Climate Change Impact Climate Change Impact and Adaptation in Asian and Adaptation in Asian

Coastal CitiesCoastal CitiesA Joint Study by the World Bank, JICA and ADB

Objective of the StudyObjective of the Study

Strengthen the understanding of the Strengthen the understanding of the economic, social and environmental economic, social and environmental impacts of climate variability and impacts of climate variability and change change

Identify what national and municipal Identify what national and municipal decision makers should expect in the decision makers should expect in the way of climate change impacts, and way of climate change impacts, and the scale of those impacts in coastal the scale of those impacts in coastal cities cities

Four CitiesFour Cities

Bangkok (World Bank)Bangkok (World Bank) Ho Chi Minh City (ADB)Ho Chi Minh City (ADB) Kolkata (World Bank)Kolkata (World Bank) Manila (JICA)Manila (JICA)

Asian Mega-City HotspotsAsian Mega-City Hotspots

Source: Adapted from (WWF, 2009).Source: Adapted from (WWF, 2009).

Study FrameworkStudy Framework Develop risk assessment modules for Develop risk assessment modules for

current conditionscurrent conditions Downscale climate change forecasts Downscale climate change forecasts

for 2050for 2050 Apply climate change parameters to Apply climate change parameters to

hazard moduleshazard modules Assess change in riskAssess change in risk Examine adaptation measures to Examine adaptation measures to

reduce risksreduce risks

Risk assessment processRisk assessment process Hazard moduleHazard module

• Event frequency relationshipsEvent frequency relationships• Hydro-meteorological modelsHydro-meteorological models

Exposure module (assets at risk)Exposure module (assets at risk) Vulnerability module (event-damage)Vulnerability module (event-damage) Damage module (damage-loss)Damage module (damage-loss) Loss moduleLoss module

• Loss exceedance relationshipLoss exceedance relationship• Expected annual loss (EAL)Expected annual loss (EAL)

Climate Change ScenariosClimate Change Scenarios

Study examined the A1FI and the B1 Study examined the A1FI and the B1 scenarios as likely high-low casesscenarios as likely high-low cases

Used 2050 as the time horizon, which Used 2050 as the time horizon, which is in line with time frame needed for is in line with time frame needed for major flood protection major flood protection planning/investments planning/investments

Statistical DownscalingStatistical Downscaling

Bangkok and Manila city case studies used Bangkok and Manila city case studies used Statistical downscaling estimates provided by the Statistical downscaling estimates provided by the Integrated Research System for Sustainability Integrated Research System for Sustainability Science (IR3S) at the University of TokyoScience (IR3S) at the University of Tokyo • Mean temperature increases factors,Mean temperature increases factors,• Precipitable water increase factors, Precipitable water increase factors, • Extreme 24-hour precipitation increase factors, Extreme 24-hour precipitation increase factors, • Seasonal mean precipitation increases factors.Seasonal mean precipitation increases factors.

Masahiro Sugiyama, Final Report, Study on Climate Change Masahiro Sugiyama, Final Report, Study on Climate Change Adaptation and Mitigation in Asian Coastal Mega-cities, Integrated Adaptation and Mitigation in Asian Coastal Mega-cities, Integrated Research System for Sustainability Science (IR3S) at the Research System for Sustainability Science (IR3S) at the University of Tokyo, July 2008. University of Tokyo, July 2008.

IR3S report highlights (1)IR3S report highlights (1) There is a robust linear relationship between the local There is a robust linear relationship between the local

temperature increase in each target area and the global temperature increase in each target area and the global mean temperature increasemean temperature increase

Precipitable water in the four megacity areas increase at a Precipitable water in the four megacity areas increase at a rate of ~ 8%/rate of ~ 8%/00K or largerK or larger

For mean seasonal precipitation change, instead of For mean seasonal precipitation change, instead of analyzing precipitation change per temperature change, analyzing precipitation change per temperature change, the study develop scenarios of seasonal mean precipitation the study develop scenarios of seasonal mean precipitation by averaging monthly data of the IPCC climate model by averaging monthly data of the IPCC climate model outputs outputs

IR3S report highlights (2)IR3S report highlights (2) For return periods larger than about 10 years, the the IPCC For return periods larger than about 10 years, the the IPCC

models projected extreme 24-hr precipitation change models projected extreme 24-hr precipitation change ranges from ~ 3%/ranges from ~ 3%/00K to ~ 28 %/K to ~ 28 %/00K. The uncertainty in K. The uncertainty in precipitation extremes is much larger than in temperature precipitation extremes is much larger than in temperature or precipitable water.or precipitable water.

To provide 24-hr extreme precipitation increases scenarios, To provide 24-hr extreme precipitation increases scenarios, the study used “physical intuition”. Some researchers the study used “physical intuition”. Some researchers argued that precipitation extremes should scale as the argued that precipitation extremes should scale as the moisture availability in the atmosphere, that is, precipitable moisture availability in the atmosphere, that is, precipitable water (Allen and Ingram 2002; Trenberth et al. 2003).water (Allen and Ingram 2002; Trenberth et al. 2003).

Allen, M. R., and W. J. Ingram, 2002: Constrains on future changes in climate and the Allen, M. R., and W. J. Ingram, 2002: Constrains on future changes in climate and the hydrologic cycle. Nature, 419, 224-232, doi: 10.1038/nature01092; hydrologic cycle. Nature, 419, 224-232, doi: 10.1038/nature01092;

Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons, 2003: The changing Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons, 2003: The changing character of precipitation. Bulletin of the American Meteorological Society, 84, 1205-character of precipitation. Bulletin of the American Meteorological Society, 84, 1205-1217, doi: 10.1175/BAMS-84-9-1205.1217, doi: 10.1175/BAMS-84-9-1205.

IR3S ResultsIR3S Results

Nested Regional Circulation ModelNested Regional Circulation Model

HCMCHCMC Southeast Asia (SEA) Regional Center (RC) Southeast Asia (SEA) Regional Center (RC)

for the Systems for Analysis, Research and for the Systems for Analysis, Research and Training (START) undertook the workTraining (START) undertook the work

Applied the PRECIS model nested in the Applied the PRECIS model nested in the low resolution (~2low resolution (~2oo) ECHAM Version 4 ) ECHAM Version 4 AOGCM model AOGCM model

Used the A2 and B2 scenarios Used the A2 and B2 scenarios

Comparison of seasonal rainfallComparison of seasonal rainfall

Bangkok City Case StudyBangkok City Case Study

Panya Consultants headed studyPanya Consultants headed study Bangkok lies in the Chao Phraya Bangkok lies in the Chao Phraya

River Basin with area of 159,000 kmRiver Basin with area of 159,000 km22

Tropical monsoon climateTropical monsoon climate 1,130 mm average annual 1,130 mm average annual

precipitation varying from 1,000 mm precipitation varying from 1,000 mm to 1,600 mmto 1,600 mm

Flooding driven by high seasonal Flooding driven by high seasonal rainfall events over 2 to 3 monthsrainfall events over 2 to 3 months

Chao Phraya River BasinChao Phraya River Basin

Bangkok historic floodingBangkok historic flooding

1995 flood caused serious damage 1995 flood caused serious damage and was estimated to have a 1/30 and was estimated to have a 1/30 year return periodyear return period

Recent floods have occurred in 2002 Recent floods have occurred in 2002 and 2006and 2006

Flood protection system is designed Flood protection system is designed for 1/30-yr flood. There is a for 1/30-yr flood. There is a surrounding embankment and surrounding embankment and pumped drainagepumped drainage

Chao Phraya Basin and Bangkok Hydrologic Chao Phraya Basin and Bangkok Hydrologic Simulation Model SchematicSimulation Model Schematic

2050 Climate Change Factors2050 Climate Change Factors

Bangkok Climate Change Impact – Bangkok Climate Change Impact – Hazard Module AdjustmentsHazard Module Adjustments

Mean seasonal increases were applied to Mean seasonal increases were applied to the 1/10-yr, 1/30-yr, and 1/100-yr the 1/10-yr, 1/30-yr, and 1/100-yr precipitation events and distributed across precipitation events and distributed across the watershed spatially and temporally the watershed spatially and temporally using historical rainfall distribution using historical rainfall distribution patterns (1995)patterns (1995)

SLR applied to hydrologic model boundary SLR applied to hydrologic model boundary conditionsconditions

Land subsidence applied to digital Land subsidence applied to digital elevation mapselevation maps

Maximum water depth for 1/30-yr Maximum water depth for 1/30-yr flood 2008 and 2050 A1FIflood 2008 and 2050 A1FI

Increasing HazardIncreasing Hazard

Direct and indirect lossesDirect and indirect losses1/30-yr A1FI Scenarion1/30-yr A1FI Scenarion

Loss exceedance curve Loss exceedance curve

Expected annual loss (mn Baht)Expected annual loss (mn Baht)

Summary of Bangkok FindingsSummary of Bangkok Findings The economic damage of flooding will rise The economic damage of flooding will rise

roughly four-fold in 2050. roughly four-fold in 2050. 70% of the cost in 2050 would be attributed to 70% of the cost in 2050 would be attributed to

land subsidence alone.land subsidence alone. About one million inhabitants of Bangkok and About one million inhabitants of Bangkok and

Samut Prakarn will be affected by the A1FI Samut Prakarn will be affected by the A1FI climate change condition in 2050. climate change condition in 2050.

One in eight of the affected inhabitants will be One in eight of the affected inhabitants will be from the condensed housing areas where most from the condensed housing areas where most live below the poverty level. live below the poverty level.

One-third of the total affected people may be One-third of the total affected people may be subjected to more than a half-meter inundation subjected to more than a half-meter inundation for at least one week. for at least one week.

Adaptation OptionsAdaptation Options

Adaptation benefits = Losses AvoidedAdaptation benefits = Losses Avoided

The expected annual The expected annual benefit with an benefit with an adaptation project is adaptation project is the difference in the the difference in the area between flood area between flood damage cost curves damage cost curves without and with the without and with the project.project.

Adaptation Benefits Adaptation Benefits = EAL= EALWithout ProjectWithout Project – – EALEALWith ProjectWith Project

Contact PointsContact Points

Synthesis Report:Synthesis Report:

Poonam Pillai, Poonam Pillai, ppillai@worldbank.org

Bangkok City Case Study:Bangkok City Case Study:

Jan Bojo, Jan Bojo, jbojo@worldbank.org

Manila City Case Study Manila City Case Study

Megumi Muto, Megumi Muto, Muto.Megumi@jica.go.jp

HCMC City Case StudyHCMC City Case Study

Jay Roop, jroop@adb.orgJay Roop, jroop@adb.org

Thank you!Thank you!