Several artificial neural network (ANN) models with a feed-forward, back-propagation network structure and various training algorithms, are developed to forecast daily and monthly river flow discharges in Manwan Reservoir. In order to test the applicability of these models, they are compared with a conventional time series flow prediction model. Results indicate that the ANN models provide bett...

Forecasting a time series became one of the most challenging tasks to variety of data sets. The existence of large number of parameters to be estimated and the effect of uncertainty and outliers in the measurements makes the time series modeling too complicated. Recently, Artificial Neural Network (ANN) became quite successful tool to handle time series modeling problem. This paper provides a s...

The paper discusses how the well known USACE HEC models, RAS and HMS, are fully integrated within the decision support system of the Romagna River Basins in order to predict flood effects. The models are fully available from the web and cope with such a variety of problems as rainfall-runoff modeling, river and civil works hydraulics, and the mapping of hydraulic hazard. The paper illustrates t...

I. INTRODUCTION We humans tend to worry first about our own happiness, then about our families, then about our communities. In times of great stress, such as war or natural disaster, we may focus temporarily on our country but we rarely think about Earth as a whole or the human species as a whole. This narrow perspective, perhaps best exemplified by the American consumer, has led to the environ...

While engineers have been quantifying rainfall-runoff processes since the mid-19th century, it is only in the last decade that artificial neural network models have been applied to the same task. This paper evaluates two neural networks in this context: the popular multilayer perceptron (MLP), and the radial basis function network (RBF). Using six-hourly rainfall-runoff data for the River Yangt...

The female and male of Dasybasis (Agelanius) cortesi, new species, is described and illustrated from specimens collected in the National Reserve of Río Clarillo, Cordillera Province, Central Chile. Its relationships to other Dasybasis species are discussed.

Forecasting a hydrologic time series has been one of the most complicated tasks owing to the wide range of data, the uncertainties in the parameters influencing the time series and also due to the non availability of adequate data. Recently Artificial Neural Networks (ANN) have become quite popular in time series forecasting in various fields. This paper demonstrates the use of ANN to forecast ...