Urban Coastal Flood-Prone Mapping under the Combined Impact of Tidal Wave and Heavy Rainfall: A Proposal to the Existing National Standard
Abstract
:1. Introduction
Study Area
2. Materials and Methods
- (a)
- Tidal data obtained from the website of Tide Observation and Prediction—Geospatial Information Agency (we referred to BIG: “Badan Informasi Geospasial” in Indonesian) (http://tides.big.go.id). The average of highest tidal data was assessed after data acquisition.
- (b)
- The rainfall data obtained from the website of the Tropical Rainfall Measuring Mission/TRMM (https://trmm.gsfc.nasa.gov) The National Aeronautics and Space Administration (NASA), USA. The maximum average of 10 years of rainfall data was assessed.
- (c)
- The land-use/land cover data obtained from the BIG digital Rupabumi map (base map) of Mataram City at a 1:5000 scale.
- (d)
- The slope data obtained from the BIG seamless digital elevation model (DEM) and National Bathymetry website (https://tides.big.go.id/DEMNAS). The digital terrain model (DTM) data were obtained within a 0.27-arc-second spatial resolution and converted into a slope by using the 3D analyst of GIS software.
- (e)
- The geomorphological data extracted and assessed from the digital land system map of Mataram City, published by BIG at a 1:25,000 scale and the digital soil map from the Indonesian Center for Agriculture Land Resources Research and Development at a 1:50,000 scale, Bogor- Indonesia.
2.1. Evaluation of the Existing Method
2.2. New Method Development
2.2.1. CFR-New method
2.2.2. CFC Method Development
2.2.3. Implementation of the Methods in Mapping
2.2.4. Field data inventory
2.2.5. Evaluation
3. Results
3.1. Coastal Flood-Prone Area Method Based on Rainfall
3.2. Coastal Flood-Prone Area Method Based on Combined Drivers
4. Discussion
- Land cover is essential for the CFR and CFC methods: [30] shows the empirical link of flooding to land use and land cover conversion that plays a vital role in the occurrence of flooding. Table 5 showed the increase of high and moderate vulnerability classes when the land cover/use parameter was added, with 42.63 ha for the high class and 125.56 ha for the moderate class from CR-2 to CR-3, respectively.
- The CFC method allows more detailed impacts on the land: [44,45] supports that coastal and deltaic areas are susceptible to flooding from the combined effects of excess rainfall and astronomic tide inundations. Table 8 describes the differences in susceptibility of the moderate and low classes in CFR-3 and CFR-new, with 142.74 ha and 140.18 ha, respectively, to CFC while an extreme tidal wave was added to the model.
- Flooding depends on geomorphological units: [46] supports the importance of hydro-geomorphological aspects for coastal flood mapping in that an alluvial plain can be used to delineate flood hazard areas based on his research in Constantine City, Algeria. The geomorphological type of the Mataram City coast is an alluvial plain. As can be seen in Figure 6, using either the CFR or CFC method, the alluvial plain area in the study site is vulnerable to flooding and can be used as a mapping unit. The observation area indicates that the highest tidal wave caused a dynamic form of the alluvial plain, which sometimes created a sand embankment along the coast of Mataram City. This condition may intensify the inundation of the area, especially in low areas that are blocked by sand embankments. In his research in Vietnam, [47] indicated that flooding and the dynamic mechanism of alluvial formation were correlated and, in turn, affected the flooding hazard.
Evaluation of the CFR-new and CFC methods
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Parameter | w | CFR-2 Classes | w | CFR-3 Classes | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
High | S | Moderate | S | Low | S | High | S | Moderate | S | Low | S | |||
Slope | 70 | 0–2% | 3 | 2–4% | 2 | >4% | 1 | 35 | 0–2% | 3 | 2–4% | 2 | >4% | 1 |
Land cover/use | 35 | Settlements | 3 | Bushes/agriculture/mixed crops/plantations | 2 | Rice fields/forest/gardens/sand/bare land | 1 | |||||||
Rainfall | 30 | ≥200 mm | 3 | 50–200 mm | 2 | ≤50 mm | 1 | 30 | ≥200 mm | 3 | 50–200 mm | 2 | ≤50 mm | 1 |
Flood-Prone Area | Class Interval | Vulnerability Classes | |
---|---|---|---|
Flood-Prone Classes | |||
>Y–Z | |||
>X–Y | |||
= X | 0–X |
Land Cover/Use | Slope | Rainfall | ∑ Row | Eigenvector | Results | Weight | Weighted Sum Vector (WSV) | Consistency Vector (CV) | |
---|---|---|---|---|---|---|---|---|---|
Land cover/use | 1 | 3 | 5 | 1.90 | 0.6333 | 1.2033 | 1.20 | 1.9458 | 3.0725 |
Slope | 0.33 | 1 | 3 | 0.78 | 0.2605 | 0.2032 | 0.20 | 0.7902 | 3.0334 |
Rainfall | 0.20 | 0.33 | 1 | 0.32 | 0.1062 | 0.0340 | 0.03 | 0.3197 | 3.0103 |
λ | 3.0387 | ||||||||
Consistency Index (CI) | 0.0194 | ||||||||
Consistency Ratio (CR) | 0.0334 |
Parameter | Weighting | Classification of the Coastal Flood-prone Area | |||||
---|---|---|---|---|---|---|---|
High | Score | Moderate | Score | Low | Score | ||
Land cover/use | 1.20 | Settlements | 3 | Bushes/agriculture/mixed crops/plantations | 2 | Rice fields/forest/gardens/sand/bare land | 1 |
Slope | 0.20 | 0–2% | 3 | 2–4% | 2 | 4% | 1 |
Rainfall | 0.03 | ≥200 mm | 3 | 50–200 mm | 2 | ≤50 mm | 1 |
Prone Classes | Area (ha) | ||
---|---|---|---|
CFR-2 | CFR-3 | CFR-New | |
High | 58.65 | 101.28 | 103.84 |
Moderate | 56.98 | 182.54 | 179.98 |
Low | 183.09 | 14.90 | 14.90 |
Slope | Tidal Wave Inundation | Land Cover/Use | Rainfall | ∑ Rows | Eigen Vector | Result | Weight | Weighted Sum Vector (WSV) | Consistency Vector (CV) | |
---|---|---|---|---|---|---|---|---|---|---|
Slope | 1 | 3 | 5 | 7 | 2.23 | 0.5579 | 1.2441 | 1.24 | 2.3556 | 4.2223 |
tidal wave inundation | 0.33 | 1 | 3 | 5 | 1.05 | 0.2633 | 0.2765 | 0.28 | 1.0995 | 4.1757 |
Land cover/use | 0.20 | 0.33 | 1 | 3 | 0.49 | 0.1219 | 0.0597 | 0.06 | 0.4919 | 4.0357 |
Rainfall | 0.14 | 0.2 | 0.33 | 1 | 0.23 | 0.0569 | 0.0131 | 0.01 | 0.2299 | 4.0403 |
λ | 4.1185 | |||||||||
Consistency Index (CI) | 0.0395 | |||||||||
Consistency Ratio (CR) | 0.0439 |
Parameter | Weighting | Classification of the Coastal Flood-Prone Area | |||||
---|---|---|---|---|---|---|---|
High | Score | Moderate | Score | Low | Score | ||
Slope | 1.24 | 0–2% | 3 | >2–4% | 2 | >4% | 1 |
Tidal wave inundation | 0.28 | ≤14.93 m | 3 | >14.93–47.68 m | 2 | >47.68 m | 1 |
Land cover/use | 0.06 | Settlements | 3 | Bushes/agriculture/mixed crops/plantations | 2 | Rice fields/forest/gardens/sand/bare land | 1 |
Rainfall | 0.01 | ≥200 mm | 3 | 50–200 mm | 2 | ≤50 mm | 1 |
Prone Classes | Area (ha) | ||
---|---|---|---|
CFR-3 | CFR-New | CFC | |
High | 101.28 | 103.84 | 244.01 |
Moderate | 182.54 | 179.98 | 48.94 |
Low | 14.9 | 14.9 | 5.76 |
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Sutrisno, D.; Rahadiati, A.; Rudiastuti, A.W.; Dewi, R.S.; Munawaroh. Urban Coastal Flood-Prone Mapping under the Combined Impact of Tidal Wave and Heavy Rainfall: A Proposal to the Existing National Standard. ISPRS Int. J. Geo-Inf. 2020, 9, 525. https://doi.org/10.3390/ijgi9090525
Sutrisno D, Rahadiati A, Rudiastuti AW, Dewi RS, Munawaroh. Urban Coastal Flood-Prone Mapping under the Combined Impact of Tidal Wave and Heavy Rainfall: A Proposal to the Existing National Standard. ISPRS International Journal of Geo-Information. 2020; 9(9):525. https://doi.org/10.3390/ijgi9090525
Chicago/Turabian StyleSutrisno, Dewayany, Ati Rahadiati, Aninda W. Rudiastuti, Ratna Sari Dewi, and Munawaroh. 2020. "Urban Coastal Flood-Prone Mapping under the Combined Impact of Tidal Wave and Heavy Rainfall: A Proposal to the Existing National Standard" ISPRS International Journal of Geo-Information 9, no. 9: 525. https://doi.org/10.3390/ijgi9090525