A comprehensive uncertainty analysis of model-estimated longitudinal and lateral dispersion coefficients in open channels
文献类型：期刊论文
| 作者 | Najafzadeh, Mohammad2; Noori, Roohollah3,6; Afroozi, Diako2; Ghiasi, Behzad4; Hosseini-Moghari, Seyed-Mohammad5; Mirchi, Ali1; Haghighi, Ali Torabi3; Klove, Bjorn3 |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2021-12-01 |
| 卷号 | 603页码:9 |
| ISSN号 | 0022-1694 |
| 关键词 | Open channel Machine learning models Rates of mixing Uncertainty |
| DOI | 10.1016/j.jhydrol.2021.126850 |
| 通讯作者 | Noori, Roohollah(roohollah.noori@oulu.fi) |
| 英文摘要 | The complexity of pollutant-mixing mechanism in open channels generates large uncertainty in estimation of longitudinal and lateral dispersion coefficients (K-x and K-y). Therefore, K-x and K-y estimation in rivers should be accompanied by an uncertainty analysis, a subject mainly ignored in previous studies. We introduce a method based on thorough analysis of different calibration datasets, resampled from a global database of tracer studies, to determine the uncertainty associated with five applicable intelligent models for estimation of K-x and K-y (model tree, evolutionary polynomial regression (EPR), gene expression programming, multivariate adaptive regression splines (MARS), and support vector machine (SVM)). Our findings suggest that SVM gives least uncertainty in both K-x and K-y estimation, while EPR and MARS generate most uncertainty in K-x and K-y estimation, respectively. By considering significant uncertainty in the model estimations, we suggest that the methodology we introduce here for uncertainty determination of the models be incorporated in empirical studies on estimation of K-x and K-y in rivers. |
| WOS关键词 | NATURAL STREAMS ; WATER-QUALITY ; PREDICTING DISPERSION ; SOLUTE TRANSPORT ; RIVER ; STRAIGHT ; PARAMETERS ; EQUATION |
| 资助项目 | Arctic Interactions (ArcI) Visit Grant program, Profi 4, University of Oulu |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:000706313000036 |
| 资助机构 | Arctic Interactions (ArcI) Visit Grant program, Profi 4, University of Oulu |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/167494]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Noori, Roohollah |
| 作者单位 | 1.Oklahoma State Univ, Dept Biosyst & Agr Engn, 111 Agr Hall, Stillwater, OK 74078 USA 2.Grad Univ Adv Technol, Fac Civil & Surveying Engn, Dept Water Engn, Kerman 76315116, Iran 3.Univ Oulu, Fac Technol, Water Energy & Environm Engn Res Unit, Oulu 90014, Finland 4.Univ Tehran, Coll Engn, Sch Environm, Tehran 1417853111, Iran 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 6.Iran Univ Sci & Technol, Sch Civil Engn, Tehran 1684613114, Iran |
| 推荐引用方式 GB/T 7714 | Najafzadeh, Mohammad,Noori, Roohollah,Afroozi, Diako,et al. A comprehensive uncertainty analysis of model-estimated longitudinal and lateral dispersion coefficients in open channels[J]. JOURNAL OF HYDROLOGY,2021,603:9. |
| APA | Najafzadeh, Mohammad.,Noori, Roohollah.,Afroozi, Diako.,Ghiasi, Behzad.,Hosseini-Moghari, Seyed-Mohammad.,...&Klove, Bjorn.(2021).A comprehensive uncertainty analysis of model-estimated longitudinal and lateral dispersion coefficients in open channels.JOURNAL OF HYDROLOGY,603,9. |
| MLA | Najafzadeh, Mohammad,et al."A comprehensive uncertainty analysis of model-estimated longitudinal and lateral dispersion coefficients in open channels".JOURNAL OF HYDROLOGY 603(2021):9. |
入库方式： OAI收割
来源：地理科学与资源研究所
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