| 14 Jan 2026
A Process-Based Four-Stage Framework for Seismic Resilience Assessment of Urban Water Distribution Networks through Multi-Attribute Metrics
Abstract. Urban water distribution networks are critical lifelines whose seismic resilience is essential for maintaining daily functions and post-disaster service continuity. However, most existing studies focus on seismic-induced functional failures and short-term recovery, while neglecting pre-disaster preparedness and long-term adaptation – two stages that fundamentally shape the overall resilience trajectory. Conventional assessments typically rely on single-dimensional hydraulic or network indicators, which tend to be one-sided and error-prone. These limitations hinder a comprehensive understanding of WDN behavior across different seismic disturbance stages, yielding only coarse performance judgments that offer limited guidance for diagnosing vulnerabilities or planning effective resilience enhancement and retrofit strategies. To address these limitations, this study proposes a process-based four-stage seismic resilience framework that explicitly incorporates preparedness, robustness, recoverability, and long-term adaptation, capturing the full evolution of WDN performance during seismic events. A multi-attribute indicator system integrating topological homogeneity, energy redundancy, pipeline fragility, hydraulic service performance, and recovery efficiency is developed to enable refined stage-specific assessment. An adaptation index (ACI) is further introduced to quantify the integrated improvement achieved by different retrofit strategies. Applications to the Jilin and Mianzhu WDNs demonstrate clear stage-dependent resilience disparities and provide actionable guidance for optimizing seismic resilience enhancement. Application to the Jilin and Mianzhu WDNs demonstrates the framework's applicability and reveals clear stage-dependent resilience disparities, which provide scientifically grounded guidance for optimizing seismic resilience enhancement in urban WDNs.
This manuscript proposes a four-stage framework (preparedness, robustness, recoverability, adaptation) for assessing seismic resilience of urban water distribution networks (WDNs). The authors integrate topological, energy-based, and hydraulic indicators into a multi-attribute system and apply it to two case study networks in China. While addressing an important research gap by incorporating pre-disaster preparedness and long-term adaptation stages, the manuscript suffers from significant methodological and presentation issues that require substantial revision.
Major Comments
1. Unclear Novelty
The abstract and introduction fail to clearly articulate what specific problem this work addresses and how the proposed framework advances beyond existing three-stage approaches. The abstract is vague about implications, and the first clear statement of the research problem appears only in lines 108-115. The manuscript reads as a pipeline of existing procedures rather than a coherent methodological advancement. Novel elements, if present, are obscured by technical details.
2. Methodology
The seismic hazard analysis (Section 3.1.1) is inadequately described. It remains unclear whether a proper PSHA was conducted or merely a simplified scenario calculation. Using only the Toro et al. (1997) ground motion model is inconsistent with state-of-the-art practice. Figure 8 presents scenario calculations, but Figure 2 mentions PGA sampling without specifying the approach. The fragility model terminology is also problematic, as the described approach differs from standard seismic fragility conventions.
3. Indicator weighting
The framework employs multiple indicators at each stage but assumes equal weights when computing aggregate resilience (Section 5.1). This assumption is unjustified, as indicators likely have unequal importance depending on network characteristics and stakeholder priorities. A sensitivity analysis exploring alternative weighting schemes is strongly recommended.
4. Adaptation quantification
Equations 16-17 introduce enhancement coefficients without explaining their derivation or calibration. The Adaptation Confidence Index (ACI) is mentioned but not adequately highlighted in results. Meanwhile, Section 5.1 introduces a Resilience Index not discussed in the methodology, creating confusion about the evaluation approach.
5. Statistics
The 200 Monte Carlo iterations lack convergence analysis justification. The case studies present limitations: both networks use only cast iron and plastic pipelines, and the Jilin WDN is small (27 nodes). Despite referencing the 2008 Wenchuan earthquake, there is no reference to the observed damage in the Mianzhu network and no comparison with the results.
Editorial quality comments
The introduction is excessively long with extended historical examples (lines 31-47) that could be condensed. Section 2 should be shortened and integrated into the introduction, as it duplicates contextual material. The manuscript contains redundant passages (e.g., lines 175-180 repeating recoverability definition; lines 22-25 repeating information). Figure 1 contains too many visual elements overwhelming the reader. Terminology is inconsistent ("renovation" versus "retrofit"; "seismic fortification intensity" undefined).
Minor Comments
Literature review lacks critical analysis of cited works. Equation 1 could be omitted. Figure 13 caption incorrectly references only Jilin WDN when showing both networks. The Gini coefficient formulation (Eq. 8) should be verified against standard forms. Provide a reference for the Gini coefficient or specify that it is a novelty.
Recommendation
The authors must: (1) clearly articulate the novel contribution beyond combining existing procedures; (2) consider a sensitivity analysis for indicator weighting; (3) clarify the seismic hazard analysis methodology; (4) check Monte Carlo convergence; (5) explain adaptation coefficient derivation; (6) substantially restructure Sections 1-2 for conciseness; and (7) consider validation against real earthquake data.