Simulation of Pan-Evaporation Using Penman and Hamon Equations and Artificial Intelligence Techniques

The evaporation losses are very high in warm-arid regions and their accurate evaluation is vital for the sustainable management of water resources. assessment such involves extremely difficult original tasks because scarcity data countries with an arid climate. main objective this paper to develop models simulation pan-evaporation help Penman Hamon’s equations, Artificial Neural Networks (ANNs), Neuro Fuzzy Inference System (ANFIS). results from five types ANN different training functions were compared find best possible function. impact using various input variables was investigated as contribution research. average temperature mean wind speed found be most influential parameters. estimation parameters equations quite a daunting task. These estimated state art optimization algorithm, namely General Reduced Gradient Technique. ANN, ANFIS compared. Thirty-eight years (from 1980 2018) manually recorded regarding daily values month, including relative humidity, speed, sunshine duration, temperature, collected three gauging stations situated Al Qassim, Saudi Arabia. Nash Sutcliffe Efficiency (NSE) Mean Square Error (MSE) evaluated performance modeling techniques. study shows that better than those equations. findings present research will managers, engineers, decision makers sustainability manage natural resources regions.