1. Initial Results and Future Applications of a CONUS - wide Flash Flood Prediction System Zachary Flamig Zac.Flamig@noaa.gov University of Oklahoma/School of Meteorology NOAA/National Severe Storms Laboratory In collaboration with: JJ Gourley Suzanne Van Cooten Yang Hong Humberto Vergara NOAA/NSSL NOAA/NSSL OU/CEES OU/CEES October 25 th, 2010 National Flood Workshop, Houston, TX

2. Looking inland… Flash Flood on June 10 th Albert Pike Campground, AR 20 Fatalities AP Photos Floods & Flash Floods around May 1st Nashville, TN >$1 Billion in damage Flash Flood on June 14 th Oklahoma City, OK >$1 Million in damage

3. Flash Flood Prediction? State of the Art: Gridded Flash Flood Guidance*  Distributed hydrologic model for soil moisture accounting  Rainfall/runoff model for runoff potential prediction  Static model for critical runoff threshold estimation *Schmidt, J., A. J. Anderson, and J. H. Paul, 2007: Spatially-variable, physically-derived flash flood guidance. Preprints 21st Conference on Hydrology, San Antonio, Amer. Meteor. Soc., 6B.2. Ultimately derives rainfall threshold which if exceeded means flash flooding is occurring or will occur! X

4. Flash Flood Prediction Observed Precipitation Forecast Precipitation Distributed Hydrologic Models Streamflow time Return Period time Flood Exposure Model $0 >$1M Crop Damage Probability $0 >$5M Property Damage Probability 0 1,000 People Affected Probability Requirements: Flash Flood Scale (1 km 2, Sub-Hourly Time Scale) Probabilistic (Ensemble) Prediction National Mosaic and Multi-Sensor QPE (NMQ-) Flooded Locations And Simulated Hydrographs (FLASH )

5. Getting Observed Precipitation  NMQ Q2, radar only product  0.01º x 0.01º (~1km x 1km)  2.5 minute update  Long term reanalysis (soon!)

6. Precipitation Forecasts  Cloud resolving NWP from 4km 2 to 1km 2  HRRR primary candidate because it assimilates NMQ 3D radar reflectivity field

7. Hydrologic Models CREST HL-RDHM  Jointly developed by OU/NASA  Runs operationally over globe  Developed by NWS  Runs operationally at RFCs

8. Simulated Threshold Frequency  Requires a long archive of precipitation (10+ years)  Run the model using the precipitation archive  Compute Log Pearson-III flood frequencies for each grid cell Return Frequency Full Archive USGS Q 14 Year USGS Q 14 Year Simulated Q 2 Years555 cms549 cms655 cms 5 Years1119 cms925 cms841 cms 10 Years1594 cms1215 cms959 cms 25 Years2297 cms1625 cms1103 cms 50 Years2888 cms1962 cms1207 cms 100 Years3540 cms2322 cms1309 cms USGS 07196500 Illinois River near Tahlequah, OK

9. Flood Exposure Model  Risk = Hazard (dynamic) * Vulnerability (static)  Property damage from ABRFC area for flash floods  Utilizes StormDat polygon data from 2006-2010  Only hazard information used in shown figure

10. Event Type: Flood Start Time: 6/27/2008 11:30 A.M. Latitude: 38.013824 Longitude: -96.715266 County: Butler State: Kansas Flood Nature: Overflow road other Depth: 0.3 m Lateral Extent: 300 m Comments: Horse corral on location was flooded. Creek flooded 1/4 mile west from location. Road closed at 150th and Highway 77. Verification Methods 1. NWS flash flood reports (StormDat) + Designed to encompass all events in forecaster’s area of responsibility - Dependent upon NWS warning process, population density 2. 15-minute streamflow data from USGS + Objective measurement of discharge - Need flashy basins with basin area < 260 km 2 (flash flood scale) - Flash flood defined as 2-year return period 3. SHAVE flash flood reports + High spatial and temporal resolution + Flood characteristics - Database is storm-targeted; does not encompass all flash flood events - Dependent on population density Event Type: Flash Flood WFO: OUN Begin Date: 3/20/2007 Begin Time: 9:30 A.M. CST County: Kay State: OK

11. Severe Hazards Analysis and Verification Experiment (SHAVE)*  SHAVE reports are more dense than NWS reports (e.g., 50:1)  Unique data collected in SHAVE  Reports of no flooding  Specific impact  Lateral extent/depth/motion of water  Respondent-estimated frequency  Lightning Creek flooding, OKC July 2010 *Ortega, K.E., T.M. Smith, K.L. Manross, A.G. Kolodziej, K.A. Scharfenberg, A. Witt, and J.J. Gourley, 2009: The severe hazards and verification experiment, Bull. Amer. Meteor. Soc., 90, 1519-1530.

12. Lets see it!

13. Back to the Coast!  Distributed hydrologic model (HL-RDHM) run for Tar & Neuse basins.  Green dots represent verification points  Red dots are hand-off points for hydrodynamic ocean model (ADCIRC)  NMQ-FLASH will allow for distributed hydrologic model results from anywhere in the CONUS including other coastal areas (Texas, South Carolina, etc)

14. Real-time Simulations  Non-optimized ensemble produces reasonable spread already at this early stage; optimized ensemble from NMQ-FLASH will produce a spread that completely envelopes the observed hydrograph.

15. National Mosaic and Multi-Sensor QPE (NMQ-) Flooded Locations And Simulated Hydrographs (FLASH) - A CONUS-wide flash-flood forecasting demonstration system NMQ/Q2 Rainfall Observations - 1km 2 /2.5 min Stormscale Rainfall Forecasts Stormscale Distributed Hydrologic Models Probabilistic Forecast Return Periods and Estimated Impacts 10-11 June 2010, Albert Pike Rec Area, Arkansas 10” 8” 6” Q2Q2 Q5Q5 5 hr Hydrograph of Simulated and Observed Discharge Simulated surface water flow 20 fatalities 80% 60% 40% Probability of life-threatening flash flood t=2300 t=0000 t=0100