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Estimation of Continuous Streamflow in Ontario Ungauged Basins: Comparison of Regionalization Methods
Regionalization, a process of transferring hydrological information [i.e., parameters of a conceptual rainfall-runoff model, namely, the McMaster University-Hydrologiska Byra˚ns Vattenbalansavdelning (MAC-HBV)] from gauged to ungauged basins, was applied to estimate continuous flows in ungauged basins across Ontario, Canada. To identify appropriate regionalization methods, different regionalization methods were applied, including the spatial proximity [i.e., kriging, inverse distance weighted (IDW), and mean parameters], physical similarity, and regression-based approaches. Furthermore, an approach coupling the spatial-proximity (IDW) method and the physical similarity approach is proposed. The analysis results show that the coupled regionalization approach as well as the IDW and kriging produce better model performances than the remaining three. Further investigations show that the coupled-regionalization approach provides slightly better performances than the other two spatial proximity methods. In addition, a modified Monte Carlo simulation method is used to assess the estimated flow confidence intervals. The prediction confidence intervals provide additional information on the range of variability of the simulated continuous streamflow in the ungauged basins, and this can be particularly useful for decision making, such as environmental flow determination in ungauged basins.
Estimation of Continuous Streamflow in Ontario Ungauged Basins: Comparison of Regionalization Methods
Regionalization, a process of transferring hydrological information [i.e., parameters of a conceptual rainfall-runoff model, namely, the McMaster University-Hydrologiska Byra˚ns Vattenbalansavdelning (MAC-HBV)] from gauged to ungauged basins, was applied to estimate continuous flows in ungauged basins across Ontario, Canada. To identify appropriate regionalization methods, different regionalization methods were applied, including the spatial proximity [i.e., kriging, inverse distance weighted (IDW), and mean parameters], physical similarity, and regression-based approaches. Furthermore, an approach coupling the spatial-proximity (IDW) method and the physical similarity approach is proposed. The analysis results show that the coupled regionalization approach as well as the IDW and kriging produce better model performances than the remaining three. Further investigations show that the coupled-regionalization approach provides slightly better performances than the other two spatial proximity methods. In addition, a modified Monte Carlo simulation method is used to assess the estimated flow confidence intervals. The prediction confidence intervals provide additional information on the range of variability of the simulated continuous streamflow in the ungauged basins, and this can be particularly useful for decision making, such as environmental flow determination in ungauged basins.
Estimation of Continuous Streamflow in Ontario Ungauged Basins: Comparison of Regionalization Methods
Samuel, Jo (author) / Coulibaly, Paulin (author) / Metcalfe, Robert A. (author)
Journal of Hydrologic Engineering ; 16 ; 447-459
2011-05-01
13 pages
Article (Journal)
Electronic Resource
English
| British Library Online Contents | 2011
Streamflow Prediction in Ungauged Basins: Review of Regionalization Methods
| British Library Online Contents | 2013
Streamflow Prediction in Ungauged Basins: Review of Regionalization Methods
| Online Contents | 2013