Parallel computing is a primary way to increase computing efficiency of grid-based distributed hydrological models. This study proposed an automatic partition-based parallel algorithm (APPA) to approach the theoretical maximum speedup ratio (TMSR). Through a combination of flexible partition for the domain decomposition and the load balance of parallel simulation, APPA optimizes the parallelization of hillslope and channel flow routing processes at sub-basin and channel unit level, respectively. To illustrate APPA's performance, we embedded it in a distributed ecohydrological model, and then applied the updated model to three watersheds at different spatial scales. The results indicate that APPA effectively promoted parallel performance. The estimated speedup ratio approached 93–97% of the TMSR for simulating hillslope processes and 91–98% of the TMSR for simulating channel processes using 26-threads in all three watersheds. These improvements justify that APPA is effective in accelerating model simulation and thus benefits future model-based research.