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Short-term forecasting of daily reference evapotranspiration using the reduced-set Penman-Monteith model and public weather forecasts

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  • Yang, Yang
  • Cui, Yuanlai
  • Bai, Kaihua
  • Luo, Tongyuan
  • Dai, Junfeng
  • Wang, Weiguang
  • Luo, Yufeng

Abstract

Farm irrigation management and real-time irrigation decisions are based on a series of parameters including irrigation water demand predictions which estimated by the short-term daily reference evapotranspiration (ETo). Based on the temperature data, a simplest empirical model called the temperature-based method, was developed to forecast near-future ETo. Although temperature is one of the most influential weather variables in ETo forecasting, wind velocity also has non-ignorable impact on the forecast performance of ETo. Therefore, we employed the Reduced-set Penman-Monteith (RPM) model for short-term ETo forecasting using temperature data derived from public weather forecasts and wind speed data. Four different types of wind speed data were adopted as model inputs, including wind speed assumed as a default value, i.e., u2 = 2.0 m s−1 (W1), forecasted wind speed (W2), long-term daily average wind speed (W3) and annual average wind speed (W4). Based on the above-mentioned wind speed inputs, we presented four types of RPM models (RC, RF, RD and RM models respectively corresponding to W1, W2, W3 and W4) to forecast daily ETo for lead times up to 7 days for eight weather stations in China. The results confirmed that the highest precision wind speed input was W3, followed by W4, W1 and W2, and the most accurate ETo forecasts of four RPM models was provided by RC, followed with RD, RM and RF. By comparing with one of the most common used temperature-based models, the Hargreaves-Samani (HS), it was found that the performance of RPM approaches were better than that of HS model for arid and sub-arid regions whereas opposite results were found in sub-tropical area, suggesting inclusion of wind speed parameter makes positive impact on ETo forecast for arid and semi-arid regions. Further, it was found that the greatest type of RPM model, the RC model, was superior to HS method for most climate regions, including arid, humid, sub-arid and sub-humid areas, thus, the W1 wind speed type could be highly recommended for ETo forecasting for most climate regions.

Suggested Citation

  • Yang, Yang & Cui, Yuanlai & Bai, Kaihua & Luo, Tongyuan & Dai, Junfeng & Wang, Weiguang & Luo, Yufeng, 2019. "Short-term forecasting of daily reference evapotranspiration using the reduced-set Penman-Monteith model and public weather forecasts," Agricultural Water Management, Elsevier, vol. 211(C), pages 70-80.
    • Handle: RePEc:eee:agiwat:v:211:y:2019:i:c:p:70-80
    DOI: 10.1016/j.agwat.2018.09.036
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    1. Lopez-Urrea, R. & Olalla, F. Martin de Santa & Fabeiro, C. & Moratalla, A., 2006. "An evaluation of two hourly reference evapotranspiration equations for semiarid conditions," Agricultural Water Management, Elsevier, vol. 86(3), pages 277-282, December.
    2. Gavilan, Pedro & Berengena, Joaquin & Allen, Richard G., 2007. "Measuring versus estimating net radiation and soil heat flux: Impact on Penman-Monteith reference ET estimates in semiarid regions," Agricultural Water Management, Elsevier, vol. 89(3), pages 275-286, May.
    3. Payero, José O. & Irmak, Suat, 2013. "Daily energy fluxes, evapotranspiration and crop coefficient of soybean," Agricultural Water Management, Elsevier, vol. 129(C), pages 31-43.
    4. Martinez-Cob, A. & Tejero-Juste, M., 2004. "A wind-based qualitative calibration of the Hargreaves ET0 estimation equation in semiarid regions," Agricultural Water Management, Elsevier, vol. 64(3), pages 251-264, February.
    5. Yang, Yang & Cui, Yuanlai & Luo, Yufeng & Lyu, Xinwei & Traore, Seydou & Khan, Shahbaz & Wang, Weiguang, 2016. "Short-term forecasting of daily reference evapotranspiration using the Penman-Monteith model and public weather forecasts," Agricultural Water Management, Elsevier, vol. 177(C), pages 329-339.
    6. Luo, Yufeng & Chang, Xiaomin & Peng, Shizhang & Khan, Shahbaz & Wang, Weiguang & Zheng, Qiang & Cai, Xueliang, 2014. "Short-term forecasting of daily reference evapotranspiration using the Hargreaves–Samani model and temperature forecasts," Agricultural Water Management, Elsevier, vol. 136(C), pages 42-51.
    7. Gavilán, P. & Castillo-Llanque, F., 2009. "Estimating reference evapotranspiration with atmometers in a semiarid environment," Agricultural Water Management, Elsevier, vol. 96(3), pages 465-472, March.
    8. Pelosi, A. & Medina, H. & Villani, P. & D’Urso, G. & Chirico, G.B., 2016. "Probabilistic forecasting of reference evapotranspiration with a limited area ensemble prediction system," Agricultural Water Management, Elsevier, vol. 178(C), pages 106-118.
    9. Yufeng Luo & Seydou Traore & Xinwei Lyu & Weiguang Wang & Ying Wang & Yongyu Xie & Xiyun Jiao & Guy Fipps, 2015. "Medium Range Daily Reference Evapotranspiration Forecasting by Using ANN and Public Weather Forecasts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3863-3876, August.
    10. Jabloun, M. & Sahli, A., 2008. "Evaluation of FAO-56 methodology for estimating reference evapotranspiration using limited climatic data: Application to Tunisia," Agricultural Water Management, Elsevier, vol. 95(6), pages 707-715, June.
    11. Tomas-Burguera, Miquel & Vicente-Serrano, Sergio M. & Grimalt, Miquel & Beguería, Santiago, 2017. "Accuracy of reference evapotranspiration (ETo) estimates under data scarcity scenarios in the Iberian Peninsula," Agricultural Water Management, Elsevier, vol. 182(C), pages 103-116.
    12. Ali Rahimikhoob & Mohsen Hosseinzadeh, 2014. "Assessment of Blaney-Criddle Equation for Calculating Reference Evapotranspiration with NOAA/AVHRR Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 3365-3375, August.
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