“THE TRUTH REVEALED: WHAT DOES A SINGLE MEASUREMENT … · “THE TRUTH REVEALED: WHAT DOES A...
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“THE TRUTH REVEALED: WHAT DOES A SINGLE MEASUREMENT MEAN WHEN IT COMES TO FLOOD PREDICTION AND ALERTING” Baxter E. Vieux, PhD, P.E. Principal Vieux & Associates, Inc., Norman Oklahoma Professor Emeritus, University of Oklahoma Adjunct Professor, Rice University, Houston Texas
Transcript of “THE TRUTH REVEALED: WHAT DOES A SINGLE MEASUREMENT … · “THE TRUTH REVEALED: WHAT DOES A...
“THE TRUTH REVEALED: WHAT DOES A SINGLE MEASUREMENT MEAN
WHEN IT COMES TO FLOOD PREDICTION AND ALERTING”
Baxter E. Vieux, PhD, P.E. Principal Vieux & Associates, Inc., Norman Oklahoma
Professor Emeritus, University of Oklahoma Adjunct Professor, Rice University, Houston Texas
3 Examples
Radar and gauge measurements as input to a distributed physics-based hydrologic model for operational applications.
1. Austin TX Memorial Day 2015 Flooding (May 22 to June 1) October 24th and 30th, 2015
2. Wimberley TX/Edwards Aquifer Authority
May 23-24 2015
October 30th 2015
3. Houston TX
October 22-30, 2015
April 17-18, 2016
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Bull Creek, City of Austin TX, Flood Early Warning System Vieux & Associates, Inc. 3
Memorial Day 2015 Flooding
City of Austin TX, Flood Early Warning System GARR Rainfall Total (5-22 to 6-01)
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NWS
High Resolution Rapid Refresh QPF HRRR (1-15 hr)
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May 24 400 May 24 500 May 24 600 May 24 700 May 24 800 May 24 900 May 24 1000 May 24 1100
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GARR + QPF on May 23 Hydrographs on May 24
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Shoal Creek Forecast May 25-26, 2015
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City of Austin Texas Flood Early Warning System (FEWS) Vieux & Associates, Inc.
Forecast Inundation
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Halloween, October 30 2015
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City of Austin Texas Flood Early Warning System (FEWS)
Forecast Lead-time
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4-hr lead time @ 9:00am How it played out within ½ ft.
RainVieux: Improving rainfall
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2015-05-25 • Bias 0.85 • 102 used 74 excluded • 27.1% AD before
calibration • 10.7% AD after calibration
Gauge-Radar QA/QC October 30, 2015
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Model of Blanco River
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Vflo 500ft Gridded Model RainVieux GARR hourly input
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Model Results (unadjusted)
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0
20,000
40,000
60,000
80,000
100,000
120,000
May
-22
May
-23
May
-24
May
-25
May
-26
May
-27
May
-28
May
-29
Dis
chag
e (c
fs)
SimulatedObserved
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October 30 2015
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Radar Rainfall Products Harris County DPR GARR
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Comparison of GARR and DPR
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GARR
DPR
G=22.052” GARR=19.087”
G=22.052” DPR=22.056”
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Depth Duration Frequency
Oct 22-30, 2015
Houston, TX Brays Bayou (Oct 22-30)
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Brays Bayou
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A few days ago…
Houston – Brays Bayou April 17, 2016
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Houston – Harris County April 17, 2016
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DPR GARR
ID REASON
3460 No Data at Location
3630 Rainfall below Calibration Threshold
3800 No Data at Location
3990 No Data at Location
4110 No Data at Location
4120 No Data at Location
4130 No Data at Location
4140 Outlier (by Mean Field Bias)
4150 No Data at Location
4160 No Data at Location
4400 Outlier (by Average Difference)
4410 No Data at Location
Bias Statistics
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Bias Correction “1.0 = Perfect”
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360 0.330 0.269 0.331 380 0.390 0.685 0.394 400 3.280 2.660 3.018 410 2.520 1.795 2.534 420 2.800 2.533 3.074 430 2.840 2.054 2.751 435 1.880 1.571 2.031 440 2.680 1.867 2.550 460 4.160 2.831 4.152 465 5.400 3.400 5.371 470 5.600 3.790 5.727 475 5.760 3.588 5.643 480 3.240 2.671 3.295 485 3.760 2.546 3.760 490 3.880 3.296 3.911 520 3.720 2.639 3.625 560 2.880 2.145 3.099 1000 3.560 2.688 3.441 1020 2.720 1.996 2.485 2010 5.400 3.942 5.324 2110 5.280 3.681 5.285 2210 2.760 1.940 2.757 2220 3.680 2.367 3.502 2240 3.680 2.845 3.747 2260 4.280 2.916 4.286 2270 6.080 3.265 6.008 2280 0.880 0.572 0.989 2290 5.470 3.130 5.219 3010 2.840 2.949 3.196 3020 2.800 2.162 2.919 3030 1.640 1.280 1.680 3040 3.600 2.220 3.034 3050 2.640 2.473 3.254 3070 1.920 1.556 1.895 3490 2.960 2.071 2.917 3500 5.040 3.530 4.888
00.20.40.60.8
11.21.41.6
18-A
pr 7
:12
18-A
pr 9
:36
18-A
pr 1
2:00
18-A
pr 1
4:24
18-A
pr 1
6:48
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pr 1
9:12
18-A
pr 2
1:36
19-A
pr 0
:00
Corr
ectio
n Fa
ctor
Summary ■ Texas witnessed a series of extreme events in 2015
2016
■ Predictive modeling with current GARR and forecast rainfall provides lead time, helping protect citizens from flood hazards
■ A single measurement is not that useful, but a network of rain gauges, or gridded radar precipitation as input to a gridded representation of watershed runoff is… and that’s the truth!
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