Reducing regional drought vulnerabilities and multi-city robustness conflicts using many-objective optimization under deep uncertainty

Abstract

5Emerging water scarcity concerns in many urban regions are associated with several 6 deeply uncertain factors, including rapid population growth, limited coordination across ad-7 jacent municipalities and the increasing risks for sustained regional droughts. Managing 8 these uncertainties will require that regional water utilities identify coordinated, scarcity-9 mitigating strategies that trigger the appropriate actions needed to avoid water shortages 10 and financial instabilities. This research focuses on the Research Triangle area of North 11 Carolina, seeking to engage the water utilities within Raleigh, Durham, Cary and Chapel 12Hill in cooperative and robust regional water portfolio planning. Prior analysis of this region 13 through the year 2025 has identified significant regional vulnerabilities to volumetric short-14 falls and financial losses. Moreover, efforts to maximize the individual robustness of any 15 of the mentioned utilities also have the potential to strongly degrade the robustness of the 16 others. This research advances a multi-stakeholder Many-Objective Robust Decision Mak-17 ing (MORDM) framework to better account for deeply uncertain factors when identifying 18 cooperative drought management strategies. Our results show that appropriately designing 19 adaptive risk-of-failure action triggers required stressing them with a comprehensive sample 20 of deeply uncertain factors in the computational search phase of MORDM. Search under 21 the new ensemble of states-of-the-world is shown to fundamentally change perceived perfor-22 mance tradeoffs and substantially improve the robustness of individual utilities as well as 23 the overall region to water scarcity. Search under deep uncertainty enhanced the discovery 24 1of how cooperative water transfers, financial risk mitigation tools, and coordinated regional 25 demand management must be employed jointly to improve regional robustness and decrease 26 robustness conflicts between the utilities. Insights from this work have general merit for 27 regions where adjacent municipalities can benefit from cooperative regional water portfolio 28 planning. 29 1 INTRODUCTION 30 Understanding and exploring the combined states-of-the-world (SOWs) that shape wa-31 ter supply risks is a fundamental challenge in any drought mitigation application, defining 32 perceptions and preferences related to key performance objectives, vulnerabilities, and/or 33 the robustness of a system. Fundamental to this challenge is the choice of what uncertain 34 factors should be sampled or included in generating alternative scenarios. Broadly, there 35 are two dominant methodologies that are at present used in water supply planning contexts: 36 (1) pre-specified deterministic scenarios/narratives and (2) globally sampled stochastic sce-37 nario analysis. As an example of deterministic scenario-based planning, Liu et al. (2008) 38 analyzed four semi-arid river basins in the south-western United States seeking to find water 39 management strategies based on integrat...

Climate Adaptation as a Control Problem: Review and Perspectives on Dynamic Water Resources Planning Under Uncertainty

“…might be more appropriate. Many of the studies in Table 1 use long-term hydroclimatic indicators to trigger infrastructure actions (Fletcher et al, 2019;Hui et al, 2018;Kwakkel et al, 2015;Trindade et al, 2017;Zeff et al, 2016). Others rely on short-term indicators such as reservoir storage to trigger operational actions, which may be adapted over time as a response to climate change (Mortazavi-Naeini et al, 2015;Paton et al, 2014).…”

“…However, this shift requires the vulnerability space to be reconciled with the likelihood of future scenarios, usually with either uniformly sampled scenarios or ensemble projections treated probabilistically (Shortridge & Zaitchik, ; Taner et al, , ). The identification of robust alternatives has been addressed both via simulation (e.g., Herman et al, ; McPhail et al, ) and robust optimization (Eker & Kwakkel, ; Giuliani & Castelletti, ; Hamarat et al, ; Trindade et al, ; Watson & Kasprzyk, ). A potential limitation of robust planning frameworks is the tendency to favor static alternatives to be implemented in the near term, which could result in costly overdesign, particularly in the case of infrastructure (Borgomeo et al, ).…”

“…, population(Beh et al, 2015;Fletcher et al, 2017;Trindade et al, 2017), or land use(Kwakkel et al, 2015;.…”

Risk, Robustness and Water Resources Planning Under Uncertainty

“…Similar to recent applications of many‐objective evolutionary algorithms to water resources system planning (Trindade et al, ; Watson & Kasprzyk, ) based on concepts from robust optimization (Hamarat et al, ; Mortazavi‐Naeini et al, ), this step directly embeds a range of uncertain factors in the simulation–optimization process. Embedding uncertain factors in the decision search aims to generate water resources management plans that are robust to a range of future scenarios much wider than the one considered in step 2.…”

“…First, they identify conditions under which the performance of the water investment becomes unacceptable prior to assigning probabilities to these conditions (Brown et al, ; Groves & Lempert, ; Lempert et al, ; Nazemi et al, ; Prudhomme et al, ; Turner et al, ). Second, they emphasize robustness to uncertainty, broadly defined as a decision that performs acceptably well under a wide range of plausible future conditions (Herman et al, ; Hine & Hall, ; Matrosov et al, ; Moody & Brown, ; Trindade et al, ). Third, these approaches highlight the importance of flexibility in water investments, that is, the ability to switch or change a decision depending on what outcomes materialize (Groves et al, ; Haasnoot et al, ; Hino & Hall, ; Jeuland & Whittington, ; Kwakkel et al, ; Woodward et al, ; Zeff et al, ).…”