Tracing ‘Third Pole’ ice meltwater contribution to the Himalayan rivers using oxygen and hydrogen isotopes

Abstract

doi: 10.7185/geochemlet.2013 Global warming is adversely affecting the melting rates of Himalayan glaciers, which feed a number of large river systems in the Indian sub-continent. Regional scale assessment of glaciers and their link to rivers are mostly quantified using remote sensing data and modelling techniques. Here we present an alternative stable water isotope modelling approach. New oxygen and hydrogen isotopes ( 18 O/ 16 O and 2 H/ 1 H, expressed as δ 18 O and δD) data from the headwater of Indus River were analysed with a comprehensively compiled δ 18 O and δD dataset of Himalayan rivers to quantify the volumetric flow of glacier ice meltwater in the headwaters of the rivers Indus, Ganges, and Brahmaputra. The isotope mixing model reveals that the discharge weighted annual average glacier ice meltwater contribution in headwaters (>2000 m) of the Indus, the Ganges, and the Brahmaputra are 47 ± 13 %, 44 ± 13 %, and 29 ± 10 %, respectively, which corresponds to a minimum of 33.5 ± 6.5 Gt yr -1 of melted ice mass. Our results show that annual glacier ice meltwater contributions vary across the river basins, with Indus River receiving the highest contribution. We conclude that stable water isotope modelling is an alternative approach to study regional scale glacier-river interactions to address the future impact of climate change over glaciated Himalayan catchments.

Moisture Sources and Pathways Determine Stable Isotope Signature of Himalayan Waters in Nepal

“…Glaciers have low δ 2 H signatures and typically melt during the summer months. Thus, glacier melt could explain the negative excursion of δ 2 H. This interpretation would be consistent with the melt period of glaciers in the Himalayas (Boral & Sen, 2020; Wulf et al., 2016). However, this isotope signature is also recorded in nearby non‐glaciated catchments (Illien et al., 2021), suggesting other drivers to be important.…”

Assessing the influence of water sampling strategy on the performance of tracer-aided hydrological modeling in a mountainous basin on the Tibetan Plateau

“…Glacier meltwater δ 18 O was assumed to be constantly lower than the weighted average of precipitation δ 18 O by an offset parameter ( δ ) during the study period (Eq. 4) because of the unavailability of glacier meltwater samples, which is generally within the range of 2 ‰-9 ‰ in the worldwide mountain regions (Rai et al, 2019;Wang et al, 2016;He et al, 2019;Ohlanders et al, 2013;Jeelani et al, 2017) and is adopted as 5 ‰ from Boral and Sen (2020) in the YTR basin.…”

“…Similarly to the tracer-based end-member mixing methods that utilize the different tracer signatures of water sources to separate the hydrograph and quantify CRCs (Klaus and McDonnell, 2013;, the traceraided hydrological models used the differed isotopic compositions of runoff components to regulate the water apportionments in runoff generation. The isotopic compositions of runoff components strongly differ in high-mountain basins resulting from the following two reasons: one is the significantly more depleted δ 18 O of meltwater compared to that of rain due to the altitude and temperature effects, and the fractionation effect during melting processes (Xi, 2014;Boral and Sen, 2020). Another is the damping and lagging isotopic variability of subsurface runoff pathway, compared to that of surface runoff, as a result of the catchment hydrological functions of storing, mixing, and transporting water (Bowen et al, 2019;Birkel and Soulsby, 2015;McGuire and McDonnell, 2006).…”

Spatiotemporal variations in runoff and runoff components in response to climate change in a glacierized subbasin of the Upper Indus Basin, Pakistan

“…Moreover, a substantial increase in glacier melt and permafrost thaw was observed since the mid-1990's in rivers originating from HMA (Li et al, 2021). The Himalayan glaciers which feed a large number of river systems in the Indian subcontinent are now experiencing adverse effects on their melting rates because of global warming (Boral and Sen, 2020) and it has been projected to increase in glacier melt runoff and total river runoff until the 2050's in rivers originating from HK region (Azam et al, 2021). Similarly, few other studies such as those (Kääb et al, 2012;Yao et al, 2012;Shean et al, 2020) found the greatest loss of glaciers in the Himalayas and Nyainqêntanglha Mountains in the 21st century.…”

“…However, the quantification of runoff components has always been a problematic issue in hydrological studies and different methods have been used for this purpose such as the stable water isotope modeling approach (Boral and Sen, 2020), statistical and empirical approaches (Mukhopadhyay and Khan, 2014;2015a) and hydrological modeling (Lutz et al, 2014(Lutz et al, , 2016Adnan et al, 2017;Ali et al, 2018;Latif et al, 2020;Khanal et al, 2021;Zhang et al, 2022). However, among these, hydrological modeling has an advantage in runoff segmentation because of its modular approach to hydrological processes (Wu et al, 2021).…”