17 research outputs found

    Landslides Hazard Mapping in Rwanda Using Bivariate Statistical Index Method

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    Landslides hazard mapping (LHM) is essential in delineating hazard prone areas and optimizing low cost mitigation measures. This study applied the Geographic Information System and statistical index method in LHM in Rwanda. Field surveys identified 336 points that were employed to construct a landslides inventory map. Ten landslides predicting factors were analyzed: normalized difference vegetation index, elevation, slope, aspects, lithology, soil texture, distance to rivers, distance to roads, rainfall, and land use. The factor variables were converted into categorized variables according to the percentile divisions of seed cells. Then, values of each factor’s class weight were calculated and summed to create landslides hazard map. The estimated hazard map was split into five hazard classes (very low, low, moderate, high, and very high). The results indicated that the northern, western, and southern provinces are largely exposed to landslides hazard. The major landslides hazard influencing factors are elevation, slope, rainfall, and poor land management. Overall, this LHM would help policy makers to recognize each area’s hazard extent, key triggering factors, and the required hazard mitigation measures. These measures include planting trees to enhance vegetation cover and reduce the runoff, and construction of buildings on low steep slope areas to reduce people’s hazard exposure; while agroforestry and bench terraces would reduce sediments that take out the exposed soil (erosion) and pollute water quality

    Seasonal assessment of drinking water sources in Rwanda using GIS, contamination degree (Cd), and metal index (MI)

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    The quality of drinking water source remains as a major concern in areas of developing and underdeveloped countries worldwide. The treatment and supply of drinking water in Rwanda are carried out by Water and Sanitation Corporation, a state-owned public company. However, it is not able to supply water to all households. Consequently, the non-serviced households depend on natural water sources, like springs, to meet their water requirements. Nevertheless, the water quality in these springs is scarcely known. Therefore, this study assessed and compared metal elements in drinking water sources in the dry and rainy seasons in 2017 using the contamination degree, metal index, and geographic information systems to reveal the spatial distribution of water quality within the considered water sources of springs in Rwanda. The samples were collected monthly from nine water sources of springs and the measured elements are aluminium, calcium, copper, iron, manganese, and zinc. The metal index indicated that during the dry season and rainy season, the sites of Kibungo (1.10 and 1.26) and Kinigi (1.01 and 1.54) have assessed a metal index which is higher than 1. Thus, the water quality of those sites was getting the threshold of warning. The analysis indicated that pollutants are easily transported into water bodies during the rainy season in urban and rural areas to a greater extent than during the dry season
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