Robust optimisation of urban drought security for an uncertain climate

Abstract Recent experience with drought and a shifting climate has highlighted the vulnerability of urban water supplies to “running out of water” in Perth, south-east Queensland, Sydney, Melbourne and Adelaide and has triggered major investment in water source infrastructure which ultimately will run into tens of billions of dollars. With the prospect of continuing population growth in major cities, the provision of acceptable drought security will become more pressing particularly if the future climate becomes drier. Decision makers need to deal with significant uncertainty about future climate and population. In particular the science of climate change is such that the accuracy of model predictions of future climate is limited by fundamental irreducible uncertainties. It would be unwise to unduly rely on projections made by climate models and prudent to favour solutions that are robust across a range of possible climate futures. This study presents and demonstrates a methodology that addresses the problem of finding “good” solutions for urban bulk water systems in the presence of deep uncertainty about future climate. The methodology involves three key steps: 1) Build a simulation model of the bulk water system; 2) Construct replicates of future climate that reproduce natural variability seen in the instrumental record and that reflect a plausible range of future climates; and 3) Use multi-objective optimisation to efficiently search through potentially trillions of solutions to identify a set of “good” solutions that optimally trade-off expected performance against robustness or sensitivity of performance over the range of future climates. A case study based on the Lower Hunter in New South Wales demonstrates the methodology. It is important to note that the case study does not consider the full suite of options and objectives; preliminary information on plausible options has been generalised for demonstration purposes and therefore its results should only be used in the context of evaluating the methodology. “Dry” and “wet” climate scenarios that represent the likely span of climate in 2070 based on the A1F1 emissions scenario were constructed. Using the WATHNET5 model, a simulation model of the Lower Hunter was constructed and validated. The search for “good” solutions was conducted by minimizing two criteria, 1) the expected present worth cost of capital and operational costs and social costs due to restrictions and emergency rationing, and 2) the difference in present worth cost between the “dry” and “wet” 2070 climate scenarios. The constraint was imposed that solutions must be able to supply (reduced) demand in the worst drought. Two demand scenarios were considered, “1.28 x current demand” representing expected consumption in 2060 and “2 x current demand” representing a highly stressed system. The optimisation considered a representative range of options including desalination, new surface water sources, demand substitution using rainwater tanks, drought contingency measures and operating rules. It was found the sensitivity of solutions to uncertainty about future climate varied considerably. For the “1.28 x demand” scenario there was limited sensitivity to the climate scenarios resulting in a narrow range of trade-offs. In contrast, for the “2 x demand” scenario, the trade-off between expected present worth cost and robustness was considerable. The main policy implication is that (possibly large) uncertainty about future climate may not necessarily produce significantly different performance trajectories. The sensitivity is determined not only by differences between climate scenarios but also by other external stresses imposed on the system such as population growth and by constraints on the available options to secure the system against drought. Recent experience with drought and a shifting climate has highlighted the vulnerability of urban water supplies to “running out of water” in Perth, south-east Queensland, Sydney, Melbourne and Adelaide and has triggered major investment in water source infrastructure which ultimately will run into tens of billions of dollars. With the prospect of continuing population growth in major cities, the provision of acceptable drought security will become more pressing particularly if the future climate becomes drier. Decision makers need to deal with significant uncertainty about future climate and population. In particular the science of climate change is such that the accuracy of model predictions of future climate is limited by fundamental irreducible uncertainties. It would be unwise to unduly rely on projections made by climate models and prudent to favour solutions that are robust across a range of possible climate futures. This study presents and demonstrates a methodology that addresses the problem of finding “good” solutions for urban bulk water systems in the presence of deep uncertainty about future climate. The methodology involves three key steps: 1) Build a simulation model of the bulk water system; 2) Construct replicates of future climate that reproduce natural variability seen in the instrumental record and that reflect a plausible range of future climates; and 3) Use multi-objective optimisation to efficiently search through potentially trillions of solutions to identify a set of “good” solutions that optimally trade-off expected performance against robustness or sensitivity of performance over the range of future climates. A case study based on the Lower Hunter in New South Wales demonstrates the methodology. It is important to note that the case study does not consider the full suite of options and objectives; preliminary information on plausible options has been generalised for demonstration purposes and therefore its results should only be used in the context of evaluating the methodology. “Dry” and “wet” climate scenarios that represent the likely span of climate in 2070 based on the A1F1 emissions scenario were constructed. Using the WATHNET5 model, a simulation model of the Lower Hunter was constructed and validated. The search for “good” solutions was conducted by minimizing two criteria, 1) the expected present worth cost of capital and operational costs and social costs due to restrictions and emergency rationing, and 2) the difference in present worth cost between the “dry” and “wet” 2070 climate scenarios. The constraint was imposed that solutions must be able to supply (reduced) demand in the worst drought. Two demand scenarios were considered, “1.28 x current demand” representing expected consumption in 2060 and “2 x current demand” representing a highly stressed system. The optimisation considered a representative range of options including desalination, new surface water sources, demand substitution using rainwater tanks, drought contingency measures and operating rules. It was found the sensitivity of solutions to uncertainty about future climate varied considerably. For the “1.28 x demand” scenario there was limited sensitivity to the climate scenarios resulting in a narrow range of trade-offs. In contrast, for the “2 x demand” scenario, the trade-off between expected present worth cost and robustness was considerable. The main policy implication is that (possibly large) uncertainty about future climate may not necessarily produce significantly different performance trajectories. The sensitivity is determined not only by differences between climate scenarios but also by other external stresses imposed on the system such as population growth and by constraints on the available options to secure the system against drought. Please cite this report as: Mortazavi, M, Kuczera, G, Kiem, AS, Henley, B, Berghout, B,Turner, E, 2013 Robust optimisation of urban drought security for an uncertain climate. National Climate Change Adaptation Research Facility, Gold Coast, pp. 74

Assessment of risks to public water supply from low flows and harmful water quality in a changing climate

Water resources planning and management by water utilities have traditionally been based on consideration of water availability. However, the reliability of public water supplies can also be influenced by the quality of water bodies. In this study, we proposed a framework that integrates the analysis of risks of inadequate water quality and risks of insufficient water availability. We have developed a coupled modeling system that combines hydrological modeling of river water quantity and quality, rules for water withdrawals from rivers into storage reservoirs, and dynamical simulation of harmful algal blooms in storage reservoirs. We use this framework to assess the impact of climate change, demand growth, and land‐use change on the reliability of public water supplies. The proposed method is tested on the River Thames catchment in the south of England. The results show that alongside the well‐known risks of rising water demand in the south of England and uncertain impacts of climate change, diffuse pollution from agriculture and effluent from upstream waste water treatment works potentially represent a threat to the reliability of public water supplies in London. We quantify the steps that could be taken to ameliorate these threats, though even a vigorous pollution‐prevention strategy would not be sufficient to offset the projected effects of climate change on water quality and the reliability of public water supplies. The proposed method can help water utilities to recognize their system vulnerability and evaluate the potential solutions to achieve more reliable water supplies. supplie

Multi-objective optimization of urban water resource systems

Research Doctorate - Doctor of Philosophy (PhD)The provision of a water supply that is secure in the face of severe drought is a primary objective for urban water agencies – “running out of water” is not a viable option for a large city. However, there are other objectives that conflict with the primary one – these include minimizing costs and environmental impacts. A major challenge facing decision makers in the urban water sector is dealing with the trade-offs between these conflicting objectives. Multi-objective optimization methods have the potential to identify the optimal trade-offs between the competing objectives. The principal aim of this thesis is to address the shortcomings in existing multi-objective optimization applications to produce methods of greater practical relevance to urban water resource management. Review of past studies identified three practically significant shortcomings. Focusing exclusively on either long-term (or infrastructure) options or on short-term options such as operation rules may lead to sub-optimal solutions. The use of short climate forcing data time series in simulation models to evaluate drought security can produce solutions that make the system highly vulnerable to severe drought. Finally, the setting of a priori environmental constraints may hide trade-offs between environmental, economic and security factors that are of considerable interest to decision makers. These shortcomings are addressed by a new multi-objective methodology that exploits the ability of evolutionary algorithms to handle complex objective functions and simulation models. The principal novelty is the explicit treatment of drought security. A case study based on the headworks system for Australia’s largest city, Sydney, demonstrates the practical significance of these shortcomings and, importantly, the ability of the new approach to deal with these shortcomings in a practicable manner. In the face of urban population growth and the accompanying growth in water demand, the performance of the urban water resource system is expected to deteriorate over time. This will result in the need to intervene and adapt the system to the changing conditions. The scheduling capacity expansion problem seeks to identify the optimal schedule for the changes to the system. In past studies, this problem has been largely tackled by minimizing the total present worth of capital, operational and rationing costs. A significant drawback of minimizing the total present worth cost is that it is likely to produce solutions that lead to more severe and frequent rationing in the future. Such a solution is likely to be socially unacceptable. A multi-objective formulation for the scheduling capacity expansion problem is developed to overcome this shortcoming while addressing the need to explicitly deal with drought security and jointly optimize operating and infrastructure decisions. The formulation enables the trade-off between cost and equity (the equal sharing of the burden of restrictions over the planning horizon) to be explored. A case study based on the headworks system for Australia’s capital city, Canberra, demonstrates the advantages of the new approach. The optimization of urban water resource systems requires running simulation models tens of thousands of times. Given that simulation run times can range from less than a minute to thirty or more minutes, it is important to use a multi-objective optimization method which converges with the least number of evaluations (or simulations). To address this need, a detailed assessment is conducted of three benchmark multi-objective optimization methods and three newly developed methods based on ant colony optimization using case studies based on the Canberra and Sydney systems. No one method emerges as superior, although two of the six methods are identified as inferior

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

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

Comparison of Heuristic Methods Applied for Optimal Operation of Water Resources

Water resources optimization problems are usually complex and hard to solve using the ordinary optimization methods, or they are at least  not economically efficient. A great number of studies have been conducted in quest of suitable methods capable of handling such problems. In recent years, some new heuristic methods such as genetic and ant algorithms have been introduced in systems engineering. Preliminary applications of these methods in water resources problems have shown that some of them are powerful tools, capable of solving complex problems. In this paper, the application of such heuristic methods as Genetic Algorithm (GA) and Ant Colony Optimization (ACO) have been studied for optimizing reservoir operation. The Dez Dam reservoir inIranwas chosen for a case study. The methods were applied and compared using short-term (one year) and long-term models. Comparison of the results showed that GA outperforms both DP and ACO in finding true global optimum solutions and operating rules

Efficient pathways to zero-carbon energy use by water supply utilities: an example from London, UK

Urban water utilities are increasing their use of energy-intensive technologies such as desalination and long-distanced pumped transfers. Under pressure to reduce their energy-related carbon emissions to zero, water utilities have devised a variety of energy management strategies, including the purchase of renewable energy and self-generation of electricity using locally installed renewables. These strategies will incur different costs for the utility, whilst some may have implications for the reliability of water supply systems. Yet the trade-offs between costs, water security and energy sustainability remain unexplored. Here, we present a regional scale analysis to test competing energy strategies, mapping pathways to zero carbon energy and water security. Results from a case-study of the London water system show a balanced approach that allows for some energy self-generation, using biogas, solar and wind, while also purchasing green energy credits from the electricity supply grid can best navigate this trade-off. Balanced investment plans can accommodate energy-intensive water supply techniques such as long-distance transfers, desalination and effluent reuse while meeting energy targets. By becoming energy generators and also adopting more flexible arrangements for energy use, water utilities could become significant players in energy markets

Risk, Robustness and Water Resources Planning Under Uncertainty

Risk‐based water resources planning is based on the premise that water managers should invest up to the point where the marginal benefit of risk reduction equals the marginal cost of achieving that benefit. However, this cost‐benefit approach may not guarantee robustness under uncertain future conditions, for instance under climatic changes. In this paper, we expand risk‐based decision analysis to explore possible ways of enhancing robustness in engineered water resources systems under different risk attitudes. Risk is measured as the expected annual cost of water use restrictions, while robustness is interpreted in the decision‐theoretic sense as the ability of a water resource system to maintain performance—expressed as a tolerable risk of water use restrictions—under a wide range of possible future conditions. Linking risk attitudes with robustness allows stakeholders to explicitly trade‐off incremental increases in robustness with investment costs for a given level of risk. We illustrate the framework through a case study of London's water supply system using state‐of‐the ‐art regional climate simulations to inform the estimation of risk and robustness.ISSN:2328-427

Evaluation of factors related to depression in peritoneal dialysis patients: a multicenter cross-sectional study

Abstract Background End-stage renal disease (ESRD) is serious global public health challenge in many developing countries. Treatment of ESRD is carried out through renal replacement therapy like peritoneal dialysis (PD). Depression is the most common mood disorder which has a strong impact on the quality of life in patients with ESRD. Little is known about the prevalence and risk factors of depression in peritoneal dialysis patients. Method and materials A multicenter cross-sectional study was conducted on 164 adult ESRD patients undergoing peritoneal dialysis for at least three months who referred to the peritoneal dialysis centers of Al-Zahra, Noor & Ali Asghar hospitals, Isfahan, Iran from May to August 2019. Beck Depression Inventory Second Edition questionnaire was used to measure the symptoms of depression and its severity. Results 43.5% of patients had some levels of depression. Assessing the association of depression with demographic and PD-related factors showed that there was no significant difference regarding age, BMI, dialysis adequacy and residual kidney function, dialysis frequency, type of dialysis solution used, disease duration, and age at the start of dialysis. Ordinal logistics regression analysis showed significant association between depression severity categories and gender (OR = 0.397, CI: 0.160–0.985, p = 0.046), marital status (OR = 2.983, CI: 1.180–7.541, p = 0.021), having a separate room for dialysis (OR = 2.511, CI: 1.108–5.692, p = 0.027). Conclusion As our findings have revealed 43.5% of our participants suffered from mild-to-severe depression, we suggest careful attention and routine evaluation for depression in PD patients, especially women and single patients and those who have low socioeconomic status

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

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