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Pengumpulan data penyelidikan alam sekitar dan perubahan iklim serta dasar dan polisi berkaitan

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Recent Submissions

Determination of Critical Environmental, Social, Infrastructure, and Economic Indicators as Evaluation Checklist for Pre-Project Abandonment Plan Assessment inline with Sustainable Development Goal Plan
(IOP Publishing, 2022) SN Abdullah; A Aznah; Mohd Hakim; MF Md Din; M Ponraj; S Mat-Taib
The increasing number of project abandonment because of the Novel Coronavirus pandemic 2019 (Covid-19) calls for better management of abandonment projects. The outbreak of Covid-19 has affected the environment, economy, and society aspects globally. In a developed country like Malaysia, the requirement to submit an abandonment plan is stipulated under the Environmental Guidelines in Malaysia (EGIM) 2016. Therefore, this study aimed to develop a Sustainable Pre-Project Abandonment Plan Assessment Checklist in Malaysia that is in line with the Sustainable Development Goal (SDG) 2030 aspirations. This new Sustainable Pre-Project Abandonment Plan Assessment Checklist in Malaysia is comprehensively structured; is expected to minimise the negative impact of the abandonment process towards the environment, socioeconomy, and efficient management of infrastructure; and complies with the related legislation in Malaysia. In this study, data was collected and analysed using NVivo12. It consisted of findings from documents reviewed such as legislations, journals, and books. From the NVivo12 analysis, the results showed 28 critical indicators for abandonment plan assessment and related legislation that synchronises with SDG 2030 is required to develop the Proposed Sustainable Pre-Project Abandonment Plan Assessment Checklist in Malaysia.
Development of Water Quality Modelling using InfoWork River Simulation in Malacca River, Malaysia and Contribution Towards Total Maximum Daily Load Approach
(IOP Publishing, 2018) Siti Aisyah Che Osmi; Wan Faizal Wan Ishak; Mohammad Adam Azman; Abdullah Siddiqi Ismail; Nurlin Abu Samah
The water quality modelling is an important tool to simulate water quality analysis and river management by addition of pollutant loads. Present work has developed water quality modelling by using InfoWork River Simulation version 10.5, to simulate the water quality condition by doing pollution reduction analysis. The modelling framework is developed to simulate the load reduction for Chemical Oxygen Demand (COD) as the pollutant controlled at the selected area.
Spatial and statistical trend characteristics of rainfall erosivity (R) in upper catchment of Baram River, Borneo
(Springer, 2019) H. Vijith; D. Dodge-Wan
The upper catchment region of the Baram River in Sarawak (Malaysian Borneo) is undergoing severe land degradation due to soil erosion. Heavy rainfall with high erosive power has led to a number of soil erosion hotspots. The goal of the present study is to generate an understanding about the spatial characteristics of seasonal and annual rainfall erosivity (R), which not only control sediment delivery from the region but also determine the quantity of material potentially eroded.
Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island, Malaysia
(Springer, 2012) Biswajeet Pradhan; Amruta Chaudhari; J. Adinarayana; Manfred F. Buchroithner
In this paper, an attempt has been made to assess, prognosis and observe dynamism of soil erosion by universal soil loss equation (USLE) method at Penang Island, Malaysia. Multi-source (map-, space- and ground-based) datasets were used to obtain both static and dynamic factors of USLE, and an integrated analysis was carried out in raster format of GIS. A landslide location map was generated on the basis of image elements interpretation from aerial photos, satellite data and field observations and was used to validate soil erosion intensity in the study area.
Suitability of ANN applied as a hydrological model coupled with statistical downscaling model: a case study in the northern area of Peninsular Malaysia
(Springer, 2015) Zulkarnain Hassan; Supiah Shamsudin; Sobri Harun; Marlinda Abdul Malek; Nuramidah Hamidon
The increase in global surface temperature in response to the changing composition of the atmosphere will significantly impact upon local hydrological regimes and water resources. This situation will then lead to the need for an assessment of regional climate change impacts. The objectives of this study are to determine current and future climate change scenarios using statistical downscaling model (SDSM) and to assess climate change impact on river runoff using artificial neural network (ANN) and identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data (IHACRES) models, respectively.