ABSTRACT

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.

摘要

排放与社会经济事务之间的关系一直是决策者关注的问题。意外的日常排放波动很容易影响农业和旅游业等。此外，由于排放被认为是一个随机变量，因此需要研究新资源以防止和减少其负面影响。我们建议将一种称为单侧动力主成分 (ODPC) 的技术应用于水文学领域。这项技术使我们能够模拟和预测拉普拉塔盆地三个测量站流量的每日变化。我们对 ODPC 和该领域用于时间序列预测的传统模型进行了比较。