SPATIO-TEMPORAL ANALYSIS OF THE EFFECTS OF LAND USE CHANGE ON WETLANDS DEGRADATION IN RWANDA FROM 2000 TO 2020. THE CASE OF BAHIMBA WETLAND IN RULINDO DISTRICT

Registration ID: IJNRD_220048

Published ID: IJNRD2404791

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Christelle UMWALI

Spatio-temporal analysis; Effects; Land Use Change; Climate change, Wetlands degradation; Bahimba wetland, Rwanda

The study entitled ‘Spatio-temporal Analysis of the Effects of Land Use Change on Wetland Degradation in Rwanda: A Case Study of Bahimba Wetland in Rulindo District’ aimed to achieve four specific objectives, such as to assess the dynamics of land use change in the area of Bahimba Wetland from 2000 to 2020; to investigate the major drivers of land use change in the vicinity of Bahimba Wetland and their impact on natural resources, particularly forested land; and to evaluate the level of degradation in Bahimba Wetland resulting from land use changes during the same period. The study employed a survey-based, descriptive, qualitative, and quantitative design, utilizing both primary and secondary data. Data collection methods included questionnaires, field interviews, and documentation. Data analysis involved tools such as SPSS (Statistical Package for Social Scientists) for quantitative data and GIS (Geographic Information System) tools along with Google Earth for geospatial data and for qualitative data, the study has summarized all ideas and reported in chapter four. The findings emphasized the critical role of wetlands as ecosystems that offer various benefits at local and global levels, including water quality enhancement, biodiversity support, and recreational opportunities. However, human-induced activities, particularly land use changes, often lead to wetland degradation. Understanding these impacts is crucial for informed decision-making. The study highlighted the negative consequences of losing ecosystem services value due to land use and land cover changes, affecting local climate, waste management, and community livelihoods. The study findings reveal that the model exhibited an F ratio of 10.184, with a P value less than 0.05. This indicates that the F ratio is statistically significant. Consequently, the overall regression model, encompassing all tested variables, also demonstrates statistical significance and can be employed for prediction at a 1% significance level. Furthermore, the predictor variables specifically, Land for agriculture (X1), Land Forest (X2), and Land for Builtup and bare soil (X3) are statistically significant in relation to wetland degradation (Y). These land use changes, including shifts in agriculture, forest, and built-up areas, significantly impact water pollution, soil quality, biodiversity, ecosystems, indigenous plants, and climate change. Notably, there exists a low level of awareness regarding land use policies, agricultural policies, environmental management, and natural resources management. Consequently, uncontrolled economic activities, such as constructing houses in Bahimba wetland, underscore the need for increased awareness and robust measures like wetland restoration to safeguard biodiversity, water quality, and ecosystem health. To mitigate this, interventions should prioritize wetland restoration and sustainable management, both in urban and rural contexts. Ultimately, achieving a balance between development and environmental conservation is essential, especially in wetland ecosystems. By understanding the consequences of land use changes, we can make informed decisions to protect these valuable natural resources.

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Christelle UMWALI (April-2024). SPATIO-TEMPORAL ANALYSIS OF THE EFFECTS OF LAND USE CHANGE ON WETLANDS DEGRADATION IN RWANDA FROM 2000 TO 2020. THE CASE OF BAHIMBA WETLAND IN RULINDO DISTRICT. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), h826-h841. https://ijnrd.org/papers/IJNRD2404791.pdf

Volume 9 Issue 4, April-2024

Pages : h826-h841

Paper Reg. ID: IJNRD_220048

Published Paper Id: IJNRD2404791

Downloads: 000122257

Research Area: Environmental Management 

Author Type: Foreign Author

Country: Ruyenzi Cell, Rwanda, Rwanda

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404791.pdf

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