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  A complex network approach to study the extreme precipitation patterns in a river basin

Agarwal, A., Guntu, R. K., Banerjee, A., Gadhawe, M. A., Marwan, N. (2022): A complex network approach to study the extreme precipitation patterns in a river basin. - Chaos, 32, 1, 013113.
https://doi.org/10.1063/5.0072520

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 Creators:
Agarwal, Ankit1, Author
Guntu, Ravi Kumar1, Author
Banerjee, Abhirup2, Author              
Gadhawe, Mayuri Ashokrao1, Author
Marwan, Norbert2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, Potsdam, ou_persistent13              

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 Abstract: The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes. Extreme precipitation networks are constructed over a river basin using event synchronization (ES) and edit distance (ED). Edit distance is an alternative to event synchronization accounting for the sequences and the magnitude of events. Network-based measure degree is employed to understand the spatial synchronization pattern of the extreme precipitation in the Ganga river basin (GRB). The influence of the topography and rainfall characteristics on the extreme precipitation networks is also quantified. The proposed study can estimate the impact of artificial boundaries, thereby better understanding the extreme precipitation network's topology and spatial risk quantification of extreme events.

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Language(s): eng - English
 Dates: 2021-09-232021-12-202022-01-112022-01-11
 Publication Status: Finally published
 Pages: 12
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1063/5.0072520
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Regional keyword: Asia
MDB-ID: No data to archive
 Degree: -

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Title: Chaos
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 32 (1) Sequence Number: 013113 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/180808
Publisher: American Institute of Physics (AIP)