TY  - GEN
A1  - Agarwal, Ankit
A1  - Marwan, Norbert
A1  - Maheswaran, Rathinasamy
A1  - Öztürk, Ugur
A1  - Kurths, Jürgen
A1  - Merz, Bruno
T1  - Optimal design of hydrometric station networks based on complex network analysis
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few 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 (WDB) measure – to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 951 
KW  - identifying influential nodes
KW  - climate networks
KW  - rainfall
KW  - streamflow
KW  - synchronization
KW  - precipitation
KW  - classification
KW  - events
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-471006
SN  - 1866-8372
IS  - 951
ER  - 
TY  - JOUR
A1  - Agarwal, Ankit
A1  - Marwan, Norbert
A1  - Maheswaran, Rathinasamy
A1  - Öztürk, Ugur
A1  - Kurths, Jürgen
A1  - Merz, Bruno
T1  - Optimal design of hydrometric station networks based on complex network analysis
JF  - Hydrology and Earth System Sciences
N2  - Hydrometric networks play a vital role in providing information for decision-making in water resource management. They should be set up optimally to provide as much information as possible that is as accurate as possible and, at the same time, be cost-effective. Although the design of hydrometric networks is a well-identified problem in hydrometeorology and has received considerable attention, there is still scope for further advancement. In this study, we use complex network analysis, defined as a collection of nodes interconnected by links, to propose a new measure that identifies critical nodes of station networks. The approach can support the design and redesign of hydrometric station networks. The science of complex networks is a relatively young field and has gained significant momentum over the last few 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 (WDB) measure – to evaluate the importance of nodes in a network. It is compared to previously proposed measures used on synthetic sample networks and then applied to a real-world rain gauge network comprising 1229 stations across Germany to demonstrate its applicability. The proposed measure is evaluated using the decline rate of the network efficiency and the kriging error. The results suggest that WDB effectively quantifies the importance of rain gauges, although the benefits of the method need to be investigated in more detail.
KW  - identifying influential nodes
KW  - climate networks
KW  - rainfall
KW  - streamflow
KW  - synchronization
KW  - precipitation
KW  - classification
KW  - events
Y1  - 2020
U6  - https://doi.org/10.5194/hess-24-2235-2020
SN  - 1027-5606
SN  - 1607-7938
VL  - 24
IS  - 5
SP  - 2235
EP  - 2251
PB  - Copernicus Publ.
CY  - Göttingen
ER  -