doi: 10.18178/ijesd.2025.16.2.1515
Modelling Capabilities of Two Physically Based Hydrologic Models for Streamflow Simulations
Udara Senatilleke1
,
Ravindu Panditharathne1 ,
Ruchiru D. Herath2 , , ,
Sajana Hemakumara1 ,
Miyuru B. Gunathilake4,5 ,
Hazi Md. Azamathulla6 ,
Komali Kantamaneni2 ,
Upaka Rathnayake3,*
- 1Water Resources Management and Soft Computing Research Laboratory, Millennium City, Athurugiriya 10150, Sri Lanka
- 2School of Engineering and Computing (SEC), University of Central Lancashire, Preston PR1 2HE, United Kingdom
- 3Faculty of Engineering and Design, Atlantic Technological University, Sligo F91 YW50, Ireland
- 4Hydrology and Aquatic Environment, Environment and Natural Resources, Norwegian Institute of Bioeconomy and Research, 1433 Ås, Norway
- 5Water, Energy, and Environmental Engineering Research Unit, Faculty of Technology, University of Oulu, P.O. Box 8000, 90014 Oulu, Finland
- 6Department of Civil Engineering, Faculty of Engineering, University of the West Indies, St. Augustine P.O. Box 331310, Trinidad and Tobago
- Manuscript receivedOctober 17, 2024
- revisedNovember 27, 2024
- acceptedDecember 6, 2024
- publishedMarch 20, 2025
Abstract
Hydrologic processes in a watershed are typicallysimulated through hydrologic models due to their availability inthe public domain and improved computational capacities.However, choosing a suitable model among the many availablefor a region of interest is challenging. In our work, we comparedstreamflow generated by the Soil and Water Assessment Tool(SWAT) and the Hydrological Engineering Centre-HydrologicModeling System (HEC-HMS) in the Kalu River Basin (KRB),Sri Lanka, frequently impacted by floods. Meteorological dataincluding rainfall and temperature from 1990 to 2000 were usedto force the hydrologic models. In addition, we used soil, landuse data and a digital elevation model (DEM) for modeldevelopment. During the calibration phase (1993-1996) of theSWAT model we achieved a coefficient of determination (R²) of0.93 and a Nash-Sutcliffe Efficiency (NSE) of 0.87. In thevalidation phase (1997–2000), these indices yielded values of 0.87and 0.66, respectively. In the HEC-HMS model, during thecalibration phase, R2 and NSE yielded values of 0.89 and 0.91while in the validation phase, these indices yielded values of 0.77and 0.56, respectively. The exceedance probabilities at 10%,50%, and 90% derived from flow duration curves (FDCs) fromHEC-HMS and SWAT models were 395, 159, 54.5 and 400.5,148, 29.11 (all in m3/s), respectively. Similarly, for observed flow,these values were 344.40, 138.98, and 65.35 m3/s, respectively.Thus, the FDCs suggest that the HEC-HMS model captures lowflows reasonably. Neither model accurately resembled highflows. During the first inter-monsoon season (March-April) theHEC-HMS and SWAT underpredicted 3%, and 4% whileduring the northeast monsoon season (December-February) themodels underpredicted 9%, and 2%, respectively. Similarly,during the second inter-monsoon season (October-November)and the southwest monsoon season (May-September), HECHMSand SWAT models overestimated observed flow by 11%,5%, and 8%, 17%, respectively. Both models performedreasonably well on a seasonal basis with slight over-predictionsand under-predictions. Overall, it is clear that both models cangenerally capture the hydrology of the KRB.
Keywords
- Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS)
- Soil & Water Assessment Tool (SWAT)
- Kalu River Basin (KRB)
- streamflow
How to Cite
Udara Senatilleke, Ravindu Panditharathne, Ruchiru D. Herath, Dushyantha M. Aththanayake, Randika K. Makubura, Sajana Hemakumara, Miyuru B. Gunathilake, Hazi Md. Azamathulla, Komali Kantamaneni, and Upaka Rathnayake, "Modelling Capabilities of Two Physically Based Hydrologic Models for Streamflow Simulations," International Journal of Environmental Science and Development, vol. 16, no. 2, pp. 103-110, 2025. https://doi.org/10.18178/ijesd.2025.16.2.1515
Copyright & License
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).