Simulation of flood protection using Hec Ras modeling: A case study of the Lam Phra Phloeng river basin

Main Article Content

Preeyaphorn Kosa
Thanutch Sukwimolseree

Abstract

The Lam Phra Phloeng reservoir, positioned within the Lam Phra Phloeng river basin and situated in Nakhon Ratchasimi province, assumes a substantial role in the realm of regional water management. During severe storms in the reservoir's upper region, excess water flows downstream, occasionally resulting in devastating floods in Pak Thongchai district, as witnessed in 2010 and 2020. Both flooding events have resulted in significant economic, social, and livelihood disruptions to the local population in the affected areas. This study pursues two primary objectives: firstly, to assess the extent of flood-prone areas across various return periods (2, 5, 10, 25, 50, 100, and 500 years); secondly, to employ Hec Ras modeling for an in-depth analysis of strategies aimed at flood prevention and mitigation within the Lam Phra Phloeng river basin. The Hec Ras modeling incorporates both 1D and 2D flow simulations. The findings reveal that the flood-prone areas, corresponding to the specified return periods, occupy 0.20%, 1.10%, 1.60%, 2.08%, 2.39%, 2.66%, and 3.17% of the total area in the Lam Phra Phloeng river basin, respectively. To safeguard against flooding and minimize its impact, a multifaceted approach is recommended, encompassing the construction of water barrier flaps, augmentation of water transmission and drainage capacity, implementation of flood alarm systems along the Lam Phra Phloeng river, installation of runoff stations, and the establishment of a comprehensive database system for flood and drought prevention. Among these measures, constructing water barrier flaps and enhancing water transmission and drainage capabilities stand out as effective strategies to protect the Lam Phra Phloeng river basin from flooding.

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1.
Kosa P, Sukwimolseree T. Simulation of flood protection using Hec Ras modeling: A case study of the Lam Phra Phloeng river basin. J Appl Res Sci Tech [Internet]. 2024 Jun. 19 [cited 2024 Nov. 21];23(2):254752. Available from: https://ph01.tci-thaijo.org/index.php/rmutt-journal/article/view/254752
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Research Articles

References

Phorathip B. The integration of remote sensing technology and geographic information systems in delineating hazard-prone areas within the Lam Phra Phloeng river basin [dissertation]. Nakhon Ratchasima: Suranaree University of Technology; 1999.

Preeyaphorn K. Integration of GIS system and HEC-RAS model for large-scale water management. 2022.

Januriyadi NF, Kazama S, Moe IR, Kure S. Effectiveness of structural and nonstructural measures on the magnitude and uncertainty of future flood risks. Journal of Water Resource and Protection. 2020;12(5):401-15.

Kundzewicz ZW. Non-structural flood protection and sustainability. Water Int. 2002;1(27):3-13.

Global Water Partnership (GWP), World Meteorological Organization (WMO). Effectiveness of flood management measures. Issue 21. Geneva: WMO; 2015.

Western Balkans Investment Framework. Flood prevention and management: Gap analysis and needs assessment in the context of implementing EU Floods Directive. 2015.

Januriyadi NF, So K, Idham RM, Shuichi K. Effectiveness of structural and nonstructural measures on the magnitude and uncertainty of future flood fisks. Journal of Water Resource and Protection. 2020;12(5):401-15.

Comprehensive report on flood and disaster management in Thailand [Internet]. Bangkok: Office of the Ombudsman; 2011 [cited 2023 Jan 20]. Availability from: www.oic.go.th/FILEWEB/CABINFOCENTER6/DRAWER073/GENERAL/DATA0000/00000014.PDF.

Sajja B, Bamphen K, Palirat K, Chaiyut C. Appropriate direction to flood disaster management by community-based participation in Thailand. In: Rethink: Social Development for Sustainability in ASEAN Community; 2014 Jun 11-13; Bangkok, Thailand. 2014. p. 548-58.

Bunnawong AR. Solving Flooding Problems in the Agricultural Areas of Bung Samboon Village, Tab Lue Bung Aor Subdistrict, Kaem Ta Sei District, Nakhon Ratchasima Province [dissertation]. Nakhon Ratchasima: Suranaree University of Technology; 2012.

Laowichien U, Saengmahachai S. Disaster management and solutions for flood problems in Bangkok metropolis. Kasem Bundit J. 2017;18(2):111-27.

Schnabl S, Kryzanowski A, Brilly M, Rusjan S. Review article: structural flood-protection measures referring to several European case studies. Nat Hazards Earth Syst Sci. 2014;14(1):135-42.

Kundzewicz ZW. Non-structural flood protection and sustainability. Water Int. 2002;27(1):3-13.

Minea G, Zaharia L. Structural and Non-Structural Measures for Flood Risk Mitigation in the Bâsca River Catchment (Romania). Forum geografic. 2011;10(1):157-66.

Kang S, Lee S, Lee K. A study on the implementation of non-structural measures to reduce urban flood damage focused on the survey results of the experts. J Asian Archit Build. 2009;8(2):385-92.

Cameron T, Ackerman PE. HEC-GeoRAS GIS Tool for Support of HEC-RAS using ArcGIS, User's Manual. Ver. 4.3.93. Davis: US Army Corps of Engineers Hydrologic Engineering Center; 2011.

Brunner GW, Ceiwr-Hec. HEC-RAS River Analysis System, User's Manual. Ver. 4.1. Davis: US Army Corps of Engineers Hydrologic Engineering Center; 2010.

Warner JC, Brunner GW, Wolfe BC, Piper SS. HEC-RAS, River Analysis System Application Guide. Ver. 4.1. Davis: US Army Corps of Engineers Hydrologic Engineering Center; 2010.

Brunner GW. HEC-RAS River Analysis System, Hydraulics Reference Manual. Ver 4.1. Davis: US Army Corps of Engineers Hydrologic Engineering Center; 2010.

Refsgaard JC, Storm B. Construction, calibration and validation of hydrological models. In: Singh VP, editor. Water Science and Technology Library. Vol. 22. SpringerLink; 1996. p. 41-54.

Madsen H. Automatic calibration of a conceptual rainfall-runoff model using multiple objectives. J Hydrol. 2000;235(3):276-88.

Nash IE, Sutcliffe IV. River flow forecasting through conceptual models, Part I. J Hydrol.1970;10:282-90.

Nash JE, Sutcliffe JV. River flow forecasting through conceptual models: Part 1. A discussion of principles. J Hydrol. 1970;10(3):282-90.

Boyle DP, Gupta HV, Sorooshian S. Toward improved calibration of hydrologic models: Combining the strengths of manual and automatic methods. Water Resour Res. 2000;36(12):3663-74.

Fricke K. Analysis and modelling of water supply and demand under climate change, land usa transformation and socio-economic development [dissertation]. Heidelberg: Heidelberg University, 2014.

Morisa DN, Arnold JG, Van Liew MW, Binger RL, Harmel RD, Veith T. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Journal of the ASABE. 2007;50(3):885-900.

Seydi ST, Kanani-Sadat Y, Hasanlou M, Sahraei R, Chanussot J, Amani M. Comparison of machine learning algorithms for flood susceptibility mapping. Remote Sens. 2023;15(1):192.

Uttharasawat T, Kosa P, Sukwimolseree T. Evaluation of Flood Areas in the Lam Phra Phloeng River Basin Using MIKE FLOOD Model. In: Proceedings of the 28th National Civil Engineering Conference; 2023 May 24-26; Phuket, Thailand. NCCE28; 2023.

Preeyaphorn K, Thanutch S. Evaluating water conveyance potential in the Lam Phra Phloeng River using HEC-RAS modeling. In: 25th National Civil Engineering Conference; 2020 Jul 15-17; Chonburi, Thailand. NCCE25; 2020. p. 2421-27.