Process-based modelling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. In this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s43017-023-00450-9","usgsCitation":"Shen, C., Appling, A.P., Gentine, P., Bandai, T., Gupta, H., Tartakovsky, A., Baity-Jesi, M., Fenicia, F., Kifer, D., Li, L., Liu, X., Ren, W., Zheng, Y., Harman, C., Clark, M., Farthing, M., Feng, D., Kumar, P., Aboelyazeed, D., Rahmani, F., Song, Y., Beck, H.E., Bindas, T., Dwivedi, D., Fang, K., Hoge, M., Rackauckas, C., Mohanty, B., , R., Xu, C., and Lawson, K., 2023, Differentiable modelling to unify machine learning and physical models for geosciences: Nature Reviews Earth & Environment, v. 4, p. 552-567, https://doi.org/10.1038/s43017-023-00450-9.","productDescription":"16 p.","startPage":"552","endPage":"567","ipdsId":"IP-147269","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":467103,"rank":2,"type":{"id":41,"text":"Open Access External Repository 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In particular, it is a key determinant of whether a wetland will provide suitable breeding habitat for amphibians and other taxa that often have specific hydrologic requirements. Yet, scientists and land managers often are challenged by a lack of sufficient monitoring data to enable the understanding of the wetting and drying dynamics of small depressional wetlands. In this study, we present and evaluate an approach to predict daily inundation dynamics using a large wetland water-level dataset and a random forest algorithm. We relied on predictor variables that described characteristics of basin morphology of each wetland and atmospheric water budget estimates over various antecedent periods. These predictor variables were derived from datasets available over the conterminous United States making this approach potentially extendable to other locations. Model performance was evaluated using two metrics, median hydroperiod and the proportion of correctly classified days. We found that models performed well overall with a median balanced accuracy of 83% on validation data. Median hydroperiod was predicted most accurately for wetlands that were infrequently inundated and least accurate for permanent wetlands. The proportion of inundated days was predicted most accurately in permanent wetlands (99%) followed by frequently inundated wetlands (98%) and infrequently inundated wetlands (93%). This modeling approach provided accurate estimates of inundation and could be useful in other depressional wetlands where the primary water flux occurs with the atmosphere and basin morphology is a critical control on wetland inundation and hydroperiods.
The steep, tectonically active terrain along the Central California (USA) coast is well known to produce deadly and destructive debris flows. However, the extent to which fire affects debris-flow susceptibility in this region is an open question. We documented the occurrence of postfire debris floods and flows following the landfall of a storm that delivered intense rainfall across multiple burn areas. We used this inventory to evaluate the predictive performance of the US Geological Survey M1 likelihood model, a tool that presently underlies the emergency assessment of postfire debris-flow hazards in the western USA. To test model performance, we used the threat score skill statistic and found that the rainfall thresholds estimated by the M1 model for the Central California coast performed similarly to training (Southern California) and testing (Intermountain West) data associated with the original model calibration. Model performance decreased when differentiating between “minor” and “major” postfire hydrologic response types, which weigh effects on human life and infrastructure. Our results underscore that the problem of false positives is a major challenge for developing accurate rainfall thresholds for the occurrence of postfire debris flows. As wildfire activity increases throughout the western USA, so too will the demand for the assessment of postfire debris-flow hazards. We conclude that additional collection of field-verified inventories of postfire hydrologic response will be critical to prioritize which model variables may be suitable candidates for regional calibration or replacement.
","language":"English","publisher":"Springer","doi":"10.1007/s10346-023-02106-7","usgsCitation":"Thomas, M.A., Kean, J.W., McCoy, S., Lindsay, D.N., Kostelnik, J., Cavagnaro, D.B., Rengers, F.K., East, A.E., Schwartz, J., Smith, D.P., and Collins, B.D., 2023, Postfire hydrologic response along the central California (USA) coast: Insights for the emergency assessment of postfire debris-flow hazards: Landslides, v. 20, p. 2421-2436, https://doi.org/10.1007/s10346-023-02106-7.","productDescription":"16 p.","startPage":"2421","endPage":"2436","ipdsId":"IP-139528","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442830,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index 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Arizona","interactions":[],"lastModifiedDate":"2026-03-09T16:17:21.530849","indexId":"sir20235052","displayToPublicDate":"2023-06-30T15:05:59","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5052","displayTitle":"Hydrologic Framework and Characterization of the Little Colorado River Alluvial Aquifer near Leupp, Arizona","title":"Hydrologic framework and characterization of the Little Colorado River alluvial aquifer near Leupp, Arizona","docAbstract":"The Little Colorado River alluvial aquifer near Leupp, Arizona, was investigated as a possible source of irrigation water for the Leupp and Birdsprings Chapters of the Navajo Nation. The physical, chemical, and hydraulic characteristics of the alluvial aquifer were studied using geophysical surveys, installation of observation wells, water-level measurements, chemical analyses, groundwater pumping simulations, and review of previous investigations. Geophysical surveys and well borings revealed that the aquifer ranges in thickness from near 0 feet around its periphery to about 100 feet in its thickest parts. Water levels were monitored in nine alluvial wells within the study area and compared with earlier measurements collected in 1998 and 1999. Comparison of those earlier water levels with water levels collected as part of this study showed a decline of between about 5 and 12 feet has occurred in the last 23 years. The water chemistry of the aquifer was analyzed for salinity hazard, sodium-adsorption hazard, and specific-ion toxicity. The sodium-adsorption hazard and specific-ion toxicity of alluvial aquifer water were found to be low. However, the salinity hazard was high enough in most areas that it could negatively affect salt-sensitive crops. Well-field pumping scenarios conducted for this study demonstrated that using groundwater from the alluvial aquifer for irrigated agriculture is theoretically possible but may be economically challenging owing to the hydraulic properties of the aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235052","collaboration":"Prepared in cooperation with the Navajo Nation","usgsCitation":"Mason, J.P., Kennedy, J.R., Macy, J.P., and Gungle, B., 2023, Hydrologic framework and characterization of the Little Colorado River alluvial aquifer near Leupp, Arizona: U.S. Geological Survey Scientific Investigations Report 2023–5052, 40 p., https://doi.org/10.3133/sir20235052.","productDescription":"Report: ix, 40 p.; 2 Data Releases; 2 Appendix","ipdsId":"IP-134871","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":418694,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5052/sir20235052.xml"},{"id":418669,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5052/sir20235052_appendix2.xlsx","text":"Appendix 2","size":"30 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Major ion chemistry results of water samples collected from springs and wells in the Moenkopi Formation in Arizona"},{"id":418668,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5052/sir20235052_appendix1.xlsx","text":"Appendix 1","size":"30 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Water-chemistry sample results from monitoring wells, Little Colorado River alluvial aquifer, northeastern Arizona"},{"id":418666,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5052/images"},{"id":418664,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E6AXVJ","text":"Gravity data along the Little Colorado River near Leupp, Arizona","description":"Kennedy, J.R., 2023, Gravity data along the Little Colorado River near Leupp, Arizona: U.S. Geological Survey data release, https://doi.org/10.5066/P9E6AXVJ."},{"id":418663,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TNW6SD","text":"Electrical resistivity tomography data along the Little Colorado River near Leupp, AZ 2019","description":"Macy, J.P., and Mason, J.P., 2023, Electrical resistivity tomography data along the Little Colorado River near Leupp, AZ 2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9TNW6SD."},{"id":418662,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5052/sir20235052.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":418661,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5052/covrthb.jpg"},{"id":500930,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114939.htm","linkFileType":{"id":5,"text":"html"}},{"id":418695,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235052/full"}],"country":"United States","state":"Arizona","otherGeospatial":"Little Colorado River Alluvial Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.11708395076475,\n 33.74094372436525\n ],\n [\n -109.23990044564536,\n 33.74094372436525\n ],\n [\n -109.23990044564536,\n 35.90430760207377\n ],\n [\n -112.11708395076475,\n 35.90430760207377\n ],\n [\n -112.11708395076475,\n 33.74094372436525\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
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520 N. Park Avenue
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Study region: This study focuses on the Colorado River watershed in the area along the South Rim of the Grand Canyon. Study focus: This study utilizes anthropogenic chemical tracers to investigate the fate of treated wastewater effluent discharged within Grand Canyon National Park. Anthropogenic chemical tracers were used to discern preferential structurally controlled pathways in a complex regional network of faults and fractures in which some are conduits and others barriers to flow. New hydrological insights for the region: Previous investigations on water resources of Grand Canyon have suggested two different discharge locations (Garden Springs versus Monument Spring) for the treated wastewater discharged on the South Rim of Grand Canyon yet the presence of wastewater at the springs remained unstudied for decades. The treated wastewater from Grand Canyon Village is released into Bright Angel Wash that flows along the surface expression of the Bright Angel Fault and past the inferred intersection with the perpendicular Monument Fault. Multiple anthropogenic compounds (pharmaceuticals, per- and polyfluoroalkyl substances (PFAS), and elevated nitrate) were found in Bright Angel Wash and Monument Spring. Stable isotopic measurements at Monument Spring show depletion over time also suggesting contribution from a depleted stable isotopic source found in the treated wastewater. The anthropogenic tracers utilized in this study provide good insight to which geologic structures are conduits versus barriers to flow and can be useful in other fracture flow and karst settings.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ejrh.2023.101461","usgsCitation":"Beisner, K.R., Paretti, N.V., Jasmann, J., and Barber, L., 2023, Utilizing anthropogenic compounds and geochemical tracers to identify preferential structurally controlled groundwater pathways influencing springs in Grand Canyon National Park, Arizona, USA: Journal of Hydrology: Regional Studies, v. 48, 101461, 15 p., https://doi.org/10.1016/j.ejrh.2023.101461.","productDescription":"101461, 15 p.","ipdsId":"IP-141572","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":442898,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ejrh.2023.101461","text":"Publisher Index Page"},{"id":418677,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.14926803785156,\n 36.52936308034002\n ],\n [\n -113.14926803785156,\n 35.57058860267266\n ],\n [\n -111.89749432574378,\n 35.57058860267266\n ],\n [\n -111.89749432574378,\n 36.52936308034002\n ],\n [\n -113.14926803785156,\n 36.52936308034002\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Beisner, Kimberly R. 0000-0002-2077-6899 kbeisner@usgs.gov","orcid":"https://orcid.org/0000-0002-2077-6899","contributorId":2733,"corporation":false,"usgs":true,"family":"Beisner","given":"Kimberly","email":"kbeisner@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paretti, Nicholas V. 0000-0003-2178-4820 nparetti@usgs.gov","orcid":"https://orcid.org/0000-0003-2178-4820","contributorId":173412,"corporation":false,"usgs":true,"family":"Paretti","given":"Nicholas","email":"nparetti@usgs.gov","middleInitial":"V.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":876795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jasmann, Jeramy Roland 0000-0002-5251-6987","orcid":"https://orcid.org/0000-0002-5251-6987","contributorId":220849,"corporation":false,"usgs":true,"family":"Jasmann","given":"Jeramy Roland","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":876796,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barber, Larry B. 0000-0002-0561-0831","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":218953,"corporation":false,"usgs":true,"family":"Barber","given":"Larry B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":876797,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70246343,"text":"70246343 - 2023 - Importance of subsurface water for hydrological response during storms in a post-wildfire bedrock landscape","interactions":[],"lastModifiedDate":"2023-07-06T11:50:21.390858","indexId":"70246343","displayToPublicDate":"2023-06-29T06:42:55","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16146,"text":"Nature Geoscience Communications","active":true,"publicationSubtype":{"id":10}},"title":"Importance of subsurface water for hydrological response during storms in a post-wildfire bedrock landscape","docAbstract":"Wildfire alters the hydrologic cycle, with important implications for water supply and hazards including flooding and debris flows. In this study we use a combination of electrical resistivity and stable water isotope analyses to investigate the hydrologic response during storms in three catchments: one unburned and two burned during the 2020 Bobcat Fire in the San Gabriel Mountains, California, USA. Electrical resistivity imaging shows that in the burned catchments, rainfall infiltrated into the weathered bedrock and persisted. Stormflow isotope data indicate that the amount of mixing of surface and subsurface water during storms was similar in all catchments, despite higher streamflow post-fire. Therefore, both surface runoff and infiltration likely increased in tandem. These results suggest that the hydrologic response to storms in post-fire environments is dynamic and involves more surface-subsurface exchange than previously conceptualized, which has important implications for vegetation regrowth and post-fire landslide hazards for years following wildfire.
The Rocky Mountains and the Colorado River Basin in the Western United States represent complex, interconnected systems that sustain a number of species, including tens of millions of humans. These systems face several challenges, including worsening drought, altered wildfire regimes, climate change, and the spread of invasive species. These factors can exacerbate one another, further contributing to habitat loss and affecting species of conservation concern. Characterizing and managing these challenges require interdisciplinary communities of scientists to develop information and decision-support tools that can inform holistic land and water management solutions. The U.S. Geological Survey (USGS) Rocky Mountain Region 2022 Science Exchange focused on the use of interdisciplinary and state-of-the-art science being conducted by USGS scientists in the region to address these complex problems.
The USGS Rocky Mountain Regional Office organized its first Science Exchange in 2017 to share scientific information between leaders and early career scientists throughout the region. Science Exchanges held in 2018 and 2020 focused on drought science relevant to the region and the Earth Monitoring, Analyses, and Prediction (EarthMAP) concept, which is designed to facilitate interdisciplinary, timely, and actionable science related to drought in the Colorado River Basin and other areas. Based on the emerging need for more holistic approaches to address increasingly complex natural resource issues that affect society, the Region hosted a virtual fourth Science Exchange for three days in April 2022. This event focused on barriers and bridges to interdisciplinary science and highlighted studies from the Region to inspire collaboration across disciplines. Presentations described recent and ongoing research that applied collaborative and state-of-the-art methods to address problems in the fields of geology, hydrology, ecology, and natural hazards. Science collaboration and outreach to all levels of stakeholders are vital elements needed for providing timely and actionable data, interpretations, analytical tools, and products. These presentations led to active online chats and panel discussions and showcased interdisciplinary science and advanced methods that may inform and lead to more effective, holistic management decisions as the Western United States adapts to ongoing and future changes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233017","usgsCitation":"Peterson, D.E., French, K.L., Oden, J.H., Anderson, P.J., Titus, T.N., Dahm, K.G., Driscoll, J., Andrews, W.J., 2022, U.S. Geological Survey Rocky Mountain Region 2022 Science Exchange, Showcasing Interdisciplinary and State-of-the-Art USGS Science, U.S. Geological Survey Fact Sheet 2023-3017, 6 p., https://doi.org/10.3133/fs20233017.","productDescription":"6 p.","onlineOnly":"Y","ipdsId":"IP-144708","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":418590,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3017/images"},{"id":418591,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3017/fs20233017.xml"},{"id":418596,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233017/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3017"},{"id":418480,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3017/coverthb.jpg"},{"id":418481,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3017/fs20233017.pdf","text":"Report","size":"4.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3017"}],"contact":"Director, Region 7 - Upper Colorado Basin
U.S. Geological Survey
Box 25046, MS-911
Denver, CO 80225-0046
Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall-to-wall explanatory variable maps to generate CONUS-wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national-scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.
Sea level rise is affecting reaches of coastal rivers by increasing water levels and propagating tides inland. The transition of river systems into tidal estuaries has been neglected in hydrogeomorphic studies. A better understanding of transitioning reaches is critical to understanding ecosystem dynamics, services, and developing predictive capabilities of change as sea levels rise. We hypothesized that river-floodplain morphology changes from fluvial to tidally dominated regimes, changing suspended sediment concentrations (SSC), sediment deposition, vegetation, and landforms. We tested this using lidar, satellite imagery, and SSC and conductivity measurements along two Coastal Plain rivers of Virginia, USA. Geomorphic channel and floodplain parameters indicated breakpoints into three regimes: fluvial, mixed, and tidal. Maximum channel width occurred with minimum floodplain widths in the mixed regime. Tidal freshwater forests had considerable elevational overlap with marshes but typically were 9.5 cm higher. SSC increased with shoal width through the mixed reaches, with maxima in the tidal reaches where estuarine influences increased. Channel erosion rates indicated that modern sediment loads and hydrology produce slow changes to channel planform and geomorphology that may not be apparent from visual comparisons. Our findings indicated that tidal floodplain forests and marshes in the mixed and tidal reaches are expected to convert to marshes or open water as sea levels rise as limited gradual sloping area exists between the active floodplain and terraces. Tidal floodplain surfaces along mixed hydrology reaches, inland of the estuarine turbidity maximum may be expected to convert to open water while inland sloping floodplains could support tidal wetland migration.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-023-01226-6","usgsCitation":"Kroes, D., Noe, G.E., Hupp, C.R., Doody, T.R., and Bukaveckas, P., 2023, Hydrogeomorphic changes along mid-Atlantic coastal plain rivers transitioning from non-tidal to tidal: Implications for a rising sea level: Estuaries and Coasts, v. 46, p. 1438-1458, https://doi.org/10.1007/s12237-023-01226-6.","productDescription":"21 p.","startPage":"1438","endPage":"1458","ipdsId":"IP-135089","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":435281,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B1UCFT","text":"USGS data release","linkHelpText":"Hydrogeomorphic data along transitioning Coastal Plain rivers (Mattaponi and Pamunkey Rivers): implications for a rising sea level"},{"id":418223,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Chesapeake Bay Watershed, Mattaponi River, Pamunkey River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.65344171287853,\n 37.86125997466432\n ],\n [\n -77.48781222047384,\n 37.86125997466432\n ],\n [\n -77.48781222047384,\n 37.46887702495529\n ],\n [\n -76.65344171287853,\n 37.46887702495529\n ],\n [\n -76.65344171287853,\n 37.86125997466432\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"46","noUsgsAuthors":false,"publicationDate":"2023-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":37277,"text":"WMA - 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2023 - Identifying hydrologic signatures associated with streamflow depletion caused by groundwater pumping","interactions":[],"lastModifiedDate":"2023-06-19T15:55:44.490498","indexId":"70245143","displayToPublicDate":"2023-06-19T10:45:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Identifying hydrologic signatures associated with streamflow depletion caused by groundwater pumping","docAbstract":"Groundwater pumping can reduce streamflow in nearby waterways (‘streamflow depletion’), a process which must be accounted for in integrated management of surface and groundwater resources. However, causal identification of streamflow depletion from hydrographs alone is challenging because pumping impacts are masked by other drivers of hydrologic variability. To identify potential indicators of streamflow depletion, we used synthetic hydrographs and an analytical streamflow depletion model to assess potential pumping impacts on specific hydrograph characteristics (‘hydrologic signatures’) for 215 streamgages spanning the conterminous United States (CONUS). We found that streamflow depletion commonly impacts signatures associated with seasonal and annual low flows and low flow recessions. The largest impacts occurred during dry years, suggesting streamflow depletion may be evident in dry years even where impacts are unmeasurable in wet years. Random forest models indicated that streamflow depletion could significantly impact Annual, Summer, and Fall signatures in most streams. Our finding that multiple hydrologic signatures are consistently responsive to streamflow depletion across CONUS suggests that the underlying hydrological processes linking pumping to streamflow reductions are consistent across diverse settings, information that will aid in identifying indicators of streamflow depletion from streamflow hydrographs.
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Analysis of groundwater-flow directions and hydraulic gradients can provide an understanding of depletion by heavy groundwater pumping and recharge through playa lakes, as well as the relationship between the groundwater levels and underlying geology. The objectives of this study, conducted by the U.S. Geological Survey in cooperation with the U.S. Air Force Civil Engineer Center, are to assist Cannon AFB in understanding and interpreting current and local hydrologic conditions and to evaluate groundwater-level change from 2015 to 2020 using new and historical data. A groundwater potentiometric surface contour map was constructed to better understand the Southern High Plains aquifer around Cannon AFB and to show the altitude of the water-table surface and groundwater-flow patterns. Four hydrographs were created from periodic measurements of groundwater levels in wells on and around Cannon AFB to provide information about historical groundwater-level changes and visualize trends from the water-level records. The long-term trend present in all four hydrographs is a steady decline in groundwater levels, with some areas declining faster than others. The groundwater-level change map presented in this study provides a visual representation of the change in groundwater level from the winter 2015 to winter 2020 measuring events. Results show that among corresponding wells measured in 2015 and 2020, 50.7 percent indicated a decline in water levels, 29.9 percent indicated neutral water levels, and 19.4 percent indicated a rise in water levels. The region to the north of the groundwater trough on Cannon AFB contained most of the groundwater-level rises, whereas the regions located near the trough and just west of Clovis, N. Mex., contained most of the declines. These results suggest that continued monitoring of declining groundwater levels in the area would provide valuable decision-support information for assessing the sustainability of this water resource.
Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
This paper broadens the description of sedimentary organic matter from the conventional use of coal petrography to include palynological and geochemical sedimentary organic matter. Palynological sedimentary organic matter includes all chemically resistant organic microfossils, such as pollen and spores, dinocysts, microforaminifera (chitinoid-like linings of foraminifera), microscopic algae, charcoal, palynodebris, acritarchs, chitinozoans, and scolecodonts. Geochemical sedimentary organic matter includes organic biomarkers, lipids, and photosynthetic pigments. We provide examples of the use of palynological and geochemical analysis of sedimentary organic matter to understand patterns and impacts of changing climate, fire regimes, hydrologic extremes, water quality, and land change on terrestrial and marine systems through geologic time to provide a long-term perspective to evaluate anthropogenic impacts on the Earth as well as to support forensics investigations.
Offutt Air Force Base, south of Omaha, Nebraska, experienced major flooding during the March 2019 flood event because of the proximity of the base to the confluence of the Missouri River and nearby tributaries, which exceeded flood stages. Postflood, standing water remained through much of the year, attracting waterfowl and other birds and posing a major safety risk to aircraft. The U.S. Geological Survey, in cooperation with the U.S. Air Force, began a study in 2020 to describe the hydrologic processes that affect the persistence of standing water on Offutt Air Force Base.
Existing site data, reviewed in concert with groundwater and surface-water elevation data collected for the study, indicate varying hydrologic responses between two areas of concern (AOCs), which can be linked to differences in subsurface geology and changes in flows of the Missouri River. An inundation map indicated that standing water would be present throughout Papillion Creek Ditch in AOC 1 and would extend upstream to AOC 2 during flow events greater than 771 cubic feet per second. A U.S. Army Corps of Engineers Hydrologic Engineering Center-River Analysis System model and a flow-duration analysis were used to infer that many of the surface-water drainage problems experienced in 2019 were the result of backwater conditions caused by higher streamflows in the Missouri River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235053","collaboration":"Prepared in cooperation with the U.S. Air Force, Offutt Air Force Base","usgsCitation":"Hobza, C.M., and Strauch, K.R., 2023, Floodwater drainage assessment of Offutt Air Force Base, Nebraska, 2020–22: U.S. Geological Survey Scientific Investigations Report 2023–5053, 31 p., https://doi.org/10.3133/sir20235053.","productDescription":"Report: vii, 31 p.; Data Release; Dataset","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-138559","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":418093,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235053/full"},{"id":417735,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":417734,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KYD1CX","text":"USGS data release","linkHelpText":"Water-surface and groundwater-level elevations on and near Offutt Air Force Base, Nebraska, summer 2020 and spring 2021"},{"id":417718,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5053/images"},{"id":417717,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5053/sir20235053.XML"},{"id":417707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5053/coverthb1.jpg"},{"id":417713,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5053/sir20235053.pdf","text":"Report","size":"5.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5053"}],"country":"United States","state":"Nebraska","otherGeospatial":"Offutt Air Force Base","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.09742410665552,\n 41.18555144700602\n ],\n [\n -96.09742410665552,\n 41.06019915604605\n ],\n [\n -95.87125037103594,\n 41.06019915604605\n ],\n [\n -95.87125037103594,\n 41.18555144700602\n ],\n [\n -96.09742410665552,\n 41.18555144700602\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
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The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, maintains a statewide group of stations known as the Ambient Water-Quality Monitoring Network, which includes selected streams and springs in Missouri. During water year 2021 (October 1, 2020, through September 30, 2021), the U.S. Geological Survey collected water-quality data at 72 stations: 70 Ambient Water-Quality Monitoring Network stations and 2 U.S. Geological Survey National Water Quality Network stations. Four of the stations have data from additional sampling completed in cooperation with the U.S. Army Corps of Engineers. Water-quality data provided in this report include dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, Escherichia coli bacteria, fecal coliform bacteria, dissolved nitrate plus nitrite as nitrogen, total phosphorus, dissolved and total recoverable lead and zinc, and selected pesticide compounds. Monitoring stations have been classified based on the physiographic province or primary land use in the drainage basin or based on the unique hydrologic characteristics of the waterbodies (springs, large rivers) monitored. A summary of hydrologic conditions, including peak streamflows, monthly mean streamflows, and 7-day low flows, also is provided for representative streamgages in the State.
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We use a combination of proxy records from a high-resolution analysis of sediments from Searsville Lake and adjacent Upper Lake Marsh and historical records to document over one and a half centuries of vegetation and socio-ecological change—relating to logging, agricultural land use change, dam construction, chemical applications, recreation, and other drivers—on the San Francisco Peninsula. A relatively open vegetation with minimal oak (Quercus) and coast redwood (Sequoia sempervirens) in the late 1850s reflects widespread logging and grazing during the nineteenth century. Forest and woodland expansion occurred in the early twentieth century, with forests composed of coast redwood and oak, among other taxa, as both logging and grazing declined. Invasive species include those associated with pasturage (Rumex, Plantago), landscape disturbance (Urtica, Amaranthaceae), planting for wood production and wind barriers (Eucalyptus), and agriculture. Agricultural species, including wheat, rye, and corn, were more common in the early twentieth century than subsequently. Wetland and aquatic pollen and fungal spores document a complex hydrological history, often associated with fluctuating water levels, application of algaecides, raising of Searsville Dam, and construction of a levee. By pairing the paleoecological and historical records of both lakes, we have been able to reconstruct the previously undocumented impacts of socio-ecological influences on this drainage, all of which overprinted known climate changes. Recognizing the ecological manifestations of these impacts puts into perspective the extent to which people have interacted with and transformed the environment in the transition into the Anthropocene.
","language":"English","publisher":"Springer","doi":"10.1007/s10113-023-02056-9","usgsCitation":"Anderson, R., Stegner, M.A., La Selle, S., Sherrod, B.L., Barnosky, A.D., and Hadly, E.A., 2023, Witnessing history: Comparison of a century of sedimentary and written records in a California protected area: Regional Environmental Change, v. 23, 65, 18 p., https://doi.org/10.1007/s10113-023-02056-9.","productDescription":"65, 18 p.","ipdsId":"IP-147736","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443145,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10113-023-02056-9","text":"Publisher Index Page"},{"id":417945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Jasper Ridge Biological Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.23418768300823,\n 37.3930404399613\n ],\n [\n -122.20397178645686,\n 37.40170883665597\n ],\n [\n -122.209679233583,\n 37.404509181302004\n ],\n [\n -122.21387588588198,\n 37.406109331254214\n ],\n [\n -122.21773680599699,\n 37.4091761898071\n ],\n [\n -122.21857613645665,\n 37.411576252406434\n ],\n [\n -122.22109412783595,\n 37.4118429212817\n ],\n [\n -122.22176559220381,\n 37.41424289844102\n ],\n [\n -122.24123805887044,\n 37.4121095892076\n ],\n [\n -122.2456025772612,\n 37.408376151853375\n ],\n [\n -122.2459383094448,\n 37.406776050314505\n ],\n [\n -122.24543471116908,\n 37.403842442069205\n ],\n [\n -122.24778483645659,\n 37.403842442069205\n ],\n [\n -122.24963136346803,\n 37.40264229649942\n ],\n [\n -122.2494634973759,\n 37.3998418820846\n ],\n [\n -122.23418768300823,\n 37.3930404399613\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"23","noUsgsAuthors":false,"publicationDate":"2023-04-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, R. 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Allison","contributorId":197658,"corporation":false,"usgs":false,"family":"Stegner","given":"M.","email":"","middleInitial":"Allison","affiliations":[],"preferred":false,"id":874943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Selle, SeanPaul 0000-0002-4500-7885 slaselle@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-7885","contributorId":181565,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul","email":"slaselle@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":874945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnosky, Anthony D.","contributorId":197553,"corporation":false,"usgs":false,"family":"Barnosky","given":"Anthony","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":874946,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hadly, Elizabeth A.","contributorId":197554,"corporation":false,"usgs":false,"family":"Hadly","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":874947,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70243499,"text":"sir20225105 - 2023 - Application of the Precipitation-Runoff Modeling System (PRMS) to simulate the streamflows and water balance of the Red River Basin, 1980–2016","interactions":[],"lastModifiedDate":"2026-02-23T19:28:22.014039","indexId":"sir20225105","displayToPublicDate":"2023-06-08T08:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5105","displayTitle":"Application of the Precipitation-Runoff Modeling System (PRMS) to Simulate the Streamflows and Water Balance of the Red River Basin, 1980–2016","title":"Application of the Precipitation-Runoff Modeling System (PRMS) to simulate the streamflows and water balance of the Red River Basin, 1980–2016","docAbstract":"The Precipitation-Runoff Modeling System (PRMS) was used to develop and calibrate a streamflow and water balance model for the Red River Basin as part of the U.S. Geological Survey National Water Census, a research effort focused on developing innovative water accounting tools and conducting assessments of water use and availability at regional and national spatial scales. The PRMS is a deterministic model that simulates the effects of climate, land cover, and water use on watershed hydrology on the basis of physical processes and spatial attributes of the watershed. The model was used to estimate streamflow at daily and monthly temporal scales for the 1980–2016 period and to evaluate the impacts of natural and anthropogenic influences on streamflow and water budget components.
Sixty-three percent of streamgages were calibrated successfully for the monthly time step and 43 percent of streamgages were successfully calibrated for the daily time step. Some of the challenges of calibrating streamgages included estimating low amounts of streamflow in dry areas of the basin and accurately representing watershed characteristics related to evapotranspiration in the basin, among other factors. The model estimated streamflow with some accuracy for 42 percent and 29 percent of the 73 streamgages used to evaluate the model at monthly and daily time steps, respectively. Relative to no-water-use conditions, water use increased streamflow volumes (that is, return flow from reservoir releases) the most on the main stem of the Red River, the North Fork of the Red River, and the Ouachita River. Water withdrawal decreased streamflow volumes most in the Red River near the outlet of the basin and in Caney Creek. Streamflow volumes on the North Fork of the Red River changed most as a result of water use. The Red River Basin PRMS model provided estimates of streamflow that were limited in their accuracy by (1) the availability of accurate water-use data; (2) the coarse resolution of spatial parameters (such as those for impervious area or plant canopy), which leads to the homogenization of physical features in small watersheds in the model domain; and (3) the accuracy of spatial patterns of precipitation distribution across the model domain. Improvements in the quality and quantity of available water-use data and finer resolution spatial parameter and climate data could lead to the development of better-informed models in the future that are capable of making more accurate estimates of streamflow, because they are more representative of physical and hydrologic conditions in the Red River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225105","issn":"2328-0328","programNote":"Water Availability and Use Science Program","usgsCitation":"Roland, V.L., II, 2023, Application of the Precipitation-Runoff Modeling System (PRMS) to simulate the streamflows and water balance of the Red River Basin, 1980–2016: U.S. Geological Survey Scientific Investigations Report 2022–5105, 37 p., https://doi.org/10.3133/sir20225105.","productDescription":"Report: viii, 37 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-091577","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":417622,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5105/coverthb.jpg"},{"id":500454,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114764.htm","linkFileType":{"id":5,"text":"html"}},{"id":417790,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZI5IVX","text":"USGS data release—Model input and output from Precipitation Runoff Modeling System (PRMS) simulation of the Red River Basin 1981–2016"},{"id":417789,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5105/images/"},{"id":417921,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225105/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5105 HTML"},{"id":417787,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5105/sir20225105.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2022-5105 XML"},{"id":417786,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5105/sir20225105.pdf","size":"16.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5105"}],"country":"United States","state":"Arkansas, Louisiana, Texas, Oklahoma","otherGeospatial":"Red River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -103.48949921760368,\n 36.13692959102481\n ],\n [\n -103.48949921760368,\n 31.242144043970583\n ],\n [\n -89.91622130795812,\n 31.242144043970583\n ],\n [\n -89.91622130795812,\n 36.13692959102481\n ],\n [\n -103.48949921760368,\n 36.13692959102481\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"For more information about this publication, contact
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
https://www.usgs.gov/centers/lmg-water/
The Great Dismal Swamp wetland, spanning >400 km2 along the Virginia and North Carolina border, was shaped by a complex combination of geomorphic, climatic, and anthropogenic forcings during the last 14,000 years. Pollen, macrofossils, charcoal, and physical properties from sediment cores at seven sites provide a detailed record of the spatial heterogeneity of the wetland and the roles played by natural hydrologic variability, wildfire, and human modification of drainage in shaping vegetation and habitats. Cold-temperate forests occupied regional uplands from at least 13.5–10.3 cal ka BP. Marshes dominated by grasses and other herbaceous taxa began developing along low-elevation streams as early as 10.3 cal ka BP, resulting in accumulation of organic silts. Long-hydroperiod, peat accumulating marshes, with abundant floating aquatic plants, developed as early as 9.6 cal ka BP, as rapid rates of sea-level rise elevated the water table and facilitated wetland development and peat accumulation along stream courses. By the mid-Holocene (c. 7–6.5 cal ka BP), when local sea-level rise began slowing and reached about 12–15 m below present, shorter hydroperiod, peat-accumulating marshes dominated the landscape, with increased wildfire activity. Great Dismal Swamp vegetation shifted from marshes to peat-accumulating forested wetlands by c. 3.7 cal ka BP; these were dominated by varying combinations of Nyssa (tupelo), Taxodium (cypress), and Chamaecyparis thyoides (Atlantic white cedar). Wildfires were infrequent during this time, and the forested wetlands persisted, with minor compositional changes related to climate-driven fluctuations in stream flow, until colonial ditching and logging began in the swamp during the late 18th century. These activities decreased cypress and cedar populations, and, by the mid-20th century, expanded ditching resulted in even drier conditions and expansion of maple-gum (dominated by Acer and Liquidambar), and pine-pocosin (dominated by Pinus) forests. The distribution of these forests differs from that of the late Holocene and represents a fundamental shift in hydrology, peat structure, vegetation, and fire regime due to landscape alterations of the last few centuries.
Arctic-boreal wetlands, important ecosystems for biodiversity and ecological services, are experiencing hydrological changes including permafrost thaw, earlier snowmelt, and increased wildfire susceptibility. These changes are affecting wetland productivity, species diversity, and biogeochemical cycles. However, given the diverse forms and structures of wetland vegetation communities, traditional wetland maps generated from lower spatial and spectral resolution satellite imagery lack community-level vegetation classification and miss spatially complex patterns. In this study, we built a cloud-based workflow to map wetland vegetation community of the Peace-Athabasca Delta (PAD), Canada, by leveraging high-resolution (5-m) airborne multi-sensor datasets, namely NASA's Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), and a historical LiDAR archive. Validation of our classifications using ground references indicates that classifications derived from AVIRIS-NG have higher accuracies (≥87.9%) than either UAVSAR (65.6%) or LiDAR (75.9%) for mapping wetland vegetation communities. We also show improved classification accuracy when combining information from multiple sensors. In particular, incorporating AVIRIS-NG and UAVSAR datasets substantially reduced omission errors of wet graminoid and wet shrub classes from 29.6% to 20.5% and from 10.8% to 7.5%, respectively. Combining AVIRIS-NG and LiDAR datasets further improves overall accuracy (+2.2%) for most classifications, especially emergent vegetation, wet graminoid, and wet shrub. The best performing model, using features derived from all three sensors, achieved an overall accuracy of 93.5%. The framework established here can be used to leverage extensive airborne AVIRIS-NG and UAVSAR datasets collected across Alaska and northwest Canada to understand the spatial distribution of Arctic-Boreal wetland vegetation communities.
Groundwater is important as a drinking-water source and for maintaining base flow in rivers, streams, and lakes. Groundwater quality can be predicted, in part, by its residence time in the subsurface, but the residence-time distribution cannot be measured directly and must be inferred from models. This report compares residence-time distributions from four areas where groundwater flow and travel time were simulated with conventional simulation-inset models (IMs) and with a new automated model-construction method called general simulation models (GSMs). The comparison provides an opportunity to explore controls on travel time and improve the methods used in the creation of GSMs. These models can be useful for three main-use cases: (1) rapid testing of relationships that govern groundwater flow and age, (2) generation of consistent examples for training a machine-learning metamodel, and (3) serving as a starting point for more detailed models.
Comparison of the GSMs to IMs indicated a qualified pattern of agreement for residence-time distributions as indicated by the Nash-Sutcliffe efficiency and Spearman’s correlation coefficient. The agreement was best for the median values of the simulated residence times in young fractions of groundwater (defined as the fractions of groundwater in samples less than 65 years old) at the scale of the eight-digit hydrologic-unit code. Generally, the median values of the young fractions in the IMs were correlated with the median values from the GSMs. The relative trends across the four areas also were similar for the other residence-time metrics. The medians of residence-time metrics at finer scales show a fair degree of scatter. The GSM results compared most poorly for median travel times in the older fraction of groundwater (older than 65 years).
The GSM approach is intended as a flexible framework for developing models that can be useful individually as screening tools or collectively to support projects in statistical learning. Although one set of GSM algorithms was presented here, the approach can accommodate many types of data and also different categories of prior information. Comparison of GSMs and IMs suggests ways in which the GSMs, while remaining easy to construct and calibrate, can be improved for estimating groundwater travel times. IMs do not yield exact travel times, and matching GSMs to IMs does not guarantee an improvement; however, IMs provide a convenient benchmark against which to explore relations between physical characteristics of watersheds and the distribution of travel times within them.
This effort was undertaken as part of the National Water Quality Program of the U.S. Geological Survey to assist in determining the susceptibility of groundwater in glacial aquifers to a variety of natural and anthropogenic contaminants.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215142","programNote":"National Water Quality Program","usgsCitation":"Starn, J.J., Kauffman, L.J., and Feinstein, D.T., 2023, Groundwater residence times in glacial aquifers—A new general simulation-model approach compared to conventional inset models: U.S. Geological Survey Scientific Investigations Report 2021–5142, 37 p., https://doi.org/10.3133/sir20215142.","productDescription":"Report: v, 37 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112499","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":500447,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114759.htm","linkFileType":{"id":5,"text":"html"}},{"id":413862,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5142/images/"},{"id":413858,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5142/coverthb.jpg"},{"id":413859,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5142/sir20215142.pdf","text":"Report","size":"6.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5142"},{"id":413861,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5142/sir20215142.XML"},{"id":413863,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HS83JL","text":"USGS data release","linkHelpText":"MODPATH-NWT and MODPATH6 models used to compare a new general simulation model approach with a conventional inset model approach for groundwater residence time in glacial aquifers"},{"id":413860,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215142/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5142"}],"country":"United States","state":"Illinois, Indiana, Michigan, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.5,\n 46\n ],\n [\n -89,\n 46\n ],\n [\n -89,\n 41.5\n ],\n [\n -84.5,\n 41.5\n ],\n [\n -84.5,\n 46\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Digital flood-inundation maps for an 8-mile reach of Papillion Creek near Offutt Air Force Base, Nebraska, were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Air Force, Offutt Air Force Base. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgages Papillion Creek at Fort Crook, Nebr. (station 06610795), and Papillion Creek at Harlan Lewis Road near La Platte, Nebr. (station 06610798). Near-real-time stages at these streamgages may be obtained from the USGS National Water Information System database at https://doi.org/10.5066/F7P55KJN or from the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/.
Flood profiles were computed for the 8-mile stream reach by means of a one-dimensional step-backwater model. The model was calibrated by adjusting roughness coefficients to best represent the current (2022) stage-streamflow relation at the Papillion Creek at Fort Crook (station 06610795) streamgage.
The hydraulic model then was used to compute water-surface profiles for 157 scenarios using a combination of stage values in 1-foot (ft) stage intervals that ranged from 27 to 39 ft at the Papillion Creek at Fort Crook (station 06610795) streamgage and from 13.9 to 30.9 ft at the Papillion Creek at Harlan Lewis Road near La Platte (station 06610798) streamgage, as referenced to the local datums. The simulated water-surface profiles then were combined by a geographic information system with a digital elevation model, which had a 3.281-ft grid to delineate the area flooded and water depths at each stage. The availability of these flood-inundation maps, along with information regarding current stage from the USGS streamgages, can provide emergency management personnel and residents with information that is critical for flood response activities and postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235054","collaboration":"Prepared in cooperation with the U.S. Air Force, Offutt Air Force Base","usgsCitation":"Strauch, K.R., and Hobza, C.M., 2023, Flood-inundation maps for an 8-mile reach of Papillion Creek near Offutt Air Force Base, Nebraska, 2022: U.S. Geological Survey Scientific Investigations Report 2023–5054, 12 p., https://doi.org/10.3133/sir20235054.","productDescription":"Report: vi, 12 p.; Data Release; Dataset","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-135851","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":417490,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5054/images"},{"id":417652,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235054/full"},{"id":417492,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XQIXMN","text":"USGS data release","linkHelpText":"Flood inundation geospatial datasets for Papillion Creek near Offutt Air Force Base, Nebraska"},{"id":417489,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5054/sir20235054.XML"},{"id":417491,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":417486,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5054/sir20235054.pdf","text":"Report","size":"3.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5054"},{"id":417485,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5054/coverthb.jpg"},{"id":500933,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114763.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Nebraska","otherGeospatial":"Offutt Air Force Base, Papillion Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -95.966667,\n 41.15\n ],\n [\n -95.966667,\n 41.05\n ],\n [\n -95.8667,\n 41.05\n ],\n [\n -95.8667,\n 41.15\n ],\n [\n -95.966667,\n 41.15\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Many data collection efforts and modeling studies have focused on providing accurate estimates of streamflow while fewer efforts have sought to identify when and where surface water is present and the duration of surface water presence in stream channels, hereafter referred to as streamflow permanence. While physically-based hydrological models are frequently used to explore how water quantity may be influenced by various climatic and basin characteristics at local, regional, national, and global extents they are less often used to explore streamflow permanence. Herein, the Watershed Erosion Prediction Project (WEPP) hydrological model is applied to watersheds in the humid H. J. Andrews Experimental Forest (HJA) and watersheds of the arid Willow and Whitehorse creeks (WW), both in Oregon, to simulate daily (WW) and annual (HJA and WW) streamflow permanence. One thousand parameter combinations were tested to calibrate WEPP to observed streamflow in the HJA watersheds and one hundred parameter combinations were tested to calibrate WEPP to observed surface water presence time series data in WW watersheds. When calibrated to observed streamflow, WEPP correctly classified annual streamflow permanence for 83% of HJA stream reaches. In the WW, WEPP simulations correctly classified 63–93% of daily streamflow permanence observations and 59-87% of annual streamflow permanence classifications. Inclusion of a dry-day threshold (the maximum number of days a stream reach could be modeled ‘dry’ but still classified as permanent for the year) improved annual accuracy in three WW watersheds from 2-10%. Parameter sets that produced the best daily accuracies in WW resulted in poor annual accuracies. Results highlight the importance of evaluating physically-based streamflow permanence models on both permanent and nonpermanent streams at daily and annual time scales to ensure evaluation metrics are appropriate for interpretation purposes. Additionally, results suggest that strategic collection of surface water presence observations and streamflow observations may support robust calibration of physically based models to simulate streamflow permanence moving forward.
Deep Springs Valley (DSV) is a hydrologically isolated valley between the White and Inyo mountains that is commonly excluded from regional paleohydrology and paleoclimatology. Previous studies showed that uplift of Deep Springs ridge (informal name) by the Deep Springs fault defeated streams crossing DSV and hydrologically isolated the valley sometime after eruption of the Pleistocene Bishop Tuff (0.772 Ma). Here, we present tephrochronology and clast counts that reaffirms interruption of the Pliocene–Pleistocene hydrology and formation of DSV during the Pleistocene. Paleontology and infrared stimulated luminescence (IRSL) dates indicate a freshwater lake inundated Deep Springs Valley from ca. 83–61 ka or during Late Pleistocene Marine Isotope Stages 5a (MIS 5a; ca. 82 ka peak) and 4 (MIS 4; ca. 71–57 ka). The age of pluvial Deep Springs Lake coincides with pluvial lakes in Owens Valley and Columbus Salt Marsh and documents greater effective precipitation in southwestern North America during MIS 5a and MIS 4. In addition, we hypothesize that Deep Springs Lake was a balanced-fill lake that overflowed into Eureka Valley via the Soldier Pass wind gap during MIS 5a and MIS 4. DSV hydrology has implications for dispersal and endemism of the Deep Springs black toad (Anaxyrus exsul).
Selenium in aquatic ecosystems of the lower Gunnison River Basin in Colorado is affecting the recovery of populations of endangered, native fish species. Dietary exposure is the primary pathway for bioaccumulation of selenium in fish, and particulate selenium can be consumed directly by fish or by the invertebrates on which fish feed. Although selenium can be incorporated into particulate matter via biogeochemical processes, particulate selenium can also enter aquatic ecosystems of the lower Gunnison River Basin from sediments derived from the selenium-rich Mancos Shale. The U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, conducted this study during 2018–19 to identify sources of selenium-rich suspended sediments from two watersheds underlain by Mancos Shale: Loutsenhizer Arroyo and Sunflower Drain, which is a locally known agricultural drainage near the municipality of Delta, Colorado.
A multipronged approach (fieldwork, laboratory work, and computer modeling) referred to as “sediment fingerprinting” was used to evaluate sources of suspended sediments in the streams flowing out of the two studied watersheds. Four potential source types for suspended sediments were identified and sampled (using soil plugs) within the watersheds: rangelands, agricultural fields, arroyo walls, and streambanks. The sediment fingerprinting approach used elemental concentrations and naturally occurring fallout radionuclides as tracers to apportion percent contributions from the four source types of suspended sediments found in streamflow from both watersheds.
To determine the dominant sources of suspended sediment in streamflow from both watersheds, a mathematical “unmixing” model was used. Unmixing models apportion source percentages to samples of material in which those sources are mixed. These models used elemental and isotopic data in the suspended sediments to unmix them into proportional contributions from source types. The results indicated that arroyo walls and streambanks generally dominated as sources of the suspended sediment. Arroyo walls and streambanks were channel-adjacent sources, with sediments mobilized by water flowing within the stream channel. These sources accounted for greater than 50 percent of suspended sediment in all but one sample and accounted for 100 percent of suspended sediment in 5 of the 11 samples collected. Rangeland and agricultural field sources were located in uplands outside of stream channels and were detected more often during the non-irrigation season. Rangeland and agricultural field sources each were found in 5 of the 11 samples collected. Concentrations of selenium in sediment-source samples were comparatively greater in streambanks and lower in rangelands, with agricultural fields and arroyo walls being intermediate. As a result, source apportionments for particulate selenium skewed towards sources adjacent to stream channels more than for suspended sediments. Water imports for irrigation have changed the hydrology of the watersheds, and a notable fraction of imported water passes through the watersheds rapidly. The rapid flowthrough water during the irrigation season likely contributes heavily to sediment erosion and transport in Loutsenhizer Arroyo and Sunflower Drain, particularly from channel-adjacent sources of sediment. Decreases in irrigation season streamflow, at least in Loutsenhizer Arroyo, may have decreased sediment erosion and transport during the 2018–20 irrigation seasons compared to the 2015–17 seasons.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235056","collaboration":"Prepared in cooperation with the Colorado Water Conservation Board","usgsCitation":"Bern, C.R., Williams, C.A., and Smith, C.G., 2023, Source contributions to suspended sediment and particulate selenium export from the Loutsenhizer Arroyo and Sunflower Drain watersheds in Colorado: U.S. Geological Survey Scientific Investigations Report 2023–5056, 32 p., https://doi.org/10.3133/sir20235056.","productDescription":"Report: vii, 32 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-132717","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":485917,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114745.htm","linkFileType":{"id":5,"text":"html"}},{"id":417883,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235056/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5056"},{"id":417619,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5056/sir20235056.xml"},{"id":417618,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5056/images"},{"id":417612,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99EZZJK","text":"USGS data release","linkHelpText":"Geochemical and fallout radionuclide data for sediment source fingerprinting studies of the Loutsenhizer Arroyo and Sunflower Drain watersheds in western Colorado"},{"id":417611,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5056/sir20235056.pdf","text":"Report","size":"3.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5056"},{"id":417610,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5056/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Loutsenhizer Arroyo Watershed, Sunflower Drain Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.2032088457371,\n 38.871468271392075\n ],\n [\n -108.2032088457371,\n 38.38029358037457\n ],\n [\n -107.27351004163626,\n 38.38029358037457\n ],\n [\n -107.27351004163626,\n 38.871468271392075\n ],\n [\n -108.2032088457371,\n 38.871468271392075\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, Colorado 80225