Stream gauge network grouping analysis using community detection
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ORIGINAL PAPER
Stream gauge network grouping analysis using community detection Hongjun Joo1 • Myungjin Lee2 • Jongsung Kim2 • Jaewon Jung3 • Jaewon Kwak4 • Hung Soo Kim2 Accepted: 22 October 2020 The Author(s) 2020
Abstract Stream gauging stations are important in hydrology and water science for obtaining water-related information, such as stage and discharge. However, for efficient operation and management, a more accurate grouping method is needed, which should be based on the interrelationships between stream gauging stations. This study presents a grouping method that employs community detection based on complex networks. The proposed grouping method was compared with the cluster analysis approach, which is based on statistics, to verify its adaptability. To achieve this goal, 39 stream gauging stations in the Yeongsan River basin of South Korea were investigated. The numbers of groups (clusters) in the study were two, four, six, and eight, which were determined to be suitable by fusion coefficient analysis. Ward’s method was employed for cluster analysis, and multilevel modularity optimization was applied for community detection. A higher level of cohesion between stream gauging stations was observed in the community detection method at the basin scale and the stream link scale within the basin than in the cluster analysis. This suggests that community detection is more effective than cluster analysis in terms of hydrologic similarity, persistence, and connectivity. As such, these findings could be applied to grouping methods for efficient operation and maintenance of stream gauging stations. Keywords Stream gauging station Cluster analysis Complex network Community detection
1 Introduction Stages or water levels are widely used in various fields, such as hydrology, water resource management, and environmental science, and one of the primary hydraulic structures for stage measurement is a stream gauging station (Sauer and Turnipseed 2010). Stage and flow data observed at stream gauging stations provide important water information for flood forecast warnings, operation of multipurpose dams, identification of available water resources, and operation of agricultural reservoirs.
& Hung Soo Kim [email protected] 1
Department of Construction Certification Center, Korea Institute of Civil Engineering and Building Technology, Ilsan 10223, Korea
2
Department of Civil Engineering, Inha University, Incheon 22201, Korea
3
Nakdong River Flood Control Office, Ministry of Environment, Busan 49300, Korea
4
Center for Hydrology and Ecology, Incheon 22201, Korea
Consistent efforts have been made to achieve accurate stage measurements and quality control as high-quality stage data affect the reliability of flood, drought, water quality, and ecological management (Joo et al. 2019a, b), which require efficient management of stream gauging stations. The operation and management of stream gauging stations require basin-scale analysis based on up-and-down streams, mainstreams, and tributaries. Specifically, strea
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