Abstract
The present study proposes a simple wavelet regression (WR) approach for modeling reference evapotranspiration (ET0). The WR model was improved combining two methods: discrete wavelet transform (DWT) and a linear regression model. The accuracy of the WR models was compared with that of the single linear regression (LR) models. The daily climatic data from three stations in central California are used as inputs to the WR models to estimate ET0 obtained using the FAO-56 Penman–Monteith equation. The comparison of these results revealed that the WR models could increase the forecast accuracy of the LR models. A comparison is also made between the estimates provided by the WR models and those of the following empirical models: CIMIS Penman, Hargreaves, Ritchie and Turc. Based on a comparison of these results, the WR models were found to perform better than the empirical models in daily ET0 modeling.
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