Wang et al. (2025) Parsimonious analytical modelling of rainwater harvesting systems’ performance under climate change in six Chinese cities

Identification

Journal: Journal of Hydrology Regional Studies
Year: 2025
Date: 2025-11-20
Authors: Jiachang Wang, Enhui Jiang, Jun Wang, Shouhong Zhang, Yiping Guo, Lei Yu, Xin Pan, Changhyun Jun, Bellie Sivakumar
DOI: 10.1016/j.ejrh.2025.102924

Research Groups

School of Civil Engineering, Shandong University, Jinan, China
Governance of Basin System Research Center, Shandong University, Jinan, China
Yellow River National Strategy Institute, Shandong University, Jinan, China
School of Soil and Water Conservation, Beijing Forestry University, Beijing, China
Department of Civil Engineering, McMaster University, Hamilton, Canada
School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou, China
School of Civil, Environmental and Architectural Engineering, College of Engineering, Korea University, Seoul, South Korea
Department of Civil Engineering, Indian Institute of Technology Bombay, Powai, India

Short Summary

This study proposed a novel quantitative assessment for data-scarce regions by integrating daily rainfall event reconstruction with an analytical probabilistic model (APM) to evaluate climate change impacts on rainwater harvesting (RWH) systems’ performance. Results in six Chinese cities reveal climate change necessitates larger RWH storage capacities to mitigate future urban flooding risk and optimize rainwater utilization, despite a trade-off where water supply reliability generally increases while stormwater control efficacy decreases.

Objective

To propose a simple but practical daily rainfall event separation method (Homogenized Threshold-based Event Separation - HTES) capable of generating accurate and reliable rainfall event characteristics from daily data.
To verify the accuracy of the Analytical Probabilistic Model for Rainwater Harvesting (APM-RWH) integrated with the proposed HTES method using daily rainfall data during historical periods.
To assess the impact of climate change on RWH system performance using the proposed APM-RWH framework in six climatically diverse Chinese cities.

Study Configuration

Spatial Scale: Six provincial capital cities in China: Beijing, Chongqing, Guangzhou, Jinan, Lanzhou, and Xi’an.
Temporal Scale:
- Historical periods: Varies by city, ranging from 1954–2014 to 1970–2014.
- Future periods: 2025–2100.
- Seasonal focus: Summer rainfall season (June to September).

Methodology and Data

Models used:
- Homogenized Threshold-based Event Separation (HTES) method for daily rainfall event separation.
- Analytical Probabilistic Model for Rainwater Harvesting (APM-RWH).
- Continuous simulation (Yield before Spillage - YBS algorithm) for validation.
Data sources:
- Observed hourly rainfall data (for benchmark and validation).
- Observed daily rainfall data.
- Projected daily rainfall data from the ensemble mean of 16 Global Climate Models (GCMs) from CMIP6 under three Shared Socioeconomic Pathways (ssp126, ssp245, ssp585).

Main Results

The HTES method significantly improved the estimation of mean rainfall event characteristics from daily data, reducing the mean relative error for event duration from 324.65% to 22.86–30.69%, for event depth from 41.08% to 4.09–8.01%, and for interevent time from 10.34% to 3.48–6.61% compared to direct daily data application.
The APM-RWH model, when integrated with HTES-processed daily GCM data, demonstrated comparable accuracy to continuous simulations using measured hourly data, with average Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) values of 0.023 and 0.026, respectively, across the six cities.
Climate change impacts on RWH systems show significant regional variations: humid regions (e.g., Guangzhou) experience substantial increases in water yield but also a sharp rise in flood control pressure, while arid northwestern cities (e.g., Lanzhou) show modest variations.
Under projected climate changes, RWH systems exhibit a significant trade-off: water supply reliability (Re) generally increases, while stormwater control efficiency (Ce) decreases. The average Ce reduction percentage escalates by 4.92% (ssp126), 5.69% (ssp245), and 10.18% (ssp585), while the average Re increase percentage rises by 11.03% (ssp126), 11.58% (ssp245), and 14.51% (ssp585) relative to historical scenarios.
Higher emission scenarios (ssp585) lead to greater rainfall, resulting in the most significant decline in runoff control performance and the highest water supply reliability.
Designing RWH systems with larger storage capacities than currently required emerges as a key solution to simultaneously mitigate future urban flooding risk and optimize rainwater utilization potential. For example, achieving a target Ce of 80% in Beijing under future scenarios requires a tank size more than three times larger than historically (50.68 cubic meters vs. 11.99 cubic meters).

Contributions

Proposed and validated a novel parsimonious daily rainfall event separation method (HTES) that enables Analytical Probabilistic Models (APMs) to accurately quantify Rainwater Harvesting (RWH) system performance using readily available daily rainfall data, overcoming the limitation of conventional APMs requiring high temporal resolution data.
Provided a robust framework for quantitative assessment of RWH systems in data-scarce regions under climate change scenarios.
Offered region-specific, climate-adaptive recommendations for the planning and design of RWH systems in diverse climatic zones of China, considering the trade-offs between stormwater control efficiency and water supply reliability under various emission pathways.
Quantified the impact of different climate change scenarios (ssp126, ssp245, ssp585) on RWH system design parameters and performance indicators.

Funding

National Natural Science Foundation of China (No.52109025)
Natural Science Foundation of Shandong Province (No. ZR2021QE001)
National Natural Science Foundation of China (NO. 52279001)
Future Plan for Young Scholars of Shandong University
Yellow River National Strategy Institute, Shandong University

Citation

@article{Wang2025Parsimonious,
  author = {Wang, Jiachang and Wang, Jiachang and Jiang, Enhui and Wang, Jun and Wang, Jun and Zhang, Shouhong and Guo, Yiping and Yu, Lei and Pan, Xin and Jun, Changhyun and Sivakumar, Bellie},
  title = {Parsimonious analytical modelling of rainwater harvesting systems’ performance under climate change in six Chinese cities},
  journal = {Journal of Hydrology Regional Studies},
  year = {2025},
  doi = {10.1016/j.ejrh.2025.102924},
  url = {https://doi.org/10.1016/j.ejrh.2025.102924}
}

Original Source: https://doi.org/10.1016/j.ejrh.2025.102924