Optimizing mannings roughness coefficient for hydraulic modelling: An application for Pinacanauan De Tuguegarao watershed, Philippines
Paper Details
Optimizing mannings roughness coefficient for hydraulic modelling: An application for Pinacanauan De Tuguegarao watershed, Philippines
Abstract
Flooding poses a significant threat to Pinacanauan de Tuguegarao watershed, with increasing frequency of occurrences prompting the urgent need for enhanced flood forecasting through model calibration and validation. The city’s most severe flood event was recorded during Typhoon Ulysses, which served as the basis for calibrating the hydrologic and hydraulic models of the Pinacanauan de Tuguegarao watershed. Using HEC-HMS, the hydrologic simulation optimized Clark’s unit hydrograph parameters (time of concentration and storage coefficient) and SCS curve number loss method parameters (curve number and initial abstraction), achieving precise simulation of observed hydrographs. Calibration of the hydraulic model using TUFLOW adjusted Manning’s roughness coefficient iteratively, settling on depth-varying values from 0.002 at 3.5 meters to 0.4 at 4 meters, with the model accurately predicting stage heights and discharge rates as evaluated by NSE, PBIAS, RMSE, and RSR metrics. Validation during Typhoons Paeng and Tisoy demonstrated the model’s proficiency in predicting extreme and moderate flood events, although with tendencies to overestimate minor floods. The calibrated model subsequently facilitated the development of a flood model for Typhoon Ulysses and an early warning system based on river stage heights, enhancing decision-making and communication for disaster preparedness and response in Tuguegarao City.
Abbott MB, Bathurst JC, Connell PE, Rasmussen JR. 1986. An introduction to the European hydrologic system—Système Hydrologique Européen (SHE): history of a physically based, distributed modeling system. Journal of Hydrology 87, 45–59.
Alfonso C, Sundo M, Zafra R, Velasco P, Aguirre J, Madlangbayan M. 2019. Flood risk assessment of major river basins in the Philippines. International Journal of GEOMATE 16, 201–208.
Barton J, Babister M, Burston J. 2015. TUFLOW Classic / TUFLOW HPC—user manual. https://www.tuflow.com/
Department of Environment and Natural Resources (DENR). n.d. Cagayan River Basin. River Basin Control Office. https://riverbasin.denr.gov.ph/river/cagayan
Eslamian S, Eslamian F. 2023. Handbook of hydroinformatics, volume III: water data management best practices. Elsevier, Inc.
Garcia FC, Retamar AE, Javier JC. 2016. Development of a predictive model for on-demand remote river level nowcasting: case study in Cagayan River Basin, Philippines. Institute of Electrical and Electronics Engineers Proceedings, 3275–3279.
Gupta HV, Sorooshian S, Yapo PO. 1999. Status of automatic calibration for hydrologic models: comparison with multilevel expert calibration. Journal of Hydrologic Engineering 4, 135–143.
Hosseiny H, Nazari F, Smith V, Nataraj C. 2020. A framework for modeling flood depth using a hybrid of hydraulics and machine learning. Scientific Reports 10, 1–13.
Kuhanestani R, Kowsar K, Bhardwaj A. 2022. Development of a 2D hydraulic model for assessing flood hazards in urban areas. Natural Hazards Review 23(2), 05021005.
Le Méhauté B. 1976. An introduction to hydrodynamics and water waves. Springer Science+Business Media, California.
Nash JE, Sutcliffe JV. 1970. River flow forecasting through conceptual models. Journal of Hydrology 10, 282–290.
Natarajahan S, Radhakrishnan N. 2020. 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) 101, 381–398.
Ngoc TA, Chinh LV, Hiramatsu K, Harada M. 2011. Parameter identification for two conceptual hydrological models of Upper Dau Tieng River watershed in Vietnam. Journal of the Faculty of Agriculture, Kyushu University 56(2), 335–341.
Noh J, Lee J, Shinogi Y, Oh T. 2018. Simulating daily runoff in hydrologic standard basin considering agricultural reservoir operation. Journal of the Faculty of Agriculture, Kyushu University 63(1), 119–130.
Philippines Historical Hazards. 2021. Climate change knowledge portal for development practitioners and policy makers. https://climateknowledgeportal.worldbank.org/country/philippines/vulnerability
Santillan JR, Ramos RV, David G, Recamadas SM. 2013. Development, calibration and validation of a flood model for Marikina River Basin, Philippines and its applications for flood forecasting, reconstruction, and hazard mapping.
Sevat E, Dezetter A. 1991. Selection of calibration objective function in the context of rainfall–runoff modeling in Sudanese savannah area. Hydrological Sciences Journal 36, 307–330.
Soomro A, Babar M, Zaidi A, Ashraf A, Lund J. 2019. Sensitivity of direct runoff to curve number using the SCS-CN method. Civil Engineering Journal 5, 2738–2746.
Syme B. 1990. Practical 1-D and 2-D computer modelling of flow and transport processes in rivers, estuaries and coastal waters. Queensland Division Technical Paper, 15–19.
World Health Organization (WHO). 2022. Floods. https://www.who.int/health-topics/floods#tab=tab_1
Policarpio L. Mabborang Jr.*, Jonathan A. Saturno, Jose D. Guzman, James B. Cabildo, Rio Jay R. Banan, Luzviminda M. Adolfo, 2025. Optimizing mannings roughness coefficient for hydraulic modelling: An application for Pinacanauan De Tuguegarao watershed, Philippines. J. Biodiv. Environ. Sci., 27(6), 102-113.
Copyright © 2025 by the Authors. This article is an open access article and distributed under the terms and conditions of the Creative Commons Attribution 4.0 (CC BY 4.0) license.