Panut Manoonvoravong ASEAN Academic Networking in Water, Disaster Management & Climate Change 23 Sept. 2014

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Panut Manoonvoravong ASEAN Academic Networking in Water, Disaster Management & Climate Change 23 Sept. 2014

Locations of early warning stations in the North No Basins Stations 1 Ping 147 2 Wang 33 3 Sarawin 84 4 Kok 67 5 North Kong 56 6 Yom 52 7 Nan 100 Total 539

Early warning installation areas Numbers of early warning stations since 2005 in the north-west Thailand Provinces Early warning stations Effective villages 1. Chiang Mai 125 368 2. Chiang Rai 105 326 3. Lampang 38 99 4. Lampoon 21 61 5. Tak 29 84 6. Kompang Pet 16 47 7. Payao 18 74 8. Mae Hon Son 61 157 แผนท แสดงตำแหน งสถำน เต อนภ ยล วงหน ำ From 2005-2012

Instrument installation 1. Hill-side villages: rainfall measurement 2. Bridge side: rainfall & flow rate measurement

Instrument set Data processor and remote transferring gear Soil moisture detector Rain gauge Alarm signals

Warning signals Light and sound warning system 3 warning levels Watching and following the situation Low sound warning, every 20 minutes Alert Medium sound warning, every 15 minutes Evacuation High sound warning, every 3 minutes

Early warning implementation Early warning stations Regional water resources offices Central water resources office Operational officials Incident Information / report of flood - Water level investigation (Max water level record) - Damage investigation Insiders - Bureau of research, development & hydrology - Water crisis prevention centre No incident Information from Web Site Information from radar and met.stations Close Water level and rain fall monitoring Close collaboration with EW officials Outsiders - Department of Disaster Prevention and Mitigation - Sub-district administration organization - Provincial national resources and environment office

Conceptual hydro-climatic landslide triggering model (After Crozier, 2010)

1. Principles and Rationale Climate change is led by high uncertainties. Earth energy consuming is the major effect of climate change causing the concerned water issues such as season changed, extreme events, etc. Increment or Decrement of annual rainfall affects to severe and frequent flood/ draught. Heavy rainfalls induce consequently to landslides. A study on perspectives of flash-flood/landslide areas induced by climate change needs the future climate scenarios synergizing with the landslide model and forecasted rainfall.

2. Objectives 2.1 To evaluate the high risk areas forecasted from mathematic climate change models 2.2 To create the knowledge guideline for handling with flash flood/landslide induced by climate change 2.3 As the fostering data in future climate change for long term planning of concerning sectors 2.4 Future supporting data for policy makers

3. Study areas The rainfall measurement led to analyze risky flash flood / landslide was conducted cover 7 basins in the North namely: - Salawin - North Kong - Kok - Ping - Wang - Yom - Nan These areas include totally 16 provinces: Kam phang Pet, Chiang Rai, Chiang Mai, Tak, Nakorn Sawan, Nan, Payao, Pi Chit, Pit Snulok, Mae Hong Son, Petcha Boon, Prae, Lampang, Lampoon, Suko Thai, and Utara Dit

4. Methodology

Input requirement 1.Rainfall results evaluated from PRECIS (A2&B2) Baseline years from 1980-2011 Predicted years from 2012-2069

Input requirement 2.Rainfall data from observation stations ( Baseline years from 1980-2011)

Input requirement 3. Maps

Input requirement 4. Historical flash-flood/landslide incidents

Activity (event) Landslide record 11 Rock Groups Landslide Activity NR MM Sum % Sum 1 Carboniferous and Permo-Triassic Granite Rocks 0 0 0 0.00 2 Triassic Granite Rock 22 6 28 16.87 3 Cretaceous Granite Rock 8 10 18 10.84 4 Extrusive and Mafic Igneous Rocks 3 8 11 6.63 5 Predominantly Sandstone and Siltstone 10 7 17 10.24 6 Predominantly Shale and Mudstone 10 13 23 13.86 7 Interbedded Sedimentary Rocks 31 7 38 22.89 8 Predominantly Metamorphic Rock 10 7 17 10.24 9 Predominantly Carbonate Rock 5 1 6 3.61 10 Quaternary deposits 0 8 8 4.82 11 Sedimentary Rock on Khorat Plateau 0 0 0 0.00 Total 99 67 166 100 40 35 30 25 20 15 10 5 0 1 2 3 4 5 6 7 8 9 10 11 Stimulated by Human 0 6 10 8 7 13 7 7 1 8 0 Stimulated by Heavy Rainfall 0 22 8 3 10 10 31 10 5 0 0 11 Rock Groups Soralump, et al

11 groups of rocks risky to induce landslide in 7 basins (Adapted from Thai geological map scale 1: 250,000 after department of mineral resources)

Analysis of appropriate bias adjustment to adjust initial rainfall simulated by PRECIS (Scenario A2 & B2)

Evaluation of high potential landslide area due to climate change DynaSlide Se-mi Statistical - DynaSlide Model - Semi Statistical Model

DynaSlide Model Pros More precise results Suitable in large-scale areas Cons Complicated, geotechni cal data used Not suitable in smallscale areas Time consuming Higher cost than semistatistical model

Antecedence Precipitation Index (API) in soil V T V v V a V w V s air water soil Porosity n Degree of saturation Sr V V V V API nsrt v T w v V T V S V v V w V a T = Total volume = Soil volume = Void = Water volume = Air volume = Thickness of crisis layer (After Soralump & Torwiwat,2008)

Se-mi Statistical Method Temporal Antecedence Precipitation Index (API t ) API t = (K t *API t-1 ) + P t API t = API at time t (t) (mm) API t-1 = Previous API (t-1) (mm) P t K t = Precipitation rate (t) (mm) = Regression Constant

Recession Constants: K K t = exp(-e t /W) เม อ E t = Evaporation at time เม อ W = Moister content (mm) W = %WHC*D B *soil depth 100 WHC = Water holding capacity (% by weight) D B Soil depth = Total density (g/cm3) = mm

Make it Dynamics Rainfall PRECIS %RTL = API t x 100 API cr Landslide Susceptibility Map (Se-mi Statistical) API cr

Summary of rainfall prediction results Description PRECIS Scenario A2 PRECIS Scenario B2 Average annual rainfall 58 years (2012-2069) compared with baseline years (1980-2011) Average wet season rainfall 58 years (2012-2069) compared with baseline years (1980-2011) Average dry season rainfall 58 years (2012-2069) compared with baseline years (1980-2011) Average max. daily rainfall 58 years (2012-2069) compared with baseline years (1980-2011) 5% 10% 3% 11% 16% 8% 11% 16% Crisis years of Kok and North Kong basins 2035 2033 Crisis years of Ping, Wang, Yom, Nan, and Salawin basins 2026 2015

Crisis rainfall years used for semi statistical landslide model PRECIS Scenario A2 B2 Crisis rainfall years 2026 2035 2015 2033

A2 the year 2026

A2 the year 2035

B2 the year 2015

B2 the year 2033

Thank you for your attention