Semi-arid parts of India face a unique problem. Most farmers have small landholdings and are reliant on increasingly unpredictable rainfall. However, the country’s water resources are already overexploited, leaving little room to expand irrigation.

For rainfed smallholders, the challenge is gaining a share of these limited resources. For farmers with access to irrigation, it is sustaining livelihoods in the face of changing rainfall patterns.

Currently, the focus is on building structures like check dams or farm ponds to harvest and store more rainwater, thereby enabling farmers to grow a dry season crop. However, many watersheds are ‘closed’, that is, all the available water is already being used. Thus, expanding irrigation for some means reducing water access elsewhere.

Further, groundwater offers a critical buffer against climate variability. As it depletes, farmers become even more vulnerable to the impacts of climate change.

We need to sustain and replenish groundwater by rationalising water use and allocating water equitably. For this, we require robust data at a granular scale on who is using water, where and how.

However, this presents two critical bottlenecks:

Data Fragmentation
Decision-makers often require data spread across multiple sources. This fragmentation creates inefficiencies and prevents them from drawing meaningful insights or triangulating different datasets.

Analytical Capacity
Grassroots organisations and village-level decision making bodies often lack the skills to access, analyse, and interpret the available data.