A two-level parallelization method for distributed hydrological models

This paper proposes a scalable two-level parallelization method for distributed hydrological models that can use parallelizability at both the sub-basin level and the basic simulation-unit level (e.g., grid cell) simultaneously. This approach first uses the message-passing programming model to dispatch parallel tasks at the sub-basin level to different nodes with multi-core CPUs in the cluster. Each node is responsible for some of the sub-basins. Parallel tasks for each sub-basin at the basic simulation-unit level are then dispatched to multiple cores within each node using the shared-memory programming model. A grid-based distributed hydrological model was parallelized to demonstrate the performance of the proposed method, which was tested in different scenarios (e.g., different data volume, different numbers of sub-basins). Results show that the proposed two-level parallelization method had better scalability than the parallel computation at sub-basin level alone, and the parallel performance increased with data volume and the number of sub-basins.