Mathematical Modelling of Evapotranspiration in Humid Semi-hot Equatorial Coastal Climate

The performances of five empirical models, namely: Hargreaves-Samani, Makkink [1], Makkink [2],
Priestley-Taylor and FAO 56-PM in estimating reference evapotranspiration (REF-ET) were
separately compared with Epan data and FAO 56-PM, respectively. The predictive perBased on
statistical analysis, Hargreaves-Samani method compared best with daily and monthly Epan data,
while Makkik2 (1984) ranked first with FAO 56-PM. In terms of regression analysis, Priestley-Taylor
performed best with daily FAO 56-PM method while Hargreaves-Samani ranked first with daily Epan
data. Hargreaves-Samani also correlated best with mean monthly Epan data. The quantitative
evaluation of cumulative daily and monthly reference-evapotranspiration (RET-ET) values showed
that Makkink [2] produced the least overestimation and percent relative error against FAO 56-PM
while Hargreaves-Samani performed best with Epan data with the least overestimation and percent
relative error. In terms of cumulative monthly ETo totals for the farming season (Dec-April) over the
study period, Hargreaves-Samani ranked best with Epan data with the least overestimation and
percent relative error while Priestley–Taylor ranked best with FAO 56-PM producing the least
overestimation. Overall, Hargreaves-Samani with its original coefficient was adjudged best, capable of
approximating FAO 56-PM and Epan data in the Lower Niger River Basin, followed by Makkink [2]
and Priestley-Taylor. Penman-Monteith estimates were used to develop monthly correction factors for
adjusting Empirical models for their potential use in Lower Niger Basin. A comparative study such as
this has not been undertaken in the Lower Niger River Basin. The models recommended in this study
are economical, lesser-data demanding and can be applied to predicting REF-ET in remote
agricultural areas. In other to create more computational skill in the subject matter a number of
illustrative example problems are presented in Appendixes B and C, manually solved for easy
comprehension.