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Use of numerical weather forecast and time series models for predicting reference evapotranspiration

Arca, Bachisio and Duce, Pierpaolo and Snyder, Richard L. and Spano, Donatella Emma Ignazia and Fiori, Mario (2004) Use of numerical weather forecast and time series models for predicting reference evapotranspiration. In: 4th International Symposium on Irrigation of Horticultural Crops, 1-6 September 2003, Davis (CA), USA. Leuven, International Society for Horticultural Science. p. 39-46. (Acta Horticulturae, 664). ISBN 978-90-66053-66-3. Conference or Workshop Item.

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Providing forecast of water balance components such as precipitation, evapotranspiration, deep percolation and runoff is important for water management and irrigation scheduling. Reference evapotranspiration (ETo) prediction will greatly enhance our capability to manage high-frequency irrigation systems and shallow-rooted crops. Reference evapotranspiration can be calculated on daily or hourly basis using analytical models (Penman-Monteith, Penman, etc.) and meteorological forecasts from numerical weather prediction models. One can also use time series analysis of ETo and meteorological variables related to evapotranspiration process. For example, autoregressive integrated moving average (ARIMA) models and artificial neural networks (ANN) can be applied in time series modeling and forecasting. The main aims of this study were to analyze and compare the performance of the above-mentioned techniques in short-term prediction of hourly and daily ETo. Reference evapotranspiration rates were calculated using the hourly Penman-Monteith equation, weather data provided by the Agrometeorological Service of Sardinia, Italy (SAR), and weather forecasts from a limited area model (BOLAM2000). Both ARIMA and ANN models were developed using four years of hourly meteorological data from three meteorological stations of SAR. Models were validated using a two-year data set from the same locations. The accuracy of models was evaluated comparing the forecasts with ETo values calculated using observed weather data from SAR weather stations. The use of meteorological variables from numerical weather forecast gave better results than those obtained from ARIMA and ANN models. The Limited Area Model gave root mean squared difference values of the forecasted ETo smaller than 0.15 mm on a hourly basis and near 1.0 mm on a daily basis. However, the analysis showed a large scatter of calculated versus predicted ETo values, in particular for hourly values. The evaluation of the effect of weather forecast variables on forecast ETo accuracy showed that solar irradiance is the main parameter affecting ETo forecast.

Item Type:Conference or Workshop Item (Paper)
ID Code:5291
Uncontrolled Keywords:Penman-Monteith equation, solar radiation, limited area model, ARIMA models, artificial neural networks
Subjects:Area 07 - Scienze agrarie e veterinarie > AGR/03 Arboricoltura generale e coltivazioni arboree
Area 07 - Scienze agrarie e veterinarie > AGR/12 Patologia vegetale
Divisions:002 Altri enti e centri di ricerca del Nord Sardegna > CNR-Consiglio Nazionale delle Ricerche > Istituto di biometeorologia, Sassari
001 Università di Sassari > 01 Dipartimenti > Economia e sistemi arborei
001 Università di Sassari > 01 Dipartimenti > Protezione delle piante
Publisher:International Society for Horticultural Science
Deposited On:10 Jan 2011 15:37

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