Fletcher Sarah, Zaniolo Marta, Zhang Mofan, Lickley Megan
Civil and Environmental Engineering, Stanford University, Stanford, CA 94305.
Woods Institute for the Environment, Stanford University, Stanford, CA 94305.
Proc Natl Acad Sci U S A. 2023 Aug 29;120(35):e2215681120. doi: 10.1073/pnas.2215681120. Epub 2023 Aug 21.
Climate oscillations ranging from years to decades drive precipitation variability in many river basins globally. As a result, many regions will require new water infrastructure investments to maintain reliable water supply. However, current adaptation approaches focus on long-term trends, preparing for average climate conditions at mid- or end-of-century. The impact of climate oscillations, which bring prolonged and variable but temporary dry periods, on water supply augmentation needs is unknown. Current approaches for theory development in nature-society systems are limited in their ability to realistically capture the impacts of climate oscillations on water supply. Here, we develop an approach to build middle-range theory on how common climate oscillations affect low-cost, reliable water supply augmentation strategies. We extract contrasting climate oscillation patterns across sub-Saharan Africa and study their impacts on a generic water supply system. Our approach integrates climate model projections, nonstationary signal processing, stochastic weather generation, and reinforcement learning-based advances in stochastic dynamic control. We find that longer climate oscillations often require greater water supply augmentation capacity but benefit more from dynamic approaches. Therefore, in settings with the adaptive capacity to revisit planning decisions frequently, longer climate oscillations do not require greater capacity. By building theory on the relationship between climate oscillations and least-cost reliable water supply augmentation, our findings can help planners target scarce resources and guide water technology and policy innovation. This approach can be used to support climate adaptation planning across large spatial scales in sectors impacted by climate variability.
从数年到数十年的气候振荡驱动着全球许多流域的降水变化。因此,许多地区将需要新的水利基础设施投资,以维持可靠的供水。然而,当前的适应方法侧重于长期趋势,为世纪中叶或末期的平均气候条件做准备。气候振荡带来持续时间长、变化但短暂的干旱期,其对增加供水需求的影响尚不清楚。当前自然 - 社会系统理论发展的方法在实际捕捉气候振荡对供水的影响方面能力有限。在此,我们开发一种方法来构建关于常见气候振荡如何影响低成本、可靠的供水增加策略的中程理论。我们提取撒哈拉以南非洲地区不同的气候振荡模式,并研究它们对通用供水系统的影响。我们的方法整合了气候模型预测、非平稳信号处理、随机天气生成以及基于强化学习的随机动态控制进展。我们发现,较长的气候振荡通常需要更大的供水增加能力,但从动态方法中受益更多。因此,在有能力频繁重新审视规划决策以适应的环境中,较长的气候振荡并不需要更大的能力。通过建立关于气候振荡与成本最低的可靠供水增加之间关系的理论,我们的研究结果可以帮助规划者将稀缺资源用于目标,并指导水技术和政策创新。这种方法可用于支持受气候变异性影响的各部门在大空间尺度上的气候适应规划。