IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i13p10657-d1188025.html
   My bibliography  Save this article

Performance Assessment Comparison between Physically Based and Regression Hydrological Modelling: Case Study of the Euphrates–Tigris Basin

Author

Listed:
  • Goksel Ezgi Guzey

    (Faculty of Civil Engineering, Istanbul Technical University, Istanbul 34469, Türkiye)

  • Bihrat Önöz

    (Faculty of Civil Engineering, Istanbul Technical University, Istanbul 34469, Türkiye)

Abstract

This paper presents two hydrological models developed for the Euphrates–Tigris Basin in Turkey. The first model is a linear regression-based model allowing the estimation of streamflow based on available hydroclimatic data (precipitation, temperature, evapotranspiration, etc.) with the use of clustering analysis. The second model consists of an elevation-based semi-distributed hydrological model (HBV model), allowing process-based modelling of the watershed. A set of performance metrics identified the HBV model as the best performance in terms of predicting streamflow (NSE = 0.752), while the RCA4-EU regression model of CORDEX showed the most robust performance. The results show the potential of regression models from a computational and data point of view in being integrated into physically based models wherein a hybrid approach might be beneficial. The comparison of conceptual models with statistical analyses of streamflow shows the potential of regression analysis when the regions are clustered in hydro-meteorologically homogeneous groups. The employment of the conceptual model HBV also provides significantly robust streamflow estimation for the region, which is especially important in estimating the hydropower potential of the region’s near future.

Suggested Citation

  • Goksel Ezgi Guzey & Bihrat Önöz, 2023. "Performance Assessment Comparison between Physically Based and Regression Hydrological Modelling: Case Study of the Euphrates–Tigris Basin," Sustainability, MDPI, vol. 15(13), pages 1-15, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10657-:d:1188025
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/13/10657/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/13/10657/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pasquale Cutore & Gabriella Cristaudo & Alberto Campisano & Carlo Modica & Antonino Cancelliere & Giuseppe Rossi, 2007. "Regional Models for the Estimation of Streamflow Series in Ungauged Basins," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 789-800, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. A. Agarwal & R. Maheswaran & J Kurths & R. Khosa, 2016. "Wavelet Spectrum and Self-Organizing Maps-Based Approach for Hydrologic Regionalization -a Case Study in the Western United States," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4399-4413, September.
    2. Mingyong Cai & Shengtian Yang & Hongjuan Zeng & Changsen Zhao & Shudong Wang, 2014. "A Distributed Hydrological Model Driven by Multi-Source Spatial Data and Its Application in the Ili River Basin of Central Asia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2851-2866, August.
    3. David J. Peres & Antonino Cancelliere, 2016. "Environmental Flow Assessment Based on Different Metrics of Hydrological Alteration," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5799-5817, December.
    4. Chang-Shian Chen & Frederick Chou & Boris Chen, 2010. "Spatial Information-Based Back-Propagation Neural Network Modeling for Outflow Estimation of Ungauged Catchment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(14), pages 4175-4197, November.
    5. Dave Deckers & Martijn Booij & Tom Rientjes & Maarten Krol, 2010. "Catchment Variability and Parameter Estimation in Multi-Objective Regionalisation of a Rainfall–Runoff Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(14), pages 3961-3985, November.
    6. Nariman Valizadeh & Majid Mirzaei & Mohammed Falah Allawi & Haitham Abdulmohsin Afan & Nuruol Syuhadaa Mohd & Aini Hussain & Ahmed El-Shafie, 2017. "Artificial intelligence and geo-statistical models for stream-flow forecasting in ungauged stations: state of the art," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(3), pages 1377-1392, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10657-:d:1188025. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.