Methodology for Climate Risk Mapping
77 this in the analysis. The weight and the formula used to calculate the index the
climate hazard is given in Table 6.2. The adjusted matrix of climate risk is presented in Table 6.3.
Table 6.2 .. Weight and formula for calculating climate hazards index
Type of
hazard Weight
Formula
Flood 1.25
Probability of having monthly rainfall of more than 339 mm multiplied by average of area of Kelurahan being impacted by
flood. In order to get the index value of between 0 and 1, the calculated value is normalized by the maximum value
Drought 1.50
Probability of having dry month with length of more than 6 month multiplied by number of dry month above the 6 month DM
6+
. Dry month is defined as month with rainfall of less than 129 mm.
If total length of dry month is 8 month, the DM
6+
= 2 months. In order to get the index value of between 0 and 1, the calculated
value is normalized by the maximum value.
Land slide
0.75 Probability of having monthly rainfall of more than Q2 multiplied
by slope indicator of the corresponding Kelurahan . Kelurahan that has locations with slope of more than 45
o
, the indicator value will be equal to 1, otherwise zero.
Sea Level Rise
1.00 Fraction of Kelurahan area being inundated by the sea level rise
Max CCHI
4.50 Note: The weight is very subjective and determined based on Expert Judgement. Drought
has the highest weight as its impact may be more severe than flood due its duration and extend of impacted area. Impact of flood, land slide and sea level rise is more localized than
that of drought.
Table 6.3 .. Matrix of Climate Risk according the coping capacity index and
composite climate hazard index Coping Capacity
Index Composite Climate Hazard Index CCHI
More than 3.5 Between 2.0 and 3.5
Less than 2.0 5
Very High High
Medium to High 4
High Medium to High
Medium 3
Medium to High Medium
Medium to Low 2
Medium Medium to Low
Low 1
Medium to Low Low
Very Lowe Methodology for defining critical rainfall causing flood and the one causing drought
was based on statistical distribution of the monthly rainfall and hazard data from 7 Kelurahan s Table 6.4. The critical rainfall threshold was determined based on the
characteristics of the hazards and time of the hazards occurrence month and year and regional monthly rainfall intensity of the
corresponding year based on data from Masgar station, 05°1012 S and 105°1029.4 E.
78 Table 6.4
.. Flood and drought hazard events in Bandar Lampung City
Type of
Disasters Name
of Village
Sub-District Lon
Lat Date and
Month Incident
Year
Flood Panjang
Selatan Panjang
105.32 31
- 5.475
2 Oct-Dec
1981- 2007
Sukabumi Indah
Sukabumi 105.29
56 -
5.398 3
Jul 2008
Pasir Gintung
Tanjung Karang Pusat
105.25 71
- 5.404
7 18-Dec
2008 Kota Karang
Teluk Betung
Barat 105.26
06 -
5.454 7
Aug-Oct 2008.20
09 Kangkung
Teluk Betung
Selatan 105.26
77 -
5.446 5
Jan 2006.20
09 Batu Putu
Teluk Betung
Utara 105.22
29 -
5.431 4
Rainy season 2006
Drought Panjang
Selatan Panjang
105.32 31
- 5.475
2 May-Aug, Jan-
Mar Every
year Sukabumi
Indah Sukabumi
105.29 57
- 5.398
3 May-Oct
Every year
Pasir Gintung
Tanjung Karang Pusat
105.25 71
- 5.404
7 Apr-Oct
Every year
Kota Karang Teluk
Betung Barat
105.26 06
- 5.454
7 Feb-Sept
Every year
Kangkung Teluk
Betung Selatan
105.26 77
- 5.446
5 Every month
Every year
Batu Putu Teluk
Betung Utara
105.22 29
- 5.431
4 May-Oct
Every year
Source: Bappeda Lampung 2006
Based on Boxplot of monthly rainfall data of dry season and wet season Figure 6.1, we found the rainfall which separate the two monthly rainfall
distributions was 129 mm. This value was taken as the critical rainfall causing drought since drought occurred every year Table 6.4. This means that if rainfall is
below 129 mm, drought will occur. For flood, we adopt the critical value of 339 mm quartile 3 of the distribution since floods did not occur every year as the
drought. Thus, if rainfall in wet season is above this value, flood will occur.
79 Figure 6.1
.Box plot of monthly rainfall in dry and wet season during hazard and no- hazards years
.