Implications of climate change on streamflow of a snow-fed river system of the Northwest Himalaya

Abstract

Air temperature and snow cover variability are sensitive indicators of climate change. This study was undertaken to forecast and quantify the potential streamflow response to climate change in the Jhelum River basin. The implications of air temperature trends (+0.11°C/decade) reported for the entire north-west Himalaya for past century and the regional warming (+0.7°C/decade) trends of three observatories analyzed between last two decades were used for future projection of snow cover depletion and stream flow. The streamflow was simulated and validated for the year 2007-2008 using snowmelt runoff model (SRM) based on in-situ temperature and precipitation with remotely sensed snow cover area. The simulation was repeated using higher values of temperature and modified snow cover depletion curves according to the assumed future climate. Early snow cover depletion was observed in the basin in response to warmer climate. The results show that with the increase in air temperature, streamflow pattern of Jhelum will be severely affected. Significant redistribution of streamflow was observed in both the scenarios. Higher discharge was observed during spring-summer months due to early snowmelt contribution with water deficit during monsoon months. Discharge increased by 5%−40% during the months of March to May in 2030 and 2050. The magnitude of impact of air temperature is higher in the scenario-2 based on regional warming. The inferences pertaining to change in future streamflow pattern can facilitate long term decisions and planning concerning hydro-power potential, water resource management and flood hazard mapping in the region.

Assessment of temporal dynamics of snow cover and its validation with hydro-meteorological data in parts of Chenab Basin, western Himalayas

“…Discharge of these rivers is mainly contributed by the snow-glacial melt during spring and summer season (Sharma et al, 2013), thus snow cover area (SCA) variation influences the sustainability of millions of people in the Himalayan region (Barnett et al, 2005). Snowmelt contributes ~50% in the annual runoff budget in the western Himalaya (Indus, Sutlej) whereas central and eastern Himalaya catchments receive more than 80% and less than 20% of their annual runoff from rainfall and snowmelt, respectively (except the large Tsangpo/Brahmaputra catchment which receives ~34% of its annual discharge from snowmelt) (Bookhagen and Burbank, 2010).…”

“…Sharma et al (2013) reported that north-western Himalayas are the source of major perennial rivers such as Indus, Jhelum, Satluj, Ravi and Chenab as the discharge of these rivers is mainly contributed by the snow-glacial melt. Thus, it also becomes crucial to analyze the sensitivity of river discharge to SCA.…”

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

“…While this approach compensates for data scarcity in remote areas, it results in snowmelt being unconstrained by the depth of snow. When applied in climate change studies, future snow depletion curves are projected based on temperature [50,89,[139][140][141], but disregard the influence of precipitation-temperature relationships on snowpack formation which has obvious limitations to represent snowmelt water availability under future climate change conditions [120]. The contribution of ice melt from glaciers to total runoff was accounted for in 59% of the applications but less than 18% modelled the mass balance of glaciers [2,51,79,85,92,94,115,130,142,143].…”

“…Similarly, the land use/land cover inputs generally used are global products derived from satellites such as Landsat [94,113,161], MODIS [107] and IRS-P6 [110,118] that, despite their acceptable spatial resolution, are only available for recent years. Furthermore, the differential illumination caused by the rugged relief can cause imperfect land cover classifications; in fact, some studies explicitly describe the topographic corrections made to obtain a normalised reflectance [78,139]. Specifically for snow cover, MODIS satellite products are the most used [89,94,97,141], sometimes combined with finer resolution Landsat products of fractional snow cover [80,95,128,138].…”

The Impact of Climate Change on Reservoir Inflows Using Multi Climate-Model under RCPs’ Including Extreme Events—A Case of Mangla Dam, Pakistan

“…Most of the research to date in the Jhelum and Upper Indus Basin have utilized a few GCMs' under SRES scenarios for climate change impact studies [16][17][18][19][20][21][22]. The SRES scenarios exaggerate resource accessibility and are unlikely on upcoming production outputs from fossil fuels [23].…”