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Abstract. We introduce a new online global database of riverine water stable isotopes (Global Network of Isotopes in Rivers, GNIR) and evaluate its longer-term data holdings. Overall, 218 GNIR river stations were clustered into three different groups based on the seasonal variation in their isotopic composition, which was closely coupled to precipitation and snowmelt water runoff regimes. Sinusoidal fit functions revealed phases within each grouping and deviations from the sinusoidal functions revealed important river alterations or hydrological processes in these watersheds. The seasonal isotopic amplitude of δ18O in rivers averaged 2.5 ‰, and did not increase as a function of latitude, like it does for global precipitation. Low seasonal isotopic amplitudes in rivers suggest the prevalence of mixing and storage such as occurs via lakes, reservoirs, and groundwater. The application of a catchment-constrained regionalized cluster-based water isotope prediction model (CC-RCWIP) allowed for direct comparison between the expected isotopic compositions for the upstream catchment precipitation with the measured isotopic composition of river discharge at observation stations. The catchment-constrained model revealed a strong global isotopic correlation between average rainfall and river discharge (R2 = 0.88) and the study demonstrated that the seasonal isotopic composition and variation of river water can be predicted. Deviations in data from model-predicted values suggest there are important natural or anthropogenic catchment processes like evaporation, damming, and water storage in the upstream catchment.
Halder et al. (Wed,) studied this question.