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Data

The New England Water Science Center operates over 500 real-time data collection sites throughout the six New England states. The sites collect surface-water, groundwater, water-quality, and precipitation data. Much of our real-time data is publicly available through NWIS. Additional data releases are also available on the page below.

Filter Total Items: 138

Massachusetts Stream Crossing Project Data Web Map Service

The U.S. Geological Survey (USGS) and the University of Massachusetts at Amherst (UMass Amherst), in cooperation with the Massachusetts Department of Environmental Protection (MassDEP), began a series of studies in 2019 to develop a web-based statewide hydraulic modeling tool to provide preliminary culvert designs to support stream crossing replacement projects in Massachusetts. This Web Map Servi

Water level, water temperature, and specific conductance data collected during natural gradient tests in observation wells set in the upper transmissive zone of the Ogallala Aquifer, North East 2nd Street Superfund Site, Happy, Texas, 2023

Water level, water temperature, and specific conductance data were collected during natural gradient tests on six observation wells screened in the upper transmissive zone of the Ogallala aquifer at the North East 2nd Street Superfund site in Happy, Texas, from November 6-13, 2023. Tests involved gravity draining 100-160 gallons of a low-concentration salt-spiked solution with an associated specif

Elevation-Derived Hydrography in the Upper Shawsheen River Basin, Massachusetts

The U.S. Geological Survey (USGS), in cooperation with the Air Force Civil Engineer Center (AFCEC), has compiled Geographic Information Systems (GIS) datasets. The spatial data layers provided in this data release are hydrography data derived from high-resolution lidar digital elevation models (DEM). They include a hydroline polyline shapefile used to hydro-enforce the high-resolution lidar DEM; a

Water Quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir, water year 2017

Water-quality data were collected by the Providence Water Supply Board (PWSB) from tributaries in the Scituate Reservoir drainage area, October 2016 through September 2017 (water year 2017). Water-quality samples were collected by the PWSB either monthly or quarterly at fixed stations on 36 tributaries in the Scituate Reservoir drainage area. These data were used to calculate instantaneous loads a

Water Quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir, water year 2015

Water-quality data were collected by the Providence Water Supply Board (PWSB) from tributaries in the Scituate Reservoir drainage area, October 2014 through September 2015 (water year 2015). These data were used to calculate instantaneous loads and yields of constituents in a report by the U.S. Geological Survey. Water-quality samples were collected by the PWSB either monthly or quarterly at fixed

Physical and Chemical Data to Characterize Water-Quality Conditions in the Sakonnet River, Rhode Island, 2018-2019

Physical and chemical data were collected to characterize water-quality conditions in the Sakonnet River, a tidal strait located on the east side of Narragansett Bay in Rhode Island, from April 28 to November 11, 2018 and from June 19 to November 26, 2019. Specifically, the 2018 information in this data release includes: vertical profiles of water quality from 16 to 18 locations and data collected

Data and model archive used to model and map lithium concentrations in groundwater sources of drinking water in the conterminous United States

This data release contains data used to develop models and maps that estimate the occurrence of lithium in groundwater used as drinking water throughout the conterminous United States. An extreme gradient boosting model was developed to estimate the most probable lithium concentration category (≤4, >4 to ≤10, >10 to ≤30, or >30 µg/L). The model uses lithium concentration data from wells located th

Data for a Pilot Study Characterizing Future Climate and Hydrology in Massachusetts

The U.S. Geological Survey has developed tools for projecting twenty-first century climate and hydrologic risk in Massachusetts in collaboration with Cornell University and Tufts University. These tools included a Stochastic Weather Generator (SWG). Output from the SWG is in this data release. The release includes daily precipitation and minimum and maximum air temperature for a 64-year period in

Pilot Study of Per- and Polyfluoroalkyl Substances (PFAS) Infiltration to Shallow Groundwater Through Selected Soils in New Hampshire, 2023

In a study conducted by the U.S. Geological Survey (USGS) and the New Hampshire Department of Environmental Services, detectable concentrations of per- and polyfluoroalkyl substances (PFAS) were found in the soil at every site despite targeting locations with no known PFAS sources (Santangelo and others, 2022). The widespread distribution of PFAS concentrations in New Hampshire has since sparked c

USGS Streamgages in the Conterminous United States Indexed to NHDPlus v2.1 Flowlines to Support Streamgage Watershed InforMation (SWIM), 2021

This U.S. Geological Survey (USGS) data release includes locations for 12,422 USGS streamgages as indexed along the network of streams (flowlines) in NHDPlus Version 2.1 (NHDPlus v2, Moore and Dewald, 2016). The dataset is one of two datasets developed for the Streamgage Watershed InforMation (SWIM) project. This dataset, which is referred to as “SWIM streamgage locations,” was created in support

Highway-Monitoring Data from Segments of Open-Graded Friction Course and Dense-Graded Hot-Mix Asphalt Pavement in Eastern Massachusetts, 2018-2021

Highway runoff is a source of chemical constituents to downstream waterbodies that can be managed with the use of stormwater-control measures that reduce sediment loads. The use of open-graded friction course (OGFC) pavement has been identified as a method to reduce loads from highway runoff because it retains sediment in pavement voids. Few datasets are available, though, in New England to charac

Model Code, Outputs, and Supporting Data for Approaches to Process-Guided Deep Learning for Groundwater-Influenced Stream Temperature Predictions

This model archive provides all data, code, and modeling results used in Barclay and others (2023) to assess the ability of process-guided deep learning stream temperature models to accurately incorporate groundwater-discharge processes. We assessed the performance of an existing process-guided deep learning stream temperature model of the Delaware River Basin (USA) and explored four approaches fo