Screening robust water infrastructure investments and their trade-offs under global change: A London Example
Screening robust water infrastructure investments and their trade-offs under global change: A London Example
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DOI：
10.1016/j.gloenvcha.2016.10.007
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发表时间：
2016-11
影响因子：
8.9
通讯作者：
I. Huskova;E. Matrosov;J. Harou;J. Kasprzyk;C. Lambert
中科院分区：
文献类型：
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作者：
I. Huskova;E. Matrosov;J. Harou;J. Kasprzyk;C. Lambert
我们提出了一种方法来筛选未来的基础设施和需求管理投资的大型供水系统受到不确定的未来条件。该方法被证明使用伦敦供水系统。有希望的干预措施组合（例如，新的供水、水资源保护计划等）满足伦敦2035年预计供水需求的项目面临着财务、工程和环境性能指标之间的重大权衡。通过对比（1）历史上观察到的基线条件与（2）未来全球变化情景所取得的多目标结果，确定了稳健的组合。使用气候变化影响的水文流量，合理的水需求，环境驱动的抽象减少，和未来的能源价格计算的全球变化情景的合奏。拟议的多情景权衡分析筛选出稳健的投资，这些投资在广泛的未来中提供收益，包括那些变化不大的投资。我们的研究结果表明，在历史条件下被确定为帕累托最优的干预组合中，有60%会在利益相关者认为相关的未来情景下失败。那些能够在历史条件下保持良好表现的公司，不能再被认为在未来情况下表现最佳。个别投资选择在科普不同情况的能力上有很大的差异。在多维空间中的帕累托最优组合中实现的各个基础设施和需求管理干预措施的可视化有助于探索干预措施如何影响系统的鲁棒性和性能。
We propose an approach for screening future infrastructure and demand management investments for large water supply systems subject to uncertain future conditions. The approach is demonstrated using the London water supply system. Promising portfolios of interventions (e.g., new supplies, water conservation schemes, etc.) that meet London’s estimated water supply demands in 2035 are shown to face significant trade-offs between financial, engineering and environmental measures of performance. Robust portfolios are identified by contrasting the multi-objective results attained for (1) historically observed baseline conditions versus (2) future global change scenarios. An ensemble of global change scenarios is computed using climate change impacted hydrological flows, plausible water demands, environmentally motivated abstraction reductions, and future energy prices. The proposed multi-scenario trade-off analysis screens for robust investments that provide benefits over a wide range of futures, including those with little change. Our results suggest that 60 percent of intervention portfolios identified as Pareto optimal under historical conditions would fail under future scenarios considered relevant by stakeholders. Those that are able to maintain good performance under historical conditions can no longer be considered to perform optimally under future scenarios. The individual investment options differ significantly in their ability to cope with varying conditions. Visualizing the individual infrastructure and demand management interventions implemented in the Pareto optimal portfolios in multi-dimensional space aids the exploration of how the interventions affect the robustness and performance of the system.