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Quantifying the roles of single stations within homogeneous regions using complex network analysis

  • Regionalization and pooling stations to form homogeneous regions or communities are essential for reliable parameter transfer, prediction in ungauged basins, and estimation of missing information. Over the years, several clustering methods have been proposed for regional analysis. Most of these methods are able to quantify the study region in terms of homogeneity but fail to provide microscopic information about the interaction between communities, as well as about each station within the communities. We propose a complex network-based approach to extract this valuable information and demonstrate the potential of our approach using a rainfall network constructed from the Indian gridded daily precipitation data. The communities were identified using the network-theoretical community detection algorithm for maximizing the modularity. Further, the grid points (nodes) were classified into universal roles according to their pattern of within- and between-community connections. The method thus yields zoomed-in details of individual rainfallRegionalization and pooling stations to form homogeneous regions or communities are essential for reliable parameter transfer, prediction in ungauged basins, and estimation of missing information. Over the years, several clustering methods have been proposed for regional analysis. Most of these methods are able to quantify the study region in terms of homogeneity but fail to provide microscopic information about the interaction between communities, as well as about each station within the communities. We propose a complex network-based approach to extract this valuable information and demonstrate the potential of our approach using a rainfall network constructed from the Indian gridded daily precipitation data. The communities were identified using the network-theoretical community detection algorithm for maximizing the modularity. Further, the grid points (nodes) were classified into universal roles according to their pattern of within- and between-community connections. The method thus yields zoomed-in details of individual rainfall grids within each community.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Ankit AgarwalORCiDGND, Norbert MarwanORCiDGND, Rathinasamy MaheswaranORCiD, Bruno MerzORCiDGND, Jürgen KurthsORCiDGND
DOI:https://doi.org/10.1016/j.jhydrol.2018.06.050
ISSN:0022-1694
ISSN:1879-2707
Titel des übergeordneten Werks (Englisch):Journal of hydrology
Verlag:Elsevier
Verlagsort:Amsterdam
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Jahr der Erstveröffentlichung:2018
Erscheinungsjahr:2018
Datum der Freischaltung:20.10.2021
Freies Schlagwort / Tag:Complex network; Event synchronization; Rainfall network; Z-P approach
Band:563
Seitenanzahl:9
Erste Seite:802
Letzte Seite:810
Fördernde Institution:Deutsche Forschungsgemeinschaft (DFG) within the graduate research training group "Natural risk in a changing world (NatRiskChange)" at the University of PotsdamGerman Research Foundation (DFG) [GRK 2043/1]; Humboldt FoundationAlexander von Humboldt Foundation
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer Review:Referiert
Publikationsweg:Open Access / Green Open-Access
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