A GIS for flood damage control planning and estimation of flood damage

English: Viljoen, Du Plessis and Booysen (1995) started in 1992 with the development of a flood damage simulation model (FLODSIM) for the Lower Orange River area. This model was based on GIS technology and was completed in 1994. The main shortcoming of this model was that it was location specific. A successive project was piloted in 1995 for the modification of the model so that it would be generally applicable in flood prone areas. Weiss (1976) already did extensive work on the estimation of flood damage for the Mfolozi floodplain and it was therefore decided to demonstrate the model on the Mfolozi floodplain. A Setup program was written to be able to adapt the model according to the different situations of floodplains. The Setup program prompts the user to indicate the features that should be included in the model and then it guides the user through a series of menus to define the variables that are required to include the specified features. Features that can be included into the model include a DTM, levees, contours, spot heights, cultivated fields, infrastructures and buildings. Flood damage can be computed for cultivated fields, infrastructures and buildings. Other enhancements of the model include programs for the manipulation of levees, loss functions for sugarcane and infrastructure and a program that computes the flooded areas. Programs were also written to speed up the process of acquiring new hydraulic data after levees were added or removed. This includes programs with which topographic data that are required by numerical flood models can be extracted from the DTM and programs with which the hydraulic data that were computed with the numerical flood model can be imported into FLODSIM. An interface with Mike Il was also developed to illustrate the coupling between FLODSIM and numerical flood models. In a literature study that was conducted to investigate different methods for obtaining data it was found that data can either be acquired in digital form from another company or it has to be digitised from maps. When no data are available for the area it may be collected in situ or by means of remote sensing. Remote sensing can also be of great value in updating data such as land use patterns that change over time. The sources that are used to derive DEM data vary from ground surveys, photograrnmetry and existing contour maps to radar or laser altimetry.