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The January 2011 flood event that impacted southeast Queensland is amongst the most extensive and severe floods in terms of loss of life and property damage that the region has experienced, despite it being only the eighth highest flood on record at the Brisbane City Gauge. The spring of 2010 was the wettest on record for Queensland, New South Wales, and the Murray-Darling Basin (Bureau of Meteorology 2011a) at that time. The flood mitigation dams in the region, Somerset Dam and Wivenhoe Dam, had to be operated for flood mitigation purposes during October 2010, which was the first occasion since February 2001 that Wivenhoe Dam had been called into action due to the Millennium Drought. The wet October was followed by a very dry November which, in turn, was followed by the wettest December on record for Brisbane. Somerset Dam and Wivenhoe Dam were again pressed into action on three separate occasions during December 2010. The resultant releases ensured that only minor flooding resulted in the Lower Brisbane River during these events. However, on the 5th of January 2011, another rainfall event started to unfold across the catchments of the dams. By the 10th of January 2011, an upper-level low combined with a humid easterly flow to bring very heavy rainfall and flash flooding to southeast Queensland and northeast New South Wales. The heaviest falls were in the areas north and west of Brisbane, with three-day totals exceeding 200 mm over most of the Brisbane River catchment. This rainfall event resulted in a flood of record in the Upper Brisbane River and Upper Lockyer Creek catchments that sadly resulted in a substantial loss of life in Toowoomba and the Lockyer Valley, and which required record releases from Wivenhoe Dam. The resultant downstream flooding saw some 14,000 properties impacted, principally in the Lockyer Valley Regional Council, Somerset Regional Council, Brisbane City Council, and Ipswich City Council local government regions. Flood damage was estimated to be around $2.53 billion. This paper discusses the event as it unfolded and the subsequent judicial inquiries, engineering reviews, and legal proceedings that resulted from the consequences of the operation of Somerset Dam and Wivenhoe Dam. [ABSTRACT FROM AUTHOR]

The earliest record of pineapple plants being grown around Sydney in the British colony of New South Wales was that of Governor King in 1803. However, the climate of a new northern settlement at Moreton Bay (later Brisbane) soon proved to be far more conducive to growing the fruit. Pineapples prospered for over 50 years around Brisbane until a mysterious disease appeared in the late 1890s. In April 1891, Professor Edward Shelton, an American who had been appointed as the Queensland government's first Instructor in Agriculture, was the first scientist to inspect the affected crops and concluded that the disease was caused by a fungus. In the following year, Shelton, Henry Tryon (then assistant curator at the Queensland Museum) and others again inspected the diseased pineapple crops. Tryon described the symptoms in detail as well as spores which were composed of two rounded elements, each having a double contour (chlamydospores). There is no doubt that the disease was caused by the oomycete Phytophthora cinnamomi that was described decades later. In 1897, Shelton was passionate about agricultural education and was appointed as the first principal of the Gatton Agricultural College, but his disciplining of some students of the college led to his forced resignation just 18 months later. In the early 1890s a serious mystery disease appeared in pineapple plantations around Brisbane, Queensland. The American-born Professor Edward Shelton, Queensland's first instructor in agriculture, Henry Tryon, assistant curator at the Queensland Museum, and others inspected diseased plants and concluded that the disease was caused by a fungus, later identified as the oomycete Phytophthora cinnamomi. Shelton went on to become the first principal of the Gatton Agricultural College, but was forced to resign after severely disciplining some of the students. Photograph by an unknown person. [ABSTRACT FROM AUTHOR]

The fidelity of the decadal experiment in Coupled Model Intercomparison Project Phase-5 (CMIP5) has been examined, over different climate variables for multiple temporal and spatial scales, in many previous studies. However, most of the studies were for the temperature and temperature-based climate indices. A quite limited study was conducted on precipitation of decadal experiment, and no attention was paid to the catchment level. This study evaluates the performances of eight GCMs (MIROC4h, EC-EARTH, MRI-CGCM3, MPI-ESM-MR, MPI-ESM-LR, MIROC5, CMCC-CM, and CanCM4) for the monthly hindcast precipitation of decadal experiment over the Brisbane River catchment in Queensland, Australia. First, the GCMs datasets were spatially interpolated onto a spatial resolution of 0.05 × 0.05° (5 × 5 km) matching with the grids of observed data and then were cut for the catchment. Next, model outputs were evaluated for temporal skills, dry and wet periods, and total precipitation (over time and space) based on the observed values. Skill test results revealed that model performances varied over the initialization years and showed comparatively higher scores from the initialization year 1990 and onward. Models with finer spatial resolutions showed comparatively better performances as opposed to the models of coarse spatial resolutions, where MIROC4h outperformed followed by EC-EARTH and MRI-CGCM3. Based on the performances, models were grouped into three categories, where models (MIROC4h, EC-EARTH, and MRI-CGCM3) with high performances fell in the first category, and middle (MPI-ESM-LR and MPI-ESM-MR) and comparatively low-performing models (MIROC5, CanCM4, and CMCC-CM) fell in the second and third categories, respectively. To compare the performances of multi-model ensembles' mean (MMEMs), three MMEMs were formed. The arithmetic mean of the first category formed MMEM1, the second and third categories formed MMEM2, and all eight models formed MMEM3. The performances of MMEMs were also assessed using the same skill tests, and MMEM2 performed best, which suggests that evaluation of models' performances is highly important before the formation of MMEM. [ABSTRACT FROM AUTHOR]