The development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g. model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts.

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Evolutionary algorithms and other metaheuristics in water resources

A highly uncertain future due to changes in climate, technology and socio-economics has led to the realisation that identification of "best-guess" future conditions might no longer be appropriate. Instead, multiple plausible futures need to be considered, which requires (i) uncertainties to be described with the aid of scenarios that represent coherent future pathways based on different sets of assumptions, (ii) system performance to be represented by metrics that measure insensitivity (i.e. robustness) to changes in future conditions, and (iii) adaptive strategies to be considered alongside their more commonly used static counterparts. However, while these factors have been considered in isolation previously, there has been a lack of discussion of the way they are connected. In order to address this shortcoming, this paper presents a multidisciplinary perspective on how the above factors fit together to facilitate the development of strategies that are best suited to dealing with a deeply uncertain future. Integrated view of concepts for dealing with a highly uncertain future in modelling.Role of multiple plausible futures amongst other paradigms for modelling the future.Relation of multiple plausible futures to deep, local/global uncertainty and VUCA.Overview of how different scenario approaches help to identify plausible futures.Factors affecting static and adaptive approaches to robustness to multiple futures.

An uncertain future, deep uncertainty, scenarios, robustness and adaptation

A survey of decision-making approaches for climate change adaptation: : Are robust methods the way forward?

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2019WR025502

Climate adaptation as a control problem: Review and perspectives on dynamic water resources planning under uncertainty

Gene expression programming (GEP) is used as a new method for estimating side weir discharge coefficient.Two sets of experimental data were used to evaluate the models.New equation proposed by GEP can be used for estimating discharge coefficient in rectangular sharp-crested side weirs. In this study, gene expression programming (GEP) is employed as a new method for estimating the side weir discharge coefficient. The accuracy of existing equations in evaluating the side weir discharge coefficient is first examined. Afterward, taking into consideration the dimensionless parameters that affect the estimation of this parameter and sensitivity analysis, five different models are presented. Coefficient determination (R2), root mean square error (RMSE), mean absolute relative error (MARE), scatter index (SI) and BIAS are used for measuring the models' performance. Two sets of experimental data are applied to evaluate the models. According to the results obtained indicate that the model with Froude number (F1), dimensionless weir length (b/B), ratio of weir length to depth of upstream flow (b/y1), and ratio of weir height to its length (p/y1) parameters of R2=0.947, MARE=0.05, RMSE=0.037, BIAS=0.01 and SI=0.067, performed the best. Accordingly, this new equation proposed through GEP can be utilized for estimating the discharge coefficient in rectangular sharp-crested side weirs.

Gene expression programming to predict the discharge coefficient in rectangular side weirs

Urban bulk water systems supply water with high reliability and, in the event of extreme drought, must avoid catastrophic economic and social collapse. In view of the deep uncertainty about future climate change, it is vital that robust solutions be found that secure urban bulk water systems against extreme drought. To tackle this challenge an approach was developed integrating: 1) a stochastic model of multi-site streamflow conditioned on future climate change scenarios; 2) Monte Carlo simulation of the urban bulk water system incorporated into a robust optimization framework and solved using a multi-objective evolutionary algorithm; and 3) a comprehensive decision space including operating rules, investment in new sources and source substitution and a drought contingency plan with multiple actions with increasingly severe economic and social impact. A case study demonstrated the feasibility of this approach for a complex urban bulk water supply system. The primary objective was to minimize the expected present worth cost arising from infrastructure investment, system operation and the social cost of "normal" and emergency restrictions. By introducing a second objective which minimizes either the difference in present worth cost between the driest and wettest future climate change scenarios or the present worth cost for driest climate scenario, the trade-off between efficiency and robustness was identified. The results show that a significant change in investment and operating strategy can occur when the decision maker expresses a stronger preference for robustness and that this depends on the adopted robustness measure. Moreover, solutions are not only impacted by the degree of uncertainty about future climate change but also by the stress imposed on the system and the range of available options.

Robust optimization to secure urban bulk water supply against extreme drought and uncertain climate change

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017EF000730

Risk, Robustness and Water Resources Planning Under Uncertainty

Significant population increase in urban areas is likely to result in a deterioration of drought security and level of service provided by urban water resource systems. One way to cope with this is to optimally schedule the expansion of system resources. However, the high capital costs and environmental impacts associated with expanding or building major water infrastructure warrant the investigation of scheduling system operational options such as reservoir operating rules, demand reduction policies, and drought contingency plans, as a way of delaying or avoiding the expansion of water supply infrastructure. Traditionally, minimizing cost has been considered the primary objective in scheduling capacity expansion problems. In this paper, we consider some of the drawbacks of this approach. It is shown that there is no guarantee that the social burden of coping with drought emergencies is shared equitably across planning stages. In addition, it is shown that previous approaches do not adequately exploit the benefits of joint optimization of operational and infrastructure options and do not adequately address the need for the high level of drought security expected for urban systems. To address these shortcomings, a new multiobjective optimization approach to scheduling capacity expansion in an urban water resource system is presented and illustrated in a case study involving the bulk water supply system for Canberra. The results show that the multiobjective approach can address the temporal equity issue of sharing the burden of drought emergencies and that joint optimization of operational and infrastructure options can provide solutions superior to those just involving infrastructure options.

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Application of multiobjective optimization to scheduling capacity expansion of urban water resource systems

Choosing secure water resource management plans inevitably requires trade-offs between risks (for a variety of stakeholders), costs, and other impacts. We have previously argued that water resources planning should focus upon metrics of risk of water restrictions, accompanied by extensive simulation and scenario-based exploration of uncertainty. However, the results of optimization subject to risk constraints can be sensitive to the specification of tolerable risk, which may not be precisely or consistently defined by different stakeholders. In this paper, we recast the water resources planning problem as a multiobjective optimization problem to identify least cost schemes that satisfy a set of criteria for tolerable risk, where tolerable risk is defined in terms of the frequency of water use restrictions of different levels of severity. Our proposed method links a very large ensemble of climate model projections to a water resource system model and a multiobjective optimization algorithm to identify a Pareto optimal set of water resource management plans across a 25 years planning period. In a case study application to the London water supply system, we identify water resources management plans that, for a given financial cost, maximize performance with respect to one or more probabilistic criteria. This illustrates trade-offs between financial costs of plans and risk, and between risk criteria for four different severities of water use restrictions. Graphical representation of alternative sequences of investments in the Pareto set helps to identify water management options for which there is a robust case for including them in the plan.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2015WR018164

Mohammad Mortazavi-Naeini

Papers

Robust optimization to secure urban bulk water supply against extreme drought and uncertain climate change

Risk, Robustness and Water Resources Planning Under Uncertainty

Application of multiobjective optimization to scheduling capacity expansion of urban water resource systems

Trading-off tolerable risk with climate change adaptation costs in water supply systems

The Spatial Dynamics of Droughts and Water Scarcity in England and Wales