Soil salinization is one of the most common land degradation processes, especially in arid and semi-arid regions, where precipitation exceeds evaporation. Under such climatic conditions, soluble salts are accumulated in the soil, influencing soil properties with ultimate decline in productivity. An integrated approach using remote sensing in addition to various statistical methods has shown success for developing soil salinity prediction models. The present study presents a model to map soil salinity using remote sensing and geographic information systems. Different spectral indices were calculated from original bands of landsat images. Statistical correlation between field measurements of electrical conductivity (ECe) and remote sensing spectral indices showed that salinity index (SI) had the highest correlation with ECe. Combining these remotely sensed and ECe variables into one model yielded the best fit with R2=0.78. The result obtained from SI was not only area-wise, but also with its intensity. Out of the total area, 18.8% and 23% were identified as moderately and slightly saline, respectively. This shows that remote sensing data can be effectively used to model and map spatial variations of soil salinity in irrigation areas

The climate variability and drought frequency over potential crop growing regions of Ethiopia during 1983−2012 were analysed. Data from 87 weather stations across the country were used for this analysis. Ethiopian agricultural activities are highly dependent on the long rainy season (June−September) rainfall, which accounts for 70% of the total annual rainfall. There was no significant change in rainfall during annual and the bimodal seasons during this period of study. However, there was significant change in the rainfall coefficient of variation. STARDEX precipitation indices provided a measure of intensity, frequency and proportion of total rainfall. Ninetieth percentile of rainfall, number of rainy days with rainfall >10 mm/day and the greatest 10 d total rainfall were increased over time at most of the stations. Among the major droughts, 1984−'85 drought was reported as the most severe drought with peak negative SPI value −3.68 in Wollo. The longest duration of drought lasted for 63 months in Borena Zone in southern Ethiopia during 1983−2012 period. Extreme maximum temperature (90th percentile) has increased over 45% of the weather stations, while, extreme minimum temperature (90th percentile) has increased 53% of the weather stations. Extreme maximum temperature events have been increasing during the seasons in Ethiopia, which is the real concern for agricultural and livestock activities, as these sectors significantly contribute to about 50% of GDP for the country. However, given the increasing response capacity of the government, as observed during 2002−'03 drought, environmental disaster is expected to be under control over time

Several, countries are struggling to establish proper waste management systems in the context of increasing population and urbanization. Urban solid waste management system needs solid waste management technique, where presence of a sanitary landfill is vital. One of the most important issues of sanitary landfill is to identify suitable locations. The main objective of the present study was to identify suitable solid waste disposal sites that are economically feasible, environmentally sound, and socially acceptable in Logia town, Ethiopia, applying Remote Sensing and Geographic Information System techniques. The present study was based on thematic maps such as groundwater well points, slope, fault, built-up area, road network, river, land-use/land-cover, geology and soil map. Analytical Hierarchy Process pair-wise comparison model was used to accomplish weights of factor parameters. Suitability map was prepared by overlay analyses and assigned as highly suitable, suitable, moderately suitable, less suitable and unsuitable. Results show that 5.93% of the study area is highly suitable, 6.5% is suitable, 3.23% is moderately suitable, 1.02% is less suitable and 83.32% is unsuitable for solid waste dumping in Logia town. Field observations also confirmed suitability of the selected sites, and hence this method can be used in urban areas for waste dumping site selection procedure. Selected sites are considered to be suitable for landfill to minimize environmental risk and human health problems.

Soil salinization is a major problem affecting productivity of irrigated lands in arid and semi-arid areas. Managing salinity to minimize environmental impact is a prerequisite for sustainable irrigated agriculture. The objective of this study was to assess the level of salinity in Sego irrigated farm, Ethiopia and to map temporal and spatial distribution of salt affected soils to support management programmes. The study employed normal image classification, and developing models from ECe vs NDSI and thematic layers to map soil salinity, using geospatial tools. Multi-temporal Landsat TM images of 1984, 1995 and 2010 were used to detect salinity affected areas in the study area. Results of the study revealed that around 6ha of the area gets moderately to strongly salinized per year. Empirical model developed from ECe vs NDSI of 2010 image using regression analysis revealed the coefficient of relation as 66%. The model was extended for the whole area, and revealed that 2.0% of the study area was strongly saline and 54.7% of the area was non-saline. Overlay model developed from water table, land form, land management type and land-cover has revealed that 11.2% of the study area was non-saline, whereas 47.2% and 3.0% was moderately and strongly saline, respectively. Validation of the models was made to test their predication capability and the overlay model has revealed better correlation coefficient of 67.3% to the measured ECe. Most of the salt affected areas were on shallow water table. Cambisols and fluvisols were greatly affected by salinity. The results indicate that long-term irrigation activities would affect agricultural potentiality of the area in the future, and geospatial tools are efficient and feasible for detecting salt affected areas from satellite images and thematic maps