IIT Bombay and IITM Pune research shows a smart irrigation plan, using weather forecasts and soil moisture data, could save farmers up to 30 per cent water by predicting crop needs weeks in advance
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Farmers could save up to 30 per cent of water by adopting a smart irrigation plan, IIT Bombay said, citing a report that stems from joint research conducted with the Indian Institute of Tropical Meteorology (IITM), Pune, reported news agency PTI.
Researchers developed a computer model that integrates weather forecast and soil moisture data to assess possible rainfall, soil water capacity, and the specific water requirements of each crop. This model can predict irrigation water needs up to three weeks in advance at a district and sub-district level. This capability will enable farmers to anticipate future rainfall and plan their irrigation accordingly, thereby aiding crop growth and conserving groundwater, IIT Bombay stated.
During a pilot study in Nashik, researchers observed that some grape growers were already using local soil moisture sensors. They would irrigate their grape farms if the sensor indicated soil dryness; however, it was also noted that if these irrigated farms subsequently received rainfall, the water was wasted, PTI reported.
To prevent such wastage in areas already facing shrinking groundwater levels, the researchers advocated for incorporating weather forecasts into irrigation planning.
"During our pilot study in Nashik, we included local weather forecasts in the soil moisture data and showed farmers that groundwater can be conserved up to 30 per cent. We initially predicted up to one week (short-range) ahead," said Prof Subimal Ghosh of IIT Bombay. He further explained that during this pilot study, researchers fed weather forecast and soil moisture data into a computer model that cross-referenced the potential amount of rainfall, soil water capacity, and crop water requirements.
"If the model predicts no rainfall in the coming days, it will suggest irrigating crops now. On the other hand, if the model predicts rainfall that can increase soil moisture, it may suggest avoiding irrigating crops. The findings showed that the grape farms could consume 10 to 30 per cent less water without compromising the yield. This approach prevents over-watering the crops and saves water," he added.
According to PTI, the researchers later expanded their experiment to include five crop varieties: maize, wheat, sunflower, groundnut, and sugarcane. This selection comprised a combination of cereals, oil seeds, and cash crops, each with varied growth patterns and water requirements. The expanded study was conducted across 12 sub-districts of Bankura, a drought-prone district in West Bengal.
"Our computer model depicts the natural process by which plants draw water from the soil, their adaptation during water stress, and the response during a water balance after irrigation or rainfall," Ghosh explained. He further clarified that to avoid making the model overly crop-specific, they developed more generalised equations.
"We used a very simple ecohydrological model that employed weather forecasts and soil moisture data, which can be adjusted based on the region and crops," he said, adding that extended-range weather forecasts can aid in predicting district-level water requirements and assist water management, PTI reported.
To extend this initiative to other districts, researchers plan to engage with farmers in villages to install additional sensors and develop an advisory system.
(With inputs from PTI)
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