Volume 15, Issue 1 (1-2025)
IJOCE 2025, 15(1): 131-140 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Sheikholeslami R, Kaveh A. NETWORK COMPLEXITY AND STABILITY IN ENVIRONMENTAL SYSTEMS: A GRAPH THEORETIC PERSPECTIVE. IJOCE 2025; 15 (1) :131-140
URL: http://ijoce.iust.ac.ir/article-1-627-en.html
URL: http://ijoce.iust.ac.ir/article-1-627-en.html
1- Department of Civil Engineering, Sharif University of Technology, Tehran, Iran
2- School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran
2- School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran
Abstract: (698 Views)
The stability of large complex systems is a fundamental question in various scientific disciplines, from natural ecosystems to engineered environmental networks. This paper examines the interplay between network complexity and stability through the lens of graph theory and spectral analysis, based on Robert May’s seminal work on stability in randomly connected networks. Environmental systems are modeled as graphs in which components, such as reservoirs in a water distribution system or physical processes in hydrological cycle, interact through defined connections of varying strengths. Stability in these networks depends on the level of connectivity, the number of interacting components, and the strength of interactions between them. Previous studies have shown that as a system becomes more interconnected, it reaches a threshold beyond which it transitions sharply from stability to instability. Using concepts from spectral graph theory, we show how structural properties of an environmental network—such as degree distribution, modularity, and spectral characteristics—shape stability. Two numerical examples are presented to illustrate how increasing connectivity affects stability in water resource networks modeled as random graphs. The results suggest that systems with many weak interactions are generally more stable, whereas systems with fewer but stronger interactions are more prone to instability unless their structure is carefully managed. These insights provide valuable insights for designing resilient environmental networks and optimizing the management of interconnected natural and engineered systems.
Send email to the article author
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
