This paper outlines the application of multiple linear regression and three different data-driven modeling techniques to river level forecasting for the River Ouse Catchment in northern England. Lead times of 6 and 24 hours ahead were modelled. The results show that the data driven approaches generally outperformed the statistical approach and that M5 model trees have great potential for the development of transparent river level forecasting models.


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    Title :

    Rainfall-Runoff Modelling using Data Driven and Statistical Methods


    Contributors:
    Khan, Saadat (author) / See, Linda (author)


    Publication date :

    2006-09-01


    Size :

    267948 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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