基于MODFLOW-CFP模型的岩溶隧道涌水量预测

潘毅; 王思琪; 谭家华; 赵恒; 林宇航; 童紫茹; 万军伟

doi:10.19509/j.cnki.dzkq.tb20240106

基于MODFLOW-CFP模型的岩溶隧道涌水量预测

doi: 10.19509/j.cnki.dzkq.tb20240106

潘毅^{1, 2,},
王思琪^{1, 2},
谭家华³,
赵恒¹,
林宇航¹,
童紫茹¹,
万军伟^1, ,

1.
中国地质大学（武汉）环境学院，武汉 430078
2.
湖北省地质局水文地质工程地质大队，湖北荆州 434020
3.
中铁第四勘察设计院集团有限公司，武汉 430063

基金项目: 中铁第四勘察设计院集团有限公司项目（五峰至恩施段岩溶发育规律及对长大隧道工程影响研究）

详细信息

作者简介:
潘毅：E-mail：903090634@qq.com

通讯作者:
E-mail：Wanjw@cug.edu.cn

中图分类号: P641.134
计量
- 文章访问数: 95
- PDF下载量: 14
- 被引次数: 0
出版历程
- 收稿日期: 2024-03-20
- 录用日期: 2024-06-04
- 修回日期: 2024-06-03
- 网络出版日期: 2025-12-18

Prediction water inflow in a karst tunnel based on MODFLOW-CFP model

PAN Yi^{1, 2
,},
WANG Siqi^{1, 2},
TAN Jiahua³,
ZHAO Heng¹,
LIN Yuhang¹,
TONG Ziru¹,
WAN Junwei^{1
, ,}

1.
School of Environmental Studies, China University of Geosciences (Wuhan), Wuhan 430078, China
2.
Hydrogeology and Engineering Geology Institute of Hubei Geology Bureau, Jingzhou Hubei 434020, China
3.
China Railway Siyuan Survey and Design Group Co., Ltd., Wuhan 430063, China

More Information

Author Bio:
E-mail：903090634@qq.com

Corresponding author: E-mail：Wanjw@cug.edu.cn

摘要

摘要:
隧道工程穿越岩溶地区时往往面临着高危害性的突涌水灾害，尤其当隧道穿越地下暗河系统时，施工和运营安全有巨大风险，因此准确预测隧道涌水量不仅是工程建设关注的焦点，同时也是隧道涌水量预测方法的难点。以鄂西后湾暗河系统为例，开展基于MODFLOW-CFP模型的隧道涌水量预测模拟方法研究，尤其是数值模型构建、模型识别过程中容易被忽视的岩溶水文地质调查、降雨与暗河流量响应过程监测以及地下水示踪试验等基础工作方法的研究，在此基础上构建岩溶地区隧道涌水量预测的MODFLOW-CFP模型，开展不同隧道设计方案的涌水量预测和对比分析，为隧道工程设计优化提供依据。研究查明了后湾岩溶水系统的范围、边界条件、地下水循环特征和降雨与水文响应规律，准确识别了后湾暗河地下管道的特征参数，为MODFLOW-CFP数值模拟方法的准确应用提供了基础，最终模型的线性相关系数R²为0.831，纳什效率系数NSE为0.71，能够良好地反映系统的水文过程。涌水量预测结果显示：极端强降雨（日降雨量P=325 mm）情景下，不同的隧道设计标高（1350，1330，1318，1270 m），涌水量峰值差异极大，分别为0，0.52，8.17，14.88 m³/s。研究表明抬高隧道设计标高能够有效减小隧道突涌水量，降低隧道突涌水风险。本研究采用的岩溶地下水系统调查、监测、试验和数值模拟方法可以为类似地区提供借鉴。
- 管道型岩溶水系统 /
- 调查方法 /
- 隧道涌水量预测 /
- 数值模拟 /
- MODFLOW-CFP
Abstract: Objective
Tunnel construction in karst areas often faces the high-risk sudden water inflow, posing serious threats to construction and operational safety. This risk is particularly critical when tunnels intersect underground river systems, where accurately prediction of water inflow is not only a key concern in engineering design but also a major challenge for existing prediction methods.
Methods
This study develops a tunnel water inflow prediction approach based on MODFLOW-CFP, using the Houwan underground river system in western Hubei as a case study. Particular emphasis is placed on several foundational tasks that are often overlooked during model construction and calibration, including detailed karst hydrogeological surveys, monitoring of rainfall-underground river discharge responses, and groundwater tracer tests. On this basis, a physically reasonable MODFLOW-CFP model for predicting tunnel water inflow in karst areas is constructed, and simulations under different tunnel design schemes are carried out to compare inflow processes and provide a basis for optimizing tunnel design.
Results
The study delineates the spatial extent and boundary conditions of the Houwan karst water system, clarifies its groundwater circulation characteristics, and rainfall-runoff response patterns, and accurately identifies the key parameters of the underground conduit network, thereby providing a foundation for the accurate application of the MODFLOW-CFP numerical model. The calibrated model yields a linear correlation coefficient (R²) of 0.831 and a Nash-Sutcliffe Efficiency (NSE) of 0.71, indicating that it can satisfactorily reproduce the hydrological behavior of the system. Under an extreme heavy rainfall scenario (P=325 mm), the predicted peak tunnel inflows differ markedly for design elevations of 1350, 1330, 1318 and 1270 m, with peak values of 0, 0.52, 8.17 and 14.88 m³/s, respectively.
Conclusion
The results demonstrate that raising the tunnel design elevation can effectively reduce the magnitude of sudden water inflow and thus lower the risk of water inrush during tunnel construction and operation. The integrated methodology of karst groundwater investigation, monitoring, testing and numerical simulation presented in this paper can provide a useful reference for similar projects in other karst regions.
- karst water system with conduit /
- survey method /
- tunnel water inflow prediction /
- numerical simulation /
- MODFLOW-CFP

HTML全文

图 1 后湾暗河系统综合岩溶水文地质图(a)及卫星影像图(b)

S+D. 志留系−泥盆系；C. 石炭系；P₂. 上二叠统；${\mathrm{T}}_1 {{d}}^1 $. 下三叠统大冶组一段；${\mathrm{T}}_1 {{d}}^2 $. 下三叠统大冶组二段；${\mathrm{T}}_1 {{d}}^3 $. 下三叠统大冶组三段；${\mathrm{T}}_1 j $. 下三叠统嘉陵江组；下同

Figure 1. Comprehensive karst hydrogeological map (a) and satellite image (b) of the Houwan underground river system

下载: 全尺寸图片幻灯片

图 2 后湾暗河水文地质剖面图（剖面位置见图1a）

Figure 2. Hydrogeological profile of the Houwan underground river

下载: 全尺寸图片幻灯片

图 3 暗河出口渠道示意图（b₁，b₂，H₁，H₁，θ均为渠道尺寸参数）

Figure 3. Schematic of the outlet of the underground river

下载: 全尺寸图片幻灯片

图 4 降雨−流量监测数据

Figure 4. Monitoring data of rainfall and discharge

下载: 全尺寸图片幻灯片

图 5 降雨入渗系数与总降雨量的关系

Figure 5. Relationship between rainfall infiltration coefficient and total rainfall

下载: 全尺寸图片幻灯片

图 6 后湾暗河示踪试验响应曲线图

Figure 6. Response curves from the tracer test in the Houwan underground river

下载: 全尺寸图片幻灯片

图 7 研究区模型结构

a. 研究区范围及边界条件；b. 模型虚拟钻孔及剖面设置；c. 模型三维网格剖分

Figure 7. Model structure of the study area

下载: 全尺寸图片幻灯片

图 8 模型参数分区图

L1-1. ${\mathrm{T}}_1 d^3 $地层岩溶主管道区；L1-2. ${\mathrm{T}}_1 d^3 $地层支岩溶管道区；L1-3. ${\mathrm{T}}_1 d^3 $地层主管道上游区域；L1-4. ${\mathrm{T}}_1 d^3 $地层其他岩溶中等发育区；L2. ${\mathrm{T}}_1 d^2 $地层区域；L3. ${\mathrm{T}}_1 d^1 $地层区域；下同

Figure 8. Parameters zoning of the model

下载: 全尺寸图片幻灯片

图 9 模型流量模拟结果图

Figure 9. Simulated flow results of the model

下载: 全尺寸图片幻灯片

图 10 不同标高隧道涌水过程

Figure 10. Tunnel water inflow for different elevations

下载: 全尺寸图片幻灯片

表 1 模型多孔介质参数取值

Table 1. Values of porous-media parameters in the model

分区	K_x/(m·h⁻¹)	K_y/(m·h⁻¹)	K_z/(m·h⁻¹)	SY
L1-1	0.8	0.96	0.4	0.008
L1-2	0.5	0.6	0.25	0.005
L1-3	0.3	0.36	0.15	0.003
L1-4	0.1	0.12	0.05	0.001
L2	0.1	0.12	0.03333	0.001
L3	0.05	0.06	0.01667	0.0005
注：K_x，K_y，K_z分别为模型x，y，z方向上的渗透系数；SY为给水度

下载: 导出CSV

表 2 模型管道参数取值

Table 2. Values of conduit parameters in the model

参数	取值	参数	取值
直径/m	6.9	下雷诺数	2300
弯曲度	1	上雷诺数	4000
实际长度/m	5480	管道交换系数/（m²·h⁻¹）	0.54978
粗糙度/m	0.1	水温/℃	12.6

下载: 导出CSV

表 3 不同标高场景下的隧道涌水过程特征参数

Table 3. Characteristic parameters of tunnel water inflow under different elevation scenarios

场景	①	②	③	④
隧道标高/m	1350	1330	1318	1270
正常涌水量/(m³·s⁻¹)	0	0	0.21	7.56
最大涌水量/(m³·s⁻¹)	0	0.52	8.17	14.88
涌水体积/(万m³)	0	3.87	108.8	640.1
滞后时间/h	0	16	5	5
延迟时间/h	0	82	169	>180

下载: 导出CSV

参考文献(40)

[1]	常威. 复杂岩溶水系统识别及其在隧道涌水量预测的应用研究: 以张吉怀高铁大青山隧道为例[D]. 武汉: 中国地质大学(武汉), 2021. CHANG W. Study on identification of complex karst water system and its application in tunnel water inflow prediction: Taking Daqingshan tunnel of Zhangjihuai high-speed railway as an example[D]. Wuhan: China University of Geosciences (Wuhan), 2021. (in Chinese with English abstract
[2]	王健华, 李术才, 李利平, 等. 富水岩层隧道区域涌水量预测方法及工程应用[J]. 人民长江, 2016, 47(14): 40-45. WANG J H, LI S C, LI L P, et al. Prediction method of water inrush tunnels in water rich area and its engineering application[J]. Yangtze River, 2016, 47(14): 40-45. (in Chinese with English abstract
[3]	YADETA D, KEBEDE A, TESSEMA N. Potential evapotranspiration models evaluation, modelling, and projection under climate scenarios, Kesem sub-basin, Awash River basin, Ethiopia[J]. Modeling Earth Systems and Environment, 2020, 6(4): 2165-2176. doi: 10.1007/s40808-020-00831-9
[4]	AFTES. Recommendations for the treatment of water inflows and outflows in operated underground structures[J]. Tunnelling and Underground Space Technology, 1989, 4(3): 343-407. doi: 10.1016/0886-7798(89)90084-9
[5]	ZHOU J Q, LIU H B, LI C D, et al. A semi-empirical model for water inflow into a tunnel in fractured-rock aquifers considering non-Darcian flow[J]. Journal of Hydrology, 2021, 597: 126149. doi: 10.1016/j.jhydrol.2021.126149
[6]	ZANG C W, HUANG H W, ZHANG Z X. Forecasting the strata condition of a long road tunnel by using fuzzy synthetic judgement[J]. International Journal of Rock Mechanics and Mining Sciences, 2004, 41(3): 406-407. doi: 10.1016/j.ijrmms.2003.12.003
[7]	肖竞, 万军伟, 成建梅, 等. MODFLOW-CFPv2模型在岩溶隧道突涌水及对地下水环境影响中的应用: 以云南鹤庆锰矿沟岩溶水系统为例[J]. 地质科技通报, 2024, 43(3): 301-310. XIAO J, WAN J W, CHENG J M, et al. Application of MODFLOW-CFPv2 model in karst tunnel water inrush and its impact on groundwater environment: Example of the Mengkuanggou karst water system in Heqing County, Yunnan Province[J]. Bulletin of Geological Science and Technology, 2024, 43(3): 301-310. (in Chinese with English abstract
[8]	SCANLON B R, MACE R E, BARRETT M E, et al. Can we simulate regional groundwater flow in a karst system using equivalent porous media models? Case study, Barton Springs Edwards aquifer, USA[J]. Journal of Hydrology, 2003, 276(1/2/3/4): 137-158.
[9]	WORTHINGTON S R H. Diagnostic hydrogeologic characteristics of a karst aquifer (Kentucky, USA)[J]. Hydrogeology Journal, 2009, 17(7): 1665-1678. doi: 10.1007/s10040-009-0489-0
[10]	GHASEMIZADEH R, HELLWEGER F, BUTSCHER C, et al. Review: Groundwater flow and transport modeling of karst aquifers, with particular reference to the North Coast limestone aquifer system of Puerto Rico[J]. Hydrogeology Journal, 2012, 20(8): 1441-1461. doi: 10.1007/s10040-012-0897-4
[11]	CHANG Y, WU J C, JIANG G H. Modeling the hydrological behavior of a karst spring using a nonlinear reservoir-pipe model[J]. Hydrogeology Journal, 2015, 23(5): 901-914. doi: 10.1007/s10040-015-1241-6
[12]	ASSARI A, MOHAMMADI Z. Assessing flow paths in a karst aquifer based on multiple dye tracing tests using stochastic simulation and the MODFLOW-CFP code[J]. Hydrogeology Journal, 2017, 25(6): 1679-1702.
[13]	CHANG Y, WU J C, LIU L. Effects of the conduit network on the spring hydrograph of the karst aquifer[J]. Journal of Hydrology, 2015, 527: 517-530. doi: 10.1016/j.jhydrol.2015.05.006
[14]	JUKIĆ D, DENIĆ-JUKIĆ V, LOZIĆ A. An alternative method for groundwater recharge estimation in karst[J]. Journal of Hydrology, 2021, 600: 126671. doi: 10.1016/j.jhydrol.2021.126671
[15]	陈迪, 闫海涛, 乔翔宇, 等. 巨厚非均质含水层中超深孔涌水量预测[J]. 地质科技通报, 2024, 43(4): 302-310. CHEN D, YAN H T, QIAO X Y, et al. Prediction of ultradeep pore water inflow in giant thick heterogeneous aquifers[J]. Bulletin of Geological Science and Technology, 2024, 43(4): 302-310. (in Chinese with English abstract
[16]	赵良杰. 岩溶裂隙−管道双重含水介质水流交换机理研究[D]. 北京: 中国地质大学(北京), 2019. ZHAO L J. Study on water exchange mechanism of karst fracture-pipeline dual water-bearing medium[D]. Beijing: China University of Geosciences(Beijing), 2019. (in Chinese with English abstract
[17]	FU T G, CHEN H S, ZHANG W, et al. Spatial variability of surface soil saturated hydraulic conductivity in a small karst catchment of Southwest China[J]. Environmental Earth Sciences, 2015, 74(3): 2381-2391. doi: 10.1007/s12665-015-4238-5
[18]	REIMANN T, HILL M E. MODFLOW-CFP: A new conduit flow process for MODFLOW-2005[J]. Groundwater, 2009, 47(3): 321-325. doi: 10.1111/j.1745-6584.2009.00561.x
[19]	常勇. 裂隙−管道二元结构的岩溶泉水文过程分析与模拟[D]. 南京: 南京大学, 2015. CHANG Y. Analysis and simulation of karst spring water process of fracture-pipeline binary structure[D]. Nanjing: Nanjing University, 2015. (in Chinese with English abstract
[20]	赵良杰, 夏日元, 杨杨, 等. 基于CFP的岩溶管道流数值模拟研究: 以桂林寨底地下河子系统为例[J]. 地球学报, 2018, 39(2): 225-232. ZHAO L J, XIA R Y, YANG Y, et al. Research on numerical simulation of karst conduit media based on CFP: A case study of Zhaidi karst underground river subsystem of Guilin[J]. Acta Geoscientica Sinica, 2018, 39(2): 225-232. (in Chinese with English abstract
[21]	罗利川. 岩溶水系统识别及水文过程模拟研究: 以香溪河岩溶流域为例[D]. 武汉: 中国地质大学(武汉), 2023. LUO L C. Characterizing the karst groundwater systems and simulating the springdischarge: A case study of the Xiangxi River karst basin, Central China[D]. Wuhan: China University of Geosciences (Wuhan), 2023. (in Chinese with English abstract
[22]	陈仲达, 齐国庆, 刘剑锋, 等. 基于属性识别理论的隧道突涌水危险性评价[J]. 水利与建筑工程学报, 2023, 21(2): 101-107. CHEN Z D, QI G Q, LIU J F, et al. Hazard analysis of tunnel water inrush based on attribute recognition theory[J]. Journal of Water Resources and Architectural Engineering, 2023, 21(2): 101-107. (in Chinese with English abstract
[23]	李玲玲, 陈植华. 鄂西丹水流域岩溶水流系统圈划与结构模式[J]. 安全与环境工程, 2022, 29(1): 135-144. LI L L, CHEN Z H. Boundary determination of karst groundwater flow system and its structural model in Danshui basin, western Hubei Province[J]. Safety and Environmental Engineering, 2022, 29(1): 135-144. (in Chinese with English abstract
[24]	陈兴聪. 滇中引水工程龙树隧洞出口段开挖对平诺村岩溶大泉影响评价[J]. 地质灾害与环境保护, 2024, 35(4): 73-77. Chen X C. Evaluation of the impact of Longshu tunnel excavation on Pingnuocun karst spring[J]. Journal of Geological Hazards and Environment Preservation, 2024, 35(4): 73-77. (in Chinese with English abstract
[25]	王泽君, 周宏, 齐凌轩, 等. 岩溶水系统结构和水文响应机制的定量识别方法: 以三峡鱼迷岩溶水系统为例[J]. 地球科学, 2020, 45(12): 4512-4523. WANG Z J, ZHOU H, QI L X, et al. Method for characterizing structure and hydrological response in karst water systems: A case study in Y-M system in Three Gorges area[J]. Earth Science, 2020, 45(12): 4512-4523. (in Chinese with English abstract
[26]	王楠, 胥芹, 孙小艳, 等. 趵突泉泉域岩溶水化学特征及成因研究[J]. 中国岩溶, 2024, 43(2): 279-290. WANG N, XU Q, SUN X Y, et al. Hydrochemical characteristics and formation mechanism of karst water in Baotu Spring watershed[J]. Carsologica Sinica, 2024, 43(2): 279-290. (in Chinese with English abstract
[27]	宋词, 杨锐锋, 谢詹, 等. 川东向阳岩溶隧道水化学特征及成因机制研究[J]. 铁道工程学报, 2024, 41(10): 44-51. SONG C, YANG R F, XIE Z, et al. Hydrochemical appraisal and formation mechanism of Xiangyang karst tunnels in eastern Sichuan Province[J]. Journal of Railway Engineering Society, 2024, 41(10): 44-51. (in Chinese with English abstract
[28]	杨楠, 苏春利, 曾邯斌, 等. 基于水化学和氢氧同位素的兴隆县地下水演化过程研究[J]. 水文地质工程地质, 2020, 47(6): 154-162. YANG N, SU C L, ZENG H B, et al. Evolutional processes of groundwater in Xinglong County based on hydrochemistry and hydrogen and oxygen isotopes[J]. Hydrogeology & Engineering Geology, 2020, 47(6): 154-162. (in Chinese with English abstract
[29]	袁建飞, 徐芬, 刘慧中, 等. 基于水化学和同位素的典型岩溶水系统溶质演化过程: 以西昌市仙人洞为例[J]. 科学技术与工程, 2019, 19(17): 76-83. YUAN J F, XU F, LIU H Z, et al. Application of hydrochemical and isotopic analysis to research a typical karst groundwater system: A case study at Xinrendong, Xichang City[J]. Science Technology and Engineering, 2019, 19(17): 76-83. (in Chinese with English abstract
[30]	朱静静, 周宏. 水文地质剖面分析在岩溶水系统研究中的应用: 以鄂西响水洞岩溶水系统为例[J]. 安全与环境工程, 2017, 24(3): 1-7. ZHU J J, ZHOU H. Application of hydrogeological profile analysis to karst water system: A case study on Xiangshuidong karst water system in western Hubei Province[J]. Safety and Environmental Engineering, 2017, 24(3): 1-7. (in Chinese with English abstract
[31]	陈含, 张冰冰, 邓刚, 等. 钻孔抽水试验水位降深计算公式推导及其应用[J]. 水利水电技术(中英文), 2025, 56(增刊1): 422-427. CHEN H, ZHANG B B, DENG G, et al. Derivation and application of calculation formula for water level drop in borehole pumping test[J]. Water Resources and Hydropower Engineering, 2025, 56(S1): 422-427. (in Chinese with English abstract
[32]	罗明明, 尹德超, 张亮, 等. 南方岩溶含水系统结构识别方法初探[J]. 中国岩溶, 2015, 34(6): 543-550. LUO M M, YIN D C, ZHANG L, et al. Identifying methods of karst aquifer system structure in South China[J]. Carsologica Sinica, 2015, 34(6): 543-550. (in Chinese with English abstract
[33]	杨闪. 基于放水试验和示踪试验的岩溶通道研究[J]. 现代矿业, 2023, 39(8): 47-50. YANG S. Study on karst channel based on water discharge test and tracer test[J]. Modern Mining, 2023, 39(8): 47-50. (in Chinese with English abstract
[34]	陈亚洲, 董维红. 利用示踪试验时间−浓度曲线分析岩溶管道结构特征[J]. 水文地质工程地质, 2022, 49(1): 41-47. CHEN Y Z, DONG W H. Analysis of structural characteristics of karst conduit by timeconcentration curve of tracer test[J]. Hydrogeology & Engineering Geology, 2022, 49(1): 41-47. (in Chinese with English abstract
[35]	康凤新, 郑婷婷, 冯亚伟, 等. 北方岩溶区降水入渗补给系数及补给机制: 以羊庄岩溶水系统为例[J]. 地质科技通报, 2024, 43(2): 268-282. KANG F X, ZHENG T T, FENG Y W, et al. Recharge coefficients and recharge mechanisms of precipitation to groundwater in karst areas of North China: A case study of Yangzhuang karst water system[J]. Bulletin of Geological Science and Technology, 2024, 43(2): 268-282. (in Chinese with English abstract
[36]	尹德超, 罗明明, 张亮, 等. 基于流量衰减分析的次降水入渗补给系数计算方法[J]. 水文地质工程地质, 2016, 43(3): 11-16. YIN D C, LUO M M, ZHANG L, et al. Methods of calculating recharge coefficient of precipitation event based on spring recession analyses[J]. Hydrogeology & Engineering Geology, 2016, 43(3): 11-16. (in Chinese with English abstract
[37]	杨平恒, 袁道先, 蓝家程, 等. 基于在线高分辨率监测和定量计算的岩溶地下水示踪试验[J]. 西南大学学报(自然科学版), 2013, 35(2): 103-108. YANG P H, YUAN D X, LAN J C, et al. Tracing test of a karst aquifer based on online, high-resolution monitoring and quantitative calculation[J]. Journal of Southwest University (Natural Science Edition), 2013, 35(2): 103-108. (in Chinese with English abstract
[38]	李兴男, 金江跃, 降亚楠. 地下水数值模型结构不确定性对模拟结果的影响分析[J]. 排灌机械工程学报, 2021, 39(2): 179-185. LI X N, JIN J Y, JIANG Y N. Analysis of groundwater numerical model structural uncertainty on simulation results[J]. Journal of Drainage and Irrigation Machinery Engineering, 2021, 39(2): 179-185. (in Chinese with English abstract
[39]	焦友军, 潘晓东, 曾洁, 等. 岩溶管道结构影响泉流量变化的数值模拟研究[J]. 中国岩溶, 2017, 36(5): 736-742. JIAO Y J, PAN X D, ZENG J, et al. Numerical modeling of the influence of karst-conduit structure on variation of spring flow[J]. Carsologica Sinica, 2017, 36(5): 736-742. (in Chinese with English abstract
[40]	武亚遵, 李彦涛, 林云, 等. 管道流模型参数敏感性分析及其在许家沟泉域的应用[J]. 水文地质工程地质, 2020, 47(2): 68-75. WU Y Z, LI Y T, LIN Y, et al. A sensitivity analysis of conduit flow model parameters and its application to the catch area of the Xujiagou spring[J]. Hydrogeology & Engineering Geology, 2020, 47(2): 68-75. (in Chinese with English abstract