4 research outputs found
Soil Loss Estimation Using GIS and Remote Sensing Techniques: The Case of Debis Watershed, Blue Nile Basin Ethiopia
No full textSoil erosion is one of the pressingproblems in highland of Ethiopia. To reduce this problem estimating amount of soil at watershed level is necessary. However, in Ethiopia area specific up to date information in many catchments (watershed) is still found to be lacking. Therefore, this research was carried out to spatially estimate the soil loss rate of Debiswatershed with a Geographic Information System (GIS) and Remote Sensing (RS)technique. Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions was used to estimate potential soil losses by utilizing information on rainfall erosivity(R) using interpolation of rainfall data, soil erodibility(K) using soil map, vegetation cover (C) using satellite images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P ) using satellite images. Result from analysis shows that soil erosion risk differs spatially in the study area because of its rugged topography, geomorphology, landform, soil types, land cover, and land use. The spatial locations of the high spot area for soil erosion in the study revealed that the potential soil loss is typically greater along the steeper slope banks of tributaries. Based on the level of soil erosion rates, the study area was divided into five priority categories for conservation interventions. About 51% (229 sqr.km) of the watershed was categorized none to slight class values ranging from 0.5 to 10 tons ha-1yr-1. The remaining 49 % (1376.48 ha) of land was classified under moderate to high class, which is greater than the maximum tolerable soil loss (11 tons ha-1 y-1).Thus, governmental,non-governmental organization and community found in watershed should focus on applying soil and water conservation intervention which helps to reduce the problem. Keywords: Debis, Soil erosion, RUSLE, Remote sensing, GIS ,Watershed
Assessment of Land Use/ Land Cover Change Using GIS and Remote Sensing Techniques: A Case Study of Dendi District, Oromiya Regional State, Ethiopia
No full textThis study was conducted to assess change in land use/ land cover in Dendi District, Oromiya regional sate Ethiopia. To conduct this study three periods of land sat images (Landsat4-5TM1984, Landsat7ETM+2000 and Landsat 8OLI/TIRS 2017) was used. In addition, field observation, focus group discussion and key informant were employed. Google Earth and global position system (GPS) have been used for ground verification. Data was analyzed by using Arcgis10.1, ERDAS imagie9.3 and Microsoft excels 2007 software. The result revealed in study period there is continuous expansion of cultivated land, which increases with rate of 570.6 hectare per year at the expanse of grassland bush/shrub land and forest areas. While forestland, bush/shrub land ,grassland and water reduce with rate of 93.5 hectare per year, 156.1 hectare per year ,318.5 hectare per year and 2.5 hectare per year respectively. This implies that in study area there loss of vegetation because of expansion of cultivated land. This study recommends applying appropriate land management practices to reverse the undesirable land use/ land cover change in the District. Keywords: Dendi District, Ethiopia, Land use/ land cover, GIS & Remote sensing
Dynamics of Land Use/Land Cover Change in Debis Watershed, West Shewa Zone, Ethiopia
No full textBackground: To implement sustainable natural resource management at local and national levels, up-to-date and area specific land use/land cover change information is required. However, dynamics of land use/land cover change in Debis watershed was not analyzed previously. Therefore, this study was designed to analysis the rate and pattern of land use/ land cover change in Debis watershed. To address the aforementioned research purpose, the period between 1984 and 2017 was considered. The results of the study reveals continuous expansion of cultivated land, urban built-up area and bare land with the increasing rate of 386ha/year, 33ha/year and 27 ha/year respectively. On the other hand, forestland, bush/shrub land and grassland showed reduction with the rate of 34 ha/year, 114ha/year and 297 ha/year respectively for the study period (1984 to 2017) in the watershed. Outrageous expansion of cultivated land, bare land and built-up area at the expense of bush/shrub land, forestland and grassland were observed in Debis Watershed. This implies that there was loss of vegetation because of expansion of cultivated land and settlement. In other words, Poor natural resources management in general and poor land use planning and management were practiced. This study recommends applying appropriate land management practices to reverse the undesirable land use/land cover change in the study area. Keywords: Change, Debis Watershed, Ethiopia, GIS&RS, Land use/land cove
Local and regional climate trends and variabilities in Ethiopia: Implications for climate change adaptations
No full textEthiopia is experiencing considerable impact of climate change and variability in the last five decades. Analyzing climate trends and variability is essential to develop effective adaptation strategies, particularly for countries vulnerable to climate change. This study analyzed trends and variabilities of climate (rainfall, maximum temperature (Tmax), and minimum temperature (Tmin)) at local and regional scales in Ethiopia. The local analysis was carried out considering each meteorological station, while the regional analyses were based on agroecological zones (AEZs). This study used observations from 47 rainfall and 37 temperature stations obtained from the Ethiopian Meteorological Institute (EMI) for the period of 1986 to 2020. The Modified Mann-Kendall (MMK) trend test and Theil Sen’s slope estimator were used to analyze the trends and magnitudes of change, respectively, in rainfall as well as temperature. The coefficient of variation (CV) and standardized anomaly index (SAI) were also employed to evaluate rainfall and temperature variabilities. The local level analysis revealed that Bega (dry season), Kiremt (main rainy season), and annual rainfall showed increasing trend, albeit no significant, in most stations, but the rainfall in Belg (small rainy) season showed a non-significant decreasing trend. The regional levels analysis also indicated an increasing trend of Bega, Kiremt, and annual rainfall in most AEZs, while Belg rainfall showed a decreasing trend in the greater number of AEZs. The result of both local and regional levels of analysis discerned a spatially and temporally more homogeneous warming trend. Both Tmax and Tmin revealed an increasing trend in annual and seasonal scales at most meteorological stations. Likewise, an increase was recorded for mean Tmax and Tmin in entire/most AEZs. The observed trends and variabilities of rainfall and temperature have several implications for climate change adaptations. For example, the decrease in Belg rainfall in most AEZs would have a negative impact on areas that heavily depend on Belg season’s rainfall for crop production. Some climate adaptation options include identifying short maturing crop varieties, soil moisture conservation, and supplemental irrigation of crops using harvested water during the main rainy season.
Conversely, since the first three months of Bega season (October to December) are crop harvest season in most parts of Ethiopia, the increase in Bega rainfall would increase crop harvest loss, and hence, early planting date and identifying short maturing crops during the main rainy season are some climate adaptation strategies.
Because of the increase in temperature, water demand for irrigation during Bega season will increase due to increased evapotranspiration. On the other hand, the increase in Kiremt rainfall can be harvested and used for supplemental irrigation during Bega as well as the small rainy season, particularly for early planting. In view of these findings, it is imperative to develop and implement effective climate-smart agricultural strategies specific to each agro-ecological zone (AEZ) to adapt to rainfall and temperature changes and variabilities
