Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2016WR019863 |
A process-based insight into nonstationarity of the probability distribution of annual runoff | |
Jiang, Cong1; Xiong, Lihua1; Guo, Shenglian1; Xia, Jun1; Xu, Chong-Yu1,2 | |
2017-05-01 | |
发表期刊 | WATER RESOURCES RESEARCH
![]() |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:5 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China; Norway |
英文摘要 | In this paper, a process-based analytical derivation approach is proposed to perform a nonstationary analysis for annual runoff distribution by taking into account the information of nonstationarities in both hydrological inputs and runoff generation processes. Under the Budyko hypothesis, annual runoff is simulated as a formulation of hydrological inputs (annual precipitation and potential evaporation) using an annual runoff model based on the Fu equation with a parameter w accounting for the runoff generation processes. The nonstationarity of the runoff generation process is captured by the dynamic Fu-equation parameter w. Then the multivariate joint probability distribution among the hydrological inputs, the Fu-equation parameter w, and the runoff model error k is constructed based on the nonstationary analysis for both the hydrological inputs and w. Finally, the annual runoff distribution is derived by integrating the multivariate joint probability density function. The derived distribution by the process-based analytical derivation approach performs well in fitting distributions of the annual runoffs from both the Yangtze River and Yellow River, China. For most study watersheds in these two basins, the derived annual runoff distributions are found to be nonstationary, due to the nonstationarities in hydrological inputs (mainly potential evaporation) or the Fu-equation parameter w. Plain Language Summary In this paper, a nonstationary process-based analytical derivation approach is proposed to estimate the annual runoff distribution by taking into account information of nonstationarities in both hydrological inputs and runoff generation processes. The annual runoff generation processes are modeled by Fu equation expressing annual runoff as a formulation of the hydrological inputs (annual precipitation and potential evaporation). Based on the nonstationarity identifications of hydrological inputs and the Fu-equation parameter, the annual runoff distribution is derived by integrating the multivariate joint probability density function among the hydrological inputs, the Fu-equation parameter, and the runoff model error. The nonstationary process-based analytical derivation approach is applied to the annual runoff series from the Yangtze River and Yellow River, China, and performs well in fitting annual runoff distributions. This approach is able to provide a process-based insight into the nonstationarity in annual runoff. |
英文关键词 | annual runoff distribution nonstationarity detection process-based analytical derivation approach Fu equation |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000403712100041 |
WOS关键词 | CHANGE-POINT DETECTION ; TERM WATER-BALANCE ; LOW-FLOW SERIES ; FREQUENCY-ANALYSIS ; CLIMATE-CHANGE ; RETURN PERIOD ; YANGTZE-RIVER ; CATCHMENTS ; HYDROLOGY ; MODEL |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
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/21823 |
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.Univ Oslo, Dept Geosci, Oslo, Norway |
推荐引用方式 GB/T 7714 | Jiang, Cong,Xiong, Lihua,Guo, Shenglian,et al. A process-based insight into nonstationarity of the probability distribution of annual runoff[J]. WATER RESOURCES RESEARCH,2017,53(5). |
APA | Jiang, Cong,Xiong, Lihua,Guo, Shenglian,Xia, Jun,&Xu, Chong-Yu.(2017).A process-based insight into nonstationarity of the probability distribution of annual runoff.WATER RESOURCES RESEARCH,53(5). |
MLA | Jiang, Cong,et al."A process-based insight into nonstationarity of the probability distribution of annual runoff".WATER RESOURCES RESEARCH 53.5(2017). |
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