Modelling the Surface Resistance of a Mid-latitude Southamerican Salt Marsh

BUREK, A.; TONTI, N.; GASSMANN, M.I.; PÉREZ, C.F.

Conferencia; 33rd Conference on Agricultural and Forest Meteorology; 2018

One of the most recommended method to estimate evapotranspiration of vegetated surfaces with different soil moisture conditions is the Penman-Monteith equation (PM). Canopy and soil conditions are parameterized through the surface resistance or conductance, while the contribution of the canopy to evapotranspiration is measured by the canopy resistance. Recently, salt marsh communities gained importance respect to carbon and water cycles. Although generally dominated by the genus Spartina and Sarcocornia, salt marshes are composed of a mixture of halophyte species that make the estimation of evapotranspiration troublesome. This feature makes them suitable for evapotranspiration estimations considering the whole canopy, represented by the surface resistance. This work aims to model the surface resistance using conventional meteorological, biological and pedological variables observed at a salt marsh used for livestock production in Buenos Aires province, Argentina. Six different nonlinear models (M1 to M6) based on the net solar radiation (Rn), air temperature (Ta), air relative humidity (RH), surface wind velocity (U), dew point departure (Dp), aerodynamic resistance (ra), leaf area index (LAI) and volumetric soil water content (q) are proposed. Surface resistances during daytime were calculated by reversing the PM equation and evapotranspiration fluxes measured with the eddy covariance method. PM-derived surface resistances varied between 40 and 1000 s/m, with a mean of 167 s/m. From 1620 observations, 468 were used for model calibration while 1152 for model validation. The determination coefficients of the calibrated models varied between 0.783 and 0.865. Models M6 = f(Rn, RH, U, LAI) and M5= f(Rn, RH, ra, LAI) are the most efficient ones, with root mean square errors (RMSE) of 80.8 s/m and 86.2 s/m, determination coefficients of 0.51 and 0.41, while the index of agreement were 0.69 and 0.67, respectively. These results show the possibility to achieve surface resistances from a minimum set of variables easily measured in the field which in turn, allows to estimate the evapotranspiration of salt marsh ecosystems with scarce meteorological information.