Skip Navigation Links.
Collapse <span class="m110 colortj mt20 fontw700">Volume 12 (2024)</span>Volume 12 (2024)
Collapse <span class="m110 colortj mt20 fontw700">Volume 11 (2023)</span>Volume 11 (2023)
Collapse <span class="m110 colortj mt20 fontw700">Volume 10 (2022)</span>Volume 10 (2022)
Collapse <span class="m110 colortj mt20 fontw700">Volume 9 (2021)</span>Volume 9 (2021)
Collapse <span class="m110 colortj mt20 fontw700">Volume 8 (2020)</span>Volume 8 (2020)
Collapse <span class="m110 colortj mt20 fontw700">Volume 7 (2019)</span>Volume 7 (2019)
Collapse <span class="m110 colortj mt20 fontw700">Volume 6 (2018)</span>Volume 6 (2018)
Collapse <span class="m110 colortj mt20 fontw700">Volume 5 (2017)</span>Volume 5 (2017)
Collapse <span class="m110 colortj mt20 fontw700">Volume 4 (2016)</span>Volume 4 (2016)
Collapse <span class="m110 colortj mt20 fontw700">Volume 3 (2015)</span>Volume 3 (2015)
Collapse <span class="m110 colortj mt20 fontw700">Volume 2 (2014)</span>Volume 2 (2014)
Collapse <span class="m110 colortj mt20 fontw700">Volume 1 (2013)</span>Volume 1 (2013)
American Journal of Water Resources. 2018, 6(6), 217-223
DOI: 10.12691/AJWR-6-6-2
Original Research

Impact of Alternative Data on the Penman-Monteith Method Considering Windy Conditions in the Semi-Arid Area

Homayoon Ganji1, and Takamitsu Kajisa1

1Graduate School of Bioresources, Mie University, 514-8507 Kurimamachiya-Cho 1577, Tsu, Japan

Pub. Date: December 12, 2018

Cite this paper

Homayoon Ganji and Takamitsu Kajisa. Impact of Alternative Data on the Penman-Monteith Method Considering Windy Conditions in the Semi-Arid Area. American Journal of Water Resources. 2018; 6(6):217-223. doi: 10.12691/AJWR-6-6-2

Abstract

When real data are unavailable, the standard Penman-Monteith method for estimating reference evapotranspiration can be calculated using alternative input data: wind speed from a nearby station, the default global average wind speed, solar radiation based on temperature and vapour pressure based on the minimum temperature. These alternative data are recommended in FAO paper 56. In this study, we assessed the accuracy achieved when using these alternative data for reference evapotranspiration estimation in a semi-arid region characterised by a strong persistent wind speed. Western Afghanistan was selected as the study site, as it is exposed to strong winds over the 120-day period from June to September. Significant differences were found in the estimates produced using full data and those obtained using wind speed data from a nearby station, the default global average wind speed, and vapour pressure based on the minimum temperature. Root Mean Square Error (RMSE) was found 1.51 mm d-1, 1.27 mm d-1 and 1.07 mm d-1, respectively. Errors were especially significant on days with strong wind. The smallest RMSE of 0.36 mm d-1 was found when basing solar radiation on temperature. The assumption that the dew point temperature will be close to the minimum temperature was shown to be unreliable on days of strong wind.

Keywords

reference evapotranspiration, Penman-Monteith, alternative data, strong wind, semi-arid

Copyright

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

[1]  Alexandris S, Kerkides P, Liakatas A, “Daily reference evapotranspiration estimates by the “Copais” approach,” Agricultural Water Management, 82: 371-386. 2005.
 
[2]  Pereira AR, Pruitt WO, Adaptation of the Thornthwaite scheme for estimating daily reference evapotranspiration,” Agricultural Water Management, 66: 251-257. 2004.
 
[3]  Chiew FHS, Kamaladasa NN, Malano HM, McMahon TA, “Penman-Monteith, FAO-24 reference crop evapotranspiration and class-A pan data in Australia,” Agricultural Water Management, 28. 9-21.1995.
 
[4]  Gavilán P, Lorite, IJ, Tornero S, Berengena J, “Regional calibration of Hargreaves equation for estimating reference evapotranspiration in a semi-arid environment,” Agricultural Water Management, 81. 257-281. 2006.
 
[5]  Allen, Richard G., L.S. Pereira, D. Raes, and Smith M, “Crop Evapotranspiration: Guidelines for Computing Crop Requirements,” Irrigation and Drainage FAO Paper No. 56: 300. 1998.
 
[6]  Ganji H, Takamitsu K, Masaaki K, Ryoei I, Behroze Rostami, “Re-examining the validity of reference evapotranspiration estimation in Herat, Afghanistan,” International Journal of GEOMATE, 12 (30). 61-68. 2017.
 
[7]  Droogers P, Richard Allen G, “Estimating reference evapotranspiration under inaccurate data conditions,” Irrigation and Drainage Systems, 16 (1). 33-45. 2002.
 
[8]  Popova Z, Milena K, Luis SP, “Validation of the FAO methodology for computing ETo with limited data. application to South Bulgaria,” Irrigation and Drainage, 55 (2). 201-215. 2006.
 
[9]  Jabloun and Sahli, “Evaluation of FAO-56 methodology for estimating reference evapotranspiration using limited climatic data application to Tunisia,” Agricultural Water Management, 95. 707-715. 2008.
 
[10]  Cordova M, Galo Carrillo-Rojas, Patricio C, Bradford W, Rolando C, “Evaluation of the Penman-Monteith (FAO 56 PM) method for calculating reference evapotranspiration using limited data application to the wet Paramo of Ecuador,” Mountain Research and Development, 35 (3). 230-39. 2015.
 
[11]  Sentelhas PC, Terry JG, Eduardo AS, “Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada,” Agricultural Water Management, 97 (5). 635-44. 2010.