Smart Irrigation Plan can save 10-30% of irrigation water in drought-prone regions: IIT Bombay research

The researchers from the Indian Institute of Technology Bombay (IIT Bombay) and the Indian Institute of Tropical Meteorology, Pune (IITM Pune) have developed a Smart Irrigation Plan to save 10-30% of irrigation water in drought-prone regions, combining weather forecasts, satellite soil moisture data, and a computer simulation for efficient irrigation water management.

Researchers from the Department of Civil Engineering and Centre for Climate Studies at the IIT Bombay and the IITM Pune formulated a method to predict the amount of irrigation water needed up to three weeks, on a district and sub-district scale.

The researchers stated that the farmers in a drought-prone area require a plan for irrigation as rains are unpredictable, and they can’t waste the diminishing groundwater. So, if farmers know beforehand how much water they will receive through rainfall in the coming weeks, they “can plan their irrigation wisely”, helping “crop growth” and “conserving groundwater”.

The pilot study was conducted in Maharashtra’s Nashik district, where researchers found that a few grape farmers used local soil moisture sensors. Thereafter, the study extended its methodology in 12 sub-districts of West Bengal’s Bankura, a drought-prone district.

“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 %. We initially predicted up to one week (short-range) ahead,” shares Professor Subimal Ghosh, from IIT Bombay. 

Professor Ghosh explained that during the execution of methodology in Bankura, they considered crop varieties, varied growth patterns, root zone depth, and water requirements. 

According to researchers, they fed weather forecast and soil moisture data into a computer model that checks the possible amount of rain, the water capacity of the soil, and the water requirements of each crop. On the basis of these details, the system provides information on the crop’s water requirement. If the model predicts no rainfall in the coming days, it will suggest irrigating crops now. In case of rainfall arrival predictions, avoid irrigation of crops. This approach prevents overwatering the crops and saves water.

The researchers highlighted that they used global soil maps and integrated satellite and field data to include soil moisture data such as root zone depth, soil texture, porosity, water-holding capacity, water conductivity, and stomatal closure.

The data on water consumption, monthly rainfall, root depth, and irrigation water requirement data from the Food and Agriculture Organisation (FAO) resource was sourced from the IMD database and IITM Pune.

“Our computer model depicts the natural process by which plants draw water from the soil, their adaptation during a water stress, and their response during a water balance after irrigation or rainfall,” says Prof Ghosh, claiming the study methodology acts as a real-time advisor for water management. 

The study was funded by the Department of Environment, Government of West Bengal, DST-Swarnajayanti Fellowship Scheme, and others.