URBAN FLOOD MITIGATION STUDY BASED ON 3D SPATIAL MODELING FOR DETERMINING INFRASTRUCTURE RESILIENCE PRIORITIES IN WARA DISTRICT, PALOPO CITY

Authors

Kastono , Citra Wahyu Annisa R , Alimuddin R

Published:

2026-09-07

Downloads

Abstract

This study examines urban flood mitigation using three-dimensional (3D) spatial modeling to determine infrastructure resilience priorities in Wara District, Palopo City. The analysis integrates DEMNAS, field topographic survey data, land use, road networks, administrative boundaries, building distribution, and critical infrastructure into an integrated 3D geospatial database. Flood simulations were conducted for 25-year and 50-year return periods with a one-hour duration. The 25-year scenario used a river discharge of 377.52 m³/s, while the 50-year scenario used 566.28 m³/s. The modeling results identified 775 affected buildings, equivalent to 27.2% of 2,846 analyzed buildings, under the 25-year scenario; this increased to 845 buildings or 29.7% under the 50-year scenario. Risk patterns concentrate along the Wara River corridor and in relatively low-lying areas with high building density. Based on the integration of hazard, exposure, and vulnerability, Amasangan and Danmobilko were classified as high-priority areas, Tompotikka as medium-to-high priority, and Lagaligo as medium priority. The 3D modeling provides an intuitive visualization of the relationships among topography, river corridors, inundation, and buildings, supporting prioritization of drainage improvement, river corridor protection, infrastructure elevation, and flood preparedness measures.

Keywords:

Urban Flood 3D Spatial Modeling Mitigation Infrastructure Resilience Wara District Palopo City

References

[1] Lu Z, Yan D, Jiang H, Xue H, Xu ZD. Cascading failures in urban infrastructure systems: A comprehensive review of disaster chain mechanisms. Journal of Infrastructure Intelligence and Resilience. 2025;4(3):100157. doi:10.1016/j.iintel .2025.100157.

[2] Brunner LG, Peer RAM, Zorn C, Paulik R, Logan TM. Understanding cascading risks through real-world interdependent urban infrastructure. Reliability Engineering & System Safety. 2024;241:109653 . doi:10.1016/j.ress .2023.109653.

[3] Bhattarai Y, Chaudhary V, Walker C, Talchabhadel R, Sharma S, et al. Ensemble learning for enhancing critical infrastructure resilience to urban flooding. Scientific Reports. 2025;15:36901 . doi:10.1038/s41598-025-20970-2.

[4] Yang C, Jin Z, Yin H. Assessment and evolution analysis of urban infrastructure resilience under flood disaster scenarios based on the PSR model and extension catastrophe progression. Scientific Reports. 2025;15:36863 . doi:10.1038/s41598-025-20939-1.

[5] Mitropoulos V, Maslen E, Chen AS, Islam T, Dimitriadis P, et al. Urban transportation disruption during pluvial floods: effects on accessibility and routing. International Journal of Disaster Risk Reduction. 2025:105475. doi:10.1016/j.ijdrr .2025.105475.

[6] Indrajaya I, Rusida R, Idrus A. Strategy for controlling the impact of Songka River flooding on residential areas in Takkalalla Village, Wara Selatan District, Palopo City. Ecosystem Scientific Journal. 2023;23(3):637-645. doi:10.35965/ eco.v 23i3.3794.

[7] Padli MI, Rasyid AR, Osman WW. Flood hazard mapping in the Latuppa watershed, South Sulawesi. Construction Technologies and Architecture. 2025;16:21 -30. doi:10.4028/p-Zi6nsA.

[8] Najib NN, et al. The effectiveness of public green open space capabilities in reducing flooding. Indonesian Journal of Applied Research (IJAR). 2024;5(2). doi:10.30997/ ijar.v 5i2.424.

[9] Padli MI, Rasyid AR, Osman WW. Flood hazard mapping in the Latuppa watershed, South Sulawesi. Construction Technologies and Architecture. 2025;16:21 -30. doi:10.4028/p-Zi6nsA.

[10] Lagaritong JP, Takwim, Muthmainnah. Strategy for controlling the impact of Songka River flooding in realizing infrastructure resilience in Palopo City. Ecosystem Scientific Journal. 2023;23(3). doi:10.35965/ eco.v 23i3.3794.

[11] Ge C, Qin S. Urban flooding digital twin system framework. Systems Science & Control Engineering. 2025;13(1). doi:10.1080/21642583.2025.2460432.

[12] Hlal M, Munyaka J-CB, Chenal J, et al. Digital twin technology for urban flood risk management: A systematic review of remote sensing applications and early warning systems. Remote Sensing. 2025;17(17):3104. doi:10.3390/rs17173104.

[13] Li X, et al. 2D and 3D computational modeling of surface flooding in urbanized floodplains: Modeling performance for various building layouts. Water Resources Research. 2024. doi:10.1029/2023WR035149.

[14] Andriessen L, Agugiaro G, Borgers A, Pauwels P. Semantic 3D city models as support for urban flood resilience: Experiences from Rotterdam. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2024;X -4/W4-2024:5-12. doi:10.5194/isprs-annals-X-4-W4-2024-5-2024.

[15] Luo S, et al. A CityGML ADE for flood simulations. Geo-spatial Information Science. 2025. doi:10.1080/10095020.2025.2547952.

[16] Laefer DF, O'Keeffe E, Chandna K, et al. Low-cost, LiDAR-based, dynamic, flood risk communication viewer. Remote Sensing. 2025;17(4):592. doi:10.3390/rs17040592.

[17] Zhu J, Laefer DF, Lejano RP, et al. From 2D to 3D: Flood risk communication in a flood-prone neighborhood via dynamic, isometric street views. Progress in Disaster Science. 2025;26:100419 . doi:10.1016/j.pdisas .2025.100419.

[18] Chen J, Shang F, Fu H, Yu Y, Wang H, Qin H, Ping Y. Inundation modeling and bottleneck identification of pipe-river systems in a highly urbanized area. Sustainability. 2025;17(15):7065. doi:10.3390/su17157065.

[19] Wang Y, Yue Q, Lu X, Gu D, Xu Z, Tian Y, Zhang S. Digital twin approach for enhancing urban resilience: A cycle between virtual space and the real world. Resources, Conservation & Recycling: Advances. 2024. doi:10.1016/j.rcns .2024.06.002.

[20] Ge C, Qin S. Urban flooding digital twin system framework. Systems Science & Control Engineering. 2025;13(1). doi:10.1080/21642583.2025.2460432.

[21] Kastono, et al. Mitigation and public coordination for Flood Disaster Risk Reduction (FDRR) in the implementation of North Luwu sustainable development. IOP Conference Series: Earth and Environmental Science. 2022;1109(1). doi:10.1088/1755-1315/1109/1/012018.

[22] Kastono, et al. Adaptation and mitigation model for flood disaster resilience in West Malangke District, North Luwu Regency, Indonesia. International Journal of Safety and Security Engineering. 2024;14(5):1627-1633. doi:10.18280/ijsse.140529.

[23] Kiparisov P, Lagutov V, Pflug G. Quantification of loss of access to critical services during floods in Greater Jakarta: Integrating social, geospatial, and network perspectives. Remote Sensing. 2023;15:5250 . doi:10.3390/rs15215250.

[24] Therias A, Rafiee A. City digital twins for urban resilience. International Journal of Digital Earth. 2023;16(2):4164-4190. doi:10.1080/17538947.2023.2264827.

[25] Andriessen L, Agugiaro G, Borgers A, Pauwels P. Semantic 3D city models as support for urban flood resilience: Experiences from Rotterdam. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2024;X -4/W4-2024:5-12. doi:10.5194/isprs-annals-X-4-W4-2024-5-2024.

[26] Rezvani SMHS, Silva MJF, de Almeida NM. Urban resilience index for critical infrastructure: A scenario-based approach to disaster risk reduction in road networks. Sustainability. 2024;16(10):4143. doi:10.3390/su16104143.

[27] Hlal M, Munyaka J-CB, Chenal J, Azmi R, Diop EB, Bounabi M, Ebnou Abdem SA, Almouctar MAS, Adraoui M. Digital twin technology for urban flood risk management: A systematic review of remote sensing applications and early warning systems. Remote Sensing. 2025;17(17):3104. doi:10.3390/rs17173104.

[28] Tsikas P, Chassiakos A, Papadimitropoulos V. Watershed-BIM integration for urban flood resilience: A framework for simulation, assessment, and planning. Sustainability. 2025;17(17):7687. doi:10.3390/su17177687.

[29] Report on 3-Dimensional Flood Risk Modeling Based on Geospatial Simulation of the Wara River, Wara District, Palopo City, internal technical document, research modeling data.

[30] DEMNAS data documents, topographic surveys, and spatial research databases for Wara District, Palopo City, data

study.

[31] UNDRR, (2017), Terminology on Disaster Risk Reduction, United Nations Office for Disaster Risk Reduction, Geneva.

[32] Ministry of PUPR, (2017), Urban Drainage System Planning Guidelines, Directorate General of Human Settlements, Jakarta.

[33] Geospatial Information Agency, (2020), National DEM (DEMNAS): Indonesian National Elevation Data, Geospatial Information Agency, Cibinong.

[34] ESRI, (2024), ArcGIS Pro Documentation: 3D Analyst and Spatial Analyst, Environmental Systems Research Institute, Redlands.

[35] Chow, VT, Maidment, DR and Mays, LW, (1988), Applied Hydrology, McGraw-Hill, New York.

[36] BNPB, (2012), General Guidelines for Disaster Risk Assessment, National Disaster Management Agency, Jakarta.

[37] Kodoatie, RJ and Sjarief, R., (2010), Water Spatial Planning, Andi, Yogyakarta.

[38] Suripin, (2004), Sustainable Urban Drainage Systems, Andi, Yogyakarta.

Author Biographies

Kastono, Politeknik Dewantara, Palopo, Sulawesi Selatan

Author Origin : Indonesia

Citra Wahyu Annisa R, Politeknik Dewantara, Palopo, Sulawesi Selatan

Author Origin : Indonesia

Alimuddin R, Universitas Andi Djemma, Palopo, Sulawesi Selatan

Author Origin : Indonesia

Downloads

Download data is not yet available.

How to Cite

Kastono, Citra Wahyu Annisa R, & Alimuddin R. (2026). URBAN FLOOD MITIGATION STUDY BASED ON 3D SPATIAL MODELING FOR DETERMINING INFRASTRUCTURE RESILIENCE PRIORITIES IN WARA DISTRICT, PALOPO CITY. Multidiciplinary Output Research For Actual and International Issue (MORFAI), 6(6), 8293–8300. https://doi.org/10.5281/zenodo.22637933

Similar Articles

<< < 2 3 4 5 6 7 8 9 10 11 > >> 

You may also start an advanced similarity search for this article.