Chen Weilun, Liu Zhonghui, Wei Xindong, He Shilong, Gao Weijun, Wang Xiaodong
School of Environment and Spatial Informatics, China University of Mining & Technology, Xuzhou 221116, China; School of International Education, Jilin Jianzhu University, Changchun 130118, China.
Key Laboratory of Songliao Aquatic Environment, Ministry of Education, Jilin Jianzhu University, Changchun 130118, China.
Sci Total Environ. 2024 Nov 15;951:175668. doi: 10.1016/j.scitotenv.2024.175668. Epub 2024 Aug 22.
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.
采用近期短期历史降雨数据可能会提高雨水收集系统（RWHs）应对气候变化的性能。然而，这一假设缺乏广泛研究，目前对雨水收集系统的评估依赖于长期历史降雨时间序列。本研究评估了这一假设的可行性，旨在确定在气候变化条件下评估雨水收集系统性能的最佳降雨时间序列。我们利用不同长度的历史降雨时间序列和30年预测降雨时间序列，对日本16个城市的住宅建筑中的雨水收集系统进行了评估。根据历史时期和未来时期评估结果之间的相似性指数，得出了最小降雨时间序列长度。可以从最小长度的相似性指数分布中确定相应的最佳序列。最后，我们引入供应压力指数（SPI）来总结这些最佳降雨时间序列的降雨特征。我们的研究结果表明，随着建筑非饮用水需求的增加和城市位置的变化，最小降雨时间序列长度从1年增加到30年。利用包含近期降雨数据的降雨时间序列，在气候变化条件下对雨水收集系统进行评估可得到更可靠的结果。这些最佳降雨时间序列具有共同特征，根据当地降雨模式，供应压力指数范围为5.37至17.87毫米/天。我们的研究得出结论，利用近期短期历史降雨数据来评估和设计气候变化条件下的雨水收集系统是可行的。
