THE ESTIMATION OF FLOOD AREA BASED ON A FEW SELECTED AND WEIGHTED PARAMETERS: CASE STUDY OF THE NANGKA RIVER BASIN, BALIKPAPAN (INDONESIA)

Totok Sulistyo; Sara Respati

doi:10.2298/IJGI2302123S

Authors

Totok Sulistyo Balikpapan State Polytechnic, Department of Civil Engineering, Balikpapan
Sara Respati Balikpapan State Polytechnic, Department of Civil Engineering, Balikpapan

DOI:

https://doi.org/10.2298/IJGI2302123S

Keywords:

flood parameters, Pareto Analysis, AHP, GIS, river basin

Abstract

In several previous studies on flood analysis and estimation, there was no clear rationale for why different researchers used a different combination of parameters in the determination of flood zones. Such research results raise the question of how to select a few dominant parameters without reducing the objectivity of the analysis. This research proposes the standardization of parameters selection by using Pareto Analysis in screening a few vital flood parameters from numerous parameters that prevail in certain areas. The selection of the right dominant parameters is the key to achieving the analysis goal and it will also simplify the analysis processes. This flood zone estimation study uses a combination of Pareto Analysis, Analytic Hierarchy Process (AHP) and Geographic Information System (GIS). The results of the study include a flood zonation map. The study area can be classified by its level of vulnerability as follow: very low vulnerability zones (0.003 km2), low vulnerability zones (5.588 km2), medium vulnerability zones (11.876 km2), high vulnerability zones (8.629 km2), and very high vulnerability zones (2.198 km2). The validation shows that the estimation of the most vulnerable zone is consistent with field validation and the flood event history of several locations in the study area. As a result, the developed model can provide an accurate flood zonation map, enabling stakeholders to take appropriate mitigation measures for different areas.

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References

AHP Calculation software by CGI [Computer software] (n.d.). Retrieved May 26, 2022, from http://www.isc.senshu-u.ac.jp/~thc0456/EAHP/AHPweb.html

Balikpapan City Government. (2021). Peraturan Daerah Kota Balikpapan Nomor 6 Tahun 2021 Tentang Rencana Pembangunan Jangka Menengah Daerah Tahun 2021-2026 [Balikpapan City Regional Regulation Number 6 of 2021 concerning Regional Medium-Term Development Plans for 2021-2026]. http://bappedalitbang.balikpapan.go.id/assets/globalimg/RPJMD_Kota_Balikpapan_Tahun_2021-_2026.pdf

Boulomytis, V. T. G., Zuffo, A. C., & Imteaz, M. A. (2019). Detection of flood influence criteria in ungauged basins on a combined Delphi-AHP approach. Operations Research Perspectives, 6, Article 100116. https://doi.org/10.1016/j.orp.2019.100116

Brunelli, M. (2015). Introduction to the Analytic Hierarchy Process. Springer International Publishing. https://doi.org/10.1007/978-3-319-12502-2

Can, E., & Erbiyik, H. (2016). Determination of the Risks That Are Emerged from the Use of Aerial Photographs in the Mapping Activities for Landslide Movements by FMEA and Pareto Analysis Methods and Suggested Solutions. Procedia Engineering, 161, 850–858. https://doi.org/10.1016/J.PROENG.2016.08.729

Das, S., & Gupta, A. (2021). Multi-criteria decision based geospatial mapping of flood susceptibility and temporal hydro-geomorphic changes in the Subarnarekha basin, India. Geoscience Frontiers, 12(5), Article 101206. https://doi.org/10.1016/j.gsf.2021.101206

European Space Agency. (n.d.). DEM Copernicus 30 (GLO-30) [Data set]. https://doi.org/10.5270/ESA-c5d3d65

Erdil, A. (2019). An Evaluation on Lifecycle of Products in Textile Industry of Turkey through Quality Function Deployment and Pareto Analysis. Procedia Computer Science, 158, 735–744. https://doi.org/10.1016/j.procs.2019.09.109

Grigorecu, I., Sima, M., Dragotă, C.-S., & Dumitrică, C. (2021). Climate hazard maps-a tool to support communication with stakeholders. A showcase of Baia Mare depression, Romania. Romanian Journal of Geography, 65(2), 105–123. http://www.rjgeo.ro/issues/revue%20roumaine%2065_2/grigorescu%20et%20al..pdf

Handini, D. R., Hidayah, E., & Halik, G. (2021). Flash Flood Susceptibility Mapping at Andungbiru Watershed, East Java Using AHP-Information Weighted Method. Geosfera Indonesia, 6(2), 127–142. https://doi.org/10.19184/geosi.v6i2.24173

Hidayat, S., & Umar, I. (1994). Peta Geologi Lembar Balikpapan, Kalimantan [Geological Map of the Balikpapan Quadrangle, Kalimantan]. https://geologi.esdm.go.id/geomap/pages/preview/peta-geologi-lembar-balikpapan-kalimantan

Jahangir, M. H., Mousavi Reineh, S. M., & Abolghasemi, M. (2019). Spatial predication of flood zonation mapping in Kan River Basin, Iran, using artificial neural network algorithm. Weather and Climate Extremes, 25, Article 100215. https://doi.org/10.1016/j.wace.2019.100215

Jordan, N. A., Sherlia, & Syafitri, E. D. (2021). Building age profile and figure-ground image: Defining the urban development pattern of Balikpapan City. IOP Conference Series: Earth and Environmental Science, 778(1), Article 012038. https://doi.org/10.1088/1755-1315/778/1/012038

Juwita, R., & Santoso, I. B. (2019). Assessment of Soil Infiltration Capability in Balikpapan City. IPTEK Journal of Proceedings Series, 5, 291–297. https://iptek.its.ac.id/index.php/jps/article/view/6341

Land and Spatial Arrangement Office Balikpapan City. (2018). Peta Tutupan Lahan [Land Use Map]. https://data.balikpapan.go.id/dataset/tutupan-lahan

Li, C., Dash, J., Asamoah, M., Sheffield, J., Dzodzomenyo, M., Gebrechorkos, S. H., Anghileri, D., & Wright, J. (2022). Increased flooded area and exposure in the White Volta river basin in Western Africa, identified from multi-source remote sensing data. Scientific Reports, 12(1), Article 3701. https://doi.org/10.1038/S41598-022-07720-4

Mujib, M. A., Apriyanto, B., Kurnianto, F. A., Ikhsan, F. A., Nurdin, E. A., Pangastuti, E. I., & Astutik, S. (2021). Assessment of Flood Hazard Mapping Based on Analytical Hierarchy Process (AHP) and GIS: Application in Kencong District, Jember Regency, Indonesia. Geosfera Indonesia, 6(3), 353–376. https://doi.org/10.19184/geosi.v6i3.21668

Notti, D., Giordan, D., Caló, F., Pepe, A., Zucca, F., & Galve, J. P. (2018). Potential and Limitations of Open Satellite Data for Flood Mapping. Remote Sensing, 10(11), Article 1673. https://doi.org/10.3390/rs10111673

Nsangou, D., Kpoumié, A., Mfonka, Z., Ngouh, A. N., Fossi, D. H., Jourdan, C., Mbele, H. Z., Mouncherou, O. F., Vandervaere, J.-P., & Ndam Ngoupayou, J. R. (2022). Urban flood susceptibility modelling using AHP and GIS approach: Case of the Mfoundi watershed at Yaoundé in the South-Cameroon plateau. Scientific African, 15, Article e01043. https://doi.org/10.1016/j.sciaf.2021.e01043

Saaty, R. W. (1987). The analytic hierarchy process—what it is and how it is used. Mathematical Modelling, 9(3–5), 161–176. https://doi.org/10.1016/0270-0255(87)90473-8

Sami, G., Hadda, D., Mahdi, K., & Abdelwahhab, F. (2020). A Multi-Criteria Analytical Hierarchy Process (AHP) to Flood Vulnerability Assessment in Batna Watershed (Algeria). Analele Universităţii Din Oradea, Seria Geografie, 30(1), 41–47. https://doi.org/10.30892/auog.301105-810

Sinha, R., Bapalu, G., Singh, L., & Rath, B. (2008). Flood risk analysis in the Kosi river basin, north Bihar using multi-parametric approach of Analytical Hierarchy Process (AHP). Journal of the Indian Society of Remote Sensing, 36, 335–349. https://doi.org/10.1007/s12524-008-0034-y

Statistics of Balikpapan Municipality. (2015). Balikpapan In Figures 2015. https://balikpapankota.bps.go.id/publication/2016/10/25/d04948397272b54a8d9cc93c/kota-balikpapan-dalam-angka-2015.html

Statistics of Balikpapan Municipality. (2010). Balikpapan In Figures 2010. https://balikpapankota.bps.go.id/publication/2016/01/06/d29f7695a456e7339c77de0e/balikpapan-dalam-angka-2010.html

Statistics of Balikpapan Municipality. (2022). Kota Balikpapan Dalam Angka 2022 [Balikpapan Municipality In Figures 2022]. https://balikpapankota.bps.go.id/publication/2022/02/25/e78628bde521d84e52633df5/kota-balikpapan-dalam-angka-2022.html

Statistics of Kalimantan Timur Municipality. (2015). Luas Wilayah Menurut Kabupaten/Kota [Total Areas of Regencies and Cities 2015] https://kaltim.bps.go.id/indicator/153/74/1/luas-wilayah-menurut-kabupaten-kota.html

Sucipto, O. (2022, March 16). Banjir Rendam Balikpapan, Terparah dalam 10 Tahun Terakhir [The Worst Flood Inundation in Balikpapan in Last Decades]. Kompas Daily News. https://www.kompas.id/baca/nusantara/2022/03/16/banjir-di-balikpapan-genangan-tersebar-di-seluruh-kecamatan

Sulistyo, T. (2003). Study on Slope Stability in Vulnerable landslide Area for Evaluation of General City Spatial Arrangement Plan in South Balikpapan. Universitas of National Development “Veteran”.

Sulistyo, T. (2012). Study on Slope Stability in Vulnerable Landslide Area for Evaluation of General City Spatial Arrangement Plan in South Balikpapan. Jurnal Ilmiah Politeknik, 4(1), 1–7. https://jurnal.poltekba.ac.id/index.php/JIP/article/view/71/841

Sulistyo, T., & Abrar, A. (2017). Characterization of Thin Alluvial Bed Aquifers in Manggar River Balikpapan East Kalimantan Indonesia. Jurnal Teknologi Terpadu, 5(1), 54–62. https://doi.org/10.32487/jtt.v5i1.212

Uddin, K., & Matin, M. A. (2021). Potential flood hazard zonation and flood shelter suitability mapping for disaster risk mitigation in Bangladesh using geospatial technology. Progress in Disaster Science, 11, Article 100185. https://doi.org/10.1016/j.pdisas.2021.100185

Yoshida, K., Pan, S., Taniguchi, J., Nishiyama, S., Kojima, T., & Islam, M. T. (2022). Airborne LiDAR-assisted deep learning methodology for riparian land cover classification using aerial photographs and its application for flood modelling. Journal of Hydroinformatics, 24(1), 179–201. https://doi.org/10.2166/HYDRO.2022.134

Zhu, H., Yu, M., Zhu, J., Lu, H., & Cao, R. (2019). Simulation study on effect of permeable pavement on reducing flood risk of urban runoff. International Journal of Transportation Science and Technology, 8(4), 373–382. https://doi.org/10.1016/j.ijtst.2018.12.001