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Nitrogen Concentrations and Loads and Seasonal Nitrogen Loads in Selected Long Island Sound Tributaries, Water Years 1995-2021 (ver. 1.1, February 2024)

This U.S. Geological Survey (USGS) data release presents tabular data on nitrogen concentrations and loads for multiple nitrogen species, and river discharge data used in the analysis of data collected from October 1994 to September 2021. Data on flow and nitrogen concentrations were analyzed using the USGS Exploration and Graphics for RivEr Trends (EGRET) R package, and the method of Weighted Reg

Harmonized continuous water quality data in support of modeling harmful algal blooms in the United States, 2005 - 2022

Harmful algal blooms (HABs) are overgrowths of algae or cyanobacteria in water and can be harmful to humans and animals directly via toxin exposure or indirectly via changes in water quality and related impacts to ecosystems services, drinking water characteristics, and recreation. While HABs occur frequently throughout the United States, the driving conditions behind them are not well understood,

2021 McKenzie River Topobathymetric Lidar Validation - USGS Field Survey Data

U.S. Geological Survey (USGS) scientists conducted field data collection efforts between July 19th and 31st, 2021 over a large stretch of the McKenzie River in Oregon using high accuracy surveying technologies. The work was initiated as an effort to validate commercially acquired topobathymetric light detection and ranging (lidar) data that was collected coincidentally between July 26th and 30th,

Digital maps of submarine landslides and mass wasting features offshore of southern California

This data release provides the locations and certain key metrics of landslide features offshore southern California, including landslide perimeters, scarps, evacuation zones, debris aprons, and slide-prone areas in geographic information system (GIS) shapefile format. The offshore region of southern California is a tectonically active area that includes more than 20 fault-bounded basins and ridges

Airborne Lidar Data (2016 and 2021) Capturing Debris Flow Erosion and Deposition after the Grizzly Creek Fire in Glenwood Canyon, Colorado

This dataset contains lidar digital elevation models (DEMs). The lidar data were collected before (2016) and after (2021) the Grizzly Creek Fire, which occurred in 2020. The 2016 lidar was collected during a series of flights between 10 June and 7 October 2016. The 2021 lidar flight was conducted in full on 24 August 2021. The files are named with the following convention: Vendor_Year_Resolution_m

Cenozoic and Mesozoic Denver Vertebrate Fossil Collection, U.S. Geological Survey Core Research Center (1948-1978)

Collection consist of vertebrates featuring stratigraphic and spatial data. Data is primarily type fossils from the USGS Denver vertebrate Catalog created and maintained by U.S. Geological Survey (USGS). Data were collected by paleontologist Dr. G. Edward Lewis during his years of service within the USGS Paleontology And Stratigraphy Branch. His catalogs were converted into digital form, Excel and

South Lake Lery Shoreline and Marsh Restoration (BS-16): 2012 and 2018 land-water classifications

The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting

Chemical Concentrations and Microbiological Results for Assessment of Mixed-Organic/Inorganic Chemical Exposures in Tapwater in Mead, Nebraska, June 2022 and January 2023

In the United States and globally, the lack of data on contaminant exposure from unregulated private-well point-of-use (POU) tapwater (TW) is a recognized public health data gap and an obstacle to risk management and homeowner decision making. Mead, Nebraska, is an agricultural community about 30 miles west of Omaha. To help address the lack of data on broad contaminant exposures in TW sourced fro

State-Wide Reconnaissance of Per- and Polyfluoroalkyl Substances, N-(1,3-Dimethylbutyl)-N-phenyl-p-phenylenediamine (6PPD), and 6PPD-Quinone in Iowa Streams, 2022-2023

Water-quality samples were collected at 49 surface water sites covering a range of land uses across the state of Iowa starting the summer of 2022 and continuing into the spring of 2023 by staff from the U.S. Geological Survey Central Midwest Water Science Center. Samples were submitted to the National Water Quality Laboratory in Denver, Colorado, and were analyzed for 32 per- and polyfluoroalkyl s

Digital Database for the Geologic Map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California

This digital map database represents the general distribution of bedrock and surficial geologic units, and related data in the Fonts Point and Seventeen Palms 7.5’ quadrangles, California. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. This investigation delineates the geologic framework of

Vegetation and geomorphic surfaces in the Elwha River delta, Washington, after dam removal, derived from 2016 and 2018 aerial imagery and 2007, 2014, and 2018 field surveys

Removal of two large dams from the Elwha River, Washington USA, in 2011-2014 released ~20.5 metric tons (Mt) of impounded sediment, ~5.4 Mt of which was deposited in the river delta and estuary. This dataset presents measurements of geomorphic surfaces, vegetation colonization, and plant community development in the Elwha River delta and estuary after dam removal. Geomorphic surfaces and vegetatio

Data from "Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning"

Accurate, high-resolution maps of bedrock outcrops are extremely valuable. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock maps. This data release contains training data created for developing a machine learning model capable of identifying exposed bedrock across the entire Sierra Nevada Mountains (California, USA).