Risk-Based Zoning for Urban Flood Mitigation Using HEC-HMS–HEC-RAS 2D Areas
DOI:
https://doi.org/10.26877/asset.v8i1.2566Keywords:
urban pluvial floodin, HEC-RAS 2D, HEC-HMS, rain-on-grid, risk-based zoning, Central Java, model validationAbstract
This study aims to assess the potential for urban inundation and formulate flood mitigation strategies based on spatial analysis. A 2D modelling approach using HEC-HMS and HEC-RAS was applied to simulate the extent and depth of inundation in the urban area of Karanganyar, Indonesia. The models were validated with field observations using RMSE. Model validation confirmed the agreement between simulated and observed data. Validation was quantified using RMSE = 0.42 m across 15 checkpoints, with an average MAE of 0.31 m, and a coefficient of determination (R²) of 0.87. The 2D mesh resolution was set at 10 m, balancing computational efficiency with spatial accuracy. The maximum inundated area reached 3.8 million m² (±0.2 million m²), and the 95th percentile inundation depth was 4.7 m, concentrated in residential and agricultural zones. The results were used to delineate risk zones for prioritised flood mitigation planning. The simulation identified risk zones for prioritised flood mitigation planning, revealing inundated areas of up to 3.8 million m² with maximum depths around 4.7 m (±0.3 m), primarily affecting residential areas, agriculture, and public areas. Risk-based zoning was used to prioritise mitigation strategies, including improved drainage and the construction of infiltration ponds. The risk-based zoning approach demonstrated that implementing infiltration ponds and improved drainage in Priority Zone A could reduce flood exposure by approximately 28% under a simulated 20-year return period storm. These findings provide a measurable basis for adaptive flood mitigation strategies in urban areas.
References
[1]. G. M. Membele, M. Naidu, and O. Mutanga, "Examining flood vulnerability mapping approaches in developing countries: A scoping review," International Journal of Disaster Risk Reduction, vol. 69, p. 102766, Dec. 2021, doi: 10.1016/j.ijdrr.2021.102766.
[2]. Y. Xing, X. Zhang, J. Chen, and L. Wang, "Investigation of the importance of different factors of flood inundation modeling applied in urbanized area with variance-based global sensitivity analysis," Science of the Total Environment, vol. 772, p. 145327, 2021, doi: 10.1016/j.scitotenv.2021.145327.
[3]. C. Martínez, Z. Vojinovic, and A. Sanchez, "Multi-objective model-based assessment of green-grey infrastructures for urban flood mitigation," Hydrology, vol. 8, no. 3, 2021.
[4]. Q. Zhou, T. Teng, X. Liu, et al., "A deep-learning-technique-based data-driven model for accurate and rapid flood predictions in temporal and spatial dimensions," Hydrology and Earth System Sciences, vol. 27, no. 5, pp. 1251–1268, 2023, doi:10.5194/hess-27-1251-2023.
[5]. A. K. B. de Oliveira et al., "Evaluating the role of urban drainage flaws in triggering cascading effects on critical infrastructure, affecting urban resilience," Infrastructures, vol. 7, no. 11, 2022.
[6]. J. Hou et al., "Rapid forecasting of urban flood inundation using multiple machine learning models," Natural Hazards, vol. 108, pp. 2335–2356, 2021. [Online]. Available: https://consensus.app/papers/forecasting-flood-inundation-using-machine-learning-hou/93489d80e0e95e218c58ebda978b2e0e/
[7]. M. Al Amin, J. Sujono, and R. Triatmadja, "Urban flood mitigation by implementing LIDs (case study: Bendung Watershed in Palembang City)," Journal of Water Management Modeling, 2024. [Online]. Available: https://consensus.app/papers/urban-flood-mitigation-by-implementing-lids-case-study-amin-sujono/444660c60ee553b0a1e8fa0dfcbb5c0e/
[8]. L. Sandoval, A. Dell’Oca, and M. Riva, "Operational sensitivity analysis of flooding volume in urban areas," Sustainable Cities and Society, 2024. [Online]. Available: https://consensus.app/papers/operational-sensitivity-analysis-of-flooding-volume-in-sandoval-dell’oca/67dd5741ad3b5dbc91f4783aefd60f71/
[9]. H. Chang et al., "Assessment of urban flood vulnerability using the social-ecological-technological systems framework in six US cities," Sustainable Cities and Society, vol. 68, p. 102786, Oct. 2020, doi: 10.1016/j.scs.2021.102786.
[10]. J. N. Acharya, W. Koedsin, and K. Techato, "Strategies for disaster management and the role of effective governance in Nepal," Journal of Water and Land Development, no. 64, pp. 130–135, 2025.
[11]. A. Rachmawardani, "Hybrid machine learning for flood prediction: Comparing CHIRPS satellite and ground station data," Journal of Water and Land Development, no. 64, pp. 87–99, 2025.
[12]. W. Qi et al., "A review on applications of urban flood models in flood mitigation strategies," Natural Hazards, vol. 108, pp. 31–62, 2021. [Online]. Available: https://consensus.app/papers/a-review-on-applications-of-urban-flood-models-in-flood-qi-ma/788f799bd65652daa22c6dfa98503193/
[13]. Y. Li, "Urban inundation mapping by coupling 1D-2D models and model comparison," International Journal of Applied Earth Observation and Geoinformation, vol. 130, p. 103869, 2024. [Online]. Available: https://consensus.app/papers/urban-inundation-mapping-by-coupling-1d-2d-models-and-model-li-osei/e92a9f218c4d50a5bf2d7bd74dfc09b1/
[14]. H. Jin, "An intelligent framework for spatiotemporal simulation of flooding considering urban underlying surface characteristics," International Journal of Applied Earth Observation and Geoinformation, vol. 130, p. 103908, Mar. 2024, doi: 10.1016/j.jag.2024.103908.
[15]. C. A. Ku, "Evaluating the effects of land-use strategies on future flood risk reduction in urban areas," Cities, vol. 150, p. 104989, Mar. 2024, doi: 10.1016/j.cities.2024.104989.
[16]. T. Pacetti., "Planning nature based solutions against urban pluvial flooding in heritage cities: A spatial multi-criteria approach for the city of Florence (Italy)," Journal of Hydrology: Regional Studies, vol. 41, p. 101081, Apr. 2022, doi: 10.1016/j.ejrh.2022.101081.
[17]. J. Wang, "Hydrological model adaptability to rainfall inputs of varied quality," Water Resources Research, vol. 59, 2023. [Online]. Available: https://consensus.app/papers/hydrological-model-adaptability-to-rainfall-inputs-of-wang-zhuo/7425b71d705f5d3f919e7b99a48fc46c/
[18]. L. Zhao, "Multi-method combined analysis of urban flood risks and its influencing factors under low impact development," Journal of Hydrology, 2024. [Online]. Available: https://consensus.app/papers/multimethod-combined-analysis-of-urban-flood-risks-and-its-zhao-li/61bfc93ab4815b61958acfb1474c2e70/
[19]. J. Schubert, A. Luke, A. Aghakouchak, and B. Sanders, "A framework for mechanistic flood inundation forecasting at the metropolitan scale," Water Resources Research, vol. 58, 2022. [Online]. Available: https://consensus.app/papers/a-framework-for-mechanistic-flood-inundation-forecasting-schubert-luke/eaa54c61985b5701a9f4f07a4a292889/
[20]. M. Wang, Y. Lu, and X. Ge, "Effect of sponge city construction on urban waterlogging reduction in semi-humid areas of China," Journal of Water and Climate Change, vol. 13, no. 10, pp. 3532–3546, 2022.
[21]. G. Adane, "Integrating satellite rainfall estimates with hydrological water balance model: Rainfall-runoff modelling in Awash River Basin, Ethiopia," Water, 2021. [Online]. Available: https://consensus.app/papers/integrating-satellite-rainfall-estimates-with-adane-hirpa/b0aed993e0a152f4832623652ef35b73/
[22]. X. Li., "High efficiency integrated urban flood inundation simulation based on the urban hydrologic unit," Journal of Hydrology, 2024. [Online]. Available: https://consensus.app/papers/high-efficiency-integrated-urban-flood-inundation-li-li/248722adec8456c9a574d5bcfe1962f0/
[23]. Y. Liao, Z. Wang, X. Chen, and C. Lai, "Fast simulation and prediction of urban pluvial floods using a deep convolutional neural network model," Journal of Hydrology, 2023. [Online]. Available: https://consensus.app/papers/fast-simulation-and-prediction-of-urban-pluvial-floods-liao-wang/cbfb2e9707745b02ba12e34f8e6582c0/
[24]. L. Wang, R. Li, and X. Dong, "Integrated modeling of urban mobility, flood inundation, and sewer hydrodynamics processes to support resilience assessment of urban drainage systems," Water Science and Technology, vol. 90, no. 1, pp. 124–141, 2024.
[25]. M. Eini, H. S. Kaboli, M. Rashidian, and H. Hedayat, "Hazard and vulnerability in urban flood risk mapping: Machine learning techniques and considering the role of urban districts," International Journal of Disaster Risk Reduction, vol. 50, p. 101687, May 2020, doi: 10.1016/j.ijdrr.2020.101687.
[26]. O. A. Mohammed et al., "Geoinformatics-based approach for aquifer recharge zone identification in the Western Desert of Iraq," International Journal of GEOMATE, vol. 25, no. 110, pp. 220–234, 2023.
[27]. S. S. Chen., "Designing sustainable drainage systems in subtropical cities: Challenges and opportunities," Journal of Cleaner Production, vol. 280, p. 124418, 2021, doi: 10.1016/j.jclepro.2020.124418.
[28]. O. A. Ibrahim, D. W. Goshime, S. Tekleab, and R. Absi, "Flood inundation mapping and mitigation options in data-scarce region of Beledwayne Town in the Wabi Shebele River Basin of Somalia," Natural Hazards Research, vol. 4, no. 2, pp. 336–346, 2024.
[29]. C. Cacciuttolo, F. Garrido, D. Painenao, and A. Sotil, "Evaluation of the use of permeable interlocking concrete pavement in Chile: Urban infrastructure solution for adaptation and mitigation against climate change," Water (Switzerland), vol. 15, no. 24, 2023.
[30]. E. Janicka and J. Kanclerz, "Assessing the effects of urbanization on water flow and flood events using the HEC-HMS model in the Wirynka River Catchment, Poland," Water (Switzerland), vol. 15, no. 1, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146051846&doi=10.3390%2Fw15010086&partnerID=40&md5=bb79d9bc7f44a0c47e839d581d0b81cd
[31]. S. Natarajan and N. Radhakrishnan, "An integrated hydrologic and hydraulic flood modeling study for a medium-sized ungauged urban catchment area: A case study of Tiruchirappalli City using HEC-HMS and HEC-RAS," Journal of The Institution of Engineers (India): Series A, vol. 101, no. 2, pp. 381–398, 2020.
[32]. M. L. Nurhakim, A. P. Hendrawan, and R. Asmaranto, "Dam-break assessment of Ciawi-Sukamahi parallel dry dams by using HEC-RAS," vol. 13, no. 3, pp. 1465–1479, 2025.
[33]. B. Khorrami, O. Fistikoglu, and O. Gunduz, "A systematic assessment of flooding potential in a semi-arid watershed using GRACE gravity estimates and large-scale hydrological modeling," Geocarto International, vol. 37, pp. 11030–11051, 2022. [Online]. Available: https://consensus.app/papers/a-systematic-assessment-of-flooding-potential-in-a-khorrami-fistikoglu/e5353374e59252cab02bfa08a9595779/
[34]. M. Połomski and M. Wiatkowski, "Water management in dam reservoirs – analysis of operational risks on the example of new facilities," Journal of Water and Land Development, no. 64, pp. 33–45, 2025.
[35]. F. A. Pradita and M. Janicka, "Predicting plant establishment: Germination responses of five Arrhenatherion alliance species from two distinct climatic origins," Journal of Water and Land Development, no. 64, pp. 148–154, 2025.
[36]. K. Hayatuddin., "The impact of human resource management on irrigation and drainage management in Indonesia," Journal of Water and Land Development, no. 64, pp. 172–180, 2025.
[37]. K. Strzęciwilk and M. Grygoruk, "Restoration is an investment. Comparing restoration costs and ecosystem services in selected European wetlands," Journal of Water and Land Development, no. 64, pp. 221–229, 2025.]
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Advance Sustainable Science Engineering and Technology
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
