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At least 721 records · Page 40Linked to original sources
USGS2018

Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa

Basin-characteristic measurements related to stream length, stream slope, stream density, and stream order have been identified as significant variables for estimation of flood, flow-duration, and low-flow discharges in Iowa. The placement of channel initiation points, however, has always been a matter of individual interpretation, leading to differences in stream definitions between analysts. This study investigated five different methods to define stream initiation using 3-meter light detection and ranging (lidar) digital elevation models (DEMs) data for 17 streamgages with drainage areas less than 50 square miles within the Des Moines Lobe landform region in north-central Iowa. Each DEM was hydrologically enforced and the five stream initiation methods were used to define channel initiation points and the downstream flow paths. The five different methods to define stream initiation were tested side-by-side for three watershed delineations: (1) the total drainage-area delineation, (2) an effective drainage-area delineation of basins based on a 2-percent annual exceedance probability (AEP) 12-hour rainfall, and (3) an effective drainage-area delineation based on a 20-percent AEP 12-hour rainfall. Generalized least squares regression analysis was used to develop a set of equations for sites in the Des Moines Lobe landform region for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEPs. A total of 17 streamgages were included in the development of the regression equations. In addition, geographic information system software was used to measure 58 selected basin-characteristics for each streamgage. Results of the regression analyses of the 15 lidar datasets indicate that the datasets that produce regional regression equations (RREs) with the best overall predictive accuracy are the National Hydrographic Dataset, Iowa Department of Natural Resources, and profile curvature of 0.5 stream initiation methods combined with the 20-percent AEP 12-hour rainfall watershed delineation method. These RREs have a mean average standard error of prediction (SEP) for 4-, 2-, and 1-percent AEP discharges of 53.9 percent and a mean SEP for all eight AEPs of 55.5 percent. Compared to the RREs developed in this study using the basin characteristics from the U.S. Geological Survey StreamStats application, the lidar basin characteristics provide better overall predictive accuracy.

Iowa↗
USGS2024

Visual interpretation of high-resolution aerial imagery: A tool for land managers

Remotely sensed imagery from various collection platforms (e.g., satellites, crewed and uncrewed aircraft) are used by biologists and other conservation personnel to support management activities ranging from monitoring invasive species to assessing land cover and vegetation characteristics. Although remote sensing–based vegetation indices and models have been developed and used for some management applications, straightforward visual interpretation of imagery by on-the-ground personnel may be a pragmatic approach for obtaining time-sensitive and spatially relevant information to support and guide local management activities. Our primary objective was to qualitatively assess our ability to identify patches of target invasive plant species based on simple visual interpretation of high-resolution aerial imagery. We also sought to compare the high-resolution imagery to widely available imagery (e.g., National Agriculture Imagery Program) to determine the efficacy of each for assessing vegetation communities and land-cover features in support of management activities. To accomplish these objectives, we obtained high-resolution imagery and visually scanned and assessed the imagery by using standard geographic information system software. We were able to differentiate patches of crownvetch Securigera varia (L.) Lassen and wild parsnip Pastinaca sativa L., but not spotted knapweed Centaurea stoebe L. or leafy spurge Euphorbia esula L. The relative success in identifying these species had a relationship to plant characteristics (e.g., flower color and morphology, height), time of year (phenology), patch size and density, and potentially site characteristics such density of the underlying vegetation (e.g., grasses), substrate color characteristics (i.e., color contrast with flowers), and physical disturbance. Our straightforward, qualitative assessment suggests that visual interpretation of high-resolution imagery, but not some lower-resolution imagery, may be an efficient and effective tool for supporting local invasive species management through activities such as monitoring known patches, identifying undetected infestations, assessing management actions, guiding field work, or prioritizing on-the-ground monitoring activities.

Journal of Fish and Wildlife Management↗
USGS2015

An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States

Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The US Geological Survey (USGS) is exploring methods to automate generalization of features in the National Hydrography Data set (NHD), to associate specific sequences of processing operations and parameters with specific landscape characteristics, thus obviating manual selection of a unique processing strategy for every NHD watershed unit. A chronology of methods to delineate physiographic regions for the United States is described, including a recent maximum likelihood classification based on seven input variables. This research compares unsupervised and supervised algorithms applied to these seven input variables, to evaluate and possibly refine the recent classification. Evaluation metrics for unsupervised methods include the Davies–Bouldin index, the Silhouette index, and the Dunn index as well as quantization and topographic error metrics. Cross validation and misclassification rate analysis are used to evaluate supervised classification methods. The paper reports the comparative analysis and its impact on the selection of landscape regions. The compared solutions show problems in areas of high landscape diversity. There is some indication that additional input variables, additional classes, or more sophisticated methods can refine the existing classification.

Cartography and Geographic Information Science↗
USGS2015

Groundwater data network interoperability

Water data networks are increasingly being integrated to answer complex scientific questions that often span large geographical areas and cross political borders. Data heterogeneity is a major obstacle that impedes interoperability within and between such networks. It is resolved here for groundwater data at five levels of interoperability, within a Spatial Data Infrastructure architecture. The result is a pair of distinct national groundwater data networks for the United States and Canada, and a combined data network in which they are interoperable. This combined data network enables, for the first time, transparent public access to harmonized groundwater data from both sides of the shared international border.

Journal of Hydroinformatics↗
USGS2012

Data resources for the Wyoming Landscape Conservation Initiative (WLCI) Integrated Assessment (IA)

The data contained in this report were compiled, modified, and analyzed for the Wyoming Landscape Conservation Initiative (WLCI) Integrated Assessment (IA). The WLCI is a long-term science based effort to assess and enhance aquatic and terrestrial habitats at a landscape scale in southwest Wyoming while facilitating responsible energy development through local collaboration and partnerships. The IA is an integrated synthesis and analysis of WLCI resource values based on best available data and information collected from multiple agencies and organizations. It is a support tool for landscape-scale conservation planning and evaluation, and a data and analysis resource that can be used for addressing specific management questions. The IA analysis was conducted using a Geographic Information System in a raster (that is, a grid) environment using a cell size of 30 meters. To facilitate the interpretation of the data in a regional context, mean values were summarized and displayed at the subwatershed unit (WLCI subwatersheds were subset from the National Hydrography Dataset, Hydrologic Unit Code 12/Level 6). A dynamic mapping platform, accessed via the WLCI webpage at http://www.wlci.gov is used to display the mapped information, and to access underlying resource values that were combined to produce the final mapped results. The raster data used in the IA are provided here for use by interested parties to conduct additional analyses and can be accessed via the WLCI webpage. This series contains 74 spatial data sets: WLCI subwatersheds (vector) and 73 geotiffs (raster) that are segregated into the major categories of Multicriteria Index (including Resource Index and Condition), Change Agents, and Future Change. The Total Multicriteria Index is composed of the Aquatic Multicriteria Index and the Terrestrial Multicriteria Index. The Aquatic Multicriteria Index is composed of the Aquatic Resource Index and the Aquatic Condition. The Aquatic Resource Index is composed of the following components: Groundwater, Special Management Areas, and Priority Areas. The Aquatic Condition is composed of the following components: Focal Species, Species of Concern, Focal Ecosystems, and Proper Functioning Condition. The Terrestrial Multicriteria Index is composed of the Terrestrial Resource Index and the Terrestrial Condition. The Terrestrial Resource Index is composed of the following components: Special Management Areas, Agriculture, and Priority Areas. The Terrestrial Condition is composed of the following components: Focal Species, Big Game, Species of Concern, Rare Plants, and Focal Ecosystems. The Change Agents are composed the following components: Roads, Energy, Mines, and Urban. The Future Change is composed of the following components: Oil-Gas-Coal, Wind, Minerals, Climate-Temperature, Invasive Species, and Urban.

Wyoming↗
USGS2004

Geographic Information Office, Information Technology Office

The Geographic Information Office, Information Technology Office (ITO), operating under the Chief Technology Officer, directs the management of U.S. Geological Survey (USGS) information technology (IT) networks and systems supporting the telecommunications, computing, software applications management, and information technology security. The ITO supports IT activities across the nation and works closely with the Department of the Interior's (DOI), Office of the Chief Information Officer. For more information about ITO activities contact: Kevin Gallagher: Chief Technology Officer, Crystal Wilson: Administrative Assistant, Faye Lee: Senior Staff Assistant.

Fact Sheet↗
USGS2001

Hydrologic data and a proposed water-quality monitoring network for the Kobuk River basin, Gates of the Arctic National Park and Preserve, and Kobuk Valley National Park, Alaska

Located in northwestern Alaska, the Kobuk River drains a watershed of approximately 12,300 square miles. Two national parks are located in the basin: the entire Kobuk Valley National Park and and a portion of Gates of the Arctic National Park and Preserve. Reconnaissance-type water-quality data collected on the Kobuk River and some of its tributaries indicate that the water is of a calcium to calcium-magnesium-bicarbonate type. To design a representative water-quality monitoring network, a geographical information system (GIS) of the Kobuk River Basin was created. The GIS was used with a statistical technique, cluster analysis, to stratify the Kobuk River Basin into different regions. Potential water-quality monitoring sites were then selected from these regions.

Alaska↗
USGS2016

A GIS model of habitat suitability for Solanum conocarpum (Solanaceae) in St. John, US Virgin Islands

Solanum conocarpum (Solanaceae) (Marron Bacora) is a rare, dry-forest shrub endemic to the island of St. John, US Virgin Islands, considered for listing under the Endangered Species Act. Given its status as a species of conservation concern, we incorporated environmental characteristics of 3 observed populations and 5 additional known locations into a geographic information system (GIS) analysis to create a habitat-suitability model for the species on the island of St. John. Our model identified 1929.87 ha of highly suitable and moderately suitable habitat. Of these, 1161.20 ha (60.2%) occurred within the boundaries of Virgin Islands National Park. Our model provides spatial information on potential locations for future surveys and restoration sites for this endemic species of the US Virgin Islands.

Caribbean Naturalist↗
USGS2002

U.S. Geological Survey 2002 petroleum resource assessment of the National Petroleum Reserve in Alaska (NPRA): play maps and technically recoverable resource estimates

This report provides a summary of the estimated volume of technically recoverable undiscovered oil and nonassociated gas resources for each of the 24 plays evaluated in the U.S. Geological Survey 2002 petroleum resource assessment of the NPRA (Bird and Houseknecht, 2002). It also provides a set of illustrations showing the stratigraphic and geographic location of each play. Additional details of this assessment will follow in later publications.

Alaska↗
USGS2002

Geologic information for aggregate resource planning

Construction and maintenance of the infrastructure is dependent on such raw materials as aggregate (crushed stone, sand, and gravel). Despite this dependence, urban expansion often works to the detriment of the production of those essential raw materials. The failure to plan for the protection and extraction of aggregate resources often results in increased consumer cost, environmental damage, and an adversarial relation between the aggregate industry and the community. As an area grows, the demand for aggregate resources increases, and industries that produce these materials are established. Aggregate is a low-cost commodity, and to keep hauling costs at a minimum, the operations are located as close to the market as possible. As metropolitan areas grow, they encroach upon established aggregate operations. New residents in the vicinity of pits and quarries object to the noise, dust, and truck traffic associated with the aggregate operation. Pressure is applied to the local government to limit operation hours and truck traffic. In addition to encroaching on established aggregate operations, urban growth commonly covers unmined aggregate resources. Frequently urban growth occurs without any consideration of the resource or an analysis of the impact of its loss. The old idea that aggregate resources can be found anywhere is false. New aggregate operations may have to be located long distances from the markets. The additional expense of the longer transport of resources must be passed on to consumers in the community. In many instances, the new deposit is of inferior quality compared with the original source, yet it is used to avoid the expense of importing high-quality material from a more-distant source. Some governmental, including city, provincial or state, and national, agencies, have enacted regulations to help maintain access to prime aggregate resources. Although regulations have met with variable success, some policy or regulation to protect aggregate resources is worth consideration. A basic requirement of any aggregate resource policy or regulation is the knowledge of the geographic distribution, volumes, and quality of aggregate resources. This knowledge commonly is obtained through geologic mapping and characterization of aggregate resources. Geographic Information Systems (GIS) and Decision Support Systems (DSS) provide excellent tools to help present and evaluate the information in a manner that is understandable by public decisionmakers.

Book chapter↗
USGS2022

The Volcano Hazards Program — Strategic science plan for 2022–2026

The U.S. Geological Survey (USGS) Volcano Hazards Program (VHP) Strategic Science Plan, developed through discussion with scientists-in-charge of the USGS volcano observatories and the director of the USGS Volcano Science Center, specifies six major strategic goals to be pursued over the next 5 years. The purpose of these goals is to help fulfill the USGS VHP mission to enhance public safety and to minimize social and economic disruption caused by volcanic eruptions in the United States and its territories, through delivery of effective forecasts, warnings, and information on volcano hazards based on scientific understanding of volcanic processes. These six major strategic goals are to (1) continue—and when possible, accelerate—implementation of the National Volcano Early Warning System (NVEWS); (2) improve community preparedness for volcanic hazards by updating and standardizing essential components of volcano hazard assessments and providing training to land managers, emergency responders, and State and local communities; (3) develop the next generation of volcano hazard assessments using geographic information systems and other digital tools; (4) make observations with new instrumentation and take advantage of advances in real-time gas sensors; (5) rebuild the Hawaiian Volcano Observatory and its monitoring capabilities; and (6) form new partnerships and strengthen existing partnerships with other government agencies and with academia and industry, to advance volcano monitoring, increase understanding of volcanic processes, and disseminate USGS information. In its effort to advance volcano science and monitoring techniques, the VHP has identified six scientific targets to pursue over the next 5 years, including: (1) increased understanding of volcano seismicity; (2) improved probabilistic forecasting; (3) deepened grasp of volcano eruption histories and geochronology; (4) newly developed and refined physical models of magmatic systems, leading to better situational awareness and accuracy of eruption forecasts; (5) improved warnings and forecasts of volcanic ash and gas clouds and characterization of volcanic smog sources; and (6) refined lava-flow modeling and forecasting of lava-flow paths.

Circular↗
USGS2003

Crater Lake revealed

Around 500,000 people each year visit Crater Lake National Park in the Cascade Range of southern Oregon. Volcanic peaks, evergreen forests, and Crater Lake’s incredibly blue water are the park’s main attractions. Crater Lake partially fills the caldera that formed approximately 7,700 years ago by the eruption and subsequent collapse of a 12,000-foot volcano called Mount Mazama. The caldera-forming or climactic eruption of Mount Mazama drastically changed the landscape all around the volcano and spread a blanket of volcanic ash at least as far away as southern Canada. Prior to the climactic event, Mount Mazama had a 400,000 year history of cone building activity like that of other Cascade volcanoes such as Mount Shasta. Since the climactic eruption, there have been several less violent, smaller postcaldera eruptions within the caldera itself. However, relatively little was known about the specifics of these eruptions because their products were obscured beneath Crater Lake’s surface. As the Crater Lake region is still potentially volcanically active, understanding past eruptive events is important to understanding future eruptions, which could threaten facilities and people at Crater Lake National Park and the major transportation corridor east of the Cascades. Recently, the lake bottom was mapped with a high-resolution multibeam echo sounder. The new bathymetric survey provides a 2m/pixel view of the lake floor from its deepest basins virtually to the shoreline. Using Geographic Information Systems (GIS) applications, the bathymetry data can be visualized and analyzed to shed light on the geology, geomorphology, and geologic history of Crater Lake.

Oregon↗
USGS2018

Flood-inundation maps for the Withlacoochee River From Skipper Bridge Road to St. Augustine Road, within the City of Valdosta, Georgia, and Lowndes County, Georgia

Digital flood-inundation maps for a 12.6-mile reach of the Withlacoochee River from Skipper Bridge Road to St. Augustine Road (Georgia State Route 133) were developed to depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey (USGS) streamgage at Withlacoochee River at Skipper Bridge Road, near Bemiss, Ga. (023177483). Real-time stage information from this streamgage can be used with these maps to estimate near real-time areas of inundation. The forecasted peak-stage information for the USGS streamgage at Withlacoochee River at Skipper Bridge Road, near Bemiss, Ga. (023177483), can be used in conjunction with the maps developed for this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers Hydrologic Engineer-ing Center’s River Analysis System (HEC–RAS) software for the Withlacoochee River and was used to compute flood profiles for a 12.6-mile reach of the Withlacoochee River. The hydraulic model was then used to simulate 23 water-surface profiles at 1.0-foot (ft) intervals at the Withlacoochee River near the Bemiss streamgage. The profiles ranged from the National Weather Service action stage of 10.7 ft, which is 131.0 ft above the North American Vertical Datum of 1988 (NAVD 88), to a stage of 32.7 ft, which is 153.0 ft above NAVD 88. The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from light detection and ranging (lidar) data having a 4.0-ft horizontal resolution—to delineate the area flooded at each 1.0-ft interval of stream stage.

Georgia↗
USGS2013

New distribution record for the rare limpet Acroloxus coloradensis (Henderson, 1930) (Gastropoda: Acroloxidae) from Montana

The Rocky Mountain Capshell, Acroloxus coloradensis (Henderson, 1930), the only North American member of the basommatophoran family Acroloxidae, is broadly distributed across southern Canada and south into the Rocky Mountains in the USA (Turgeon et al., 1998; Lee and Ackerman, 2000). Despite its wide geographic range, A. coloradensis has been documented from < 30 locations, mostly in British Columbia, Alberta, Ontario, and Quebec (Lee and Ackerman, 2000; Anderson, 2005). Relict populations of A. coloradensis in the USA have been documented from only 6 sites in Colorado and 2 sites in Glacier National Park (Glacier NP), Montana (Anderson, 2005; Ellis et al., 2004). In Glacier NP, A. coloradensis was first reported from Lost Lake (Figure 1; Russell and Brunson, 1967). A second population in the park was discovered in Trout Lake in 2001 (Ellis et al., 2004). In both lakes, A. coloradensis was found primarily under rocks and other cover objects.

Montana↗
USGS2017

A synthesis of living shoreline perspectives

The main goal of this summary chapter is to synthesize author perspectives across the contributed chapters, make recommendations on the correct usage of the term living shorelines, and offer guidance for planning in the future. Nature-based approaches are being applied globally, as signified by the breadth of geographic coverage in this book. The author’s institutions and locations of study span the East, Gulf, and West Coasts of the United States, including the states of Massachusetts, New York, New Jersey, Maryland, Virginia, North Carolina, Florida, Alabama, Mississippi, Louisiana, Texas, California, Washington, and several national perspectives, including Hawaii; British Columbia in Canada; the Netherlands, as well as perspectives across Europe also including Belgium, Denmark, France, Germany, Spain, and the United Kingdom; Sydney Harbor in Australia; and Belize. Living shoreline techniques are very diverse and practices can vary by region, salinity and tidal regime, and degrees of natural and artificial components. Techniques covered in this book include restoring oyster reefs, eelgrass, and mangroves, planting marshes with and without supportive sills (e.g., stone, oyster shell bags, coir logs), incorporating structures such as logs and reef balls, nourishing beaches and dunes with sediment, engineering habitat features into seawalls, and managed realignment. All of these can have a variety of components, such as permitting, land acquisition, design, and monitoring. However, given the diverse representation, there are some shared commonalities that can help inform and direct shoreline management moving forward.

Book chapter↗
USGS2003

Status and interconnections of selected environmental issues in the global coastal zones

This study focuses on assessing the state of population distribution, land cover distribution, biodiversity hotspots, and protected areas in global coastal zones. The coastal zone is defined as land within 100 km of the coastline. This study attempts to answer such questions as: how crowded are the coastal zones, what is the pattern of land cover distribution in these areas, how much of these areas are designated as protected areas, what is the state of the biodiversity hotspots, and what are the interconnections between people and coastal environment. This study uses globally consistent and comprehensive geospatial datasets based on remote sensing and other sources. The application of Geographic Information System (GIS) layering methods and consistent datasets has made it possible to identify and quantify selected coastal zones environmental issues and their interconnections. It is expected that such information provide a scientific basis for global coastal zones management and assist in policy formulations at the national and international levels.

Ambio↗
USGS2008

Potential environmental contaminant risks to avian species at important bird areas in the northeastern United States

Environmental contaminants can have profound effects on birds, acting from the molecular through population levels of biological organization. An analysis of potential contaminant threats was undertaken at 52 Important Bird Areas (IBAs) within the northeastern Atlantic coast drainage. Using geographic information system methodology, data layers describing or integrating contamination (impaired waters, fish or wildlife consumption advisories, toxic release inventory sites, and estimates of pesticide use) were overlaid on buffered IBA boundaries, and the relative threat at each site was ranked. The most threatened sites include Jefferson National Forest (NF), Stewart B. McKinney National Wildlife Refuge (NWR), Great Dismal Swamp NWR, Blue Ridge Parkway, Shenandoah National Park (NP), Adirondack Park, Edwin B. Forsythe NWR, George Washington NF, Green Mountain NF, Long Island Piping Plover Beaches, and Merrymeeting Bay. These sites exhibited moderate to high percentages of impaired waters and had fish consumption advisories related to mercury and polychlorinated biphenyls, and were located in counties with substantial pesticide use. Endangered, threatened and Watch List bird species are present at these sites. The Contaminant Exposure and Effects--Terrestrial Vertebrates database was searched within buffered IBA boundaries, and for a moderate number of sites there was concordance between the perceived risk and contaminant exposure. Several of the IBAs with apparently substantial contaminant threats had no avian ecotoxicological data (e.g., George Washington NF, Shenandoah NP). Based upon this screening level risk assessment, contaminant biomonitoring is warranted at such sites, and data generated from these efforts should foster natural resource management activities.

Integrated Environmental Assessment and Management↗
USGS2008

Sediment deposition, erosion, and bathymetric change in central San Francisco Bay: 1855-1979

Central San Francisco Bay is the hub of a dynamic estuarine system connecting the San Joaquin and Sacramento River Deltas, Suisun Bay, and San Pablo Bay to the Pacific Ocean and South San Francisco Bay. To understand the role that Central San Francisco Bay plays in sediment transport throughout the system, it is necessary to first determine historical changes in patterns of sediment deposition and erosion from both natural and anthropogenic forces. The first extensive hydrographic survey of Central San Francisco Bay was conducted in 1853 by the National Ocean Service (NOS) (formerly the United States Coast and Geodetic Survey (USCGS)). From 1894 to 1979, four additional surveys, composed of a total of approximately 700,000 bathymetric soundings, were collected within Central San Francisco Bay. Converting these soundings into accurate bathymetric models involved many steps. The soundings were either hand digitized directly from the original USCGS and NOS hydrographic sheets (H-sheets) or obtained digitally from the National Geophysical Data Center's (NGDC) Geophysical Data System (GEODAS) (National Geophysical Data Center, 1996). Soundings were supplemented with contours that were either taken directly from the H-sheets or added in by hand. Shorelines and marsh areas were obtained from topographic sheets. The digitized soundings, depth contours, shorelines, and marsh areas were entered into a geographic information system (GIS) and georeferenced to a common horizontal datum. Using surface modeling software, bathymetric grids with a horizontal resolution of 25 m were developed for each of the five hydrographic surveys. Before analyses of sediment deposition and erosion were conducted, interpolation bias was removed and all of the grids were converted to a common vertical datum. These bathymetric grids were then used to develop bathymetric change maps for subsequent survey periods and to determine long-term changes in deposition and erosion by calculating volumes and rates of net sediment change. Central San Francisco Bay experienced periods of both deposition and erosion, but overall experienced a net gain in sediment from 1855 to 1979 of approximately 42x10 6 m 3 (0.33x10 6 m 3 / yr). Over this same time period, 92 percent of the tidal marsh and 69 percent of the intertidal mudflats were lost as human activity increased and the shorefront was developed. During the first time period, from 1855 to 1895, Central San Francisco Bay was erosional, losing roughly 2x10 6 m 3 / yr of sediment. The next time period was depositional, with a net gain of approximately 3x10 6 m 3 / yr of sediment from 1895 to 1947. The last time period, from 1947 to 1979, was erosional again, losing roughly 2x10 6 m 3 / yr of sediment. Sedimentation patterns also varied spatially. The northern part of Central San Francisco Bay was depositional during all change periods while the eastern region alternated between erosional and depositional. Central San Francisco Bay sedimentation patterns have also been strongly impacted by anthropogenic activities, such as dredging and dredge disposal, borrow pits, and sand mining. For example, bathymetric change at a borrow pit created near Bay Farm Island sometime between the 1947 and 1979 surveys indicates roughly 25x10 6 m 3 of sediment was removed from the system

California↗