学术前沿 | Engineering Geology 评估预测震后泥石流的阈值:气象、水文气象和临界排放方法的比较

学术   2024-11-28 08:03   陕西  

• 在一个活跃的泥石流易发集水区记录了 30 次泥石流事件;

• 比较了三种不同的方法来评估泥石流开始阈值;

• 引入绝对能量以提高阈值的准确性;

• 与其他模型相比,水文气象模型的性能优于其他模型。

地震后泥石流在大型地震事件后对山区构成重大危害。评估用于预测这些流发生的阈值至关重要。然而,缺乏对不同预测方法的比较阻碍了改进和更新泥石流预测的进展。本研究基于对 2022 年泸定 Ms6.8 地震后第一年活跃集水区震后泥石流的现场测量,确定并观测了 30 起泥石流事件。我们建立并比较了三种不同的方法,即气象方法、水文气象方法和临界排放方法,用于预测震后泥石流的发生。此外,我们还引入了一个称为绝对能量的因子,以提高传统气象方法的准确性。绝对能量定义为时间序列中数值的平方和。我们的研究结果表明,水文气象模型在预测震后泥石流方面优于其他模型,而气象方法,尤其是强度-持续时间 (I-D) 阈值表现出次优性能。此外,与传统气象方法(如强度-持续时间 (I-D) 阈值)相比,包含绝对能量的更新气象模型显示出更高的预测能力。我们认为,这种比较分析将有助于选择合适的方法来预测震后泥石流。

Fig. 1Mogangling landslides (a) Topographic map indicating the locations of monitoring instruments. The inset presents the slope frequency distribution; (b) Debris-flow fan; (c) Outlet of the catchment adjacent to the rural road; (d) Debris-flow channel proximal to the outlet; (e) Debris-flow channel near the flow velocity monitoring station; (f) Rainfall monitoring site; (g) Initial section of the debris-flow channel.

Fig. 2Grain-size distribution derived from the soil sample collected in the study area.

Fig. 3Monitoring stations for, flow stage and flow velocity (a), water content (b), and flow evolution in the channel through a video camera (c).

Fig. 4Distribution of main rainfall features for triggering rainfall events and non-triggering rainfall events (a) cumulative rainfall; (b) rainfall intensity; (c) maximum hour rainfall intensity; (d) absolute energy.

Fig. 5Intensity-duration rainfall thresholds of the study area.

Fig. 8Relationship between water content and rainfall in the enlarged view.

Fig. 9The hydrometeorological thresholds of the study area: (a) E-MW threshold; (b)I-MW threshold; (c) E-AW threshold; (d) I-AW threshold.

Fig. 10(a) Comparison of the calculated water discharge with the observed flow velocity; (b) Enlarged view of the hydrograph with observed flow velocity peaks between 7/10 and 7/18; (c) Enlarged view of the hydrograph with observed flow velocity peaks between 8/17 and 8/20.

Fig. 11Critical discharge thresholds of the study area (a) thresholds based on rainfall intensity and peak discharge; (b) thresholds based on the cumulative rainfall and peak discharge.

Fig. 12Correctness of different thresholds (a) I-D; (b) E-AE; (c) E-MW; (d) I-MW; (e) E-AW; (f) I-AW; (g) E-PD; (h) I-PD,

Fig. 15Distribution of initial water content for triggering and non-triggering rainfall events; (b) I-IW model.

Fig. 16Compared our hydrometeorological model with other studies. Thresholds −15 cm depth refers to the hydrometeorological thresholds based on the soil water content recorded at the 15 cm depth. Thresholds-30 cm depth refers to the hydrometeorological thresholds based on the soil water content recorded at a depth of 30 cm. Both sets of thresholds were derived from Oorthuis et al. (2023).

在这项研究中,我们采用了三种不同的方法——经验 I-D 阈值、水文气象阈值和临界流量阈值——来建立和比较震后泥石流的阈值。通过分析泸定地震后第一年记录的降水和泥石流数据,我们评估了每种方法的性能。结果表明,水文气象模型在三种模型中表现最好,水文气象和临界流量阈值均超过了传统的 I-D 阈值。此外,我们引入了一个称为绝对能量的因子,以增强泥石流的传统气象阈值。绝对能量定义为时间序列中平方值的总和。我们的研究结果表明,与传统的 I-D 阈值相比,加入绝对能量可以带来卓越的性能。我们建议在未来的研究中考虑绝对能量,以进一步提高泥石流的降雨阈值。此外,我们的分析表明,与类似研究相比,我们的 I-D 阈值中的 α 值更小,而 β 值更大。水文气象和临界流量阈值的更好性能也凸显了合并其他功能以提高阈值精度的重要性。为此,我们建议利用 AI 模型来提取更多与触发泥石流相关的特征。

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