Kerawanan Bencana Banjir Di DAS Kecamatan Suli Kabupaten Luwu

Esse Syam; Rudi Latief; Baso Jaya

doi:10.35965/ursj.v7i2.6058

Authors

Esse Syam Dinas Pekerjaan Umum dan Penataan Ruang Kabupaten Luwu
Rudi Latief Program Studi Perencanaan Wilayah dan Kota, Program Pascasarjana, Universitas Bosowa
Baso Jaya Program Studi Perencanaan Wilayah dan Kota, Program Pascasarjana, Universitas Bosowa

DOI:

https://doi.org/10.35965/ursj.v7i2.6058

Keywords:

Banjir, Kerawanan Banjir, DAS Kecamatan Suli, Scoring, Overlay

Abstract

Kecamatan Suli merupakan salah satu kawasan yang menjadi langganan banjir di Kabupaten Luwu terutama kawasan yang berada di daerah aliran sungai (DAS). Bencana banjir tersebut menimbulkan banyak kerugian. Penelitian ini ditujukan untuk mengkaji serta menganalisis penyebab kerawanan bencana banjir, wilayah kerawanan bencana banjir di Kecamatan Suli Kabupaten Luwu menggunakan parameter-parametersignifikan yang mempengaruhi terjadinya banjir serta merumuskan strategi penanganan kerawanan banjir. Penelitian ini menggunakan pendekatan metode kuantitatif untuk data yang dihasilkan dari analisis Weighted Overlay serta metode kualitatif dengan analisis teoritical deskriptif. Hasil penelitian menunjukkan terdapat 5 faktor penyebab bencana banjir di Kecamatan Suli Kabupaten Luwu serta memetakan tingkat kerawanan banjir dengan memperhatikan 6 aspek lalu menerapkan metode scoring memberikan bobot parameter yang berpengaruh signifikan terhadap penentuan wilayah sebaran kerawanan bencana banjir di DAS Kecamatan Suli Kabupaten Luwu dengan metode overlay terhadap parameter yang berpengaruh banjir secara signifikan. Selanjutnya hasil pemetaan kerawanan banjir di DAS Kecamatan Suli Kabupaten Luwu diperoleh kesimpulan bahwa tingkat sangat rawan banjir menyebar di bagian hilir DAS Kecamatan Suli sedangkan daerah yang tidak rawan berada dibagian hulu atau yang memiliki topografi yangb berada di dataran tinggi.

Suli District is one of the areas that is prone to flooding in Luwu Regency, especially areas located in river basins (DAS). The flood disaster caused many losses. This study aims to examine and analyze the causes of flood disaster vulnerability, flood disaster prone areas in Suli District, Luwu Regency using significant parameters that affect flooding and formulating flood vulnerability management strategies. This study uses a quantitative method approach for data generated from the Weighted Overlay analysis and a qualitative method with descriptive theoretical analysis. The results of the study showed that there were 5 factors causing flood disasters in Suli District, Luwu Regency and mapping the level of flood vulnerability by considering 6 aspects and then applying the scoring method to provide parameter weights that significantly influence the determination of the distribution area of flood disaster vulnerability in the Suli District Watershed, Luwu Regency with the overlay method on parameters that significantly influence flooding. Furthermore, the results of flood vulnerability mapping in the Suli District Watershed, Luwu Regency concluded that the very flood-prone level was spread in the downstream part of the Suli District Watershed, while areas that were not prone were in the upstream part or those with topography that was in the highlands.

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References

Ahmad, D., & Afzal, M. (2022). Flood hazards vulnerability and risk of food security in Bait community flood-prone areas of Punjab Pakistan: In SDGs achievement threat. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-022-21683-z

Arabameri, A., Seyed Danesh, A., Santosh, M., Cerda, A., Pal, S. C., Ghorbanzadeh, O., Roy, P., & Chowdhuri, I. (2022). Flood susceptibility mapping using meta-heuristic algorithms. Geomatics, Natural Hazards and Risk. https://doi.org/10.1080/19475705.2022.2060138

Bello, A.-A. D., & Haniffah, M. R. M. (2021). Modelling the effects of urbanization on nutrients pollution for prospective management of a tropical watershed: A case study of Skudai River watershed. Ecological Modelling. https://doi.org/10.1016/J.ECOLMODEL.2021.109721

Bibi, T. S., & Kebebew, A. S. (2023). Assessment of the drainage systems performance in response to future scenarios and flood mitigation measures using stormwater management model. City and Environment Interactions. https://doi.org/10.1016/j.cacint.2023.100111

Chan, S. W., Abid, S. K., Sulaiman, N., Nazir, U., & Azam, K. (2022). A systematic review of the flood vulnerability using geographic information system. Heliyon. https://doi.org/10.1016/j.heliyon.2022.e09075

Cruz-Bello, G. M., & Alfie-Cohen, M. (2022). Capturing flood community perceptions for social vulnerability reduction and risk management planning. Environmental Science & Policy. https://doi.org/10.1016/j.envsci.2022.02.029

Handayani, D. A., Kurniadi, A., & Bahar, F. (2023). Upstream Brantas Watershed management strategies for flood mitigation (a review: Batu District). IOP Conference Series. https://doi.org/10.1088/1755-1315/1173/1/012053

Horton, A., Nygren, A., Diaz-Perera, M. A., & Kummu, M. (2021). Flood severity along the Usumacinta River, Mexico: Identifying the anthropogenic signature of tropical forest conversio

Hosseini, F. S., Sigaroodi, S. K., Salajegheh, A., Moghaddamnia, A., & Choubin, B. (2021). Towards a flood vulnerability assessment of watershed using integration of decision-making trial and evaluation laboratory, analytical network process, and fuzzy theories. Environmental Science and Pollution Research.

Ismana, D., Baehera, S., Fitrianto, A., Sartono, B., & Oktarina, S. (2022). Penggerombolan Desa di Jawa Barat Berdasarkan Daerah Rawan Bencana.Jurnal Statistika Dan Aplikasinya.

Lin, L., Tang, C., Liang, Q., Wu, Z. N., Wang, X., & Zhao, S. (2022). Rapid urban flood risk mapping for data-scarce environments using social sensing and region-stable deep neural network. Journal of Hydrology.

Nauditt, A., Stahl, K., Rodríguez, E., Birkel, C., Formiga-Johnsson, R. M., Marko, K., Ribbe, L., Baez-Villanueva, O. M., Thurner, J., & Hann, H. (2022). Evaluating tropical drought risk by combining open access gridded vulnerability and hazard data products. Science of The Total Environment.

Nofal, O. M., & van de Lindt, J. W. (2021). High-resolution flood risk approach to quantify the impact of policy change on flood losses at community-level. International Journal of Disaster Risk Reduction.

Owokotomo, A. I., Ajayi, O. O., Alabi, O. O., & Chukwuka, A. V. (2020). Watershed land use, surface water vulnerability and public health risks of two urban rivers, Ado-Ekiti, South-West Nigeria.

Park, J., Park, C., An, J., & Yoon, H. (2020). An Assessment Method for Evaluating Vulnerability to Regional Disasters and Its Application to Disaster due to Heavy Rain. https://doi.org/10.9798/KOSHAM.2020.20.1.151

Pradhan, B., Lee, S., Dikshit, A., & Kim, H. (2023). Spatial flood susceptibility mapping using an explainable artificial intelligence (XAI) model. Geoscience Frontiers. https://doi.org/10.1016/j.gsf.2023.101625

Richard, J. U., & Okeke, F. I. (2023). Climate change and urban flooding in South-South Nigeria from 1990 - 2020.World Journal of Advanced Engineering Technology and Sciences. https://doi.org/10.30574/wjaets.2023.8.1.0013

Sahraei, R., Kanani-Sadat, Y., Safari, A., & Homayouni, S. (2023). Flood susceptibility modelling using geospatial-based multi-criteria decision making in large scale areas. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. https://doi.org/10.5194/isprs-annals-x-4-w1-2022-677-2023

Sharafutdinov, V. F. (2022). Hydrological challenges in urban areas.

Shmilovitz, Y., Morin, E., Rinat, Y., Haviv, I., Carmi, G., Mushkin, A., & Enzel, Y. (2020). Linking frequency of rainstorms, runoff generation and sediment transport across hyperarid talus-pediment slopes. Earth Surface Processes and Landforms.

Sholanke, A. B., Chilaka, D. A., Oti, M. A., Nelson, S. A., Nnatuanya, M. C., & Udezi, B. E. (2021). Resilient Design Strategy: Engaging Amphibious Structures to Combat Flood in the Development of an Internally Displaced Persons Settlement Scheme in Nigeria.

Singh, A. K., Sharma, P., & Prasath Kumar, V. R. (2022). Design and Analysis of Flood Resisting Residential Building: A Case Study in Malappuram-KERALA.Magallat Al-Abhat al-Handasiyyat.

Utama, F., Setiawan, Y., Vatresia, A., & Sari, J. P. (2021). Flood Vulnerability Analysis using Weighted Overlay. https://doi.org/10.25299/ITJRD.2022.6193

Winter, A., & Karvonen, A. (2022). Climate governance at the fringes: Peri-urban flooding drivers and responses. Land Use Policy.

Zhang, W., Liu, Y., Tang, W., Wang, W., & Liu, Z. (2022). Assessment of the effects of natural and anthropogenic drivers on extreme flood events in coastal regions. Stochastic Environmental Research and Risk Assessment.