Satellite-Based Psychrometric Approach for Understanding and Quantifying Evapotranspiration.

Remote sensing-based evapotranspiration (ET) can be derived using various methods, from soil moisture accounting to vegetation-index based approaches to simple and complex surface energy balance techniques. Due to the complexity of fully representing and parameterizing ET sub-processes, different models tend to diverge in their estimations. However, most models appear to provide reasonable estimations that can meet user requirements for seasonal water use estimation and drought monitoring. One such model is the Operational Simplified Surface Energy Balance (SSEBop). SSEBop can be explained using the psychrometric principle for vapor pressure/relative humidity measurements where the “dry bulb” and “wet bulb” equivalent readings can be made using satellite-based land surface temperature (LST) estimates. The difference in LST between the dry (desired location) and wet limit (reference value) is directly correlated to the soil-vegetation complex moisture status (soil humidity) and thus producing a fractional value (0-1) to scale the reference ET. The reference ET is independently calculated using available weather data through the standardized Penman-Monteith equation. Satellite-based Psychrometric Approach (SPA) explains the SSEBop model more effectively than the energy balance principle because SSEBop does not solve all terms of the surface energy balance such as sensible and ground-heat fluxes. The SPA explanation demonstrates the psychrometric constant for the air can be readily adapted to a comparable constant for the surface, thus allowing the creation of a “surface” psychrometric constant that is unique to a location and day-of-year. This new surface psychometric constant simplifies the calculation and explanation of satellite-based ET for several applications in agriculture and hydrology. Illustrative case studies that show the SPA explanation of the SSEBop model will be presented for crop water use mapping and drought monitoring in the US and around the world using the Landsat and MODIS (MODerate Resolution Imaging Spectroradiometer) datasets.