Employing recent short-term historical rainfall data may enhance the performance of rainwater harvesting systems (RWHs) in response to climate change. However, this assumption lacks extensive research, and the evaluation of RWHs currently relies on long-term historical rainfall time series. This study evaluates the feasibility of this assumption and aims to identify the optimal rainfall time series for evaluating RWH performance under climate change. We evaluated RWHs in residential buildings across 16 Japanese cities utilizing historical rainfall time series of varying lengths and 30-year predicted rainfall time series. The minimum rainfall time series length was obtained based on the similarity index between the evaluation results for historical and future periods. The corresponding optimal series can be determined from the distribution of similarity indices in the minimum length. Finally, we introduce supply pressure indices (SPIs) to summarize the rainfall characteristics of these optimal rainfall time series. Our findings highlight that the minimum rainfall time series length increased from 1 year to 30 years as building non-potable water demand rose and city locations varied. Utilizing rainfall time series incorporating recent rainfall data yielded more dependable evaluation results for RWHs under climate change. These optimal rainfall time series share common characteristics with SPIs ranging from 5.37 to 17.87 mm/d, contingent on the local rainfall patterns. Our study concludes that utilizing recent short-term historical rainfall data is feasible to evaluate and design RWHs under climate change.
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