Estimating surface flow paths on a digital elevation model using a triangular facet network

This study attempts to develop a method for the simulation of surface flow paths on a digital elevation model (DEM). The objective is to use a facet-based algorithm to estimate the surface flow paths on a raster DEM. A grid DEM was used to create a triangular facet network (TFN) over which the surface flow paths were determined. Since each facet in the network has a constant slope and aspect, the estimations of, for example, flow direction and divergence/ convergence are less complicated compared to traditional raster-based solutions. Experiments were undertaken by estimating the specific catchment area (SCA) over a number of mathematical surfaces, as well as on a real-world DEM. Comparisons were made between the derived SCA by the TFN algorithm with some algorithms reported in the literature. The results show that the TFN algorithm produced the closest outcomes to the theoretical values of the SCA compared with other algorithms, deriving more consistent outcomes and being less influenced by surface shapes. The real-world DEM test also shows that the TFN was capable of modeling flow distribution without noticeable "artifacts," and its ability of tracking flow paths makes it an appropriate platform for dynamic surface flow simulation.