Sensitivity of a clumped model of evapotranspiration to surface resistance parameterisations: Application in a semi-arid environment

Abstract This paper explores the sensitivity of a three-source (vegetation, P, bare soil, BS, and soil under plant, S) evapotranspiration clumped model (CM) developed for sparsely vegetated areas, to the parameterisation of the surface resistances in semi-arid climate. We analysed the sensitivity of the CM to: (i) the location and depth of the soil water content ( θ ) measurements, (ii) the accuracy in the measurements of the variables involved in the parameterisation of the surface resistances, with special attention to the in-canopy water vapour saturation deficit ( D 0 ) and to the average plant leaf area index ( L ), and (iii) the simplification of the parametric equations of the soil surface resistances. The sensitivity of the CM was tested in a stand of Anthyllis cytisoides located in a semi-arid area of the Southeast of Spain. In this stand, θ was measured at three different depths (0.02 m, 0.05 m and 0.15 m), D 0 was calculated through iterations of the CM, taking into account the water vapour fluxes of the different evaporating sources, and L was measured with a destructive direct method. These variables were included in parametric equations for estimating the surface resistances of P ( g s p ), BS and S ( r s p , r s bs and r s s , respectively). Evapotranspiration estimates were compared to Eddy Covariance system measurements. Results showed that for estimating r s bs and r s s the θ should be measured as superficially as possible, whereas when estimating r s p the θ should be measured at a depth where the effect of the extremely low values of the superficial layer of soil is excluded or attenuated (in our study area this depth was 0.15 m or the integrated θ of the first 0.15 m). Moreover, the CM was more sensitive to the accuracy in the estimation of D 0 than to any other variable, while errors in the measurement of L and θ had similar effects in the CM evapotranspiration estimates (a 50% underestimation of D 0 gave rise to an underestimation of λE of 70%, whereas an overestimation of 50% in D 0 led to an overestimation of λE of 16%; errors of ±50% in L and θ gave rise to errors of λE of ±16%). Finally, the CM showed a higher sensitivity to the parameterisation of each surface separately, with a specific parametric equation for each soil surface resistance, than to the use of specific values of θ measured in each soil surface.

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