Analysis of Annual Drought Episodes Using Complex Networks

Konstantinos Spiliotis, Konstantinos Voudouris, Harris Vangelis and Mike Spiliotis ()
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Konstantinos Spiliotis: Laboratory of Mathematics and Informatics (ISCE), Department of Civil Engineering, Democritus University of Thrace, Kimmeria Campus, 67100 Xanthi, Greece
Konstantinos Voudouris: Laboratory of Engineering Geology and Hydrogeology, School of Geology, Aristotle University of Thessaloniki (AUTh), 54124 Thessaloniki, Greece
Harris Vangelis: Centre for the Assessment of Natural Hazards and Proactive Planning & Laboratory of Reclamation Works and Water Resources Management, School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, 9 Heroon Polytechniou St., Zographou, 15780 Athens, Greece
Mike Spiliotis: Division of Hydraulic Works, Department of Civil Engineering, Democritus University of Thrace, Kimmeria Campus, 67100 Xanthi, Greece

Sustainability, 2025, vol. 17, issue 4, 1-17

Abstract: In this work, a new method to analyze the drought episodes based on the annual precipitation time series and utilizing complex networks theory is proposed. The precipitation time series is transformed into a complex network using the visibility algorithm.Then, several network measures are computed to characterize the underlying connectivity. The proposed analysis identifies important nodes which correspond to the low annual precipitation volume, providing a way to assess drought intensity without the use of the mean value and standard deviation, which are sensitive to climate change. Additionally, using community detection algorithms and network centrality measures, the method identifies ∼10-year and ∼4-year cycles within a period of 57 years. Using macroscopic measures like network distributions, we can identify rare high-intensity drought events. Finally, network analysis shows that the closeness centrality measure is in very good agreement with the well-known Standardised Precipitation Index (SPI) and thus can be used to characterize drought intensity.

Keywords: meteorological drought; complex networks; betweenness centrality; modularity; drought cyclicity; extreme drought events (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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