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This study focuses on the quantification of climate change (CC) effects on agricultural water availability in Cyprus. Projections of climatic variables, based on Regional Climate Models (RCMs) forced by the Representative Concentration Pathways (RCPs) 4.5 and 8.5, were used as CC driving forces affecting water availability. Groundwater flow models were developed for specific high-interest agricultural areas in Larnaca and Paphos to assess the CC impacts on these groundwater systems, while the Standardized Precipitation–Evapotranspiration Index (SPEI) analysis was also adopted, for the first time in Cyprus, to assess future trends of water reservoir storage under the projected climatic conditions. Considering the current cultivation and irrigation practices, a decrease in groundwater level close to 1 m and further inland seawater intrusion in Larnaca aquifers are expected, while in Paphos’ aquifers, the predicted water table fluctuations are not significant. Additionally, SPEI values at the Asprokemos and Kouris dams are correlated with water storage measurements, showing that a SPEI downward trend observed in these reservoirs could set off an alarm to the water authorities with respect to water availability as more severe drought events are expected in the future. The expected pressure on surface waters imposes the need for an improved water management plan that will not depend on the further exploitation of groundwater.

In this study, 17 hydrologists with different experience in hydrological modelling applied the same conceptual catchment model (HBV) to a Greek catchment, using identical data and model code. Calibration was performed manually. Subsequently, the modellers were asked for their experience, their calibration strategy, and whether they enjoyed the exercise. The exercise revealed that there is considerable modellers’ uncertainty even among the experienced modellers. It seemed to be equally important whether the modellers followed a good calibration strategy, and whether they enjoyed modelling. The exercise confirmed previous studies about the benefit of model ensembles: Different combinations of the simulation results (median, mean) outperformed the individual model simulations, while filtering the simulations even improved the quality of the model ensembles. Modellers’ experience, decisions, and attitude, therefore, have an impact on the hydrological model application and should be considered as part of hydrological modelling uncertainty.

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