The Human Factor in Hydrology

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Rhys Thomson, Daniel Wood, Monique Retallick, Mark Babister

Friday 3 july 2015

14:00 - 14:15h at Europe 2 (level 0)

Themes: (T) Water resources and hydro informatics (WRHI), (ST) Catchment hydrology

Parallel session: 16I. Extreme events - Resilient

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The estimation of catchment runoff in urban environments is complex due to the interaction of rainfall/runoff processes in pervious and impervious areas, trapping of runoff by buildings and other structures, and the hydraulic limitations of inlets and the conveyance capacity of piped drainage systems. While much research has been conducted on the testing of different hydrological estimation techniques in gauged urban catchments, practitioners are generally faced with the challenge of estimating flows in ungauged urban catchments. This requires them to estimate parameter values for hydrologic and hydraulic models based on experience, research, available guidelines and/or best available information. As a part of the current revision of the Australian Rainfall and Runoff (ARR) guidelines (national guide to design flood estimation), a “blind testing” regime was undertaken of the human factor inherent in the estimation of catchment runoff. Three independent modellers, in three separate offices in Australia (and in two separate companies), were commissioned to develop a number of hydrological models for two gauged urban catchments located in Victoria and in Western Australia. However, these modellers were not provided with any gauged flow data and consequently they needed to use the best available information and apply their experience to establish and run the hydrological models. The key aim of this test was to compare the consistency in the approaches and results between the modellers, as well as a Flood Frequency Analysis (FFA) that was undertaken using the flow gauge data that was available. The approaches which were tested, included the Direct Rainfall method (rainfall applied to a 2D grid), Rainfall/runoff modelling (XP-RAFTS, RORB) and the Rational Method. Different tests were also undertaken on alternative model setups by each of the modellers. The outcomes of these tests are presented in this paper. This includes a comparison of the different hydrological techniques, as well as the results generated by the different modellers. Significant variance was observed both between the different hydrological techniques as well as between the different modellers. The results provide a unique insight into the need for clear guidance and leadership in the development of hydrological models