1College of Technology, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand
2Department of Horticulture, J. V. College, Baraut, Baghpat, (U. P)
*Corresponding author email, sushmatamta91@gmail.com
Online published on 4 September, 2020.
Evaporation is a process by which liquid is converted into vapor. Evaporation is important element of the hydrological cycle. Because of increasing temperature of earth surface, evaporation is also increasing. Increased evaporation cause reduces the water availability in the earth surface. In this regard, understanding of hydrological cycle play an important role to conserve the water. Evaporation is very important component of the hydrological cycle. Evaporation can occur only when water is available. It also requires that the humidity of the atmosphere is less than the evaporating surface (at 100% relative humidity there is no more evaporation). It plays an important role for planning and management of water resources projects, necessary for scheduling of irrigation and in planning farm irrigation systems. Different methods have to be used to estimate evaporation, but for estimating the evaporation firstly we should have to knowledge about which parameters are more responsible for creating evaporation. So in this study we used different combinations of parameters to find out which combination is mostly influenced the evaporation using R software. The data set consisted daily records of four years from 2010 to 2013 and the data set consisted of these parameters, temperature, relative humidity, wind speed, sunshine hour and evaporation. In R software we used simple linear regression and multiple linear regression models to find out the most appropriate combination for estimating the evaporation.In this study different combinations of parameters with E such as Temperature (T), Sunshine hour(S), Wind speed (W), Relative humidity (R), T+R, T+S, T+W, R+S, R+W, S+W, T+R+S, T+R+W, R+S+W, T+S+W and T+R+S+W have been used. Besides all these combinations, T+S+R+W gave best results using R software. In this combination R2 is 0.812 which is highest than other combinationswith highly significant value of p. So for the best estimation of evaporation we should be used T+S+W+R combination.
Correlation coefficient, Multiple linear regressions, R software, R2, P value