Land use and land cover change and its implications in Kagera river basin, East Africa

Berakhi, Robel Ogbaghebriel; Oyana, Tonny J.; Adu-Prah, Samuel

doi:10.1080/19376812.2014.912140

Cited by 20 publications

(6 citation statements)

References 22 publications

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“…However within sub-saharan Africa region east African countries such as Burundi, Rwanda, Tanzania and Uganda had generally shown a 3% increase of forest from 1984 to 2011 (e.g. Berakhi et al 2015). Though forest cover increased in the eastern Africa region, it was not due to what some calls as a "forest transition" where net afforestation exceeds net deforestation (Lambin and Meyfroidt 2011) rather land clearance for agriculture was mainly depended on woodland savanna than forests in these counties (Berakhi et al 2015).…”

Section: Deforestation Reforestation Dynamics and Forest Susceptibilmentioning

confidence: 99%

Land use and forest cover dynamics in the North-eastern Addis Ababa, central highlands of Ethiopia

Deribew

Dalacho

2019

Environ Syst Res

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Background: The Ethiopian highlands have experienced intense levels of land use dynamics and forest cover transformations over the past few decades. Multiple socioeconomic , demographic and bio-physical factors have driven such transformations. Nevertheless, recent expansion of urban settlements and infrastructural development could have accelerated the rate at which land cover transformations preceded but little is known about their impacts on land cover transformations in the vicinity of Addis Ababa, Ethiopia. This study, therefore, focuses on detecting long term dynamics of land use/land cover (LULC) change since the 1950s and current state of forest susceptibility to degradation in Northeastern Addis Ababa, Ethiopia. In this study Panchromatic Aerial photographs (1957), MSS (1975), TM (1995) and Sentinel-2 (2017) images were used to generate LULC types. We employed object-based classification techniques to generate LULC types for 1957 aerial photographs and maximum likelihood algorithm for images of 1975, 1995 and 2017. We also generated forest degradation susceptibility map for the study area by employing a multi-criteria approach on the ArcGIS analysis platform. Results: Over the course of 60 years (1957-2017) the extent and direction of LULC have become more dynamic. Agricultural land and forest land showed a comparably equal extent of net change (+ 36.7% and − 37.8%, respectively) but to opposite directions. Forest lost 25.1% and 18.7% of its cover to barren land and agricultural land, respectively. The net change for forest was negative except for the period 1975-1995, with varying rates of deforestation during the four distinct study periods. However, a heightened level of deforestation occurred after the mid-1990s due to rapid urban growth and a change in government economic policy. A 6.2% net change of urban/settlement served as a catalyst for LULC transformations in the last two decades. Our findings also revealed that 97.2% of forests were located at a radius of 1 km distance from urban centers and settlements whereas 92% of them were accessible by road networks of a km radius. Similarly, 71% of forests suffer from edge effects while biophysical factors such as streams as vectors of disturbance and slopes expose about 35% of forests to degradation. Conclusion: Over the last six decades the study area has shown an unprecedented level of LULC change. The main drivers of change were the combination of bio-physical processes especially drought cycles, demographic dynamics (population growth, density and internal migration), urbanization and successive government development policies. The massive conversion of forests to agricultural land and barren land in the study area will have far reaching impact on biodiversity and ecosystem services, land degradation and a change in local hydrological regime.

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Section: Deforestation Reforestation Dynamics and Forest Susceptibilmentioning

confidence: 99%

Land use and forest cover dynamics in the North-eastern Addis Ababa, central highlands of Ethiopia

Deribew

Dalacho

2019

Environ Syst Res

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“…The Kagera River (0°45′–3°35′ S, 29°15′–30°51′ E) is located on the East Africa Plateau, the most remote headstream of the Nile River and the largest of the 23 rivers that drain into Lake Victoria, supplying 34% of the annual inflow into the lake. Sediment carried by runoff from the Kagera River is a major part of Lake Victoria’s sediments [ 24 , 25 ]. The KB ( Figure 1 ) covers extends over four countries: Burundi (23% of the basin), Rwanda (34%), Tanzania (35%), and Uganda (8%), with a total area of 60,000 km 2 .…”

Section: Methodsmentioning

confidence: 99%

Grid-Scale Impact of Climate Change and Human Influence on Soil Erosion within East African Highlands (Kagera Basin)

Yang

et al. 2021

IJERPH

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Under global climate change and pressure from human activities, soil erosion is becoming a major concern in the quest for regional sustainable development in the Kagera basin (KB). However, few studies in this region have comprehensively considered the impact of climate change and human influence on soil erosion, and the associated processes are unclear. Based on the premise of quantifying climate change, human influence, and soil erosion, this study undertook a neighborhood analysis as the theoretical support, for a grey relation analysis which was conducted to realize the qualitative assessment of the influence of climate change and human activities on soil erosion. The results show that 90.32% of the KB saw climate change as having a greater influence on soil erosion than human influence, with the remaining area 9.68% seeing human influence having a greater impact than climate change, mainly as a result of the effect of rangeland and farmland. The average soil erosion rate of the KB shows a very low level (10.54 t ha−1 yr−1), with rangeland and farmland being the main land use/land cover (LULC) types that see soil loss, followed by forest, wetland, and built-up areas. The climate change trends of the KB show the most dramatic changes in the northeast and southwest, gradually decreasing towards the line crossing from the Birunga National Park (Rwanda) to the Keza district (Tanzania). The human influence intensity (HII) shows a high level in the KB (21.93), where it is higher in the west and lower in the east of the basin.

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“…Identifying drivers and extrapolating trends are especially sensitive to potential nonlinear dynamics, while trend comparisons on broad spatiotemporal scales often are less affected. By reviewing peer-reviewed studies on drivers in agricultural systems in Sub-Saharan Africa over the past 15 years, resulting in a selection of 60 studies, the most common methodologies for identifying drivers were found to be household surveys, focus groups, or interviews in areas where changes and trends have been identified (Nin-Pratt & McBride, 2014;Ouedraogo, Mbow, Balinga, & Neufeldt, 2015;Ouédraogo et al, 2017;Valbuena, Groot, Mukalama, Gérard, & Tittonell, 2015;Wood et al, 2014); quantitative correlation to potential factors (Abro, Alemu, & Hanjra, 2014;Bachewe et al, 2015;Epule & Bryant, 2015;García De Jalón, Iglesias, & Barnes, 2016;Michler & Josephson, 2017;Nielsen & Reenberg, 2010;Ouédraogo et al, 2017;Wood et al, 2014); and attribution by qualitative analysis to political and socioeconomic factors (Berakhi, Oyana, & Adu-Prah, 2014;Kamwi, Kaetsch, Graz, Chirwa, & Manda, 2017;Li, Oyana, & Mukwaya, 2016;Mbow, Mertz, Diouf, Rasmussen, & Reenberg, 2008;Sandstrom & Juhola, 2017). For any of these methodologies, a specified understanding of the patterns of change would guide the driver identification not only spatiotemporally but could also provide information on the characteristics of the driver, as drivers with gradual or abrupt effects might be distinguishable in the given context.…”

Section: Nonlinear Dynamics In Agricultural Systems In Sub-saharan Afmentioning

confidence: 99%

Nonlinear dynamics in agricultural systems in Chad

Nilsson

Uvo

2018

African Geographical Review

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Changes to agricultural systems in Sub-Saharan Africa are subject to a wide range of drivers, often resulting in rapid and nonlinear dynamics. Such dynamics are however rarely recognized in studies of trends and drivers, which usually rely on assumptions of gradual progressions, and often using highly aggregated data. This paper addresses this lack of recognition and understanding of nonlinear processes in agricultural systems in Sub-Saharan Africa by statistically identifying breakpoints and trends in regional crop production data in Chad for 1983-2016, which also makes it the most extensive and detailed study of the agricultural sector in Chad to date. By summarizing and visualizing the identified breakpoints and trends of a large group of variables in a concise and informative way, the roles of both abrupt and gradual processes are made clear. Results show that the progressions in the data predominantly have been driven by abrupt changes with lasting effects rather than gradual changes, contrary to what analyses on higher levels of aggregation would conclude. The potency of the developed methodology lies in its capacity to identify and summarize nonlinear progressions in agricultural systems constituted by a large set of variables, by separating the influence of abrupt and gradual processes.

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Land use and land cover change and its implications in Kagera river basin, East Africa

Cited by 20 publications

References 22 publications

Land use and forest cover dynamics in the North-eastern Addis Ababa, central highlands of Ethiopia

Land use and forest cover dynamics in the North-eastern Addis Ababa, central highlands of Ethiopia

Grid-Scale Impact of Climate Change and Human Influence on Soil Erosion within East African Highlands (Kagera Basin)

Nonlinear dynamics in agricultural systems in Chad

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