Asare-Kyei Daniel, Renaud Fabrice G, Kloos Julia, Walz Yvonne, Rhyner Jakob
United Nations University, (UNU-EHS), UN Campus, Platz der Vereinten Nationen 1, Bonn, Germany.
PLoS One. 2017 Mar 1;12(3):e0171921. doi: 10.1371/journal.pone.0171921. eCollection 2017.
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.
西非被视为气候变化的热点地区。超过65%的人口依赖雨养农业，这意味着该地区对干旱、暴雨和洪水等气候灾害的脆弱性将持续存在。然而，人们对受多种灾害影响的不同农村社会生态系统（SES）所面临的脆弱性和风险水平了解甚少。为填补这一空白，本研究对农村社区遭受干旱和洪水的风险及脆弱性进行了量化。风险评估采用基于指标的方法。研究遵循一种逐步推进的方法，将参与式方法与统计、遥感和地理信息系统技术相结合，以制定三个流域（布基纳法索的达诺、贝宁的达萨里、加纳的韦亚）的社区层面脆弱性指数。结果显示，三个流域的风险概况各不相同。在布基纳法索的达诺地区发现了具有统计学意义的高平均风险水平，而贝宁达萨里地区的社区平均风险较低。达诺地区的高风险是由多种因素造成的，包括干旱和暴雨的高暴露度、较长的旱季时长、人均热量摄入低以及当地机构薄弱等。该研究引入了社区影响得分（CIS）的概念，以验证基于指标的风险和脆弱性模型。CIS衡量了五年内多种灾害发生的累积影响。风险模型解释了65.3%的灾害观测影响/CIS方差，模拟灾害风险高的社区通常与观测到的灾害影响高的地区相符。本研究结果将有助于灾害管理者更好地理解灾害风险，并在地方层面制定适当、包容且整合良好的减灾和适应计划。它满足了日益增长的需求，即在全球/区域评估与社区层面评估之间取得平衡，因为在社区层面才实际做出并实施应对风险的重大决策。
