High-Performance Forecasting of Spring Flood in Mountain River Basins with Complex Landscape Structure

Short term river flood forecasting with neural networks

This paper reports results obtained using artificial neural networks (ANN) models for shortterm river flow forecasting under heavy rain storms, in the upper Serpis river basin (460 km), with the outlet in Beniarrés reservoir (29 hm ). The system is monitored by 6 raingauges, providing 5-min rainfall intensities, while reservoir inflows are derived from depth measurements in the reservoir every ...

Comparison of several flood forecasting models in Yangtze River

Abstract In a flood-prone region, quick and accurate flood forecasting is imperative. It can extend the lead time for issuing disaster warnings and allow sufficient time for habitants in hazardous areas to take appropriate action, such as evacuation. In this paper, two hybrid models based on recent artificial intelligence technology, namely, genetic algorithm-based artificial neural network (AN...

River Basins: Water and Complex Adaptive Systems

River Flood Forecasting Using Complementary Muskingum Rating Equations

A model for real-time flood forecasting in river systems with large drainage areas has been developed. Flow variations between upstream and downstream stations are interlinked and are typically governed by reach properties. Unique paired variations establish useful flow correspondence resulting in inflow and outflow forecasting models for a reach. The proposed model can generate forecasts with ...

Regression-based Daugava River Flood Forecasting and Monitoring

The paper discusses the application of linear and symbolic regression to forecast and monitor river floods. Main tasks of the research are to find an analytical model of river flow and to forecast it. The challenges are a small set of flow measurements and a small number of input factors. Genetic programming is used in the task of symbolic regression. To train the model, historical data of the ...