Assessing the effect of future landslide on ecosystem services in Aqabat Al-Sulbat region,Saudi Arabia     

Alqadhi  Saeed  Mallick  Javed  Talukdar  Swapan  Ahmed  Mohd.  Khan  Roohul Abad  Sarkar  Showmitra Kumar  Rahman  Atiqur 《Natural Hazards》2022,111(1):641-660

Natural Hazards - Co-occurrence events of droughts and heatwaves characterized by abnormal low soil moisture (SM) and high temperatures may cause more significant impacts on society and natural...  相似文献   

Soil erosion assessment on hillslope of GCE using RUSLE model     

Md. Rabiul Islam  Wan Zurina Wan Jaafar  Lai Sai Hin  Normaniza Osman  Moktar Aziz Mohd Din  Fathiah Mohamed Zuki  Prashant Srivastava  Tanvir Islam  Md. Ibrahim Adham 《Journal of Earth System Science》2018,127(4):50

A new method for obtaining the C factor (i.e., vegetation cover and management factor) of the RUSLE model is proposed. The method focuses on the derivation of the C factor based on the vegetation density to obtain a more reliable erosion prediction. Soil erosion that occurs on the hillslope along the highway is one of the major problems in Malaysia, which is exposed to a relatively high amount of annual rainfall due to the two different monsoon seasons. As vegetation cover is one of the important factors in the RUSLE model, a new method that accounts for a vegetation density is proposed in this study. A hillslope near the Guthrie Corridor Expressway (GCE), Malaysia, is chosen as an experimental site whereby eight square plots with the size of \(8\times 8\) and \(5\times 5\) m are set up. A vegetation density available on these plots is measured by analyzing the taken image followed by linking the C factor with the measured vegetation density using several established formulas. Finally, erosion prediction is computed based on the RUSLE model in the Geographical Information System (GIS) platform. The C factor obtained by the proposed method is compared with that of the soil erosion guideline Malaysia, thereby predicted erosion is determined by both the C values. Result shows that the C value from the proposed method varies from 0.0162 to 0.125, which is lower compared to the C value from the soil erosion guideline, i.e., 0.8. Meanwhile predicted erosion computed from the proposed C value is between 0.410 and \(3.925\, \hbox {t ha}^{-1 }\,\hbox {yr}^{-1}\) compared to 9.367 to \(34.496\, \hbox {t ha}^{-1}\,\hbox {yr}^{-1 }\) range based on the C value of 0.8. It can be concluded that the proposed method of obtaining a reasonable C value is acceptable as the computed predicted erosion is found to be classified as a very low zone, i.e. less than \(10\, \hbox {t ha}^{-1 }\,\hbox {yr}^{-1}\) whereas the predicted erosion based on the guideline has classified the study area as a low zone of erosion, i.e., between 10 and \(50\, \hbox {t ha}^{-1 }\,\hbox {yr}^{-1}\).  相似文献   

A hybrid model using machine learning methods and GIS for potential rockfall source identification from airborne laser scanning data     

Ali Mutar Fanos  Biswajeet Pradhan  Shattri Mansor  Zainuddin Md Yusoff  Ahmad Fikri bin Abdullah 《Landslides》2018,15(9):1833-1850

The main objectives of this paper are to design and evaluate a hybrid approach based on Gaussian mixture model (GMM) and random forest (RF) for detecting rockfall source areas using airborne laser scanning data. The former model was used to calculate automatically slope angle thresholds for different type of landslides such as shallow, translational, rotational, rotational-translational, complex, debris flow, and rockfalls. After calculating the slope angle thresholds, a homogenous morphometric land use area (HMLA) was constructed to improve the performance of the model computations and reduce the sensitivity of the model to the variations in different conditioning factors. After that, the support vector machine (SVM) was applied in addition to backward elimination (BE) to select and rank the conditioning factors considering the type of landslides. Then, different machine learning methods [artificial neural network (ANN), logistic regression (LR), and random forest (RF) were trained with the selected best factors and previously prepared inventory datasets. The best fit method (RF) was then used to generate the probability maps and then the source areas were detected by combining the slope raster (reclassified according to the thresholds found by the GMM model) and the probability maps. The accuracy assessment shows that the proposed hybrid model could detect the potential rockfalls with an accuracy of 0.92 based on training data and 0.96 on validation data. Overall, the proposed model is an efficient model for identifying rockfall source areas in the presence of other types of landslides with an accepted generalization performance.  相似文献   

Groundwater beneath the urban area of Khan Younis City,southern Gaza Strip (Palestine): hydrochemistry and water quality     

Jabal  Mohd S. Abu  Abustan  Ismail  Rozaimy  Mohd Remy  El Najar  Hussam 《Arabian Journal of Geosciences》2015,8(4):2203-2215

Arabian Journal of Geosciences - This paper presents the results of a groundwater hydrochemical assessment in the urban area of Khan Younis City in the southern Gaza Strip by measuring its...  相似文献   

Heavy metal resistant endophytic fungi isolated from Nypa fruticans in Kuching Wetland National Park     

Choo  Jenny  Sabri  Nuraini Binti Mohd  Tan  Daniel  Mujahid  Aazani  Müller  Moritz 《Ocean Science Journal》2015,50(2):445-453

Heavy metal pollution is an environmental issue globally and the aim of this study was to isolate endophytic fungi from mangrove wetlands of Sarawak to assess and test their ability to grow in the presence of various heavy metals (copper (Cu), zinc (Zn), lead (Pb), and chromium (Cr)). Samples of Nypa fruticans were collected from Kuching Wetland National Park (KWNP) for subsequent endophyte isolation. Ninety-three (93) isolates were obtained and assessed and the most resistant isolates (growing at concentrations up to 1000 ppm) were identified using fungal primers ITS 1 and ITS 4. All of the endophytic fungi were identified to be closely related to Pestalotiopsis sp. and this is to our knowledge the first study reporting the ability of Pestalotiopsis sp. to grow at high concentrations of copper, lead, zinc and chromium. Our results highlight the potential of using endophytic fungi for the treatment of heavy metal pollution, for example as biosorbents.

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Development of Rapid Consolidation Equipment for Cohesive Soil   总被引：1，自引：1，他引：0  

Khairul Anuar Kassim  Ahmad Safuan A. Rashid  Ahmad Beng Hong Kueh  Chong Siaw Yah  Lam Chee Siang  Norhazilan Mohd Noor  Hossein Moayedi 《Geotechnical and Geological Engineering》2015,33(1):167-174

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The impact of climate change on sea level rise at Peninsular Malaysia and Sabah–Sarawak     

Ali Ercan  Mohd Fauzi Bin Mohamad  M. Levent Kavvas 《水文研究》2013,27(3):367-377

The sea level change along the Peninsular Malaysia and Sabah–Sarawak coastlines for the 21st century is investigated along the coastal areas of Peninsular Malaysia and Sabah–Sarawak because of the expected climate change during the 21st century. The spatial variation of the sea level change is estimated by assimilating the global mean sea level projections from the Atmosphere–Ocean coupled Global Climate Model/General Circulation Model (AOGCM) simulations to the satellite altimeter observations along the subject coastlines. Using the assimilated AOGCM projections, the sea level around the Peninsular Malaysia coastline is projected to rise with a mean in the range of 0.066 to 0.141 m in 2040 and 0.253 m to 0.517 m in 2100. Using the assimilated AOGCM projections, the sea level around Sabah–Sarawak coastlines is projected to rise with a mean in the range of 0.115 m to 0.291 m in 2040 and 0.432 m to 1.064 m in 2100. The highest sea level rise occurs at the northeast and northwest regions in Peninsular Malaysia and at north and east sectors of Sabah in Sabah–Sarawak coastline. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

Simulation of horizontal well performance using Visual MODFLOW   总被引：2，自引：2，他引：0  

Wan Mohd Zamri W. Ismail  Ismail Yusoff  Bahaa-eldin E. A. Rahim 《Environmental Earth Sciences》2013,68(4):1119-1126

A proposed horizontal well or radial collector well installation in shallow aquifers to enhance water withdrawal rates in Pintu Geng well field in Kelantan, Malaysia was simulated using the Drainage Package of MODFLOW groundwater model. The modelling exercise aimed at identifying an optimum pumping rate that would safely achieve the desired drawdown of less than 2 m in an area of 300 m radius surrounding the Pintu Geng horizontal collector well. The model also would serve as a basis for the design of the horizontal well components. High degree of grid refinement for the well location is needed to simulate the real field installation. However, for the purpose of designing water withdrawal systems, it is important to obtain the correct production rate of these wells for a given drawdown. A transient groundwater flow model was calibrated and validated with few assumptions of the horizontal well hydraulic properties. The model demonstrates that under natural flow condition at ?3 m depth, the six collectors (drains) tap a volume of 19,200–43,700 m³/day. A steady-state model was also developed to predict the capture zone delineation. Attention is also given to the impact of the well installation to the surrounding 300 m radius by inspecting the degree of the drawdown.  相似文献   

Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery     

Mustafa Neamah Jebur  Helmi Zulhaidi Mohd Shafri  Mahyat Shafapour Tehrany 《国际地球制图》2013,28(7):792-806

To have sustainable management and proper decision-making, timely acquisition and analysis of surface features are necessary. Traditional pixel-based analysis is the popular way to extract different categories, but it is not comparable by the achievements that can be achieved through the object-based method that uses the additional characteristics of features in the process of classification. In this paper, three types of classification were used to classify SPOT 5 satellite image in mapping land cover; Support vector machine (SVM) pixel-based, SVM object-based and Decision Tree (DT) pixel-based classification. Normalised Difference Vegetation Index and the brightness value of two infrared bands (NIR and SWIR) were used in manually developed DT classification. The classification of the SVM (pixel based) was generated using the selected groups of pixels that represent the selected features. In addition, the SVM (object based) was implemented by using radial-based function kernel. The classified features were oil palm, rubber, urban area, soil, water and other vegetation. The study found that the overall classification of the DT was the lowest at 69.87% while those of SVM (pixel based) and SVM (object based) were 76.67 and 81.25%, respectively.  相似文献   

Electrical resistivity imaging and hydrochemical analysis for groundwater investigation in Kuala Langat,Malaysia     

Mahmoud Khaki  Ismail Yusoff  Nur Islami 《水文科学杂志》2013,58(4):751-762

ABSTRACT

Integrated two-dimensional electrical resistivity imaging (ERI) and hydrochemical surveys were used to investigate the groundwater alluvial aquifer in Kuala Langat, Malaysia. The study in the Langat basin considered the thickness of the aquifer, the depth of the bedrock, the regions influenced by seawater intrusion, and the monitoring of water levels. The resistivity imaging results show that the upper layer consists of clay, while the second layer is an aquifer whose thickness varies mostly in the range of 10–30 m, and in some cases extends to 40 m. The bedrock depth varies from 30 to 65 m. The chemical analyses were carried out on groundwater samples from nine boreholes collected between 2008 and 2012. The analyses indicate that the total dissolved solids (TDS) exceed 1000 mg L^-1 near the coastal area and are often less than 500 mg L^-1 further inland. The ERI and hydrochemical analyses reveal that groundwater in the study area, especially towards the coast, is a mixture of brackish and fresh waters.