Modeling Nitrate Concentration in Natural Streams by Using Artificial Neural Networks
Publication: World Water & Environmental Resources Congress 2003
Abstract
Artificial neural networks (ANNs) are applied to estimating nitrate concentrations in a typical Midwestern river, i.e., the Upper Sangamon River in Illinois. Throughout the Midwestern U.S., nitrate in raw water has recently become an increasingly important problem. This is due to recent changes in the USEPA nitrate standard and to the increasingly widespread use of chemical fertilizers in agriculture. Back-propagation neural networks (BPNN) and radial basis function neural networks (RBFNN) are compared as to their effectiveness in water quality modeling. Training of the RBFNN is much faster than that of the BPNN and yields more robust results. These two types of ANNs are compared to traditional regression and mechanistic water quality modeling, based on overall accuracy and on the frequency of false-negative prediction. The RBFNN achieves the best results of all models in terms of overall accuracy, and both BPNN and RBFNN yield the same false-negative frequency, which is better than that of the traditional models.
Get full access to this article
View all available purchase options and get full access to this chapter.
Information & Authors
Information
Published In
Copyright
© 2003 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
ASCE Technical Topics:
- Artificial intelligence and machine learning
- Chemical compounds
- Chemicals
- Chemistry
- Computer models
- Computer programming
- Computing in civil engineering
- Engineering fundamentals
- Environmental engineering
- Fertilizers
- Model accuracy
- Models (by type)
- Neural networks
- Nitrates
- Pollutants
- Pollution
- Salts
- Water pollution
- Water quality
- Water treatment
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.