oa Jamba : Journal of Disaster Risk Studies - Disaster risk assessment at Roburnia Plantation, Mpumalanga, South Africa : original research
|Article Title||Disaster risk assessment at Roburnia Plantation, Mpumalanga, South Africa : original research|
|Journal||Jamba : Journal of Disaster Risk Studies|
|Affiliations||1 University of the Free State and 2 National Research Foundation|
|Publication Date||Jan 2013|
|Pages||1 - 6|
This study reports about disaster risk assessment undertaken at Roburnia Plantation, Mpumalanga Province, South Africa. Both quantitative and qualitative approaches were followed to collect data. A total of eight experienced foresters and fire fighters were purposively sampled for interview at Roburnia Plantation. A questionnaire survey was also used to collect the data. Risk levels were quantified using the risks equations of Wisner et al. (2004) and the United Nations International Strategy for Disaster Reduction (UNISDR 2002). Data were analysed using descriptive and inferential statistics. Analysis of variance (ANOVA, single factor) was also applied. This study found that Roburnia Plantation is highly exposed to fire risks. The mean (± s.d.) output from the Wisner risk equation shows that fire is the highest risk at 7.7 ± 0.3, followed by harsh weather conditions at 5.6 ± 0.4 and least by tree diseases, pests and pathogens at 2.3 ± 0.2. Similarly, the mean (± s.d.) output from the UNISDR risk equation also shows that fire is the highest risk at 2.9 ± 0.2, followed by harsh weather conditions at 2.2 ± 0.3 and least by tree diseases, pests and pathogens at 1.3 ± 0.2. There was no significant deference in the risk analysis outputs (p = 0.13). This study also found that the number of fire incidents were low during summer, but increased during winter and spring. This variation is mainly due to a converse relationship with rainfall, because the availability of rain moistens the area as well as the fuel. When the area and fuel is moist, fire incidents are reduced, but they increase with a decrease in fuel moisture.
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