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The simulation of surface flow dynamics using a flow-path network model

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This paper proposes a flow-path network (FPN) model to simulate complex surface flow based on a drainage-constrained triangulated irregular network (TIN). The TIN was constructed using critical points and drainage lines extracted from a digital terrain surface. Runoff generated on the surface was simplified as ‘water volumes’ at constrained random points that were then used as the starting points of flow paths (i.e. flow source points). The flow-path for each ‘water volume’ was constructed by tracing the direction of flow from the flow source point over the TIN surface to the stream system and then to the outlet of the watershed. The FPN was represented by a set of topologically defined one-dimensional line segments and nodes. Hydrologic variables, such as flow velocity and volume, were computed and integrated into the FPN to support dynamic surface flow simulation. A hypothetical rainfall event simulation on a hilly landscape showed that the FPN model was able to simulate the dynamics of surface flow over time. A real-world catchment test demonstrated that flow rates predicted by the FPN model agreed well with field observations. Overall, the FPN model proposed in this study provides a vector-based modeling framework for simulating surface flow dynamics. Further studies are required to enhance the simulations of individual hydrologic processes such as flow generation and overland and channel flows, which were much simplified in this study.

Keywords: digital terrain analysis; flow-path network model; surface flow; triangulated irregular networks

Document Type: Research Article

Affiliations: 1: School of Resource and Environment Science, Wuhan University, Wuhan, Hubei, China 2: Department of Geography, Hong Kong Baptist University, Kowloon, Hong Kong 3: Potato Research Centre, Fredericton, NB, Canada 4: Faculty of Forestry and Environmental Management, University of New Brunswick, Fredericton, NB, Canada 5: Spatial Sciences Institute, University of Southern California, Los Angeles, CA, USA 6: Department of Earth and Environmental Sciences, University of British Columbia, Kelowna, BC, Canada

Publication date: November 2, 2014

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