The U.S. Geological Survey 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 Service (WMS) has been developed to query data from the hydraulic models at select stream crossing locations using the StreamStats web application for Massachusetts. The WMS contains stream crossing point locations with hydrology and hydraulic data tables and associated watershed polygons. These stream crossing locations were derived from the North Atlantic Aquatic Connectivity Collaborative data center (NAACC Data Center). Preliminary culvert designs for three-sided box, conspan arch, and a pipe culvert have been modeled using the U.S. Army Corps of Engineer’s Hydrologic Engineering Center’s River Analysis System (HEC-RAS) software with cross-sectional and channel geometry data derived from high-resolution light detection and ranging (lidar) Digital Elevation Models (DEM). The WMS layer provides the ability to generate reports in the StreamStats web application for Massachusetts at the stream crossing locations for site location information, preliminary culvert designs, flood flows, bankfull channel geometry, aquatic habitat and stream connectivity restoration potential, basin characteristics, and other select information.

This software release provides the database application that runs the Connecticut Streamflow and Sustainable Water Use Estimator (CT SSWUE) computer program (version 1.0). The CT SSWUE was developed by the U.S. Geological Survey, in cooperation with the Connecticut Department of Energy and Environmental Protection, to provide a planning-level decision-support tool designed to help decision makers estimate daily mean streamflows and selected streamflow statistics that can be used to assess sustainable water use at ungaged sites in Connecticut. The CT SSWUE provides estimates of unaltered streamflow (which is assumed to include effects of minimal human development but not the effects of instream regulation or water use), net streamflow alterations caused by water use, water-use-adjusted streamflow, streamflow yields (estimated unaltered streamflow minus user-defined flow targets), and estimates of the accuracy and uncertainty of estimated unaltered streamflow. The CT SSWUE uses basin characteristics and water-use volumes (water withdrawals and wastewater-return flows) obtained from the U.S. Geological Survey online StreamStats application to estimate the unaltered and water-use-adjusted streamflows. The CT SSWUE is a database application with a graphical user interface developed by using Visual Basic for Applications with the 32-bit version of Microsoft Access©. The graphical user interface is designed to include full documentation for users: an introductory instruction form and onscreen help within each interactive form, including explanation buttons, context-sensitive help buttons, and tool-tip and status-bar messages.

The USGS Water Mission Area (WMA) - Ecosystems Mission Area (EMA) EcoDrought project is comprised of interdisciplinary teams in five pilot regions across the country. The over-arching project goal is to measure streamflow in headwater streams and to relate flow variation to stream fish population dynamics. In the northeast, the New England Water Science Center (NewEngWSC) partnered with the fish ecology group at the S.O. Conte Anadromous Fish Research Lab (Conte), a part of the EMA’s Eastern Ecological Science Center. The Conte fish ecology team has been collecting ecological and stream water temperature data in the West Brook watershed located in Whately, Massachusetts, since 1997, where they developed novel methods to track individual fish and populations. The Conte team has leveraged these data to understand growth, survival, habitat use, genetic structure, population abundance and movement of Atlantic Salmon, Brook Trout and Brown Trout as well as stream temperature impacts on Brook Trout in the West Brook. However, they have not historically had the expertise or equipment to accurately measure discharge in these headwater streams, which hindered their ability to examine the role of streamflow in fish ecology. Starting in August of 2019 the NewEngWSC trained a team from Conte to install and maintain in-stream pressure gaging sites including surveying to monitor and account for any movement of the pressure sensor, performing streamflow measurements, developing rating curves to relate gage height and discharge, and carrying out routine and emergency maintenance. This data set is comprised of the continuous gage height, discharge, water temperature, air temperature, and air pressure data, as well as discrete discharge measurements and site information for ten headwater stream gaging stations located in the West Brook watershed in Whately, Massachusetts. The date range for this data set is 2019-04-01 through 2025-01-03. Once collected, the continuous gage height data were reviewed, and offsets were applied to correct for instrument movement and instrument drift under the guidance of NewEngWSC Hydrologic Monitoring Program staff. Continuous gage height is converted to a continuous discharge record by relating discrete gage height and discharge measurements with a rating model developed in accordance with USGS WMA standards. Please note that the "EcoDrought_Continuous_MA.csv" data file has over 1.7 million rows, meaning it is too large to open and manipulate in Microsoft Excel. Please take caution when working with these data in Excel.

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 the Nashua River watershed (that includes the Squannacook River) in Massachusetts and New Hampshire. There are 100 ensembles from the SWG for warming scenarios of 0 to 8 degrees Celsius in 0.5-degree increments. The SWG data were converted to a format utilized by the Precipitation-Runoff Modeling System (PRMS; https://www.usgs.gov/software/precipitation-runoff-modeling-system-prms) and input to a PRMS model for the Squannacook River watershed. The PRMS input and output files for the 100 ensembles of each of the 17 warming scenarios are also included in this data release. The 1,700 PRMS output files were utilized by a Stochastic Watershed Modeling tool to correct modeling biases that are inherent with a deterministic model such as PRMS. This data release includes the output from this Stochastic Watershed Model (SWM). For each of the 100 ensembles, the SWM was used to generate 10,000 ensembles, resulting in 1 million ensembles of 64-year periods for each of the warming scenarios. For each ensemble, streamflow characteristics of the annual maximum daily discharge at the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence interval and of the annual 7-day low flow at the 2- and 10-year recurrence interval were determined.

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 stream network centerline polyline shapefile derived from the hydro-enforcement that shows stream location; a sub-basin polygon shapefile derived from the hydro-enforcement representing watershed areas for all stream network centerline polylines; a flow direction raster, predicting the direction of flow based on direction of steepest drop; and a flow accumulation raster, predicting the number of upstream cells flowing into each one-meter cell. Field verification was conducted for locations where the high-resolution lidar digital elevation models were unclear on hydraulic connection. Photographs were captured to confirm the conveyance of flow. The datasets are provided in separate child items.

This data set archives all inputs, outputs and scripts needed to reproduce the findings of W.H. Farmer and S. Levin in the 2017 Journal of the American Water Resources Association article entitled “Characterizing Uncertainty in Daily Streamflow Estimates at Ungauged Locations in Support of the Massachusetts Sustainable Yield Estimator”. Input data includes observed streamflow values, in cubic feet per second, for 66 streamgages in and around Massachusetts from 01 October 1960 through 30 September 2004. Cross-validated streamflows, in cubic feet per second, and estimated correlations are included for all basin pairs as archived by Archfield et al. (2010; USGS SIR 2009–5227). Comma-separated-values files contain output data, including all estimated daily confidence intervals, performance thereof (coverage ratio, average width indices and interval skill scores), and multi-day aggregated performance metrics. ESRI ArcGIS shapefiles are available for all maps produced in the original publication. This archive also includes an R script capable of reading the input files and producing output files and figures. See the README.txt file for a full description of model application. The larger publication can be found at https://doi.org/10.1111/1752-1688.12603.

The Stochastic Empirical Loading and Dilution Model (SELDM) was developed by the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration (FHWA) Office of Project Delivery and Environmental Review to transform complex scientific data into meaningful information about the risk of adverse effects of runoff on receiving waters, the potential need for mitigation measures, and the potential effectiveness of such management measures for reducing these risks (Granato 2013; Granato and Jones, 2014). SELDM is a stochastic model because it uses Monte Carlo methods to produce the random combinations of input variable values needed to generate the stochastic population of values for each component variable. SELDM calculates the dilution of runoff in the receiving waters and the resulting downstream event mean concentrations and annual average lake concentrations. Results are ranked, and plotting positions are calculated, to indicate the level of risk of adverse effects caused by runoff concentrations, flows, and loads on receiving waters by storm and by year. Unlike deterministic hydrologic models, SELDM is not calibrated by changing values of input variables to match a historical record of values. Instead, input values for SELDM are based on site characteristics and representative statistics for each hydrologic variable. Thus, SELDM is an empirical model based on data and statistics rather than theoretical physiochemical equations. The SELDM was developed as a database application with a simple graphical user interface (GUI) by using Microsoft Access® to facilitate highway and urban runoff analyses by scientists, engineers, and decisionmakers without specialized modeling skills. SELDM uses information about a highway site, the associated receiving-water basin, precipitation events, stormflow, water quality, and the performance of mitigation measures to produce a stochastic population of runoff-quality variables. SELDM provides input statistics for precipitation, prestorm flow, runoff coefficients, and concentrations of selected water-quality constituents from National datasets. Input statistics may be selected on the basis of the latitude, longitude, and physical characteristics of the site of interest and the upstream basin. The user also may derive and input statistics for each variable that are specific to a given site of interest or a given area. This software archive is designed to document different versions of SELDM that have been used by the USGS, Federal and State transportation engineers, and others since version 1.0 was published as a USGS techniques and methods report (Granato 2013). Versions 1.0.1 through 1.0.3 were developed to implement minor modifications to the software. Version 1.1.0 was developed to provide an interface to run multiple analyses in one session, which facilitates use of the model for scenario and sensitivity analyses. Details about version changes are provided within SELDM’s GUI and in the “ReadMe” files within this software release.

This data release consists of four datasets which were used for evaluating winter drawdown (WD) lakes to follow the Massachusetts general WD guidelines. The first dataset ("Water level observations.csv") provides water level monitoring data of 21 (18 WD and 3 non-WD) recreational lakes in Massachusetts from 2014 to 2018. The water levels were measured by paired nonvented pressure transducers (HOBO U20L-01) and processed by ContDataQC package to remove potential inaccurate observations. For better comparison between lakes, the water level was relativized to each lake's normal pool level. This dataset was used for understanding the hydrology of WD and non-WD lakes and validating the hydrological model that we developed for WD lakes. Details of the hydrological model were described in the software release (https://doi.org/10.5066/P9C8BVY2). The second dataset ("Water level simulations.csv") is the hydrological model simulated daily water level (relative to each lake's normal pool level) time series of the WD lakes from the first dataset (15 lakes, 2014-2018). To validate the applicability of the model on simulating water levels in WD lakes, the actual drawdown rules were set in the model to recreate the historical water levels and compare with the in-situ observations in the first dataset. The third dataset ("Guideline_Eval_Dec1drawdown.csv") contains the probability of each WD lake reaching the drawdown level by Dec 1 which is required by the guidelines when selecting different drawdown magnitudes (1-6ft) by Dec 1 in 2015. 2016 and 2017. The fourth dataset (“Guidleine_Eval_Apr1refill.csv”) consists of the latest refill starting dates of each lake with different designed drawdown magnitude (1-6 ft) to ensure over 95% possibility for each WD lake to be fully refilled by Apr 1 in 2016, 2017, 2018.