In this paper, with debris flow in Zhouqu as the research object, combined with experiments such as cation exchange capacity (CEC), mineral chemical composition and water quality analysis, relation between water and salt in solid source forming debris flow was studied via soil column leaching test and soluble salt analysis, and internal characteristics of debris flow was accordingly showed. It was found that, the soil was loose, and the content of gravel and sand was high, and the content of fine particle was low. The soluble contents at the slope of the accumulation body were described as, collapsed accumulation body > landslide accumulation body, slope toe > slope top, gentle slope > steep slope, also related to length of the slope. The results indicated that accumulations released a large number of base ion after intense weathering, which migrated with water, concentrated and enriched at the slope toe. Saline soil with high salt content collapsed when encountering water and then formed mudflow, thus becoming the internal power to trigger and initiate debris flow to some extent.
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. Further, a statistical-based frequency ratio analysis was carried out in the study area for correlation purposes. The results of the statistical correlation showed a satisfactory agreement between the prepared USLE-based soil erosion map and landslide events/locations, and are directly proportional to each other. Prognosis analysis on soil erosion helps the user agencies/decision makers to design proper conservation planning program to reduce soil erosion. Temporal statistics on soil erosion in these dynamic and rapid developments in Penang Island indicate the co-existence and balance of ecosystem.
Matched MeSH terms: Landslides/statistics & numerical data
Slope failure has become a major concern in Malaysia due to the rapid development and urbanisation in the country. It poses severe threats to any highway construction industry, residential areas, natural resources and tourism activities. The extent of damages that resulted from this catastrophe can be lessened if a long-term early warning system to predict landslide prone areas is implemented. Thus, this study aims to characterise the relationship between Oxisols properties and soil colour variables to be manipulated as key indicators to forecast shallow slope failure. The concentration of each soil property in slope soil was evaluated from two different localities that consist of 120 soil samples from stable and unstable slopes located along the North-South Highway (PLUS) and East-West Highway (LPT). Analysis of variance established highly significant difference (P
Landslides are major hazards for human activities often causing great damage to human lives and infrastructure. Therefore, the main aim of the present study is to evaluate and compare three machine learning algorithms (MLAs) including Naïve Bayes (NB), radial basis function (RBF) Classifier, and RBF Network for landslide susceptibility mapping (LSM) at Longhai area in China. A total of 14 landslide conditioning factors were obtained from various data sources, then the frequency ratio (FR) and support vector machine (SVM) methods were used for the correlation and selection the most important factors for modelling process, respectively. Subsequently, the resulting three models were validated and compared using some statistical metrics including area under the receiver operating characteristics (AUROC) curve, and Friedman and Wilcoxon signed-rank tests The results indicated that the RBF Classifier model had the highest goodness-of-fit and performance based on the training and validation datasets. The results concluded that the RBF Classifier model outperformed and outclassed (AUROC = 0.881), the NB (AUROC = 0.872) and the RBF Network (AUROC = 0.854) models. The obtained results pointed out that the RBF Classifier model is a promising method for spatial prediction of landslide over the world.
The 2004 Banda Aceh earthquake and ensuing Andaman mega tsunami that killed a quarter million people worldwide is a wake-up call to many. Active research was initiated in Universiti Sains Malaysia (USM) immediately after the infamous event with the aims to help develop human capacity and resources, and to mitigate any future earthquake and tsunami. The Disaster Research Nexus (DRN) was formed recently within the School of Civil Engineering, USM, to facilitate active collaborative research on earthquakes and tsunamis, as well as on other natural disasters, such as landslides. This paper begins with an introduction to DRN. This is followed by a description of some research achievements undertaken by DRN staff. A concise exposition on the tsunami simulation model TUNA developed by the authors and its application to the 2004 Andaman tsunami are given to illustrate the capability of TUNA. The role of mangrove in reducing the impact of tsunami is then modelled. Tsunami may inundate coastal plain with large quantity of saline water, changing the salinity regimes in the soil and inducing vegetative succession changes. A model called MANHAM was developed to simulate the salinity changes and its associated vegetative evolution to assist in the rehabilitation of vegetation destroyed by tsunami. Meanwhile, an earthquake risk analysis for the Upper Pandas Dam in Sabah is then presented, and this is followed by a model estimation of tsunami forces on the coastal structures. The main objective of this paper is to reach out to research scientists and onsite risk reduction professionals to collaborate towards the development of a vibrant research culture to face future natural disasters such as earthquakes and tsunamis. It is hoped that DRN will move forward to further enhance active collaborations with other research and operational institutions worldwide towards developing earthquake and tsunami resilient communities.
Long-term (21-30 years) erosional responses of rainforest terrain in the Upper Segama catchment, Sabah, to selective logging are assessed at slope, small and large catchment scales. In the 0.44 km(2) Baru catchment, slope erosion measurements over 1990-2010 and sediment fingerprinting indicate that sediment sources 21 years after logging in 1989 are mainly road-linked, including fresh landslips and gullying of scars and toe deposits of 1994-1996 landslides. Analysis and modelling of 5-15 min stream-suspended sediment and discharge data demonstrate a reduction in storm-sediment response between 1996 and 2009, but not yet to pre-logging levels. An unmixing model using bed-sediment geochemical data indicates that 49 per cent of the 216 t km(-2) a(-1) 2009 sediment yield comes from 10 per cent of its area affected by road-linked landslides. Fallout (210)Pb and (137)Cs values from a lateral bench core indicate that sedimentation rates in the 721 km(2) Upper Segama catchment less than doubled with initially highly selective, low-slope logging in the 1980s, but rose 7-13 times when steep terrain was logged in 1992-1993 and 1999-2000. The need to keep steeplands under forest is emphasized if landsliding associated with current and predicted rises in extreme rainstorm magnitude-frequency is to be reduced in scale.
This article presents a preliminary investigation on the motivations for and the barriers that hinder preparedness toward disasters in a community. Survey questionnaires were distributed to local individuals in the nine districts of Selangor state in Malaysia. A total of 402 usable questionnaires were analyzed. The initial findings revealed that community members are motivated for disaster preparedness mainly for family safety reason. However, generally they do not know how to be prepared. This article concludes by highlighting the importance of knowledge and information in community preparedness. This research is limited to one state in Malaysia. However, the chosen state has a large effect on the Malaysian gross domestic product; hence, lack of preparedness poses a critical risk to its large population. This study on motivation and barriers for disaster preparedness is intended to increase the effectiveness of community readiness as a whole toward major disasters such as landslide and flood. The result of this study is valuable to the scientific community within the disaster management domain, the government agencies for policy and strategy formulations, and the local community to preempt, deal with, and ultimately survive disasters. This research aims to ensure that the community is continuously prepared and able to meet the evolving needs of the individual citizen as the nation strives toward promoting a knowledgeable society.