A Decade of Remote Sensing and Evapotranspiration Research at USDA-ARS Conservation and Production Research Laboratory

Abstract

Abstract. It is widely recognized that image-based remote sensing can provide spatially and temporally distributed information on soil and crop characteristics including tillage and evapotranspiration (ET) from plot to regional scales. ET is an important component of the water balance and the major consumptive use of irrigation water and precipitation on cropland. Numerous ET models have been developed in the last three decades to make use of visible, near‐infrared (NIR), shortwave infrared (SWIR), and most importantly, thermal data acquired by sensors on airborne and satellite platforms. However, there are numerous challenges related to spatial and temporal resolutions of remotely sensed data. These include the need for a comprehensive database for model development, enhancement, and testing; availability of cloud-free images; high quality weather data; accurate estimation and partitioning of evaporation and transpiration; and user-friendly platforms for distributing ET maps for irrigation scheduling and groundwater management purposes in arid and semiarid regions such as the Texas High Plains. In the last decade (2005-2015), researchers at the USDA-ARS Conservation and Production Research Laboratory, home of four large monolithic weighing lysimeters, in collaboration with Texas AM measurements of turbulent fluxes with eddy covariance and Bowen ratio systems, sensible heat flux induced light intensity scintillations, net radiation and soil heat fluxes, crop growth parameters, and ET by mass balance. This has allowed the development, enhancement, and testing of numerous remote sensing ET models; development of a framework to generate daily time series ET maps; and development of ET mapping and reference ET software. In this paper, we discuss these accomplishments and the status of ongoing research projects in detail. Keywords. Energy Balance Models, Evapotranspiration, Irrigation Management, Hydrologic models