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Shreya Kayal,
Susmita Ghosh,
Swapan Kumar Ghosh,
Sandip Sarkar,
Subhojit Chattaraj,
- U G Student, Department of Civil Engineering, Greater Kolkata College of Engineering and Management, JIS Group, Baruipur, West Bengal, India
- U G Student, Department of Civil Engineering, Greater Kolkata College of Engineering and Management, JIS Group, Baruipur, West Bengal, India
- U G Student, Department of Civil Engineering, Greater Kolkata College of Engineering and Management, JIS Group, Baruipur, West Bengal, India
- Assistant Professor, Department of Civil Engineering, Greater Kolkata College of Engineering and Management, JIS Group, Baruipur, West Bengal, India
- Assistant Professor, Department of Civil Engineering, Greater Kolkata College of Engineering and Management, JIS Group, Baruipur, West Bengal, India
Abstract
Hydrology is the science which deals with the existence, movement and distribution of water of the earth, below the earth and earth’s atmosphere. As one of the branches of earth science, hydrology deals with the water in waterways and lakes, precipitation and snow, snow on the terrestrial and water underneath the earth and rocks. Hydrology has its links with meteorology, geography, measurements, science, material science and liquid mechanics. Engineers and hydrologists are highly concerned about the amount of runoff generating from a given rainfall amount. The surface excess water is most basic and vital parameter for the appraisal of watershed water yield. Watershed management has made use of hydrological models since they are crucial instruments for comprehending the hydrological behaviour of the watersheds. The hydrological models can replicate the effects of various soil and water conservation structures. This aids decision-makers in implementing appropriate conservation strategies in regions that are vulnerable to erosion. A summary of various hydrological models and their uses in watershed management is provided in this article.
Keywords: Artificial neural network, hydrological modeling, SCS-CN, SWAT
[This article belongs to Journal of Water Resource Engineering and Management ]
Shreya Kayal, Susmita Ghosh, Swapan Kumar Ghosh, Sandip Sarkar, Subhojit Chattaraj. Hydrological Modeling and Classification of Various Models: A Review. Journal of Water Resource Engineering and Management. 2026; 13(01):1-5.
Shreya Kayal, Susmita Ghosh, Swapan Kumar Ghosh, Sandip Sarkar, Subhojit Chattaraj. Hydrological Modeling and Classification of Various Models: A Review. Journal of Water Resource Engineering and Management. 2026; 13(01):1-5. Available from: https://journals.stmjournals.com/jowrem/article=2026/view=236389
References
1. Akbarpour, M. (2004). Simulation of rainfall-runoff process by artificial neural networks and HEC
HMS model (case study Zard River basin). In Fourth International Iran and Russia Conference.
Shahrekord University (pp. 1143-1148).
2. Bingner, R. L. (1996). Runoff simulated from Goodwin Creek watershed using SWAT.
Transactions of the ASAE, 39(1), 85-90.
3. Daniel, E. B., Camp, J. V., LeBoeuf, E. J., Penrod, J. R., Dobbins, J. P., & Abkowitz, M. D. (2011).
Watershed modeling and its applications: A state-of-the-art review. Open Hydrology Journal, 5(1),
26-50.
4. Djokic, D., & Maidment, D. R. (1991). Terrain analysis for urban stormwater modelling.
Hydrological processes, 5(1), 115-124.
5. Gosain, A. K., Mani, A., & Dwivedi, C. (2009). Hydrological modelling-literature review.
Advances in Fluid Mechanics, 339, 63-70.
6. Himanshu, S. K., Pandey, A., & Shrestha, P. (2017). Application of SWAT in an Indian river basin
for modeling runoff, sediment and water balance. Environmental Earth Sciences, 76, 1-18.
7. Jain, S. K., Tyagi, J., & Singh, V. (2010). Simulation of runoff and sediment yield for a Himalayan
watershed using SWAT model. Journal of Water Resource and Protection, 2(3), 267-281.
8. Jowitt, P. W. (1985). Teaching aids in hydrology.
9. Mugume, S. N., Murungi, J., Nyenje, P. M., Sempewo, J. I., Okedi, J., & Sörensen, J. (2024).
Development and application of a hybrid artificial neural network model for simulating future
stream flows in catchments with limited in situ observed data. Journal of Hydroinformatics, 26(8),
1944-1969.
10. Nayak, P. C., Sudheer, K. P., Rangan, D. M., & Ramasastri, K. S. (2004). A neuro-fuzzy computing
technique for modeling hydrological time series. Journal of Hydrology, 291(1-2), 52-66.
11. Singh, V. P., & Frevert, D. K. (Eds.). (2002). Mathematical models of small watershed hydrology
and applications. Water Resources Publication.
12. Singh, V. P., & Woolhiser, D. A. (2002). Mathematical modeling of watershed hydrology. Journal
of hydrologic engineering, 7(4), 270-292.
13. Stuebe, M. M., & Johnston, D. M. (1990). Runoff volume estimation using GIS techniques 1.
JAWRA Journal of the American Water Resources Association, 26(4), 611-620.
14. Takele, G. S., Gebre, G. S., Gebremariam, A. G., & Engida, A. N. (2021). Hydrological modeling
in the Upper Blue Nile basin using soil and water analysis tool (SWAT). Modeling Earth Systems
and Environment, 1-16.
15. Thavhana, M. P., Savage, M. J., & Moeletsi, M. E. (2018). SWAT model uncertainty analysis,
calibration and validation for runoff simulation in the Luvuvhu River catchment, South Africa.
Physics and Chemistry of the Earth, Parts A/B/C, 105, 115-124.
16. Van Liew, M. W., & Garbrecht, J. (2003). Hydrologic simulation of the little Washita river
experimental watershed using SWAT 1. JAWRA Journal of the American Water Resources
Association, 39(2), 413-426.
17. Verma, A. K., Jha, M. K., & Mahana, R. K. (2010). Evaluation of HEC-HMS and WEPP for
simulating watershed runoff using remote sensing and geographical information system. Paddy and
Water Environment, 8, 131-144.
18. Xu, Z. X., Pang, J. P., Liu, C. M., & Li, J. Y. (2009). Assessment of runoff and sediment yield in
the Miyun Reservoir catchment by using SWAT model. Hydrological Processes: An International
Journal, 23(25), 3619-3630.

Journal of Water Resource Engineering and Management
| Volume | 13 |
| Issue | 01 |
| Received | 06/12/2025 |
| Accepted | 21/01/2026 |
| Published | 24/01/2026 |
| Publication Time | 49 Days |
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