Integrated Flood Analysis System (IFAS)For local flood forecasting and warning using

satellite-based rainfall and global GIS databases for poorly gauged basin anywhere

in the world

Global Flood Alert System (GFAS) – Streamflow

Kazuhiko FUKAMI

International Centre for Water Hazard and Risk Management under the auspices of UNESCO

(ICHARM),Public Works Research Institute (PWRI), Japan

Integrated Flood Analysis System IFASToolkit to implement “Global Flood Alert System (GFAS) – Streamflow”

Example of Satellite-based rainfall data disclosed without cost through internet

Product name 3B42RT CMORPH QMORPH GSMaP_NRT

Developer and provider NASA/GSFC NOAA/CPC NOAA/CPC JAXA/EORC

Coverage N60°- S60°

Resolution 0.25° 0.25° 0.25° 0.1°

Resolution time 3 hours 3 hours 0.5 hour 1 hour

Time lag 10 hours 15 hours 2.5 hours 4 hours

Coordinate system WGS

Historical data Dec 1997- Dec 2002- nearest past 2 days Dec. 2007～

Sensors

TRMM/TMI Aqua/AMSR-E AMSU-B DMSP/SSM/I IR

Aqua/AMSR-E AMSU-B

DMSP/SSM/I TRMM/TMI

IR

Aqua/AMADEOS-AMSR SSM/IIR

TRMM/TMI SR-E Ⅱ/

AMSU-B

4

GSMaP_NRT

JAXA, JST-CREST(Prof. Ken’ichi

OKAMOTO, Osaka Pref. Univ. et al.)

ICHARM/PWRI

http://sharaku.eorc.jaxa.jp/GSMaP/index.htm

5

Present

１hour later

2 hour later

＋

＋

＝

＋

＋

＝

3h additional rainfall

Present

１hour later

2 hour later

3h additional rainfall

Slowly moving pattern

= Large spatial variance of cumulative rainfall

On a certain scale

Quickly moving pattern

= Small spatial variance of cumulative rainfall

On a certain scale

Adjustment by rainfall-area movement patternUnderestimate Correct

Selection of grids to characterize spatial variance

( ) )2(4:12

0

2 　　　 =−= ∑=

nXXn

Sn

iicn

( ) )1(:1

0

hoursktxk

Xk

tii ∑

=

=

Yoshiki Shiraishi, ICHARM

2008

)4(),( kSmXR ncc ×=

( ){ } )3(1809.784.0055.0ln8641.2 ++−= kSm n

6

Fig.1 3 hour-rainfall（-2009/08/08 03:00（UTC））（Left：Ground gauged, Center_L：GFAS、Center_R：GSMaP、Right：Corrected GSMaP）

Comparison

-999 ～ 0

0 ～ 10

10 ～ 20

20 ～ 40

40 ～ 60

60 ～ 80

80 ～ 100

> 100

①GSMaP uses several satellite sensors which aren’t used in GFAS, so the rainfall distribution is different from each other.②GSMaP is basically underestimated because GSMaP didn’t get the information from satellite microwave radiometer during the peak heavy rainfall.

1.Background 2.Correction 3.Analysis of Morakot 4.Conclusion

7

GSMaP Total Rainfall in Taiwan [mm](2009/08/06 18:00 ～ 08/10 09:00 (UTC))

1:2000000

114100

112111

179175

171172

169152

155142

140131

129105

114112

122118

125120

123117

110110

96 109

470521

438474

399388

357344

308292

275251

242207

219196

196191

173177

169 182

160 166

489470

452458

521481

554516

588577

589556

600624

605680

648742

647708

585 556

684 639

544483

447435

560 556

585 567

102101101928670575652

106107103817358484541

168145136164150139153175183

148128109131131138162159164

151109109121126127150144133

142129118125120126133125119

142135120106109116128105115

1221151119910411110499106

1071079592103108969784

106100100102106109848576

1019498101101102927774

10197103969998848168

1009610610210181747467

56 60 66 78 98 99 111 99 96

571672774952106011351057995855

500550667756848980957884822

430464529606649725788821716

359394424475527601676678693

297318348400461489528549582

237275299336365392420433444

207234265289310342365380401

191200236239252298334345348

183192213199206228271314317

180192183190204202222250264

173179178194

203 193 163 165 168 188 183 164 174

232 211 199 168 186

407408408414512512556572605

384384376390458487545593588

379386382373420409473535503

456443406355338326373450440

530489410331368380396444466

562540492401416435462510513

598546503491501527525543551

657602648624630585577581547

7557668349741033760824681514

7117898971010130915261041899810

6808239821053

1006 1087 1226 1278 1224 1008 916 773 629

795 1110 1494 1495 1206

570567553563587

440448460477555547527546619

611 539 468 466

588 574 599 628 616 619 627 624 594

626 640 657 695 734 717 645 602 614

454033232339607478

403629234153515975

203219205219209179196161170

171193198206190163164163184

136155182180163146160159172

128146144164156150143109140

1221301341261191321238366

114116108951031121415851

879998939198494140

757870796646302936

626768634325282339

555956473221162150

56

70 66 49 32 16 24 36 41 51

54 37 32 29 22 37 49 55

762722602555490477484485490

729682629545455472482490502

666650561488476489480487484

645612559490466470464461459

608564526484459448431428404

487490440421426415399368373

430448389370385417379361349

371376340321351364361338271

304320321312301331326302224

251262289267261276271280242

237252248243

192 188 205 207 227 234 236 238 229

233 234 239 253 237

646601529482520525568566548

645500495466494516515576524

508437398415446514534560517

462405396435459503549549529

456456454467467455575483499

438481493483457502567568549

499484524487477496474480512

501497468480483458459481483

463445446444468518534496479

527403440454532534508501468

765677589502

475 482 490 513 498 480 601 861 852

471 488 502 523 520

615599579555548

581574550536624665611587542

581 562 592 585

529 530 537 551 609 635 622 609 601

532 497 510 545 583 598 652 621 617

596984898779

807678727481

837784687889

879277837879

256246233236236237

213227203219230201

203195193210217162

185220195202194121

23220518416312296

1781701221199799

13910679769194

997167737071

657366565670

566466536698

4767666671115

5673738290105

597278777862

75 84 88 73 72 62

570530496547529476

494535521560543513

515505577559545525

489510547575533535

483496548537509501

494518491492457451

500482465473411414

497467460430394377

475461415403365342

419401368331308293

369358347328295294

359389361309283254

304340337295277275

275292297282259228

488 514 514 501 499 516

449 489 491 464 480 491

411 442 444 454 465 484

394 418 422 431 462 476

388 427 445 439 467 492

401 435 459 480 507 528

419 429 466 503 543 536

426 452 479 526 559 571

458 469 503 533 563 562

459 477 490 509 527 538

GFAS Total Rainfall in Taiwan [mm](2009/08/06 18:00 ～ 08/10 09:00 (UTC))

1:2000000

420395435431478526493459

742631690709840781763784

780750821787973905801720

7577917948018791084924772

739725665762908963932705

7778018418959061032953619

728804881791693660688501

596650677613524454477379

464518502439368338304319

358272272243268188189123

2841631321411811219860

137121961051081105695

1021169676956585112

103909989475381109

10272811045610210899

Observed Total Rainfall in Taiwan [mm](2009/08/06 18:00 ～ 08/10 09:00 (UTC))

1:2000000

688

139

205

64

766

82

667

384

31661

381

700

1857

317

360

645

185

989

608

79

333

300

223

342

775

111

363

215189

90

572

92

195

153

229

635579

904

1120

167

67

458

210

206155

417

116

122

231

144

348323

473

791

63

87

92

349

228

101

483

203

93

227

330

2129

12

471

152

413

77

442

271

83

173

713

480

1286

327

388

186

191

65

706

544

363

57

261

404

720

533

210

342

227

147

135

40

992

229318

1

46

846

188

107

304

462

46

1014556

98

91

527

304

820

305

102

266

351

808

537

653

502

1179

2283

233

1014

1777

1059

1112

699

208

725

2723

886

278

823

1480

857

974

751

1024 218

1023

175

2891825

916

225

573

723

709

1116

2605

362

252

2011

635

823

1567

2161

868

1995

914

865

572

1929 2052

775

215

838

941

1257

447

656

1624

1330

408335

536

1418

630

229

744

2147

1101

832

2336

322740

712

1027

1096

511

422

1169

280

522

1305

172

302

942

275

636

1001

379

294

1259

1678

728

235868

327

878

1408

838

555

1194

227

252330

2749

977

662

1096

267

1307

250

638

522

631

261

913

630

688

541

389

642

219

854

469

276

570

528

578

2082

323

8582648

1932

1367

147

638

-999 ～ 0

0 ～ 100

100 ～ 200

200 ～ 500

500 ～ 800

800 ～ 1000

1000 ～ 1500

1500 ～ 2000

> 2000

Fig.1 Total rainfall（2009/08/06 18:00 ～ 08/10 09:00）（UTC）（Left：Ground gauged, Center_L：GFAS、Center_R：GSMaP、Right：Corrected GSMaP）

Comparison

①GSMaP is underestimated. However, rainfall area which concentrates on south part of Taiwan is similarly distributed.②Comparing corrected GSMaP with ground gauged rainfall, corrected GSMaP is better than GSMaP row data.

1.Background 2.Correction 3.Analysis of Morakot 4.Conclusion

Global Precipitation Measurement (GPM)

Core SatelliteDual Frequency RadarMulti Frequency Radiometer

Observation of rainfall with more accurate and higher resolution

Adjustment of data from constellation satellites

8 Constellation SatellitesSatellites with Micro-wave Radiometers

More frequent Observation

Global Observation every 3 hours

Current Observation System: TRMM and other orbital Satellites, and 5 Geostationary Satellites

JAXA (Japan)Dual frequency Radar, Rocket

NASA(US)Satellite Bus, Micro-wave

gauging measurement

Cooperation ：NOAA(US),NASA(US),ESA(EU), China, Korea and others

•IWRM•Flood Forecasting•Forecasting of cropproductivity

–Earth heating Phenomena–Study of Climate Change–Improvement offorecasting system

Integrated Flood Analysis System IFASToolkit to implement “Global Flood Alert System (GFAS) – Streamflow”

10

Design concept of IFAS

1. To prepare interfaces to get satellite-based rainfall data in addition to ground-based rainfall data, to secure the worldwide availability of input data for flood forecasting/analysis system.

2. To adopt two types of distributed-parameter hydrologic models, the parameters of which can be estimated as the first approximation based on globally-available GIS databases to secure the worldwide availability of hydrologic models for flood forecasting/analysis.

3. To implement GIS analysis modules in the system to set up the parameters for the flood forecasting/analysis model, therefore no need to depend on external GIS softwares.

5. To prepare a series of easy-to-understand graphical user interfaces for data input, modeling, runoff-analysis, and displaying the outputs.

6. To distribute the executable program, free of charge, from the ICHARM/PWRI website

11

2) Ground-based rainfall data•Observed local data (The source of

local ownership of forecasts)

1 ) Satellite-based rainfall data• TMPA-3B42RT (NASA)• QMORPH/CMORPH (NOAA)• GSMaP (JST/CREST, OPU, JAXA etc.)

Global coverage : between 60N-60S latitude

Mesh size: 0.25 degrees (25km) or 0.1 degree (10km)

Automatic Data Extraction for area of interest

Provided by NASA, NOAA, JAXA and IFNet-GFAS through the Internet for free

Use of Satellite Information

3) Adjustment of Satellite

Rainfall1. Self adjustment within observations

2. Physically-based statistcal adjustment

3. Data assimilation with ground observations

4. Regional model+ AGCM + Satellite observations

Modeling functionDEM dataGTOPO30 (USGS)

Create a basin boundary

Create a river channel network

Set parameter

automatically

automatically

automatically

IFAS creates a basin boundary and a river channel network use of digital elevation data.

IFAS estimates parameter based on the classification that we set up beforehand.

800 634 533 500 382 329 307 290 268 259 290 262

688 580 504 400 352 301 297 290 271 267 253 246

688 547 429 381 340 309 310 294 292 299 300 246

643 510 400 382 358 345 322 314 306 299 300 245

600 471 401 400 376 347 334 320 300 287 273 271

491 452 426 406 385 368 348 318 300 287 291 288

504 495 490 470 447 430 393 355 313 280 268 262

560 569 570 546 512 500 445 384 307 289 265 259

653 672 682 670 623 576 517 500 417 323 291 296

800 806 828 827 731 668 586 597 549 382 297 288

Landuse dataGLCC (USGS)

YHyM/BTOP Model Ao et. al, 1998 ~

Ver. 1.4 (Coming Very Soon)

Runoff AnalysisPWRI-Distributed Hydrological Model

(PDHM) Suzuki et.al, 1996 ~ Ver. 2.0

• Easy calibration for parameters• Tested in many basins in Japan• Suitable for flash floods in small andmedium basins < a few tens of thousands square

kilometers

Multi Runoff Analysis Engines

• Well-known in journal papers in the world• Tested Easy parameter calibration• Tested in a variety of climatic and

hydrologic conditions of the world• Suitable also for seasonal floods

in large continental basins

Display Results (IFAS-PDHM)Hydro-graph Plan view of river discharge

Graph of tank water level and discharge Plan view of satellite-based rainfall

18

Example of outputs overlaid on Google Earth

図-6 Google earth上での表示（川内川）（計算結果（上段タンク水位）の平面図表示）

Purpose of the training course To build capacities to undertake hydrological prediction/forecasting in relatively ungauged basins using satellite-based rainfall.

ParticipantsEthiopia, Zambia, Cuba, Argentina, Bangladesh, Guatemala, Nepal

(7countries)

ProgramRemote Sensing of Precipitation from Space (JAXA)Historical evolution of flood management system in Japan Introduction of Global Flood Alert System Operating procedures for IFAS Validation method of satellite-based rainfall Current conditions and problems in each country Validation plans using IFAS

TRAINING WORKSHOPFOR THE GLOBAL FLOOD ALERT SYSTEM (GFAS) VALIDATION3-8 Oct, 2008 JAPAN

Experimental application to actual basinsMembramo River Basin in Republic of Indonesia

A=78,992km2Un-gauged basin

Pasig River Basin in Republic of the Philippines

A=499km2

Awash River Basin in Ethiopia

A=66,308km2

Barak River Basinin Bangladesh

A=31,026m2

IFAS : local ownership of flood forecasts

TrainingSystem

Local DataGlobal Data

Low accuracy High accuracy