Application of joint probability to respond to climate change and avoid cumulative extreme assumptions
Presentation the Hydrology and Water Resources Symposium at the Hilton George Street Sydney by Professor Peter J Coombes at 12:20 pm on Wednesday 15 November 2023.
The investigation considered the need to determine the relative timing and magnitude of inputs to analysis of flood risks in urban areas that include the potential for riverine and local catchment, and coastal flooding. This paper demonstrates the utility of replacing the use of cumulative extreme assumptions with joint probability methods based on observed data in analysis of flood risks. Climate change considerations should be added to the analysis of flooding after adequate resolution of these joint probability interactions.
The results of this study are based a particular urban area in North Melbourne in Victoria that includes interactions with a regional waterway, local catchment and Port Phillip Bay. However, these results reveal that use of joint probability methods can provide improved understanding of urban flood risks and significant benefits. The consequences of “conservative” cumulative extreme assumptions are variable and uncertain across urban catchments. It is proposed that joint probability methods can replace assumptions.
The investigation considered the problem of determinating the relative timing and magnitude of inputs to analysis of flood risks in urban areas that may include riverine and local catchment, and coastal flooding. The paper demonstrates the utility of replacing the use of cumulative maximum assumptions with joint probability methods based on the observed data in analysis of flood risks. There is a need to include climate change consideration after adequate resolution of the joint probability interactions. The results of this study are based a particular urban area in North Melbourne in Victoria. However, these results reveal that use of joint probability methods can provide improved understanding of urban flood risks and significant benefits. The consequences of “conservative” cumulative maximum assumptions are variable and uncertain across urban catchments.
