Assessing the impact of CFSR and local climate datasets on hydrological modeling performance in the mountainous Black Sea catchment

Precise representation of precipitation input is one of the predominant factors affecting the simulation of hydrological processes in catchments. Choosing the representative climate datasets is crucial to obtain accurate model results, especially in mountainous regions. Hence, this study assesses the suitability of the Climate Forecasting System Reanalysis (CFSR) and local climate data to simulate the streamflow at multiple gauges in the data-scarce mountainous Black Sea catchment. Moreover, the applicability of using the elevations band in the model is also tested. The Soil andWater Assessment Tool (SWAT) is used as a hydrological simulator. Calibration and uncertainty analysis are performed by using SWAT-CUP with the Sequential Uncertainty Fitting (SUFI-2) algorithm based on monthly streamflow data at six different hydrometric stations located at different altitudes. The results reveal that the CFSR dataset provides quite reasonable agreements between the simulated and the observed streamflow at the gauge stations compared to the local dataset. However, SWAT simulations with both datasets result in poor performance for the upstream catchments of the study area. Considering orographic precipitation by applying elevation bands to the local climate dataset using CFSR data leads also to significant improvements to the model's performance. Model results obtained with both climate datasets result in similar objective metrics, and larger uncertainty with a coefficient variation (CV) ranging from 73% to 107%. This paper mainly highlights that (i) global climate datasets (i.e., CFSR) can be a good alternative especially for data-scarce regions, (ii) elevation band application can improve the model performance for the catchments with high elevation gradients, and iii) CFSR data can be used to determine precipitation lapse rate in data scarce-regions.