Prediction of Surface Flow by Forcing of Climate Forecast System Reanalysis Data
Arid regions; Calibration; Forecasting; Hydrology; Meteorology; Rain; Runoff; Uncertainty analysis; Calibration and validations; CFSR; Hydrological simulations; Meteorological variables; Reanalysis; Sequential uncertainty fittings; Soil and water assessment tool; SWAT model; Data visualization
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2023
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my.uniten.dspace-227142023-05-29T14:11:47Z Prediction of Surface Flow by Forcing of Climate Forecast System Reanalysis Data Jajarmizadeh M. Sidek L.M. Mirzai M. Alaghmand S. Harun S. Majid M.R. 55251767200 35070506500 54941702700 55193594200 15724724300 56962732700 Arid regions; Calibration; Forecasting; Hydrology; Meteorology; Rain; Runoff; Uncertainty analysis; Calibration and validations; CFSR; Hydrological simulations; Meteorological variables; Reanalysis; Sequential uncertainty fittings; Soil and water assessment tool; SWAT model; Data visualization Meteorological data are key variables for hydrologists to simulate the rainfall-runoff process using hydrological models. The collection of meteorological variables is sophisticated, especially in arid and semi-arid climates where observed time series are often scarce. Climate Forecast System Reanalysis (CFSR) Data have been used to validate and evaluate hydrological modeling throughout the world. This paper presents a comprehensive application of the Soil and Water Assessment Tool (SWAT) hydrologic simulator, incorporating CFSR daily rainfall-runoff data at the Roodan study site in southern Iran. The developed SWAT model including CFSR data (CFSR model) was calibrated using the Sequential Uncertainty Fitting 2 algorithm (SUFI-2). To validate the model, the calibrated SWAT model (CFSR model) was compared with the observed daily rainfall-runoff data. To have a better assessment, terrestrial meteorological gauge stations were incorporated with the SWAT model (Terrestrial model). Visualization of the simulated flows showed that both CFSR and terrestrial models have satisfactory correlations with the observed data. However, the CFSR model generated better estimates regarding the simulation of low flows (near zero). The results of the uncertainty analysis showed that the CFSR model predicted the validation period more efficiently. This might be related with better prediction of low flows and closer distribution to observed flows. The Nash-Sutcliffe (NS) coefficient provided good- and fair-quality modeling for calibration and validation periods for both models. Overall, it can be concluded that CFSR data might be promising for use in the development of hydrological simulations in arid climates, such as southern Iran, where there are shortages of data and a lack of accessibility to the data. � 2016, Springer Science+Business Media Dordrecht. Final 2023-05-29T06:11:47Z 2023-05-29T06:11:47Z 2016 Article 10.1007/s11269-016-1303-0 2-s2.0-84963758720 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963758720&doi=10.1007%2fs11269-016-1303-0&partnerID=40&md5=2f169a7f6cf249c786293dbe3a18ab10 https://irepository.uniten.edu.my/handle/123456789/22714 30 8 2627 2640 Springer Netherlands Scopus |
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Arid regions; Calibration; Forecasting; Hydrology; Meteorology; Rain; Runoff; Uncertainty analysis; Calibration and validations; CFSR; Hydrological simulations; Meteorological variables; Reanalysis; Sequential uncertainty fittings; Soil and water assessment tool; SWAT model; Data visualization |
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55251767200 |
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55251767200 Jajarmizadeh M. Sidek L.M. Mirzai M. Alaghmand S. Harun S. Majid M.R. |
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Article |
| author |
Jajarmizadeh M. Sidek L.M. Mirzai M. Alaghmand S. Harun S. Majid M.R. |
| spellingShingle |
Jajarmizadeh M. Sidek L.M. Mirzai M. Alaghmand S. Harun S. Majid M.R. Prediction of Surface Flow by Forcing of Climate Forecast System Reanalysis Data |
| author_sort |
Jajarmizadeh M. |
| title |
Prediction of Surface Flow by Forcing of Climate Forecast System Reanalysis Data |
| title_short |
Prediction of Surface Flow by Forcing of Climate Forecast System Reanalysis Data |
| title_full |
Prediction of Surface Flow by Forcing of Climate Forecast System Reanalysis Data |
| title_fullStr |
Prediction of Surface Flow by Forcing of Climate Forecast System Reanalysis Data |
| title_full_unstemmed |
Prediction of Surface Flow by Forcing of Climate Forecast System Reanalysis Data |
| title_sort |
prediction of surface flow by forcing of climate forecast system reanalysis data |
| publisher |
Springer Netherlands |
| publishDate |
2023 |
| _version_ |
1806423296527302656 |
| score |
13.214268 |