Climatic variability and the quantification of climate change impacts on hydrological parameters are persistently uncertain. Remote sensing aids valuable information to streamflow estimations and hydrological parameter projections. However, few studies have been implemented using remote sensing and CMIP6 data embedded with hydrological modeling. This research studied how changing climate influences the hydro-climatic parameters based on the earth system models that participated in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). GRACE evapotranspiration data were forced into the Soil and Water Assessment Tool (SWAT) to project hydrologic responses to future climatic conditions in the Hongshui River basin (HRB) model. A novel approach based on climate elasticity was utilized to determine the extent to which climate variability affects stream flow. CMIP6 SSPs (shared socio-economic pathways) for the second half of the 20th century (1960–2020) and 21st century (2021–2100) projected precipitation (5–16%) for the whole Hongshui River basin (HRB). The ensemble of GCMs projected an increase of 2 °C in mean temperature. The stream flow is projected to increase by 4.2% under SSP-1.26, 6.2% under SSP-2.45, 8.45% under SSP-3.70, and 9.5% under SSP-5.85, based on the average changes throughout the various long-term future scenarios. We used the climate elasticity method and found that climate change contributes 11% to streamflow variability in the Hongshui River basin (HRB). Despite the uncertainty in projected hydrological variables, most members of the modeling ensemble present encouraging findings for future methods of water resource management.

Integrated Flood Analysis System (IFAS) model, based on Tank model philosophy, is a widely used flood forecasting model that has the capability to simulate the catchment processes of any river system provided the surface and aquifer parameters of each sub-model are accurately calibrated. In this study, sensitivity analysis and optimization of hydrogeological parameters of Tank model have been performed to identify the key hydrogeological parameters and their significance in simulating the stream flows in the basins of two important rivers of Pakistan – Jhelum River and Chenab Rivers – respectively. IFAS includes a set of four sub-models namely: surface tank model, sub-surface tank model, aquifer tank model and river course model. Each of the sub-models simulates its own flow processes using surface/aquifer parameters. In this study, sensitivity analysis is performed to identify the parameters that significantly affect the model performance to simulate the flows in the river. Linear stochastic metamodels of Jhelum River and Chenab River Basins developed in this study played the role of metamodels or surrogate functions to determine the ranges of parameter values in different flow periods. The outcome demonstrates when the aquifer tank parameters values obtained from metamodels are applied, the simulation results in a nearly accurate calibration, which clearly indicates the efficiency of present methodology and the important role of hydrogeological parameters. Further, the analysis of the variability in the effectiveness of these parameters in different flow periods as well as for different catchments areas depicts spatial-temporal heterogeneous characteristics. This confirms that the analysis should be directed independently for each study basin because the results of sensitivity analysis are not transferable among catchments.