Statistical Study of Infiltration Parameters Variations of Kostiakov-Lewis Equation in Furrow Irrigation During Three Farming Seasons

Soil and biological factors can be extremely variable in place and time. Therefore, differences in soil water infiltration both in place and time is expected. Due to temporal variability of infiltration parameter, its direct estimation requires lots of time and sampling. Hence, empirical and physical equations exist for quantification of infiltration process in surface irrigation. Plenty methods are available for estimating infiltration equations parameters, which are different, depending on estimated data in the field. Selecting proper method depends on the available field data for estimating infiltration parameters. Some random parameters occur in different parts of the field that cause variations in the soil water infiltration. Considering infiltration spatial variations in irrigation increases accuracy in estimating infiltrated water volume and distribution uniformity. Therefore, in the current study it is attempted to survey variations of soil water infiltration parameters in furrow irrigation during three farming seasons.
Current study was carried out using collected data during the farming seasons 2011, 2012 and 2013 from a field located in Meshkindasht area of Karaj. Type of the crop was maize and the field had a loamy soil. At the each of the farming seasons, 8 separate experiments were implemented that each one was comprised of 4 furrows with the length of 120 meters and width of 75 centimeters. At the each of the farming seasons, 15 irrigation events were done. 8 experiments were implemented at relatively identical sites during three farming seasons. At the each of the irrigation events, type 3 WSC flumes were used for measuring the inflow and outflow of the furrows. In this study, Kostiakov-Lewis infiltration equation was used. For each irrigation, a and k parameters of Kostiakov-Lewis equation were calculated using volume-balance method in Excel software. In this method using furrow inflow and outflow hydrographs, basic infiltration rate was calculated. Means of spatial and temporal variations of the Kostiakov-Lewis equation parameters in three farming seasons were compared using Duncan’s Multiple Range Test using SPSS software.
Data were subjected to composite analysis of variance using General Linear Model by SPSS software. Effects of experiment number (spatial variations) and irrigation event (temporal variations) on variations of k infiltration parameter were significant at %1 level; while, effect of farming season was significant at %5 level. Difference between the 8 experiments during three farming seasons was significant at %5 level. Effects of the three aforementioned sources of variation on alterations of a infiltration parameter were significant at %1 level. Effect of experiment number on the average of temporal variations of a infiltration parameter in three farming seasons, showed significant difference at %5 level among the 8 experiments. Effect of farming season on the average of spatial and temporal variations of a infiltration parameter indicated its significant superiority (0.6108) in the farming season 2011 compared to the rest of the seasons at %5 level. While, in the farming seasons 2012 and 2013 there were no significant differences between the averages of the mentioned variations.
In general, there were significant differences in three farming seasons in regard to the average variations of each of the a and k infiltration parameters and also among the 8 experiments regarding the mean variations of each of the mentioned parameters. Finally, taking significant differences of the average spatial and temporal variations of a and k infiltration parameter into consideration, seasonal variations of soil water infiltration parameters in the three farming seasons were not negligible. Based on the results of the current investigation, a and k infiltration parameters of the Kostiakov-Lewis equation, showed erratic and unpredictable variations, spatially and temporally in different farming seasons.