Adopting an integrated catchment-based management approach for Putrajaya Lake and Wetlands

Majizat, Akashah; Ahmad, Robiah; Noordin, Normaliza; Sharip, Zati

doi:10.1504/ijw.2016.10000411

Cited by 3 publications

(1 citation statement)

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“…To make sure that the wetlands and the Putrajaya Lake remain in balance and serve as favorable urban ecosystems, water quality and catchment are considered in an integrated manner comprising thorough monitoring and assessment of the ecosystem's status (Noordin et al 2016). Data gathered from 17 sampling stations provide information about the water quality, especially to identify point-source-induced pollution in the lake.…”

Section: Putrajaya Lakementioning

confidence: 99%

Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia

Najah

Teo

Fai

et al. 2021

Int. J. Environ. Sci. Technol.

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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.

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Section: Putrajaya Lakementioning

confidence: 99%