中国非地震触发滑坡时空分布规律

doi:10.3799/dqkx.2026.066

中国非地震触发滑坡时空分布规律

doi: 10.3799/dqkx.2026.066

刘陈^1,4,
栗帅²,
尹陈^1,4,
王文松^3, ,,
曾超^1,4,
何大祥^1,4

1. 西南科技大学环境与资源学院, 四川绵阳 621010;
2. 中国科学院, 水利部成都山地灾害与环境研究所山地自然灾害与工程安全重点实验室, 四川成都 610066;
3. 成都理工大学地质灾害防治与地质环境保护国家重点实验室, 四川成都 610059;
4. 西南科技大学固体废物处理与资源化教育部重点实验室, 四川绵阳 621010

基金项目:

地球深部探测与矿产资源勘查国家科技重大专项（2024ZD1000500）；国家自然科学基金项目（42471094）；四川省自然科学基金（2024NSFSC0068）；中国科学院青年创新促进会资助项目（2022379）；中国科学院成都山地所自主部署科研项目（IMHE-ZYTS-01）；地质灾害防治与地质环境保护国家重点实验室开放基金资助项目（SKLGP2024K015）；地质灾害防治与地质环境保护国家重点实验室开放基金资助项目（SKLGP2022K009）

详细信息

作者简介:
刘陈（2000-），男，硕士.主要从事滑坡时空分布规律研究.E-mail:1376610978@qq.com

通讯作者:
王文松，研究员，E-mail:wws@cdut.edu.cn

中图分类号: P642.22
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出版历程
- 收稿日期: 2025-09-30
- 网络出版日期: 2026-05-13

Study on the Spatiotemporal Distribution Patterns of Non-Earthquake Triggered Landslides in China

LIU Chen^1,4,
LI Shuai²,
YIN Chen^1,4,
WANG Wensong^{3
, ,},
ZENG Chao^1,4,
HE Daxiang^1,4

1. School of Environment and Resource, Southwest University of Science and Technolo gy, Mianyang 621010, China;
2. Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610066, China;
3. State Key Laboratory of Geological Hazard Prevention and Geological Environment Protection, Chengdu University of Technology, Chengdu 610059, China;
4. Key Laboratory of Solid Waste Treatment and Resource Recycling of the Ministry of Education, Southwest University of Science and Technology, Mianyang 621010, China

摘要

摘要: 为解决中国非地震触发滑坡多尺度时空分布分析不足、尤其缺乏小时尺度规律研究的问题，本研究首先构建1982-2025年时间精度达小时级的中国非地震触发滑坡数据库（含347起滑坡），然后采用卡方拟合优度检验、卡方独立性检验、皮尔逊相关系数检验、二项分布检验及单样本t检验，系统开展多尺度时空分布规律分析。结果显示，空间上单位面积滑坡密度呈现“西南最高、华南及东南次之、西北与华中及华东较低、华北及东北最低”的特征，以人口密度与GDP密度为指标计算的滑坡暴露度指数指示华南及东南为最高风险区，华中及华东为高风险区，西南为中风险区，华北及东北为低风险区，西北为最低风险区。滑坡频次与平均坡度强线性正相关（R²≥0.49）、与平均高程中等线性正相关（0.09≤R²<0.49），且受降雨气候显著影响，即空间分布由地形与气候共同决定；月尺度上，全国5个区域滑坡均高发于6-8月，滑坡频次与月均降雨量强线性正相关（R²≥0.49），即月尺度分布由夏季集中降雨主导；小时尺度上，全国滑坡高发时段为03:00-15:00，其中降雨触发型高发于00:00-12:00（与夜雨水文响应匹配），非降雨触发型高发于08:00-20:00（与人类日间活动关联），即小时尺度分布受降雨与人类活动双重驱动。本研究表明中国非地震触发滑坡多尺度时空分布特征与区域地形气候条件及人类活动密切相关，不仅填补了中国非地震触发滑坡精确到小时级时间分布规律的研究空白，而且为滑坡分时段、分区域预警及风险防控提供了科学参考。
- 中国非地震触发滑坡 /
- 小时级滑坡数据库 /
- 多尺度时空分布
Abstract: To address the inadequacies in the multi-scale spatiotemporal distribution analysis of non-earthquake triggered landslides in China, particularly the lack of research on hourlyscale patterns, this study first established a 1982- 2025 non-earthquake triggered landslide database for China with hourly temporal precision (containing 347 landslides). Subsequently, systematic multi-scale spatiotemporal distribution pattern analysis was conducted using statistical methods including the chi-square goodness-of-fit test, chi-square test of independence, Pearson correlation coefficient test, binomial test, and one-sample t-test. The results show that spatially, the landslide distribution density exhibits the characteristic of "the highest in Southwest China, followed by South and Southeast China, lower in Northwest, Central and East China, and the lowest in North and Northeast China". The landslide exposure index calculated based on population density and GDP density indicates that South and Southeast China are the highest-risk zone, Central and East China are the high-risk zone, Southwest China is the medium-risk zone, North and Northeast China are the low-risk zone, and Northwest China is the lowest-risk zone. Landslide frequency has a strong positive linear correlation with average slope (R²≥0.49) and a moderate positive linear correlation with average elevation (0.09≤R²<0.49), and is significantly influenced by rainfall and climate conditions— indicating that the spatial distribution is jointly determined by terrain and climate. On the monthly scale, landslides in five regions of China are concentrated in June- August, and landslide frequency has a strong positive linear correlation with monthly average rainfall (R²≥0.49), meaning the monthly-scale distribution is dominated by concentrated summer rainfall. On the hourly scale, national landslides are predominantly concentrated in the 03:00- 15:00 period, with rainfall-triggered landslides peaking in 00:00- 12:00 (consistent with the hydrological response to nocturnal rainfall) and non-rainfall-triggered landslides peaking in 08:00- 20:00 (associated with diurnal human activities)—indicating that the hourly-scale distribution is dually driven by rainfall and human activities. This study demonstrates that the multi-scale spatiotemporal distribution characteristics of nonearthquake triggered landslides in China are closely related to regional terrain, climate conditions, and human activities. It not only fills the research gap in the hourly-scale temporal distribution patterns of non-earthquake triggered landslides in China but also provides scientific references for time-specific and region-specific early warning and risk prevention and control of landslides.
- non-earthquake triggered landslides in China /
- hourly-scale landslide database /
- multi-scale spatiotemporal distribution

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参考文献(61)

Ankang Municipal Bureau of Natural Resources, (2024-08-22) [2025-09-13]. Ankang Successfully Forecasts a Geological Disaster. https://zrzy.ankang.gov.cn/Content-2739645.html.
Baoji Municipal Water Resources Bureau, Baoji Municipal Meteorological Bureau, (2025-07-02) [2025-09-13]. Meteorological Early Warning for Flash Flood Disasters.
http://www.baoji.gov.cn/col9816/col9818/col9857/col9865/202507/t20250702_1164049.html.
Chen, X. B., (2025-07-27) [2025-09-13]. 5 People Confirmed Dead After Being Buried in a Car in a Landslide in Pu'er, Yunnan Province. Xinhua News Agency.
https://www.news.cn/politics/20250727/bba0e2a6a76942b387f59f1bae6dc426/c.html.
Cruden, D. M.,Varnes, D. J., 1996. Landslide Types and Processes, Special Report,Transportation Research Board, National Academyof Sciences, 247: 36-75.
David, P., 2012. Global patterns of loss of life from landslides. Geology, 40(10): 927-930. https://doi.org/10.1130/G33217.1
Feng, W. K., Zhao, J. C., Yi, X. Y., et al., 2025. Characteristics and Driving Factors of "6·16" Rainfall-Induced Group Landslides in the Fujian-Guangdong-Jiangxi Border Region. Earth Science, 50(10): 4111-4124 (in Chinese with English abstract).
Görüm, T., Fidan, S., 2021. Spatiotemporal variations of fatal landslides in Turkey. Landslides, 18: 1691-1705. https://doi.org/10.1007/s10346-020-01580-7
He, X. R., Liao, X. H., Zhang, L. Q., et al., 2022. Clustering Zoning of Landslide-Prone Factors and Analysis of Road Engineering Disturbance Effects in the Bailongjiang River Basin. Journal of Engineering Geology, 30(3): 672-687 (in Chinese with English abstract).
Huang, F. M., Ouyang, W. P., Jiang, S. H., et al., 2024. Landslide Susceptibility Prediction Modeling Considering the Spatiotemporal Partition Principle of Training/Testing Sets in Machine Learning. Earth Science, 49(5): 1607-1618 (in Chinese with English abstract).
Jiang, W. Y., (2024-07-29) [2025-09-18]. Sudden Landslide Geological Disaster in Xilin County, Baise City, with No Casualties. Nanguo Morning Post. https://www.ngzb.com.cn/news/2024/07/29/baise-linxian-tufa-huapo-dizhi-zaihai-renyuan-shangwang.html.
Kang, C., Zhang, F. Y., Pan, F. Z., et al., 2018. Characteristics and dynamic runout analyses of 1983 Saleshan landslide. Engineering Geology, 243: 181-195. https://doi.org/10.1016/j.enggeo.2018.07.006
Kirschbaum, D. B., Adler, R., Hong, Y., et al., 2010. A global landslide catalog for hazard applications: method, results, and limitations. Natural Hazards, 52: 561-575. https://doi.org/10.1007/s11069-009-9401-4
Kirschbaum, D., Stanley, T., Zhou, Y., 2015. Spatial and temporal analysis of a global landslide catalog. Geomorphology, 249: 4-15. https://doi.org/10.1016/j.geomorph.2015.03.016
Klose, M., Damm, B., Highland, L. M., 2015. Databases in geohazard science: An introduction. Geomorphology, 249: 1-3. https://doi.org/10.1016/j.geomorph.2015.06.029
Li, Z., Yang, M., Qiu, H., et al., 2025. Spatiotemporal patterns of non-seismic fatal landslides in China from 2010 to 2022. Landslides, 22: 221-233. https://doi.org/10.1007/s10346-024-02362-1
Lin, Q., Wang, Y., 2018. Spatial and temporal analysis of a fatal landslide inventory in China from 1950 to 2016. Landslides, 15: 2357-2372. https://doi.org/10.1007/s10346-018-1037-6
Lin, Q., Wang, Y., Liu, T., et al., 2017. The Vulnerability of People to Landslides: A Case Study on the Relationship between the Casualties and Volume of Landslides in China. International Journal of Environmental Research and Public Health, 14(2):212. https://doi.org/10.3390/ijerph14020212
Liu, Q., Gan, J. J., Chen, H., et al., 2024. Formation Mechanism and Rainfall Factor Stability Evaluation of Small-Scale Soil Landslides in Eastern Jiangxi. Bulletin of Geological Science and Technology, 43(6): 235-243 (in Chinese with English abstract).
Marc, O., Gosset, M., Saito, H., et al., 2019. Spatial patterns of storm-induced landslides and their relation to rainfall anomaly maps. Geophysical Research Letters, 46: 11167-11177. https://doi.org/10.1029/2019GL083173
Monsieurs, E., Jacobs, L., Michellier, C., et al., 2018. Landslide inventory for hazard assessment in a data-poor context: a regional-scale approach in a tropical African environment. Landslides, 15, 2195-2209. https://doi.org/10.1007/s10346-018-1008-y
Rosser, B., Dellow, S., Haubrock, S., et al., 2017. New Zealand’s National Landslide Database. Landslides, 2017, 14: 1949-1959. https://doi.org/10.1007/s10346-017-0843-6
Sepúlveda, S. A., Petley, D. N., 2015. Regional trends and controlling factors of fatal landslides in Latin America and the Caribbean, Natural Hazards and Earth System Sciences, 15: 1821-1833. https://doi.org/10.5194/nhess-15-1821-2015
Shibasaki, T., Matsuura, S., Okamoto, T., 2016. Experimental evidence for shallow, slow-moving landslides activated by a decrease in ground temperature. Geophysical Research Letters, 43: 6975-6984. https://doi.org/10.1002/2016GL069604
Van Den Eeckhaut, M., Hervás, J., 2012. State of the art of national landslide databases in Europe and their potential for assessing landslide susceptibility, hazard and risk. Geomorphology, 139-140: 545-558. https://doi.org/10.1016/j.geomorph.2011.12.006
Wang, J. S., Jiang, X., Zhang, X. D., 2022. Study on Spatiotemporal Variation Characteristics of Night Rain in China. Journal of Nanjing University (Natural Sciences), 58(5): 750-765 (in Chinese with English abstract).
Wen, A. B., Tang, Q., Ouyang, C. J., et al., 2023. Protection and Development of Mountains in China: Review and Prospect. Bulletin of the Chinese Academy of Sciences, 38(3): 376-384 (in Chinese with English abstract).
Wen, B., Wang, S., Wang, E., et al., 2004. Characteristics of rapid giant landslides in China. Landslides, 1: 247-261. https://doi.org/10.1007/s10346-004-0022-4
Wu, K., Chen, N., Hu, G., et al., 2021. Failure mechanism of the Yaoba loess landslide on March 5, 2020: the early-spring dry spell in Southwest China. Landslides, 18: 3183-3195. https://doi.org/10.1007/s10346-021-01703-8
Wu, Q. H., Wang, K., 2025. Influence of Slope Angle and Lithological Characteristics of Fine/Coarse Binary Structure Slopes on Their Rainfall Infiltration Barrier Effect. Earth Science, 50(1): 311-321 (in Chinese with English abstract).
Wu, Y. H., Nie, Y., Han, L. Q., 2024. Landslide Event Dataset of the China-Pakistan Economic Corridor (2010-2022). National Cryosphere Desert Data Center. http://www.ncdc.ac.cn.
Xin, Y., (2025-07-30) [2025-09-13]. Rescue Continues for Missing Bus in Tianzhen County, Shanxi Province: 10 Missing Persons Found, All Deceased. Sina Finance. https://finance.sina.com.cn/jjxw/2025-07-30/doc-infifzsr3724785.shtml.
Xu, H., 2023. Extreme Characteristics of Precipitation and Variation Trends for Landslide Induction in China. Journal of Mountain Science, 41(4): 545-553 (in Chinese with English abstract).
Xu, X. D., Qi, D. M., Li, Y. Q., et al., 2024. Spatio-Temporal Characteristics of Floods and Landslide-Debris Flow Disasters in China and the Advancement Process of the East Asian Summer Monsoon under Multi-Scale Topographical Background. Plateau and Mountain Meteorology Research, 44(4): 1-10 (in Chinese with English abstract).
Yin, Y., Wang, F., Sun, P., 2009. Landslide hazards triggered by the 2008 Wenchuan earthquake, Sichuan, China. Landslides, 6: 139-152. https://doi.org/10.1007/s10346-009-0148-5
Zhang, F., Huang, X., 2018. Trend and spatiotemporal distribution of fatal landslides triggered by non-seismic effects in China. Landslides, 15: 1663-1674. https://doi.org/10.1007/s10346-018-1007-z
Zhang, S. F., Wang, Y. F., Jia, B., et al., 2017. Spatiotemporal Variations and Influencing Factors of Geological Disasters in China from 2005 to 2016. Journal of Geo-Information Science, 19(12): 1567-1574 (in Chinese with English abstract).
Zhang, S., Li, C., Peng, J., et al., 2023. Fatal landslides in China from 1940 to 2020: occurrences and vulnerabilities. Landslides, 20: 1243-1264. https://doi.org/10.1007/s10346-023-02034-6
Zhang, Y. F., Liao, X. P., Li, J., et al., 2023. Prevention and Control of Landslide Disasters in Mountain Road Engineering. China Science and Technology Achievements, 24(23): 51-53, 74 (in Chinese with English abstract).
Zhang, Y. N., 2021. Landslide Point Data of the Weihe River Basin (1915-2021). National Cryosphere Desert Data Center. http://www.ncdc.ac.cn.
Zhou, W., Qiu, H., Wang, L., et al., 2022. Combining rainfall-induced shallow landslides and subsequent debris flows for hazard chain prediction. Catena, 213: 106199. https://doi.org/10.1016/j.catena.2022.106199
中文参考文献
安康市自然资源局, (2024-08-22) [2025-09-13].安康成功预报一起地质灾害. https://zrzy.ankang.gov.cn/Content-2739645.html.
宝鸡市水利局, 宝鸡市气象局, (2025-07-02) [2025-09-13]. 山洪灾害气象预警. http://www.baoji.gov.cn/col9816/col9818/col9857/col9865/202507/t20250702_1164049.html.
陈欣波, (2025-07-27) [2025-09-13]. 云南普洱山体滑坡被埋车内 5 人确认遇难. 新华社. https://www.news.cn/politics/20250727/bba0e2a6a76942b387f59f1bae6dc426/c.html.
冯文凯, 赵家琛, 易小宇, 等, 2025. 闽粤赣边区“6·16”强降雨诱发群发滑坡特征与驱动因素. 地球科学, 50(10): 4111-4124.
何晓锐, 廖小辉, 张路青, 等, 2022. 白龙江流域崩滑灾害孕灾因子聚类分区与道路工程扰动效应分析. 工程地质学报, 30(3): 672-687.
黄发明, 欧阳慰平, 蒋水华, 等, 2024. 考虑机器学习建模中训练/测试集时空划分原则的滑坡易发性预测建模. 地球科学, 49(5): 1607-1618.
蒋文跃, (2024-07-29) [2025-09-18]. 百色西林县突发滑坡地质灾害, 无人员伤亡. 南国早报. https://www.ngzb.com.cn/news/2024/07/29/baise-linxian-tufa-huapo-dizhi-zaihai-renyuan-shangwang.html.
刘清, 甘建军, 陈浩, 等, 2024. 赣东小型土质滑坡形成机理及降雨因子稳定性评价. 地质科技通报, 43(6): 235-243.
王敬诗, 蒋熹, 张夕迪, 2022. 中国夜雨的时空变化特征研究. 南京大学学报（自然科学）, 58(5): 750-765.
文安邦, 汤青, 欧阳朝军, 等, 2023. 中国山地保护与山区发展:回顾与展望. 中国科学院院刊, 38(3): 376-384.
吴庆华, 王珂, 2025. 细/粗二元结构边坡角度与岩性特征对其阻隔降雨入渗的影响规律. 地球科学, 50(1): 311-321.
吴宇宏, 聂勇, 韩立钦, 2024. 中巴经济走廊滑坡事件数据集（2010-2022年）. 国家冰川冻土沙漠科学数据中心. http://www.ncdc.ac.cn.
辛圆, (2025-07-30) [2025-09-13]. 山西省天镇县客车失联救援继续: 已发现 10 名失联人员, 均已遇难. 新浪财经. https://finance.sina.com.cn/jjxw/2025-07-30/doc-infifzsr3724785.shtml.
徐辉, 2023. 中国诱发滑坡的降水极端性特征及变化趋势. 山地学报, 41(4): 545-553.
徐祥德, 齐冬梅, 李跃清, 等, 2024. 多尺度地形背景下东亚夏季风推进过程与我国洪涝和滑坡泥石流灾害时空特征. 高原山地气象研究, 44(4): 1-10.
张耀南, 2021. 渭河流域滑坡点数据（1915-2021年）. 国家冰川冻土沙漠科学数据中心. http://www.ncdc.ac.cn.
张玉芳, 廖小平, 李健, 等, 2023. 山区道路工程滑坡灾害防治. 中国科技成果, 24(23): 51-53, 74.
章诗芳, 王玉芬, 贾蓓, 等, 2017. 中国2005-2016年地质灾害的时空变化及影响因素分析. 地球信息科学学报, 19(12): 1567-1574.