Differentiating Snow and Glacier Melt Contribution to Runoff in the Gilgit River Basin via Degree-Day Modelling Approach

Latif, Yasir; Ma, Yaoming; Ma, Wei; Sher, Muhammad; Adnan, Muhammad; Yaseen, Muhammad; Fealy, Rowan

doi:10.3390/atmos11101023

Cited by 44 publications

(15 citation statements)

References 63 publications

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“…The contribution of snow to runoff was estimated using various methods and data including the ratio of snowfall to the total precipitation [18], snowfall to total runoff [2,18], SWE to precipitation [19], snowmelt runoff to total runoff [20], degree-day approaches [21][22][23]. Kang et al [24] quantified the contribution of snow to runoff by using the ratio of the spatially averaged peak SWE to runoff and showed that the ratio was in decrease during the period 1949 to 2006 over Fraser River Basin.…”

Section: Introductionmentioning

confidence: 99%

Contribution of Snow-Melt Water to the Streamflow over the Three-River Headwater Region, China

Liu

Adam

et al. 2021

Remote Sensing

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Snowmelt water is essential to the water resources management over the Three-River Headwater Region (TRHR), where hydrological processes are influenced by snowmelt runoff and sensitive to climate change. The objectives of this study were to analyse the contribution of snowmelt water to the total streamflow (fQ,snow) in the TRHR by applying a snowmelt tracking algorithm and Variable Infiltration Capacity (VIC) model. The ratio of snowfall to precipitation, and the variation of the April 1 snow water equivalent (SWE) associated with fQ,snow, were identified to analyse the role of snowpack in the hydrological cycle. Prior to the simulation, the VIC model was validated based on the observed streamflow data to recognize its adequacy in the region. In order to improve the VIC model in snow hydrology simulation, Advanced Scanning Microwave Radiometer E (ASMR-E) SWE product data was used to compare with VIC output SWE to adjust the snow parameters. From 1971 to 2007, the averaged fQ,snow was 19.9% with a significant decreasing trend over entire TRHR (P<0.05).The influence factor resulted in the rate of change in fQ,snow which were different for each sub-basin TRHR. The decreasing rate of fQ,snow was highest of 0.24%/year for S_Lantsang, which should be due to the increasing streamflow and the decreasing snowmelt water. For the S_Yangtze, the increasing streamflow contributed more than the stable change of snowmelt water to the decreasing fQ,snow with a rate of 0.1%/year. The April 1 SWE with the minimum value appearing after 2000 and the decreased ratio of snowfall to precipitation during the study period, suggested the snow solid water resource over the TRHR was shrinking. Our results imply that the role of snow in the snow-hydrological regime is weakening in the TRHR in terms of water supplement and runoff regulation due to the decreased fQ,snow and snowfall.

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Section: Introductionmentioning

confidence: 99%

Contribution of Snow-Melt Water to the Streamflow over the Three-River Headwater Region, China

Liu

Adam

et al. 2021

Remote Sensing

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“…It can be said that the negative trend in mean flows affects the dimensions, and hence, the construction cost of the dam can be also considered as a limiting factor for the water quantity withdrawn from the reservoir and storage capacity due to changing climate concerning variability in hydroclimatic trends [67][68][69]. Therefore, it may be concluded that low flows are decreasing annually and seasonally in summer and autumn.…”

Section: Discussionmentioning

confidence: 99%

Contemporary Trends in High and Low River Flows in Upper Indus Basin, Pakistan

Yaseen

Latif

Waseem

et al. 2022

Water

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The Upper Indus Basin (UIB) features the high mountain ranges of the Hindukush, Karakoram and Himalaya (HKH). The snow and glacier meltwater contribution feeds 10 major river basins downstream including Astore, Gilgit, Hunza, Jhelum, Kabul, Shyok and Shigar. Climate change is likely to fluctuate the runoff generated from such river basins concerning high and low streamflows. Widening the lens of focus, the present study examines the magnitude and timing of high flows variability as well as trends variability in low streamflows using Sen’s slope and the Mann-Kendall test in UIB from 1981 to 2016. The results revealed that the trend in the magnitude of the high flows decreased at most of the sub-basins including the Jhelum, Indus and Kabul River basins. Significantly increased high flows were observed in the glacier regime of UIB at Shigar and Shyok while decreased flows were predominant in Hunza River at Daniyor Bridge. A similar proclivity of predominantly reduced flows was observed in nival and rainfall regimes in terms of significant negative trends in the Jhelum, Kunhar, Neelum and Poonch River basins. The timing of the high flows has not changed radically as magnitude at all gauging stations. For the low flows, decreasing significant trends were detected in the annual flows as well as in other extremes of low flows (1-day, 7-day, 15-day). The more profound and decreasing pattern of low flows was observed in summer at most of the gauging stations; however, such stations exhibited increased low flows in autumn, winter and spring. The decrease in low flows indicates the extension of dry periods particularly in summer. The high-water demand in summer will be compromised due to consistently reducing summer flows; the lower the water availability, the lower will be the crop yield and electricity generation.

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“…Some hydrological models, such as Snowmelt Runoff Model (SRM) [12,13] and the HBV model [14,15], also use an empirical model to describe the melting process of ice, snow and glacier. These snowmelt runoff simulations also achieved good results [16][17][18][19]. However, the empirical model simulation accuracy decreases with the improvement in time resolution, and it is impossible to describe the spatial variation of snow surface ablation [20].…”

Section: Introductionmentioning

confidence: 96%

Modeling Snow Depth and Snow Water Equivalent Distribution and Variation Characteristics in the Irtysh River Basin, China

et al. 2021

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Accurate simulation of snow cover process is of great significance to the study of climate change and the water cycle. In our study, the China Meteorological Forcing Dataset (CMFD) and ERA-Interim were used as driving data to simulate the dynamic changes in snow depth and snow water equivalent (SWE) in the Irtysh River Basin from 2000 to 2018 using the Noah-MP land surface model, and the simulation results were compared with the gridded dataset of snow depth at Chinese meteorological stations (GDSD), the long-term series of daily snow depth dataset in China (LSD), and China’s daily snow depth and snow water equivalent products (CSS). Before the simulation, we compared the combinations of four parameterizations schemes of Noah-MP model at the Kuwei site. The results show that the rainfall and snowfall (SNF) scheme mainly affects the snow accumulation process, while the surface layer drag coefficient (SFC), snow/soil temperature time (STC), and snow surface albedo (ALB) schemes mainly affect the melting process. The effect of STC on the simulation results was much higher than the other three schemes; when STC uses a fully implicit scheme, the error of simulated snow depth and snow water equivalent is much greater than that of a semi-implicit scheme. At the basin scale, the accuracy of snow depth modeled by using CMFD and ERA-Interim is higher than LSD and CSS snow depth based on microwave remote sensing. In years with high snow cover, LSD and CSS snow depth data are seriously underestimated. According to the results of model simulation, it is concluded that the snow depth and snow water equivalent in the north of the basin are higher than those in the south. The average snow depth, snow water equivalent, snow days, and the start time of snow accumulation (STSA) in the basin did not change significantly during the study period, but the end time of snow melting was significantly advanced.

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Differentiating Snow and Glacier Melt Contribution to Runoff in the Gilgit River Basin via Degree-Day Modelling Approach

Cited by 44 publications

References 63 publications

Contribution of Snow-Melt Water to the Streamflow over the Three-River Headwater Region, China

Contribution of Snow-Melt Water to the Streamflow over the Three-River Headwater Region, China

Contemporary Trends in High and Low River Flows in Upper Indus Basin, Pakistan

Modeling Snow Depth and Snow Water Equivalent Distribution and Variation Characteristics in the Irtysh River Basin, China

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