River water pollution incidents seriously threaten the ecological environment and people's health. Effective determination of the pollution source information contributes to minimizing the scope of water pollution incidents. A surface water pollution traceability model based on the social spider optimization algorithm and differential evolution algorithm was proposed to more accurately trace the pollution sources of surface water pollution events. The diffusion law of pollutants in rivers could be described by the migration and diffusion model. Relevant parameters (e.g., water flow velocity and river diffusion coefficient) varied depending on the season and weather. First, parameters in the migration and diffusion model were calibrated using the social spider optimization algorithm to coincide with the real hydrological environment. Then, the traceability of pollution source information was completed by simulating mutation, crossing, and selection between individuals based on a differential evolution algorithm, which obtained the optimal pollution source location, discharge volume, and discharge time. Finally, the relevant experiment data of the water pollution events between the Jingshi Section and the Puyang Section of the Waterproof River in Ref. [32] were used for simulation experiments. Results were compared with the probabilistic method and coupled density method in Ref. [32]. The average absolute errors of the two methods were 201.0 and 36.43, respectively. The error of the traceability results obtained by the traceability model in the work significantly decreased, with an average absolute error of 1.557. The SSO and DE algorithms had good convergence speed and global search capabilities. Besides, the DE algorithm is a multi-objective optimization algorithm solving multi-dimensional spatial data. Therefore, the surface water pollution traceability model had a high traceability accuracy and certain application value. It reduced the impact of water pollution on the environment and health by quickly responding to water pollution incidents.