Articles | Volume 14, issue 10
Geosci. Model Dev., 14, 5915–5925, 2021
Geosci. Model Dev., 14, 5915–5925, 2021

Development and technical paper 30 Sep 2021

Development and technical paper | 30 Sep 2021

GP-SWAT (v1.0): a two-level graph-based parallel simulation tool for the SWAT model

Dejian Zhang et al.

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Cited articles

Cai, X., Yang, Z.-L., Fisher, J. B., Zhang, X., Barlage, M., and Chen, F.: Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions, Geosci. Model Dev., 9, 1–15,, 2016. 
Chandra, R., Azam, D., Kapoor, A., and Müller, R. D.: Surrogate-assisted Bayesian inversion for landscape and basin evolution models, Geosci. Model Dev., 13, 2959–2979,, 2020. 
Ercan, M. B., Goodall, J. L., Castronova, A. M., Humphrey, M., and Beekwilder, N.: Calibration of SWAT models using the cloud, Environ. Modell. Softw., 62, 188–196,, 2014. 
Fang, Y., Chen, X., Gomez Velez, J., Zhang, X., Duan, Z., Hammond, G. E., Goldman, A. E., Garayburu-Caruso, V. A., and Graham, E. B.: A multirate mass transfer model to represent the interaction of multicomponent biogeochemical processes between surface water and hyporheic zones (SWAT-MRMT-R 1.0), Geosci. Model Dev., 13, 3553–3569,, 2020. 
Gorgan, D., Bacu, V., Mihon, D., Rodila, D., Abbaspour, K., and Rouholahnejad, E.: Grid based calibration of SWAT hydrological models, Nat. Hazards Earth Syst. Sci., 12, 2411–2423,, 2012. 
Short summary
GP-SWAT is a two-layer model parallelization tool for a SWAT model based on the graph-parallel Pregel algorithm. It can be employed to perform both individual and iterative model parallelization, endowing it with a range of possible applications and great flexibility in maximizing performance. As a flexible and scalable tool, it can run in diverse environments, ranging from a commodity computer with a Microsoft Windows, Mac or Linux OS to a Spark cluster consisting of a large number of nodes.