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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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California's Central Valley ranges from the mountain fronts toward a central trough, mainly defined by the San Joaquin and Sacramento Rivers, and the relative distance from trough to valley edges is of interest. This data release provides supplemental data for the USGS Professional Paper 1766, titled Groundwater Availability of the Central Valley Aquifer, California and provides geographic information systems (GIS) datasets containing this relative distance grid and supporting data. Included in this data release are shapefiles used to define the Central Valley study area, the Central Valley trough, and a relative distance grid that may be used to spatially define other GIS data into zones between the edge of the...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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The U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management, used streamflow measurements at 11 partial-record sites and related them to nearby USGS or Idaho Power Company real-time streamgages (index sites) to provide daily mean streamflow values at ungaged (partial-record) sites within the Wild and Scenic River of the Owyhee Canyonlands Wilderness, Idaho. Daily mean streamflow was estimated by developing a regression relationship between streamflow at each partial-record site and the index site for the period of record of the index site. The regressions are then used to estimate annual and semimonthly 20-, 50-, and 80-percent exceedance probability streamflow statistics at each partial-record...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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The U.S. Geological Survey, in cooperation with the California Department of Water Resources (DWR), has constructed a new spatially distributed Precipitation-Runoff Modeling System (PRMS) for the Merced River Basin (Koczot and others, 2021), which is a tributary of the San Joaquin River in California. PRMS is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of streamflow and basin hydrology to various combinations of climate and land use (Markstrom and others, 2015). Although further refinement may be required to apply the Merced PRMS for official streamflow forecast operations, this application of PRMS is calibrated with intention to simulate (and...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service, Shapefile; Tags: California, Climate, Climatology, Draper Climate-Distribution Software (Draper), Geography, All tags...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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This data set consists of a polygon representing the study area for Paradise Valley, Humboldt County, Nevada as published in the U.S. Geological Survey Professional Paper 1409-F titled "Ground-water flow and simulated effects of development in Paradise Valley, a basin tributary to the Humboldt River in Humboldt County, Nevada," 1996.
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...


map background search result map search result map Archive of Merced River Basin Precipitation-Runoff Modeling System, with forecasting, climate-file preparation, and data-visualization tools Study area, Paradise Valley, Humboldt County, Nevada (U.S. Geological Survey Professional Paper 1409-F) shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cedar Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Edwin B. Forsythe NWR, NJ, 2010 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2010 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2012 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Parker River, MA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cape Lookout, NC, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cape Hatteras, NC, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Rhode Island National Wildlife Refuge, RI, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assateague Island, MD & VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assawoman Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cobb Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Metompkin Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Myrtle Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Parramore Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Wreck Island, VA, 2014 Streamflow regressions and annual and semimonthly exceedance probability statistics for wild and scenic rivers, Owyhee Canyonlands Wilderness, Idaho 1:24,000-scale hydrographic areas, Walker River Basin, California and Nevada Relative distance of California's Central Valley from trough to valley edge and supporting data shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Wreck Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Myrtle Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cobb Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Metompkin Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assawoman Island, VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Edwin B. Forsythe NWR, NJ, 2010 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2012 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2010 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Rhode Island National Wildlife Refuge, RI, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assateague Island, MD & VA, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cape Lookout, NC, 2014 Study area, Paradise Valley, Humboldt County, Nevada (U.S. Geological Survey Professional Paper 1409-F) shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cape Hatteras, NC, 2014 Archive of Merced River Basin Precipitation-Runoff Modeling System, with forecasting, climate-file preparation, and data-visualization tools 1:24,000-scale hydrographic areas, Walker River Basin, California and Nevada Streamflow regressions and annual and semimonthly exceedance probability statistics for wild and scenic rivers, Owyhee Canyonlands Wilderness, Idaho Relative distance of California's Central Valley from trough to valley edge and supporting data