1 / 60

Budhi Setiawan Civil Engineering Department, Sriwijaya University INDONESIA

Presented at Kaohsiung Water Forum April 21-25, 2013 – Kaohsiung Taiwan. Climate Risk and Adaptation Assessment in City Level Greater Malang, Palembang City and Tarakan Island. Budhi Setiawan Civil Engineering Department, Sriwijaya University INDONESIA

emiko
Download Presentation

Budhi Setiawan Civil Engineering Department, Sriwijaya University INDONESIA

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Presented at Kaohsiung Water Forum April 21-25, 2013 – Kaohsiung Taiwan Climate Risk and Adaptation Assessment in City Level Greater Malang, Palembang City and Tarakan Island BudhiSetiawan Civil Engineering Department, Sriwijaya University INDONESIA Senior Technical Advisor on Office for Climate Change Resilience– Ministry of National Development Planning

  2. 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

  3. Climate risk and adaptation assessment IN INDONESIA

  4. Approaches in Research of Climate Change Impact (CCIAVA)(Modified from IPCC, 2007)

  5. Risk Assessment Approach Elements of Built Environment Additional analysis/ modeling • Climate stimuli • Temperature • Rainfall • Sea level • Social • Population density • # Vulnerable group • etc • Bio-Physical • # Houses • Cultivated area • etc • 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 IPCC AR4 • Economic • # Assets • GDP growth • etc • Vulnerability Components • (E)xposure • (S)ensitivity • (A)daptive- (C)apacity • Projected changes in : • mean • variability • extremes • Surface • condition : • topography • land cover • etc (R) isk = H×V H = F(f,M,p) Pseudo Equation (Wisner et al., 2004)

  6. Adaptation Planning with DRR Framework (1)Understand the climatic hazard (2)Assess Risks (3)Reduce Risks • Hazard Assessments • Vulnerability Assessments • Risk Maps • Potential Impact Assess. • Reduce Hazard Level • Reduce Vulnerability Level uncertainty • Structural • Technological • Socio-cultural • etc. measures past proxy data • Macro-scale : • National scale • Policy & Laws • Long-term planning • Meso-scale : • Province & Municipality • Policy / Strategy • Mid-term Planning • Micro-scale : • Municipality • Spatial planning • Adaptation action • To save human lives • To save investments presentobs. data future climate model (4)Transfer Risks • Financial instruments • Reduce economic loss • Accelerate recovery Climate scientists, engineers, economic & policy analysts Climate scientists Planners, Decision makers

  7. (2) Risk Analysis • VulnerabilityAnalysis : • Bio-Physic, Social, Economic • Baseline • Dynamic Vulnerability (1)Science Basis ClimatevAnalysis & Projection • Hazard Analysis : • Water shortage/drought • Flood • Landslide Rainfall andtemperature inbaselineand projection Vulnerability Map Risk Map as Impact of Climate Change HazardMap (3) Adaptation Policy • Identify of risk area • Prioritize ofadaptation program • Recommendation

  8. General Method Hazard Stimulation (climatic driven) H / V Components (non-climatic driven) Hazards (H) Vulnerabilities (V) H, V & R Analysis (Baseline/B & Projection/P) GIS R : H x V (E,S,AC) Risks (R) Adaptation Policy & Strategy Adaptation Analysis (B & P) Adaptation Measures (Programs& Activities)

  9. FLOOD RISK And adaptation assessment

  10. Swamp and river Inundation Land Use and RTRW PDA Statistic AdministrativeBoundary Drainage Infrastructure Building Data Process Vulnerability Hazard Risk analysis Adaptation strategy

  11. Landslide risk and adaptation assessment

  12. Triggering Factor Environmental Factor STEP I Landuse Geology Building Soil Type Density Slope Landslide Occurences Rainfall Infrastructure CRD IDF STEP II Ground water Table Recharge Soil Strength Decreases Landslide Hazard Analysis (Map of Hazard) Vulnerability Analysis (Map of Landslide Vulnerability) STEP III Risk= Hazard x Vulnerability (Map of Landslide Risk) STEP IV STEP V Adaptation Strategy

  13. Analysis of Climate risk and adaptation assessment in Greater malang (flood and landslide)

  14. Climate condition in Greater Malang 1 yr 5 yr 2 yr 10 yr Relationship between monthly rainfall and probability of extreme rainfall Probability of exceedence rainfall with return periods 1, 2, 5, and 10 years

  15. Hazard Potential of Flood in Greater Malang Baseline Projection

  16. 16 Flood vulnerability in Greater Malang Baseline Projection

  17. Flood Risk in Baru City Baseline Projection

  18. Flood Risk in Malang City Baseline Projection

  19. Flood Risk in Malang Regency Baseline Projection

  20. Slope stability analysis based on climate change hazard

  21. Landslide Hazard in Greater Malang Hazard Baseline Map of December2006, as the most wet month Hazard Baseline Map of December2007 as the most dry month

  22. Landslide Vulnerability in Greater Malang baseline projection

  23. Landslide risk map for baseline condition (Observation data) Landslide risk map for baseline condition (Simulation data) Landslide Risk Area of Great Malang Landslide risk map for projection condition

  24. Analysis of Climate risk and adaptation assessment in Palembang city (flood)

  25. Palembang City

  26. Palembang inCoastal Area, Swamp Area, River and Lowland The Development in Swamp Area

  27. = River

  28. Regional Climate Aldrian and Susanto (2003) Sumselberiklimbasah; batasantaratipemonsunal (satupuncak) danekuatorial (duapuncak) ? (CurahHujandi Asia Tenggara  petaawal 1900-an, Broek, 1944)

  29. Past Local Climate in Palembang Equatorial Monsunal Limit of dry/wet monthfrom Indonesian Agency for Meteorology, Climatology and Geophysics Ekuatorial in dry season 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.

  30. TEMPERATURE 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). • Source : Hadi, 2011 • 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 relativeto (1961-1990) • Figure below shows Baseline condition of temperature for baseline (1955-1999) and projection of temperature (2009-2099). Development Verification  weighting Projection • Source : Hadi, 2011

  31. RAINFALL • Source : Hadi, 2011 • Source : Hadi, 2011 • Slightly different in the mountains area on the North West it becomes unclear in dry season (rainfall is relatively higher) 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. • 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

  32. Hazard analysis Baseline (2010) Projection (2030)

  33. Vulnerability Baseline (2010) Projection (2030)

  34. Difference Analysis Level of Vulnerability Messo Micro Local Baseline Baseline Baseline Projection Projection Projection

  35. Risk Analysis • R= H x V Baseline (2010) Projection (2030)

  36. Analysis of Climate risk and adaptation assessment in tarakan island (landslide)

  37. 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 • Slope0-15% • 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

  38. Survey Titik Longsor di Kota Tarakan 61 points of Landslide Occurences in Tarakan

  39. Annual pattern of climate Rainfall Temperatur

  40. Projection of climate

  41. Survey lokasi longsor Hazard Components: • Landslide occurence • Slope • Geology • Ground Water Recharge Stabiliy modelling Modelling Landslide existing map Probability index

  42. Hazard Components : • Landslide occurence • Slope • Geology • Ground Water Recharge

  43. Hazard Components: • Landslide occurence • Slope • Geology • Ground water recharge

  44. Rainfall - Recharge Rainfall Hazard Components: • Landslide occurence • Slope • Geologi • Ground Water Recharge Using Cummulative Rainfall Departure Method (CRD)

  45. Ground Water Recharge Modelling in Tarakan Island Februari Maret April Mei Juni Januari Juli Agustus September Oktober November Desember

  46. Modelling process of slope stability using input of soil strength decrease

  47. Slope Stability Modelling using input of Soil Strength Decrease

More Related