METU Civil Engineering Department and Fatih Keskin State Hydraulic - - PowerPoint PPT Presentation

• Dr. Ismail Yucel

METU Civil Engineering Department and Fatih Keskin State Hydraulic Works HydroPredict 2010 Prague Sep 20-23, 2010 Evaluation of Flash flood Events Using NWP Model and Remotely Sensed Rainfall Estimates

Outline

• Introduction
• Data & Methodology
• Satellite, Radar, Station and NWP rain
• Hydrologic Modeling
• Conclusion

Water and energy cycle

• Warming climate leads to heavy precipitation

events.

• This tends to increase the risk of flood

events.

250 mm 2500 mm

Annual Rainfall Distribution of Turkey

LONG-TERM OCCURRENCE DISTRIBUTION OF METEOROLOGICAL HAZARDS IN TURKEY ( 1940 - 2002 )

AVALANCHE 0% TORNEDO 0% THUNDERSTORM 2% FOG 1% HEAVY SNOW 8% HAIL 23% FLOOD 30% MUDFLOW 0% FROST 9% STORM/HEAVY WIND 27%

• Flood hazards represented 30 % of all water related disasters in Turkey.
• 1,344 people died due to 1,768 floods in last 50 years in Turkey.
• Economic damage is more than USD 3,000 million during this period.
• 255,640 ha agricultural area was effected.

MAJOR FLOODS AND LOSSES DATE AREA AFFECTED LOSS EVENT ECONOMIC LOSS DEATHS 9-15 May 1993 Eastern and Southeastern Parts Heavy rain Hundreds of houses damaged. Major losses to agriculture 5 1-2 Dec. 1994 SE, Adana Heavy rain Hundreds of houses damaged. Major losses to agriculture 1-5 May 1995 E, Bitlis Heavy rain $23,000,000.00 8-14 July 1995 Istanbul, Senirkent, Ankara, Trabzon Heavy rain, landslides $ 30,000,000.00 70 3-5 Nov. 1995 Izmir, Isparta, Antalya Floods $ 50,000,000.00 61 6 Feb. 1996 Izmir, Antalya, Canakkale Heavy rain 1,000 houses damaged 5 9 Aug. 1996 Istanbul Heavy rain $ 4,000,000.00 11-13 Aug. 1997 Istanbul, Zonguldak, Bursa, Bolu Heavy rain, landslides $ 1,000,000.00 13 6-22 May 1998 North, Southeast, South and Anatolia Heavy rain, large hail, landslides, mudslides $ 2,000,000,000.00 27 12 June 1998 Sanliurfa, Diyarbakir Heavy rain Roads flooded, bridge destroyed 8 9-13 Aug. 1998 Trabzon Torrential rain, landslides 300 building, 1 mosque destroyed 10 27 May 2000 Samsun, Tokat, Carsamba, Salipazari, Heavy rain Hundreds of houses flooded, roads, bridges damaged. 2 7-18 May 2001 Hatay, Osmaniye, Konya, Nevşehir Rainstorm, torrential rain $ 3,500,000.00 3 10-12 May 2001 Antalya Heavy rain 500 homes flooded, 37 buildings damaged, 4 bridges collapsed 10-14 Nov. 2001 Rize, Artvin Heavy rain, mudslides Buildings, roads, highways, bridges damaged 8

• Dec. 2001

Mersin, Izmir, Istanbul, Ankara, Icel, Yalova Heavy rain, blizzards, high wind speeds $ 30,000,000.00 5 23-25 July 2002 Rize, Corum, Yozgat, Kars, Tokat, Van Torrential rain, high wind speeds, mudslides $ 20,000,000.00 40

• Investigation of heavy rainfall events occurred during Sep 7-12 2009.
• Rainfall occured 10 times gerater than September average value (25 mm)

during these days.

• Station, satellite, radar, and NWP model rainfall data are used.

0.5 1 1.5 2 2.5 3 3.5 1 5 9 1 3 1 7 2 1 1 5 9 1 3 1 7 2 1 1 5 9 1 3 1 7 2 1 Hour Area-averaged raınfall (mm) HE Ortalama İstasyon Ortalama

NOAA’s Satellite Rainfall Algorithm: Hydro Estimator (HE)

Sep 8, 2009 (gauge) Sep 8, 2009 (HE) Sep 8, 2009 (Radar) Sep 9, 2009 (gauge) Sep 9, 2009 (HE) Sep 9, 2009 (Radar)

Event totals for 7-9 Sep, 2009

Rain gauge Satellite Algorithm

Weather Research and Forecasting (WRF) model Simulations:

12-km and 4-km WRF domain setups 3-D Var data asimilation

WRF with and without 3D-Var Simulations for Sep 8,9,10,11, and 12, 2009

Hourly Daily Event Totals

Satellite rain (Sep 8, 2009) Gauge rain (Sep 8, 2009)

1/5000 scaled Topographic map is used in the study.

Ayamama Basin Characteristics:

Land use Soil type

Ayamama Basin Characteristics:

Topography Sope Sub-basins

Mean slope Mean Elevation Accumulation Time Longest Channel Length Basin Area 6.94 % 86,64 meter 7.11 hour 41,314 km 71,02 km2

00:00:00 7-9-2009 00:00:00 8-9-2009 00:00:00 9-9-2009 00:00:00 10-9-2009 00:00:00 11-9-2009 00:00:00 12-9-2009 00:00:00 13-9-2009 0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 200.0 220.0 240.0 260.0 [m^3/s] Debi 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 [mm/h] Yagis

Ayamama Deresi Modelleme

50 100 150 200 250 300 HE Radar Station WRF_NA WRF_A

September 5 September 6 September 7 September 8 September 9 September 10 September 11 September 12

Mean gauge

rain

Runoff (gauge) Runoff (HE) Mean radar rain Runoff (WRF) Runoff

(radar)

HEC-HMM Hydrological Modeling

Ayamama_Main 15937.10 15487.10 15087.10 14737.10 14312.10 13962.10 13562.10 13187.10 12762.10 12387.10 12012.10 11512.10 11112.10 10637.10 10287.10 9912.107 9562.107 9162.107 8787.107 8408.316 7937.106 7587.106 7212.106 6312.106 5762.106 4887.106 4196.927 3666.750 2843.568 1785.938 1310.938 860.9385 410.9385 A y am a ma Ayamama_1 4575.827 4175.827 3775.827 3425.827 3050.827 2725.827 2375.827 2000.827 1675.827 1325.827 975.8277 631.4237 A ya mam a_1

15937.10 15387.10 15062.10 14762.10 14362.10 14062.10 13737.10 13337.10 12987.10 12612.10 12312.10 11812.10 11512.10 11162.10 10887.10 10587.10 10287.10 9962.107 9662.107 9337.107 8937.107 8562.107 8212.107 7962.106 7687.106 7412.106 7137.106 6312.106 6012.106 5709.065 5385.921 4987.106 4662.106 4196.927 3875.452 3528.358 3165.309 2843.568 2410.938 2060.938 1735.938 1310.938 1010.938 760.9385 510.9385 260.9385

Ayamama Creek Plan: Plan 01 15.09.2010

Input is prepared in ArcGIS with help of HEC-GeoRAS module Imported in HEC-RAS and run in steady state mode Water coverage calculations along with river path for determining flooded areas

Satellite (HE) Radar Station HEC-RAS Ras Mapper Results:

WRF-No assimilation WRF with assimilation

Comparison between HE and Radar

Summary and Conclusions

• The performance of the HE together with the radar, rain gauge and NWP model

data is investigated to monitor and quantify the precipitation events for accuracy assesment and hydrological model application.

• Satellite rainfall estimates potentially improve spatial prediction of precipitation in

data poor areas.

• HE underestimates the precipitation, but its frequency cycle matches well with
• bservations.
• The data poor areas can be filled by the radar data but the radar data should be

used after full calibration process and error elimination.

• Different precipitation inputs resulted in different storm hydrographs.
• Based on the records, the realistic hydrograph is obtained from radar precipitation

data.

• Some differences in the coverage of the flooded areas are obtained in Ayamama

basin after using peak values of the storm hydrographs in HEC-RAS program.