Neural Networks and Rainfall-Runoff Model, its Calibration and Validation

U. Ghani, A.R. Ghumman, M.A. Shamim

2004

Abstract

In this study a rainfall-runoff model was developed with the help of neural networks. Input to the model is precipitation and potential evapotranspiration (both on monthly basis). Output from the model is the simulated runoff at the watershed outlet. The model was calibrated and tested for Brandu river catchment of Pakistan.The data was collected from Meteorological Department Pakistan. Statistical results showed that the model preformed well. The correlation co-efficient between the simulated and measured data was found to be 87.5%.

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Paper Citation


in Harvard Style

Ghani U., Ghumman A. and Shamim M. (2004). Neural Networks and Rainfall-Runoff Model, its Calibration and Validation . In Proceedings of the First International Workshop on Artificial Neural Networks: Data Preparation Techniques and Application Development - Volume 1: ANNs, (ICINCO 2004) ISBN 972-8865-14-7, pages 60-66. DOI: 10.5220/0001150000600066


in Bibtex Style

@conference{anns04,
author={U. Ghani and A.R. Ghumman and M.A. Shamim},
title={Neural Networks and Rainfall-Runoff Model, its Calibration and Validation},
booktitle={Proceedings of the First International Workshop on Artificial Neural Networks: Data Preparation Techniques and Application Development - Volume 1: ANNs, (ICINCO 2004)},
year={2004},
pages={60-66},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001150000600066},
isbn={972-8865-14-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Workshop on Artificial Neural Networks: Data Preparation Techniques and Application Development - Volume 1: ANNs, (ICINCO 2004)
TI - Neural Networks and Rainfall-Runoff Model, its Calibration and Validation
SN - 972-8865-14-7
AU - Ghani U.
AU - Ghumman A.
AU - Shamim M.
PY - 2004
SP - 60
EP - 66
DO - 10.5220/0001150000600066