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Keywords = Upper Vakhsh River Basin

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2 pages, 530 KiB  
Correction
Correction: Gulakhmadov et al. 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. Atmosphere 2021, 12, 1334
by Aminjon Gulakhmadov, Xi Chen, Manuchekhr Gulakhmadov, Zainalobudin Kobuliev, Nekruz Gulahmadov, Jiabin Peng, Zhengyang Li and Tie Liu
Atmosphere 2021, 12(12), 1641; https://doi.org/10.3390/atmos12121641 - 8 Dec 2021
Cited by 2 | Viewed by 1763
Abstract
The authors were not aware of errors that were made during the proofreading phase and would hence wish to make the below-mentioned corrections to this paper [...] Full article
(This article belongs to the Section Climatology)
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40 pages, 7533 KiB  
Article
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
by Aminjon Gulakhmadov, Xi Chen, Manuchekhr Gulakhmadov, Zainalobudin Kobuliev, Nekruz Gulahmadov, Jiabin Peng, Zhengyang Li and Tie Liu
Atmosphere 2021, 12(10), 1334; https://doi.org/10.3390/atmos12101334 - 12 Oct 2021
Cited by 8 | Viewed by 3322 | Correction
Abstract
In this study, the applicability of three gridded datasets was evaluated (Climatic Research Unit (CRU) Time Series (TS) 3.1, “Asian Precipitation—Highly Resolved Observational Data Integration Toward the Evaluation of Water Resources” (APHRODITE)_V1101, and the climate forecast system reanalysis dataset (CFSR)) in different combinations [...] Read more.
In this study, the applicability of three gridded datasets was evaluated (Climatic Research Unit (CRU) Time Series (TS) 3.1, “Asian Precipitation—Highly Resolved Observational Data Integration Toward the Evaluation of Water Resources” (APHRODITE)_V1101, and the climate forecast system reanalysis dataset (CFSR)) in different combinations against observational data for predicting the hydrology of the Upper Vakhsh River Basin (UVRB) in Central Asia. Water balance components were computed, the results calibrated with the SUFI-2 approach using the calibration of soil and water assessment tool models (SWAT–CUP) program, and the performance of the model was evaluated. Streamflow simulation using the SWAT model in the UVRB was more sensitive to five parameters (ALPHA_BF, SOL_BD, CN2, CH_K2, and RCHRG_DP). The simulation for calibration, validation, and overall scales showed an acceptable correlation between the observed and simulated monthly streamflow for all combination datasets. The coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) showed “excellent” and “good” values for all datasets. Based on the R2 and NSE from the “excellent” down to “good” datasets, the values were 0.91 and 0.92 using the observational datasets, CRU TS3.1 (0.90 and 0.90), APHRODITE_V1101+CRU TS3.1 (0.74 and 0.76), APHRODITE_V1101+CFSR (0.72 and 0.78), and CFSR (0.67 and 0.74) for the overall scale (1982–2006). The mean annual evapotranspiration values from the UVRB were about 9.93% (APHRODITE_V1101+CFSR), 25.52% (APHRODITE_V1101+CRU TS3.1), 2.9% (CFSR), 21.08% (CRU TS3.1), and 27.28% (observational datasets) of annual precipitation (186.3 mm, 315.7 mm, 72.1 mm, 256.4 mm, and 299.7 mm, out of 1875.9 mm, 1236.9 mm, 2479 mm, 1215.9 mm, and 1098.5 mm). The contributions of the snowmelt to annual runoff were about 81.06% (APHRODITE_V1101+CFSR), 63.12% (APHRODITE_V1101+CRU TS3.1), 82.79% (CFSR), 81.66% (CRU TS3.1), and 67.67% (observational datasets), and the contributions of rain to the annual flow were about 18.94%, 36.88%, 17.21%, 18.34%, and 32.33%, respectively, for the overall scale. We found that gridded climate datasets can be used as an alternative source for hydrological modeling in the Upper Vakhsh River Basin in Central Asia, especially in scarce-observation regions. Water balance components, simulated by the SWAT model, provided a baseline understanding of the hydrological processes through which water management issues can be dealt with in the basin. Full article
(This article belongs to the Special Issue Advanced Climate Simulation and Observation)
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