RASP - A hierarchy of risk-based methods and their application

Sayers, P. and Meadowcroft, I. (2005) RASP - A hierarchy of risk-based methods and their application. In: Defra Flood and Coastal Management Conference 2005, 5 - 7 July 2005, York, UK.

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Abstract

It has long been recognised that flood risk cannot be eliminated completely and that understanding risk is key to improving risk management. In particular, this means deciding on actions such as: • construction of new defences where they are most efficient in reducing risk; • maintaining and operating defences and defence systems to minimise risk; • flood forecasting and warning to minimise the consequences in the event of flooding; • restricting development in flood and erosion-prone areas to control the impacts. The need for improved risk assessment methodologies to support better flood risk management has been widely recognised and in 2001 the Environment Agency and Defra commissioned HR Wallingford to lead an R&D project titled RASP – Risk Assessment for Strategic Planning. The RASP project was completed in 2004 and for the first time provided a hierarchical risk-based analysis framework to help the Environment Agency and Defra understand flood risk and in particular how flood defences, and investment in flood management, influence flood risk. This paper builds upon previous presentations at the Defra conference in 2002 and 2003 (Sayers et al, 2002, 2003). The development of the RASP methodologies and the hierarchy of decision-specific tools which they are now beginning to support are outlined and the hierarchical nature of the RASP methods are demonstrated. The paper concludes that a sound risk assessment approach is essential for better flood risk management decision-making and to improve the effectiveness of our flood management systems. In particular, it shows how a structured hierarchical approach to risk assessment ensures that the level of analysis undertaken is appropriate to the complexity of the decision at hand and its sensitivity to uncertainty – thus maximising the efficiency of the resources applied to the decision making process.

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