EXPERIMENTAL STUDY TO ANALYSE COMPENSATD ROOT WATER UPTAKE

Abstract

Many industries, including irrigation engineering, ground water hydrology, and environmental engineering, require an understanding of moisture transport through the unsaturated root zone of soils. Water flow through the root zone is generally calculated using Richards equation plus a sink factor to account for root water uptake (RWU). The constitutive relationships between moisture content, hydraulic conductivity, and pressure head are required for the solution of Richards equation. The soil hydraulic qualities, such as saturated hydraulic conductivity and water retention parameters, are the primary determinants of these constitutive relationships. The quantity of RWU depends on root density and soil water availability (Molz and Remson 1970; Feddes 1982). Studies (Leib et al. 2006, Šimůnek and Hopmans 2009) show that the lower uptake in the water stressed part is compensated by higher uptake from the zone where water is easily available. Modelling root water uptake process in the vadose zone is done either by using the microscopic or macroscopic approach. Models based on microscopic approach consider water uptake by every single root (Doussan 1998; Javaux et al. 2008). Microscopic modeling requires a detailed investigation of the spatial distribution of roots and their properties. The macroscopic approach is much simpler and effective in representing the RWU process. A sink term is considered in Richards equation for the RWU. The simulation of RWU requires information about root density distribution, root hydraulic properties, soil water availability and soil salinity. The RWU parameters can be estimated through inverse modeling of root zone soil moisture dynamics (Hupet et al. 2003; Shankar et al. 2012; Sonkar et al. 2018 ; Vrugt et al. 2001) using soil moisture information. Ojha and Rai (1996) introduced the nonlinear RWU parameter β representing root water extraction pattern whose value varies with different crops and can be obtained through inverse modeling. Shankar et al. (2012) developed empirical formulae for determining β from maximum daily transpiration, rooting depth and time to reach peak transpiration. Vrugt et al. (2001) simultaneously estimated the RWU model parameter and soil hydraulic parameter through inverse modeling using observed root zone soil moisture data. Hupet (2002) showed that there is uncertainty in the estimation of RWU parameter especially when soil hydraulic parameters are not known well. The inverse procedure for RWU and soil parameter estimation mainly involves prediction of soil moisture resulting from root zone soil water flow dynamics. The simulated soil moisture data are compared with observed data with the objective of minimizing the difference between them. However, the inverse approach was found to be ill posed in case of estimating these parameters for fine soils (Hupet et al. 2003). This is due to major flow of water in vertical direction, which overshadows RWU, thus making RWU insensitive to soil moisture dynamics in the root zone.