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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Article
Author(s)
Nguyen Hien Than1, Che Dinh Ly1, Pham Van Tat2 and Nguyen Ngoc Thanh3
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DOI:10.17265/2162-5263/2016.07.007
Affiliation(s)
1. Department of Natural Resources Management, Institute of Environment and Resources, Vietnam National University, HCMC 700000, Vietnam
2. Faculty of Science and Technology, Hoa Sen University, HCMC 700000, Vietnam
3. Institute of Environmental Science, Engineering and Management, Industrial University of Ho Chi Minh City 700000, Vietnam
ABSTRACT
Recent trends in
environmental management of water resource have enlarged the demand for predicting techniques that can provide reliable, efficient and accurate water
quality. In this case study, the authors applied the Artificial Neural Networks (ANN) to
estimate the water quality index on the Dong Nai River flowing through Dong Nai
and Binh Duong provinces. The information and data including 10 water quality
parameters of the Dong Nai River at 23 monitoring stations were collected
during the recorded time period from 2010 to 2014 to build water quality
prediction models. The results of the study demonstrated that the Water Quality Index (WQI) forecasted
with GRNN was very significant and had
high correlation coefficient (R2 = 0.974
and p = 0.0) compared to the real values of the WQI. Moreover, the ANN models
provided better predicted values than the multiple regression models did.
KEYWORDS
Artificial Neural Networks, water quality forecast, water quality prediction.
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