Abstract:
Potential evapo-transpiration (PET) is an essential tool widely used in hydrological studies. The magnitude and the variation of PET are required for water resources planning and management, proper irrigation scheduling, assessment of irrigation efficiency in different irrigation methods and estimation of water supply requirements of irrigation projects.
Owing to the wide ranging inconsistency in meteorological data collection procedures and standards, two types of PET equations have been used by different authors; empirical equations with lower data requirement and physically-based equations that require more data. The International Commission for Irrigation and Drainage (ICID), the Food and Agriculture Organization (FAO) and the American Society of Civil Engineers (ASCE) have adopted the Penman-Monteith (PM) method as the standard way to compute PETfrom climate data. PM is widely used as it is predominantly a physically-based approach that can be used globally and that has been widely tested using Lysimeter data from a wide range of climatic conditions (Itenfisu et al., 2000).
When the data are limited, PET is calculated by estimating the absent parameters indirectly from the available data to use in PM equation (Allen et al., 1998) or by the use of less data intensive empirical equations some of which are based on temperature (e.g. Thornthwaite, 1948; Blaney and Criddle, 1950; Romanenko, 1961; Hargreaves, 1975 and Kharrufa, 1985). It is generally accepted that empirical formulae may be reliable in the areas and over the periods for which they were developed, but large errors can be expected when they are extrapolated to other climatic areas without recalibrating the constants involved in the formulae (Hounam, 1971).
There is a scarcity of accurate meteorological data in Uva Province of Sri Lanka for estimating PET using standard PM method. Therefore, this research was conducted to analyze and compare temperature-based methods with the standard Modified Penman-
Monteith (MPM) method and to select the best equation/s which can be applied to estimate the PET of the region.
