Estimation of Surface Water Vapour Density and its Fluctuations with Climatic Variables at Owerri, Nigeria

*1Zakariya Abdullahi, 2Davidson Odafe Akpootu, 2Musa Momoh,
3Lawal Sa’ad, 1Yusuf Ibrahim Bawa, 4Tanko Sanusi Sununu, 5Ibrahim Nouhou, 2Sunday Bongde Yohanna, 2Emmanuel Oluwamayowa Agidi
and 6Abdullahi Yusuf

1Department of Physics, Adamu Augie College of Education Argungu Kebbi State
2Deapartment of Physics, Usmanu Danfodiyo University Sokoto, Nigeria
3Department of Physics, Federal University Gusau
4Department of Physics, Kebbi State University of Science and Technology Aleru
5Dėpartment de Physique, Facultė des Sciences et Techniques (FST), Universitė Dan Dicko Dankoulodo, Maradi Rėpublique du Niger
6Department of Science Education, Ibrahim Badamasi Babangida University, Lapai, Nigeria

*Corresponding author’s Email:,


Water vapour is the common term used to describe the hydrological cycle’s connection between the surface and the atmosphere. Almost all of the water vapour in the atmosphere is derived from the earth’s surface, where sunlight causes water to evaporate from the ocean and continents. Plants and animals then transpire and respire this water vapour into the sky. This study looked at the relationships between monthly variations in Surface Water Vapour Density (SWVD) and various meteorological parameters for Owerri. The data were collected over a thirty-eight￾year period (1979–2016). The study looked at the daily fluctuation in SWVD for the two different seasons in 2014, taking into account two typical months in each. The findings demonstrated variations in the SWVD on a daily basis during the duration of the study. The highest recorded SWVD value throughout the investigation period was 22.7604 gm-3 on May 28, 2014, while the lowest recorded value was 9.6567 gm-3 on December 26, 2014. Three simple two variable correlation models were developed to estimate SWVD, and were statistically tested and compared using the statistical indices of coefficient of determination (R2), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), Nash-Sutcliffe  equation (NSE), and index of agreement (IA) to deduce which of the three SWVD –based models is most suitable to estimate SWVD. After comparing the three simple two-variable correlation models, it was determined that the model that relates pressure and precipitable water vapour was the most appropriate for estimating SWVD. The results in this study will help hydro-meteorologist to know the amount of SWVD in the atmosphere for Owerri.


Statistical Indices,