Hydrological Simulation of Bakhtegan Basin in Iran Using the SWAT Model

Document Type : Research Paper


1 PhD candidate of water resources engineering, Faculty of Water & Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

2 Associate professor, Faculty of Water & Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

3 Assistant professor, Faculty of Water & Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.


Continuous-time, distributed parameter hydrologic models like SWAT have opened several opportunities to boost watershed modeling accuracy. This study has described the essential parameterization issues involved when predicting watershed stream runoff using SWAT. Understanding these issues is expected to guide to improved SWAT runoff prediction performance. This research describes the important parameterization issues involved when modeling watershed hydrology for runoff prediction using SWAT, emphasizing the thanks to improving model performance without resorting to the tedious and arbitrary parameter by parameter calibration. The Bakhtegan watershed was used to illustrate runoff prediction's sensitivity to spatial variability, watershed decomposition, and spatial and temporal adjustment of curve numbers and return flow contribution. The SWAT model finishes hydrological simulation with good performance calibration (2006 to 2012) and validation (2013) periods. SWAT was also conversant in predict runoff from Bakhtegan that has extensive subsurface drainage. If properly validated, the study showed that the SWAT model would be used effectively in testing management scenarios within the Bakhtegan watershed. The result showed that the Nash–Sutcliffe of calibration and the validation between simulated and observed are 0.71 and 0.74, respectively. The SWAT model application, supported by GIS technology, proved to be a flexible and reliable water decision-making tool.


Main Subjects

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Volume 44, Issue 2
September 2021
Pages 39-51
  • Receive Date: 06 March 2021
  • Revise Date: 25 May 2021
  • Accept Date: 31 May 2021
  • Publish Date: 22 June 2021