High flood levels on the lower Avon River in Christchurch can be caused by high river discharges, high sea levels or both. HKV and GHD collaborated in the design of a statistical model to assess compound flooding in the Avon River Delta of Christchurch. The quantification of the probability of coincidence leads to better boundary conditions for hydraulic models and better estimate of flood risks along the Avon River. The analysis includes (1) assessment of sea level rise, (2) the derivation of extreme value statistics and (3) the design of a correlation model.
Relative sea level rise. This analysis researches what the historic sea level rise is, provides insight in the causes of this rise and explores if the rate of sea level rise is potentially accelerating. The analysis makes use of sea level measurement during the past century from the Lyttelton Port tide gauge. The approach filters temporal physical components from the measurements to improve estimates of the average sea level for any given time period as much as possible. These physical components include i.e. tidal fluctuations, barometric surge, decadal oscillation patterns (IPO and ENSO) and season effects. Linear regression is applied to the residual signal to investigate potential trends.
Extreme value analysis of the sea water levels. For determining the magnitude of extreme sea water levels in the boundary conditions, it is necessary to have an estimate for the height of infrequent sea water levels. The extreme value statistics and corresponding confidence intervals have been assesst.
Correlation model. Lines or equal probability consist of different boundary conditions, which have an equal probability of occurrence based on the correlation model. These lines are derived based on the three components: extreme sea levels, extreme rainfall and the correlation between rainfall and surge. The results are based on local weather patterns (Kidson patterns) and significantly improve the reliability of subsequent flood risk modelling.