A Conceptual Data Science Framework for Forecasting Water Availability and Guiding Crop Choice in the Cauvery Delta
DOI:
https://doi.org/10.26821/IJSHRE.14.07.2026.140702Keywords:
Cauvery Delta, ENSO, El Niño, Mettur Reservoir, Decision-Support Framework, Data Science, Agricultural Drought, Groundwater Salinization, Kuruvai, Samba, ThaladiAbstract
Water availability in the Cauvery delta of Tamil Nadu is shaped by a chain of climatic and hydrological events that begins with Pacific Ocean sea-surface temperature anomalies and ends with the storage level of the Mettur reservoir, the principal irrigation source for over 360,000 acres of paddy. Farmers there plan three sequential cropping seasons, Kuruvai, Samba, and Thaladi, without any system that connects ENSO forecasts, upstream reservoir behaviour, and district-level groundwater vulnerability into a single, actionable signal. This paper proposes such a system as a conceptual decision-support framework, not as an implemented or field-validated forecasting model. The framework specifies how five open data streams, the NOAA Oceanic Niño Index, India Meteorological Department seasonal outlooks, Tamil Nadu reservoir telemetry, India-WRIS discharge records, and Central Ground Water Board salinity data, could be combined through an explicit weighted decision rule into a season-specific, district-specific crop advisory, and gives the rule's equations and parameters in a form intended to be directly implementable and testable. The proposal is grounded in a 90-year historical review of Mettur Dam opening outcomes against ENSO state, in which 8 of 17 identified El Niño years coincided with a delayed or failed opening, and is extended with a district-level resilience comparison for Thanjavur, Tiruvarur, Nagapattinam, and Mayiladuthurai. District infrastructure figures, including verified tank counts for each district, are drawn from official Tamil Nadu government storage reporting. The paper's contribution is the framework's architecture, its decision logic, and a concrete pathway for the empirical validation that has not yet been carried out, rather than a finished or tested forecasting tool.
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