Faecal coliform (FC) concentration was monitored weekly in the Tangipahoa River over an eight year period. Available USGS discharge and precipitation data were used to construct a nonparametric multiplicative regression (NPMR) model for both forecasting and backcasting of FC density. NPMR backcasting and forecasting of FC allowed for estimation of concentration for any flow regime. During this ...

A new hybrid model which combines wavelets and Artificial Neural Network (ANN) called wavelet neural network (WNN) model was proposed in the current study and applied for time series modeling of river flow. The time series of daily river flow of the Malaprabha River basin (Karnataka state, India) were analyzed by the WNN model. The observed time series are decomposed into sub-series using discr...

The aim of this work is the development of an integrated Data Based Mechanistic (DBM) rainfall-flow/flow-routing model of the Upper River Narew catchment and the river reach between Bondary and Suraż suitable for scenario analysis. The modelling tool developed is formulated in MATLAB-SIMULINK language. It has a flexible, modular structure that can easily be extended by adding new features, such...

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

— In this paper we introduce a new symbolic type neural tree network called symbolic function network (SFN) that is based on using elementary functions to model systems in a symbolic form. The proposed formulation permits feature selection, functional selection, and flexible structure. We applied this model on the River Flow forecasting problem. The results found to be superior in both fitness ...

Due to the serious climate change, severe weather conditions constantly change the environment’s phenomena. Floods turned out to be one of the most devastating catastrophes for Europe's population, economy and environment during the past decades. In this paper we are using geographic information systems (GIS) as a modeling tool for the prediction and prevention of such effects. We provide an em...

Models incorporating the appropriate temporal scales of dominant indicators for low flows are assumed to perform better than models with arbitrary selected temporal scales. In this paper, we investigate appropriate temporal scales of dominant low flow indicators: precipitation (P), evapotranspiration (ET) and the standardized groundwater storage index (G). This analysis is done in the context o...