Data and Tools

Science Datasets

The data collected and the techniques used by USGS scientists should conform to or reference national and international standards and protocols if they exist and when they are relevant and appropriate. For datasets of a given type, and if national or international metadata standards exist, the data are indexed with metadata that facilitates access and integration.

Filter Total Items: 9,328
Date published: December 31, 2019

Microplastics in Lake Mead National Recreation Area, 2017-2018: U.S. Geological Survey data release

This dataset describes the quantity and morphology of microplastics in water, surficial sediment, sediment core, fish, and shellfish samples from Lake Mead National Recreation Area (Nevada/Arizona). Water and surficial sediment samples were collected once at 9 locations. A sediment core (33 cm long) was extracted from Las Vegas Bay to assess changes in microplastic deposition over time....

Date published: October 21, 2019

Data Release: The effects of wildfire on snow water resources estimated from canopy disturbance patterns and meteorological conditions

These are Snow Water Equivalent (SWE) SnowPALM model output data for an area in the Valles Caldera, northern New Mexico. These pre-fire model output data are intended to accompany a published report (The effects of wildfire on snow water resources estimated from canopy disturbance patterns and meteorological conditions [Moeser, Broxton and Harpold, 2019]). All data are in a gridded format...

Date published: October 21, 2019

Chesapeake Bay Nontidal Network 1985-2017: WRTDS input data

Nitrogen, phosphorus, and suspended-sediment loads, and changes in loads, in major rivers across the Chesapeake Bay watershed have been calculated using monitoring data from the Chesapeake Bay River Input Monitoring Network (RIM) stations for the period 1985 through 2017. Nutrient and suspended-sediment loads and changes in loads were determined by applying a weighted regression approach...

Date published: October 21, 2019

CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in San Francisco County

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...

Date published: October 21, 2019

Data Release: The effects of wildfire on snow water resources estimated from canopy disturbance patterns and meteorological conditions

These are model input and comparative data derived from post-fire aerial LiDAR acquired in May 2012 for a small basin in the Valles Caldera, Northern New Mexico to represent canopy characteristics post-fire. These characteristics include, (1) canopy closure, (2) edginess to the north, (3) edginess to the south, (4) leaf area index, (5) maximum tree height, (6) mean distance to canopy, (7) mean...

Date published: October 21, 2019

Chesapeake Bay River Input Monitoring Network 1985-2017: Average annual yields

Nitrogen, phosphorus, and suspended-sediment loads, and changes in loads, in major rivers across the Chesapeake Bay watershed have been calculated using monitoring data from the Chesapeake Bay River Input Monitoring Network (RIM) stations for the period 1985 through 2017. Nutrient and suspended-sediment loads and changes in loads were determined by applying a weighted regression approach...

Date published: October 21, 2019

CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in San Francisco County

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...

Date published: October 21, 2019

Data Release: The effects of wildfire on snow water resources estimated from canopy disturbance patterns and meteorological conditions

These are model input and comparative data derived from pre-fire aerial LiDAR acquired in May 2012 for a small basin in the Valles Caldera, Northern New Mexico to represent canopy characteristics pre-fire. These characteristics include, (1) canopy closure, (2) edginess to the north, (3) edginess to the south, (4) leaf area index, (5) maximum tree height, (6) mean distance to canopy, (7) mean...

Date published: October 21, 2019

Chesapeake Bay River Input Monitoring Network 1985-2017: Annual loads

Nitrogen, phosphorus, and suspended-sediment loads, and changes in loads, in major rivers across the Chesapeake Bay watershed have been calculated using monitoring data from the Chesapeake Bay River Input Monitoring Network (RIM) stations for the period 1985 through 2017. Nutrient and suspended-sediment loads and changes in loads were determined by applying a weighted regression approach...

Date published: October 21, 2019

Data Release: The effects of wildfire on snow water resources estimated from canopy disturbance patterns and meteorological conditions

These are Snow Water Equivalent (SWE) SnowPALM model output data for an area in the Valles Caldera, northern New Mexico. These pre-fire model output data are intended to accompany a published report (The effects of wildfire on snow water resources estimated from canopy disturbance patterns and meteorological conditions [Moeser, Broxton and Harpold, 2019]). All data are in a gridded format...

Date published: October 21, 2019

Chesapeake Bay River Input Monitoring Network 1985-2017: Monthly loads

Nitrogen, phosphorus, and suspended-sediment loads, and changes in loads, in major rivers across the Chesapeake Bay watershed have been calculated using monitoring data from the Chesapeake Bay River Input Monitoring Network (RIM) stations for the period 1985 through 2017. Nutrient and suspended-sediment loads and changes in loads were determined by applying a weighted regression approach...

Date published: October 21, 2019

CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in San Francisco County

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...