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Data on predictive resilience of interdependent water and transportation infrastructures: A sociotechnical approach

ABSTRACT: Interdependent infrastructure systems are vulnerable to the cascading effect of failures resulting from random failures and natural disasters. The data provided in this work is the processed data used for the proposed resilience assessment framework for interdependent water and transportation networks dealing with both types of failure [1]. The case study is the interconnected networks of water and transportation in Tampa, Florida. The data for the random failure is obtained from the developed algorithmic framework and the land use and social vulnerability data provided by the U.S. Census datasets. We then used a subset of this produced data to construct predictive models for the network resilience to random failures. As for the natural disaster scenario, we focused on hurricane Irma in 2017 as it directly affected the focused region in Florida. We used the specific guidelines and the raw flooding data for this hurricane, provided by FEMA, to estimate the standing water for each geographical area (polygons) and the associated network components. We labeled the areas as failed and undamaged based on the estimated water levels. Finally, we used this data for developing a geospatial Geographical Weighted Regression (GWR) model to predict the resilience in each polygon. We present the final dataset for water and transportation networks to facilitate reusability for any future resilience study in the selected urban area.

SUBMITTER: Aslani B

PROVIDER: S-EPMC8570939 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Modelling and evaluating the resilience of environmental systems has recently raised significant interest among both practitioners and researchers. However, it has not yet been used to measure the absorption and recovery capacities of a river subject to varying levels of pollution due to natural and anthropic sources of contamination within the basin. Fast worldwide population growth and climate change are contributing to an increased degradation status in surface water bodies and to a decreased efficiency of their natural self-purification processes. Decision-makers are, therefore, more and more encouraged to implement alternative management strategies focussed on improving the system resilience to current and future perturbations. To this end, a novel Water Resilience Index (WRI), based on different quality parameters, was developed, and it is here proposed to estimate the ability of the river Bacchiglione, located in Northeast Italy, absorb continuous and unpredictable changes due to potential effects of point sources of pollution, that is, urban and industrial wastewater, and still maintain its vital functions. This new index is integrated in a mathematical model, which represents the river as an influence diagram where the nodes are the gauged stations and the arcs are the fluvial reaches among the stations, to identify the river reaches in need of resilience improvement. In addition, in order to simplify the analytical procedure and lower the costs and times of the monitoring activities, a principal component analysis is also used, as it is able to reduce the number of the water quality parameters to be collected from the sampling stations, distributed along the main river, and thus to calculate a minimum WRI. The good agreement between the results obtained by both the original and minimum WRI shows the effectiveness of the proposed methodology. This approach could be applied to all basins with the same issues, and not just in the Italian case study here analysed, as it might be a valid tool to plan interventions and mitigation actions, protecting the resource from pollution risks and achieving environmental quality and Sustainable Development Goals both in the water bodies and their surrounding territories. In addition, this strategy could be integrated in the existing models supporting local decision-makers and administrators, aiming at increasing the resilience of urban and rural areas to pollution phenomena and facilitating the development of effective policies to reduce the impacts of global change on water quality.

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Data on predictive resilience of interdependent water and transportation infrastructures: A sociotechnical approach

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