Runoff forecasting by artificial neural network and conventional model

Runoff forecasting by artificial neural network and conventional model

Rainfall runoff models are highly useful for water resources planning and development. In the present study rainfall–runoff model based on Artificial Neural Networks (ANNs) was developed and applied on a watershed in Pakistan. The model was developed to suite the conditions in which the collected da...

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Bibliographic Details
Main Authors: A.R. Ghumman, Yousry M. Ghazaw, A.R. Sohail, K. Watanabe
Format: Article
Language:English
Published: Elsevier 2011-12-01
Series:Alexandria Engineering Journal
Subjects:
Hub River
ANN models
Mathematical models
Low quality data
Runoff analysis
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016812000105
Description
Summary:Rainfall runoff models are highly useful for water resources planning and development. In the present study rainfall–runoff model based on Artificial Neural Networks (ANNs) was developed and applied on a watershed in Pakistan. The model was developed to suite the conditions in which the collected dataset is short and the quality of dataset is questionable. The results of ANN models were compared with a mathematical conceptual model. The cross validation approach was adopted for the generalization of ANN models. The precipitation used data was collected from Meteorological Department Karachi Pakistan. The results confirmed that ANN model is an important alternative to conceptual models and it can be used when the range of collected dataset is short and data is of low standard.
ISSN:1110-0168

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