Articles | Volume 28, issue 17
https://doi.org/10.5194/hess-28-4239-2024
© Author(s) 2024. 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-28-4239-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Sep 2024
Research article |
| 13 Sep 2024
| 13 Sep 2024
Karst aquifer discharge response to rainfall interpreted as anomalous transport
Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel
Nadine Goeppert
Division of Hydrogeology, Institute of Applied Geosciences, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Hydrogeology Group, Institute of Geological Sciences, Free University of Berlin, Berlin, Germany
Brian Berkowitz
Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel
Related authors
Dan Elhanati, Erwin Zehe, Ishai Dror, and Brian Berkowitz
EGUsphere, https://doi.org/10.5194/egusphere-2025-3365, https://doi.org/10.5194/egusphere-2025-3365, 2025
Short summary
Short summary
Measurements of water isotopes are often used to estimate water transit time distributions and aquifer storage thickness in catchments. However, laboratory-scale measurements show that water isotopes exhibit transport behavior identical to that of inert chemical tracers rather than of pure water. The measured mean tracer and apparent mean water velocities are not necessarily equal; recognition of this inequality is critical when estimating catchment properties such as aquifer storage thickness.
Dan Elhanati, Erwin Zehe, Ishai Dror, and Brian Berkowitz
EGUsphere, https://doi.org/10.5194/egusphere-2025-3365, https://doi.org/10.5194/egusphere-2025-3365, 2025
Short summary
Short summary
Measurements of water isotopes are often used to estimate water transit time distributions and aquifer storage thickness in catchments. However, laboratory-scale measurements show that water isotopes exhibit transport behavior identical to that of inert chemical tracers rather than of pure water. The measured mean tracer and apparent mean water velocities are not necessarily equal; recognition of this inequality is critical when estimating catchment properties such as aquifer storage thickness.
Brian Berkowitz
Hydrol. Earth Syst. Sci., 26, 2161–2180, https://doi.org/10.5194/hess-26-2161-2022, https://doi.org/10.5194/hess-26-2161-2022, 2022
Short summary
Short summary
Extensive efforts have focused on quantifying conservative chemical transport in geological formations. We assert that an explicit accounting of temporal information, under uncertainty, in addition to spatial information, is fundamental to an effective modeling formulation. We further assert that efforts to apply chemical transport equations at large length scales, based on measurements and model parameter values relevant to significantly smaller length scales, are an unattainable
holy grail.
Alexander Sternagel, Ralf Loritz, Brian Berkowitz, and Erwin Zehe
Hydrol. Earth Syst. Sci., 26, 1615–1629, https://doi.org/10.5194/hess-26-1615-2022, https://doi.org/10.5194/hess-26-1615-2022, 2022
Short summary
Short summary
We present a (physically based) Lagrangian approach to simulate diffusive mixing processes on the pore scale beyond perfectly mixed conditions. Results show the feasibility of the approach for reproducing measured mixing times and concentrations of isotopes over pore sizes and that typical shapes of breakthrough curves (normally associated with non-uniform transport in heterogeneous soils) may also occur as a result of imperfect subscale mixing in a macroscopically homogeneous soil matrix.
Erwin Zehe, Ralf Loritz, Yaniv Edery, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 25, 5337–5353, https://doi.org/10.5194/hess-25-5337-2021, https://doi.org/10.5194/hess-25-5337-2021, 2021
Short summary
Short summary
This study uses the concepts of entropy and work to quantify and explain the emergence of preferential flow and transport in heterogeneous saturated porous media. We found that the downstream concentration of solutes in preferential pathways implies a downstream declining entropy in the transverse distribution of solute transport pathways. Preferential flow patterns with lower entropies emerged within media of higher heterogeneity – a stronger self-organization despite a higher randomness.
Markus Merk, Nadine Goeppert, and Nico Goldscheider
Hydrol. Earth Syst. Sci., 25, 3519–3538, https://doi.org/10.5194/hess-25-3519-2021, https://doi.org/10.5194/hess-25-3519-2021, 2021
Short summary
Short summary
Soil moisture levels have decreased significantly over the past 2 decades. This decrease is not uniformly distributed over the observation period. The largest changes occur at tipping points during years of extreme drought, after which soil moisture levels reach significantly different alternate stable states. Not only the overall trend in soil moisture is affected, but also the seasonal dynamics.
Alexander Sternagel, Ralf Loritz, Julian Klaus, Brian Berkowitz, and Erwin Zehe
Hydrol. Earth Syst. Sci., 25, 1483–1508, https://doi.org/10.5194/hess-25-1483-2021, https://doi.org/10.5194/hess-25-1483-2021, 2021
Short summary
Short summary
The key innovation of the study is a method to simulate reactive solute transport in the vadose zone within a Lagrangian framework. We extend the LAST-Model with a method to account for non-linear sorption and first-order degradation processes during unsaturated transport of reactive substances in the matrix and macropores. Model evaluations using bromide and pesticide data from irrigation experiments under different flow conditions on various timescales show the feasibility of the method.
Cited articles
Afzaal, H., Farooque, A. A., Abbas, F., Acharya, B., and Esau, T.: Groundwater Estimation from Major Physical Hydrology Components Using Artificial Neural Networks and Deep Learning, Water, 12, 5, https://doi.org/10.3390/w12010005, 2020.
Anderson, S. and Radić, V.: Evaluation and interpretation of convolutional long short-term memory networks for regional hydrological modelling, Hydrol. Earth Syst. Sci., 26, 795–825, https://doi.org/10.5194/hess-26-795-2022, 2022.
Aquilina, L., Ladouche, B., and Dörfliger, N.: Water storage and transfer in the epikarst of karstic systems during high flow periods, J. Hydrol., 327, 472–485, https://doi.org/10.1016/j.jhydrol.2005.11.054, 2006.
Assari, A. and Mohammadi, Z.: Evaluation des voies d'écoulement dans un aquifère karstique à partir d'essais de traçage artificiels multiples en utilisant une simulation stochastique et le code MODFLOW-CFP, Hydrogeol. J., 25, 1679–1702, https://doi.org/10.1007/s10040-017-1595-z, 2017.
Bakalowicz, M.: Karst groundwater: A challenge for new resources, Hydrogeol. J., 13, 148–160, https://doi.org/10.1007/s10040-004-0402-9, 2005.
Berkowitz, B., Cortis, A., Dentz, M., and Scher, H.: Modeling non-Fickian transport in geological formations as a continuous time random walk, Rev. Geophys., 44, 1–49, https://doi.org/10.1029/2005RG000178, 2006.
Chen, Z. and Goldscheider, N.: Modeling spatially and temporally varied hydraulic behavior of a folded karst system with dominant conduit drainage at catchment scale, Hochifen-Gottesacker, Alps, J. Hydrol., 514, 41–52, https://doi.org/10.1016/j.jhydrol.2014.04.005, 2014.
Chen, Z., Hartmann, A., and Goldscheider, N.: A new approach to evaluate spatiotemporal dynamics of controlling parameters in distributed environmental models, Environ. Model. Softw., 87, 1–16, https://doi.org/10.1016/j.envsoft.2016.10.005, 2017.
Cinkus, G., Mazzilli, N., Jourde, H., Wunsch, A., Liesch, T., Ravbar, N., Chen, Z., and Goldscheider, N.: When best is the enemy of good – critical evaluation of performance criteria in hydrological models, Hydrol. Earth Syst. Sci., 27, 2397–2411, https://doi.org/10.5194/hess-27-2397-2023, 2023a.
Cinkus, G., Wunsch, A., Mazzilli, N., Liesch, T., Chen, Z., Ravbar, N., Doummar, J., Fernández-Ortega, J., Barberá, J. A., Andreo, B., Goldscheider, N., and Jourde, H.: Comparison of artificial neural networks and reservoir models for simulating karst spring discharge on five test sites in the Alpine and Mediterranean regions, Hydrol. Earth Syst. Sci., 27, 1961–1985, https://doi.org/10.5194/hess-27-1961-2023, 2023b.
Collon, P., Bernasconi, D., Vuilleumier, C., and Renard, P.: Statistical metrics for the characterization of karst network geometry and topology, Geomorphology, 283, 122–142, https://doi.org/10.1016/j.geomorph.2017.01.034, 2017.
Cortis, A. and Knudby, C.: A continuous time random walk approach to transient flow in heterogeneous porous media, Water Resour. Res., 42, 1–5, https://doi.org/10.1029/2006WR005227, 2006.
D'Errico, J.: fminsearchbnd, fminsearchcon, MATLAB Central File Exchange, https://www.mathworks.com/matlabcentral/fileexchange/8277-fminsearchbnd-fminsearchcon (last access: 7 March 2017), 2024.
Dentz, M., Kirchner, J. W., Zehe, E., and Berkowitz, B.: The role of anomalous transport in long-term, stream water chemistry variability, Geophys. Res. Lett., 50, 1–8, https://doi.org/10.1029/2023GL104207, 2023.
Edery, Y., Guadagnini, A., Scher, H., and Berkowitz, B.: Origins of anomalous transport in heterogeneous media: Structural and dynamic controls, Water Resour. Res., 50, 1490–1505, https://doi.org/10.1111/j.1752-1688.1969.tb04897.x, 2014.
Edery, Y., Geiger, S., and Berkowitz, B.: Structural controls yon anomalous transport in fractured porous rock, Water Resour. Res., 52, 5634–5643, https://doi.org/10.1111/j.1752-1688.1969.tb04897.x, 2016.
Elhanati, D. and Berkowitz, B.: CTRW simulations of karst aquifer discharge response to rainfall, Zenodo [data set], https://doi.org/10.5281/zenodo.10635640, 2024.
Elhanati, D., Dror, I., and Berkowitz, B.: Impact of time-dependent velocity fields on the continuum-scale transport of conservative chemicals, Water Resour. Res., 59, 1–19, https://doi.org/10.1029/2023WR035266, 2023.
Fleury, P., Ladouche, B., Conroux, Y., Jourde, H., and Dörfliger, N.: Modelling the hydrologic functions of a karst aquifer under active water management – The Lez spring, J. Hydrol., 365, 235–243, https://doi.org/10.1016/j.jhydrol.2008.11.037, 2009.
Ford, D. and Williams, P.: Karst Hydrogeology and Geomorphology, John Wiley & Sons, https://doi.org/10.1002/9781118684986, 1–562, 2007.
Frank, S., Goeppert, N., and Goldscheider, N.: Improved understanding of dynamic water and mass budgets of high-alpine karst systems obtained from studying a well-defined catchment area, Hydrol. Process., 35, 1–15, https://doi.org/10.1002/hyp.14033, 2021.
Goeppert, N., Goldscheider, N., and Berkowitz, B.: Experimental and modeling evidence of kilometer-scale anomalous tracer transport in an alpine karst aquifer, Water Res., 178, 115755, https://doi.org/10.1016/j.watres.2020.115755, 2020.
Hartmann, A., Goldscheider, N., Wagner, T., Lange, J., and Weiler, M.: Karst water resources in a changing world: Review of hydrological modeling approaches, Rev. Geophys., 52, 218–242, https://doi.org/10.1002/2013RG000443, 2014.
Jeannin, P. Y., Artigue, G., Butscher, C., Chang, Y., Charlier, J. B., Duran, L., Gill, L., Hartmann, A., Johannet, A., Jourde, H., Kavousi, A., Liesch, T., Liu, Y., Lüthi, M., Malard, A., Mazzilli, N., Pardo-Igúzquiza, E., Thiéry, D., Reimann, T., Schuler, P., Wöhling, T., and Wunsch, A.: Karst modelling challenge 1: Results of hydrological modelling, J. Hydrol., 600, 126508, https://doi.org/10.1016/j.jhydrol.2021.126508, 2021.
Jouves, J., Viseur, S., Arfib, B., Baudement, C., Camus, H., Collon, P., and Guglielmi, Y.: Speleogenesis, geometry, and topology of caves: A quantitative study of 3D karst conduits, Geomorphology, 298, 86–106, https://doi.org/10.1016/j.geomorph.2017.09.019, 2017.
Jukić, D. and Denić-Jukić, V.: Groundwater balance estimation in karst by using a conceptual rainfall–runoff model, J. Hydrol., 373, 302–315, https://doi.org/10.1016/j.jhydrol.2009.04.035, 2009.
Kaufmann, G., Gabrovšek, F., and Turk, J.: Modelling Flow of Subterranean Pivka River in Postojnska Jama, Slovenia, Acta Carsolog., 45, 57–70, https://doi.org/10.3986/ac.v45i1.3059, 2016.
Kratzert, F., Klotz, D., Brenner, C., Schulz, K., and Herrnegger, M.: Rainfall–runoff modelling using Long Short-Term Memory (LSTM) networks, Hydrol. Earth Syst. Sci., 22, 6005–6022, https://doi.org/10.5194/hess-22-6005-2018, 2018.
Mazzilli, N., Guinot, V., Jourde, H., Lecoq, N., Labat, D., Arfib, B., Baudement, C., Danquigny, C., Dal Soglio, L., and Bertin, D.: KarstMod: A modelling platform for rainfall – discharge analysis and modelling dedicated to karst systems, Environ. Model. Softw., 122, https://doi.org/10.1016/j.envsoft.2017.03.015, 2019.
Nissan, A., Dror, I., and Berkowitz, B.: Time-dependent velocity-field controls on anomalous chemical transport in porous media, Water Resour. Res., 53, 3760–3769, https://doi.org/10.1111/j.1752-1688.1969.tb04897.x, 2017.
Pronk, M., Goldscheider, N., and Zopfi, J.: Dynamics and interaction of organic carbon, turbidity and bacteria in a karst aquifer system, Hydrogeol. J., 14, 473–484, https://doi.org/10.1007/s10040-005-0454-5, 2006.
Renard, P. and Bertrand, C. (Eds):. EuroKarst 2016, Neuchâtel: Advances in the Hydrogeology of Karst and Carbonate Reservoirs, Springer, ISBN 978-3-319-45464-8, https://doi.org/10.1007/978-3-319-45465-8, 2017.
Rimmer, A. and Salingar, Y.: Modelling precipitation-streamflow processes in karst basin: The case of the Jordan River sources, Israel, J. Hydrol., 331, 524–542, https://doi.org/10.1016/j.jhydrol.2006.06.003, 2006.
Stevanović, Z.: Karst waters in potable water supply: a global scale overview, Environ. Earth Sci., 78, 1–12, https://doi.org/10.1007/s12665-019-8670-9, 2019.
Stoll, S., Hendricks Franssen, H. J., Butts, M., and Kinzelbach, W.: Analysis of the impact of climate change on groundwater related hydrological fluxes: a multi-model approach including different downscaling methods, Hydrol. Earth Syst. Sci., 15, 21–38, https://doi.org/10.5194/hess-15-21-2011, 2011.
Tritz, S., Guinot, V., and Jourde, H.: Modelling the behaviour of a karst system catchment using non-linear hysteretic conceptual model, J. Hydrol., 397, 250–262, https://doi.org/10.1016/j.jhydrol.2010.12.001, 2011.
Wunsch, A., Liesch, T., Cinkus, G., Ravbar, N., Chen, Z., Mazzilli, N., Jourde, H., and Goldscheider, N.: Karst spring discharge modeling based on deep learning using spatially distributed input data, Hydrol. Earth Syst. Sci., 26, 2405–2430, https://doi.org/10.5194/hess-26-2405-2022, 2022.
Zhang, X., Huang, Z., Lei, Q., Yao, J., Gong, L., Sun, S., and Li, Y.: Connectivity, permeability and flow channelization in fractured karst reservoirs: A numerical investigation based on a two-dimensional discrete fracture-cave network model, Adv. Water Resour., 161, 104142, https://doi.org/10.1016/j.advwatres.2022.104142, 2022.
Short summary
A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
A continuous time random walk framework was developed to allow modeling of a karst aquifer...
