Adaptive operation policies for reservoir management in a changing world

Jiajia Huang, Wenyan Wu, Q. J. Wang, H. Maier, J. Hughes
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Abstract

: Reservoirs are essential infrastructure, supplying water for domestic, industrial and irrigation uses. Due to long-term climate and water demand changes, the performance of reservoirs may decrease throughout their lifespan, potentially requiring interventions such as reservoir expansion and/or water demand reduction. However, these interventions are often expensive and result in prolonged social and environmental disruptions. Consequently, there is a need to explore opportunities to enhance reservoir performance before these interventions are necessary. Adapting reservoir operation policies, which are functions to assist in making water release decisions, to cater for changed future water availability and demand conditions could best utilise the capacity of existing reservoir systems and potentially delay costly or disruptive interventions. In this study, the benefits of adapting reservoir policies as part of long-term reservoir management are demonstrated for a proposed water supply reservoir in the Northern Territory, Australia. This is done by directly optimising parameters (weights and biases) in an artificial neural network (ANN)-based reservoir operation policy model through a multi-objective robust optimisation framework with the aim to identify operation policies that can perform well under various plausible future conditions. Results show that the utilisation of adaptive operation policies can effectively manage future decadal changes in water availability and demand. Such policies generally show better performance, with lower water supply deficit and water storage violation values, compared to operation policies that remain stationary in the future, especially when the future is drier with increasing water demand (Figure 1). These changes in system performance can be explained by analysing the changes in the characteristics of ANN-based operation policy. For example, operation policies that adapt to conditions in the 2030s tend to release more water, leading to a significantly lower water supply deficit but a slightly higher water storage violation. Furthermore, the narrower performance range of adaptive operation policies compared to that of fixed operation policies indicates reduced performance uncertainty, which allows us to schedule additional interventions strategically, ensuring they are neither too late nor too soon. In summary, adaptive operation policies can provide various benefits for long-term reservoir management and ensure a reliable and secure source of water supply in a changing world.
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变化世界中水库管理的适应性操作策略
水库是必不可少的基础设施,为家庭、工业和灌溉用水供水。由于长期气候和水需求的变化,水库的性能可能在其整个生命周期中下降,可能需要采取诸如水库扩建和/或减少水需求等干预措施。然而,这些干预措施往往是昂贵的,并导致长期的社会和环境破坏。因此,在进行必要的干预之前,有必要探索提高油藏性能的机会。调整水库运行政策是协助作出放水决定的职能,以适应未来水供应和需求条件的变化,可以最好地利用现有水库系统的能力,并可能推迟昂贵或破坏性的干预措施。在这项研究中,调整水库政策作为长期水库管理的一部分的好处被证明在澳大利亚北领地拟议的供水水库。这是通过多目标鲁棒优化框架直接优化基于人工神经网络(ANN)的油藏操作策略模型中的参数(权重和偏差)来实现的,目的是确定在各种可能的未来条件下能够表现良好的操作策略。结果表明,利用适应性操作政策可以有效地管理未来年代际水供应和水需求的变化。与未来保持稳定的运行策略相比,特别是当未来的水需求增加,变得更加干燥时(图1),这些策略通常表现出更好的性能,具有更低的供水赤字和储水违规值。这些系统性能的变化可以通过分析基于人工神经网络的运行策略特征的变化来解释。例如,适应21世纪30年代条件的操作政策往往会释放更多的水,导致供水赤字显著降低,但储水量违规程度略高。此外,与固定操作策略相比,自适应操作策略的性能范围较窄,这表明性能不确定性降低,这使我们能够战略性地安排额外的干预措施,确保它们既不会太晚也不会太早。总之,适应性操作政策可以为长期水库管理提供各种好处,并在不断变化的世界中确保可靠和安全的水源供应。
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