Modeling snowmelt-runoff under climate scenarios in the Hunza River basin, Karakoram Range, Northern Pakistan

Tahir, Adnan Ahmad; Chevallier, Pierre; Arnaud, Yves; Neppel, Luc; Ahmad, Bashir

doi:10.1016/j.jhydrol.2011.08.035

Cited by 216 publications

(200 citation statements)

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“…The purpose was to study the variations in hydrological processes due to climate change. The SRM was used for the prediction of future flows under different climate change scenarios in the Hunza River basin in Pakistan [40]. The most common expression related to snowmelt and temperature index is given below in Equation (1):…”

Section: Snowmelt Runoff Modelmentioning

confidence: 99%

“…In summer (April to June) it varies from 0.057 mm/100 m to 0.0002 mm/100 m. In winter, the value of precipitation lapse rate is higher in December (about 0.76 mm/100 m). The average annual precipitation lapse rate from low to high climatic stations is about 0.506 mm/100 m. The Gilgit flows in summer (June-September) are mainly affected by snow-and glacier melt [40].…”

Section: Characteristics Of the Study Areamentioning

confidence: 99%

“…In previous studies, MODIS satellite products were widely used all over the world to estimate the snow cover areas in high elevation basins [39,49]. [40] validated a cloud-free MODIS image with an ASTER image on the same date in the Hunza River basin, which is near the Gilgit River basin. The validation was performed on both the basin and the zone-wide snow cover areas of the images.…”

Section: Modis Satellite Datamentioning

confidence: 99%

“…The SRM is designed to work under scarcity of data so that in the absence of precipitation data it encounters the snow-covered area to compute the runoff. The discharge obtained from SRM is mainly affected by temperature and less affected by precipitation [40]. Thus, daily average temperature and precipitation data from the high altitude and low altitude climatic stations of the Gilgit catchment were used as inputs in all SRM elevation zones.…”

Section: Calibration and Validation Of The Snowmelt Runoff Modelmentioning

confidence: 99%

“…Thus, daily average temperature and precipitation data from the high altitude and low altitude climatic stations of the Gilgit catchment were used as inputs in all SRM elevation zones. The parameters necessary for calibration were extracted from past data analyses and some parameters from past studies [10,35,40,52].…”

Section: Calibration and Validation Of The Snowmelt Runoff Modelmentioning

confidence: 99%

See 4 more Smart Citations

Snowmelt Runoff Modelling under Projected Climate Change Patterns in the Gilgit River Basin of Northern Pakistan

Adnan¹,

Nabi²,

Kang³

et al. 2017

Pol. J. Environ. Stud.

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Pakistan is home to three of the world's largest mountain ranges in the Upper Indus Basin (UIB), where the majority of Pakistan's water resources are located: the Himalayan, Karakorum, and Hindu-Kush. This work estimated the (snow+glacier) and rainfall runoff from one of the major tributaries, the Gilgit River, nestled within the UIB of Pakistan. The snowmelt runoff model (SRM) derived by the cryospheric data from the MODIS (moderate resolution imaging spectroradiometer) was employed to predict the daily discharges of the Gilgit. The SRM was successfully calibrated, and the simulation was undertaken from 2005 to 2010, with a coefficient of model efficiency ranging from 0.84-0.94. The average contributions of (snow+glacier) and rainfall to the stream flows of the Gilgit from 2001-10 were 78.35% and 21.65%, respectively, derived from the SRM. The representative concentration pathways (RCP) 4.5 and 8.5 scenarios of the Intergovernmental Panel on Climate Change (IPCC) AR5 were used to investigate the effects of the changes in temperature on climate of the Gilgit catchment. Under the RCP 4.5 scenario, the air temperature

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Section: Snowmelt Runoff Modelmentioning

confidence: 99%

Section: Characteristics Of the Study Areamentioning

confidence: 99%

Section: Modis Satellite Datamentioning

confidence: 99%

Section: Calibration and Validation Of The Snowmelt Runoff Modelmentioning

confidence: 99%

Section: Calibration and Validation Of The Snowmelt Runoff Modelmentioning

confidence: 99%

See 3 more Smart Citations

Snowmelt Runoff Modelling under Projected Climate Change Patterns in the Gilgit River Basin of Northern Pakistan

Adnan¹,

Nabi²,

Kang³

et al. 2017

Pol. J. Environ. Stud.

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The importance of observed gradients of air temperature and precipitation for modeling runoff from a glacierized watershed in the Nepalese Himalayas

Immerzeel

Petersen

Ragettli

et al. 2014

Water Resources Research

233

281

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The performance of glaciohydrological models which simulate catchment response to climate variability depends to a large degree on the data used to force the models. The forcing data become increasingly important in high-elevation, glacierized catchments where the interplay between extreme topography, climate, and the cryosphere is complex. It is challenging to generate a reliable forcing data set that captures this spatial heterogeneity. In this paper, we analyze the results of a 1 year field campaign focusing on air temperature and precipitation observations in the Langtang valley in the Nepalese Himalayas. We use the observed time series to characterize both temperature lapse rates (LRs) and precipitation gradients (PGs). We study their spatial and temporal variability, and we attempt to identify possible controlling factors. We show that very clear LRs exist in the valley and that there are strong seasonal differences related to the water vapor content in the atmosphere. Results also show that the LRs are generally shallower than the commonly used environmental lapse rates. The analysis of the precipitation observations reveals that there is great variability in precipitation over short horizontal distances. A uniform valley wide PG cannot be established, and several scale-dependent mechanisms may explain our observations. We complete our analysis by showing the impact of the observed LRs and PGs on the outputs of the TOPKAPI-ETH glaciohydrological model. We conclude that LRs and PGs have a very large impact on the water balance composition and that short-term monitoring campaigns have the potential to improve model quality considerably.

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Integrated simulation of snow and glacier melt in water and energy balance‐based, distributed hydrological modeling framework at Hunza River Basin of Pakistan Karakoram region

et al. 2015

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Energy budget-based distributed modeling of snow and glacier melt runoff is essential in a hydrologic model to accurately describe hydrologic processes in cold regions and high-altitude catchments. We developed herein an integrated modeling system with an energy budget-based multilayer scheme for clean glaciers, a single-layer scheme for debris-covered glaciers, and multilayer scheme for seasonal snow over glacier, soil, and forest within a distributed biosphere hydrological modeling framework. Model capability is demonstrated for Hunza River Basin (13,733 km 2 ) in the Karakoram region of Pakistan on a 500 m grid for 3 hydrologic years (2002)(2003)(2004). Discharge simulation results show good agreement with observations (Nash-Sutcliffe efficiency = 0.93). Flow composition analysis reveals that the runoff regime is strongly controlled by the snow and glacier melt runoff (50% snowmelt and 33% glacier melt). Pixel-by-pixel evaluation of the simulated spatial distribution of snow-covered area against Moderate Resolution Imaging Spectroradiometer-derived 8 day maximum snow cover extent data indicates that the areal extent of snow cover is reproduced well, with average accuracy 84% and average absolute bias 7%. The 3 year mean value of net mass balance (NMB) was estimated at +0.04 myr À1 . It is interesting that individual glaciers show similar characteristics of NMB over 3 years, suggesting that both topography and glacier hypsometry play key roles in glacier mass balance. This study provides a basis for potential application of such an integrated model to the entire Hindu-Kush-Karakoram-Himalaya region toward simulating snow and glacier hydrologic processes within a water and energy balance-based, distributed hydrological modeling framework.

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Modeling snowmelt-runoff under climate scenarios in the Hunza River basin, Karakoram Range, Northern Pakistan

Cited by 216 publications

References 28 publications

Snowmelt Runoff Modelling under Projected Climate Change Patterns in the Gilgit River Basin of Northern Pakistan

Snowmelt Runoff Modelling under Projected Climate Change Patterns in the Gilgit River Basin of Northern Pakistan

The importance of observed gradients of air temperature and precipitation for modeling runoff from a glacierized watershed in the Nepalese Himalayas

Integrated simulation of snow and glacier melt in water and energy balance‐based, distributed hydrological modeling framework at Hunza River Basin of Pakistan Karakoram region

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