Extreme weather damaged 17.41 million hectares of cropped area in India during 2025. This figure is 4.3 times higher than the area affected in 2024. Experts said, "Exposure should be systemic." Farmers need simple, 24x7 access to data to manage climate risks effectively instead of relying on slow, complex reports.
Globally, naturally triggered disasters cost agriculture an estimated $99 billion every year, according to FAO's 2025 report covering 1991 to 2023. In India, extreme weather damaged at least 17.41 million hectares of cropped area in 2025. That is roughly 4.3 times the area affected in 2024, and nearly nine times that of 2022. The escalation is stark.
For the farmer, floods, cyclones, hailstorms, heatwaves are not headlines. They are a flattened field, a waterlogged godown, a lost season and repayment obligations that survive the damage.
Natural hazard is real for today's farmer. It is not a forecast. It is the operating condition.
The science of natural hazards does not require a spaceship. Flood plains, drainage, elevation, rainfall intensity, river proximity, soil saturation and historical inundation have been studied for decades. Satellite data is affordable. Technology is accessible.
Sitting between 2 extremes
So, with a known problem, a known science and accessible technology, why is knowing the exposure of a farmer's land and value chain still a 30 to 90 day project?
Climate risk still sits between two extremes. On one end, Excel workbooks, Word documents and consulting hours that arrive after the sowing window has closed. On the other, complex climate models, separate tools for separate hazards and weather forecasts that arrive with a confused farmer who is not a climate engineer. Neither leads to decisions on the farmland and its value chain. Both are expensive.
Exposure should not be a project. Exposure should be systemic.
A farmer producer organisation, cooperative or local grassroots agency should be able to open a platform at any hour and see where its farmland, livestock, storage and warehouses stand. Not once a year. Not after a tender. 24x7.
Moment that matters
The moment that matters is the transition, when monsoon, which is weather, becomes flood, which is a natural hazard. Knowing the exposure before that transition is the difference between preparing and recovering, and it must be simple to read. Picture a quadrant. Every land parcel and every link in the farmer's value chain, the godown, the store, the warehouse where produce waits before the mandi, is plotted on it. High exposure, low readiness is fragile. High exposure, high readiness is resilient. The cooperative knows which farmer to call first, which warehouse to empty, which route to the mandi to avoid.
The farmer is not a climate engineer. Behind the simple view must sit scientific evidence and clearly stated assumptions. Interpreting hazard science is the system's job. The platform should explain risk in the local language and link it to practical choices: check drainage, find alternative storage, protect equipment, coordinate transport or seek a detailed assessment.
Farming is a community livelihood. A safe field offers limited protection when the shared road or warehouse is vulnerable, so the platform must show community exposure too.
Machine learing and AI
This is where machine learning and Artificial intelligence earn their place beside science, as accelerators. A platform can stitch together hazard layers, land parcels, asset locations and historical loss patterns into a reading a farmer collective can act on within 72 hours, refreshed on command as the landscape changes. Techno-science gifts speed and precision.
Lastly, knowing the exposure to natural hazards does not need to be free. Free platforms often lack the one thing that matters when the water rises: reliability. Data must be maintained, models validated, updates timely. Someone must be accountable when the map is wrong.
Ignorance has a price. The question is whether we keep paying it in losses and consulting fees after the flood, heatwave or cyclone, or invest in it as a system before the next one. Resilience begins with knowing. A platform can give farmers the know-how to protect the land, produce and community that sustain their income with human-assistance for decisions.
Samhita is Co-founder & CEO, and Gokul is Senior Research Associate, Resilience AI