Preparation and data acquisition Pre-processing

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3.4.1 Preparation and data acquisition

This phase consists of activities such as: literatures review, primary data collection, and problem identification. The literature studied deals with tidal flood, the climate hazard impact, sea level rise, el nino – la nina phenomenon, and IPCC sea level projection by MRI model. This phase includes journals and previous research results collection which are related with this research. The primary data was collected in this phase from National Mapping and Coordination Survey Agency Bakosurtanal, Indonesian Geology Bureau Badan Geologi.

3.4.2 Pre-processing

Pre-processing phase includes the process for producing vulnerable map as a reference to determine feasible area at the fieldwork phase. The pre-processing data started by cropping DEM-SRTM, rectification projected to UTM WGS 49S zone coordinate system, and convertion into grid format using 3DEM software. The geometric data were used to determine the inundation area using the sea level projection formula. Let say the sea level relative calculation resulted 4 meter, it means in area with 3 meter elevation above sea level, the inundation level will be 1 meter depth, and in elevation 4 meter or more there is no inundation or not affected. The next step is to define the value of sea level relative, by extracting raw data of high wave from AVISO and tide gauge raw data from UHSLC using Panoply software. The data were converted those data into Ms Excel format. Then putted the subsidence level data which gotten from Indonesian Geology Bureau in Ms Excel. Global mean sea level from IPCC model projection which has already downloaded from https:esg.llnl.gov:8443data were extracted to text format file using Panoply software and converted into ms excel file format. All data has processed and calculated in Ms Excel software. The formula of sea level relative is modification of the Sofian 2008 sea level projection equation, as follow: T EE =M SL +H EL +H W +H PS +S L 1 Where T EE : sea level on extreme climate in year projected, M SL : average sea level from IPCC model projection, H EL : sea level in El Nino and La Nina transition period, H W : wave height, H PS : sea level caused by tidal wave, S L : Subsidence level. 25 Prediction of the sea level was done for 2010, 2030, and 2100. The 1900 used as a baseline year measurement; so that the value at 2.1 meter of 2010 for example, is the rising of the sea from 1900. The projection was divided into common and extreme conditions. Common condition is the sea level in general climate while extreme condition is the sea level in the extreme climate condition namely in the transition period of El Nino-La Nina. Thus prediction of sea level especially in year period of El Nino and La Nina, range in between common and extreme condition. The formula of common condition t SLCC and extreme condition t SLEC of sea level projection can be seen as follows: LS TWL HW MSLM SLCC t t + + + = 2 t t t HEL LS TWL HWex MSLM SLEC + + + + = 3 Where: t MSLM : Global Mean Sea Level in t year observed data according IPCC model projection. HW : Average of high wave data. HWex : Maximum value of high wave data. TWL : Average range between maximum and minimum of tides data. LS : Land subsidence data. t HEL : Sea level in t El Nino and La Nina transition period. To define level inundation, the value of HW has to multiply by 30, because wave energy to push sea water up to the mainland is decrease about 30 due to hit the material which stand on the coastline area. The value of sea level relatives has resulted and use as guidance to specify the level of inundation in year observation. Then in same time, the data resulted was overlaid with the topographic map RBI map, to make a vulnerable map that possible to be displayed and geo-processed using Arc-view software.

3.4.3 Fieldwork