Assessing the Impact of CFSR and Local Climate Datasets on Hydrological Modeling Performance in the Mountainous Black Sea Catchment

Abstract

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 and Water 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.

Evaluation of the CRU TS3.1, APHRODITE_V1101, and CFSR Datasets in Assessing Water Balance Components in the Upper Vakhsh River Basin in Central Asia

“…Liu et al found that the performance of the hydrological model for the monthly scale of CMADS (NSE = 0.78) was higher than that of the CFSR (NSE = 0.69) [32]. However, our results, as found in the UVRB, conflict with the findings of Tolere et al [16], Fuka et al [45], Cuceloglu and Ozturk [46], and Grusson et al [89]. For instance, Tolere et al [16] reported more successful SWAT streamflow simulation results using the CFSR than conventional datasets from 1990 to 1995 for the Keleta watershed in Ethiopia, where conventional data are scarce [16].…”

“…The results revealed that the CFSR provided better hydrological simulations than conventional datasets [89]. Differences in climate and geographic conditions are the most likely explanation for such differences between the findings of Tolere et al [16], Fuka et al [45], Cuceloglu and Ozturk [46], Grusson et al [89], and the results presented in this study.…”

“…Fuka et al [45] reported that the SWAT model presented better simulation results with CFSR datasets, compared to using traditional weather-gauging stations in the Catskill Mountains, NY, USA, and the Gumera Watershed in the Blue Nile River in Ethiopia, from 1996 to 2010. Similarly, Cuceloglu and Ozturk [46] evaluated CFSR using the SWAT model as a hydrological simulator in the Black Sea catchment from 2000 to 2012. The results showed that the CFSR gives quite reasonable agreement between simulated and observed river flow, compared to the observational dataset.…”

“…For this study, we obtained all variables of the CFSR data for 54 locations (Figure 1). Previously, many studies have been conducted to compare CFSR climate data with observational datasets to assess the reliability of gridded climate data by applying hydrological models [46,47].…”

Evaluation of satellite-based and reanalysis precipitation datasets by hydrologic simulation in the Chenab river basin

“…In China, CFSR data was used to simulate streamflow in the Bahe River Basin (Hu et al 2017), the Kaidu River Basin (Tian et al 2017) and the Kash River Basin (Gao et al 2018a(Gao et al , 2018b, and the results were satisfactory. A study conducted to assess the hydrologic performance of CFSR using the SWAT model showed good results than using local climate data for streamflow simulation (Cuceloglu & Ozturk 2019). In another study, the simulated streamflow with CFSR showed a poor performance than using local climate data (Alemayehu et al 2018).…”