A Vector‐Based River Routing Model for Earth System Models: Parallelization and Global Applications

• Published in: Journal of advances in modeling earth systems Vol. 13; no. 6
• Main Authors: Mizukami, Naoki, Clark, Martyn P., Gharari, Shervan, Kluzek, Erik, Pan, Ming, Lin, Peirong, Beck, Hylke E., Yamazaki, Dai
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 01.06.2021; American Geophysical Union (AGU)
• Subjects: Atmospheric forcing; Boxes; Catchment area; Connectivity; Costs; Datasets; Decomposition; Earth System modeling; Efficiency; Hydrologic networks; Lakes; Land surface models; parallel computing; Physical properties; Polygons; river; River basins; River networks; Rivers; Runoff; Scaling; Simulation; Stream discharge; Stream flow; Surface runoff; Tributaries
• ISSN: 1942-2466; 1942-2466
• DOI: 10.1029/2020MS002434

A vector‐river network explicitly uses realistic geometries of river reaches and catchments for spatial discretization in a river model. This enables improving the accuracy of the physical properties of the modeled river system, compared to a gridded river network that has been used in Earth System Models. With a finer‐scale river network, resolving smaller‐scale river reaches, there is a need for efficient methods to route streamflow and its constituents throughout the river network. The purpose of this study is twofold: (1) develop a new method to decompose river networks into hydrologically independent tributary domains, where routing computations can be performed in parallel; and (2) perform global river routing simulations with two global river networks, with different scales, to examine the computational efficiency and the differences in discharge simulations at various temporal scales. The new parallelization method uses a hierarchical decomposition strategy, where each decomposed tributary is further decomposed into many sub‐tributary domains, enabling hybrid parallel computing. This parallelization scheme has excellent computational scaling for the global domain where it is straightforward to distribute computations across many independent river basins. However, parallel computing for a single large basin remains challenging. The global routing experiments show that the scale of the vector‐river network has less impact on the discharge simulations than the runoff input that is generated by the combination of land surface model and meteorological forcing. The scale of vector‐river networks needs to consider the scale of local hydrologic features such as lakes that are to be resolved in the network. Plain Language Summary This study introduces a parallel computing method for river models that simulate discharges at many nested river reaches. The new parallelization method enables us to reduce the computation time over the global domain including numerous independent river basins, but we face difficulty in reducing the computation time for simulations over single river basins even using increased computing resources. Nevertheless, the improved computational efficiency enables us to perform a series of daily global river discharge simulations, one of which simulates at ∼3 million reaches. We found that the simulation using coarser scale river data including 300,000 reaches were more similar to the results with the fine‐scale data for longer time scale analysis such as annual scale than the daily scale analysis. Key Points Hierarchical river network decomposition enables hybrid parallel computing and improves the computational efficiency of global river models Runoff input and routing schemes have larger impacts on river flow simulations than the vector river network with different catchment scales The scale of vector river networks needs to consider the scale of local hydrologic features such as lakes that are to be resolved