Temporal variability of influence factors weights and rainfall thresholds of geological hazards in Ningbo City

SUN Liying; ZHANG Honghuai; QIU Changjun; YANG Zhenbin; ZHANG Changxiang; ZHANG Bin; ZHANG Taili

doi:10.16788/j.hddz.32-1865/P.2024.02.007

2024 Vol. 45, No. 2

Article Contents

Article navigation > East China Geology > 2024 > 45(2): 218-227

Next Article Previous Article

SUN Liying, ZHANG Honghuai, QIU Changjun, YANG Zhenbin, ZHANG Changxiang, ZHANG Bin, ZHANG Taili. 2024. Temporal variability of influence factors weights and rainfall thresholds of geological hazards in Ningbo City. East China Geology, 45(2): 218-227. doi: 10.16788/j.hddz.32-1865/P.2024.02.007

Citation:

SUN Liying, ZHANG Honghuai, QIU Changjun, YANG Zhenbin, ZHANG Changxiang, ZHANG Bin, ZHANG Taili. 2024. Temporal variability of influence factors weights and rainfall thresholds of geological hazards in Ningbo City. East China Geology, 45(2): 218-227. doi: 10.16788/j.hddz.32-1865/P.2024.02.007

Temporal variability of influence factors weights and rainfall thresholds of geological hazards in Ningbo City

1. Ningbo Centre of Natural Resources Ecological Restoration and Marine Management Service, Ningbo 315099, Zhejiang, China;
2. Ningbo Qiannuo Technology Co., Ltd., Ningbo 315099, Zhejiang, China;
3. Nanjing Center, China Geological Survey, Nanjing 210016, Jiangsu, China

More Information

Corresponding author: ZHANG Honghuai, 16516771@qq.com

Received Date: 25 July 2023

Revised Date: 16 January 2024

Abstract

Abstract

Rainfall is one of the key inducements of geological hazards. Continuous rainfall coupled with the geological environment elements will lead to the deformation and failure of the slope, which in turn causes the continuous changes in the weighting system of the various influence factors of geological hazards. Therefore, it is of great significance for accurate hazard warning and forecast to fully consider the temporal variability of the influence factors' weights of geological hazards in the research of rainfall threshold. This paper selected nine influence factors(lithology, slope, etc.)for four types of geological hazards including landslides, collapses, slope debris flows and gully debris flows to analyze the changes in the weighting system of ten rainfall periods(1 h,3 h,6 h etc.)in Ningbo, and finally put forward three levels (red, orange and yellow) of warning and forecasting value for different geo-hazard risk prevention zones. The results show that the weights of the nine influence factors of the four types of geological hazards change apparently within 24 hours after rainfall. The weights of the six influence factors, including the slope and soil layer thickness of landslides, the slope and elevation difference of collapses, the slope and lithology of slope debris flows, and the slope and elevation of the gully debris flows, change more obviously in the process of rainfall. The weights of slopes are generally positively correlated with time, while the weights of the other factors are negatively correlated with time. Comparing the rainfall thresholds calculated by the method considering the time-varying weights and the I-D logarithmic method, the result indicates that the rainfall thresholds calculated by the former method can reflect more real warning values.
- geological hazards /
- temporal variability of weights /
- weighted rainfall /
- threshold /
- influence factors /
- Ningbo, Zhejiang

FullText(HTML)

References

[1]	张泰丽, 孙强, 李绍鹏, 等. 浙江飞云江流域玄武岩残积土滑坡降雨入渗柱状实验研究[J]. 华东地质, 2021, 42(4): 367-372. Google Scholar ZHANG T L, SUN Q, LI S P, et al. Columnar experimental study on rainfall infiltration of basalt residual soil landslide in Feiyun River Basin of Zhejiang Province[J]. East China Geology, 2021, 42(4): 367-372. Google Scholar
[2]	陈有利, 崔飞君. 宁波地质灾害气象风险预警方法与实践[M]. 北京: 气象出版社, 2016. CHEN Y L, CUI F J. Method and practice of meteorological risk early warning of geological hazards in Ningbo[M]. Beijing: Meteorological Press, 2016. Google Scholar
[3]	KEEFER D K, WILSON R C, MARK R K, et al. Real-time landslide warning during heavy rainfall[J]. Science, 1987, 238(4829): 921-925. Google Scholar
[4]	姚学祥, 徐晶, 薛建军, 等. 基于降水量的全国地质灾害潜势预报模式[J]. 中国地质灾害与防治学报, 2005, 16(4): 97-102, 129. Google Scholar YAO X X, XU J, XUE J J, et al. A potential forecast model for geological-related disasters based on precipitation[J]. The Chinese Journal of Geological Hazard and Control, 2005, 16(4): 97-102, 129. Google Scholar
[5]	赵衡, 宋二祥. 诱发区域性滑坡的降雨阈值[J]. 吉林大学学报(地球科学版), 2011, 41(5): 1481-1487. Google Scholar ZHAO H, SONG E X. Rainfall thresholds for regional landslides[J]. Journal of Jilin University (Earth Science Edition), 2011, 41(5): 1481-1487. Google Scholar
[6]	薛群威, 刘艳辉, 唐灿. 突发地质灾害气象预警统计模型与应用[J]. 吉林大学学报(地球科学版), 2013, 43(5): 1614-1622. Google Scholar XUE Q W, LIU Y H, TANG C. Early warning statistical model of sudden geological hazards and its application[J]. Journal of Jilin University (Earth Science Edition), 2013, 43(5): 1614-1622. Google Scholar
[7]	赵卫东, 季斌, 田剑, 等. 一种区域地质灾害气象预报预警方法: 中国, 114093133A[P]. 2022-02-25. Google Scholar ZHAO W D, JI B, TIAN J, et al. The invention relates to a meteorological forecasting and early warning method for regional geological hazards: CN, 114093133A[P]. 2022-02-25. Google Scholar
[8]	WILSON R C, KEEFER D K. Dynamic analysis of a slope failure from the 6 August 1979 coyote lake, California, earthquake[J]. Bulletin of the Seismological Society of America, 1983, 73(3): 863-877. Google Scholar
[9]	BRAND E W, PREMEHITT J, PHILLIPSON H B. Relationship between rainfall and landslides in Hong Kong[C]//Proc. 4th International Symposium on Landslides. Toronto, Ontario: BITech Publishers, 1984: 377-384. Google Scholar
[10]	陈剑, 杨志法, 李晓. 三峡库区滑坡发生概率与降水条件的关系[J]. 岩石力学与工程学报, 2005, 24(17): 3052-3056. Google Scholar CHEN J, YANG Z F, LI X. Relationship between landslide probability and rainfall in three gorges reservoir area[J]. Chinese Journal of Rock Mechanics and Engineering, 2005, 24(17): 3052-3056. Google Scholar
[11]	庄建琦, 彭建兵, 张利勇. 不同降雨条件下黄土高原浅层滑坡危险性预测评价[J]. 吉林大学学报(地球科学版), 2013, 43(3): 867-876. Google Scholar ZHUANG J Q, PENG J B, ZHANG L Y. Risk assessment and prediction of the shallow landslide at different precipitation in loess plateau[J]. Journal of Jilin University (Earth Science Edition), 2013, 43(3): 867-876. Google Scholar
[12]	张丽红, 张新海, 蓝海波, 等. 基于气象预报的山洪地质灾害预警技术研究[J]. 人民黄河, 2020, 42(S1): 16-17. Google Scholar ZHANG L H, ZHANG X H, LAN H B, et al. Research on early warning technology of mountain torrent geological disaster based on meteorological forecast[J]. Yellow River, 2020, 42(S1): 16-17. Google Scholar
[13]	张凯翔. 基于"3S "技术的地质灾害监测预警系统在我国应用现状[J]. 中国地质灾害与防治学报, 2020, 31(6): 1-11. Google Scholar ZHANG K X. Review on geological disaster monitoring and early warning system based on " 3S" technology in China[J]. The Chinese Journal of Geological Hazard and Control, 2020, 31(6): 1-11. Google Scholar
[14]	孙德亮. 基于机器学习的滑坡易发性区划与降雨诱发滑坡预报预警研究[D]. 上海: 华东师范大学, 2019. SUN D L. Mapping landslide susceptibility based on machine learning and forecast warning of landslide induced by rainfall[D]. Shanghai: East China Normal University, 2019. Google Scholar
[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. Google Scholar 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. Google Scholar
[16]	伍剑波, 孙强, 张泰丽, 等. 地形起伏度与滑坡发育的相关性——以丽水市滑坡为例[J]. 华东地质, 2022, 43(2): 235-244. Google Scholar WU J B, SUN Q, ZHANG T L, et al. Research for the correlation between relief amplitude and landslides: a case study of Lishui City[J]. East China Geology, 2022, 43(2): 235-244. Google Scholar
[17]	孙强, 张泰丽, 伍剑波, 等. SHALSTAB模型在浙南林溪流域滑坡预测中的应用[J]. 华东地质, 2021, 42(4): 383-389. Google Scholar SUN Q, ZHANG T L, WU J B, et al. Application of shallow landslide stability model to landslide prediction in the Linxi River basin of southern Zhejiang[J]. East China Geology, 2021, 42(4): 383-389. Google Scholar