Budhi Setiawan Civil Engineering Department, Sriwijaya University INDONESIA Senior Technical Advisor...
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Transcript of Budhi Setiawan Civil Engineering Department, Sriwijaya University INDONESIA Senior Technical Advisor...
Budhi SetiawanCivil Engineering Department, Sriwijaya University INDONESIA
Senior Technical Advisor on Office for Climate Change Resilience – Ministry of National Development Planning
Climate Risk and Adaptation Assessment in City Level Greater Malang, Palembang City and Tarakan Island
Presented at Kaohsiung Water ForumApril 21-25, 2013 – Kaohsiung Taiwan
Outline
• Climate Risk and Adaptation Assesssment Framework in Indonesia
• Flood Risk and Adaptation Method• Landslide Risk and Adaptation Method• Analysis of Climate Risk and Adaptation in :
– Greater Malang– Palembang City– Tarakan Island
CLIMATE RISK AND ADAPTATION ASSESSMENT IN INDONESIA
Approach
Impact Vulnerability Adaptation RISK Integrated
Scientific Objective Impact and risk under future climate
Processes effecting vulnerability to climate
change
Processes effecting adaptation and adaptive
capacity
Risk and Policy Response
Assessment
Interaction and feedbacks between multiple driver
and impacts
Practical aims Actions to reduce risks Action to reduce vulnerability
Action to improve adaptation
Mainstreaming intoPolicy Making
Global policy options and costs
Research methods
Standard approach to CCIAV
Driver-pressure-state-impact-response (DPSIR) methods
Hazard-driven risk assessment
Vulnerability indicators and profilesPast and present climate risk
Livelihood analysisAgent-based methods
Narrative methodsRisk perception including critical threshold
Development/sustainability policy performanceRelationship of adaptive capacity to sustainable
development
Risk Assessment Procedures
Risk composes of Hazards and
Vulnerability
Integrated assessment modeling
Cross-sectoral interactionsIntegration of climate with
other driversStakeholder discussions
linking models across types and scales
Combining assessment approaches/methods
Motivation Research Driven Research/Stakeholders Driven Policy Driven Research/Stakeholders Driven
Approaches in Research of Climate Change Impact (CCIAVA)(Modified from IPCC, 2007)
Risk Assessment Approach
Climate stimuli • Temperature • Rainfall • Sea level
Surface condition :• topography • land cover• etc
Projected changes in :• mean • variability• extremes
CC Hazards (by sectors)
• Water resources• availability ()• flood & drought ()
• Agricultural• production () planting failure harvest failure lower productivity
• Health • incidence rate () DBD Malaria Diarrhea
• Coastal • inundated area () SLR Extreme events
H = F(f,M,p)
Bio-Physical• # Houses• Cultivated area• etc
Vulnerability Components• (E)xposure • (S)ensitivity• (A)daptive- (C)apacity
(R) isk = H×V
Elements of Built Environment
Social• Population density• # Vulnerable group• etc
Economic • # Assets • GDP growth • etc
AC
SEV
Additional analysis/ modeling
IPCC AR4
Pseudo Equation (Wisner et al., 2004)
Adaptation Planning with DRR Framework
(1)Understand the climatic hazard
(2)Assess Risks (3)Reduce Risks
(4)Transfer Risks
uncertainty
past proxy data
• Hazard Assessments• Vulnerability Assessments• Risk Maps• Potential Impact Assess.
Macro-scale :• National scale • Policy & Laws • Long-term planningMeso-scale :• Province & Municipality • Policy / Strategy• Mid-term PlanningMicro-scale :• Municipality • Spatial planning• Adaptation action
• Reduce Hazard Level• Reduce Vulnerability Level
• Structural• Technological • Socio-cultural • etc. measures
• Financial instruments
present obs. data
future climate model
• To save human lives• To save investments
Climate scientists Climate scientists, engineers, economic & policy analysts Planners, Decision makers
• Reduce economic loss• Accelerate recovery
(1)Science Basis (2) Risk Analysis
(3) Adaptation Policy
Hazard Analysis :• Water shortage/drought• Flood• Landslide
• Identify of risk area• Prioritize of adaptation program• Recommendation
ClimatevAnalysis & Projection
Rainfall and temperature in baseline and projection
Vulnerability Analysis :• Bio-Physic, Social, Economic• Baseline• Dynamic Vulnerability
Hazard Map
Vulnerability Map
Risk Map as Impact of Climate Change
General MethodHazard Stimulation
(climatic driven)
Hazards (H) Vulnerabilities (V)
Risks (R)
GISR : H x V (E,S,AC)
Adaptation Policy & Strategy
Adaptation Measures (Programs & Activities)
H, V &
R Analysis (Baseline/B &
Projection/P)
Adaptation Analysis (B &
P)
H / V Components (non-climatic driven)
FLOOD RISK AND ADAPTATION ASSESSMENT
Building
Data Process
Vulnerability Hazard
Risk analysis
Infrastructure
Administrative Boundary
PDA Statistic
Land Use and RTRW
Inundation
Swamp and river
Adaptation strategy
Drainage
LANDSLIDE RISK AND ADAPTATION ASSESSMENT
SlopeSoil TypeGeology
Infrastructure
Density
Building
Landuse
Environmental FactorTriggering Factor
Landslide Occurences Rainfall
IDFCRD
Ground water Table Recharge
Soil Strength Decreases
Landslide Hazard Analysis
(Map of Hazard)
Vulnerability Analysis(Map of Landslide Vulnerability)
Risk= Hazard x Vulnerability(Map of Landslide Risk)
Adaptation Strategy
STEP I
STEP IV
STEP II
STEP III
STEP V
ANALYSIS OF CLIMATE RISK AND ADAPTATION ASSESSMENT
IN GREATER MALANG (FLOOD AND LANDSLIDE)
0 50 100 150 200 250 3000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Rainfall (mm/day)
Pro
ba
bili
ty o
f Exc
ee
de
nce
1 yr
2 yr
5 yr
10 yr
Probability of exceedence rainfall with return periods 1, 2, 5, and 10 years
Relationship between monthly rainfall and probability of extreme rainfall
Climate condition in Greater Malang
Hazard Potential of Flood in Greater Malang
Baseline Projection
Flood vulnerability in Greater Malang
Baseline Projection
16
Flood Risk in Baru City
Baseline Projection
Baseline Projection
Flood Risk in Malang City
Flood Risk in Malang Regency
Baseline Projection
5 10 20 30 40 50 60
kurva-basis
280.019911036715
200.599566037805
127.99479493829
93.9798415674982
74.2481898485282
61.3643609539033
52.2906824352334
25.0
75.0
125.0
175.0
225.0
275.0
Kurva IDF (Intensity-Duration Frequency)
kurva-basis
durasi
inte
nsit
as
Slope stability analysis based on climate change hazard
Hazard Baseline Map of December 2006, as the most wet month
Hazard Baseline Map of December 2007 as the most dry month
Landslide Hazard in Greater Malang
Components Indicators Sub-indicators Weighting
Exposure Population densityPopulation and population growth per sub-district
0.54
Landuse Landuse as in regional planning 0.22Sensitivity Role of infrastructure Road infrastructure 0.18Adaptive Capacity Population Welfare Population’s income 0.06
baseline projection
Landslide Vulnerability in Greater Malang
Landslide risk map for baseline condition(Observation data)
Landslide risk map for baseline condition(Simulation data)
Landslide risk map for projection condition
Risk Level
Risk Area (m2)
Baseline Projection
Observation Simulation Simulation
Very Low 760.260.000 792.590.000 2.141.700.000
Low 1.639.880.000 1.657.270.000 328.540.000
Moderate 152.550.000 115.720.000 56.510.000
High 33.440.000 20.620.000 54.200.000
Very High 250.000 190.000 880.000
Landslide Risk Area of Great Malang
ANALYSIS OF CLIMATE RISK AND ADAPTATION ASSESSMENT
IN PALEMBANG CITY (FLOOD)
Palembang City
Palembang inCoastal Area, Swamp Area, River and Lowland
The Development in Swamp Area
= River
(Curah Hujan di Asia Tenggara peta awal 1900-an,Broek, 1944)
Aldrian and Susanto (2003)
Sumsel beriklim basah; batas antara tipe monsunal (satu puncak) dan ekuatorial (dua puncak) ?
Regional Climate
Past Local Climate in Palembang
Equatorial
Monsunal
Ekuatorial in dry season
Limit of dry/wet month from Indonesian Agency for Meteorology, Climatology and Geophysics
De gemiddelde jaartemperaturen op de kustplaatsen verschillen minder dan l°C. en bewegen zich, voor zoover bekend, tusschen 26.6 en 27.3° C. ; het gemiddelde verschil tusschen dag- en nachttemperatuur is 5 a 6° C. ; dat tusschen de warmste en de koudste maand iets meer dan 1° C.
Temperature :• Monthly mean temperature has two peaks that seems
to lag about one month or more from the equinoxes with an average value of slightly above 27° C. It is of interest to note that the temperature difference between warmest (May) and coolest (January) months is about 1° C. (C. Lekkerkerker, 1916).
Development Verification weighting Projection
The trend of temperature does not show significant increasing from year of 1951 to 2030. From the 3 scenarios SRES the temperature increase to 1° C relative to (1961-1990)
Source : Hadi, 2011
Source : Hadi, 2011
Figure below shows Baseline condition of temperature for baseline (1955-1999) and projection of temperature (2009-2099).
TEMPERATURE
Slightly different in the mountains area on the North West it becomes unclear in dry season (rainfall is relatively higher)
Source : Hadi, 2011
The models shows the spatial variability of rainfall for baseline condition (1951-1990) by using Observation data (left) and SRA1B scenarios of IPCC.Source : Hadi, 2011
Source : Hadi, 2011
Rainfall analysis are using some scenarios of IPCC, although the models show large discrepancy from observations, the increase of rainfall during the last decade was obtained from the results from A1B and A2 scenarios. In general, results from these two scenarios produce similar rainfall variations at least until early 2030s.
RAINFALL
Hazard analysis
Baseline (2010) Projection (2030)
Vulnerability
Baseline (2010) Projection (2030)
Difference Analysis Level of VulnerabilityMesso Micro Local
Baseline
Projection
Baseline
Projection
Baseline
Projection
Risk Analysis
• R= H x V
Baseline (2010) Projection (2030)
Adaptation Strategy/Action
Land use type Short-term Long term
Road Drainage normalisation
Increasing level of road surface
Increasing level of pavement
Housing and building Drainage normalisation
Bio-pore
Increasing the amount of
farming
Watershed areaRiver normalisation
Install embankmentPumping
Swamp area Drainage normalisation Monitoring to the regulation
Industry, office, trade and service
area
Infiltration Measure
(permeable paving)
Bio-pore
Detention
Other landuse type
Infiltration Measure
(permeable paving)Canalisation
Drainage normalisation Green space
ANALYSIS OF CLIMATE RISK AND ADAPTATION ASSESSMENT IN TARAKAN ISLAND (LANDSLIDE)
Tarakan Island• On east-side of Kalimantan, Indonesia• Located at 3o14'23"-3o26'37" Northern Latitude and 117o30'50"-117o40'12“ Eastern Longitude• 61 Landslide occurences until 2010• Slope 0-15%• Extreme scenario of rainfall intensity is 100 mm/Hours (with the longest duration is 2 hours) • Annual rainfall has two peak; on April (338 mm with average monthly temperature) and November, 360 mm mmt), meanwhile the most dry is on February (252 mm mmt)• The estimation of temperature increasing is higher than 0,5 degree C/100 years
Survey Titik Longsor di Kota Tarakan
61 points of Landslide Occurences in Tarakan
Annual pattern of climate
Rainfall
Temperatur
Projection of climate
Hazard Components:• Landslide occurence• Slope• Geology• Ground Water Recharge
11 2 3
4
5 6
7
89
1.960
Distance (m)
0 50 100 150 200 250 300 350 400 450 500 550
Elevation (m)
01020304050607080
90100110
Kelurahan X_coord Y_coord Kelurahan X_coord Y_coordKampung Enam 1 569047 365608 Karang Balik 2 565467 365390Kampung Enam 2 569439 366217 Karang Balik 3 565526 365380Pamusian (Ladang dalam) 566939 366518 Karang Balik 4 565182 365781Kampung Baru 1 566233 366429 Mamburungan Timur 569581 361431Kampung Baru 2 566273 366198 Juata Laut 1 560885 380305Kampung Baru 3 566506 366206 Juata Laut 2 561024 380413Pamusian (Markoni dalam) 566662 365150 Juata Laut 3 561763 380233Gunung Lingkas (Jl.TMD) 566369 364409 karang harapan 1 563223 370499Sebengkok 7 566377 364453 karang harapan 2 563569 369782Sebengkok 8 566034 364745 pantai amal 1 571892 364062Sebengkok 9 565766 365248 pantai amal 2 571835 364144Sebengkok 10 565817 364186 pantai amal 3 569838 366204Kampung Satu Skip 1 565648 367837 kampung enam 3 569316 365575Kampung Satu Skip 2 565730 367939 Karang Balik 1 565428 365739Kampung Satu Skip 3 565924 368020 Karang Balik 2 565611 365728Kampung Satu Skip 4 565861 367787 Sebengkok 1 565882 365505Kampung Satu Skip 5 567049 367541 Sebengkok 2 565892 365396Kampung Satu Skip 6 567535 367070 Sebengkok 3 565871 365463Kampung Satu Skip 7 567391 366852 Sebengkok 4 565945 365619Karanganyar 1 565197 367188 Sebengkok 5 565945 365491Karanganyar 2 565114 367103 Sebengkok 6 565992 365463Karanganyar 3 565141 367188 Selumit 1 565704 364833Karanganyar 4 565078 366936 Selumit 2 565710 364987karang anyar 5 564499 367360 Selumit 3 565433 364782Karanganyar 6 565260 366824 Gn. Lingkas ujung 565538 363812Karanganyar 7 566021 367099 Gn.Lingkas 1 566319 364375Karanganyar 8 566456 367367 Gn.Lingkas 2 566394 364447Juata Permai 1 560370 371544 Gn.Lingkas 3 566516 364805Juata Permai 2 560377 371540 Kampung Bugis 566137 367079Karang Balik 1 565484 365358 Perumnas 564366 367152
Survey lokasi longsor
Stabiliy modelling
Landslide existing map
Probability index
Modelling
N
555000
555000
560000
560000
565000
565000
570000
570000
575000
575000
580000
580000
360000 360000
365000 365000
370000 370000
375000 375000
380000 380000
Index :12345
3 0 3 6KM
Skala :
Hazard Components :• Landslide occurence• Slope• Geology• Ground Water Recharge
No Steepness Slope1 Flat 0-2 %2 Gently Sloping 3-7 %3 Sloping 8-13 %4 Steep 14-20 %5 Very steep 21-55 %6 Extremely steep >56%
Hazard Components:• Landslide occurence• Slope• Geology• Ground water recharge
No Geology Grain size Texture Cohession Phi Consolidation Total Index1 Clayey sand 3 2 2 3 2 12 42 Monmorilonit 1 1 4 3 1 10 13 Conglomerate 4 1 1 4 1 11 2
4 Quarter Sediment 1 1 3 2 3 10 1
5 Coal 4 3 2 3 1 13 36 Sandstone 3 3 1 4 1 12 47 Claystone 1 3 4 1 3 12 4
N
555000
555000
560000
560000
565000
565000
570000
570000
575000
575000
580000
580000
360000 360000
365000 365000
370000 370000
375000 375000
380000 380000
3 0 3 6KM
Skala :
Indeks :1234
Hazard Components:• Landslide occurence• Slope• Geologi• Ground Water Recharge
Rainfall - Recharge
Rainfall
Using Cummulative Rainfall Departure Method (CRD)
0
100
200
300
400
500
600
-20000
-15000
-10000
-5000
0
5000
10000
15000
20000
Rainfall (mm) Water Level (mm)
Januari Februari Maret April Mei Juni
Juli Agustus September Oktober November Desember
Ground Water Recharge Modelling in Tarakan Island
5 10 20 30 40 50 60
kurva-basis
280.019911036715
200.599566037805
127.99479493829
93.9798415674983
74.2481898485282
61.3643609539033
52.2906824352334
25.0
75.0
125.0
175.0
225.0
275.0
Kurva IDF (Intensity-Duration Frequency)
kurva-basis
durasi
inte
nsit
as
Modelling process of slope stability using
input of soil strength decrease
Slope Stability Modelling using input of Soil Strength Decrease
Landslide Hazard (2020) In Tarakan Island
Januari Februari Maret April Mei Juni
Juli Agustus September Oktober November Desember
Landslide Hazard Area in Tarakan Island
January February March April May JuneVery Low 66,52 84,56 66,57 66,52 43,34 66,57
Low 111,55 122,52 128,81 111,55 61,35 111,62
Moderate 57,34 39,43 48,24 57,30 119,29 65,43
High 14,38 3,30 6,18 14,39 25,14 6,18
Very High 0,03 0,00 0,02 0,05 0,70 0,02
July August September October November DecemberVery Low 66,57 66,57 84,56 66,52 51,45 51,45
Low 128,81 128,81 122,52 111,55 105,05 73,06
Moderate 48,24 48,24 39,40 57,30 67,60 99,60
High 6,18 6,18 3,32 14,39 25,02 25,02
Very High 0,02 0,02 0,01 0,05 0,69 0,69
Hazard Area (KM2)
Landslide Vulnerability
Peta IndeksBuilding 0,3
Population density 0,25
Slope 0,23Infrastructure and public facilities 0,12
Landuse 0,1
Landslide Risk (2020) in Tarakan Island
Januari Februari Maret April Mei Juni
Juli Agustus September Oktober November Desember
Landslide Adaptatation Assessment
Refferring : • Australian Geomechanics Society (AGS)• Landslide Risk Assessment and Mitigation
(LARAM-2000) Describe 4 typical works, i.e : Drainage installation, Slope modification, Retaining Wall, and Internal Slope Reinforcement
Risk
Evaluation
Conceptual designClient/Owner/Regulator to
decide to accept or treat technical specialist to advise
Design to implement preferred site
Review preliminary design and select optimum method of
stabilising landslide
Detailed design of short and long term monitoring system
Specify any special measures specific to construction through
landslide zone
MonitoringInstall monitoring
system
Construct
Is project performing satisfactory ?
Continue periodic monitoring
Reconsider
Feedback
Feedback
Design phase
Construction phase
Maintenance phase
Feedback
Feedback
Revised design
No
Yes
Phase of Location Assessment
Tata Guna Lahan High Risk (m2)
Desain Non-Desain Hutan Lebat 13.056,98 Jalan 9.530,95 Kawasan Terbangun 55.804,71 Kebun Campuran 341.448,53 Kilang Minyak 81,49 Kolam 107,32 Kuburan 9.714,04 Lapangan Olahraga 0,06 Mangrove 24,81 Perkebunan 51,08 Pertanian Lahan Kering 64.510,56 Rawa 401,48 Semak Belukar 191.261,46 Tambak 1.851,31 Tanah Kosong/Tegalan 30.250,18 Tubuh Air 2.823,97
Landuse in High Risk Landslide
Adaptation and non-adaptation area
3 0 3 6KM
Skala :
Lokasi Desain
Penanggulangan Longsor
555000
555000
560000
560000
565000
565000
570000
570000
575000
575000
580000
580000
360000 360000
365000 365000
370000 370000
375000 375000
380000 380000
N
Map of landslide Adaptation
Evaluation of Landslide Risk Assessment of Landslide Location
Adaptation Modelling Process
N
Skala :
561200 561600 562000 562400
379
800
380
200
380
600
Peta Lokasi Desain
Penanggulangan Longsor
0.1 0 0.1 0.2 0.3 0.4KM
Elevasi97.222 - 11084.444 - 97.22271.667 - 84.44458.889 - 71.66746.111 - 58.88933.333 - 46.11120.556 - 33.3337.778 - 20.556-5 - 7.778
BangunanBahaya Sangat TinggiResiko Tinggi
Keterangan :
•Lokasi longsor berada pada Kecamatan Tarakan Utara, Kelurahan juata laut, •Slope 21-40%•Geologi batu pasir•Tata guna lahan berada di pinggir laut dengan kawasan terbangun •Vegetasi rapat•Safety factor 0,79•kejadian longsor 3 titik (56173,380233), (561024,380413), (560885,380305)
0.790
Distance (m)
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
Elevation (m
)
-1
1
3
5
7
9
11
1.649
Distance (m)
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
Ele
vation
(m)
-1
1
3
5
7
9
11
Kondisi awal dengan FK = 0,790 (tidak stabil)
Desain kestabilan lereng menghasilkan FK = 1,649 (stabil)
1 Risk Analysis
2 Ground Survey
3 Collecting Data
4 Adaptation Measurement
Thank you for your attention