Performance Prediction Of A Constructed
Wetland Wastewater Treatment Plant
Author(s)
V. Tomenko, S. Ahmed & V. Popov
Abstract
Artificial neural network (ANN) models were developed to predict the
performance of a constructed wetland wastewater treatment plant (CWWTP).
The model assesses the Biochemical Oxygen Demand (BOD) concentration at
outlet of a treatment plant. Training of ANN models was based on experimental
results of a pilot plant study in India. The data used in this work were obtained
under various hydraulic and BOD loading. Regular records of BOD were made
at inlet, and outlet levels through various stages of the treatment process for over
18 months. The ANN-based models were found to provide an efficient and a
robust tool in predicting CWWTP performance.
Keywords: neural networks, constructed wetland, model studies, prediction,
optimization, biochemical oxygen demand.
1 Introduction
The proper operation and management of constructed wetland wastewater
treatment plants (CWWTP) is receiving attention because of the rising concern
about environmental issues and growing importance of sustainable and natural
wastewater treatment techniques. Improper design and operation of a CWWTP
may cause serious environmental and public health implications, as its effluent
may contaminate receiving water body, causing severe aquatic pollution and
spread various water born diseases. For proper design and assessment of quality
of non-conventional wastewater treatment and thereafter to conserve the
receiving water bodies, reliable prediction of effluent from Constructed Wetland
(CW) is essential. A better control can be achieved by developing a
Keywords
neural networks, constructed wetland, model studies, prediction,
optimization, biochemical oxygen demand.
Related Book
Other papers in this volume
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