Evaluation of the Climate Forecast System Reanalysis data for hydrological model in the Arctic watershed Målselv

• Published in: Journal of Water and Climate Change
• Main Authors: Minh Tuan Bui, Jinmei Lu, Linmei Nie
• Format: Article in Journal/Newspaper
• Language: English
• Published: IWA Publishing 2021
• Subjects: arctic region; climate forecast system reanalysis (cfsr); ground-based weather data; målselv watershed; qswat model; uncertainty analysis; Environmental technology. Sanitary engineering; TD1-1066; Environmental sciences; GE1-350; Arctic; Nash; Sutcliffe; Målselv
• Online Access: https://doi.org/10.2166/wcc.2021.346; https://doaj.org/article/54ea3ac0e60c4c12a5f97fb332e226cc

The high-resolution Climate Forecast System Reanalysis (CFSR) data have recently become an alternative input for hydrological models in data-sparse regions. However, the quality of CFSR data for running hydrological models in the Arctic is not well studied yet. This paper aims to compare the quality of CFSR data with ground-based data for hydrological modeling in an Arctic watershed, Målselv. The QSWAT model, a coupling of the hydrological model SWAT (soil and water assessment tool) and the QGIS, was applied in this study. The model ran from 1995 to 2012 with a 3-year warm-up period (1995–1997). Calibration (1998–2007), validation (2008–2012), and uncertainty analyses were performed by the Sequential Uncertainty Fitting Version 2 (SUFI-2) algorithm in the SWAT Calibration Uncertainties Program for each dataset at five hydro-gauging stations within the watershed. The objective function Nash–Sutcliffe coefficient of efficiency for calibration is 0.65–0.82 with CFSR data and 0.55–0.74 with ground-based data, which indicate higher performance of the high-resolution CFSR data than the existing scattered ground-based data. The CFSR weather grid points showed higher variation in precipitation than the ground-based weather stations across the whole watershed. The calculated average annual rainfall by CFSR data for the whole watershed is approximately 24% higher than that by ground-based data, which results in some higher water balance components. The CFSR data also demonstrates its high capacities to replicate the streamflow hydrograph, in terms of timing and magnitude of peak and low flow. Through examination of the uncertainty coefficients P-factors (≥0.7) and R-factors (≤1.5), this study concludes that CFSR data is a reliable source for running hydrological models in the Arctic watershed Målselv. HIGHLIGHTS The high-resolution CFSR dataset has higher performance than the existing scattered ground-based dataset in terms of statistical coefficients, R2, NSE, and RSR.; The CFSR dataset has higher simulation results for ...