Abstract
Abstract. The heterogeneity of Agroecosystems, in terms of hydric conditions, crop types and states, and meteorological forcing, is difficult to characterize precisely at the field scale over an agricultural landscape. This study aims to perform a sensitivity study with respect to the uncertain model inputs of two classical approaches used to map the evapotranspiration of agroecosystems: (1) a surface energy balance (SEB) model, the Two-Source Energy Balance (TSEB) model, forced with thermal infrared (TIR) data as a proxy for the crop hydric conditions, and (2) a soil–vegetation–atmosphere transfer (SVAT) model, the SEtHyS model, where hydric conditions are computed from a soil water budget. To this end, the models' skill was compared using a large and unique in situ database covering different crops and climate conditions, which was acquired over three experimental sites in southern France and Morocco. On average, the models provide 30 min estimations of latent heat flux (LE) with a RMSE of around 55 W m−2 for TSEB and 47 W m−2 for SEtHyS, and estimations of sensible heat flux (H) with a RMSE of around 29 W m−2 for TSEB and 38 W m−2 for SEtHyS. A sensitivity analysis based on realistic errors aimed to estimate the potential decrease in performance induced by the spatialization process. For the SVAT model, the multi-objective calibration iterative procedure (MCIP) is used to determine and test different sets of parameters. TSEB is run with only one set of parameters and provides acceptable performance for all crop stages apart from the early growing season (LAI < 0.2 m2 m−2) and when hydric stress occurs. An in-depth study on the Priestley–Taylor key parameter highlights its marked diurnal cycle and the need to adjust its value to improve flux partitioning between the sensible and latent heat fluxes (1.5 and 1.25 for France and Morocco, respectively). Optimal values of 1.8–2 were highlighted under cloudy conditions, which is of particular interest due to the emergence of low-altitude drone acquisition. Under developed vegetation (LAI > 0.8 m2 m−2) and unstressed conditions, using sets of parameters that only differentiate crop types is a valuable trade-off for SEtHyS. This study provides some scientific elements regarding the joint use of both approaches and TIR imagery, via the development of new data assimilation and calibration strategies.
Highlights
Exchange of water at the soil–vegetation–atmosphere interface is of prime importance for weather forecasting and for climate studies (Shukla and Mintz, 1982); it is a key component for hydrology, and catchment water balance (Milly, 1994), as well as for agronomy in order to improve irrigation scheduling (Allen et al, 1998)
Available energy is well simulated for both models with daily averaged root-mean-square error (RMSE) of 43 and 19 W m−2 for Two-Source Energy Balance (TSEB) and SEtHyS, respectively
Monitoring evapotranspiration at the field scale over a large agricultural landscape is a challenge as it requires detailed information about the surface state and meteorological forcing, which is prone to uncertainties and unavailability
Summary
Exchange of water at the soil–vegetation–atmosphere interface is of prime importance for weather forecasting and for climate studies (Shukla and Mintz, 1982); it is a key component for hydrology, and catchment water balance (Milly, 1994), as well as for agronomy in order to improve irrigation scheduling (Allen et al, 1998). There are several in situ techniques available to measure ET (Allen et al, 2011) but most suffer from a lack of spatial representativeness. This prevents their use as a sustainable solution for regional applications, especially for agricultural landscapes where spatial heterogeneity – in terms of farming and technical itineraries, including the resulting pattern of moisture conditions – is high. Remote sensing offers an attractive alternative due to the synoptic and repeated data acquisition it provides. Even if ET is not directly observable from space, remote sensing data in different parts of the electromagnetic spectrum are related to the characteristics of the land surface governing the evapotranspiration process
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