Control of Anthropogenic Factors on the Dissolved Carbon Sources in the Ramganga River, Ganga Basin, India

The Ramganga River is an important tributary of the Ganga River flowing through diverse land use classes. To examine seasonal variations in dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) concentration and assess the potential impact of natural processes and human activities, we collected water samples from the Ramganga River and its tributaries during the pre-monsoon, monsoon, and post-monsoon seasons of 2014. DOC and DIC concentration, total dissolved solids (TDS), nitrate (NO3-), chloride (Cl-), and proxies like DOC/DIC ratio, percentage share of anthropogenic contribution, and percentage of pollution were evaluated using Hierarchical Cluster Analysis. The results show annual average DOC concentration in the Ramganga basin is 2.0 +/- 1.2 mg/l. The DOC and DIC concentration represent a distinct seasonal variation being higher in the non-monsoon and lower in the monsoon season. The DIC/DOC ratio of 11.3, NO3-/Ca2+ and Ca2+/Cl- suggests elevated carbonate weathering, with floodplains likely acting as the dominant source of DIC flux. DOC transport is controlled by basin physiography, the river carries 3.8 times higher DOC concentrations in the floodplains than that in the mountainous region. However, high DOC concentration in the middle and lower sections of the basin indicates a strong control of anthropogenic activities. The positive linear relationship between the percentage of pollution index and DOC, percentage share of anthropogenic contribution and DOC, and Cl- and DOC suggest a significant influence of residential wastewater on the river's DOC flux. Hierarchical cluster analysis revealed that factors like physiography, seasonal variation, tributary contributions, and the presence of the Kalagarh dam differentially influence DOC and DIC concentration across the basin. The findings shed light on the substantial impact of urbanization on carbon transportation pathways, emphasizing the need for further research to incorporate these anthropogenically driven changes into global climate models for more accurate predictions.