An automatic parameter calibration method for the SWAT model in runoff simulation

• Published in: River research and applications Vol. 36; no. 7; pp. 1321 - 1333
• Main Authors: Wang, Yongzhi, Zhu, Sijing, Yuan, Liu, Deng, Rui
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 01.09.2020; Wiley Subscription Services, Inc
• Subjects: Accuracy; Algorithms; automatic parameter calibration; Calibration; Computer simulation; Environmental monitoring; Feasibility studies; Flood control; Flood forecasting; Flood management; Flood peak; Forecasting; genetic algorithm; Genetic algorithms; Hydrologic models; Hydrologic research; Hydrology; Model accuracy; Parameters; Particle swarm optimization; particle swarm optimization method; Resource management; Runoff; runoff simulation; Simulation; Soil; Soil water; SWAT; Water management; Water resources; Water resources management
• ISSN: 1535-1459; 1535-1467
• DOI: 10.1002/rra.3655

Runoff simulation is highly significant for hydrological monitoring, flood peak simulation, water resource management, and basin protection. Runoff simulation by distributed hydrological models, such as the soil and water assessment tool (SWAT) model which is the most widely used, is becoming a hotspot for hydrological forecasting research. However, parameter calibration is inefficient and inaccurate for the SWAT model. An automatic parameter calibration (APC) method of the SWAT model was developed by hybrid of the genetic algorithm (GA) and particle swarm optimization (PSO). Multi‐station and multi‐period runoff simulation and accuracy analysis were conducted in the basin of the Zhangjiang River on the basis of this hybrid algorithm. For example, in the Yaoxiaba Station, the calibration results produced an R2 of 0.87 and Nash Sutcliffe efficiency (NSE) index of 0.85, while verification results revealed an R2 of 0.83 and NSE of 0.83. Results of this study show that the proposed method can effectively improve the efficiency and simulation accuracy of the model parameters. It can be concluded that the feasibility and applicability of GA‐PSO as an APC method for the SWAT model were confirmed via case studies. The proposed method can provide theoretical guidance for many hydrological research fields, such as hydrological simulation, flood prevention, and forecasting.