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Planning water resource systems is challenged primarily by two realities. First, uncertainty is inherent in the predictions of future supplies and demands due for example to hydrological variability and climate change. To build societal resilience water planners should seek to enhance the adaptability and robustness of water resource system interventions. Second, water resource developments typically involve competing interests which implies considering the trade-offs and synergies implied by the highest performing combinations of development options is useful. This work describes a real options based planning framework that generates adaptive and robust water system design alternatives able to consider and trade-off different goals. The framework can address different types of uncertainties and suggests the highest performing designs across multiple evaluation criteria, such as financial costs and water supply service performance metrics. Using a global city’s water resource and supply system as a demonstration of the approach, we explore the trade-offs between a long-term water management plan’s infrastructure services (service resilience, reliability, vulnerability) and its financial costs under supply and demand uncertainty. The set of trade-off solutions consist of different investment plans which are adaptive and robust to future changing conditions. Results show that the highest performing plans lower net present value (NPV) of needed investments by up to 18%, while maintaining similar performance across the other objectives. The real option value of delaying investments as much as possible approaches up to 14% of total NPV.
|Journal||Advances in Water Resources|
|Publication status||Published - 12 Jan 2022|
- Water resource systems planning
- Adaptive infrastructure planning
- Real options analysis
- Robust decision making
- Multi-objective search
- Stakeholder-driven environmental planning
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- 2 Finished
GCRF: DAMS 2.0: Design and assessment of resilient and sustainable interventions in water-energy-food-environment Mega-Systems
Hulme, D., Anderson, K., Bottacin Busolin, A., Dimova, R., Foster, T., Harou, J., Imai, K., Larkin, A., Lavers, T., Mancarella, P., Mutale, J., Panteli, M., Sen, K. & Whittington, D.
1/10/17 → 31/12/21
Uncertainty reduction in Models For Understanding deveLopment Applications
15/06/15 → 14/12/19