基于发生指数的临沂岩溶塌陷预警模型研究

邹连庆; 褚福建; 王振涛; 姚春梅; 陈亚男; 廉波; 魏忠爱; 蒙永辉

doi:10.11932/karst20230518

基于发生指数的临沂岩溶塌陷预警模型研究

doi: 10.11932/karst20230518

邹连庆^{1, 2,},
褚福建^{1, 2, ,},
王振涛^{1, 2},
姚春梅^{1, 2},
陈亚男³,
廉波⁴,
魏忠爱⁵,
蒙永辉^{1, 2}

1.
山东省国土空间生态修复中心, 山东济南 250014
2.
自然资源部黄河三角洲土地利用安全野外科学观测研究站, 山东滨州 251900
3.
临沂市自然资源和规划局测绘院, 山东临沂 276001
4.
山东省第七地质矿产勘查院, 山东临沂 276006
5.
临沂市自然资源开发服务中心, 山东临沂 276001

基金项目: 山东省重点研发计划项目（2021CXGX010704）；临沂市自然资源和规划局项目（SDTZLY-2019-21）；临沂市自然资源开发服务中心项目（SDGP371300202102000363）

详细信息

作者简介:
邹连庆（1985－），男，高级工程师，硕士研究生，主要从事水工环地质工作。E-mail：zoulianqing2010@163.com

通讯作者:
褚福建（1964－），男，高级工程师，主要从事水工环地质工作。E-mail：chufujian@shandong.cn

中图分类号: P642.25
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出版历程
- 收稿日期: 2023-04-20
- 录用日期: 2023-08-04
- 修回日期: 2023-08-03
- 刊出日期: 2023-10-01

Study on the early warning model based on the occurrence index of karst collapse in Linyi City

ZOU Lianqing^{1, 2
,},
CHU Fujian^{1, 2
, ,},
WANG Zhentao^{1, 2},
YAO Chunmei^{1, 2},
CHEN Yanan³,
LIAN Bo⁴,
WEI Zhongai⁵,
MENG Yonghui^{1, 2}

1.
Shandong Provincial Territorial Spatial Ecological Restoration Center, Jinan, Shandong 250014, China
2.
Field Scientific Observation and Research Station for Land Use Safety in the Yellow River Delta, Ministry of Natural Resources, Binzhou, Shandong 251900, China
3.
Surveying and Mapping Institute of Linyi Natural Resources and Planning Bureau, Linyi, Shandong 276001, China
4.
Shandong Seventh Institute of Geology and Mineral Resources, Linyi, Shandong 276006, China
5.
Linyi Services Center for Natural Resources Development, Linyi, Shandong 276001, China

摘要

摘要: 临沂市区中奥陶系灰岩岩溶发育，第四系覆盖层较薄，具备岩溶塌陷发育条件。20世纪80年代至21世纪初期岩溶塌陷灾害频发。文章以临沂市区岩溶塌陷作为研究对象，对其分布规律及影响因素进行了研究，提出了基于岩溶塌陷发生指数的预警模型，该模型以水位为主控监测因素，多因素叠加综合判定进行预警，并使用历史数据对模型进行验证，结果表明：该模型在临沂市城区重点监测区预警结果验证的可靠性较高，可为其他地区岩溶塌陷地质灾害监测预警提供借鉴。
- 岩溶塌陷 /
- 综合判定 /
- 监测预警 /
- 临沂市区 /
- 中奥陶系灰岩 /
- 第四系覆盖层
Abstract: The urban area of Linyi City is endowed with the basic conditions for the development of karst collapse. In this area, Ordovician limestone with karst development is widely distributed, and the limestone is covered by a thin Quaternary overburden with a binary phase structure. From the 1980s to the early 21^st century, the rapid development of Linyi City, the increase of groundwater exploitation and the decline of the overall regional water level led to the frequent occurrence of geological disasters of karst collapses, causing serious economic losses and social impact.In this study, the karst collapse in Linyi City is taken as the research object. The distribution law, geological conditions, and inducing factors of karst collapses are studied through statistical analysis. According to the analysis of the genesis mechanism of karst collapse in Linyi City, an early warning model based on the occurrence index of karst collapse is proposed. Taking the water level as the main monitoring factor, this model is constructed to comprehensively judge the early warning by the combination of multi-factors, and is verified by historical data.During the high incidence period from 1993 to 2012, a total of 17 karst collapses occurred in the study area. These karst collapses were caused by geological conditions such as topography, geological structure, and formation lithology, as well as inducing factors such as groundwater exploitation, human engineering activities, and precipitation. The distribution law of karst collapse reflects the consistency with its related influencing factors. Karst collapses are mainly distributed in the caprock area of double-layer structure with shallow karst development and small overburden thickness. They are also distributed near the surface water body and fault zone. Generally, karst collapses take place in the funnel areas and in the seasons with a large variation of water levels, They also occur in the influence range of human engineering activities. With a comprehensive index method, an early warning model based on the judgment made through multi-factors is established. The model comprehensively considers geological conditions and inducing factors and selects 10 influencing factors, including karst development degree, caprock thickness, caprock structure, distance from structure, distance from surface water, distance between water level and limestone roof, water level amplitude, distance from the center of depression cone, precipitation, and human engineering activities. Different weights of influencing factors and the range of influencing factors of each sub-condition are given and the early warning level is divided into four grades according to the occurrence index value.The model is verified by using historical data of the collapse when it occurred. For example, the data of 2003 was used for simulation and early warning validation. The karst collapse occurred in the east of the No.32 building in Lanshan community on May 8 and June 22 in 2003, and all the collapse points were located in the area at a high early warning level, and also fell into the time period of high early warning level. The results show that the model has high reliability in the verification of early warning in key monitoring areas of Linyi City, which can provide a reference for monitoring and early warning of karst collapse in other areas.
- karst collapse /
- comprehensive judgment /
- monitoring and early warning /
- Linyi City /
- middle Ordovician limestone /
- Quaternary cover

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图 1 研究区区域地质概况

Figure 1. Regional geological overview of the study area

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图 2 岩溶塌陷点(坑)分布图

Figure 2. Distribution of karst collapse points

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图 3 岩溶水降落漏斗及塌陷点分布图

Figure 3. Distribution of depression cones of karst water and collapse points

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图 4 月发生岩溶塌陷频率统计分布

Figure 4. Statistical distribution of monthly karst collapse frequency

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图 5 岩溶塌陷点水位过程线图(兰山小区)

Figure 5. Water level process diagram of karst collapse point (Lanshan community)

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图 6 岩溶塌陷形成机制示意图

Figure 6. Schematic diagram of formation mechanism of karst collapse

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图 7 岩溶塌陷发生指数分区图

Figure 7. Zoning map of occurrence index of karst collapse

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图 8 兰山小区岩溶塌陷发生指数(2003.4.1—2003.7.26)

Figure 8. Occurrence index of karst collapse in Lanshan community (2003.4.1–2003.7.26)

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图 9 兰山小区岩溶塌陷发生指数(2022.4.1—2022.7.30)

Figure 9. Occurrence index of karst collapse in Lanshan community (2022.4.1–2022.7.30)

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表 1 主要岩溶塌陷情况一览表

Table 1. List of main karst collapses

序号	塌陷年月	塌陷位置	陷坑个数	陷坑形态			地层结构
序号	塌陷年月	塌陷位置	陷坑个数	陷坑长度/m	陷坑宽度/m	陷坑深度/m	地层结构	覆层厚度/m
1	1993.6	苗庄小区	1	25.0	15.0	5.0	−	−
2	1994.3	道沟村	1	3.0	3.0	2.8	二元相结构	3.0
3	1994.4	国棉八厂	3	6.3	6.3	2.3	二元相结构	8.0
				8.0	8.0	5.0
				2.2	2.2	2.1
4	1995.4	药材批发市场	多个	<3.0	<3.0	2.8	−	−
5	2002.8	杜三岗村	3	10.0	10.0	2.5	−	6.1
				4.5	4.5	2.5
				1.5	1.5	2.5
6	2003.2	苗庄小区	−	−	−	−	二元相结构	4.0
7	2003.5	临沂监狱	1	15.0	7.0	4.0	二元相结构	−
8	2003.6	兰山小区	1	4.7	4.7	4.0	二元相结构	10.0
9	2003.6	红埠寺村	1	0.8	0.8	−	二元相结构	−
10	2003.6	兰山小区	1	5.5	4.0	2.5	二元相结构	10.0
11	2005.6	雅禾纺织	1	20.0	10.0	5.0	二元相结构	−
12	2007.8	道沟村	1	1.0	1.0	9.0	二元相结构	−
13	2008.1	道沟村	1	1.5	1.5	−	二元相结构	−
14	2008.5	大岭村	9	−	−	−	二元相结构	6.0
15	2011.6	后岗头村	1	−	−	2.5	二元相结构	−
16	2011.8	道沟村	1	0.5	0.5	−	二元相结构	−
17	2012.7	大岭村	2	5.0	3.0	2.0	二元相结构	−
17	2012.7	大岭村	2	3.3	1.2	1.5	二元相结构	−

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表 2 岩溶塌陷分布规律(地质条件)

Table 2. Distribution law of karst collapse (geological conditions)

	距离/km	塌陷数量/个	所占比例/%
地表水体	<1	16	76.2
地表水体	>1	5	23.8
断裂带	<1	15	71.4
断裂带	>1	6	28.6

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表 3 岩溶塌陷分布规律(诱发因素)

Table 3. Distribution law of karst collapse (inducing factors)

	距离/km	塌陷数量/个	所占比例/%
漏斗中心	<2	14	66.7
漏斗中心	>2	7	33.3

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表 4 指标权重取值表

Table 4. List of index weight value

基本条件	权重取值	分项条件	权重取值
地质条件	0.572 1	岩溶发育程度	0.257 4
		盖层厚度	0.074 4
		盖层结构	0.097 3
		与构造距离	0.085 8
		与地表水体距离	0.057 2
诱发因素	0.427 9	水位与界面距离	0.124 1
		水位变幅	0.132 6
		与降落漏斗中心距离	0.055 6
		降水量	0.038 5
		人类工程活动	0.077 1

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表 5 影响因子取值范围表

Table 5. List of the value range of influencing factors

基本条件	分项条件		分项条件影响因素取值范围（0~10）
基本条件	分项条件		0~2	2~4	4~6	6~8	8~10
地质条件	岩溶发育程度		无	很不发育	不发育	发育	很发育
	盖层厚度/m		<0.5 >25	20~25	15~20	0.5~3 11~15	3~11
	盖层结构		无	一元结构	一元结构	二元结构	多元结构
	与构造距离/m		>1 000	700~1 000	400~700	200~400	<200
	与地表水体距离/m		>1 000	700~1 000	400~700	200~400	<200
诱发因素	水位与基岩面关系		水位处于基岩面以上	水位偶尔处于基岩面以下5~10 m	水位偶尔处于基岩面以下10~20 m	水位长期处于基岩面以下10~20 m	基岩面附近5 m以内波动或长期处于基岩面20 m以下
	水位变幅/m		<1	1~4	4~7	7~10	>10
	与降落漏斗中心距离		>8 000或不处于漏斗范围内	5 000~8 000	3 000~5 000	2 000~3 000	<2 000
	降水量/mm	小时降雨量	<2.6	2.6~8	8~12	12~16	>16
		日降雨量	<10	10~25	25~50	25~50	>50
		月降雨量环比增长	<40	40~60	60~80	80~100	>100
	与抽水井距离/m		>500	200~500	100~200	50~100	<50

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