1. bookVolume 13 (2017): Issue 4 (December 2017)
Journal Details
License
Format
Journal
eISSN
2784-1391
First Published
12 Apr 2013
Publication timeframe
4 times per year
Languages
English
access type Open Access

Genetic Programming Technique Applied for Flash-Flood Modelling Using Radar Rainfall Estimates

Published Online: 06 Feb 2018
Volume & Issue: Volume 13 (2017) - Issue 4 (December 2017)
Page range: 27 - 38
Journal Details
License
Format
Journal
eISSN
2784-1391
First Published
12 Apr 2013
Publication timeframe
4 times per year
Languages
English
Abstract

The rainfall-runoff transformation is a highly complex dynamic process and the development of fast and robust modelling instruments has always been one of the most important topics for hydrology. Over time, a significant number of hydrological models have been developed with a clear trend towards a process-based approach. The downside of these types of models is the significant amount of data required for building the model and for the calibration process: in practice, the collection of all necessary data for such models proves to be a difficult task. In order to cope with this issue, various data-driven modelling techniques have been introduced for hydrological modelling as an alternative to more traditional approaches, on the basis of their capacity of mapping out complex relationships from observation data. Having the capacity to generate meaningful mathematical structures as results, genetic programming (GP) presents a high potential for rainfall-runoff modelling as a data-driven method. Using ground and radar rainfall observation, the aim of this study is to investigate the GP technique capability for modelling the rainfall-runoff process, taking into consideration a flash-flood event.

Keywords

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