Abstract
The common practices for the planning and management of Water Resources Systems (WSSs) have been challenged in the last few decades by global climate change processes, which are observed around the world in increasing frequencies. Climate change is manifested by climate variability, temperature increase, and extreme events such as droughts and floods, which have a decisive effect on natural resource availability and in turn on water quality. Historical records may not be sufficient to reliably account for uncertain future predictions under climate change conditions. While such highly uncertain situations become the “normal” case worldwide, the traditional practices of probabilistic risk measures cannot be used to appropriately quantify the uncertain phenomena under non-stationarity conditions. To better account for uncertain future conditions, the objective of this study is to develop a water management model based on Info-Gap Decision Theory (IGDT) using optimization under deep uncertainty conditions. The Info-Gap theory is a framework that measures the confidence in the operational decisions by quantifying the robustness to uncertainty without accounting for any probabilistic data. To demonstrate the method as a tool to better guide the long-term sustainable operation of the water supply system under uncertain future conditions, we applied the Info-Gap model to the Sea of Galilee (SoG) regional WSS, which is a significant part of the Israeli National Water System (INWS). For Israel, which is, like other Middle East semi-arid regions, prone to dry conditions and limited water availability, there are well-founded concerns that prolonged periods of drought lie ahead, as a consequence of the global climate change processes. This study contributes a management tool for decision making under deep uncertainty to improve the decision-making process and better adapt to unpredictable uncertain future conditions. We demonstrate how the IGDT could be formulated and used to analyze WSSs under different settings and demonstrate how decisions could be derived from the IGDT formulation. We also show a sensitivity analysis for the obtained solutions.
Highlights
Introduction iationsThe optimal planning and management of Water Supply Systems (WSSs) require the consideration of multiple aspects to assure that the needs of all stakeholders are satisfied [1].The complexity and variety of system components that compose the Water Resources Systems (WSSs), the size of these components and the large sums of money involved in the regular operation, modification and future expansion of WSSs intensify the importance of optimal decision-making [2].Traditionally, decision-making in WSSs deals with operation and investment decisions for spatial planning and construction efforts to utilize the available water resources in the most effective ways [3]
We focused on the impact of climate change related to hydrological uncertainty, where only the replenishment into the natural resources is taken as an uncertain parameter
To incorporate explicit considerations of uncertainty, an appropriate decision-making framework under uncertainty should be selected such that the real nature of the problem will be reflected during the modeling process, and that the results are usable in the real world
Summary
In the past two decades, the Info-Gap decision theory gained a significant amount of applications in a variety of fields, such as engineering, economics, ecology, environmental protection, biology, medicine, project management, and national security [6,7]. Hine and Hall [17] introduced IGDT to the field of flood management as an alternative to probability and fuzzy sets methods, to account for the uncertainty more adequately in highly uncertain fluvial rivers. An additional application of Info-Gap analysis to a flood risk management problem was performed in [6], where few defense rising options have been considered to deal with potential damage caused by a given depth of floodwater. The objective of this research is to develop a water management model based on the Info-Gap theory using optimization under uncertainty conditions to guide the long-term operation of the Sea of Galilee (SoG) WSS
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