Lake Hawassa is one of the Major Ethiopian Rift Valley Lakes which is situated in southern regional state, which has a closed basin system and receives water from only Tikurwuha River and runoff from the catchment. Quality of the lake water is vital for the surrounding community for proper and safe use of the lake. The present study was designed to examine the physicochemical and biological water quality suitability for multiple purposes and to determine trophic state index of the lake for a period of three months from December to February, 2011/12. Water samples were collected from the lake on monthly basis and analyzed for all water quality parameters by using standard methods. Data analysis was performed by descriptive, multivariate analysis (MANOVA) and Tukey-Kramer test. The overall water quality parameters analytical results have been observed as pH (7. . The values of the whole analyzed parameters have shown significant variation in site (P<0.05). As irrigation water quality mainly focuses on the indices of SAR and EC/TDS, the lake water is in good condition for the purpose. The values of trace heavy metals were under permissible limits for multiple aspects. On average, the trophic state index of the Lake Hawassa was hypereutrophic (TSI = 72.6), as Carlson value category. In general, the lake water is not suitable for drinking, recreational and irrigation of some raw consuming crops but it is suitable for aquatic life.

Lake Hawassa is one of the Major Ethiopian Rift Valley Lakes which is situated in southern regional state, which has a closed basin system and receives water from only Tikurwuha River and runoff from the catchment. Quality of the lake water is vital for the surrounding community for proper and safe use of the lake. The present study was designed to examine the physicochemical and biological water quality suitability for multiple purposes and to determine trophic state index of the lake for a period of three months from December to February, 2011/12. Water samples were collected from the lake on monthly basis and analyzed for all water quality parameters by using standard methods. Data analysis was performed by descriptive, multivariate analysis (MANOVA%

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Climate change impact studies that evaluated the biases of climate models' simulations showed the presence of large systematic errors in their outputs. However, many studies continue to arbitrarily select bias correction methods for error reduction. This work evaluated the implications of bias correction methods on the projections of climate change impact on streamflow of the Gidabo sub-basin, Ethiopia. Climate outputs from four global climate model and regional climate model (GCM–RCM) combinations for the representative concentration pathway (RCP4.5) scenario were used. Five bias correction methods were used to reduce the systematic errors of the simulated rainfall data. The future changes in rainfall pattern, evapotranspiration, and streamflow were analyzed by using their relative percentage difference between the projected and the baseline period. The distribution mapping method provided better results in mean and extreme rainfall cases. This is also reflected in streamflow projections, as the daily interquartile range value indicates the lowest variability of the projected streamflow. The wet season streamflow will likely decrease in the future, whereas the short rainy season streamflow will increase. Our findings show that climate models and bias correction methods considerably limit the magnitude of future projections of streamflow. However, similar research should be conducted in other catchments to extend the conclusions of this study.