Articles | Volume 24, issue 5
https://doi.org/10.5194/hess-24-2235-2020
https://doi.org/10.5194/hess-24-2235-2020
Research article
 | 
08 May 2020
Research article |  | 08 May 2020

Optimal design of hydrometric station networks based on complex network analysis

Ankit Agarwal, Norbert Marwan, Rathinasamy Maheswaran, Ugur Ozturk, Jürgen Kurths, and Bruno Merz

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Cited articles

Adhikary, S. K., Yilmaz, A. G., and Muttil, N.: Optimal design of rain gauge network in the Middle Yarra River catchment, Australia, Hydrol. Process., 29, 2582–2599, https://doi.org/10.1002/hyp.10389, 2015. 
Agarwal, A.: Unraveling spatio-temporal climatic patterns via multi-scale complex networks, Universität Potsdam, Potsdam, 2019. 
Agarwal, A., Marwan, N., Rathinasamy, M., Merz, B., and Kurths, J.: Multi-scale event synchronization analysis for unravelling climate processes: a wavelet-based approach, Nonlin. Processes Geophys., 24, 599–611, https://doi.org/10.5194/npg-24-599-2017, 2017. 
Agarwal, A., Marwan, N., Maheswaran, R., Merz, B., and Kurths, J.: Quantifying the roles of single stations within homogeneous regions using complex network analysis, J. Hydrol., 563, 802–810, https://doi.org/10.1016/j.jhydrol.2018.06.050, 2018a. 
Agarwal, A., Maheswaran, R., Marwan, N., Caesar, L., and Kurths, J.: Wavelet-based multiscale similarity measure for complex networks, Eur. Phys. J. B, 91, 296, https://doi.org/10.1140/epjb/e2018-90460-6, 2018b. 
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Short summary
In the climate/hydrology network, each node represents a geographical location of climatological data, and links between nodes are set up based on their interaction or similar variability. Here, using network theory, we first generate a node-ranking measure and then prioritize the rain gauges to identify influential and expandable stations across Germany. To show the applicability of the proposed approach, we also compared the results with existing traditional and contemporary network measures.