Fields of Data: Mapping Vulnerability in Bengal’s Rice Belt

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Story Behind the Research

Listening to the Fields

It began under a gentle morning sun in Paschim Medinipur, where the mist still clung to the rice paddies and the air carried the scent of wet earth. A farmer, perhaps in his late fifties, bent over the seedlings with a calm focus that comes only from decades of tending the land. When we asked about his biggest worry, he didn’t speak of politics or markets. He simply said, “Rain now comes when it wants. We adjust as best we can, yet sometimes it feels like no matter what we do, it’s never enough — and still, we have no choice but to keep farming, for there’s nothing else to eat.”

This quiet resilience, repeated in voices across 1,814 farmers we met in eight districts of West Bengal, became the heart of our research. As researchers, we are trained to see numbers, maps, and patterns. But in this work, we also learned to see patience, ingenuity, and endurance etched into the lives of people whose livelihoods depend entirely on the rhythm of nature.

 Why Vulnerability Matters

Rice farming in West Bengal is more than an occupation — it is heritage, identity, and community survival. Yet the farmers who sustain this system live at the frontline of climate uncertainty. Erratic rainfall, sudden dry spells, rising temperatures, and pest outbreaks are no longer exceptions; they are becoming the new normal.

These changes do not affect all farmers equally. Some districts face more flooding, others more drought; some communities have better education and technology access, others face greater isolation. Understanding this unevenness is crucial if we are to design fair and effective support systems.

 Turning Field Insights into Measurable Knowledge

To capture this complexity, we used a framework called the Livelihood Vulnerability Index (LVI) and its climate-focused version, LVI-IPCC. In simple terms, these are tools that combine many different indicators — from a farmer’s income and education level to their exposure to weather extremes — into a single picture of vulnerability.

What made our study different was how we built this picture. Instead of relying only on secondary data, we went directly to the source: the farmers themselves. Using carefully designed field surveys and GPS mapping, we gathered 17 specific indicators, grouped into three main pillars:

1. Adaptive Capacity — the resources and skills a farmer can draw on to cope with change.
2. Exposure — the degree to which their livelihood is affected by climate and environmental stresses.
3. Sensitivity — how strongly these stresses impact their productivity and income.

We then used a method called EDAS (Evaluation Based on Distance from Average Solution) to analyse this data. While the name sounds technical, the principle is straightforward: it ranks each location based on how far it is from the “average” conditions across the study area. This helped us identify districts most in need of urgent support, without letting one factor unfairly overshadow another.

 What the Patterns Revealed
The results were as varied as the landscapes themselves:

• Birbhum and Murshidabad emerged as the most vulnerable districts overall, with high exposure to erratic rainfall and limited adaptive capacity in some areas.
• Jhargram faced severe adaptive capacity challenges, driven by lower education levels and limited income diversification.
• Purba Bardhaman stood out for its high exposure, especially due to heavy rainfall and soil salinity in certain pockets.
• Bankura showed lower exposure but higher sensitivity, meaning that even moderate climatic stresses could cause significant disruptions.

Numbers alone, however, do not tell the full story. In Birbhum, for example, the vulnerability score reflects the daily struggle to protect crops from both drought and pests, while in Purba Bardhaman it captures the frustration of losing harvests to unexpected downpours just days before reaping.

 Beyond the Maps
One of the most humbling moments during this project came in a village in Paschim Medinipur, where an elderly farmer invited us to sit on a woven cot under a Banyan tree. He spoke about how his father taught him to read the clouds — skills that worked well until the last decade. Now, he said, the sky no longer “speaks the same language.”

This is why combining local wisdom with scientific analysis is so important. While satellite data and statistical models can reveal patterns over large areas, farmers hold intimate, place-based knowledge that no machine can replicate. Our hope is that tools like LVI–EDAS can be a bridge between these two worlds, ensuring that adaptation plans are both evidence-based and grounded in reality.

Hope in Action
The purpose of this research was never to label some places as “hopelessly vulnerable.” On the contrary, it was to shine a light on where small, well-targeted changes could have the greatest impact. Some examples include:

• Digital literacy programs in Jhargram to help farmers use weather forecasts and market apps.
• Drainage and water management improvements in Purba Bardhaman to reduce flood exposure.
• Climate-resilient rice varieties in Birbhum and Murshidabad to cope with erratic rainfall.
• Soil health restoration in Bankura to lower sensitivity and improve yields.

By linking these interventions to the United Nations Sustainable Development Goals (SDGs) — especially SDG 1 (No Poverty), SDG 2 (Zero Hunger), and SDG 13 (Climate Action) — we can align local actions with global priorities.

 Reflections and Gratitude

Research often feels like a race for data, results, and publications. But in the rice fields of West Bengal, we were reminded that patience, like the slow growth of a seedling, is strength. Farmers do not measure success in days or weeks, but in seasons and years.

This work is dedicated to them — not as “subjects” of a study, but as partners in knowledge. Every number in our tables and every pixel in our maps represents someone’s hard work, risk, and hope for the future.

We believe that science has its greatest value when it listens first, calculates second, and returns what it learns in a form that communities can use. That is the spirit in which we offer this research — as one small step towards a future where climate resilience is not a privilege, but a shared right.