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Prediction of Surface Flow by Forcing of Climate Forecast System Reanalysis Data

Author

Listed:
  • Milad Jajarmizadeh

    (Universiti Tenaga Nasinal Malaysia)

  • Lariyah Mohd Sidek

    (Universiti Tenaga Nasinal Malaysia)

  • Majid Mirzai

    (Universiti Tuanku Abdul Rahman)

  • Sina Alaghmand

    (Monash University Malaysia)

  • Sobri Harun

    (Universiti Teknologi Malaysia)

  • Mohammad Rafee Majid

    (Universiti Teknologi Malaysia)

Abstract

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.

Suggested Citation

  • Milad Jajarmizadeh & Lariyah Mohd Sidek & Majid Mirzai & Sina Alaghmand & Sobri Harun & Mohammad Rafee Majid, 2016. "Prediction of Surface Flow by Forcing of Climate Forecast System Reanalysis Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2627-2640, June.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:8:d:10.1007_s11269-016-1303-0
    DOI: 10.1007/s11269-016-1303-0
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    References listed on IDEAS

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    1. Ali Suliman & Milad Jajarmizadeh & Sobri Harun & Intan Mat Darus, 2015. "Comparison of Semi-Distributed, GIS-Based Hydrological Models for the Prediction of Streamflow in a Large Catchment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3095-3110, July.
    2. Martine Nyeko, 2015. "Hydrologic Modelling of Data Scarce Basin with SWAT Model: Capabilities and Limitations," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(1), pages 81-94, January.
    3. Wouter Buytaert & Jan Friesen & Jens Liebe & Ralf Ludwig, 2012. "Assessment and Management of Water Resources in Developing, Semi-arid and Arid Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(4), pages 841-844, March.
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