The isotopic composition of the world’s highest river basins: Role of hydrological mixing ratios and transit time

• Published in: Journal of hydrology (Amsterdam) Vol. 638; p. 131544
• Main Authors: Dasgupta, Bibhasvata, Prakash, Puneet, Sen, Rahul, Noble, Jacob, Chatterjee, Shamik, Sanyal, Prasanta
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.07.2024
• Subjects: Baseflow; Bayesian; Himalaya; Runoff; Seasonality; Snowmelt; Baseflow; Snowmelt; Runoff; Himalaya; Seasonality; Bayesian
• ISSN: 0022-1694
• DOI: 10.1016/j.jhydrol.2024.131544

•Hydrological mixing ratios vary with source, season, and catchment characteristics.•Flux-weighted source isotopic apportionment may overlook reservoir intermixing.•Contiguous, hydrometeorlogically constrained, source isotopic apportionment is key. Hydrological mixing models rely on assumptions governing the rate and timing of mixing proportions, the degree to which isotope ratios conserve the mixing ratios and the estimation of the prior behaviour of meteoric reservoirs. However, these models only describe the integrated catchment response based on different sources having unique and constant isotopic compositions as opposed to location-specific information. Erroneous projection of the hydrological budget can have severe repercussions on climate and eco-hydrological studies, estimation of freshwater availability, and civil and engineering work. Consequently, we design a real-time, multi-parameter, hydrometeorological-constrained, Bayesian-mixing model that can relate meteoric reservoirs to streamflow, and temporal and spatial behaviour of flow paths. Developed for pan-Himalayan catchments (up to 5200 m), with four end-members and pre/post-monsoon seasonality, the isotopic analysis reveals distinct δ18O values: stream water (–9 ± 2.6 ‰), snowpack (–10.7 ± 8.1 ‰), lake water (–12.2 ± 2.5 ‰), and groundwater (–8.4 ± 1.6 ‰). Initial results based on the isotope-enabled, flux-weighted mixing didn’t fully capture spatiotemporal isotopic heterogeneity, affecting hydrograph separation. A revised model, considering the transit time of meteoric reservoirs before their mixing with river discharge, was developed. The revised model illustrates that isotope-enabled mixing models must also consider the hydrometeorological properties of individual reservoirs, the high probability of intermixing between the various reservoirs, and the variable transit time of different meteoric waters in a catchment. With implications for isotope-enabled hydrology, this work describes a novel method applicable to high-mountain hydrology, separating them from other montane or lowland geographies.