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International Journal of Oceans and Oceanography
ISSN 0973-2667 Volume 13, Number 1 (2019), pp. 129-146
© Research India Publications
http://www.ripublication.com
Sea Level Rise-Impacted Tuban Coastal
Vulnerability Model
Marita Ika Joesidawati1), Suntoyo2), Wahyudi2), Kriyo Sambodo2)
1)Faculty of Fisheries and Marine Science, Universitas PGRI Ronggolawe, Tuban, Indonesia
2) Department of Ocean Engineering, Faculty of Marine Technology, Institut Teknologi Sepuluh, Nopember (ITS), Surabaya 60111, Indonesia
Abstract
Indicators of climate change related to global warming include temperature
rise, rainfall change and sea level rise (SLR). The impact of climate change is
beginning to be felt in Indonesia, including the increasingly uncertain weather,
floods, long droughts, strong winds. While the impact of rising sea levels
began to inundate the productive lands. Tuban Regency is the northern coastal
area of East Java Indonesia is also estimated to be affected by SLR. The aim
of this research is to develop susceptibility model of the effect of SLR and to
know the magnitude of the impact of SLR that occurred. Determination of
coastal susceptibility index to SLR used in this research is 6 physical
parameters and 6 parameters of human activity. The impact of SLR that occurs
using Coastal Vulnerability Index (CVI) matrix is then simulated by using the
impact magnitude map
Keywords: Sea Level Rise, Coastal Vulnerability Index, physical parameters,
human activity parameters
1. INTRODUCTION
Sea level rise (SLR) due to climate change can affect human populations in coastal
areas, small islands and marine ecosystems. SLR are expected to continue for
centuries (Bindoff et al., 2013; Fischlin; et al., 2007). IPCC (2013) estimates sea level
rise to reach 42-98 cm by 2100. To reduce the impact that will occur due to SLR it is
necessary to identify and protect vulnerable parts of the coast to prevent unpredictable
disasters. Therefore, to be able to determine the appropriate protection of coastal
130 Marita Ika Joesidawati, Suntoyo, Wahyudi, Kriyo Sambodo
susceptibility assessment activities on the impact of SLR. Özyurt (2007) and Özyurt
et al. (2008) developed Coastal Vulnerability Index (CVI) specifically assess the
impact caused by SLR. The index is determined through 5 parameters: coastal
erosion, storm flood, permanent flood, sea water intrusion into groundwater and river.
ETC CCA (2011) assessed coastal vulnerability to sea level rise using 12 coastal
physical parameters and 7 parameters of human activities. Pendleton et al. (2005) and
Gornitz et al. (1997) analyzed the vulnerability of coastal areas with two variables,
namely geological variables (geomorphology, elevation / surface elevation in coastal
areas and coastline changes) and marine process physical variables (relative sea level
rise, average tidal ridge and significant wave height). This parameter is commonly
used as a susceptibility analysis of SLR.
Determination of coastal susceptibility index to SLR used in this study was a
modification of Pendleton et al. (2005) and Gornitz et al. (1997) and Özyurt, (2007).
Physical Geomorphology, (2) Soil Surface height, (3) Average tidal raise, (4)
Significant wave height (5) Relative sea water advance rise (KMR) (3) Ground Water
Consumption, (4) Land Use Pattern, (5) Natural protection against degradation, (6)
Coastal protection structure The purpose of this research is to develop susceptibility
model of the effect of SLR and to know the magnitude of the impact of SLR that
occurred.
2. STUDY AREA
Tuban Regency is one of the coastal cities located in East Java Province, Indonesia
Geographically Tuban Regency is located at coordinates 111º30'-112º35'EL and
6º40'-7º18'SL. The scope of research macro area of coastal area of Tuban Regency is
the sub-districts bordering the waters of the North Sea of Java. The macro area
consists of 5 coastal sub-districts (Bancar District, Tambakboyo, Jenu, Tuban and
Palang). While the micro area in this research that is land in coastal area of Tuban
Regency which predicted will be affected or area 300 m from shoreline at the time of
research.
The problem of coastal cities in the global scope is due to climate change is very
influential on local issues. UNDP (2007) describes the impacts of global climate
change can exacerbate existing risks and vulnerabilities in local issues that can
threaten coastal sustainability and increase the burden of their ability to deal with
local problems. Condition of Coastal Area of Tuban Regency Climate Change, among
others:
Rainfall Pattern
Fig 1 showed that the dry season in Tuban Regency is longer than the rainy season
but with higher bulk. While the rain pattern is erratic, this proves the changing climate
and the amount of rainfall is also changing. UNDP (2007) explains with frequent
unpredictable rainfall, higher air temperatures can drain soil, reduce groundwater
sources, degrade land, and in some cases, can lead to desertification.
Sea Level Rise-Impacted Tuban Coastal Vulnerability Model 131
Fig 1 Comparison of rainy season, dry season and rainfall pattern
of Tuban district (2000-2015)
Air Temperature Trends
Air temperature data obtained from Meteorology, Climatology and Geophysics
Agency Surabaya and Tuban Environmental Agency showed that the increase in air
temperature during the year 2000-2015 amounted to 0.131 ºC from the annual average
temperature (Fig 2). This indicates that the air temperature in the coastal areas of
Tuban district has also increased as a result of climate change. IPCC (2007) explains
the Earth's surface temperature at the end of the 21st century will rise from 1.1ºC to
6.4ºC, if air temperatures rise by 1ºC the sea begins to lose the ice layer above it will
absorb more heat and accelerate global warming; Fresh water disappears from a third
of Earth's surface; Lowland areas on the coast will be hit by floods.
132 Marita Ika Joesidawati, Suntoyo, Wahyudi, Kriyo Sambodo
Fig 2. Trends in the average temperature of Tuban district (2000-2015)
Sea Water Temperature Trends
Sea water temperature for coastal area of Tuban Regency, measured directly on Boom
Tuban beach in 2008-2015 with 3 depth and 3 different observation time, the result
shows that the greater the intensity of the sun that received sea water the higher the
temperature of the sea water while the depth no effect. While the average of each year
as shown in Fig 3 shows an increase in sea water temperature of 0.0895oC from the
mean annual sea water temperature.
Fig 3. Average per year of sea water temperature at Tuban beach (2007-2016)
Sea Level Rise-Impacted Tuban Coastal Vulnerability Model 133
Fig 4 Flood rob at high tide
Flood and Rob
Flood and rob in Tuban Regency was also a problem that is quite influential on
coastal communities, because it often disturbs the activities of coastal communities
themselves. Based on the results of the field survey. Fig 4 most of the coast in coastal
areas prone to rob especially when the big tide (month of dead or full moon in
October-December).
Retreat Shoreline
The analysis of Digital Shoreline Analysis System (DSAS) at Tuban Beach from 1972
to 2015 by combining 5 coastlines from Landsat multitemporal satellite images
declined with an average rate of change of 15.23 m / year (EPR/End Point Rate) and
13.86 m / year (LRR / Linear Regression Rate) (Joesidawati and Suntoyo, 2016).
3. METHODOLOGY
Measurement measures of coastal vulnerability in coastal areas of Tuban Regency due
to sea level rise using 3 stages:
Phase I is the determination of coastal vulnerability index parameter, coastal
vulnerability assessment due to sea level rise using 6 physical parameters which is a
modification of Pendleton et al. (2005) and Gornitz et al. (1997), namely geological
parameters (geomorphology (GF), surface elevation (E) in coastal areas and coastline
changes (PGP) and marine physical process parameters (relative sea rise/KMR),
average tidal ridge (TR), and significant high wave (SHW) .This parameter is
commonly used as a susceptibility analysis of the SLR and 6 parameters of human
activities (Özyurt, 2007) include 1) Sand Mining, (2) Beach Reclamation (RP) (3)
134 Marita Ika Joesidawati, Suntoyo, Wahyudi, Kriyo Sambodo
Land Use (PL), (5) Natural protection against degradation (PA), (6) Coastal
protection structure (SP).
Phase II is the process of obtaining Parameters of coastal vulnerability index. Phase
III is the weighting (scoring), The weighting of physical parameters of coastal
vulnerability to sea level rise Table 1 and 2.
Table 1. Weighting of Physical Coastal Vulnerability to Sea Level Rise
No
Parameter
Weight / Class Vulnerability
Not
vulnerable
Less
vulnerable
Medium Susceptible Very vulnerable
1 2 3 4 5
1 Coastal
Geomorphology
(GF) (1)
High cliff Medium
Cliff
Low
cliffs,
alluvial
plains
Estuarine,
Lagoon
Sandy beach,
Swamp,
brackish, mud,
delta, mangrove,
coral exposure
2 Soil Surface Level
(Elevation/E) (2) (in
m)
>30,0 20.1-30.0 10.1-20.0 5.1-10.0 0.0-5.0
3 Average tidal
distance (TR) (3) (in
m)
> 6.0 4.0-6.0 2.0-4.0 1.0-2.0 < 1.0
4 Significant Wave
Height (SWH) (3)
(in m)
< 0.55
0.55-0.85
0.85-1.05
1.05-1.25
> 1.25
5 Relative Sea Water
Rise (KMR) (3) (in
mm / yr)
< 1.8 1.8-2.5 2.5-3.0 3.0-3.4 > 3.4
6 Relative coastline
change (PGP)
The calculation results Changes Coastline adjusted field conditions (the
accretion, erosion). There are 2 Reference scores
Relative coastline
change (m / th)
(Accretion and
abrasion) (3)
> 2.0
(Accretion)
1.0-2.0
(Accretion)
-1.0-1.0
(stable)
-2.0- -1.0
(Abrasion)
< -2.0
(Abrasion)
Relative coastline
change(4) (m / th)
(Abrasion)
0 0-1 1.01-5 5.01-10 > 10
Source: Thieler and Hammar-Klose, 2000(1); Gornitz et al. 1997 (2); Pendleton et al., 2005 (3); Boruff et al., 2005(4)
Sea Level Rise-Impacted Tuban Coastal Vulnerability Model 135
Table 2. Weighting of Parameters of Coastal Vulnerability Effects on Coastal SLR
No
Parameter
Weight / Class Vulnerability
Not
vulnerable
Less
vulnerable
Medium Susceptible Very
vulnerable
1 2 3 4 5
1 Sand Mining >80% 60-80% 40-60% 20-40% <20%
2 River Basin Rules Not
affected
Affected
moderately
Greatly
affected
3 Beach reclamation <5% 5-20% 20-30% 30-50% >50%
4 Ground Water
Consumption
>20% 20-30% 30-40% 40-50% >50%
5 Pattern of Land
use
Protected
area
Unclaimed Residence Industry Agricultural
6 Natural protection
against
degradation
>80% 60- 80% 40- 60% 20 -40% <20%
7 Coastal protection
structures
>50% 30- 50% 2 20- 30% 5 - 20% <5%
Source:Özyurt (2007)
So that coastal susceptibility index is calculated with the following formulation as
follows:
CVI = √(𝒑𝒂𝒓𝒂𝒎𝒆𝒕𝒆𝒓 𝑨∗ 𝒑𝒂𝒓𝒂𝒎𝒆𝒕𝒆𝒓 𝑩………∗𝒑𝒂𝒓𝒂𝒎𝒆𝒕𝒆𝒓 𝒕𝒐−𝒏)
𝒑𝒂𝒓𝒂𝒎𝒆𝒕𝒆𝒓 …..(3.1)
where:
CVI = Coastal Vulnerability Index
After the calculation results are obtained, the coastal susceptibility index was further
classified into 5 classes, ie, areas that are not vulnerable, less vulnerable, moderate,
vulnerable and very vulnerable. Values range between 1 and 5 The class breakdown
was done by dividing by percent with a range between classes of 20%. Values less
than 20% including non-vulnerable classes, 20% - 40% included in less vulnerable
classes, 40% - 60% middle class, 60% - 80% were in vulnerable classes, and more
than 80% susceptible.
136 Marita Ika Joesidawati, Suntoyo, Wahyudi, Kriyo Sambodo
The impact of SLR is calculated by the formula
CVI impact =(0.5 x ∑ PPn)+ (0.5 x ∑ HPm)m
1n1
CVI least vulnerable …..(3.2)
where: PP = Physical Parameter;
HP = Human Parameter;
n and m = number of physical parameters and human influence
CVIleastvulnerable= value of vulnerability index (vulnerable-very
vulnerable)
CVI (SLR) =∑ Total impact5
𝑖=1
∑ Least Vulnerable Case5𝑖=1
…..(3.3)
Where the value of CVI (SLR) is determined as follows:
Not Vulnerable: 1 ≤CVI (SLR) <1,5
Less Vulnerable: 1.5 ≤CVI (SLR) <2.5
Medium Vulnerability: 2.5 ≤CVI (SLR) <3,5
High Vulnerability (Vulnerable): 3,5 ≤CVI (SLR) <4,5
Very Vulnerable: 4,5 ≤CVI (SLR) <5
4. RESULTS
Assessment of coastal vulnerability of coastal areas of Tuban Regency to sea level
rise (SLR) with physical parameters.
Fig 5. Map of CVI Value/Coastal Vulnerability Index of Tuban Regency on Sea
Level Rise (Physical Parameter)
Sea Level Rise-Impacted Tuban Coastal Vulnerability Model 137
Based on Fig 5, the grouping or range of CVI values with the physical parameters of
the SLR, the sub-districts are in the "moderate" and "very vulnerable" vulnerability
levels. Tambakboyo sub-district is at "very vulnerable" level in all coastal villages,
while Tuban District is at "vulnerable" and "medium" levels and barriers at
"vulnerable" and "very vulnerable" levels.
Assessment of coastal vulnerability of coastal areas of Tuban to SLR with human
activity parameters (Fig 6)
Fig 6. Map of CVI Value / Coastal Vulnerability Index of Tuban Regency on Sea
Level Rise (Parameter of Human Activity)
Based on Fig 6, the grouping or range of CVI values of human activities: Bancar,
Tambakboyo, Palang and Tuban sub-districts are at "vulnerable" to "moderate"
vulnerabilities. Jenu sub-districts were at“not vulnerable”to“very vulnerable” levels.
Impact of Sea Level Rise (SLR)
The coastal susceptibility assessment model of the impact of sea level rise uses the
CVI (SLR) matrix. Matrix displays the vulnerability index score of both physical
parameters and human activities) with the aim of prioritizing the impact of sea level
rise. Based on Table 3 it can be seen that the impact of sea level rise has 3 groups,
namely coastline retreat, waterlogging, and intrusion of sea water, with impact value
of 3.5 - 4 (vulnerable). The priority scale of the impact of sea level rise in the study
sites indicates the presence of inundation (4), seawater intrusion (4) and coastline
retreat (3.5).
138 Marita Ika Joesidawati, Suntoyo, Wahyudi, Kriyo Sambodo
Coastal of Tuban Regency most susceptible to inundation (CVI = 4) means threat of
damage to soil loss due to inundation of coastal erosion Effect of human activity
parameters may increase vulnerability to pools and the absence of coastal protection
(at the long coastal structuring research location of 22,640 M or 34% of the existing
coastal length, and the natural protective length in this case the mangrove 9406 m
wide and 294 m wide).
The coastline retreat (CVI SLR = 3.5) is the most significant problem of coastal
Tuban district. So, engineering of coastal areas is very important because it shows
vulnerability to coastal erosion due to rising sea levels. The physical parameters of the
coastal coast of Tuban will increase due to human activities such as sand mining,
reclamation of dock development. Fig 7 shows the effect of physical and human
parameters equally affecting coastal vulnerability of Tuban district.
Fig 7. Effects of Physical Parameters and Human Activity Levels on the Impact of
Sea Level Rise
Table 3. Matrix of the Impact of Sea Level Rise in the Research Sites
Impact Physical Parameters Parameter of Human Activities Total
value
Lowest
Vulnerability
Index
CVI
Impact
Impact
Class Parameter 1 2 3 4 5 Total No Parameter 1 2 3 4 5 Total
Coastline
Setback
(Beach
Erosion)
1 Coastal Geomorphology 1 4 1 Mining of sand 1 1
2 Ground Surface Level 1 5 2 Beach reclamation 1 1
3 Average Tidal ride 1 5 3 Natural Protection 1 5
4 Significant Wave Height 1 1 4 Coastal Protection Structure 1 3
5 Relative sea water level rise 1 5
6 Coastline Changes 1 5
Total 1 0 1 4 25 Total 2 1 1 10 18.5 5 3.5 vulnerable
Inundation
(Flood
ROB)
1 Ground Surface Level 1 5 1 Natural Protection 1 5
2 Average Tidal ride 1 5 2 Coastal Protection Structure 1 3
3 Significant Wave Height 1 1
4 Relative sea water level rise 1 5
Total 1 0 3 16 Total 1 1 8 12 3 4 vulnerable
Intrusion
Sea water
in Ground
Water
1 Coastal Geomorphology 1 4 1 Ground Water Consumption 1 5
2 Ground Surface Level 1 5 2 Pattern of land use 1 3
3 Average Tidal ride 1 5
4 Significant Wave Height 1 1
5 Relative sea water level rise 1 5
Total 1 0 1 3 20 Total 1 1 8 14 3.5 4 vulnerable
139
140 Marita Ika Joesidawati, Suntoyo, Wahyudi, Kriyo Sambodo
The freshwater source of the coastal community of Tuban Regency comes from
ground water. The intrusion of sea water into ground water occupies the second rank
(CVI = 4). In this research has not been studied in depth about the map pemar of salt
ground water to brackish, both on shallow aquifer and deep aquifer and also to know
the cause of salt water salinity. The data obtained is the source of clean water use
from coastal communities through drilling wells with a minimum depth of 25 m.
5. DISCUSSION
Impact of Coastline Slope Degradation
Based on the validation of the model (Joesidawati and Suntoyo, 2017) using the
smallest error method, the Hennecke Method has a smaller value (0.245%) than the
Bruun Method (0.377%). So, the calculation of the impact losses from the shoreline
changes using the Hennecke method.
Fig 8 is a predicted shoreline change with the overlapped Hennecke Method with
high-resolution Google Earth imagery and Table 4 shows the extent of land affected
by the Hennecke Model shoreline retreat.
Fig 8. Lost Land Predictions Impacts of Hennecke Model Lines Degradation in 2050
(red) and in 2100 (pink) on Overlay with Google Earth Resolution High Image
Sea Level Rise-Impacted Tuban Coastal Vulnerability Model 141
Table 4 Extent and Percentage of Affected Lands of Hennecke Coastline Lines
Year
Average
Coastline
Lift
(m)
Lost area of
land (m2)
Percentage
Average Lost
Land / Area of
Village
Average
Percentage of
Land Missing /
Area of
District
Percentage
Average Lost
Land / Area of
Regency
2050 88,22 16.140.631,571 22,82% 0,26% 0,017%
2100 161,01 23.324.606,539 31,06% 0,37% 0,024%
The existing landuse shows that the strategic lands of the fishery and marine areas
affected by the SLR shoreline (Fig 9), the PPI (100%) and the National PPI (99.99%),
and Tambak (31.15%).
Fig 9. Area of Land due to Coastline Degradation in 2050 and 2100 by Land Use
Type Existing
142 Marita Ika Joesidawati, Suntoyo, Wahyudi, Kriyo Sambodo
Impact of inundation due to SLR
Regional Prediction Flooded in 2050 and 2100 for the district of Tuban in Fig 10, Fig
11 and Table 5
Fig 10. Predicted Area Flooded by Sea Level Reversal in 2050 on Overlay with High
Resolution Image Google Earth
Fig 11. Regional Prediction Flooded by Sea Level Reversal in 2100 on Overlay with
High Resolution Image Google Earth
Sea Level Rise-Impacted Tuban Coastal Vulnerability Model 143
Table 5. Area and Percentage of Land Flooded by Impact of SLR
Year Sea Level
Rise (m)
Land area was
Flooded (m2)
Average
Percentage of
Land Area
Flooded / Area
of Village
Average Percentage
of Land Area
Flooded / Area of
District
Average Percentage
of Land Area / Area
of Regency
2050 1,44 30.102.134,636 10,04% 0,24% 0,016%
2100 2,64 71.396.054,437 25,36% 0,57% 0,037%
When viewed from the type of land use, some potential lands such as rice fields,
ponds, settlements are also affected by inundation due to SLR as shown in Fig 12,
infrastructure in the field of fisheries and marine affected by the largest inundation is
the National PPI, regional Jenu port, TPI, Year 2100 above 65%, while for the field of
fisheries activities that ponds flooded 71.57% in 2050 and 87% in 2100.
Fig 12. Land which Flooded in 2050 and 2100 by type of Existing Land Use
144 Marita Ika Joesidawati, Suntoyo, Wahyudi, Kriyo Sambodo
Based on Fig 13 it can be seen that the effect of intrusion is also influenced by sea
level rise. It was evident that the intrusion of seawater into groundwater at a moderate
rate occurs in the longer-flooded areas and coastal retreat. Based on the distribution
map of existing DHL value in Tuban Regency it was seen that groundwater slightly
brackish in shallow aquifer in the area ie groundwater having DHL value more than
1500 μS/cm in four subdistricts (Bancar, Tambakboyo, part of Jenu and Palang). The
area has a distance with the sea was quite close, but in some places the location was
also still found water conditions that are not salty. A slightly brackish groundwater
distribution area occupies an aquifer clay aquifer which is alluvial deposits with
generally low permeability and flat topography to ramps, making it very susceptible
to sea water intrusion. Ground water was slightly brackish dominated by aquifers in
the form of gampingan sands to clay gampingan, but some also still enter into the
alluvial sedimentary aquifer system. In addition to the differences in the system of
rocks of the constituent aquifer distance between wells with sea water is also one of
the factors causing differences in the level of ground water salinity.
Fig 13. Intrusion Conditions of Sea Water Research Sites (Groundwater Sampling
300 m from the Beach in October-November 2014)
Sea Level Rise-Impacted Tuban Coastal Vulnerability Model 145
6. CONCLUSIONS
Based on the CVI Matrix (SLR) it can be seen that the impact of the increase in SLR
is 3 groups: causing coastline retreatment, inundation, and intrusion of sea water, with
impact value of 3.5 - 4 (vulnerable).
Acknowledgments
Acknowledgment of the authors convey to all parties involved, especially at the
Institute of Technology Sepuluh Nopember Surabaya and the University of PGRI
Ronggolawe Tuban
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