Dr. Gopal Das Singhal, Associate Professor, Department of Civil Engineering (CED) received DST funded project entitled “Development of AI based DSS for Improved Crop Water Use Efficiency under Regulated Deficit Drip Irrigation Regime in the Backdrop of Climate Change”. The research project (duration: 2 years) an academic-industry collaboration and the amount of grant is ₹105 Lakhs.
Project Thrust: Water saving for optimal water use in agriculture using drip system under regulated drip irrigation (RDI) regimes, Climate change mitigation, Development of AI based DSS tools
Summary of the project:
India has reached Critical Water Stress level of 1400 cum/person/annum and rushing to Extremely Critical ‘Water Scarce’ threshold limit of 1000 cum/person/annum in not too distant future. This rise water demand is ascribed to population growth, multi-sectoral water uses and is compounded by global warming and climate change. This project attempts to provide water saving solution for the two widely grown and consumed crop e.g. rice and wheat crops. Different variants of water saving Regulated Deficit Irrigation (RDI) irrigation regimes will be used to find answers for the looming shortage of water in backdrop of climate change vagaries. For optimal crop water use, an Artificial Intelligence (AI) based DSS software will be innovated using the experimental and remote sensing data collected from the experimental field plots representing different water stress conditions in rice and wheat crops, thus mimicking vagaries of climate change/global warming.
Image of the experimental setup (Polyhouse and
experimental field plots)
Drip irrigation system installed in the experimental
Wheat crop grown in experimental field plots
Data collection from the experimental field plots