Raj Hari Sharma

Stormwater treatment systems play an integral part in achieving sustainable urban development. The performance of these systems is likely to be impacted by potential changes in climatic patterns, including precipitation. This project investigates the simulated impacts of climate change on the performance of stormwater treatment systems used as a part of Water-Sensitive Urban Design (WSUD). Townsville and the Gold Coast of Queensland, Australia, were selected for the study to investigate tropical and sub-tropical climates experienced by cities across the globe adjoining sensitive coastal environments such as wetlands and coral reefs. The daily precipitation output projected by Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models was downscaled to pluviograph input into the Model for Urban Improvement Conceptualisation (MUSIC). The treatment performance of bioretention systems and constructed wetlands was variable across both locations, with some models showing little to no change or improvement. Worsening of treatment performance was more prominent in the tropical climate, with numerous models reaching a decline of up to 16%. However, the highest observed reduction from a single model output occurred in the sub-tropical climate location. To make the WSUD treatment system effective under the future climate scenarios, physical modification is necessary to increase the treatment area or depth. Increasing the area in the worst-case scenario could incur a cost increase of 20% to 30% and present challenges due to development constraints. Increasing the depth could be a viable alternative for bioretention systems but is likely impractical for constructed wetlands.

Flood modelling of a large basin like the Fitzroy is a difficult task due to its large catchment size, the long duration of flood events, the non‐uniform spatial distribution of rainfall and a lack of required data for modelling purposes. This paper presents a systematic methodology for the flood modelling of the Fitzroy Basin using hydrologic and hydrodynamic modelling approach with Geographic Information System (GIS) capabilities. This study developed five flood scenarios analysing historical flood events and considering three impacts of climate change: upstream subcatchments flooding, local rainfall fluctuations and sea level rise. A hydrologic model was developed within the wider Fitzroy Basin with the five upstream subcatchments and the upper Fitzroy subcatchment in order to simulate discharge data for these scenarios at the Gap measurement location. An integrated hydrologic–hydrodynamic model was developed for the lower Fitzroy subcatchment where output discharges of the hydrologic model were considered as the upstream boundaries. The peak flood levels, peak flow rates and flood inundation durations at Rockhampton city were identified using this integrated model. GIS capabilities were specially used for automatic watershed delineation and river cross‐section extraction from Digital Elevation Model (DEM) data. The methodology proposed here is a case study and can be applied to other similar basins or catchments.

A distributed 1D rainfall–runoff model is presented. It consists of the Saint Venant continuity and momentum equations for overland flow and a modified Green-Ampt model for the infiltration on railway embankment steep slopes. The model is applied to adjacent 10-m-wide erosion control experimental plots with different percentages of grass cover. A relationship between the 2-day antecedent rainfall and initial moisture content was established and used to predict the saturated hydraulic conductivity (Ks). Average values of Ks for 0, 50 and 100% grass cover were found to be 0.1, 1.19 and 2.56 mm/h, respectively. For the majority of cases, the model simulated runoff with acceptable accuracy, 68% having Nash-Sutcliffe efficiency (NSE) values above 0.50. The average NSE value varied between 0.60 and 0.80, with 0% grass-covered plots yielding the highest values. As expected, the runoff volume decreased with increasing percentage of grass cover. Citation Sajjan, A.K., Gyasi-Agyei, Y., and Sharma, R.H., 2013. Rainfall–runoff modelling of railway embankment steep slopes. Hydrological Sciences Journal, 58 (5), 1162–1176. Editor D. Koutsoyiannis

This paper presents a large scale hydrological model for the Fitzroy Basin using the MIKE 11 NAM modelling system. This model simulates the rainfall runoff processes for the three different and interrelated storages which are surface storage, root zone storage and groundwater storage. The parameters of such model cannot be obtained directly from measurable quantities of catchment characteristics. Hence model calibration is required to get the model parameters. Manual calibration is very time consuming and it only focuses on a single objective function. Thus tradeoff exists between the different objectives. For this study, an automatic calibration was done considering the four multiple objectives and obtained the optimal values of the model parameters for each catchment. The simulated and observed discharge hydrographs show a reasonable good match for each sub-catchment. Moreover model reliability was evaluated using the statistical methods Index of Agreement (IA) and Efficiency Index (EI). The IA and EI obtained 0.821-0.951 and 0.849-0.961 for different sub-catchments

Fitzroy Basin is the second largest catchment that drains to the coast in Australia. Fitzroy Basin is capable of producing severe flooding from tropical cyclone with heavy rainfall due its immense size and fan-like shape. Analysis shows that the historical peaks of different tributaries in different sub-basins of the Fitzroy River occurred in different years and their contributions are different for each flood event. However a scenario might happen when the flood peaks of different tributaries would synchronize and its consequence will be mass devastation indeed. The impact of combination of extreme flood peaks of different tributaries in different sub-basins to the total flood magnitude of the Fitzroy river is presented in this study using an integrated hydrological and hydrodynamic model. The discharge found from the synchronized extreme flood event was about 36% higher than the most severe historical flood that occurred in 1918