In this study, an improved multi-scale algorithm was developed to analyze the effects of temperature on the bioclogging processes at pore and Representative Elementary Volume (REV) scales. In this algorithm, Immersed Boundary-Lattice Boltzmann Method- Cellular Automata (IB-LBM-CA) model for pore-scale simulation and Discrete Unified Gas-Kinetic Scheme-Cellular Automata (DUGKS-CA) model for REV simulation were coupled with the porosity and permeability obtained at pore-scale simulation as connecting bridge. In this study, a biofilm detachment model with non-Newtonian shear-thinning characteristics was considered, and also the tendency of high nutrient concentration for microbes and the inoculation rates of microbes were taken into account. The simulation results had been validated by laboratory percolation experiments with a high consistence. The main results are as follows: (1) At the pore scale, as the temperature increased, the clogging time decreased, the proportion of the clogging time occupied by slow decline period decreased and the proportion of the clogging time taken by rapid decline period increased. (2) At the REV scale, the clogging time decreased with the increasing temperature and inoculation rate. The relationship between clogging time and inoculation rate could be described by an exponential decay model. (3) A linear relationship was found between the clogging time at the pore and REV scales, and the proportion coefficient decreased as the inoculation rate increased. The influences of inoculation rates and temperatures on the clogging time proportion coefficients could be described by exponential decay model and linear decay model, respectively. The average exponential decay rate of clogging time proportion coefficient for the inoculation rate is 0.54 / % and the linear decay rates of clogging time proportion coefficient for the temperature are mainly decreased with increasing inoculation rate.