On projected hydrological scenarios under the influence of bias-corrected climatic variables and LULC

Abstract Assessing the impact of climate variability is important for water resources planning and management. In the present study, climate model data were utilized in conjunction with the hydrological model to analyze the effect of climate change on projected streamflow and groundwater recharge values for the Dwarakeswar-Gandherswari basin, India. Regional Climate Model (RCM) data [Representative Concentration Pathway (RCP 2.6, RCP 4.5, RCP 6 and RCP 8.5)] were considered for future climate change scenarios. Five bias correction methods [linear scaling (LS), local intensity scaling (LOCI), power transformation (PWTR), distribution mapping (DM) and variance scaling (VARI)] were applied for RCM based precipitation and temperature data. Projected Land Use and Land Cover (LULC) values were obtained from Dyna-CLUE model. Discharge data (1990–2016) was utilized for model calibration and validation purpose. Total twelve scenarios (4 RCPs per year for the years 2030, 2050 and 2080) were considered. The results showed increasing trend in simulated discharge for the months June to September and reverse trend for the months October to December. The results also showed that groundwater recharge increased for the maximum number of sub-watersheds for the interval 2016–2030 compared to 2016–2050 and 2016–2080 under all RCPs. Uncertainties in streamflow were quantified in terms of exceedance probability and recurrence interval. ALPHA_BF was the most sensitive parameter for the river basin. However, gross increase in groundwater recharge was observed for all the scenarios. These results can be effectively utilized for irrigation planning purpose.