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Regional Models for the Estimation of Streamflow Series in Ungauged Basins

Author

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  • Pasquale Cutore
  • Gabriella Cristaudo
  • Alberto Campisano
  • Carlo Modica
  • Antonino Cancelliere
  • Giuseppe Rossi

Abstract

The assessment of water resources in a region usually must cope with a general lack of data, both in time (short observed series) as well as in space (ungauged basins). Such a lack of data is generally overcome by combining rainfall–runoff models with regionalization techniques in order to transfer information to sites without or with short available observed series. The present paper aims to analyze applicability and limitations of two regionalization procedures for estimating the parameters of simple rainfall–runoff models respectively based on a “two-step” and on a “one-step” approach, for the estimation of monthly streamflow series in ungauged basins. In particular, an application to a Sicilian river basin of multiple regression equations according to a “two-step” and a “one-step” approaches and of a “one-step” approach based on neural networks is reported. For the investigated region, results indicate that models based on the “one-step” approach appear to be robust and adequate for estimating the streamflows in ungauged basins. Copyright Springer Science+Business Media, Inc. 2007

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:21:y:2007:i:5:p:789-800
    DOI: 10.1007/s11269-006-9110-7
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.

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