Development Of AI-Based DSS For Improved Crop Water Use Efficiency Under Regulated Deficit Drip Irrigation Regime
This project attempts to provide water saving solution for the two widely grown and consumed crop. 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.
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.
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.
Focus of the project
- 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
Funding Agency: DST under the scheme “Water Technology Initiative (WTI) 2019”
Faculty: Dr. Gopal Singhal, Associate Professor