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Soil hydrodynamic parameters are the basic parameters for simulating the process of soil material transport in the field. Accurate determination of soil hydrodynamic parameters is of great significance to achieve precise regulation of farmland habitat. For one-dimensional vertical infiltration experimental data,，based on algebraic and numerical methods, three different objective functions were constructed, and the applicability of the whale optimization algorithm and grey wolf optimizer was analyzed to invert the parameters of the Brooks-Corey-Mualem model. The result showed that by choosing an appropriate objective function, both swarm intelligence optimization algorithms can be used to invert soil hydrodynamic parameters. In the algebraic method, the whale optimization algorithm optimized the soil hydrodynamic parameters with the fixed parameters θr and θs under the objective function two (relative error composed of cumulative infiltration, time, and soil water content profiles) with the smallest error. The relative errors of the cumulative infiltration volume, infiltration rate, and soil water content profiles obtained from the inversion parameters were all below 9.74%, the determination coefficients were all above 0.9040, and the inversion time was 70s. In the numerical method, the parameter error derived from the fixed parameters θr and θs under the objective function three (relative error composed of cumulative infiltration, depth of wetting front, and soil water content profile) of the grey wolf optimizer was the smallest. The relative errors of the cumulative infiltration volume, infiltration rate, and soil water content profiles obtained from the inversion parameters were all below 2.53%, the determination coefficients were all above 0.9917, and the inversion time was 115s. Therefore, the algebraic method took a short time and has relatively low accuracy, while the numerical method took a long time and has a relatively high accuracy. When inverting soil hydrodynamic parameters, an appropriate optimization method can be selected according to the error accuracy requirements.