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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.
F.L.N. Ling, K.A. Robinson, J.C. Bennett, D.E. Robertson, D. Krushka
New technology and outputs from flood forecasting systems can raise issues for dam safety managers in how they use uncertain information to make critical dam safety decisions. In particular, making operational decisions around pre-releases based on forecast inflow presents challenges. In this case dam safety risk needs to be weighed up with other risks such as increasing downstream flooding, or being able to supply water into the future. The process of developing a flood forecasting system should be a close collaboration between the developers and the users. This ensures that outputs provide meaningful information that can be used to support operational decision-making in a flood or emergency response situation.Learn more
Barton Maher, Michel Raymond, Mike Philips
The Queensland Bulk Water Supply Authority (trading as Seqwater) owns and operates North Pine Dam, situated on the North Pine River in the Northern Suburbs of Brisbane. North Pine Dam is an Extreme Hazard Dam consisting of a concrete gravity dam with earthfill embankments at both abutments and three earthfill saddle dams. The spillway consists of five radial gates which are manually operated. Flood operations at the dam are controlled in real time by the Seqwater Flood Operations Centre.Learn more
In January 2011, North Pine Dam experienced the flood of record at the dam site with a peak inflow of approximately 3,500 m3/s and a corresponding outflow of approximately 2,850 m3/s. This inflow was more than double the previously recorded flood of record. The inflow was generated by high intensity rainfall both at the dam and in the upper catchment resulting in a rapid rise of the storage. The system which caused this rainfall was also contributing to the major flooding occurring in the adjacent Wivenhoe – Somerset catchment, also being managed by the Seqwater Flood Operations Centre. The rapid rise and fall of the storage presented difficulties for both the Seqwater Flood Operations Centre and the operators at the dam site.
Following the flood event, an analysis of the rainfall and the resulting inflows indicated a significant difference between the Annual Exceedance Probability (AEP) of the rainfall in the catchment and the estimated AEP of the inflow and peak water levels from previous hydrology studies. A detailed review of the flood event was commissioned by Seqwater and undertaken by URS Australia Pty Ltd.
This paper presents details of the flood event, lessons learned for the operation of the dam, upgrade works undertaken to date, results of the hydrology review and the conclusions of the Acceptable Flood Capacity (AFC) study. A key implication for dam owners was the increase in the estimate of the Probable Maximum Flood (PMF) by over 30% due to changes in calibration of the hydrologic model for the catchment.
Keywords: Probable Maximum Flood, Flood Operations, North Pine Dam, Flood Estimation
Rob Ayre, Simone Gillespie, Peter Richardson, Mark Harvey
In November 2007, NQWater (now Townsville City Council) completed the upgrade of Ross River Dam near Townsville. This upgrade included the installation of a Program Logic Control (PLC) operated radial gate structure in the existing spillway. The purpose of the upgrade was threefold; to meet current design standards regarding dam safety and flood capacity; increase the town water supply to Townsville and Thuringowa; and to maintain the flood mitigation benefit of the dam during flood events in the Ross River catchment.
The designers of the dam upgrade completed a risk assessment at the commencement of the design phase and concluded that a PLC operated gated dam posed less risk than an approach that relied purely on dam operators. This is seen as the “new way forward” in gate operated dams by many designers. The regulator of dam safety in Queensland has indicated a preference for an operator to remain on site full time whilst the PLC system is ‘proved’. As a consequence a flood operations team was engaged to monitor the dam during times of flood through the commissioning period of the upgrade.
This paper discusses the lessons learnt from the experiences of the Ross River Dam during its first few flood events and issues associated with the adopted design approach.
Keywords: Dam Safety, Gated Spillway, Flood Operations, Ross River Dam, NQWater, Townsville City Council, SunWater, Queensland.Learn more