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Quantifying location error to define uncertainty in volcanic mass flow hazard simulations
Natural Hazards and Earth System Sciences ( IF 4.6 ) Pub Date : 2021-02-17 , DOI: 10.5194/nhess-2021-49
Stuart R. Mead , Jonathan Procter , Gabor Kereszturi

Abstract. The use of mass flow simulations in volcanic hazard zonation and mapping is often limited by model complexity (i.e. uncertainty in correct values of model parameters), a lack of model uncertainty quantification, and limited approaches to incorporate this uncertainty into hazard maps. When quantified, mass flow simulation errors are typically evaluated on a pixel-pair basis, using the difference between simulated and observed (actual) map-cell values to evaluate the performance of a model. However, these comparisons conflate location and quantification errors, neglecting possible spatial autocorrelation of evaluated errors. As a result, model performance assessments typically yield moderate accuracy values. In this paper, similarly moderate accuracy values were found in a performance assessment of three depth-averaged numerical models using the 2012 debris avalanche from the Upper Te Maari crater, Tongariro Volcano as a benchmark. To provide a fairer assessment of performance and evaluate spatial covariance of errors, we use a fuzzy set approach to indicate the proximity of similarly valued map cells. This fuzzification of simulated results yields improvements in targeted performance metrics relative to a length scale parameter, at the expense of decreases in opposing metrics (e.g. less false negatives results in more false positives) and a reduction in resolution. The use of this approach to generate hazard zones incorporating the identified uncertainty and associated trade-offs is demonstrated, and indicates a potential use for informed stakeholders by reducing the complexity of uncertainty estimation and supporting decision making from simulated data.

中文翻译:

量化位置误差以定义火山质量流危害模拟中的不确定性

摘要。在模型中(例如,模型参数正确值的不确定性),缺乏模型不确定性量化以及将这种不确定性纳入危害图的方法有限,通常会限制在火山灾害分区和制图中使用质量流量模拟。量化后,通常会使用模拟值与实测值(实际值)映射单元格值,以评估模型的性能。但是,这些比较混淆了位置和量化误差,而忽略了评估误差的可能空间自相关。结果,模型性能评估通常会得出中等精度值。在本文中,在以汤加里罗火山上Te Maari火山口的2012年碎片雪崩为基准的三个深度平均数值模型的性能评估中,发现了类似的中等精度值。为了提供更公平的性能评估并评估错误的空间协方差,我们使用模糊集方法来指示相似值的地图像元的接近度。这种模糊化相对于长度标度参数,模拟结果的改进可提高目标性能指标的性能,但以相反指标的减少为代价(例如,较少的假阴性导致更多的假阳性)并降低分辨率。演示了使用这种方法生成包含已确定的不确定性和相关权衡因素的危险区域,并通过降低不确定性估计的复杂性并支持从模拟数据中进行决策,为知情的利益相关者指明了潜在的用途。
更新日期:2021-02-17
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