Urban stormwater harvesting - sensitivity of a storage behaviour model

  • Authors:

  • V. G. Mitchell;D. T. McCarthy;A. Deletic;T. D. Fletcher

  • Affiliations:

  • Institute for Sustainable Water Resources, Department of Civil Engineering, Building 60, Monash University, Clayton, Vic 3800, Australia;Institute for Sustainable Water Resources, Department of Civil Engineering, Building 60, Monash University, Clayton, Vic 3800, Australia;Institute for Sustainable Water Resources, Department of Civil Engineering, Building 60, Monash University, Clayton, Vic 3800, Australia;Institute for Sustainable Water Resources, Department of Civil Engineering, Building 60, Monash University, Clayton, Vic 3800, Australia

  • Venue:
  • Environmental Modelling & Software
  • Year:
  • 2008

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Abstract

The harvesting of urban stormwater to supply non-potable water demands is emerging as a viable option, amongst others, as a means to augment increasingly stressed urban water supply systems. This paper investigates the sensitivity of an urban stormwater harvesting system's capacity-yield-reliability relationship to variations in the behaviour modelling method used, focusing on the storage and demand components of a single reservoir system. The aim is to enhance our understanding of the appropriate computational method for assessing such volumetric reliability/storage capacity relationships. Four reference scenarios were developed, based on two different climates and two different water demand patterns. A sensitivity analysis was conducted, which considered the following computational, storage and demand parameters: yield-spillage order, modelling time-step, length of rainfall record, initial storage volume, open/closed storage surface, dead storage volume, diurnal and weekly pattern of water demand, and inter-annual variability of seasonal water demand. It was found that several parameters had an insignificant impact on the estimation of volumetric reliability for the scenarios tested, whilst the three most significant parameters were: length of rainfall record, inter-annual variability of seasonal demand, and storage surface type. Recommendations about the minimum length of rainfall record used and the inclusion of both the inter-annual variability of seasonal demand and net evaporative losses in the case of an open store are made.