Producing and Integrating Time Series of Gridded Evapotranspiration for Irrigation Management, Hydrology and Remote Sensing Applications
Evapotranspiration (ET) is the second largest component of hydrologic systems and water balances, following precipitation, and is the driving component for irrigation water requirements (IWR) of agricultural crops. Quantifying ET for specific crops and regions is required for design of irrigation systems, basin water balance estimates, irrigation water management, improvement of crop yields and water-use efficiency, and review and litigation of water right applications and disputes; all of which are receiving more and more high priority attention. Current methods for estimating ET and IWR across the US and among federal and state entities are 1) typically based on sparse weather station data, some of which are in dry, nonevaporating environments; 2) have incomplete data for applying the better, physics-based ET equations; and 3) are not
consistent among regions nor governmental entities and/or are not what are generally considered to be state-of-the-art. Over the past 10 to 20 years, an alternative to the traditional use of weather station based historical weather data for establishment of ET and IWR methods has become available, with the advent of gridded historical weather data derived from sophisticated land data assimilation systems (LDAS) operated by NOAA's National Centers for Environmental Prediction (NCEP) and the National Science Foundation sponsored National Center for Atmospheric Research (NCAR). However, the use of LDAS data to estimate ET and irrigation water requirements presents the challenge of containing artifacts in temperature, humidity and wind speed that stem from the dry environments from which assimilated weather data often originate, especially in the western US where ET demand can greatly exceed
precipitation input. It is shown that use of air temperature and humidity data collected from non-irrigated settings can cause overestimation of reference ET by as much as 20 to 25% by ignoring the influence of feedback and conditioning of the equilibrium boundary layer (EBL) by evaporative cooling that occurs over irrigated agriculture. Reference ET is the ET from a defined reference surface (crop) that is actively growing, not limited by soil moisture, and is at full ground-cover and has defined vegetation height, surface conductance, and aerodynamic roughness. Reference ET is used to approximate the upper limit of ET expected from extensive well-watered surfaces. The proposed conditioning approach is considered to be revolutionary in transforming the gridded LDAS weather data sets into data sets that describe weather conditions that would occur over evaporating surfaces, thereby
removing biases in reference ET estimates. The approach will push and evolve the state of the art in estimating reference ET over a wide range of land surfaces and will improve the value of ET estimates for irrigation water planning and management. The ET product will rectify current errors and biases committed by current applications of these weather data products for water management.