Land-use/land-cover changes and implications in Southern Ethiopia: evidence from remote sensing and informants

Impact of land use land cover change using remote sensing with integration of socio-economic data on Rural Livelihoods in the Nashe watershed, Ethiopia

“…This outcome was due to lack appropriate of stakeholder's participation and lack of problem identification during screening and scoping EIA process [ 29 , 30 ]. Therefore deforestation of native trees for lumber, charcoal production, and irreplaceable building materials are serious problems that lead to the loss of various forest forms and native trees in mostly in rural are due to the construction of Nashe Dam and LULCC [ 6 , 31 , 32 ].…”

Analyze of the socio-economic drivers of land use land cover changes in Western Ethiopia

“…The drivers of LULC dynamics are diverse and complex varying in space and time, demanding more investigation in Ethiopia (Reid et al, 2000;Hassen & Assen, 2017;Tolessa, 2020). Agricultural land expansion, increasing demand of fuel-wood and construction material, illegal settlement within forests, illegal logging were/are said to be the major LULC change drivers in Ethiopia (Meragiaw et al, 2022;Kuma et al, 2022). In Western Ethiopia, anthropogenic activities-induced LULC changes are frequently observed in Wayu-Tuka District, where this study was conducted (Badasa et al, 2022;Urgesa et al, 2016).…”

Modeling canopy water content in the assessment for rainfall induced surface and groundwater nitrate contamination: The Bilate cropland sub watershed

“…Climatic changes in the Bilate watershed [ 14 ] have been recognized in previous studies as having a climatic impact on nitrogen fertilizer loss from agricultural land [ [14] , [15] ]; however, considering the entire watershed as an agricultural area, its research still revealed a knowledge gap excluding crop species and growing season. Nitrogen loss from cropland is not continuous, so it is important to consider specific growing seasons, crop classification and biomass index [ 14 ]. This hypothesis helps calibrate model parameters and improves the accuracy of model predictions based on estimated plant canopy water content.…”