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...

Precipitation forecasting due to its random nature in space and time always faced with many problems and this uncertainty reduces the validity of the forecasting model. Nowadays nonlinear networks as intelligent systems to predict such complex phenomena are widely used. One of the methods that have been considered in recent years in the fields of hydrology is use of wavelet transform as a moder...

In this paper, Multi-Layer Perceptron and RadialBasis Function Neural Networks, along with the Nearest Neighbour approach and linear regression are utilized for flash-flood forecasting in the mountainous Nysa Klodzka river catchment. It turned out that the Radial-Basis Function Neural Network is the best model for 3and 6-h lead time prediction and the only reliable one for 9-h lead time forecas...

The area of the Dansuie River watershed located in the northern Taiwan is 2,726 km. The main stream runs 159km through the Taipei metropolitan areas as the political, economic, and cultural centers of Taiwan. Owing to short and steep runoff path-lines and non-uniform rainfall patterns, large floods arrive rapidly in the middle-to-downstream reaches of the watershed, causing serious damage. In o...

Most of the recently developed intelligent systems have a knowledge base that incorporates the expertise domain knowledge and use it in reasoning chains during decision making. An important problem that should be solved by an intelligent system is forecasting the evolution of specific parameters that are monitored, for example. Among the various approaches that provide an efficient solution to ...