Urban Drainage Network Generation with Geographic Information Systems Using Remotely Sensed Data

Civil Engineer, Mapping Section BSc. Civil Engineering, MEng., AMIESL. Professor of Civil Engineering and the Chairman of the International Center for Geoinformatics Applications and Training BSc Eng. (Hons) Sri Lanka, PG Dip (Moratuwa), M.Eng. (Tokyo), D.Eng. (Tokyo), CEng., MICE (London). FIE (Sri Lanka) In Sri Lanka most of the existing urban drainage systems are not functioning properly. Establishing a proper drainage system in an urban area.is extremely important since it could avoid floods and inundation which causes damage to property and inconvenience to city dwellers; improve health conditions of the urban community by avoiding stagnant water; give an aesthetically pleasing environment, etc. Therefore, in Sri Lanka, establishing a proper drainage system and maintaining the same has become a major challenge in urban areas. Urban drainage network identification is a primary requirement for developing a proper drainage system. Urban drainage network identification is a tedious task, which is usually done through engineering surveys. The computer aided Geographical Information Systems (GIS) can be utilized to generate drainage network from the terrain data. The main objective of this work is the study of stream network generation in GIS using data extracted from aerial photographs, carryout accuracy comparison with surveyed drainage network and then to identify the parameters that affect the accuracy of generating streamlines. In this study, two urban watersheds from Colombo and one watershed from Moratuwa were studied to identify the stream network generation and associated terrain indicators using data extracted from aerial photographs. The data extraction for the study was done using three methods. Existing drainage network and watershed boundary were digitized from hard copy maps of Sri Lanka Land Reclamation and Development Corporation (SLLRDC). Contours, spot heights, buildings and road data in digital form were extracted from the digital archives of the National Survey Department (NSD). Some of the existing streamlines and culvert locations were surveyed specifically using GPS. Then the generation of the Triangulated Irregular Network (TIN) was carried out using the extracted contours and spot heights. Using the TIN, Digital Elevation Models (DEM) for spatial resolutions of 2m, 5m, 10m, 20m & 50m were generated. For each DEM, flow direction grids and flow accumulation grids were generated as components of stream network generation. Once the streamlines are generated from the flow accumulation grid, it is necessary to give a threshold value