An Integrated Modeling Framework in Projections of Hydrological Extremes
文献类型：期刊论文
| 作者 | Meresa, Hadush1; Zhang, Yongqiang1; Tian, Jing1; Ma, Ning1; Zhang, Xuanze1; Heidari, Hadi2; Naeem, Shahid1 |
| 刊名 | SURVEYS IN GEOPHYSICS
 |
| 出版日期 | 2022-10-03 |
| 页码 | 46 |
| 关键词 | Climate change Uncertainty Hydrological modeling Bias correction Attribution Hydrological extremes |
| ISSN号 | 0169-3298 |
| DOI | 10.1007/s10712-022-09737-w |
| 通讯作者 | Zhang, Yongqiang(yongqiang.zhang2014@gmail.com) |
| 英文摘要 | Quantitative and qualitative knowledge about the potential impacts of climate change on extreme hydrological events is crucial for water resource management and extreme risk management under climate change. This has theoretical and realistic implications to study and couple the climate system with hydrologic processes, to understand the system and solve related problems in water resources and extreme hydrology, such as decision making, plan management, environmental protection, and ecological balance. This paper reviews recent studies investigating climate change impact on hydrological extremes using a perspective of the integrated modeling framework comprising climate change scenarios, climate models, bias correction methods, hydrological modeling (model structure and parameterization), and reducible uncertainty arising from these sources characterized by a paucity of knowledge. The available research outcomes show the extreme high flows are likely to increase under climate change in the most parts of Europe, Asia, and the USA, but greatly vary and decrease in Africa and Latin America, which is highly variable and uncertain in space and time. Each component in integrated modeling has an important role in shifting and producing uncertainty in projected extreme flow. Among them, the climate model's discrepancy and hydrological models' structure are the more dominant source of uncertainty in projection of extreme high and low (or mean) flow in most of the regions, respectively. However, the quality of input data and hydrological model structures are the most dominant source of uncertainty in Africa, Latin America, and some parts of Asia. This indicated that these regions have strong hydrological cycle and higher physiographic heterogeneity. We believe that our existing knowledge and skills need to be improved and transformed into an accurate mathematical and physical representation, to minimize the uncertainty due to the effect of choices in the methodology chain. So, disentangling the aggregated uncertainty in the cascade modeling chain can be done by using variances, which can help understand the interaction effect and identify their contribution to the projected extreme flow. This comprehensive review can help modelers to identify and reduce uncertainty in projecting hydrological extremes and policy makers for full awareness of the various uncertainties to make a robust decision for water resources management under climate change. |
| WOS关键词 | CLIMATE-CHANGE PROJECTIONS ; BIAS CORRECTION METHODS ; BLUE NILE BASIN ; WATER-RESOURCES ; CHANGE IMPACTS ; GLOBAL CLIMATE ; UNCERTAINTY SOURCES ; FLOOD HAZARD ; RIVER-BASIN ; SCALE |
| 资助项目 | Talents Program of the Chinese Academy of Science ; National Natural Science Foundation of China[41971032] ; CAS President's International Fellowship Initiative (PIFI)[2020PE0048] |
| WOS研究方向 | Geochemistry & Geophysics |
| 语种 | 英语 |
| WOS记录号 | WOS:000865224000001 |
| 出版者 | SPRINGER |
| 资助机构 | Talents Program of the Chinese Academy of Science ; National Natural Science Foundation of China ; CAS President's International Fellowship Initiative (PIFI) |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/185646]  |
| 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 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proces, Beijing 100101, Peoples R China 2.Univ Massachusetts, Dept Civil & Environm Engn, Amherst, MA 01002 USA |
| 推荐引用方式 GB/T 7714 | Meresa, Hadush,Zhang, Yongqiang,Tian, Jing,et al. An Integrated Modeling Framework in Projections of Hydrological Extremes[J]. SURVEYS IN GEOPHYSICS,2022:46. |
| APA | Meresa, Hadush.,Zhang, Yongqiang.,Tian, Jing.,Ma, Ning.,Zhang, Xuanze.,...&Naeem, Shahid.(2022).An Integrated Modeling Framework in Projections of Hydrological Extremes.SURVEYS IN GEOPHYSICS,46. |
| MLA | Meresa, Hadush,et al."An Integrated Modeling Framework in Projections of Hydrological Extremes".SURVEYS IN GEOPHYSICS (2022):46. |
入库方式： OAI收割
来源：地理科学与资源研究所
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