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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)
Abstract
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• 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.
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• 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.
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• 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.
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• 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.
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• This paper recommends that vegetation parameters should not be calibrated by optimisation against soil moisture data.
Résumé
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• 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.
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• 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.
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• 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.
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• 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.
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• 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
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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
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DOI: https://doi.org/10.1051/forest:2008046