Abstract
Daily pan evaporation is of utmost importance in planning and managing water resources. The present paper involves estimation of daily pan evaporation at a particular climatic station using daily pan evaporations of surrounding ten climatic stations covering six districts of Maharashtra state (India) with variation in elevations and weather. The surrounding stations were added one by one based on the correlation of each station with the output station. The soft computing technique of linear genetic programming was employed for this spatial mapping exercise. The models were developed for each station as output station (total 11) with the remaining stations (1 to 10) as inputs added one by one. In all 110 LGP models were developed to examine the ability of linear genetic programming to work as virtual pan as and when existing evaporimeters become inoperative. The best LGP model was for Suksale station with coefficient of correlation (r = 0.94) between observed and estimated pan evaporation. This will retrieve the missing evaporation data at one location using data at other locations.
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