Optimal adaptation pathway for sustainable low impact development planning under deep uncertainty of climate change: A greedy strategy

Te Xu; Ke Li; Bernard A Engel; Haifeng Jia; Linyuan Leng; Zhaoxia Sun; Shaw L Yu

doi:10.1016/j.jenvman.2019.109280

Optimal adaptation pathway for sustainable low impact development planning under deep uncertainty of climate change: A greedy strategy

J Environ Manage. 2019 Oct 15:248:109280. doi: 10.1016/j.jenvman.2019.109280. Epub 2019 Jul 18.

Authors

Te Xu¹, Ke Li², Bernard A Engel³, Haifeng Jia⁴, Linyuan Leng¹, Zhaoxia Sun⁵, Shaw L Yu⁶

Affiliations

¹ School of Environment, Tsinghua University, Beijing, China.
² School of Environment, Tsinghua University, Beijing, China; CentraleSupélec, Université Paris-Saclay, Gif-sur-Yvette cedex, France.
³ Department of Agricultural & Biological Engineering, Purdue University, West Lafayette, IN, USA.
⁴ School of Environment, Tsinghua University, Beijing, China; Jiangsu Collaborative Innovation Center of Technology and Material of Water Treatment, Suzhou, China. Electronic address: jhf@tsinghua.edu.cn.
⁵ Jiangsu Collaborative Innovation Center of Technology and Material of Water Treatment, Suzhou, China.
⁶ Department of Civil & Environmental Engineering, University of Virginia, Charlottesville, VA, USA.

PMID: 31326726
DOI: 10.1016/j.jenvman.2019.109280

Abstract

Robustness and cost effectiveness are major concerns for sustainable stormwater management under deep uncertainty of climate change. Given that many traditional static planning strategies are not working with unpredictable future conditions, the possibility of system failure, and the lock-in effects, the Adaptation Pathway (AP) approach was adopted for dynamically robust and cost-effective planning in this paper. In order to increase optimization accuracy of multi-staged planning, a continuous definition of the AP optimization problem was raised by improving the simplified versions in existing studies. A case study in Suzhou, a provincial pilot Sponge City in China undergoing increasing annual rainfall and severe water environment deterioration, was included by integrating Long-Term Hydrologic Impact Assessment-Low Impact Development model with optimization methods, aiming to persistently control the non-point source total phosphorus loading below an acceptable amount in the following unforeseen 20 years via multi-staged low-impact development (LID) construction. A novel optimization method developed by the authors in a companion paper, namely marginal-cost-based greedy strategy (MCGS), was successfully applied to efficiently solve the continuous version of the AP optimization problem. The popular genetic algorithm (GA) was used as a contrast. A weather generator was elaborated based on four Representative Concentration Pathway scenarios and 17 spatial downscaled general circulation models to simulate the unforeseen future annual rainfalls that helped with evaluating cost effectiveness of each prospective LID plan. Results showed that the adaptation pathways optimized by MCGS could save the whole life net present cost of an LID plan by 1%-60% compared with those optimized by GA, and the computational efficiency of MCGS was over 13 times faster than GA.

Keywords: Adaptation pathway; Climate change; Deep uncertainty; Greedy strategy; Low-impact development; Robust decision making.

MeSH terms

China
Cities
Climate Change*
Prospective Studies
Social Planning*
Uncertainty