Decision-Support System for Mitigating Long-Term Flood Risk

Abstract:

Long-term flood risk in urban areas is expected to increase as a result of a number of factors, such as an increase in the severity of flood events due to the impact of climate change and the exposure of a larger number of people to flooding as a result of population growth. In order to facilitate the development of long-term flood mitigation plans, a framework for a decision-support system (DSS) is presented in this paper. The framework consists of an integrated model (see Figure) consisting of dynamic, spatially distributed land-use and flood inundation models. It also enables the impact of various flood mitigation strategies to be assessed, such as spatial planning, land management, structural measures (e.g. levees, changes in building codes), and community education. The framework considers a number of external drivers that are represented in the form of long-term planning scenarios. These include the impact of climate drivers on the extent of flooding via the flood inundation model and the impact of population and economic drivers on the size and distribution of the population via the land use allocation model.

Using this framework, a DSS is being developed and applied to the Greater Adelaide region of South Australia. This DSS includes an intuitive, user-friendly interface for enabling different planning scenarios and mitigation portfolios to be selected, as well as temporal changes in flood risk maps under each of these scenarios to be observed. Changes in flood risk maps are investigated over a 30-year period with climate drivers represented by different representative concentration pathways, population drivers represented by different population projections and economic drivers represented by different employment rates. The impact of different combinations of mitigation measures is also investigated. The results indicate that climate, population and economic drivers have a significant impact on the temporal evolution of flood risk for the case study area and that the mitigation options investigated can result in a substantial decrease in flood risk.