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An Artificial Neural Network Model for Rainfall Forecasting in Bangkok, Thailand : Volume 5, Issue 1 (30/01/2008)

By Hung, N. Q.

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Book Id: WPLBN0003976311
Format Type: PDF Article :
File Size: Pages 36
Reproduction Date: 2015

Title: An Artificial Neural Network Model for Rainfall Forecasting in Bangkok, Thailand : Volume 5, Issue 1 (30/01/2008)  
Author: Hung, N. Q.
Volume: Vol. 5, Issue 1
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Tripathi, N. K., Babel, M. S., Weesakul, S., & Hung, N. Q. (2008). An Artificial Neural Network Model for Rainfall Forecasting in Bangkok, Thailand : Volume 5, Issue 1 (30/01/2008). Retrieved from

Description: School of Engineering and Technology, Asian Institute of Technology, Thailand. The present study developed an artificial neural network (ANN) model to overcome the difficulties in training the ANN models with continuous data consisting of rainy and non-rainy days. Among the six models analyzed the ANN model which used generalized feedforward type network and a hyperbolic tangent function and a combination of meteorological parameters (relative humidity, air pressure, wet bulb temperature and cloudiness), and the rainfall at the point of forecasting and rainfall at the surrounding stations, as an input for training of the model was found most satisfactory in forecasting rainfall in Bangkok, Thailand. The developed ANN model was applied to derive rainfall forecast from 1 to 6 h ahead at 75 rain gauge stations in the study area as forecast point from the data of 3 consecutive years (1997–1999). Results were highly satisfactory for rainfall forecast 1 to 3 h ahead. Sensitivity analysis indicated that the most important input parameter beside rainfall itself is the wet bulb temperature in forecasting rainfall. Based on these results, it is recommended that the developed ANN model can be used for real-time rainfall forecasting and flood management in Bangkok, Thailand.

An artificial neural network model for rainfall forecasting in Bangkok, Thailand

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