Researchers from the Indian Institute of Technology (IIT) Delhi have combined traditional models used to predict streamflow in India’s rivers with artificial intelligence, finding that the new approach significantly improved prediction accuracy in 208 of the 220 rivers tested.
Accurate information of river flow is critical for water resources management, including irrigation scheduling, reducing flood risk, and reservoir operations.
The team, Bhanu Magotra and Manabendra Saharia, said that large-scale hydrological models often produce significant uncertainties in streamflow estimates at local scales unless extensive basin-specific calibration is performed.
Such calibration is computationally expensive and challenging to implement across a country as hydrologically diverse as India, they said.
Calibration refers to the technique of adjusting a model’s output to better align with observed real-world data.
The AI-integrated approach, described in a paper in the journal Water Resource​Researchers from the Indian Institute of Technology (IIT) Delhi have combined traditional models used to predict streamflow in India’s rivers with artificial intelligence, finding that the new approach significantly improved prediction accuracy in 208 of the 220 rivers tested.
Accurate information of river flow is critical for water resources management, including irrigation scheduling, reducing flood risk, and reservoir operations.
The team, Bhanu Magotra and Manabendra Saharia, said that large-scale hydrological models often produce significant uncertainties in streamflow estimates at local scales unless extensive basin-specific calibration is performed.
Such calibration is computationally expensive and challenging to implement across a country as hydrologically diverse as India, they said.
Calibration refers to the technique of adjusting a model’s output to better align with observed real-world data.
The AI-integrated approach, described in a paper in the journal Water Resource ​Latest News [ SOBAN NEWS: International and National ]
