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We consider the management of urban stormwater in two connected dams. Stormwater generated by local rainfall flows into a capture dam and is subsequently pumped into a similar sized holding dam. We assume random gross inflow and constant demand. If we wish to minimise overflow from the system then the optimal management policy is to pump as much water as possible each day from the capture dam to the holding dam without allowing the holding dam to overflow. We shall refer to this policy as the pump-to-fill policy. The model is based on the Parafield stormwater management system in the City of Salisbury (CoS) but assumes constant demand instead of level dependent outflow. If there is insufficient water in the holding dam to meet the desired daily demand then all water in the holding dam is used and the shortfall is obtained from other sources. CoS, in suburban Adelaide in South Australia, is recognised in local government circles as a world leader in urban stormwater management. The water is supplied to local industry to replace regular mains water and is also used to restore and maintain urban wetlands. In mathematical terms the pump-to-fill policy defines a Markov chain with a large transition matrix and a characteristic regular block structure. We use specialised Matrix Analytic Methods to decompose the event space and find simplified equations for the steady state probability vector. In this way we enable an elementary solution procedure which we illustrate by solving the modified Parafield problem. The optimal nature of the pump-to-fill policy is established in a recent paper by Pearce et al. (JIMO 3(2):313–320, ). The purpose of the current study is to find optimal management policies for urban stormwater systems. [ABSTRACT FROM AUTHOR]

Due to significant weather variabilities of rainfalls, potential water savings through rainwater tanks are expected to vary significantly. Moreover, within some large cities, significant spatial variations are reported. With the emerging impacts of climate change, existing weather and spatial variabilities of potential water savings are also likely to be changed, which are unknown to the end-users. This paper presents the impacts of climate change on current weather and spatial variabilities of potential water savings for Adelaide, a large city in Australia. Future daily rainfall data was collected from a data portal provided by the Australian government derived through a statistical downscaling modelling. Projected daily rainfall data was fed to an earlier developed daily water balance model (eTank) to calculate water savings for three future periods; 2030–2050, 2055–2075 and 2080–2100. Three weathers (dry, average and wet) in each period were considered along with two climate change scenarios (RCP 4.5 and RCP 8.5) and two tank sizes (5 kL and 10 kL). It is found that varying outcomes without any general trend are expected depending on the projection scenario, period and weather condition. Contrary to the general perception, it is found that in several cases, the potential water savings are expected to increase compared to the current climate. Most of those expected increases in water savings are attributed to the projection scenario of RCP 4.5, in the near future and in dry years. In the far-future and with the projection scenario of RCP 8.5, most of the potential water savings are expected to decrease compared to the current climate. Regarding changes in spatial variability of water savings, it is found that the spatial variability will decrease in the near future, but will increase towards the far future. [ABSTRACT FROM AUTHOR]