LAUSR

The improvement in soil and root parameterization is a key to enhance the root zone moisture depletion pattern prediction capability. In the present study, a new compensated non‐linear root water uptake (RWU) model is developed to analyse moisture flow under various crop growth and soil conditions. This is achieved by introducing a water stress index in the calibrated non‐linear RWU model that takes care of RWU compensation. The present study also deals with the identifiability of soil hydraulic and RWU parameters using soil moisture and percolation data with an inverse approach. For parameter estimation, the numerical model has been coupled with a genetic algorithm‐based optimizer. The efficacy of the coupled simulation‐optimization model is tested for wheat (Triticum aestivum) crops grown in loamy, sandy clay loam, and sandy loam soil. The study shows that the RWU is less sensitive to soil moisture dynamics in sandy loam soil due to predominant vertical flow. Further, these parameters were estimated for four major Indian crops, that is, berseem (Trifolium alexandrinum), wheat, maize (Zea mays), and pearl millet (Pennisetum glaucum). In soils of higher hydraulic conductivity, the inverse approach was found to be ill‐posed in estimating RWU and soil parameters using only soil moisture information. Hence, for such soils, both soil moisture and percolation data are necessary for estimating these parameters uniquely.