The Ethiopian Rift Valley lakes have been subjected to environmental and ecological changes due to recent development endeavors and natural phenomena, which are visible in the alterations to the quality and quantity of the water resources. Monitoring lakes for temporal and spatial alterations has become a valuable indicator of environmental change. In this regard, hydrographic information has a paramount importance. The first extensive hydrographic survey of Lake Hawassa was conducted in 1999. In this study, a bathymetric map was prepared using advances in global positioning systems, portable sonar sounder technology, geostatistics, remote sensing and geographic information system (GIS) software analysis tools with the aim of detecting morphometric changes. Results showed that the surface area of Lake Hawassa increased by 7.5% in 1999 and 3.2% in 2011 from that of 1985. Water volume decreased by 17% between 1999 and 2011. Silt accumulated over more than 50% of the bed surface has caused a 4% loss of the lake's storage capacity. The sedimentation patterns identified may have been strongly impacted by anthropogenic activities including urbanization and farming practices located on the northern, eastern and western sides of the lake watershed. The study demonstrated this geostatistical modeling approach to be a rapid and cost-effective method for bathymetric mapping.
Introduction The health insurance system has been proven to offer effective and efficient health care for the community, particularly community-based health insurance is expected to ensure health care access for people with low economic status and vulnerable groups. Despite the significance of evidence-based systems and implementation, there is a limited report about the magnitude of CBHI utilization. Therefore, this study was done to assess factors associated with community-based health insurance utilization in Basona Worena District, North Shewa Zone, Ethiopia. Method A community-based cross-sectional study was employed. We have included 530 households from 6 randomly selected kebeles. The data was entered using Epi-Data V 3.1 and exported to SPSS version 20.0 for statistical analysis. Bi-variable and multivariable logistic regression analyses were computed to determine factors associated with community-based health insurance utilization. Result The study finding shows that 58.6% of the respondents were members of community-based health insurance. Respondents who had primary and secondary education levels were 2 times more likely to be members than those who had no formal education. As compared to those who had awareness, respondents who had no awareness about CBHI were 0.27 times less likely to be insured. Respondents who did not experience illness were 0.27 times less likely to be members than respondents who experienced illness. Conclusion Educational status, awareness about CBHI, perception of CBHI scheme and illness experience of family influence CBHI utilization. There is a need to strengthen awareness creation to improve the CBHI utilization.
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