<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The use of artificial neural networks (ANNs) in modelling the hydrological processes has become a common approach in the last two decades, among side the traditional methods. In regard to the rainfall-runoff modelling, in both traditional and ANN models the use of ground rainfall measurements is prevalent, which can be challenging in areas with low rain gauging station density, especially in catchments where strong focused rainfall can generate flash-floods. The weather radar technology can prove to be a solution for such areas by providing rain estimates with good time and space resolution. This paper presents a comparison between different ANN setups using as input both ground and radar observations for modelling the rainfall-runoff process for Bahluet catchment, with focus on a flash-flood observed in the catchment.</p></abstract>

The use of artificial neural networks (ANNs) in modelling the hydrological processes has become a common approach in the last two decades, among side the traditional methods. In regard to the rainfall-runoff modelling, in both traditional and ANN models the use of ground rainfall measurements is prevalent, which can be challenging in areas with low rain gauging station density, especially in catchments where strong focused rainfall can generate flash-floods. The weather radar technology can prove to be a solution for such areas by providing rain estimates with good time and space resolution. This paper presents a comparison between different ANN setups using as input both ground and radar observations for modelling the rainfall-runoff process for Bahluet catchment, with focus on a flash-flood observed in the catchment.

FLASH-FLOOD MODELLING WITH ARTIFICIAL NEURAL NETWORKS USING RADAR RAINFALL ESTIMATES

Modelling in Civil Environmental Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The use of artificial neural networks (ANNs) in modelling the hydrological processes has become a common approach in the last two decades, among side the...

FLASH-FLOOD MODELLING WITH ARTIFICIAL NEURAL NETWORKS USING RADAR RAINFALL ESTIMATES

Online veröffentlicht: 07. Nov. 2017

Seitenbereich: 10 - 20

DOI: https://doi.org/10.1515/mmce-2017-0008

Schlüsselwörter
Artificial neural network, flash-floods, radar rainfall estimates, rainfall-runoff modelling

© by Cristian Dinu

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

FLASH-FLOOD MODELLING WITH ARTIFICIAL NEURAL NETWORKS USING RADAR RAINFALL ESTIMATES

Online veröffentlicht: 07. Nov. 2017

Seitenbereich: 10 - 20

DOI: https://doi.org/10.1515/mmce-2017-0008

SchlüsselwörterArtificial neural network, flash-floods, radar rainfall estimates, rainfall-runoff modelling

© by Cristian Dinu

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Artificial neural network, flash-floods, radar rainfall estimates, rainfall-runoff modelling