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Michelle P Katoski

Michelle is a Physical Scientist at the Lower Mississippi-Gulf Water Science Center.

Michelle is a Physical Scientist at the Lower Mississippi-Gulf (LMG) Water Science Center, stationed at EPA’s Chesapeake Bay Program (CBP) Office in Annapolis, MD. She joined the CBP in October 2023, and now supports efforts to monitor and benchmark Chesapeake restoration progress using geospatial analysis and modelling.

Prior to joining the LMG and CBP, Michelle spent 4 years as a Physical Scientist at the MD-DE-DC Water Science Center in Baltimore, MD. During her time at MD-DE-DC, Michelle provided science and leadership support to local, regional, and national projects funded by DC DOEE, USGS Chesapeake Bay PES, USGS Water Mission Area, and USGS Community for Data Integration.

 

  • Recent project themes:

    • Urban flood frequency analysis
    • Water Use data acquisition, storage and management
    •  Anomaly detection for timeseries data
    •  Software development
    • Cloud computing; Statistical programming
    • Geospatial programming
    • Sediment budgets.
    • Watershed modelling

 

Professional Experience

  • Physical Scientist (September 2023 – Present) - Lower Mississippi-Gulf Water Science Center, Chesapeake Bay Program Office, Annapolis, MD 

  • Physical Scientist (September 2019 – October 2023) - MD-DE-DC Water Science Center Baltimore, MD 

  • Student Researcher (December 2017 – September 2019) - University of Maryland, Baltimore County Baltimore, MD

  • Seasonal Technician (May 2018 – November 2018) - Maryland Department of Natural Resources, Annapolis, MD

Education and Certifications

  • M.S. Student (2020 - Present) University of Maryland, Baltimore County

    Department of Geography and Environmental Systems, Committee Chair: Matthew Baker

  • B.S. Environmental Science, GIS Certificate (2014 - 2017)

    University of Maryland, Baltimore County

Abstracts and Presentations

  • Katoski, M.P., Cashman, M.J., and Lester T., Vogel K., 2023. From reactive- to condition-based maintenance: Artificial intelligence for anomaly predictions and operational decision-making. USGS Timeseries Record Automation Focus Group. June 22, 2023. 

  • Katoski, M.P., Baker, M.E, 2023. Characterizing urban woodlands using LiDAR derived metrics of vertical structure in Baltimore, MD. International Association of Landscape Ecology – North America Annual Meeting. Riverside, CA; March 22, 2023.

  • Katoski, M.P., Cashman, M.J., and Lester T., Vogel K., 2022. From reactive- to condition-based maintenance: Artificial intelligence for anomaly predictions and operational decision-making. USGS Community for Data Integration. August 11, 2022. 

Science and Products

Digital elevation model and derivative datasets to support the integration of stormwater drainage into the Washington, D.C. Stormwater StreamStats application

This dataset was created to support the Washington D.C. StreamStats project funded by the Washington D.C. Department of Energy and Environment (DOEE). The dataset contains digital elevation model (DEM), flow direction and catchment layers that were conditioned using Washingtons D.C.’s stormwater network layer. The data are hosted online as a component of the USGS StreamStats web application (https
By
Maryland-Delaware-D.C. Water Science Center

Basin characteristics data for the Washington, D.C. StreamStats application

This data was created to support the Washington D.C. StreamStats project funded by the Washington D.C. Department of Energy and Environment (DOEE). The data release contains high-resolution (1-meter) land cover data layers for Washington D.C. and its tributaries that represent canopy cover, canopy cover with building and road coverage removed (“pervious canopy”), impervious cover, slope (in units
By
Chesapeake Bay Activities, Maryland-Delaware-D.C. Water Science Center

Questions and responses to USGS-wide poll on quality assurance practices for timeseries data, 2021

This data record contains questions and responses to a USGS-wide survey conducted to identify issues and needs associated with quality assurance and quality control (QA/QC) of USGS timeseries data streams. This research was funded by the USGS Community for Data Integration as part of a project titled “From reactive- to condition-based maintenance: Artificial intelligence for anomaly predictions an
By
Maryland-Delaware-D.C. Water Science Center

Hydrogen and oxygen stable isotope mass balance evaluation of the National Water Model (v2.1) streamflow, runoff and groundwater flows

This data release contains the results of an isotopic mass balance approach to provide an estimate of the long-term average isotope ratios of NWM streamflow for the summer season (JJA) between 2000 and 2019 in the Western United States. The NWM-estimated long-term average isotope ratios are compared directly to 6426 stream stable isotope observations in 995 unique catchments. Quantified similariti
By
Utah Water Science Center

Sediment model inputs and outputs for the Smith Creek watershed near New Market, Virginia for 2012-2016

This data release includes data created, collected, and/or otherwise modified in the process of quantifying a sediment budget for the Smith Creek Watershed near New Market, Virginia, USA. Five raster files are included, namely a modeled index of hydrological connectivity, a raster model of modeled floodplain depositional masses and extent, a rasters of modeled gross and delivered upland erosion, a
By
Maryland-Delaware-D.C. Water Science Center

Visible and near-infrared spectroscopy for sediment samples collected across North-eastern U.S.

This data record contains a CSV file with spectral reflectance (420-2114 nm) for sediment samples collected from each of four source locations (cropland, stream bank, glaciolacustrine, and street dust) located across sites in the Northwestern US during prior studies. Data were collected in a laboratory setting using Spectrecology USB4000-VIS-NIR and NIRQuest512-2.2 spectrometers. The data contain
By
Maryland-Delaware-D.C. Water Science Center

Isotopic evaluation of the National Water Model reveals missing agricultural irrigation contributions to streamflow across the western United States

The National Water Model (NWM) provides critical analyses and projections of streamflow that support water management decisions. However, the NWM performs poorly in lower-elevation rivers of the western United States (US). The accuracy of the NWM depends on the fidelity of the model inputs and the representation and calibration of model processes and water sources. To evaluate the NWM performance
Authors
Annie L. Putman, Patrick C. Longley, Morgan C. McDonnell, James E. Reddy, Michelle Patricia Katoski, Olivia L. Miller, J. Renee Brooks
By
Water Resources Mission Area, New York Water Science Center, Utah Water Science Center

Quantifying connectivity and its effects on sediment budgeting for an agricultural basin, Chesapeake Bay Watershed, United States

Excessive sediment runoff as a result of anthropogenic activities is a major concern for watershed ecologic health. This study sought to determine the sources, storage, and delivery of sediment using a sediment budget approach for the predominantly pasture and forested Smith Creek watershed, Virginia United States, a tributary to the Chesapeake Bay. Utilizing a novel combination of the Universal S
Authors
Zachary Clifton, Allen C. Gellis, Matthew Joseph Cashman, Michelle Patricia Katoski, Lucas A Nibert, Gregory Noe
By
Chesapeake Bay Activities, Maryland-Delaware-D.C. Water Science Center

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.

Science and Products

Digital elevation model and derivative datasets to support the integration of stormwater drainage into the Washington, D.C. Stormwater StreamStats application

This dataset was created to support the Washington D.C. StreamStats project funded by the Washington D.C. Department of Energy and Environment (DOEE). The dataset contains digital elevation model (DEM), flow direction and catchment layers that were conditioned using Washingtons D.C.’s stormwater network layer. The data are hosted online as a component of the USGS StreamStats web application (https
By
Maryland-Delaware-D.C. Water Science Center

Basin characteristics data for the Washington, D.C. StreamStats application

This data was created to support the Washington D.C. StreamStats project funded by the Washington D.C. Department of Energy and Environment (DOEE). The data release contains high-resolution (1-meter) land cover data layers for Washington D.C. and its tributaries that represent canopy cover, canopy cover with building and road coverage removed (“pervious canopy”), impervious cover, slope (in units
By
Chesapeake Bay Activities, Maryland-Delaware-D.C. Water Science Center

Questions and responses to USGS-wide poll on quality assurance practices for timeseries data, 2021

This data record contains questions and responses to a USGS-wide survey conducted to identify issues and needs associated with quality assurance and quality control (QA/QC) of USGS timeseries data streams. This research was funded by the USGS Community for Data Integration as part of a project titled “From reactive- to condition-based maintenance: Artificial intelligence for anomaly predictions an
By
Maryland-Delaware-D.C. Water Science Center

Hydrogen and oxygen stable isotope mass balance evaluation of the National Water Model (v2.1) streamflow, runoff and groundwater flows

This data release contains the results of an isotopic mass balance approach to provide an estimate of the long-term average isotope ratios of NWM streamflow for the summer season (JJA) between 2000 and 2019 in the Western United States. The NWM-estimated long-term average isotope ratios are compared directly to 6426 stream stable isotope observations in 995 unique catchments. Quantified similariti
By
Utah Water Science Center

Sediment model inputs and outputs for the Smith Creek watershed near New Market, Virginia for 2012-2016

This data release includes data created, collected, and/or otherwise modified in the process of quantifying a sediment budget for the Smith Creek Watershed near New Market, Virginia, USA. Five raster files are included, namely a modeled index of hydrological connectivity, a raster model of modeled floodplain depositional masses and extent, a rasters of modeled gross and delivered upland erosion, a
By
Maryland-Delaware-D.C. Water Science Center

Visible and near-infrared spectroscopy for sediment samples collected across North-eastern U.S.

This data record contains a CSV file with spectral reflectance (420-2114 nm) for sediment samples collected from each of four source locations (cropland, stream bank, glaciolacustrine, and street dust) located across sites in the Northwestern US during prior studies. Data were collected in a laboratory setting using Spectrecology USB4000-VIS-NIR and NIRQuest512-2.2 spectrometers. The data contain
By
Maryland-Delaware-D.C. Water Science Center

Isotopic evaluation of the National Water Model reveals missing agricultural irrigation contributions to streamflow across the western United States

The National Water Model (NWM) provides critical analyses and projections of streamflow that support water management decisions. However, the NWM performs poorly in lower-elevation rivers of the western United States (US). The accuracy of the NWM depends on the fidelity of the model inputs and the representation and calibration of model processes and water sources. To evaluate the NWM performance
Authors
Annie L. Putman, Patrick C. Longley, Morgan C. McDonnell, James E. Reddy, Michelle Patricia Katoski, Olivia L. Miller, J. Renee Brooks
By
Water Resources Mission Area, New York Water Science Center, Utah Water Science Center

Quantifying connectivity and its effects on sediment budgeting for an agricultural basin, Chesapeake Bay Watershed, United States

Excessive sediment runoff as a result of anthropogenic activities is a major concern for watershed ecologic health. This study sought to determine the sources, storage, and delivery of sediment using a sediment budget approach for the predominantly pasture and forested Smith Creek watershed, Virginia United States, a tributary to the Chesapeake Bay. Utilizing a novel combination of the Universal S
Authors
Zachary Clifton, Allen C. Gellis, Matthew Joseph Cashman, Michelle Patricia Katoski, Lucas A Nibert, Gregory Noe
By
Chesapeake Bay Activities, Maryland-Delaware-D.C. Water Science Center

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.

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