Trend and magnitude of changes in climate variables and reference evapotranspiration over 116-yr period in the Platte River Basin, central Nebraska–USA

Abstract

Summary Some studies that investigate the climate change and hydrologic balance relationships utilize reference (potential) evapotranspiration (ETref) to either calculate the changes in trends and magnitude of actual ET or to determine changes in atmospheric demand. In such cases, it is important to acquire robust ETref estimates to correctly assess the impact of changes in meteorological variables on atmospheric evaporative demand, hydrologic balances, response of vegetation to climate, and their interactions. Despite its crucial importance, unfortunately, ETref is sometimes poorly addressed in climate change studies as some studies utilize temperature or radiation-based empirical equations due to various reasons (unavailability of climate data to solve combination-based energy balance equations, etc.). Since many climate variables that affect ETref rates have been changing and are expected to change in the future, single-variable equations for estimating the trend in ETref should be avoided due to the inherent nature of the trend passed to ETref from the variable. Here, we showed an integrated approach of practical and robust procedures that are already exist to estimate necessary climate variables [incoming shortwave radiation (Rs), net radiation (Rn), wind speed at 2-m (u2), relative humidity (RH), and vapor pressure deficit (VPD)] only from observed maximum and minimum air temperatures (Tmax and Tmin) and precipitation (P) data to be used in Penman–Monteith-type combination-based energy balance equations to predict grass-and alfalfa-reference evapotranspiration (ETo and ETr, respectively). We analyzed the trends and magnitudes of change in meteorological variables for a 116-yr period from 1893 to 2008 in the agro-ecosystem-dominated Platte River Basin in central Nebraska, USA. Although we found a significant (P 70 mm d−1). We present detailed analyses of relationships between ETref and all meteorological variables. On an annual time step ETref significantly (P