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Exploring vulnerability and impact of floods in Malawi : a first step towards impact-based forecasting
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Resumo(s)
Forecast-based financing is a methodology to trigger early actions when a forecast exceeds a danger level in a vulnerable intervention area. The first three implementation steps aim at impact-based forecasting: (1) Understanding risk scenarios, (2) Identifying available hazard forecasts and (3) Identifying danger levels. Impact-based forecasting requires timely, complete, reliable and accurate data at a subnational level, which is however – especially in developing countries with a high data poverty – challenging. 510, The Netherlands Red Cross data team, has developed a Community Risk Assessment dashboard, that visualizes data on the INFORM risk index with three dimensions: Hazard & Exposure, Vulnerability and Lack of Coping Capacity. However, the number of available indicators decreases sharply when one goes from national down to district or even to the community level. The aim of this study was to downscale the vulnerability index to subnational level and to examine the relation between vulnerability and impact in Malawi. A literature review was conducted to understand the existing frameworks of vulnerability and the concept of impact. Thereafter, global and national open data sources were accessed to collate data of vulnerability and impact on subnational level. To determine the vulnerability level on subnational level, the gap in vulnerability data is characterized both vertically, in terms of data missing at lower administrative levels on indicators already used, as well as horizontally by adding new indicators. Thereafter, factor analysis was performed to reduce dimensionality of the dataset (in which there are a large number of uncorrelated variables) and to determine the vulnerability level. Reducing the dimensionality of the dataset makes it easier to visualize and understand the differences in vulnerability level across areas and to examine the relation with impact of floods. Five factors were identified and subsequently the five factors and the total vulnerability were successfully mapped to visualize the vulnerability level on Traditional Authority level in Malawi. The mapping revealed large differences between TAs and made it clear that data on a subnational level is essential in order to have a proper understanding of the reality on the ground. Finally, relations between these factors and impact data were examined. Impact data consisted of Internally Displaced Persons, Food Deficit and People Affected after being exposed to a flood. In conclusion, three relations were found between the vulnerability factors and impact which is a first essential step towards Impact-based Forecasting.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
Palavras-chave
Forecast-based financing Vulnerability Floods Impact-based forecasting Malawi