Journal of Natural Resources and Environmental Management http://dx.
org/10.
29244/jpsl.
RESEARCH ARTICLE
Vulnerability Assessment to Flash Floods Disasters in the Upper Cisadane Watershed Fitriany Amalia Wardhania.
Andrea Emma Pravitasarib,c.
Iwan Ridwansyaha Research Center for Limnology and Water Resources.
National Research and Innovation Agency.
Indonesia Division of Regional Development Planning.
Departement of Soil Science and Land Resources.
Faculty of Agriculture.
IPB University.
Indonesia Center for Regional.
Systems.
Analysis.
Planning and Development (CRESTPENT).
LPPM-IPB University.
Indonesia Article History Received 6 December 2022 Revised 21 June 2023 Accepted 27 June 2023 Keywords flash floods, upper cisadane, vulnerability.
ABSTRACT Flash floods are sudden flood disasters that can be triggered by several factors, one of which is landslides that occur in the upper watershed.
In Bogor Regency, there are 14 sub-districts located in the Upper Cisadane watershed area that are prone to flash flood disasters.
This study aimed to determine the social, economic, physical, and environmental vulnerability assessment of the community in the Upper Cisadane watershed area based on the modification assessment from Regulation of The Head of National Disaster Management Authority Number 12 of 2012.
This vulnerability assessment is part of disaster risk assessment, which is an approach to show the potential negative impacts of a disaster that occurs in an area.
This potential negative impact can be seen in the potential number of lives exposed, property loss, and environmental damage.
According to the vulnerability index, the Upper Cisadane watershed has high and very high classes of flash flood vulnerability, with ten .
sub-districts having high vulnerability index classes, and fourteen .
districts having very high vulnerability index classes.
The level of vulnerability in the sub-districts is influenced by the level of social, physical, and economic vulnerability, which has high to very high classes compared to other sub-districts.
The vulnerability index class maps from this study are expected to be used as references for local governments and related parties in regional spatial planning and flash flood disaster mitigation planning.
Introduction Flash flood disasters can cause physical and non-physical damage.
It is caused by floating debris from landslide that occurred around steeply sloping valleys of watersheds and small catchment areas .
Ae.
Climate change increases the risk of extreme rainfall, landslides, and flash floods in river basins.
The large number of victims affected by flash floods indicates that they cause extensive losses and damage to society.
According to several studies, flash flooding is the most devastating disaster and causes the worst damage It is relatively fast and occurs within a short time .
Ae.
A disaster risk assessment is conducted to identify the negative impacts .
otential hazard.
that could occur if a disaster occurs.
Negative impacts can be seen in the number of affected people, property loss, and environmental damage .
Vulnerability is the inability of society to resist and respond to a disaster .
The impacts of flash floods in each area depend on the ability of society to respond to a disaster.
for instance, a certain area with good socioeconomic status is relatively less vulnerable to disasters and has more efficient mitigation .
Social, economic, physical, and environmental vulnerabilities are affected by several factors.
Therefore, it is necessary to understand the characteristics and vulnerability of society to the impact of hazards .
Index based vulnerability Assessment is a practical tool that helps compare and rank regions in terms of vulnerability .
Vulnerability assessment is an important step in determining community resilience to disasters to plan mitigation and disaster management in flash flood disaster-prone area .
Ae.
Corresponding Author: Fitriany Amalia Wardhani Research and Innovation Agency.
Indonesia.
fitr024@brin.
Research Center for Limnology and Water Resources.
National A 2024 Wardhani et al.
This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY) license, allowing unrestricted use, distribution, and reproduction in any medium, provided proper credit is given to the original authors.
Think twice before printing this journal paper.
Save paper, trees, and Earth! Bogor City and Bogor Regency are most likely to experience flash floods and landslide disasters.
In Bogor Regency area, medium to severe landslide problem can occur in 26 .
wenty-si.
sub-districts, while 14 .
other sub-districts are most likely to be affected by flash floods or the flow of debris, including Caringin.
Ciampea.
Cibungbulang.
Cigombong.
Cijeruk.
Ciomas.
Dramaga.
Kemang.
Leuwiliang.
Pamijahan.
Rancabungur.
Rumpin.
Tamansari, and Tenjolaya.
The 14 sub-districts are prone to flash floods and debris flows and are located in the Upper Cisadane watershed .
Heavy rainfall has caused flash floods and landslides in Pamijahan and Leuwiliang Districts.
Bogor Regency.
West Java, on June 22, 2022.
At least 1,335 residents from those districts were affected, 335 of those residents were evacuated, three people were reported to have died, 11 bridges collapsed, and 281 houses were damaged .
The flash floods and landslides that occurred in the research area have caused many victims from the community.
Research to determine the level of community vulnerability to flash flood disasters is needed for disaster mitigation planning in the study area.
The objective of this study was to determine the social, economic, physical, and environmental vulnerability of the community in the Upper Cisadane watershed area based on the modification assessment from Regulation of The Head of National Disaster Management Authority Number 2 of 2012.
Materials and Methods Study Area The upper Cisadane Watershed covers about 835.
79 km 2 which consists of Bogor City with four sub-districts (West Bogor.
South Bogor.
Central Bogor.
East Bogo.
and Bogor Regency with twenty sub-districts (Caringin.
Ciampea.
Ciawi.
Cibungbulang.
Cigombong.
Cigudeg.
Cijeruk.
Ciomas.
Dramaga.
Kemang.
Leuwiliang.
Leuwisadeng.
Megamendung.
Nanggung.
Pamijahan.
Rancabungur.
Rumpin.
Sukajaya.
Tamansari, and Tenjolay.
(Error! Reference source not found.
The Upper Cisadane Watershed has a gently undulating and hilly surface, 45.
6% of which has heights varying from 200 to 500 msl .
ean sea leve.
According to the Land Use Land Cover (LULC), the study area was classified into several classes such as primary forest .
78%),
secondary dryland forest .
96%), plantation forest .
41%), shrubs .
24%), plantations .
57%),
36%), open/vacant land .
14%), water bodies .
43%), dry land agriculture .
29%), mixed dry land agriculture .
94%), rice fields .
87%), and mining .
01%).
(Error! Reference source not Topographical conditions and slope steepness in the Cisadane Watershed consist of variations in the slope from upstream to downstream.
In the upstream area, the slopes were steeper, gentler, and even flatter in the downstream area.
The slope was waver and undulating in the upstream area.
In mountainous areas such as the Ciawi and Cijeruk sub-districts, the slope of the land is hilly to steep .
Figure 1.
Map of the study area: .
watershed boundary, .
land cover map, 2020 .
Data Collection Sources of secondary data include data on disaster events, population, topography.
LULC, protected forest area, spatial planning and regional planning map, land use/cover map, and productive land area from 2014 This journal is AWardhani et al.
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to 2021 was used in this study.
These data were obtained from relevant agencies, such as the Regional Agency for Disaster Management.
Central Agency on Statistics.
Geospatial Information Agency.
Ministry of Environment and Forestry (MoEF).
Bogor Regency Government website .
ttps://opendata.
id/).
West Java Provincial Government website .
ttps://opendata.
id/), and the website of each subdistrict in the study areas (Table .
Table 1.
Data types and sources in research area.
Objectives Social Economic Physical Environmental Data types Population data .
ender, poverty, persons with disabilities, age Area of productive land and resident occupations Total of residential houses .
ermanent, semi-permanent, non-permanen.
, public facilities .
osque, church, school, etc.
) and critical facilities .
ealth facilitie.
and the prices.
Total area of natural forests, mangroves, swamps and shrubs.
Data Tabular Tabular Tabular Map Sources https://opendata.
https://opendata.
Central Agency on Statistics https://opendata.
https://opendata.
Central Agency on Statistics https://opendata.
https://opendata.
Central Agency on Statistics.
Geospatial Information Agency MoEF.
Geospatial Information Agency Data Analysis The analysis of the vulnerability index .
ocial, economic, physical, and environmental vulnerabilit.
to flas h flood disasters was performed based on a modification of the analytical method in Regulation of The Head of National Disaster Management Authority Number 2 of 2012 about General Guidelines for Disaster Risk Assessment.
In this study, each vulnerability type has different parameters.
Each parameter has different classes, which are represented by a specific score: three for the high class, two for the medium class, and one for the low class.
After the scoring process, the social, economic, physical, environmental, and total vulnerability index values were divided into five classes: very high .
4Ae.
, high .
8Ae2.
, medium .
21Ae1.
61Ae1.
and very low .
Ae0.
,11,.
The parameters used to measure the social vulnerability index were population density, sex ratio, poverty ratio, disability ratio, and the ratio of vulnerable age groups.
Population density is the number of people divided by the area in km 2.
The sex ratio is the ratio between men and women.
The poverty ratio is calculated from the percentage of poor people below the poverty line in Bogor Regency/City based on data derived from Bogor Regency in Figures 2021 and Bogor City in Figures 2021.
The ratio of disability is the number of people with disabilities divided by the total population in each sub-district.
The vulnerable age group ratio is the number of people aged 0Ae14 years plus the number of people aged over 65 years divided by the total population of each sub-district .
The weights of each parameter and equation of the social vulnerability index are listed in Table 2.
Table 2.
Social vulnerability index.
Classes Weight
Score
Low
Medium
High
(%)
Population density <500 people/km2 500 Ae 1,000 people/km2 >1,000 people/km2 Sex ratio
Class/maximum score class
Poverty ratio
Disability ratio
<20%
20 Ae 40% >40% Vulnerable age groups ratio 10 Parameters Source : .
Social vulnerability index analysed based on the following equation .
ycIycuycaycnycayco ycOycycoycuyceycycaycaycnycoycnycyc yaycuyccyceycu = .
6 y ycEycuycyycycoycaycycnycuycu yccyceycuycycnycy.
1 y ycIyceycu ycycaycycnyc.
1 y ycEycuycyceycycyc ycycaycycnyc.
1 y yaycnycycaycaycnycoycnycyc ycycaycycnyc.
1 y ycOycycoycuyceycycaycaycoyce ycayciyce yciycycuycycyyc ycycaycycnyc.
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The parameters used in the economic vulnerability index in this study were the area of productive land and vulnerable occupations.
These parameters were modified from Regulation of The Head of National Disaster Management Authority Number 2 of 2012, which includes productive land areas and gross regional domestic products (GRDP).
The available GRDP parameter data are at the district level, so they do not describe the conditions per sub-district.
The productive land area in rupiah .
ncluding rice fields and secondary crop.
and types of vulnerable occupations are used as parameters for the economic vulnerability index analysis.
The weight of each parameter and equation of the economic vulnerability index are listed in Table 3.
Table 3.
Economic vulnerability index.
Classes Weight
Score
Low
Medium
High
(%)
Productive land
<50 million 50 Ae 200 million >200 million
Class/maximum score class
Vulnerable occupation 40
<20%
20 Ae 40% >40% Parameters Source : .
Economic vulnerability index analysed based on the following equation .
yaycaycuycuycuycoycnyca ycycycoycuyceycycaycaycnycoycnycyc ycnycuyccyceycu = .
6 y ycEycycuyccycycaycycnycyce ycoycaycuyc.
4 y ycOycycoycuyceycycaycaycoyce ycuycaycaycycyycaycycnycuyc.
The physical parameters of the building, such as residential houses .
ermanent, semi-permanent, nonpermanen.
, public facilities .
osques, churches, schools, etc.
), and critical facilities .
ealth facilitie.
are the three parameters used for the physical vulnerability index analysis.
Residential house density is the number of residential units per hectare multiplied by the unit price of each type of house.
The weights of each parameter and the physical vulnerability index equation are listed in Table 4.
Moreover, land cover, which consists of natural forests, mangroves, swamps, and shrubs, is used as a parameter for environmental vulnerability index analysis.
The weights of each parameter and the equation for the environmental vulnerability index are listed in Table 5.
Table 4.
Physical vulnerability index.
Classes Weight
Score
Low
Medium
High
(%)
Residential house 40 <400 million 400 Ae 800 million >800 million Public facilities 30 <500 million 500 million Ae 1 billion >1 billion Class/maximum score class Critical facilities 30 <500 million 500 million Ae 1 billion >1 billion Parameters Source : .
Physical vulnerability index analysed based on the following equation.
ycEEaycycycnyca ycycycoycuyceycycaycaycnycoycnycyc ycnycuyccyceycu = .
4 y ycIyceycycnyccyceycuycycnycayco Eaycuycycyc.
3 y ycEycycaycoycnyca yceycaycaycnycoycnycycnycey.
3 y yaycycnycycnycaycayco yceycaycaycnycoycnycycnycey.
Table 5.
Environmental vulnerability index.
Parameters Weight Classes .
Score
(%)
Low Medium High
Protected forests 30
Natural forests 30
Mangrove Shrubs Swamps <20 20 Ae 50
<25 25 Ae 75
<10 10 Ae 30
<10 10 Ae 30
<5 5 Ae 20
>50
>75
>30 Class/maximum score class
>30
>20
Source : .
Environmental vulnerability index analysed based on the following equation.
yaycuycycnycycuycuycoyceycuycycayco ycycycoycuyceycycaycaycnycoycnycyc ycnycuyccyceycu = .
3 y ycEycycuycyceycaycyceycc yceycuycyceycycy.
3 y ycAycaycycycycayco yceycuycyceycycy.
3 y ycAycaycuyciycycuycyc.
1 y ycIEaycycycay.
2 y ycIycycaycoycyy.
The results from the analysis of social, economic, physical, and environmental vulnerability indices were then converted into a flash flood vulnerability index based on the following equation .
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yaycoycaycEa yceycoycuycuycc ycycycoycuyceycycaycaycnycoycnycyc ycnycuyccyceycu = .
4 y ycycuycaycnycayco ycycycoycuyceycycaycaycnycoycnycyc ycnycuyccyceyc.
25 y ycyEaycycycnycaycayco ycycycoycuyceycycaycaycnycoycnycyc ycnycuyccyceyc.
25 y yceycaycuycuycuycoycnyca ycycycoycuyceycycaycaycnycoycnycyc ycnycuyccyceyc.
1 y yceycuycycnycycuycuycoyceycuycycayco ycycycoycuyceycycaycaycnycoycnycyc ycnycuyccyceyc.
Eventually, the social, economic, physical, environmental, and flash flood disaster vulnerability indices were displayed in a vulnerability index map using ArcGIS 10.
3 software.
Results and Discussion Social Vulnerability Index Based on the social vulnerability index, the study area was divided into three classes: medium, high, and very The Sukajaya sub-district was identified as medium, two sub-districts (Nanggung and Cigude.
as high, and other sub-districts as very high (Table .
The social vulnerability index is highly affected by population The highest weight of the parameter is the population density, which is approximately 60%.
Therefore, the sub-district with more than 1,000 person/km2 has very high vulnerability, while the sub-district with a density between <500 person/km 2 and 1,000 person/km2 has medium to high vulnerability, such as the Nanggung.
Cigudeg, and Sukajaya sub-districts.
The social vulnerability maps have three different colors:
red, very high vulnerability.
orange, high vulnerability.
and yellow, medium vulnerability (Figure 2.
Table 6.
Social Vulnerability Index in the Upper Cisadane Watershed.
Population density .
eople/km.
Sex ratio Poverty ratio Disability ratio Vulnerable age groups ratio Social vulnerability Sum Score Sum Score Sum Score Sum Score Sum Score Score Class Pamijahan 1,258.
High West Bogor 7,112.
Very high South Bogor Very high 6,622.
Very high Central Bogor 11,839.
Very high East Bogor 10,278.
Very high Caringin 2,778.
Very high Ciampea 5,095.
Very high Ciawi 1,481.
Very high Cibungbulang 3,789.
Very high Cigombong 1,016.
Very high Cigudeg High Cijeruk 1,912.
Very high Ciomas 9,141.
Very high Dramaga 4,364.
Very high Kemang 3,120.
Very high Leuwiliang 1,369.
Very high Leuwisadeng 2,185.
Very high Megamendung 1,448.
Very high Rancabungur 2,678.
Very high Rumpin 1,066.
Very high Sukajaya Medium Tamansari 3,173.
Very high Tenjolaya 1,772.
Very high No.
Sub-districts Nanggung Source of data: .
Ae.
Population density greatly affects the social vulnerability of an area to a disaster.
Areas with a denser population have a greater chance of social loss from disasters than others because flash flood disasters occur in a relatively short time in a limited area .
In addition, the number of people who are vulnerable to flash flood disasters is equivalent to the workload of rescue teams in the event of a flood disaster .
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high population density in the study area is caused by various factors.
The research area is directly adjacent to the city area, close to the Central Business District (CBD) area and state universities, and is included in the Jabodetabekpunjur area, which has easy access to highway infrastructure .
rimary arterial roads and toll road.
that are integrated with suburban areas.
In addition, the ease of finding large tracts of land at relatively lower prices compared to the surrounding cities has caused many investors to build housing, increasing population density .
Economic Vulnerability Index The parameters of productive lands were paddy, corn, soybeans, and peanut fields.
The income per hectare from each type of productive land uses the data from production values and production costs per planting season per hectare of lowland rice, upland rice, corn, and soybeans in 2017 .
The production value per hectare is IDR 4,955,540, which has the following details: IDR 2,284,080 for paddy fields.
IDR 4,188,390 for cornfields, and IDR 1,228,460 for soybean field .
The parameter of job type .
rofession/occupatio.
is the type of occupation that is considered more vulnerable to flash floods, including the service sector, small businesses sector, daily wage employees, precarious workers, farmers, and fishermen.
The number of residents with vulnerable jobs in Bogor City is the total number of workers in the entire region of Bogor who work in the service sectors, daily wage employees, and small to medium business sectors.
understand economic vulnerability in the study area, there are three classes of economic vulnerability .
edium, high, and very hig.
West Bogor.
Central Bogor.
South Bogor, and East Bogor are identified as medium, six sub-districts (Caringin.
Cigombong.
Cigudeg.
Ciomas.
Sukajaya, and Tenjolay.
as very high, and other sub-districts as high (Table 7 and Figure 2.
Table 7.
The economic vulnerability index of Upper Cisadane Watershed.
No.
Sub district Nanggung Pamijahan West Bogor South Bogor Central Bogor East Bogor Caringin Ciampea Ciawi Cibungbulang Cigombong Cigudeg Cijeruk Ciomas Dramaga Kemang Leuwiliang Leuwisadeng Megamendung Rancabungur Rumpin Sukajaya Tamansari Tenjolaya Paddy (H.
3,578 6,580 1,926 1,007 2,183 1,301 2,832 1,366 3,920
1,705
2,652
2,753
2,169
Productive lands for corn and (H.
The total (Millio.
The score The job (%) Score Economic Economic 17,730.
32,607.
1,238.
9,544.
4,990.
3,488.
10,817.
6,530.
14,034.
7,229.
1,813.
1,328.
19,425.
8,449.
1,357.
1,189.
13,217.
13,643.
3,260.
10,748.
High High Medium Medium Medium Medium Very high High High High Very high Very high High Very high High High High High High High High Very high High Very high Source of data : .
Ae.
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In the economic vulnerability index, the highest value of the parameter is the weight of productive land .
%), while the sub-district in Bogor City with a paddy field of less than 500 ha has a medium vulnerability index.
Sub-districts with a high number of productive lands and high number of farmers have high vulnerability.
Sub-districts with very high vulnerability had a medium class of vulnerable occupation .
Ae40%).
The agricultural sector influences economic vulnerability to natural disasters, especially floods and droughts .
Ae Land use in the study area is dominated by dry-land agriculture .
29%), mixed dry-land agriculture .
,94%), and rice fields .
87%) .
Thus, the agricultural sector contributes to economic vulnerability both in the research area and in Bogor Regency .
This is also related to food security in the study area.
agricultural land is damaged by flash floods, economic stability and food security will be disrupted.
In addition to disrupting the economy, flash flood disasters also disrupt the movement of residents in their daily activities .
The duration of flash flood disasters also affects damage to agricultural land .
Physical Vulnerability Index The components of the physical vulnerability index for flash flood disasters are the density of residential houses .
ermanent, semi-permanent, and non-permanen.
, public infrastructure .
rayer building and school buildin.
, and critical facilities .
ealth facilit.
In this study, this assumption was used to determine the housing cost.
The permanent house is valued at IDR 200,000,000, the semi-permanent house at IDR 150,000,000, and the non-permanent house at IDR 75,000,000.
Public infrastructure was valued at IDR 200,000,000, while critical facilities were valued at IDR 250,000,000 (Table .
Table 8.
Physical vulnerability index of Upper Cisadane Watershed.
No.
Sub district Nanggung Pamijahan West Bogor South Bogor Central Bogor East Bogor Caringin Ciampea Ciawi Cibungbulang Cigombong Cigudeg Cijeruk Ciomas Dramaga Kemang Leuwiliang Leuwisadeng Megamendung Rancabungur Rumpin Sukajaya Tamansari Tenjolaya Housing density Public facility Critical facilities Total Score Total Price (Millio.
Score Total Price (Millio.
Score 1,033.
1,456.
3,218.
6,939.
4,678.
1,956.
3,841.
2,757.
1,046.
1,584.
5,062.
3,840.
2,816.
1,070.
1,654.
1,106.
2,021.
1,029.
2,259.
1,458.
20,800
83,600
63,600
123,200
44,200
27,400
39,400
32,800
67,800
58,400
41,400
30,000
18,400
31,000
32,000
27,800
61,200
27,200
26,600
28,000
50,200
46,400
68,200
54,200
9,750
4,500
9,500
3,500
2,750
1,000
3,250
2,000
2,500
1,250
3,250
4,250
1,750
7,500
2,000
1,000
1,750
1,000
1,000
4,750
Physical vulnerability The Total Class Score Medium Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high High Very high Very high Source of data: .
Physical vulnerability analysis shows that there are three physical vulnerability classes in the study area:
medium, high, and very high.
The Nanggung sub-district is medium, the Sukajaya sub-district is high, and other sub-districts are relatively high.
The highest weight of parameter measurement was the weight of housing .
ermanent, semi-permanent, and non-permanen.
, with a score of 40% (Figure 2.
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Settlement location affects the level of damage, as well as access and movement of people when a disaster Settlements in rural areas in mountains are separated and scattered, which can lead to difficulties accessing residents and rescue teams .
The effects of flash flood disasters not only affect the damage to each house but also the surrounding environment and infrastructure in one village.
This was due to strong flash flood currents accompanied by other materials, causing more severe damage to the environment .
Environmental Vulnerability Index The components of the environmental vulnerability index parameters used to flash flood disasters, such as natural forests, mangroves, swamps, and shrubs, are obtained from the LULC Map 2020 from MoEF in Figure The results of the environmental vulnerability index are listed in Table 9.
Three classes of environmental vulnerability were identified in the study area: high, medium, and low.
The Nanggung and Leuwiliang subdistricts have high environmental vulnerability.
Pamijahan.
Caringin.
Ciawi.
Cigombong.
Cijeruk.
Sukajaya.
Tamansari and Tenjolaya are medium, while other sub districts are low (Figure 2.
The protected forest in the study area consisted of primary and secondary dry forests with varying vegetation.
The environmental vulnerability index in the study area is influenced by the area of protected forest and natural forest in the upstream area of the river.
Flash floods can occur from the accumulation and rapid retention of water from upstream areas owing to landslides and heavy rains.
The water flow can carry material in its path, so it has the potential to damage upstream areas, which are usually dominated by forests .
Therefore, sub-districts with protected forest areas and natural forests upstream are more vulnerable than other sub-districts.
Table 9.
Environmental vulnerability index of Upper Cisadane Watershed Protected forest Nature forest Mangrove Shrub land Swamp Score Area (H.
Score Area (H.
Area (H.
Area (H.
Score Areas (H.
Score Total Score Class 4,206.
High 3,723.
Medium West Bogor Low South Bogor Low Central Bogor Low East Bogor Low Caringin 2,588.
Medium Ciampea Low Ciawi Medium Cibungbulang Low Cigombong Medium Cigudeg Low Cijeruk Medium Ciomas Low Dramaga Low Kemang Low Leuwiliang High Leuwisadeng Low Megamendung Low Rancabungur Low Rumpin Low Sukajaya Medium Tamansari Medium Tenjolaya Medium No.
Sub district Area (H.
Nanggung Pamijahan Environmental vulnerability Source of data: .
Flash Floods Vulnerability Index Upper Cisadane Watershed The flash flood vulnerability index in the Upper Cisadane watershed was calculated from the social, economic, physical, and environmental vulnerability indices based on the formula in Regulation of The Head of National This journal is AWardhani et al.
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Disaster Management Authority Number 2 of 2012.
The calculation results from Equation .
are listed in Table 10.
Table 10.
Flash Floods Vulnerability Index of Upper Cisadane Watershed.
Social vulnerability Physical vulnerability Economic vulnerability Environmental vulnerability The total of vulnerability Nanggung Weight Class High Weight Class Medium Weight Class High Weight Class High Weight Class High Pamijahan Very high Very high High Medium High West Bogor Very high Very high Medium Low High South Bogor Very high Very high Medium Low High Central Bogor Very high Very high Medium Low High East Bogor Very high Very high Medium Low High Caringin Very high Very high Very high Medium Very high Ciampea Very high Very high High Low Very high Ciawi Very high Very high High Medium Very high Cibungbulang Very high Very high High Low High Cigombong Very high Very high Very high Medium Very high Cigudeg High Very high Very high Low High Cijeruk Very high Very high High Medium Very high Ciomas Very high Very high Very high Low Very high Dramaga Very high Very high High Low Very high Kemang Very high Very high High Low Very high Leuwiliang Very high Very high High High Very high Leuwisadeng Very high Very high High Low High Megamendung Very high Very high High Low Very high Rancabungur Very high Very high High Low Very high Rumpin Very high Very high High Low Very high Sukajaya Medium High Very high Medium High Tamansari Very high Very high High Medium Very high Tenjolaya Very high Very high Very high Medium Very high Sub district Calculation of the flash flood disaster index based on Regulation of The Head of National Disaster Management Authority Number 12 of 2012 indicated that there are two classes of vulnerability .
igh and very hig.
According to the vulnerability map of the Upper Cisadane Watershed to flash flood disasters, orange color represents high vulnerability of the sub-district, while red color indicates very high vulnerability of the sub-district.
There are ten sub-districts (Nanggung.
Pamijahan.
West Bogor.
South Bogor.
Central Bogor.
East Bogor.
Cibungbulang.
Cigudeg.
Leuwisadeng, and Sukajay.
are categorized into high vulnerability, while 14 sub districts (Caringin.
Ciampea.
Ciawi.
Cigombong.
Cijeruk.
Ciomas.
Dramaga.
Kemang.
Leuwiliang.
Megamendung.
Rancabungur.
Rumpin.
Tamansari, and Tenjolay.
are categorized into very high class (Figure .
All sub-districts in the Upper Cisadane Watershed are highly vulnerable to flash floods, based on four types of vulnerability analysis .
ocial, economic, physical, and environmental indexe.
Very high vulnerability indicated that the social, economic, physical, and environmental conditions in the subdistrict were relatively more vulnerable than the sub-districts with high vulnerability.
Each parameter in social, economic, physical, and environmental vulnerability affects the other.
The population density parameter of social vulnerability affects land requirements, infrastructure facilities, housing, and livelihood, as well as economic, physical, and environmental vulnerability .
Local governments can lower the value of the vulnerability index by assisting the community in improving the economy and mitigating efforts by carrying out physical and non-physical activities.
Increasing economic value can help communities increase agricultural productivity after disasters.
The local government can also provide educational activities to the community for socializing the potential hazards of landslides and flash floods in the research area as non-physical activities .
Ae.
Vulnerability analysis of flash floods is important for creating a disaster mitigation map and a regional spatial planning map (RTRW) of Bogor Regency and Bogor City.
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29244/jpsl.
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Figure 2.
Vulnerability maps of the Upper Cisadane Watershed: .
Social vulnerability, .
Economic vulnerability, .
Physical vulnerability, .
Environmental vulnerability.
Figure 3.
Vulnerability index map of the Upper Cisadane Watershed to flash flood disasters.
Conclusions The social, economic, physical, and environmental vulnerability of the community in the Upper Cisadane watershed area needed for disaster mitigation planning in the study area.
The study found variations in vulnerability indices for flash floods ranging from moderate to very high.
It is worth considering whether these findings are reasonable, given the physical and demographic conditions of the study area.
Special attention needs to be given to areas with very high vulnerability, which include districts Kecamatan Caringin.
Ciampea.
Ciawi.
Cigombong.
Cijeruk.
Ciomas.
Dramaga.
Kemang.
Leuwiliang.
Megamendung.
Rancabungur.
Rumpin.
Tamansari, and Tenjolaya are very high.
In conclusion, it is hoped that local authorities will consider these study findings seriously and use them to plan measures to reduce community vulnerability to flash This journal is AWardhani et al.
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Regulation of The Head of National Disaster Management Authority Number 2 of 2012 used two parameters of economic vulnerability: productive land area and gross regional domestic product (GRDP).
The available GRDP parameter data do not describe conditions per district.
therefore, it is modified by the number of people with vulnerable jobs .
This modification is expected to show the real economic conditions of the community at the sub-district and village levels.
The flash flood disaster vulnerability map from this research sufficiently describes the real conditions, where sub-districts with very high flash flood disaster vulnerability are affected by flash floods.
Based on this map, the upstream area is prone to flash flood disasters.
Research in downstream areas needs to be conducted to determine the level of vulnerability to flash floods Acknowledgements I would like to express my gratitude to SAINTEK Scholarship.
National Research and Innovation Agency (BRIN), and IPB University for their support in this study.
References