Estimation of Evapotranspiration with Fao-56 penman-monteith Equation for three Agroecological zones of Nigeria
Abstract
The Food and Agriculture Organisation (FAO) irrigation and drainage Paper 56 recommends the use of Penman-Monteith (PM) method for calculating reference evapotranspiration (ETo). This method has been widely accepted. Alternative methods recommended where data requirements for the PM cannot be met are Hargreaves (HG) and pan methods. Therefore, this study was carried out to evaluate ETo with the PM method and develop its relationship with HG and pan methods for Onne (humid), Ibadan (sub-humid) and Kano (semi-arid), Nigeria using 1990-2005 daily climatic data. The data were resolved to daily means of each week of the year, and monthly and annual totals. Deviations of the data from long-term means were determined and the ETo methods were compared using root mean square error (RMSE) and mean bias error (MBE). Autocorrelation coefficients and regression analysis were also carried out. The daily means for each week with PM ETo ranged from 2.39-3.82 mm in Onne, 2.45-4.48 mm in Ibadan and 3.62-7.92 mm in Kano. Mean annual PM ETo was 1130 mm vs. 2450 mm of rainfall in Onne; 1249 mm in Ibadan vs. 1286 mm of rainfall and 2007 mm in Kano vs. 786 mm of rainfall. The HG method over-predicted PM ETo in Onne and Ibadan and under-predicted it in Kano. The pan method under-predicted it in Onne and Ibadan. Nonetheless, the HG method was a better estimator of PM ETo in Kano than Onne and Ibadan, although daily means in the dry season were more variable. Daily means of PM ETo were significantly related to means HG ETo (P < 0.0001, r2 from 0.72-0.93) and pan ETo (P < 0.0001, r2 from 0.91-0.93). Autocorrelation lengths of annual ETo ranged from 2-2.8 years, suggesting a period of about 3 years of temporal dependence. The study showed that apart from the differences in magnitude of ETo, trends of PM, HG and pan methods were similar, particularly for daily means and monthly totals. Therefore, the regression equations developed in this study can be used to estimate PM ETo for similar climatic zones where the data requirements cannot be met but data for HG or pan method are available.
References
Analytical Software. 1998. STATISTIX for windows Version 2. Tallahassee, Florida.
Chineke, T. C., Jagtap, S. S., Aina, J. I. 1999. Applicability of a weather simulation model based on observed daily meteorological data in humid tropical climate. Theor. Appl. Climatol. 64: 15-25.
Droogers, P., Allen, R. G. 2002. Estimating reference evapotranspiration under inaccurate data conditions. Irrig. Drain. Syst. 16: 33-45.
Hess, T. M. 1998. Trends in reference evapotranspiration in the North East arid zone in Nigeria, 1961-1990. J. Arid Environ. 38: 99-115.
Hillel, D. 1998. Environmental soil physics. Elsevier Academic press, California.
Hsiao T., P. Steduto, E. Fereres. 2007. A systematic and quantitative approach to improve water use
efficiency in agriculture. Irrig. Sci. 25: 209-231.
Kirkham, M. B. 2005. Principles of soil and plant water relations. Elsevier Academic Press, MA.
Lawes Agricultural Trust. 2005. GenStat for Windows, Release 4.2. GenStat Discovery edition 2. Rothamsted Experimental Station.
Nielsen, D. R., Wendroth, O. 2003. Spatial and temporal statistics: Sampling field soils and their vegetation. Catena Verlag GMBH, Reiskirchen.
Oluwasemire, K. O., C. J. Stigter, Owonubi, J. J. S. S. Jagtap. 2002. Seasonal water use and water productivity of millet-based cropping systems in the Nigerian Sudan savanna near Kano. Agric. Water. Manage. 56: 207-227.
Paltineanu.,C., Mihailscu, I. E. Seceleanu, I. Dragota, C., Vasenciuc, F. 2007. Using aridity indices to describe some climate and soil features in Eastern Europe: a Romanian case study. Theor. Appl. Climatol. (DOI 10.1007/s00704-007-0295-3).
Paturel, J. E., Servat,E. Kouamé, B. Lubès, H. Ouedraogo,M. Mason J. M. 1997. Climatic variability in humid Africa along the Gulf of Guinea Part II: an integrated regional approach. J. Hydrol. 191: 16-36.
Rockström, J., Barron J. 2007. Water productivity in rainfed systems: overview of challenges and analysis of opportunities in water scarcity prone savannahs. Irrig. Sci. 25: 299-311.
Servat, E., Paturel J. E., Lubès, H. Kouamé, B. Ouedraogo, M. Masson, J. M. 1997. Climatic variability in humid Africa along the Gulf of Guinea Part I: detailed analysis of the phenomenon in Côte d’Ivoire. J. Hydrol. 191:1-15.
Stöckle, C. O., Kjelgaard,J. Bellochi. G. 2004. Evaluation of estimated weather data for calculating Penman-Monteith reference crop evapotranspiration. Irrig. Sci. 23: 39-46.
Yu, P., Yang, T., Chou, C. 2002. Effects of climate change on evapotranspiration from paddy fields in southern Taiwan. Climatic Change 54: 165-179.
