automating flood damage assessment (katie graves, arup)

Katie GravesNovember 2013

Automating Flood Damage Assessment

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Agenda

• Introduction to Flood Damage Assessment• Types of Flooding• Types of Data• Challenges• Types of Analysis• Increasing Efficiencies

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Flood Damage Assessment

Residential Non-residential

Emergency Services

Other Critical Infrastructure

(other than emergency services)

Road and Rail (km)

Ground Floor

Upper Floor

Ground Floor

Upper Floor Road Rail

Receptors at risk of flooding

Scenario 1 Baseline

30 Year 807 307 257 9 1 56 38.14 0.20

75 Year 1100 600 550 44 4 91 81.54 0.32

100 Year 1212 712 662 50 6 106 99.64 0.37

30 Year CC 1162 662 612 45 5 102 95.79 0.36

75 Year CC 1555 1055 1005 70 9 174 170.68 0.54

100 Year CC 1650 1150 1100 77 10 190 194.84 0.68

2007 1356 856 806 60 8 146 140.47 0.56

Scenario 3

30 Year 779 279 229 9 0 50 28.83 0.20

75 Year 1067 567 517 43 3 79 60.04 0.31

100 Year 1173 673 623 49 4 91 74.11 0.36

30 Year CC 1122 622 572 44 4 86 71.87 0.35

75 Year CC 1477 977 927 67 8 146 131.17 0.52

100 Year CC 1574 1074 1024 74 10 158 150.35 0.62

2007 1277 777 727 57 7 114 97.51 0.54

Scenario 4 30 Year 659 159 109 4 0 40 14.37 0.20

75 Year 832 332 282 22 3 58 28.01 0.31

100 Year 914 414 364 22 4 69 36.77 0.36

Scenario 5 30 Year 644 144 94 2 0 37 12.84 0.20

75 Year 816 316 266 17 2 55 24.18 0.31

100 Year 854 354 304 18 3 62 32.11 0.36

Scenario 6

30 Year 614 114 64 0 0 33 8.71 0.15

75 Year 805 305 255 17 2 53 21.67 0.31

100 Year 848 348 298 18 3 61 29.37 0.36

30 Year CC 842 342 292 21 3 62 30.23 0.36

75 Year CC 1010 510 460 26 4 85 54.50 0.50

100 Year CC 1052 552 502 29 4 91 63.30 0.58

Receptors benefiting from solution

Benefit Scenario 3 over Scenario 1

30 Year 528 28 20 0 1 6 9.31 0.00

75 Year 533 33 25 1 1 12 21.49 0.01

100 Year 539 39 28 1 2 15 25.53 0.01

30 Year CC 540 40 30 1 1 16 23.91 0.01

75 Year CC 578 78 28 3 1 28 39.51 0.02

100 Year CC 576 76 26 3 0 32 44.49 0.06

2007 579 79 29 3 1 32 42.96 0.02


30 Year 648 148 98 5 1 16 23.78 0.00

75 Year 768 268 218 22 1 33 53.52 0.01

100 Year 798 298 248 28 2 37 62.88 0.01


30 Year 663 163 113 7 1 19 25.31 0.00

75 Year 784 284 234 27 2 36 57.36 0.01

100 Year 858 358 308 32 3 44 67.53 0.01

Do Nothing Net Present Value Damages

Flood Cell 1 Flood Cell 2 Flood Cell 3 Flood Cell 4 Flood Cell 5 Flood Cell 6 Flood Cell 7 Flood Cell 8 Total

Residential 1,000 5,160 1,105 12,045,054 354,045 12,406,364

Non-residential 1,250 6,540 1,505 540,654 549,949

Sub-total 2,250 - 11,700 2,610 - 12,585,708 - 354,045 12,956,313

Risks to life 65,000

Intangible benefit

Emergency Services 250,004

TOTAL 26,227,630

Do Minimum Net Present Value Damages


Residential 887 5,047 992 8,640,646 353,932 9,001,504

Non-residential 1,137 6,427 1,392 540,541 549,497

Sub-total 2,024 - 11,474 2,384 - 9,181,187 - 353,932 9,551,001


Intangible benefit


TOTAL 19,416,780

75 Year SOP Net Present Value Damages


Residential 590 - 297 4,750 695 - 297 2,540,564 - 297 353,635 2,899,343

Non-residential 840 - 297 6,130 1,095 - 297 540,244 - 297 - 297 547,121

Sub-total 1,430 - 594 10,880 1,790 - 594 3,080,808 - 594 353,338 3,446,464


Intangible benefit


TOTAL 7,207,480

Annual Averages

Property damages 2015 2020-2039 2040 - 2069 2070

onwardsPVD (pre-

capping)

PVD (disallow

ed)

PVD (capped)

Do Nothing 1,425,640 4,654,687 5,646,543 6,546,544 43,503,544 694,654 42,808,890

Do Minimum 1,350,456 1,486,223 2,478,079 3,378,080 15,606,455 654,354 14,952,101

75 Year SOP 52,405 77,839 103,273 128,707 4,564,064 4,564,064

Risk to Life 2015 2020-2039 2040 - 2069 2070

onwards PVD

Do Nothing 1,354 6,506 8,048 12,455 254,064

Do Minimum 1,154 4,504 7,540 10,654 168,713

75 Year SOP 840 3,545 6,505 84,056 115,406

Intangible Benefit 2015 2020-2039 2040 - 2069 2070

onwards PVD

Do Minimum 34,540 31,640 25,456 22,840 7,654,654

75 Year SOP 46,546 46,546 45,466 43,515 1,387,354

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What is Flood Risk?

• Flood risk = probability of flooding x impact of flooding

• Probability is the likelihood that a flood will occur over the period of a year.

• 1% probability of flood event refers to a 1 in 100 chance of occurrence.

• This would be a relatively large event. • This is a flood with a 100 year return period

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Flood Risk

• Flooding from rivers• Flooding from the sea• Flooding from surface water• Flooding from sewers• Flooding from groundwater• Flooding from infrastructure failure

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Modelling Flood Risk

• Hydraulic modelling outputs – Fluvial (ISIS/TuFLOW)- 1D cross section data- 2D raster data with water levels or

water depths• Hydraulic modelling outputs – Drainage

modelling (Infoworks ICM)- 1D Node data- Vector triangulated surface

representing flooding• Topographic data

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Challenges

• Rapidly modelling numerous scenarios and return periods• Naming multiple datasets• Long field names required• Iterative process• Engineers like spread sheets• Results required rapidly as the project evolves to feed back into

the design

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Flood Damage Assessment Analysis

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Flood Damage Assessment Analysis

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Increasing Efficiencies

• Iterative folders to run through files quickly• File naming using in-line variable substitution (parse path)• Results available spatially to allow any inconsistencies to be

picked up

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Increasing Efficiencies

Models can be re-run with different inputs

Geodatabases essential for long file names

Models can be run be people with little GIS experience

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Summary

• Flood damage assessment involves lots of complex calculations• Using models can allow these calculations to be calculated

quickly and efficiently in a spatial environment

Next Steps:• Encouraging engineers to adopt these approaches across multiple

projects.• Further automate different stages of the process and ensure that

the tools are user friendly.

Any Questions?

automating flood damage assessment (katie graves, arup)

Technology

flood

run

minimum 1