A common parallel computing framework for modeling hydrological processes of river basins

Restricted computing power has become one of the primary factors obstructing advancement in basin simulations for majority of hydrological models. Parallel computing is one of the most available approaches to solve this problem. Using binary-tree theory, we present in this study a common parallel computing framework based on the message passing interface (MPI) protocol for modeling hydrological processes of river basins. A practical and dynamic spatial domain decomposition method, based on the binary-tree structure of the drainage network, is proposed. This framework is computationally efficient, and is independent of the type of physical models chosen. The framework is tested in the Chabagou river basin of China, where two years of runoff processes of the entire basin were simulated. Results demonstrate that the system may provide efficient computing performance. However, primarily because of the constraint of the binary-tree structure for drainage network, this study finds that unlimited enhancement of computing efficiency is impossible to realize.