An enhanced technique in construction of the discrete drainage network from low-resolution spatial database

Abstract

A digital elevation model (DEM) of a watershed can be used to acquire various parameters such as basin-wide information about overland flow direction, flow accumulation and area contributing flow to any point. The resolution and quality of a DEM are important to achieve a significant level of accuracy in derived parameters. Inadequate elevation information exacerbated by applied interpolation methods, reduce DEM accuracy, resulting in pits and flat areas and makes flow tracing a difficult task. These types of problems are more prominent in cases of residual undulating terrains. In the present paper, an attempt has been made to review and suggest an improved method for the generation of a DEM from raster contour data. Further, a criteria-based region growing method (CBRGM) is presented for the extraction of discrete drainage network (cell size: 20×20 m) of the watershed. Here, the flat area removal algorithm, with a variable increment, is used to generate the DEM. This induces a gradual slope even in the case of a large contour interval (20 m) extended over larger area, as is commonly available from a topographic map at a scale of 1:50,000. Further, in order to capture topographic information in flow tracing, the CBRGM is followed. The rasterised stream network from the same topographic sheet is used as ancillary data to make the concentrated flow lines to follow the channel. The methodology has been tested over Gandheshwari subwatershed under the lower part of Chhotanagpur Plateau in Eastern India. The DEM generated using this method gives a better representation of the terrain, which shows good agreement with the terrain information delineated by using the contour and channel information available in the topographic sheet. The drainage network derived shows additional extra-concentrated flow lines, many of which match the drainage network obtained from satellite imagery (cell size: 23.5×23.5 m). The algorithm thus shows superiority over other available methods for the extraction of drainage networks.