Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia
Agricultural robots; Ammonia; Forecasting; Lakes; Learning algorithms; Machine learning; Motion estimation; Multilayer neural networks; Rivers; Sensitivity analysis; Water quality; Agricultural activities; Health condition; Movement control; Multi layer perceptron; Reconnaissance surveys; Three para...
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2023
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my.uniten.dspace-262802023-05-29T17:08:38Z Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia Najah A. Teo F.Y. Chow M.F. Huang Y.F. Latif S.D. Abdullah S. Ismail M. El-Shafie A. 57214837520 35249518400 57214146115 55807263900 57216081524 56509029800 57210403363 16068189400 Agricultural robots; Ammonia; Forecasting; Lakes; Learning algorithms; Machine learning; Motion estimation; Multilayer neural networks; Rivers; Sensitivity analysis; Water quality; Agricultural activities; Health condition; Movement control; Multi layer perceptron; Reconnaissance surveys; Three parameters; Water quality indexes; World Health Organization; Quality control; COVID-19; lake water; river water; spatiotemporal analysis; surface water; water quality; World Health Organization; Malaysia; Penang; Putrajaya; Putrajaya Lake; West Malaysia Global concerns have been observed due to the outbreak and lockdown causal-based COVID-19, and hence, a global pandemic was announced by the World Health Organization (WHO) in January 2020. The Movement Control Order (MCO) in Malaysia acts to moderate the spread of COVID-19 through the enacted measures. Furthermore, massive industrial, agricultural activities and human encroachment were significantly reduced following the MCO guidelines. In this study, first, a reconnaissance survey was carried out on the effects of MCO on the health conditions of two urban rivers (i.e., Rivers of Klang and Penang) in Malaysia. Secondly, the effect of MCO lockdown on the water quality index (WQI) of a lake (Putrajaya Lake) in Malaysia is considered in this study. Finally, four machine learning algorithms have been investigated to predict WQI and the class in Putrajaya Lake. The main observations based on the analysis showed that noticeable enhancements of varying degrees in the WQI had occurred in the two investigated rivers. With regard to Putrajaya Lake, there is a significant increase in the WQI Class I, from 24% in February 2020 to 94% during the MCO month of March 2020. For WQI prediction, Multi-layer Perceptron (MLP) outperformed other models in predicting the changes in the index with a high level of accuracy. For sensitivity analysis results, it is shown that NH3-N and COD play vital rule and contributing significantly to predicting the class of WQI, followed by BOD, while the remaining three parameters (i.e. pH, DO, and TSS) exhibit a low level of importance. � 2021, Islamic Azad University (IAU). Final 2023-05-29T09:08:38Z 2023-05-29T09:08:38Z 2021 Article 10.1007/s13762-021-03139-y 2-s2.0-85100431119 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100431119&doi=10.1007%2fs13762-021-03139-y&partnerID=40&md5=95f9f1662d0868335fba25599511d2eb https://irepository.uniten.edu.my/handle/123456789/26280 18 4 1009 1018 All Open Access, Bronze, Green Springer Science and Business Media Deutschland GmbH Scopus |
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Agricultural robots; Ammonia; Forecasting; Lakes; Learning algorithms; Machine learning; Motion estimation; Multilayer neural networks; Rivers; Sensitivity analysis; Water quality; Agricultural activities; Health condition; Movement control; Multi layer perceptron; Reconnaissance surveys; Three parameters; Water quality indexes; World Health Organization; Quality control; COVID-19; lake water; river water; spatiotemporal analysis; surface water; water quality; World Health Organization; Malaysia; Penang; Putrajaya; Putrajaya Lake; West Malaysia |
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57214837520 |
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57214837520 Najah A. Teo F.Y. Chow M.F. Huang Y.F. Latif S.D. Abdullah S. Ismail M. El-Shafie A. |
| format |
Article |
| author |
Najah A. Teo F.Y. Chow M.F. Huang Y.F. Latif S.D. Abdullah S. Ismail M. El-Shafie A. |
| spellingShingle |
Najah A. Teo F.Y. Chow M.F. Huang Y.F. Latif S.D. Abdullah S. Ismail M. El-Shafie A. Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia |
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Najah A. |
| title |
Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia |
| title_short |
Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia |
| title_full |
Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia |
| title_fullStr |
Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia |
| title_full_unstemmed |
Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia |
| title_sort |
surface water quality status and prediction during movement control operation order under covid-19 pandemic: case studies in malaysia |
| publisher |
Springer Science and Business Media Deutschland GmbH |
| publishDate |
2023 |
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1806426359873929216 |