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USGS2017

Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania

An evaluation of trends in hydrologic and water quality conditions and estimation of water budgets through 2013 was done by the U.S. Geological Survey in cooperation with the Chester County Water Resources Authority. Long-term hydrologic, meteorologic, and biologic data collected in Chester County, Pennsylvania, which included streamflow, groundwater levels, surface-water quality, biotic integrity, precipitation, and air temperature were analyzed to determine possible trends or changes in hydrologic conditions. Statistically significant trends were determined by applying the Kendall rank correlation test; the magnitudes of the trends were determined using the Sen slope estimator. Water budgets for eight selected watersheds were updated and a new water budget was developed for the Marsh Creek watershed. An average water budget for Chester County was developed using the eight selected watersheds and the new Marsh Creek water budget. Annual and monthly mean streamflow, base flow, and runoff were analyzed for trends at 10 streamgages. The periods of record at the 10 streamgages ranged from 1961‒2013 to 1988‒2013. The only statistically significant trend for annual mean streamflow was for West Branch Brandywine Creek near Honey Brook, Pa. (01480300) where annual mean streamflow increased 1.6 cubic feet per second (ft 3 /s) per decade. The greatest increase in monthly mean streamflow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 47 ft 3 /s per decade. No statistically significant trends in annual mean base flow or runoff were determined for the 10 streamgages. The greatest increase in monthly mean base flow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 26 ft 3 /s per decade. The magnitude of peaks greater than a base streamflow was analyzed for trends for 12 streamgages. The period of record at the 12 stream gages ranged from 1912‒2012 to 2004–11. Fifty percent of the streamgages showed a small statistically significant increase in peaks greater than the base streamflow. The greatest increase was for Brandywine Creek at Chadds Ford, Pa. (01481000) during 1962‒2012; the increase was 1.8 ft 3 /s per decade. There were no statistically significant trends in the number of floods equal to or greater than the 2-year recurrence interval flood flow. Twenty‒one monitoring wells were evaluated for statistically significant trends in annual mean water level, minimum annual water level, maximum annual water level, and annual range in water-level fluctuations. For four wells, a small statistically significant increase in annual mean water level was determined that ranged from 0.16 to 0.7 feet per decade. There was poor or no correlation between annual mean groundwater levels and annual mean streamflow and base flow. No correlation was determined between annual mean groundwater level and annual precipitation. Despite rapid population growth and land-use change since 1950, there appears to have been little or no detrimental effects on groundwater levels in 21 monitoring wells. Long-term precipitation and temperature data were available from the West Chester (1893‒2013) and Phoenixville, Pa. (1915‒2013) National Oceanic and Atmospheric Administration (NOAA) weather stations. No statistically significant trends in annual mean precipitation or annual mean temperature were determined for either station. Both weather stations had a significant decrease in the number of days per year with precipitation greater than or equal to 0.1 inch. Annual mean minimum and maximum temperatures from the NOAA Southeastern Piedmont Climate Division increased 0.2 degrees Fahrenheit (F) per decade between 1896 and 2014. The number of days with a maximum temperature equal to or greater than 90 degrees F increased at West Chester and decreased at Phoenixville. No statistically significant trend was determined for annual snowfall amounts. Data from 1974 to 2013 for three stream water-quality monitors in the Brandywine Creek watershed were evaluated. The monitors are on the West Branch Brandywine Creek at Modena, Pa. (01480617), East Branch Brandywine Creek below Downingtown, Pa. (01480870), and Brandywine Creek at Chadds Ford, Pa. (01481000). Statistically significant upward trends were determined for annual mean specific conductance at all three stations, indicating the total dissolved solids load has been increasing. If the current trend continues, the annual mean specific conductance could almost double from 1974 to 2050. The increase in specific conductance likely is due to increases in chloride concentrations, which have been increasing steadily over time at all three stations. No correlation was found between monthly mean specific conductance and monthly mean streamflow or base flow. Statistically significant upward trends in pH were determined for all three stations. Statistically significant upward trends in stream temperature were determined for East Branch Brandywine Creek below Downingtown, Pa. (01480870) and Brandywine Creek at Chadds Ford, Pa. (01481000). The stream water-quality data indicate substantial increases in the minimum daily dissolved oxygen concentrations in the Brandywine Creek over time. The Chester County Index of Biotic Integrity (CC-IBI) determined for 1998‒2013 was evaluated for the five biological sampling sites collocated with streamgages. CC-IBI scores are based on a 0‒100 scale with higher scores indicating better stream quality. Statistically significant upward trends in the CC-IBI were determined for West Branch Brandywine Creek at Modena, Pa. (01480617) and East Branch Brandywine Creek below Downingtown, Pa. (01480870). No correlation was found between the CC-IBI and streamflow, precipitation, or stream specific conductance, pH, temperature, or dissolved oxygen concentration. A Chester County average water budget was developed using the nine estimated watershed water budgets. Average precipitation was 48.4 inches, and average streamflow was 21.4 inches. Average runoff and base flow were 8.3 and 13.1 inches, respectively, and average evapotranspiration and estimation of errors was 27.2 inches."

Pennsylvania↗

USGS2019

Offshore shallow structure and sediment distribution, Punta Gorda to Point Arena, Northern California

This publication consists of two map sheets that display shallow geologic structure, along with sediment distribution and thickness, for an approximately 150-km-long offshore section of the northern California coast between Punta Gorda and Point Arena. Each map sheet includes three maps at scales of either 1:100,000 or 1:200,000, and together the sheets include 30 figures that contain representative high-resolution seismic-reflection profiles. The maps and seismic-reflection surveys cover most of the continental shelf in this region. In addition, the maps show the locations of the shelf break and the 3-nautical-mile limit of California’s State Waters. The seismic-reflection data, which are the primary dataset used to develop the maps, were collected to support the California Seafloor Mapping Program, U.S. Geological Survey Offshore Geologic Hazards projects, and National Oceanic and Atmospheric Administration’s (NOAA’s) Ocean Explorer program. In addition to the two map sheets, this publication includes geographic information system data files of faults, sediment thicknesses, and depths-to-base of sediment The map area includes the northernmost section of the right-lateral San Andreas Fault, which extends offshore from Point Arena in the south to Point Delgada in the north. The San Andreas Fault is the primary structure in the widely distributed plate boundary between the Pacific Plate and the Sierra Nevada–Great Valley Microplate, with estimates of cumulative right slip of as much as up to 450 km. South of Point Delgada, fault-related transtension has resulted in development of the Noyo Basin. North of Point Delgada, the San Andreas Fault transitions into a complex contractional zone in and (or) south of the King Range, including a possible nearshore fault that may connect with the Mattole Canyon Fault. Quaternary sediments and bedrock underlie the shelf. On the seismic-reflection profiles, we digitally traced the thickness and depth of the uppermost seismic-stratigraphic unit, which is a focus of this publication. The upper contact of this unit is the seafloor; the lower contact is a transgressive surface of erosion, a commonly angular, wave-cut unconformity characterized by an upward change to lower amplitude, more diffuse reflections. On the basis of this lower contact, this stratigraphic unit is inferred to have been deposited on the shelf in the last about 21,000 years during the sea-level rise that followed the last major lowstand and the Last Glacial Maximum (LGM). Maps in this publication show both the thickness of this upper sediment unit and the depth to the base of the sediment unit. Within the map region, five different “domains” of post-LGM shelf sediment are delineated on the basis of sediment thickness and coastal geomorphology. Maximum sediment thickness (as much as 67 m) is found in the northern part of the region, along the steep south flank of the King Range. Minimum sediment thickness (areas of exposed bedrock) is found on fault-bounded uplifts, which include Tolo bank and Punta Gorda bank. Mean sediment thickness for the entire shelf in the map area between Punta Gorda and Point Arena is 8.9 m, and total sediment volume is 12,824×10 6 m 3 .

California↗

USGS2010

Southeast Regional Assessment Project for the National Climate Change and Wildlife Science Center, U.S. Geological Survey

The Southeastern United States spans a broad range of physiographic settings and maintains exceptionally high levels of faunal diversity. Unfortunately, many of these ecosystems are increasingly under threat due to rapid human development, and management agencies are increasingly aware of the potential effects that climate change will have on these ecosystems. Natural resource managers and conservation planners can be effective at preserving ecosystems in the face of these stressors only if they can adapt current conservation efforts to increase the overall resilience of the system. Climate change, in particular, challenges many of the basic assumptions used by conservation planners and managers. Previous conservation planning efforts identified and prioritized areas for conservation based on the current environmental conditions, such as habitat quality, and assumed that conditions in conservation lands would be largely controlled by management actions (including no action). Climate change, however, will likely alter important system drivers (temperature, precipitation, and sea-level rise) and make it difficult, if not impossible, to maintain recent historic conditions in conservation lands into the future. Climate change will also influence the future conservation potential of non-conservation lands, further complicating conservation planning. Therefore, there is a need to develop and adapt effective conservation strategies to cope with the effects of climate and landscape change on future environmental conditions. Congress recognized this important issue and authorized the U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center (NCCWSC; http://nccw.usgs.gov/) in the Fiscal Year 2008. The NCCWSC will produce science that will help resource management agencies anticipate and adapt to climate change impacts to fish, wildlife, and their habitats. With the release of Secretarial Order 3289 on September 14, 2009, the mandate of the NCCWSC was expanded to address climate change-related impacts on all Department of the Interior (DOI) resources. The NCCWSC will establish a network of eight DOI Regional Climate Science Centers (RCSCs) that will work with a variety of partners to provide natural resource managers with tools and information that will help them anticipate and adapt conservation planning and design for projected climate change. The forecasting products produced by the RCSCs will aid fish, wildlife, and land managers in designing suitable adaptive management approaches for their programs. The DOI also is developing Landscape Conservation Cooperatives (LCCs) as science and conservation action partnerships at subregional scales. The USGS is working with the Southeast Region of the U.S. Fish and Wildlife Service (FWS) to develop science collaboration between the future Southeast RCSC and future LCCs. The NCCWSC Southeast Regional Assessment Project (SERAP) will begin to develop regional downscaled climate models, land cover change models, regional ecological models, regional watershed models, and other science tools. Models and data produced by SERAP will be used in a collaborative process between the USGS, the FWS (LCCs), State and federal partners, nongovernmental organizations, and academia to produce science at appropriate scales to answer resource management questions. The SERAP will produce an assessment of climate change, and impacts on land cover, ecosystems, and priority species in the region. The predictive tools developed by the SERAP project team will allow end users to better understand potential impacts of climate change and sea level rise on terrestrial and aquatic populations in the Southeastern United States. The SERAP capitalizes on the integration of five existing projects: (1) the Multi-State Conservation Grants Program project "Designing Sustainable Landscapes," (2) the USGS multidisciplinary Science Thrust project "Water Availability for Ecological Needs," (3) the USGS Southeast Pilot Project "Climate Change in the Southeastern U.S. and its Impacts on Bird Distributions and Habitats," (4) a sea-level rise impacts study envisioned jointly with the National Oceanic and Atmospheric Administration (NOAA), and (5) two USGS sea-level rise impact assessment projects that address inundation hazards and provide probabilistic forecasts of coastal geomorphic change. The SERAP will expand on these existing projects and include the following tasks, which were initiated in summer 2009: * Regionally downscaled probabilistic climate-change projections * Integrated coastal assessment * Integrated terrestrial assessment * Multi-resolution assessment of potential climate change effects on biological resources: aquatic and hydrologic dynamics * Optimal conservation strategies to cope with climate change The SERAP seeks to formally integrate these tasks to aid conservation planning and design so that ecosystem management decisions can be optimized for providing desirable outcomes across a range of species and environments. The following chapters detail SERAP's efforts in providing a suite of regional climate, watershed, and landscape-change analyses and develop the interdisciplinary framework required for the biological planning phases of adaptive management and strategic conservation. The planning phase will include the identification of conservation alternatives, development of predictive models and decision support tools, and development of a template to address similar challenges and goals in other regions. The project teams will explore and develop ways to link the various ecological models arising from each component. The SERAP project team also will work closely with members of the LCCs and other partnerships throughout the life of the project to ensure that the objectives of the project meet resources mangers needs in the Southeast.

Open-File Report↗

USGS2003

Simulation of streamflow and water quality in the Red Clay Creek subbasin of the Christina River Basin, Pennsylvania and Delaware, 1994-98

The Christina River Basin drains 565 square miles (mi 2 ) in Pennsylvania and Delaware and includes the major subbasins of Red Clay Creek, White Clay Creek, Brandywine Creek, and Christina River. The Red Clay Creek is the smallest of the subbasins and drains an area of 54 mi 2 . Streams in the Christina River Basin are used for recreation, drinking-water supply, and to support aquatic life. Water quality in some parts of the Christina River Basin is impaired and does not support designated uses of the stream. A multi-agency, waterquality management strategy included a modeling component to evaluate the effects of point and nonpointsource contributions of nutrients and suspended sediment on stream water quality. To assist in nonpointsource evaluation, four independent models, one for each of the four main subbasins of the Christina River Basin, were developed and calibrated using the model code Hydrological Simulation Program?Fortran (HSPF). Water-quality data for model calibration were collected in each of the four main subbasins and in smaller subbasins predominantly covered by one land use following a nonpoint-source monitoring plan. Under this plan, stormflow and base-flow samples were collected during 1998 at 1 site in the Red Clay Creek subbasin and at 10 sites elsewhere in the Christina River Basin. The HSPF model for the Red Clay Creek subbasin simulates streamflow, suspended sediment, and the nutrients, nitrogen and phosphorus. In addition, the model simulates water temperature, dissolved oxygen, biochemical oxygen demand, and plankton as secondary objectives needed to support the sediment and nutrient simulations. For the model, the basin was subdivided into nine reaches draining areas that ranged from 1.7 to 10 mi 2 . One of the reaches contains a regulated reservoir. Ten different pervious land uses and two impervious land uses were selected for simulation. Land-use areas were determined from 1995 land-use data. The predominant land uses in the Red Clay Creek subbasin are agricultural, forested, residential, and urban. The hydrologic component of the model was run at an hourly time step and calibrated using streamflow data from three U.S. Geological Survey (USGS) streamflow-measurement stations for the period of October 1, 1994, through October 29, 1998. Daily precipitation data from one National Oceanic and Atmospheric Administration (NOAA) gage and hourly data from one NOAA gage were used for model input. The difference between observed and simulated stream- flow volume ranged from -0.8 to 2.1 percent for the 4-year period at the three calibration sites. Annual differences between observed and simulated streamflow generally were greater than the overall error for the 4-year period. For example, at a site near Stanton, Del., near the bottom of the basin (drainage area of 50.2 mi 2 ), annual differences between observed and simulated streamflow ranged from -5.8 to 6.0 percent and the overall error for the 4-year period was -0.8 percent. Calibration errors for 36 storm periods at the three calibration sites for total volume, low-flow-recession rate, 50-percent lowest flows, 10-percent highest flows, and storm peaks were 20 percent or less. Much of the error in simulating storm events on an hourly time step can be attributed to uncertainty in the rainfall data. The water-quality component of the model was calibrated using nonpoint-source monitoring data collected in 1998 at one USGS streamflowmeasurement station and other water-quality monitoring data collected at three USGS streamflowmeasurement stations. The period of record for waterquality monitoring was variable at the stations, with an end date of October 1998 but the start date ranging from October 1994 to January 1998. Because of availability, monitoring data for suspended-solids concentrations were used as surrogates for suspendedsediment concentrations, although suspended solids may underestimate suspended sediment and affect apparent accuracy of the suspended-sediment simulation. Comparison of observed to simulated loads for ﬁve storms in 1998 at the one nonpoint-source monitoring site at Wooddale, Del., indicates that simulation error commonly is as large as an order of magnitude for suspended sediment and nutrients. The simulation error tends to be smaller for dissolved utrients than particulate nutrients. Errors of 40 percent or less for monthly or annual values indicate a fair to good water-quality calibration according to recommended criteria, with much larger errors possible for individual storm events. Assessment of the accuracy of the water-quality calibration under stormﬂow conditions is limited by the sparsity of available water-quality data in the basin. Users of the Red Clay Creek HSPF model should be aware of model limitations and consider the following when predictive scenarios are desired: streamﬂow-duration curves indicate the model simulates stream-ﬂow reasonably well when evaluated over a broad range of conditions and time, although streamﬂow and the corresponding water quality for individual storm events may not be well simulated; streamﬂow-duration curves for the simulation period compare well with duration curves for the 57.5-year period ending in 2001 at Wooddale, Del., and include all but the extreme high-ﬂow and low-ﬂow events; calibration for water quality was based on sparse data, with the result of increasing uncertainty in the water-quality simulation.

Water-Resources Investigations Report↗

USGS2003

Simulation of streamflow and water quality in the White Clay Creek subbasin of the Christina River Basin, Pennsylvania and Delaware, 1994-98

The Christina River Basin drains 565 square miles (mi 2 ) in Pennsylvania, Maryland, and Delaware. Water from the basin is used for recreation, drinking water supply, and to support aquatic life. The Christina River Basin includes the major subbasins of Brandywine Creek, White Clay Creek, and Red Clay Creek. The White Clay Creek is the second largest of the subbasins and drains an area of 108 mi 2 . Water quality in some parts of the Christina River Basin is impaired and does not support designated uses of the streams. A multi-agency water-quality management strategy included a modeling component to evaluate the effects of point and nonpoint-source contributions of nutrients and suspended sediment on stream water quality. To assist in non point-source evaluation, four independent models, one for each of the three major subbasins and for the Christina River, were developed and calibrated using the model code Hydrological Simulation Program—Fortran (HSPF). Water-quality data for model calibration were collected in each of the four main subbasins and in smaller subbasins predominantly covered by one land use following a nonpoint-source monitoring plan. Under this plan, stormflow and base- flow samples were collected during 1998 at two sites in the White Clay Creek subbasin and at nine sites in the other subbasins. The HSPF model for the White Clay Creek Basin simulates streamflow, suspended sediment, and the nutrients, nitrogen and phosphorus. In addition, the model simulates water temperature, dissolved oxygen, biochemical oxygen demand, and plankton as secondary objectives needed to support the sediment and nutrient simulations. For the model, the basin was subdivided into 17 reaches draining areas that ranged from 1.37 to 13 mi 2 . Ten different pervious land uses and two impervious land uses were selected for simulation. Land-use areas were determined from 1995 land-use data. The predominant land uses in the White Clay Creek Basin are agricultural, forested, residential, and urban. The hydrologic component of the model was run at an hourly time step and primarily calibrated using streamflow data from two U.S. Geological Survey (USGS) streamflow-measurement stations for the period of October 1, 1994, through October 29, 1998. Additional calibration was done using data from two other USGS streamflow-measurement stations with periods of record shorter than the calibration period. Daily precipitation data from two National Oceanic and Atmospheric Administration (NOAA) gages and hourly precipitation and other meteorological data for one NOAA gage were used for model input. The difference between simulated and observed streamflow volume ranged from -0.9 to 1.8 percent for the 4-year period at the two calibration sites with 4-year records. Annual differences between observed and simulated streamflow generally were greater than the overall error. For example, at a site near the bottom of the basin (drainage area of 89.1 mi 2 ), annual differences between observed and simulated streamflow ranged from -5.8 to 14.4 percent and the overall error for the 4-year period was -0.9 percent. Calibration errors for 36 storm periods at the two calibration sites for total volume, low-flowrecession rate, 50-percent lowest flows, 10-percent highest flows, and storm peaks were within the recommended criteria of 20 percent or less. Much of the error in simulating storm events on an hourly time step can be attributed to uncertainty in the hourly rainfall data. The water-quality component of the model was calibrated using data collected by the USGS and state agencies at three USGS streamflow-measurement stations with variable water-quality monitoring periods ending October 1998. Because of availability, monitoring data for suspended-solids concentrations were used as surrogates for suspended-sediment concentrations, although suspended solids may underestimate suspended sediment and affect apparent accuracy of the suspended-sediment simulation. Comparison of observed to simulated loads for up to ﬁve storms in 1998 at each of the two nonpoint-source monitoring sites in the White Clay Creek Basin indicate that simulation error is commonly as large as an order of magnitude for suspended sediment and nutrients. The simulation error tends to be smaller for dissolved nutrients than for particulate nutrients. Errors of 40 percent or less for monthly or annual values indicate a fair to good water-quality calibration according to recommended criteria, with much larger errors possible for individual events. The accuracy of the water-quality calibration under stormﬂow conditions is limited by the relatively small amount of water-quality data available for the White Clay Creek Basin. Users of the White Clay Creek HSPF model should be aware of model limitations and consider the following if the model is used for predictive purposes: streamﬂow and water quality for individual storm events may not be well simulated, but the model performance is reasonable when evaluated over longer periods of time; the observed ﬂow-duration curve for the simulation period is similar to the long-term ﬂow-duration curve at White Clay Creek near Newark, Del., indicating that the calibration period is representative of all but highest 0.1 percent and lowest 0.1 percent of ﬂows at that site; relative errors in streamﬂow and water-quality simulations are greater for smaller drainage areas than for larger areas; and calibration for water-quality was based on sparse data.

Water-Resources Investigations Report↗

USGS2020

Cascadia Margin cold seeps: Subduction zone fluids, gas hydrates, and chemosynthetic habitats

Priority Geographic Area: The outer continental shelf and upper continental slope from Canada/U.S. border offshore Washington State to the Mendocino Fracture Zone (Northern California), entirely within the U.S. Exclusive Economic Zone (EEZ), from the outermost shelf to at least 2000 m water depth (Figure 1). Description of Priority Area: Since 2015, over a thousand water column gas plumes originating at seafloor gas seeps have been discovered landward of the Cascadia deformation front (e.g., Embley et al., 2016; Johnson et al., 2015, 2019; Merle and Embley, 2016; NA-95 Cruise Report, 2018; Riedel et al., 2018), adding to those that had long been known on Hydrate Ridge (e.g., Heeschen et al., 2003; Tréhu et al., 2004). The recently-discovered seeps stretch from offshore Vancouver Island to the Mendocino Fracture Zone and from the outer shelf to ~2000 m water depth, occurring both landward and seaward of the nominal limit for gas hydrate stability zone on the upper continental slope (Figure 1). Hundreds of seeps likely remain undiscovered. Water column imaging is incomplete both within the target geographic area and farther seaward, between the 2000 m isobath and the deformation front, which is the subject of an imaging study described in a white paper by Watt et al. The recently-discovered Cascadia Margin cold seeps partially overlap an important active margin gas hydrate province (Spence et al., 2001; Tréhu et al., 2003, 2004), as well as an area where sediments on the North American plate are folded and faulted and affected by fluids generated in the subduction complex beneath the Cascadia forearc (e.g., Saffer and Tobin, 2011). Several Ocean Drilling Program expeditions have focused on hydrate systems offshore Vancouver and Oregon (e.g., Riedel et al., 2009; Tréhu et al., 2004) and on the connection between the shallow and deep hydrogeologic systems. Cabled observatories now continuously monitor physical, chemical, and venting processes on south Hydrate Ridge (OOI; e.g., Philip et al., 2016a) and offshore Vancouver Island (NEPTUNE; e.g. Römer et al., 2016). Outside of these well-studied gas hydrate areas, a subset of the recently-discovered Cascadia seeps, including some that we visited with R/V Falkor in 2019 (e.g., https://schmidtocean.org/cruise/methane-seeps-at-edge-of-hydrate-stability/), also likely emit methane associated with shallow subseafloor gas hydrate systems. Other seeps are delivering not only methane, but also deep-derived gases (Baumberger et al., 2018, 2020) to the seafloor. Many Cascadia Margin seeps have also been recognized at water depths too shallow (e.g., 175 m) to be connected to gas hydrate dynamics. These seeps are postulated to be emitting gas and fluids that originated deep in accretionary wedge before migrating up normal faults generated during forearc extension associated with large earthquakes (Johnson et al., 2019). Only a small fraction of the recently discovered U.S. Cascadia Margin water column gas plumes has so far been verified by ROVs (Hercules from E/V Nautilus in 2016 and 2018; SuBastian from R/V Falkor in 2018 and 2019) to correspond to seafloor seeps. Careful scientific mapping, investigation, and sampling at the seeps have also been limited (e.g., Baumberger et al., 2018, 2020; Merle and Embley, 2016; Seabrook et al., 2018; Greinert et al. 2019). This white paper focuses on expanding exploration of already-identified U.S. Cascadia Margin cold seeps through a multipronged and multidisciplinary discovery program that could be accomplished with a variety of NOAA assets. The goals of the proposed exploration activities are to develop high-resolution maps of seep fields from deep ocean vehicles; to verify (and sample) seafloor gas emissions at the locations of water column plumes for compositional and isotopic studies; to map, sample, and conduct analyses on chemosynthetic communities and deep-sea coral habitats near seep sites to document species distributions and habitats as a function of depth and latitude along the margin; to collect seep geologic samples that can constrain the timing of methane emissions through geochronology; and to record environmental data (e.g., CTD) near the seafloor and in the water column above the seeps. Seafloor mapping using shipboard systems (multibeam/backscatter) would be needed to characterize seafloor features near seep sites. Water column imaging (EK60/80 and/or multibeam WCD data) conducted before and after seafloor explorations would capture active methane plumes and constrain temporal variations in seep emissions (e.g., Kannberg et al., 2013; Philip et al., 2016a, 2016b), which are known to vary on time scales as rapid as tidal cycles on this margin (e.g., Römer et al., 2016). What are the characterization and data needs in this area? Check all that apply: __x_ Biology, Geology, Physical Oceanography, Chemistry ___ Marine Archaeology ___ Other Provide a list or brief description of the data needed within this area, from your perspective: 1. Water column backscatter to image active gas plumes 2. High-resolution multibeam bathymetry, seafloor backscatter, and shallow sub-bottom imaging 3. Visual characterization and ground truthing of potential seeps, including high-resolution mapping and photography from near-seafloor vehicles; collection of seep-associated species, corals, sediments, authigenic carbonates, gases, and seawater Describe relevance to national security, conservation, and/or the economy: The Cascadia margin seeps provide significant ecosystem services, including habitat for commercially important fishes and support for diversity along the continental margin. Methane seeps are also biological hotspots for krill, plankton, and crustaceans, which in turn sustain higher trophic levels (e.g., whales). Methane-derived authigenic carbonates serve as a hard substrate for deep-sea corals and sponges on millennial time scales. The studies proposed here will elucidate the relationship among seep environments, deep-sea corals, sponges, fisheries, and other organisms and provide new insight into subduction zone and hydrate-associated fluids in this important seismogenic zone. The studies address fishery management concerns and inform future conservation of sensitive species (e.g., deep-sea corals) and benthic habitats. From your perspective, what makes this area unique? The Cascadia Margin seeps are a critical component of the leaky margin that stretches from Baja California to the Aleutian Arc along the Pacific coastline of North America. Cold seeps have been intensely studied on the Gulf of Mexico and U.S. Atlantic passive margins with a focus on chemosynthetic communities, deep-sea corals, and leakage of microbially-generated and/or thermogenic hydrocarbons; however, the recently-discovered Cascadia Margin seeps, as well as active margin seep systems in general, remain more poorly characterized. Such seeps not only contribute to the ocean carbon cycle (e.g., Pohlman et al., 2011), thereby fueling the base of the food chain in these settings, but also emit subduction zone fluids that provide clues about processes within the seismogenic zone and the accretionary complex. The Cascadia seeps area allows both biological (e.g., benthic habitats, coral distributions) and physical processes (e.g., generation of subduction zone fluids) to be studied along both depth (perpendicular to the deformation front) and latitudinal gradients.

California, Oregon, Washington↗

USGS2025

Estimated average annualized tsunami losses for the United States

Tsunami hazards are substantial threats to coastal communities across the United States (U.S.) and its territories. U.S. states and territories collaborate through the National Tsunami Hazard Mitigation Program (NTHMP) to develop their own tsunami-hazard information for outreach and evacuation planning. An effort to curate this tsunami-hazard information to support comprehensive risk analysis at the national level has not yet been completed. In support of this effort, the Federal Emergency Management Agency (FEMA) collaborated with the NTHMP, the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS) starting in 2023. This collaboration included the collection and analysis of existing tsunami hazard data and methods in the U.S. Tsunami subject matter experts identified and selected scientifically defensible methods for estimating the risks to buildings and populations in coastal communities. These efforts may support decision making regarding resilience policies, priorities, strategies and funding levels. Tsunamis can be triggered by earthquakes, subaerial or submarine landslides, volcanic eruptions, glacial calving, near-earth objects, weather or other events. These events can cause severe destruction, injuries, and loss of life due to powerful currents and flooding. Tsunamis pose a substantial threat to the western United States and all U.S. territories, as described below. ■ Hawaii is threatened by distant tsunamis due to its central location in the Pacific Ocean basin and has a history of local events. ■ Alaska, particularly the Aleutian Islands, faces local tsunami threats due to proximity to the Alaska-Aleutian Subduction Zone, as well as distant tsunamis from around the Pacific Ocean basin. ■ The western coast of the U.S. is threatened by distant tsunamis from around the Pacific Ocean basin and local source tsunamis from earthquakes generated within the Cascadia Subduction Zone in the Pacific Northwest. ■ American Samoa faces local tsunami threats from earthquakes generated in the nearby Tonga Trench, as well as distant tsunami threats. ■ Guam and the Commonwealth of the Northern Mariana Islands are threatened by local tsunamis from the nearby Mariana Subduction Zone, as well as distant sources from around the Pacific Ocean Basin. ■ Puerto Rico and the United States Virgin Islands are threatened by multiple local and distant tsunami sources, such as the Puerto Rico Trench (PRT), given their location in the complex seismic region of the Caribbean Sea. Several historical events stand out because of their catastrophic impacts. ■ In the Pacific Northwest, the 1700 Cascadia earthquake caused a tsunami that affected coastal Native American communities, though the extent of the damage is not fully documented (Ludwin, et al., 2005). ■ In Puerto Rico, the 1918 earthquake triggered a tsunami that caused $77 million in damage in 2022 dollars and 116 fatalities, primarily along the western coast (Coffman et al., 1982). ■ The 1946 Aleutian Islands earthquake triggered a massive tsunami that devastated Hilo, Hawaii, killing 158 people and resulting in approximately $375 million in damage (adjusted to 2022 dollars) (Fisher et al., 2023). ■ The 1964 Alaska earthquake (M 9.2) generated tsunamis that caused severe destruction in some communities across Alaska, Oregon, and California. This disaster led to a total of 124 fatalities and approximately $2.9 billion in property damage (adjusted to 2022 dollars) (Brocher et al., 2014) (Alaska Science Center, 2024). ■ In American Samoa, a tsunami generated by the 2009 Samoa earthquake (Mw 8.1) caused widespread devastation, resulting in 34 confirmed fatalities (Apatu et al., 2013) and economic losses exceeding $160 million (adjusted to 2022 dollars) (DHS, 2011). More recent events, including the 2010 Chile earthquake, the 2011 Japan earthquake, and the 2022 Tonga volcanic eruption, resulted in millions of dollars in damage to numerous ports and harbors in the U.S. South Pacific territories, Hawaii, and along the west coast of the U.S. (Lynett, et al., 2022) (Wilson, et al., 2013). Since these events, the expansion of the built environment in lowlying areas along the coast has increased the exposure of buildings and people, thereby further escalating community risk from tsunamis. This report provides a comprehensive national assessment of earthquake-generated tsunami risk. It does not include impacts from tsunamis generated by landslides, volcanic eruptions, glacial calving, near-earth objects, weather, or other events. This study is based on the best available hazard data from the U.S. Pacific Coast (California, Oregon and Washington), Alaska, Hawaii, U.S. Pacific Territories (American Samoa, Guam and Commonwealth of the Northern Mariana Islands) and Caribbean Territories (Puerto Rico and United States Virgin Islands). Tsunami risks associated with states along the East Coast, Gulf Coast, and Great Lakes are not included in this study because Hazus 6.1 software (FEMA 2024a) does not currently include the ability to analyze tsunami risk in those states. Once modeling capabilities and tsunami hazard data become available for additional states, FEMA may incorporate these data into future editions of this study.

Alaska, California, Hawaii Oregon, Washington↗

USGS2010

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: NLCD 2001 Imperviousness

This data set represents the mean percent impervious surface from the Imperviousness Layer of the National Land Cover Dataset 2001 (LaMotte and Wieczorek, 2010), compiled for every catchment of NHDPlus for the conterminous United States. The source data set represents imperviousness for the conterminous United States for 2001. The Imperviousness Layer of the National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Data Series↗

USGS2010

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: NLCD 2001 Land Use and Land Cover

This data set represents the estimated area of land use and land cover from the National Land Cover Dataset 2001 (LaMotte, 2008), compiled for every catchment of NHDPlus for the conterminous United States. The source data set represents land use and land cover for the conterminous United States for 2001. The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Data Series↗

USGS2003

Simulation of streamflow and water quality in the Christina River subbasin and overview of simulations in other subbasins of the Christina River Basin, Pennsylvania, Maryland, and Delaware, 1994-98

The Christina River Basin drains 565 square miles (mi 2 ) in Pennsylvania and Delaware and includes the major subbasins of Brandywine Creek, Red Clay Creek, White Clay Creek, and Christina River. The Christina River subbasin (exclusive of the Brandywine, Red Clay, and White Clay Creek subbasins) drains an area of 76 mi 2 . Streams in the Christina River Basin are used for recreation, drinking water supply, and support of aquatic life. Water quality in some parts of the Christina River Basin is impaired and does not support designated uses of the stream. A multi-agency water-quality management strategy included a modeling component to evaluate the effects of point- and nonpoint-source contributions of nutrients and suspended sediment on stream water quality. To assist in nonpoint-source evaluation, four independent models, one for each of the four main subbasins of the Christina River Basin, were developed and calibrated using the model code Hydrological Simulation Program–Fortran (HSPF). Water-quality data for model calibration were collected in each of the four main subbasins and in small subbasins predominantly covered by one land use following a nonpoint- source monitoring plan. Under this plan, stormflow and base-flow samples were collected during 1998 at two sites in the Christina River subbasin and nine sites elsewhere in the Christina River Basin. The HSPF model for the Christina River subbasin simulates streamflow, suspended sediment, and the nutrients, nitrogen and phosphorus. In addition, the model simulates water temperature, dissolved oxygen, biochemical oxygen demand, and plankton as secondary objectives needed to support the sediment and nutrient simulations. For the model, the basin was subdivided into nine reaches draining areas that ranged from 3.8 to 21.9 mi 2 . Ten different pervious land uses and two impervious land uses were selected for simulation. Land-use areas were determined from 1995 land-use data. The predominant land uses in the Christina River subbasin are residential, urban, forested, agricultural, and open. The hydrologic component of the model was run at an hourly time step and calibrated using streamflow data from two U.S. Geological Survey (USGS) streamflow-measurement stations for the period of October 1, 1994, through October 29, 1998. Daily precipitation data from one National Oceanic and Atmospheric Administration (NOAA) meteorologic station and hourly data from one NOAA meteorologic station were used for model input. The difference between observed and simulated streamflow volume ranged from -2.3 to 5.3 percent for a 10-month portion of the calibration period at the two calibration sites. Annual differences between observed and simulated streamflow generally were greater than the overall error for the 4-year period. For example, at Christina River at Coochs Bridge, near the bottom of the free-flowing part of the subbasin (drainage area of 21 mi 2 ), annual differences between observed and simulated streamflow ranged from -6.9 to 6.5 percent and the overall error for the 4-year period was -1.1 percent. Calibration errors for 36 storm periods at the three calibration sites for total volume, low-flow recession rate, 50-percent lowest flows, 10-percent highest flows, and storm peaks were within the recommended criteria of 20 percent or less. Much of the error in simulating storm events on an hourly time step can be attributed to uncertainty in the rainfall data. The water-quality component of the model was calibrated using nonpoint-source monitoring data collected at two USGS streamflow-measurement stations and other water-quality monitoring data. The period of record for water-quality monitoring was variable at the stations, with a start date ranging from October 1994 to January 1998 and an end date of October 1998. Because of availability, monitoring data for suspended-solids concentrations were used as surrogates for suspended-sediment concentrations, although suspended-solids data may underestimate suspended sediment and affect apparent accuracy of the suspended-sediment simulaion. Comparison of observed to simulated loads for up to six storms in 1998 at the two nonpoint-source monitoring sites (Little Mill Creek near Newport and Christina River at Coochs Bridge, Del.) indicate that simulation error is commonly as large as an order of magnitude for suspended sediment and nutrients. The simulation error tends to be smaller for dissolved nutrients than for particulate nutrients. Errors of 40 percent or less for monthly or annual values indicate a fair to good water-quality calibration according to recommended criteria; much larger errors are possible for individual events. Assessment of the water-quality calibration under stormﬂow conditions is limited by the relatively small amount of available water-quality data in the subbasin. Users of the Christina River subbasin HSPF model and HSPF models for other subbasins in the Christina River Basin should be aware of model limitations and consider the following if the model is used for predictive purposes: streamﬂow-duration curves suggest the model simulates streamﬂow reasonably well when measured over a broad range of conditions and time although streamﬂow and the corresponding water quality for individual storm events may not be well simulated; streamﬂow-duration curves for the simulation period compare well with duration curves for the 8-year period ending in 2001 at Christina River at Coochs Bridge, Del., and include all but the extreme high-ﬂow and low-ﬂow events; and calibration for water quality was based on limited data, with the result of increasing uncertainty in the water-quality simulation.

Water-Resources Investigations Report↗

USGS2014

The future of nearshore processes research

The nearshore is the transition region between land and the continental shelf including (from onshore to offshore) coastal plains, wetlands, estuaries, coastal cliffs, dunes, beaches, surf zones (regions of wave breaking), and the inner shelf (Figure ES-1). Nearshore regions are vital to the national economy, security, commerce, and recreation. The nearshore is dynamically evolving, is often densely populated, and is under increasing threat from sea level rise, long-term erosion, extreme storms, and anthropogenic influences. Worldwide, almost one billion people live at elevations within 10 m of present sea level. Long-term erosion threatens communities, infrastructure, ecosystems, and habitat. Extreme storms can cause billions of dollars of damage. Degraded water quality impacts ecosystem and human health. Nearshore processes, the complex interactions between water, sediment, biota, and humans, must be understood and predicted to manage this often highly developed yet vulnerable nearshore environment. Over the past three decades, the understanding of nearshore processes has improved. However, societal needs are growing with increased coastal urbanization and threats of future climate change, and significant scientific challenges remain. To address these challenges, members of academia, industry, and federal agencies (USGS, USACE, NPS, NOAA, FEMA, ONR) met at the “The Past and Future of Nearshore Processes Research: Reflections on the Sallenger Years and a New Vision for the Future” workshop to develop a nearshore processes research vision where societal needs and science challenges intersect. The resulting vision is comprised of three broad research themes: Long-term coastal evolution due to natural and anthropogenic processes: As global climate change alters the rates of sea level rise and potentially storm patterns and coastal urbanization increases over the coming decades, an understanding of coastal evolution is critical. Improved knowledge of long-term morphological, ecological, and societal processes and their interactions will result in an improved ability to simulate coastal change. This will enable proactive solutions for resilient coasts and better guidance for reducing coastal vulnerability. Extreme Events: Flooding, erosion, and the subsequent recovery: Hurricane Sandy caused flooding and erosion along hundreds of miles of shoreline, flooded New York City, and impacted communities and infrastructure. Overall U.S. coastal extreme event related economic losses have increased substantially. Furthermore, climate change may cause an increase in coastal extreme events and rising sea levels could increase the occurrence of extreme events. Addressing this research theme will result in an improved understanding of the physical processes during extreme events, leading to improved models of flooding, erosion, and recovery. The resulting societal benefit will be more resilient coastal communities. The physical, biological and chemical processes impacting human and ecosystem health: Nearshore regions are used for recreation, tourism, and human habitation, and provide habitat and valuable ecosystem services. These areas must be sustained for future generations, however overall coastal water quality is declining due to microbial pathogens, fertilizers, pesticides, and heavy metal contamination, threatening ecosystem and human health. To ensure sustainable nearshore regions, predictive real-time water- and sediment-based based pollutant modeling capabilities must be developed, which requires expanding our knowledge of the physics, chemistry, and biology of the nearshore. The resulting societal benefits will include better beach safety, healthier ecosystems, and improved mitigation and regulatory policies. The scientists and engineers of the U.S. nearshore community are poised to make significant progress on these research themes, which have significant societal impact. The U.S. nearshore community, including academic, government, and industry colleagues, recommends multi-agency investment into a coordinated development of observational and modeling research infrastructure to address these themes, as discussed in the whitepaper. The observational infrastructure should include development of new sensors and methods, focused observational programs, and expanded nearshore observing systems. The modeling infrastructure should include improved process representation, better model coupling, incorporation of data assimilation techniques, and testing of real-time models. The observations will provide test beds to compare and improve models.

Report↗

USGS2009

Sidescan Sonar Imagery of the Escanaba Trough, Southern Gorda Ridge, Offshore Northern California

This map features sidescan imagery of the northern Escanaba (NESCA) site at the Escanaba Trough, southern Gorda Ridge, offshore northern California. The Escanaba Trough, a largely sediment-covered seafloor spreading center, contains at least six large massive sulfide deposits. It is a slow spreading center (2.5 cm/yr) with axial depths locally exceeding 3,300 m. Discrete igneous centers occur at 5- to 10-km intervals along this slow-spreading ridge. Basaltic magma intrudes the sediment fill of the axial valley, creating uplifted sediment hills, and, in some areas, erupts onto the sea floor. Large massive sulfide deposits occur along the margins of the uplifted sediment hills. The only active hydrothermal system is located on Central Hill where 220 deg C fluids construct anhydrite chimneys on pyrrhotite-rich massive sulfide mounds (Campbell and others, 1994). Central Hill is bounded by both ridge-parallel basement faults and a concentric set of faults that rim the top of the hill and may be associated with sill intrusion. Central Hill was one of the primary drill sites for Ocean Drilling Program (ODP) Leg 169. The sidescan sonar data (mosaics A, B, C, D) were collected aboard the National Oceanic and Atmospheric Administration (NOAA) research vessel Discoverer in the summer of 1996 with a 60-kHz system towed 100 to 200 m above the sea floor. Major faults and contacts are interpreted from the sidescan mosaics and 4.5-kHz seismic profiles collected simultaneously, as well as from previously conducted camera transects and submersible dives. The seismic profiles (lines 9, 11, 13) provide high-resolution subbottom structure and stratigraphy to a depth of about 50 m. In the sidescan images (mosaics A, B, C, D), bright areas denote high-energy returns from hard reflectors such as volcanic flows, sulfide deposits, or seafloor scarps. Dark areas denote low-energy returns and generally signify relatively undisturbed surface sediment. The grid lines mark one-minute intervals of latitude and longitude. The large sidescan sonar image (mosaic A) is centered on the NESCA igneous center. The spreading axis is flanked on either side by uplifted, sediment-covered terraces that show relatively continuous and undisturbed turbiditic sediment. These terraces bound the 4- to 5-km-wide neotectonic zone that is characterized by more closely spaced, small offset (<20 m) faults, volcanic flows (brightest area of backscatter), and areas where the seismic layering of the turbidites has been partially to completely disrupted by the intrusion of basaltic sills. The most prominent bathymetric features are the three uplifted sediment hills: Central Hill, Southwest Hill, and an unnamed uplifted hill to the north. These features are interpreted to be uplifted above large-volume basaltic intrusions emplaced near the basalt/sediment interface. Southwest Hill is adjacent to the zone of most recent faulting. This hill no longer retains the circular shape of the other hills due to slumps (lines 9, 11), which may have failed along faults related to the most recent spreading. Central Hill is interpreted to be the most recently uplifted sediment hill based on the morphology of the hill and the presence of an active hydrothermal system. The generally continuous area of volcanic basalt flow east of Central Hill appears as a distinct, bright sonar reflector stretching for approximately 6 km along axis (red contact on mosaic A). This flow may be related to the intrusion that is presumed to have uplifted Central Hill. Submersible observations indicate that lava flowed around the sediment hills and ponded against the eastern up-faulted turbidite-covered sediment terrace. Previously collected, deep-penetration seismic data indicate that the lavas overlie about 450 m of sediment (Morton and Fox, 1994). Late-stage emplacement of magma in the shallow subsurface beneath the exposed lava flow is interpreted to have domed the lava flow, forming the east-west-

Scientific Investigations Map↗

USGS2026

Vessel surveys for marine birds in the Gulf of America (Gulf of Mexico): Protocol manual (2017–2025)

This manual provides contextual background and detailed instructions for survey procedures that were used to collect, enter, archive, and analyze digitally-entered field data collected for marine birds during three large-vessel survey projects in the northern Gulf of America (also Gulf of Mexico, hereafter “Gulf”). Projects using this protocol included the Gulf of Mexico Marine Assessment Program for Protected Species (GoMMAPPS: 2017-2018), the Vessel Surveys for Abundance and Distribution of Marine Mammals and Seabirds (VSAD: 2023-2024), and certain repositioning legs of the Atlantic Marine Assessment Program for Protected Species (AMAPPS: 2021, 2023). Based substantially on Ballance and Force (2011), the protocol used in the Gulf is based on a standardized 300 m wide strip transect using software architecture available in program SeeBird (v.4.3.7), a data collection program developed by Robert Holland at the National Oceanic and Atmospheric Administration (NOAA) Southwest Fisheries Science Center, La Jolla, CA. Survey protocols relied on the digital entering of standardized metadata linked to sightings of seabirds (e.g., species, number, location, distance bin, association[s], behavior, flight direction, flight height, angle from ship, age, sex, plumage, and optional comments) as well as other protected species. SeeBird has additional modules that may be used to input data on mixed-species seabird flocks and flying fish (only the latter was used in the Gulf). SeeBird includes “user-driven” commands issued through the keyboard, touch screen, and/or mouse, many of which are aided by drop-down menus that prompt the user options that are available for input. In addition, the program features “event–driven” inputs updated at intervals selected by the user, and that also record exact time and location of such edits. We describe how SeeBird was adapted in the Gulf both to run directly via serial connections from the ship’s navigation system and to operate independently from the ship through a satellite-derived GPS feed. This user manual also gives information about: procedures used to document flying fish abundance on Gulf surveys; how to use the Beaufort scale for standardizing wind force and sea state environmental conditions; how to make and use a hand-held rangefinder for delimiting strip transect bin distances; additional functionalities in SeeBird for which user guides are not available; file-naming, file-archiving, and file location conventions used on Gulf marine bird surveys; protocols used in the Gulf for describing relative abundance of the macro-alga Sargassum as an environmental covariate; the standardized four-letter taxa codes (summarized in a SpeciesCode.txt file) used in the Gulf for denoting species, other taxonomic, and event categories as inputs to SeeBird; an Excel example spreadsheet that has successfully imported SeeBird’s ASCII text file; procedural steps to import, edit, and archive into Excel ASCII text files from SeeBird; initialization instructions for starting up program SeeBird on a Panasonic ToughBook™ that relies on integrated, satellite-derived GPS, and for writing “S” (seabirds + other taxa) and “E” (flying fish) ASCII files to a folder or subfolder other than the default root location on the laptop that contains program SeeBird; how to trouble-shoot miscellaneous start-up problems with program SeeBird; how to add new four-letter codes (into a SpeciesCode.txt file) when additional taxa or objects of interest are encountered. The primary objective of this manual is to archive a permanent, replicable history of survey methodology to facilitate continuity with comparable future projects that may be conducted in the Gulf. A secondary objective is to describe why and how program SeeBird was applied and adapted specifically for operating in Gulf survey conditions. As of late 2025, user guides for software program SeeBird were no longer readily accessible, so this manual serves also to address that gap.

Northern Gulf of America↗

USGS2011

Compilation of watershed models for tributaries to the Great Lakes, United States, as of 2010, and identification of watersheds for future modeling for the Great Lakes Restoration Initiative

As part of the Great Lakes Restoration Initiative (GLRI) during 2009–10, the U.S. Geological Survey (USGS) compiled a list of existing watershed models that had been created for tributaries within the United States that drain to the Great Lakes. Established Federal programs that are overseen by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Army Corps of Engineers (USACE) are responsible for most of the existing watershed models for specific tributaries. The NOAA Great Lakes Environmental Research Laboratory (GLERL) uses the Large Basin Runoff Model to provide data for the management of water levels in the Great Lakes by estimating United States and Canadian inflows to the Great Lakes from 121 large watersheds. GLERL also simulates streamflows in 34 U.S. watersheds by a grid-based model, the Distributed Large Basin Runoff Model. The NOAA National Weather Service uses the Sacramento Soil Moisture Accounting model to predict flows at river forecast sites. The USACE created or funded the creation of models for at least 30 tributaries to the Great Lakes to better understand sediment erosion, transport, and aggradation processes that affect Federal navigation channels and harbors. Many of the USACE hydrologic models have been coupled with hydrodynamic and sediment-transport models that simulate the processes in the stream and harbor near the mouth of the modeled tributary. Some models either have been applied or have the capability of being applied across the entire Great Lakes Basin; they are (1) the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model, which was developed by the USGS; (2) the High Impact Targeting (HIT) and Digital Watershed models, which were developed by the Institute of Water Research at Michigan State University; (3) the Long-Term Hydrologic Impact Assessment (L–THIA) model, which was developed by researchers at Purdue University; and (4) the Water Erosion Prediction Project (WEPP) model, which was developed by the National Soil Erosion Research Laboratory of the U.S. Department of Agriculture. During 2010, the USGS used the Precipitation-Runoff Modeling System (PRMS) to create a hydrologic model for the Lake Michigan Basin to assess the probable effects of climate change on future groundwater and surface-water resources. The Water Availability Tool for Environmental Resources (WATER) model and the Analysis of Flows In Networks of CHannels (AFINCH) program also were used to support USGS GLRI projects that required estimates of streamflows throughout the Great Lakes Basin. This information on existing watershed models, along with an assessment of geologic, soils, and land-use data across the Great Lakes Basin and the identification of problems that exist in selected tributary watersheds that could be addressed by a watershed model, was used to identify three watersheds in the Great Lakes Basin for future modeling by the USGS. These watersheds are the Kalamazoo River Basin in Michigan, the Tonawanda Creek Basin in New York, and the Bad River Basin in Wisconsin. These candidate watersheds have hydrogeologic, land-type, and soil characteristics that make them distinct from each other, but that are representative of other tributary watersheds within the Great Lakes Basin. These similarities in the characteristics among nearby watersheds will enhance the usefulness of a model by improving the likelihood that parameter values from a previously modeled watershed could reliably be used in the creation of a model of another watershed in the same region. The software program Hydrological Simulation Program–Fortran (HSPF) was selected to simulate the hydrologic, sedimentary, and water-quality processes in these selected watersheds. HSPF is a versatile, process-based, continuous-simulation model that has been used extensively by the scientific community, has the ongoing technical support of the U.S. Environmental Protection Agency and USGS, and provides a means to evaluate the effects that land-use changes or management practices might have on the simulated processes.

Great Lakes Basin↗

USGS2020

Total water level data from the January and March 2018 nor’easters for coastal areas of New England

During winter 2017–18 coastal areas of New England were impacted by the January 4, and March 2–4, 2018, nor’easters. The U.S. Geological Survey (USGS), under an interagency agreement with the Federal Emergency Management Agency (FEMA), collected total water level data (the combination of tide, storm surge, wave runup and setup, and freshwater input) using the North American Vertical Datum of 1988 (NAVD 88) from high-water marks and continuous water-level sensors, to better understand the areal extent, timing, and impact of coastal flooding from strong storms. During the January 4, 2018, nor’easter the National Oceanic and Atmospheric Administration (NOAA) Boston, Massachusetts, tide gage recorded the highest total water level on record of 9.66 ft. During the March 2–4, 2018, nor’easter, the Boston tide gage recorded its third highest total water level on record of 9.16 ft. After the January and March 2018 nor’easter storms, the USGS deployed field teams that identified and flagged high-water marks along the coastlines of eastern Massachusetts in January and from Portland, Maine, south to the Connecticut-New York State border in March. In preparation for the approach of the March 2018 nor’easter, the USGS deployed 35 temporary water-level sensors along the coastline of New England to collect total water level data during the storm. Total water level data were also collected at 28 tide gages and 14 coastal streamgages (affected tidally or by tidal backwater during coastal storms) in New England during both nor’easters. Total water level elevations at 71 high-water marks collected after the January 2018 nor’easter in coastal areas of eastern Massachusetts ranged from 5.8 to 15.1 feet (ft), with an average elevation of 9.4 ft and a median elevation of 9.6 ft. Total water level elevations at 10 tide gages and 7 coastal streamgages from Portland to Cape Cod Bay ranged from 4.8 to 11.2 ft, with an average of 9.1 ft and a median of 9.6 ft. Following the March 2018 nor’easter, 111 high-water marks were collected along the New England coastline. Of the 111 high-water marks, 100 were along the eastern coastline of New England from Portland to Cape Cod and had elevations that ranged from 5.3 to 15.1 ft, with an average of 8.9 ft and a median of 8.6 ft. The remaining 11 high-water marks along the southern coastline of New England in Connecticut, Rhode Island, and Massachusetts had elevations that ranged from 3.1 to 7.5 ft, with an average of 4.3 ft and a median of 4.9 ft. Total water level elevations for 19 USGS temporary water-level sensors from Portland to Cape Cod Bay ranged from 6.2 to 10.4 ft, with an average of 8.4 ft and a median of 8.7 ft. Total water level elevations at 10 tide gages and 6 coastal streamgages from Portland to Cape Cod Bay ranged from 7.8 to 10.8 ft, with an average of 9.1 ft and a median of 9.2 ft. There were 10 tide gages and 5 coastal streamgages with data from both nor’easters from Portland to Cape Cod Bay; for the January nor’easter, the average and median elevations were about 0.3 and 0.5 ft higher, respectively, than for the March nor’easter. At the 52 high-water mark locations with data for both nor’easters in Massachusetts, the average and median elevations were 0.1 and 0.4 ft higher, respectively, for the January nor’easter than for the March nor’easter. At 10 tide gages along the coastline from Portland to Cape Cod Bay, the observed peak total water level elevations for the January nor’easter ranged from 1.6 to 3.7 ft higher than the concurrent predicted elevations, with an average of 2.8 ft and a median of 3.0 ft higher. For the March nor’easter, the observed peak total water level elevations ranged from 1.8 to 4.0 ft higher than the concurrent predicted elevations, with an average of 2.7 ft and a median of 3.0 ft higher. This is approximately the amount of storm surge that was experienced during the highest tides of the two nor’easters along the coastline from Portland to Cape Cod Bay.

Connecticut, Maine, Massachusetts, New Hampshire, ↗