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Modified SWAT to Forecast Water Availability in Mediterranean Mountainous Watersheds with Snowmelt Dominated Runoff

Author

Listed:
  • G. Harik

    (Khalifa University
    American University of Beirut)

  • I. Alameddine

    (American University of Beirut)

  • M. Abou Najm

    (University of California, Davis)

  • M. El-Fadel

    (Khalifa University
    American University of Beirut)

Abstract

The assessment of the hydrological response to projected changes in climatic variables is imperative for water resources management, especially in watersheds where snowmelt represents a significant source of runoff. In this study, we modify the source code of the snow accumulation and melting algorithm of the Soil and Water Assessment Tool (SWAT) model to improve runoff simulations in snow dominated basins. A sinusoidal snowmelt function under the degree-day factor method was adopted with its parameters calibrated based on historical data. River flow simulations were compared to measured data under the modified and unmodified SWAT models. Model differences in future predictions of river flows (2032- RCP 4.5) were also assessed. The results showed that the modifications improved runoff simulations by better capturing flow dynamics as represented by daily flows and corresponding variability during the snowmelt period. The modified model increased the Nash–Sutcliffe Efficiency (from 0.64 to 0.79; 0.60 to 0.80; 0.70 to 0.75) and the coefficient of determination (from 48 to 67%, 48 to 69%, 58 to 70%) at three gauging stations. While both models predicted a decrease of water availability in the basin, future simulations with the modified snowmelt algorithm predicted that the drop in water availability as compared to baseline year (2008) will be less dramatic (24%) compared to predictions from the unmodified SWAT (31%). We argue that the proposed source code modifications to the snowmelt algorithm of SWAT provide better insights about future water availability in snow-dominated watersheds.

Suggested Citation

  • G. Harik & I. Alameddine & M. Abou Najm & M. El-Fadel, 2023. "Modified SWAT to Forecast Water Availability in Mediterranean Mountainous Watersheds with Snowmelt Dominated Runoff," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(5), pages 1985-2000, March.
    • Handle: RePEc:spr:waterr:v:37:y:2023:i:5:d:10.1007_s11269-023-03466-4
    DOI: 10.1007/s11269-023-03466-4
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    References listed on IDEAS

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    1. Rong Gan & Changzheng Chen & Jie Tao & Yongqiang Shi, 2021. "Hydrological Process Simulation of Sluice-Controlled Rivers in the Plains Area of China Based on an Improved SWAT Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(6), pages 1817-1835, April.
    2. Bekele Debele & Raghavan Srinivasan & A. Gosain, 2010. "Comparison of Process-Based and Temperature-Index Snowmelt Modeling in SWAT," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(6), pages 1065-1088, April.
    3. Pandey, Vishnu Prasad & Dhaubanjar, Sanita & Bharati, Luna & Thapa, Bhesh Raj, 2020. "Spatio-temporal distribution of water availability in Karnali-Mohana Basin, western Nepal: hydrological model development using multi-site calibration approach (Part-A)," Papers published in Journals (Open Access), International Water Management Institute, pages 1-29:100690.
    4. Xiaoyan Gong & Jianmin Bian & Yu Wang & Zhuo Jia & Hanli Wan, 2019. "Evaluating and Predicting the Effects of Land Use Changes on Water Quality Using SWAT and CA–Markov Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4923-4938, November.
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    Cited by:

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