Field study and regression modeling on soil water distribution with mulching and surface or subsurface drip irrigation systems

Abstract

The soil water status was investigated under soil surface mulching techniques and two drip line depths from the soil surface (DL). These techniques were black plastic film (BPF), palm tree waste (PTW), and no mulching (NM) as the control treatment. The DL were 15 cm and 25 cm, with surface drip irrigation used as the control. The results indicated that both the BPF and PTW mulching enhanced the soil water retention capacity and there was about 6% water saving in subsurface drip irrigation, compared with NM. Furthermore, the water savings at a DL of 25 cm were lower (15-20 mm) than those at a DL of 15 cm (19-24 mm), whereas surface drip irrigation consumed more water. The distribution of soil water content (θv) for BPF and PTW were more useful than for NM. Hence, mulching the soil with PTW is recommended due to the lower costs and using a DL of 15 cm. The θv values were derived using multiple linear regression (MLR) and multiple nonlinear regression (MNLR) models. Multiple regression analysis revealed the superiority of the MLR over the MNLR model, which in the training and testing processes had coefficients of correlation of 0.86 and 0.88, root mean square errors of 0.37 and 0.35, and indices of agreement of 0.99 and 0.93, respectively, over the MNLR model. Moreover, DL and spacing from the drip line had a significant effect on the estimation of θv.