Skip to main content
Download PDF
  • Original Article
  • Published:

A Linking Test that establishes if groundwater recharge can be determined by optimising vegetation parameters against soil moisture

Un Test de Liaison qui établit si la recharge des eaux souterraines peut être quantifiée en optimisant les paramètres de végétation grâce aux profils d’humidité du sol

Annals of Forest Science volume 65, page 702 (2008)Cite this article

Abstract

  • • The impact of afforestation/deforestation on groundwater recharge can be predicted by using one-dimensional soil-vegetation water flow models based on Richards’ equation. However simulations depend upon parameters that are not easily measurable.

  • • Pollacco et al. (2008) showed that the hydraulic parameters can be determined, if the vegetation parameters are known, by fitting simulated time series of soil moisture profiles to those measured in situ. This paper presents a case study to determine if the interception and crop factor parameters can tentatively be calibrated by fitting soil moisture profiles. Synthetic data were used and the other vegetation parameters and the soil hydraulic parameters were assumed to be known.

  • • We applied and improved the Linking Test developed by Pollacco et al. (2008) to look for links between the parameters that need to be calibrated, and thus to investigate whether inverse modelling is feasible, which depends on the accuracy of the calibration data.

  • • The Linking Test established that interception and evapotranspiration parameters are linked and, therefore, uncertainty on interception compensates for uncertainty on evapotranspiration. Thus in spite of a good match between observed and simulated soil moisture data, inverse modelling is unfeasible. This is true even if the interception or the crop factor parameters are known, because an error on interception or evapotranspiration will be compensated by an error on groundwater recharge without affecting soil moisture.

  • • This paper recommends that vegetation parameters should not be calibrated by optimisation against soil moisture data.

Résumé

  • • L’impact de la déforestation/reforestation, sur la recharge des eaux souterraines, peut être quantifié en employant les modèles unidimensionnels d’écoulement dans le continuum sol-plante-atmosphère. Ces modèles sont fondés sur la solution de l’équation de Richards. Cependant, quel que soit le modèle, les simulations dépendent de paramètres qui sont difficilement mesurables.

  • • Pollacco et al. (2008) ont montré comment les paramètres hydrodynamiques du sol peuvent être déterminés, lorsque ceux de la végétation sont supposés connus, en ajustant une série chronologique simulée de profils d’humidité du sol à des profils mesurés in situ. Cet article recherche, à travers une étude de cas, si les paramètres d’interception et le coefficient cultural peuvent être estimés à partir des profils d’humidité du sol. Des données synthétiques simulées sont employées dans l’estimation tout en supposant connus les autres paramètres de végétation et les paramètres hydrodynamiques du sol.

  • • Le Test de Liaison développé par Pollacco et al. (2008) a été amélioré afin d’établir le lien existant entre les paramètres qui doivent être estimés, et de déterminer si la modélisation inverse est réalisable, ce qui dépend de la précision des données d’étalonnage.

  • • Le Test de Liaison a permis d’établir le degré de liaison entre les paramètres d’interception et d’évapotranspiration, et en conséquence d’estimer de combien l’incertitude sur l’interception compense celle sur l’évapotranspiration. Ainsi, malgré une bonne correspondance entre les données d’humidité de sol observées et simulées, la modélisation inverse n’est pas faisable. Ceci reste vrai même lorsque les paramètres d’interception et le coefficient cultural sont connus, car les erreurs sur l’interception ou l’évapotranspiration sont compensées par une erreur sur la recharge. Ces erreurs n’ont pas d’effet sur l’humidité du sol.

  • • Cet article suggère que les paramètres de végétation ne devraient pas être estimés par optimisation sur des données d’humidité du sol.

Abbreviations

C:

shape parameter of interception model

E:

actual evapotranspiration

Ec :

extension parameter

Ep :

potential evaporation

ΣE ref :

reference cumulative evapotranspiration

ΣE sim :

simulated cumulative evapotranspiration

FILEsim :

file that records OF, Qsim and PARAMsim during optimisation

g(h):

reduction of root water uptake at pressure head per cell

h :

matric potential

h(θ):

soil water retention curve

hae :

air-entry matrix potential or bubbling pressure head

hsv :

matric potential at the onset of plant water stress

hpw :

matric potential at permanent wilting point

INT:

interception loss per day

INTmax :

maximum interception loss per day

ΣINT ref :

reference cumulative interception

K(θ):

unsaturated hydraulic conductivity

Ks :

saturated hydraulic conductivity

L :

shape factor

m :

shape parameter

n :

pore-size distribution

OF :

objective Function

OFfield :

uncertainty of the soil moisture data

OFΔQmax :

greatest value of OF such that ΔQ = ΔQmax

PARAMfeas :

sets of feasible hydraulic parameters

PARAMref :

sets of reference hydraulic parameters

PARAMim :

sets of simulated hydraulic parameters

Pg :

daily gross precipitation

PTF(s) :

pedo-transfer functions

qref :

daily reference groundwater recharge

qsim :

daily simulated groundwater recharge

Qref :

reference cumulative groundwater recharge

Qsim :

simulated cumulative groundwater recharge

zdown :

depth of bottom cell

zmax :

root-zone depth

zup :

depth of top cell

ΔQ :

discrepancy between Qref and Qsim

ΔQmax :

maximum tolerated inaccuracy of the inverse modelling

ΔINT:

discrepancy between ΣINTref and ΣINTsim

ΔE :

discrepancy between ΣEref and ΣEsim

ΔRDfi :

vertical fraction of the roots density function per cell β crop factor

Θ :

volumetric water content

θe :

normalised volumetric water content

θr :

residual water content or residual degree of saturation

θref :

reference volumetric water content

θs :

saturated volumetric water content

θsim :

simulated volumetric water content

References

  • Ball J. and Trudgill S.T., 1995. Review of solute modelling. Solute modelling in catchment systems. ST Trudgill. Overview of solute modeling. in: Solute modeling in catchement systems. Wiley, London.

    Google Scholar 

  • Beven K.J., 1993. Prophecy, reality and uncertainty in distributed hydrological modelling. Adv. Water Resour. Res. 16: 41–51.

    Article  Google Scholar 

  • Bobay V., 1990. Influence d’une eclaircie sur le flux de seve et la transpiration de taillis de chataignier. Ph.D. University de Paris sud.

  • Bouraoui F., 2007. Testing the PEARL model in the Netherlands and Sweden, Environ. Modell. Software 22: 937–950.

    Article  Google Scholar 

  • Braud I., 2000. SiSPAT User’s Manual Version 3.0, Laboratoire d’Étude des Transferts en Hydrologie et Environnement, Grenoble, France, 106 p.

    Google Scholar 

  • Braud I., 2002. SiSPAT User’s Manual Update, Laboratoire d’Étude des Transferts en Hydrologie et Environnement, Genoble, France, 13 p.

    Google Scholar 

  • Braud I., Dantas-Antonino A.C., Vauclin M., Thony J.L., and Ruelle P., 1995. A Simple Soil Plant Atmosphere Transfer model (SiSPAT). Development and field verification. J. Hydrol. 166: 213–250.

    Article  Google Scholar 

  • Braud I., Varado N., and Olioso A., 2005. Comparison of root water uptake modules using either the surface energy balance or potential transpiration. J. Hydrol. 301: 267–286.

    Article  Google Scholar 

  • Burdine N.T., 1953. Relative permeability calculations for pore size distribution data. Trans. Am. Inst. Univ. Metall. Pet. Eng., 198, 71–87.

    Google Scholar 

  • Calder I.R., 1990. Evaporation in the uplands. Chichester; New York: John Wiley & Sons.

    Google Scholar 

  • Calder I.R., Reid I., Nisbit T., Robinson M., and Walker D.R., 2002. Trees and Drought Project on Lowland England (TADPOLE). Scoping Study Report to Department of the Environment.

  • Celia M.A., Bouloutas E.T., and Zarba R.L. 1990. A general massconservation numerical solution for the unsaturated flow equation. Water Resour. Res. 26: 1483–1496.

    Article  Google Scholar 

  • Doorenbos J. and Pruitt W.O. 1977. Guidelines for predicting crop water requirements. FAO Irrigation and Drainage Paper 24 (Rev.) Rome, 156 p.

  • Duan Q.Y., Sorooshian S., and Gupta V.K., 1994. Optimal use of the SCEUA global optimization method for calibrating watershed models. J. Hydrol. 158: 265–284.

    Article  Google Scholar 

  • Duan Q.Y., Gupta V.K., and Sorooshian S. 1992. Effective and efficient global optimisation for conceptual rainfall-runoff models. Water Resour. Res. 28: 1015–1031.

    Article  Google Scholar 

  • EEC 1992. Council Regulation No. 3508/92.

  • Cubera E. and Moreno G. 2007. Effect of single Quercus ilex trees upon spatial and seasonal changes in soil water content in dehesas of central western Spain Ann. For. Sci. 64: 3355–3364.

    Article  Google Scholar 

  • Ewen J., Parkin G., and O’Connell P.E., 2000. SHETRAN: a coupled surface/subsurface modelling system for 3D water flow and sediment and solute transport in river basins. ASCE, J. Hydrol. Eng. 5: 250–258.

    Article  Google Scholar 

  • FAO, 1977. Guidelines for predicting crop water requirements. J. Doorenbos, and W.O. Pruitt (Eds.), FAO Irrigation and Drainage Paper 24 (Rev.) Rome 156 p.

  • Feddes R. Kabat P.J.T., van Bakel J.J.B., Bronswijk, Halbertsma J., 1988. Modelling soil water dynamics in the unsaturated zone — state of the art. J. Hydrol. 100: 69–111.

    Article  Google Scholar 

  • Forestry Commission, 1998. A New Focus for England’s Woodlands. Forestry Commission.

  • Gale M.R. and Grigal D.F., 1987. Vertical root distributions of northern tree species in relation to successional status. Can. J. For. Res. 17: 829–834.

    Article  Google Scholar 

  • Haverkamp R. Vauclin M., and Vachaud G., 1984. Error analysis in estimating soil water content from neutron probe measurements: I. Local standpoint. Soil. Sci. 137: 78–90.

    Article  Google Scholar 

  • Her Majesty’s Stationary Office, 1995. Rural England: a nation committed to a living countryside. Department of the Environment, The Stationery Office.

  • Hupet F.S., Lambot M., Javaux M., and Vanclooster M., 2002. On the identification of macroscopic root water uptake parameters from soil water content observations. Water Resour. Res. 38: 1300.

    Article  Google Scholar 

  • Hupet F., Lambot S., Feddes R., van Dam J.C., and Vanclooster M. 2003. Estimation of root water uptake parameters by inverse modeling with soil water content data. Water Resour. Res. 39: 1312.

    Article  Google Scholar 

  • Jackson R.B., Canadell J., Ehleringer J.R., Mooney H.A., Sala O.E., and Schulze E.D., 1996. A global analysis of root distributions for terrestrial biomes. Oecologia 108: 398–411.

    Article  Google Scholar 

  • Keese K.E., Scanlon B.R., and Reedy R.C., 2005. Assessing controls on diffuse groundwater recharge using unsaturated flow modeling Water Resour. Res. 41 W06010, doi 10.1029/2004WR003841.

  • Kosugi K., 1999. General model for unsaturated hydraulic conductivity for soils with lognormal pore-size distribution. Soil Sci. Soc. Am. J. 63, 270–277.

    Article  CAS  Google Scholar 

  • Krysanova V., Hattermann F., and Wechsung F., 2007. Implications of complexity and uncertainty for integrated modelling and impact assessment in river basins. Environm. Model. Soft. 22: 701–709.

    Article  Google Scholar 

  • Milly P.C.D., 1982. Moisture and heat transport in hysteretic, inhomogeneous porous media: a matric head-based formulation and a numerical model. Water Resour. Res. 18: 498.

    Article  Google Scholar 

  • Mroczkowski M., Raper G.P., and Kuczera G., 1997. The quest for more powerful validation of conceptual catchment models. Water Resour. Res. 33: 2325–2336.

    Article  Google Scholar 

  • Mualem Y., 1976. A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res. 12: 513–522.

    Article  Google Scholar 

  • Musters P.A.D. and Bouten W., 1999. Assessing routing depths of an Austrian pine stand by inverse modeling soil water content maps. Water Resour. Res. 35: 3041–3048.

    Article  Google Scholar 

  • Musters P.A.D. and Bouten W., 2000. A method for identifying optimum strategies of measuring soil water contents for calibrating a root water uptake model. J. Hydrol. 227: 273–286.

    Article  Google Scholar 

  • Musters P.A.D., Bouten W., and Verstraten J.M., 2000. Potentials and limitations of modelling vertical distributions of root water uptake of an Austrian pine forest on a sandy soil. Hydrol. Processes 14: 103–115.

    Article  Google Scholar 

  • Nizinski J. and Saugier B., 1989. Dynamique de l’eau dans une chênaie en forêt de Fontainebleau. Ann. Sci. For. 46: 173–186.

    Article  Google Scholar 

  • Pollacco J.A.P., 2005. Inverse methods to determine parameters in a physically-based model of soil water balance, University of Newcastle upon Tyne, UK, Newcastle upon Tyne, February, 190 p.

    Google Scholar 

  • Pollacco J.A.P., Soria-Ugalde J.M., Angulo-Jaramillo R., Braud I., Saugier B., 2008. A linking Test to reduce the number of hydraulic parameters necessary to simulate groundwater recharge in unsaturated soils Adv. Water Resour. 31: 355–369.

    Google Scholar 

  • Prasad R., 1986. A linear root water uptake model. J. Hydrol. 99: 297–306.

    Article  Google Scholar 

  • Ross P.J., 1990. Efficient numerical methods for infiltration using Richards’ Equation. Water Resour. Res. 26: 279–290.

    Article  Google Scholar 

  • Simunek J., Huang K., and van Genuchten M.T.h., 1998. The HYDRUS code for simulating the one-dimensional movement of water, heat, and multiple solutes in variably-saturated media. Version 6.0, Research Report No. 144, US Salinity Laboratory, University of California, Riverside, California.

    Google Scholar 

  • Sinclair D.F., and Williams J., 1979. Components of variance involved in estimation soil water content and water content change using a neutron moisture meter. Austr. J. Soil Res. 17: 237–247.

    Article  Google Scholar 

  • Singh V.P., 1995. Computer models of watershed hydrology. Water Resources Publications: Littleton, Colorado.

    Google Scholar 

  • Sorooshian S., Duan Q.Y., and Gupta V.K., 1993. Calibration of rainfallrunoff models: Application of global optimization to the Sacramento soil moisture accounting model. Water Resour. Res. 29: 1185–1194.

    Article  Google Scholar 

  • van Genuchten M.T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Am. J. 44: 892–898.

    Article  Google Scholar 

  • White A., Cannell M.G.R., and Friend A.D. 2000, The high-latitude terrestrial carbon sink: a model analysis. GCB 6 227–245.

    Google Scholar 

  • Zhang L., and Dawes W. 1998., WAVES — An integrated energy and water balance model. CSIRO Land and Water Technical Report No. 31/98.

Download references

Author information

Authors and Affiliations

  1. Laboratoire des Sciences de l’Environnement, ENTPE, Rue Maurice Audin, 69518, Vaulx en Vélin, France

    Joseph Alexander Paul Pollacco & Rafael Angulo-Jaramillo

  2. UR Hydrologie-Hydraulique, CEMAGREF, 3bis Quai Chauveau, CP 220, 69336, Lyon Cedex 9, France

    Isabelle Braud

  3. Laboratoire d’étude des Transferts en Hydrologie et Environnement, LTHE, UMR 5564 CNRS INPG UJF IRD, BP 53, 38041, Grenoble Cedex 9, France

    Rafael Angulo-Jaramillo

  4. Systématique et Évolution, Université Paris-Sud, Écologie, Bât. 362, 91405, Orsay Cedex, France

    Bernard Saugier

Authors
  1. Joseph Alexander Paul Pollacco
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Isabelle Braud
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rafael Angulo-Jaramillo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Bernard Saugier
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Joseph Alexander Paul Pollacco.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pollacco, J.A.P., Braud, I., Angulo-Jaramillo, R. et al. A Linking Test that establishes if groundwater recharge can be determined by optimising vegetation parameters against soil moisture. Ann. For. Sci. 65, 702 (2008). https://doi.org/10.1051/forest:2008046

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1051/forest:2008046

Keywords

Mots-clés

Annals of Forest Science

ISSN: 1297-966X