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Water 2015, 7(1), 99-115; doi:10.3390/w7010099

Development of Flow Forecasting Models in the Bow River at Calgary, Alberta, Canada

1
Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, 2500 University Dr. NW, Calgary, Alberta T2N 1N4, Canada
2
Department of Civil Engineering, Schulich School of Engineering, University of Calgary, 2500 University Dr. NW, Calgary, Alberta T2N 1N4, Canada
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Miklas Scholz
Received: 16 November 2014 / Accepted: 16 December 2014 / Published: 24 December 2014
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Abstract

River flow forecasting is critical for flood forecasting, reservoir operations, and water resources management. However, flow forecasting can be difficult, challenging and time consuming due to the spatial and temporal variability of climatic conditions and watershed characteristics. From a practical point of view, a simple and intuitive approach might be more preferable than a complex modeling approach. In this study, our objective was to develop short-term (i.e., daily) flow forecasting models in the Bow River at the city of Calgary, Alberta, Canada. Here, we evaluated the performance of several regression models, along with a newly proposed “base difference” model, by using antecedent daily river flow values from three gauge stations (i.e., Banff, Seebe, and Calgary). Our analyses revealed that using a multivariable linear regression formulated as a function of upstream gauge stations (i.e., Banff or Seebe) and the station of interest (i.e., Calgary) using antecedent flows demonstrated strong relationships (i.e., having r2 (coefficient of determination) and RMSE (root-mean-square deviation) of approximately 0.93 and 14 m3/s, respectively). As such, we opted to suggest that the use of Banff and Calgary stations in forecasting the flows at Calgary could be considered as it would require a relatively lower number of gauge stations. View Full-Text
Keywords: base difference model; flow modelling at daily scale; linear regression; temporal analysis base difference model; flow modelling at daily scale; linear regression; temporal analysis
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Veiga, V.B.; Hassan, Q.K.; He, J. Development of Flow Forecasting Models in the Bow River at Calgary, Alberta, Canada. Water 2015, 7, 99-115.

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