A probabilistic approach to rainwater harvesting systems design and evaluation

Although rainwater harvesting system (RHS) is an effective alternative to water supply, its efficiency is often heavily influenced by temporal distribution of rainfall and water demand. Since natural precipitation is a random process and has probabilistic characteristics, it will be more appropriate to describe these probabilistic features of rainfall and its relationship with design storage capacity as well as supply deficit of RHS. This paper aims at developing a methodology for establishing the probabilistic relationship between storage capacities and deficit rates of RHS. A simulation model was built to simulate the input rainfall and water release in RHS. Historical rainfall records were then used as input for simulation and the results were used in probabilistic analysis for establishing the relationships between storage capacities and water supply deficits. The city of Taipei was used as study area for demonstration of this methodology and probabilistic distribution curves for storage capacity and deficit rate relationships were presented. As a result, a set of curves describing the continuous relationships between storage capacities and deficit rates under different exceedance probabilities were generated as references to RHS storage design. At a chose exceedance probability of failure, the engineer can decide from the curve on the storage size under a preset deficit rate.