RunCA: a cellular automata model for simulating surface runoff at different scales

Shao, Qi, Weatherley, Dion, Huang, Longbin and Baumgartl, Thomas (2015) RunCA: a cellular automata model for simulating surface runoff at different scales. Journal of Hydrology, 529 P3: 816-829. doi:10.1016/j.jhydrol.2015.09.003


Author Shao, Qi
Weatherley, Dion
Huang, Longbin
Baumgartl, Thomas
Title RunCA: a cellular automata model for simulating surface runoff at different scales
Journal name Journal of Hydrology   Check publisher's open access policy
ISSN 0022-1694
Publication date 2015-10-01
Year available 2015
Sub-type Article (original research)
DOI 10.1016/j.jhydrol.2015.09.003
Open Access Status Not Open Access
Volume 529
Issue P3
Start page 816
End page 829
Total pages 14
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Collection year 2016
Language eng
Abstract The Runoff Model Based on Cellular Automata (RunCA) has been developed to simulate surface runoff at different scales by integrating basic cellular automata (CA) rules with fundamental measureable hydraulic properties. In this model, a two-dimensional lattice composed of a series of rectangular cells was employed to cover the study area. Runoff production within each cell was simulated by determining the cell state (height) that consists of both cell elevation and water depth. The distribution of water flow among cells was determined by applying CA transition rules based on the minimization-of-difference algorithm and the calculated spatially varied flow velocities. RunCA was verified and validated by three steps. Good agreement with the analytical solution was achieved under simplified conditions in the first step. Then, results from runoff experiments on small laboratory plots (2 m × 1 m) showed that the model was able to well predict the hydrographs, with the mean Nash–Sutcliffe efficiency greater than 0.90. RunCA was also applied to a large scale site (Pine Glen Basin, USA) with data taken from literature. The predicted hydrograph agreed well with the measured results. Simulated flow maps in this basin also demonstrated the model capability in capturing both the spatial and temporal variations in the runoff process. Model sensitivity analysis results showed that the calculated total runoff and total infiltration were most sensitive to the input parameters representing the final steady infiltration rate at both scales. The Manning’s roughness coefficient and the setting of cell size did not affect the results much at the small plot scale, but had large influences at the large basin scale.
Keyword Runoff modeling
Cellular automata
Model validation
Scale
Infiltration
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Centre for Mined Land Rehabilitation Publications
Julius Kruttschnitt Mineral Research Centre Publications
Official 2016 Collection
 
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