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This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Beaches,
CMHRP,
Central California,
Central California Coast,
Climate change,
This dataset contains projections for Monterey County. CoSMoS makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.1 for Central California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Data for Central California covers the coastline from Pt. Conception to Golden Gate Bridge. Methods and...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Beaches,
CMHRP,
Central California,
Central California Coast,
Climate change,
This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Beaches,
CMHRP,
Central California,
Central California Coast,
Climate change,
This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Beaches,
CMHRP,
Central California,
Central California Coast,
Climate change,
This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Beaches,
CMHRP,
Central California,
Central California Coast,
Climate change,
This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Beaches,
CMHRP,
Central California,
Central California Coast,
Climate change,
This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions) and simulated...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Beaches,
CMHRP,
Central California,
Central California Coast,
Climate change,
This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average atmospheric conditions)...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Beaches,
CMHRP,
Central California,
Central California Coast,
Climate change,
This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Beaches,
CMHRP,
Central California,
Central California Coast,
Climate change,
This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate bridge. Outputs include SLR scenarios of 0.0, 0.25, 0.5, 0.75, 1.0, 1.5, 2.0, 2.5, 3.0, and 5.0 meters; storm scenarios include background conditions (astronomic spring tide and average...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Beaches,
CMHRP,
Central California,
Central California Coast,
Climate change,
Situated in a remote corner of northwestern New Mexico, Chaco Culture National Historical Park (CCNHP) was once the center of a sophisticated social, political and architectural civilization with a 50,000-square mile sphere of influence. The park protects the greatest concentration of Chacoan historical sites in the American Southwest and is arguably the most significant prehistoric site in North America. Following decades of unsuccessful attempts to develop usable near-surface water sources, the National Park Service constructed a 3,100-foot deep well into the Gallup Sandstone aquifer in 1972, providing the park with the first reliable drinking water source since it was established in 1907. The ~100-foot thick...
This data release provides source code and an R workspace with functions comprising a non-linear baseflow separation model, calibrated values of parameters and estimates of the baseflow component of daily streamflow at selected streamflow gages. Parameter values were determined by calibration of the model. Estimates of the baseflow component include daily values and the total baseflow as a fraction of streamflow for the analysis period. The file 'run_bf_sep.zip' in the directory 'Nonlinear Baseflow Model Source Code, Functions, and Scripts" has a complete set of model functions, parameters for 13,208 USGS streamflow gages, and a script to run the model. Instructions and software requirements for running the model...
Categories: Data,
Data Release - Revised;
Tags: USGS Science Data Catalog (SDC),
United States,
baseflow,
hydrograph separation,
mathematical modeling,
Site-specific parameters for a non-linear baseflow separation model determined by automated calibration to maximize baseflow. The file "bf_param_usgs.csv" has parameter values for 13,208 sites where USGS operated a streamflow gage and calculated daily streamflow for at least 300 days from water year 1981 to 2020. The file "bf_param_wa_ecy.csv" has parameter values for 41 sites where the Washington Department of Ecology operated a streamflow gage from water year 1991 to 2019. The parameters may need to be re-calibrated at a site for some applications.
Categories: Data;
Tags: United States,
baseflow,
hydrograph separation,
mathematical modeling,
streamflow
This data release contains monthly 270-meter resolution Basin Characterization Model (BCMv8) climate and hydrologic variables for Localized Constructed Analog (LOCA; Pierce et al., 2014)-downscaled GFDL-CM3 Global Climate Model (GCM) for Representative Concentration Pathway (RCP) 4.5 (medium-low emissions) and 8.5 (high emissions) for hydrologic California. The LOCA climate scenarios span water years 1950 to 2099 with greenhouse-gas forcings beginning in 2006. The LOCA downscaling method has been shown to produce better estimates of extreme events and reduces the common downscaling problem of too many low-precipitation days (Pierce et al., 2014). Ten GCMs were selected from the full ensemble of models from the fifth...
The data includes dates, places, and times of sampling events for eggs and larvae of invasive Grass Carp (Ctenopharyngodon idella) in tributaries to Lake Erie between 2015 and 2020. Reference data on locations and dates sampled, gears used, and effort are included. Developmental stages for a subset of undamaged, fertilized eggs are provided. Tables include common fields to allow for integration into a relational database to aid data extraction and associating data among tables.
This data release contains output and components of the initial conterminous United States (CONUS) application of the Precipitation-Runoff Modeling System (PRMS) as implemented in the National Hydrologic Model (NHM) infrastructure (Regan et al, 2018). The PRMS version 5.0.0 hydrologic simulation code was used with the accompanying parameter files in the NHM infrastructure to produce the attached output files. Model input climate drivers include climate data derived from the Daymet gridded data set version 2 (Thornton et al., 2014) with values spatially-distributed to the HRUs using the USGS Geo Data Portal (https://cida.usgs.gov/gdp/; Blodgett et al., 2011). The parameter values are maintained in the National Hydrologic...
Categories: Data;
Tags: Hydrologic processes,
Hydrology,
Mathematical modeling,
United States,
Visualization methods
Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including specific conductance (SC), total dissolved solids (TDS), and chloride (Cl) concentrations—across three drinking-water aquifers of the Mississippi embayment. A ML approach was used because it accommodates a large and diverse set of explanatory variables, does not assume monotonic relations between predictors and response data, and results can be extrapolated to areas of the aquifer not sampled. These aspects of ML allowed potential drivers and sources of high salinity water that have been hypothesized in other studies to...
ABSTRACT: The Upper Colorado River Basin contains appreciable amounts of undeveloped fuel resources. Large quantities of oil shale, coal, and uranium have attracted recent economic and commercial interests. Development of these resources and subsequent conversion to alternative energy forms require an adequate supply of water. Water use for large scale energy development will place increasing demands on an already overstressed allocation of Colorado River water. Present water quality is at a concentration where increased salinity will result in economic detriments to holders of downstream water rights. The salt and water exchange in mining, processing, and spent fuel disposal processes has been incorporated as part...
Categories: Publication;
Types: Citation;
Tags: coal,
energy development,
mathematical modeling,
oil shale,
optimization,
These data were compiled to explore the foraging ecology of Rainbow Trout (Oncorhynchus mykiss) in the Colorado River, Grand Canyon, Arizona. These data represent samples characterizing the availability of drifting invertebrate prey (hereafter, drift) and use of these invertebrate prey by rainbow trout determined by gut samples (hereafter, diets). Drift and diet sampling occurred in five distinct reaches downstream of Glen Canyon Dam (river kilometer (rkm) from the dam): (I) rkm 16.3-21.7; (II) rkm 52.8-58.3; (III) rkm 86.6-91.9; (IV) rkm 122.0-123.6; and (V) rkm 127.1-129.6. Samples were taken on 12 trips in April, July, September and January from April 2012 through January 2015. The aquatic prey base consists...
Categories: Data;
Tags: Aquatic Biology,
Arizona,
Bayesian discrete choice model,
Colorado River,
Ecology,
Groundwater is a vital resource to the Mississippi embayment region of the central United States. Regional and integrated assessments of water availability that link physical flow models and water quality in principal aquifer systems provide context for the long-term availability of these water resources. An innovative approach using machine learning was employed to predict groundwater pH across drinking water aquifers of the Mississippi embayment. The region includes two principal regional aquifer systems; the Mississippi River Valley alluvial (MRVA) aquifer and the Mississippi embayment aquifer system that includes several regional aquifers and confining units. Based on the distribution of groundwater use for...
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