Pollutant Loading Analysis of Suspended Solid, Nitrogen and Phosphorus at Bertam Catchment, Cameron Highlands using MUSIC

Noh, N. S. Mohd; Sidek, Lariyah Mohd; Haron, S. H.; Puad, Amirah Hanim Mohd; Selamat, Zalilah

doi:10.14419/ijet.v7i4.35.23100

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…There are six typical physicochemical water quality parameters used; BOD, COD, DO, ammoniacal nitrogen (NH 3 -N), SS and pH value [3]. Second process is the calculation of sub-index value for each selected parameter where specific best fitted equations were developed to transform the measured water quality value to a non-dimensional sub-index value [4,33,34] The third process is to identify parameters weighting factor where each parameter is assigned to have different weight value as per expert panel opinions. According to the WQI Eq.…”

Section: Water Quality Indexmentioning

confidence: 99%

Developing an ensembled machine learning model for predicting water quality index in Johor River Basin

Sidek,

Mohiyaden,

Marufuzzaman

et al. 2024

Environ Sci Eur

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Currently, the Water Quality Index (WQI) model becomes a widely used tool to evaluate surface water quality for agriculture, domestic and industrial. WQI is one of the simplest mathematical tools that can assist water operator in decision making in assessing the quality of water and it is widely used in the last years. The water quality analysis and prediction is conducted for Johor River Basin incorporating the upstream to downstream water quality monitoring station data of the river. In this research, the numerical method is first used to calculate the WQI and identify the classes for validating the prediction results. Then, two ensemble and optimized machine learning models including gradient boosting regression (GB) and random forest regression (RF) are employed to predict the WQI. The study area selected is the Johor River basin located in Johor, Peninsular Malaysia. The initial phase of this study involves analyzing all available data on parameters concerning the river, aiming to gain a comprehensive understanding of the overall water quality within the river basin. Through temporal analysis, it was determined that Mg, E. coli, SS, and DS emerge as critical factors affecting water quality in this river basin. Then, in terms of WQI calculation, feature importance method is used to identify the most important parameters that can be used to predict the WQI. Finally, an ensemble-based machine learning model is designed to predict the WQI using three parameters. Two ensemble ML approaches are chosen to predict the WQI in the study area and achieved a R2 of 0.86 for RF-based regression and 0.85 for GB-based ML technique. Finally, this research proves that using only the biochemical oxygen demand (BOD), the chemical oxygen demand (COD) and percentage of dissolved oxygen (DO%), the WQI can be predicted accurately and almost 96 times out of 100 sample, the water class can be predicted using GB ensembled ML algorithm. Moving forward, stakeholders may opt to integrate this research into their analyses, potentially yielding economic reliability and time savings.

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Section: Water Quality Indexmentioning

confidence: 99%

Developing an ensembled machine learning model for predicting water quality index in Johor River Basin

Sidek,

Mohiyaden,

Marufuzzaman

et al. 2024

Environ Sci Eur

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“…With the increasing number of land opening for agricultural purpose, it is considered as a nonpoint source of pollution. Nonpoint sources become difficult to determine due to pollutant movement through surface and subsurface pathway that also depends on many factors such as weather and slope characteristics [4]. The overall agricultural coverage in Cameron Highlands is relatively small and is mostly done on steep slopes.…”

Section: Introductionmentioning

confidence: 99%

Erosion and Sediment Control Best Management Practices in Agricultural Farms for Effective Reservoir Sedimentation Management at Cameron Highlands

Noh*,

Sidek,

Wayayok

et al. 2019

IJRTE

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For many years, lands in Cameron Highland have been opened and leveled for agricultural farming and intensive crop production. Land-disturbing activities such as agricultural operations that are conducted on regions with steep slopes leads to a high potential of soil erosion, sedimentation and landslide occurrences. As a results, this phenomenon producing large amounts of sediment transported and deposited to the receiving waters or reservoirs. The development of best management practices (BMPs) for agricultural activities is an important step towards minimizing the amount of soil erosion and landslide incidents in Cameron Highlands. Therefore, this Erosion and Sediment Control Guideline for Agricultural Activities in Hilly Area aims to minimize erosion and sedimentation from the agricultural area in Cameron Highlands especially in the scope of reservoir sedimentation management. There numbers of steps taken in order to establish this guidelines. The first step is to define the scope with the purpose of the guideline and conduct a literature review. In order to assess the quality and feasibility of the study to formulate the frameworks, engagement with stakeholders was conducted. Lastly is to undergo review and update based on the recommendations by related stakeholders. Finally, before the establishment of guidelines, all recommendations by related stakeholders are take in account that consists of Best Management Practices components which will be applied in the agricultural area to mitigate issues and problems especially in erosion control and reservoir sedimentation management. The Erosion Control Measures are including agronomic measures, soil management, mechanical methods and Rainwater Harvesting Techniques. Subsequently, these measures are used to apply in open or sheltered farming to control the erosion and sedimentation issues based on the erosion risk level. As a conclusion, this guideline will be useful for the stakeholders especially to local community, dam owners and local authority to mitigate and solve the issues related to erosion and sedimentation in hilly agricultural area

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Stormwater characterisation and modelling for Sungai Air Hitam in Selangor, Malaysia using model for urban stormwater improvement conceptualisation (music)

Idros,

Sidek,

Rahim

et al. 2024

Ecological Indicators

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Pollutant Loading Analysis of Suspended Solid, Nitrogen and Phosphorus at Bertam Catchment, Cameron Highlands using MUSIC

Cited by 5 publications

References 15 publications

Developing an ensembled machine learning model for predicting water quality index in Johor River Basin

Developing an ensembled machine learning model for predicting water quality index in Johor River Basin

Erosion and Sediment Control Best Management Practices in Agricultural Farms for Effective Reservoir Sedimentation Management at Cameron Highlands

Stormwater characterisation and modelling for Sungai Air Hitam in Selangor, Malaysia using model for urban stormwater improvement conceptualisation (music)

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