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How much does the rainfall temporal resolution affect rainfall thresholds for landslide triggering?

Author

Listed:
  • Stefano Luigi Gariano

    (CNR IRPI)

  • Massimo Melillo

    (CNR IRPI)

  • Silvia Peruccacci

    (CNR IRPI)

  • Maria Teresa Brunetti

    (CNR IRPI)

Abstract

In many areas of the world, the prediction of rainfall-induced landslides is usually carried out by means of empirical rainfall thresholds. Their definition is complicated by several issues, among which are the evaluation and quantification of diverse uncertainties resulting from data and methods. Threshold effectiveness and reliability strongly depend on the quality and quantity of rainfall measurements and landslide information used as input. In this work, the influence of the temporal resolution of rainfall measurements on the calculation of landslide-triggering rainfall thresholds is evaluated and discussed. For the purpose, hourly rainfall measurements collected by 172 rain gauges and geographical and temporal information on the occurrence of 561 rainfall-induced landslides in Liguria region (northern Italy) in the period 2004–2014 are used. To assess the impact of different temporal resolutions on the thresholds, rainfall measurements are clustered in increasing bins of 1, 3, 6, 12 and 24 h. A comprehensive tool is applied to each dataset to automatically reconstruct the rainfall conditions responsible for the failures and to calculate frequentist cumulated event rainfall–rainfall duration (ED) thresholds. Then, using a quantitative procedure, the calculated ED thresholds are validated. The main finding of the work is that the use of rainfall measurements with different temporal resolutions results in considerable variations of the shape and the validity range of the thresholds. Decreasing the rainfall temporal resolution, thresholds with smaller intercepts, higher slopes, shorter ranges of validity and higher uncertainties are obtained. On the other hand, it seems that the rainfall temporal resolution does not influence the validation procedure and the threshold performance indicators. Overall, the use of rainfall data with coarse temporal resolution causes a systematic underestimation of thresholds at short durations, resulting in relevant drawbacks (e.g. false alarms) if the thresholds are implemented in operational systems for landslide prediction.

Suggested Citation

  • Stefano Luigi Gariano & Massimo Melillo & Silvia Peruccacci & Maria Teresa Brunetti, 2020. "How much does the rainfall temporal resolution affect rainfall thresholds for landslide triggering?," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 100(2), pages 655-670, January.
    • Handle: RePEc:spr:nathaz:v:100:y:2020:i:2:d:10.1007_s11069-019-03830-x
    DOI: 10.1007/s11069-019-03830-x
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    References listed on IDEAS

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    1. Dieu Tien Bui & Biswajeet Pradhan & Owe Lofman & Inge Revhaug & Øystein Dick, 2013. "Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 66(2), pages 707-730, March.
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    2. S. L. Gariano & G. Verini Supplizi & F. Ardizzone & P. Salvati & C. Bianchi & R. Morbidelli & C. Saltalippi, 2021. "Long-term analysis of rainfall-induced landslides in Umbria, central Italy," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(3), pages 2207-2225, April.
    3. Weidong Zhao & Yunyun Cheng & Jie Hou & Yihua Chen & Bin Ji & Lei Ma, 2023. "A regional early warning model of geological hazards based on big data of real-time rainfall," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(3), pages 3465-3480, April.
    4. Luca Schilirò & Gian Marco Marmoni & Matteo Fiorucci & Massimo Pecci & Gabriele Scarascia Mugnozza, 2023. "Preliminary insights from hydrological field monitoring for the evaluation of landslide triggering conditions over large areas," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(2), pages 1401-1426, September.
    5. Zhongyuan Xu & Zhilin Xiao & Xiaoyan Zhao & Zhigang Ma & Qun Zhang & Pu Zeng & Xiaoqiong Zhang, 2024. "Derivation of Landslide Rainfall Thresholds by Geostatistical Methods in Southwest China," Sustainability, MDPI, vol. 16(10), pages 1-15, May.
    6. Alessandro C. Mondini & Fausto Guzzetti & Massimo Melillo, 2023. "Deep learning forecast of rainfall-induced shallow landslides," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    7. Paulo Rodolpho Pereira Hader & Fábio Augusto Gomes Vieira Reis & Anna Silvia Palcheco Peixoto, 2022. "Landslide risk assessment considering socionatural factors: methodology and application to Cubatão municipality, São Paulo, Brazil," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(2), pages 1273-1304, January.
    8. Rattana Salee & Avirut Chinkulkijniwat & Somjai Yubonchit & Suksun Horpibulsuk & Chadanit Wangfaoklang & Sirirat Soisompong, 2022. "New threshold for landslide warning in the southern part of Thailand integrates cumulative rainfall with event rainfall depth-duration," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(1), pages 125-141, August.

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