Variation of representative rainfall time series length for rainwater harvesting modelling in different climatic zones.

Rainwater harvesting systems (RHS) have been increasingly used to mitigate urban water scarcity and flooding problems. Rainfall data with various lengths have been used for RHS modelling. However, short-term rainfall data with inadequate lengths used for the modelling of RHS may lead to considerable errors. In this study, a method that can be used to identify representative length of short-term rainfall data for RHS modelling was proposed and tested in 12 cities located in different climatic zones. The influences of local rainfall characteristics on the variation of representative time series lengths (RTSL) were revealed using linear regression and partial correlation analyses. The results show that RHS with larger storage capacity and located in more humid cities can provide higher water saving efficiency and reliability. Rainfall time series length has significant influence on the modelling results of RHS. The RTSL for the 12 cities vary from 6 to 21 years. The RTSL for the 12 cities are non-significantly correlated with mean annual rainfall (R2 = 0.32, n = 12, p > 0.05) and seasonality index (R2 = 0.28, n = 12, p > 0.05), but significantly correlated with variation coefficients of annual rainfall (R2 = 0.76, n = 12, p < 0.05). The partial correlation coefficient between RTSL and the variation coefficients of annual rainfall is 0.878, while the partial correlation coefficients between RTSL and the mean annual rainfall and seasonality index are -0.569 and -0.522, respectively. The results demonstrate the feasibility of using short-term rainfall data with adequate length instead of long-term rainfall data for RHS modelling and also provide insights into the variation of RTSL in different climatic zones.

Impacts of climate change on urban rainwater harvesting systems.

Rainwater harvesting (RWH) is promoted in many cities (e.g., Beijing and Shenzhen) as a climate change adaptation measure to relieve urban water supply and drainage pressures. In this study, the impacts of future climate change on water saving and stormwater capture performances of RWH systems at cities across four climatic zones of China are investigated. A downscaling technique based on the Climate Generator is evaluated and employed to generate future (2020-2050) daily rainfall data. Performance indices of RWH systems (i.e., water saving efficiency, reliability, and stormwater capture efficiency) calculated using both the future and historical (1985-2015) daily rainfall data are compared. Two water demand scenarios (i.e., lawn irrigation and toilet flushing) are included in the investigation. The water saving performance is positively affected by the increases in future rainfall at the four cities, while the stormwater capture performance is negatively affected as a larger tank size is required to achieve a desired stormwater capture efficiency in the future period. The responses of water saving and stormwater capture performances of RWH systems to climate change are varying with not only the system dimensions (i.e., storage capacity and catchment area), but also the water demand scenarios and locations. RWH systems with larger storage capacity for larger water demand scenarios at humid and semi-humid cities is expected to be more resilient to climate change. The various changing patterns of the performance indices highlight the importance of incorporating climate change in the design of RWH systems. Location-specific adaptive adjustments (e.g., adjusting tank sizes, catchment areas or water demand rates) need to be adopted so that RWH systems can sustainably meet water saving and stormwater control requirements under future climate conditions.