Evaluation of the Hargreaves-Samani Method for Estimating Reference Evapotranspiration with Ground and Gridded Weather Data Sources
2019
De S. Notia Junior, Rogerio | Fraisse, Clyde William | Cerbaro, Vinicius Andrei | Karrei, Mauricio Alex Z. | Guindin, Noemi
Methods of estimating evapotranspiration require weather variables as their main input data. Thus, the lack of full weather data sets is one of the main challenges for evaluating and mitigating the effects of climate variability and climate change on agricultural production systems. The Hargreaves-Samani method (HS) is one of the ways to estimate reference evapotranspiration (ETo) when only temperature observations are available, which is a common situation in many agricultural enterprises. Another possible option for regions not served by weather stations is the use of gridded weather data (GWD). Based on that, the main objective of this study was to evaluate the performance of the HS method to estimate ETo in different regions of the United States, as well as to assess the suitability of two gridded weather data (PRISM and NOAA-RTMA) sources to estimate ETo by comparing the results obtained to ETo estimated by the Penman-Monteith (FAO-PM) method, which is the recommended methodology by FAO Irrigation and Drainage Paper 56 when all weather variables are available. Weather observations were obtained for 17 locations across the United States representing regions with subtropical humid and semi-arid continental climates, considering the period of one year (2017). These observations were used to estimate daily ETo with the HS and Penman-Monteith methods. Our results demonstrated that the HS method performance varied according to the location and month of the year. Due to the high relative humidity (RH) during the winter, and high air temperature (Ta) during the summer, the locations selected in the state of Florida, presented the worst performance. The HS method performed well in many other locations such as Froid – MT. Also, the estimation of ETo by HS method and by using PRISM and NOAA-RTMA gridded weather databases showed a good agreement with the ETo estimated by FAO-PM based on weather station observations.
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