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Description: Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban...
Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban Flooding Patterns and Extents
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Description: Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban...
Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban Flooding Patterns and Extents

Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban Flooding Patterns and Extents

Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban Flooding Patterns and Extents

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Description: Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban...
Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban Flooding Patterns and Extents
Abstract
651 flooding tweet locations along with dates and times were extracted using publicly available data on Twitter for Allegheny County, Pennsylvania. The flooding tweet locations were then used to perform statistical analysis of the data. Results indicated that approximately 70% of the flood tweets were spatially located in the southern half of the county. The locations were compared to existing FEMA flood zones and it was determined that 55% of the flood tweet locations were outside designated flood zone areas. The majority of the flood tweets occurred between the months of May and September indicating flash flooding by heat-induced thunderstorms is likely. This hypothesis was tested and confirmed for flood tweet locations within the Saw Mill Run watershed in Allegheny County with 15-minute high-resolution radar rainfall data. Rainfall distribution patterns were calculated for the flood events in Saw Mill Run, which can be used for future planning and design efforts.
651 flooding tweet locations along with dates and times were extracted using publicly available data on Twitter for Allegheny County, Pennsylvania. The flooding tweet locations were then used to perform statistical analysis of the data. Results indicated that approximately 70% of the flood tweets were spatially located in the southern half of the county. The locations were compared to existing FEMA flood zones and it was determined that 55% of the flood tweet locations were outside designated flood zone areas. The majority of the flood tweets occurred between the months of May and September indicating flash flooding by heat-induced thunderstorms is likely. This hypothesis was tested and confirmed for flood tweet locations within the Saw Mill Run watershed in Allegheny County with 15-minute high-resolution radar rainfall data. Rainfall distribution patterns were calculated for the flood events in Saw Mill Run, which can be used for future planning and design efforts.
SpeakerBatroney, Thomas
Presentation time
11:10:00
11:30:00
Session time
10:30:00
11:30:00
Session#StormwaterData: Using Technology to Inform Program Decisions
Session number317
TopicIntelligent Water, Stormwater, Green Infrastructure, and Wet Weather
TopicIntelligent Water, Stormwater, Green Infrastructure, and Wet Weather
Author(s)
T. Batroney
Author(s)T. Batroney1;
Author affiliation(s)AKRF, PA1
SourceProceedings of the Water Environment Federation
Document typeConference Paper
PublisherWater Environment Federation
Print publication date Oct 2020
DOI10.2175/193864718825157893
Volume / Issue
Content sourceWEFTEC
Copyright2020
Word count15

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Description: Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban...
Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban Flooding Patterns and Extents
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Details

Description: Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban...
Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban Flooding Patterns and Extents
Abstract
651 flooding tweet locations along with dates and times were extracted using publicly available data on Twitter for Allegheny County, Pennsylvania. The flooding tweet locations were then used to perform statistical analysis of the data. Results indicated that approximately 70% of the flood tweets were spatially located in the southern half of the county. The locations were compared to existing FEMA flood zones and it was determined that 55% of the flood tweet locations were outside designated flood zone areas. The majority of the flood tweets occurred between the months of May and September indicating flash flooding by heat-induced thunderstorms is likely. This hypothesis was tested and confirmed for flood tweet locations within the Saw Mill Run watershed in Allegheny County with 15-minute high-resolution radar rainfall data. Rainfall distribution patterns were calculated for the flood events in Saw Mill Run, which can be used for future planning and design efforts.
651 flooding tweet locations along with dates and times were extracted using publicly available data on Twitter for Allegheny County, Pennsylvania. The flooding tweet locations were then used to perform statistical analysis of the data. Results indicated that approximately 70% of the flood tweets were spatially located in the southern half of the county. The locations were compared to existing FEMA flood zones and it was determined that 55% of the flood tweet locations were outside designated flood zone areas. The majority of the flood tweets occurred between the months of May and September indicating flash flooding by heat-induced thunderstorms is likely. This hypothesis was tested and confirmed for flood tweet locations within the Saw Mill Run watershed in Allegheny County with 15-minute high-resolution radar rainfall data. Rainfall distribution patterns were calculated for the flood events in Saw Mill Run, which can be used for future planning and design efforts.
SpeakerBatroney, Thomas
Presentation time
11:10:00
11:30:00
Session time
10:30:00
11:30:00
Session#StormwaterData: Using Technology to Inform Program Decisions
Session number317
TopicIntelligent Water, Stormwater, Green Infrastructure, and Wet Weather
TopicIntelligent Water, Stormwater, Green Infrastructure, and Wet Weather
Author(s)
T. Batroney
Author(s)T. Batroney1;
Author affiliation(s)AKRF, PA1
SourceProceedings of the Water Environment Federation
Document typeConference Paper
PublisherWater Environment Federation
Print publication date Oct 2020
DOI10.2175/193864718825157893
Volume / Issue
Content sourceWEFTEC
Copyright2020
Word count15

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T. Batroney#. Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban Flooding Patterns and Extents. Water Environment Federation, 2020. Web. 30 May. 2025. <https://www.accesswater.org?id=-10028705CITANCHOR>.
T. Batroney#. Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban Flooding Patterns and Extents. Water Environment Federation, 2020. Accessed May 30, 2025. https://www.accesswater.org/?id=-10028705CITANCHOR.
T. Batroney#
Unlocking Twitter and High-Resolution Radar Rainfall to Better Understand Urban Flooding Patterns and Extents
Access Water
Water Environment Federation
October 6, 2020
May 30, 2025
https://www.accesswater.org/?id=-10028705CITANCHOR