Implication of bias correction on climate change impact projection of surface water resources in the Gidabo Sub-basin, southern Ethiopia
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 corre...
| Autores principales: | , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
IWA Publishing
2022
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| Acceso en línea: | https://hdl.handle.net/10568/119988 |
| _version_ | 1855542613323546624 |
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| author | Worako, A. W. Haile, Alemseged Tamiru Taye, Meron Teferi |
| author_browse | Haile, Alemseged Tamiru Taye, Meron Teferi Worako, A. W. |
| author_facet | Worako, A. W. Haile, Alemseged Tamiru Taye, Meron Teferi |
| author_sort | Worako, A. W. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. |
| format | Journal Article |
| id | CGSpace119988 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | IWA Publishing |
| publisherStr | IWA Publishing |
| record_format | dspace |
| spelling | CGSpace1199882025-08-18T04:57:05Z Implication of bias correction on climate change impact projection of surface water resources in the Gidabo Sub-basin, southern Ethiopia Worako, A. W. Haile, Alemseged Tamiru Taye, Meron Teferi climate change forecasting surface water water resources water availability stream flow climate models extreme weather events rainfall patterns temperature 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. 2022-05-01 2022-06-30T20:58:40Z 2022-06-30T20:58:40Z Journal Article https://hdl.handle.net/10568/119988 en Open Access IWA Publishing Worako, A. W.; Haile, Alemseged Tamiru; Taye, Meron Teferi. 2022. Implication of bias correction on climate change impact projection of surface water resources in the Gidabo Sub-basin, southern Ethiopia. Journal of Water and Climate Change, 13(5):2070-2088. [doi: https://doi.org/10.2166/wcc.2022.396] |
| spellingShingle | climate change forecasting surface water water resources water availability stream flow climate models extreme weather events rainfall patterns temperature Worako, A. W. Haile, Alemseged Tamiru Taye, Meron Teferi Implication of bias correction on climate change impact projection of surface water resources in the Gidabo Sub-basin, southern Ethiopia |
| title | Implication of bias correction on climate change impact projection of surface water resources in the Gidabo Sub-basin, southern Ethiopia |
| title_full | Implication of bias correction on climate change impact projection of surface water resources in the Gidabo Sub-basin, southern Ethiopia |
| title_fullStr | Implication of bias correction on climate change impact projection of surface water resources in the Gidabo Sub-basin, southern Ethiopia |
| title_full_unstemmed | Implication of bias correction on climate change impact projection of surface water resources in the Gidabo Sub-basin, southern Ethiopia |
| title_short | Implication of bias correction on climate change impact projection of surface water resources in the Gidabo Sub-basin, southern Ethiopia |
| title_sort | implication of bias correction on climate change impact projection of surface water resources in the gidabo sub basin southern ethiopia |
| topic | climate change forecasting surface water water resources water availability stream flow climate models extreme weather events rainfall patterns temperature |
| url | https://hdl.handle.net/10568/119988 |
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