Towards improving the spatial testability of aftershock forecast models

IF 4.2 2区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Natural Hazards and Earth System Sciences Pub Date : 2023-07-31 DOI:10.5194/nhess-23-2683-2023
Asim M. Khawaja, Behnam Maleki Asayesh, S. Hainzl, D. Schorlemmer
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Abstract

Abstract. Aftershock forecast models are usually provided on a uniform spatial grid, and the receiver operating characteristic (ROC) curve is often employed for evaluation, drawing a binary comparison of earthquake occurrences or non-occurrence for each grid cell. However, synthetic tests show flaws in using the ROC for aftershock forecast ranking. We suggest a twofold improvement in the testing strategy. First, we propose to replace ROC with the Matthews correlation coefficient (MCC) and the F1 curve. We also suggest using a multi-resolution test grid adapted to the earthquake density. We conduct a synthetic experiment where we analyse aftershock distributions stemming from a Coulomb failure (ΔCFS) model, including stress activation and shadow regions. Using these aftershock distributions, we test the true ΔCFS model as well as a simple distance-based forecast (R), only predicting activation. The standard test cannot clearly distinguish between both forecasts, particularly in the case of some outliers. However, using both MCC-F1 instead of ROC curves and a simple radial multi-resolution grid improves the test capabilities significantly. The novel findings of this study suggest that we should have at least 8 % and 5 % cells with observed earthquakes to differentiate between a near-perfect forecast model and an informationless forecast using ROC and MCC-F1, respectively. While we cannot change the observed data, we can adjust the spatial grid using a data-driven approach to reduce the disparity between the number of earthquakes and the total number of cells. Using the recently introduced Quadtree approach to generate multi-resolution grids, we test real aftershock forecast models for Chi-Chi and Landers aftershocks following the suggested guideline. Despite the improved tests, we find that the simple R model still outperforms the ΔCFS model in both cases, indicating that the latter should not be applied without further model adjustments.
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提高余震预报模型的空间可检验性
摘要余震预报模型通常在一个均匀的空间网格上提供,通常采用接收者工作特征(ROC)曲线进行评估,在每个网格单元中绘制地震发生或不发生的二元比较。然而,综合检验显示,使用ROC进行余震预测排序存在缺陷。我们建议对测试策略进行双重改进。首先,我们建议用马修斯相关系数(MCC)和F1曲线代替ROC。我们还建议采用与地震密度相适应的多分辨率测试网格。我们进行了一个综合实验,分析了库仑失效(ΔCFS)模型产生的余震分布,包括应力激活和阴影区域。使用这些余震分布,我们测试了真实的ΔCFS模型以及一个简单的基于距离的预测(R),仅预测激活。标准检验不能明确区分这两种预测,特别是在一些异常值的情况下。然而,使用MCC-F1代替ROC曲线和简单的径向多分辨率网格可以显著提高测试能力。本研究的新发现表明,我们应该至少有8%和5%的细胞观测到地震,以区分使用ROC和MCC-F1的近乎完美的预测模型和无信息的预测。虽然我们不能改变观测数据,但我们可以使用数据驱动的方法调整空间网格,以减少地震次数与单元总数之间的差异。使用最近引入的四叉树方法生成多分辨率网格,我们按照建议的准则测试了Chi-Chi和Landers余震的真实余震预测模型。尽管进行了改进的测试,但我们发现在这两种情况下,简单R模型仍然优于ΔCFS模型,这表明如果不进一步调整模型,则不应采用ΔCFS模型。
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来源期刊
Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences 地学-地球科学综合
CiteScore
7.60
自引率
6.50%
发文量
192
审稿时长
3.8 months
期刊介绍: Natural Hazards and Earth System Sciences (NHESS) is an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences. Embracing a holistic Earth system science approach, NHESS serves a wide and diverse community of research scientists, practitioners, and decision makers concerned with detection of natural hazards, monitoring and modelling, vulnerability and risk assessment, and the design and implementation of mitigation and adaptation strategies, including economical, societal, and educational aspects.
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