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At IIT Bombay, we are working with the Maharashtra Department of Agriculture on building climate resilience in agriculture of rural Maharashtra. A crucial input for agriculture is rainfall. We've built a model to compute distribution of rainfall into various components such as crop water uptake, soil moisture, groundwater recharge and surface runoff. Using PostgreSQL and PostGIS, we are able to deploy this model at scale, to ingest hourly rainfall data from 1400+ weather stations on a daily basis, spanning more than 20,000 villages within Maharashtra. The results are providing key insights into the state of agriculture at village level. PostgreSQL enables aggregation of the results over any administrative region, such as a village, a revenue circle, a taluka or a district. Using pg_tileserv exetnsion and GeoServer, the results can be rendered as maps, suitable for decision making at various levels within the DoA.

As part of this talk, we look forward to sharing technical details of our geospatial stack, a sample of spatial queries we are using, and a few lessons learned.

Co-authored-by: Sameer Mannava sameer.mannava7@gmail.com, B.Tech. student at IIT Bombay.