Soil attributes, climate, and time since reclamation have important implications for oil and gas reclamation success on drylands. It is uncertain if reclaimed well pads, on highly degraded drylands, can successfully regain ecological function or meet indicator benchmarks for reclamation. Here, our goals were to assess patterns in reclamation outcomes relative to (1) soil attributes, climate, and time since reclamation; and (2) plant and soil reference benchmarks. We collected a suite of plant, soil, and landscape characteristics from 134 reclaimed well pads on the Colorado Plateau that spanned climate and soil gradients and ranged from 2 to 20 years post-reclamation, then compared characteristics to those from 583 reference plots. On the reclaimed pads, less saline soils, more mesic climates, and longer time since reclamation were associated with favorable reclamation outcomes based on metrics of plant species richness and diversity, plant structure, and cover of important plant functional groups. However, most pads had major departures in 1/4 indicators, suggesting unsuccessful reclamation. Arid warm locations with shallow soils had the greatest percentage of major departures, and noxious plant richness had the greatest departures across soil and climate settings. Our assessment indicates reclamation is failing in key metrics for most pads, and the results highlight the role of environmental conditions in driving reclamation outcomes. These new insights are valuable for ascertaining possible reclamation outcomes and success rates following energy related disturbance, including orphaned wells and renewable energy development. Importantly, the approach used here has applicability for setting benchmarks and outcome standards.
Explosive eruptions at basaltic volcanoes remain poorly understood. Kīlauea Volcano is a type locality for basaltic eruptions and is well-known for effusive activity. However, more than 7 m of phreatomagmatic Keanakākoʻi Tephra unit D deposits from explosive eruptions crown the southern rim of the summit caldera and provide a stark reminder of Kīlauea’s explosive past and future potential. We used detailed field observations as well as granulometric and morphological analysis of 100 samples from two proximal sections to assess the eruption style and fragmentation mechanism. The deposits can be divided into four subunits, six different lithofacies, and contain three juvenile tephra components. Each juvenile component shows distinct shape variability resulting from molten fuel-coolant interaction (MFCI) explosions of magma of variable vesicularity. Fragmentation of dense glass generates olive-green ash, fragmentation of low to moderately vesicular magma generates a dark gray ash-lapilli component, and fragmentation of highly vesicular magma generates light-yellow pumice. Our work shows that magma structure impacts MFCI explosion efficiency. Small-scale planar bedding throughout most of the deposit points to a general eruption style of small, frequent explosions generating low plumes. Thicker beds of accretionary lapilli of fine-extremely fine ash are related to very efficient magma-water mixing. Pyroclastic density current (PDC) deposits in the upper part of the stratigraphy contain at least three flows but show no significant dune or cross-bedding structures. We suggest that this is a function of the vent being situated in a caldera that was then ∼600 m deep, where the caldera wall acted as a barrier and changed the flow dynamics to very dilute overspills and co-PDC plume falls over the wall. Deconvolution modeling of the polymodal grain size distributions is used to assess grain size changes of each juvenile component for this deposit, which greatly improves interpretation of lithofacies generation and eruption dynamics. Size-correlated shape parameters show that shape data across a wide size range are needed to accurately track grain shapes. This study demonstrates how careful examination of grain size and shape of juvenile tephra clasts can help volcanologists understand how effusive basaltic volcanoes can become violently explosive.
Four days after the 12 May 2008 M 7.9 Wenchuan earthquake struck the Sichuan region of China, we submitted a prospective earthquake forecast based on transfer of stress from the mainshock onto significant faults crossing through populated areas. We identified where the largest aftershocks were likely to occur that could cause loss of life. We returned the revised article to the journal on 5 June 2008, marking the last day of our observation period. The primary testable features are locations and focal mechanisms of larger (M ≥ 4.5) earthquakes; did these events happen on or very near the faults we said they would? Did they have the same strikes, dips, and rakes as the faults we modeled? In retrospect, is the stress transfer method consistent with all M ≥ 4.5 earthquakes that occurred? We find all but one M ≥ 4.5 aftershock with known focal mechanisms located on stress‐increased faults, and their focal mechanism parameters overlap with geological characteristics we used in making calculations. Six of the seven lethal M > 4.5 earthquakes that occurred in the region since 5 June 2008 were located on stress‐increased faults, with the lone exception triggered by hydraulic fracturing.
The Hawaiian hoary bat (Lasiurus semotus; Chiroptera: Vespertilionidae), commonly and locally known as ‘ōpe‘ape‘a, is a solitary, insectivorous, and foliage-roosting species distributed across a wide range of habitats in lowland and montane environments. The species, as with many others in the Hawaiian archipelago, are facing a suite of challenges due to habitat loss and degradation, introduced predators and pests, and climate change. An understanding of the roost requirements of foliage-roosting tree bats is critical to their conservation as these habitats provide several important benefits to survival and reproduction. Because little is known about ‘ōpe‘ape‘a roost ecology and considerable effort is needed to capture and track bats to roost locations, we examined resource selection at multiple spatial scales—perch location within a roost tree, roost tree, and forest stand. We used a discrete choice modeling approach to investigate day-roost selection and describe attributes of roost trees including those used as maternity roosts. ‘Ōpe‘ape‘a were found roosting in 19 tree species and in an assortment of landcover types including native and non-native habitats. Our results are largely consistent with findings of other studies of foliage-roosting, insectivorous tree bats where bats selected roost locations that may offer protection and thermoregulatory benefits.
This report documents a three-part continental-scale calibration procedure and a new streamflow routing algorithm using the U.S. Geological Survey National Hydrologic Model (NHM) infrastructure along with an application of the Precipitation-Runoff Modeling System (PRMS). The traditional approach to hydrologic model calibration and evaluation, which relies on comparing observed and simulated streamflow, is not sufficient for accurately representing the non-streamflow parts of the water budget. If intermediate process variables computed by the hydrologic model are not examined, the variables could be characterized by parameter values that do not replicate those hydrological processes present in the physical system. In answer to this potential problem, alternative hydrologic process variables from the model (in addition to streamflow) are included in a calibration procedure applied to the conterminous United States (CONUS) domain.
The three-part calibration procedure presented in this report considers volume (calibration by hydrologic response unit [byHRU]), timing (calibration by headwater watershed [byHW]), and measured streamflow [byHWobs]). The first part, byHRU, is considered a water-balance volume calibration that uses five alternative (non-streamflow) hydrologic quantities (runoff, actual evapotranspiration, recharge, soil moisture, and snow-covered area) as calibration targets for each hydrologic response unit (HRU). These alternative data products were derived, with error bounds, from multiple sources for each of the 109,951 HRUs in the NHM on time scales varying from annual to daily. The second part of the calibration, byHW, is considered a streamflow timing calibration that uses statistically based streamflow simulations developed using ordinary kriging for 7,265 headwater watersheds that had drainage areas of less than 3,000 square kilometers (1,158 square miles) across the CONUS. Two streamflow routing algorithms were tested in this byHW calibration: (1) continuity without attenuation of the flood pulse and (2) a new formulation of the Muskingum routing method, which was added to the PRMS as part of this study. The third part of the calibration, byHWobs, refines the model parameters using available measured streamflow using 1,417 streamgage locations. A multiple-objective, stepwise, automated calibration procedure was used to identify the optimal set of parameters for each calibration procedure.
Using a variety of alternative datasets for calibration of the water budget provides users of the NHM-PRMS with improved initial parameters and helps alleviate the equifinality problem (getting the right answer for the wrong reason). Through a community effort, these alternative data products, with error bounds, can be used to improve and expand our understanding of hydrologic-process representation in models. The broader modeling community can use these data products, with error bounds, to calibrate and evaluate hydrologic models using more than streamflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6B10","programNote":"Water Availability and Use Science Program","usgsCitation":"Hay, L.E., LaFontaine, J.H., Van Beusekom, A.E., Norton, P.A., Farmer, W.H., Regan, R.S., Markstrom, S.L., and Dickinson, J.E., 2023, Parameter estimation at the conterminous United States scale and streamflow routing enhancements for the National Hydrologic Model infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS): U.S. Geological Survey Techniques and Methods 6–B10, 50 p., https://doi.org/10.3133/tm6B10.","productDescription":"Report: vii, 50 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-121885","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":501163,"rank":7,"type":{"id":36,"text":"NGMDB Index 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1770 Corporate Drive, Suite 500
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The primary objective of the National Aeronautics and Space Administration (NASA) Surface Biology and Geology (SBG) mission is to measure biological, physical, chemical, and mineralogical features of the Earth's surface, realizing a key conceptual component of the envisioned NASA Earth System Observatory (ESO). SBG is planned to launch as a two-platform mission in the late 2020s, the first of the ESO satellites. Targeted science and applications objectives based on observations of the Earth's SBG helped to define the mission architecture and instrument capabilities for the SBG mission concept. These objectives further drove the need for enabling change detection and trending of surface biological and geological features. These needs implied fundamental calibration goals to achieve the necessary science data quality characteristics. To meet those goals, calibration and validation pre-launch and on-orbit methods formed a basis of the calibration and validation concept, including the combined use of on-board references, vicarious techniques, and routine lunar imaging. International collaboration with space agencies in other countries, an important feature of the recommended SBG mission architecture, uncovered and emphasized the need for inter-calibration techniques that underscored the importance of collaborative instrument characterization data sharing and the use of common calibration references that are International System of Units (SI) traceable in pre-launch and post-launch on orbit calibration mission phases. International collaboration through the use of terrestrial and aquatic networks on six continents for vicarious calibration and validation activities will further assure necessary science data quality while in orbit.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JG007452","usgsCitation":"Turpie, K.R., Casey, K.A., Crawford, C., Guild, L.S., Kieffer, H.H., Lin, G., Kokaly, R.F., Shrestha, A., Anderson, C., Ramaseri Chandra, S.N., Green, R., Hook, S., Lukashin, C., and Thome, K., 2023, Calibration and validation for the Surface Biology and Geology (SBG) mission concept: Recommendations for a multi-sensor system for imaging spectroscopy and thermal imagery: JGR Biogeosciences, v. 128, no. 9, e2023JG007452, 36 p., https://doi.org/10.1029/2023JG007452.","productDescription":"e2023JG007452, 36 p.","ipdsId":"IP-139909","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"links":[{"id":442328,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jg007452","text":"Publisher Index Page"},{"id":420972,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","issue":"9","noUsgsAuthors":false,"publicationDate":"2023-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Turpie, Kevin R.","contributorId":257569,"corporation":false,"usgs":false,"family":"Turpie","given":"Kevin","email":"","middleInitial":"R.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":883501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casey, Kimberly Ann 0000-0002-6115-7525","orcid":"https://orcid.org/0000-0002-6115-7525","contributorId":245548,"corporation":false,"usgs":true,"family":"Casey","given":"Kimberly","email":"","middleInitial":"Ann","affiliations":[{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":883502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":883503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guild, Liane S","contributorId":329863,"corporation":false,"usgs":false,"family":"Guild","given":"Liane","email":"","middleInitial":"S","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":883504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kieffer, Hugh H.","contributorId":41137,"corporation":false,"usgs":false,"family":"Kieffer","given":"Hugh","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":883505,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lin, Guoqing","contributorId":329864,"corporation":false,"usgs":false,"family":"Lin","given":"Guoqing","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":883506,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":883507,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shrestha, Alok","contributorId":329865,"corporation":false,"usgs":false,"family":"Shrestha","given":"Alok","email":"","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":883508,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Anderson, Cody 0000-0001-5612-1889 chanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5612-1889","contributorId":195521,"corporation":false,"usgs":true,"family":"Anderson","given":"Cody","email":"chanderson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":883509,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ramaseri Chandra, Shankar N. 0000-0002-4434-4468","orcid":"https://orcid.org/0000-0002-4434-4468","contributorId":216043,"corporation":false,"usgs":true,"family":"Ramaseri Chandra","given":"Shankar","email":"","middleInitial":"N.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":883510,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Green, Robert O.","contributorId":225049,"corporation":false,"usgs":false,"family":"Green","given":"Robert O.","affiliations":[{"id":41027,"text":"NASA JPL/CalTech","active":true,"usgs":false}],"preferred":false,"id":883511,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hook, Simon","contributorId":150339,"corporation":false,"usgs":false,"family":"Hook","given":"Simon","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":883512,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lukashin, Constantine","contributorId":242007,"corporation":false,"usgs":false,"family":"Lukashin","given":"Constantine","email":"","affiliations":[{"id":48472,"text":"NASA Langley Reseach Center","active":true,"usgs":false}],"preferred":false,"id":883513,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thome, Kurt","contributorId":140792,"corporation":false,"usgs":false,"family":"Thome","given":"Kurt","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":883514,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70247937,"text":"70247937 - 2023 - Investigating microbial size classes associated with the transmission of stony coral tissue loss disease (SCTLD)","interactions":[],"lastModifiedDate":"2023-08-25T13:38:01.248449","indexId":"70247937","displayToPublicDate":"2023-08-23T08:35:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Investigating microbial size classes associated with the transmission of stony coral tissue loss disease (SCTLD)","docAbstract":"Effective treatment and prevention of any disease necessitates knowledge of the causative agent, yet the causative agents of most coral diseases remain unknown, in part due to the difficulty of distinguishing the pathogenic microbe(s) among the complex microbial backdrop of coral hosts. Stony coral tissue loss disease (SCTLD) is a particularly destructive disease of unknown etiology, capable of transmitting through the water column and killing entire colonies within a matter of weeks. Here we used a previously described method to (i) isolate diseased and apparently healthy coral colonies within individual mesocosms containing filtered seawater with low microbial background levels; (ii) incubate for several days to enrich the water with coral-shed microbes; (iii) use tangential-flow filtration to concentrate the microbial community in the mesocosm water; and then (iv) filter the resulting concentrate through a sequential series of different pore-sized filters. To investigate the size class of microorganism(s) associated with SCTLD transmission, we used 0.8 µm pore size filters to capture microeukaryotes and expelled zooxanthellae, 0.22 µm pore size filters to capture bacteria and large viruses, and 0.025 µm pore size filters to capture smaller viruses. In an attempt to further refine which size fraction(s) contained the transmissible element of SCTLD, we then applied these filters to healthy “receiver” coral fragments and monitored them for the onset of SCTLD signs over three separate experimental runs. However, several factors outside of our control confounded the transmission results, rendering them inconclusive. As the bulk of prior studies of SCTLD in coral tissues have primarily investigated the associated bacterial community, we chose to characterize the prokaryotic community associated with all mesocosm 0.22 µm pore size filters using Illumina sequencing of the V4 region of the 16S rRNA gene. We identified overlaps with prior SCTLD studies, including the presence of numerous previously identified SCTLD bioindicators within our mesocosms. The identification in our mesocosms of specific bacterial amplicon sequence variants that also appear across prior studies spanning different collection years, geographic regions, source material, and coral species, suggests that bacteria may play some role in the disease.
","language":"English","publisher":"PeerJ Publishing","doi":"10.7717/peerj.15836","usgsCitation":"Evans, J.S., Paul, V.J., Ushijima, B., Pitts, K.A., and Kellogg, C.A., 2023, Investigating microbial size classes associated with the transmission of stony coral tissue loss disease (SCTLD): PeerJ, v. 11, e15836, 36 p., https://doi.org/10.7717/peerj.15836.","productDescription":"e15836, 36 p.","ipdsId":"IP-148858","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442330,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.15836","text":"Publisher Index Page"},{"id":420151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-08-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, James S. 0000-0002-9977-1627 jsevans@usgs.gov","orcid":"https://orcid.org/0000-0002-9977-1627","contributorId":279528,"corporation":false,"usgs":true,"family":"Evans","given":"James","email":"jsevans@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":881127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paul, Valerie J. 0000-0002-4691-1569","orcid":"https://orcid.org/0000-0002-4691-1569","contributorId":279530,"corporation":false,"usgs":false,"family":"Paul","given":"Valerie","email":"","middleInitial":"J.","affiliations":[{"id":57268,"text":"Smithsonian Marine Station","active":true,"usgs":false}],"preferred":false,"id":881128,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ushijima, Blake","contributorId":91782,"corporation":false,"usgs":false,"family":"Ushijima","given":"Blake","email":"","affiliations":[{"id":13394,"text":"Hawai‘i Institute of Marine Biology","active":true,"usgs":false}],"preferred":false,"id":881129,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitts, Kelly A. 0000-0002-8555-0719","orcid":"https://orcid.org/0000-0002-8555-0719","contributorId":328732,"corporation":false,"usgs":false,"family":"Pitts","given":"Kelly","email":"","middleInitial":"A.","affiliations":[{"id":57268,"text":"Smithsonian Marine Station","active":true,"usgs":false}],"preferred":false,"id":881130,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":881131,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254450,"text":"70254450 - 2023 - Fluid migration pathways to groundwater in mature oil fields: Exploring the roles of water injection/production and oil-well integrity in California, USA","interactions":[],"lastModifiedDate":"2024-05-24T11:45:46.389957","indexId":"70254450","displayToPublicDate":"2023-08-23T06:43:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Fluid migration pathways to groundwater in mature oil fields: Exploring the roles of water injection/production and oil-well integrity in California, USA","docAbstract":"Mature oil fields potentially contain multiple fluid migration pathways toward protected groundwater (total dissolved solids, TDS, in nonexempted aquifer <10,000 mg/L) because of their extensive development histories. Time-series data for water use, fluid pressures, oil-well construction, and geochemistry from the South Belridge and Lost Hills mature oil fields in California are used to explore the roles of injection/production of oil-field water and well-integrity issues in fluid migration. Injection/production of oil-field water modified hydraulic gradients in both oil fields, resulting in chemical transport from deeper groundwater and hydrocarbon-reservoir systems to aquifers in the oil fields. Those aquifers are used for water supply outside the oil-field boundaries. Oil wells drilled before 1976 can be fluid migration pathways because a relatively large percentage of them have >10 m of uncemented annulus that straddles oil-well casing damage and/or the base of groundwater with TDS <10,000 mg/L. The risk of groundwater-quality degradation is higher when wells with those risk factors occur in areas with upward hydraulic gradients created by positive net injection, groundwater withdrawals, or combinations of these variables. The complex changes in hydrologic conditions and groundwater chemistry likely would not have been discovered in the absence of years to decades of monitoring data for groundwater elevations and chemistry, and installation of monitoring wells in areas with overlapping risk factors. Important monitoring concepts based on results from this and other studies include monitoring hydrocarbon-reservoir and groundwater systems at multiple spatiotemporal scales and maintaining transparency and accessibility of data and analyses. This analysis focuses on two California oil fields, but the methods used and processes affecting fluid migration could be relevant in other oil fields where substantial injection/production of oil-field water occurs and oil-well integrity is of concern.
Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543-1598
We used multi-component seismic data (including two-dimensional images of compressional-wave velocity [vP], shear-wave velocity [vS], the ratio of compressional-wave velocity to shear-wave velocity [vP/vS ratio], Poisson’s ratio [μ], and seismic reflections) along a transect across northeastern Edwards Air Force Base to investigate the upper few hundred meters of the subsurface. The shallow subsurface there is characterized by unconsolidated sediments (vP of less than 2,500 meters per second [m/s]; vS of less than 1,500 m/s) in the upper 40 meters (m), underlain by weathered granitic basement rock (vP of 2,500–4,000 m/s; vS of 1,500–2,700 m/s) to about 100 m depth and unweathered granitic basement rock (vP of 4,000–6,000 m/s; vS of 2,700–4,000 m/s). The depth to basement rock varies laterally along the transect by as many as tens of meters. The top of groundwater, as indicated by both the 1,500-m/s vP contour and measurements in five wells along the transect, is located 8–30 m below the surface. In places, the top of groundwater is vertically offset over short lateral distances, likely the result of fault barriers. Faults mapped at the surface along the northeastern part of the transect correlate with multiple seismic indicators of faulting at the same locations. These same indicators show evidence for faulting in several other places along the transect beneath the alluvium. A major zone of faulting is apparent near the center of the seismic profile and is characterized by offsets in the top of groundwater; diffractions on the reflection image; a near-vertical zone of low vS; a corresponding near-vertical, shallow-depth zone of high vP relative to adjacent rocks (indicating high saturation); a near-vertical zone of high vP/vS ratios; and a near-vertical zone of high Poisson’s ratios (also indicating saturation). Many of these anomalies extend at least 400 m deep, reaching into granitic basement rock and indicating that the fault zone is water-saturated to those depths. There is likely vertical flow of contaminants along these fault zones, which are apparently barriers to the lateral flow of groundwater. The major central fault zone marks a boundary beyond which contaminant flow is apparently impeded. Along the southwestern part of the transect, there are also areas with similar indicators of faulting, but these appear to be smaller fault zones.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231018","collaboration":"Prepared in cooperation with the U.S. Air Force","usgsCitation":"Catchings, R.D., Goldman, M.R., Chan, J.H., Sickler, R.R., and Criley, C.J., 2023, Seismic images and subsurface structures of northeastern Edwards Air Force Base, Kern County, California: U.S. Geological Survey Open-File Report 2023–1018, 29 p., https://doi.org/10.3133/ofr20231018.","productDescription":"Report: vii, 29 p.,; Data Release; 8 Figures","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-139215","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":499769,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115219.htm","linkFileType":{"id":5,"text":"html"}},{"id":420028,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZAM79S","text":"Data release for a 2020 high-resolution seismic survey across northeastern Edwards Air Force Base, Kern County, California","description":"Goldman, M.R., Catchings, R.D., Chan, J.H., Criley, C.J., and Sickler, R.R., 2021, Data release for a 2020 high-resolution seismic survey across northeastern Edwards Air Force Base, Kern County, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZAM79S."},{"id":420027,"rank":10,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure14.pdf","text":"Figure 14","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional Poisson’s ratio model along the Edwards seismic profile (Edwards Air Force Base, California), annotated with interpretative faults shown in figure 11."},{"id":420024,"rank":8,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure08def.pdf","text":"Figure 8D, E, F","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Unmigrated reflection image of the upper 400 meters (depth) along the Edwards seismic profile, Edwards Air Force Base, California."},{"id":420025,"rank":7,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure08abc.pdf","text":"Figure 8A, B, C","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Unmigrated reflection image of the upper 400 meters (depth) along the Edwards seismic profile, Edwards Air Force Base, California."},{"id":420023,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure07a.pdf","text":"Figure 7A","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional Poisson’s ratio model along the Edwards seismic profile (Edwards Air Force Base, California), derived from the tomographic compressional-wave velocity model and the multichannel analysis of surface waves shear-wave velocity model."},{"id":420022,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure06a.pdf","text":"Figure 6A","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional model of the ratio of compressional-wave velocity to shear-wave velocity along the Edwards seismic profile (Edwards Air Force Base, California), derived from the tomographic compressional-wave velocity model and the multichannel analysis of surface waves shear-wave velocity model."},{"id":420021,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure05.pdf","text":"Figure 5","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional shear-wave velocity model along the Edwards seismic profile (Edwards Air Force Base, California) developed from Rayleigh surface waves and the multichannel analysis of surface waves modeling technique."},{"id":420019,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420018,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1018/covrthb.jpg"},{"id":420020,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure04a.pdf","text":"Figure 4A","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional compressional-wave velocity tomography model along the Edwards seismic profile (Edwards Air Force Base, California), generated using a subset of the seismic data with short offset distances between the shots and the receivers."},{"id":420026,"rank":9,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2023/1018/ofr20231018_figure13.pdf","text":"Figure 13","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Two-dimensional model of the ratio of compressional-wave velocity to shear-wave velocity along the Edwards seismic profile (Edwards Air Force Base, California), annotated with interpretive faults shown in figure 11"}],"country":"United States","state":"California","county":"Kern County","otherGeospatial":"Edwards Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.13696891699124,\n 35.05523690329453\n ],\n [\n -118.13696891699124,\n 34.719740760796995\n ],\n [\n -117.59793378058632,\n 34.719740760796995\n ],\n [\n -117.59793378058632,\n 35.05523690329453\n ],\n [\n -118.13696891699124,\n 35.05523690329453\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
350 N. Akron Road
Moffett Field, CA 94035
Aeromagnetic surveys were conducted to improve understanding of the geology and structure in northeastern California, a region predominantly covered by Quaternary and Tertiary, mainly Neogene, volcanic rocks including Medicine Lake volcano. New aeromagnetic data are a substantial improvement over existing data and reveal structural details not resolved by older surveys. Here we show how these data (1) do not support the presence of a northwest-striking structural feature across the Modoc Plateau, (2) reveal a northeast-striking fault-bounded block of predominantly reversely magnetized material that may influence tectonism at Medicine Lake volcano, and (3) constrain possible right-lateral offsets along the Likely Fault Zone and other faults that traverse the region. The data also highlight possible extensions of mapped faults, such as those in Fall River Valley and the Tule and Lower Klamath Lake areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3505","usgsCitation":"Langenheim, V.E. and Sweetkind, D.S., 2023, Aeromagnetic map of northeastern California: U.S. Geological Survey Scientific Investigations Map 3505, pamphlet 21 p., https://doi.org/10.3133/sim3505.","productDescription":"Pamphlet: iv, 21 p.; 3 Data Releases; 1 Sheet: 30.82 × 39.53 inches","numberOfPages":"21","additionalOnlineFiles":"Y","ipdsId":"IP-137584","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":500211,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115218.htm","linkFileType":{"id":5,"text":"html"}},{"id":435213,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TQGRDW","text":"USGS data release","linkHelpText":"Aeromagnetic and derivative gridded data, and magnetization boundaries of northeastern California"},{"id":420034,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91Y9L0H","text":"Data release of geologic data for the aeromagnetic map of northeastern California","description":"Sweetkind, D.S., and Langenheim, V.E., 2022, Data release of geologic data for the aeromagnetic map of northeastern California: U.S. Geological Survey data release, https://doi.org/10.5066/P91Y9L0H."},{"id":420033,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PUFYDD","text":"Aeromagnetic and derivative gridded data, and magnetization boundaries of northeastern California","description":"Langenheim, V.E., 2023, Aeromagnetic and derivative gridded data, and magnetization boundaries of northeastern California: U.S. Geological data release, https://doi.org/10.5066/P9PUFYDD."},{"id":420032,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LU37RC","text":"Aeromagnetic Data of Alturas, California, and Surrounding Areas","description":"Langenheim, V.E., 2022, Aeromagnetic Data of Alturas, California, and Surrounding Areas: U.S. Geological Survey data release, https://doi.org/10.5066/P9LU37RC."},{"id":420031,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3505/sim3505_sheet.pdf","text":"Map Sheet","size":"30 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420030,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3505/sim3505_pamphlet.pdf","text":"Pamphlet","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":420029,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3505/covrthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.03188053680955,\n 42.02157881382186\n ],\n [\n -122.00857149452494,\n 42.02157881382186\n ],\n [\n -122.00857149452494,\n 40.50279454574354\n ],\n [\n -120.03188053680955,\n 40.50279454574354\n ],\n [\n -120.03188053680955,\n 42.02157881382186\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
Considering global market trends and concerns about climate change and sustainability, increased biomass use for energy is expected to continue. As more diverse materials are being utilized to manufacture solid biomass fuels, it is critical to implement quality assessment methods to analyze these fuels thoroughly. One such method is reflected light microscopy (RLM), which has the potential to complement and enhance current standard testing, leading to improving fuel quality assessment and, ultimately, preventing avoidable air pollution.
An interlaboratory study (ILS) was conducted to test the reproducibility of biomass fuels component identification using a reflected light microscopy technique. The exercise was conducted on thirty photomicrographs showing biomass and various undesired components (like plastics or mineral matter), which were purposely added (by the ILS organizers) to contaminate wood pellets and charcoal-based grilling fuels.
Forty-six participants had various levels of difficulty identifying the marked components, and as a result, the percentage of correct answers ranged from 52.2 to 94.4%. Among the most difficult components to distinguish were petroleum products and inorganic matter. Various reasons led to the misidentification, including insufficient morphological descriptions of the components provided to participants, ambiguities of the nomenclature, limitations of the analytical and exercise method, and insufficient experience of the participants.
Overall, the results indicate that RLM has the potential to enhance the quality assessment of biomass fuels. However, they also demonstrate that the petrographic classification used in this exercise requires further refinement before it can be standardized. While a new simplified classification of solid biomass fuels components was created as an outcome of this study, future research is necessary to refine the nomenclature, develop a microscopic morphological description of the components, and verify the accuracy of component identification with a follow-up ILS.
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We hypothesized the elevated NVDOC is comprised of water-soluble photooxidation products transported from the surface to the aquifer. We use field and laboratory samples in combination with complementary analytical methods to test this hypothesis and determine the biological response to these products. Observations from optical spectroscopy and ultrahigh-resolution mass spectrometry reveal a significant correlation between the chemical composition of NVDOC leached from photochemically weathered soils and groundwater monitoring wells with high NVDOC concentrations measured in the aquifer beneath the contaminated soil. Conversely, the chemical composition from the uncontaminated soil photoleachate, matches the NVDOC observed in the uncontaminated wells. Contaminated groundwater and photodissolution leachates from contaminated soil activated biological targets indicative of xenobiotic metabolism and exhibited potential for adverse effects. Newly formed hydrocarbon oxidation products (HOPs) from fresh oil could be distinguished from those downgradient. This study illustrates another pathway for dissolved HOPs to infiltrate groundwater and potentially affect human health and the environment.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhazmat.2023.132312","usgsCitation":"Zito, P., Bekins, B.A., Martinović-Weigelt, D., Harsha, M.L., Humpal, K.E., Trost, J.J., Cozzarelli, I.M., Mazzoleni, L.R., Schum, S.K., and Podgorski, D.C., 2023, Photochemical mobilization of dissolved hydrocarbon oxidation products from petroleum contaminated soil into a shallow aquifer activate human nuclear receptors: Journal of Hazardous Materials, v. 459, 132312, 13 p., https://doi.org/10.1016/j.jhazmat.2023.132312.","productDescription":"132312, 13 p.","ipdsId":"IP-152602","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":442340,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhazmat.2023.132312","text":"Publisher Index Page"},{"id":420013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","city":"Bemidji","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.2463950473577,\n 47.67295060211438\n ],\n [\n -95.2463950473577,\n 47.46414380926609\n ],\n [\n -94.87012999033621,\n 47.46414380926609\n ],\n [\n -94.87012999033621,\n 47.67295060211438\n ],\n [\n -95.2463950473577,\n 47.67295060211438\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"459","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zito, Phoebe","contributorId":206101,"corporation":false,"usgs":false,"family":"Zito","given":"Phoebe","email":"","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":880767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekins, Barbara A. 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":1348,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - 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Eastern Branch","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":880773,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mazzoleni, Lynn R.","contributorId":328611,"corporation":false,"usgs":false,"family":"Mazzoleni","given":"Lynn","email":"","middleInitial":"R.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":880774,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schum, Simeon K.","contributorId":328613,"corporation":false,"usgs":false,"family":"Schum","given":"Simeon","email":"","middleInitial":"K.","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":880775,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Podgorski, David C.","contributorId":178153,"corporation":false,"usgs":false,"family":"Podgorski","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":880776,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70248297,"text":"70248297 - 2023 - Genetic structure of the Silver Chub indicates distinctiveness of Lake Erie population","interactions":[],"lastModifiedDate":"2023-11-07T16:00:35.204044","indexId":"70248297","displayToPublicDate":"2023-08-22T07:01:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Genetic structure of the Silver Chub indicates distinctiveness of Lake Erie population","docAbstract":"Silver Chub Macrhybopsis storeriana is a small riverine minnow endemic to North American fresh waters. Its range extends from the southern USA to southcentral Canada; the latter includes a rare lacustrine population in Lake Erie. Anthropogenic activities pose an immediate threat to several Silver Chub populations, currently categorized from special concern to threatened at the state level in the USA and federally and provincially not-at-risk to endangered in Canada. Several studies have examined the anthropogenic causes for the decline of Silver Chub populations, but conservation efforts have been hindered by the lack of knowledge of the population genetics of this species.
Here, we provide an assessment of the genetic diversity of Silver Chub populations across the USA and Canada using a fast-evolving mitochondrial gene, with particular focus on the Lake Erie population.
We found the Lake Erie population to be divergent from all other populations, with nearly all the haplotypes sampled there being private.
Our study provides genetic evidence that the Silver Chub population in Lake Erie could be considered a separate conservation unit.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10888","usgsCitation":"Elbassiouny, A., Fontenelle, J.P., Kocovsky, P.M., Mandrak, N.E., and Lovejoy, N.R., 2023, Genetic structure of the Silver Chub indicates distinctiveness of Lake Erie population: North American Journal of Fisheries Management, v. 43, no. 5, p. 1180-1189, https://doi.org/10.1002/nafm.10888.","productDescription":"10 p.","startPage":"1180","endPage":"1189","ipdsId":"IP-138845","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":442344,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10888","text":"Publisher Index Page"},{"id":420613,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"http://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.61430687726288,\n 43.069674577022425\n ],\n [\n -83.61430687726288,\n 41.27939486382931\n ],\n [\n -78.65061625011087,\n 41.27939486382931\n ],\n [\n -78.65061625011087,\n 43.069674577022425\n ],\n [\n -83.61430687726288,\n 43.069674577022425\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"43","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Elbassiouny, Ahmed","contributorId":329433,"corporation":false,"usgs":false,"family":"Elbassiouny","given":"Ahmed","email":"","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":882311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fontenelle, Joao Pedro","contributorId":329434,"corporation":false,"usgs":false,"family":"Fontenelle","given":"Joao","email":"","middleInitial":"Pedro","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":882312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kocovsky, Patrick M. 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":3429,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true}],"preferred":true,"id":882313,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mandrak, Nicholas E.","contributorId":177869,"corporation":false,"usgs":false,"family":"Mandrak","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":882314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lovejoy, Nathan R","contributorId":329435,"corporation":false,"usgs":false,"family":"Lovejoy","given":"Nathan","email":"","middleInitial":"R","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":882315,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248378,"text":"70248378 - 2023 - A Monte-Carlo chemical budget approach to assess ambient groundwater flow in bedrock open boreholes","interactions":[],"lastModifiedDate":"2024-02-26T15:44:30.373759","indexId":"70248378","displayToPublicDate":"2023-08-22T06:58:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10067,"text":"Groundwater Monitoring and Remediation","active":true,"publicationSubtype":{"id":10}},"title":"A Monte-Carlo chemical budget approach to assess ambient groundwater flow in bedrock open boreholes","docAbstract":"In low-permeability rocks, ambient groundwater flow in open boreholes may go undetected using conventional borehole-flowmeter tools and alternative approaches may be needed to identify flow. Understanding ambient flow in open boreholes is important for tracking of cross contamination in groundwater. Chlorinated volatile organic compound (CVOC) concentrations from three open boreholes set in a crystalline-rock aquifer (two of three open boreholes) and a siltstone aquifer (one of three open boreholes) were examined using a new approach and associated software program called the AFCE (Aqueous-Flow-Concentration-Estimator). The program allows comparison of coupled chemical datasets through a Monte-Carlo simulation and a chemical-budget approach to assess ambient groundwater flow in open boreholes. The coupled datasets required for the comparison include aqueous CVOC concentrations from groundwater samples from (1) discrete fractures, such as those measured from temporary deployment of straddle-borehole packer assemblies; and (2) the concentration of the open borehole (wellbore) water, as measured by a vertical profile of passive samplers from within the same open borehole. Because results from the passive samplers represent a composite mixture of the results from the discrete samples under ambient groundwater-flow conditions, potentially at unknown proportions, the comparison between coupled datasets affords the ability to discern likely water contributions of CVOC from discrete fractures (or fracture zones), and which fractures may be dominating the water chemistry of the open borehole.
The 6th annual Environmental DNA (eDNA) Technical Exchange Workshop was a virtual workshop hosted and coordinated by the Government eDNA Working Group (GEDWG) on January 24–26, 2023. GEDWG is a no-cost consortium that focuses on bringing together stakeholders associated with federal, state, provincial, municipal, and other government and non-government agencies interested in eDNA and related fields, for the purposes of sharing technical expertise and experience during monthly discussion meetings and annual workshops. Over 400 participants registered for the virtual Workshop, which featured four keynote speakers, 23 platform talks, eight short-form poster presentations, and an extended discussion session. Workshop attendees represented a broad cross-section of disciplines and backgrounds, including research scientists, natural resource managers, and conservation policy experts, and many different government agencies, private environmental consulting firms, trade organizations, non-governmental organizations, and others in the environmental management sector. Key takeaways from the workshop included moving the application of eDNA into resource management and discovering ways to improve policy uptake in the development of nationwide biodiversity monitoring, some of which is happening in the development of eDNA networks and national strategies. Future research directions discussed include studies of fate and transport, autonomous sampling/sample processing, and reference library curation. Additionally, co-design of studies and improved engagement and communication among scientists and managers are needed to ensure clear expectations and outcomes.
No abstract available.
","language":"English","publisher":"Utah Department of Natural Resources, Division of Forestry Fire and State Lands","usgsCitation":"Putman, A.L., Blakowski, M.A., McDonnell, M.C., DiViesti, D.N., Fernandez, D.P., Longley, P.C., and Jones, D.K., 2023, Assessing exposure of northern Utah communities to dust from the contaminated and dynamic Great Salt Lake playa, 47 p.","productDescription":"47 p.","ipdsId":"IP-154410","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":420096,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ffsl.utah.gov/grants/great-salt-lake-research-grants/"},{"id":427248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Great Salt Lake playa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.58942154206203,\n 41.98082247807224\n ],\n [\n -113.58942154206203,\n 40.391157251539084\n ],\n [\n -111.43572662768739,\n 40.391157251539084\n ],\n [\n -111.43572662768739,\n 41.98082247807224\n ],\n [\n -113.58942154206203,\n 41.98082247807224\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Putman, Annie L. 0000-0002-9424-1707","orcid":"https://orcid.org/0000-0002-9424-1707","contributorId":225134,"corporation":false,"usgs":true,"family":"Putman","given":"Annie","email":"","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakowski, Molly A. 0000-0003-4196-2161","orcid":"https://orcid.org/0000-0003-4196-2161","contributorId":316614,"corporation":false,"usgs":true,"family":"Blakowski","given":"Molly","middleInitial":"A.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McDonnell, Morgan C. 0000-0001-6946-9286","orcid":"https://orcid.org/0000-0001-6946-9286","contributorId":296906,"corporation":false,"usgs":true,"family":"McDonnell","given":"Morgan","email":"","middleInitial":"C.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DiViesti, Destry N. 0000-0002-9220-4734","orcid":"https://orcid.org/0000-0002-9220-4734","contributorId":316616,"corporation":false,"usgs":true,"family":"DiViesti","given":"Destry","middleInitial":"N.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881009,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fernandez, Diego P.","contributorId":138701,"corporation":false,"usgs":false,"family":"Fernandez","given":"Diego","email":"","middleInitial":"P.","affiliations":[{"id":12499,"text":"Univ. of Utah","active":true,"usgs":false}],"preferred":false,"id":881010,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Longley, Patrick C. 0000-0001-8767-5577","orcid":"https://orcid.org/0000-0001-8767-5577","contributorId":268147,"corporation":false,"usgs":true,"family":"Longley","given":"Patrick","email":"","middleInitial":"C.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881011,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":881012,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70247789,"text":"tm2E4 - 2023 - Evaluating oil and gas industry two-dimensional multichannel seismic data for use in near-surface assessment of geologic framework and potential marine minerals resources","interactions":[],"lastModifiedDate":"2023-09-19T17:51:24.462124","indexId":"tm2E4","displayToPublicDate":"2023-08-21T09:32:23","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2-E4","subseriesTitle":"Book 2, Collection of Environmental Data","displayTitle":"Evaluating Oil and Gas Industry Two-Dimensional Multichannel Seismic Data for Use in Near-Surface Assessment of Geologic Framework and Potential Marine Minerals Resources","title":"Evaluating oil and gas industry two-dimensional multichannel seismic data for use in near-surface assessment of geologic framework and potential marine minerals resources","docAbstract":"Marine seismic reflection data acquired across the Gulf of Mexico during oil and gas exploration are available to the public through an online database archive. The data are archived as two-dimensional multichannel seismic data in two digital formats. The formats include image files in portable document format (PDF), and binary files in industry standard Society for Exploration Geophysicists revision Y (SEG-Y) format. Also included in the database are navigation files and acquisition information associated with the collection of the data.
This study examines the data acquired within two geographic areas in the northern Gulf of Mexico. Although the seismic reflection data are acquired for oil and gas exploration many kilometers below the seafloor, this study focuses on the feasibility of using the data for near-surface geologic and seafloor morphologic studies (<100 meters below the seafloor). The report outlines the methodologies used to recover and process the data, including computer processing steps to convert the PDF imagery into SEG-Y format. The report includes two-dimensional profiles of the data to demonstrate the efficacy of the data in near-surface geologic studies. The study found that, for the two areas of interest, the seafloor reflectors in most of the available data are not resolvable. Although the data are readily available and computer processing can adequately image the uppermost reflectors of the seismic profiles, the resolution of the data in most cases are not suitable for near-surface geologic evaluations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm2E4","issn":"2328-7055","collaboration":"Prepared in cooperation with the Bureau of Ocean and Energy Management","programNote":"Coastal and Marine Hazards and Resources Program","usgsCitation":"Flocks, J., Forde, A., and Bosse, S., 2023, Evaluating oil and gas industry two-dimensional multichannel seismic data for use in near-surface assessment of geologic framework and potential marine minerals resources: U.S. Geological Survey Techniques and Methods, book 2, chap. E4, 25 p., https://doi.org/10.3133/tm2E4.","productDescription":"Report: viii, 25 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-145218","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":419907,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://walrus.wr.usgs.gov/namss/","text":"U.S. Geological Survey database—National Archive of Marine Seismic Surveys (NAMSS)"},{"id":419905,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/tm/02/e4/tm2E4.XML","linkFileType":{"id":8,"text":"xml"},"description":"Techniques and Methods, book 2, chap. E4 XML"},{"id":419903,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/02/e4/tm2E4.pdf","size":"11.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Techniques and Methods, book 2, chap. E4 pdf"},{"id":419902,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/02/e4/coverthb.jpg"},{"id":420017,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/tm2E4/full","description":"Techniques and Methods, book 2, chap. E4 HTML"},{"id":419904,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/tm/02/e4/images"}],"country":"United States","state":"Alabama, Florida, Louisiana, Mississippi, Texas","otherGeospatial":"northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.64481214506837,\n 30.353047922248734\n ],\n [\n -96.4342072827106,\n 25\n ],\n [\n -83.21418390807747,\n 25\n ],\n [\n -82.7732558453231,\n 30.619210947002145\n ],\n [\n -96.64481214506837,\n 30.353047922248734\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
600 4th Street South
St. Petersburg, FL 33701
The Souris River Basin is an international basin in southeast Saskatchewan, north-central North Dakota, and southwest Manitoba. Sustained exceedances of water-quality objectives for total phosphorus, sodium, sulfate, total dissolved solids, and total iron have been reported since the late 1990s at the two binational sites on the Souris River (Souris River near Sherwood, North Dakota [U.S. Geological Survey station 05114000] and Souris River near Westhope, N. Dak. [U.S. Geological Survey station 05124000]). To understand conditions at the binational sites, it is important to understand water-quality changes on a basin-wide scale. Because streamflow is highly variable in the basin and changes in streamflow affect water-quality conditions, it is particularly important to use a trend-analysis method that accounts for changes in streamflow. Trends in water-quality concentrations can be affected by human-induced changes on the landscape or natural changes in land-runoff interactions that are driven by climate patterns and reflected by changes in streamflow (commonly referred to as “hydroclimatic variability”). In the primarily agricultural Souris River Basin, human-induced changes that are likely to affect trends are widespread changes in agricultural management such as fertilizer application, tilling practices, and crop types, as well as dam emplacement and artificial drainage. Around 1970, there was a long-term natural (hydroclimatic) change in the basin in which a significant transition from a dry climate state to a wet climate state resulted in higher streamflow in the basin. To assist the International Souris River Board in assessing current water-quality conditions in the Souris River Basin and exceedances of water-quality objectives at the binational sites, the U.S. Geological Survey, in cooperation with the International Joint Commission, completed a comprehensive analysis for selected ions, nutrients, and trace metals for many sites in the basin that included descriptive water-quality statistics, trend analysis using a trend method that considers interannual hydroclimatic variability, and an assessment of exceedances of the water-quality objectives for the binational sites.
Water-quality and streamflow or reservoir inflow or outflow data were compiled for 34 sites (30 stream sites and four reservoir sites) and 23 constituents with established water-quality objectives from 1970 to 2020 in the Souris River Basin and were used for descriptive statistics and water-quality trend analysis. Median total dissolved solids, sulfate, and sodium concentrations were low in the headwaters of the Souris River and some of the highest median concentrations were measured in the upper basin. At main-stem Souris River sites, all median sodium concentrations were greater than the binational water-quality objective. Median total phosphorus concentrations in the Souris River Basin were highest in the headwaters of the Souris River and all sites had median concentrations greater than the water-quality objective. Median total iron concentrations were highly variable across the basin, and for most main-stem sites, median concentrations were greater than or equal to the water-quality objective.
During the recent period (2009–19), the annual flow-averaged concentrations of total dissolved solids and sulfate increased for nearly all stream sites with most sites having mildly significant or significant increases. One-half of the sites had an annual flow-averaged geometric mean concentration greater than the total dissolved solids water-quality objective, and four sites had sulfate increases greater than 100 milligrams per liter. Trends in annual flow-averaged concentrations of sodium and chloride generally were small and nonsignificant. Most sites had concentrations greater than the sodium water-quality objective, whereas all sites had concentrations much less than the chloride water-quality objective. Annual flow-averaged geometric mean concentration of total phosphorus decreased for nearly all sites across the Souris River Basin, but all sites had concentrations greater than the total phosphorus water-quality objective for the entire period. Small and nonsignificant changes in annual flow-averaged geometric mean concentration of total iron were detected at all sites but the binational site at Sherwood, N. Dak., and by 2019 all sites had concentrations greater than the total iron water-quality objective. For the reservoir sites, during 2000–15, mostly significant increases for total dissolved solids, sulfate, and sodium were detected, whereas changes in total phosphorus and total iron were mixed.
During the historical period (1976–2019), large and consistent increases in total dissolved solids and sulfate have occurred since the late 1980s, with the largest increases and the most sites with mildly significant or significant increases generally occurring during the middle period (1988–2005). Large and significant or mildly significant increases in sodium concentrations occurred at eight of 10 sites in the middle period (1988–2005), and by the late period (2005–19) changes were small and nonsignificant. Similar to other basins in the region, such as the Red River of the North and Heart River, large and overall consistent increases since the late 1980s in total dissolved solids and sulfate in the Souris River Basin suggest that long-term natural (hydroclimatic) processes are large contributors to increases in the concentration of salts in streams and reservoirs associated with the onset of wetter conditions. The concurrent increases in sulfate and sodium concentrations at all sites during the middle period (1988–2005) suggest that sodium-sulfate evaporite dissolution may be a factor contributing to increases.
Total phosphorus concentrations oscillated between increasing and decreasing during the historical period, with concentrations increasing during the first trend period (1976–88) and decreasing in the fourth trend period (2009–19) to the lowest flow-averaged geometric mean concentration by 2019 for most sites. During the historical period, changes in total iron concentrations were mostly nonsignificant and generally small, and variability in total iron concentrations likely affected the ability to detect statistically significant changes in concentration.
The probability of exceeding the water-quality objective for total dissolved solids, sulfate, and sodium increased between 1976 and 2019 for the binational sites, especially for sulfate, which more than doubled for Souris River near Sherwood, N. Dak. and increased more than seven times for Souris River near Westhope, N. Dak. Total phosphorus and total iron concentrations for the binational sites were likely to exceed the water-quality objective for most of the year, but seasonal patterns of total phosphorus and total iron concentrations were different between the sites, suggesting that different factors may affect concentrations at different times of the year. For sodium, total phosphorus, and total iron, exceedance of the water-quality objective most of the time is not unexpected given that the flow-averaged geometric mean concentration for these three constituents for most sites across the basin are greater than the water-quality objective for most of the period. If natural processes are affecting total dissolved solids and sulfate concentrations, concentrations would be expected to vary with time, and as a result, extended periods of concentrations greater or less than the water-quality objective are likely to occur depending upon climatic conditions.
A better understanding of the state of water quality across the Souris River Basin is beneficial to understanding and interpreting water-quality conditions at the two Souris River binational sites. The most consistent spatial and temporal change observed for this study was large and consistent increases in sulfate and total dissolved solids among tributary and main-stem sites since the late 1980s. For sulfate and total dissolved solids, wetter climatic conditions combined with naturally occurring and abundant sources of sulfate likely contributed to sustained exceedances of water-quality objectives in recent decades, and extended periods of concentrations greater than or less than the water-quality objective are likely to occur depending on climatic conditions. For sodium, total iron, and total phosphorus, sustained exceedances of the current water-quality objective likely will continue because most sites across the basin had flow-averaged geometric mean concentrations greater than the water-quality objective; and during the 43-year period of analysis, regardless of climatic conditions, exceedances were consistently greater than the water-quality objective. Further investigation into the factors causing increasing sulfate concentrations and a better understanding of reservoir dynamics would enhance the understanding of changes in water-quality conditions in the Souris River Basin.
The basin-wide approach of this report provided an improved understanding of water-quality conditions in the Souris River Basin, and results can be used to inform the current water-quality objectives, inform potential changes to water management in the basin, and serve as a starting point for tracking future progress. Gaps in understanding of water-quality conditions can be closed through continued monitoring and further investigation into causes behind changes in water-quality conditions identified in this report.
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Contamination from acid mine drainage affects ecosystems and usability of groundwater for domestic and municipal purposes. The Captain Jack Superfund Site outside of Ward, Boulder County, Colorado, USA, hosts a draining mine adit that was remediated through emplacement of a hydraulic bulkhead to preclude acid mine drainage from entering nearby Lefthand Creek. During impoundment of water within the mine workings in 2020, a diverse and novel dataset of stable isotopes of water, sulfate, and carbon (δ2H, δ18OH2O, δ18OSO4, δ34S, δ13CDIC), rare earth elements, and environmental tracers (noble gases and tritium) were collected to understand groundwater recharge and mixing, mechanisms of sulfide oxidation and water-rock interaction, and the influence of remediation on the hydrologic and geochemical system. Water isotopes indicate that groundwater distal from the mine workings has seasonally variable recharge sources whereas water within the workings has a distinctive composition with minimal temporal variability. Sulfate isotopes indicate that sulfide oxidation occurs both within the mine workings and in adjacent igneous dikes, and that sulfide oxidation may occur under suboxic conditions with ferric iron as the oxidant. Carbon isotopes track the neutralization of acidic waters and the carbon mass budget of the system. Rare earth elements corroborate stable isotopes in indicating groundwater compartmentalization, and additionally illustrate enhanced mineral weathering in the mine workings. Environmental tracers indicate mixing of modern and pre-modern groundwater and inform timelines that active remediation may be needed. Together these datasets provide a useful template for similar investigations of abandoned mine sites where physical mixing processes, sources of solute loading, or remediation timeframes are of importance.
Floodplains provide critical ecosystem services to people by regulating floodwaters and retaining sediments and nutrients. Geospatial analyses, field data collection, and modeling were integrated to quantify a portfolio of services that floodplains provide to downstream communities within the Chesapeake Bay and Delaware River watersheds. The portfolio of services included floodplain sediment and nutrient retention and flood regulation. Sediment and nutrient retention were quantified and valued for all non-tidal wadable streams in the Chesapeake Bay and Delaware River watersheds. Predicted nitrogen fluxes from measurements of streambanks and floodplain geomorphic changes were summarized at various scales (river basin, state, and county) and valued using a benefits transfer approach. Floodplain flood regulation services were assessed through a pilot study focused on the Schuylkill River watershed in the Delaware River watershed. Geospatial analysis and published flood frequency estimates were used to assess baseline and counterfactual (i.e., floodplain storage removed) scenarios. Flood regulation was valued using the Federal Emergency Management Agency's Hazus model to compare differences in structural damage to private residences under baseline and counterfactual scenarios. The estimated value of floodplain sediment and nutrient retention was \\$223 million United States dollars (USD) per year in the Chesapeake Bay watershed and \\$38 million USD per year in the Delaware River watershed. Sediment and nutrient retention benefits were offset by a streambank erosion cost of \\$123 million and \\$14 million USD annually in the Chesapeake and Delaware watersheds, respectively. In the Schuylkill River watershed floodplain flood regulation was valued at \\$860,000 USD per year, with an additional \\$7.2 million USD annually provided through floodplain sediment and nutrient retention. Together this portfolio of floodplain ecosystem services indicates that floodplains provide substantial benefits to people by trapping nutrients and storing floodwaters.
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range of hydrologic responses can be observed in steep, recently burned terrain, which makes predicting the spatial distribution of large debris flows challenging. Studies from rainfall-induced landslides in unburned areas show evidence of hydroclimatic tuning of landslide triggering, such that the spatial distribution of events is best predicted by the observed rainfall anomaly relative to climatic norms rather than by absolute rainfall. In this paper, we test whether the spatial distribution of debris flows in response to rainfall can be similarly predicted by rainfall anomaly. The 520 km2 Dolan Fire burn scar in Monterey County, California, USA, spans a sharp hydroclimatic gradient and experienced a widespread storm in January 2021 that triggered floods and debris flows, providing a natural experiment in which to test this hypothesis. In this study, we use remote and field methods to map debris-flow response and examine its spatial heterogeneity. Together with rainfall data, our mapping reveals that the observed anomalies in peak 15-min rainfall intensity (I15) relative to the intensity of the 1-yr return interval storm predict debris-flow occurrence better than the absolute peak I15. Our findings indicate that debris-flow processes and threshold rainfall required for debris-flow initiation may be tuned to local hydroclimate.
","conferenceTitle":"8th International Conference on Debris Flow Hazard Mitigation","conferenceDate":"June 26-29, 2023","conferenceLocation":"Turin, Italy","language":"English","publisher":"EDP Sciences","doi":"10.1051/e3sconf/202341504003","usgsCitation":"Cavagnaro, D.B., McCoy, S., Thomas, M.A., Kostelnik, J., and Lindsay, D.N., 2023, The spatial distribution of debris flows in relation to observed rainfall anomalies: Insights from the Dolan Fire, California, 8th International Conference on Debris Flow Hazard Mitigation, v. 415, Turin, Italy, June 26-29, 2023, 04003, 4 p., https://doi.org/10.1051/e3sconf/202341504003.","productDescription":"04003, 4 p.","ipdsId":"IP-142506","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":442361,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1051/e3sconf/202341504003","text":"Publisher Index Page"},{"id":420912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Dolan fire","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.7,\n 36.3\n ],\n [\n -121.7,\n 35.9\n ],\n [\n -121.2,\n 35.9\n ],\n [\n -121.2,\n 36.3\n ],\n [\n -121.7,\n 36.3\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"415","noUsgsAuthors":false,"publicationDate":"2023-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Cavagnaro, David B.","contributorId":267181,"corporation":false,"usgs":false,"family":"Cavagnaro","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":883279,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Scott W.","contributorId":267182,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott W.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":883280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883281,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kostelnik, Jaime 0000-0002-1817-5461","orcid":"https://orcid.org/0000-0002-1817-5461","contributorId":300717,"corporation":false,"usgs":true,"family":"Kostelnik","given":"Jaime","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883282,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsay, Donald N.","contributorId":216337,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","email":"","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":883283,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70239939,"text":"70239939 - 2023 - Bedrock erosion by debris flows at Chalk Cliffs, Colorado, USA: Implications for bedrock channel evolution","interactions":[],"lastModifiedDate":"2024-02-23T16:33:01.079388","indexId":"70239939","displayToPublicDate":"2023-08-18T10:23:09","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Bedrock erosion by debris flows at Chalk Cliffs, Colorado, USA: Implications for bedrock channel evolution","docAbstract":"Debris flow erosion into bedrock helps to set the pace of mountain denudation, but there are few empirical observations of this process. We studied the effects of debris flows on bedrock erosion using Structure-From-Motion photogrammetry and multiple real-time monitoring measurements. We found that the distribution of bedrock erosion across the channel cross-section could be generalized as an exponentially decreasing function of height above the channel thalweg. Using this empirical function, we simulated the erosion at a cross-section after the theoretical passage of a migrating knickpoint effectively matching the upstream pre-knickpoint cross-sectional shape to the downstream post-knickpoint cross-sectional shape via debris-flow bedrock erosion.
","conferenceTitle":"8th International Conference on Debris Flow Hazard Mitigation (DFHM8)","conferenceDate":"June 26-29, 2023","conferenceLocation":"Torino, Italy","language":"English","publisher":"E3S Web of Conferences","doi":"10.1051/e3sconf/202341503024","usgsCitation":"Rengers, F.K., Kean, J.W., Coe, J.A., Hanson, M., and Smith, J., 2023, Bedrock erosion by debris flows at Chalk Cliffs, Colorado, USA: Implications for bedrock channel evolution, 8th International Conference on Debris Flow Hazard Mitigation (DFHM8), v. 415, Torino, Italy, June 26-29, 2023, 03024, 4 p., https://doi.org/10.1051/e3sconf/202341503024.","productDescription":"03024, 4 p.","ipdsId":"IP-145430","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":442364,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1051/e3sconf/202341503024","text":"Publisher Index Page"},{"id":425947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Chalk Cliffs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.15715370629714,\n 38.746275047848656\n ],\n [\n -106.22600073568945,\n 38.746275047848656\n ],\n [\n -106.22600073568945,\n 38.705844444526775\n ],\n [\n -106.15715370629714,\n 38.705844444526775\n ],\n [\n -106.15715370629714,\n 38.746275047848656\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"415","noUsgsAuthors":false,"publicationDate":"2023-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":862444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":895352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":895353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanson, Megan","contributorId":334352,"corporation":false,"usgs":false,"family":"Hanson","given":"Megan","email":"","affiliations":[],"preferred":false,"id":895354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Joel","contributorId":334353,"corporation":false,"usgs":false,"family":"Smith","given":"Joel","email":"","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":895355,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}