Articles | Volume 28, issue 7
https://doi.org/10.5194/hess-28-1585-2024
© 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-28-1585-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Apr 2024
Research article |
| 09 Apr 2024
| 09 Apr 2024
Identification of parameter importance for benzene transport in the unsaturated zone using global sensitivity analysis
The Dead Sea and Arava Science Center (DSASC), Mitzpe Ramon, Israel
Nimrod Schwartz
The Robert H. Smith Faculty of Agriculture, Food and Environment, The Institute of Environmental Sciences, The Hebrew University of Jerusalem, Rehovot 76100, Israel
Ravid Rosenzweig
Geological Survey of Israel, Jerusalem, Israel
Related authors
No articles found.
Sonya S. Altzitser, Yael G. Mishael, and Nimrod Schwartz
SOIL, 11, 95–104, https://doi.org/10.5194/soil-11-95-2025, https://doi.org/10.5194/soil-11-95-2025, 2025
Short summary
Short summary
Our study uses a noninvasive geoelectrical method to monitor hydroquinone oxidation in MnO2-rich soil. We combined it with chemical analyses to observe real-time changes in soil pH, calcium, and manganese levels. Our findings reveal that MnO2 oxidation of hydroquinone triggers reactions such as calcite dissolution and amorphous manganese oxide formation. This research advances the understanding of soil–pollutant interactions and highlights the method's potential in tracking soil remediation.
Edwin Saavedra Cifuentes, Alex Furman, Ravid Rosenzweig, and Aaron I. Packman
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-251, https://doi.org/10.5194/hess-2024-251, 2024
Revised manuscript under review for HESS
Short summary
Short summary
Our research addresses the operational challenge of SAT systems that clog with biomass. A model to optimize their operation is proposed and considers the dynamic interactions between microbial activity, water flow, and soil clogging. Simulations showed the duration of wet and dry periods that enhance water infiltration. A link between the biomass spatial distribution and the wet and dry cycles was discovered. These findings can provide practical insights for real-world SAT systems.
Cited articles
Abu Hamed, T., Bayraktar, E., Mehmetoglu, Ü., and Mehmetoglu, T.: The biodegradation of benzene, toluene and phenol in a two-phase system, Biochem. Eng. J., 19, 137–146, https://doi.org/10.1016/j.bej.2003.12.008, 2004.
Akbariyeh, S., Bartelt-Hunt, S., Snow, D., Li, X., Tang, Z., and Li, Y.: Three-dimensional modeling of nitrate-N transport in vadose zone: Roles of soil heterogeneity and groundwater flux, J. Contam. Hydrol., 211, 15–25, https://doi.org/10.1016/j.jconhyd.2018.02.005, 2018.
Alvarez, P. J. J., Anid, P. J., and Vogel, T. M.: Kinetics of aerobic biodegradation of benzene and toluene in sandy aquifer material, Biodegradation, 2, 43–51, https://doi.org/10.1007/BF00122424, 1991.
Archer, G. E. B., Saltelli, A., and Sobol, I. M.: Sensitivity measures ANOVA-like techniques and the use of bootstrap, J. Stat. Comput. Sim., 58, 99–120, https://doi.org/10.1080/00949659708811825, 1997.
Baek, D. S., Kim, S. B., and Kim, D. J.: Irreversible sorption of benzene in sandy aquifer materials, Hydrol. Process., 17, 1239–1251, https://doi.org/10.1002/hyp.1181, 2003.
Bear, J.: Dynamics of Fluids in Porous Media, Dover Publications, New York, ISBN 0486656756, https://lib.ugent.be/catalog/rug01:000487153 (last access: 8 April 2024), 1972.
Bear, J. and Cheng, A.: Modeling Groundwater Flow and Contaminant Transport, Springer Science & Business Media, Berlin, https://doi.org/10.1007/978-1-4020-6682-5, 2010.
Berlin, M. and Suresh, K. G.: Numerical Experiments on Fate and Transport of Benzene with Biological Clogging in Vadoze Zone, Environ. Process., 6, 841–858, https://doi.org/10.1007/s40710-019-00402-w, 2019.
Berlin, M., Vasudevan, M., Kumar, G. S., and Nambi, I. M.: Numerical modelling on fate and transport of coupled adsorption and biodegradation of pesticides in an unsaturated porous medium, ISH J. Hydraul. Eng., 22, 236–246, https://doi.org/10.1080/09715010.2016.1166073, 2016.
Borgonovo, E.: A new uncertainty importance measure, Reliab. Eng. Syst. Safe., 92, 771–784, 2007.
Botros, F. E., Onsoy, Y. S., Ginn, T. R., and Harter, T.: Richards Equation–Based Modeling to Estimate Flow and Nitrate Transport in a Deep Alluvial Vadose Zone, Vadose Zone J., 11, vzj2011.0145, https://doi.org/10.2136/vzj2011.0145, 2012.
Brauner, J. S. and Widdowson, M. A.: Numerical Simulation of a Natural Attenuation Experiment with a Petroleum Hydrocarbon NAPL Source, Groundwater, 39, 939–952, https://doi.org/10.1111/j.1745-6584.2001.tb02482.x, 2001.
Brunetti, G., Šimùnek, J., and Piro, P.: A comprehensive numerical analysis of the hydraulic behavior of a permeable pavement, J. Hydrol., 540, 1146–1161, https://doi.org/10.1016/j.jhydrol.2016.07.030, 2016.
Brunetti, G., Šimùnek, J., Turco, M., and Piro, P.: On the use of surrogate-based modeling for the numerical analysis of Low Impact Development techniques, J. Hydrol., 548, 263–277, https://doi.org/10.1016/j.jhydrol.2017.03.013, 2017.
Brunetti, G., Šimùnek, J., Turco, M., and Piro, P.: On the use of global sensitivity analysis for the numerical analysis of permeable pavements, Urban Water J., 15, 269–275, https://doi.org/10.1080/1573062X.2018.1439975, 2018.
Brunetti, G., Stumpp, C., and Šimùnek, J.: Balancing exploitation and exploration: A novel hybrid global-local optimization strategy for hydrological model calibration, Environ. Model. Softw., 150, 105341, https://doi.org/10.1016/j.envsoft.2022.105341, 2022.
Campolongo, F., Cariboni, J., and Saltelli, A.: An effective screening design for sensitivity analysis of large models, Environ. Model. Softw., 22, 1509–1518, https://doi.org/10.1016/j.envsoft.2006.10.004, 2007.
Carsel, R. F. and Parrish, R. S.: Developing joint probability distributions of soil water retention characteristics, Water Resour. Res., 24, 755–769, https://doi.org/10.1029/WR024i005p00755, 1988..
Chen, N., Valdes, D., Marlin, C., Blanchoud, H., Guerin, R., Rouelle, M., and Ribstein, P.: Water, nitrate and atrazine transfer through the unsaturated zone of the Chalk aquifer in northern France, Sci. Total Environ., 652, 927–938, https://doi.org/10.1016/j.scitotenv.2018.10.286, 2019.
Choi, J.-W., Ha, H.-C., Kim, S.-B., and Kim, D.-J.: Analysis of benzene transport in a two-dimensional aquifer model, Hydrol. Process., 19, 2481–2489, 2005.
Choi, N. C., Choi, J. W., Kim, S. B., Park, S. J., and Kim, D. J.: Two-dimensional modelling of benzene transport and biodegradation in a laboratory-scale aquifer, Environ. Technol., 30, 53–62, 2009.
Ciriello, V., Lauriola, I., Bonvicini, S., Cozzani, V., Di Federico, V., and Tartakovsky, D. M.: Impact of Hydrogeological Uncertainty on Estimation of Environmental Risks Posed by Hydrocarbon Transportation Networks, Water Resour. Res., 53, 8686–8697, https://doi.org/10.1002/2017WR021368, 2017.
Cohen, M.: Output and results of all GSA, figshare [data set], https://doi.org/10.6084/m9.figshare.22012718.v1, 2023.
Dai, H., Chen, X., Ye, M., Song, X., and Zachara, J. M.: A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling, Water Resour. Res., 53, 4327–4343, https://doi.org/10.1111/j.1752-1688.1969.tb04897.x, 2017.
Davis, J. W., Klier, N. J., and Carpenter, C. L.: Natural biological attenuation of Benzene in ground water beneath a manufacturing facility, Groundwater, 32, 215–226, https://doi.org/10.1111/j.1745-6584.1994.tb00636.x, 1994.
Dell'Oca, A., Riva, M., and Guadagnini, A.: Moment-based metrics for global sensitivity analysis of hydrological systems, Hydrol. Earth Syst. Sci., 21, 6219–6234, https://doi.org/10.5194/hess-21-6219-2017, 2017.
Domenico, P. A. and Schwartz, F. W.: Physical and Chemical Hydrogeology, 2nd edn., John Wiley & Sons, New York, https://doi.org/10.1017/S0016756800019890, 1990.
Du, P., Sagehashi, M., Terada, A., and Hosomi, M.: Numerical modeling of benzene transport in andosol and sand: Adequacy of diffusion and equilibrium adsorption equations, World Acad. Sci. Eng. Technol., 66, 38–42, https://doi.org/10.5281/zenodo.1330975, 2010.
Duneja, A. and Puyalnithi, T.: Enhancing Classification Accuracy of K-Nearest Neighbours Algorithm Using Gain Ratio, Int. Res. J. Eng. Technol., 4, 1385–1388, 2017.
Ecker, A.: Selected geological cross-sections and subsurface maps in the coastal aquifer of Israel, Atlas, Geological Survey of Israel, Jerusalem, 1999.
Efron, B. and Tibshirani, R.: Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy, Stat. Sci., 1, 54–75, 1986.
Fan, X., He, L., Lu, H. W., and Li, J.: Environmental and health-risk-induced remediation design for benzene-contaminated groundwater under parameter uncertainty: A case study in Western Canada, Chemosphere, 111, 604–612, 2014.
Farhadian, M., Vachelard, C., Duchez, D., and Larroche, C.: In situ bioremediation of monoaromatic pollutants in groundwater: A review, Bioresource Technol., 99, 5296–5308, https://doi.org/10.1016/j.biortech.2007.10.025, 2008.
Gal, Y., Azenkot, A., Peres, M., and Levingart, M.: Converting irrigation coefficnets based on Class A pan to calculated evaporation (Penman Montieth FAO 56), Alon Hanotea, 66, 28–32, 2012.
Gatel, L., Lauvernet, C., Carluer, N., Weill, S., Tournebize, J., and Paniconi, C.: Global evaluation and sensitivity analysis of a physically based flow and reactive transport model on a laboratory experiment, Environ. Model. Softw., 113, 73–83, https://doi.org/10.1016/j.envsoft.2018.12.006, 2019.
Gatel, L., Lauvernet, C., Carluer, N., Weill, S., and Paniconi, C.: Sobol global sensitivity analysis of a coupled surface/subsurface water flow and reactive solute transfer model on a real hillslope, Water (Switzerland), 12, 1–21, https://doi.org/10.3390/w12010121, 2020.
Gribb, M. M., Bene, K. J., and Shrader, A.: Sensitivity analysis of a soil leachability model for petroleum fate and transport in the vadose zone, Adv. Environ. Res., 7, 59–72, https://doi.org/10.1016/S1093-0191(01)00107-1, 2002.
Hartmann, A., Šimùnek, J., Aidoo, M. K., Seidel, S. J., and Lazarovitch, N.: Implementation and Application of a Root Growth Module in HYDRUS, Vadose Zone J., 17, 170040, https://doi.org/10.2136/vzj2017.02.0040, 2018.
Hastie, T., Tibshirani, R., and Friedman, J.: The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition, Springer Science & Business Media, New York, ISBN 9780387848846, 2009.
Herman, J. and Usher, W.: SALib: An open-source Python library for Sensitivity Analysis, J. Open Source Softw., 2, 18155, https://doi.org/10.21105/joss.00097, 2017.
Herman, J. D., Kollat, J. B., Reed, P. M., and Wagener, T.: Technical Note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models, Hydrol. Earth Syst. Sci., 17, 2893–2903, https://doi.org/10.5194/hess-17-2893-2013, 2013.
Jaxa-Rozen, M., Pratiwi, A. S., and Trutnevyte, E.: Variance-based global sensitivity analysis and beyond in life cycle assessment: an application to geothermal heating networks, Int. J. Life Cycle Ass., 26, 1008–1026, https://doi.org/10.1007/s11367-021-01921-1, 2021.
Kessler, N.: Summary of actions to prevent water contamination from fuels in the years of 2020–2021, Israel water authority report, https://www.gov.il/BlobFolder/reports/fuel/he/water-sources-status_fuel_fuel-20-21.pdf (last access: 8 April 2024), 2022.
Khorashadi Zadeh, F., Nossent, J., Sarrazin, F., Pianosi, F., van Griensven, A., Wagener, T., and Bauwens, W.: Comparison of variance-based and moment-independent global sensitivity analysis approaches by application to the SWAT model, Environ. Model. Softw., 91, 210–222, https://doi.org/10.1016/j.envsoft.2017.02.001, 2017.
Lahvis, M. A., Baehr, A. L., and Baker, R. J.: Quantification of aerobic biodegradation and volatilization rates of gasoline hydrocarbons near the water table under natural attenuation conditions, Water Resour. Res., 35, 753–765, https://doi.org/10.1029/1998WR900087, 1999.
Levy, Y.: Observations and Modeling of Nitrate Fluxes to Groundwater under Diverse Agricultural Land-Uses: From the Fields to the Pumping Wells, Master thesis, The Hebrew University of Jerusalem, https://www.agri.gov.il/download/files/LevyYehuda2015MSc_2.pdf (last access: 8 April 2024), 2015.
Liu, H., Chen, W., and Sudjianto, A.: Relative entropy based method for probabilistic sensitivity analysis in engineering design, J. Mech. Design, 182, 326–336, 2006.
Logeshwaran, P., Megharaj, M., Chadalavada, S., Bowman, M., and Naidu, R.: Petroleum hydrocarbons (PH) in groundwater aquifers: An overview of environmental fate, toxicity, microbial degradation and risk-based remediation approaches, Environ. Technol. Innov., 10, 175–193, https://doi.org/10.1016/j.eti.2018.02.001, 2018.
López, E., Schuhmacher, M., and Domingo, J. L.: Human health risks of petroleum-contaminated groundwater, Environ. Sci. Pollut. R., 15, 278–288, https://doi.org/10.1065/espr2007.02.390, 2008.
Lu, G., Clement, T. P., Zheng, C., and Wiedemeier, T. H.: Natural Attenuation of BTEX Compounds Model Development and Field-Scale Application, Ground Water, 37, 707–701, https://doi.org/10.1111/j.1745-6584.1999.tb01163.x, 1999.
Millington, R. J. and Quirk, J. P.: Permeability of porous solids, T. Faraday Soc., 57, 1200–1207, https://doi.org/10.1039/TF9615701200, 1961.
Mohamed, M. M. A. and Sherif, N. E. S. M. M.: Modeling in situ benzene bioremediation in the contaminated Liwa aquifer (UAE) using the slow-release oxygen source technique, Environ. Earth Sci., 61, 1385–1389, 2010.
Moret-Fernández, D., Peña-Sancho, C., Latorre Garcés, B., Pueyo, Y., Sánche, L., and Victoria, M.: Estimating the van Genuchten retention curve parameters of undisturbed soil from a single upward infiltration measurement, Soil Res., 55, 682–691, 2017.
Morris, M. D.: Factorial Sampling Plans for Preliminary Computational Experiments Max, Technometrics, 33, 161–174, 1991.
Mualem, Y.: A New Model for Predicting Hydraulic Conductivity of Unsaturated Porous-Media., Water Resour. Res., 12, 513–522, https://doi.org/10.1029/WR012i003p00513, 1976.
Nadim, F., Hoag, G. E., Liu, S., Carley, R. J., and Zack, P.: Detection and remediation of soil and aquifer systems contaminated with petroleum products: An overview, J. Petrol. Sci. Eng., 26, 169–178, https://doi.org/10.1016/S0920-4105(00)00031-0, 2000.
Nemes, A., Wösten, J., and Lilly, A.: Development of soil hydraulic pedotransfer functions on a European scale: their usefulness in the assessment of soil quality, Sustaining the Global Farm, Selected papers from the 10th International Soil Conservation Organization Meeting, 24–29 May 1999, West Lafayette, Indiana, USA, Purdue University and the USDA-ARS National Soil Erosion Research Laboratory, edited by: Stott, D. E., Mohtar, R. H., and Steinhardt, G. C., 541–549, https://topsoil.nserl.purdue.edu/nserlweb-old/isco99/pdf/ISCOdisc/SustainingTheGlobalFarm/P282-Nemes.pdf (last access: 8 April 2024), 2001.
Neumann, M. B.: Comparison of sensitivity analysis methods for pollutant degradation modelling: A case study from drinking water treatment, Sci. Total Environ., 433, 530–537, https://doi.org/10.1016/j.scitotenv.2012.06.026, 2012.
Nossent, J., Elsen, P., and Bauwens, W.: Sobol' sensitivity analysis of a complex environmental model, Environ. Model. Softw., 26, 1515–1525, https://doi.org/10.1016/j.envsoft.2011.08.010, 2011.
Pan, F., Zhu, J., Ye, M., Pachepsky, Y. A., and Wu, Y. S.: Sensitivity analysis of unsaturated flow and contaminant transport with correlated parameters, J. Hydrol., 397, 238–249, https://doi.org/10.1016/j.jhydrol.2010.11.045, 2011.
Périard, Y., Gumiere, S. J., Rousseau, A. N., and Caron, J.: Sensitivity analyses of a colloid-facilitated contaminant transport model for unsaturated heterogeneous soil conditions, EGU General Assembly 2013, 7–12 April 2013, Vienna, Austria, Geophysical Research Abstracts, EGU2013-510, 2013.
Plischke, E., Borgonovo, E., and Smith, C. L.: Global sensitivity measures from given data, Eur. J. Oper. Res., 226, 536–550, https://doi.org/10.1016/j.ejor.2012.11.047, 2013.
Rawls, W. J. J., Brakenseik, D. L., Saxton, K. E. E., Brakensiek, C. L., and Saxton, K. E. E.: Estimation of soil water properties, T. ASAE, 25, 1316–1320, https://doi.org/10.13031/2013.33720, 1982.
Razavi, S., Tolson, B. A., and Burn, D. H.: Review of surrogate modeling in water resources, Water Resour. Res., 48, W07401, https://doi.org/10.1029/2011WR011527, 2012.
Razavi, S., Jakeman, A., Saltelli, A., Prieur, C., Iooss, B., Borgonovo, E., Plischke, E., Lo Piano, S., Iwanaga, T., Becker, W., Tarantola, S., Guillaume, J. H. A., Jakeman, J., Gupta, H., Melillo, N., Rabitti, G., Chabridon, V., Duan, Q., Sun, X., Smith, S., Sheikholeslami, R., Hosseini, N., Asadzadeh, M., Puy, A., Kucherenko, S., and Maier, H. R.: The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support, Environ. Model. Softw., 137, 104954, https://doi.org/10.1016/j.envsoft.2020.104954, 2021.
Reshef, G. and Gal, H.: Summary of actions to prevent pollution of water sources from fuels 2016, Israel water authority report, https://www.provectusenvironmental.com/p-ebr/sikum_dlakim_2017.pdf (last access: 8 April 2024), 2017.
Rimon, Y., Dahan, O., Nativ, R., and Geyer, S.: Water percolation through the deep vadose zone and groundwater recharge: Preliminary results based on a new vadose zone monitoring system, Water Resour. Res., 43, 1–12, https://doi.org/10.1029/2006WR004855, 2007.
Rivett, M. O., Wealthall, G. P., Dearden, R. A., and McAlary, T. A.: Review of unsaturated-zone transport and attenuation of volatile organic compound (VOC) plumes leached from shallow source zones, J. Contam. Hydrol., 123, 130–156, https://doi.org/10.1016/j.jconhyd.2010.12.013, 2011.
Rockhold, M., Thorne, P., Song, X., Tartakovsky, G., Tagestad, J., and Chen, X.: Sensitivity Analysis of Contaminant Transport from Vadose Zone Sources to Groundwater Case Study for Hanford Site B-Complex, Richland, Washington, https://doi.org/10.2172/1488866, 2018.
Saltelli, A. and Annoni, P.: How to avoid a perfunctory sensitivity analysis, Environ. Model. Softw., 25, 1508–1517, https://doi.org/10.1016/j.envsoft.2010.04.012, 2010.
Saltelli, A., Tarantola, S., Campolongo, F., and Ratto, M.: Sensitivity analysis in practice: a guide to assessing scientific models (Google eBook), Wiley, New York, 219 pp., ISBN 0-470-87093-1, 2004.
Saltelli, A., Annoni, P., Azzini, I., Campolongo, F., Ratto, M., and Tarantola, S.: Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index, Comput. Phys. Commun., 181, 259–270, https://doi.org/10.1016/j.cpc.2009.09.018, 2010.
Sarrazin, F., Pianosi, F., and Wagener, T.: Global Sensitivity Analysis of environmental models: Convergence and validation, Environ. Model. Softw., 79, 135–152, https://doi.org/10.1016/j.envsoft.2016.02.005, 2016.
Schaap, M. G., Leij, F. J., and Van Genuchten, M. T.: Rosetta: A computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions, J. Hydrol., 251, 163–176, https://doi.org/10.1016/S0022-1694(01)00466-8, 2001.
Schmidt, T. C., Schirmer, M., Weiß, H., and Haderlein, S.: Microbial degradation of tert-butyl ether and tert-butyl alcohol in the subsurface., J. Contam. Hydrol., 70, 173–203, 2004.
Schübl, M., Stumpp, C., and Brunetti, G.: A Bayesian perspective on the information content of soil water measurements for the hydrological characterization of the vadose zone, J. Hydrol., 613, 128429, https://doi.org/10.1016/j.jhydrol.2022.128429, 2022.
Shapiro, A. M. and Day-Lewis, F. D.: Reframing groundwater hydrology as a data-driven science, Groundwater, 1–2, https://doi.org/10.1111/gwat.13195, 2022.
Sheikholeslami, R., Razavi, S., and Haghnegahdar, A.: What should we do when a model crashes? Recommendations for global sensitivity analysis of Earth and environmental systems models, Geosci. Model Dev., 12, 4275–4296, https://doi.org/10.5194/gmd-12-4275-2019, 2019.
Šimùnek, J., Šejna, M., Saito, H., Sakai, M., and van Genuchten, M. T.: The HYDRUS-1D Software Package for Simulating the One-Dimensional Movement of Water, Heat, and Multiple Solutes in Variably-Saturated Media, Department of Environmental Sciences, University of California Riverside, Riverside, CA, USA, https://www.pc-progress.com/en/Default.aspx?hydrus-1d (last access: 8 April 2024), 2013.
Sobol, I. M.: Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates, Math. Comput. Simulat., 55, 271–280, https://doi.org/10.1016/S0378-4754(00)00270-6, 2001.
Song, X., Zhang, J., Zhan, C., Xuan, Y., Ye, M., and Xu, C.: Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications, J. Hydrol., 523, 739–757, https://doi.org/10.1016/j.jhydrol.2015.02.013, 2015.
Stewart, O.: Sulfolane Technical Assistance and Evaluation Report, Alaska Department of Environmental Conservation, 61, https://dec.alaska.gov/media/6169/sulfolane-tech-assist-report.pdf (last access: 8 April 2024), 2010.
Stumm, W. and Morgan, J. J.: Aquatic Chemistry: An Introduction Emphasizing Chemical Equilibria in Natural Waters, 2nd Edition, John Wiley & Sons Ltd., New York, ISBN 0471048313, ISBN 9780471048312, 1981.
Tartakovsky, D. M.: Probabilistic risk analysis in subsurface hydrology, Hydrol. L. Surf. Stud., 34, L05404, https://doi.org/10.1029/2007GL029245, 2007.
Troldborg, M., Binning, P. J., Nielsen, S., Kjeldsen, P., and Christensen, A. G.: Unsaturated zone leaching models for assessing risk to groundwater of contaminated sites, J. Contam. Hydrol., 105, 28–37, https://doi.org/10.1016/j.jconhyd.2008.11.002, 2009.
Troyanskaya, O., Cantor, M., Sherlock, G., Brown, P., Hastie, T., Tibshirani, R., Botstein, D., and Altman, R. B.: Missing value estimation methods for DNA microarrays, Bioinformatics, 17, 520–525, https://doi.org/10.1093/bioinformatics/17.6.520, 2001.
Turco, M., Kodešová, R., Brunetti, G., Nikodem, A., Fér, M., and Piro, P.: Unsaturated hydraulic behaviour of a permeable pavement: Laboratory investigation and numerical analysis by using the HYDRUS-2D model, J. Hydrol., 554, 780–791, https://doi.org/10.1016/j.jhydrol.2017.10.005, 2017.
Turkeltauub, T.: Monitoring and modeling recharge-water fluxes in the deep vadose-zone under different land uses over the southern coastal aquifer, Israel, Master thesis, Ben-Gurion University of the Negev, 99 pp., https://www.agri.gov.il/databases/dissertations/729.aspx (last access: 8 April 2024), 2011.
U.S. EPA: Edition of the Drinking Water Standards and Health Advisories Tables, EPA's Office of Water, Washington, DC, 822 pp., https://www.epa.gov/system/files/documents/2022-01/dwtable2018.pdf (last access: 8 April 2024), 2018.
Upreti, D., Pignatti, S., Pascucci, S., Tolomio, M., Li, Z., Huang, W., and Casa, R.: A Comparison of moment-independent and variance-based global sensitivity analysis approaches for wheat yield estimation with the Aquacrop-OS model, Agronomy, 10, 607, https://doi.org/10.3390/AGRONOMY10040607, 2020.
van Genuchten, M. T. T.: A Closed-form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils, Soil Sci. Soc. Am. J., 44, 892–898, https://doi.org/10.2136/sssaj1980.03615995004400050002x, 1980.
Wainwright, H. M., Finsterle, S., Zhou, Q., and Birkholzer, J. T.: Modeling the performance of large-scale CO2 storage systems: A comparison of different sensitivity analysis methods, Int. J. Greenh. Gas Con., 17, 189–205, https://doi.org/10.1016/j.ijggc.2013.05.007, 2013.
Wang, A. and Solomatine, D. P.: Practical experience of sensitivity analysis: Comparing six methods, on three hydrological models, with three performance criteria, Water (Switzerland), 11, 1–26, https://doi.org/10.3390/w11051062, 2019.
Whiting, D., Card, A., Wilson, C., and Reeder, J.: Estimating Soil Texture, Colorado Master Gardener, 1–5, Colorado State University, https://cmg.extension.colostate.edu/Gardennotes/214.pdf (last access: 8 April 2024), 2011.
Wołowiec, K. and Malina, G.: Laboratory studies on benzene sorption processes in clay formations, Geol. Geophys. Environ., 41, 43, https://doi.org/10.7494/geol.2015.41.1.43, 2015.
Yadav, B. K. and Hassanizadeh, S. M.: An overview of biodegradation of LNAPLs in coastal (Semi)-arid environment, Water. Air. Soil Poll., 220, 225–239, https://doi.org/10.1007/s11270-011-0749-1, 2011.
Zanello, V., Scherger, L. E., and Lexow, C.: Assessment of groundwater contamination risk by BTEX from residual fuel soil phase, SN Appl. Sci., 3, 1–20, https://doi.org/10.1007/s42452-021-04325-w, 2021.
Zhou, T., Šimùnek, J., Braud, I., Nasta, P., Brunetti, G., and Liu, Y.: The impact of evaporation fractionation on the inverse estimation of soil hydraulic and isotope transport parameters, J. Hydrol., 612, https://doi.org/10.1016/j.jhydrol.2022.128100, 2022.
Zytner, R. G.: Sorption of benzene, toluene, ethylbenzene and xylenes to various media, J. Hazard. Mater., 38, 113–126, https://doi.org/10.1016/0304-3894(94)00027-1, 1994.
Short summary
Contamination from fuel constituents poses a major threat to groundwater. However, studies devoted to identification of the driving parameters for fuel derivative transport in soils are scarce, and none have dealt with heterogeneous layered media. Here, we performed global sensitivity analysis (GSA) on a model of benzene transport to groundwater. The results identified the parameters controlling benzene transport in soils and showed that GSA is as an important tool for transport model analysis.
Contamination from fuel constituents poses a major threat to groundwater. However, studies...
