The Comparative Accuracy Evaluation of Water Evaporation using Multiple Linear Regression and Simplified Penman's Equation.
Keywords:
Evaporation, Multiple Linear Regression, Simplified Penman's Equation, Accuracy EvaluationAbstract
Accurately estimation of water evaporation is very difficult due to the complex relation between land, atmosphere and water surface conditions. Therefore, many researchers have improved the Penman’s prediction equation and develop the statistically regression model of meteorology data that giving simple and non-complex water evaporation equation. This research uses data from the last 15 years of Nakhon Ratchasima Province consisting of the maximum and minimum temperatures, maximum and minimum relative humidity, wind speed, sunshine hours and evaporation values. The collected data was categorized into 6 models and then analyzed by Multiple Linear Regression (MLR) method. The MLR analysis result shown Model 1 had the highest Coefficient of Determination of 83.6% (4 variables, 5 years data set), which presented the water evaporation are consecutively related to wind speed, mean temperature, sunshine hours and average relative humidity. Additionally, model’s error calculation using the Absolute Mean Deviation (MAD), Mean Square Error (MSE) and Mean Absolute Precent Error (MAPE) were performed for inspective comparation of the MLR models and the Simplified Penman's Equation (SPE). Ten months of most recent evaporation data were used and resulted that MLR Model 2 (4 variables, 10 years data set) had the least errors as MAD = 0.41, MSE = 0.29, and MAPE = 7.9. Therefore, the appropriate equation for predicting the water evaporation should consider both the errors and the Coefficient of Determination.
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