Articles | Volume 30, issue 5
https://doi.org/10.5194/hess-30-1309-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-1309-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Novel insights into deep groundwater exploration by geophysical estimation of hard rock permeability
Muhammad Hasan
State Key Laboratory of Mountain Hazards and Engineering Resilience, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China
China-Pakistan Joint Research Center on Earth Sciences, CAS-HEC, Islamabad, Pakistan
University of Chinese Academy of Sciences, Beijing 100049, China
Lijun Su
CORRESPONDING AUTHOR
State Key Laboratory of Mountain Hazards and Engineering Resilience, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China
China-Pakistan Joint Research Center on Earth Sciences, CAS-HEC, Islamabad, Pakistan
University of Chinese Academy of Sciences, Beijing 100049, China
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Short summary
Short summary
This research presents a unique 64-year (1961–2024) debris-flow dataset for Jiangjia Ravine, Dongchuan, Yunnan, China. The dataset includes detailed measurements of debris-flow kinematic parameters (velocity, depth, and discharge), physical–mechanical properties (particle size, yield stress, and viscosity), seismic data, and hydrometeorological records (e.g., minute-by-minute rainfall and soil moisture). The dataset is publicly accessible via the National Cryosphere Desert Data Center (NCDC).
Cited articles
Abbas, M., Deparis, J., Isch, A., Mallet, C., Jodry, C., Azaroual, M., Abbar, B., and Baltassat, J. M.: Hydrogeophysical characterization and determination of petrophysical parameters by integrating geophysical and hydrogeological data at the limestone vadose zone of the Beauce aquifer, J. Hydrol., 615, 128725, https://doi.org/10.1016/j.jhydrol.2022.128725, 2022.
Allègre, V., Brodsky, E. E., Xue, L., Nale, S. M., Parker, B. L., and Cherry, J. A.: Using earth-tide induced water pressure changes to measure in situ permeability: A comparison with long-term pumping tests, Water Resour. Res., 52, 3113–3126, https://doi.org/10.1002/2015WR017346, 2016.
Amiotte Suchet, P., Probst, J. L., and Ludwig, W.: Worldwide distribution of continental rock lithology: Implications for the atmospheric/soil CO2 uptake by continental weathering and alkalinity river transport to the oceans, Glob. Biogeochem. Cycles, 17, 1038, https://doi.org/10.1029/2002GB001891, 2003.
Archie, G. E.: The electrical resistivity log as an aid in determining some reservoir characteristics, Transactions of the AIME, 146, 54–62, https://doi.org/10.2118/942054-G, 1942.
Asfahani, J.: Estimation of the hydraulic parameters by using an alternative vertical electrical sounding technique: case study from semiarid Khanasser valley region Northern Syria, Acta Geophys., 71, 997–1013, https://doi.org/10.1007/s11600-022-00926-0, 2023.
ASTM International: Standard Test Methods for Measurement of Hydraulic Conductivity of Saturated Porous Materials Using a Flexible Wall Permeameter, ASTM D5084-24, ASTM International, https://store.astm.org/d5084-24.html (last access: 28 September 2025), 2024.
Bauer-Gottwein, P., Gondwe, B. N., Christiansen, L., Herckenrath, D., Kgotlhang, L., and Zimmermann, S.: Hydrogeophysical exploration of three-dimensional salinity anomalies with the time domain electromagnetic method (TDEM), J. Hydrol., 380, 318–329, https://doi.org/10.1016/j.jhydrol.2009.11.007, 2010.
Bear, J.: Dynamics of Fluids in Porous Media, American Elsevier Publishing Company, New York, ISBN 978-0-444-00114-6, 1972.
Binley, A., Cassiani, G., and Deiana, R.: Hydrogeophysics: opportunities and challenges, B. Geofis. Teor. Appl., 51, 267–287, http://www.scopus.com/inward/record.url?eid=2-s2.0-78650438167&partnerID=40&md5=96e14979c82f4b23e8fed0ac0140e7db (last access: 28 September 2025), 2010.
Binley, A., Hubbard, S. S., Huisman, J. A., Revil, A., Robinson, D. A., Singha, K., and Slater, L. D.: The emergence of hydrogeophysics for improved understanding of subsurface processes over multiple scales, Water Resour. Res., 51, 3837–3866, https://doi.org/10.1002/2015WR017016, 2015.
Borah, U. K. and Patro, P. K.: Estimation of the depth of investigation in the magnetotelluric method from the phase, Geophysics, 84, E377–E385, https://doi.org/10.1190/geo2018-0124.1, 2019.
Brace, W. F., Walsh, J. B., and Frangos, W. T.: Permeability of granite under high pressure, J. Geophys. Res., 73, 2225–2236, https://doi.org/10.1029/JB073i006p02225, 1968.
Cagniard, L.: Basic theory of the magneto-telluric method of geophysical prospecting, Geophysics, 18, 605–635, https://doi.org/10.1190/1.1437915, 1953.
Carbillet, L., Griffiths, L., Heap, M. J., Duwiquet, H., Baud, P., Violay, M. E. S., Reuschlé, T., and Guillou-Frottier, L.: The Influence of Micro- and Macrocracks on the Permeability of Granite, Rock Mech. Rock Eng., 58, 1361–1378, https://doi.org/10.1007/s00603-024-04174-0, 2024.
Chapuis, R. P. and Aubertin, M.: Predicting the Coefficient of Permeability of Soils Using the Kozeny-Carman Equation, École Polytech. Montréal, http://publications.polymtl.ca/2605/ (last access: 28 September 2025), 2003.
Condon, L. E., Markovich, K. H., Kelleher, C. A., McDonnell, J. J., Ferguson, G., and McIntosh, J. C.: Where Is the Bottom of a Watershed?, Water Resour. Res., 56, e2019WR026010, https://doi.org/10.1029/2019WR026010, 2020.
Daily, W., Ramirez, A., LaBrecque, D., and Nitao, J.: Electrical resistivity tomography of vadose water movement, Water Resour. Res., 28, 1429–1442, https://doi.org/10.1029/91WR03087, 1992.
DallaValle, J. M.: Flow of Gases through Porous Media, edited by: Carman, P. C., Academic Press, New York, Butterworths, London, 182 pp. Illus, https://doi.org/10.1126/science.124.3234.1254.b, 1956.
Dewandel, B., Lachassagne, P., Wyns, R., Maréchal, J. C., and Krishnamurthy, N. S.: A generalized 3-D geological and hydrogeological conceptual model of granite aquifers controlled by single or multiphase weathering, J. Hydrol., 330, 260–284, https://doi.org/10.1016/j.jhydrol.2006.03.026, 2006.
Di, Q., Fu, C., An, Z., Wang, R., Wang, G., Wang, M., Qi, S., and Liang, P.: An application of CSAMT for detecting weak geological structures near the deeply buried long tunnel of the Shijiazhuang-Taiyuan passenger railway line in the Taihang Mountains, Eng. Geol., 268, 105517, https://doi.org/10.1016/j.enggeo.2020.105517, 2020.
Esmaeilpour, M., Ghanbarian, B., Sousa, R., Peter, R., and King, P. R.: Estimating Permeability and Its Scale Dependence at Pore Scale Using Renormalization Group Theory, Water Resour. Res., 59, e2022WR033462, https://doi.org/10.1029/2022WR033462, 2023.
Ferguson, G., McIntosh, J. C., Jasechko, S., Kim, J. H., Famiglietti, J. S., and McDonnell, J. J.: Groundwater deeper than 500 m contributes less than 0.1 % of global river discharge, Commun. Earth Environ., 4, 48, https://doi.org/10.1038/s43247-023-00697-6, 2023.
Fernando, A. and Pacheco, L.: Regional groundwater flow in hard rocks, Sci. Total Environ., 506–507, 182–195, https://doi.org/10.1016/j.scitotenv.2014.11.008, 2015.
Ferré, T., Bentley, L., Binley, A., Linde, N., Kemna, A., Singha, K., Holliger, K., Huisman, J. A., and Minsley, B.: Critical Steps for the Continuing Advancement of Hydrogeophysics, Eos, Transactions American Geophysical Union, 90, 200, https://doi.org/10.1029/2009EO230004, 2009.
Fiandaca, G., Maurya, P. K., Balbarini, N., Hördt, A., Christiansen, A. V., Foged, N., Bjerg, P. L., and Auken, E.: Permeability estimation directly from logging-while-drilling induced polarization data, Water Resour. Res., 54, 2851–2870, https://doi.org/10.1002/2017WR022411, 2018.
Fu, C., Di, Q., and An, Z.: Application of the CSAMT method to groundwater exploration in a metropolitan environment, Geophysics, 78, B201–B209, https://doi.org/10.1190/geo2012-0533.1, 2013.
Fusheng, G., Haiyan, Y., Zengqian, H., Zhichun, W., Ziyu, L., Guocan, W., Linfu, X., Ye, G., and Wanpeng, Z.: Structural setting of the Zoujiashan-Julong'an region, Xiangshan volcanic basin, China, interpreted from modern CSAMT data, Ore Geol. Rev., 150, 105180, https://doi.org/10.1016/j.oregeorev.2022.105180, 2022.
Gerke, H. H., Dusek, J., and Vogel, T.: Mass transfer effects in 2-D dual-permeability modeling of field preferential bromide leaching with drain effluent, Hydrol. Earth Syst. Sci. Discuss., 8, 5917–5967, https://doi.org/10.5194/hessd-8-5917-2011, 2011.
Gleeson, T., Moosdorf, N., Hartmann, J., and van Beek, L. P. H.: A glimpse beneath earth's surface: Global hydrogeology maps (GLHYMPS) of permeability and porosity, Geophys. Res. Lett., 41, 3891–3898, https://doi.org/10.1002/2014GL059856, 2014.
Glover, P. W. J.: What is the cementation exponent? A new interpretation, Leading Edge, 28, 82–85, https://doi.org/10.1190/1.3064150, 2009.
Glover, P. W. J.: Geophysical properties of the near surface Earth: electrical properties, Treatise on Geophysics, 11, 89–137, https://doi.org/10.1016/B978-0-444-53802-4.00189-5, 2015.
Gonzalez-Duque, D., Gomez-Velez, J. D., Person, M. A., Kelley, S., Key, K., and Lucero, D.: Groundwater Circulation Within the Mountain Block: Combining Flow and Transport Models With Magnetotelluric Observations to Untangle Its Nested Nature, Water Resour. Res., 60, e2023WR035906, https://doi.org/10.1029/2023WR035906, 2024.
Hasan, M. and Shang, Y.: Geophysical evaluation of geological model uncertainty for infrastructure design and groundwater assessments, Eng. Geol., 299, 106560, https://doi.org/10.1016/j.enggeo.2022.106560, 2022.
Hasan, M., Shang, Y., Jin, W., and Akhter, G.: Estimation of hydraulic parameters in a hard rock aquifer using integrated surface geoelectrical method and pumping test data in southeast Guangdong China, Geosci. J., 25, 223–242, https://doi.org/10.1007/s12303-020-0018-7, 2021.
Hasan, M., Su, L., Cui, P., and Shang, Y.: Development of deep-underground engineering structures via 2D and 3D RQD prediction using non-invasive CSAMT, Sci. Rep., 15, 1403, https://doi.org/10.1038/s41598-025-85626-7, 2025.
Herckenrath, D., Auken, E., Christiansen, L., Behroozmand, A. A., and Bauer-Gottwein, P.: Coupled hydrogeophysical inversion using time-lapse magnetic resonance sounding and time-lapse gravity data for hydraulic aquifer testing: Will it work in practice?, Water Resour. Res., 48, W01539, https://doi.org/10.1029/2011WR010411, 2012.
Herckenrath, D., Odlum, N., Nenna, V., Knight, R., Auken, E., and Bauer-Gottwein, P.: Calibrating a Salt Water Intrusion Model with Time-Domain Electromagnetic Data, Groundwater, 51, 385–397, https://doi.org/10.1111/j.1745-6584.2012.00974.x, 2013.
Hinnell, A. C., Ferré, T. P. A., Vrugt, J. A., Huisman, J. A., Moysey, S., Rings, J., and Kowalsky, M. B.: Improved extraction of hydrologic information from geophysical data through coupled hydrogeophysical inversion, Water Resour. Res., 46, W00D40, https://doi.org/10.1029/2008WR007060, 2010.
Hu, X. Y., Peng, R. H., Wu, G. J., Wang, W. P., Huo, G. P., and Han, B.: Mineral exploration using CSAMT data: application to Longmen region metallogenic belt, Guangdong Province, China, Geophysics, 78, B111–B119, https://doi.org/10.1190/geo2012-0115.1, 2013.
Ingebritsen, S. E. and Manning, C. E.: Permeability of the continental crust: dynamic variations inferred from seismicity and metamorphism, Geofluids, 10, 193–205, https://doi.org/10.1111/j.1468-8123.2010.00278.x, 2010.
ISRM: Suggested methods for rock characterization, testing and monitoring: 2007–2014, Springer, https://doi.org/10.1007/978-3-319-07713-0, 2015.
Jardani, A., Revil, A., Santos, F., Fauchard, C., and Dupont, J. P.: Detection of preferential infiltration pathways in sinkholes using joint inversion of self-potential and EM-34 conductivity data, Geophys. Prospect., 55, 749–760, https://doi.org/10.1111/j.1365-2478.2007.00638.x, 2007.
Jasechko, S., Seybold, H., Perrone, D., Fan, Y., Shamsudduha, M., Taylor, R. G., Fallatah, O., and Kirchner, J. W.: Rapid groundwater decline and some cases of recovery in aquifers globally, Nature, 625, 715–721, https://doi.org/10.1038/s41586-023-06879-8, 2024.
Jiang, X. W., Wan, L., Wang, J. Z., Yin, B. X., Fu, W. X., and Lin, C. H.: Field identification of groundwater flow systems and hydraulic traps in drainage basins using a geophysical method, Geophys. Res. Lett., 41, 2812–2819, https://doi.org/10.1002/2014GL059579, 2014.
Kouadio, K. L., Liu, R., Malory, A. O., and Liu, C.: A novel approach for water reservoir mapping using controlled source audio-frequency magnetotelluric in Xingning area, Hunan Province, China, Geophys. Prospect., 71, 1708–1727, https://doi.org/10.1111/1365-2478.13385, 2023.
Laghari, A. N., Vanham, D., and Rauch, W.: The Indus basin in the framework of current and future water resources management, Hydrol. Earth Syst. Sci., 16, 1063–1083, https://doi.org/10.5194/hess-16-1063-2012, 2012.
Majumdar, R. K. and Das, D.: Hydrological characterization and estimation of aquifer properties from electrical sounding data in Sagar Island region, South 24 Parganas, West Bengal, India, Asian J. Earth Sci., 4, 60–74, https://doi.org/10.3923/ajes.2011.60.74, 2011.
Manning, C. E. and Ingebritsen, S. E.: Permeability of the continental crust: Implications of geothermal data and metamorphic systems, Rev. Geophys., 37, 127–150, https://doi.org/10.1029/1998RG900002, 1999.
Mira Geoscience Ltd.: GOCAD Mining Suite 3D Geological Modeling Software, Nancy University, Lorraine, France, 1999.
Mudunuru, M. K., Cromwell, E. L. D., Wang, H., and Chen, X.: Deep learning to estimate permeability using geophysical data, Adv. Water Resour., 167, 104272, https://doi.org/10.1016/j.advwatres.2022.104272, 2022.
Niwas, S. and De Lima, O. A. L.: Aquifer parameter estimation from surface resistivity data, Groundwater, 41, 94–99, https://doi.org/10.1111/j.1745-6584.2003.tb02572.x, 2003.
Nwosu, L. I., Nwankwo, C. N., and Ekine, A. S.: Geoelectric investigation of the hydraulic properties of the aquiferous zones for evaluation of groundwater potentials in the complex geological area of imostate, Nigeria, Asian J. Earth Sci., 6, 1–15, https://scialert.net/abstract/?doi=ajes.2013.1.15 (last access: 28 September 2025), 2013.
Pellet, H., Arfib, B., Henry, P., Touron, S., and Gassier, G.: Mesoscale permeability variations estimated from natural airflows in the decorated Cosquer Cave (southeastern France), Hydrol. Earth Syst. Sci., 28, 4035–4057, https://doi.org/10.5194/hess-28-4035-2024, 2024.
Phoenix Geophysics CMTPro: The Canadian Phoenix CMT Pro Version software for CSAMT data processing, Toronto, Ontario, Canada, https://www.phoenixgeophysics.com/downloads-support (last access: 28 September 2025), 2020.
Phoenix Geophysics CSAMT-SW: The Canadian Phoenix CSAMT-SW Version software for CSAMT data inversion, Toronto, Ontario, Canada, https://www.phoenixgeophysics.com/downloads-support (last access: 28 September 2025), 2020.
Pollock, D. and Cirpka, O. A.: Fully coupled hydrogeophysical inversion of a laboratory salt tracer experiment monitored by electrical resistivity tomography, Water Resour. Res., 48, W01505, https://doi.org/10.1029/2011WR010779, 2012.
Qin, X.: Application of Unwedge program to geological stability analysis of deep buried deposits, Comprehensive, 8, 270–273, 2017 (in Chinese).
Revil, A. and Cathles III, L. M.: Permeability of shaly sands, Water Resour. Res., 35, 651–662, https://doi.org/10.1029/98WR02700, 1999.
Rodi, W. and Mackie, R. L.: Nonlinear conjugate gradients algorithm for 2-D magnetotelluric inversion, Geophysics, 66, 174–187, https://doi.org/10.1190/1.1444893, 2001.
Saar, M. O. and Manga, M.: Depth dependence of permeability in the Oregon Cascades inferred from hydrogeologic, thermal, seismic, and magmatic modeling constraints, J. Geophys. Res., 109, B04204, https://doi.org/10.1029/2003JB002855, 2004.
Simpson, F. and Bahr, K.: Practical magnetotellurics, Cambridge University Press, Cambridge, 254 pp., https://doi.org/10.1017/CBO9780511614095, 2005.
Singh, K. P.: Nonlinear estimation of aquifer parameters from surficial resistivity measurements, Hydrol. Earth Syst. Sci. Discuss., 2, 917–938, https://doi.org/10.5194/hessd-2-917-2005, 2005.
Smith, J. T. and Booker, J. R.: Rapid inversion of two-and three-dimensional magnetotelluric data, J. Geophys. Res.-Sol. Ea., 96, 3905–3922, https://doi.org/10.1029/90JB02416, 1991.
Soupios, P. M., Kouli, M., Vallianatos, F., Vafidis, A., and Stavroulakis, G.: Estimation of aquifer hydraulic parameters from surficial geophysical methods: a case study of Keritis Basin in Chania (Crete–Greece), J Hydrol, 1, 122–131, https://doi.org/10.1016/j.jhydrol.2007.02.028, 2007.
Wada, Y., Van Beek, L. P., Van Kempen, C. M., Reckman, J. W., Vasak, S., and Bierkens, M. F.: Global depletion of groundwater resources, Geophys. Res. Lett., 37, L20402, https://doi.org/10.1029/2010GL044571, 2010.
Wang, R., Yin, C., Wang, M., and Di, Q.: Laterally constrained inversion for CSAMT data interpretation, J. Appl. Geophys., 121, 63–70, https://doi.org/10.1016/j.jappgeo.2015.07.009, 2015.
Waxman, M. H. and Smits, L. J. M.: Electrical conductivities in oil-bearing shaly sands, Soc. Petrol. Eng. J., 8, 107–122, https://doi.org/10.2118/1863-A, 1968.
Webring, M. W.: MINC: A Gridding Program Based on Minimum Curvature: U.S. Geological Survey Open File Report, 81–1224, p. 41, https://doi.org/10.3133/ofr811224, 1981.
Worthington, S. R. H., Davies, G. J., and Alexander Jr., E. C.: Enhancement of bedrock permeability by weathering, Earth-Sci. Rev., 160, 188–202, https://doi.org/10.1016/j.earscirev.2016.07.002, 2016.
Yan, Y., Ma, L., Qian, J., Zhao, G., Fang, Y., Ma, H., and Wang, J.: Estimating permeability of rock fracture based on geometrical aperture using geoelectrical monitoring, J. Hydrol., 644, 132067, https://doi.org/10.1016/j.jhydrol.2024.132067, 2024.
Yang, J., Zhang, H., and Cui, Z.: Stability Analysis and Countermeasures of Rock Block in Underground Cavern, Guangdong Water Resources and Hydropower, 5, 23–27, 2021 (in Chinese).
Zhang, M., Farquharson, C. G., and Liu, C.: Improved controlled source audio-frequency magnetotelluric method apparent resistivity pseudo-sections based on the frequency and frequency–spatial gradients of electromagnetic fields, Geophys. Prospect., 69, 474–490, https://doi.org/10.1111/1365-2478.13059, 2021.
Zhu, L., Gong, H., Dai, Z., Guo, G., and Teatini, P.: Modeling 3-D permeability distribution in alluvial fans using facies architecture and geophysical acquisitions, Hydrol. Earth Syst. Sci., 21, 721–733, https://doi.org/10.5194/hess-21-721-2017, 2017.
Zonge, K. L. and Hughes, L. J.: Chapter 9: Controlled Source Audio-Frequency Magnetotellurics, Investigations in Geophysics, 713–810, https://doi.org/10.1190/1.9781560802686.ch9, 1991.
Short summary
Permeability is a crucial hydraulic parameter extensively utilized in groundwater research. Until now, permeability has only been determined using borehole experiments. However, conventional approaches possess numerous limitations and still cannot estimate permeability at large depths. This research uses geophysical methods for the first time to assess 2D and 3D permeability across extensive areas at significant depths in extremely heterogeneous hard rock.
Permeability is a crucial hydraulic parameter extensively utilized in groundwater research....