Robustness-Based Evaluation of Budhigandaki Multipurpose Hydropower Project of Nepal Under Climate Change

The conventional tools of decision-making in water resources infrastructure planning have been developed for problems with well-characterized uncertainties and are ill-suited for problems involving climate nonstationarity. In the past 20 years, a predict-then-act-based approach to the incorporation of climate nonstationarity has been widely adopted in which the outputs of biascorrected climate model projections are used to evaluate planning options. However, the ambiguous nature of results has often proved unsatisfying to decision makers. This paper presents the use of a bottom-up, decision scaling framework for the evaluation of water resources infrastructure design alternatives regarding their robustness to climate change and expected value of performance. For the analysis, Budhigandaki Multipuropose Hydroelectric project of Nepal is selected for analysis.The analysis begins with an assessment of the vulnerability of the alternative designs under a wide domain of systematically-generated plausible future climates and utilizes downscaled climate projections ex post to inform likelihoods within a risk-based evaluation. The outcomes under different project designs are compared by way of a set of decision criteria, including the performance under the most likely future, expected value of performance across all evaluated futures and robustness.. The results indicate that recommendations from the decision scaling analysis can be substantially different from the scenario-led approach, alleviate common shortcomings related to the use of climate projections in water resources planning, and produce recommendations that are more robust to future climate uncertainty. From the analysis we can also say that reliability, vulnerability and resilient time of project is highly dependent on precipitation and demand discharge. The project is found to be more reliable, more resilient and less vulnerable with increase in precipitation with lower water demand and not significantly affected by increase in temperature. For all combinations of weather and demand scenarios, the value of reliability and resilience time are less than 0.96 and greater than 6 month respectively so the project was not found to be reliable and resilient based on climate change scenario using decision tree framework.

Keywords: Climate change,Decision Tree framework ,Deep uncertainty, Climate variability, Robustness , Decision scaling