FLOOD HAZARD MAPPING BASED ON MULTI-CRITERIA SPATIAL ANALYSIS IN THE SAMIN WATERSHED, INDONESIA

Sofyan Sholeh, Chatarina Muryani, Suryanto Suryanto

Abstract

The Samin watershed which is located in the Mount Lawu area is vulnerable to flood disasters due to human activities. This research was carried out by inventorying parameter data to create a flood disaster vulnerability map using a GIS-based multi-criteria spatial approach. The seven parameters used in flood disaster analysis are Elevation, Slope, Distance from River, Drainage density, Topographic Wetness Index (TWI), Landuse, Rainfall, Type of Soil, Geology. The weight of each parameter is determined using the Analytical Hierarchy Process (AHP) which has the driving factors for flood disasters. The flood hazard map was obtained using a weighted overlay method and grouped into five classes, namely very low, low, medium, high and very high. The results of the analysis show that 11.36% of the study area has a very low hazard, 27.10% has a low hazard, 39.57% has a medium hazard, 20.43% has a high hazard and 1.54% has a very high hazard.

Keywords

Flood; AHP; GIS; Samin watershed

Full Text:

PDF

References

Atharinafi, Z., & Wijaya, N. (2021). Land use change and its impacts on surface runoff in rural areas of the upper citarum watershed (case study: Cirasea subwatershed). Journal of Regional and City Planning, 32(1), 36–55. https://doi.org/10.5614/jpwk.2021.32.1.3

Bubeck, P., Botzen, W. J. W., & Aerts, J. C. J. H. (2012). A Review of Risk Perceptions and Other Factors that Influence Flood Mitigation Behavior. Risk Analysis, 32(9), 1481–1495. https://doi.org/10.1111/j.1539-6924.2011.01783.x

Budiarti, W. at all. (2017). View of Upaya Mitigasi Banjir di Sub DAS Samin Melalui Pengembangan Masyarakat Tangguh Bencana.pdf.

Caruso, G. D. (2017). The legacy of natural disasters: The intergenerational impact of 100 years of disasters in Latin America. Journal of Development Economics, 127(March), 209–233. https://doi.org/10.1016/j.jdeveco.2017.03.007

Entin Hidayah, Gusfan Halik, Indarto Indarto, D. W. K. (2021). Flood hazard mapping of the Welang river, Pasuruan, East Java, Indonesia. Journal of Applied Water Engineering and Research, 11(3), 333–344.

Kankanamge, N., Yigitcanlar, T., Goonetilleke, A., & Kamruzzaman, M. (2020). Determining disaster severity through social media analysis: Testing the methodology with South East Queensland Flood tweets. International Journal of Disaster Risk Reduction, 42(June 2019). https://doi.org/10.1016/j.ijdrr.2019.101360

Kazakis, N., Kougias, I., & Patsialis, T. (2015). Assessment of flood hazard areas at a regional scale using an index-based approach and Analytical Hierarchy Process: Application in Rhodope-Evros region, Greece. Science of the Total Environment, 538, 555–563. https://doi.org/10.1016/j.scitotenv.2015.08.055

Kundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P., Mechler, R., Bouwer, L. M., Arnell, N., Mach, K., Muir-Wood, R., Brakenridge, G. R., Kron, W., Benito, G., Honda, Y., Takahashi, K., & Sherstyukov, B. (2014). Le risque d’inondation et les perspectives de changement climatique mondial et régional. Hydrological Sciences Journal, 59(1), 1–28. https://doi.org/10.1080/02626667.2013.857411

Mardikaningsih, S. M., Muryani, C., & Nugraha, S. (2017). Studi Kerentanan dan Arahan Mitigasi Bencana Banjir di Kecamatan Puring Kabupaten Kebumen Tahun 2016. Jurnal Geo Eco, 3(2), 157–163.

Mostofi Zadeh, S., Burn, D. H., & O’Brien, N. (2020). Detection of trends in flood magnitude and frequency in Canada. Journal of Hydrology: Regional Studies, 28(February 2019). https://doi.org/10.1016/j.ejrh.2020.100673

Mudashiru, R. B., Sabtu, N., Abustan, I., & Balogun, W. (2021). Flood hazard mapping methods: A review. Journal of Hydrology, 603(PA), 126846. https://doi.org/10.1016/j.jhydrol.2021.126846

Perdana, Redho Surya, et. al. (2019). Flood Hazard Mapping Using GIS Spatial Analisis Functions in Baleedah, Bandung, West Java. Rabit : Jurnal Teknologi Dan Sistem Informasi Univrab, 1(1), 2019.

Razavi Termeh, S. V., Kornejady, A., Pourghasemi, H. R., & Keesstra, S. (2018). Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms. Science of the Total Environment, 615, 438–451. https://doi.org/10.1016/j.scitotenv.2017.09.262

Rosser, J. F., Leibovici, D. G., & Jackson, M. J. (2017). Rapid flood inundation mapping using social media, remote sensing and topographic data. Natural Hazards, 87(1), 103–120. https://doi.org/10.1007/s11069-017-2755-0

Saaty, T. . (1980). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234–281.

Saaty, T., & Vargas, L. (2012). Models, methods, concepts & applications of the analytic hierarchy process. … -Driven Demand and Operations Management Models, 1–20. https://doi.org/10.1007/978-1-4614-3597-6

Sajikumar, N., & Remya, R. S. (2015). Impact of land cover and land use change on runoff characteristics. Journal of Environmental Management, 161, 460–468. https://doi.org/10.1016/j.jenvman.2014.12.041

Sholeh, S., & Yusup, Y. (2023). Cross-Border Flood Management in Bengawan Solo Hulu Watershed. GeoEco, 9(2), 215. https://doi.org/10.20961/ge.v9i2.74476

Sonu, T. S., Mohammed Firoz, C., & Bhagyanathan, A. (2022). The impact of upstream land use land cover change on downstream flooding: A case of Kuttanad and Meenachil River Basin, Kerala, India. Urban Climate, 41(April 2021), 101089. https://doi.org/10.1016/j.uclim.2022.101089

Tehrany, M. S., Pradhan, B., & Jebur, M. N. (2014). Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS. Journal of Hydrology, 512, 332–343. https://doi.org/10.1016/j.jhydrol.2014.03.008

DOI: https://doi.org/10.20961/ge.v10i1.82973

Refbacks

  • There are currently no refbacks.