Environmental Fluid Mechanics

, Volume 10, Issue 1–2, pp 121–135 | Cite as

Estimating travel time of recharge water through a deep vadose zone using a transfer function model

Original Article


We estimate the travel time of percolating water through a deep vadose zone at the regional scale using a transfer function model and a physical based conceptual flow model (Hydrus-1D), thereby exploiting the time series of precipitation, actual evapotranspiration and groundwater piezometry and generic vadose zone data. With the transfer function model we observe a high variability of estimated travel time varying from 0.9 to 3.1 years, corresponding to estimated vertical water flux velocities varying from 6.6 to 28.0 m/year. These results were compared with the travel time estimated from the physical based conceptual model. With the flow model, estimated travel time varies between 4.7 and 15.5 years, corresponding to water flux velocities varying between 1.7 and 4.1 m/year. The estimated travel time calculated with the flow model were therefore about five times larger than those estimated with the transfer function model. This could be explained by the fact that the transfer function model considers heterogeneous recharge from the vadose zone as well as from the vicinity of the piezometer through the so called “pushing effect”. In addition, the flow model requires various hydrogeological and hydrodynamic parameters which were estimated using generic parametrisation approaches, that are largely affected by uncertainty and may not reflect the local conditions. In contrast, the transfer function model only exploits available measurable time series and has the advantage of being site-specific.


Transfer function model Travel time Soil Groundwater level fluctuations Brusselian sands 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Allison G, Stone W, Hughes M (1985) Recharge in karst and dune elements of a semi-arid landscape as indicated by natural isotopes and chloride. J Hydrol 76(1–2): 1–25CrossRefGoogle Scholar
  2. 2.
    Alvarez-Benedi J, Munoz-Carpena R (eds) (2005) Soil-water-solute processes in environmental systems. Monitoring, characterization and modelling. CRC Press, Boca RatonGoogle Scholar
  3. 3.
    Barnes C, Allison G (1988) Tracing of water movement in the unsaturated zone using stable isotopes of hydrogen and oxygen. J Hydrol 100(1–3): 143–176CrossRefGoogle Scholar
  4. 4.
    Bear J (1972) Dynamics of fluids in porous media. Dover, New YorkGoogle Scholar
  5. 5.
    Birdsell KH, Newman BD, Broxton DE, Robinson BA (2005) Conceptual models of vadose zone flow and transport beneath the Pajarito Plateau, Los Alamos, New Mexico. Vadose Zone J 4(3): 620–636CrossRefGoogle Scholar
  6. 6.
    Carsel RF, Parrish RS (1988) Developing joint probability-distributions of soil-water retention characteristics. Water Resour Res 24(5): 755–769CrossRefGoogle Scholar
  7. 7.
    Constantz J, Tylerb SW, Kwicklisc E (2003) Temperature-profile methods for estimating percolation rates in arid environments. Vadose Zone J 2: 12–24CrossRefGoogle Scholar
  8. 8.
    Cook PG, Jolly ID, Leaney FW, Walker GR, Allan GL, Fifield LK, Allison GB (1994) Unsaturated zone tritium and Cl-36 profiles from Southern Australia—their use as tracers of soil-water movement. Water Resour Res 30(6): 1709–1719CrossRefGoogle Scholar
  9. 9.
    Dettinger MD (1989) Reconnaissance estimates of natural recharge to desert basins in Nevada, U.S.A., by using chloride-balance calculations. J Hydrol 106(1–2): 55–78CrossRefGoogle Scholar
  10. 10.
    Dyck MF, Kachanoski RG, de Jong E (2005) Spatial variability of long-term chloride transport under semiarid conditions: Pedon scale. Vadose Zone J 4(4): 915–923CrossRefGoogle Scholar
  11. 11.
    Faust AE, Ferre TPA, Schaap MG, Hinnell AC (2006) Can basin-scale recharge be estimated reasonably with water-balance models?. Vadose Zone J 5(3): 850–855CrossRefGoogle Scholar
  12. 12.
    Feddes R, de Rooij G, van Dam J (eds) (2004) Unsaturated zone modelling: progress, challenges and applications. Kluwer, DordrechtGoogle Scholar
  13. 13.
    Flint AL, Ellett KM (2004) The role of the unsaturated zone in artificial recharge at San Gorgonio Pass, California. Vadose Zone J 3(3): 763–774Google Scholar
  14. 14.
    Gasser M, Caron J, Lagace R, Laverdiere M (2003) Predicting nitrate leaching under potato crops using transfer functions. J Environ Qual 32(4): 1464–1473CrossRefGoogle Scholar
  15. 15.
    Gee GW, Hillel D (1988) Groundwater recharge in arid regions—review and critique of estimation methods. Hydrol Process 2(3): 255–266CrossRefGoogle Scholar
  16. 16.
    Holt RM, Nicholl MJ (2004) Uncertainty in vadose zone flow and transport prediction. Vadose Zone J 3(2): 480–484CrossRefGoogle Scholar
  17. 17.
    Hubbell JM, Nicholl MJ, Sisson JB, McElroy DL (2004) Application of a Darcian approach to estimate liquid flux in a deep vadose zone. Vadose Zone J 3(2): 560–569CrossRefGoogle Scholar
  18. 18.
    Hupet F, van Dam JC, Vanclooster M (2004) Impact of within-field variability in soil hydraulic properties on transpiration fluxes and crop yields: a numerical study. Vadose Zone J 3(4): 1367–1379CrossRefGoogle Scholar
  19. 19.
    IBW (1987) Étude des ressources en eau du Brabant Wallon, contrat Région Wallonne. Technical report, Intercommunale du Brabant WallonGoogle Scholar
  20. 20.
    Javaux M, Vanclooster M (2003) Robust estimation of the generalized solute transfer function parameters. Soil Sci Soc Am J 67(1): 81–91CrossRefGoogle Scholar
  21. 21.
    Javaux M, Vanclooster M (2003) Scale- and rate-dependent solute transport within an unsaturated sandy monolith. Soil Sci Soc Am J 67(5): 1334–1343Google Scholar
  22. 22.
    Javaux M, Vanclooster M (2004) In situ long-term chloride transport through a layered, nonsaturated subsoil. 2. Effect of layering on solute transport processes. Vadose Zone J 3(4): 1331–1339CrossRefGoogle Scholar
  23. 23.
    Javaux M, Vanclooster M (2006) Scale-dependency of the hydraulic properties of a variably saturated heterogeneous sandy subsoil. J Hydrol 327(3–4): 376–388CrossRefGoogle Scholar
  24. 24.
    Javaux M, Vanderborght J, Kasteel R, Vanclooster M (2006) Three-dimensional modeling of the scale-and flow rate-dependency of dispersion in a heterogeneous unsaturated sandy monolith. Vadose Zone J 5(2): 515–528CrossRefGoogle Scholar
  25. 25.
    Jury WA (1982) Simulation of solute transport using a transfer-function model. Water Resour Res 18(2): 363–368CrossRefGoogle Scholar
  26. 26.
    Jury WA, Flühler H (1992) Transport of chemicals through soil: mechanisms, models, and field applications, vol. 47. Academic Press, New York, pp 141–201Google Scholar
  27. 27.
    Kim SJ, Hyun Y, Lee KK (2005) Time series modeling for evaluation of groundwater discharge rates into an urban subway system. Geosci J 9(1): 15–22CrossRefGoogle Scholar
  28. 28.
    Leterme B, Vanclooster M, Rounsevell MD, Bogaert P (2006) Discriminating between point and non-point sources of atrazine contamination of a sandy aquifer. Sci Total Environ 362(1–3): 124–142Google Scholar
  29. 29.
    Levitt DG, Newell DL, Stone WJ, Wykoff DS (2005) Surface water-groundwater connection at the Los Alamos Canyon weir site: Part 1. Monitoring site installation and tracer tests. Vadose Zone J 4(3): 708–717CrossRefGoogle Scholar
  30. 30.
    Mallants D, Jacques D, Vanclooster M, Diels J, Feyen J (1996) A stochastic approach to simulate water flow in a macroporous soil. Geoderma 70(2–4): 299–324CrossRefGoogle Scholar
  31. 31.
    Mattern S, Bogaert P, Vanclooster M (2008) Advances in subsurface pollution of porous media—indicators, processes and modelling: IAH selected papers, vol 14. Taylor and Francis. Introducing time variability and sampling rate in the mapping of groundwater contamination by means of the Bayesian Maximum Entropy (BME) method. IAH—Selected Papers on Hydrogeology, ISBN:9780415476904Google Scholar
  32. 32.
    McElroy DL, Hubbell JM (2004) Evaluation of the conceptual flow model for a deep vadose zone system using advanced tensiometers. Vadose Zone J 3(1): 170–182CrossRefGoogle Scholar
  33. 33.
    MRW-DGRNE Ddes (2008) Banque de données “10-sous”. Technical report, 15, Avenue Prince de Liège, B-5100 JambesGoogle Scholar
  34. 34.
    Nativ R, Adar E, Dahan O, Geyh M (1995) Water recharge and solute transport through the vadose zone of fractured chalk under desert conditions. Water Resour Res 31(2): 253–261CrossRefGoogle Scholar
  35. 35.
    O’Geen AT, McDaniel PA, Boll J (2002) Chloride distributions as indicators of vadose zone stratigraphy in Palouse loess deposits. Vadose Zone J 1: 150–157CrossRefGoogle Scholar
  36. 36.
    Oger R (1991) Rétrospective climatologique de la période 1950–1989, poste d’Ernage-Gembloux, 106 pp. Technical report, Centre de Recherches Agronomiques de GemblouxGoogle Scholar
  37. 37.
    Onsoy YS, Harter T, Ginn TR, Horwath WR (2005) Spatial variability and transport of nitrate in a deep alluvial vadose zone. Vadose Zone J 4(1): 41–54CrossRefGoogle Scholar
  38. 38.
    Ott WR (1990) A physical explanation of the lognormality of pollutant concentrations. J Air Waste Manag Assoc 40(10): 1378–1383Google Scholar
  39. 39.
    Robinson BA, Cole G, Carey JW, Witkowski M, Gable CW, Lu ZM, Gray R (2005) A vadose zone flow and transport model for Los Alamos Canyon, Los Alamos, New Mexico. Vadose Zone J 4(3): 729–743CrossRefGoogle Scholar
  40. 40.
    Schaap M, Leij F, Genuchten MV (2001) Rosetta: a computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions. J Hydrol 251(3–4): 163–176CrossRefGoogle Scholar
  41. 41.
    Si BC, de Jong E (2007) Determining long-term (decadal) deep drainage rate using multiple tracers. J Environ Qual 36(6): 1686–1694CrossRefGoogle Scholar
  42. 42.
    Simunek J, van Genuchten MT, Sejna M (2008) Development and applications of the HYDRUS and STANMOD software packages and related codes. Vadose Zone J 7(2): 587–600CrossRefGoogle Scholar
  43. 43.
    Stewart IT, Loague K (1999) A type transfer function approach for regional-scale pesticide leaching assessments. J Environ Qual 28(2): 378–387CrossRefGoogle Scholar
  44. 44.
    Tank AMGK, Wijngaard JB, Konnen GP, Bohm R, Demaree G, Gocheva A, Mileta M, Pashiardis S, Hejkrlik L, Kern-Hansen C, Heino R, Bessemoulin P, Muller-Westermeier G, Tzanakou M, Szalai S, Palsdottir T, Fitzgerald D, Rubin S, Capaldo M, Maugeri M, Leitass A, Bukantis A, Aberfeld R, Van Engelen AFV, Forland E, Mietus M, Coelho F, Mares C, Razuvaev V, Nieplova E, Cegnar T, Lopez JA, Dahlstrom B, Moberg A, Kirchhofer W, Ceylan A, Pachaliuk O, Alexander LV, Petrovic P (2002) Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment. Int J Climatol 22(12): 1441–1453CrossRefGoogle Scholar
  45. 45.
    Vanclooster M, Mallants D, Diels J, Feyen J (1993) Determining local-scale solute transport parameters using time domain reflectometry (tdr). J Hydrol 148(1–4): 93–107CrossRefGoogle Scholar
  46. 46.
    Vanderborght J, Vanclooster M, Mallants D, Diels J, Feyen J (1996) Determining convective lognormal solute transport parameters from resident concentration data. Soil Sci Soc Am J 60(5): 1306–1317Google Scholar
  47. 47.
    van der Velde M, Javaux M, Vanclooster M, Clothier BE (2006) El Nino-Southern Oscillation determines the salinity of the freshwater lens under a coral atoll in the Pacific Ocean. Geophys Res Lett 33(21): L21403CrossRefGoogle Scholar
  48. 48.
    Van Genuchten M (1980) A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci Soc Am J 44: 892–898CrossRefGoogle Scholar
  49. 49.
    Wang W, Neuman SP, Yao Tm, Wierengac PJ (2003) Simulation of large-scale field infiltration experiments using a hierarchy of models based on public, generic, and site data. Vadose Zone J 2: 297–312CrossRefGoogle Scholar
  50. 50.
    Wu YS, Lu GP, Zhang K, Bodvarsson GS (2004) A mountain-scale model for characterizing unsaturated flow and transport in fractured tuffs of Yucca Mountain. Vadose Zone J 3(3): 796–805CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  1. 1.Université catholique de LouvainLouvain-la-NeuveBelgium

Personalised recommendations