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Open AccessArticle

Predicting Crop Evapotranspiration by Integrating Ground and Remote Sensors with Air Temperature Forecasts

1
Department of Civil Engineering, University of Salerno, 84084 Fisciano, Italy
2
Interdepartmental Research Centre on the "Earth Critical Zone" (CRISP) of the University of Naples Federico II, 80055 Portici, Italy
3
Ariespace s.r.l., 80143 Naples, Italy
4
Department of Agricultural Sciences, University of Naples Federico II, 80055 Portici, Italy
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in: Pelosi, A; Chirico, G.B.; Falanga Bolognesi, S.; De 13 Michele, C.; D’Urso, G. Forecasting crop evapotranspiration under standard conditions in precision farming. 14 In Proceedings of IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), 15 Portici, Italy, 24–26 October 2019.
Sensors 2020, 20(6), 1740; https://doi.org/10.3390/s20061740
Received: 18 February 2020 / Revised: 11 March 2020 / Accepted: 19 March 2020 / Published: 20 March 2020
(This article belongs to the Special Issue Metrology for Agriculture and Forestry 2019)
Water use efficiency in agriculture can be improved by implementing advisory systems that support on-farm irrigation scheduling, with reliable forecasts of the actual crop water requirements, where crop evapotranspiration (ETc) is the main component. The development of such advisory systems is highly dependent upon the availability of timely updated crop canopy parameters and weather forecasts several days in advance, at low operational costs. This study presents a methodology for forecasting ETc, based on crop parameters retrieved from multispectral images, data from ground weather sensors, and air temperature forecasts. Crop multispectral images are freely provided by recent satellite missions, with high spatial and temporal resolutions. Meteorological services broadcast air temperature forecasts with lead times of several days, at no subscription costs, and with high accuracy. The performance of the proposed methodology was applied at 18 sites of the Campania region in Italy, by exploiting the data of intensive field campaigns in the years 2014–2015. ETc measurements were forecast with a median bias of 0.2 mm, and a median root mean square error (RMSE) of 0.75 mm at the first day of forecast. At the 5th day of accumulated forecast, the median bias and RMSE become 1 mm and 2.75 mm, respectively. The forecast performances were proved to be as accurate and as precise as those provided with a complete set of forecasted weather variables. View Full-Text
Keywords: crop evapotranspiration; remote sensing; numerical weather forecasts; Hargreaves–Samani equation; Penman–Monteith equation; irrigation advisory systems crop evapotranspiration; remote sensing; numerical weather forecasts; Hargreaves–Samani equation; Penman–Monteith equation; irrigation advisory systems
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MDPI and ACS Style

Pelosi, A.; Villani, P.; Falanga Bolognesi, S.; Chirico, G.B.; D’Urso, G. Predicting Crop Evapotranspiration by Integrating Ground and Remote Sensors with Air Temperature Forecasts. Sensors 2020, 20, 1740. https://doi.org/10.3390/s20061740

AMA Style

Pelosi A, Villani P, Falanga Bolognesi S, Chirico GB, D’Urso G. Predicting Crop Evapotranspiration by Integrating Ground and Remote Sensors with Air Temperature Forecasts. Sensors. 2020; 20(6):1740. https://doi.org/10.3390/s20061740

Chicago/Turabian Style

Pelosi, Anna; Villani, Paolo; Falanga Bolognesi, Salvatore; Chirico, Giovanni B.; D’Urso, Guido. 2020. "Predicting Crop Evapotranspiration by Integrating Ground and Remote Sensors with Air Temperature Forecasts" Sensors 20, no. 6: 1740. https://doi.org/10.3390/s20061740

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