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    Modeling the Hydrological Impacts of the Yarnell Hill Fire Using the Automated Geospatial Watershed Assessment (AGWA) Tool

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    MS-GIST_2022_Shafer.pdf
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    Description:
    MS-GIST Report
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    Author
    Shafer, David
    Issue Date
    2022-12
    Keywords
    Yarnell Hill
    Wildfires
    hydrology
    modeling
    AGWA
    Advisor
    Korgaonkar, Yoganand
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Collection Information
    This item is part of the MS-GIST Master's Reports collection. For more information about items in this collection, please contact the UA Campus Repository at repository@u.library.arizona.edu.
    Abstract
    The highly publicized 2013 Yarnell Hill Fire is the deadliest wildfire in Arizona history, killing 19 members of the Granite Mountain Hotshots firefighting crew. Wildland fires like Yarnell Hill have immediate effects on human life and property, but they can also increase the frequency and severity of flooding events due to loss of vegetation and hydrophobicity of soils and ash. This study seeks to model hydrological impacts due to land cover change following the Yarnell Hill Fire using the Automated Geospatial Watershed Assessment (AGWA) Tool. AGWA can enable hydrologic modeling using the Soil & Water Assessment Tool (SWAT) or the Kinematic Runoff and Erosion Model (KINEROS2) and can help land and water resource managers make quick decisions regarding flood mitigation strategies following a wildfire. In this study, AGWA is used to model the change in land cover due to the Yarnell Hill fire based on a burn intensity map created using the differenced Normalized Burn Ratio (dNBR) and based on pre- and post-fire Landsat 8 Operational Land Imager (OLI) imagery. Storm conditions included in the model represent a variety of storm recurrence intervals based on National Weather Service (NWS) data for the town of Yarnell. For all post-fire storm conditions modeled, flooding increases more rapidly and with greater volume as compared to pre-fire conditions.
    Type
    Electronic Report
    text
    Degree Name
    M.S.
    Degree Level
    masters
    Degree Program
    Geographic Information Systems Technology
    Degree Grantor
    University of Arizona
    Collections
    MS-GIST (Master's Reports)

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