Calibration and validation of the SWAT model for Upper Bernam River Basin in Malaysia

User Rating:  / 0
PoorBest 

Authors:


M. D. Zakari*, orcid.org/0000-0001-9681-2254, University Putra Malaysia, Faculty of Engineering, Department of Biological and Agricultural Engineering, Serdang, Malaysia; Bayero University Kano, Faculty of Engineering, Agricultural and Environmental Engineering Department, Kano, Nigeria, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Md R. Kamal*, orcid.org/0009-0008-0750-905X, University Putra Malaysia, Faculty of Engineering, Department of Biological and Agricultural Engineering, Serdang, Malaysia, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

N. M. Ramli, orcid.org/0000-0002-8640-1598, University Putra Malaysia, Faculty of Engineering, Department of Biological and Agricultural Engineering, Serdang, Malaysia

B. M. Rehan, orcid.org/0000-0002-9404-0809, University Putra Malaysia, Faculty of Engineering, Department of Civil Engineering, Serdang, Malaysia

M. S. F. Bin Mohd, orcid.org/0000-0002-2050-6071, National Water Research Institute of Malaysia, River Basin Research Centre, Seri Kembangan, Malaysia

* Corresponding authors e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.; This email address is being protected from spambots. You need JavaScript enabled to view it.


повний текст / full article



Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2025, (6): 168 - 178

https://doi.org/10.33271/nvngu/2025-6/168



Abstract:



Purpose.
The calibration and validation of the Soil and Water Assessment Tool (SWAT) model are essential to ensure its accuracy in simulating hydrological processes for effective decision-making. This study focuses on the Upper Bernam River Basin (UBRB) in Malaysia, where the SWAT model was calibrated and validated using observed streamflow data from 1985 to 2022.


Methodology.
Calibration and validation were performed in three categories: category 1 (10-year calibration, 5-year validation), category 2 (15-year calibration, 10-year validation), and category 3 (20-year calibration, 10-year validation).


Findings.
Statistical indices for category 1 indicated a satisfactory model performance, with calibration results showing a p-factor of 0.82, r-factor of 0.88, R2 of 0.72, NSE of 0.70, PBIAS of -1.1 %, and KGE of 0.85. Validation results indicated a p-factor of 0.80, r-factor of 1.04, R2 of 0.75, NSE of 0.65, PBIAS of -6.6 %, and KGE of 0.79. Moreover, the results from category 1 showed better performance over the other categories indicating that simulation length does not usually improve data quality or model performance. The 15-year model setup for category 1 was subjected to water balance evaluation and the result shows that the simulated inflow (precipitation) and outflow (water yield + ET) differences for 1991‒2005 and 2006‒2020 were 9.8 and 11.5 %, respectively.


Originality.
This study uniquely applies long-term observed streamflow data and multi-scenario calibration-validation to improve SWAT model reliability for simulating hydrology in the Upper Bernam River Basin.


Practical values.
This study demonstrates the SWAT model’s reliability in predicting agro-hydrological processes and provides insights into sustainable agricultural water management in UBRB.



Keywords:
SWAT model, calibration, validation, Upper Bernam River Basin (UBRB), streamflow, agricultural water management

References.


1. Mustafa, Y., Amin, M., Lee, T., & Shariff, A. (2012). Evaluation of land development impact on a tropical watershed hydrology using remote sensing and GIS. Journal of spatial hydrology, 5(2), 1.

2. Hashim, M., Nayan, N., Setyowati, D. L., Said, Z. M., Mahat, H., & Saleh, Y. (2021). Analysis of water quality trends using the Mann-Kendall test and Sen’s Estimator of Slope in a tropical river basin. Pollution, 7(4), 933-942. https://doi.org/10.22059/poll.2021.325794.1118

3. Ahmed, F., Siwar, C., & Begum, R.A. (2014). Water resources in Malaysia: Issues and challenges. Journal of Food, Agriculture and Environment, 12(2), 1100-1104.

4. Tran, H. Q., & Fehér, Z. Z. (2022). Water balance calculation capability of hydrological models. Acta Agraria Kaposváriensis, 26(1), 37-53. https://doi.org/10.31914/aak.2877

5. Gujree, I., Zhang, F., Meraj, G., Farooq, M., Muslim, M., & Arshad, A. (2022). Soil and Water Assessment Tool for Simulating the Sediment and Water Yield of Alpine Catchments: A Brief Review. Geospatial Modeling for Environmental Management, 37-57. https://doi.org/10.1201/9781003147107-4

6. Das, S. K., Ahsan, A., Khan, M. H. R. B., Yilmaz, A. G., Ahmed, S., Imteaz, M., …, & Al-Ansari, N. (2024). Calibration, validation and uncertainty analysis of a SWAT water quality model. Applied Water Science, 14(4), 86. https://doi.org/10.1007/s13201-024-02138-x

7. Dlamini, N. S., Kamal, M. R., Soom, M. A. B. M., Faisal bin Mohd, M. S., Abdullah, A. F. B., & Hin, L. S. (2017). Modeling potential impacts of climate change on streamflow using projections of the 5th assessment report for the Bernam River Basin, Malaysia. Water, 9(3), 226. https://doi.org/10.3390/w9030226

8. Kondum, F., Rowshon, M. K., Luqman, C., Hasfalina, C., & Zakari, M. (2024). Change analyses and prediction of land use and land cover changes in Bernam River Basin, Malaysia. Remote Sensing Applications: Society and Environment, 36, 101281. https://doi.org/10.1016/j.rsase.2024.101281

9. Ismail, H., Kamal, M. R., Abdullah, A. F. B., Jada, D. T., & Sai Hin, L. (2020). Modeling Future Streamflow for Adaptive Water Allocation under Climate Change for the Tanjung Karang Rice Irrigation Scheme Malaysia. Applied Sciences, 10(14), 4885. https://doi.org/10.3390/app10144885

10.      Saadati, Z., Pirmoradian, N., & Rezaei, M. (2011). Calibration and evaluation of aqua crop model in rice growth simulation under different irrigation managements. ICID 21 st International Congress on Irrigation and Drainage, 589-600.

11.      Rowshon, M. K., Dlamini, N. S., Mojid, M. A., Adib, M., Amin, M. S. M., & Lai, S. H. (2019). Modeling climate-smart decision support system (CSDSS) for analyzing water demand of a large-scale rice irrigation scheme. Agricultural Water Management, 216, 138-152. https://doi.org/10.1016/j.agwat.2019.01.002

12.      Dile, Y. T., Daggupati, P., George, C., Srinivasan, R., & Arnold, J. (2016). Introducing a new open source GIS user interface for the SWAT model. Environmental Modelling & Software, 85, 129-138. https://doi.org/10.1016/j.envsoft.2016.08.004

13.      Winchell, M. F., Folle, S., Meals, D., Moore, J., Srinivasan, R., & Howe, E. A. (2015). Using SWAT for sub-field identification of phosphorus critical source areas in a saturation excess runoff region. Hydrological Sciences Journal, 60(5), 844-862. https://doi.org/10.1080/02626667.2014.980262

14.      Kmoch, A., Moges, D. M., Sepehrar, M., Narasimhan, B., & ­Uuemaa, E. (2022). The Effect of Spatial Input Data Quality on the Performance of the SWAT Model. Water, 14(13), 1988. https://doi.org/10.3390/w14131988

15.      Abbaspour, K. C. (2015). SWAT calibration and uncertainty programs. A user manual, 103, 17-66.

16.      Bilondi, M. P., & Abbaspour, K. C. (2013). Application of three different calibration-uncertainty analysis methods in a semi-distributed rainfall-runoff model application. Middle-East Journal of Scientific Research, 15.

17.      Abbaspour, K. C., Vaghefi, S. A., & Srinivasan, R. (2017). A guideline for successful calibration and uncertainty analysis for soil and water assessment: a review of papers from the 2016 international SWAT conference. Water journal, 10(1), 6. https://doi.org/10.3390/w10010006

18.      Tudaji, M., Nan, Y., & Tian, F. (2025). Assessing the value of high-resolution data and parameter transferability across temporal scales in hydrological modeling: a case study in northern China. Hydrology and Earth System Sciences, 29(12), 2633-2654. https://doi.org/10.5194/hess-29-2633-2025

19.      Abbaspour, K. (2020). SWAT-CUP Tutorial (2): Introduction to SWAT-CUP program. Parameter Estimator (SPE).

20.      Janjić, J., & Tadić, L. (2023). Fields of application of SWAT hydrological model – a review. Earth, MDPI, 4(2), 331-344. https://doi.org/10.3390/earth4020018

21.      Neitsch, S. L., Arnold, J. G., Kiniry, J. R., & Williams, J. R. (2011). Soil and water assessment tool theoretical documentation version 2009.

22.      Abbaspour, K. C. (2022). The fallacy in the use of the “best-fit” solution in hydrologic modeling. Science of The Total Environment, 802, 149713. https://doi.org/10.1016/j.scitotenv.2021.149713

23.      Mollel, G. R., Mulungu, D. M., Nobert, J., & Alexander, A. C. (2023). Assessment of climate change impacts on hydrological processes in the Usangu catchment of Tanzania under CMIP6 scenarios. Journal of Water and Climate Change, 14(11), 4162-4182. https://doi.org/10.2166/wcc.2023.542

24.      Moriasi, D. N., Gitau, M. W., Pai, N., & Daggupati, P. (2015). Hydrologic and water quality models: Performance measures and evaluation criteria. Transactions of the ASABE, 58(6), 1763-1785. https://doi.org/10.13031/trans.58.10715

25.      Khalid, K., Ali, M., Rahman, N., Mispan, M., Rasid, M., Haron, S., & Mohd, M. (2015). Optimization of spatial input parameter in distributed hydrological model. ARPN J Eng Appl Sci, 10(15), 6628-6633.

26.      Phomcha, P., Wirojanagud, P., Vangpaisal, T., & Thaveevouthti, T. (2011). Predicting sediment discharge in an agricultural watershed: a case study of the Lam Sonthi watershed, Thailand. Science Asia, 37, 43-50. https://doi.org/10.2306/scienceasia1513-1874.2011.37.043

27.      Apostel, A., Kalcic, M., Dagnew, A., Evenson, G., Kast, J., King, K., …, & Scavia, D. (2021). Simulating internal watershed processes using multiple SWAT models. Science of The Total Environment, 759, 143920. https://doi.org/10.1016/j.scitotenv.2020.143920

28.      Gyamfi, C., Ndambuki, J. M., & Salim, R. W. (2016). Application of SWAT model to the Olifants Basin: calibration, validation and uncertainty analysis. Journal of Water Resource and Protection, 8(03), 397. https://doi.org/10.4236/jwarp.2016.83033

29.      Hafiz, I., Nor, N., Sidek, L., Basri, H., & Hanapi, M. (2013). Application of integrated flood analysis system (IFAS) for Dungun River Basin. IOP Conference Series: Earth and Environmental Science. https://doi.org/10.1088/1755-1315/16/1/012128

30.      Manisha, K., Dhakal, N. R., Aryal, I., & Marahatta, S. (2023). Application of SWAT hydrological model to simulate flow of Seti-Gandaki Basin. Jalawaayu, 3(1), 43-62. https://doi.org/10.3126/jalawaayu.v3i1.52060

 

Guest Book

If you have questions, comments or suggestions, you can write them in our "Guest Book"

Registration data

ISSN (print) 2071-2227,
ISSN (online) 2223-2362.
Journal was registered by Ministry of Justice of Ukraine.
Registration number КВ No.17742-6592PR dated April 27, 2011.

Contacts

D.Yavornytskyi ave.,19, pavilion 3, room 24-а, Dnipro, 49005
Tel.: +38 (066) 379 72 44.
e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
You are here: Home Home EngCat Archive 2025 Content №6 2025 Calibration and validation of the SWAT model for Upper Bernam River Basin in Malaysia