{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:33:37Z","timestamp":1760060017898,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T00:00:00Z","timestamp":1754006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2021YFB2300603","2022KY53ZD(CHY)-10","2024-W04","2024-W02"],"award-info":[{"award-number":["2021YFB2300603","2022KY53ZD(CHY)-10","2024-W04","2024-W02"]}]},{"name":"Key R&amp;D Program of China Railway First Survey and Design Institute Group Co., Ltd.","award":["2021YFB2300603","2022KY53ZD(CHY)-10","2024-W04","2024-W02"],"award-info":[{"award-number":["2021YFB2300603","2022KY53ZD(CHY)-10","2024-W04","2024-W02"]}]},{"name":"Major Science and Technology R&amp;D Program of China Railway Construction Corporation Limited","award":["2021YFB2300603","2022KY53ZD(CHY)-10","2024-W04","2024-W02"],"award-info":[{"award-number":["2021YFB2300603","2022KY53ZD(CHY)-10","2024-W04","2024-W02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>This paper introduces a knowledge\u2013data dual-driven method for predicting groundwater conditions during tunnel construction. Unlike existing methods, our approach effectively integrates trend characteristics of apparent resistivity from detection results with geological distribution characteristics and expert insights. This dual-driven strategy significantly enhances the accuracy of the prediction model. The intelligent prediction process for tunnel groundwater conditions proceeds in the following steps: First, the apparent resistivity data matrix is obtained from transient electromagnetic detection results and standardized. Second, to improve data quality, trend characteristics are extracted from the apparent resistivity data, and outliers are eliminated. Third, expert insights are systematically integrated to fully utilize prior information on groundwater conditions at the construction face, leading to the establishment of robust predictive models tailored to data from various construction surfaces. Finally, the relevant prediction segment is extracted to complete the groundwater condition forecast.<\/jats:p>","DOI":"10.3390\/info16080659","type":"journal-article","created":{"date-parts":[[2025,8,5]],"date-time":"2025-08-05T10:50:21Z","timestamp":1754391021000},"page":"659","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Knowledge\u2013Data Dual-Driven Groundwater Condition Prediction Method for Tunnel Construction"],"prefix":"10.3390","volume":"16","author":[{"given":"Yong","family":"Huang","sequence":"first","affiliation":[{"name":"Facuity of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Fu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Intelligent Geotechnics and Tunnelling, Xi\u2019an 710043, China"},{"name":"China Railway First Survey and Design Institute Group Co., Ltd., Xi\u2019an 710043, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiewen","family":"Hu","sequence":"additional","affiliation":[{"name":"Facuity of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1016\/j.proeng.2017.12.061","article-title":"Investigation and analysis on the setting of cross passage and auxiliary passage in extra-long highway tunnel","volume":"211","author":"Zhang","year":"2018","journal-title":"Procedia Eng."},{"key":"ref_2","first-page":"1041","article-title":"Classification, geological identification, hazard mode and typical case studies of hazard-causing structures for water and mud inrush in tunnels","volume":"37","author":"Li","year":"2018","journal-title":"Chin. J. Rock Mech. Eng."},{"key":"ref_3","first-page":"523","article-title":"Study of mechanism of water inrush induced by hydraulic fracturing in karst tunnels","volume":"31","author":"Li","year":"2010","journal-title":"Rock Soil Mech."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"105994","DOI":"10.1016\/j.tust.2024.105994","article-title":"Study on the minimum safe thickness of water inrush prevention in karst tunnel under the coupling effect of blasting power and water pressure","volume":"153","author":"Li","year":"2024","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1007\/s10064-023-03468-x","article-title":"A new method for detecting karst and groundwater by 3D seismic wave: Case study of the karst tunnel in Zhangjihuai Railway, China","volume":"82","author":"Lou","year":"2023","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"104019","DOI":"10.1016\/j.tust.2021.104019","article-title":"Collapse risk assessment of deep-buried tunnel during construction and its application","volume":"115","author":"Ou","year":"2021","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"104460","DOI":"10.1016\/j.tust.2022.104460","article-title":"Statistical analysis of major tunnel construction accidents in China from 2010 to 2020","volume":"124","author":"Zhu","year":"2022","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.tust.2017.06.018","article-title":"Gaussian process model of water inflow prediction in tunnel construction and its engineering applications","volume":"69","author":"Li","year":"2017","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.autcon.2018.07.006","article-title":"Damage detection and quantitative analysis of shield tunnel structure","volume":"94","author":"Huang","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.enggeo.2016.02.009","article-title":"Application of time series analysis and PSO-SVM model in predicting the Bazimen landslide in the Three Gorges Reservoir, China","volume":"204","author":"Zhou","year":"2016","journal-title":"Eng. Geol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1061\/(ASCE)0887-3801(2002)16:1(59)","article-title":"Neural network forecast model in deep excavation","volume":"16","author":"Jan","year":"2002","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.tust.2019.02.012","article-title":"Intelligent information-based construction in tunnel engineering based on the GA and CCGPR coupled algorithm","volume":"88","author":"Liu","year":"2019","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"103948","DOI":"10.1016\/j.tust.2021.103948","article-title":"Multi-sources information fusion analysis of water inrush disaster in tunnels based on improved theory of evidence","volume":"113","author":"Li","year":"2021","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"510","DOI":"10.1016\/j.apor.2016.07.013","article-title":"Large scale three-dimensional seepage analysis model test and numerical simulation research on undersea tunnel","volume":"59","author":"Li","year":"2016","journal-title":"Appl. Ocean. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1680\/jgeen.15.00165","article-title":"Criteria for assessment of internal stability of granular soil","volume":"170","author":"Zhou","year":"2017","journal-title":"Proc. Inst. Civ.-Eng.-Geotech. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.tust.2016.11.004","article-title":"Model test to investigate waterproof-resistant slab minimum safety thickness for water inrush geohazards","volume":"62","author":"Jiang","year":"2017","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.enggeo.2016.12.006","article-title":"Variations of hydraulic properties of granular sandstones during water inrush: Effect of small particle migration","volume":"217","author":"Ma","year":"2017","journal-title":"Eng. Geol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.ijrmms.2016.08.007","article-title":"Rock mass characterization for shallow granite by integrating rock core indices and seismic velocity","volume":"93","author":"Lin","year":"2017","journal-title":"Int. J. Rock Mech. Min. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.jappgeo.2006.02.003","article-title":"Correlations between geotechnical and electrical data: A case study at Garchy in France","volume":"60","author":"Cosenza","year":"2006","journal-title":"J. Appl. Geophys."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/s10064-021-02503-z","article-title":"Site suitability for engineering-infrastructure (EI) development and groundwater exploitation using integrated geophysical approach in Guangdong, China","volume":"81","author":"Hasan","year":"2022","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"B231","DOI":"10.1190\/1.2360184","article-title":"Electrical resistivity tomography applied to geologic, hydrogeologic, and engineering investigations at a former waste-disposal site","volume":"71","author":"Chambers","year":"2006","journal-title":"Geophysics"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.enggeo.2008.01.010","article-title":"Resistivity and induced polarization surveys for slope instability studies in the Swiss Alps","volume":"98","author":"Marescot","year":"2008","journal-title":"Eng. Geol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"106560","DOI":"10.1016\/j.enggeo.2022.106560","article-title":"Geophysical evaluation of geological model uncertainty for infrastructure design and groundwater assessments","volume":"299","author":"Hasan","year":"2022","journal-title":"Eng. Geol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"19608","DOI":"10.1007\/s11356-021-16703-3","article-title":"Comprehensive study on identification of water inrush sources from deep mining roadway","volume":"29","author":"Chen","year":"2022","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1007\/s12517-019-4832-z","article-title":"Advanced geological prediction technology of tunnel based on image recognition","volume":"12","author":"Chen","year":"2019","journal-title":"Arab. J. Geosci."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/16\/8\/659\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:20:36Z","timestamp":1760034036000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/16\/8\/659"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,1]]},"references-count":25,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["info16080659"],"URL":"https:\/\/doi.org\/10.3390\/info16080659","relation":{},"ISSN":["2078-2489"],"issn-type":[{"type":"electronic","value":"2078-2489"}],"subject":[],"published":{"date-parts":[[2025,8,1]]}}}