Modeling runoff-sediment influx responses to alternative BMP interventions in the Gojeb watershed,Ethiopia, using the SWAT hydrological model

Environmental Science and Pollution Research - The Soil & Water Assessment Tool (SWAT) has been calibrated over a 33-year period to evaluate the Gojeb watershed’s hydrological...     

Land use and land cover dynamics in the Keleta watershed,Awash River basin,Ethiopia

Unprecedented pace and magnitude of land use/land cover (LULC) change in the Ethiopian highlands is a key problem threatening the natural ecosystem and creates vulnerability to an environmental hazard. A combination of remote sensing, field observations and focus group discussions were used to analyze the dynamics and drivers of LULC change from 1985 to 2011 in the Keleta watershed, Ethiopia. Supervised image classification was used to map LULC classes. Focus group discussions and ranking were used to explain the drivers and causes linked to the changes. The result showed rapid expansion of farmland and settlement (36%), shrublands cover shrinking by 50%, while the size of degraded land increased by 45%. Rapid population growth, rainfall variability and soil fertility decline, lack of fuelwood and shortage of cultivation land were ranked as the main causes of LULC change in the watershed according to the focus group discussion. Further effort is needed to improve the creation of new job opportunity, promotion of improved technologies to boost productivity and soil fertility, provide credit facility, extra push on irrigation infrastructure development and soil, water and natural ecosystem conservation practices. Generally, better community-based land resource management will need to ensure sustainable rural livelihoods.     

Dynamics of land change: insights from a three-level intensity analysis of the Legedadie-Dire catchments,Ethiopia

Earlier studies on land change (LC) have focused on size and magnitude, gains and losses, or land transfers between categories. Therefore, these studies have failed to simultaneously show the complete LC processes. This paper examines LCs in the Legedadie-Dire catchments in Oromia State, Ethiopia, using land-category maps with intensity analysis (IA) at three points in time. We comprehensively analyze LC to jointly encompass the rate, intensity, transition, and process. Thirty-meter US Geological Survey (USGS) Landsat imagery from 1986, 2000, and 2015 (<?10% cloud) is processed using TerrSet-LCM and ArcGIS. Six categories are identified using a maximum likelihood classification technique: settlement, cultivation, forest, water, grassland, and bare land. Then, classified maps are superimposed on the images to statistically examine changes with an IA. Considerable changes are observed among categories, except for water, between 1986–2000 and 2000–2015. Overall land change occurred quickly at first and then slowly in the second time interval. The total land area that exhibited change (1st?≈?54% and 2nd?≈?51%) exceeded the total area of persistence (1st?≈?46% and 2nd?≈?49%) across the landscape. Cultivation and human settlements were the most intensively increased categories, at the expense of grassland and bare ground. Hence, when grassland was lost, it tended to be displaced by cultivation more than other categories, which was also true with bare land. Annual intensity gains were active for forest but minimal for cultivation, implying that the gains of forest were associated with in situ reforestation practices and that the gains in cultivation were caused by its relatively large initial area under a uniform intensity concept. This study demonstrates that IA is valuable for investigating LC across time intervals and can help distinguish dormant vs. active and targeted vs. avoided land categories.