RESEARCH ARTICLE


Spatial Analysis of Leakage Accidents of Oil Pipeline River Crossing Sections



Zegen Wang*, Kexia Li, Mingjun Xi
School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China


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Creative Commons License
© Wang et al.; Licensee Bentham Open

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address for correspondence with this author at the School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China; Tel: +86-136-6822-1158; E-mail: Zegen01@126.com


Abstract

Oil pipeline leakages often bring catastrophic impacts on rivers along the pipeline, drinking water sources, and farm land irrigation etc. Based on the distinct spatial-temporal attributes in the analysis of oil spill, diffusion and consequences thereof, we present the theoretical concept and reasoning for leakage accidents spatial analysis through combining GIS and accident aftermath model. Specifically, we aim to achieve quantitative analysis and visualization of oil spill accidents through several GIS functions, which include buffer analysis, overlay analysis, spatial statistical analysis and visualized analysis. Taking a specific leakage accident of oil pipeline river-crossing section as an example, we have analyzed the polluted areas under different diffusion time and the hydrological conditions. In addition, we have evaluated populations and farm land areas affected in terms of drinking water and irrigation as well as their spatial distributions. The results demonstrate that our method can achieve quantitative analysis and visualized representations of oil spills to support policy-makers in making contingency plans.

Keywords: GIS, Oil pipelines, Oil spills, Quantitative analysis, River, Spatial analysis.