Seismic Performance Assessment of Water Distribution Systems Based on Multi-Indexed Nodal Importance

Seismic performance assessment of water distribution systems (WDSs) based on hydraulic simulation is essential for resilience evaluation of WDSs under earthquake disasters. The assessment is mainly to determine how the water supply will be affected due to pipe breaks caused by the earthquake, with the water supply loss estimated based on the loss of supply to nodes. Existing research works usually use the average or overall performance metric of all user nodes as the system performance indicator without considering user nodes’ individual performance and criticality. This paper proposes a framework to evaluate the importance of user nodes considering post-earthquake rescue service and the seismic performance of individual user nodes in the WDS, which supports the pipeline renovation plan to improve the performance of critical user nodes. The importance of user nodes is evaluated by a multi-index model, including the indices for daily service, post-earthquake rescue service, and network topology influence of user nodes. These indices evaluate the importance of user nodes in terms of their roles for daily water service, emergent rescue service, and water transmission to other nodes, respectively. Fragility model of pipelines evaluates the earthquake-induced damages of the WDS, and the seismic performance assessment of the WDS system is performed by the hydraulic model of the WDS with pipeline damages. The proposed framework is implemented in an actual WDS; the results show that the importance classification to user nodes by multi-index approach can identify the critical user nodes for post-earthquake rescue service, which traditional methods may ignore. The importance classification and seismic performance of individual user nodes make it feasible to check the seismic performance of critical user nodes and formulate a targeted pipeline renovation plan to focus limited resources on critical user nodes.

[1]  Do Guen Yoo,et al.  Optimal design of water supply networks for enhancing seismic reliability , 2016, Reliab. Eng. Syst. Saf..

[2]  Wei Wang,et al.  Seismic Resilience Enhancement of Urban Water Distribution System Using Restoration Priority of Pipeline Damages , 2020 .

[3]  Leonardo Dueñas-Osorio,et al.  Exploring Topological Effects on Water Distribution System Performance Using Graph Theory and Statistical Models , 2017 .

[4]  Enrico Creaco,et al.  Topological Placement of Quality Sensors in Water-Distribution Networks without the Recourse to Hydraulic Modeling , 2020 .

[5]  Hyung-Jo Jung,et al.  A comprehensive framework for seismic risk assessment of urban water transmission networks , 2018, International Journal of Disaster Risk Reduction.

[6]  H. Sebnem Düzgün,et al.  A GIS-based software for lifeline reliability analysis under seismic hazard , 2012, Comput. Geosci..

[7]  Junho Song,et al.  Efficient risk assessment of lifeline networks under spatially correlated ground motions using selective recursive decomposition algorithm , 2012 .

[8]  U. Brandes A faster algorithm for betweenness centrality , 2001 .

[9]  David H. Marks,et al.  Water Distribution Reliability: Simulation Methods , 1988 .

[10]  P. Nath,et al.  An Empirical Assessment of Comparative Approaches to Service Quality Measurement , 2005 .

[11]  Leonardo Dueñas-Osorio,et al.  Cascading failures in complex infrastructure systems , 2009 .

[12]  Guangtao Fu,et al.  Topological attributes of network resilience: A study in water distribution systems. , 2018, Water research.

[13]  Hua Yu,et al.  Evaluate the node importance for water network based on complex network theory , 2014 .

[14]  Wei Liu,et al.  Genetic algorithm for seismic topology optimization of lifeline network systems , 2008 .

[15]  David L. Olson,et al.  Comparison of weights in TOPSIS models , 2004, Math. Comput. Model..

[16]  Carlo Giudicianni,et al.  The faster the better: On the shortest paths role for near real-time decision making of water utilities , 2021, Reliab. Eng. Syst. Saf..

[17]  Alessandro Pagano,et al.  Water Distribution Networks Resilience Analysis: a Comparison between Graph Theory-Based Approaches and Global Resilience Analysis , 2019, Water Resources Management.

[18]  Donghwi Jung,et al.  Shortest-Path-Based Two-Phase Design Model for Hydraulically Efficient Water Distribution Network: Preparing for Extreme Changes in Water Availability , 2021, IEEE Access.

[19]  R. Greco,et al.  A Community-Structure-Based Method for Estimating the Fractal Dimension, and its Application to Water Networks for the Assessment of Vulnerability to Disasters , 2021, Water Resources Management.

[20]  Paul Jeffrey,et al.  Water distribution system vulnerability analysis using weighted and directed network models , 2012 .

[21]  T. D. O'Rourke,et al.  Seismic Hazards and Water Supply Performance , 2010 .

[22]  Bruce R. Ellingwood,et al.  Serviceability Assessment of a Municipal Water System Under Spatially Correlated Seismic Intensities , 2009, Comput. Aided Civ. Infrastructure Eng..

[23]  Daniele B. Laucelli,et al.  Vulnerability Assessment of Water Distribution Networks under Seismic Actions , 2015 .

[24]  Thomas D. O'Rourke,et al.  Northridge Earthquake Effects on Pipelines and Residential Buildings , 2005 .

[25]  Jeroen Langeveld,et al.  Identifying critical elements in drinking water distribution networks using graph theory , 2020, Structure and Infrastructure Engineering.

[26]  Gyutai Kim,et al.  Identifying investment opportunities for advanced manufacturing systems with comparative-integrated performance measurement , 1997 .

[27]  Jeroen Langeveld,et al.  Identifying Critical Elements in Sewer Networks Using Graph-Theory , 2018 .

[28]  Zoran Kapelan,et al.  Improving the Resilience of Postdisaster Water Distribution Systems Using Dynamic Optimization Framework , 2020 .

[29]  Paul Jeffrey,et al.  Applying Network Theory to Quantify the Redundancy and Structural Robustness of Water Distribution Systems , 2012 .

[31]  Bałut,et al.  Ranking Approach to Scheduling Repairs of a Water Distribution System for the Post-Disaster Response and Restoration Service , 2019, Water.

[32]  M. Shinozuka,et al.  Serviceability of Water Transmission Systems Under Seismic Risk , 1981 .

[33]  Jack W. Baker,et al.  Statistical learning techniques for the estimation of lifeline network performance and retrofit selection , 2020, Reliab. Eng. Syst. Saf..

[34]  Devika Subramanian,et al.  Performance assessment of topologically diverse power systems subjected to hurricane events , 2010, Reliab. Eng. Syst. Saf..

[35]  Siu-Kui Au,et al.  Spatial distribution of water supply reliability and critical links of water supply to crucial water consumers under an earthquake , 2009, Reliab. Eng. Syst. Saf..

[36]  Gian Paolo Cimellaro,et al.  Downtime estimation and analysis of lifelines after an earthquake , 2018 .

[37]  Howard H. M. Hwang,et al.  Seismic Performance Assessment of Water Delivery Systems , 1998 .

[38]  Mingju Zhang,et al.  Improved AHP Method and Its Application in Risk Identification , 2013 .

[39]  Jun He,et al.  A recursive decomposition algorithm for network seismic reliability evaluation , 2002 .

[40]  S. Galelli,et al.  Battle of Postdisaster Response and Restoration , 2020, Journal of Water Resources Planning and Management.

[41]  Ryoji Isoyama,et al.  Seismic damage estimation procedure for water supply pipelines , 2000 .

[42]  S. Hallett,et al.  Improving pipe failure predictions: Factors effecting pipe failure in drinking water networks. , 2019, Water research.

[43]  Jian Li,et al.  AC power flow importance measures considering multi-element failures , 2017, Reliab. Eng. Syst. Saf..

[44]  Do Guen Yoo,et al.  Comparative Study of Hydraulic Simulation Techniques for Water Supply Networks under Earthquake Hazard , 2019, Water.

[45]  Craig A. Davis Water System Service Categories, Post-Earthquake Interaction, and Restoration Strategies , 2014 .