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A Comparison of Low Flow Estimates in Ungauged Catchments Using Regional Regression and the HBV-Model

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  • K. Engeland
  • H. Hisdal

Abstract

Estimates of a low flow index in ungauged catchments calculated by a regional regression model and a regional hydrological model were compared for a study region southwestern Norway. The regression method was based on a relationship between the low flow index and an optimal set of catchment descriptors, established using stepwise linear regression for homogeneous subregions. Subregions were distinguished according to the season in which the lowest flow occurs, summer (May to October) or winter (November to April), and the average July temperature was found to be the best index for determining the low flow season for ungauged catchments. Catchment descriptors characterising the presence of lakes and bogs, in addition to catchment length and indicators of climatic conditions, were found to be important in the regression models. A cross-validation procedure was used to evaluate the predictive performance of the model in ungauged catchments. A gridded version of HBV, a daily rainfall-runoff model was also applied as a regional hydrological model and was calibrated using the average Nash–Sutcliffe coefficient for log-transformed streamflow as the calibration criterion. A comparison of the two methods in 21 independent catchments indicates that the regression method generally gives better estimates of Q c in ungauged catchments than does the HBV model, particularly in those catchments with the lowest Q c values. Copyright Springer Science+Business Media B.V. 2009

Suggested Citation

  • K. Engeland & H. Hisdal, 2009. "A Comparison of Low Flow Estimates in Ungauged Catchments Using Regional Regression and the HBV-Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(12), pages 2567-2586, September.
    • Handle: RePEc:spr:waterr:v:23:y:2009:i:12:p:2567-2586
    DOI: 10.1007/s11269-008-9397-7
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    Citations

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    Cited by:

    1. Jordan Clayton & Jason Kean, 2010. "Establishing a Multi-scale Stream Gaging Network in the Whitewater River Basin, Kansas, USA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(13), pages 3641-3664, October.
    2. Saeid Eslamian & Mehdi Ghasemizadeh & Monireh Biabanaki & Mansoor Talebizadeh, 2010. "A Principal Component Regression Method for Estimating Low Flow Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2553-2566, September.
    3. Gokmen Tayfur & Vijay Singh, 2011. "Predicting Mean and Bankfull Discharge from Channel Cross-Sectional Area by Expert and Regression Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(5), pages 1253-1267, March.
    4. Konstantina Risva & Dionysios Nikolopoulos & Andreas Efstratiadis & Ioannis Nalbantis, 2018. "A Framework for Dry Period Low Flow Forecasting in Mediterranean Streams," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 4911-4932, December.
    5. Pao-Shan Yu & Tao-Chang Yang & Chen-Min Kuo & Yi-Tai Wang, 2014. "A Stochastic Approach for Seasonal Water-Shortage Probability Forecasting Based on Seasonal Weather Outlook," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 3905-3920, September.
    6. 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.
    7. Sabrina Ali & Ataur Rahman, 2022. "Development of a kriging-based regional flood frequency analysis technique for South-East Australia," 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. 114(3), pages 2739-2765, December.
    8. Paolo Vezza & Claudio Comoglio & Maurizio Rosso & Alberto Viglione, 2010. "Low Flows Regionalization in North-Western Italy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(14), pages 4049-4074, November.
    9. Ye Tian & Yue-Ping Xu & Xu-Jie Zhang, 2013. "Assessment of Climate Change Impacts on River High Flows through Comparative Use of GR4J, HBV and Xinanjiang Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2871-2888, June.
    10. 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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