Please use this identifier to cite or link to this item: http://197.159.135.214/jspui/handle/123456789/1222
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dc.contributor.authorBarry, Thierno Hamidou Mariama-
dc.date.accessioned2026-06-05T12:17:58Z-
dc.date.available2026-06-05T12:17:58Z-
dc.date.issued2025-07-09-
dc.identifier.urihttp://197.159.135.214/jspui/handle/123456789/1222-
dc.descriptionA Thesis submitted to the West African Science Service Center on Climate Change and Adapted Land Use and Université Joseph KI-ZERBO, Burkina Faso in partial fulfillment of the requirements for the Master of Science Degree in Informatics for Climate Changeen_US
dc.description.abstractLike most West African countries, Guinea experiences recurrent flooding that severely affects its infrastructure, economy, and the lives of the population. These phenomena are exacerbated by climate change, and the country's vulnerability is particularly evident in poorly planned urban areas, where people often settle in high risk flood zones. The main objective is to study flood anticipatory actions in Guinea through data driven risk assessments. To better understand these risks, several types of data were combined: We used rainfall data from CHIRPS 1981 to 2024, river flow data 1992 to 2024, information on soil permeability, and risk exposure, vulnerability, and ability to adapt. Four main indicators are used to analyze flood risk: hazard, exposure, vulnerability, and Coping capacity. Hazard was measured using average annual precipitation, the 95th percentile of rainfall, and soil permeability coefficients, allowing for the evaluation of the intensity, frequency of extreme rainfall events and soil characteristics. Exposure was calculated based on the population, agricultural land, and livestock in risk prone areas. Vulnerability was assessed through the Multidimensional Poverty Index (MPI), the presence of thatched or earthen roofs, and the number of vulnerable individuals (children under 4, the elderly, and people with disabilities). Lack of coping capacity was measured through access to essential services such as emergency services, health infrastructure, and communication networks. All data were processed and analyzed using Python and the R package. The results showed that pluvial flood hazards (i.e., floods resulting from heavy rainfall) are concentrated in coastal areas and the southern part of the country, while fluvial flood risks (linked to rivers exceeding their capacity) occur throughout the country. The selection of vulnerability indicators also has a significant impact on the results. The analysis reveals that Kindia is the most affected region while presenting the highest flood risk.en_US
dc.description.sponsorshipThe Federal Ministry of Research, Technology and Space (BMFTR)en_US
dc.language.isoenen_US
dc.publisherWASCALen_US
dc.subjectFloodingen_US
dc.subjectRisken_US
dc.subjectAnalysisen_US
dc.subjectAnticipatory Measuresen_US
dc.subjectGuineaen_US
dc.titleFlood Risk Analysis for Anticipatory Action in Guineaen_US
dc.typeThesisen_US
Appears in Collections:Informatics for Climate Change - Batch 4

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