Climate change decisive for Asia’s snow meltwater supply

Kraaijenbrink, Philip; Stigter, Emmy E.; Yao, Tandong; Immerzeel, Walter W.

doi:10.1038/s41558-021-01074-x

Cited by 208 publications

(148 citation statements)

References 99 publications

(122 reference statements)

Supporting

Mentioning

140

Contrasting

Order By: Relevance

“…The mean annual snow ablation (sum of snowmelt and sublimation) is 113 Gt (standard deviation 12 Gt), which is close but lower than the annual snowfall value of 121.8 ± 7.7 Gt estimated by [6] over the period 1979-2019. This discrepancy can be due to (i) different periods of study (2000-2016 versus 1979-2019), (ii) differences in the basin delimitation [17] and (iii) net accumulation of snowfall in the glacier accumulation areas.…”

Section: Discussionmentioning

confidence: 53%

“…In the upper Indus basin, snowmelt is the dominant contributor to water resources, providing 74% of annual runoff above 2000 m during the period 2001-2014 (23% rainfall, 3% ice melt) [5]. Another study estimated the contribution of snowmelt to annual streamflow to 55.4 ± 2.4% [6], but this estimate excluded seasonal snowmelt from the glacier area, which may explain the lower percentage. Snowmelt contribution to runoff is also significant in the high elevation regions of the Ganges and Brahmaputra basins, but not as much as in the Indus [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

“…Another study estimated the contribution of snowmelt to annual streamflow to 55.4 ± 2.4% [6], but this estimate excluded seasonal snowmelt from the glacier area, which may explain the lower percentage. Snowmelt contribution to runoff is also significant in the high elevation regions of the Ganges and Brahmaputra basins, but not as much as in the Indus [5][6][7]. Above estimates of snowmelt in the Indus basin were obtained using temperature index models [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…Snowmelt contribution to runoff is also significant in the high elevation regions of the Ganges and Brahmaputra basins, but not as much as in the Indus [5][6][7]. Above estimates of snowmelt in the Indus basin were obtained using temperature index models [5,6]. These empirical models rely on air temperature to compute snowmelt while the energy balance of the snow cover is also controlled by additional meteorological variables such as shortwave and longwave radiation, wind speed and air humidity [8,9].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Snowmelt and Snow Sublimation in the Indus Basin

Gascoin

2021

Water

View full text Add to dashboard Cite

The Indus basin is considered as the one with the highest dependence on snowmelt runoff in High Mountain Asia. The recent High Mountain Asia snow reanalysis enables us to go beyond previous studies by evaluating both snowmelt and snow sublimation at the basin scale. Over 2000–2016, basin-average snowmelt was 101 ± 11 Gt.a−1 (121 ± 13 mm.a−1), which represents about 25–30% of basin-average annual precipitation. Snow sublimation accounts for 11% of the mean annual snow ablation, but with a large spatial variability across the basin.

show abstract

Section: Discussionmentioning

confidence: 53%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Snowmelt and Snow Sublimation in the Indus Basin

Gascoin

2021

Water

View full text Add to dashboard Cite

show abstract

“…The snowmelt in the Tibetan Plateau showed an increasing trend from 1951 to 2017, and as the temperature is projected to rises further in the future, it is likely that both the snowmelt and snowmelt runoff ratio will decrease in the near future. Other studies have similarly concluded that the snowmelt and snowmelt runoff ratio in the Tibetan Plateau will decline in the future (Qin et al, 2020;Kraaijenbrink et al, 2021). The Tibetan Plateau and its surrounding downstream areas are projected to experience declines in the share of water from snowmelt and will thus require increases in alternative water 570 supplies.…”

Section: Tibetan Plateaumentioning

confidence: 98%

Trends and variability in snowmelt in China under climate change

Yang

Chen

et al. 2021

Preprint

View full text Add to dashboard Cite

Abstract. Snowmelt is a major fresh water resource, and quantifying snowmelt and its variability under climate change is necessary for planning and management of water resources. Spatiotemporal changes in snow properties in China have drawn wide attention in recent decades; however, country-wide assessments of snowmelt are lacking. Using precipitation and temperature data with a high spatial resolution (0.5 seconds, approximately 1 km), this study calculated the monthly snowmelt in China for the 1951–2017 period using a simple temperature index model, and the model outputs were validated using snowfall, snow depth, snow cover extent and snow water equivalent. Precipitation and temperature scenarios developed from five CMIP5 models were used to predict future snowmelt in China under three different representative concentration pathways (RCP) scenarios (RCP2.6, RCP4.5 and RCP8.5). The results showed that the mean annual snowmelt in China from 1951 to 2017 was 2.41 × 1011 m3. The mean annual snowmelts in Northern Xinjiang, Northeast China, and the Tibetan Plateau – China’s three main stable snow cover regions – were 0.18 × 1011 m3, 0.42 × 1011 m3 and 1.15 × 1011 m3, respectively. From 1951 to 2017, the snowmelt increased significantly in the Tibetan Plateau and decreased significantly in North, Central and Southeast China. In the whole of China, there was a decreasing trend in snowmelt, but this was not statistically significant. The mean annual snowmelt runoff ratios were generally more than 10 % in almost all third-level basins in West China, more than 5 % in third-level basins in North and Northeast China, and less than 2 % in third-level basins in South China. From 1951 to 2017, the annual snowmelt runoff ratios decreased in most third-level basins in China. Under RCP2.6, RCP4.5 and RCP8.5, the projected snowmelt in China in 2030s (2050s, 2090s) may decrease by 13.4 % (16.3 %, 13.8 %), 19.1 % (19.8 %, 22.5 %), 17.1 % (24.7 %, 42.8 %) compared with the historical period (1951–2017), respectively. Most of the projected mean annual snowmelt runoff ratios in third-level basins in different decades (2030s, 2050s and 2090s) were lower than those in the historical period. Low temperature regions can tolerate more warming, and the snowmelt change in these regions is mainly influenced by precipitation; however, the snowmelt change in warm regions is more sensitive to temperature increases. The spatial variability of snowmelt changes may lead to regional differences in the impact of snowmelt on water supply.

show abstract

Response of runoff components to climate change in the source‐region of the Yellow River on the Tibetan plateau

Zhang

2022

Hydrological Processes

View full text Add to dashboard Cite

Climate change will likely increase the total streamflow in most headwaters on the Tibetan Plateau in the next decades, yet the response of runoff components to climate change and permafrost thaw remain largely uncertain. Here, we investigate the changes in runoff components under a changing climate, based on a high-resolution cryosphere-hydrology model (Spatial Processes in Hydrology model, SPHY) and multi-decadal streamflow observations at the upstream (Jimai) and downstream stations (Maqu and Tangnaihai) in the source-region of the Yellow River (SYR). We find that rainfall flow dominates the runoff regime in SYR (contributions of 48%-56%), followed by snowmelt flow (contributions of 26%/23% at Maqu/Tangnaihai). Baseflow is more important at Jimai (32%) than at the the downstream stations (21%-23%). Glacier meltwater from the Anyê Maqên and Bayankala Mountains contributes negligibly to the downstream total runoff. With increasing temperature and precipitation, the increase in total runoff is smaller in the warm and wet downstream stations than in the cold and dry upstream station. This is because of a higher increase in evapotranspiration and a larger reduction in snowmelt flow in the downstream region in response to a warming climate. With temperature increase, there is less increase in rainfall flow in the downstream region due to increased water loss through evapotranspiration. Meanwhile, the decline in snowmelt flow is larger further downstream, which can negatively impact the spring irrigation for the whole Yellow River basin that supports the livelihoods of 140 million people. Importantly, we find that baseflow plays an increasingly important role in the permafrost-dominated upstream region with atmospheric warming and permafrost thaw, accompanied by decreased surface flow. These findings improve our current understanding of how different hydrological processes respond to climate change and provide insights for optimizing hydropower and irrigation systems in the entire Yellow River basin under a rapidly changing climate.

show abstract

Climate change decisive for Asia’s snow meltwater supply

Cited by 208 publications

References 99 publications

Snowmelt and Snow Sublimation in the Indus Basin

Snowmelt and Snow Sublimation in the Indus Basin

Trends and variability in snowmelt in China under climate change

Response of runoff components to climate change in the source‐region of the Yellow River on the Tibetan plateau

Contact Info

Product

Resources

About