Transcript Initial Results and Future Applications of a CONUS

Initial Results and Future
Applications of a CONUS-wide
Flash Flood Prediction System
Zachary Flamig
[email protected]
University of Oklahoma/School of Meteorology
NOAA/National Severe Storms Laboratory
In collaboration with:
JJ Gourley
NOAA/NSSL
October 25th, 2010
Suzanne Van Cooten
NOAA/NSSL
Yang Hong
Humberto Vergara
OU/CEES
National Flood Workshop, Houston, TX
OU/CEES
Looking inland…
Floods & Flash Floods around May 1st
Nashville, TN
>$1 Billion in damage
Flash Flood on June 14th
Oklahoma City, OK
>$1 Million in damage
Flash Flood on June 10th
Albert Pike Campground, AR
20 Fatalities
AP Photos
Flash Flood Prediction?
State of the Art: Gridded Flash Flood Guidance*

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Distributed hydrologic model for
soil moisture accounting
Rainfall/runoff model for runoff
potential prediction
Static model for critical runoff
threshold estimation
Ultimately derives rainfall threshold
which if exceeded means flash flooding
is occurring or will occur!
*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.
Flood
Exposure
Model
1,000
People Affected
$0
>$5M
Property Damage
$0
>$1M
Crop Damage
Probability
time
0
time
Requirements:
Flash Flood Scale (1 km2, Sub-Hourly Time Scale)
Probabilistic (Ensemble) Prediction
Probability
Forecast
Precipitation
Distributed
Hydrologic
Models
Return Period
Observed
Precipitation
Streamflow
National Mosaic and Multi-Sensor QPE (NMQ-)
Flooded Locations And Simulated Hydrographs (FLASH)
Probability
Flash Flood Prediction
Getting Observed Precipitation
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NMQ Q2,
radar only
product
0.01º x 0.01º
(~1km x 1km)
2.5 minute
update
Long term
reanalysis
(soon!)
Precipitation Forecasts
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Cloud resolving NWP from 4km2 to 1km2
HRRR primary candidate because it assimilates
NMQ 3D radar reflectivity field
Hydrologic Models
HL-RDHM
CREST

Jointly developed by OU/NASA

Developed by NWS

Runs operationally over globe

Runs operationally at RFCs
Simulated Threshold Frequency
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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
USGS 07196500 Illinois River near Tahlequah, OK
Return
Frequency
Full Archive
USGS Q
14 Year
USGS Q
14 Year
Simulated Q
2 Years
555 cms
549 cms
655 cms
5 Years
1119 cms
925 cms
841 cms
10 Years
1594 cms
1215 cms
959 cms
25 Years
2297 cms
1625 cms
1103 cms
50 Years
2888 cms
1962 cms
1207 cms
100 Years
3540 cms
2322 cms
1309 cms
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
Verification Methods
NWS flash flood reports (StormDat)
1.
+
Designed to encompass all events in
forecaster’s area of responsibility
-
Dependent upon NWS warning
process, population density
15-minute streamflow data from
USGS
2.
+
Objective measurement of
discharge
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Need flashy basins with basin area <
260 km2 (flash flood scale)
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Flash flood defined as 2-year return
period
SHAVE flash flood reports
3.
+
High spatial and temporal
resolution
+
Flood characteristics
-
Database is storm-targeted; does
not encompass all flash flood events
-
Dependent on population density
Event Type: Flood
Start Time: 6/27/2008 11:30 A.M.
Latitude: 38.013824
Longitude: -96.715266
Event
County:
ButlerType: Flash Flood
State: WFO:
Kansas OUN
Flood Nature: Overflow road other
Begin Date: 3/20/2007
Depth: 0.3 m
LateralBegin
Extent:Time:
300 m 9:30 A.M. CST
Comments:
HorseKay
corral on location was
County:
flooded.
CreekOK
flooded 1/4 mile west from
State:
location. Road closed at 150th and
Highway 77.
Severe Hazards Analysis and
Verification Experiment (SHAVE)*
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SHAVE reports are more
dense than NWS reports
(e.g., 50:1)
Unique data collected in
SHAVE
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Reports of no flooding

Specific impact

Lateral extent/depth/motion of
water
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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.
Lets see it!
Back to the Coast!
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Distributed hydrologic
model (HL-RDHM) run
for Tar & Neuse basins.
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Green dots represent
verification points
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Red dots are hand-off
points for hydrodynamic
ocean model (ADCIRC)
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NMQ-FLASH will allow
for distributed hydrologic
model results from
anywhere in the CONUS
including other coastal
areas (Texas, South
Carolina, etc)
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.
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
-1km2/2.5 min
Stormscale Rainfall Forecasts
Stormscale Distributed
Hydrologic Models
Probabilistic Forecast
Return Periods and
Estimated Impacts
5 hr
Q5
Q2
Hydrograph of Simulated and
Observed Discharge
Simulated surface
water flow
6”
8”
10”
40%
60%
80%
t=0100
t=0000
20
fatalities
10-11 June 2010, Albert Pike Rec
Area, Arkansas
t=2300
Probability of life-threatening
flash flood