Can GeoAI Help Farmers Prepare for Extreme Weather Before Crops Are Hit?

Farmers often receive weather information after conditions have already started affecting their crops. ICAR is now looking at digital tools that could help move agricultural advice closer to the field, including GeoAI, mobile advisories and real-time field monitoring.

The focus emerged at a three-day NICRA-TDC stakeholders’ meeting that began at ICAR-CRIDA in Hyderabad on September 22. The meeting is reviewing the programme’s work and preparing location-specific action plans for the next phase of climate-resilient farming.

What is GeoAI?

GeoAI combines artificial intelligence with geographic information and location-based data. In agriculture, such systems can help analyse information connected to specific fields, villages or regions.

The technology can bring together different types of information, such as weather, satellite observations and field conditions. The aim is to produce information that is more relevant to a particular location rather than giving every farmer the same advice.

A weather event can affect nearby farms differently. Soil, crop type, irrigation access, sowing date and local rainfall can all change how a field responds to heat, drought or heavy rain.

ICAR’s NICRA programme has been using location-specific interventions through KVKs in climate-vulnerable districts. The programme currently operates through 151 KVKs across 33 states.

Real-time monitoring can provide information about changing field conditions while a crop is still growing. When combined with weather information, it can help agricultural experts identify emerging risks.

ICAR has identified real-time field monitoring as one of the digital tools that can strengthen climate-resilient agricultural extension. The current NICRA-TDC discussions are examining how such tools can support location-specific action plans.

Can AI predict crop damage?

AI can analyse large amounts of data and identify patterns, but a prediction is not the same as a guaranteed outcome. The quality of an advisory depends on the data, models and local information used.

ICAR is also stressing field-level experience and updated contingency plans. The organisation has called for plans to be revised using lessons from weather-related events experienced during 2026.

Mobile advisories allow agricultural information to reach farmers through digital channels rather than requiring every farmer to visit a KVK or agriculture office.

ICAR has already used digital extension platforms for location-specific advisories. Kisan Sarathi, for example, is designed to help KVK experts provide scientifically validated information to farmers through digital services.

The advice could relate to weather risks, crop management, irrigation or other actions included in local contingency plans. The exact recommendation would depend on the crop, location and developing conditions.

ICAR-CRIDA’s contingency planning work has been used to respond to weather-related challenges. At the September meeting, scientists discussed updating these plans using field experience from the current year.

Potentially, yes. Location-based data can help identify areas facing water stress and support more targeted agricultural advisories.

ICAR-CRIDA has also worked with the International Water Management Institute on SukhaRakshak AI, a drought advisory system that combines AI, satellite observations, weather forecasts and local agricultural contingency plans. The system was designed to provide predictive drought advice in more than 20 Indian languages.

What about farmers who do not use smartphones?

Digital agriculture cannot depend only on smartphone access. Farmers need advisory channels that match local connectivity and digital access.

ICAR’s experience with Kisan Sarathi includes digital advisory services for remote areas, while Bharat-VISTAAR was launched as an AI-based multilingual advisory system accessible through mobile phones and simple phone calls.

The current approach does not suggest that. ICAR describes digital tools as part of agricultural extension, while KVKs and agricultural experts remain involved in preparing and delivering advisories.  The Kisan Sarathi programme, for example, emphasises expert-generated and scientifically validated information. Digital tools can help distribute that information to more farmers, but local expertise remains part of the process.

A contingency plan gives farmers options when weather conditions disrupt normal crop planning. It can include changes in crops, varieties, sowing decisions or farm management practices. ICAR-CRIDA has prepared such plans for climate-vulnerable areas, and several states are already using them. The current NICRA-TDC meeting is reviewing these plans and preparing location-specific actions for the next phase.

ICAR officials specifically discussed the use of contingency plans during El Niño-related weather challenges. They also said the plans need to be updated using experiences from 2026. This matters because climate conditions can change the timing and severity of weather risks. A plan prepared several years earlier may need changes when farmers encounter different rainfall or temperature patterns.

What data does AI need?

AI systems need reliable data to produce useful results. Weather observations, satellite information, crop details and field-level information can all contribute to agricultural advisory systems.

The developers of SukhaRakshak AI have also highlighted data quality, forecast integration and local relevance as issues that need attention before wider deployment. These factors determine whether an advisory is useful at the farm level.

That would defeat much of the purpose of location-specific digital agriculture. Farmers in different regions can face different soil, rainfall, temperature and crop conditions. NICRA-TDC is specifically preparing location-specific action plans. ICAR says the next phase will focus on farming-system interventions tailored to local conditions and village-level climate resilience.

AI cannot remove the uncertainty associated with weather. Forecast errors, incomplete field data, poor connectivity and differences between farms can affect the usefulness of an advisory. Farmers also need practical options after receiving an alert. A warning about water stress is useful only when the farmer has access to measures such as irrigation, water-saving practices, suitable seed or an alternative crop.

What happens next?

The NICRA-TDC stakeholders’ meeting runs from September 22 to 24. More than 100 delegates from ICAR institutes, KVKs, ATARIs and other participating organisations are reviewing the programme’s work and discussing the next phase. The recommendations from the meeting will guide the next phase of NICRA-TDC. ICAR says the focus will include location-specific farming systems, digital monitoring, coordination among agencies and climate-resilience measures at village level.

For farmers, the main change could be how quickly and specifically agricultural advice reaches them. GeoAI, mobile advisories and real-time monitoring are being considered as tools to connect climate information with field-level decisions. The technology still depends on reliable data, local expertise and access to practical farm measures. The next phase of NICRA-TDC will show how far these digital tools move from research and planning into regular agricultural advice.