Climate risks and adaptation in Asian coastal megacities: A synthesis

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Box 3.4 ■ Overview of Downscaling and Hydrological Analysis Carried out forHCMC StudyGHG Emission Scenarios PRECIS IR3SHigh +7.5 (A2) +4.4 (A1FI)Low +1.5 (B2) +2.9 (B1)Low-resolution outputs (~2o) from ECHAM’s (European Centre for Medium Range Weather Forecast-University of Hamburg) atmosphere-ocean-coupledglobal circulation model (GCM) Version 4 were downscaled by PRECIS (Providing Regional Climates for Impacts Studies, and a dynamic modeling tooldeveloped by the UK Met Office Hadley Centre for Climate Prediction and Research, precis.metoffice.com). Two IPCC SRES greenhouse gas emissionscenarios were used as inputs to the GCM. SRES A2 is a high-emission scenario, while B2 represents the low-emission world.ECHAM is considered a “moderate” GCM in that it does not give any extreme temperature or precipitation projections, but tends to be in themiddle ranges. However, other GCM’s are also available and need to be included in subsequent studies. PRECIS was used because it is the regionalmodeling tool that has been most widely used globally, as well as being the tool that the UNDP National Communication Support Unit recommendsfor countries receiving GEF funding.PRECIS gridded outputs at resolution 0.22o (~25km) for the Sai Gon-Dong Nai Basin were provided by SEA START RC. Daily outputs for maximum/minimum temperature and rainfall for the baseline decade (1994–2003) and a future decade (2050–59), which represent the year 2050, were takenas a key input for the hydrodynamic model—HydroGIS—to calculate the water and flood regime of Ho Chi Minh City. PRECIS gave the total andseasonal rainfall anomalies that are comparable, though with a slightly wider range than the JBIC/IR3S ensemble, which was used by the other citystudies in this collaborative initiative (see table below). By using PRECIS, the daily outputs as well as spatial distribution of climate variables were alsoobtained to get more in-depth information on temporal and geographic variables for the study area.The table below provides a comparison of 10 years averaged June-July-August rainfall from PRECIS and the IR3S rainfall ensemble for Ho ChiMinh City for the year 2050 (%change relative to baseline)Monsoon-driven seasonal rainfall years with maximum and minimumannual rainfall for each decade were selected to represent “wet” and“dry” years of the baseline and future A2 and B2 decades.Event-based rainfall extremes for the baseline and future timeslices were derived from the 1-, 3-, 5-, and 7-day maximum rainfall fromPRECIS over the HCMC urban area. Extreme rainfalls of 30- and 100-yearreturn periods were extrapolated from the log-log (power) regressionbetween the frequency of occurrence (years) and amount of each rainfall extreme. The 30-year and 100-year extremes and 1-, 3-, 5-, and 7-day rainfalldata were rescaled to the observed extreme rainfalls at Tan Song Nhat Airport. The scaling factors for each extreme period were used for scaling therespective future extreme rainfall.Source: Adapted from ADB (2010).master plan prepared by the Department of Planningand Architecture, the land use plan preparedby DoNRE, and the socioeconomic developmentplan prepared by the Department of Planningand Investment. These are prepared by differentagencies under different time scales with littlecoordination between them, thus posing a difficultproblem in estimating future infrastructure andurbanization scenarios. In terms of a developmentscenario for 2050, HCMC has an urban master planthat was approved in 1998. In 2007, a study wascompleted to adjust the HCMC master plan upto 2025 (commonly referred to as the AdjustmentPlan). 40 The city case study used the Adjustment Planas the basis of the most likely development scenario for2050 (ADB 2010).In terms of land use, key trends include a decliningpopulation in central HCMC; doughnut-shapedurbanization, with higher population growth within10 kms from the center of the city; and industries beingrelocated and established in industrial zones. Agricultureand forest land (primarily made up by theCan Gio biosphere reserve) situated in the rural andsuburban areas, has declined from 64 percent in 1997to 59 percent in 2006. According to DONRE’s landuse plans, open space is expected to decline by 25percent by 2020 (ADB 2010). Rivers and canals coverclose to 15 percent of the total land use, reflecting the40Even though it is in the process of being formally approvedby the government, in the interim, it is the recognizedupdate for the 1998 Master Plan.42 | Climate Risks and Adaptation in Asian Coastal Megacities: A Synthesis Report
original swamp land on which the city was settled.Roads and other transport facilities occupy around 3percent; land for industry and commerce is expandingrapidly and now represents about 5 percent ofthe city’s land use. There are 90 parks in HCMC. Inaddition to the urban master plan and the HCMCland use plans, the department of transportation hasprepared a transport master plan for HCMC until2020, which has been used for modeling impacts ofclimate change on the transport sector (ADB 2010).HCMC also has a power development plan and ahealth sector master plan, both to 2020. Similarly,a water supply master plan until 2025 is currentlyunder preparation (ADB 2010) and has been used tomodel impacts on the water sector in 2050.Flood protection infrastructures assumedfor the hydrological analysisHCMC has a planned flood protection dyke andsluice system to protect much of the city from floodingwith an estimated cost of $650 million. This is tobe implemented in phases, which will allow lessonslearned during implementation to be applied to thelater stages. The 2050 modeling has developed scenariosassuming implementation and no implementationof the proposed flood protection measures.Dynamic downscaling technique applied tomodel 2050 climate changeThe HCMC study used the SRES A2 and B2 scenariosas the enveloping case for high and low projections.Further, unlike the other cities in the study, whichused statistical downscaling, the HCMC case studyused both statistical downscaling and also a PRECISdynamic downscaling technique to model futureclimate change parameters (Box 3.4). The dynamicdownscaling approach allowed the study to addressthe complex hydrometeorological and oceanographicchanges. Specifically, PRECIS allowed simulationof mean (minimum and maximum temperatures)for the base case and A2 and B2 scenarios, simulationof daily rainfall data in the base year (averagedover 1994–2003) and for 2050 (based on averageof 2050–59). Based on this, the percent increase inrainfall in terms of average increase and increase forextreme events (1-in-30 year, 1-in-100 year, etc.) wascalculated. Thus, it was estimated that future extremerainfall under the high emissions scenario will increase bymore than 20 percent for a 1-in-30-year flood and by 30percent for a 1-in-100-year flood. This information wasthen used as input into the hydrological modeling.Inputs and outputs for the hydrologicalmodelingThe main drivers of the water regime in the HCMCinclude the following: seasonal monsoon-drivenrainfall, extreme rainfall due to typhoons and tropicalstorms in the vicinity of the city, local SLR, stormsurge, upstream-downstream inflow as a function ofcatchment basin hydrology, and various land usessuch as water management infrastructure, hydrologic/hydrodynamicconductivity, and water demandby sectors and geographic locations. Some of theseare related to regional climate change and are more afunction of land use and development. For instance,“over 75 percent of flooding points in HCMC haveoccurred following rainfall of 40mm even duringebb tide,” which indicates that surcharge from stormdrains is a major factor contributing to flooding. Forthe hydrological simulations, it was assumed that thepopulation and land use in 2050 were the same as thebase year (see HCMC annex). For the HCMC study,a hydrodynamic modeling tool—Hydro-GIS—wasused to integrate information about these driversand derive output variables (such as flood depth,duration, salinity distribution, etc) for an assessmentof risks and impacts in 2050.Estimates for sea level rise and storm surgeIn addition to using dynamic downscaling to estimateprecipitation changes, the study used the DIVA(Dynamic Interactive Vulnerability Assessment) tooldeveloped by the DINAS-COAST consortium. 41 Theresults from that tool yielded SLR of 0.26 m and 0.24 m41In DINAS-COAST, the DIVA method was applied toproduce a software tool that enables its users to producequantitative information on a range of coastal vulnerabilityindicators, for user-selected climatic and socioeconomicscenarios and adaptation policies, on national, regional andglobal scales, covering all coastal nations. http://www.pikpotsdam.de/research/research-domains/transdisciplinaryconcepts-and-methods/project-archive/favaia/divaEstimating Flood Impacts and Vulnerabilities in Coastal Cities | 43
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© 2010 The International Bank for
Page 7 and 8:
Figure 4.6 Damage Costs Associated
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AcknowledgmentsThis synthesis repor
Page 13 and 14: Executive SummaryIntroduction and R
Page 15 and 16: For each city, complex hydrometeoro
Page 17 and 18: infrastructure but a high emission
Page 19: these include strategies that focus
Page 23 and 24: policy implications have broader re
Page 25: 2Methodologies forDownscaling, Hydr
Page 28 and 29: Table 2.1 ■ Climate Change Foreca
Page 30 and 31: Return periods considered 18In this
Page 32 and 33: Figure 2.2 ■ Manila Rainfall-Runo
Page 34 and 35: Figure 2.3 ■ Estimation of Damage
Page 36 and 37: sion and distribution lines, and en
Page 38 and 39: Figure 2.5 ■ Possible Relationshi
Page 40 and 41: prices and the same prices are appl
Page 43 and 44: 3Estimating Flood Impactsand Vulner
Page 45 and 46: Table 3.2 ■ Bangkok Monthly Avera
Page 47 and 48: Estimation of storm surge in the ca
Page 49 and 50: Climate Change Impact and Adaptatio
Page 51 and 52: Figure 3.5a ■ Affected Condensed
Page 53 and 54: Manila’s current climate—Tropic
Page 55 and 56: Table 3.6 ■ Manila Climate Change
Page 57 and 58: Figure 3.10 ■ Areas of High Popul
Page 59 and 60: is also a key economic and financia
Page 61: Box 3.3 ■ HCMC in 2050Future land
Page 65 and 66: from 68 percent to 71 percent; that
Page 67 and 68: Table 3.15 ■ Districts Affected b
Page 69 and 70: Table 3.16 ■ Effects of Flooding
Page 71 and 72: 4Assessing Damage Costsand Prioriti
Page 73 and 74: Table 4.2 ■ Summary of Flood and
Page 75 and 76: uilt outside the cities and are not
Page 77 and 78: ■■■■■■For the eastern p
Page 79 and 80: Table 4.6 ■ Flood Damage Costs Wi
Page 81 and 82: Table 4.8 ■ Flood Damage Costs in
Page 83 and 84: Figure 4.5 ■ Loss Exceedance Curv
Page 85 and 86: Box 4.3 ■ Increased Time Costs an
Page 87 and 88: Table 4.11 ■ Adaptation Investmen
Page 89 and 90: Marikina River areas through a dam,
Page 91 and 92: Table 4.14 ■ Present Value of the
Page 93 and 94: of reducing vulnerability of the po
Page 95 and 96: 5Conclusions andPolicy Implications
Page 97 and 98: open land use is expected to be flo
Page 99 and 100: hydrometeorological data, yielding
Page 101 and 102: BibliographyAllen, M. R., and W. J.
Page 103: Reduction: Inventory and Prospect.
Page 106 and 107: a paper commissioned by JICA (Sugiy
Page 108 and 109: mercial and industrial establishmen
Page 110 and 111: ADB. The selection and prioritizati
Page 113 and 114:
AnnexCAdaptation to IncreasedFloodi
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of people and institutions to manag
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THE WORLD BANK1818 H Street, NWWash
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Climate risks and adaptation in Asian coastal megacities: A synthesis

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