A bottom-up robust optimization framework for identifying river basin development pathways under deep climate uncertainty
Abstract
Hydroclimatic nonstationarity due to climate change poses challenges for long-term water infrastructure planning in river basin systems. While designing strategies that are flexible or adaptive hold intuitive appeal, development of well-performing strategies requires rigorous quantitative analysis that address uncertainties directly while making the best use of scientific information on the expected evolution of future climate. Multi-stage robust optimization (RO) offers a potentially effective and efficient technique for addressing the problem of staged basin-level planning under climate change, however the necessity of assigning probabilities to future climate states or scenarios is an obstacle to implementation, given that methods to reliably assign probabilities to future climate states are not well developed. We present a method that overcomes this challenge by creating a bottom-up RO-based framework that decreases the dependency on probability distributions of future climate and rather employs them after optimization to aid selection amongst competing alternatives. The iterative process yields a vector of `optimal' decision pathways each under the associated set of probabilistic assumptions. In the final phase, the vector of optimal decision pathways is evaluated to identify the solutions that are least sensitive to the scenario probabilities and are most-likely conditional on the climate information. The framework is illustrated for the planning of new dam and hydro-agricultural expansions projects in the Niger River Basin over a 45-year planning period from 2015 to 2060.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.H51A1416T
- Keywords:
-
- 1834 Human impacts;
- HYDROLOGYDE: 1880 Water management;
- HYDROLOGYDE: 6309 Decision making under uncertainty;
- POLICY SCIENCESDE: 6344 System operation and management;
- POLICY SCIENCES