Forecasting reference evapotranspiration

The ability to forecast reference evapotranspiration (ETo) accurately will greatly enhance our capability to manage the irrigation of high-frequency irrigation systems and shallow-rooted crops. If weather data are accurately forecast from synoptic and mesoscale models, then ETo forecasts are likely to be more accurate than statistical models. In addition, accurate ETo forecasts can eliminate or reduce the size of automated weather networks that are currently used to provide near-real time ETo data for irrigation scheduling. This will reduce costs and provide ETo data in a more timely fashion. In this paper, the inclusion of ETo in an existing mesoscale weather forecast model is presented. The mesoscale model inputs data from a synoptic forecast provided by the US National Weather Service and predicts hourly weather variables for up to 72 hours for any location in California. ETo was calculated from solar irradiance, temperature, humidity, and wind speed using a modified Penman-Monteith equation. Hourly ETo forecasts for six locations in California were compared with ETo values calculated using weather data from the California Irrigation Management Information System. The effect of each weather variable on forecast ETo accuracy was also investigated. The forecast underestimated observed ETo by 2 to 10 %. The slope and the root mean square error were nearly the same at each prediction time. Solar irradiance seems to be the main variable affecting the ETo forecast.