Integrated Dynamic Planning of Adaptation Technologies Using Multi-Objective Optimization
Abstract
The need to consider the long-term, ambiguity in who takes responsibility and the innate uncertainties in climate projections are barriers for local governments when deciding to take action on the intensifying impacts of climate change (Carlsson-Kanyama et al., 2013). A recent suggested strategy is using the concept of "adaptation pathways" to systematically and dynamically sequence adaptation solutions across a long time-frame (Haasnoot et al., 2013; Kwakkel et al., 2016), where each pathway represents an alternative plan. A sequential approach can realistically consider the short-term constraints with a goal-oriented long term perspective.
This study develops a method to identify optimal adaptation pathways using a multi-objective genetic algorithm that considers the interactions between adaptation technologies across multiple sectors. A district especially vulnerable to urban flooding and heat island effects in Seoul, South Korea was selected as a sample site to model the effect of 8 nature-based and human-built adaptation technologies. Future climate impacts and technology effects were modeled from 2015 to 2045. Optimization was conducted using a non-dominated sorting algorithm (NSGA-II) and the optimality of plans were determined by two decision variables - total adaptation effect on reducing flooding, heat-related moralities and mean radiant temperature (MRT) as well as cost. Optimized pathways varied significantly depending on the planning time horizon (1~10 year intervals) and the variability of decision variables. Rather than fixing the budget constraint or the adaptation goal, this model is able to provide real-time simulation of optimal plans depending on the user's needs and uncertainties. By developing this model into a user interface, the usability of this method in planning for adaptation will be evaluated by actual policy practitioners. Benchmarking this case study and methodology, decision-makers will be able to actively engage in developing their adaptation pathway. The option to integrate and disintegrate adaptation planning across climate impacts and sectors ultimately lowers the knowledge barrier while maintaining high scientific reliability in the results.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFMNH53B0810H
- Keywords:
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- 1630 Impacts of global change;
- GLOBAL CHANGE;
- 4321 Climate impact;
- NATURAL HAZARDS;
- 4327 Resilience;
- NATURAL HAZARDS;
- 4328 Risk;
- NATURAL HAZARDS