Snowmelt runoff prediction under changing climate in the Himalayan cryosphere: A case of Gilgit River Basin

Adnan, Muhammad; Nabi, Ghulam; Poomee, Muhammad Saleem; Ashraf, Arshad

doi:10.1016/j.gsf.2016.08.008

Cited by 72 publications

(42 citation statements)

References 12 publications

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“…Further evaluation of the SRM was carried out with the Pearson correlation coefficient and the Root Mean Square Error (RMSE) to determine the correlation between the measured and simulated daily discharges (Table II). Landsat and MODIS satellite remote sensing products are widely used as input for snowmelt runoff modelling for current and future runoff simulations (Martinec and Rango, 1986;Dey et al, 1989;Tahir et al, 2011;Adnan et al, 2017;Azmat et al, 2017;Hayat et al, 2019), although these products have limitation in snow cover estimation due to their spatio-temporal resolution and cloud cover. There are also limitations with assuming the future SCA for runoff simulation.…”

Section: Snowmelt Runoff Modelmentioning

confidence: 99%

Incorporating snow model and snowmelt runoff model for streamflow simulation in a snow-dominated mountainous basin in the western Hindukush-Himalaya region

Azizi

Asaoka

2020

Hydrological Research Letters

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A Snow Model (SM) using a temperature-index method was used to optimize the degree-day factor (DDF) and precipitation gradient (PG) for the different elevation zones of the Panjshir sub-basin for snowmelt runoff modelling. The values derived for DDF and PG were calibrated and validated by comparing observed snow cover area and snow cover area simulated by SM. The Snowmelt Runoff Model (SRM) was used to simulate daily runoff over the hydrological years 2009-2014 using the optimized values for SRM accuracy. The optimized DDF values were 0.3 to 0.9 (cm °C-1 d-1) for elevations from 1593 m to 5694 m. Meanwhile the PG was +0.002 m-1 for elevations 1593-4000 m and 0 m-1 above 4000 m. The simulated runoff by SRM during the entire data period correlated very well with a Nash-Sutcliffe coefficient NS = 0.93 utilizing both observed and simulated snow cover area. This method not only evaluates the characteristics of snowfall and snowmelt in different elevation zones to obtain the DDF and PG, but can also estimate the snowmelt runoff.

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Section: Snowmelt Runoff Modelmentioning

confidence: 99%

Incorporating snow model and snowmelt runoff model for streamflow simulation in a snow-dominated mountainous basin in the western Hindukush-Himalaya region

Azizi

Asaoka

2020

Hydrological Research Letters

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“…Some studies that use larger grid cells introduce sub-grid variability of land cover, glacier and hydrological processes [32,51,99]. The review revealed a significant number of applications of empirical models applied in a semi-distributed way using elevation bands [50,95,97,110,111]. Interestingly, many conceptual model applications combine the use of elevation bands with other spatial discretisation, mostly sub-basins [78,[112][113][114] but also grids [115], thereby aiming to capture the influence of the extremely steep terrain together with the spatial variability of landscape features.…”

Section: Model Typementioning

confidence: 99%

“…The length of the calibration period is also relevant to ensure that the model captures the historical variability of the hydrological processes, which influences model performance [70]. More than half of the reviewed models are calibrated using 5 years or less data [50,89,90,111,113,128,133], whilst 23% use more than 10 years for calibration [77,87,115,160]. Unsurprisingly, the studies that require satellite snow cover data fall into the former group, as these products are only available from 2000 to present.…”

Section: Calibrationmentioning

confidence: 99%

Current Practice and Recommendations for Modelling Global Change Impacts on Water Resource in the Himalayas

Momblanch

Holman

Jain

2019

Water

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Global change is expected to have a strong impact in the Himalayan region. The climatic and orographic conditions result in unique modelling challenges and requirements. This paper critically appraises recent hydrological modelling applications in Himalayan river basins, focusing on their utility to analyse the impacts of future climate and socio-economic changes on water resource availability in the region. Results show that the latter are only represented by land use change. Distributed, process-based hydrological models coupled with temperature-index melt models are predominant. The choice of spatial discretisation is critical for model performance due to the strong influence of elevation on meteorological variables and snow/ice accumulation and melt. However, the sparsity and limited reliability of point weather data, and the biases and low resolution of gridded datasets, hinder the representation of the meteorological complexity. These data limitations often limit the selection of models and the quality of the outputs by forcing the exclusion of processes that are significant to the local hydrology. The absence of observations for water stores and fluxes other than river flows prevents multi-variable calibration and increases the risk of equifinality. The uncertainties arising from these limitations are amplified in climate change analyses and, thus, systematic assessment of uncertainty propagation is required. Based on these insights, transferable recommendations are made on directions for future data collection and model applications that may enhance realism within models and advance the ability of global change impact assessments to inform adaptation planning in this globally important region.

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“…The mean projection for RCP8.5 for the period 2071-2100 also shows the same intra-annual pattern for the near future but with more intensity. Many studies [5,84,85] has projected the receding of the glaciated areas in the UIB, which will significantly reduce the share of glacial meltwater that will ultimately cause a reduction in the discharge during the summer season. Also, the decline in the glacier meltwater, our analysis shows a reduction in the monsoon precipitation along with a highly significant (p ≥ 0.01) increase in evapotranspiration in the RCP4.5 and RCP8.5 climate change scenarios.…”

Section: Pattern Of Hydroclimatic Shift In Astore Basinmentioning

confidence: 99%

Modeling Hydrological Response to Climate Change in a Data-Scarce Glacierized High Mountain Astore Basin Using a Fully Distributed TOPKAPI Model

Atif¹,

Iqbal

2019

Climate

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Water scarcity is influencing environmental and socio-economic development on a global scale. Pakistan is ranked third among the countries facing water scarcity. This situation is currently generating intra-provincial water disputes and could lead to transboundary water conflicts. This study assessed the future water resources of Astore basin under representative concentration pathways (RCP) 4.5 and 8.5 scenarios using fully distributed TOPographic Kinematic APproximation and Integration (TOPKAPI) model. TOPKAPI model was calibrated and validated over five years from 1999–2003 with a Nash coefficient ranging from 0.93–0.97. Towards the end of the 21st century, the air temperature of Astore will increase by 3°C and 9.6 °C under the RCP4.5 and 8.5 scenarios, respectively. The rise in air temperature can decrease the snow cover with Mann Kendall trend of –0.12%/yr and –0.39%/yr (p ≥ 0.05) while annual discharge projected to be increased 11% (p ≤ 0.05) and 37% (p ≥ 0.05) under RCP4.5 and RCP8.5, respectively. Moreover, the Astore basin showed a different pattern of seasonal shifts, as surface runoff in summer monsoon season declined further due to a reduction in precipitation. In the spring season, the earlier onset of snow and glacier melting increased the runoff due to high temperature, regardless of the decreasing trend of precipitation. This increased surface runoff from snow/glacier melt of Upper Indus Basin (UIB) can potentially be utilized to develop water policy and planning new water harvesting and storage structures, to reduce the risk of flooding.

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Snowmelt runoff prediction under changing climate in the Himalayan cryosphere: A case of Gilgit River Basin

Cited by 72 publications

References 12 publications

Incorporating snow model and snowmelt runoff model for streamflow simulation in a snow-dominated mountainous basin in the western Hindukush-Himalaya region

Incorporating snow model and snowmelt runoff model for streamflow simulation in a snow-dominated mountainous basin in the western Hindukush-Himalaya region

Current Practice and Recommendations for Modelling Global Change Impacts on Water Resource in the Himalayas

Modeling Hydrological Response to Climate Change in a Data-Scarce Glacierized High Mountain Astore Basin Using a Fully Distributed TOPKAPI Model

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