Using remotely sensed data to estimate area-averaged daily surface fluxes over a semi-arid mixed agricultural land

Abstract

Optical remote sensing has been widely used for diagnostics of land surface atmosphere exchanges, including evapotranspiration (ET). Estimating ET now benefits from modeling maturity at local scale, while ongoing challenges include both spatial and temporal issues: influences of spatial heterogeneities on non-linear behavior when upscaling and extrapolation of instantaneous estimates at satellite overpass to the daily scale. Both issues are very important when using remote sensing for managing water resources, especially in agriculture. The two main contributions of the current study are first the examination of the diurnal behavior of evaporative fraction (EF) and available energy (AE) over heterogeneous agricultural land surfaces, and second presenting a simple approach to derive area-averaged daily ET under such conditions. Area-averaged fluxes are expressed using the same equations as those used over homogeneous areas, but whose arguments are effective expressions of the local parameters involved. Next, heuristic formulations are proposed to estimate the diurnal courses of EF and AE, by combining diurnal meteorological information available from observation networks (or weather forecasts) with instantaneous estimates at satellite overpass obtained from a simple energy balance model. These investigations were conducted using ground based data collected in the semi-arid Yaqui valley, north-western Mexico, over three adjacent agricultural fields which different crops and soil moisture conditions. This approach accurately reproduced the diurnal course of ET. However, these promising results have to be confirmed using actual satellite and operational meteorological data. This work is the subject of ongoing investigations.