A stormdrain receiving water input during a high-precipitation storm in Massachusetts.
Alana Burton Spaetzel
Alana Burton Spaetzel is a Supervisory Hydrologist in the New England Water Science Center.
Alana Spaetzel studies surface water-quality issues in New England. Her interests include nutrient loading in the urban environment, highway-runoff quality, and coastal water-quality monitoring.
Professional Experience
Supervisory Hydrologist, U.S. Geological Survey, New England Water Science Center, 2024 to Present
Hydrologist, U.S. Geological Survey, New England Water Science Center, 2017 to 2024
Education and Certifications
M.S. Geology, Boston College, 2018
B.S. Geology, College of William & Mary, 2015
Science and Products
Delineating High-Resolution Urban Drainage Systems for Stormwater Management in the Neponset River Watershed
Delineating High-Resolution Urban Drainage Systems for Stormwater Management in the Mystic River Watershed
Transportation-Related Water Projects in New England
Assessment of Nutrient Transport and Discharge to Coastal Embayments, Wickford, Rhode Island
Herring River Water Quality
Transportation-Related Water Projects
SELDM: Stochastic Empirical Loading and Dilution Model - Project page
Highway-Runoff Database (HRDB) Version 1.2.0
Physical and Chemical Data to Characterize Water-Quality Conditions in the Sakonnet River, Rhode Island, 2018-2019
Highway-Monitoring Data from Segments of Open-Graded Friction Course and Dense-Graded Hot-Mix Asphalt Pavement in Eastern Massachusetts, 2018-2021
Digital Elevation Model and Derivative Datasets to Support the Integration of Stormwater Drainage into the StreamStats Application for the Mystic River Watershed, Massachusetts
Basin Characteristics Data for the StreamStats Application in the Mystic River Basin, Massachusetts
Model Archive for Analysis of Flows, Concentrations, and Loads of Highway and Urban Runoff and Receiving-Stream Stormwater in Southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)
Water-Quality, Streamflow, and Quality-Control Data Supporting Estimation of Nutrient and Sediment Loads in the Scituate Reservoir Drainage Area, Rhode Island, Water Years 2016-19
Water-quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir (ver. 3.0, November 2023)
Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)
Basin characteristics and point locations of road crossings in Connecticut, Massachusetts, and Rhode Island for highway-runoff mitigation analyses using the Stochastic Empirical Loading and Dilution Model
Discrete water quality data supporting Herring River restoration project, Cape Cod National Seashore, 1984-2017
A stormdrain receiving water input during a high-precipitation storm in Massachusetts.
This is a downstream view of the Herring River from the Chequessett Neck Road dike. The site was visited on November 6, 2017 to collect water-quality samples. An automated sampler inside the gage house was used to collect samples over an approximately 24-hour period and combine them into two bottles.
This is a downstream view of the Herring River from the Chequessett Neck Road dike. The site was visited on November 6, 2017 to collect water-quality samples. An automated sampler inside the gage house was used to collect samples over an approximately 24-hour period and combine them into two bottles.
Highway-runoff quality from segments of open-graded friction course and dense-graded hot-mix asphalt pavement on Interstate 95, Massachusetts, 2018–21
Highway runoff is a source of sediment and associated 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; however, few datasets are available in New En
Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)
Water-quality conditions and constituent loads, water years 2013–19, and water-quality trends, water years 1983–2019, in the Scituate Reservoir drainage area, Rhode Island
Assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015 to September 2017
Statistical methods for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)
This report documents statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM). The U.S. Geological Survey developed SELDM and the statistics documented in this report in cooperation with the Federal Highway Administration to indicate the risk for stormwater flows, concentrations, and loads to exceed us
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
SELDM: Stochastic Empirical Loading and Dilution Model - Software page
Overview
The Stochastic Empirical Loading and Dilution Model (SELDM) is designed 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.
Science and Products
Delineating High-Resolution Urban Drainage Systems for Stormwater Management in the Neponset River Watershed
Delineating High-Resolution Urban Drainage Systems for Stormwater Management in the Mystic River Watershed
Transportation-Related Water Projects in New England
Assessment of Nutrient Transport and Discharge to Coastal Embayments, Wickford, Rhode Island
Herring River Water Quality
Transportation-Related Water Projects
SELDM: Stochastic Empirical Loading and Dilution Model - Project page
Highway-Runoff Database (HRDB) Version 1.2.0
Physical and Chemical Data to Characterize Water-Quality Conditions in the Sakonnet River, Rhode Island, 2018-2019
Highway-Monitoring Data from Segments of Open-Graded Friction Course and Dense-Graded Hot-Mix Asphalt Pavement in Eastern Massachusetts, 2018-2021
Digital Elevation Model and Derivative Datasets to Support the Integration of Stormwater Drainage into the StreamStats Application for the Mystic River Watershed, Massachusetts
Basin Characteristics Data for the StreamStats Application in the Mystic River Basin, Massachusetts
Model Archive for Analysis of Flows, Concentrations, and Loads of Highway and Urban Runoff and Receiving-Stream Stormwater in Southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)
Water-Quality, Streamflow, and Quality-Control Data Supporting Estimation of Nutrient and Sediment Loads in the Scituate Reservoir Drainage Area, Rhode Island, Water Years 2016-19
Water-quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir (ver. 3.0, November 2023)
Statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)
Basin characteristics and point locations of road crossings in Connecticut, Massachusetts, and Rhode Island for highway-runoff mitigation analyses using the Stochastic Empirical Loading and Dilution Model
Discrete water quality data supporting Herring River restoration project, Cape Cod National Seashore, 1984-2017
A stormdrain receiving water input during a high-precipitation storm in Massachusetts.
A stormdrain receiving water input during a high-precipitation storm in Massachusetts.
This is a downstream view of the Herring River from the Chequessett Neck Road dike. The site was visited on November 6, 2017 to collect water-quality samples. An automated sampler inside the gage house was used to collect samples over an approximately 24-hour period and combine them into two bottles.
This is a downstream view of the Herring River from the Chequessett Neck Road dike. The site was visited on November 6, 2017 to collect water-quality samples. An automated sampler inside the gage house was used to collect samples over an approximately 24-hour period and combine them into two bottles.
Highway-runoff quality from segments of open-graded friction course and dense-graded hot-mix asphalt pavement on Interstate 95, Massachusetts, 2018–21
Highway runoff is a source of sediment and associated 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; however, few datasets are available in New En
Approaches for assessing flows, concentrations, and loads of highway and urban runoff and receiving-stream stormwater in southern New England with the Stochastic Empirical Loading and Dilution Model (SELDM)
Water-quality conditions and constituent loads, water years 2013–19, and water-quality trends, water years 1983–2019, in the Scituate Reservoir drainage area, Rhode Island
Assessment of water quality and discharge in the Herring River, Wellfleet, Massachusetts, November 2015 to September 2017
Statistical methods for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM)
This report documents statistics for simulating structural stormwater runoff best management practices (BMPs) with the Stochastic Empirical Loading and Dilution Model (SELDM). The U.S. Geological Survey developed SELDM and the statistics documented in this report in cooperation with the Federal Highway Administration to indicate the risk for stormwater flows, concentrations, and loads to exceed us
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
SELDM: Stochastic Empirical Loading and Dilution Model - Software page
Overview
The Stochastic Empirical Loading and Dilution Model (SELDM) is designed 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.