An intelligent front-end for selecting evapotranspiration estimation methods

Abstract Evapotranspiration (ET) is an important parameter needed by water managers for the design, operation and management of irrigation systems. Since there are many methods to compute ET, based on climatic data, an inexperienced engineer or hydrologist is perplexed with the selection of an appropriate method. In this context, an expert system (ES) would be of great use to aid in selection of a suitable ET estimation method, given the location, data availability and climatic conditions. In this paper an intelligent front-end expert system (ETES), that has been developed to select suitable ET estimation methods under South Indian climatic conditions, is presented. Ten meteorological stations located in different climatic regions and thirteen ET estimation methods have been considered in this ES. Like a human consultant, the system asks the user for detailed information regarding the details of the project site such as location, season, climatic zone, and data availability. It then makes a recommendation based on this information and the system's own knowledge of such a situation. Along with the recommended method, ETES will also suggest suitable correction factors for converting the resulting ET values to those of methods that result in accurate estimation. The developed ES would be of much potential use in irrigation management in developing countries like India.