For Libraries For Publication Open Access Downloads About Us Contact Us
Paper Titles
Near Real Time Ionosphere Opening Channel Information for HF near Vertical Incidence Skywave Communication over Kupang Nusa Tenggara Timur Indonesia
p.393
Multi-Object Trajectory Prediction with Crossing Detection Using Interacting Multiple Model Kalman Filter
p.403
Simulation and Performance Analysis of Manet in Post-Disaster Areas Utilizing Proactive Routing Protocol (Case Study: Palu Earthquake 2018)
p.413
Moving Zone Clustering for Device-to-Device Users Based on Binary Message Passing
p.425
Flood Risk Mapping in Katingan Regency Using Composite Mapping Analysis (CMA) Method
p.437
Study on the Quality of Land Data Utilised in Land Policy Making around the International Borders in Sebatik Island
p.452
Built-Up Land Change and Spatial Population Distribution in Madiun City
p.459
Analysis of VTEC and Scintillation Parameters during Very Strong Geomagnetic Storm Events at Pontianak
p.471
Design of Shipping Channels, Berthing Areas and Turning Basin by Utilizing Bathymetry and Side Scan Sonar Data at the Branta Harbor, East Java
p.481

Flood Risk Mapping in Katingan Regency Using Composite Mapping Analysis (CMA) Method

Article Preview

Abstract:

Flooding is the most common disaster in Katingan Regency. However, global warming worsens the flood risk, and making a flood risk map is the first step in generating a disaster management policy in Katingan Regency. This research uses spatial data to create flood risk modelling for the Katingan Regency. The Composite Mapping Analysis (CMA) method was applied to map the flood risk in Katingan Regency using four parameters: slope, soil type, precipitation and land-use type. The flood risk map shows that there are five classes of flood risk in Katingan Regency that are low risk (580.319,25 Ha or 29,12%), relatively low risk (760.974,50 Ha or 38,18%), medium risk (308.233,16 Ha or 15,47%), relatively high risk (293.040,65 Ha or 14,70%) and high risk (50.439,87 Ha or 2,53%). Medium to high risk of flooding in Katingan Regency is primarily distributed near the river with developed areas since this land use group is the most vulnerable to loss from flooding. Moreover, the Katingan Regency area, formed from an alluvial process characterized by a flat slope and clay-textured soil, has a higher chance of puddles.

You might also be interested in these eBooks
The 10th International Conference on Science and Technology (ICST) View Preview

Info:

Periodical:

Engineering Headway (Volume 27)

Pages:

437-451

DOI:

https://doi.org/10.4028/p-1CBoNp

Citation:

Cite this paper

Online since:

October 2025

Authors:

Igor Aviezena Eris*, Hikmah Fajar Assidiq, Didit Wahyudi, Loetvy Wahyuningtiyas

Keywords:

Composite Mapping Analysis, Flood Risk Mapping, Flood Risk Parameters, GIS Mapping, Spatial Modelling

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2025 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

References

[1] Casey, Michael. 2015. Global Cost of Flooding to Increase Tenfold by 2030 https://www.cbsnews.com/news/global-cost-of-flooding-to-increase-tenfold-by-2030/

Google Scholar

[2] Gofur, Abdul. 2021. Kerugian Akibat Banjir di Katingan Ditaksir Lebih dari Rp 600 Miliar https://www.borneonews.co.id/berita/236291-kerugian-akibat-banjir-di-katingan-ditaksir-lebih-rp-600-miliar

DOI: 10.31227/osf.io/qa5gh

Google Scholar

[3] Kron, W. Keynote lecture: Flood risk= hazard× exposure× vulnerability. Flood Def. 2002, p.82–97. Tersedia online di https://www.iahr.org/library/infor?pid=16216 (diakses 19 Oktober 2024)

Google Scholar

[4] Amen, Aumed Rahman M., Mustafa, Andam., Kareem, Dalshad Ahmed., Hameed, Hasan Mohammed., Mirza, Ayub Anwar., Szydlowski, Michal., & Saleem, Bala Kawa M. 2023. Saleem. 2023. "Mapping of Flood-Prone Areas Utilizing GIS Techniques and Remote Sensing: A Case Study of Duhok, Kurdistan Region of Iraq" Remote Sensing 15, no. 4: 1102

DOI: 10.3390/rs15041102

Google Scholar

[5] Legislation of Indonesia Number 24/2007 about Disaster Mitigation

Google Scholar

[6] Ozkan, S. P., & Tarhan, C. (2016). Detection of flood hazard in urban areas using GIS: Izmir case. Procedia Technology,22, 373–381.

DOI: 10.1016/j.protcy.2016.01.026

Google Scholar

[7] Abdo, H. G., Zeng, · Taorui, Alshayeb, M. J., Prasad, P., Fatahalla, M., Ahmed, M., Jasem, ·, Albanai, A., Maged, ·, Alharbi, M., & Mallick, · Javed. (n.d.). 2024. Multi-criteria analysis and geospatial applications-based mapping flood vulnerable areas: a case study from the eastern Mediterranean. Natural Hazards

DOI: 10.1007/s11069-024-06864-y

Google Scholar

[8] Sugumaran, Ramanathan & John Degroote. 2011. Spatial Decision Support System: Principles and Practices. Boca Raton: CRC Press

Google Scholar

[9] Dyah Sukowati, K. A., & Kusratmoko, E. 2019. Analysis of the distribution of flood area in Karawang Regency using SAR Sentinel 1A image. IOP Conference Series: Earth and Environmental Science, 311(1), 012085

DOI: 10.1088/1755-1315/311/1/012085

Google Scholar

[10] Faisol, Arif., Bachri, Samsul., & Mashudi. 2024. Komparasi Data Digital Elevation Model (Dem) Resolusi Menengah Dalam Mengestimasi Ketinggian Lahan Di Kabupaten Manokwari Provinsi Papua Barat. Majalah lmiah lobe, 26(1), 11–20. https://jurnal.big.go.id/GL/article/view/137

DOI: 10.24895/gl.2024.26.1.11-20

Google Scholar

[11] Fakhruddin, Akmal Wahyu., & Harindataka. 2019. Analisis Akurasi Vertikal Model Elevasi Digital Nasional [Bachelor Thesis, Universitas Gadjah Mada]. Universitas Gadjah Mada Electronic Theses & Dissertations

DOI: 10.20885/jattec.vol5.iss1.art9

Google Scholar

[12] Minister Regulation of Ministry of Environment and Forestry number 10/2022 about Forest and Land Rehabilitation In River Water Area and Annual Plan For Forest and Land Rehabilitation

Google Scholar

[13] Sahu, A., Bose, T., & Samal, D. R. 2021. Urban Flood Risk Assessment and Development of Urban Flood Resilient Spatial Plan for Bhubaneswar. Environment and Urbanization ASIA, 12(2), 269-291. https://doi-org.ezproxy.ugm.ac.id/

DOI: 10.1177/09754253211042489

Google Scholar

[14] Razzaghi Asl, S., & Pearsall, H. 2023. How do spatial factors of green spaces contribute to flood regulation in urban areas? A systematic mapping approach. Progress in Physical Geography: Earth and Environment, 47(5), 702-720. https://doi-org.ezproxy.ugm.ac.id/

DOI: 10.1177/03091333231156511

Google Scholar

[15] Hagos, Y. G., Andualem, T. G., Yibeltal, M., & Mengie, M. A. (2022). Flood hazard assessment and mapping using GIS integrated with multi-criteria decision analysis in upper Awash River basin, Ethiopia. Applied Water Science, 12(7)

DOI: 10.1007/s13201-022-01674-8

Google Scholar

[16] Dewan, A., Kankam-Yeboah, K., & Nishigaki, M. 2006. Using Synthetic Aperture Radar (SAR) Data for Mapping River Water Flooding in an Urban Landscape: A Case Study of Greater Dhaka, Bangladesh. Journal of Japan Society of Hydrology & Water Resources, 19, 44–54

DOI: 10.3178/jjshwr.19.44

Google Scholar

[17] Surampudi, S., & Yarrakula, K. 2020. Mapping and assessing spatial extent of floods from multitemporal synthetic aperture radar images: a case study on Brahmaputra River in Assam State, India. Environmental Science and Pollution Research, 27(2), 1521–1532

DOI: 10.1007/s11356-019-06849-6

Google Scholar

[18] Uddin Kabir and Matin, M. A., & T. R. B. 2021. Rapid Flood Mapping Using Multi-temporal SAR Images: An Example from Bangladesh. In R. B. and M. M. A. Bajracharya Birendra and Thapa (Ed.), Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region: A Decade of Experience from SERVIR (p.201–210). Springer International Publishing

DOI: 10.1007/978-3-030-73569-2_10

Google Scholar

[19] Muttaqin, K., Maulita, M., Fitria, L., Ihsan, A., & Mulya, R. (2023). Mapping Flood-Prone Areas Based Geographic Information System Using Composite Mapping Analysis. International Journal of Geoinformatics, 19(12), 93–105

DOI: 10.52939/ijg.v19i12.2983

Google Scholar

© 2025 Trans Tech Publications Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For open access content, terms of the Creative Commons licensing CC-BY are applied.
Scientific.Net is a registered trademark of Trans Tech Publications Ltd.