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Joseph Alexander Paul POLLACCO José Miguel SORIA UGDALE Rafael ANGULO-JARAMILLO Isabelle BRAUD

A LINKING TEST THAT EXPLORES THE NON UNIQUENESS OF SOIL AND VEGETATION PARAMETERS OF AN UNSATURATED FLOW MODEL. Joseph Alexander Paul POLLACCO José Miguel SORIA UGDALE Rafael ANGULO-JARAMILLO Isabelle BRAUD Bernard SAUGIER. SCOPE.

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Joseph Alexander Paul POLLACCO José Miguel SORIA UGDALE Rafael ANGULO-JARAMILLO Isabelle BRAUD

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  1. A LINKING TEST THAT EXPLORES THE NON UNIQUENESS OF SOIL AND VEGETATION PARAMETERS OF AN UNSATURATED FLOW MODEL Joseph Alexander Paul POLLACCO José Miguel SORIA UGDALE Rafael ANGULO-JARAMILLO Isabelle BRAUD Bernard SAUGIER

  2. SCOPE To determine the impact of land use change on groundwater recharge by using a reliable and cost-effective model and method. What is the minimum number of soil parameters required to determine recharge? Can we determine the soil parameters by matching soil moisture data (vegetation parameters known)? Can we estimate the interception &evapotranspiration parameters by matching soil moisture profile(hydraulic parameters known)?

  3. Presentation of the 1D flow model • Describing the Linking Test – inverse modeling • Estimation of the hydraulic parameters with vegetation parameters known • Estimation of the interception & evapotranspiration parameters with hydraulic parameters known • Conclusions Linking Test :the power of simplicity

  4. INTERCEPTION MODEL PRECIPITATION(t) = INTERCEPTION(t) + THROUGHFALL(t) + STEMFLOW(t) EFFECTIVE PRECIPITATION(t) = PRECIPITATION(t) - INTERCEPTION(t) Throughfall Stemflow

  5. SINK TERM FOR EACH CELL IN THE ROOT ZONE Root Density Distribution, Gale and Grigal, (1987) S(hi)=  [Penman pot. Evaporation] [: Transpiration factor parameter] RDFi RWU(hi) Root Water Uptake, Prasad, (1986)

  6. VAN GENUCHTEN SOIL MOISTURE CHARACTERISTIC CURVE sat :saturated volumetric water content (pore space); res :residual water content; hae(cm) :air-entry value; n : h() shape parameter; wind method

  7. 2 é ù 1 - 1 n æ ö n ê ú * ç ÷ - = - - q L n 1 K ( ) Ksat * 1 1 q q ç ÷ ê ú è ø ê ú ë û VAN GENUCHTEN EXPRESSION FOR SOIL PERMEABILITY Ksat : saturated hydraulic conductivity L : “lumped” parameter that accounts for pore tortuosity & pore connectivity n : h()shape parameter K():can be determined from infiltration experiments. Lassabatère et al. 2006, SSSAJ

  8. REFERENCE PARAMETERS Hydraulic parameters Vegetation parameters

  9. IS YOUR INVERSE MODELING FEASIBLE ? To answer this question lets assume: • Your model represents perfectly the reality; • All the model outputs are know:Qref(recharge); Selecting your goals: What is the maximum tolerated inaccuracy in the prediction:Qmax The maximum accuracy of the data used to calibrate the model is OFfield. The tolerated measuring inaccuracy to achieveQmax correspondsto OFQmax The inverse modeling is feasible if Q Qmax&OFfieldOFQmax

  10. LINKING TEST PARAMsim Qsim Qref PARAMsim Forcing data PARAMref FLOW MODEL FLOW MODEL NO Optimizationfinished Sim ref OPTIMIZATION ALGORITHM OF (ref,sim) Increment a parameter YES FILEsim PARAMfeas FILTERINGDATA Q< Qmax

  11. FEASIBILITY DOMAIN OF THE INVERSE MODELING Pollacco et al., 2007 Advances in Water Resources

  12. FEASIBILITY DOMAIN OF THE INVERSE MODELING

  13. Linked Hydraulic Parameters Only 2 functional hydraulic parameters are required to predict recharge with an accuracy of Qmax

  14. s, hae Ks , n a, b s, hae Ks , n a, b s , hae , Ks , n s, hae Ks , n a, b s, hae Ks , n a, b a , b EFFECTIVE PARAMETERS It is easier to find the effective hydraulic parameters with2 functional hydraulic parameters than with 4field hydraulic parameters (s, hae, Ks, n) .

  15. Explaining why the Hydraulic Parameters Are Linked COMPENSATION EQUIFINALITY Lower k() gravity driven flux. Ruled surface Higher water storage & higher capillary driven. RANGE EQUIFINALITY

  16. Relationship between the different vegetations parameters Compensation equifinality

  17. WHAT TO TAKE HOME • The Linking Test helps you to determine • If you can achieve the required accuracy by performing a inverse modeling • If the inverse modeling is not feasible than the cause(s) can be determined and further action can be taken • If the Linking Test determines that the inverse problem is feasible but the parameters are linked than • The Linking Test would compute all the different parameter sets giving similar outputs • The Linking Test would determine the minimum number of parameters required Linking Test : the power of simplicity

  18. HYDROLOGICAL CONCLUSIONS • The Linking Test helped to determine • That only 2 functional hydraulic parameters are required to determine accurate recharge for soils not reaching saturation • The hydraulic parameters are truly linked due to compensation equifinality& range equifinality • Thevegetations parameters are falsely linkedand can not be determined by calibrating against soil moisture data • Thevegetation parameters arefalsely linkeddue to compensation equifinalityandfrequency distribution equifinality Linking Test : the power of simplicity

  19. QUESTION TIME joseph.pollacco@entpe.fr Linking Test : the power of simplicity

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