Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019WR026659 |
Impacts of Using State-of-the-Art Multivariate Bias Correction Methods on Hydrological Modeling Over North America | |
Guo, Qiang1,2; Chen, Jie1,2; Zhang, Xunchang John3; Xu, Chong-Yu4; Chen, Hua1 | |
2020-04-21 | |
发表期刊 | WATER RESOURCES RESEARCH
![]() |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2020 |
卷号 | 56期号:5 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China; USA; Norway |
英文摘要 | Bias correction techniques are widely used to bridge the gap between climate model outputs and input requirements of hydrological models to assess the climate change impacts on hydrology. In addition to univariate bias correction methods, several multivariate bias correction methods were proposed recently, which can not only correct the biases in marginal distributions of individual climate variables but also properly adjust the biased intervariable correlations simulated by climate models. Due to the diversities of climate regime and climate model bias, hydrological simulation for watersheds under different climate conditions may show various sensitivities to the correction of intervariable correlations. Therefore, it is of great importance to investigate (1) whether the correction of intervariable correlations has impacts on the hydrological modeling and (2) how these impacts vary with watersheds under different climate conditions. To achieve these goals, this study evaluates behaviors and their spatial variability of multiple state-of-the-art multivariate bias correction methods in hydrological modeling over 2,840 watersheds distributed in different climate regimes in North America. The results show that, compared to using a quantile mapping univariate bias correction method, applying multivariate methods can improve the simulation of snow proportion, snowmelt, evaporation, and several streamflow variables. In addition, this improvement is more clear for watersheds with arid and warm temperate climates in southern regions, while it is limited for northern snow-characterized watersheds. Overall, this study demonstrates the importance of using multivariate bias correction methods instead of univariate methods in hydrological climate change impact studies, especially for watersheds with arid and warm temperate climates. |
英文关键词 | multivariate bias correction methods hydrological modeling intervariable correlation climate regimes North America |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000537736400042 |
WOS关键词 | CLIMATE-CHANGE IMPACTS ; PART 2 ; PRECIPITATION ; SIMULATIONS ; TEMPERATURE ; OUTPUTS ; UNCERTAINTY ; SENSITIVITY ; DEPENDENCE ; RUNOFF |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
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/249199 |
专题 | 资源环境科学 |
作者单位 | 1.Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan, Peoples R China; 2.Wuhan Univ, Hubei Prov Key Lab Water Syst Sci Sponge City Con, Wuhan, Peoples R China; 3.ARS, USDA, Grazinglands Res Lab, El Reno, OK USA; 4.Univ Oslo, Dept Geosci, Oslo, Norway |
推荐引用方式 GB/T 7714 | Guo, Qiang,Chen, Jie,Zhang, Xunchang John,et al. Impacts of Using State-of-the-Art Multivariate Bias Correction Methods on Hydrological Modeling Over North America[J]. WATER RESOURCES RESEARCH,2020,56(5). |
APA | Guo, Qiang,Chen, Jie,Zhang, Xunchang John,Xu, Chong-Yu,&Chen, Hua.(2020).Impacts of Using State-of-the-Art Multivariate Bias Correction Methods on Hydrological Modeling Over North America.WATER RESOURCES RESEARCH,56(5). |
MLA | Guo, Qiang,et al."Impacts of Using State-of-the-Art Multivariate Bias Correction Methods on Hydrological Modeling Over North America".WATER RESOURCES RESEARCH 56.5(2020). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论