<?xml version="1.0" encoding="UTF-8" standalone="no"?><metadata xml:lang="en">
    <Esri>
        <CreaDate>20220206</CreaDate>
        <CreaTime>16400600</CreaTime>
        <ArcGISFormat>1.0</ArcGISFormat>
        <SyncOnce>TRUE</SyncOnce>
    </Esri>
    <dataIdInfo>
        <idCitation>
            <resTitle>Map1</resTitle>
        </idCitation>
        <idAbs>The Elbow River Reservoir Project (ERRP) intends to find suitable location for an off-stream river reservoir for the Elbow River, as part of flood mitigation efforts. This layer corresponds to the initial study area considered for the project. It includes the folowwing feature classes.&lt;div&gt;&lt;ul&gt;&lt;li&gt;City of Calgary boundary&lt;/li&gt;&lt;li&gt;City of Cochrane boundary&lt;/li&gt;&lt;li&gt;Tsuu T'ina Nation boundary&lt;/li&gt;&lt;li&gt;Stoney-Nakoda Nation boundary&lt;/li&gt;&lt;li&gt;Elbow River line&lt;/li&gt;&lt;li&gt;Bow River line&lt;/li&gt;&lt;li&gt;Initial Study Area as a refined buffer up to 50Km West of the City of Calgary&lt;/li&gt;&lt;/ul&gt;The proposed reservoir location will be contained within this study area, according to well-defined criteria.&lt;/div&gt;</idAbs>
        <searchKeys>
            <keyword>Flood Mitigation</keyword>
            <keyword>Off-Stream River Reservoir</keyword>
            <keyword>Elbow River</keyword>
            <keyword>Story Map</keyword>
            <keyword>GEOS450</keyword>
        </searchKeys>
        <idPurp>ERRP = "Elbow River Reservoir Project".
This layer shows the initial study area for the ERR project as a 50Km buffer West of the City of Calgary. It also shows four urban boundaries and two major rivers in the context of the study area.</idPurp>
        <idCredit>Cartographer: Gerardo Pirela, Data Source: Government of Alberta Open Data Portal: m https://open.alberta.ca/opendata</idCredit>
        <resConst>
            <Consts>
                <useLimit/>
            </Consts>
        </resConst>
    </dataIdInfo>
    <Binary>
        <Thumbnail>
            <Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAAAAAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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</Data>
        </Thumbnail>
    </Binary>
</metadata>