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Phillip Jordan, Alan Seed, Rory Nathan, Peter Hill, Eva Kordomenidi, Clive Pierce, Michael Leonard
This paper discusses the stochastic framework that was used to generate the 5449 sets of inflow hydrographs, to develop and stress test a dam operations model. The stochastic simulations were driven by 600 different space-time patterns of rainfall generated using a stochastic space-time multiplicative cascade model. Eight significant storms were identified in the radar archive to identify parameter sets for the stochastic generation algorithm and 600 replicates of space-time rainfall were generated. The statistical properties of spatial patterns of 48-hour rainfall bursts on eight major subcatchments of the Brisbane River catchment from the 600 stochastic replicates were verified against the same statistics derived from 38 major flood causing rainfall events observed in the catchment. The hydrographs were generated using an URBS rainfall runoff routing model of the Brisbane River catchment, which was calibrated to 38 historical flood events (between 1955 and 2013) and tested on a further 10 historical flood events (between 1887 and 1947).
The stochastically simulated sets of inflow hydrographs were then used to assess the impact of variations in flood operation rules for Wivenhoe and Somerset dams. The stochastically generated events exhibit substantial variability in runoff hydrographs but with variability that is statistically consistent with observed events. The stochastically generated hydrographs provide a considerably more realistic basis for testing the outcomes for different flood operations strategies than the single design event approaches that have previously been adopted.