Yield plays a central role in the processes, practices, management and operation of urban water supply systems. In Australia, yield is commonly defined as the maximum average annual volume of water that can be supplied from the water supply system subject to climate variability, operating rules, demand pattern and adopted level of service (or security criteria). For a given water supply system, yield is typically estimated via computational simulation using the entire sequence of available historic climate data. This means that the simulation, and hence the estimation of yield, is subject to a range of extreme climate events consisting of various dry and wet spells with a multitude of severities and durations, present in the historic data. System management policies and rules are optimised to a single climate scenario that may not match the planning length of the studies conducted by the water authority, nor allowing for the effects of future climate variability. This study is on the importance of input variables and climate variability to the estimation of yield of an urban water supply system. Primarily, the effects of planning period and the climate variability on the yield and on the importance of input variables are assessed.
A preliminary case study on a simple, hypothetical urban water supply system was conducted primarily to assess the applicability and limitations of three sensitivity analysis (SA) techniques, namely the Morris Method, the Fourier Amplitude Sensitivity Test and Sobol’s method of SA. These techniques produced mostly reliable results which revealed some limitations of the SA framework adopted. The findings and conclusions of the preliminary study bore important improvements before use on the complex case study of the Barwon Water supply system. Employing 20 climate scenarios over four simulation lengths, the input variables used in the estimation of yield for the Barwon urban water supply system were subjected to SA using the above-mentioned techniques. Significant findings of the study showed that the estimation of yield is more volatile to changes in the input variables and climate variability for shorter planning periods. This was indicated by the average and the range of the yield estimate decreasing as the planning length increased.