Evaluation of the performance of SWAT model in simulating the inflow to the dam reservoir to deal with climate change (Case study: the catchment area upstream of the ZayandehRoud Dam)

Document Type : Original Article


1 Master's degree, civil engineering, water resources engineering and management, Yasouj University

2 Assistant Professor, Department of Civil Engineering, Water Resources Engineering and Management, Yasouj University

3 Professor, Department of Water Engineering, Faculty of Agriculture, Isfahan University of Technology, Isfahan, Iran

4 Master's degree, civil engineering, water resources engineering and management, Yasouj University


Climate change is one of the biggest challenges facing humanity that affects the sciences related to nature and environment. Changes in factors affecting climate change affect the hydrological responses of watersheds and this phenomenon affects the quantity and quality of water resources such as lakes, reservoirs and dams. Today, the development and progress of computer and computing technologies has had a significant impact on hydrological modeling. In recent years, conceptual and physical models based on the characteristics of watersheds for hydrological systems have attracted the attention of researchers. Due to the emergence of such developments, there will be complications in the process of hydrological modeling. Correct management forecasts in the field of water resources due to the lack of water resources, is one of the topics of interest in the institutions in charge of water resources management, which should use high-precision simulator models for long-term estimates and planning. Considering the crisis and shortage of water resources in Iran, the sub-catchment upstream of Zayandeh Rood Dam was selected as a case study in this research, and the hydrological processes in the sub-basins of Zayandeh Rood Dam were simulated and the inflow to the reservoir of Zayandeh Rood Dam was estimated. For this purpose, the water and soil assessment model SWAT has been used to simulate the rainfall-runoff process and finally to estimate the inflow to the reservoir. Based on the simulated runoff from the three sub-basins of Buin-Damneh, Qala Shahrokh-Chelgerd and Chadegan-Ceshmeh, the model showed acceptable results for the simulation in the three sub-basins mentioned by the model, and it was estimated from the algebraic sum of the three inflows that the mentioned error coefficients are equal to 0.86 has been obtained. This result shows the high accuracy of the models in the simulation


  1. Aawar, T. and Khare, D. (2020) ‘Assessment of climate change impacts on streamflow through hydrological model using SWAT model: a case study of Afghanistan’, Modeling Earth Systems and Environment, 6(3), 1427–1437.
  2. Akoko, G. et al. (2021). ‘A review of SWAT model application in Africa’, Water, 13(9), p. 1313.
  3. Bouslihim, Y. et al. (2019). ‘Understanding the effects of soil data quality on SWAT model performance and hydrological processes in Tamedroust watershed (Morocco)’, Journal of African Earth Sciences, 160, p. 103616.
  4. Dhami, B. et al. (2018). ‘Evaluation of the SWAT model for water balance study of a mountainous snowfed river basin of Nepal’, Environmental Earth Sciences, 77(1), 1–20.
  5. Hallouz, F. et al. (2018). ‘Modeling of discharge and sediment transport through the SWAT model in the basin of Harraza (Northwest of Algeria)’, Water Science, 32(1), 79–88.
  6. Himanshu, S.K. et al. (2019). ‘Evaluation of best management practices for sediment and nutrient loss control using SWAT model’, Soil and Tillage Research, 192, 42–58.
  7. Jeon, D.J. et al. (2019). ‘Evaluating the influence of climate change on the fate and transport of fecal coliform bacteria using the modified SWAT model’, Science of the Total Environment, 658, pp. 753–762.
  8. Khalili, R., Parvinnia, M. and Motaghi, H. (2021) ‘The effects of forecasted precipitation amount on probable maximum precipitation and probable maximum flood parameters’, Journal of Environmental Science Studies, 5(4), pp. 2982–2989. Available at: http://www.jess.ir/article_113402.html.
  9. Khalili, R. et al. (2021) ‘Simultaneous removal of binary mixture dyes using Mn - Fe layered double hydroxide coated chitosan fibers prepared by wet spinning’, Surfaces and Interfaces, p. 100976. doi: https://doi.org/10.1016/j.surfin.2021.100976.
  10. Khalili, R. Montaseri, H. and Motaghi, H. (2021) ‘Evaluation of water quality in the Chalus River using the statistical analysis and water quality index (WQI)’, Water and Soil Management and Modelling. doi: 10.22098/ mmws.2021.9300.1031.
  11. Khalili, R., Zali, A. and Motaghi, H. (2021) ‘Evaluating the Heavy Metals in the Water and Sediments of Haraz River, Using Pollution Load Index (PLI) and Geo accumulation Index (Igeo)’, Iranian Journal of Soil and Water Research. doi: 10.22059/ijswr.2021.316080.668850.
  12. Li, C. and Fang, H. (2021) ‘Assessment of climate change impacts on the streamflow for the Mun River in the Mekong Basin, Southeast Asia: Using SWAT model’, Catena, 201, p. 105199.
  13. Li, M., Di, Z. and Duan, Q. (2021) ‘Effect of sensitivity analysis on parameter optimization: case study based on streamflow simulations using the SWAT model in China’, Journal of Hydrology, 603, p. 126896.
  14. Van Liew, M.W., Arnold, J.G. and Bosch, D.D. (2005) ‘Problems and potential of autocalibrating a hydrologic model’, Transactions of the ASAE, 48(3), pp. 1025–1040.
  15. Luan, X. et al. (2018) ‘Quantitative study of the crop production water footprint using the SWAT model’, Ecological Indicators, 89, pp. 1–10.
  16. Mahaffey, C. et al. (2020). ‘Impacts of climate change on dissolved oxygen concentration relevant to the coastal and marine environment around the UK’, MCCIP Science Review 2020, pp. 31–53.
  17. Mahtsente, T., Assefa, M. M. and Dereje, H. (2017). ‘Rainfall-runoff relation and runoff estimation for Holetta River, Awash subbasin, Ethiopia using SWAT model’, International Journal of Water Resources and Environmental Engineering, 9(5),. 102–112.
  18. Mehrparvar, M., Asghari, K. and Golmohammadi, M.H. (2019). ‘Reducing Error of Rainfall-Runoff Simulation Using Coupled Hydrological SWAT Model and Data Assimilation Technique’, Iran-Water Resources Research, 14(5), pp. 85–102. Available at: http://www.iwrr.ir/article_65744.html.
  19. Mengistu, A.G., van Rensburg, L.D. and Woyessa, Y.E. (2019). ‘Techniques for calibration and validation of SWAT model in data scarce arid and semi-arid catchments in South Africa’, Journal of Hydrology: Regional Studies, 25, p. 100621.
  20. Mohammadi, H., khalili, R. and Mohammadi, S. (2021). ‘Forecasting future temperature and precipitation under the effects of climate change using the LARS-WG climate generator (Case Study: South Zagros Region of Iran(’, Nivar, 45(114–115), pp. 137–153. doi: 10.30467/nivar.2022.319565.1209.
  21. Myers, D. T., Ficklin, D. L. and Robeson, S. M. (2021). ‘Incorporating rain-on-snow into the SWAT model results in more accurate simulations of hydrologic extremes’, Journal of Hydrology, 603, p. 126972.
  22. Oo, H.T., Zin, W.W. and Kyi, C.C.T. (2020). ‘Analysis of streamflow response to changing climate conditions using SWAT model’, Civil Engineering Journal, 6(2), pp. 194–209.
  23. Pang, S. et al. (2020). ‘Development and testing of a modified SWAT model based on slope condition and precipitation intensity’, Journal of Hydrology, 588, p. 125098.
  24. Saade, J. et al. (2021). ‘Modeling Impact of Climate Change on Surface Water Availability Using SWAT Model in a Semi-Arid Basin: Case of El Kalb River, Lebanon’, Hydrology, 8(3), p. 134.
  25. Senent-Aparicio, J. et al. (2019). ‘Coupling machine-learning techniques with SWAT model for instantaneous peak flow prediction’, Biosystems engineering, 177, pp. 67–77.
  26. Shi, W. and Huang, M. (2021). ‘Predictions of soil and nutrient losses using a modified SWAT model in a large hilly-gully watershed of the Chinese Loess Plateau’, International Soil and Water Conservation Research, 9(2), pp. 291–304.
  27. Vilaysane, B. et al. (2015). ‘Hydrological stream flow modelling for calibration and uncertainty analysis using SWAT model in the Xedone river basin, Lao PDR’, Procedia Environmental Sciences, 28, pp. 380–390.
  28. Wang, Y. et al. (2019). ‘Soil and water assessment tool (SWAT) model: A systemic review’, Journal of Coastal Research, 93(SI), pp. 22–30.
  29. Wu, J. et al. (2019). ‘Assessing the impact of human regulations on hydrological drought development and recovery based on a ‘simulated-observed’comparison of the SWAT model’, Journal of Hydrology, 577, 123990.
  30. Yuan, Y. and Koropeckyj-Cox, L. (2022). ‘SWAT model application for evaluating agricultural conservation practice effectiveness in reducing phosphorous loss from the Western Lake Erie Basin’, Journal of Environmental Management, 302, p. 114000.
  31. Zhang, H. et al. (2020). ‘Using an improved SWAT model to simulate hydrological responses to land use change: A case study of a catchment in tropical Australia’, Journal of Hydrology, 585, p. 124822.