Application of the Systems Approach to the Management of Complex Water Systems

Simonović́, Slobodan P.

doi:10.3390/w12102923

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…Therefore, exogenous drivers might not be able to explain and anticipate a system's main pattern of behaviors, as the cause and the effect are often distant in time and space in dynamically complex systems (Davis, 2003). In spite of the wide application of system dynamics in different areas (Wiener, 1948;Zera, 2002;Hofkirchner and Schafranek, 2011;Seth and Bayne, 2022) and water management (Bai et al, 2021;Simonovic, 2020) in which natural system only plays a minor role, to our knowledge, the concept has rarely been used in hydrology under natural conditions. System dynamics approach may thus open a new avenue to understand the mechanisms of long-term and slow dynamics of hydrological system.…”

Section: Introductionmentioning

confidence: 99%

System dynamics perspective: lack of long-term endogenous feedback accounts for failure of bucket models to replicate slow hydrological behaviors

Zhou,

Sheng,

Manevski

et al. 2024

Preprint

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Abstract. Hydrological models with the conceptual tipping bucket and the process-based evapotranspiration models are the most common tools in hydrology. However, these models consistently fail to replicate long-term and slow dynamics of a hydrological system, indicating the need for model augmentation and shift in approach. This study employed an entirely different approach – system dynamics – towards more realistic replication of long-term and slow hydrological behaviors by removing limits of exogenous climate on evapotranspiration and involving endogenous soil water-vegetation feedback loop. Using the headwaters of Baiyang Lake in China as a case study, the mechanisms of slow hydrological dynamics were gradually unraveled from 1982 to 2015 through wavelet analysis, Granger's causality test, and system dynamics. The wavelet analysis and Granger's causality test identified a negative-correlated, bidirectional causal relationship between evapotranspiration and the water budget across distinct climatic periodicities, suggesting a robust endogenous soil water-vegetation feedback structure operating on a long-term scale. The system dynamics approach successfully captured the slow behavior of the hydrological system under both natural and human-intervention scenarios, demonstrating a self-sustained oscillation arising within the system's boundary. Conventional hydrological models, which rely on process-based evapotranspiration models, operate on an instantaneous scale and are thus susceptible to short-time climatic and vegetation physiological variations. This results in inaccurate depletion rate of soil water stock and in turn, can lead to incorrect calculations of other hydrological variables. However, long-term and slow hydrological dynamics typically involves in endogenous state-dependent modulation and feedback related to changes in vegetation structure, thus are insensitive to exogenous disturbances and can be well replicated using system dynamics approach. This insight that the failure of hydrological models to replicate slow dynamics can be attributed to a time-scale mismatch may offer potential solutions for improving conventional hydrological models.

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Section: Introductionmentioning

confidence: 99%

System dynamics perspective: lack of long-term endogenous feedback accounts for failure of bucket models to replicate slow hydrological behaviors

Zhou,

Sheng,

Manevski

et al. 2024

Preprint

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“…Nowadays, novel digital technologies, such as digital twins (DT), as a new paradigm in simulation, provide tools capable of solving different issues in the water sector (Seshan et al 2020 ; Alzamora et al 2021 ; Bartos and Kerkez 2021 ; Savić, 2022 ). DT can facilitate a comprehensive analysis of the DRSs’ behavior in adverse operating conditions using the system dynamics (SD) modelling approach (Regan 2010 ; Simonovic and Arunkumar 2016 ; King et al 2017 ; Stojkovic and Simonovic 2019 ; King 2020 ; Lee and Kang 2020 ; Simonovic 2020 ; Ignjatović et al 2021 ; Momeni et al . 2021 ; Samadi-Foroushani et al 2022 ) coupled with expert knowledge.…”

Section: Introductionmentioning

confidence: 99%

Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic

Milašinović

Ivetić

Stojković³

et al. 2023

Water Resour Manage

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Climate change, energy transition, population growth and other natural and anthropogenic impacts, combined with outdated (unfashionable) infrastructure, can force Dam and Reservoir Systems (DRS) operation outside of the design envelope (adverse operating conditions). Since there is no easy way to redesign or upgrade the existing DRSs to mitigate against all the potential failure situations, Digital Twins (DT) of DRSs are required to assess system’s performance under various what-if scenarios. The current state of practice in failure modelling is that failures (system’s not performing at the expected level or not at all) are randomly created and implemented in simulation models. That approach helps in identifying the riskiest parts (subsystems) of the DRS (risk-based approach), but does not consider hazards leading to failures, their occurrence probabilities or subsystem failure exposure. To overcome these drawbacks, this paper presents a more realistic failure scenario generator based on a causal approach. Here, the novel failure simulation approach utilizes fuzzy logic reasoning to create DRS failures based on hazard severity and subsystems’ reliability. Combined with the system dynamics (SD) model this general failure simulation tool is designed to be used with any DRS. The potential of the proposed method is demonstrated using the Pirot DRS case study in Serbia over a 10-year simulation period. Results show that even occasional hazards (as for more than 97% of the simulation there were no hazards), combined with outdated infrastructure can reduce DRS performance by 50%, which can help in identifying possible “hidden” failure risks and support system maintenance prioritization. Graphical Abstract

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