Spatially distributed monthly reference evapotranspiration derived from the calibration of Thornthwaite equation: a case study, South of Iran

摘要

The Penman-Monteith equation is the most common method for estimating reference crop evapotranspiration (ET sub(o)). Using this method reqiures many different meteorological data, yet few stations with adequate meteorological data may exist in a region. Setting up a station that records the required data for Penman-Monteith equation is expensive. Alternatively, the Thornthwaite equation is a simpler method for estimating ET sub(o) since it is a temperature-based method. In this study, the Thornthwaite equation was spatially calibrated based on the Penman-Monteith method (as the standard and reference method to compute ET sub(o)) for every month of the year, using the meteorologica data of seven synoptic weather stations in Fars province, and seven synoptic stations outside the Fars province. The Thornthwaite equation using effective temperature that has been introduced recently in other studies was used (Camargo et al. in Revista Brasileira de Agrometeorologica 7:251-257, 1999). For this purpose a calibration coefficient k must be determined. The results of the spatial and temporal calibration of the new approach using the Thornthwaite equation showed that for each station different k values should be used monthly. Generally, the k values fluctuated between 0.55 and 1.12, and the mean RMSE for all stations was less than 1 mm day super(-1), which showed good and reliable agreement between the ET sub(o) estimations obtained from the Penman-Monteith and calibrated Thornthwaite equations. Depending on the geographical location of each station, spatial distribution maps of monthly k values were created for the study area using the inverse distance weighting (IDW) interpolation method. It is therefore possible to estimate monthly ET sub(o) using the appropriate k map and the Thornthwaite equation for different regions of study area instead of using the Penman-Monteith method. This case study showed that the same analysis might be used for the other parts of the country or any part of the world and would result in efficient scheduling of water resources for agriculture.