Estimation of Vegetation Parameters of the VIC Model Using Remotely Sensed Data

This paper presents a methodology for estimating vegetation parameters such as LAI, albedo, and FCANOPY based on remotely sensed data to model actual evapotranspiration (ET) in the Bajos Submeridionales region (Argentina). The data used were available and processed on the Google Earth Engine platform. Those parameters were introduced into the VIC model to simulate the water and energy balance during the period 2000-2019. The focus of this paper is only simulated ET, its annual cycle, and spatial patterns associated with the surface control exerted by different land cover types. Model results indicate that the annual ET cycle is related to the annual cycle of major meteorological forcings, including precipitation and temperature, as well as to the seasonal cycle of LAI, FCANOPY, and other vegetation structure parameters. Forest cover exhibits the highest ET rates, followed by herbaceous vegetation and crops. In poorly gauged regions such as the Bajos Submeridionales, the use of remotely sensed information and hydrologic models proves highly useful in improving the understanding of the hydrological cycle, thus contributing to better water/natural resources management.