Seasonal variation in the quantitative contribution of water sources: A case study from the Yamuna River, India

Hydrological parameters are dynamic within the context of regional climatic zones worldwide. The regional difference is prominent in the riverine systems of the Indian subcontinent and varies significantly for both perennial and ephemeral rivers. The contribution of discharge from the tributaries can incorporate an additional level of intricacy while impacting the changes in seasonal signatures. In the present study, we have deduced the seasonal changes in the relative contribution of the surface runoff or precipitation, glacial meltwater and groundwater for the Yamuna River, including one of the tributaries, the Betwa, using the Discharge Dependent Budget Estimation (DDBE) model [1]. We were able to discriminate the contribution of glacial meltwater through isotopic fingerprints of the Yamuna River (with glacial contribution) while comparing with the rain-fed tributary, the Betwa. The measured values of δ²H and δ¹⁸O of water samples collected on a monthly interval around a year (2023-2024) from the Yamuna, the tributary Betwa river and the confluence of Yamuna-Betwa: Hamirpur, Himachal Pradesh, and the monitored annual discharge values were used for the estimation of seasonal variation in proportional contribution of the sources. Implementation of the IMix model application[2] led to the estimation of increased discharge through the Yamuna, contributing 62-67% (normal distribution model), during the monsoon and similar discharge of both the Yamuna and the Betwa, throughout the rest of the year. The D-excess values in combination with the δ¹⁸O mixing allowed for quantitatively defining the contribution of water sources in the sub-tropical climatic zone. We would be implementing the existing Bayesian Model(MixSIAR) for the same set of data to quantify the uncertainty associated with each of the components, which can help us in the assessment of regional hydrological component turnovers.

 

[1] Kumar et al. (2023) River Res. Applic.

[2] Song et al. (2025) Eco. Proc.