How to use the Damage Costs of Exposed Infrastructures User Story (#5)

“I need to quantify damage costs of infrastructures exposed to flooding and assess how it evolves under different climate change scenarios”

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1. What is a CoCliCo User Story?

User Stories are ready-made map datasets in the CoCliCo platform. They combine different types of important information to show scenarios for coastal risk resulting from sea-level rise,  floods and / or erosion. These layers make complex analyses easier and help users to quickly get a sense of coastal risks. 

User research showed that policymakers need clear, actionable data for flood directives, while urban planners want tools to assess local risks, and where infrastructure managers focus on long-term resilience planning. These insights helped shape User Stories to provide accessible, scenario-driven visualizations for diverse decision-making needs. There are six User Stories:

1. Sea Level Rise Projections
2. Inundation Distribution During a Flood Event
3. Building Exposure
4. Projections of Exposed People
5. Damage Costs of Exposed Infrastructures
6. Adaptation Based on Cost-Benefit Analysis

In this e-guideline, we walk you through the Damage Costs of Exposed Infrastructures User Story.

2. Introduction to the Damage Costs of Exposed Infrastructures User Story

The User Story on Damage Costs for Exposed Infrastructures in the CoCliCo platform aims at presenting the direct economical impacts of coastal flooding under different climate scenarios. While many coastal infrastructures are protected today, rising sea levels will increase flood extent and depth, leading to higher damage costs without further adaptation. 

This tool helps policymakers and planners assess these costs at national, regional, and local levels in order to inform adaptation strategies. It combines the latest sea level projections, European flood hazard data, and infrastructure inventories to provide city-scale estimates of future flood damage. 

3. Step-by-Step Platform Usage

1. Access the CoCliCo Platform:
   1. On the left-hand menu bar, navigate to the “Exposure & Vulnerability” category, then “Damage Costs of Exposed Infrastructures” under “User Stories”. 
2. Select a Scenario:
   1. Choose a climate scenario (e.g., SSP1-2.6, SSP2-4.5, etc.), the percentile of the probabilistic projection (e.g. 17th, median or 83rd) and time horizon.
3. Analyze Visualizations:
   1. Use interactive tools to zoom into regions and access localized insights.
   2. Use the “Add to Dashboard” feature to retain charts and graphs for further comparison and analysis
   3. Toggle on other layers, such as “natural hazards” and “exposure & vulnerability,” for more context on the impacts and risks faced by that area. For simpler comparisons, make sure you add your charts and graphs to your dashboard to compare across time and geographies and observe various layers and user stories of that area. 
4. Further Analysis:
   1. Export maps or raw datasets for further analysis in the Workbench or other GIS tools​​.
   2. Assess local projections with vertical land motion (VLM) using our coastal hazard assessment.

4. Target Users & Intended Use

Target Users:

• Policymakers implementing national and EU flood directives.
• European, national and regional policy makers assessing needs for adaptation and to handle losses and damages.
• Urban planners and city authorities in coastal areas assessing future risks.
• Infrastructure management assessing risks in the immediate surrounding of their facilities
• Researchers and consultants assessing coastal risks.

Intended Use:
The layer provides simplified, robust visualizations to identify coastal risks due to flooding in the context of sea-level rise. It supports broad-scale assessments, preliminary decision-making, and compliance with policies like the European Flood Directive.

Key Benefits:

• Enables informed decisions based assessments of risks, and not only hazards and exposure (national to municipal).
• Improves stakeholder engagement with clear, accessible data.
• Aids investment prioritization and strategic land-use decisions.

5. Example of Use 

“National policy makers used the damage costs estimates to get a first order estimate of costs in regions and municipalities and prioritize on adaptation actions and investments in order to maximize the efficiency of public investments in adaptation. While this information can not be used as a single source of information to guide adaptation investments, it provides an element that can be considered together with additional evidence and selection criteria of decision makers”

“The damage costs estimates at municipal level have been used to identify the potential damage costs in a particular flood plain, allowing to anticipate to what extent existing compensation mechanisms (e.g. insurance) are adequately designed to address loss and damages a now and in the future”

6. Data, Methods, and Model Overview

Data Sources:

Damage costs on infrastructures are calculated by crossing hazard, buildings and vulnerability curves.

• Hazards: Flood maps (water depth) calculated either with or without defences from the CoCliCo project (data producer: IH-Cantabria; available on the CoCliCo STAC Catalog). Flood maps are provided for hindcast, 2030, 2050, 2100 and 2150 for permanent flooding, 1-yr, 100-yr and 1000-yr return period with various SLR scenarios. 
• Exposure: Coastal European Exposure Database (data producer: Institute for Environmental Studies, Vrije Universiteit Amsterdam, available on the CoCliCo STAC Catalog). 11 classes of infrastructures are considered: Building, Power, Wastewater, Telecom, Oil, Gaz, Education, Healthcare, Rail, Road and Water. Infrastructures can be represented as points, lines, polygons or multipolygons. 
• Vulnerability curves: Physical Vulnerability Database for Critical Infrastructure Hazard Risk Assessments. (data producer: Institute for Environmental Studies, Vrije Universiteit Amsterdam, Dataset: Physical Vulnerability Database for Critical Infrastructure Hazard Risk Assessments).The data comes from a study that compiles most of the existing vulnerability curves found in the literature, along with the associated cost. It consists of 102 different vulnerability curves, which depend on the type of infrastructure, and 179 different cost values. The vulnerability curves are used to characterize the percentage of damage to infrastructure based on water height. 

Methods:

The damage costs are calculated by intersecting hazard (raster) and exposure (polygons) data layers, and vulnerability curves. First, we overlay the coastal flood hazard map with infrastructure data to obtain an average water height for each infrastructure. Then, based on the category of the infrastructure, we apply the corresponding vulnerability curves (e.g. healthcare, education, railway, etc).

For the CoCliCo project, we used 18 different vulnerability curves. Once the damage is determined, the associated cost calculation is carried out: the damage cost is the product of the building’s surface area, the percentage of damage, and the maximum damage, based on construction costs.

Model Outputs:

• Potential costs can be visualized in different ways: through a map that displays a color gradient based on the total damage cost for each LAU (Local Administrative Unit) across all infrastructures. To do this, the user selects the type of defense, the desired SSP scenario, the time horizon and the return period. The user can also view more details by clicking on a specific LAU. In this case, they can select the defense level, return period, and the category of infrastructure they are interested in. A graph will appear showing the evolution of costs over time, based on the different SSP scenarios.
• Importantly, the costs presented here are the costs associated to a particular return period. It neither corresponds to the costs associated to a particular event that would affect a specific region, nor to an expected annual damage value that would integrate costs of various return periods.

Limitations

One of the main limitations of this method lies in the assumption that infrastructures remain unchanged over time, without considering any construction or destruction of infrastructure. Additionally, the lack of detailed information on certain infrastructures can affect the accuracy of selecting the vulnerability curve, which may lead to variations in the estimated cost. Similarly, the price used is an average price that does not account for specific factors such as the location of the damage or the current local construction costs.

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