This study describes a novel methodology for predicting spring hydrographs based on Regional Climate Model (RCM) projections to evaluate climate change impact on karstic spring discharge. A combined stochastic-analytical modelling methodology was developed and demonstrated on the Bukovica karst spring catchment at the Durmitor National Park, Montenegro. As a first step, climate model projections of the EURO-CORDEX ensemble were selected, and bias correction was applied based on historical climate data. The regression function between rainfall and peak discharge was established using historical data.
The baseflow recession was described using a double-component exponential model, where hydrograph decomposition and parameter fitting were performed on the Master Recession Curve. Rainfall time series from two selected RCM scenarios were applied to predict future spring discharge time series. Bias correction of simulated hydrographs was performed, and bias-corrected combined stochastic-analytical models were applied to predict spring hydrographs based on RCM simulated rainfall data. Simulated climate scenarios predict increasing peak discharges and decreasing baseflow discharges throughout the 21st century. Model results suggest that climate change will likely exaggerate the extremities regarding climate parameters and spring discharge by the end of the century. The annual number of drought days shows a large variation over time. Extremely dry years are periodic, with a frequency between 5-7 years. The number of drought days seems to increase over time during these extreme years. The study confirmed that the applied methodology can successfully be applied for spring discharge prediction