No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Environmental modelling with GIS and remote sensing","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Taylor & Francis","doi":"10.4324/9780203302217","usgsCitation":"2002, Geographic data for environmental modelling and assessment, chap. 4 of Environmental modelling with GIS and remote sensing, p. 52-69, https://doi.org/10.4324/9780203302217.","productDescription":"17 p.","startPage":"52","endPage":"69","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":462124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2017-08-11","publicationStatus":"PW","contributors":{"editors":[{"text":"Skidmore, Andrew K","contributorId":147736,"corporation":false,"usgs":false,"family":"Skidmore","given":"Andrew","email":"","middleInitial":"K","affiliations":[{"id":16918,"text":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":913617,"contributorType":{"id":2,"text":"Editors"},"rank":1}]}} ,{"id":50555,"text":"ofr02423 - 2002 - Agenda, extended abstracts, and bibliographies for a workshop on Deposit modeling, mineral resources assessment, and their role in sustainable development","interactions":[],"lastModifiedDate":"2018-02-20T15:29:00","indexId":"ofr02423","displayToPublicDate":"2002-12-01T00:00:00","publicationYear":"2002","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":"2002-423","title":"Agenda, extended abstracts, and bibliographies for a workshop on Deposit modeling, mineral resources assessment, and their role in sustainable development","docAbstract":"Global demand for mineral resources continues to increase because of increasing global population and the desire and efforts to improve living standards worldwide. The ability to meet this growing demand for minerals is affected by the concerns about possible environmental degradation associated with minerals production and by competing land uses. Informed planning and decisions concerning sustainability and resource development require a long-term perspective and an integrated approach to land-use, resource, and environmental management worldwide. This, in turn, requires unbiased information on the global distribution of identified and especially undiscovered resources, the economic and political factors influencing their development, and the potential environmental consequences of their exploitation. \r\n\r\nThe purpose of the IGC workshop is to review the state-of-the-art in mineral-deposit modeling and quantitative resource assessment and to examine their role in the sustainability of mineral use. The workshop will address such questions as: Which of the available mineral-deposit models and assessment methods are best suited for predicting the locations, deposit types, and amounts of undiscovered nonfuel mineral resources remaining in the world? What is the availability of global geologic, mineral deposit, and mineral-exploration information? How can mineral-resource assessments be used to address economic and environmental issues? Presentations will include overviews of assessment methods used in previous national and other small-scale assessments of large regions as well as resulting assessment products and their uses.","language":"ENGLISH","doi":"10.3133/ofr02423","usgsCitation":"2002, Agenda, extended abstracts, and bibliographies for a workshop on Deposit modeling, mineral resources assessment, and their role in sustainable development (Version 1.0): U.S. Geological Survey Open-File Report 2002-423, 1 CD-ROM : col. ill., col. maps ; 4 3/4 in., https://doi.org/10.3133/ofr02423.","productDescription":"1 CD-ROM : col. ill., col. maps ; 4 3/4 in.","costCenters":[],"links":[{"id":176028,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":4365,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2002/of02-423/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae3e4b07f02db6891fd","contributors":{"editors":[{"text":"Briskey, Joseph A.","contributorId":77605,"corporation":false,"usgs":true,"family":"Briskey","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":729053,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Schulz, Klaus J. 0000-0003-2967-4765 kschulz@usgs.gov","orcid":"https://orcid.org/0000-0003-2967-4765","contributorId":2438,"corporation":false,"usgs":true,"family":"Schulz","given":"Klaus","email":"kschulz@usgs.gov","middleInitial":"J.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":729054,"contributorType":{"id":2,"text":"Editors"},"rank":2}]}} ,{"id":70180965,"text":"70180965 - 2002 - Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat: Tucson","interactions":[],"lastModifiedDate":"2017-02-10T13:23:05","indexId":"70180965","displayToPublicDate":"2002-12-01T00:00:00","publicationYear":"2002","noYear":false,"publicationType":{"id":21,"text":"Thesis"},"title":"Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat: Tucson","docAbstract":"The research accomplished in this dissertation used both mathematical and statistical techniques to extract and evaluate measures of landscape temporal dynamics and spatial structure from remotely sensed data for the purpose of mapping wildlife habitat. By coupling the landscape measures gleaned from the remotely sensed data with various sets of animal sightings and population data, effective models of habitat preference were created.
Measures of temporal dynamics of vegetation greenness as measured by National Oceanographic and Atmospheric Administration’s Advanced Very High Resolution Radiometer (AVHRR) satellite were used to effectively characterize and map season specific habitat of the Sonoran pronghorn antelope, as well as produce preliminary models of potential yellow-billed cuckoo habitat in Arizona. Various measures that capture different aspects of the temporal dynamics of the landscape were derived from AVHRR Normalized Difference Vegetation Index composite data using three main classes of calculations: basic statistics, standardized principal components analysis, and Fourier analysis. Pronghorn habitat models based on the AVHRR measures correspond visually and statistically to GIS-based models produced using data that represent detailed knowledge of ground-condition.
Measures of temporal dynamics also revealed statistically significant correlations with annual estimates of elk population in selected Arizona Game Management Units, suggesting elk respond to regional environmental changes that can be measured using satellite data. Such relationships, once verified and established, can be used to help indirectly monitor the population.
Measures of landscape spatial structure derived from IKONOS high spatial resolution (1-m) satellite data using geostatistics effectively map details of Sonoran pronghorn antelope habitat. Local estimates of the nugget, sill, and range variogram parameters calculated within 25 x 25-meter image windows describe the spatial autocorrelation of the image, permitting classification of all pixels into coherent units whose signature graphs exhibit a classic variogram shape. The variogram parameters captured in these signatures have been shown in previous studies to discriminate between different species-specific vegetation associations.
The synoptic view of the landscape provided by satellite data can inform resource management efforts. The ability to characterize the spatial structure and temporal dynamics of habitat using repeatable remote sensing data allows closer monitoring of the relationship between a species and its landscape.
","language":"English","publisher":"The University of Arizona","usgsCitation":"Wallace, C., and Advised by Marsh, S.E., 2002, Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat: Tucson, 198 p.","productDescription":"198 p.","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":335123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","city":"Tuscon","publicComments":"Submitted for a Doctor of Philosophy","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"589edf2ce4b099f50d3dc5af","contributors":{"authors":[{"text":"Wallace, Cynthia S.A.","contributorId":70487,"corporation":false,"usgs":true,"family":"Wallace","given":"Cynthia S.A.","affiliations":[],"preferred":false,"id":662974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Advised by Marsh, Stuart E.","contributorId":179145,"corporation":false,"usgs":false,"family":"Advised by Marsh","given":"Stuart","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":662975,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":44690,"text":"fs13202 - 2002 - Forecasting bacteria levels at bathing beaches in Ohio","interactions":[],"lastModifiedDate":"2019-05-22T10:38:40","indexId":"fs13202","displayToPublicDate":"2002-12-01T00:00:00","publicationYear":"2002","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"132-02","displayTitle":"Forecasting Bacteria Levels at Bathing Beaches in Ohio","title":"Forecasting bacteria levels at bathing beaches in Ohio","docAbstract":"The U.S. Geological Survey developed models for predicting exceedance of the bathing-water standard for Escherichia coli (E. coli) at three Lake Erie beaches and one inland lake in Ohio. The statistical models were specific to each beach, and the best model for each beach was based on a unique combination of environmental and water-quality variables as explanatory factors. For the Lake Erie beaches, these factors included wave height, number of birds on the beach at the time of sampling, lake-current direction, rainfall, turbidity, and streamflow of a nearby river. For the inland lake, these factors included date, wind direction and speed, number of birds, and rainfall. The prediction error in the models was too large to accurately estimate concentrations of E. coli; however, the models can be used like weather forecasts to predict the probability, given a set of input variables, that the Ohio bathing-water standard used to judge swimming safety will be exceeded.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs13202","usgsCitation":"Francy, D.S., and Darner, R.A., 2002, Forecasting bacteria levels at bathing beaches in Ohio: U.S. Geological Survey Fact Sheet 132-02, 4 p., https://doi.org/10.3133/fs13202.","productDescription":"4 p.","costCenters":[],"links":[{"id":3776,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2002/0132/fs2002132.pdf","text":"Report","size":"157 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2002-132"},{"id":120314,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2002/0132/coverthb.jpg"}],"country":"United States","state":"Ohio","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.452392578125,\n 41.12074559016745\n ],\n [\n -80.79345703125,\n 41.50857729743935\n ],\n [\n -80.947265625,\n 41.95131994679697\n ],\n [\n -82.452392578125,\n 41.59490508367679\n ],\n [\n -82.452392578125,\n 41.12074559016745\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.79139709472656,\n 41.2834825246581\n ],\n [\n -80.7278823852539,\n 41.2834825246581\n ],\n [\n -80.7278823852539,\n 41.31830206651102\n ],\n [\n -80.79139709472656,\n 41.31830206651102\n ],\n [\n -80.79139709472656,\n 41.2834825246581\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio Water Science Center
U.S. Geological Survey
6460 Busch Blvd.
Columbus, OH 43229
The lower Charles River, the water body between the Watertown Dam and the New Charles River Dam, is an important recreational resource for the Boston, Massachusetts, metropolitan area, but impaired water quality has affected its use. The goal of making this resource fishable and swimmable requires a better understanding of combined-sewer-overflow discharges, non-combined-sewer-overflow stormwater runoff, and constituent loads. This report documents the modeling effort used to calculate non-combined-sewer-overflow runoff to the lower Charles River.
During the 2000 water year, October 1, 1999–September 30, 2000, the U.S. Geological Survey collected precipitation data at Watertown Dam and compiled data from five other precipitation gages in or near the watershed. In addition, surface-water discharge data were collected at eight sites—three relatively homogenous land-use sites, four major tributary sites, and the Charles River at Watertown Dam, which is the divide between the upper and lower watersheds. The precipitation and discharge data were used to run and calibrate Stormwater Management Models developed for the three land-use subbasins (single-family, multi-family, and commercial), and the two tributary subbasins (Laundry and Faneuil Brooks). These calibrated models were used to develop a sixth model to simulate 54 ungaged outfalls to the lower Charles River. Models developed by the U.S. Geological Survey at gaged sites were calibrated with up to 24 storms. Each model was evaluated by comparing simulated discharge against measured discharge for all storms with appreciable precipitation and reliable discharge data. The model-fit statistics indicated that the models generally were well calibrated to peak discharge and runoff volumes. The model fit of the commercial land-use subbasin was not as well calibrated compared to the other models because the measured flows appear to be affected by variable conditions not represented in the model. A separate Stormwater Management Model of the Stony Brook Subbasin previously developed by others was evaluated with the newly collected data from this study; this model had a model fit comparable to the models developed by the U.S. Geological Survey.
The total annual runoff to the lower Charles River during the 2000 water year, not including contributions from combined-sewer-overflows except from the Stony Brook Subbasin, was 16,500 million cubic feet; 92 percent of the inflow was from the Charles River above Watertown Dam, 3 percent was from the Stony Brook Subbasin, 2 percent was from the Muddy River Subbasin, and less than 1 percent was from the combined inflows of Laundry and Faneuil Brooks. The remaining ungaged drainage area contributed about 2 percent of the total annual inflow to the lower Charles River. Excluding discharge from the Charles River above Watertown Dam, total annual runoff to the lower Charles River was 1,240 million cubic feet; 39 percent was from the Stony Brook Subbasin, 27 percent was from the Muddy River, which includes runoff that drains to the Muddy River conduit, 7 percent was from the Laundry Brook Subbasin, and 4 percent was from the Faneuil Brook Subbasin. Flow from the ungaged areas composed about 23 percent of the total annual inflow to the lower Charles River, excluding discharge from the Charles River above Watertown Dam.
Runoff to the lower Charles River was calculated for two design storms representing a 3-month and a 1-year event, 1.84 and 2.79 inches of total rainfall, respectively. These simulated discharges were provided to the Massachusetts Water Resources Authority for use in a receiving-water model of the lower Charles River. Total storm runoff to the lower Charles River was 111 and 257 million cubic feet for the 3-month and 1-year storms, respectively. Excluding discharge from the Charles River above Watertown Dam, total runoff to the lower Charles River was 30 and 53 million cubic feet for the 3-month and 1-year storms, respectively. Runoff from the various tributary areas for the design storms was about in the same proportion as that for the annual runoff.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/wri024129","usgsCitation":"Zarriello, P.J., and Barlow, L.K., 2002, Measured and simulated runoff to the lower Charles River, Massachusetts, October 1999–September 2000: U.S. Geological Survey Water-Resources Investigations Report 2002-4129, vi, 89 p., https://doi.org/10.3133/wri024129.","productDescription":"vi, 89 p.","costCenters":[],"links":[{"id":135337,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":394619,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_54107.htm"},{"id":3938,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/wri024129/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Massachusetts","otherGeospatial":"Charles River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.2,\n 42.2667\n ],\n [\n -71.0667,\n 42.2667\n ],\n [\n -71.0667,\n 42.3833\n ],\n [\n -71.2,\n 42.3833\n ],\n [\n -71.2,\n 42.2667\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a27e4b07f02db610826","contributors":{"authors":[{"text":"Zarriello, Phillip J. 0000-0001-9598-9904 pzarriel@usgs.gov","orcid":"https://orcid.org/0000-0001-9598-9904","contributorId":1868,"corporation":false,"usgs":true,"family":"Zarriello","given":"Phillip","email":"pzarriel@usgs.gov","middleInitial":"J.","affiliations":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":231096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barlow, Lora K.","contributorId":90279,"corporation":false,"usgs":true,"family":"Barlow","given":"Lora","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":231097,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70186925,"text":"70186925 - 2002 - Physical attributes of some clouds amid a forest ecosystem's trees","interactions":[],"lastModifiedDate":"2017-04-14T13:41:10","indexId":"70186925","displayToPublicDate":"2002-12-01T00:00:00","publicationYear":"2002","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":928,"text":"Atmospheric Research","active":true,"publicationSubtype":{"id":10}},"title":"Physical attributes of some clouds amid a forest ecosystem's trees","docAbstract":"Cloud or fog water collected by forest canopies of any elevation could represent significant sources of required moisture and nutrients for forest ecosystems, human consumption, and as an alternative source of water for agriculture and domestic use. The physical characteristics of fogs and other clouds have been well studied, and this information can be useful to water balance or canopy–cloud interaction model verification and to calibration or training of satellite-borne sensors to recognize atmospheric attributes, such as optical thickness, albedo, and cloud properties. These studies have taken place above-canopy or within canopy clearings and rarely amid the canopy. Simultaneous physical and chemical characteristics of clouds amid and above the trees of a mountain forest, located about 3.3 km southwest of Mt. Mitchell, NC, were collected between 13 and 22 June 1993. This paper summarizes the physical characteristics of the cloud portions amid the trees. The characteristic cloud amid the trees (including cloud and precipitation periods) contained 250 droplet/cm3 with a mean diameter of 9.5 μm and liquid water content (LWC) of 0.11 g m−3. The cloud droplets exhibited a bimodal distribution with modes at about 2 and 8 μm and a mean diameter near 5 μm during precipitation-free periods, whereas the concurrent above-canopy cloud droplets had a unimodal distribution with a mode near 6 μm and a mean diameter of 6 μm. The horizontal cloud water flux is nonlinearly related to the rate of collection onto that surface amid the trees, especially for the Atmospheric Sciences Research Center (ASRC) sampling device, whereas it is linear when the forward scattering spectrometer probe (FSSP) are is used. These findings suggest that statements about the effects clouds have on surfaces they encounter, which are based on above-canopy or canopy-clearing data, can be misleading, if not erroneous.
","language":"English","publisher":"Elsevier","doi":"10.1016/S0169-8095(02)00112-6","usgsCitation":"DeFelice, T.P., 2002, Physical attributes of some clouds amid a forest ecosystem's trees: Atmospheric Research, v. 65, no. 1-2, p. 17-34, https://doi.org/10.1016/S0169-8095(02)00112-6.","productDescription":"18 p.","startPage":"17","endPage":"34","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":339737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","issue":"1-2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f1e0cbe4b08144348b7e1e","contributors":{"authors":[{"text":"DeFelice, Thomas P.","contributorId":103831,"corporation":false,"usgs":true,"family":"DeFelice","given":"Thomas","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":691022,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159112,"text":"70159112 - 2002 - Historical and future land use effects on N2O and NO emissions using an ensemble modeling approach: Costa Rica's Caribbean lowlands as an example","interactions":[],"lastModifiedDate":"2015-10-15T13:09:56","indexId":"70159112","displayToPublicDate":"2002-12-01T00:00:00","publicationYear":"2002","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Historical and future land use effects on N2O and NO emissions using an ensemble modeling approach: Costa Rica's Caribbean lowlands as an example","docAbstract":"[1] The humid tropical zone is a major source area for N2O and NO emissions to the atmosphere. Local emission rates vary widely with local conditions, particularly land use practices which swiftly change with expanding settlement and changing market conditions. The combination of wide variation in emission rates and rapidly changing land use make regional estimation and future prediction of biogenic trace gas emission particularly difficult. This study estimates contemporary, historical, and future N2O and NO emissions from 0.5 million ha of northeastern Costa Rica, a well-documented region in the wet tropics undergoing rapid agricultural development. Estimates were derived by linking spatially distributed environmental data with an ecosystem simulation model in an ensemble estimation approach that incorporates the variance and covariance of spatially distributed driving variables. Results include measures of variance for regional emissions. The formation and aging of pastures from forest provided most of the past temporal change in N2O and NO flux in this region; future changes will be controlled by the degree of nitrogen fertilizer application and extent of intensively managed croplands.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2001GB001437","usgsCitation":"Reiners, W.A., Liu, S., Gerow, K., Keller, M., and Schimel, D.S., 2002, Historical and future land use effects on N2O and NO emissions using an ensemble modeling approach: Costa Rica's Caribbean lowlands as an example: Global Biogeochemical Cycles, v. 16, no. 4, p. 1-18, https://doi.org/10.1029/2001GB001437.","productDescription":"18 p.","startPage":"1","endPage":"18","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":309937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2002-10-26","publicationStatus":"PW","scienceBaseUri":"5620ce75e4b06217fc478aea","contributors":{"authors":[{"text":"Reiners, William A.","contributorId":147117,"corporation":false,"usgs":false,"family":"Reiners","given":"William","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":577634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, S.","contributorId":149250,"corporation":false,"usgs":false,"family":"Liu","given":"S.","email":"","affiliations":[],"preferred":false,"id":577635,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerow, K.G.","contributorId":17003,"corporation":false,"usgs":true,"family":"Gerow","given":"K.G.","email":"","affiliations":[],"preferred":false,"id":577636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keller, M.","contributorId":149251,"corporation":false,"usgs":false,"family":"Keller","given":"M.","email":"","affiliations":[],"preferred":false,"id":577637,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schimel, D. S.","contributorId":84104,"corporation":false,"usgs":true,"family":"Schimel","given":"D.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":577638,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":39954,"text":"wri024223 - 2002 - Bed-material entrainment potential, Roaring Fork River at Basalt, Colorado","interactions":[],"lastModifiedDate":"2012-02-02T00:10:18","indexId":"wri024223","displayToPublicDate":"2002-12-01T00:00:00","publicationYear":"2002","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2002-4223","title":"Bed-material entrainment potential, Roaring Fork River at Basalt, Colorado","docAbstract":"The Roaring Fork River at Basalt, Colorado, has a frequently mobile streambed composed of gravel, cobbles, and boulders. Recent urban and highway development on the flood plain, earlier attempts to realign and confine the channel, and flow obstructions such as bridge openings and piers have altered the hydrology, hydraulics, sediment transport, and sediment deposition areas of the Roaring Fork. Entrainment and deposition of coarse sediment on the streambed and in large alluvial bars have reduced the flood-conveying capacity of the river. Previous engineering studies have identified flood-prone areas and hazards related to inundation and high streamflow velocity, but those studies have not evaluated the potential response of the channel to discharges that entrain the coarse streambed. This study builds upon the results of earlier flood studies and identifies some potential areas of concern associated with bed-material entrainment. \r\n\r\nCross-section surveys and simulated water-surface elevations from a previously run HEC?RAS model were used to calculate the boundary shear stress on the mean streambed, in the thalweg, and on the tops of adjacent alluvial bars for four reference streamflows. Sediment-size characteristics were determined for surficial material on the streambed, on large alluvial bars, and on a streambank. The median particle size (d50) for the streambed samples was 165 millimeters and for the alluvial bars and bank samples was 107 millimeters. \r\n\r\nShear stresses generated by the 10-, 50-, and 100-year floods, and by a more common flow that just inundated most of the alluvial bars in the study reach were calculated at 14 of the cross sections used in the Roaring Fork River HEC?RAS model. The Shields equation was used with a Shields parameter of 0.030 to estimate the critical shear stress for entrainment of the median sediment particle size on the mean streambed, in the thalweg, and on adjacent alluvial bar surfaces at the 14 cross sections. \r\n\r\nSediment-entrainment potential for a specific geomorphic surface was expressed as the ratio of the flood-generated boundary shear stress to the critical shear stress (to/tc) with respect to two threshold conditions. The partial entrainment threshold (to/tc=1) is the condition where the mean boundary shear stress (to) equals the critical shear stress for the median particle size (tc) at that cross section. At this threshold discharge, the d50 particle size becomes entrained, but movement of d50-size particles may be limited to a few individual particles or in a small area of the streambed surface. The complete entrainment threshold (to/tc=2) is the condition where to is twice the critical shear stress for the median particle size, the condition where complete or widespread mobilization of the d50 particle-size fraction is anticipated. \r\n\r\nEntrainment potential for a specific reference streamflow varied greatly in the downstream direction. At some cross sections, the bed or bar material was mobile, whereas at other cross sections, the bed or bar material was immobile for the same discharge. The significance of downstream variability is that sediment entrained at one cross section may be transported into, but not through, a cross section farther downstream, a situation resulting in sediment deposition and possibly progressive aggradation and loss of channel conveyance. \r\n\r\nLittle or no sediment in the d50-size range is likely to be entrained or transported through much of the study reach by the bar-inundating streamflow. However, the entrainment potential at this discharge increases abruptly to more than twice the critical value, then decreases abruptly, at a series of cross sections located downstream from the Emma and Midland Avenue Bridges. Median particle-size sediment is mobile at most cross sections in the study reach during the 10-year flood; however, the bed material is immobile at cross sections just upstream from the Upper Bypass and Midland Avenue Bridges. A similar s","language":"ENGLISH","doi":"10.3133/wri024223","usgsCitation":"Elliott, J.G., 2002, Bed-material entrainment potential, Roaring Fork River at Basalt, Colorado: U.S. Geological Survey Water-Resources Investigations Report 2002-4223, iv, 33 p. : col. ill., col. maps ; 28 cm., https://doi.org/10.3133/wri024223.","productDescription":"iv, 33 p. : col. ill., col. maps ; 28 cm.","costCenters":[],"links":[{"id":3648,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/wri024223","linkFileType":{"id":5,"text":"html"}},{"id":170420,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a6be4b07f02db63dbb1","contributors":{"authors":[{"text":"Elliott, John G. jelliott@usgs.gov","contributorId":832,"corporation":false,"usgs":true,"family":"Elliott","given":"John","email":"jelliott@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":222675,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":45095,"text":"wri024212 - 2002 - Probability distributions of hydraulic conductivity for the hydrogeologic units of the Death Valley regional ground-water flow system, Nevada and California","interactions":[],"lastModifiedDate":"2012-02-02T00:05:00","indexId":"wri024212","displayToPublicDate":"2002-12-01T00:00:00","publicationYear":"2002","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2002-4212","title":"Probability distributions of hydraulic conductivity for the hydrogeologic units of the Death Valley regional ground-water flow system, Nevada and California","docAbstract":"The use of geologic information such as lithology and rock properties is important to constrain conceptual and numerical hydrogeologic models. This geologic information is difficult to apply explicitly to numerical modeling and analyses because it tends to be qualitative rather than quantitative. This study uses a compilation of hydraulic-conductivity measurements to derive estimates of the probability distributions for several hydrogeologic units within the Death Valley regional ground-water flow system, a geologically and hydrologically complex region underlain by basin-fill sediments, volcanic, intrusive, sedimentary, and metamorphic rocks. Probability distributions of hydraulic conductivity for general rock types have been studied previously; however, this study provides more detailed definition of hydrogeologic units based on lithostratigraphy, lithology, alteration, and fracturing and compares the probability distributions to the aquifer test data. Results suggest that these probability distributions can be used for studies involving, for example, numerical flow modeling, recharge, evapotranspiration, and rainfall runoff. These probability distributions can be used for such studies involving the hydrogeologic units in the region, as well as for similar rock types elsewhere.\r\n\r\nWithin the study area, fracturing appears to have the greatest influence on the hydraulic conductivity of carbonate bedrock hydrogeologic units. Similar to earlier studies, we find that alteration and welding in the Tertiary volcanic rocks greatly influence hydraulic conductivity. As alteration increases, hydraulic conductivity tends to decrease. Increasing degrees of welding appears to increase hydraulic conductivity because welding increases the brittleness of the volcanic rocks, thus increasing the amount of fracturing.","language":"ENGLISH","doi":"10.3133/wri024212","usgsCitation":"Belcher, W., Sweetkind, D., and Elliott, P.E., 2002, Probability distributions of hydraulic conductivity for the hydrogeologic units of the Death Valley regional ground-water flow system, Nevada and California: U.S. Geological Survey Water-Resources Investigations Report 2002-4212, 18 p., https://doi.org/10.3133/wri024212.","productDescription":"18 p.","costCenters":[],"links":[{"id":3940,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/wri024212","linkFileType":{"id":5,"text":"html"}},{"id":135358,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9ee4b07f02db660b9d","contributors":{"authors":[{"text":"Belcher, Wayne R.","contributorId":79446,"corporation":false,"usgs":true,"family":"Belcher","given":"Wayne R.","affiliations":[],"preferred":false,"id":231102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweetkind, Donald S.","contributorId":18732,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","affiliations":[],"preferred":false,"id":231101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, Peggy E. 0000-0002-7264-664X pelliott@usgs.gov","orcid":"https://orcid.org/0000-0002-7264-664X","contributorId":3805,"corporation":false,"usgs":true,"family":"Elliott","given":"Peggy","email":"pelliott@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":231100,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":50564,"text":"ofr02451 - 2002 - Modeling GPR data to interpret porosity and DNAPL saturations for calibration of a 3-D multiphase flow simulation","interactions":[],"lastModifiedDate":"2012-02-02T00:11:15","indexId":"ofr02451","displayToPublicDate":"2002-12-01T00:00:00","publicationYear":"2002","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":"2002-451","title":"Modeling GPR data to interpret porosity and DNAPL saturations for calibration of a 3-D multiphase flow simulation","docAbstract":"Dense nonaqueous phase liquids (DNAPLs) are a pervasive and persistent category of groundwater contamination. In an effort to better understand their unique subsurface behavior, a controlled and carefully monitored injection of PCE (perchloroethylene), a typical DNAPL, was performed in conjunction with the University of Waterloo at Canadian Forces Base Borden in 1991. Of the various geophysical methods used to monitor the migration of injected PCE, the U.S. Geological Survey collected 500-MHz ground penetrating radar (GPR) data. These data are used in determining calibration parameters for a multiphase flow simulation. GPR data were acquired over time on a fixed two-dimensional surficial grid as the DNAPL was injected into the subsurface. Emphasis is on the method of determining DNAPL saturation values from this time-lapse GPR data set. Interactive full-waveform GPR modeling of regularized field traces resolves relative dielectric permittivity versus depth profiles for pre-injection and later-time data. Modeled values are end members in recursive calculations of the Bruggeman-Hanai-Sen (BHS) mixing formula, yielding interpreted pre-injection porosity and post-injection DNAPL saturation values. The resulting interpreted physical properties of porosity and DNAPL saturation of the Borden test cell, defined on a grid spacing of 50 cm with 1-cm depth resolution, are used as observations for calibration of a 3-D multiphase flow simulation. Calculated values of DNAPL saturation in the subsurface at 14 and 22 hours after the start of injection, from both the GPR and the multiphase flow modeling, are interpolated volumetrically and presented for visual comparison.","language":"ENGLISH","doi":"10.3133/ofr02451","usgsCitation":"Sneddon, K.W., Powers, M.H., Johnson, R.H., and Poeter, E.P., 2002, Modeling GPR data to interpret porosity and DNAPL saturations for calibration of a 3-D multiphase flow simulation (Version 1.0): U.S. Geological Survey Open-File Report 2002-451, 29 p., illus. incl. 2 tables, 53 refs, https://doi.org/10.3133/ofr02451.","productDescription":"29 p., illus. incl. 2 tables, 53 refs","costCenters":[],"links":[{"id":176833,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":4373,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2002/ofr-02-451/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b05e4b07f02db699a4b","contributors":{"authors":[{"text":"Sneddon, Kristen W.","contributorId":82783,"corporation":false,"usgs":true,"family":"Sneddon","given":"Kristen","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":241842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powers, Michael H. 0000-0002-4480-7856 mhpowers@usgs.gov","orcid":"https://orcid.org/0000-0002-4480-7856","contributorId":851,"corporation":false,"usgs":true,"family":"Powers","given":"Michael","email":"mhpowers@usgs.gov","middleInitial":"H.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":241840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Raymond H. rhjohnso@usgs.gov","contributorId":707,"corporation":false,"usgs":true,"family":"Johnson","given":"Raymond","email":"rhjohnso@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":241839,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poeter, Eileen P.","contributorId":78805,"corporation":false,"usgs":true,"family":"Poeter","given":"Eileen","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":241841,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":51130,"text":"ofr02414 - 2002 - Digital data grids for the magnetic anomaly map of North America","interactions":[],"lastModifiedDate":"2025-12-29T18:19:32.991511","indexId":"ofr02414","displayToPublicDate":"2002-12-01T00:00:00","publicationYear":"2002","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":"2002-414","title":"Digital data grids for the magnetic anomaly map of North America","docAbstract":"The digital magnetic anomaly database and map for the North American continent is the result of a joint effort by the Geological Survey of Canada (GSC), U. S. Geological Survey (USGS), and Consejo de Recursos Minerales of Mexico (CRM). This integrated, readily accessible, modern digital database of magnetic anomaly data is a powerful tool for further evaluation of the structure, geologic processes, and tectonic evolution of the continent and may also be used to help resolve societal and scientific issues that span national boundaries. The North American magnetic anomaly map derived from the digital database provides a comprehensive magnetic view of continental-scale trends not available in individual data sets, helps link widely separated areas of outcrop, and unifies disparate geologic studies.
This open-file report presents three unique, gridded data sets used to make the magnetic anomaly map of North America. Subsets of these three grids that span only the United States were also created, giving a total of six grids. Details on the data processing and compilation procedures used to produce the grids are described in the booklet that accompanies the North American magnetic anomaly map. All three grids have 1-km spacing and are projected to the DNAG projection (spherical transverse mercator, central meridian of 100 o W, base latitude of 0o, scale factor of 0.926 and Earth radius of 6,371,204 m.) More details are given in the metadata files that accompany the gridded data files. These grids are presented in Geosoft binary grid format, with two files describing each of the six grids (suffixes .grd and .gi). This format can be easily converted to numerous other formats using the free conversion software offered by this company at http://www.geosoft.com/.
The first grids (NAmag_origmrg.grd and USmag_origmrg.grd) show the magnetic field at 305 m. above terrain.
For the second grids (NAmag_hp500.grd and USmag_hp500.grd) we removed long-wavelength anomalies (500 km and greater) from the first grid. This grid was used for the published map. Although the North American merged grid represents a significant upgrade to older compilations, the existing patchwork of surveys is inherently unable to accurately represent anomalies with long (greater than roughly 150 km) wavelengths, particularly in the US and Canada (U.S. Magnetic-Anomaly Data Set Task Group, 1994). The lack of information about long wavelength anomalies is primarily related to datum shifts between merged surveys, caused by data acquisition at widely different times and by differences in merging procedures. Therefore, we removed anomalies with wavelengths greater than 500 km from the merged grid to reduce the effects caused by the spurious long wavelengths but still maintain the continuity of anomalies. The correction was accomplished by transforming the merged grid to the frequency domain, filtering the transformed data with a long-wavelength cutoff at 500 km, and subtracting the long-wavelength data grid from the merged grid.
In addition to the 500-km high pass filter, an equivalent source method, based on long-wavelength characterization using satellite data (CHAMP satellite anomalies, Maus and others, 2002), was also used to correct for spurious shifts in the original magnetic anomaly grid (Ravat and others, 2002). These results are presented in the third grids (NAmag_CM.grd and USmag_CM.grd), in which the wavelengths longer than 500 km have been replaced by downward-continued satellite data. The steps used to create the third long-wavelength-corrected grid are:
0. The North American 1-km merged grid was decimated to 5 km.
1. This 5-km grid was converted to a 0.05 degree grid and was low-pass filtered using a Gaussian filter with a 500-km cutoff, then decimated to 1 degree.
2. A joint inversion of this 1-degree low-pass aeromagnetic grid and satellite data, with the aeromagnetic data weighted very low, was used to produce a stabilized downward continuation of the satellite data.
3. The inverted data were interpolated to 0.05 degrees and again low-pass filtered using the same Gaussian 500-km filter to remove short-wavelength artifacts.
4. The low-pass grid from step 1 was subtracted from the original 0.05-degree aeromagnetic grid to create a 500-km high-pass aeromagnetic grid. This grid was added to the low-pass inverted grid from step 3 to get a corrected 0.05-degree aeromagnetic grid.
5. The corrected 0.05-degree aeromagnetic grid was projected to the DNAG projection and regridded to 5 km. This was subtracted from the decimated 5-km aeromagnetic grid to generate a 5-km correction grid. A matched filter was used to remove short-wavelength artifacts resulting from the projection and regridding process.
6. The resulting 5-km correction grid was regridded to the original 1-km grid and subtracted from the original 1-km aeromagnetic grid to generate the final 1-km corrected aeromagnetic grid.
The six grids described in this report are available for download. Two metadata files, one for the North American grids and one for the United States grids, are also included with the gridded data.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr02414","usgsCitation":"Bankey, V., Cuevas, A., Daniels, D., Finn, C.A., Hernandez, I., Hill, P., Kucks, R., Miles, W., Pilkington, M., Roberts, C., Roest, W., Rystrom, V., Shearer, S., Snyder, S., Sweeney, R.E., Velez, J., Phillips, J., and Ravat, D., 2002, Digital data grids for the magnetic anomaly map of North America: U.S. Geological Survey Open-File Report 2002-414, HTML Document, https://doi.org/10.3133/ofr02414.","productDescription":"HTML Document","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":426141,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/70211067","text":"Magnetic anomaly map of North America"},{"id":179516,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2002/ofr-02-414/coverthb.jpg"},{"id":425660,"rank":3,"type":{"id":15,"text":"Index 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E.","contributorId":89564,"corporation":false,"usgs":true,"family":"Sweeney","given":"Ronald","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":243021,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Velez, Julio","contributorId":100941,"corporation":false,"usgs":true,"family":"Velez","given":"Julio","email":"","affiliations":[],"preferred":false,"id":243024,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Phillips, J. D. 0000-0002-6459-2821","orcid":"https://orcid.org/0000-0002-6459-2821","contributorId":22366,"corporation":false,"usgs":true,"family":"Phillips","given":"J. D.","affiliations":[],"preferred":false,"id":243012,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Ravat, D.K.A.","contributorId":89599,"corporation":false,"usgs":true,"family":"Ravat","given":"D.K.A.","email":"","affiliations":[],"preferred":false,"id":243022,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70180963,"text":"70180963 - 2002 - A model project for exploring the role of sustainability science in a citizen-centered, collaborative decision-making process","interactions":[],"lastModifiedDate":"2017-02-10T11:14:48","indexId":"70180963","displayToPublicDate":"2002-12-01T00:00:00","publicationYear":"2002","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1911,"text":"Human Ecology Review","active":true,"publicationSubtype":{"id":10}},"title":"A model project for exploring the role of sustainability science in a citizen-centered, collaborative decision-making process","docAbstract":"The role of science in society is evolving as we enter the 21st century. The report, Science — The Endless Frontier (Bush 1990[1945]), outlined a model of national scientific research that served the country for 50 years. The contract between science and society established in that report stipulated that science is essential and that basic research meets national needs (Pielke and Byerly 1998). This stipulation and the abundant — seemingly unlimited and unquestioned — funding for research during the Cold War caused many scientists to come to believe that funding for science was an entitlement independent of societal needs. Implicit in this belief is that science alone can solve society’s problems. We now are learning that many policy issues that involve science involve diverse economic, political, social, and aesthetic values as well, and rarely, if ever, is scientific information alone the basis of public policy (e.g., see Sarewitz 1996a, 1996b; Frodeman 1997). Moreover, resources are increasingly more limited and many in society are questioning the value of public-supported science.
","language":"English","publisher":"Society for Human Ecology","publisherLocation":"Bar Harbor, ME","usgsCitation":"Karl, H.A., and Turner, C., 2002, A model project for exploring the role of sustainability science in a citizen-centered, collaborative decision-making process: Human Ecology Review, v. 9, no. 1, p. 67-71.","productDescription":"5 p.","startPage":"67","endPage":"71","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":335112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335111,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.humanecologyreview.org/91.htm"}],"country":"United States","volume":"9","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"589edf2ce4b099f50d3dc5b1","contributors":{"authors":[{"text":"Karl, Herman A.","contributorId":80649,"corporation":false,"usgs":true,"family":"Karl","given":"Herman","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":662972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turner, Christine cturner@usgs.gov","contributorId":1189,"corporation":false,"usgs":true,"family":"Turner","given":"Christine","email":"cturner@usgs.gov","affiliations":[],"preferred":true,"id":662973,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70201072,"text":"70201072 - 2002 - A prototype drought monitoring system integrating climate and satellite data","interactions":[],"lastModifiedDate":"2018-12-13T10:07:46","indexId":"70201072","displayToPublicDate":"2002-11-30T09:39:10","publicationYear":"2002","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A prototype drought monitoring system integrating climate and satellite data","docAbstract":"Droughts are natural hazards with varying patterns in space, time, and intensity. Their dynamic character challenges our ability in planning, predicting, monitoring, and providing relief to affected areas. Because of the spatial and temporal variability and multiple impacts of droughts, we need to improve the tools and data available for mapping and monitoring this phenomenon on all scales. A team of researchers from the US Geological Survey’s EROS Data Center, the National Drought Mitigation Center, and the High Plains Regional Climate Center are developing methods for regional-scale mapping and monitoring drought conditions for the conterminous U.S. Currently in its first year, the project is focusing on developing a prototype model for the central U.S. The ultimate goal of the project is to deliver timely geo-referenced information (in the form of maps and data) about areas where the vegetation is impacted by drought, using the Internet as the primary delivery mechanism. Data collected from the Advanced Very High Resolution Radiometer (AVHRR) sensor provide synoptic, near real time measurements of surface conditions. Previous studies have established significant relationships between climate variables and satellite-derived vegetation indices over non-irrigated croplands and grasslands. We are researching methods for integrating information provided by satellite-derived metrics on seasonal vegetation performance and climate-based drought indicators to produce a timely and spatially-detailed drought monitoring product. Eventually, this information, coupled with map products of key drought indicators, will be available to many end users for making critical and timely decisions, from farm to regional scale.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Integrated remote sensing at the global, regional, and local scale","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"15th William T. Pecora Memorial Symposium on Remote Sensing","conferenceDate":"November 10–15, 2002","conferenceLocation":"Denver, Colorado","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","publisherLocation":"Bethesda, Maryland","usgsCitation":"Brown, J.F., Reed, B.C., Hayes, M., Wilhite, D.A., and Hubbard, K.G., 2002, A prototype drought monitoring system integrating climate and satellite data, in Integrated remote sensing at the global, regional, and local scale, Denver, Colorado, November 10–15, 2002, Paper 00074; 10 p.","productDescription":"Paper 00074; 10 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":359692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bfe65e5e4b0815414ca610b","contributors":{"authors":[{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":3241,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":752256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Bradley C. 0000-0002-1132-7178 reed@usgs.gov","orcid":"https://orcid.org/0000-0002-1132-7178","contributorId":2901,"corporation":false,"usgs":true,"family":"Reed","given":"Bradley","email":"reed@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":752257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Michael J.","contributorId":197222,"corporation":false,"usgs":false,"family":"Hayes","given":"Michael J.","affiliations":[{"id":34856,"text":"National Drought Mitigation Center, Unversity of Nebraska","active":true,"usgs":false}],"preferred":false,"id":752258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilhite, Donald A.","contributorId":210837,"corporation":false,"usgs":false,"family":"Wilhite","given":"Donald","email":"","middleInitial":"A.","affiliations":[{"id":34856,"text":"National Drought Mitigation Center, Unversity of Nebraska","active":true,"usgs":false}],"preferred":false,"id":752259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hubbard, Kenneth G.","contributorId":177373,"corporation":false,"usgs":false,"family":"Hubbard","given":"Kenneth","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":752260,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189690,"text":"70189690 - 2002 - Is it More Important to Characterize Heterogeneity or Differences in Hydraulic Conductivity Measurements?","interactions":[],"lastModifiedDate":"2017-07-20T11:20:07","indexId":"70189690","displayToPublicDate":"2002-11-28T00:00:00","publicationYear":"2002","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Is it More Important to Characterize Heterogeneity or Differences in Hydraulic Conductivity Measurements?","docAbstract":"As a first step toward understanding the role of sedimentary structures in flow and transport through porous media, this work deterministically examines how transport simulations compare to observed transport through simple, artificial structures in a laboratory experiment. Small-scale laboratory-measured values of hydraulic conductivity were used to simulate transport in an intermediate-scale (10-m long), two-dimensional, heterogeneous porous medium (s 2 lnK=1.26, mlnK = 4.18, where K is cm hr-1 ). Results were judged based on how well the simulated transport matched observed transport through the tank. Permeameter and column experiments produced laboratory measurements of hydraulic conductivity for each of the five sands used in the intermediate-scale experiments. Despite explicit numerical representation of the heterogeneity, predictions using the laboratory-measured values under-estimated the mean arrival time by as much as 35%. The significance of differences between simulated and observed mean arrival time was investigated by comparing variability of transport predictions using the different measurement methods to that produced by different realizations of the heterogeneous distribution. Results indicate that the variations in measured hydraulic conductivity were more important to transport than variations between realizations of the heterogeneous distribution of hydraulic conductivity.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"”Bridging the gap between measurements and modelling”, Special issue with selected papers from the IAHR International Groundwater","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Bridging the Gap Between Measurement and Modeling - Groundwater 2002","conferenceDate":"March 2002","language":"English ","publisher":"International Association for Hydro-Environment Engineering and Research","usgsCitation":"Barth, G., Hill, M.C., Illangasekare, T.H., and Rajaram, H., 2002, Is it More Important to Characterize Heterogeneity or Differences in Hydraulic Conductivity Measurements?, in ”Bridging the gap between measurements and modelling”, Special issue with selected papers from the IAHR International Groundwater, March 2002, 8 p. .","productDescription":"8 p. ","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":344118,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":344117,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sspa.com/conference-proceedings"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5971c1c7e4b0ec1a4885daf7","contributors":{"authors":[{"text":"Barth, G.","contributorId":7069,"corporation":false,"usgs":true,"family":"Barth","given":"G.","email":"","affiliations":[],"preferred":false,"id":705830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":705831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Illangasekare, Tissa H.","contributorId":194933,"corporation":false,"usgs":false,"family":"Illangasekare","given":"Tissa","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":705832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rajaram, Harihar","contributorId":61328,"corporation":false,"usgs":true,"family":"Rajaram","given":"Harihar","affiliations":[],"preferred":false,"id":705833,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70206236,"text":"70206236 - 2002 - Time‐lapse inversion of crosswell radar data","interactions":[],"lastModifiedDate":"2019-10-25T12:07:06","indexId":"70206236","displayToPublicDate":"2002-11-01T12:02:24","publicationYear":"2002","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1808,"text":"Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Time‐lapse inversion of crosswell radar data","docAbstract":"The combination of differential radar tomography with conventional tracer and/or hydraulic tests facilitates high‐resolution characterization of subsurface heterogeneity and enables the identification of preferential flow paths. In dynamic imaging, each tomogram is typically inverted independently, under the assumption that data sets are collected quickly relative to changes in the imaged property (e.g., attenuation or velocity); however, such “snapshot” tomograms may contain large errors if the imaged property changes significantly during data collection. Acquisition of less data over a shorter time interval could ameliorate the problem, but the resulting decrease in ray density and angular coverage could degrade model resolution. To address these problems, we propose a new sequential approach for time‐lapse tomographic inversion. The method uses space‐time parameterization and regularization to combine data collected at multiple times and to account for temporal variation. The inverse algorithm minimizes the sum of weighted squared residuals and a measure of solution complexity based on an a priori space‐time covariance function and a spatiotemporally variable mean. We demonstrate our approach using a synthetic 2‐D time‐lapse (x,z,t) data set based loosely on a field experiment in which difference‐attenuation radar tomography was used to monitor the migration of a saline tracer in fractured rock. We quantitatively show the benefits of space‐time inversion by comparing results for snapshot and time‐lapse inversion schemes. Inversion over both space and time results in superior estimation error, model resolution, and data reproduction compared to conventional snapshot inversion. Finally, we suggest strategies to improve time‐lapse cross‐hole inversions using ray‐based inversion constraints and a modified survey design in which different sets of rays are collected in alternating time steps.
","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/1.1527075","usgsCitation":"Day-Lewis, F.D., Harris, J.M., and Gorelick, S.M., 2002, Time‐lapse inversion of crosswell radar data: Geophysics, v. 67, no. 6, p. 1740-1752, https://doi.org/10.1190/1.1527075.","productDescription":"13 p.","startPage":"1740","endPage":"1752","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":368611,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"67","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":773900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Jerry M.","contributorId":4116,"corporation":false,"usgs":false,"family":"Harris","given":"Jerry","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":773901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorelick, Steven M.","contributorId":8784,"corporation":false,"usgs":true,"family":"Gorelick","given":"Steven","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":773902,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":50746,"text":"wri024185 - 2002 - Flow-system analysis of the Madison and Minnelusa aquifers in the Rapid City area, South Dakota — Conceptual model","interactions":[],"lastModifiedDate":"2022-01-18T22:47:50.271307","indexId":"wri024185","displayToPublicDate":"2002-11-01T00:00:00","publicationYear":"2002","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2002-4185","title":"Flow-system analysis of the Madison and Minnelusa aquifers in the Rapid City area, South Dakota — Conceptual model","docAbstract":"The conceptual model of the Madison and Minnelusa aquifers in the Rapid City area synthesizes the physical geography, hydraulic properties, and ground-water flow components of these important aquifers. The Madison hydrogeologic unit includes the karstic Madison aquifer, which is defined as the upper, more permeable 100 to 200 ft of the Madison Limestone, and the Madison confining unit, which consists of the lower, less permeable part of the Madison Limestone and the Englewood Formation. Overlying the Madison hydrogeologic unit is the Minnelusa hydrogeologic unit, which includes the Minnelusa aquifer in the upper, more permeable 200 to 300 ft and the Minnelusa confining unit in the lower, less permeable part. The Madison and Minnelusa hydrogeologic units outcrop in the study area on the eastern flank of the Black Hills where recharge occurs from streamflow losses and areal recharge. The conceptual model describes streamflow recharge, areal recharge, ground-water flow, storage in aquifers and confining units, unsaturated areas, leakage between aquifers, discharge from artesian springs, and regional outflow.
Effective transmissivities estimated for the Madison aquifer range from 500 to 20,000 ft2/d and for the Minnelusa aquifer from 500 to 10,000 ft2/d. Localized anisotropic transmissivity in the Madison aquifer has tensor ratios as high as 45:1. Vertical hydraulic conductivities for the Minnelusa confining unit determined from aquifer tests range from 1.3x10-3 to 3.0x10-1 ft/d. The confined storage coefficient of the Madison and Minnelusa hydrogeologic units was estimated as 3x10-4 ft/d. Specific yield was estimated as 0.09 for the Madison and Minnelusa aquifers and 0.03 for the Madison and Minnelusa confining units. Potentiometric surfaces for the Madison and Minnelusa aquifers have a general easterly gradient of about 70 ft/mi with local variations. Temporal change in hydraulic head in the Madison and Minnelusa aquifers ranged from about 5 to 95 ft in water years 1988-97. The unconfined areas were estimated at about 53 and 36 mi2 for the Madison and Minnelusa hydrogeologic units, respectively, in contrast to an aquifer analysis area of 629 mi2.
Dye-tracer tests, stable isotopes, and hydrogeologic features were analyzed conjunctively to estimate generalized ground-water flowpaths in the Madison aquifer and their influences on the Minnelusa aquifer. The western Rapid City area between Boxelder Creek and Spring Creek was characterized as having undergone extensive tectonic activity, greater brecciation in the Minnelusa Formation, large transmissivities, generally upward hydraulic gradients from the Madison aquifer to the Minnelusa aquifer, many karst springs, and converging flowpaths.
Water-budget analysis included: (1) a dry-period budget for declining water levels; October 1, 1987, to March 31, 1993; (2) a wet-period budget for rising water levels, April 1, 1993, to September 30, 1997; and (3) a full 10-year period budget for water years 1988-97. By simultaneously balancing these water budgets, initial estimates of recharge, discharge, change in storage, and hydraulic properties were refined. Inflow rates for the 10-year budget included streamflow recharge of about 45 ft3/s or 61 percent of the total budget and areal recharge of 22 ft3/s or 30 percent. Streamflow recharge to the Madison hydrogeologic unit was about 86 percent of the total streamflow recharge. Outflow for the 10-year budget included springflow of 31 ft3/s or 42 percent of the total budget, water use of about 10 ft3/s or 14 percent, and regional outflow of 22 ft3/s or 30 percent. Ground-water storage increased 9 ft3/s during the 10-year period, and net ground-water movement from the Madison to Minnelusa hydrogeologic unit was about 8 ft3/s.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/wri024185","usgsCitation":"Long, A.J., and Putnam, L.D., 2002, Flow-system analysis of the Madison and Minnelusa aquifers in the Rapid City area, South Dakota — Conceptual model: U.S. Geological Survey Water-Resources Investigations Report 2002-4185, vii, 100 p., https://doi.org/10.3133/wri024185.","productDescription":"vii, 100 p.","costCenters":[],"links":[{"id":175295,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":4237,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/wri024185/","linkFileType":{"id":5,"text":"html"}},{"id":394486,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_52784.htm"}],"country":"United States","state":"South Dakota","city":"Rapid City","otherGeospatial":"Madison and Minnelusa aquifers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.5296630859375,\n 43.810747313446996\n ],\n [\n -102.9144287109375,\n 43.810747313446996\n ],\n [\n -102.9144287109375,\n 44.422011314236634\n ],\n [\n -103.5296630859375,\n 44.422011314236634\n ],\n [\n -103.5296630859375,\n 43.810747313446996\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e478ee4b07f02db489a6a","contributors":{"authors":[{"text":"Long, Andrew J. 0000-0001-7385-8081 ajlong@usgs.gov","orcid":"https://orcid.org/0000-0001-7385-8081","contributorId":989,"corporation":false,"usgs":true,"family":"Long","given":"Andrew","email":"ajlong@usgs.gov","middleInitial":"J.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":242218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Putnam, Larry D. ldputnam@usgs.gov","contributorId":990,"corporation":false,"usgs":true,"family":"Putnam","given":"Larry","email":"ldputnam@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":242219,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159118,"text":"70159118 - 2002 - Assessing satellite-derived start-of-season measures in the conterminous USA","interactions":[],"lastModifiedDate":"2015-10-15T13:27:51","indexId":"70159118","displayToPublicDate":"2002-11-01T00:00:00","publicationYear":"2002","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Assessing satellite-derived start-of-season measures in the conterminous USA","docAbstract":"National Oceanic and Atmospheric Administration (NOAA)-series satellites, carrying advanced very high-resolution radiometer (AVHRR) sensors, have allowed moderate resolution (1 km) measurements of the normalized difference vegetation index (NDVI) to be collected from the Earth's land surfaces for over 20 years. Across the conterminous USA, a readily accessible and decade-long data set is now available to study many aspects of vegetation activity in this region. One feature, the onset of deciduous plant growth at the start of the spring season (SOS) is of special interest, as it appears to be crucial for accurate computation of several important biospheric processes, and a sensitive measure of the impacts of global change.
\nIn this study, satellite-derived SOS dates produced by the delayed moving average (DMA) and seasonal midpoint NDVI (SMN) methods, and modelled surface phenology (spring indices, SI) were compared at widespread deciduous forest and mixed woodland sites during 1990–93 and 1995–99, and these three measures were also matched to native species bud-break data collected at the Harvard Forest (Massachusetts) over the same time period. The results show that both SOS methods are doing a modestly accurate job of tracking the general pattern of surface phenology, but highlight the temporal limitations of biweekly satellite data. Specifically, at deciduous forest sites: (1) SMN SOS dates are close in time to SI first bloom dates (average bias of +0.74 days), whereas DMA SOS dates are considerably earlier (average bias of −41.24 days) and also systematically earlier in late spring than in early spring; (2) SMN SOS tracks overall yearly trends in deciduous forests somewhat better than DMA SOS, but with larger average error (MAEs 8.64 days and 7.37 days respectively); and (3) error in both SOS techniques varies considerably by year. Copyright © 2002 Royal Meteorological Society.
\nThese maps present the results of assessments of peak discharges that can potentially be generated by debris flows issuing from the basins burned by the Coal Seam fire of June and July 2002, near Glenwood Springs, Colorado. The maps are based on a regression model for debris-flow peak discharge normalized by average storm intensity as a function of basin gradient and burned extent, and limited field checking. A range of potential peak discharges that could potentially be produced from each of the burned basins between 1 ft3/s (0.03 m3/s) and greater than 5,000 ft3/s (>141 m3/s) is calculated for the 5-year, 1-hour storm of 0.80 inches (20 mm). The 25-year, 1-hour storm of 1.3 inches (33 mm). The 100- year, 1-hour storm of 1.8 inches (46 mm) produced peak discharges between 1 and greater than 8,000 ft3/s (>227 m3/s). These maps are intended for use by emergency personnel to aid in the preliminary design of mitigation measures, and the planning of evacuation timing and routes.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr02379","usgsCitation":"Cannon, S.H., Michael, J.A., Gartner, J.E., Rea, A.H., and Garcia, S.P., 2002, Emergency assessment of potential debris-flow peak discharges, Coal Seam fire, Colorado (Version 1.0): U.S. Geological Survey Open-File Report 2002-379, 1 Plate: 53.00 × 36.00 inches, https://doi.org/10.3133/ofr02379.","productDescription":"1 Plate: 53.00 × 36.00 inches","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":409006,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_52356.htm","linkFileType":{"id":5,"text":"html"}},{"id":178354,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":4344,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2002/ofr-02-0379/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","otherGeospatial":"Coal Seam fire","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.4583,\n 39.633\n ],\n [\n -107.4583,\n 39.5\n ],\n [\n -107.2917,\n 39.5\n ],\n [\n -107.2917,\n 39.633\n ],\n [\n -107.4583,\n 39.633\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a19e4b07f02db60597a","contributors":{"authors":[{"text":"Cannon, Susan H. cannon@usgs.gov","contributorId":1019,"corporation":false,"usgs":true,"family":"Cannon","given":"Susan","email":"cannon@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":241715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Michael, John A. jmichael@usgs.gov","contributorId":1877,"corporation":false,"usgs":true,"family":"Michael","given":"John","email":"jmichael@usgs.gov","middleInitial":"A.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":241718,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gartner, Joseph E. jegartner@usgs.gov","contributorId":1876,"corporation":false,"usgs":true,"family":"Gartner","given":"Joseph","email":"jegartner@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":241717,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rea, Alan H. ahrea@usgs.gov","contributorId":1813,"corporation":false,"usgs":true,"family":"Rea","given":"Alan","email":"ahrea@usgs.gov","middleInitial":"H.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":241716,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garcia, Steven P.","contributorId":78009,"corporation":false,"usgs":true,"family":"Garcia","given":"Steven","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":241719,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":50518,"text":"ofr02346 - 2002 - Intensity distribution and isoseismal maps for the Nisqually, Washington, earthquake of 28 February 2001","interactions":[],"lastModifiedDate":"2012-02-02T00:11:16","indexId":"ofr02346","displayToPublicDate":"2002-11-01T00:00:00","publicationYear":"2002","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":"2002-346","title":"Intensity distribution and isoseismal maps for the Nisqually, Washington, earthquake of 28 February 2001","docAbstract":"We present isoseismal maps, macroseismic intensities, and\r\ncommunity summaries of damage for the MW=6.8\r\nNisqually, Washington, earthquake of 28 February, 2001.\r\nFor many communities, two types of macroseismic intensity\r\nare assigned, the traditional U.S. Geological Survey\r\nModified Mercalli Intensities (USGS MMI) and a type of\r\nintensity newly introduced with this paper, the USGS\r\nReviewed Community Internet Intensity (RCII). For most\r\ncommunities, the RCII is a reviewed version of the\r\nCommunity Internet Intensity (CII) of Wald and others\r\n(1999). For some communities, RCII is assigned from\r\nsuch non-CII sources as press reports, engineering reports,\r\nand field reconnaissance observations. We summarize differences\r\nbetween procedures used to assign RCII and\r\nUSGS MMI, and we show that the two types of intensity\r\nare nonetheless very similar for the Nisqually earthquake.\r\nWe do not see evidence for systematic differences between\r\nRCII and USGS MMI that would approach one intensity\r\nunit, at any level of shaking, but we document a tendency\r\nfor the RCII to be slightly lower than MMI in regions of\r\nlow intensity and slightly higher than MMI in regions of\r\nhigh intensity. The highest RCII calculated for the\r\nNisqually earthquake is 7.6, calculated for zip code 98134,\r\nwhich includes the ?south of downtown? (Sodo) area of\r\nSeattle and Harbor Island. By comparison, we assigned a\r\ntraditional USGS MMI 8 to the Sodo area of Seattle. In\r\nall, RCII of 6.5 and higher were assigned to 58 zip-code\r\nregions. At the lowest intensities, the Nisqually earthquake\r\nwas felt over an area of approximately 350,000 square km\r\n(approximately 135,000 square miles) in Washington,\r\nOregon, Idaho, Montana, and southern British Columbia,\r\nCanada. On the basis of macroseismic effects, we infer\r\nthat shaking in the southern Puget Sound region was\r\nsomewhat less for the 2001 Nisqually earthquake than for\r\nthe Puget Sound earthquake of April 13, 1949, which had\r\nnearly the same hypocenter and magnitude. Allowing for\r\ndifferences in hypocenter, shaking in the 2001 earthquake\r\nwas very similar to that produced by the Puget Sound\r\nearthquake of April 25, 1965. First-person accounts of the\r\neffects of the 2001 earthquake on individual households\r\nare given for some communities.","language":"ENGLISH","doi":"10.3133/ofr02346","usgsCitation":"Dewey, J.W., Hopper, M.G., Wald, D.J., Quitoriano, V., and Adams, E.R., 2002, Intensity distribution and isoseismal maps for the Nisqually, Washington, earthquake of 28 February 2001 (Version 1.0): U.S. Geological Survey Open-File Report 2002-346, 57 p., illus. incl. sketch maps, 23 refs, https://doi.org/10.3133/ofr02346.","productDescription":"57 p., illus. incl. sketch maps, 23 refs","costCenters":[],"links":[{"id":175485,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":4330,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2002/ofr-02-0346/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49dbe4b07f02db5e10f6","contributors":{"authors":[{"text":"Dewey, James W. 0000-0001-8838-2450 jdewey@usgs.gov","orcid":"https://orcid.org/0000-0001-8838-2450","contributorId":5819,"corporation":false,"usgs":true,"family":"Dewey","given":"James","email":"jdewey@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":241671,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hopper, Margaret G. hopper@usgs.gov","contributorId":2227,"corporation":false,"usgs":true,"family":"Hopper","given":"Margaret","email":"hopper@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":241670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":241669,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quitoriano, Vincent","contributorId":29514,"corporation":false,"usgs":true,"family":"Quitoriano","given":"Vincent","email":"","affiliations":[],"preferred":false,"id":241672,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Elizabeth R.","contributorId":56102,"corporation":false,"usgs":true,"family":"Adams","given":"Elizabeth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":241673,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":50516,"text":"ofr02342 - 2002 - Catalog of earthquake hypocenters at Alaskan volcanoes: January 1, 2000 through December 31, 2001","interactions":[],"lastModifiedDate":"2016-09-07T15:08:43","indexId":"ofr02342","displayToPublicDate":"2002-11-01T00:00:00","publicationYear":"2002","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":"2002-342","title":"Catalog of earthquake hypocenters at Alaskan volcanoes: January 1, 2000 through December 31, 2001","docAbstract":"The Alaska Volcano Observatory (AVO), a cooperative program of the U.S. Geological Survey, the Geophysical Institute of the University of Alaska Fairbanks, and the Alaska Division of Geological and Geophysical Surveys, has maintained seismic monitoring networks at potentially active volcanoes in Alaska since 1988 (Power and others, 1993; Jolly and others, 1996; Jolly and others, 2001). The primary objectives of this program are the seismic surveillance of active, potentially hazardous, Alaskan volcanoes and the investigation of seismic processes associated with active volcanism. This catalog reflects the status and evolution of the seismic monitoring program, and presents the basic seismic data for the time period January 1, 2000, through December 31, 2001. For an interpretation of these data and previously recorded data, the reader should refer to several recent articles on volcano related seismicity on Alaskan volcanoes in Appendix G.
The AVO seismic network was used to monitor twenty-three volcanoes in real time in 2000-2001. These include Mount Wrangell, Mount Spurr, Redoubt Volcano, Iliamna Volcano, Augustine Volcano, Katmai Volcanic Group (Snowy Mountain, Mount Griggs, Mount Katmai, Novarupta, Trident Volcano, Mount Mageik, Mount Martin), Aniakchak Crater, Pavlof Volcano, Mount Dutton, Isanotski Peaks, Shishaldin Volcano, Fisher Caldera, Westdahl Peak, Akutan Peak, Makushin Volcano, Great Sitkin Volcano, and Kanaga Volcano (Figure 1). AVO located 1551 and 1428 earthquakes in 2000 and 2001, respectively, on and around these volcanoes.
Highlights of the catalog period (Table 1) include: volcanogenic seismic swarms at Shishaldin Volcano between January and February 2000 and between May and June 2000; an eruption at Mount Cleveland between February and May 2001; episodes of possible tremor at Makushin Volcano starting March 2001 and continuing through 2001, and two earthquake swarms at Great Sitkin Volcano in 2001.
This catalog includes: (1) earthquake origin times, hypocenters, and magnitudes with summary statistics describing the earthquake location quality; (2) a description of instruments deployed in the field and their locations; (3) a description of earthquake detection, recording, analysis, and data archival systems; (4) station parameters and velocity models used for earthquake locations; (5) a summary of daily station usage throughout the catalog period; and (6) all HYPOELLIPSE files used to determine the earthquake locations presented in this report.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr02342","usgsCitation":"Dixon, J.P., Stihler, S.D., Power, J.A., Tytgat, G., Estes, S., Moran, S.C., Paskievitch, J., and McNutt, S.R., 2002, Catalog of earthquake hypocenters at Alaskan volcanoes: January 1, 2000 through December 31, 2001: U.S. Geological Survey Open-File Report 2002-342, Report: PDF, 56 p.; Report: TXT; Appendix F; Data, https://doi.org/10.3133/ofr02342.","productDescription":"Report: PDF, 56 p.; Report: TXT; Appendix F; Data","numberOfPages":"56","additionalOnlineFiles":"Y","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":176638,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr02342.jpg"},{"id":283822,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2002/0342/catalogavo.txt"},{"id":283821,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2002/0342/pdf/of02-342.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":283823,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2002/0342/pdf/appendixf.pdf","text":"Appendix F","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix F"},{"id":283824,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2002/0342/avocatalog2000_2001.tar.z.Z","text":"Data Files","size":"2.7 MB","description":"Data Files"},{"id":4328,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2002/0342/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,51.21 ], [ -180.0,67.0 ], [ -140.0,67.0 ], [ -140.0,51.21 ], [ -180.0,51.21 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49f3e4b07f02db5ef8a2","contributors":{"authors":[{"text":"Dixon, James P. 0000-0002-8478-9971 jpdixon@usgs.gov","orcid":"https://orcid.org/0000-0002-8478-9971","contributorId":3163,"corporation":false,"usgs":true,"family":"Dixon","given":"James","email":"jpdixon@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":241658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stihler, Scott D.","contributorId":31373,"corporation":false,"usgs":true,"family":"Stihler","given":"Scott","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":241659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Power, John A. 0000-0002-7233-4398 jpower@usgs.gov","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":2768,"corporation":false,"usgs":true,"family":"Power","given":"John","email":"jpower@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":241657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tytgat, Guy","contributorId":71152,"corporation":false,"usgs":true,"family":"Tytgat","given":"Guy","email":"","affiliations":[],"preferred":false,"id":241662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Estes, Steve","contributorId":55881,"corporation":false,"usgs":true,"family":"Estes","given":"Steve","email":"","affiliations":[],"preferred":false,"id":241661,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moran, Seth C. 0000-0001-7308-9649 smoran@usgs.gov","orcid":"https://orcid.org/0000-0001-7308-9649","contributorId":548,"corporation":false,"usgs":true,"family":"Moran","given":"Seth","email":"smoran@usgs.gov","middleInitial":"C.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":241656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Paskievitch, John","contributorId":74050,"corporation":false,"usgs":true,"family":"Paskievitch","given":"John","affiliations":[],"preferred":false,"id":241663,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McNutt, Stephen R.","contributorId":38133,"corporation":false,"usgs":true,"family":"McNutt","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":241660,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":50522,"text":"ofr02352 - 2002 - Preliminary report on geophysical data in Yavapai County, Arizona","interactions":[],"lastModifiedDate":"2023-06-27T14:24:15.185096","indexId":"ofr02352","displayToPublicDate":"2002-11-01T00:00:00","publicationYear":"2002","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":"2002-352","title":"Preliminary report on geophysical data in Yavapai County, Arizona","docAbstract":"Recently acquired geophysical data provide information on the geologic framework and its effect of groundwater flow and on stream/aquifer interaction in Yavapai County, Arizona. High-resolution aeromagnetic data reflect diverse rock types at and below the topographic surface and have permitted a preliminary interpretation of faults and underlying rock types (in particular, volcanic) that will provide new insights on the geologic framework, critical input to future hydrologic investigations. Aeromagnetic data map the western end of the Bear Wallow Canyon fault into the sedimentary fill of Verde Valley. Regional gravity data indicate potentially significant accumulations of low-density basin fill in Big Chino, Verde, and Williamson Valleys. Electrical and seismic data were also collected and help evaluate the approximate depth and extent of recent alluvium overlying Tertiary and Paleozoic sediments. These data will be used to ascertain the potential contribution of shallow ground-water subflow that cannot be measured by gages or flow meters and whether stream flow in losing reaches is moving as subflow or is being lost to the subsurface. The geophysical data will help produce a more robust groundwater flow model of the region.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr02352","usgsCitation":"Langenheim, V., Hoffmann, J., Blasch, K., DeWitt, E., and Wirt, L., 2002, Preliminary report on geophysical data in Yavapai County, Arizona: U.S. Geological Survey Open-File Report 2002-352, Report: PDF, 29 p.; Report: TXT, https://doi.org/10.3133/ofr02352.","productDescription":"Report: PDF, 29 p.; Report: TXT","numberOfPages":"30","additionalOnlineFiles":"Y","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":283851,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr02352.jpg"},{"id":86332,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2002/0352/pdf/of02-352.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":4334,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2002/0352/","linkFileType":{"id":5,"text":"html"}},{"id":283850,"rank":1,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2002/0352/ofr02-352.txt","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"Arizona","county":"Yavapai County","otherGeospatial":"Bear Wallow Canyon, Big Chino Valley, Verde Valley, Williamson Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.9999,34.348 ], [ -112.9999,35.268 ], [ -111.5977,35.268 ], [ -111.5977,34.348 ], [ -112.9999,34.348 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aafe4b07f02db66cba5","contributors":{"authors":[{"text":"Langenheim, V.E. 0000-0003-2170-5213","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":54956,"corporation":false,"usgs":true,"family":"Langenheim","given":"V.E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":241682,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoffmann, J.P.","contributorId":76389,"corporation":false,"usgs":true,"family":"Hoffmann","given":"J.P.","email":"","affiliations":[],"preferred":false,"id":241684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blasch, K.W.","contributorId":29877,"corporation":false,"usgs":true,"family":"Blasch","given":"K.W.","affiliations":[],"preferred":false,"id":241681,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeWitt, Ed","contributorId":65081,"corporation":false,"usgs":true,"family":"DeWitt","given":"Ed","affiliations":[],"preferred":false,"id":241683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wirt, Laurie","contributorId":13204,"corporation":false,"usgs":true,"family":"Wirt","given":"Laurie","affiliations":[],"preferred":false,"id":241680,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70161957,"text":"70161957 - 2002 - Modeling fish community dynamics in Florida Everglades: Role of temperature variation","interactions":[],"lastModifiedDate":"2016-01-11T11:22:23","indexId":"70161957","displayToPublicDate":"2002-11-01T00:00:00","publicationYear":"2002","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3724,"text":"Water Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling fish community dynamics in Florida Everglades: Role of temperature variation","docAbstract":"Temperature variation is an important factor in Everglade wetlands ecology. A temperature fluctuation from 17°C to 32°C recorded in the Everglades may have significant impact on fish dynamics. The short life cycles of some of Everglade fishes has rendered this temperature variation to have even more impacts on the ecosystem. Fish population dynamic models, which do not explicitly consider seasonal oscillations in temperature, may fail to describe the details of such a population. Hence, a model for fish in freshwater marshes of the Florida Everglades that explicitly incorporates seasonal temperature variations is developed. The model's main objective is to assess the temporal pattern of fish population and densities through time subject to temperature variations. Fish population is divided into 2 functional groups (FGs) consisting of small fishes; each group is subdivided into 5-day age classes during their life cycles. Many governing sub-modules are set directly or indirectly to be temperature dependent. Growth, fecundity, prey availability, consumption rates and mortality are examples. Several mortality sub-modules are introduced in the model, of which starvation mortality is set to be proportional to the ratio of prey needed to prey available at that particular time step. As part of the calibration process, the model is run for 50 years to ensure that fish densities do not go to extinction, while the simulation period is about 8 years.
\nThe model shows that the temperature dependent starvation mortality is an important factor that influences fish population densities. It also shows high fish population densities at some temperature ranges when this consumption need is minimum. Several sensitivity analyses involving variations in temperature terms, food resources and water levels are conducted to ascertain the relative importance of temperature dependence terms.
","language":"English","publisher":"IWA Publishing","usgsCitation":"Al-Rabai’ah, H.A., Koh, H.L., DeAngelis, D., and Lee, H., 2002, Modeling fish community dynamics in Florida Everglades: Role of temperature variation: Water Science and Technology, v. 46, no. 9, p. 71-78.","productDescription":"8 p.","startPage":"71","endPage":"78","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":314112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":314111,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://wst.iwaponline.com/content/46/9/71"}],"volume":"46","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5694e049e4b039675d005e3b","contributors":{"authors":[{"text":"Al-Rabai’ah, H. A.","contributorId":152147,"corporation":false,"usgs":false,"family":"Al-Rabai’ah","given":"H.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":588194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koh, H. 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Gamma-gamma density logs from two wells in Frenchman Flat constrained the density profiles used to create the gravity inversion model. Three initial models were considered using data from one well, then a final model is proposed based on new information from the second well. The preferred model indicates that a northeast-trending oval-shaped basin underlies Frenchman Flat at least 2,100 m deep, with a maximum depth of 2,400 m at its northeast end. No major horst and graben structures are predicted. Sensitivity analysis of the model indicates that each parameter contributes the same magnitude change to the model, up to 30 meters change in depth for a 1% change in density, but some parameters affect a broader area of the basin. The horizontal resolution of the model was determined by examining the spacing between data stations, and was set to 500 square meters.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr02363","usgsCitation":"Phelps, G., and Graham, S.E., 2002, Preliminary gravity inversion model of Frenchman Flat Basin, Nevada Test Site, Nevada: U.S. Geological Survey Open-File Report 2002-363, Report: 23 p.; 1 Plate: 21.61 x 30.53 inches, https://doi.org/10.3133/ofr02363.","productDescription":"Report: 23 p.; 1 Plate: 21.61 x 30.53 inches","additionalOnlineFiles":"Y","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":175711,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr02363.jpg"},{"id":283852,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2002/0363/pdf/of02-363plate1.pdf","text":"Plate 1"},{"id":283855,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2002/0363/of02-363depthdata.asc"},{"id":283854,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2002/0363/of02-363metadata.txt"},{"id":283853,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2002/0363/pdf/of02-363.pdf"},{"id":4338,"rank":6,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2002/0363/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Universal Transverse Mercator, zone 11","datum":"North American Datum of 1927","country":"United States","state":"Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.000,36.750 ], [ -116.000,36.875 ], [ -115.800,36.875 ], [ -115.800,36.750 ], [ -116.000,36.750 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afee4b07f02db697503","contributors":{"authors":[{"text":"Phelps, Geoffrey A.","contributorId":17262,"corporation":false,"usgs":true,"family":"Phelps","given":"Geoffrey A.","affiliations":[],"preferred":false,"id":241693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Scott E. sgraham@usgs.gov","contributorId":2907,"corporation":false,"usgs":true,"family":"Graham","given":"Scott","email":"sgraham@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":241692,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}