Aridity Correction of Weather Data Observed at Non-Reference Weather Sites to Compute Reference Evapotranspiration – Case Study in Urmia Lake Basin

Abstract

  This study investigates the importance of aridity correction when weather data are used for reference evapotranspiration computation. Correction is important when weather data are measured in dry conditions. However, the correction procedure and its impact have not been thoroughly investigated, and such corrections have rarely been applied. This study aims to illustrate the impact of aridity correction, by accepting a FAO’s suggested procedure, with reinvestigating some of the input data and the parameters used. In this study, the aridity correction was applied to five weather station datasets located in the Urmia Lake Basin of Iran, where the basin is in a semi-arid climate. The results of the analysis indicated that the correction significantly improved the reference evapotranspiration estimation, particularly when weather data measured at stations surrounded by dry-type land were used. Sensitivity analysis indicated that the reference evapotranspiration was overestimated by more than 15% or approximately 250 mm yr^-1 without correcting the weather data observed at the dry weather stations. Overestimation occurred primarily during dry summers in the study area. This type of correction is very important for irrigation water planning and management using weather data observed at dry conditions, called ‘non-reference weather data’.