Abstract
This paper considers a nonlinear method for the forecasting of river flows, developed in its univariate form in the context of modern nonlinear time series analysis by Farmer and Sidorowich [Phys. Rev. Lett. 59 (1987) 845] and usually referred to as nonlinear prediction (NLP). Here, such a method is extended to a multivariate form to include information from other time series in addition to that of discharge. The conceptual basis of the multivariate approach is explained in the first part of the paper, while the second part deals with the application to forecasting of river flow. The good quality of the predictions obtained, along with the flexibility of the multivariate method to adapt to the different sources of information, indicates that this technique could be of real interest in the hydrologic field.
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