match between simulated and measured long-term base flow indicates the groundwater model accurately simulates groundwater flow in the study area. The change in groundwater level through recent years compared to the August 1940 groundwater level map has been documented and used to assess the change of storage volume of the Equus Beds aquifer in and near the Wichita well field for three different areas. Two methods were used to estimate changes in storage from simulation results using simulated change in groundwater levels in layer 1 between stress periods, and using ZONEBUDGET to calculate the change in storage in the same way the effects of artificial recharge were estimated within the basin storage area. The three methods indicate similar trends although the magnitude of storage changes differ. Information about the change in storage in response to hydrologic stresses is important for managing groundwater resources in the study area. The comparison between the three methods indicates similar storage change trends are estimated and each could be used to determine relative increases or decreases in storage. Use of groundwater level changes that do not include storage changes that occur in confined or semi-confined parts of the aquifer will slightly underestimate storage changes; however, use of specific yield and groundwater level changes to estimate storage change in confined or semi-confined parts of the aquifer will overestimate storage changes. Using only changes in shallow groundwater levels would provide more accurate storage change estimates for the measured groundwater levels method. The value used for specific yield is also an important consideration when estimating storage. For the Equus Beds aquifer the reported specific yield ranges between 0.08 and 0.35 and the storage coefficient (for confined conditions) ranges between 0.0004 and 0.16. Considering the importance of the value of specific yield and storage coefficient to estimates of storage change over time, and the wide range and substantial overlap for the reported values for specific yield and storage coefficient in the study area, further information on the distribution of specific yield and storage coefficient within the Equus Beds aquifer in the study area would greatly enhance the accuracy of estimated storage changes using both simulated groundwater level, simulated groundwater budget, or measured groundwater level methods.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135042","collaboration":"Prepared in cooperation with the city of Wichita, Kansas, as part of the Equus Beds Groundwater Recharge Project","usgsCitation":"Kelly, B.P., Pickett, L.L., Hansen, C.V., and Ziegler, A., 2013, Simulation of groundwater flow, effects of artificial recharge, and storage volume changes in the Equus Beds aquifer near the city of Wichita, Kansas well field, 1935–2008: U.S. Geological Survey Scientific Investigations Report 2013-5042, Report: viii, 92 p.; Downloads Directory, https://doi.org/10.3133/sir20135042.","productDescription":"Report: viii, 92 p.; Downloads Directory","numberOfPages":"102","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-042806","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":271633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/SIR20135042.gif"},{"id":271632,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5042/downloads/"},{"id":271630,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5042/"},{"id":271631,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5042/sir2013-5042.pdf"}],"country":"United States","state":"Kansas","city":"Wichita","otherGeospatial":"Equus Beds Aquifer","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.3,37.6 ], [ -98.3,38.05 ], [ -97.16,38.05 ], [ -97.16,37.6 ], [ -98.3,37.6 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5180d9dce4b0df838b924d35","contributors":{"authors":[{"text":"Kelly, Brian P. 0000-0001-6378-2837 bkelly@usgs.gov","orcid":"https://orcid.org/0000-0001-6378-2837","contributorId":897,"corporation":false,"usgs":true,"family":"Kelly","given":"Brian","email":"bkelly@usgs.gov","middleInitial":"P.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":478069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pickett, Linda L.","contributorId":108377,"corporation":false,"usgs":true,"family":"Pickett","given":"Linda","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":478070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Cristi V. chansen@usgs.gov","contributorId":435,"corporation":false,"usgs":true,"family":"Hansen","given":"Cristi","email":"chansen@usgs.gov","middleInitial":"V.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":478068,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ziegler, Andrew C. aziegler@usgs.gov","contributorId":433,"corporation":false,"usgs":true,"family":"Ziegler","given":"Andrew C.","email":"aziegler@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":478067,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045073,"text":"sir20135049 - 2013 - Shallow groundwater in the Matanuska-Susitna Valley, Alaska—Conceptualization and simulation of flow","interactions":[],"lastModifiedDate":"2018-07-18T13:50:39","indexId":"sir20135049","displayToPublicDate":"2013-03-29T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5049","title":"Shallow groundwater in the Matanuska-Susitna Valley, Alaska—Conceptualization and simulation of flow","docAbstract":"The Matanuska-Susitna Valley is in the Upper Cook Inlet Basin and is currently undergoing rapid population growth outside of municipal water and sewer service areas. In response to concerns about the effects of increasing water use on future groundwater availability, a study was initiated between the Alaska Department of Natural Resources and the U.S. Geological Survey. The goals of the study were (1) to compile existing data and collect new data to support hydrogeologic conceptualization of the study area, and (2) to develop a groundwater flow model to simulate flow dynamics important at the regional scale. The purpose of the groundwater flow model is to provide a scientific framework for analysis of regional-scale groundwater availability. To address the first study goal, subsurface lithologic data were compiled into a database and were used to construct a regional hydrogeologic framework model describing the extent and thickness of hydrogeologic units in the Matanuska-Susitna Valley. The hydrogeologic framework model synthesizes existing maps of surficial geology and conceptual geochronologies developed in the study area with the distribution of lithologies encountered in hundreds of boreholes. The geologic modeling package Geological Surveying and Investigation in Three Dimensions (GSI3D) was used to construct the hydrogeologic framework model. In addition to characterizing the hydrogeologic framework, major groundwater-budget components were quantified using several different techniques. A land-surface model known as the Deep Percolation Model was used to estimate in-place groundwater recharge across the study area. This model incorporates data on topography, soils, vegetation, and climate. Model-simulated surface runoff was consistent with observed streamflow at U.S. Geological Survey streamgages. Groundwater withdrawals were estimated on the basis of records from major water suppliers during 2004-2010. Fluxes between groundwater and surface water were estimated during field investigations on several small streams. Regional groundwater flow patterns were characterized by synthesizing previous water-table maps with a synoptic water-level measurement conducted during 2009. Time-series water-level data were collected at groundwater and lake monitoring stations over the study period (2009–present). Comparison of historical groundwater-level records with time-series groundwater-level data collected during this study showed similar patterns in groundwater-level fluctuation in response to precipitation. Groundwater-age data collected during previous studies show that water moves quickly through the groundwater system, suggesting that the system responds quickly to changes in climate forcing. Similarly, the groundwater system quickly returns to long-term average conditions following variability due to seasonal or interannual changes in precipitation. These analyses indicate that the groundwater system is in a state of dynamic equilibrium, characterized by water-level fluctuation about a constant average state, with no long-term trends in aquifer-system storage. To address the second study goal, a steady-state groundwater flow model was developed to simulate regional groundwater flow patterns. The groundwater flow model was bounded by physically meaningful hydrologic features, and appropriate internal model boundaries were specified on the basis of conceptualization of the groundwater system resulting in a three-layer model. Calibration data included 173 water‑level measurements and 18 measurements of streamflow gains and losses along small streams. Comparison of simulated and observed heads and flows showed that the model accurately simulates important regional characteristics of the groundwater flow system. This model is therefore appropriate for studying regional-scale groundwater availability. Mismatch between model-simulated and observed hydrologic quantities is likely because of the coarse grid size of the model and seasonal transient effects. Next steps towards model refinement include the development of a transient groundwater flow model that is suitable for analysis of seasonal variability in hydraulic heads and flows. In addition, several important groundwater budget components remain poorly quantified—including groundwater outflow to the Matanuska River, Little Susitna River, and Knik Arm.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135049","collaboration":"Prepared in cooperation with the Alaska Department of Natural Resources","usgsCitation":"Kikuchi, C.P., 2013, Shallow groundwater in the Matanuska-Susitna Valley, Alaska—Conceptualization and simulation of flow: U.S. Geological Survey Scientific Investigations Report 2013-5049, Report: viii, 86 p.; 4 Appendices, https://doi.org/10.3133/sir20135049.","productDescription":"Report: viii, 86 p.; 4 Appendices","numberOfPages":"96","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":270376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135049.jpg"},{"id":270372,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5049/sir20135049_appendixA.xlsx"},{"id":270373,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5049/sir20135049_appendixB.xlsx"},{"id":270374,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5049/sir20135049_appendixC.xlsx"},{"id":270375,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5049/sir20135049_appendixD.xlsx"},{"id":270370,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5049/"},{"id":270371,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5049/pdf/sir20135049.pdf"}],"country":"United States","state":"Alaska","otherGeospatial":"Matanuska-susitna Valley","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5156a9e9e4b06ea905cdbff6","contributors":{"authors":[{"text":"Kikuchi, Colin P.","contributorId":61311,"corporation":false,"usgs":true,"family":"Kikuchi","given":"Colin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":476735,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70188514,"text":"70188514 - 2013 - Lateglacial and Holocene climate, disturbance and permafrost peatland dynamics on the Seward Peninsula, western Alaska","interactions":[],"lastModifiedDate":"2017-06-14T13:36:29","indexId":"70188514","displayToPublicDate":"2013-03-20T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Lateglacial and Holocene climate, disturbance and permafrost peatland dynamics on the Seward Peninsula, western Alaska","docAbstract":"Northern peatlands have accumulated large carbon (C) stocks, acting as a long-term atmospheric C sink since the last deglaciation. How these C-rich ecosystems will respond to future climate change, however, is still poorly understood. Furthermore, many northern peatlands exist in regions underlain by permafrost, adding to the challenge of projecting C balance under changing climate and permafrost dynamics. In this study, we used a paleoecological approach to examine the effect of past climates and local disturbances on vegetation and C accumulation at a peatland complex on the southern Seward Peninsula, Alaska over the past ∼15 ka (1 ka = 1000 cal yr BP). We analyzed two cores about 30 m apart, NL10-1 (from a permafrost peat plateau) and NL10-2 (from an adjacent thermokarst collapse-scar bog), for peat organic matter (OM), C accumulation rates, macrofossil, pollen and grain size analysis.
A wet rich fen occurred during the initial stages of peatland development at the thermokarst site (NL10-2). The presence of tree pollen from Picea spp. and Larix laricinia at 13.5–12.1 ka indicates a warm regional climate, corresponding with the well-documented Bølling–Allerød warm period. A cold and dry climate interval at 12.1–11.1 ka is indicated by the disappearance of tree pollen and increase in Poaceae pollen and an increase in woody material, likely representing a local expression of the Younger Dryas (YD) event. Following the YD, the warm Holocene Thermal Maximum (HTM) is characterized by the presence of Populus pollen, while the presence of Sphagnum spp. and increased C accumulation rates suggest high peatland productivity under a warm climate. Toward the end of the HTM and throughout the mid-Holocene a wet climate-induced several major flooding disturbance events at 10 ka, 8.1 ka, 6 ka, 5.4 ka and 4.7 ka, as evidenced by decreases in OM, and increases in coarse sand abundance and aquatic fossils (algae Chara and water fleas Daphnia). The initial peatland at permafrost site (NL10-1) is characterized by rapid C accumulation (66 g C m−2 yr−1), high OM content and a peak in Sphagnum spp. at 5.8–4.6 ka, suggesting the lack of permafrost. A transition to extremely low C accumulation rates of 6.3 g C m−2 yr−1 after 4.5 ka at this site suggests the onset of permafrost aggradation, likely in response to Neoglacial climate cooling as documented across the circum-Arctic region. A similar decrease in C accumulation rates also occurred at non-permafrost site NL10-2. Time-weighted C accumulation rates are 21.8 g C m−2 yr−1 for core NL10-1 during the last ∼6.5 ka and 14.8 g C m−2 yr−1 for core NL10-2 during the last ∼15 ka. Evidence from peat-core analysis and historical aerial photographs shows an abrupt increase in Sphagnum spp. and decrease in area of thermokarst lakes over the last century, suggesting major changes in hydrology and ecosystem structure, likely due to recent climate warming.
Our results show that the thermokarst–permafrost complex was much more dynamic with high C accumulation rates under warmer climates in the past, while permafrost was stabilized and C accumulation slowed down following the Neoglacial cooling in the late Holocene. Furthermore, permafrost presence at local scales is controlled by both regional climate and site-specific factors, highlighting the challenge in projecting responses of permafrost peatlands and their C dynamics to future climate change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2012.11.019","usgsCitation":"Hunt, S.D., Yu, Z., and Jones, M.C., 2013, Lateglacial and Holocene climate, disturbance and permafrost peatland dynamics on the Seward Peninsula, western Alaska: Quaternary Science Reviews, v. 63, p. 42-58, https://doi.org/10.1016/j.quascirev.2012.11.019.","productDescription":"16 p.","startPage":"42","endPage":"58","ipdsId":"IP-042048","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342495,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska ","otherGeospatial":"Seward Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -163.47381591796875,\n 64.66225203688786\n ],\n [\n -163.41699600219727,\n 64.66225203688786\n ],\n [\n -163.41699600219727,\n 64.68105206571617\n ],\n [\n -163.47381591796875,\n 64.68105206571617\n ],\n [\n -163.47381591796875,\n 64.66225203688786\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"63","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59424b3ce4b0764e6c65dc6b","contributors":{"authors":[{"text":"Hunt, Stephanie D.","contributorId":58532,"corporation":false,"usgs":true,"family":"Hunt","given":"Stephanie","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":698173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yu, Zicheng 0000-0003-2358-2712","orcid":"https://orcid.org/0000-0003-2358-2712","contributorId":147521,"corporation":false,"usgs":false,"family":"Yu","given":"Zicheng","email":"","affiliations":[{"id":16857,"text":"Lehigh Univ.","active":true,"usgs":false}],"preferred":false,"id":698174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Miriam C. 0000-0002-6650-7619 miriamjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":4056,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"miriamjones@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":698109,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042497,"text":"sir20125265 - 2013 - Summary and interpretation of discrete and continuous water-quality monitoring data, Mattawoman Creek, Charles County, Maryland, 2000-11","interactions":[],"lastModifiedDate":"2023-03-10T12:37:02.469065","indexId":"sir20125265","displayToPublicDate":"2013-01-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5265","title":"Summary and interpretation of discrete and continuous water-quality monitoring data, Mattawoman Creek, Charles County, Maryland, 2000-11","docAbstract":"Discrete samples and continuous (15-minute interval) water-quality data were collected at Mattawoman Creek (U.S. Geological Survey station number 01658000) from October 2000 through January 2011, in cooperation with the Charles County (Maryland) Department of Planning and Growth Management, the Maryland Department of the Environment, and the Maryland Geological Survey. Mattawoman Creek is a fourth-order Maryland tributary to the tidal freshwater Potomac River; the creek’s watershed is experiencing development pressure due to its proximity to Washington, D.C. Data were analyzed for the purpose of describing ambient water quality, identifying potential contaminant sources, and quantifying nutrient and sediment loads to the tidal freshwater Mattawoman estuary. Continuous data, collected at 15-minute intervals, included discharge, derived from stage measurements made using a pressure transducer, as well as water temperature, pH, specific conductance, dissolved oxygen, and turbidity, all measured using a water-quality sonde. In addition to the continuous data, a total of 360 discrete water-quality samples, representative of monthly low-flow and targeted storm conditions, were analyzed for suspended sediment and nutrients. Continuous observations gathered by a second water-quality sonde, which was temporarily deployed in 2011 for quality-control purposes, indicated substantial lateral water-quality gradients due to inflow from a nearby tributary, representing about 10 percent of the total gaged area upstream of the sampling location. These lateral gradients introduced a time-varying bias into both the continuous and discrete data, resulting in observations that were at some times representative of water-quality conditions in the main channel and at other times biased towards conditions in the tributary. Despite this limitation, both the continuous and discrete data provided insight into the watershed-scale factors that influence water quality in Mattawoman Creek. Annual precipitation over the study period was representative of the long-term record for southern Maryland. The median value of continuously measured discharge was 25 cubic feet per second (ft3/s), and the maximum observed value was 3,210 ft3/s; there were 498 days, or about 15 percent of the study period, when flow was zero or too low to measure. Continuously measured water temperature followed a seasonal trend characteristic of the geographic setting; the trend in dissolved oxygen was inverted relative to temperature, and reflected nearly saturated conditions year round. Relations between discharge and both pH and specific conductance indicate that stream water can be conceptualized as a mixture of acidic, dilute precipitation with pH-neutral groundwater of higher conductance. Specific conductance data showed a pronounced winter peak in both median and extreme measurements, indicating the influence of road salt. However, this influence is minor relative to that observed in the Northeast Branch Anacostia River (U.S. Geological Survey station number 01649500), a nearby, more heavily urbanized comparison basin. The median suspended-sediment concentration in discrete samples was 24 milligrams per liter (mg/L), with minimum and maximum concentrations of 1 mg/L and 2,890 mg/L, respectively. Total nitrogen ranged from 0.21 mg/L to 4.09 mg/L, with a median of 0.69 mg/L; total phosphorus ranged from less than 0.01 mg/L to 0.98 mg/L, with a median of 0.07 mg/L. Total nitrogen was dominated by the dissolved organic fraction (49 percent based on median species concentrations); total phosphorus was predominantly particulate (70 percent). Seasonal trends in suspended-sediment concentration indicate a supply subsidy in late winter and spring; this could be linked to flood-plain interaction, mobilization of sediment from the channel or banks, or anthropogenic input. Seasonal trends for both total phosphorus and total nitrogen generally corresponded to seasonal trends for suspended sediment, indicating a common underlying physical control, likely acting in synchrony with seasonal biological controls on total nutrient concentrations. Speciation of phosphorus, including proportional concentration of the biologically available dissolved inorganic fraction, did not vary seasonally. The speciation of nitrogen reflected demand for inorganic nitrogen and associated transformation into organic nitrogen during the growing season. Stepwise regression models were developed, using continuous data corresponding to collection times for discrete samples as candidate surrogates for suspended sediment, total phosphorus, and total nitrogen. Turbidity and discharge were both included in the model for suspended sediment (R2 = 0.76, n = 185); only turbidity was selected as a robust predictor of total phosphorus and nitrogen (R2 = 0.68 and 0.61, respectively, n = 186 for both). Loads of sediment and nutrients to the downstream Mattawoman estuary were computed using the U.S. Geological Survey computer program LOADEST. Load estimation included comparison of a routinely applied seven-parameter regression model based on time, season, and discharge, with an eight-parameter model that also includes turbidity. Adding turbidity decreased total load estimates, based on hourly data for a fixed 2-month period, by 21, 8, and 3 percent for suspended sediment, total phosphorus, and total nitrogen, respectively, in addition to decreasing the standard error of prediction for all three constituents. The seasonal pattern in specific conductance, reflecting road salt application, is the strongest evidence of the effect of upstream development on water quality at Mattawoman Creek. Accordingly, ongoing continuous monitoring for trends in specific conductance would be the most reliable means of detecting further degradation associated with increased development.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125265","collaboration":"Prepared in cooperation with the Charles County Department of Planning and Growth Management; Maryland Department of the Environment; Maryland Geological Survey","usgsCitation":"Chanat, J.G., Miller, C.V., Bell, J.M., Majedi, B.F., and Brower, D.P., 2013, Summary and interpretation of discrete and continuous water-quality monitoring data, Mattawoman Creek, Charles County, Maryland, 2000-11: U.S. Geological Survey Scientific Investigations Report 2012-5265, vii, 42 p., https://doi.org/10.3133/sir20125265.","productDescription":"vii, 42 p.","startPage":"i","endPage":"42","numberOfPages":"54","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2000-10-01","temporalEnd":"2011-01-31","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":265497,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5265.gif"},{"id":265498,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5265/"},{"id":265499,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5265/pdf/sir2012-5265.pdf"}],"state":"Maryl","city":"Charles County","otherGeospatial":"Mattawoman Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.3155,38.1713 ], [ -77.3155,38.7047 ], [ -76.6719,38.7047 ], [ -76.6719,38.1713 ], [ -77.3155,38.1713 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ee9177e4b0160a2d0ee34b","contributors":{"authors":[{"text":"Chanat, Jeffrey G. 0000-0002-3629-7307 jchanat@usgs.gov","orcid":"https://orcid.org/0000-0002-3629-7307","contributorId":5062,"corporation":false,"usgs":true,"family":"Chanat","given":"Jeffrey","email":"jchanat@usgs.gov","middleInitial":"G.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Cherie V. 0000-0001-7765-5919 cvmiller@usgs.gov","orcid":"https://orcid.org/0000-0001-7765-5919","contributorId":863,"corporation":false,"usgs":true,"family":"Miller","given":"Cherie","email":"cvmiller@usgs.gov","middleInitial":"V.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":471651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bell, Joseph M. 0000-0002-2536-2070 jmbell@usgs.gov","orcid":"https://orcid.org/0000-0002-2536-2070","contributorId":5063,"corporation":false,"usgs":true,"family":"Bell","given":"Joseph","email":"jmbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":471654,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Majedi, Brenda Feit","contributorId":81361,"corporation":false,"usgs":true,"family":"Majedi","given":"Brenda","email":"","middleInitial":"Feit","affiliations":[],"preferred":false,"id":471655,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brower, David P. dpbrower@usgs.gov","contributorId":5061,"corporation":false,"usgs":true,"family":"Brower","given":"David","email":"dpbrower@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":471652,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70041357,"text":"70041357 - 2013 - Spatial and temporal variations in landscape evolution: historic and longer-term sediment flux through global catchments","interactions":[],"lastModifiedDate":"2013-11-14T11:53:24","indexId":"70041357","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3566,"text":"The Journal of Geology","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal variations in landscape evolution: historic and longer-term sediment flux through global catchments","docAbstract":"Sediment generation and transport through terrestrial catchments influence soil distribution, geochemical cycling of particulate and dissolved loads, and the character of the stratigraphic record of Earth history. To assess the spatiotemporal variation in landscape evolution, we compare global compilations of stream gauge–derived () and cosmogenic radionuclide (CRN)–derived (predominantly 10Be; ) denudation of catchments (mm/yr) and sediment load of rivers (Mt/yr). Stream gauges measure suspended sediment loads of rivers during several to tens of years, whereas CRNs provide catchment-integrated denudation rates at 102–105-yr time scales. Stream gauge–derived and CRN-derived sediment loads in close proximity to one another (<500 km) exhibit broad similarity ( stream gauge samples; CRN samples). Nearly two-thirds of CRN-derived sediment loads exceed historic loads measured at the same locations (). Excessive longer-term sediment loads likely are a result of longer-term recurrence of large-magnitude sediment-transport events. Nearly 80% of sediment loads measured at approximately the same locations exhibit stream gauge loads that are within an order of magnitude of CRN loads, likely as a result of the buffering capacity of large flood plains. Catchments in which space for deposition exceeds sediment supply have greater buffering capacity. Superior locations in which to evaluate anthropogenic influences on landscape evolution might be buffered catchments, in which temporary storage of sediment in flood plains can provide stream gauge–based sediment loads and denudation rates that are applicable over longer periods than the durations of gauge measurements. The buffering capacity of catchments also has implications for interpreting the stratigraphic record; delayed sediment transfer might complicate the stratigraphic record of external forcings and catchment modification.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Journal of Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The University of Chicago Press","doi":"10.1086/668680","usgsCitation":"Covault, J.A., Craddock, W.H., Romans, B.W., Fildani, A., and Gosai, M., 2013, Spatial and temporal variations in landscape evolution: historic and longer-term sediment flux through global catchments: The Journal of Geology, v. 121, no. 1, p. 35-56, https://doi.org/10.1086/668680.","productDescription":"22 p.","startPage":"35","endPage":"56","numberOfPages":"22","ipdsId":"IP-033166","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":279078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279077,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1086/668680"}],"volume":"121","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528607a5e4b00926c21865ba","contributors":{"authors":[{"text":"Covault, Jacob A.","contributorId":35951,"corporation":false,"usgs":true,"family":"Covault","given":"Jacob","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":469607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Craddock, William H. 0000-0002-4181-4735 wcraddock@usgs.gov","orcid":"https://orcid.org/0000-0002-4181-4735","contributorId":3411,"corporation":false,"usgs":true,"family":"Craddock","given":"William","email":"wcraddock@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":469605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romans, Brian W.","contributorId":40426,"corporation":false,"usgs":true,"family":"Romans","given":"Brian","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":469608,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fildani, Andrea","contributorId":45993,"corporation":false,"usgs":true,"family":"Fildani","given":"Andrea","affiliations":[],"preferred":false,"id":469609,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gosai, Mayur","contributorId":15510,"corporation":false,"usgs":true,"family":"Gosai","given":"Mayur","affiliations":[],"preferred":false,"id":469606,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70042357,"text":"sir20125269 - 2012 - Sediment transport to and from small impoundments in northeast Kansas, March 2009 through September 2011","interactions":[],"lastModifiedDate":"2013-01-17T11:22:10","indexId":"sir20125269","displayToPublicDate":"2013-01-08T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5269","title":"Sediment transport to and from small impoundments in northeast Kansas, March 2009 through September 2011","docAbstract":"The U.S. Geological Survey, in cooperation with the Kansas Water Office, investigated sediment transport to and from three small impoundments (average surface area of 0.1 to 0.8 square miles) in northeast Kansas during March 2009 through September 2011. Streamgages and continuous turbidity sensors were operated upstream and downstream from Atchison County, Banner Creek, and Centralia Lakes to study the effect of varied watershed characteristics and agricultural practices on sediment transport in small watersheds in northeast Kansas. Atchison County Lake is located in a predominantly agricultural basin of row crops, with wide riparian buffers along streams, a substantial amount of tile drainage, and numerous small impoundments (less than 0.05 square miles; hereafter referred to as “ponds”). Banner Creek Lake is a predominantly grassland basin with numerous small ponds located in the watershed, and wide riparian buffers along streams. Centralia Lake is a predominantly agricultural basin of row crops with few ponds, few riparian buffers along streams, and minimal tile drainage. Upstream from Atchison County, Banner Creek, and Centralia Lakes 24, 38, and 32 percent, respectively, of the total load was transported during less than 0.1 percent (approximately 0.9 days) of the time. Despite less streamflow in 2011, larger sediment loads during that year indicate that not all storm events transport the same amount of sediment; larger, extreme storms during the spring may transport much larger sediment loads in small Kansas watersheds. Annual sediment yields were 360, 400, and 970 tons per square mile per year at Atchison County, Banner, and Centralia Lake watersheds, respectively, which were less than estimated yields for this area of Kansas (between 2,000 and 5,000 tons per square mile per year). Although Centralia and Atchison County Lakes had similar percentages of agricultural land use, mean annual sediment yields upstream from Centralia Lake were about 2.7 times those at Atchison County or Banner Creek Lakes. These data indicate larger yields of sediment from watersheds with row crops and those with fewer small ponds, and smaller yields in watersheds which are primarily grassland, or agricultural with substantial tile drainage and riparian buffers along streams. These results also indicated that a cultivated watershed can produce yields similar to those observed under the assumed reference (or natural) condition. Selected small ponds were studied in the Atchison County Lake watershed to characterize the role of small ponds in sediment trapping. Studied ponds trapped about 8 percent of the sediment upstream from the sediment-sampling site. When these results were extrapolated to the other ponds in the watershed, differences in the extent of these ponds was not the primary factor affecting differences in yields among the three watersheds. However, the selected small ponds were both 45 years old at the time of this study, and have reduced capacity because of being filled in with sediments. Additionally, trapping efficiency of these small ponds decreased over five observed storms, indicating that processes that suspended or resuspended sediments in these shallow ponds, such as wind and waves, affected their trapping efficiencies. While small ponds trapped sediments in small storms, they could be a source of sediment in larger or more closely spaced storm events. Channel slope was similar at all three watersheds, 0.40, 0.46, and 0.31 percent at Atchison County, Banner Creek, and Centralia Lake watersheds, respectively. Other factors, such as increased bank and stream erosion, differences in tile drainage, extent of grassland, or riparian buffers, could be the predominant factors affecting sediment yields from these basins. These results show that reference-like sediment yields may be observed in heavily agricultural watersheds through a combination of field-scale management activities and stream channel protection. When computing loads using published erosion rates obtained by single-point survey methodology, streambank contributions from the main stem of Banner Creek are three times more than the sediment load observed by this study at the sediment sampling site at Banner Creek, 2.6 times more than the sediment load observed by this study at the sediment sampling site at Clear Creek (upstream from Atchison County Lake), and are 22 percent of the load observed by this study at the sediment sampling site at Black Vermillion River above Centralia Lake. Comparisons of study sites to similarly sized urban and urbanizing watersheds in Johnson County, Kansas indicated that sediment yields from the Centralia Lake watershed were similar to those in construction-affected watersheds, while much smaller sediment yields in the Atchison County and Banner Creek watersheds were comparable to stable, heavily urbanized watersheds. Comparisons of study sites to larger watersheds upstream from Tuttle Creek Lake indicate the Black Vermillion River watershed continues to have high sediment yields despite 98 percent of sediment from the Centralia watershed (a headwater of the Black Vermillion River) being trapped in Centralia Lake. Estimated trapping efficiencies for the larger watershed lakes indicated that Banner Creek and Centralia Lakes trapped 98 percent of incoming sediment, whereas Atchison County Lake trapped 72 percent of incoming sediment during the 3-year study period.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125269","collaboration":"Prepared in cooperation with the Kansas Water Office","usgsCitation":"Foster, G., Lee, C., and Ziegler, A., 2012, Sediment transport to and from small impoundments in northeast Kansas, March 2009 through September 2011: U.S. Geological Survey Scientific Investigations Report 2012-5269, vi, 38 p., https://doi.org/10.3133/sir20125269.","productDescription":"vi, 38 p.","numberOfPages":"48","onlineOnly":"Y","temporalStart":"2009-03-01","temporalEnd":"2011-09-30","ipdsId":"IP-035289","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":265371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5269.gif"},{"id":265370,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5269/"},{"id":265369,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5269/sir12-5269.pdf"}],"country":"United States","state":"Kansas","county":"Atchison;Brown;Doniphan;Jackson;Jefferson;Marshall;Nemaha;Pottawatomie","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.333333,39.366667 ], [ -96.333333,39.8 ], [ -95.25,39.8 ], [ -95.25,39.366667 ], [ -96.333333,39.366667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ed3fe1e4b0438b00db0746","contributors":{"authors":[{"text":"Foster, Guy M. gfoster@usgs.gov","contributorId":3437,"corporation":false,"usgs":true,"family":"Foster","given":"Guy M.","email":"gfoster@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":471375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Casey J. 0000-0002-5753-2038","orcid":"https://orcid.org/0000-0002-5753-2038","contributorId":31062,"corporation":false,"usgs":true,"family":"Lee","given":"Casey J.","affiliations":[],"preferred":false,"id":471376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziegler, Andrew C. aziegler@usgs.gov","contributorId":433,"corporation":false,"usgs":true,"family":"Ziegler","given":"Andrew C.","email":"aziegler@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":471374,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70044141,"text":"70044141 - 2012 - Igneous activity, metamorphism, and deformation in the Mount Rogers area of SW Virginia and NW North Carolina: A geologic record of Precambrian tectonic evolution of the southern Blue Ridge Province","interactions":[],"lastModifiedDate":"2019-02-01T16:15:07","indexId":"70044141","displayToPublicDate":"2013-01-01T14:10:48","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Igneous activity, metamorphism, and deformation in the Mount Rogers area of SW Virginia and NW North Carolina: A geologic record of Precambrian tectonic evolution of the southern Blue Ridge Province","docAbstract":"Mesoproterozoic basement in the vicinity of Mount Rogers is characterized by considerable lithologic variability, including major map units composed of gneiss, amphibolite, migmatite, meta-quartz monzodiorite and various types of granitoid. SHRIMP U-Pb geochronology and field mapping indicate that basement units define four types of occurrences, including (1) xenoliths of ca. 1.33 to ≥1.18 Ga age, (2) an early magmatic suite including meta-granitoids of ca. 1185–1140 Ma age that enclose or locally intrude the xenoliths, (3) metasedimentary rocks represented by layered granofels and biotite schist whose protoliths were likely deposited on the older meta-granitoids, and (4) a late magmatic suite composed of younger, ca. 1075–1030 Ma intrusive rocks of variable chemical composition that intruded the older rocks. The magmatic protolith of granofels constituting part of a layered, map-scale xenolith crystallized at ca. 1327 Ma, indicating that the lithology represents the oldest, intact crust presently recognized in the southern Appalachians. SHRIMP U-Pb data indicate that periods of regional Mesoproterozoic metamorphism occurred at 1170–1140 and 1070–1020 Ma. The near synchroneity in timing of regional metamorphism and magmatism suggests that magmas were emplaced into crust that was likely at near-solidus temperatures and that melts might have contributed to the regional heat budget. Much of the area is cut by numerous, generally east- to northeast-striking Paleozoic fault zones characterized by variable degrees of ductile deformation and recrystallization. These high-strain fault zones dismember the terrane, resulting in juxtaposition of units and transformation of basement lithologies to quartz- and mica-rich tectonites with protomylonitic and mylonitic textures. Mineral assemblages developed within such zones indicate that deformation and recrystallization likely occurred at greenschist-facies conditions at ca. 340 Ma.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From the Blue Ridge to the Coastal Plain: Field Excursions in the Southeastern United States","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2012.0029(01)","usgsCitation":"Tollo, R.P., Aleinikoff, J.N., Mundil, R., Southworth, C.S., Cosca, M.A., Rankin, D., Rubin, A.E., Kentner, A., Parendo, C.A., and Ray, M.S., 2012, Igneous activity, metamorphism, and deformation in the Mount Rogers area of SW Virginia and NW North Carolina: A geologic record of Precambrian tectonic evolution of the southern Blue Ridge Province, chap. of From the Blue Ridge to the Coastal Plain: Field Excursions in the Southeastern United States, v. 29, p. 1-66, https://doi.org/10.1130/2012.0029(01).","productDescription":"67 p.","startPage":"1","endPage":"66","ipdsId":"IP-039522","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":278458,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278457,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/2012.0029(01)"}],"country":"United States","state":"North Carolina, Virginia","otherGeospatial":"Blue Ridge Province","volume":"29","noUsgsAuthors":false,"publicationDate":"2012-11-27","publicationStatus":"PW","scienceBaseUri":"526b9307e4b058918d0acc14","contributors":{"authors":[{"text":"Tollo, Richard P.","contributorId":6465,"corporation":false,"usgs":true,"family":"Tollo","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":474879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":474876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mundil, Roland","contributorId":23061,"corporation":false,"usgs":true,"family":"Mundil","given":"Roland","email":"","affiliations":[],"preferred":false,"id":474880,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Southworth, C. Scott 0000-0002-7976-7807 ssouthwo@usgs.gov","orcid":"https://orcid.org/0000-0002-7976-7807","contributorId":1608,"corporation":false,"usgs":true,"family":"Southworth","given":"C.","email":"ssouthwo@usgs.gov","middleInitial":"Scott","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":474877,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cosca, Michael A. 0000-0002-0600-7663 mcosca@usgs.gov","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":1000,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"mcosca@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":474875,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rankin, Douglas W. dwrankin@usgs.gov","contributorId":1770,"corporation":false,"usgs":true,"family":"Rankin","given":"Douglas W.","email":"dwrankin@usgs.gov","affiliations":[],"preferred":true,"id":474878,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rubin, Allison E.","contributorId":43664,"corporation":false,"usgs":true,"family":"Rubin","given":"Allison","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":474883,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kentner, Adrienne","contributorId":34818,"corporation":false,"usgs":true,"family":"Kentner","given":"Adrienne","email":"","affiliations":[],"preferred":false,"id":474882,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Parendo, Christopher A.","contributorId":23839,"corporation":false,"usgs":true,"family":"Parendo","given":"Christopher","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474881,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ray, Molly S.","contributorId":62131,"corporation":false,"usgs":true,"family":"Ray","given":"Molly","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":474884,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70100649,"text":"70100649 - 2012 - The effects of wildfire on the sediment yield of a coastal California watershed","interactions":[],"lastModifiedDate":"2014-04-04T10:23:05","indexId":"70100649","displayToPublicDate":"2012-11-05T10:16:02","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"The effects of wildfire on the sediment yield of a coastal California watershed","docAbstract":"The occurrence of two wildfires separated by 31 yr in the chaparral-dominated Arroyo Seco watershed (293 kmMany basins throughout the world have sparse hydrologic and geologic data, but have increasing demands for water and a commensurate need for integrated understanding of surface and groundwater resources. This paper demonstrates a methodology for using a distributed parameter water-balance model, gaged surface-water flow, and a reconnaissance-level groundwater flow model to develop a first-order water balance. Flow amounts are rounded to the nearest 5 million cubic meters per year.
The San Diego River basin is 1 of 5 major drainage basins that drain to the San Diego coastal plain, the source of public water supply for the San Diego area. The distributed parameter water-balance model (Basin Characterization Model) was run at a monthly timestep for 1940–2009 to determine a median annual total water inflow of 120 million cubic meters per year for the San Diego region. The model was also run specifically for the San Diego River basin for 1982–2009 to provide constraints to model calibration and to evaluate the proportion of inflow that becomes groundwater discharge, resulting in a median annual total water inflow of 50 million cubic meters per year. On the basis of flow records for the San Diego River at Fashion Valley (US Geological Survey gaging station 11023000), when corrected for upper basin reservoir storage and imported water, the total is 30 million cubic meters per year. The difference between these two flow quantities defines the annual groundwater outflow from the San Diego River basin at 20 million cubic meters per year. These three flow components constitute a first-order water budget estimate for the San Diego River basin. The ratio of surface-water outflow and groundwater outflow to total water inflow are 0.6 and 0.4, respectively. Using total water inflow determined using the Basin Characterization Model for the entire San Diego region and the 0.4 partitioning factor, groundwater outflow from the San Diego region, through the coastal plain aquifer to the Pacific Ocean, is calculated to be approximately 50 million cubic meters per year.
The area-scale assessment of water resources highlights several hydrologic features of the San Diego region. Groundwater recharge is episodic; the Basin Characterization Model output shows that 90 percent of simulated recharge occurred during 3 percent of the 1982–2009 period. The groundwater aquifer may also be quite permeable. A reconnaissance-level groundwater flow model for the San Diego River basin was used to check the water budget estimates, and the basic interaction of the surface-water and groundwater system, and the flow values, were found to be reasonable. Horizontal hydraulic conductivity values of the volcanic and metavolcanic bedrock in San Diego region range from 1 to 10 m per day. Overall, results establish an initial hydrologic assessment formulated on the basis of sparse hydrologic data. The described flow variability, extrapolation, and unique characteristics represent a realistic view of current (2012) hydrologic understanding for the San Diego region.
Love and Gannon (2009) discovered that statistically, over a fifty year period the difference in the dawn and dusk disturbance‐field H component at low latitudes (hourly averaged) is linearly proportional to Dst. If the difference is designated by δDD in units of nT/RE, then the Love‐Gannon (L‐G) relation is δDD = −0.2 Dst. At any time departures from the relation can be large. Nonetheless, the relation is evident for all values of Dst and persists throughout magnetic storms, both the main phase and the recovery phase. The Love‐Gannon discovery presents a problem to current understanding of the relation between the causes of δDD and Dst because the dawn dusk asymmetry in the disturbance field is presumably governed by a long‐established magnetosphere‐ionosphere coupling theory which predicts a characteristic time scale (the shielding time) of less than an hour whereas the characteristic time scale for Dst (the ring current decay time) is more like ten hours. Thus, without forcing both time scales toward each other to the limits of their ranges, a linear proportionality between δDD and Dst cannot be derived from the current understanding of the causes of the asymmetry and the ring current. This conclusion is the paper's main contribution. In addition, we attempt to get around the conflict of time scales by looking at other possibilities for generating δDD that depend directly on the ring current. The most promising of these is the possibility that the ring current decay mechanism creates a quasi‐permanent, local‐time modification of the ring current compared to what it would be in the absence of the decay mechanism and that this modification causes a field‐aligned current that closes through the ionosphere and generates the asymmetry δDD. This idea has the virtue of coupling the asymmetry directly to the ring current and of accounting for the persistence of the L‐G proportionality through the recovery phase of magnetic storms.
","language":"English","publisher":"AGU","doi":"10.1029/2012JA017879","usgsCitation":"Siscoe, G.L., Love, J.J., and Gannon, J., 2012, Problem of the Love‐Gannon relation between the asymmetric disturbance field and Dst: Journal of Geophysical Research A: Space Physics, v. 117, no. A9, A09216; 11 p., https://doi.org/10.1029/2012JA017879.","productDescription":"A09216; 11 p.","ipdsId":"IP-039196 ","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":358987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"A9","noUsgsAuthors":false,"publicationDate":"2012-09-06","publicationStatus":"PW","scienceBaseUri":"5c10bd73e4b034bf6a7efe19","contributors":{"authors":[{"text":"Siscoe, G. L.","contributorId":210281,"corporation":false,"usgs":false,"family":"Siscoe","given":"G.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":750359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":750360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gannon, J.L.","contributorId":78275,"corporation":false,"usgs":true,"family":"Gannon","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":750361,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}