摘要：Problem statement: Pan Evaporation has extensively been used for estimating reference Evapotranspiration (ETo) due to its simplicity, low cost, ease of data interpretation and application and suitability for locations with limited availability of meteorological data. With this method, the pan coefficient (Kp) is a key element to be determined as well as the pan Evaporation (Ep) data. Approach: This study presents the development of new pan coefficient (Kp) equations for Class A pan and Colorado sunken pan under green and dry fetch conditions by using M5 model tree based on soft computing technique. The Kp values were taken from FAO-24 Kp table for the development of Kp equations. Results: The results of the study indicate the usefulness and applicability of the M5 model tree in developing Kp equations. Those proposed equations based on the M5 model tree gave better performance in estimating Kp values than the previous Kp equations as well as the new Kp equations developed by indicator regression technique. Conclusion: M5 model tree gave more accuracy in estimating Kp values. The new proposed Kp equations can be reliably used.
关键词：Estimating equation; indicator regression technique; M5 model tree; soft computing
