Climatic variability, unplanned land use pattern and encroachment into the flood plain are affecting the hydrology of Bagmati river basin of Nepal. In this study, methodology to improve present flood management system with non-structural countermeasures has been elaborated. Study of hydrological condition, basin scale rainfall runoff modeling and inundation analysis is helpful to prepare commun...

Flash Flood Guidance consists of indices that estimate the amount of rain of a certain duration that is needed over a given small basin in order to cause minor flooding. Backwater catchment inundation from swollen rivers or regional groundwater inputs are not significant over the spatial and temporal scales for the majority of upland flash flood prone basins, as such, these effects are not cons...

Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal). Making improvements to extended-range rainfall and flood forecast models, assessing forecast s...

Streamflow forecasting is very important for water resources management and flood defence. In this paper two forecasting methods are compared: ARIMA versus a multilayer perceptron neural network. This comparison is done by forecasting a streamflow of a Mexican river. Surprising results showed that in a monthly basis, ARIMA has lower prediction errors than this Neural Network. Key-Words: Auto re...

Among the many challenges of Alpine flood prediction is describing complex, meteo-hydrological processes in a simplified, robust manner that can be easily integrated into operational forecasting. In this dissertation, improved methods to characterize these processes are developed and integrated into the hydrological modeling component of an operational flood forecasting system used in the Swiss...

Existing flood forecasting models are highly data specific, and their operational performance depends upon the science used to build and operate these models as well as their ability to respond to dynamic and rapidly changing events. Soft computing is one of the latest approaches for the development of systems, which possess computational intelligence. It attempts to integrate several different...

Flood forecasting remains a very important task. Good forecast values with sufficient lead times can help reduce flood damages significantly. This paper proposes two types of black-box model obtained by using multiple regression analysis and backpropagation neural networks in forecasting 6-h water levels at three important stations on the upstream section of the Red River basin, North Vietnam. ...

This paper describes a workflow management system that was implemented according to the requirements of a Flood forecasting application [1] developed in the CrossGrid project [2]. The flood forecasting application contains several simulation models (meteorological, hydrological, hydraulic) implemented as the grid jobs. A need for a cascade execution of these models has been a motivation for cre...

the multi-criteria decision making model is an important tool for decision making in water resource management. in this paper, the topsis model was used to rank seven flood management options in the gorganrood river flood management project, including conservation of natural condition, golestan reservoir management, levee construction, diversions-channel construction, flood forecasting and warn...

Flooding in the major river basins of the Central Europe is a recurrent event affecting many countries. Almost every year, it takes away lives and causes damage to infrastructure, agricultural and industrial production and severely affects socio-economic development. Recurring floods of the magnitude and frequency observed in this region is a significant impediment, which requires rapid develop...