A framework for testing dynamic classification of vulnerable scenarios in ensemble water supply projections

A framework for testing dynamic classification of vulnerable scenarios in ensemble water supply projections
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用于测试集合供水预测中脆弱情景动态分类的框架

DOI:
10.1007/s10584-018-2347-3
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发表时间:
2019
期刊:
影响因子:
4.8
通讯作者:
Herman, Jonathan D.
Herman, Jonathan D.
中科院分区:
环境科学与生态学2区
文献类型:
--
作者:
Robinson, Bethany;Herman, Jonathan D.

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最近的水资源规划研究提出了气候适应战略,其中基础设施和政策行动由观察到的阈值或“路标”触发。然而,这种战略的成功取决于阈值是否能够与未来的脆弱性准确地联系起来。这项研究提出了一个框架,用于测试适应阈值的能力,动态识别脆弱的情况下集成预测。径流预测主要是在美国西部的91个河流站点作为一个案例研究,其中脆弱性是由合奏成员的最低的10%,结束了世纪平均年流量。说明性的规划阈值定义通过时间为每个网站的基础上的平均流量低于指定比例的情况是脆弱的。我们执行留一交叉验证来计算错误识别或未能识别脆弱场景的频率(分别为误报和漏报)。结果表明,一般来说,这种定义阈值的方法可以识别具有低误报率(< 10%)的脆弱情景,但许多河流的误报率仍然高于随机概率,直到大约2060年。这一发现强调了频繁触发不必要的行动和直到世纪晚些时候才发现潜在漏洞之间的权衡,并表明可以用这种方法进行基准测试的阈值设置技术有改进的空间。这个测试框架可以扩展到用多元统计定义的阈值,或任何使用阈值和集合预测的应用,如长期洪水和干旱风险,或海平面上升。
Recent water resources planning studies have proposed climate adaptation strategies in which infrastructure and policy actions are triggered by observed thresholds or “signposts.” However, the success of such strategies depends on whether thresholds can be accurately linked to future vulnerabilities. This study presents a framework for testing the ability of adaptation thresholds to dynamically identify vulnerable scenarios within ensemble projections. Streamflow projections for 91 river sites predominantly in the western USA are used as a case study in which vulnerability is determined by the ensemble members with the lowest 10% of end-of-century mean annual flow. Illustrative planning thresholds are defined through time for each site based on the mean streamflow below which a specified fraction of scenarios is vulnerable. We perform a leave-one-out cross-validation to compute the frequency of incorrectly identifying or failing to identify a vulnerable scenario (false positives and false negatives, respectively). Results show that in general, this method of defining thresholds can identify vulnerable scenarios with low false positive rates (< 10%), but with false negative rates for many rivers remaining higher than random chance until roughly 2060. This finding highlights the tradeoff between frequently triggering unnecessary action and failing to identify potential vulnerabilities until later in the century, and suggests room for improvement in the threshold-setting technique that could be benchmarked with this approach. This testing framework could extend to thresholds defined with multivariate statistics, or to any application using thresholds and ensemble projections, such as long-term flood and drought risk, or sea level rise.
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