Composition of deposited sediment and its temporal variation in a disturbed tropical catchment in the Kelantan river basin, Peninsular Malaysia

Sugumaran, Dhinesh; Blake, William; Millward, Geoffrey; Yusop, Zulkifli; Yusoff, Abdull Rahim Mohd; Mohamad, Noor Ashikin; Nainar, Anand; Annammala, Kogila Vani

doi:10.1007/s11356-022-19904-6

Cited by 7 publications

(4 citation statements)

References 47 publications

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“…Additionally, most of the landslides that occur in Langat River Basin are caused by heavy rain, which occurs most frequently from May to September in the southwest monsoon and from October to March in the northeast monsoon. These findings are consistent with [85,116,117], which found that increasing rainfall intensity throughout the monsoon season will lead to an increase in landslide occurrences. The high intensity of rainfall is frequently related to the slope stability, where it affects the run-off water pressure.…”

Section: Discussionsupporting

confidence: 90%

“…The growth in population has also increased the environmental burden due to development pressure to fulfil needs and demands. Human activities, such as the development of buildings, roads, and agricultural activities, will change the slope structure and stability, thereby leading to landslide occurrences [42,115,116]. Given the importance of this region in supporting urban activities, it must be carefully preserved and managed to ensure that local communities continue with a high quality of life and benefit from any future development [117].…”

Section: Discussionmentioning

confidence: 99%

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Landslide Susceptibility Model Using Artificial Neural Network (ANN) Approach in Langat River Basin, Selangor, Malaysia

Selamat

Majid

Taha

et al. 2022

Land

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Landslides are a natural hazard that can endanger human life and cause severe environmental damage. A landslide susceptibility map is essential for planning, managing, and preventing landslides occurrences to minimize losses. A variety of techniques are employed to map landslide susceptibility; however, their capability differs depending on the studies. The aim of the research is to produce a landslide susceptibility map for the Langat River Basin in Selangor, Malaysia, using an Artificial Neural Network (ANN). A landslide inventory map contained a total of 140 landslide locations which were randomly separated into training and testing with ratio 70:30. Nine landslide conditioning factors were selected as model input, including: elevation, slope, aspect, curvature, Topographic Wetness Index (TWI), distance to road, distance to river, lithology, and rainfall. The area under the curve (AUC) and several statistical measures of analyses (sensitivity, specificity, accuracy, positive predictive value, and negative predictive value) were used to validate the landslide predictive model. The ANN predictive model was considered and achieved very good results on validation assessment, with an AUC value of 0.940 for both training and testing datasets. This study found rainfall to be the most crucial factor affecting landslide occurrence in the Langat River Basin, with a 0.248 weight index, followed by distance to road (0.200) and elevation (0.136). The results showed that the most susceptible area is located in the north-east of the Langat River Basin. This map might be useful for development planning and management to prevent landslide occurrences in Langat River Basin.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Landslide Susceptibility Model Using Artificial Neural Network (ANN) Approach in Langat River Basin, Selangor, Malaysia

Selamat

Majid

Taha

et al. 2022

Land

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“…Besides material mobilization within the channel, it is also possible that other deposition mechanisms, namely material mobilization from the catchment side slope to the river channel, may have contributed to the changes in the river bars (Chappell et al 2004). This can only be ascertained with further geochemical or geophysical investigation in the future (Sugumaran et al 2023). At present, our aim is not to balance the sediment budget but to demonstrate the extent of bedload mobilization following an earthquake.…”

Section: Discussionmentioning

confidence: 99%

Assessment of immediate and five-year earthquake impacts on river systems in sabah, Malaysia using multi-temporal satellite imageries

Chai,

Nainar,

Roslee

et al. 2024

Geoenviron Disasters

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Background Earthquake is one of the most destructive natural disasters, which cause immediate and long-term changes to the river systems. This research aimed to examine the immediate and five-year impacts of the 2015 Ranau Earthquake (6.0 Mw) on river systems in Malaysian state of Sabah, a region of low earthquake hazard. Methods We used object-based classification on Landsat 8 (2014 and 2015) and Sentinel-2A (2020) satellite imageries to derive land cover time series for investigating the impacts on the riparian areas. Results The earthquake removed vegetation in the riparian zones of four rivers, the highest being the Penataran River (69.21 ha). During the immediate impact period (2014–2015), river bar formation occurred in all rivers, with the largest increase occurring in the Kadamaian River (56.97 ha), followed by the Panataran River (54.36 ha), which had no river bar before the earthquake. The river bar of the Kadamaian River continued to increase, whereas the river bar of the Panataran River decreased five years after the earthquake. Land cover transition analysis revealed that 78.39 ha of vegetation, barren land, and river water areas changed to river bars in the Kadamaian riparian area during the immediate impact period. Except for 26.87% of river bars in the Kadamaian riparian area in 2015, most river bars transitioned to other land cover types five years later. During the period of immediate impact, 22.05 ha of vegetation and 10.71 ha of river water were transformed into river bars along the Penataran River. Five years later, except for 16.2 ha, all river bar areas had transitioned to other cover types. Additionally, 17.7 ha of new river bars were formed. This study provides crucial data on post-earthquake land cover changes, particularly river bar formation and changes, for assessing the earthquake impacts on the river systems and supporting impact mitigation.

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“…The majority of research conducted in Malaysia focuses on the levels of potentially harmful metals such as Zn, Cu, Ni, Mn, Cr, Cd, Pb, and As in sediment or the muscle tissue of bivalves captured in mangrove swamp habitats [13][14][15][16]. Only a small number of researchers have studied the content of macro elements such Ca, Mg, Na, K, and Fe in sediments or the muscle of bivalves [17,18]. Finding out whether macro elements can affect the bioaccumulation of major and trace elements is equally important.…”

Section: Introductionmentioning

confidence: 99%

Bioaccumulation of Metals in Mangrove Snail (Cerithidea obtusa) from Southwest Johor, Malaysia

Krishnan¹,

Saion²,

Yap³

et al. 2022

eer

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Pollutants are persistent in the environment, taint the food chain, and harm people's health because of their toxicity. In this study, mangrove snails called Cerithidea obtusa (C. Obtusa) were gathered from Southwest Johor, Malaysia, and the amounts of macro and micro elements Ca, Fe, K, Mg, Na, As, Mn, and Zn in their soft tissues, shells, and related surface sediments were analysed. The Neutron Activation Analysis (NAA) method was used to calculate the elements concentration. The mean concentrations of Ca,

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Composition of deposited sediment and its temporal variation in a disturbed tropical catchment in the Kelantan river basin, Peninsular Malaysia

Cited by 7 publications

References 47 publications

Landslide Susceptibility Model Using Artificial Neural Network (ANN) Approach in Langat River Basin, Selangor, Malaysia

Landslide Susceptibility Model Using Artificial Neural Network (ANN) Approach in Langat River Basin, Selangor, Malaysia

Assessment of immediate and five-year earthquake impacts on river systems in sabah, Malaysia using multi-temporal satellite imageries

Bioaccumulation of Metals in Mangrove Snail (Cerithidea obtusa) from Southwest Johor, Malaysia

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