Complex network analysis and robustness evaluation of spatial variation of monthly rainfall-Reference-Cited by-同舟云学术

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Complex network analysis and robustness evaluation of spatial variation of monthly rainfall

Published:2023-10-17 Issue: Volume: Page:
ISSN:1436-3240
Container-title:Stochastic Environmental Research and Risk Assessment
language:en
Short-container-title:Stoch Environ Res Risk Assess

Author:

Tongal Hakan,Sivakumar Bellie

Funder

Indian Institute of Technology Bombay

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00477-023-02578-y.pdf

Reference85 articles.

1. Abbot J, Marohasy J (2014) Input selection and optimisation for monthly rainfall forecasting in Queensland, Australia, using artificial neural networks. Atmos Res 138:166–178

2. Abu Romman Z, Al-Bakri J, Al Kuisi M (2021) Comparison of methods for filling in gaps in monthly rainfall series in arid regions. Int J Climatol 41(15):6674–6689

3. Agarwal A, Marwan N, Maheswaran R, Merz B, Kurths J (2018) Quantifying the roles of single stations within homogeneous regions using complex network analysis. J Hydrol 563:802–810

4. Agarwal A, Guntu RK, Banerjee A, Gadhawe MA, Marwan N (2022) A complex network approach to study the extreme precipitation patterns in a river basin. Chaos Interdiscip J Nonlinear Sci 32(1):013113

5. Aldecoa R, Marin I (2012) Closed benchmarks for network community structure characterization. Phys Rev E 85(2):026109

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