It is the key to numerical modeling of water and solute transportation in unsaturated soil to identify parameters of the transportation. Based on the vertical one-dimensional equation for transportation of water-solute in unsaturated adsorptive soil, a multi-target optimized model for identification of parameters of water-solute transportation was established, using KBr as infiltration solution and the minimum standard deviations between measured and observed values of water content and solute concentration as targets of optimization. The multi-target optimization issue was converted into a single-target one, with the weight coefficient method. The particle swarm optimization (PSO) algorithm of dynamic weight and asynchronous time-varying learning factors was used to solve the model. A soil column experiment was conducted in lab to determine water content and spatial distribution of K+ at the time of 220,380 and 780 minutes, separately. The data of the first two time groups were used for identification of parameters, and those of the third group for validation. Results show that the correlation coefficient between measured and calculated values of water content and K+ concentration was 0.977 and 0.952, when the weight coefficient of the treatment of 780 min infiltration was 0.5, demonstrating that they are well dovetailed and that it is feasible to use PSO to identify soil transportation parameters of water and solute in the soil. The numerical simulation indicates that the higher the weight, the higher the correlation coefficient between measured and calculated values of water content and the lower the correlation coefficient between measured and calculated values of K+ concentration.