集中降雨影响下辽南仙人洞国家级自然保护区滑坡灾害多因子风险评价

郑德凤; 潘美伊; 高敏; 闫成林; 李媛媛; 年廷凯

doi:10.19509/j.cnki.dzkq.tb20240509

集中降雨影响下辽南仙人洞国家级自然保护区滑坡灾害多因子风险评价

doi: 10.19509/j.cnki.dzkq.tb20240509

郑德凤^{1a, 1b,},
潘美伊^1a,
高敏^1a,
闫成林^1a,
李媛媛^1a,
年廷凯^2, ,

1a.
辽宁师范大学地理科学学院
1b.
辽宁师范大学大连市农业气象灾害风险防控重点实验室，辽宁大连 116029
2.
大连理工大学建设工程学院，辽宁大连 116024

基金项目: 国家自然科学基金项目（42077272）；辽宁师范大学高端科研成果培育资助计划项目（23GDL007）

详细信息

作者简介:
郑德凤：E-mail：defengzheng@lnnu.edu.cn

通讯作者:
E-mail：tknian@dlut.edu.cn

中图分类号: P642.22
计量
- 文章访问数: 90
- PDF下载量: 9
- 被引次数: 0
出版历程
- 收稿日期: 2024-09-06
- 录用日期: 2024-11-06
- 修回日期: 2024-11-02
- 网络出版日期: 2024-11-18

Multi-factor risk assessment of landslide disasters under concentrated rainfall in Xianrendong national nature reserve in southern Liaoning Province

ZHENG Defeng^{1a, 1b
,},
PAN Meiyi^1a,
GAO Min^1a,
YAN Chenglin^1a,
LI Yuanyuan^1a,
NIAN Tingkai^{2
, ,}

1a.
Liaoning Normal University School of Geography
1b.
Liaoning Normal University Dalian Key Laboratory of Agro-Meteorological Disaster Risk Prevention and Control, Liaoning Normal University, Dalian Liaoning 116029, China
2.
School of Construction Engineering, Dalian University of Technology, Dalian Liaoning 116024, China

More Information

Author Bio:
E-mail：defengzheng@lnnu.edu.cn

Corresponding author: E-mail：tknian@dlut.edu.cn

摘要

摘要:
位于辽宁省南部的仙人洞国家级自然保护区及毗邻区域，近年来在集中降雨期间多次发生滑坡等地质灾害；然而，针对集中降雨影响下该区域滑坡灾害易发性与风险评价还很少探究，因此亟待开展深入研究，这对有效减轻保护区地质灾害危害、提升地质灾害应急和风险防控能力具有重要意义。首先利用SMOTE-Tomek综合采样法、耦合XGBoost模型，对地形地貌、地质岩性、水文气象和人类工程活动因子等12个指标进行深入分析，以获取滑坡灾害易发性评价结果；其次，着重考虑短时间集中降雨和连续性降雨影响，利用研究区周围4个气象站的日降雨数据，计算2018−2023年平均暴雨强度和3 d累计降雨量，作为危险性评价指标，实现对滑坡灾害危险性的量化评估。在此基础上，考虑承灾体的易损性特点和区域防灾减灾能力，构建适用于研究区的多因子滑坡灾害风险评价模型，进而得到滑坡灾害风险评价分区图。结果表明：较高及以上等级风险区约占研究区总面积的10%，主要分布在仙人洞镇东北部、步云山乡北部、长岭镇北部和荷花山镇西南部。未来应重点关注滑坡地质灾害风险较高的仙人洞镇和步云山乡，加强监测和预警工作，为整个研究区的地质灾害防控提供决策支持。
- 滑坡灾害 /
- 易发性评价 /
- 风险评价 /
- SMOTE-Tomek算法 /
- XGBoost模型 /
- 防灾减灾能力 /
- 自然保护区 /
- 集中降雨
Abstract: Objective
Xianrendong National Nature Reserve in southern Liaoning Province and its adjacent areas have experienced numerous geological disasters, such as landslides, during periods of concentrated rainfall in recent years. However, the vulnerability and risk assessment of landslide disasters in this region under the influence of concentrated rainfall have been rarely explored. Therefore, it is urgent to conduct in-depth research, which is of great significance for effectively reducing the harm of geological disasters in the reserve and enhancing the capacity for emergency response and risk prevention and control.
Method
Firstly, using the SMOTE-Tomek comprehensive sampling method coupled with an XGBoost model, 12 indices including topography, geology and lithology, hydrometeorology, and human engineering activities are deeply analyzed to obtain the evaluation results of landslide susceptibility. Secondly, focusing on the impact of short-term concentrated rainfall and continuous rainfall, daily rainfall data from four weather stations surrounding the study area are used to calculate annual average rainstorm intensity from 2018 to 2023 and three-day cumulative rainfall as risk assessment indicators, enabling the quantitative assessment of landslide hazards. On this basis, considering the vulnerability characteristics of the disaster-bearing body and regional disaster prevention and mitigation capabilities, a multi-factor landslide disaster risk assessment model suitable for the study area is constructed, resulting in a landslide disaster risk zoning map.
Result
The results show that high-risk and above areas account for approximately 10% of the total study area, primarily distributed in the northeast of Xianrendong Town, the north of Buyunshan Town, the north of Changling Town, and the southwest of Hehuashan Town.
Conclusion
In the future, efforts should focus on high-risk areas such as Xianrendong Town, strengthening monitoring and early warning systems to provide decision support for the prevention and control of geological disasters across the entire study area.
- landslide disaster /
- susceptibility evaluation /
- risk assessment /
- SMOTE-Tomek algorithm /
- XGBoost model /
- disaster prevention and mitigation capacity /
- nature reserve /
- concentrated rainfall

HTML全文

图 1 研究区位置(a)和概况图(b)

Figure 1. Location (a) and overview map (b) of the study area

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图 2 SMOTE-Tomek算法原理（图中x₁，x₂为2个不同样本的特征值）

Figure 2. SMOTE-Tomek algorithm principle

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图 3 研究区2018−2023年平均降雨强度空间分布图

Figure 3. Spatial distribution map of annual average rainfall intensity from 2018 to 2023 in the study area

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图 4 研究区3 d累计降雨量空间分布图

Figure 4. Spatial distribution map of three-day cumulative rainfall in the study area

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图 5 研究区滑坡灾害承灾体易损性评价因子分布图

Figure 5. Distribution map of vulnerability evaluation factors of landslide disaster-bearing bodies in the study area

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图 6 研究区滑坡灾害易发性分区图

Figure 6. Zoning diagram of landslide disaster susceptibility

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图 7 滑坡灾害易发性评价ROC曲线

Figure 7. ROC curve of landslide disaster susceptibility evaluation

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图 8 研究区滑坡灾害危险性分区图

Figure 8. Landslide risk zoning map of the study area

下载: 全尺寸图片幻灯片

图 9 研究区滑坡灾害承灾体易损性分区图

Figure 9. Vulnerability zoning map of landslide disaster-bearing bodies in the study area

下载: 全尺寸图片幻灯片

图 10 研究区防灾减灾能力分区图

Figure 10. Zoning map of disaster prevention and mitigation capacity of the study area

下载: 全尺寸图片幻灯片

图 11 研究区滑坡灾害风险分区图

Figure 11. Risk zoning map of landslide disaster in the study area

下载: 全尺寸图片幻灯片

表 1 研究区滑坡灾害易发性评价因子及其分类区间和分类标准

Table 1. Evaluation factors, classification intervals and standards of landslide disaster susceptibility in the study area

一级指标	二级指标	分类区间	分级标准
地形地貌	高程/m	<134，[134，238)，[238，370)，[370，549]，>549	自然断点法
	坡向	平地、北、东北、东、东南、南、西南、西、西北	文献[21]
	坡度/(°)	<5.97，[5.97，11.73)，[11.73，18.14)，[18.14，25.4]，>25.4	自然断点法
	地形起伏度/m	<9，[9，19)，[19，29)，[29，41]，>41	自然断点法
	地形湿度指数	<5.86，[5.86，7.74)，[7.74，10.67)，[10.67，14.75]，>14.75	自然断点法
地质岩性	岩性	极硬、硬、较硬、较软、软	工程岩体分级标准
地质岩性	距断层距离/m	<500，[500，1000)，[1000，1500)，[1500，2000]，>2000	等间距划分
气象水文	汛期年降雨量/（mm·a⁻¹）	<502.2，[502.2，520.0)，[520.0，538.2)，[538.2，556.0]，>556.0	自然断点法
气象水文	距河流距离/m	<200，[200，400)，[400，600)，[600，800]，>800	等间距划分
人类工程活动	土地利用	水域、未利用地、耕地、建设用地、林地、草地	国家土地利用分类标准
	距道路距离/m	<200，[200，500)，[500，800)，[800，1200)，[1200，2500]，>2500	文献[22-23]
	归一化植被指数	<0.68，[0.68，0.74)，[0.74，0.80)，[0.80，0.85]，>0.85	自然断点法
注：数据来源①数字高程模型数据：中国地理空间数据云网（http://www.gscloud.cn/），分辨率为30 m×30 m；②土地利用数据：地理监测云平台（https://www.dsac.cn）；③岩性和断层数据：提取自大连市1∶25万地质图（全国地质资料馆网站thhp://www.ngac.cn）；④水文气象数据：中国气象数据网（http://data.cma.cn）；⑤水系和道路数据：OpenStreetMap网站（https://www.openstreetmap.org）；⑥归一化植被指数数据：资源环境科学与数据中心（https://www.resdc.cn），分辨率为1 km×1 km

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表 2 研究区滑坡灾害承灾体易损性评价因子和分级标准

Table 2. Vulnerability evaluation factors and grading standards of landslide disaster-bearing bodies in the study area

一级指标	二级指标	指标权重	低易损性	较低易损性	中易损性	较高易损性	高易损性
人口易损性	人口密度/(人·km⁻²)	0.3664	<156	[156，179)	[179，212)	[212，250]	>250
物质易损性	农村居民点密度/(10⁴m²·km⁻²)	0.1496	<2.45	[2.45，2.94)	[2.94，3.10)	[3.10，3.73]	>3.73
物质易损性	道路密度/(km·km⁻²)	0.0849	<0.31	[0.31，0.69)	[0.69，1.73)	[1.73，2.66]	>2.66
经济易损性	耕地密度/(km²·km⁻²)	0.1245	<0.18	[0.18，0.19)	[0.19，0.24)	[0.24，0.34]	>0.34
	国内生产总值/(万元·km⁻²)	0.0522	<660	[660，1064)	[1064，1292)	[1292，1611]	>1611
	林地密度/(km²·km⁻²)	0.2224	<0.44	[0.44，0.55)	[0.55，0.68)	[0.68，0.72]	>0.72
注：①人口密度和国内生产总值数据来源于资源环境科学数据注册与出版系统(https://www.resdc.cn)；②农村居民点、耕地、林地数据来源于资源环境科学与数据中心(https://www.resdc.cn)

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表 3 研究区防灾减灾能力评价指标及对应权重

Table 3. Indicators and corresponding weights of disaster prevention and mitigation capacity in the study area

一级指标	一级指标权重${\omega _{\mathrm{f}}}$	二级指标	二级指标权重${\omega _{\mathrm{g}}}$
防灾能力	0.3091	地质勘探与测绘公司数量/个	0.6667
防灾能力	0.3091	地方一般公共预算支出/万元	0.3333
应灾能力	0.5813	义务教育在校学生数/人	0.2298
		居民青壮年人数占长居人数比例	0.6479
		医护人员数/人	0.1223
灾后重建能力	0.1096	住户储蓄存款余额/万元	0.7500
灾后重建能力	0.1096	医疗、社区、卫生院床位/张	0.2500
注：防灾减灾能力数据来源于《2023中国县域统计年鉴（乡镇版）》、《2023大连市统计年鉴》

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