Abstract
Forecasting of pan evaporation is important for management of water resources. Evaporation process is highly nonlinear and complex. Hydrologists therefore try another technique in place of traditional deterministic and conceptual models to forecast pan evaporation with relative simplicity and accuracy. The present work uses genetic programming (GP) and model tree (MT) to forecast pan evaporation one day ahead at Pali in the Raigad district of Maharashtra, India. Daily minimum and maximum humidity, minimum and maximum temperature, wind speed, pan water temperature, and sunshine were the seven input parameters. Both models performed well for 2 years data with accuracy of prediction. Excellence of GP model is proved with correlation coefficient between GP forecasted and observed pan evaporation (r = 0.97), least error (MSRE = 0.012 mm/day), and high index of agreement (d = 0.98). These models can be useful for hydrologists and farm water managers.
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Chaudhari, N.D., Chaudhari, N.N. (2016). One Day Ahead Forecast of Pan Evaporation at Pali Using Genetic Programming. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 436. Springer, Singapore. https://doi.org/10.1007/978-981-10-0448-3_10
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DOI: https://doi.org/10.1007/978-981-10-0448-3_10
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