Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2020.105331 |
Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China | |
Limin Zhang, Fei Yuan, Bing Wang, Liliang Ren, ... Shuya Liu | |
2020-10-22 | |
发表期刊 | Atmospheric Research |
出版年 | 2020 |
英文摘要 | Extreme flow projections are of considerable necessity for flood and drought disaster prevention and sustainable water resources management to adapt to future climate change. However, these projections are usually associated with large uncertainties arising from different sources. A numerical modeling system including three emission scenarios (ESs), four climate models (CMs), four statistical downscaling (SD) methods, four hydrological modeling (HM) schemes, and four probability distribution (PD) functions was established in this study to project future extreme flow changes at basin scales. This modeling system was employed in the following three watersheds with different climatic and topographical characteristics in China: The Upper Ganjiang River basin (UGRB) in the humid region, the Laoha River basin (LRB) in the semi-arid region, and the Yellow River source region (YRSR) in the semi-humid region. Subsequently, the analysis of variance approach (ANOVA) was used to quantify the contribution of different uncertainty sources in extreme flow projections. Results show that extreme high flow was projected to increase in all basins. By contrast, extreme low flow would decrease in UGRB, and inconsistent change signals were found in LRB and YRSR. The ANOVA-based assessment reveals that CM is generally the dominant uncertainty source for mean monthly streamflow and extreme low flow projections. ES explains a large proportion of total uncertainty for extreme low flow projection in the 2060s in UGRB because of the large difference in non-precipitation frequency projected under different ESs. SD is the main uncertainty source in extreme high flow projection in UGRB where extreme precipitation events frequently occur. Compared with other basins, HM produces relatively high uncertainty in LRB due to its inferior performance in historical streamflow simulations. PD contributes a low percentage of uncertainty in extreme flow projections. Interactions among uncertainty sources even produce larger uncertainties than most individual sources. Although future extreme flow projections are associated with non-negligible uncertainties, the projected remarkable changes in extreme high and low flows indicate that stakeholders should take certain measures to mitigate flood risks in the three basins and alleviate drought risks in UGRB |
领域 | 地球科学 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/300122 |
专题 | 地球科学 |
推荐引用方式 GB/T 7714 | Limin Zhang, Fei Yuan, Bing Wang, Liliang Ren, ... Shuya Liu. Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China[J]. Atmospheric Research,2020. |
APA | Limin Zhang, Fei Yuan, Bing Wang, Liliang Ren, ... Shuya Liu.(2020).Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China.Atmospheric Research. |
MLA | Limin Zhang, Fei Yuan, Bing Wang, Liliang Ren, ... Shuya Liu."Quantifying uncertainty sources in extreme flow projections for three watersheds with different climate features in China".Atmospheric Research (2020). |
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