Key indicator tools for shallow slope failure assessment using soil chemical property signatures and soil colour variables.

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ID: 33433
2017
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Abstract
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 < 0.0001) between the locations, the total organic carbon (TOC), soil pH, cation exchange capacity (CEC), soil texture, soil chromaticity and all combinations of interactions. The overall CIELAB analysis leads to the conclusion that the CIELAB variables lightness L*, c* (Chroma) and h* (Hue) provide the most information about soil colour and other related soil properties. With regard to the relationship between colour variables and soil properties, the analysis detected that soil texture, organic carbon, iron oxide and aluminium concentration were the key factors that strongly correlate with soil colour variables at the studied area. Indicators that could be used to predict shallow slope failure were high value of L*(62), low values of c* (20) and h* (66), low concentration of iron (53 mg kg) and aluminium oxide (37 mg kg), low soil TOC (0.5%), low CEC (3.6 cmol/kg), slightly acidic soil pH (4.9), high amount of sand fraction (68%) and low amount of clay fraction (20%).
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othman2017keyenvironmental Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Othman, Rashidi;Hasni, Shah Irani;Baharuddin, Zainul Mukrim;Hashim, Khairusy Syakirin Has-Yun;Mahamod, Lukman Hakim;
Journal Environmental science and pollution research international
Year 2017
DOI
10.1007/s11356-017-9715-9
URL
Keywords Keywords not found

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