Flood forecast and inundation mapping using a combined hydrologic and hydraulic model on Muga River Abay Basin, Ethiopia

Abstract

This study presents an integrated flood forecasting and inundation mapping framework using coupled SWAT, HEC-HMS, and HEC-RAS models for the Muga River basin in the Abay Basin, Ethiopia. The study addresses the limited application of integrated hydrologic-hydraulic modeling and the uncertainty associated with digital elevation model (DEM) resolution in data-scarce regions. Flood discharges corresponding to 2-, 5-, 10-, 25-, 50-, and 100-year return periods, which are commonly used for flood risk assessment and infrastructure design, were simulated. SWAT was applied for continuous hydrological simulation, while the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) supported event-based peak flow estimation. Model performance was evaluated using observed streamflow and the 2017 historical flood event. Flood inundation characteristics were assessed using ALOS 30 m, SRTM 30 m, and SRTM 90 m DEMs to quantify terrain-related uncertainty. Results show that SWAT produced slightly higher peak discharges than HEC-HMS, providing conservative estimates for flood risk planning; therefore, SWAT-derived flows were used for final inundation mapping. Among the tested DEMs, ALOS 30 m exhibited the closest agreement with observed flood extent and depth. The proposed framework is transferable to other sub-basins of the Abay Basin with similar hydro-geomorphic characteristics and offers practical support for flood hazard mitigation and planning.

Keywords

DEM resolution / flood forecasting / inundation mapping / Muga River / SWAT / HEC-RAS

References

[1] Alborzi, A., Zhao, Y., Nazemi, A., Mirchi, A., Mallakpour, I., Moftakhari, H., Ashraf, S., Izadi, R., & AghaKouchak, A. (2022). The tale of three floods: From extreme events and cascades of highs to anthropogenic floods. Weather and Climate Extremes, 38(August), 100495. https://doi.org/10.1016/j.wace.2022.100495

[2] Angelakis, A. N., Capodaglio, A. G., Valipour, M., Krasilnikoff, J., Ahmed, A. T., Mandi, L., Tzanakakis, V. A., Baba, A., Kumar, R., Zheng, X., Min, Z., Han, M., Turay, B., Bilgiç, E., & Dercas, N. (2023). Evolution of floods: From ancient times to the present times (ca 7600 BC to the Present) and the future. Land, 12(6), 1211. https://doi.org/10.3390/land12061211

[3] Ashok, S. P., & Pekkat, S. (2022). A systematic quantitative review on the performance of some of the recent short-term rainfall forecasting techniques. Journal of Water and Climate Change, 13(8), 3004-3029. https://doi.org/10.2166/wcc.2022.302

[4] Awu, J. I., Mbajiorgu, C. C., Manta, H. I., & James, D. D. (2017). Flood inundation simulation using HEC-RAS hydrologic model: A case study of Oyun River, Nigeria. International Journal of Basic and Applied Sciences, 7(1), 62-68.

[5] Ayele, E. G., Buba, Z. M., & Garo, O. O. (2024). Evaluation of satellite rainfall products to estimate extreme flow events over the Kulfo watershed in Ethiopia. Water Practice & Technology, 19(11), 4647-4666. https://doi.org/10.2166/wpt.2024.278

[6] Bakhtiari, V., Piadeh, F., Behzadian, K., & Kapelan, Z. (2023). A critical review for the application of cutting-edge digital visualisation technologies for effective urban flood risk management. Sustainable Cities and Society, 99(July), 104958. https://doi.org/10.1016/j.scs.2023.104958

[7] Bhuyian, M. N. M., Kalyanapu, A. J., & Nardi, F. (2015). Approach to digital elevation model correction by improving channel conveyance. Journal of Hydrologic Engineering, 20(5), 1-10. https://doi.org/10.1061/(asce)he.1943-5584.0001020

[8] Bloomfield, H. C., Hillier, J., Griffin, A., Kay, A. L., Shaffrey, L. C., Pianosi, F., James, R., Kumar, D., Champion, A., & Bates, P. D. (2023). Co-occurring wintertime flooding and extreme wind over Europe, from daily to seasonal timescales. Weather and Climate Extremes, 39(February), 100550. https://doi.org/10.1016/j.wace.2023.100550

[9] Botzen, W. J. W., Deschenes, O., & Sanders, M. (2019). The economic impacts of natural disasters: A review of models and empirical studies. Review of Environmental Economics and Policy, 13(2), 167-188. https://doi.org/10.1093/reep/rez004

[10] Brunner, M. I., Slater, L., Tallaksen, L. M., & Clark, M. (2021). Challenges in modeling and predicting floods and droughts: A review. Wiley Interdisciplinary Reviews: Water, 8(3), 1-32. https://doi.org/10.1002/wat2.1520

[11] Budhathoki, B. R., Adhikari, T. R., Shu, L., Shrestha, S., Awasthi, R. P., Dawadi, B., Baniya, B., & Dhital, Y. P. (2025). Evaluation of distributed and semi-distributed hydrological models in complex river basin system, Nepal. HydroResearch, 8, 49-57. https://doi.org/10.1016/j.hydres.2024.09.006

[12] Byaruhanga, N., Kibirige, D., Gokool, S., & Mkhonta, G. (2024). Evolution of flood prediction and forecasting models for flood early warning systems: A scoping review. Water, 16(13), 1-29. https://doi.org/10.3390/w16131763

[13] Caldera, H. P. G. M., Piyathisse, V. R. P. C., & Nandalal, K. D. W. (2016). A comparison of methods used in estimating missing rainfall data. Journal of Agricultural Sciences, 3(4), 1-8. https://doi.org/10.4038/jas.v3i2.8107

[14] Cao, Z., Wang, S., Luo, P., Xie, D., & Zhu, W. (2022). Watershed ecohydrological processes in a changing environment: Opportunities and challenges. Water, 14(9), 1502. https://doi.org/10.3390/w14091502

[15] Cea, L., & Costabile, P. (2022). Flood risk in urban areas: modelling, management and adaptation to climate change: A review. Hydrology, 9(3), 50. https://doi.org/10.3390/hydrology9030050

[16] Chathuranika, I. M., Gunathilake, M. B., Baddewela, P. K., Sachinthanie, E., Babel, M. S., Shrestha, S., Jha, M. K., & Rathnayake, U. S. (2022). Comparison of two hydrological models, HEC-HMS and. Fluids, 7(8), 267. https://doi.org/10.3390/fluids7080267

[17] Chen, Z., Lin, H., & Shen, G. (2023). TreeLSTM: A spatiotemporal machine learning model for rainfall-runoff estimation. Journal of Hydrology: Regional Studies, 48(July), 101474. https://doi.org/10.1016/j.ejrh.2023.101474

[18] Desta, G., Legesse, G., Ahmed, M. I., Muluneh, A., & Birhanu, B. (2024). Assessing flood risks and exploring opportunities for flood-based farming in the dry lowlands of Ethiopia. Frontiers in Sustainable Food Systems, 8(March), 1-17. https://doi.org/10.3389/fsufs.2024.1348094

[19] DeVilleneuve, S., Kelly, A., Miyanaka, N., Shanmuhasundaram, T., Murphree, P., & Wyatt, B. M. (2023). Impacts of vegetation and topsoil removal on soil erosion, soil moisture, and infiltration. Agrosystems, Geosciences & Environment, 6(3), 1-10. https://doi.org/10.1002/agg2.20402

[20] Ebi, K. L., Vanos, J., Baldwin, J. W., Bell, J. E., Hondula, D. M., Errett, N. A., Hayes, K., Reid, C. E., Saha, S., Spector, J., & Berry, P. (2021). Extreme weather and climate change: Population health and health system implications. Annual Review of Public Health, 42(1), 293-315. https://doi.org/10.1146/annurev-publhealth-012420-105026

[21] Echendu, A. J. (2023). Human factors vs climate change; experts' view of drivers of flooding in Nigeria. Natural Hazards Research, 3(2), 240-246. https://doi.org/10.1016/j.nhres.2023.04.002

[22] Flores, N., Rodríguez, R., Yépez, S., Osores, V., Rau, P., Rivera, D., & Balocchi, F. (2021). Comparison of three daily rainfall-runoff hydrological models using four evapotranspiration models in four small forested watersheds with different land cover in south-central Chile. Water, 13(22), 1-28. https://doi.org/10.3390/w13223191

[23] García-Marín, A. P., Estévez, J., Morbidelli, R., Saltalippi, C., Ayuso-Muñoz, J. L., & Flammini, A. (2020). Assessing inhomogeneities in extreme annual rainfall data series by multifractal approach. Water, 12(4), 1-18. https://doi.org/10.3390/W12041030

[24] El Garnaoui, M., Boudhar, A., Nifa, K., El Jabiri, Y., Karaoui, I., El Aloui, A., Midaoui, A., Karroum, M., Mosaid, H., & Chehbouni, A. (2024). Nested Cross-Validation for HBV conceptual rainfall-runoff model spatial stability analysis in a Semi-Arid context. Remote Sensing, 16(20), 3756. https://doi.org/10.3390/rs16203756

[25] Ginige, K., Mendis, K., & Thayaparan, M. (2022). An assessment of structural measures for risk reduction of hydrometeorological disasters in Sri Lanka. Progress in Disaster Science, 14(January), 100232. https://doi.org/10.1016/j.pdisas.2022.100232

[26] Hakim, D. K., Gernowo, R., & Nirwansyah, A. W. (2024). Flood prediction with time series data mining: Systematic review. Natural Hazards Research, 4(2), 194-220. https://doi.org/10.1016/j.nhres.2023.10.001

[27] Harada, N., Satofuka, Y., & Mizuyama, T. (2024). The impacts of river channel blockages caused by sliding embankment collapses during earthquakes. Water, 16(6), 822. https://doi.org/10.3390/w16060822

[28] He, M., & Lee, H. (2021). Advances in hydrological forecasting. Forecasting, 3(3), 517-519. https://doi.org/10.3390/forecast3030032

[29] Hooker, H., Dance, S. L., Mason, D. C., Bevington, J., & Shelton, K. (2022). Spatial scale evaluation of forecast flood inundation maps. Journal of Hydrology, 612(PB), 128170. https://doi.org/10.1016/j.jhydrol.2022.128170

[30] Ibrahim, O. A., Goshime, D. W., Tekleab, S., & Absi, R. (2024). Flood inundation mapping and mitigation options in data-scarce region of Beledwayne town in the Wabi Shebele River Basin of Somalia. Natural Hazards Research, 4(2), 336-346. https://doi.org/10.1016/j.nhres.2023.11.001

[31] Iwasaki, T., Shimizu, Y., & Kimura, I. (2016). Numerical simulation of bar and bank erosion in a vegetated floodplain: A case study in the Otofuke River. Advances in Water Resources, 93, 118-134. https://doi.org/10.1016/j.advwatres.2015.02.001

[32] Jonkman, S. N., Curran, A., & Bouwer, L. M. (2024). Floods have become less deadly: An analysis of global flood fatalities 1975-2022. Natural Hazards, 120(7), 6327-6342. https://doi.org/10.1007/s11069-024-06444-0

[33] Kazemzadeh, M., & Malekian, A. (2018). Homogeneity analysis of streamflow records in arid and semi-arid regions of northwestern Iran. Journal of Arid Land, 10(4), 493-506. https://doi.org/10.1007/s40333-018-0064-4

[34] Khan, S., Ncibi, K., Hamdi, N., & Hamed, Y. (2022). Flood analysis using HEC-RAS and HEC-HMS: A case study. Water, 14(1-19), 3779. https://doi.org/10.3390/w14223779

[35] Kumar, V., Sharma, K., Caloiero, T., Mehta, D., & Singh, K. (2023). Comprehensive overview of flood modeling approaches: A review of recent advances. Hydrology, 10(7), 141. https://doi.org/10.3390/hydrology10070141

[36] Lee, J., Perera, D., Glickman, T., & Taing, L. (2020). Water-related disasters and their health impacts: A global review. Progress in Disaster Science, 8, 100123. https://doi.org/10.1016/j.pdisas.2020.100123

[37] Legese, B., & Gumi, B. (2020). Flooding in ethiopia; causes, impact, and coping mechanism. A review. International Journal of Research and Analytical Reviews (IJRAR), 7(3), 707. Www.Ijrar.Org<www.ijrar.org.

[38] Maria, D., Sushama, L., Almansour, H., Khaliq, M. N., Nguyen, V. T. V., & Chouinard, L. (2024). Future flood envelope curves for the estimation of design flood magnitudes for highway bridges at river crossings. Results in Engineering, 22(March), 102038. https://doi.org/10.1016/j.rineng.2024.102038

[39] Mera, G. A. (2018). Drought and its impacts in Ethiopia. Weather and Climate Extremes, 22(September), 24-35. https://doi.org/10.1016/j.wace.2018.10.002

[40] Muleta, T. N., & Marcell, K. (2023). Rainfall-runoff modeling and hydrological responses to the projected climate change for Upper Baro Basin, Ethiopia. American Journal of Climate Change, 12(02), 219-243. https://doi.org/10.4236/ajcc.2023.122011

[41] Orkaido Garo, O., H/slassie Mamecha, S., Shale Sasa, M., & Mehari Andiye, Y. (2025). Flood forecasting, inundation mapping, and risk analysis mapping for Phase-I ribb irrigation area in Amhara Region, Ethiopia. Modeling Earth Systems and Environment, 11(3), 188. https://doi.org/10.1007/s40808-025-02368-1

[42] Pandi, D., Kothandaraman, S., & Kuppusamy, M. (2023). Simulation of water balance components using SWAT model at sub catchment level. Sustainability, 15(2), 1438. https://doi.org/10.3390/su15021438

[43] Patel, A., Yadav, S. M., & Teegavarapu, R. (2024). Enhancing real-time flood forecasting and warning system by integrating ensemble techniques and hydrologic model simulations. Journal of Water and Climate Change, 15(9), 4307-4327. https://doi.org/10.2166/wcc.2024.052

[44] Rasouli, K., Pomeroy, J. W., & Whitfield, P. H. (2019). Are the effects of vegetation and soil changes as important as climate change impacts on hydrological processes? Hydrology and Earth System Sciences, 23(12), 4933-4954. https://doi.org/10.5194/hess-23-4933-2019

[45] De Risi, R., Jalayer, F., De Paola, F., Carozza, S., Yonas, N., Giugni, M., & Gasparini, P. (2020). From flood risk mapping toward reducing vulnerability: The case of Addis Ababa. Natural Hazards, 100(1), 387-415. https://doi.org/10.1007/s11069-019-03817-8

[46] Sortino Barrionuevo, J. F., Castro Noblejas, H., & Mérida Rodríguez, M. F. (2024). Mapping tools for flood risk rescue and assistance management. Land, 13(1), 68. https://doi.org/10.3390/land13010068

[47] Tambal, S. A. R. M. A., Elsawahli, H. M. H., Ibrahim, E. I. E., & Lumbroso, D. (2024). Increasing urban flood resilience through public participation: A case study of Tuti Island in Khartoum, Sudan. Journal of Flood Risk Management, 17(2), 1-24. https://doi.org/10.1111/jfr3.12966

[48] Tang, Y., Sun, Y., Han, Z., Soomro, S. ehyde, Wu, Q., Tan, B., & Hu, C. (2023). Flood forecasting based on machine learning pattern recognition and dynamic migration of parameters. Journal of Hydrology: Regional Studies, 47, 101406. https://doi.org/10.1016/j.ejrh.2023.101406

[49] Tareke, K. A., & Awoke, A. G. (2023). Hydrological drought forecasting and monitoring system development using artificial neural network (ANN) in Ethiopia. Heliyon, 9(2), e13287. https://doi.org/10.1016/j.heliyon.2023.e13287

[50] Tariq, M. A. U. R., Farooq, R., & van de Giesen, N. (2020). A critical review of flood risk management and the selection of suitable measures. Applied Sciences (Switzerland), 10(23), 1-18. https://doi.org/10.3390/app10238752

[51] Tefera, G. W., Dile, Y. T., Srinivasan, R., Baker, T., & Ray, R. L. (2023). Hydrological modeling and scenario analysis for water supply and water demand assessment of Addis Ababa city, Ethiopia. Journal of Hydrology: Regional Studies, 46(September 2022), 101341. https://doi.org/10.1016/j.ejrh.2023.101341

[52] Teshome Nigatu, G., Abebe, B. A., Grum, B., Kebedew, M. G., & Semane, E. M. (2023). Investigation of flood incidence causes and mitigation: Case study of Ribb river, northwestern Ethiopia. Natural Hazards Research, 3(3), 408-419. https://doi.org/10.1016/j.nhres.2023.04.009

[53] Tsegaye, S., Kebedew, M. G., Albrecht, K. K., Missimer, T. M., Thomas, S., & Elshall, A. S. (2024). Integrated GIS-hydrologic-hydraulic modeling to assess combined flood drivers in coastal regions: A case study of Bonita Bay, Florida. Frontiers in Water, 6(October). https://doi.org/10.3389/frwa.2024.1468354

[54] Uddin, K., & Matin, M. A. (2021). Potential flood hazard zonation and flood shelter suitability mapping for disaster risk mitigation in Bangladesh using geospatial technology. Progress in Disaster Science, 11(March 2019), 100185. https://doi.org/10.1016/j.pdisas.2021.100185

[55] Wang, L., Cui, S., Li, Y., Huang, H., Manandhar, B., Nitivattananon, V., Fang, X., & Huang, W. (2022). A review of the flood management: From flood control to flood resilience. Heliyon, 8(11), e11763. https://doi.org/10.1016/j.heliyon.2022.e11763

[56] Weday, M. A., Tabor, K. W., & Gemeda, D. O. (2023). Flood hazards and risk mapping using geospatial technologies in Jimma City, southwestern Ethiopia. Heliyon, 9(4), e14617. https://doi.org/10.1016/j.heliyon.2023.e14617

[57] Zhao, X., Wang, H., Bai, M., Xu, Y., Dong, S., Rao, H., & Ming, W. (2024). A comprehensive review of methods for hydrological forecasting based on deep learning. Water, 16(10), 1407. https://doi.org/10.3390/w16101407

RIGHTS & PERMISSIONS

2026 The Author(s). River published by Wiley-VCH GmbH on behalf of China Institute of Water Resources and Hydropower Research (IWHR).