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Article Navigation >  Bulletin of Geological Science and Technology  > 2025  > Corrected proof
LU Cao，YAN Echuan，CHEN Xiating，et al. Research on the I-D-M threshold model for regional rainfall-induced landslide hazard early warning at a regional scale[J]. Bulletin of Geological Science and Technology，2025，44（6）：1-9 doi: 10.19509/j.cnki.dzkq.tb20250216
Citation: LU Cao，YAN Echuan，CHEN Xiating，et al. Research on the I-D-M threshold model for regional rainfall-induced landslide hazard early warning at a regional scale[J]. Bulletin of Geological Science and Technology，2025，44（6）：1-9 doi: 10.19509/j.cnki.dzkq.tb20250216
shu

Research on the I-D-M threshold model for regional rainfall-induced landslide hazard early warning at a regional scale

doi: 10.19509/j.cnki.dzkq.tb20250216
  • 1 .

    Zhejiang Engineering Survey and Design Institute Group Co. Ltd.，Ningbo Zhejiang 315000，China

  • 2 .

    Faculty of Engineering，China University of Geosciences (Wuhan)，Wuhan 430074，China

More Information
  • Author Bio:

    E-mail：921587171@qq.com

  • Corresponding author: E-mail：yecyec6970@163.com
  • Received Date: 12 May 2025
  • Accepted Date: 15 Aug 2025
  • Rev Recd Date: 08 Aug 2025
    • Available Online: 29 Oct 2025
    Abstract
  • Objective

    Regional early warning of rainfall-induced landslide has been a research hotpot in recent years, with the primary challenge being the formulation of rainfall threshold models. Based on hourly rainfall data, this study introduces peak rainfall (M) to construct a three-dimensional characterization model, which can provide a scientific basis for regional rainfall-induced landslide early warning.

    Methods

    The research was conducted using data from 104 rainfall-induced landslide events recorded between 2010 and 2022 in the three northern districts of Ningbo City (Cixi, Jiangbei, and Zhenhai). Firstly, the spatial distribution of rainfall stations associated with landslides was delineated using Voronoi diagram method to reveal the effective rainfall characteristic information landslide hazards. Secondly, the rainfall intensity-rainfall duration (I-D) threshold model was established based on landslide inventory, with critical threshold curves defined using quantile regression. Finally, to address the limitations of the I-D model, peak rainfall (M) was incorporated to propose an improved I-D-M model. The accuracy of both models was evaluated and compared using ROC curves and historical landslide cases to identify the optimal threshold model for regional early warning.

    Results

    The results demonstrate that the I-D-M model, incorporating peak rainfall (M), achieves higher warning accuracy than the conventional I-D model. Probability of landslide occurrence increased by 8% for yellow warnings, 17% for orange warnings, and 16% for red warnings, indicating the significant role of peak rainfall on landslide initiation. The quantile regression-based I-D-M threshold model can be effectively applied as a criterion for implementing three-tiered (red, orange, yellow) rainfall landslide early warning in the study area.

    Conclusion

    The proposed three-dimensional rainfall threshold model provides theoretical and practical insights for improving regional landslide early warning systems, demonstrating enhanced predictive capability and operational applicability.

     

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    • References(41)
  • [1]
    THOMAS J, GUPTA M, PRUSTY G. Assessing global parameters of slope stability model using Earth data observations for forecasting rainfall–induced shallow landslides[J]. Journal of Applied Geophysics, 2023, 212: 104994. doi: 10.1016/j.jappgeo.2023.104994
    [2]
    ZHAN Q H, WANG S M, GUO F, et al. Early warning model and model test verification of rainfall-induced shallow landslide[J]. Bulletin of Engineering Geology and the Environment, 2022, 81(8): 318. doi: 10.1007/s10064-022-02827-4
    [3]
    MA S Y, SHAO X Y, XU C. Physically-based rainfall-induced landslide thresholds for the Tianshui area of Loess Plateau, China by TRIGRS model[J]. Catena, 2023, 233: 107499. doi: 10.1016/j.catena.2023.107499
    [4]
    WANG C H, FANG L, CHANG D T, et al. Back-analysis of a rainfall-induced landslide case history using deterministic and random limit equilibrium methods[J]. Engineering Geology, 2023, 317: 107055. doi: 10.1016/j.enggeo.2023.107055
    [5]
    SEOK K, ONDA Y, UCHIDA T, et al. Effect of seepage on shallow landslides in consideration of changes in topography: Case study including an experimental sandy slope with artificial rainfall[J]. Catena, 2018, 161: 50-62. doi: 10.1016/j.catena.2017.10.004
    [6]
    LUO X X, LI C J, ZHOU J W. GIS-based prediction method of shallow landslides induced by heavy rainfall in large mountainous areas[J]. Journal of Mountain Science, 2024, 21(5): 1534-1548. doi: 10.1007/s11629-023-8535-2
    [7]
    卢操, 晏鄂川, 张瑜, 等. 降雨作用下青石镇政府后山堆积层滑坡渗流与稳定性[J]. 地质科技通报, 2020, 39(2): 139-147.

    LU C, YAN E C, ZHANG Y, et al. Seepage and stability of the colluvial landslide on the back hill of Qingshi Town Government under rainfall[J]. Bulletin of Geological Science and Technology, 2020, 39(2): 139-147. (in Chinese with English abstract
    [8]
    POSNER A J, GEORGAKAKOS K P. Soil moisture and precipitation thresholds for real-time landslide prediction in El Salvador[J]. Landslides, 2015, 12(6): 1179-1196. doi: 10.1007/s10346-015-0618-x
    [9]
    BEZAK N, ŠRAJ M, MIKOŠ M. Copula-based IDF curves and empirical rainfall thresholds for flash floods and rainfall-induced landslides[J]. Journal of Hydrology, 2016, 541: 272-284. doi: 10.1016/j.jhydrol.2016.02.058
    [10]
    IRAWAN A M, VIRGIANTO R H, SAFRIL A, et al. Rainfall threshold and soil moisture indexes for the initiation of landslide in Banjarmangu sub-district, central Java, Indonesia[J]. IOP Conference Series (Earth and Environmental Science), 2019, 243(1): 012028.
    [11]
    LI W Y, LIU C, SCAIONI M, et al. Spatio-temporal analysis and simulation on shallow rainfall-induced landslides in China using landslide susceptibility dynamics and rainfall I-D thresholds[J]. Science China (Earth Sciences), 2017, 60(4): 720-732. doi: 10.1007/s11430-016-9008-4
    [12]
    YANG H J, WEI F Q, MA Z F, et al. Rainfall threshold for landslide activity in Dazhou, southwest China[J]. Landslides, 2020, 17(1): 61-77. doi: 10.1007/s10346-019-01270-z
    [13]
    SEGONI S, ROSI A, ROSSI G, et al. Analysing the relationship between rainfalls and landslides to define a mosaic of triggering thresholds for regional-scale warning systems[J]. Natural Hazards and Earth System Sciences, 2014, 14(9): 2637-2648. doi: 10.5194/nhess-14-2637-2014
    [14]
    ROSI A, PETERNEL T, JEMEC-AUFLIČ M, et al. Rainfall thresholds for rainfall-induced landslides in Slovenia[J]. Landslides, 2016, 13(6): 1571-1577. doi: 10.1007/s10346-016-0733-3
    [15]
    李环禹, 陈朝晖, 范文亮, 等. 区域降雨型滑坡风险分析统计模型研究[J]. 自然灾害学报, 2018, 27(4): 103-111.

    LI H Y, CHEN Z H, FAN W L, et al. The statistical risk analysis model of rainfall-induced landslide in large areas[J]. Journal of Natural Disasters, 2018, 27(4): 103-111. (in Chinese with English abstract
    [16]
    CAINE N. The rainfall intensity: Duration control of shallow landslides and debris flows[J]. Geografiska Annaler Series A, Physical Geography, 1980, 62(1/2): 23-27. doi: 10.2307/520449
    [17]
    GUZZETTI F, PERUCCACCI S, ROSSI M, et al. The rainfall intensity-duration control of shallow landslides and debris flows: An update[J]. Landslides, 2008, 5(1): 3-17. doi: 10.1007/s10346-007-0112-1
    [18]
    MILLÁN-ARANCIBIA C, LAVADO-CASIMIRO W. Rainfall thresholds estimation for shallow landslides in Peru from gridded daily data[J]. Natural Hazards and Earth System Sciences, 2023, 23(3): 1191-1206. doi: 10.5194/nhess-23-1191-2023
    [19]
    夏梦想, 李远耀, 吴吉民, 等. 基于I-D统计模型的张家界市滑坡灾害降雨预警阀值研究[J]. 自然灾害学报, 2021, 30(4): 203-212.

    XIA M X, LI Y Y, WU J M, et al. Research on rainfall early warning threshold of landslide disaster in Zhangjiajie City based on I-D statistical model[J]. Journal of Natural Disasters, 2021, 30(4): 203-212. (in Chinese with English abstract
    [20]
    龚泉冰, 殷坤龙, 肖常贵, 等. 基于I-D阈值的滑坡气象预警双指标模型[J]. 地质科技通报, 2024, 43(1): 262-274.

    GONG Q B, YIN K L, XIAO C G, et al. Double-index model of landslide meteorological warning based on the I-D threshold[J]. Bulletin of Geological Science and Technology, 2024, 43(1): 262-274. (in Chinese with English abstract
    [21]
    黄发明, 曹中山, 姚池, 等. 基于决策树和有效降雨强度的滑坡危险性预警[J]. 浙江大学学报(工学版), 2021, 55(3): 472-482.

    HUANG F M, CAO Z S, YAO C, et al. Landslides hazard warning based on decision tree and effective rainfall intensity[J]. Journal of Zhejiang University (Engineering Science), 2021, 55(3): 472-482. (in Chinese with English abstract
    [22]
    ROSSI M, LUCIANI S, VALIGI D, et al. Statistical approaches for the definition of landslide rainfall thresholds and their uncertainty using rain gauge and satellite data[J]. Geomorphology, 2017, 285: 16-27. doi: 10.1016/j.geomorph.2017.02.001
    [23]
    DAS S, PANDIT K, KANUNGO D P, et al. Developing hillslope hydrology based probabilistic rainfall threshold for shallow landslides[J]. Natural Hazards, 2025, 121(5): 5363-5385. doi: 10.1007/s11069-024-07018-w
    [24]
    李长江, 麻土华, 李炜, 等. 滑坡频度-降雨量的分形关系[J]. 中国地质灾害与防治学报, 2010, 21(1): 87-93.

    LI C J, MA T H, LI W, et al. Fractal relation of landslide frequency and rainfall[J]. The Chinese Journal of Geological Hazard and Control, 2010, 21(1): 87-93. (in Chinese with English abstract
    [25]
    张永双, 姚鑫, 郭长宝, 等. 龙门山地区震后泥石流灾害区域预警研究[J]. 西南交通大学学报, 2016, 51(5): 1014-1023.

    ZHANG Y S, YAO X, GUO C B, et al. Regional warning of debris flow hazards after Wenchuan earthquake in Longmenshan region[J]. Journal of Southwest Jiaotong University, 2016, 51(5): 1014-1023. (in Chinese with English abstract
    [26]
    NOCENTINI N, MEDICI C, BARBADORI F, et al. Optimization of rainfall thresholds for landslide early warning through false alarm reduction and a multi-source validation[J]. Landslides, 2024, 21(3): 557-571. doi: 10.1007/s10346-023-02176-7
    [27]
    刘谢攀, 殷坤龙, 肖常贵, 等. 基于I-D-R阈值模型的滑坡气象预警[J]. 地球科学, 2024, 49(3): 1039-1051.

    LIU X P, YIN K L, XIAO C G, et al. Meteorological early warning of landslide based on I-D-R threshold model[J]. Earth Science, 2024, 49(3): 1039-1051. (in Chinese with English abstract
    [28]
    WANG S W, SUN L S, RONG J, et al. Transit traffic analysis zone delineating method based on Thiessen polygon[J]. Sustainability, 2014, 6(4): 1821-1832. doi: 10.3390/su6041821
    [29]
    ZHAO B R, DAI Q, HAN D W, et al. Probabilistic thresholds for landslides warning by integrating soil moisture conditions with rainfall thresholds[J]. Journal of Hydrology, 2019, 574: 276-287. doi: 10.1016/j.jhydrol.2019.04.062
    [30]
    KOENKER R, BASSETT G. Regression quantiles[J]. Econometrica, 1978, 46(1): 33.
    [31]
    陈建宝, 丁军军. 分位数回归技术综述[J]. 统计与信息论坛, 2008, 23(3): 89-96.

    CHEN J B, DING J J. A review of technologies on quantile regression[J]. Statistics & Information Forum, 2008, 23(3): 89-96. (in Chinese with English abstract
    [32]
    SEGONI S, PICIULLO L, GARIANO S L. A review of the recent literature on rainfall thresholds for landslide occurrence[J]. Landslides, 2018, 15(8): 1483-1501. doi: 10.1007/s10346-018-0966-4
    [33]
    CHIEN L K, HSU C F, YIN L C. Warning model for shallow landslides induced by extreme rainfall[J]. Water, 2015, 7(8): 4362-4384. doi: 10.3390/w7084362
    [34]
    HUANG J, JU N P, LIAO Y J, et al. Determination of rainfall thresholds for shallow landslides by a probabilistic and empirical method[J]. Natural Hazards and Earth System Sciences, 2015, 15(12): 2715-2723. doi: 10.5194/nhess-15-2715-2015
    [35]
    FAWCETT T. An introduction to ROC analysis[J]. Pattern Recognition Letters, 2006, 27(8): 861-874. doi: 10.1016/j.patrec.2005.10.010
    [36]
    DOU H Q, WANG R, WANG H, et al. Rainfall early warning threshold and its spatial distribution of rainfall-induced landslides in China[J]. Rock Mechanics Bulletin, 2023, 2(3): 100056. doi: 10.1016/j.rockmb.2023.100056
    [37]
    TAN J Y, YANG C, WANG Y Z, et al. A hybrid model to overcome landslide inventory incompleteness issue for landslide susceptibility prediction[J]. Geocarto International, 2024, 39(1): 2322066. doi: 10.1080/10106049.2024.2322066
    [38]
    LÜ Q, WU J Y, LIU Z H, et al. The Fuyang shallow landslides triggered by an extreme rainstorm on 22 July 2023 in Zhejiang, China[J]. Landslides, 2024, 21(11): 2725-2740. doi: 10.1007/s10346-024-02314-9
    [39]
    XIAO T, ZHANG L M, CHEUNG R W M, et al. Predicting spatio-temporal man-made slope failures induced by rainfall in Hong Kong using machine learning techniques[J]. Géotechnique, 2023, 73(9): 749-765.
    [40]
    窦杰, 向子林, 许强, 等. 机器学习在滑坡智能防灾减灾中的应用与发展趋势[J]. 地球科学, 2023, 48(5): 1657-1674.

    DOU J, XIANG Z L, XU Q, et al. Application and development trend of machine learning in landslide intelligent disaster prevention and mitigation[J]. Earth Science, 2023, 48(5): 1657-1674. (in Chinese with English abstract
    [41]
    屈鹏鑫, 谢婉丽, 刘琦琦, 等. 基于机器学习方法改进IVM-RF耦合模型的崩滑灾害危险性评价: 以延安市志丹县为例[J]. 地质科技通报, 2025, 44(3): 280-295.

    QU P X, XIE W L, LIU Q Q, et al. Collapse and landslide risk assessment based on machine learning improved IVM-RF coupling method: A case study of Zhidan County, Yan'an City[J]. Bulletin of Geological Science and Technology, 2025, 44(3): 280-295. (in Chinese with English abstract
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