High fluoride (F) groundwaters (>1 mg/L) have been recognized as a water quality problem for nearly a century and occur in many countries worldwide. The affected aquifers can be sedimentary, metamorphic or igneous rocks, but the process giving rise to high-F concentrations has been studied with geochemical modeling and an examination of the rock sources. The association of high-F with silicic igneous rocks such as granites and rhyolites results from magmatic differentiation (fractional crystallization, fractional melting, and crustal assimilation) wherein F is enriched in the liquid phase because of its incompatibility in the mafic minerals that crystallize early during cooling. Further development of F-rich groundwaters occurs during the evolution of Na-HCO3 waters because of removal of Ca through ion-exchange and calcite precipitation, thereby raising the F concentration from minerals like fluorite and fluorapatite to maintain solubility equilibrium. Increasing temperatures enhance this effect because of the retrograde solubility of calcite. From geochemical modeling using the PhreeqcI code, the primary variables controlling F concentrations are DIC (dissolved inorganic carbon), salinity (ionic strength), PCO2, and temperature. Complexing is also important but plays a more secondary role. Considering these variables, an improved set of plotting parameters, F/Cl vs. HCO3/Cl, are shown to be effective in interpreting groundwater analyses. This approach is demonstrated by examining case studies from the Black Creek aquifer, South Carolina, USA, the Madison regional aquifer, midwestern USA, the Mizunami Underground Research Laboratory, Japan, New Zealand thermal waters, the San Luis Valley groundwaters, Colorado, USA, and the Aquia aquifer, Maryland, USA.
Mangrove surface elevation is the crux of mangrove vulnerability to sea level rise. Local topography influences critical periods of tidal inundation that govern distributions of mangrove species and dictates future distributions. This study surveyed ground surface elevations of the extensive mangroves of Pohnpei, Federated States of Micronesia, integrating four survey technologies to solve issues of canopy blocking satellite reception, dense aerial roots limiting line-of-sight, and remoteness from surveyed datums. The island-wide average elevation of the mangrove seaward edge was −0.57 ± 0.13 m relative to MSL, while the landward average elevation was 0.33 ± 0.12 m relative to MSL. The overall mangrove elevation range was thus estimated to be 0.90 m. Mangrove species Bruguiera gymnorrhiza, Rhizophora apiculata and Sonneratia alba had large, overlapping elevation ranges, while Rhizophora stylosa occurred low in the tide frame. These species are likely to be less vulnerable to rising sea level given their greater range of elevation occurrence and presumably flooding tolerance, and hence have the highest adaptive capacity to rising sea level. Some landward edge species had very narrow elevation ranges, increasing their vulnerability to sea-level rise, with adjacent potential upland migration areas limited due to steep topography and human development. Pohnpei mangroves occupied 74% of the mean tidal range, similar to surveys elsewhere in the Pacific. This study demonstrates how more extensive understanding of the elevation distributions of intertidal species can contribute to sea-level rise vulnerability assessments, to allow prioritised climate change adaptation. However, more work is needed in standardizing approaches for global comparisons.
Gas hydrate production technologies commonly feature reservoir depressurization. Depressurization occurs when a pressure gradient is established in a well, drawing mobile water from the reservoir and reducing reservoir pressure. As such, the occurrence of mobile water is a necessary condition for effective gas production from gas hydrate reservoirs using common borehole-based methods. However, recent field programs have revealed that mobile water exists widely within the overall gas hydrate reservoir system, including within overlying and underlying units once thought of as virtually impermeable seals. Further, excess free water may also be commonly found in hydrate-free or hydrate-poor permeable strata interbedded within the larger gas hydrate reservoir system. Such internal sources of water are complex to characterize, difficult to explain, potentially highly heterogeneous, and may pose significant challenges to depressurization-based production. This report summarizes the general occurrence of water in gas hydrate systems and select technical implications.
The study of volcano deformation has grown significantly through they year 2020 since the development of interferometric synthetic aperture radar (InSAR) in the 1990s. This relatively new data source, which provides evidence of changes in subsurface magma storage and pressure without the need for ground-based equipment, has matured during the past decade. It now provides a means to address previously inaccessible questions and offers input to increasingly complex models of magmatic processes. Here, we review how technological advances in InSAR during 2010-2020 have facilitated our ability to monitor and interpret volcanic processes, primarily through rapid and accurate observations of the changing surfaces at active volcanoes worldwide. Specifically, we examine how current systems achieve excellent resolution in time and space, provide global coverage, and generate products that are easy to use by non-specialists—factors that have often limited the practical study of volcanoes using radar measurements. We also look to the future, offering our perspective about how advancements in technology and data management in the decade to come will increase the value and accessibility of InSAR applied to the geodetic study of volcanoes and monitoring of hazardous volcanic processes. New developments will include the launch of additional satellites by both public space agencies and private companies, as well as implementation of algorithms for exploiting the growing volumes of data. To meet their full potential, these efforts will require coordination between data users and data providers so that the relevant imagery is acquired, made available to volcanologists in a timely fashion, and utilized to assess and mitigate volcanic hazards.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-022-01531-1","usgsCitation":"Poland, M., and Zebker, H., 2022, Volcano geodesy using InSAR in 2020: The past and next decades: Bulletin of Volcanology, v. 84, no. 3, 27, 8 p., https://doi.org/10.1007/s00445-022-01531-1.","productDescription":"27, 8 p.","ipdsId":"IP-133322","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":397694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael 0000-0001-5240-6123","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":49920,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":838942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zebker, Howard 0000-0001-9931-5237","orcid":"https://orcid.org/0000-0001-9931-5237","contributorId":289333,"corporation":false,"usgs":false,"family":"Zebker","given":"Howard","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":838943,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70251316,"text":"70251316 - 2022 - Permeability measurement and prediction with nuclear magnetic resonance analysis of gas hydrate-bearing sediments recovered from Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well","interactions":[],"lastModifiedDate":"2024-02-03T14:13:07.268011","indexId":"70251316","displayToPublicDate":"2022-02-22T08:06:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17149,"text":"Energy and Fuels Journal","active":true,"publicationSubtype":{"id":10}},"title":"Permeability measurement and prediction with nuclear magnetic resonance analysis of gas hydrate-bearing sediments recovered from Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well","docAbstract":"Permeability of porous media, such as oil and gas reservoirs, is the crucial material parameter for predicting their hydraulic behavior. A nuclear magnetic resonance (NMR) analyzer is widely used as a powerful tool to predict permeability of various media. NMR T2 (transverse or spin–spin) relaxation time distribution, which is related to pore size distribution, gives the information to allow calculation of effective (initial) permeability. In this study, we investigate effective, intrinsic (absolute), and relative water and gas permeabilities of hydrate-bearing pressure core samples. These samples were recovered from the Alaska North Slope 2018 Hydrate-01 Stratigraphic Test Well by sidewall pressure coring and then analyzed in a laboratory using both fluid flow test and NMR analyzer. The peak of the NMR T2 distribution was measured at 10–20 ms using a laboratory NMR analyzer, which compares well with in situ measurements obtained via logging while drilling NMR data for two samples with high gas hydrate saturations (Sh = 76% and 74%). Further, comparison of laboratory NMR T2 distribution after hydrate dissociation revealed that the hydrate existed in large pore spaces. Effective permeabilities predicted by the Timur-Coates (TC) model and the Schlumberger-Doll-Research (SDR) model, with T2 cutoff 33 ms, were about an order of magnitude less than the laboratory measured values. Alternative TC model-based calculations with the T2 cutoff reduced to 10 ms and a newly developed hydraulic radius model better matched the laboratory data. For the analysis of the intrinsic permeabilities, the TC model with a T2 cutoff of 33 ms and SDR model were greater than the laboratory derived values, while the hydraulic radius model more closely matched the laboratory-derived values. In addition, permeability measurements were also made relative to gas and water under constant three-phase flow (water–gas–hydrate) conditions. After hydrate dissociation, a relative permeability curve was developed for each of the analyzed core samples based on the Corey petrophysical model. The results indicate that the gas permeability changed rapidly at high water saturation around 90%. Thus, we infer that the selection of relative reservoir parameters should focus on the higher water saturation conditions.
We introduce procedures to validate site response in sedimentary basins as predicted using ground motion simulations. These procedures aim to isolate contributions of site response to computed intensity measures relative to those from seismic source and path effects. In one of the validation procedures, simulated motions are analyzed in the same manner as earthquake recordings to derive non-ergodic site terms. This procedure compares the scaling with sediment isosurface depth of simulated versus empirical site terms (the latter having been derived in a separate study). A second validation procedure utilizes two sets of simulations, one that considers three-dimensional (3D) basin structure and a second that utilizes a one-dimensional (1D) representation of the crustal structure. Identical sources are used in both procedures, and after correcting for variable path effects, differences in ground motions are used to estimate site amplification in 3D basins. Such site responses are compared to those derived empirically to validate both the absolute levels and the depth scaling of site response from 3D simulations. We apply both procedures to southern California in a manner that is consistent between the simulated and empirical data (i.e. by using similar event locations and magnitudes). The results show that the 3D simulations overpredict the depth-scaling and absolute levels of site amplification in basins. However, overall patterns of site amplification with depth are similar, suggesting that future calibration may be able to remove observed biases.
Episodes of unrest are not as well documented as eruptions at most volcanoes globally. Iliamna is an andesitic stratovolcano in the Cook Inlet of Alaska that has experienced several episodes of unrest. Unrest in 1996 was previously studied. Here we present data from a minor period of unrest between 2002 and 2006, and a more significant period in 2012. None of the episodes led to an eruption. A dike intrusion was suggested for the 1996 unrest based on increases in gas emissions and seismic analysis. The 2002–2006 period was characterized by a slight increase in the rate of seismicity to 13 events per day and was particularly notable due to an increase in deep long period (DLP) seismic events between 15 and 37 km that were not observed at other times. This period also included one airborne gas measurement with and elevated CO2/SO2 molar ratio (17). In 2012, Iliamna unrest was characterized by significantly elevated gas emissions (up to 582 t/d SO2 and 1385 t/d CO2) and up to 49 located earthquakes per day (M > 0), and was remarkably similar to the 1996 unrest. Differences in the observed evolution of the CO2/SO2 gas ratio in 2012 (2.2–4) compared to that in 1996 (up to 18) suggests that no new deep magma was involved in 2012, however this does not preclude the movement of a previously intruded magma. A months-long increase in the SO2/H2S molar ratio from 8 to 17 during the peak of the activity could reflect a temperature increase on the order of 10–30 °C of the emitted gas. Compared to pre-eruptive unrest at other Cook Inlet volcanoes, Iliamna unrest in 2012 differed in that gas emissions were < 1500 t/d and seismicity lacked a rapidly escalating sequence of earthquakes and volcanic tremor, which is normally observed in the hours to days before eruption. The observation of DLPs, the fact that Iliamna produces moderately elevated degassing over decadal timeframes, and the persistent dominance of SO2 over H2S, suggests that periodic input of fresh magma from the lower crust sustains the shallower magmatic system over time, which sets it apart from neighboring volcanoes in the Cook Inlet that show minimal activity between eruptions. Various scenarios could explain why Iliamna did not proceed to eruption in 2012. Finally, we present criteria by which monitoring data may suggest an increased likelihood of eruption at Iliamna in the future.
The Neosho madtom (Noturus placidus) is a small catfish, generally less than 3 inches in length, unique to the Neosho-Spring River system within the Arkansas River Basin. It was federally listed as threatened in 1990, largely due to habitat loss. For conservation efforts, we generated whole-genome sequence data from 10 Neosho madtom individuals originating from 3 geographically separated populations to evaluate genetic diversity and population structure. A Neosho madtom genome was de novo assembled, and genome size and content were assessed. Single nucleotide polymorphisms were assessed from de Bruijn graphs, and via reference alignment with both the channel catfish (Ictalurus punctatus) reference genome and Neosho madtom reference genome. Principal component analysis and structure analysis indicated weak population structure, suggesting fish from the 3 locations represent a single population. Using a novel method, genome-wide conservation and divergence between the Neosho madtom, channel catfish, and zebrafish (Danio rerio) was assessed by pairwise contig alignment, which demonstrated that genes important to embryonic development frequently had conserved sequences. This research in a threatened species with no previously published genomic resources provides novel genetic information to guide current and future conservation efforts and demonstrates that using whole-genome sequencing provides detailed information of population structure and demography using only a limited number of rare and valuable samples.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/g3journal/jkac046","usgsCitation":"Whitacre, L.K., Wildhaber, M.L., Johnson, G., Durbin, H.J., Rowan, T.N., Peoria Tribe, Schnabel, R.D., Mhlanga-Mutangadura, T., Tabor, V.M., Fenner, D., and Decker, J.E., 2022, Exploring genetic variation and population structure in a threatened species, Noturus placidus, with whole-genome sequence data: G3: Genes, Genomes, Genetics, v. 12, no. 4, jkac046, 9 p., https://doi.org/10.1093/g3journal/jkac046.","productDescription":"jkac046, 9 p.","ipdsId":"IP-088642","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":448714,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/g3journal/jkac046","text":"Publisher Index Page"},{"id":435950,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MAPT9T","text":"USGS data release","linkHelpText":"Neosho Madtom (Noturus placidus) short read archive and whole genome sequence data"},{"id":398631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.50390624999999,\n 36.35052700542763\n ],\n [\n -93.251953125,\n 36.35052700542763\n ],\n [\n -93.251953125,\n 37.99616267972814\n ],\n [\n -96.50390624999999,\n 37.99616267972814\n ],\n [\n -96.50390624999999,\n 36.35052700542763\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Whitacre, Lynsey 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D.","contributorId":290184,"corporation":false,"usgs":false,"family":"Schnabel","given":"Robert","email":"","middleInitial":"D.","affiliations":[{"id":62373,"text":"Informatics Institute, University of Missouri, Columbia, Missouri","active":true,"usgs":false}],"preferred":false,"id":840472,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mhlanga-Mutangadura, Tendai","contributorId":290186,"corporation":false,"usgs":false,"family":"Mhlanga-Mutangadura","given":"Tendai","email":"","affiliations":[{"id":62375,"text":"Department of Veterinary Pathobiology, College of Veterinary Medicine, University of Missouri, Columbia, Missouri","active":true,"usgs":false}],"preferred":false,"id":840473,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tabor, Vernon M.","contributorId":290187,"corporation":false,"usgs":false,"family":"Tabor","given":"Vernon","email":"","middleInitial":"M.","affiliations":[{"id":62378,"text":"U.S. Fish and Wildlife Service, Kansas Ecological 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complexity","interactions":[],"lastModifiedDate":"2022-02-25T12:48:05.003019","indexId":"70229024","displayToPublicDate":"2022-02-22T06:46:39","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Kelp-forest dynamics controlled by substrate complexity","docAbstract":"The factors that determine why ecosystems exhibit abrupt shifts in state are of paramount importance for management, conservation, and restoration efforts. Kelp forests are emblematic of such abruptly shifting ecosystems, transitioning from kelp-dominated to urchin-dominated states around the world with increasing frequency, yet the underlying processes and mechanisms that control their dynamics remain unclear. Here, we analyze four decades of data from biannual monitoring around San Nicolas Island, CA, to show that substrate complexity controls both the number of possible (alternative) states and the velocity with which shifts between states occur. The superposition of community dynamics with reconstructions of system stability landscapes reveals that shifts between alternative states at low-complexity sites reflect abrupt, high-velocity events initiated by pulse perturbations that rapidly propel species across dynamically unstable state–space. In contrast, high-complexity sites exhibit a single state of resilient kelp–urchin coexistence. Our analyses suggest that substrate complexity influences both top-down and bottom-up regulatory processes in kelp forests, highlight its influence on kelp-forest stability at both large (island-wide) and small (<10 m) spatial scales, and could be valuable for holistic kelp-forest management.
We analyzed impacts of interannual disturbance on the water balance of watersheds in different forested ecosystem case studies across the United States from 1985 to 2016 using a remotely sensed long-term land cover monitoring record (U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1.0 Science products), gridded precipitation and evaporation data, and streamgaging data using paired watersheds (high and low disturbance). LCMAP products were used to quantify the timing and degree of interannual disturbance and to gain a better understanding of how land cover change affects the water balance of disturbed watersheds. In this paper, we present how LCMAP science products can be used to improve knowledge for hydrologic modeling, climate research, and forest management. Anthropogenic influences (e.g., dams and irrigation diversions) often minimize the impacts of land cover change on water balance dynamics when compared to interannual fluctuations of hydroclimatic events (e.g., drought and flooding). Our findings show that each watershed exhibits a complex suite of influences involving climate variables and other factors that affect each of their water balances differently when land cover change occurs. In this study, forests within arid to semi-arid climates experience greater water balance effects from land cover change than watersheds where water is less limited.
","language":"English","publisher":"MDPI","doi":"10.3390/land11020316","usgsCitation":"Healey, N.C., and Rover, J., 2022, Analyzing the effects of land cover change on the water balance for case study watersheds in different forested ecosystems in the USA: Land, v. 11, no. 2, 316, 43 p., https://doi.org/10.3390/land11020316.","productDescription":"316, 43 p.","ipdsId":"IP-130474","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":448718,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/land11020316","text":"Publisher Index Page"},{"id":396438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n 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-117.03121,\n 49\n ],\n [\n -116.04818,\n 49\n ],\n [\n -113,\n 49\n ],\n [\n -110.05,\n 49\n ],\n [\n -107.05,\n 49\n ],\n [\n -104.04826,\n 48.99986\n ],\n [\n -100.65,\n 49\n ],\n [\n -97.22872,\n 49.0007\n ],\n [\n -95.15907,\n 49\n ],\n [\n -95.15609,\n 49.38425\n ],\n [\n -94.81758,\n 49.38905\n ]\n ]\n ]\n ]\n },\n \"properties\": {\n \"name\": \"United States\"\n }\n }\n ]\n}","volume":"11","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Healey, Nathan C. 0000-0002-8516-2636","orcid":"https://orcid.org/0000-0002-8516-2636","contributorId":280023,"corporation":false,"usgs":false,"family":"Healey","given":"Nathan","email":"","middleInitial":"C.","affiliations":[{"id":57411,"text":"KBR, Inc.","active":true,"usgs":false}],"preferred":false,"id":835894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rover, Jennifer 0000-0002-3437-4030","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":211850,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":835895,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70264656,"text":"70264656 - 2022 - Rainfall triggering of post-fire debris flows over a 28-year period near El Portal, California, USA","interactions":[],"lastModifiedDate":"2025-03-18T16:02:43.640972","indexId":"70264656","displayToPublicDate":"2022-02-21T10:55:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7559,"text":"Environmental and Engineering Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Rainfall triggering of post-fire debris flows over a 28-year period near El Portal, California, USA","docAbstract":"Wildfires frequently affect the steep hillslopes near El Portal, California (United States), a small community established during the California Gold Rush in the mid-1800s. In addition to the historical significance of El Portal, State Route 140 (SR 140) is a major transportation and economic corridor connecting the San Joaquin Valley to Yosemite National Park (YNP). In 2019, an estimated 4.5 million tourists visited and accessed YNP via SR 140. In the years after wildfires, the burned watersheds produced debris flows during intense rainfall, impacting the El Portal community and motorists traveling on SR 140 and local roads. The steepness of the hillslopes and confinement of the valley limit options for mitigating debris-flow risk. As such, emergency managers are left with evacuation orders or temporary road closures as the best options for risk reduction. The effectiveness of these options is highly dependent on establishing an accurate local rainfall intensity-duration threshold that officials can use to guide emergency response actions and timing. We present an overview of the rainfall conditions that initiated 12 post-fire debris-flow events near El Portal from 1991 to 2018 and objectively define rainfall intensity-duration thresholds from triggering rainfall rates. Our results highlight the modest rainfall rates that triggered debris flows in these steep watersheds, while radar data from more recent events (2012–2018) portray the spatial variability of intense rainfall in the area. Additional rainfall monitoring is needed to provide a robust rainfall threshold that will effectively mitigate risk for residents and motorists while minimizing the impact of road closures and evacuations.
","language":"English","publisher":"Association of Environmental & Engineering Geologists","doi":"10.2113/EEG-D-21-00031","usgsCitation":"De Graff, J.V., Staley, D.M., Stock, G., Takenaka, K., Gallegos, A., and Neptune, C., 2022, Rainfall triggering of post-fire debris flows over a 28-year period near El Portal, California, USA: Environmental and Engineering Geoscience, v. 28, no. 1, p. 133-145, https://doi.org/10.2113/EEG-D-21-00031.","productDescription":"14 p.","startPage":"133","endPage":"145","ipdsId":"IP-134684","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":483478,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"El Portal, Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.333,\n 38\n ],\n [\n -120.25,\n 38\n ],\n [\n -120.25,\n 37.333\n ],\n [\n -119.333,\n 37.333\n ],\n [\n -119.333,\n 38\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"28","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"De Graff, Jerome V.","contributorId":195393,"corporation":false,"usgs":false,"family":"De Graff","given":"Jerome","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":931121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":931122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stock, Greg M.","contributorId":258810,"corporation":false,"usgs":false,"family":"Stock","given":"Greg M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":931123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takenaka, Kellen","contributorId":352407,"corporation":false,"usgs":false,"family":"Takenaka","given":"Kellen","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":931124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gallegos, Alan L.","contributorId":352408,"corporation":false,"usgs":false,"family":"Gallegos","given":"Alan L.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":931125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neptune, Chad K.","contributorId":352411,"corporation":false,"usgs":false,"family":"Neptune","given":"Chad K.","affiliations":[{"id":84211,"text":"California State University, Fresno CA USA","active":true,"usgs":false}],"preferred":false,"id":931126,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70235911,"text":"70235911 - 2022 - Rockfall kinematics from massive rock cliffs: Outlier boulders and flyrock from Whitney Portal, California, rockfalls","interactions":[],"lastModifiedDate":"2022-08-25T15:34:43.529882","indexId":"70235911","displayToPublicDate":"2022-02-21T10:17:41","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7559,"text":"Environmental and Engineering Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Rockfall kinematics from massive rock cliffs: Outlier boulders and flyrock from Whitney Portal, California, rockfalls","docAbstract":"Geologic conditions and topographic setting are among the most critical factors for assessing rockfall hazards. However, other subtle features of rockfall motion may also govern the runout of rockfall debris, particularly for those sourced from massive cliffs where debris can have substantial momentum during transport. Rocks may undergo collisions with trees and talus boulders, with the latter potentially generating flyrock—launched rock pieces resulting from boulder collisions that follow distinctively different paths than the majority of debris. Collectively, these intricacies of rockfall kinematics may substantially govern the hazards expected from rockfall to both persons and infrastructure located beneath steep cliffs. Here, we investigate the kinematics, including outlier boulder and flyrock trajectories, of seismically triggered rockfalls on 24 June 2020 that damaged campground facilities near Whitney Portal, CA, a heavily used outdoor recreation gateway to the Sierra Nevada mountains. Our results, obtained in part by rockfall runout model simulations, indicate that outlier boulder trajectories resulted from opportunities provided by less steep terrain beyond the talus edge. The influence of trees, initially thought to have served a protective capacity in attenuating rockfall energy, appears to have been negligible for the large boulder volumes (>50 m3) mobilized, although they did potentially deflect the trajectory of flyrock debris. Rockfall outlier boulders from the event were comparable in volume and runout distance to prehistoric boulders located beyond the talus slope, thereby providing some level of confidence in the use of a single rockfall shadow angle for estimating future rockfall hazards at the site.
","language":"English","publisher":"Association of Environmental & Engineering Geologists","doi":"10.2113/EEG-D-21-00023","usgsCitation":"Collins, B.D., Corbett, S.C., Horton, E.J., and Gallegos, A., 2022, Rockfall kinematics from massive rock cliffs: Outlier boulders and flyrock from Whitney Portal, California, rockfalls: Environmental and Engineering Geoscience, v. 28, no. 1, p. 3-24, https://doi.org/10.2113/EEG-D-21-00023.","productDescription":"22 p.","startPage":"3","endPage":"24","ipdsId":"IP-126637","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":435954,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93TJUXH","text":"USGS data release","linkHelpText":"Field, remote sensing, and modeling data used for Collins et al., Rockfall Kinematics from Massive Rock Cliffs: Outlier Boulders and Flyrock Resulting from the 2020 Whitney Portal, California Rockfalls"},{"id":405580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Whitney Portal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.32550048828126,\n 36.54688017175944\n ],\n [\n -118.20001602172852,\n 36.54688017175944\n ],\n [\n -118.20001602172852,\n 36.615252060835196\n ],\n [\n -118.32550048828126,\n 36.615252060835196\n ],\n [\n -118.32550048828126,\n 36.54688017175944\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":849667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corbett, Skye C. 0000-0003-3277-1021 scorbett@usgs.gov","orcid":"https://orcid.org/0000-0003-3277-1021","contributorId":200617,"corporation":false,"usgs":true,"family":"Corbett","given":"Skye","email":"scorbett@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":849668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horton, Elizabeth Jean","contributorId":295558,"corporation":false,"usgs":true,"family":"Horton","given":"Elizabeth","email":"","middleInitial":"Jean","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":849669,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gallegos, Alan J.","contributorId":295559,"corporation":false,"usgs":false,"family":"Gallegos","given":"Alan J.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":849670,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237759,"text":"70237759 - 2022 - Unravelling a 2300 year long sedimentary record of megathrust and intraslab earthquakes in proglacial Skilak Lake, south-central Alaska","interactions":[],"lastModifiedDate":"2023-11-14T15:06:47.199697","indexId":"70237759","displayToPublicDate":"2022-02-21T09:14:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3369,"text":"Sedimentology","active":true,"publicationSubtype":{"id":10}},"title":"Unravelling a 2300 year long sedimentary record of megathrust and intraslab earthquakes in proglacial Skilak Lake, south-central Alaska","docAbstract":"Seismic hazards in subduction settings typically arise from megathrust, intraslab and crustal earthquake sources. Despite the frequent occurrence of intraslab earthquakes in subduction zones and their potential threat to communities, their long-term recurrence behaviour is barely studied. Sedimentary sequences in lakes may register ground shaking from different seismic sources. This study investigates two long sediment cores (13 m and 16 m) from Skilak Lake, a proglacial lake in south-central Alaska, to evaluate whether different seismic sources leave a distinct imprint. The sedimentary record shows a continuously varved sediment sequence, occasionally interrupted by turbidites, slump deposits and tephra beds. Turbidites and slump deposits were objectively identified using a statistical outlier analysis on varve thickness. The earthquake origin of these deposits was ascertained by resemblance with deposits induced by instrumentally recorded earthquakes (for example, 1964 ce Mw 9.2 megathrust and 1954 ce Mw 6.4 intraslab earthquakes) and correlation with multiple coeval landslide deposits on sub-bottom profiles. The Skilak Lake record chronicles 19 earthquakes with moderate to very high confidence level in the past 1350 years. The sedimentary evidence of instrumentally-recorded intraslab and megathrust earthquakes within the past 70 years demonstrates that not only megathrust earthquakes, but also past intraslab events are recorded. Although reported seismic intensities at Skilak Lake are comparable for the 1964 ce megathrust and the 1954 ce intraslab earthquakes, the long duration and low frequency content of seismic ground motion during megathrust earthquakes facilitate the triggering of multiple, voluminous landslides and the generation of megaturbidites. In contrast, the shorter duration and higher frequency source spectrum of intraslab earthquakes may only induce surficial slope remobilization and the generation of thinner turbidites. This study demonstrates that the sedimentary record of Skilak Lake has the potential to decipher multiple seismic sources, which opens possibilities for a comprehensive seismic hazard analysis for south-central Alaska.
","language":"English","publisher":"Wiley","doi":"10.1111/sed.12986","usgsCitation":"Praet, N., Van Daele, M., Moernaut, J., Mestdagh, T., Vandorpe, T., Jensen, B.J., Witter, R., Haeussler, P., and De Batist, M., 2022, Unravelling a 2300 year long sedimentary record of megathrust and intraslab earthquakes in proglacial Skilak Lake, south-central Alaska: Sedimentology, v. 69, no. 5, p. 2151-2180, https://doi.org/10.1111/sed.12986.","productDescription":"30 p.","startPage":"2151","endPage":"2180","ipdsId":"IP-135294","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":408605,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Skilak Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -150.55,\n 60.5\n ],\n [\n -150.55,\n 60.35\n ],\n [\n -150.05,\n 60.35\n ],\n [\n -150.05,\n 60.5\n ],\n [\n -150.55,\n 60.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"69","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-04-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Praet, Nore","contributorId":194083,"corporation":false,"usgs":false,"family":"Praet","given":"Nore","email":"","affiliations":[],"preferred":false,"id":855465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Daele, Maarten 0000-0002-8530-4438","orcid":"https://orcid.org/0000-0002-8530-4438","contributorId":194085,"corporation":false,"usgs":false,"family":"Van Daele","given":"Maarten","email":"","affiliations":[{"id":27279,"text":"Department of Geology and Soil Science, Ghent University, Ghent, Belgium","active":true,"usgs":false}],"preferred":false,"id":855466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moernaut, Jasper","contributorId":194084,"corporation":false,"usgs":false,"family":"Moernaut","given":"Jasper","email":"","affiliations":[],"preferred":false,"id":855467,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mestdagh, Thomas 0000-0002-6312-7039","orcid":"https://orcid.org/0000-0002-6312-7039","contributorId":298372,"corporation":false,"usgs":false,"family":"Mestdagh","given":"Thomas","email":"","affiliations":[{"id":64542,"text":"Flanders Marine Institute","active":true,"usgs":false}],"preferred":false,"id":855468,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vandorpe, Thomas 0000-0002-1461-2484","orcid":"https://orcid.org/0000-0002-1461-2484","contributorId":298373,"corporation":false,"usgs":false,"family":"Vandorpe","given":"Thomas","email":"","affiliations":[{"id":64542,"text":"Flanders Marine Institute","active":true,"usgs":false}],"preferred":false,"id":855469,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jensen, Britta J.L. 0000-0001-9134-7170","orcid":"https://orcid.org/0000-0001-9134-7170","contributorId":244298,"corporation":false,"usgs":false,"family":"Jensen","given":"Britta","email":"","middleInitial":"J.L.","affiliations":[{"id":36696,"text":"University of Alberta","active":true,"usgs":false}],"preferred":false,"id":855470,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":855471,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":219956,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":855472,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"De Batist, Marc 0000-0002-1625-2080","orcid":"https://orcid.org/0000-0002-1625-2080","contributorId":194089,"corporation":false,"usgs":false,"family":"De Batist","given":"Marc","email":"","affiliations":[],"preferred":false,"id":855473,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70228780,"text":"70228780 - 2022 - Detrital zircon provenance of the Cretaceous-Neogene East Coast Basin reveals changing tectonic conditions and drainage reorganization along the Pacific margin of Zealandia","interactions":[],"lastModifiedDate":"2022-04-12T13:34:28.945014","indexId":"70228780","displayToPublicDate":"2022-02-21T08:56:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Detrital zircon provenance of the Cretaceous-Neogene East Coast Basin reveals changing tectonic conditions and drainage reorganization along the Pacific margin of Zealandia","docAbstract":"The Upper Cretaceous–Pliocene strata of New Zealand record ~100 m.y. of Zealandia’s evolution, including development of the Hikurangi convergent margin and Alpine transform plate boundary. A comprehensive, new detrital zircon U-Pb data set (8315 analyses from 61 samples) was generated along a ~700 km transect of the East Coast Basin of New Zealand. Age distributions were analyzed and interpreted in terms of published data available for Cambrian–Cretaceous igneous and metasedimentary source terranes using a Monte Carlo mixture modeling approach. Results indicate a widespread Early Cretaceous transition in sediment source from the Gondwana interior to the Median Batholith magmatic arc prior to Late Cretaceous rifting from Antarctica. Submergence of Zealandia during a Late Cretaceous–Paleogene drift phase led to major drainage reorganization and the influx of Eastern Province sediment to the East Coast Basin. A long-lived sediment conduit that transported extraregional Western Province detritus to the south-central East Coast Basin may have developed along a structural precursor to the Alpine Fault. Marked Neogene increase of Upper Jurassic–Lower Cretaceous Torlesse Composite Terrane sediment to the central East Coast Basin resulted from exhumation of the Axial Ranges, convergence along the Hikurangi subduction margin, and concurrent development of the Alpine Fault. Concurrent influx of contemporaneous Neogene zircon in the northern East Coast Basin indicated the onset of subduction-related volcanism of the Northland–Coromandel Volcanic Arc. Middle Miocene–Pliocene exhumation and dextral translation of the Nelson region along the Alpine Fault resulted in the eastward routing of Western Province sediment to the central East Coast Basin. Finally, topography developed across the plate boundary and ultimately partitioned continental drainage of Zealandia, such that sediment from the Murihiku, Caples, and Rakaia Terranes in the Otago region was routed to the southern extent of the East Coast Basin. These results illuminate the evolution of the Zealandia continental drainage divide in response to the initiation of the Pacific-Australian plate boundary and demonstrate the power of mixture modeling and large data sets for deciphering sediment routing in dynamic tectonic environments.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02404.1","usgsCitation":"Gooley, J.T., and Nieminski, N.M., 2022, Detrital zircon provenance of the Cretaceous-Neogene East Coast Basin reveals changing tectonic conditions and drainage reorganization along the Pacific margin of Zealandia: Geosphere, v. 18, no. 2, p. 616-646, https://doi.org/10.1130/GES02404.1.","productDescription":"31 p.","startPage":"616","endPage":"646","ipdsId":"IP-125520","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":448721,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02404.1","text":"Publisher Index Page"},{"id":396221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 170.068359375,\n -47.04018214480665\n ],\n [\n 179.296875,\n -37.78808138412045\n ],\n [\n 173.935546875,\n -34.089061315849946\n ],\n [\n 172.44140625,\n -34.813803317113134\n ],\n [\n 173.49609375,\n -38.89103282648846\n ],\n [\n 170.947265625,\n -40.51379915504413\n ],\n [\n 165.76171875,\n -45.644768217751924\n ],\n [\n 168.57421875,\n -48.10743118848039\n ],\n [\n 170.068359375,\n -47.04018214480665\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Gooley, Jared T. 0000-0001-5620-3702","orcid":"https://orcid.org/0000-0001-5620-3702","contributorId":248710,"corporation":false,"usgs":true,"family":"Gooley","given":"Jared","email":"","middleInitial":"T.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":835452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nieminski, Nora Maria 0000-0002-4465-8731","orcid":"https://orcid.org/0000-0002-4465-8731","contributorId":279764,"corporation":false,"usgs":true,"family":"Nieminski","given":"Nora","email":"","middleInitial":"Maria","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":835453,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70228797,"text":"70228797 - 2022 - Hypotheses and lessons from a native moth outbreak in a low-diversity, tropical rainforest","interactions":[],"lastModifiedDate":"2022-02-21T14:55:42.496268","indexId":"70228797","displayToPublicDate":"2022-02-21T08:40:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Hypotheses and lessons from a native moth outbreak in a low-diversity, tropical rainforest","docAbstract":"Outbreaks of defoliating insects in low-diversity tropical forests occur infrequently but provide valuable insights about outbreak ecology in temperate environments and in general. 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Lightly defoliated small trees refoliated more quickly than did heavily defoliated ones but the opposite was true for large trees, which also produced a greater proportion of phyllodes. Mortality was greatest for heavily defoliated small koa. Caterpillar frass caused larger increases in soil nitrogen (N) than phosphorus (P) availability, with the greatest N increases in fine-textured soils. Foliar N increased in alien grasses under koa canopies compared to grasses away from koa and to native woody understory species. Bird activity was influenced by ‘ōhi‘a flower abundance and the severity of koa defoliation; birds switched to outbreaking caterpillar prey, and they gained weight during the outbreak. Bat foraging times decreased during the outbreak, apparently because they became satiated quickly each night. Parasitoid wasps increased with caterpillar abundance but had little influence on outbreak dynamics. Reducing alien grass cover and increasing tree diversity would likely reduce the impacts of insect outbreaks and similar perturbations to native forests.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.3926","usgsCitation":"Banko, P.C., Peck, R.W., Yelenik, S.G., Paxton, E.H., Bonaccorso, F., Montoya-Aiona, K., Hughes, R.F., and Perakis, S.S., 2022, Hypotheses and lessons from a native moth outbreak in a low-diversity, tropical rainforest: Ecosphere, v. 13, no. 2, p. 1-41, https://doi.org/10.1002/ecs2.3926.","productDescription":"e3926, 41 p.","startPage":"1","endPage":"41","ipdsId":"IP-080107","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":448722,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3926","text":"Publisher Index Page"},{"id":435958,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HE9WKK","text":"USGS data release","linkHelpText":"Hawaii Island insect response to koa moth (Scotorythra paludicola) outbreak, 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Flint","contributorId":140151,"corporation":false,"usgs":false,"family":"Hughes","given":"R.","email":"","middleInitial":"Flint","affiliations":[{"id":13397,"text":"USDA Forest Service, fhughes@fs.fed.us","active":true,"usgs":false}],"preferred":false,"id":835506,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":835507,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70229156,"text":"70229156 - 2022 - DSWEmod - The production of high-frequency surface water map composites from daily MODIS images","interactions":[],"lastModifiedDate":"2022-04-12T13:36:29.136585","indexId":"70229156","displayToPublicDate":"2022-02-21T06:51:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"DSWEmod - The production of high-frequency surface water map composites from daily MODIS images","docAbstract":"Optical satellite imagery is commonly used for monitoring surface water dynamics, but clouds and cloud shadows present challenges in assembling complete water time series. To test whether the daily revisit rate of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery can reduce cloud obstruction and improve high-frequency surface water mapping, we compared map results derived from Landsat (30-m) and MODIS (250-m) data across the state of California for 2003–2019. We adapted the Dynamic Surface Water Extent (DSWE) model in Google Earth Engine to generate surface water map composites from MODIS imagery every 5, 10, 15, and 30 days, and compared products to monthly Landsat-based DSWE maps. Results for DSWEmod (DSWE MODIS) in California suggest that more than 5% data loss (cloud obstruction, etc.) was present in only 2% of the 15-day time series, as compared to 32% of the monthly Landsat DSWE time series. The five-day DSWEmod composites averaged 8.4% obscuration in the winter months. Area estimates derived from cloud-filtered MODIS and Landsat monthly products have the highest linear correlations compared to streamgage discharge records, suggesting that monthly scale analyses best explain the relationship between surface water area and general streamflow dynamics. Shorter-interval DSWEmod products have lower correlations but utility for understanding the timing of surface water peaks and past flood events.
Spring floods trigger spawning in many native fishes of the desert Southwest (USA), but less is known about fish community response when native fishes are rare. Here, we document change to native and nonnative fish captures and instream habitat features following a decade-high flooding event (2019) in the Verde River (AZ) where native fish captures were rare in the years pre-flood. Using prepositioned areal electrofishing devices (PAEDs), we sampled the fish community at 90 sampling units pre-flood (2017) and resampled those same units post-flood (2019) to compare and identify changes to catch and habitat features. Relative abundance of native fishes increased from 0.6% pre-flood (0.01 fish/PAED) to 53.0% post-flood (1.66 fish/PAED) and was largely attributable to the presence of juvenile Roundtail Chub Gila robusta (≤ 70 mm total length (TL)) and juvenile Sonora Sucker Catostomus insignis (≤ 100 mm TL). Juvenile Desert Sucker Catostomus clarkii experienced a lesser increase. One adult native fish was captured in 2017 and adult native fishes were absent from 2019 sampling. The catch of adult/subadult Common Carp Cyprinus carpio (> 100 mm TL) declined; however, this could be related to reservoir management and not the flood. The abundance of all size-classes of Black Bass Micropterus spp., Red Shiner Cyprinella lutrensis and other nonnative fishes did not change. The majority (97%) of juvenile native fishes were captured at the uppermost sampling reach. A 54% reduction to canopy cover across all sampling reaches and an increase of fine sediments at the most downstream reach demonstrates how floods can restructure the river environment. This case-study adds evidence that protection of spring floods is vital to the persistence and recolonization of fishes native to the desert Southwest, especially where they are rare. The continued presence of nonnative species may preclude juvenile native fishes from recruiting to adults.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02705060.2021.2002734","usgsCitation":"Jenney, C.J., Nemec, Z.C., Lee, L.N., and Bonar, S.A., 2022, Increased juvenile native fish abundance following a major flood in an Arizona river: Journal of Freshwater Ecology, v. 37, no. 1, p. 1-14, https://doi.org/10.1080/02705060.2021.2002734.","productDescription":"14 p.","startPage":"1","endPage":"14","ipdsId":"IP-135120","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":448726,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2021.2002734","text":"Publisher Index Page"},{"id":429646,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.47741088388918,\n 33.945270025606774\n ],\n [\n -111.47741088388918,\n 34.92271952728409\n ],\n [\n -112.26906155680956,\n 34.92271952728409\n ],\n [\n -112.26906155680956,\n 33.945270025606774\n ],\n [\n -111.47741088388918,\n 33.945270025606774\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"37","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Jenney, Christopher J.","contributorId":288206,"corporation":false,"usgs":false,"family":"Jenney","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":902326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nemec, Zach C.","contributorId":288222,"corporation":false,"usgs":false,"family":"Nemec","given":"Zach","email":"","middleInitial":"C.","affiliations":[{"id":56363,"text":"uaz","active":true,"usgs":false}],"preferred":false,"id":902327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Larissa N.","contributorId":288223,"corporation":false,"usgs":false,"family":"Lee","given":"Larissa","email":"","middleInitial":"N.","affiliations":[{"id":56363,"text":"uaz","active":true,"usgs":false}],"preferred":false,"id":902328,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902325,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240968,"text":"70240968 - 2022 - Occurrence and sources of lead in private wells, Sturbridge, Massachusetts","interactions":[],"lastModifiedDate":"2023-03-03T12:39:51.735588","indexId":"70240968","displayToPublicDate":"2022-02-20T06:36:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence and sources of lead in private wells, Sturbridge, Massachusetts","docAbstract":"Lead (Pb) occurrence and sources and aqueous geochemistry were assessed in private wellhead and tap water at a targeted area of concern for possible exceedances and at a control area in the same geologic formation, and in wells at a nearby landfill in south-central Massachusetts (MA). Total Pb concentrations were below the U.S. Environmental Protection Agency (USEPA) Action Level of 15 μg/L in all samples, and about 6% of unfiltered samples contained Pb concentrations that exceeded 1.0 μg/L. Pb concentrations were higher under conditions that are acidic and oxic (pH ≤ 6.5 and dissolved oxygen [DO] ≥ 2 mg/L), in which minerals that could sequester lead or manganese typically are undersaturated, and adsorption by hydrous ferric oxide is limited. Under more neutral to alkaline conditions, the precipitation of Pb in solid solution series minerals such as (Ca,Pb)CO3 and (Ba,Pb)SO4−2, and adsorption by amorphous ferric hydroxides, could limit Pb solubility in the bedrock aquifer or in the plumbing. The low Pb concentrations and the absence of distinctive Pb and strontium (Sr) isotope ratio patterns in samples indicate that a nearby landfill is not likely a significant Pb source. Dissolved concentrations of Pb, copper (Cu), and zinc (Zn) in tap samples were significantly greater than those in wellhead samples, indicating that some Pb is derived from plumbing. Wellhead or tap samples with the highest Pb concentrations also had the greatest corrosivity potential based on the calcite saturation index and the PPGC (Potential to Promote Galvanic Corrosion) and supports the premise that Pb concentrations in tap samples were derived partly from corrosion of plumbing. Concentrations of other constituents, including arsenic (As), uranium (U), Sr, boron (B), and lithium (Li) were not statistically different between the tap and wellhead samples but, apart from Sr, all were statistically higher in the control area than in the target area. This variation in constituent concentrations suggests geochemical variation within the host Paxton Formation, possibly related to faulting and contact with the Ayer granite east of the control area.
Behavioral interactions between conspecific animals can be influenced by relatedness and familiarity. Compared to other vertebrate taxa, considering such aspects of social behavior when housing captive reptiles has received less attention, despite the implications this could have for informing husbandry practices, enhancing welfare, and influencing outcomes of conservation translocations. In this study, to test how kinship and familiarity influenced social behavior in a reptile, we reared 16 captive-born Eastern Box Turtles (Terrapene carolina) under semi-natural conditions in four equally sized groups, where each group comprised pairs of siblings and non-siblings. Using separation distance between pairs of turtles in rearing enclosures as a measure of gregariousness, we found no evidence suggesting siblings more frequently interacted with one another compared to non-relatives over the first five months of life (β = -0.016, 95% CI: -0.117 to 0.084). Average pair separation distance decreased during this time (β = -0.146, 95% CI: -0.228 to -0.063) but may have been due to turtles aggregating around concentrated resources like heat and moist retreat areas as cold winter temperatures approached. When subject were eight months old, we measured repeated separation distances between unique pair combinations in an experimental environment and similarly found no support for gregariousness (associations) being influenced by kinship or familiarity (β = -1.554, 95% CI: -9.956 to 6.848). Additionally, differences in body size between pairs of turtles (β = -22.289, 95% CI: -68.448 to 23.870) nor the five-minute time interval during the 90-minute trial (P ≥ 0.18) had any apparent effect on associations. Agonistic interactions between individuals were never observed. Encouragingly, based on our results, group housing and rearing of juvenile box turtles did not appear to negatively impact their behavioral and physiological well-being. Unlike findings for other taxa, including some reptiles, our results suggest strategically housing groups of juvenile T. carolina to maintain social stability may not be an important husbandry consideration, or even a requirement, when planning releases of captive-reared individuals for conservation purposes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.applanim.2022.105586","usgsCitation":"Tetzlaff, S.J., Sperry, J.H., and DeGregorio, B.A., 2022, You can go your own way: No evidence for social behavior based on kinship or familiarity in captive juvenile box turtles: Applied Animal Behaviour Science, v. 248, 105586, 5 p., https://doi.org/10.1016/j.applanim.2022.105586.","productDescription":"105586, 5 p.","ipdsId":"IP-136145","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":448731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.applanim.2022.105586","text":"Publisher Index Page"},{"id":432047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"248","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tetzlaff, Sasha J.","contributorId":341593,"corporation":false,"usgs":false,"family":"Tetzlaff","given":"Sasha","email":"","middleInitial":"J.","affiliations":[{"id":81758,"text":"US Army ERDC-CERL","active":true,"usgs":false}],"preferred":false,"id":908665,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sperry, Jinelle H.","contributorId":341594,"corporation":false,"usgs":false,"family":"Sperry","given":"Jinelle","email":"","middleInitial":"H.","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":908666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908667,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70209990,"text":"70209990 - 2022 - Climate change and fishes in estuaries","interactions":[],"lastModifiedDate":"2022-10-05T16:09:41.785456","indexId":"70209990","displayToPublicDate":"2022-02-18T10:50:55","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","title":"Climate change and fishes in estuaries","docAbstract":"This chapter provides an overview of the main drivers of change in estuarine systems, their expected causes and impacts on estuarine fish and fisheries. An analysis of global, regional and local patterns of estuarine fish and how climate-induced change may impact estuarine systems and their fish communities is provided. We also examine the main environmental, climatic and biological stressors likely to impact estuarine fish and associated fisheries. A set of case studies is used to illustrate the differences in potential impacts associated with various global regions and types of estuaries. An understanding of climate change in estuaries will support estuarine ecosystem resilience, inform management and facilitate adaptation.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Fish and fisheries in estuaries: A global perspective","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Wiley","doi":"10.1002/9781119705345.ch7","usgsCitation":"Gillanders, B.M., McMillan, M.N., Reis-Santos, P., Baumgartner, L.J., Brown, L.R., Conallin, J., Feyrer, F.V., Henriques, S., James, N.C., Jaureguizar, A.J., Pessanha, A.L., Vasconcelos, R.P., Vu, A., Walther, B., and Wibowo, A., 2022, Climate change and fishes in estuaries, chap. 7 of Fish and fisheries in estuaries: A global perspective, p. 380-457, https://doi.org/10.1002/9781119705345.ch7.","productDescription":"78 p.","startPage":"380","endPage":"457","ipdsId":"IP-116180","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":407966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-02-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Gillanders, Bronwyn M","contributorId":291280,"corporation":false,"usgs":false,"family":"Gillanders","given":"Bronwyn","email":"","middleInitial":"M","affiliations":[{"id":62654,"text":"School of Biological Sciences, and Environment Institute, University of Adelaide","active":true,"usgs":false}],"preferred":false,"id":853893,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMillan, Matthew N.","contributorId":297357,"corporation":false,"usgs":false,"family":"McMillan","given":"Matthew","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":853894,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reis-Santos, P.","contributorId":93283,"corporation":false,"usgs":true,"family":"Reis-Santos","given":"P.","email":"","affiliations":[],"preferred":false,"id":853895,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baumgartner, Lee J.","contributorId":203990,"corporation":false,"usgs":false,"family":"Baumgartner","given":"Lee","email":"","middleInitial":"J.","affiliations":[{"id":36787,"text":"Charles Sturt University, Institute for Land, Water, and Society","active":true,"usgs":false}],"preferred":false,"id":853896,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788727,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Conallin, John","contributorId":220478,"corporation":false,"usgs":false,"family":"Conallin","given":"John","email":"","affiliations":[{"id":40173,"text":"Charles Sturt University","active":true,"usgs":false}],"preferred":false,"id":853897,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Feyrer, Frederick V. 0000-0003-1253-2349 ffeyrer@usgs.gov","orcid":"https://orcid.org/0000-0003-1253-2349","contributorId":178379,"corporation":false,"usgs":true,"family":"Feyrer","given":"Frederick","email":"ffeyrer@usgs.gov","middleInitial":"V.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":788726,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Henriques, Sofia","contributorId":297358,"corporation":false,"usgs":false,"family":"Henriques","given":"Sofia","email":"","affiliations":[],"preferred":false,"id":853898,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"James, Nicola C.","contributorId":297359,"corporation":false,"usgs":false,"family":"James","given":"Nicola","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":853899,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jaureguizar, Andres J","contributorId":297360,"corporation":false,"usgs":false,"family":"Jaureguizar","given":"Andres","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":853900,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pessanha, Andre L. M.","contributorId":297361,"corporation":false,"usgs":false,"family":"Pessanha","given":"Andre","email":"","middleInitial":"L. M.","affiliations":[],"preferred":false,"id":853901,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Vasconcelos, Rita P.","contributorId":297362,"corporation":false,"usgs":false,"family":"Vasconcelos","given":"Rita","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":853902,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Vu, An V.","contributorId":297363,"corporation":false,"usgs":false,"family":"Vu","given":"An V.","affiliations":[],"preferred":false,"id":853903,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Walther, Benjamin","contributorId":297364,"corporation":false,"usgs":false,"family":"Walther","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":853904,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wibowo, Arif","contributorId":220488,"corporation":false,"usgs":false,"family":"Wibowo","given":"Arif","email":"","affiliations":[{"id":40178,"text":"Ministry of Marine Affairs and Fisheries, Indonesia","active":true,"usgs":false}],"preferred":false,"id":853905,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70228753,"text":"fs20223005 - 2022 - South Carolina and Landsat","interactions":[],"lastModifiedDate":"2023-01-24T11:49:10.467656","indexId":"fs20223005","displayToPublicDate":"2022-02-18T09:50:49","publicationYear":"2022","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":"2022-3005","displayTitle":"South Carolina and Landsat","title":"South Carolina and Landsat","docAbstract":"South Carolina, the eighth State admitted to the union, transcends its size with its deep, rich history; striking beauty; vast natural resources; and extensive cultural diversity. Home to part of the Blue Ridge Mountains of the Central Appalachians, the Upstate is graced with more than 100 waterfalls, while the Lowcountry borders the Atlantic Ocean with 187 miles of coastline and 35 barrier islands. Forests cover two-thirds of the State, and forestry and agriculture together, as agribusiness, make up South Carolina’s leading industry. Two historic crops—cotton and tobacco—still rank in the top 10 commodities, though corn and soybeans now rank higher. Poultry, cattle, peanuts, and flowers also make the list.
South Carolina’s population totals more than five million. Other residents include a variety of wildlife, bird, reptile, and fish species, including Ursus americanus (black bears), Alligator mississippiensis (American alligators), and Tursiops truncatus (bottlenose dolphins). More than 100 tree species also reside in South Carolina, which pays homage to one with its “The Palmetto State” nickname.
South Carolina’s subtropical climate, long coastline, and lower elevations make it highly susceptible to tornado and hurricane activity and coastal flooding. Projected sea-level rise is a growing concern. A view from space can help monitor and manage natural resources on the land and in rivers, marshes, and the coast. Landsat reveals not just what an area looks like now, but also insights from decades ago.
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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Reliable estimates of the magnitude of peak flows in streams are required for the economical and safe design of transportation and water conveyance structures. In addition, reliable estimates of the magnitude of low flows at defined frequencies and durations are needed for meeting regulatory requirements, quantifying base flows in streams and rivers, and evaluating time of travel and dilution of toxic spills. This report, in cooperation with the Delaware Department of Transportation and the Delaware Geological Survey, presents methods for estimating the magnitude of peak flows and low flows at defined frequencies and durations on nontidal streams in Delaware, at locations both monitored by streamflow-gage sites and ungaged. Methods are presented for estimating (1) the magnitude of peak flows for return periods ranging from 2 to 500 years (50-percent to 0.2-percent annual-exceedance probability), and (2) the magnitude of low flows as applied to 7-, 14-, and 30-consecutive day low-flow periods with recurrence intervals of 2, 10, and 20 years (50-, 10-, and 5-percent annual non-exceedance probabilities). These methods are applicable to watersheds that exhibit a full range of development conditions in Delaware. The report also describes StreamStats, a web application that allows users to easily obtain peak-flow and low-flow magnitude estimates for user-selected locations in Delaware.
Peak-flow and low-flow magnitude estimates for ungaged sites are obtained using statistical regression analysis through a process known as regionalization, where information from a group of streamflow-gage sites within a region forms the basis for estimates for ungaged sites within the same region. Ninety-four streamflow-gage sites in and near Delaware with at least 10 years of nonregulated annual peak-flow data were used for the peak-flow regression analysis, a subset of the 121 sites for which peak-flow estimates were computed. These sites included both continuous-record streamflow-gage sites as well as partial record sites. Forty-five streamflow-gage sites with at least 10 years of nonregulated low-flow data available were used for the low-flow regression analyses, a subset of the 68 sites for which low-flow estimates were computed. Estimates for gaged sites are obtained by combining (1) the station peak-flow statistics (mean, standard deviation, and skew) and peak-flow estimates using the recent Bulletin 17C guidelines that incorporate the Expected Moments Algorithm with (2) regional estimates of peak-flow magnitude derived from regional regression equations and regional skew derived from sites with records greater than or equal to 35 years. Example peak-flow estimate calculations using the methods presented in the report are given for (1) ungaged sites, (2) gaged sites, (3) sites upstream or downstream from a gaged location, and (4) sites between gaged locations. Estimates for low-flow gaged sites are obtained by combining (1) the station low-flow statistics (mean, standard deviation, and skew) and low-flow estimates with (2) regional estimates of low-flow magnitude derived from regional regression equations. Example low-flow estimate calculations using the methods presented in the report are given for (1) ungaged sites, (2) gaged sites, (3) sites upstream or downstream from a gaged location, and (4) sites between gaged locations. A total of 54 sites in the Coastal Plain region were used to develop peak-flow regressions for the region and 40 sites were used for the Piedmont region. Similarly, 24 sites were used for low-flow regression equation development in the Coastal Plain, with 21 in the Piedmont. Peak and low-flow site inclusion in the Coastal Plain tended to be more restricted with tidal influence and ranges of basin characteristics, including drainage area, limiting regression equation development and application.
Regional regression equations for peak flows and low flows, as applicable to ungaged sites in the Piedmont and Coastal Plain Physiographic Provinces in Delaware, are presented. Peak-flow regression equations used variables that quantified drainage area, basin slope, percent area with well-drained soils, percent area with poorly drained soils, impervious area, and percent area of surface water storage in estimating peak-flow estimates, whereas low-flow regression equations used only drainage area and percent poorly drained soils in the estimation of low flows. Average standard errors for peak-flow regressions tended to be lower than those for low- flow regressions, with lower errors in the Piedmont region for both peak- and low-flow regressions. For peak-flow estimates, a sensitivity analysis of Piedmont regression equation estimates to changes in impervious area is also presented.
Additional topics associated with the analyses performed during the study are discussed, including (1) the availability and description of 32 basin and climatic characteristics considered during the development of the regional regression equations; (2) the treatment of increasing trends in the annual peak-flow series identified at 18 gaged sites and inclusion in or exclusion from the regional analysis; (3) regional skew analysis and determination of regression regions; (4) sample adjustments and removal of sites owing to regulation and redundancy; and (5) a brief comparison of peak- and low-flow estimates at gages used in previous studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225005","collaboration":"Prepared in cooperation with the Delaware Department of Transportation and the Delaware Geological Survey","usgsCitation":"Hammond, J.C., Doheny, E.J., Dillow, J.J.A., Nardi, M.R., Steeves, P.A., and Warner, D.L., 2022, Peak-flow and low-flow magnitude estimates at defined frequencies and durations for nontidal streams in Delaware: U.S. Geological Survey Scientific Investigations Report 2022–5005, 46 p., https://doi.org/10.3133/sir20225005.","productDescription":"Report: vi, 46 p.; 4 Data Releases","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127314","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":396171,"rank":9,"type":{"id":39,"text":"HTML 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Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Catonsville, MD 21228