MODELING AND WEB-BASED VISUALIZATION OF FLOOD ZONES: A CASE STUDY OF THE BUKTYRMA RIVER SECTION
DOI:
https://doi.org/10.37943/23KFOU5095Keywords:
flood modelling, HEC-RAS, web-GIS, NDWI, Landsat-7, Copernicus DEM, Buktyrma RiverAbstract
This study focuses on flood risk assessment in a vulnerable reach of the Buktyrma River basin, located in the East Kazakhstan region. The main goal was to develop and validate a modelling workflow that uses open-access data and software to simulate flood dynamics and visualize the results through an interactive GIS-based interface. The approach involved statistical analysis of 24 years of annual maximum discharge and water level data from gauging station to define a representative flood event. Terrain data were derived from the 30 m Copernicus Digital Elevation Model, which was used to construct the hydraulic geometry of the study area. Two-dimensional flood modeling was carried out in HEC-RAS 6.6, incorporating spatially differentiated Manning’s roughness values based on cadastral land-use classification maps.
The modeling results were verified using satellite imagery from Landsat 7 by calculating the Normalized Difference Water Index for the 2018 flood event, which had a 4 % exceedance probability. The comparison showed a high degree of agreement, indicating that the simulated flood zone overlapped 87 % with the NDWI-derived water mask, and the total inundation area differed by less than 2 %. Model outputs such as flood depth, flow velocity, and cross-sectional profiles were visualized, and the resulting flood map was uploaded within a web-GIS platform. The study demonstrates a transparent and cost-effective methodology that can be applied to other river basins in Kazakhstan, offering a practical tool for spatial planning, risk mitigation, and early warning systems based entirely on publicly available data and software.
References
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 8 (3), 1-11. https://doi.org/10.1016/j.heliyon.2022.e09075
Ngenyam Bang, H., & Church Burton, N. (2021). Contemporary flood risk perceptions in England: Implications for flood risk management foresight. Climate Risk Management, 32, 100317. https://doi.org/10.1016/j.crm.2021.100317
Chettykbayev, R. K., & Denisova, N. F. (2020). Analysis of computer modeling tools for assessing the risk of flooding in the East Kazakhstan region. In Digitalization and Industry 4.0: Economic and Societal Development: An International and Interdisciplinary Exchange of Views and Ideas (pp. 283-290). Wiesbaden: Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-27110-7_20
Mihu-Pintilie, A., Cîmpianu, C. I., Stoleriu, C. C., Pérez, M. N., & Paveluc, L. E. (2019). Using high-density LiDAR data and 2D streamflow hydraulic modeling to improve urban flood hazard maps: A HEC-RAS multi-scenario approach. Water, 11(9), 1832. https://doi.org/10.3390/w11091832
Shustikova, I., Domeneghetti, A., Neal, J. C., Bates, P., & Castellarin, A. (2019). Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography. Hydrological Sciences Journal, 64(14), 1769–1782. https://doi.org/10.1080/02626667.2019.1671982
Djafri, S. A., Cherhabil, S., Hafnaoui, M. A., & Madi, M. (2024). Flood modeling using HEC-RAS 2D and IBER 2D: A comparative study. Water Supply, 24(9), 3061–3076. https://doi.org/10.2166/ws.2024.184
Lidberg, W., Nilsson, M., Lundmark, T., & Ågren, A. M. (2017). Evaluating preprocessing methods of digital elevation models for hydrological modelling. Hydrological Processes, 31(26), 4660–4668. https://doi.org/10.1002/hyp.11385
Ansarifard, S., et al. (2024). Simulation of floods under the influence of effective factors in hydraulic and hydrological models using HEC-RAS and MIKE 21. Discover Water, 4(1), 92. https://doi.org/10.1007/s43832-024-00155-0
Tamiru, H., & Dinka, M. O. (2021). Application of ANN and HEC-RAS model for flood inundation mapping in lower Baro Akobo River Basin, Ethiopia. Journal of Hydrology: Regional Studies, 36, 100855. https://doi.org/10.1016/j.ejrh.2021.100855
Brunner, G. (2018). Benchmarking of the HEC-RAS two-dimensional hydraulic modeling capabilities. US Army Corps of Engineers: Davis, CA, USA, 1-137. https://www.hec.usace.army.mil/software/hec-ras/documentation/RD-51_Benchmarking_2D.pdf
Ongdas, N., Akiyanova, F., Karakulov, Y., Muratbayeva, A., & Zinabdin, N. (2020). Application of HEC-RAS (2D) for flood hazard maps generation for Yesil (Ishim) River in Kazakhstan. Water, 12(10), 2672. https://doi.org/10.3390/w12102672
Kalashnikova, O., Nurbacina, A., & Niyazov, D. (2023). Otsenka riskov navodnenii i pavodkov v tselyakh ustoichivogo razvitiya v basseine reki Zhabai (Kazakhstan) [Assessment of flood and high-water risks for sustainable development in the Zhabai River basin (Kazakhstan)]. Central Asian Journal of Water Research, 2(1), 22–45. https://doi.org/10.29258/CAJSCR/2023-R1.v2-1/22-45.rus
Akiyanova, F., et al. (2023). Operation of gate-controlled irrigation system using HEC-RAS 2D for spring flood hazard reduction. Computation, 11(2), 27. https://doi.org/10.3390/computation11020027
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
Costabile, P., Costanzo, C., Ferraro, D., Macchione, F., & Petaccia, G. (2020). Performances of the new HEC-RAS version 5 for 2-D hydrodynamic-based rainfall-runoff simulations at basin scale: Comparison with a state-of-the-art model. Water, 12(9), 2326. https://doi.org/10.3390/w12092326
Liu, Z., Merwade, V., & Jafarzadegan, K. (2019). Investigating the role of model structure and surface roughness in generating flood inundation extents using one- and two-dimensional hydraulic models. Journal of Flood Risk Management, 12(1), e12347. https://doi.org/10.1111/jfr3.12347
Kim, B., Sanders, B. F., Schubert, J. E., & Famiglietti, J. S. (2014). Mesh type tradeoffs in 2D hydrodynamic modeling of flood inundation. Advances in Water Resources, 68, 42–61. https://doi.org/10.1016/j.advwatres.2014.02.013
Sikan, A. V. (2020). Veroiatnostnye raspredeleniia v gidrologii [Probability distributions in hydrology], 286. http://elib.rshu.ru/files_books/pdf/rid_87d638c890a947f99fcec9099b397e64.pdf
European Space Agency (2024). Copernicus Global Digital Elevation Model. Distributed by OpenTopography. https://doi.org/10.5069/G9028PQB. Accessed 2025-04-04
McFeeters, S. K. (1996). The use of the normalized difference water index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7), 1425–1432. https://doi.org/10.1080/01431169608948714
Komitet po upravleniiu zemel’nymi resursami Ministerstva sel’skogo khoziaistva Respubliki Kazakhstan. (2025, April 15). Publichnaia kadastrivaia karta Respubliki Kazakhstan [Public cadastral map of the Republic of Kazakhstan]. https://map.gov4c.kz/egkn/
Dorin, G. et al. (2022). Mathematical modelling and numerical analysis of hydraulic system behaviour: A case study with application in HEC-RAS. IOP Conference Series: Materials Science and Engineering, 1256(1), 012027. IOP Publishing. https://doi.org/10.1088/1757-899X/1256/1/012027
Hossain, M. S., Bujang, J. S., Zakaria, M. H., & Hashim, M. (2015). Assessment of Landsat 7 Scan Line Corrector-off data gap-filling methods for seagrass distribution mapping. International Journal of Remote Sensing, 36(4), 1188–1215. https://doi.org/10.1080/01431161.2015.1007257
Downloads
Published
How to Cite
Section
License
Copyright (c) 2025 Articles are open access under the Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.