Coupling higher-order probability weighted moments with norming constants method for non-stationary annual maximum flood frequency analysis
文献类型：期刊论文
| 作者 | Chen, Fei1,7; Sang, Yan-Fang4,5,6; Xie, Ping7; Wu, Linqian3; Huo, Jingqun7; Singh, Vijay P.2 |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2024-09-01 |
| 卷号 | 641页码:131832 |
| 关键词 | Hydrologic frequency analysis Non-stationary characteristics Flood Norming constants method Higher-order probability weighted moments |
| DOI | 10.1016/j.jhydrol.2024.131832 |
| 产权排序 | 3 |
| 文献子类 | Article |
| 英文摘要 | Non-stationary flood frequency analysis (NFFA) is essential for reducing the risk of hydrologic engineering design and operation, especially when done under the severe influences of climate change and strong human activities. Although different types of methods have been proposed, NFFA is still a challenging task due to the complex characteristics of hydroclimatic data and weaknesses of diverse methods. In this article, a new method, called HPWM-NCM, is proposed for NFFA. The method uses the higher-order probability weighted moments (HPWM) method to accurately estimate parameters of flood data, and then applies the norming constants method (NCM) to precisely calculate the norming constants and further do NFFA. Results of both Monte-Carlo experiments and observed hydrologic data at 62 stations in the Rhine River basin illustrated that HPWM-NCM significantly improved the NFFA results compared to conventional NCM and the probability weighted moments method, as evaluated by overall fitting bias, residuals' correlation, and residuals' maximum error. Results highlighted the importance of using the information in high quantiles (rather than low quantiles) of flood data for NFFA, which is the key of the proposed method and ensures its superiority. Overall, the advantages of HPWM-NCM for nonstationary flood frequency analysis were confirmed, and the method has the potential for wide use in hydrologic and climate sciences. |
| WOS关键词 | DURATION CURVES ; CLIMATE-CHANGE ; BOUNDING ORDINATE ; RETURN PERIOD ; DISTRIBUTIONS ; STATIONARITY ; STREAMFLOW ; PREDICTION ; PARAMETERS ; TRENDS |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| WOS记录号 | WOS:001296839600001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/206890]  |
| 专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
| 通讯作者 | Sang, Yan-Fang |
| 作者单位 | 1.POWERCHINA Chengdu Engn Corp Ltd, Chengdu 610072, Peoples R China 2.Texas A&M Univ, Dept Biol & Agr Engn, Zachry Dept Civil & Environm Engn, College Stn, TX 77843 USA 3.Minist Ecol & Environm, Yellow River Basin Ecol Environm Supervis Adm, Yellow River Ecol Environm Sci Res Inst, Zhengzhou 450001, Peoples R China 4.Univ Chinese Acad Sci, Beijing 101407, Peoples R China 5.Minist Emergency Management China, Key Lab Cpd & Chained Nat Hazards Dynam, Beijing 100085, Peoples R China 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 7.Wuhan Univ, State Key Lab Water Resources Engn & Management, Wuhan 430072, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Fei,Sang, Yan-Fang,Xie, Ping,et al. Coupling higher-order probability weighted moments with norming constants method for non-stationary annual maximum flood frequency analysis[J]. JOURNAL OF HYDROLOGY,2024,641:131832. |
| APA | Chen, Fei,Sang, Yan-Fang,Xie, Ping,Wu, Linqian,Huo, Jingqun,&Singh, Vijay P..(2024).Coupling higher-order probability weighted moments with norming constants method for non-stationary annual maximum flood frequency analysis.JOURNAL OF HYDROLOGY,641,131832. |
| MLA | Chen, Fei,et al."Coupling higher-order probability weighted moments with norming constants method for non-stationary annual maximum flood frequency analysis".JOURNAL OF HYDROLOGY 641(2024):131832. |
入库方式： OAI收割
来源：地理科学与资源研究所
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