Probabilistic estimation of the storage capacity of a rainwater harvesting system considering climate change

Although a rainwater harvesting system (RWHS) is an effective water supply alternative, its efficiency is often heavily influenced by the temporal distributions of precipitation and water demand. Furthermore, because recent precipitation patterns have changed due to climate change and will likely continue to do so, RWHS designs must take future precipitation forecasts into account. This study aimed to develop a methodology for establishing the probabilistic relationships between the storage capacity and deficit rate of an RWHS when considering climate change. A four-story building at a university was selected as a case study. The A2 scenario of the CGCM3 (Canadian Global Coupled Model 3) was considered and downscaled to the study area using the SDSM (Statistical DownScaling model), and the fitted probabilistic distributions were selected and modeled according to the results of goodness-of-fit tests. As a result, a set of curves describing the relationships between storage capacity and deficit rate was derived. From these curves, we determined that the studied RWHS's storage capacity could be reduced due to increased annual mean precipitation when the impact of climate change is considered. However, climate change consideration may not be important to determine the storage capacity of RWHS when the places showing enough rainfall all year around are planned. This result can be helpful for RWHS engineers and decision makers.