Improving urban sustainability and resilience with the optimal arrangement of water-energy-food related practices

Abstract

Water-, energy-, and food (WEF) related practices, such as low impact development (LID), residential solar panels, and rooftop urban agriculture, have been applied to improve urban sustainability and resilience under climate change and urbanization. However, most practices require space. This requirement may result in competition for land. In addition, not all newly built practices benefit the environment from the life cycle perspective. Therefore, this study aims to develop a systematic WEF-related practice planning method to improve urban sustainability and resilience in a limited space. The core method is a multi-objective optimization model that considers the performance and environmental impacts of the selected practices. The assessment was conducted in a densely populated area in Taipei, the capital city of Taiwan, to describe the planning processes and demonstrate the feasibility of the methods. In the Taipei case, five goals were defined: the supply of WEF, the sponge city development target, and the greenhouse gas reduction target. The optimal results of the multi-objective optimization model indicated the closeness of the optimal implementation of WEF-related practices to achieving the goals. The results showed that the optimal arrangement of WEF-related practices could provide water supply benefits and was favorable for developing a sponge city. According to the sensitivities, to achieve urban sustainability and resilience, the priorities in order of importance are as follows: establish a rainwater harvesting system for buildings, encourage the implementation of rooftop photovoltaic systems, and improve the materials and processes used solar panel and bioretention cell production. The systematic planning method provides a quantitative assessment and delivers practical cross-sectoral integrated strategies for decision-making.

Keywords: Life Cycle Assessment (LCA); Low-impact development (LID); Multi-objective optimization; Photovoltaic system; Spatial analysis; Urban agriculture.