Various models, based on a filtered Poisson process, are used for the flow of a river. The aim is to forecast the next peak value of the flow, given that another peak was observed not too long ago. The most realistic model is the one when the time between the successive peaks does not have an exponential distribution, as is often assumed. An application to the Delaware River, in the USA, is pre...

This study aims to set up a comprehensive approach to the Vulnerability and Impact Assessment (VIA) of river erosion and to suggest Ecosystem-based Adaptation (EbA) practices. Based on the analysis of vulnerability using the Driver-Pressure-State-Impact-Response (DPSIR) framework, this paper discusses some of the significant climatic (rainfall pattern, temperature, seasonal drift, cold wave and...

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

Traffic flow forecasting is useful for controlling traffic flow, traffic lights, and travel times. This study uses a multilayer perceptron neural network and the mutual information (MI) technique to forecast traffic flow and compares the prediction results with conventional traffic flow forecasting methods. The MI method is used to calculate the interdependency of historical traffic data and fu...

The hydrological model WASA (Model of Water Availability in Semi-Arid Environments) has been developed as a deterministic, spatially distributed model, consisting of conceptual, process-based approaches, to quantify water availability in large semi-arid regions. Water availability can be calculated with a daily resolution and on different spatial levels. The model has been applied by Güntner (2...

Global hydrological cycles mainly depend on climate changes whose occurrence is predominantly triggered by solar and terrestrial influence, and the knowledge of the high water regime is widely applied in hydrology. Regular monitoring and studying of river water level behavior is important from several perspectives. On the basis of the given data, by using modifications of general approaches kno...

Combined forecasting has attracted lots of attention in the hydrological community recently. In this study, an autoregressive and moving average model, a periodic AR model, a normal multi-layer perceptron artificial neural network model and a periodic artificial neural network model are fitted to a univariate daily stream flow process for the upper Yellow River in China to forecast stream flows...