Short-term forecasting of daily reference evapotranspiration using the Hargreaves–Samani model and temperature forecasts

Yufeng Luo, Xiaomin Chang, Shizhang Peng, Shahbaz Khan, Weiguang Wang, Qiang Zheng and Xueliang Cai

Agricultural Water Management, 2014, vol. 136, issue C, 42-51

Abstract: Accurate daily reference evapotranspiration (ET0) forecasting is necessary for real-time irrigation forecasting. We proposed a method for short-term forecasting of ET0 using the locally calibrated Hargreaves–Samani model and temperature forecasts. Daily meteorological data from four stations in China for the period 2001–2013 were collected to calibrate and validate the Hargreaves–Samani (HS) model against the Penman–Monteith (PM) model, and the temperature forecasts for a 7-day horizon in 2012–2013 were collected and entered into the calibrated HS model to forecast the ET0. The proposed method was tested through comparisons between ET0 forecasts and ET0 calculated from observed meteorological data and the PM model. The correlation coefficients between observed and forecasted temperatures for all stations were all greater than 0.94, and the accuracy of the minimum temperature forecast (error within ±2°C) ranged from 60.48% to 76.29% and the accuracy of the maximum temperature forecast ranged from 50.18% to 62.94%. The accuracy of the ET0 forecast (error within ±1.5mmday−1) ranged from 77.43% to 90.81%, the average values of the mean absolute error ranged from 0.64 to 1.02mmday−1, the average values of the root mean square error ranged from 0.87 to 1.36mmday−1, and the average values of the correlation coefficient ranged from 0.64 to 0.86. The sources of errors were the error in the temperature forecasts and the fact that the effects of wind speed and relative humidity were not considered in the HS model. The applications illustrated that the proposed method could provide daily ET0 forecasts with a certain degree of accuracy for real-time irrigation forecasts.

Keywords: Reference evapotranspiration; Irrigation forecast; Observed meteorological data; Weather forecast data; Irrigation scheduling (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378377414000225
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:agiwat:v:136:y:2014:i:c:p:42-51

DOI: 10.1016/j.agwat.2014.01.006

Access Statistics for this article

Agricultural Water Management is currently edited by B.E. Clothier, W. Dierickx, J. Oster and D. Wichelns

More articles in Agricultural Water Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().