Disentangling aggregated uncertainty sources in peak flow projections under different climate scenarios
文献类型：期刊论文
| 作者 | Meresa, Hadush; Zhang, Yongqiang; Tian, Jing; Faiz, Muhammad Abrar |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2022-10-01 |
| 卷号 | 613页码:15 |
| 关键词 | Uncertainty Projection Flood Climate change Model Bias correction |
| ISSN号 | 0022-1694 |
| DOI | 10.1016/j.jhydrol.2022.128426 |
| 通讯作者 | Zhang, Yongqiang(yongqiang.zhang2014@gmail.com) |
| 英文摘要 | Evaluation of peak flood magnitude and frequency in the future at a catchment scale under global warming is crucial for water resource management and flood risk management. Climate model outputs provide a leading source of information to quantify the effect of the foreseen natural and anthropogenic climate change on the environment and natural systems. However, modelling climate change impact on peak flow is subject to considerable uncertainties from the climate model discrepancies, bias correction methods, and hydrological model parameters. This study develops a framework to examine changes and disentangle uncertainties in peak flow, which is tested at five Awash catchments in Ethiopia, a region exposed to extreme flood risk. The results showed that projected extreme precipitation and peak flow magnitude could increase substantially in the coming decades by 30% to 55%. The uncertainty analysis confirms that the dominant factor in peak flood projection is climate models in catchments like Akaki (55%) and Awash H (51%), but the bias correction methods in Awash B (58%) and Kela (50%), respectively. The least important factor is the hydrological parameter set for flood projections. Moreover, the findings reveal that peak flood risks would noticeably increase in the near and far future in all catchments, in Awash located in the Tropical dry region. Therefore, various state water agencies from local to national scales must take certain non-structural/structural measures to mitigate flood risks in the future, and to adapt to future climate. |
| WOS关键词 | BIAS CORRECTION ; FREQUENCY-ANALYSIS ; CHANGE IMPACTS ; MODEL ; FLOODS ; PRECIPITATION ; DISTRIBUTIONS ; CALIBRATION ; MANAGEMENT ; CATCHMENTS |
| 资助项目 | CAS Pioneer Talents Program ; CAS Presidents International Fellowship Initiative (PIFI)[2020PE0048] ; National Natural Science Foundation of China[41971032] |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:000862333300002 |
| 出版者 | ELSEVIER |
| 资助机构 | CAS Pioneer Talents Program ; CAS Presidents International Fellowship Initiative (PIFI) ; National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/185531]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhang, Yongqiang |
| 作者单位 | Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Meresa, Hadush,Zhang, Yongqiang,Tian, Jing,et al. Disentangling aggregated uncertainty sources in peak flow projections under different climate scenarios[J]. JOURNAL OF HYDROLOGY,2022,613:15. |
| APA | Meresa, Hadush,Zhang, Yongqiang,Tian, Jing,&Faiz, Muhammad Abrar.(2022).Disentangling aggregated uncertainty sources in peak flow projections under different climate scenarios.JOURNAL OF HYDROLOGY,613,15. |
| MLA | Meresa, Hadush,et al."Disentangling aggregated uncertainty sources in peak flow projections under different climate scenarios".JOURNAL OF HYDROLOGY 613(2022):15. |
入库方式： OAI收割
来源：地理科学与资源研究所
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