Grid-based spatially distributed hydrological modeling became feasible
along with advances in watershed routing scheme, remote sensing
technology, and computing resources. Such modeling is expected to be
common in routine hydrological analysis and watershed management
planning as it can maximize the use of spatial information and provide
the detailed picture of transport processes. However, the heavy
computational requirement and resulting long running time are still
barriers that prevent the spatially detailed modeling practices from
being employed widely, particularly in a fine-resolution large-scale
study. Parallelizing computational tasks has been successful in
mitigating the difficulty. We propose a noble way to improve the
simulation efficiency of direct runoff transport processes by carefully
grouping watershed areas based on the time-area routing scheme. The
proposed parallelization method was applied to simulating the runoff
routing processes of three watersheds draining the areas of 3.79 km2,
133.59 km2, and 2,800 km2 respectively at a 30-m resolution. Results
demonstrated that the new method could substantially improve the
computational efficiency of the time-area routing method with common
computing resources. The efficiency of the parallelization scheme was
not limited by the hierarchical relationship between upstream and
downstream catchments along flow paths, which could be possible with the
Lagrangian flow tracking strategy of the time-area routing method.