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            <resTitle>StormSense Sensor Data</resTitle>
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                <reviseDate>2023-02-07T15:45:16</reviseDate>
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            <keyword>StormSense</keyword>
            <keyword>Sensors</keyword>
            <keyword>StormSense Sensors</keyword>
            <keyword>StormSense Data Feed</keyword>
            <keyword>Flood Sensors</keyword>
            <keyword>Sea Level Rise</keyword>
            <keyword>Environmental</keyword>
            <keyword>Flooding</keyword>
            <keyword>Water Level</keyword>
            <keyword>Rainfall</keyword>
            <keyword>Streamflow</keyword>
            <keyword>Wind Speed</keyword>
            <keyword>Real-Time</keyword>
            <keyword>Public Infrastructure</keyword>
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        <idPurp>The StormSense Project is an award-winning inundation forecasting research initiative participating in the Global City Teams Challenge (GCTC). The project was initially funded by the National Institute of Standards and Technology via a Replicable Smart City Technologies grant announced by the White House in Sept. 2016. City of Virginia Beach participates regionally. Most of the funding for the sensors within the city are funded through the Capital Improvement Program (CIP).

This dataset shows water levels and several other parameters in near real-time as shown in the keywords from different sensor sources in the Hampton Roads region. It does not show any historic data. The data can be plotted on a live map. Current sensor types include ultrasonic, radar and others dependent on the parameter. The data sources are from USGS and StormSense. Each location may have a single or multiple sensors for different purposes. The data collection efforts will provide crucial information about the surface water flow across the region at all times of the year in different weather scenarios. The data will be used to support modeling efforts for research communities, emergency preparedness and planning, decision making processes by city officials during adverse weather conditions such as hurricanes, nor’easter and other rainfall events.
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        <idAbs>&lt;p style='margin-top:0px; margin-bottom:0in;'&gt;&lt;span style='font-family:inherit; color:black; background-image:initial; background-position:initial; background-size:initial; background-repeat:initial; background-attachment:initial; background-origin:initial; background-clip:initial;'&gt;The &lt;span style='font-family:inherit;'&gt;objective&lt;/span&gt; of StormSense is to enhance the capability of communities to prepare and respond to the disastrous impacts of sea level rise and coastal flooding in ways that are &lt;/span&gt;&lt;a href='https://vims-wm.maps.arcgis.com/apps/MapJournal/index.html?appid=62c80853313743f3acf5a83ab420d015' style='color:rgb(0, 121, 193); text-decoration-line:none; font-family:inherit;' rel='nofollow ugc'&gt;&lt;b&gt;&lt;span style='font-family:inherit; color:rgb(85, 85, 85); background-image:initial; background-position:initial; background-size:initial; background-repeat:initial; background-attachment:initial; background-origin:initial; background-clip:initial;'&gt;replicable&lt;/span&gt;&lt;/b&gt;&lt;/a&gt;&lt;span style='font-family:inherit; color:black; background-image:initial; background-position:initial; background-size:initial; background-repeat:initial; background-attachment:initial; background-origin:initial; background-clip:initial;'&gt;, &lt;/span&gt;&lt;a href='https://vims-wm.maps.arcgis.com/apps/MapJournal/index.html?appid=62c80853313743f3acf5a83ab420d015' style='color:rgb(0, 121, 193); text-decoration-line:none; font-family:inherit;' rel='nofollow ugc'&gt;&lt;b&gt;&lt;span style='font-family:inherit; color:rgb(85, 85, 85); background-image:initial; background-position:initial; background-size:initial; background-repeat:initial; background-attachment:initial; background-origin:initial; background-clip:initial;'&gt;scalable&lt;/span&gt;&lt;/b&gt;&lt;/a&gt;&lt;span style='font-family:inherit; color:black; background-image:initial; background-position:initial; background-size:initial; background-repeat:initial; background-attachment:initial; background-origin:initial; background-clip:initial;'&gt;, &lt;/span&gt;&lt;a href='https://vims-wm.maps.arcgis.com/apps/MapJournal/index.html?appid=62c80853313743f3acf5a83ab420d015' style='color:rgb(0, 121, 193); text-decoration-line:none; font-family:inherit;' rel='nofollow ugc'&gt;&lt;b&gt;&lt;span style='font-family:inherit; color:rgb(85, 85, 85); background-image:initial; background-position:initial; background-size:initial; background-repeat:initial; background-attachment:initial; background-origin:initial; background-clip:initial;'&gt;measurable&lt;/span&gt;&lt;/b&gt;&lt;/a&gt;&lt;span style='font-family:inherit; color:black; background-image:initial; background-position:initial; background-size:initial; background-repeat:initial; background-attachment:initial; background-origin:initial; background-clip:initial;'&gt;, and &lt;/span&gt;&lt;a href='https://vims-wm.maps.arcgis.com/apps/MapJournal/index.html?appid=62c80853313743f3acf5a83ab420d015' style='color:rgb(0, 121, 193); text-decoration-line:none; font-family:inherit;' rel='nofollow ugc'&gt;&lt;b&gt;&lt;span style='font-family:inherit; color:rgb(85, 85, 85); background-image:initial; background-position:initial; background-size:initial; background-repeat:initial; background-attachment:initial; background-origin:initial; background-clip:initial;'&gt;make a comparable difference&lt;/span&gt;&lt;/b&gt;&lt;/a&gt;&lt;span style='font-family:inherit; color:black; background-image:initial; background-position:initial; background-size:initial; background-repeat:initial; background-attachment:initial; background-origin:initial; background-clip:initial;'&gt; worldwide. In pursuit of this, the project's mantra is to advance the field of emergency preparedness by advancing research to help &lt;i&gt;predict flooding resulting from storm surge, rain, and tides&lt;/i&gt;.&lt;/span&gt;&lt;/p&gt;&lt;p style='margin-top:0px; margin-bottom:0in;'&gt;&lt;span style='font-family:inherit; color:rgb(0, 0, 0);'&gt;The StormSense Project is an award-winning inundation forecasting research initiative participating in the Global City Teams Challenge (GCTC). The project was initially funded by the National Institute of Standards and Technology via a Replicable Smart City Technologies grant announced by the White House in Sept. 2016. City of Virginia Beach participates regionally. Most of the funding for the sensors within the city are funded through the Capital Improvement Program (CIP).&lt;/span&gt;&lt;br /&gt;&lt;/p&gt;&lt;p style='margin-top:0px; margin-bottom:0in;'&gt;&lt;span style='font-family:inherit; color:rgb(0, 0, 0);'&gt;&lt;br /&gt;&lt;/span&gt;&lt;/p&gt;&lt;p style='margin-top:0px; margin-bottom:0in;'&gt;&lt;span style='font-family:inherit; color:rgb(0, 0, 0);'&gt;This dataset shows water levels and several other parameters in near real-time as shown in the keywords from different sensor sources in the Hampton Roads region. It does not show any historic data. The data can be plotted on a live map. Current sensor types include ultrasonic, radar and others dependent on the parameter. The data sources are from USGS and StormSense. Each location may have a single or multiple sensors for different purposes. The data collection efforts will provide crucial information about the surface water flow across the region at all times of the year in different weather scenarios. The data will be used to support modeling efforts for research communities, emergency preparedness and planning, decision making processes by city officials during adverse weather conditions such as hurricanes, nor’easter and other rainfall events.&lt;/span&gt;&lt;br /&gt;&lt;/p&gt;&lt;div style='font-family:inherit;'&gt;&lt;br /&gt;&lt;/div&gt;</idAbs>
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