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DOI | 10.1002/2017WR021253 |
Symbolic Regression for the Estimation of Transfer Functions of Hydrological Models | |
Klotz, D.; Herrnegger, M.; Schulz, K. | |
2017-11-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:11 |
文章类型 | Article |
语种 | 英语 |
国家 | Austria |
英文摘要 | Current concepts for parameter regionalization of spatially distributed rainfall-runoff models rely on the a priori definition of transfer functions that globally map land surface characteristics (such as soil texture, land use, and digital elevation) into the model parameter space. However, these transfer functions are often chosen ad hoc or derived from small-scale experiments. This study proposes and tests an approach for inferring the structure and parametrization of possible transfer functions from runoff data to potentially circumvent these difficulties. The concept uses context-free grammars to generate possible proposition for transfer functions. The resulting structure can then be parametrized with classical optimization techniques. Several virtual experiments are performed to examine the potential for an appropriate estimation of transfer function, all of them using a very simple conceptual rainfall-runoff model with data from the Austrian Mur catchment. The results suggest that a priori defined transfer functions are in general well identifiable by the method. However, the deduction process might be inhibited, e.g., by noise in the runoff observation data, often leading to transfer function estimates of lower structural complexity. |
英文关键词 | transfer function estimation regionalization symbolic regression model calibration virtual experiments |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000418736700041 |
WOS关键词 | PARAMETER-ESTIMATION ; REGIONALIZATION METHODS ; RUNOFF ; UNCERTAINTY ; CALIBRATION ; DRAINAGE ; BASINS ; SIZE |
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/21572 |
专题 | 资源环境科学 |
作者单位 | Univ Nat Resources & Life Sci, Inst Water Management Hydrol & Hydraul Engn, Vienna, Austria |
推荐引用方式 GB/T 7714 | Klotz, D.,Herrnegger, M.,Schulz, K.. Symbolic Regression for the Estimation of Transfer Functions of Hydrological Models[J]. WATER RESOURCES RESEARCH,2017,53(11). |
APA | Klotz, D.,Herrnegger, M.,&Schulz, K..(2017).Symbolic Regression for the Estimation of Transfer Functions of Hydrological Models.WATER RESOURCES RESEARCH,53(11). |
MLA | Klotz, D.,et al."Symbolic Regression for the Estimation of Transfer Functions of Hydrological Models".WATER RESOURCES RESEARCH 53.11(2017). |
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