Forecasting the daily variability discharge in the fluvial system of the Parana River: an ODPC hydrology application

The relation between discharge and matters of social economy is of constant interest for decision makers. Unexpected daily discharge fluctuations could easily affect agriculture and tourism, among other things. Moreover, because discharge is considered a stochastic variable, studies of new resources to prevent and reduce their negative impacts are needed. We propose the novel application of a technique known as one-sided dynamical principal components (ODPC) to the field of hydrology. This technique allowed us to model and predict the daily variability of the streamflow of three gauge stations of the La Plata Basin. We did a comparison between ODPC and the traditional models used in the field for time series forecasts. This comparison demonstrated that the ODPC method provides some improvement for treatment and forecasting of the daily variability in discharge.

Automated summary

The relation between discharge and social economy matters is of constant interest for decision makers, as unexpected fluctuations in discharge can easily impact various sectors such as agriculture and tourism. This study proposes the novel application of the one-sided dynamical principal components (ODPC) technique to hydrology, allowing for improved modeling and prediction of daily streamflow variability. A comparison between ODPC and traditional models showed that ODPC provides some improvement in the treatment and forecasting of discharge variability.