KINEROS2 calibration using particle swarm optimization in hydroPSO environment (Case study: Tamar watershed, Golestan, Iran)

Simulation of rainfall-runoff process for planning and management of water resources and watersheds, requires the use of a conceptual hydrological models, and play an important role in predicting theresponse to management scenarios in different climatic areas. In this study, the hydroPSO package wasused to assess parameter identification and uncertainty for the KINEROS2 model applied in the Tamar watershed, Iran. Sixteen parameters were selected based on previous studies and parameter sensitivity analysis. According to validation metrics, results indicate better efficiency of K2 based on the event #٢.The coefficient of determination (R2) resulting by comparison of simulated flow and measured flow is equal to 0.9٠٨٤. The events #٣ and #4 with NSE equal to 0.٨٩ and 0.٨٦ had the excellent and very good fitness of simulated flow compared to observed flow, respectively. Sensitivity analysis shows that theparameters Ks_p, Ks_c, n_p, n_c, CV_p, and Sat were the most effective parameters in K2 calibration, respectively. The posterior distributions of some parameters such as Ks_p and n_c appear to be more sharply peaked than other parameters which establishes less uncertainty in hydrological modeling. Visual inspection of Boxplots shows that for 6 out of 16 parameters (Ks_c, n_c, G_c, Rock,Dist_c and Smax) the optimum value found during the optimization coincides with the median of all the sampled values confirming that most of the particles converged into a small region of the solution space. For In and Sat, sampled values were placed within the second quartile. Dotty plots show that the optimumvalues found for Ks_p, Ks_c, and n_c define a narrow range of the parameter space with high modelperformance. On the other hand, the model performance is more impacted by the interaction of Ks and n parameters. The parameters CV_p and n_p show a wider range of the optimized levels. Good model performance for a wide range of values of other parameters confirms that these parameters are not well identified.

Keywords:

KINEROS2 , rainfall-runoff , simulation , particle swarm optimization (PSO)