Optimal Design of Hydrometric Station Networks Based on Complex Network Analysis

Hydrometric networks play a vital role in providing information for decision-making in water resources management. They should be set up optimally to provide as much and as accurate information as possible, and at the same time, be cost-effective. We propose a new measure, based on complex network analysis, to support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum in the last years in different areas such as brain networks, social networks, technological networks or climate networks. The identification of influential nodes in complex networks is an important field of research. We propose a new node ranking measure, the weighted degree-betweenness, to evaluate the importance of nodes in a network. It is compared to previously proposed measures on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to check its applicability in the optimal design of hydrometric networks. The proposed measure is evaluated using the decline rate of network efficiency and the kriging error. The results suggest that it effectively quantifies the importance of rain stations. The new measure is very useful in identifying influential stations which need high attention and expendable stations which can be removed without much loss of information provided by the station network.