Estimation of root water uptake and soil hydraulic parameters from root zone soil moisture and deep percolation

For efficient irrigation management practices, an accurate prediction of water uptake in the root zone and soil information are foremost important. The present study deals with the identification and estimation of root water uptake (RWU) and soil hydraulic parameters using inverse modeling. These parameters were estimated by minimizing the difference between observed and model simulated soil moisture and deep percolation during the crop growth period. The linked simulation optimization model is tested for three different objective functions using hypothetically generated observed data. Results indicate that the optimizer with objective function defined by soil moisture, failed to provide unique estimate of RWU and soil hydraulic parameters. Further, it has been observed that with the objective function defined by deep percolation, soil hydraulic parameters were uniquely estimated but RWU parameter was not estimated accurately. However, with the objective function, that includes both soil moisture and deep percolation, these parameters were uniquely estimated. A Lysimeter experiments were conducted with four crops i.e. berseem (Trifolium alexandrinum), wheat (Triticum aestivurn), maize (Zea mays) and pearl millet (Penniseturn glaucum). Daily monitoring of soil moisture and deep percolation along with soil and crop parameter measurements were done for model validation. Inversely estimated soil hydraulic parameters were found to be in close agreement with laboratory obtained values. The results indicate that specifically for soils with high hydraulic conductivity, the information about deep percolation along with soil moisture is necessary for inverse estimation of root and soil parameters simultaneously. The moisture depletion pattern and deep percolation corresponding to optimized parameters for these crops were found to be in close agreement with observed values.