StormSense: Difference between revisions
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|leader=Jon Loftis | |leader=Jon Loftis | ||
|imagecaption=StormSense | |imagecaption=StormSense | ||
|municipalities=Newport News VA, | |municipalities=Newport News VA, Virginia Beach VA, Norfolk VA, Hampton VA, Portsmouth VA, Chesapeake VA, Williamsburg VA, York County VA | ||
|status=Implemented | |status=Implemented | ||
|website=https://vims-wm.maps.arcgis.com/apps/MapJournal/index.html?appid=62c80853313743f3acf5a83ab420d015 | |website=https://vims-wm.maps.arcgis.com/apps/MapJournal/index.html?appid=62c80853313743f3acf5a83ab420d015 | ||
| | |description=Objectives | ||
* Apply modeling to address multiple-flood types to determine the probable areas at risk by utilizing fixed sensors, crowd-sourced data collection verified by post-flood analysis. | |||
* Use new state-of-the-art high resolution hydrodynamic models driven with atmospheric model weather predictions to forecast flooding from storm surge, rain, and tides at the street-level scale to improve disaster preparedness. | * Use new state-of-the-art high resolution hydrodynamic models driven with atmospheric model weather predictions to forecast flooding from storm surge, rain, and tides at the street-level scale to improve disaster preparedness. | ||
|challenges=* Communities are often at risk from different types for flooding, however, current models tend to focus on a single type/source | |challenges=* Communities are often at risk from different types for flooding, however, current models tend to focus on a single type/source | ||
| Line 14: | Line 14: | ||
* Forecast model integration with existing GIS systems for short term pre-disaster planning and deployment of resources | * Forecast model integration with existing GIS systems for short term pre-disaster planning and deployment of resources | ||
|solutions=A Long-Term Predictive Modeling Plan for local, regional, national, and global applications described [https://wm1693.app.box.com/s/v2nw4b01cwj1py6xwaxi6i7r0hbl9s57 here]. | |solutions=A Long-Term Predictive Modeling Plan for local, regional, national, and global applications described [https://wm1693.app.box.com/s/v2nw4b01cwj1py6xwaxi6i7r0hbl9s57 here]. | ||
|requirements= | |requirements=* Determine applicable models best suited to local conditions | ||
* Determine applicable models best suited to local conditions | |||
* Beginning with tidal/surge modeling, conduct local verification of models vs. “ground truth” | * Beginning with tidal/surge modeling, conduct local verification of models vs. “ground truth” | ||
* Determine locations for additional sensors and types | * Determine locations for additional sensors and types | ||
| Line 21: | Line 20: | ||
* Recruit/train local personnel to take real-time readings to update the forecasting | * Recruit/train local personnel to take real-time readings to update the forecasting | ||
* Expand the program to neighboring jurisdictions, then regionally | * Expand the program to neighboring jurisdictions, then regionally | ||
|kpi= | |kpi=* Verify the accuracy of the VIMS TideWatch predictions with post-storm analysis | ||
* Verify the accuracy of the VIMS TideWatch predictions with post-storm analysis | |||
* Verify the accuracy of the multi-flood type models with post-storm analysis with future goals are to improve prediction of flood depths and extents by 10% between stages 2 and 3; data was collected during Jan. 2016 winter storm event; not yet validated. | * Verify the accuracy of the multi-flood type models with post-storm analysis with future goals are to improve prediction of flood depths and extents by 10% between stages 2 and 3; data was collected during Jan. 2016 winter storm event; not yet validated. | ||
|measurement= | |measurement=* Statistical analysis of forecasts vs. time issued, actual flood area and depth. | ||
* Statistical analysis of forecasts vs. time issued, actual flood area and depth. | |||
* Emergency response-time analytics during upcoming flood scenarios | * Emergency response-time analytics during upcoming flood scenarios | ||
|standards= | |standards=* Sensors utilizing common internet protocols over the city’s WiFi and existing SCADA systems | ||
* Sensors utilizing common internet protocols over the city’s WiFi and existing SCADA systems | |||
* Crowd sourced data collection via a smartphone application | * Crowd sourced data collection via a smartphone application | ||
* Modeling will be accessible via a website | * Modeling will be accessible via a website | ||
| Line 34: | Line 30: | ||
* Expand the program and modeled areas to neighboring jurisdictions, then regionally via A Long-Term Predictive Modeling Plan for local, regional, national, and global applications | * Expand the program and modeled areas to neighboring jurisdictions, then regionally via A Long-Term Predictive Modeling Plan for local, regional, national, and global applications | ||
|cybersecurity=TBD | |cybersecurity=TBD | ||
|impacts= | |impacts=* Predicts the timing of flooding and flooded evacuation routes | ||
* Predicts the timing of flooding and flooded evacuation routes | |||
* Aids in rerouting emergency routes for public safety | * Aids in rerouting emergency routes for public safety | ||
* Saves lives and reduces property damage | * Saves lives and reduces property damage | ||
* Identified future mitigation projects | * Identified future mitigation projects | ||
|demonstration= | |demonstration=* Phase I Pilot/Demonstration: | ||
* Phase I Pilot/Demonstration: | |||
# Deploy the VIMS forecast and Tidal/Surge maps | # Deploy the VIMS forecast and Tidal/Surge maps | ||
# Deploy the data collection application | # Deploy the data collection application | ||
| Line 50: | Line 44: | ||
# Add additional TideWatch gauges in the James River | # Add additional TideWatch gauges in the James River | ||
# Expand the project throughout the Peninsula and into other parts of the Hampton Roads Region | # Expand the project throughout the Peninsula and into other parts of the Hampton Roads Region | ||
|chapter=Predictive Modeling | |||
|supercluster=Public Safety | |supercluster=Public Safety | ||
|year=2016, 2017, 2018 | |year=2016, 2017, 2018 | ||
|title=StormSense - Tidal, Riverine, Inland, Surge Flood Management Program | |title=StormSense - Tidal, Riverine, Inland, Surge Flood Management Program | ||
}} | }} | ||
Latest revision as of 05:53, January 25, 2023
| StormSense | |
|---|---|
| |
 StormSense | |
| Team Organizations | Virginia Institute of Marine Science (VIMS) College of William and Mary Commonwealth Center for Recurrent Flooding Resilience State of VA Department of Health |
| Team Leaders | Jon Loftis |
| Participating Municipalities | Newport News VA Virginia Beach VA Norfolk VA Hampton VA Portsmouth VA Chesapeake VA Williamsburg VA York County VA |
| Status | Implemented |
| Document | None |
Description
Objectives
- Apply modeling to address multiple-flood types to determine the probable areas at risk by utilizing fixed sensors, crowd-sourced data collection verified by post-flood analysis.
- Use new state-of-the-art high resolution hydrodynamic models driven with atmospheric model weather predictions to forecast flooding from storm surge, rain, and tides at the street-level scale to improve disaster preparedness.
Challenges
- Communities are often at risk from different types for flooding, however, current models tend to focus on a single type/source
- Sensors and gauges are typically deployed to detect single types of flooding (riverine, tidal, rainfall, etc.)
- Forecast model integration with existing GIS systems for short term pre-disaster planning and deployment of resources
Solutions
A Long-Term Predictive Modeling Plan for local, regional, national, and global applications described here.
Major Requirements
- Determine applicable models best suited to local conditions
- Beginning with tidal/surge modeling, conduct local verification of models vs. “ground truth”
- Determine locations for additional sensors and types
- Utilize the existing WiFi connectivity for sensors, and alerting systems
- Recruit/train local personnel to take real-time readings to update the forecasting
- Expand the program to neighboring jurisdictions, then regionally
Performance Targets
| Key Performance Indicators (KPIs) | Measurement Methods |
|---|---|
|
|
Standards, Replicability, Scalability, and Sustainability
- Sensors utilizing common internet protocols over the city’s WiFi and existing SCADA systems
- Crowd sourced data collection via a smartphone application
- Modeling will be accessible via a website
- Linkages to alerting would be via the flood model’s Online GIS Data Release Platform and potentially through the SLR mobile App
- Expand the program and modeled areas to neighboring jurisdictions, then regionally via A Long-Term Predictive Modeling Plan for local, regional, national, and global applications
Cybersecurity and Privacy
TBD
Impacts
- Predicts the timing of flooding and flooded evacuation routes
- Aids in rerouting emergency routes for public safety
- Saves lives and reduces property damage
- Identified future mitigation projects
Demonstration/Deployment
- Phase I Pilot/Demonstration:
- Deploy the VIMS forecast and Tidal/Surge maps
- Deploy the data collection application
- Verify accuracy of maps and forecasts as opportunities arise
- Phase II Deployment:
- Add additional flood forecasting tools and display methods
- Add additional fixed sensors and collection infrastructure
- Add additional TideWatch gauges in the James River
- Expand the project throughout the Peninsula and into other parts of the Hampton Roads Region