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Development and validation of risk profiles of West African rural communities facing multiple natural hazards

View Article: PubMed Central - PubMed

ABSTRACT

West Africa has been described as a hotspot of climate change. The reliance on rain-fed agriculture by over 65% of the population means that vulnerability to climatic hazards such as droughts, rainstorms and floods will continue. Yet, the vulnerability and risk levels faced by different rural social-ecological systems (SES) affected by multiple hazards are poorly understood. To fill this gap, this study quantifies risk and vulnerability of rural communities to drought and floods. Risk is assessed using an indicator-based approach. A stepwise methodology is followed that combines participatory approaches with statistical, remote sensing and Geographic Information System techniques to develop community level vulnerability indices in three watersheds (Dano, Burkina Faso; Dassari, Benin; Vea, Ghana). The results show varying levels of risk profiles across the three watersheds. Statistically significant high levels of mean risk in the Dano area of Burkina Faso are found whilst communities in the Dassari area of Benin show low mean risk. The high risk in the Dano area results from, among other factors, underlying high exposure to droughts and rainstorms, longer dry season duration, low caloric intake per capita, and poor local institutions. The study introduces the concept of community impact score (CIS) to validate the indicator-based risk and vulnerability modelling. The CIS measures the cumulative impact of the occurrence of multiple hazards over five years. 65.3% of the variance in observed impact of hazards/CIS was explained by the risk models and communities with high simulated disaster risk generally follow areas with high observed disaster impacts. Results from this study will help disaster managers to better understand disaster risk and develop appropriate, inclusive and well integrated mitigation and adaptation plans at the local level. It fulfills the increasing need to balance global/regional assessments with community level assessments where major decisions against risk are actually taken and implemented.

No MeSH data available.


Related in: MedlinePlus

Development of multi-hazard index map.                        The figure on the left is a modified representation of the flood                            modelling approach introduced in Asare-Kyei et al.                                [38] whilst                            the figure on the right is a modified abstraction of FAO GIEWS [48] illustrating                            the development of DSI computed from the mean season of the VHI. VCI is                            the scaling of maximum and minimum Normalized Difference Vegetation                            Index (NDVI) and TCI is the scaling of maximum and minimum brightness                            temperature (BT), estimated from thermal infrared band of AVHRR channel                            4 [49]. The final                            VHI is derived by applying weight, “a” to the VCI and                            TCI. The end results of these two methods were combined in GIS to                            develop the multi-hazard map.
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pone.0171921.g005: Development of multi-hazard index map. The figure on the left is a modified representation of the flood modelling approach introduced in Asare-Kyei et al. [38] whilst the figure on the right is a modified abstraction of FAO GIEWS [48] illustrating the development of DSI computed from the mean season of the VHI. VCI is the scaling of maximum and minimum Normalized Difference Vegetation Index (NDVI) and TCI is the scaling of maximum and minimum brightness temperature (BT), estimated from thermal infrared band of AVHRR channel 4 [49]. The final VHI is derived by applying weight, “a” to the VCI and TCI. The end results of these two methods were combined in GIS to develop the multi-hazard map.

Mentions: The development of the multi-hazard index maps considered two components (see Fig 5), integrating the flood hazard intensity developed in Asare-Kyei et al. [16] and drought hazard. The first part was the development of a flood hazard index map. This approach presented in detail in Asare-Kyei et al., [38] drew on the strengths of a simple hydrological model and statistical methods integrated in GIS to develop a Flood Hazard Index (FHI) to an acceptable accuracy level. The FHI was validated with participatory GIS techniques using information provided by local disaster managers and historical data. The flood hazard component shows the intensity of flood at the pixel level on a scale of 1 to 5, with one being areas with least flood intensity and 5, areas of highest flood intensity.


Development and validation of risk profiles of West African rural communities facing multiple natural hazards
Development of multi-hazard index map.                        The figure on the left is a modified representation of the flood                            modelling approach introduced in Asare-Kyei et al.                                [38] whilst                            the figure on the right is a modified abstraction of FAO GIEWS [48] illustrating                            the development of DSI computed from the mean season of the VHI. VCI is                            the scaling of maximum and minimum Normalized Difference Vegetation                            Index (NDVI) and TCI is the scaling of maximum and minimum brightness                            temperature (BT), estimated from thermal infrared band of AVHRR channel                            4 [49]. The final                            VHI is derived by applying weight, “a” to the VCI and                            TCI. The end results of these two methods were combined in GIS to                            develop the multi-hazard map.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5382969&req=5

pone.0171921.g005: Development of multi-hazard index map. The figure on the left is a modified representation of the flood modelling approach introduced in Asare-Kyei et al. [38] whilst the figure on the right is a modified abstraction of FAO GIEWS [48] illustrating the development of DSI computed from the mean season of the VHI. VCI is the scaling of maximum and minimum Normalized Difference Vegetation Index (NDVI) and TCI is the scaling of maximum and minimum brightness temperature (BT), estimated from thermal infrared band of AVHRR channel 4 [49]. The final VHI is derived by applying weight, “a” to the VCI and TCI. The end results of these two methods were combined in GIS to develop the multi-hazard map.
Mentions: The development of the multi-hazard index maps considered two components (see Fig 5), integrating the flood hazard intensity developed in Asare-Kyei et al. [16] and drought hazard. The first part was the development of a flood hazard index map. This approach presented in detail in Asare-Kyei et al., [38] drew on the strengths of a simple hydrological model and statistical methods integrated in GIS to develop a Flood Hazard Index (FHI) to an acceptable accuracy level. The FHI was validated with participatory GIS techniques using information provided by local disaster managers and historical data. The flood hazard component shows the intensity of flood at the pixel level on a scale of 1 to 5, with one being areas with least flood intensity and 5, areas of highest flood intensity.

View Article: PubMed Central - PubMed

ABSTRACT

West Africa has been described as a hotspot of climate change. The reliance on rain-fed agriculture by over 65% of the population means that vulnerability to climatic hazards such as droughts, rainstorms and floods will continue. Yet, the vulnerability and risk levels faced by different rural social-ecological systems (SES) affected by multiple hazards are poorly understood. To fill this gap, this study quantifies risk and vulnerability of rural communities to drought and floods. Risk is assessed using an indicator-based approach. A stepwise methodology is followed that combines participatory approaches with statistical, remote sensing and Geographic Information System techniques to develop community level vulnerability indices in three watersheds (Dano, Burkina Faso; Dassari, Benin; Vea, Ghana). The results show varying levels of risk profiles across the three watersheds. Statistically significant high levels of mean risk in the Dano area of Burkina Faso are found whilst communities in the Dassari area of Benin show low mean risk. The high risk in the Dano area results from, among other factors, underlying high exposure to droughts and rainstorms, longer dry season duration, low caloric intake per capita, and poor local institutions. The study introduces the concept of community impact score (CIS) to validate the indicator-based risk and vulnerability modelling. The CIS measures the cumulative impact of the occurrence of multiple hazards over five years. 65.3% of the variance in observed impact of hazards/CIS was explained by the risk models and communities with high simulated disaster risk generally follow areas with high observed disaster impacts. Results from this study will help disaster managers to better understand disaster risk and develop appropriate, inclusive and well integrated mitigation and adaptation plans at the local level. It fulfills the increasing need to balance global/regional assessments with community level assessments where major decisions against risk are actually taken and implemented.

No MeSH data available.


Related in: MedlinePlus