Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2016WR019981 |
Information theory-based decision support system for integrated design of multivariable hydrometric networks | |
Keum, Jongho1; Coulibaly, Paulin1,2 | |
2017-07-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:7 |
文章类型 | Article |
语种 | 英语 |
国家 | Canada |
英文摘要 | Adequate and accurate hydrologic information from optimal hydrometric networks is an essential part of effective water resources management. Although the key hydrologic processes in the water cycle are interconnected, hydrometric networks (e.g., streamflow, precipitation, groundwater level) have been routinely designed individually. A decision support framework is proposed for integrated design of multivariable hydrometric networks. The proposed method is applied to design optimal precipitation and streamflow networks simultaneously. The epsilon-dominance hierarchical Bayesian optimization algorithm was combined with Shannon entropy of information theory to design and evaluate hydrometric networks. Specifically, the joint entropy from the combined networks was maximized to provide the most information, and the total correlation was minimized to reduce redundant information. To further optimize the efficiency between the networks, they were designed by maximizing the conditional entropy of the streamflow network given the information of the precipitation network. Compared to the traditional individual variable design approach, the integrated multivariable design method was able to determine more efficient optimal networks by avoiding the redundant stations. Additionally, four quantization cases were compared to evaluate their effects on the entropy calculations and the determination of the optimal networks. The evaluation results indicate that the quantization methods should be selected after careful consideration for each design problem since the station rankings and the optimal networks can change accordingly. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000407895000057 |
WOS关键词 | MONITORING NETWORK ; ENTROPY APPROACH ; OPTIMIZATION ; UNCERTAINTY ; VARIABILITY ; STREAMFLOW ; ALGORITHM |
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/21908 |
专题 | 资源环境科学 |
作者单位 | 1.McMaster Univ, Dept Civil Engn, Hamilton, ON, Canada; 2.McMaster Univ, Sch Geog & Earth Sci, Hamilton, ON, Canada |
推荐引用方式 GB/T 7714 | Keum, Jongho,Coulibaly, Paulin. Information theory-based decision support system for integrated design of multivariable hydrometric networks[J]. WATER RESOURCES RESEARCH,2017,53(7). |
APA | Keum, Jongho,&Coulibaly, Paulin.(2017).Information theory-based decision support system for integrated design of multivariable hydrometric networks.WATER RESOURCES RESEARCH,53(7). |
MLA | Keum, Jongho,et al."Information theory-based decision support system for integrated design of multivariable hydrometric networks".WATER RESOURCES RESEARCH 53.7(2017). |
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