Modelling infrastructure interdependencies, resiliency and sustainability

Nguyen, Tri Dung; Cai, Ximing; Ouyang, Yanfeng; Housh, Mashor

doi:10.1504/ijcis.2016.075868

Cited by 18 publications

(14 citation statements)

References 16 publications

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“…Except for internal and external impact analyses, assessment of the whole system performance, such as resilience (Hosseini et al, 2016) and sustainability (Nguyen et al, 2014), is another nascent field of current research.…”

Section: Evaluation Of the Coupled Systemmentioning

confidence: 99%

“…Establishing a biofuel production system consisting of three subsystems (e.g. water supply, biomass production and biofuel), Nguyen et al (2014) demonstrated that raising the dependencies of water supply on biomass production may decrease the system sustainability, implying that the quality of the coupled system may degrade as time went on. However, due to the vague definition of system sustainability, quantifications of this performance measure are still limited.…”

Section: Evaluation Of the Coupled Systemmentioning

confidence: 99%

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Water-energy-food nexus: Concepts, questions and methodologies

Zhang

Chen

et al. 2018

Journal of Cleaner Production

385

189

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The water-energy-food nexus has gained increasing attention in the research communities as the security of water, energy and food becomes a very high concern due to future uncertainties. Studies pertaining to calculations of flows and dependencies between different resources, assessments of technology and policy applications, and quantifications of system performance have been conducted to understand their interlinkages and develop management options. This paper provides a state-of-the-art review on the concepts, research questions and methodologies in the field of waterenergy-food. First, two types of nexus definition are compared and discussed to understand the nature of nexus research issues. Then, nexus research questions are summarized into three themes: internal relationship analysis, external impact analysis, and nexus system evaluation. Eight nexus modelling approaches are discussed in terms of their advantages, disadvantages and applications, and guidance is provided on the selection of an appropriate modelling approach. Finally, future research challenges are identified, including system boundary, data uncertainty and modelling, underlying mechanism of nexus issues and system performance evaluation. This review helps bring research efforts together to address the challenging questions in the nexus research and develop sustainable and resilient water, energy and food systems. 2 Highlights: 1. Two definitions of nexus exist but they can be unified under integrated system assessment 2. Nexus research is classified into three questions: internal relationship, external analysis, system evaluation 3. Nexus modelling should consider research questions, system scales and data availability 4. Future research challenges are identified to develop sustainable and resilient nexus systems

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Section: Evaluation Of the Coupled Systemmentioning

confidence: 99%

Section: Evaluation Of the Coupled Systemmentioning

confidence: 99%

Water-energy-food nexus: Concepts, questions and methodologies

Zhang

Chen

et al. 2018

Journal of Cleaner Production

385

189

View full text Add to dashboard Cite

show abstract

“…The concept of resilience has been applied in many areas, including ecosystems (Botter et al, ; Holling, ; Srinivasan & Kumar, ), water resources systems (Hashimoto, ; Simonovic & Arunkumar, ; Simonovic & Peck, ), and infrastructure development (Bruneau & Reinhorn, ; Nguyen et al, ). Peterson et al () defined resilience as the difference in system state between a stable state and the threshold of a regime shift.…”

Section: Introductionmentioning

confidence: 99%

“…Botter et al () defined resilience as the sensitivity of regime instability to climate change and estimated the resilience of streamflow regimes. In the literature, the various definitions of resilience can be grouped into two categories (Holling, ; Walker et al, ): (1) engineering (ENG‐) resilience usually refers to the recovery rate from an nonstationary state to the initial, stationary state (Holling, ; Nguyen et al, ; Walker et al, ); (2) ecological (ECO‐) resilience refers to the maximum disturbance that a system is capable of withstanding without incurring a regime shift (Carpenter, ; Knowlton, ; Peterson et al, ).…”

Section: Introductionmentioning

confidence: 99%

Understanding the Resilience of Soil Moisture Regimes

Feng

Liu

Cai

et al. 2019

Water Resources Research

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Resilience of soil moisture regimes (SMRs) describes the stability of a particular SMR and its ability to withstand disturbances. This study analyzes the resilience of SMRs with quantifiable ecological (ECO‐) and engineering (ENG‐) metrics for a stochastic dynamic soil moisture system. The SMR is defined by the stationary state, described by a stationary probability distribution function (pdf), of the soil moisture dynamical system, and further classified into arid, semiarid, semiwet, and wet classes. Applying the stationary pdf of soil moisture dynamics derived by Rodriguez‐Iturbe et al. (1999, https://doi.org/10.1098/rspa.1999.0477) and Laio, Porporato, Ridolfi, et al. (2001, https://doi.org/10.1016/S0309-1708(01)00005-7), the ENG‐ and ECO‐ resilience metrics of the various SMRs are quantified. We show that the recovery rate of soil moisture is a convex function of the expected soil moisture at the stationary state―the recovery rate reaches a minimum value at some intermediate soil moisture status. We also show that the maximum acceptable changes in the infiltration condition indicate the capacity of a system to avoid possible regime shifts. SMR shifts are characterized by phenomena of stagnation and hysteresis, which suggest two distinct thresholds for SMR shifts and their reversions. In particular, the semiwet SMR that is favorable to agriculture requires stricter infiltration conditions than other SMRs. This resilience analysis provides better understanding of how natural hydrological conditions control soil moisture, which helps provide guidance on maintaining SMRs suitable for agricultural activities and desertification prevention.

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“…In recent literature, infrastructures are classified as a special instance of systems-of-systems of which they possess a number of distinctive features such as operational and managerial independence, geographical distribution, emergent behaviour and evolutionary development (Sousa-Poza et al, 2008;Jamshidi, 2008;Eusgeld et al, 2011;Kotov, 1997;Nguyen et al, 2016;Polinpapilinho and Keating, 2015).…”

Section: Introductionmentioning

confidence: 99%

A deterministic approach for systems-of-systems resilience quantification

Ed-daoui

Itmi

Hami

et al. 2018

IJCIS

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With recent advances in systems-of-systems, reliability analysis becomes a very challenging research topic. One of the most pressing issues is to figure out a plan to handle resilience. On this basis, we propose, in this paper, a structural deterministic approach to quantitatively measure systems resilience. This approach is based on a three-step method. First, evaluate the functional dependencies between groups by considering a system-of-systems as a large-scale interconnected network of systems distributed into interdependent groups. This leads us to better understand the overall connections and process continuity. Next, analyse how much the global architecture of the system-of-systems depends on every group. Last, estimate its structural resilience by measuring the impact of each system's failure on the other systems forming the global system and building the process. Two case studies are provided to experiment our approach. The results are cross-compared and evaluated.

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Modelling infrastructure interdependencies, resiliency and sustainability

Cited by 18 publications

References 16 publications

Water-energy-food nexus: Concepts, questions and methodologies

Water-energy-food nexus: Concepts, questions and methodologies

Understanding the Resilience of Soil Moisture Regimes

A deterministic approach for systems-of-systems resilience quantification

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