http://repository.pauwes-cop.net/handle/1/86 Fri, 09 Oct 2026 20:44:49 GMT 2026-10-09T20:44:49Z http://repository.pauwes-cop.net/handle/1/597 Assessing Tropical Cyclones risks in Comoros Islands Using Geospatial Technologies Moutoiwaf, Boussoury Tropical cyclones (TCs) are major natural hazards in the Indian Ocean region, particularly in the Comoros Islands, which are regularly hit by tropical cyclones, the latest of which was Cyclone Kenneth in April 2019. The intensity and extent of TCs and their impacts are likely to increase in the future due to climate change. It is therefore essential to carry out a proper cyclone risk assessment, create risk maps and to identify areas where TCs risks are relatively high to minimize potential losses caused by these cyclones. This study developed a multi-criteria spatial approach to map the levels of TCs risk using geospatial technologies to quantify the degree of risk in all the prefectures of the Comoros. A total of 14 spatial criteria covering three risk components vulnerability and exposure, hazard and mitigation capacity were taken into account. A spatial layer was then generated for each criterion with a weighted score using the Analytic Hierarchy Process (AHP) and ArcGIS. Map were then produced for all risk components, and a final cyclone risk map was produced considering vulnerability, hazard and mitigation capacity components. The maps obtained were then used to identify the spatial extent and levels of risk considering four levels (very high, high, moderate, low and very low). The results indicated that the prefecture of Ouani area was more vulnerable to TCs, due to its low altitude, low slopes, being close to the costs, large number of historical cyclone paths and the high population density. The methodological approach and results were then validated by a qualitative assessment carried out in the field. Finally, cyclone risk reduction strategies were suggested. This study has potential and valuable implications for experts and policymakers as it provides a solid basis for the development of national risk maps and mitigation strategies to reduce the disastrous impacts of TCs Fri, 22 Mar 2024 00:00:00 GMT http://repository.pauwes-cop.net/handle/1/597 2024-03-22T00:00:00Z http://repository.pauwes-cop.net/handle/1/592 A COMPREHENSIVE STUDY ON FLOOD RISK ASSESSMENT CONSIDERING THE IMPACTS OF CLIMATE CHANGE AND LAND USE: CASE STUDY OF FREETOWN, SIERRA LEONE. KOROMA, Abdulai Osman This study presents a comprehensive assessment of flood risk in Freetown, Sierra Leone, incorporating the impacts of climate change and land use changes over a 30-year period from 1991 to 2020. Utilizing the Mann-Kendall trend analysis, it evaluates historical climate data, including rainfall and temperature, to find out the climatic influences on flooding. The study leverages the Rainfall-Runoff Inundation (RRI) model to simulate flood hazard inundation depths in two key basins within Freetown. Additionally, it integrates the Analytic Hierarchy Process (AHP) with Multi-Criteria Decision Making (MCDM) and Geographic Information System (GIS) technologies to create an intricate flood risk map of the city. A detailed analysis of land use and land cover (LULC) changes over the two decades, based on MODIS classification, illustrates how rapid urbanization and the reduction in vegetation cover elevate flood risks. The research utilizes 11 indicators for flood risk assessment using AHP_MCDM method, Rainfall, Slope, Elevation, Distance from River, Slope, LULC, Drainage Density, Population Density, Distance from Road, NDVI and TWI. The findings indicate a steady increase in rainfall and temperature throughout the study period, with notable seasonal variations that influence flooding patterns. The RRI model's performance was validated by correlating simulated depth against observed flood depths from twelve (12) data points, showing coefficients of determination (R2) of 0.6582, Nash-Sutcliffe Efficiency (NSE) of 0.621, and Percent Bias (PBIAS) of -4.73%, indicating a generally reliable model for simulating flood hazards in Freetown. The results from the AHP_MCDM reveal that a significant portion of Freetown is subjected to high to very high flood risks, highlighting the urgent need for effective flood management, adaptation and mitigation strategies. By combining climate data analysis, hydrological modelling, and spatial analysis within a multi-criteria decision framework, this thesis not only delineates the current flood risk landscape but also lays a robust foundation for future urban planning and environmental management initiatives in Freetown Wed, 24 Apr 2024 00:00:00 GMT http://repository.pauwes-cop.net/handle/1/592 2024-04-24T00:00:00Z http://repository.pauwes-cop.net/handle/1/579 FLOOD RISK MAPPING AND IMPACTS ASSESSMENT IN KEEA MUNICIPALITY Flood is the most disastrous natural disaster in the world due to its devastating effects that endanger lives and cause property damage to the affected areas. Flood events are alarmingly increasing all over the world; and despite the recent efforts towards mitigation and management, vulnerability to flood damages is likely to continue to grow. This research mainly aimed at identifying areas at risk of flooding through the application of two different models namely the Analytical Hierarchy Process (AHP) and Fuzzy Analytical Hierarchy Process (FAHP) using remote sensing data (RS) and Geographical Information System (GIS), extract 2022 flood extent using Sentinel-1 SAR product, and assess the impacts of floods on communities. The study was conducted in the Komenda Edina Eguafo Abrem Municipality, Ghana, and consisted of the use of fourteen predicting factors for the flood risk mapping and 300 respondents for the field data collection. The results indicated that the FAHP model performed best for the risk mapping in the study area disclosing a 94.3% prediction rate compared to the AHP model (86.4%). Moreover, the flood inundation extent of 2022 covered 4,553 hectares of the study area with 19% of the urban areas being inundated. The findings revealed a staggering 90% of respondents within flood-prone communities experienced flooding in the past 5 years. Torrential rainfall emerged as the primary flood trigger, often leading to rivers overflowing and causing extensive damage. Approximately 74% and 56% of respondents reported property and agricultural damage, respectively, ranging from building collapses to crop and livestock destruction, along with associated psychological effects. Over 50% of respondents prioritized building flood steps and reconstructing damaged houses with cement as a coping mechanism with sociocultural barriers and limited access to climate information hindering mitigation and adaptation efforts. Respondents prioritized community education, early warning systems, and financial support to address these challenges, emphasizing the importance of building adaptive capacities in flood-prone communities. The outcome of this study can be used by planners and policymakers to implement different management and mitigation measures with a view to the local environment. Fri, 01 Mar 2024 00:00:00 GMT http://repository.pauwes-cop.net/handle/1/579 2024-03-01T00:00:00Z http://repository.pauwes-cop.net/handle/1/575 Modelling the Impact of Climate Change on Flood Hazard in Rift Valley Basin of Ethiopia KASSA, Dawit Kanito The increase of climate change-induced events, such as flooding, has intensified, particularly impacting developing countries over the last few decades. It is essential to develop flood hazard maps to identify and protect vulnerable regions. This will also help establish early warnings system execute both structural and non-structural measures effectively. The study area is the Rift Valley basin of Ethiopia, which has experienced 11 out of 15 recorded flood events in the past. The aim is to forecast the impacts of climate change on flooding, considering both present and future climate scenarios. Through the participatory approach by engaging stakeholders, this study evaluates the reliability of conventional flood risk assessment approaches. Primary and secondary datasets were acquired through field visits and from both non-governmental and governmental organizations. To achieve the objectives of the study, eight flood risk indicators namely, rainfall, DR, land elevation, slope, TRI, TWI, LULC, and soil type were chosen. Two climate scenarios namely SSP245 and SSP585 were used to project the near and far future rainfall based on CMIP6. The study makes use of three standout climate models namely, NoRESM2, CNRM-ESM2-1, and CanESM5. The AHP model and PGIS were used for relative importance analysis, including affected communities from Bilate, Kulfo Gina, Sile-sego, and Lake Hassa sub-basins. The finding revealed that in 2060, both SSP245 and SSP585 scenarios show an increasing trend in high and very high flood-risk areas, with SSP585 indicating a more considerable rise. By 2100, the spatial distribution of very high and high class concentrates in the northern and central parts, emphasizing greater risk under SSP585. Comparison with the baseline period reveals a spatiotemporal change, suggesting climate change's potential contribution to increased flood likelihood and extent in the Rift Valley basin Fri, 01 Mar 2024 00:00:00 GMT http://repository.pauwes-cop.net/handle/1/575 2024-03-01T00:00:00Z