Articles | Volume 13, issue 4
https://doi.org/10.5194/npg-13-443-2006
https://doi.org/10.5194/npg-13-443-2006
25 Aug 2006
 | 25 Aug 2006

Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study

A. Piotrowski, J. J. Napiórkowski, and P.M. Rowiński

Abstract. In this paper, Multi-Layer Perceptron and Radial-Basis 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 3- and 6-h lead time prediction and the only reliable one for 9-h lead time forecasting for the largest flood used as a test case.