Temporally And Spatially Varying River Ganges Water-groundwater Interaction Through Hydrograph Separation And Stable Isotope Fingerprints

Assessment of flux quantification and exchange between river water and groundwater is essential to understand the hydrodynamics and water storage estimation. In this study we estimate temporal and spatial variation of contributing factors to the total discharge of middle reaches of the Himalayan mega-river, Ganges, in India, through three component hydrograph separation and end member mixing analysis using high-temporal resolution stable isotope and electrical conductivity data. Glacial melt, groundwater fraction and precipitation were identified to be the major three end members. From the mixing model it has been found that Ganges behave as a gaining stream in the studied reaches, with groundwater contributing a major fraction of the total discharge (>70% and 46% during pre-and post-monsoon, respectively). Substantial rain water input during monsoon months, convert the river to loosing stream, with river water recharging the adjoining aquifers. Glacial melt influx was found to be low across the hydrological year (mean 10%). Subparallel isotopic trend lines with respect to global and local mean meteoric lines, combined with d-excess signatures indicate evaporative fractionation river water during pre-monsoon and parts of post-monsoon. End member mixing analysis demonstrates evaporation-induced low stream flow rate and mixing of isotopically enriched base-flow. River water-groundwater mixing is also found to be dependent on river geometry as well as alluvial setting of the studied reaches. These results help in understanding complex dynamics of river water and groundwater in pollutant flux through aquifer recharge or fluvial baseflow. Further, the study provides one of the first-understanding of regional hydrodynamics of a perennial mega-river, which is extremely critical for the water and food security for the huge population striving on it's intensely-cultivated alluvial plains.