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ABSTRACT

The purpose of this study is to examine local level spatiotemporal rainfall and temperature variability in drought-prone districts of rural Sidama, Central Rift Valley region of Ethiopia. The study used 129 gridded monthly rainfall and temperature data of 32 years (1983–2014). The gridded rainfall and temperature records were encoded into GIS software and evaluated through different statistical and geospatial techniques. Mann-Kendal rank test and F distribution tests were used to test temporal and spatial statistical significance, respectively, of the data. The analysis revealed that Belg and Kiremt are the main rainfall seasons, constituting 81% of the annual rainfall. Although annual, Kiremt, and Belg rainfall amounts appear to have decreased over time, the decreasing trend is statistically significant only for Belg rainfall records. On the other hand, rainfall standard anomaly results indicated seven droughts of different magnitudes: one extreme, two severe, and four moderate. The study also revealed increasing temperature trends over the years under consideration that are statistically significant. The findings of this study on rainfall contradict other findings obtained around the study area. Thus, climate change adaptations need to focus on location-specific climate data analysis so that the intended adaptive interventions can be successful.  相似文献   
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Angularity is an important parameter in the characterization of particle morphology that is used to interpret the transport history of particles in sedimentary deposits. In the past, visual classification using silhouette charts was widely used to determine particle angularity, but this approach is subjective and time‐consuming. With advances in modern image analysis techniques and low‐cost software packages, it is possible to rapidly quantify particle angularity more objectively than using visual classification methods. This study re‐examines the performance of three existing image analysis methods and one new image analysis procedure, applied to six rock and sediment samples that were visually different in angularity. To facilitate comparison between the angularity results, measurements were reduced to rankings for each aggregate sample. These results show that the four image analysis methods rank the angularity of the samples differently, and that none rank the mean angularity index in the same order as the angularity ranking using visual classification. Therefore, further research is needed to develop an image analysis method that can quantify the angularity of sedimentary particles more precisely.  相似文献   
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