Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2017WR020682 |
Gauging Through the Crowd: A Crowd-Sourcing Approach to Urban Rainfall Measurement and Storm Water Modeling Implications | |
Yang, Pan; Ng, Tze Ling | |
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 | Peoples R China |
英文摘要 | Accurate rainfall measurement at high spatial and temporal resolutions is critical for the modeling and management of urban storm water. In this study, we conduct computer simulation experiments to test the potential of a crowd-sourcing approach, where smartphones, surveillance cameras, and other devices act as precipitation sensors, as an alternative to the traditional approach of using rain gauges to monitor urban rainfall. The crowd-sourcing approach is promising as it has the potential to provide high-density measurements, albeit with relatively large individual errors. We explore the potential of this approach for urban rainfall monitoring and the subsequent implications for storm water modeling through a series of simulation experiments involving synthetically generated crowd-sourced rainfall data and a storm water model. The results show that even under conservative assumptions, crowd-sourced rainfall data lead to more accurate modeling of storm water flows as compared to rain gauge data. We observe the relative superiority of the crowd-sourcing approach to vary depending on crowd participation rate, measurement accuracy, drainage area, choice of performance statistic, and crowd-sourced observation type. A possible reason for our findings is the differences between the error structures of crowd-sourced and rain gauge rainfall fields resulting from the differences between the errors and densities of the raw measurement data underlying the two field types. |
英文关键词 | crowd-sourcing rain gauging rainfall monitoring urban storm water modeling computer simulation |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000418736700044 |
WOS关键词 | STREAMFLOW OBSERVATIONS ; HYDROLOGICAL MODELS ; CROWDSOURCED DATA ; MOVING CARS ; NETWORKS ; RESOLUTION ; RADAR ; SCALE ; ASSIMILATION ; VARIABILITY |
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/19965 |
专题 | 资源环境科学 |
作者单位 | Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Kowloon, Hong Kong, Peoples R China |
推荐引用方式 GB/T 7714 | Yang, Pan,Ng, Tze Ling. Gauging Through the Crowd: A Crowd-Sourcing Approach to Urban Rainfall Measurement and Storm Water Modeling Implications[J]. WATER RESOURCES RESEARCH,2017,53(11). |
APA | Yang, Pan,&Ng, Tze Ling.(2017).Gauging Through the Crowd: A Crowd-Sourcing Approach to Urban Rainfall Measurement and Storm Water Modeling Implications.WATER RESOURCES RESEARCH,53(11). |
MLA | Yang, Pan,et al."Gauging Through the Crowd: A Crowd-Sourcing Approach to Urban Rainfall Measurement and Storm Water Modeling Implications".WATER RESOURCES RESEARCH 53.11(2017). |
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