National Institute of Technology Hamirpur, India
Vijay Shankar completed PhD from IIT Roorkee in 2007 and presently working as Associate Professor at Department of Civil Engineering, NIT Hamirpur. He has published more than 40 papers in reputed journals and international and national conference proceedings.
Improved irrigation water management requires precise scheduling of irrigation, which in turn requires an accurate computation of daily crop water use. Crop water use is dependent on soil moisture uptake by plants. Moisture uptake based irrigation scheduling necessitates modeling the water movement in the cropped soil by formulating a numerical model solving the moisture flow equation in the unsaturated soil coupled with a sink term representing moisture uptake by plants. In the present study a numerical model, based on a mass conservative, fully implicit finite difference scheme has been formulated, wherein Richards equation coupled with a non-linear root water uptake term has been subjected to appropriate boundary conditions. The model yields spatial distribution of pressure head and moisture content at successive advancing times in the soil. From the model computed moisture contents, the moisture depletion values at different zones of crop root at different times are computed by numerical integration. The input data required for prediction of soil moisture uptake by plants includes soil parameters, plant parameters and meteorological parameters to compute evapotranspiration. Field experiments under controlled conditions on a crop “Maize” were performed at Semi-arid and hill-temperate agro-climates of Roorkee and Hamirpur respectively. Study focuses on effect of different plant parameters on moisture uptake prediction. Investigations reveal that measured plant parameters i.e., root length, leaf area index and plant height, are insufficient to accurately predict moisture depletion in upper and lower layers of root zone. This results in improper irrigation schedules. Study puts forward plant parameters which have potential to accurately predict moisture uptake in entire crop root zone and optimised irrigation schedules.