Civil Engineering and Architecture Vol. 9(5), pp. 1365 - 1375
DOI: 10.13189/cea.2021.090510
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Prediction of Water Quality for Free Water Surface Constructed Wetland Using ANN and MLRA

Rohaya Alias ^1,*, Nur Asmaliza Mohd Noor ¹, Lariyah Mohd Sidek ², Anuar Kasa ^3
1 School of Civil Engineering, College of Engineering, Universiti Teknologi MARA Pahang, 26400 Bandar Tun Razak Jengka, Pahang, Malaysia
² Department of Civil Engineering, College of Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia
³ Department of Civil Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia

ABSTRACT

Constructed wetland is commonly used as a practice to reduce non-point source pollutants and as a stormwater treatment system. For many years, the evaluation of water quality assessment for the constructed wetland is using normal sampling and laboratory work. However, in line with the technology expansion, the prediction for water quality using modelling has been developed. This study focuses on the prediction of water quality parameter for constructed wetland under tropical climate using Artificial Neural Networks (ANN) and Multiple Linear Regressions Analysis (MLRA). There are five input parameters such as water quality at the inlet point, detention time, depth of water, ratio length to width, and rainfall. The output parameters consist of the water quality at the outlet point namely Biochemical Oxygen Demand (BOD5), Chemical Oxygen Demand (COD), Total Phosphorus (TP), Total Nitrogen (TN), and Total Suspended Solid (TSS). Squared correlation coefficient (R2) and root mean square error (RMSE) were applied to assess the model presentation and the result indicated that the ANN model shows excellent performance compared to MLRA. The R² value for each output parameter is higher than 0.90 and the RMSE values were closer to zero. However, TN has shown a very good pollutant removal in constructed wetland compared to other water quality tested. Findings from this study will contribute towards the enhancement of design performance and guideline for constructed wetlands under tropical climate.

KEYWORDS
Artificial Neural Network, Constructed Wetland, Hydraulics Characteristics, Multiple Linear Regression, Prediction

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Rohaya Alias , Nur Asmaliza Mohd Noor , Lariyah Mohd Sidek , Anuar Kasa , "Prediction of Water Quality for Free Water Surface Constructed Wetland Using ANN and MLRA," Civil Engineering and Architecture, Vol. 9, No. 5, pp. 1365 - 1375, 2021. DOI: 10.13189/cea.2021.090510.

(b). APA Format:
Rohaya Alias , Nur Asmaliza Mohd Noor , Lariyah Mohd Sidek , Anuar Kasa (2021). Prediction of Water Quality for Free Water Surface Constructed Wetland Using ANN and MLRA. Civil Engineering and Architecture, 9(5), 1365 - 1375. DOI: 10.13189/cea.2021.090510.