JWSS - Journal of Water and Soil Science

Increasing crop production per unit volume of water consumption requires recognizing the most dependent variable in drip irrigation to the volume of water consumption and also identifying the most important variables independent of water productivity in surface and subsurface drip irrigation for optimal use of available water resources. The present research was carried out in Behbahan Agricultural Research Station during four cropping seasons (2013-2017) on a Kabkab date variety. Experimental treatments include the amount of water in the subsurface drip irrigation method based on two levels of 75% and 100% water requirement and in surface drip irrigation based on 100% water demand. Data were analyzed using a randomized complete block design with three replications. The results of the analysis of variance of the mean of different irrigation treatments in quantitative traits showed that the effect of irrigation was significant at the level of 1% in terms of cluster weight index, fruit weight, and fruit flesh to kernel weight ratio. The results of regression analysis of variance showed that in the dependent variable of cluster weight, the consumption water volume explained 19.1% (R2 = 0.191) of the fluctuations of the dependent variable (cluster weight). Among all the studied variables, the volume of water consumption explained the most significant changes in date cluster drying. Fruit moisture with t (2.096) and equivalent beta coefficient (0.046) had a significant positive effect on water productivity at the level of 5%. The results of the Pearson correlation coefficient showed that the effect of yield on changes in water productivity was much greater than the volume of water consumed so the yield caused significant changes in water productivity. While the effect of water consumption on water productivity was not significant.

The objective of the present study was to conduct field studies for direct measurement of canola under farmers' management in one crop season (2019-2020) in 27 farms in Behbahan, Khuzestan province. Water requirement was calculated based on the FAO Penman-Monteith model using the daily statistics of the Behbahan synoptic meteorological station. A T-test was used to statistically compare the results such as the depth of irrigation and applied water productivity in the field in different irrigation systems. Linear multivariate regression analysis was used to investigate the effects of the independent variable on the dependent parameter of water productivity. The volume of applied water in the fields ranged from 4085.5 to 7865.3 m³/ha. The results of comparing the average yield of two irrigation systems in the t-test showed that the two sprinkler and surface irrigation systems with yields of 2614 and 2330 kg/ha, respectively, were not significantly different. Applied water productivity in traditional and modern irrigation systems was calculated to be 0.386 and 0.486 kg/m³, respectively, which had significant differences. The results of the analysis of variance in the regression model showed that among the independent variables, yield with t-statistic (23.997) and equivalent beta coefficient (0.880) had the most significant positive effect at a 1% level on applied water productivity. After that, the volume of applied water (irrigation water + effective rainfall) with a t-statistic of (-11.702) and a beta coefficient of equivalent (-0.793) had the most negative and significant effect at the level of 1% on the applied water productivity. The results of the Pearson correlation coefficient showed that irrigation events had a positive and significant correlation at a 5% level with applied water and yield. These correlations were 0.455 and 0.380, respectively. By increasing irrigation events, the volume of applied water has practically decreased and has become as close as the plant needs, and has increased water productivity.