Abstract
Climate change is modifying the way we design and operate water infrastructure, including reservoirs. A particular issue is that current infrastructure and reservoir management rules will likely operate under changing conditions different to those used in their design. Thus, there is a big need to identify the obsolescence of current operation rules under climate change, without compromising the proper treatment of uncertainty. Acknowledging that decision making benefits from the scientific knowledge, mainly when presented in a simple and easy-to-understand manner, such identification—and the corresponding uncertainty—must be clearly described and communicated. This paper presents a methodology to identify, in a simple and useful way, the time when current reservoir operation rules fail under changing climate by properly treating and presenting its aleatory and epistemic uncertainties and showing its deep uncertainty. For this purpose, we use a reliability–resilience–vulnerability framework with a General Circulation Models (GCM) ensemble under the four Representative Concentration Pathways (RCP) scenarios to compare the historical and future long-term reservoir system performances under its current operation rule in the Limarí basin, Chile, as a case study. The results include percentiles that define the uncertainty range, showing that during the 21st century there are significant changes at the time-based reliability by the 2030s, resilience between the 2030s and 2040s, volume-based reliability by the 2080s, and the maximum failure by the 2070s. Overall, this approach allows the identification of the timing of systematic failures in the performance of water systems given a certain performance threshold, which contributes to the planning, prioritization and implementation timing of adaptation alternatives.
Highlights
This article is an open access articleReservoirs are fundamental infrastructure for water supply and irrigation, especially in semiarid and arid regions, such as Central Chile, characterized by a marked seasonality of the hydrological cycle
The objective of this paper is to identify the obsolescence of current operation rules of a reservoir system under climate change scenarios, and accomplish a clear, simple, and useful representation of this identification for its use by water managers and decision makers, without compromising the complex analysis required in the assessment of climate change uncertainty
In particular the approach takes into account three sources of uncertainty: (a) aleatory uncertainty, i.e., the natural variability represented by intra-General Circulation Models (GCM) uncertainties, (b) epistemic uncertainty, i.e., as represented by the spread of multi-GCM ensembles, and (c) deep uncertainty, i.e., as represented by the choice of Representative Concentration Pathway (RCP) scenario
Summary
Reservoirs are fundamental infrastructure for water supply and irrigation, especially in semiarid and arid regions, such as Central Chile, characterized by a marked seasonality of the hydrological cycle. Historical reservoir performance is expected to worsen with climate change in many cases [6,7,8], building new infrastructure is not always feasible due to economic and environmental constrains, which are likely to increase in time [9,10,11,12]. Developing operational strategies to maximize the performance of existing infrastructure is essential, and represents an opportunity to adapt to climate change [13]. Reservoirs’ reliability depends on operation rules that specify desired storage volumes or releases based on the time of the year and the water demand. Ahmad et al [9], and Fayaed et al [14], identify different approaches used to assess optimal reservoir operation rules, which can be classified into linear programming [15,16], nonlinear programming [17,18,19], dynamic programming [20,21,22], and computational intelligence optimization methods such as fuzzy set programing [23,24] and artificial neural networks tools [25,26]
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