Global climate change is having a significant impact on water distribution networks in many regions of the globe. Watershed management failures, such as extensive deforestation, poor land-use management, and unsustainable agricultural methods, are responsible for the worst scenarios (Mwangu, 2021). Currently, environmental circumstances are very worrisome and need appropriate watershed policies for long-term sustainability. All climatic processes are unquestionably increasing in intensity (Gao et al., 2018). Floods, warmer temperatures, and droughts are illustrations of extreme events that show the situation's severity. According to climate models, global temperatures will rise due to an increase in mean near-surface air temperature (Griggs & Noguer, 2002). This may significantly improve the hydrological cycle variability, including variations in the precipitation, evapotranspiration and flow rate. Freshwater resources are enormously important for human civilization and ecosystems, yet they are susceptible and may be damaged by global climate change (Mallakpour & Villarini, 2015; Oki & Kanae, 2006). In addition, the huge contradiction between supply and demand of freshwater resources provides a significant need to forecast hydrological responses to climate change and to manage water resources appropriately.
Presently, one of the most pressing issues in the field of water quantity management is climate change. Keeping the acknowledgments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change in 2014 (IPCC AR5, 2014), temperatures might elevate by 3.7°C until 2100. Global warming is triggering changes to the watershed management across the globe. Thus, the impacts on water resources due to climate change is of greater concern for future water management and to respond effectively to the worse scenarios (Nilawar & Waikar, 2019). Many researchers such as (Pandey & Palmate, 2019; Shrestha et al., 2016; Zhang et al., 2016) have used IPCC AR5 for the future projection and evaluation of the future climate change. Generally, global circulation model (GCMs) are used for the climate change scenarios in many regions of the world. In addition, statistical or dynamic downscaling methods are essential for the evaluation of GCM’s because of their high spatial resolutions it needs proper assessment (Fowler et al., 2007; Mahmood & Babel, 2013). The Coupled Model Inter-comparison Project (CMIP) was initiated in 1995 under the World Climate Research Program (WCRP) to assess the changes in the climate scenarios through multi-model context from past to future (Meehl et al., 2014). CMIP6 is the latest edition of CMIP, in which climatic projections are based on shared socioeconomic paths (SSP). Broadly, SSP’s are updated and revised version of the representative concentration pathways (RCP’s), in which anthropogenic drivers are further improved for the assessment of future scenarios along with socio-economic development (Stouffer et al., 2017). Furthermore, evaluation of updated and revised phase of CMIP is necessary to make proper sustainable resources to challenge worse scenarios.
Inter-model comparison Project Phase 5 (CMIP5) models have greatly accompanied in determining climate change scenarios (Li et al., 2017). Previous researchers such as (Saha et al., 2014; Zhao & Dai, 2017) used CMIP5 models to predict future drought risk and water availability. However, CMIP5-based GCMs reveal substantial uncertainty in future summer monsoon precipitation projections (Long & Li, 2021). Numerous CMIP5 based GCM’s failed in south Asia for capturing monsoon precipitation; at the very outset of monsoon and large-scale variability in the future climate (Ashfaq et al., 2017; Sabeerali et al., 2015). In CMIP6, the main aims are the advancement and improvement of the parametrization and representation for the climate change projections. Recent researchers such as (GUSAIN et al., 2020; Xin et al., 2020) have stated that the assessment on the CMIP6 based GCM’s apprehended the efficient results as compare to CMIP5 based GCM’s during the evaluation of Indian summer monsoon.
Combination of the representative concentration pathway (RCP) and alternative techniques has been offered in the CMIP6 climate model for modelling future emission scenarios. A number of innovative combinations of SSP scenarios have been developed for use in CMIP6. These scenarios are based on updated versions of the SSP scenarios from CMIP5 (SSP119, SSP370, SSP434, SSP245 and SSP585). SSP scenarios encompass socioeconomic elements such as population growth, economy, urbanization, and other factors (Eyring et al., 2016, O'Neill et al., 2016). Wider Equilibrium Climate Sensitivity (ECS) with an expanding temperature range of 1.5–4.5°C is one of the improvements to CMIP6 scenarios. CMIP6 models were projected to enhance in capabilities and minimize uncertainty over the earlier CMIP5 and CMIP3 models (Chen et al., 2020). SSP245 and SSP585 predict that by the end of the 21st century, radiative forcing will have stabilized at 4.5 and 8.5 W m− 2, respectively. The SSP245 scenario is subjective for most countries pursuing sustainable growth The SSP585 scenario, on the other hand, emphasizes the worst-case scenario (a fossil-fuel-based economy) as well as the repercussions of unconventional energy development. (Zhou et al., 2019).
Currently, various tools are available to evaluate the impacts on watershed mainly due to alterations in river runoff and base flow. However, most of the hydrologic methods have the similarity within the watersheds, corresponding catchments, and hydrological modeling (Dey & Mishra, 2017). Among all, the most appealing and conceptual approach for the evaluation of watershed is to use Soil and Water assessment tool (SWAT) model (Swain & Patra, 2017). Moreover, SWAT model is enormously used around the globe for the evaluation of hydrological processes and also for environmental and ecological variations at any catchment scales (Liang et al., 2020). SWAT model allows interconnection among variant physical processes (Yan et al., 2018).
The Upper Indus Basin of Pakistan supplies water to one of the world’s largest irrigation systems. For the past several decades, the region has been experiencing imminent threats from climate change. The runoff in UIB depends on the host of factors, including the melting of seasonal snowpack, glacier melting and precipitation. The erratic changes in maximum and mean temperature during summer and especially in winter has intensified the glacier melting and consequently river flow, adding to the woes of the indigenous community living in the UIB. Mountain ecosystems are widely acknowledged to be most sensitive to climate change. These vulnerabilities are anticipated to be exacerbated by disproportionate warming in mountain areas, notably in the Gilgit Baltistan, which is one of the world's most mountainous and glaciated countries outside of the Polar Regions. This study mainly focuses on using CMIP6 based GCM’s for the projection of future climate change and their impacts on river runoff using SWAT model. The main objectives of this research are; To employ CMIP6-based GCM’s in SWAT model for the projection of stream flow, to examine the implications of climate change on stream flow, and to evaluate total change in projected precipitation, temperature (max & min), and their influence on stream flow in the Upper Regions of Indus Basin.