Estimation of Seasonal Freshwater Inflows in Coastal Southern India using Stable Isotope Analysis and Machine Learning Techniques

Cochin backwater region in Southern India is one of the most dynamic estuaries, strongly influenced by seasonal river runoff and seawater intrusion. This study explores the rela-tionship between monsoonal rains, salinity, and stable isotopic composition (δ¹⁸O and δ¹³C) to estimate the contribution of freshwater fluxes at different seasonal intervals for the Cochin Backwater (CBW) estuary. Seasonal variations in oxygen isotopes and salinity re-vealed distinct trends indicative of freshwater-seawater mixing dynamics. The compari-son of Local and Global Meteoric Water Lines highlighted enriched isotope values during the pre-monsoon season, showing significant evaporation effects. Carbon (C) isotopic analysis in dissolved inorganic matter (δ¹³CDIC) at 17 stations during the pre-monsoon season revealed spatially distinct carbon dynamics zones, influenced by various sources. These characteristic zones were Zone 1, dominated by seawater, exhibited heavier δ¹³CDIC values; Zone 2 showing significant contributions of lighter terrestrial δ¹³C; while Zone 3 reflected inputs from regional and local paddy fields with a distinct C3 isotopic signature (-25‰), modified by estuarine productivity. In addition, different advanced machine learning techniques were tested to improve analysis and prediction of seasonal variations in isotopic composition and salinity. The combination of these advanced machine learn-ing models not only improved the predictive accuracy of seasonal freshwater fluxes but also provided a robust framework for understanding the estuarine ecosystem and would pave way for better management and conservation strategies.