1. National Situational Awareness Predictive Analytics (SAPA) Jesse Rozelle FEMA Region VIII GIS Coordinator FEMA Modeling Task Force SME Jesse.rozelle@fema.dhs.gov MOTF/Risk Analytics Training July 27-31, 2015

2. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov National SAPA How do we create consistent national situational awareness predictive analytics?

3. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov National SAPA Steps toward standardization 1)Define SAPA operational requirements 2)Define standard processes based on hazard, scale, and required turnaround time 3)Establish a framework for successful practices 4)Strengthen our analytic credibility

4. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Defining SAPA Operational Requirements Who is our audience? FEMA? State, County, and local partners? All of the above?

5. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Defining Situational Awareness Requirements What analytics do we need? Some examples Primary List: Hazard Extent Population Impacts Building Impacts CIKR (Critical Infrastructure/Key Resources) Impacts Transportation Impacts Secondary List: Mass Care Requirements NFIP Impacts/Coverage Other? We can create a very long list of potential impact analytics, but should we first all agree on basic, then extended lists?

6. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Defining SAPA Operational Requirements What is our goal? Situational awareness? Expediting declarations? Expediting IA rental assistance? Expediting response resources? Public outreach and risk communication? Projecting long term economic impacts?

7. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov What does SAPA Look Like? Product Formats Operations Dashboard Viewer GeoPlatform ViewerSpreadsheets Static Maps

8. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Define Standard Processes Based on Hazard, Scale, and Turnaround Time Develop SAPA SOP’s for each hazard, for large scale and small scale events. SOP’s should cover basic and advanced analytic component lists

9. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Scope of the Event/Turnaround Time First, what scale of SAPA is appropriate (and possible) for a given event? What is the extent of the disaster? Is our product time dependent? (most likely) Is the scale of a request realistic with the given time frame? The answer for deriving analytics for Minot and Hurricane Sandy will be very different

10. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Is our disaster striking a small, rural town? Minot, ND 2011

11. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Is our disaster causing impacts across a state? Colorado Floods of 2013

12. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Is our disaster causing devastating impacts across the entire east coast? Hurricane Sandy

13. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Depending on the scale, phase of an event and time for completion, the analysis method will vary The goal is always to provide the most detailed analytics possible, in an acceptable timeframe Managing expectations for what can be provided is critical The larger the extent of an event, the lower the detail of the analytics possible The shorter the turnaround time allowed, the lower the detail of the analytics possible Finding a middle ground is key

14. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Weather Watches/Warning, Pre Activation Example

15. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Your RRCC is activated for a flooding response, flood gages show major to historic flooding, and the extent of impacts is still unknown. Some questions you’ll want to ponder before beginning your analysis: How many communities could be affected based on USGS stream gages? One community, or 50? 100? Multiple states? How soon do you need to provide estimates? Two hours, two days, or two weeks? Do you want to provide basic impact analytics (number of households/people affected, CIKR)? Or do you want detailed economic impact projections? Imminent Flooding Event Sample Request:

16. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Small Scale Event – One Community (2 FTE) 1-3 hours – DFIRM based exposure 1 week – custom inundation mapping 2-3 weeks – event based inundation mapping, economic impacts and percent damage per structure Custom inundation mapping availability dependent on access to hydrologist support, high resolution terrain data (LIDAR)

17. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Statewide Event – Regional – (3-4FTE) 1 day – DFIRM based exposure 2-3 months– custom inundation mapping 3-6 months– event based inundation mapping, economic impacts and percent damage per structure Custom inundation mapping availability dependent on access to hydrologist support, high resolution terrain data (LIDAR)

18. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov National Level 1 Event – Full MOTF Activation (8 FTE) 1 day – SLOSH/NHC advisory based exposure – updated daily 1 week - high water mark based event inundation mapping 3 weeks – final custom storm surge inundation mapping for entire event 3 months– event based inundation mapping, full suite of impacts to all sectors and programs 1 year– event based inundation mapping, full suite of impacts to all sectors and programs

19. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Other Federal Agencies Are the Authority on Estimating the Hazard Always defer to the authoritative science agency for estimating the extent and severity of each hazard USGS, NOAA, NWS, SPC, NHC These agencies are the authority on hazard extent, but they do not estimate impacts (SPC is beginning to deliver very rough impact information) FEMA is the lead on impacts Flood inundation mapping is currently unsolved for

20. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Common Pitfalls When Estimating the Hazard in Hazus The level of accuracy you get out of Hazus, is dependent on the accuracy of your inputs, time spent setting up your model, and SME experience with Hazus prior to the request. Garbage in, garbage out. Quality in, quality out. The following are common mistakes which can lead to inaccurate analytics when using Hazus. Hazus can estimate the hazard when OFA data isn’t available, but its real value lies in loss estimation Creating your own earthquake scenarios in Hazus earthquake vs. using USGS shakemaps Using the Hazus level 1 flood methodology – inundation mapping for an event is very challenging Using Hurrevac wind field data from outdated advisories when using the Hazus hurricane wind model

21. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Hazus Flood Model Time Investment/Limitations There are limitations for all three Hazus models, but the flood model limitations are most prominent Hazus level 1 flood analysis for 1 county takes approximately 2 days to run full H and H with 10 meter NED. Detailed site specific Hazus flood estimates for one county takes about 2 weeks DFIRM exposure estimation for 1 county takes about 1 hour

22. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Hazus Level 1 Flood Methodology LIDAR derived level 1 flood hazard methodology is very time consuming, if it works at all. 30/10meter DEM derived flood hazard is low resolution. Over estimation for level 1 flood model aggregated general building stock. This is minimized with the dasymetric inventory. Time required from start to completion? Approximately 2 days of processing per county, assuming no problem reaches or unresolvable errors. Issues are being addressed in the Hazus modernization effort for the future, but for now is not applicable for response

23. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov National Hazus Level 1 2009 Archive National Hazus level 1 analysis run in 2009 for every county in the US; offers a means to skip level 1 hydrology Lower level of confidence, intended for general county by county risk Utilized 30 meter resolution terrain data, outdated hydrological and hydraulic methodology, and homogenous distribution aggregated building stock loss estimation methodology Average AAL reported by NWS (Verify) $6-8B Hazus AAL from national study $60B Use of year 2000 census data vs 2010

24. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Analyzing Flood Losses Using FEMA’s Hazus Flood Model Aggregated vs. Site Specific Building Losses

25. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Establishing a Framework for Successful Analytical Processes 1)Build out an Org Chart of SME’s 2)Train and Certify those SME’s, invest in new SME’s 3)Establish QA/QC processes

26. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Who is providing SAPA and when? Build out an organizational chart for contributors to SAPA Includes names, titles, and organizational location; not just titles Establish roles/responsibilities for regional staff, MOTF, AGTS, EAD, HQ Recovery Build out a chart for regional and national hypothetical events; not just level 1, but level 2, 3 Plan strategically for how this would look in the future (NHAP/institutionalizing the MOTF and other staffing initiatives), and how it would look next week.

27. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov How do we standardize SAPA? Develop New SME’s, and Maintain Current SME’s Identify key players for the future, and next week Make sure they’re qualified Train them Train them again Not just Hazus training! Focus on this steady state, not only during response Certify and credential SME’s GISP’s, ArcGIS Professional certification, Hazus certification

28. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Establish Credibility in our Analytics Consistency Establish pre defined products we’ll provide as a cadre Establish pre defined product formats we’ll provide as a cadre (Geoplatform viewers, ArcGIS Operations Dashboards, static pdf/jpg map templates) Delivery – upon activation, don’t wait for requests, implement our SOPs

29. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Establish Credibility in our Analytics Transparency Clearly document your loss estimation methods so they can be provided to our customers. This includes data sources, impact estimation methodologies, and how recent your information was generated. The more details page in the FEMA GeoPlatform provides a great place to do so.

30. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Establish Credibility in our Analytics Validity Are you prepared to stand behind your analytics? Are you willing to publicly put your name on it? Are you willing to answer press inquiries? Are you documenting your methodology in detail in Geoplatform? Are you practicing proper QA/QC on your numbers before they go out?

31. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov QA/QC processes are crucial! A second set of eyes on your results before distributing can often catch easily identified issues.

32. Jesse.rozelle@fema.dhs.gov FEMA.MOTF@fema.dhs.gov Questions?