Analysing land cover changes, land degradation and the responses to restoration and conservation practices in the Manafwa watershed - Uganda

Project: PhD

Project Details


Watersheds in the mountainous landscapes are sensitive to land cover changes. The major conversion of, for instance; from nature into arable land accelerates land degradation processes and hazards in the entire watershed, such as soil erosion. Farmer’s practices too have an impact especially on accelerated soil erosion. The soil erosion risk assessment of Uganda highlights districts in Mount Elgon to be on the highest (>10t/ha/yr) erosion risk (Karamage, Zhang, Liu, Maganda, & Isabwe, 2017). In Mount Elgon National Park (MENP), the recent decades marked a very considerable loss of woodland vegetation and forest cover opened up through deforestation for arable farming (Mugagga, Kakembo, & Buyinza, 2012b). This has further accelerated occurrence of land degradation and disasters along river banks and steep hill slopes. Anecdotal evidence exists on the impacts of this degradation, yet quantification has remained limited. The present study seeks to analyse forms of land cover changes and soil erosion processes in Manafwa Watershed using Earth Observation Technologies. Using the hotspot-hopespot concepts (UNEP, 2013), the study will critically examine land degradation characteristics, restoration and conservation practices at a local level. This concept has not been applied in the previous studies within the study area. The study will evaluate the effectiveness of farmers’ conservation practices in reducing soil erosion at a sub-watershed level. Using the OpenLISEM soil erosion model, the study will evaluate the effect of conservation practices on event-based soil erosion processes at a watershed level. Overall; satellite imagery, aerial photographs, field surveys and measurements will be conducted intensively in combination with semi structured interviews and Key Informant Interviews. The study will provide more data, input variables for evaluating and validating the performance of landscape models across mountainous terrains.
Effective start/end date1/11/19 → …


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