2,963
Views
70
CrossRef citations to date
0
Altmetric
Articles

Study of different climatic conditions to assess the role of solar radiation in reference crop evapotranspiration equations

Pages 679-694 | Received 11 May 2014, Accepted 01 Jul 2014, Published online: 22 Jul 2014
 

Abstract

This study aims to assess radiation-based models versus the FAO Penman–Monteith (FPM) model to determine the best model using linear regression under different weather conditions. The reference evapotranspiration was estimated using 22 radiation-based methods and was compared with the FPM. The results showed that the Stephens method estimates the reference evapotranspiration better than other methods in the most provinces of Iran (nine provinces). However, the values of R2 were more than 0.9930 for 24 provinces of Iran. The radiation-based methods estimated the reference evapotranspiration near the Caspian Sea better than other regions. The most precise methods were the Berengena–Gavilan, Modified Priestley–Taylor, and Priestley–Taylor methods for the provinces ES (center of Iran), GI and GO (north of Iran) and the Stephens–Stewart method for IL (west of Iran). Finally, a list of the best performance of each method has been presented to use other regions and next research steps according to the values of mean, maximum, and minimum temperature, relative humidity, solar radiation, elevation, sunshine, and wind speed. The best weather conditions to use radiation-based equations are 23.6–24.6 MJ m−2 day−1, 12–20°C, 18–24°C, 5–13°C, and <180 hour month−1 for solar radiation, mean, maximum, and minimum temperature, and sunshine, respectively.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access
  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart
* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.