The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 20 of 3549
Back to Result List

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.show moreshow less

Export metadata

Additional Services

Search Google Scholar Statistics
Metadaten
Author details: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
Title of parent work (English):Journal of hydrology
Publisher:Elsevier
Place of publishing:Amsterdam
Publication type:Article
Language:English
Year of first publication:2018
Publication year:2018
Release date:2021/10/20
Tag:Complex network; Event synchronization; Rainfall network; Z-P approach
Volume:563
Number of pages:9
First page:802
Last Page:810
Funding 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
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer review:Referiert
Publishing method:Open Access / Green Open-Access
Accept ✔
This website uses technically necessary session cookies. By continuing to use the website, you agree to this. You can find our privacy policy here.