scholarly journals Direct flood risk assessment of the European road network: an object-based approach

2020 ◽  
Author(s):  
Kees C. H. van Ginkel ◽  
Francesco Dottori ◽  
Lorenzo Alfieri ◽  
Luc Feyen ◽  
Elco E. Koks
Keyword(s):  
High Resolution ◽  
Flood Risk ◽  
Road Network ◽  
Flood Damage ◽  
Transport Infrastructure ◽  
Damage Functions ◽  
Road Infrastructure ◽  
Continental Scale ◽  
Object Based ◽  
River Floods

Abstract. River floods pose a significant threat to road transport infrastructure in Europe. This study presents a high-resolution object-based continental-scale assessment of direct flood risk of the European road network for the present climate, using high-resolution exposure data from OpenStreetMap. A new set of road-specific damage functions is developed and validated for an observed flood event. We estimate the median annual expected direct damage from river floods to road infrastructure in Europe at 250 million euro per year. A comparison with grid-based approaches suggests that these methods likely overestimate direct flood damage to road infrastructure and might allocate infrastructural damage to the wrong land use classes. A first validation shows that our object-based method computes realistic damage estimates, paving the way for targeted risk adaptation strategies.

scholarly journals Flood risk assessment of the European road network

2021 ◽  
Vol 21 (3) ◽  
pp. 1011-1027
Author(s):  
Kees C. H. van Ginkel ◽  
Francesco Dottori ◽  
Lorenzo Alfieri ◽  
Luc Feyen ◽  
Elco E. Koks
Keyword(s):  
High Resolution ◽  
Flood Risk ◽  
Road Network ◽  
Large River ◽  
Transport Infrastructure ◽  
Reference Case ◽  
Damage Functions ◽  
Continental Scale ◽  
Object Based ◽  
River Floods

Abstract. River floods pose a significant threat to road transport infrastructure in Europe. This study presents a high-resolution object-based continental-scale assessment of direct flood risk of the European road network for the present climate, using high-resolution exposure data from OpenStreetMap. A new set of road-specific damage functions is developed. The expected annual direct damage from large river floods to road infrastructure in Europe is EUR 230 million per year. Compared to grid-based approaches, the object-based approach is more precise and provides more action perspective for road owners because it calculates damage directly for individual road segments while accounting for segment-specific attributes. This enables the identification of European hotspots, such as roads in the Alps and along the Sava River. A first comparison to a reference case shows that the new object-based method computes realistic damage estimates, paving the way for targeted risk reduction strategies.

Object-based flood risk modelling of the European road network: physical damage and mobility disruptions

2020 ◽  
Author(s):  
Ana Laura Costa ◽  
Elco Koks ◽  
Kees van Ginkel ◽  
Frederique de Groen ◽  
Lorenzo Alfieri ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Road Network ◽  
Road Transport ◽  
Transport Infrastructure ◽  
Network Data ◽  
Physical Damage ◽  
Continental Scale ◽  
Object Based ◽  
Grid Based

<p>River flooding is among the most profound climate hazards in Europe and poses a threat to its road transport infrastructure. Traditional continental-scale flood risk studies do not accurately capture these disruptions because they are typically grid-based, whereas roads are relatively narrow line elements which are therefore omitted. Moreover, these grid-approaches disregard the network properties of roads, whereas the costs of reduced mobility could largely exceed the costs of the physical damage to the infrastructure.</p><p>We address these issues by proposing and applying an improved physical damage assessment coupled with the assessment of mobility disruption for a comprehensive risk assessment at a continental level.</p><p>In this study, we introduce an object-based, continental scale flood risk assessment of the European road network. We improve the estimates of direct, physical damage, by drawing road network data from OpenStreetMap, while making optimal use of the available metadata. We also introduce a set of road-specific flood damage functions, which are validated for an observed flood event in Germany. The results of this approach are compared to the traditional, grid-based approach to modelling road transport damage.</p><p>Next, we showcase how the object-based approach can be used to study potential mobility disruptions. In this study we present how the network data from OpenStreetMap and available metadata can be used to assess the flood impacts in terms of decreased connectivity, that is, increased distance, time and/or costs. The approach is flexible in physical scope, able to address national and continental resilience assessments and provide advice on tipping points of service performance. Furthermore, flexibility is also incorporated in terms of different resilience perspectives including decision-making by the asset owner or the national or trans-national supply chain disruption to a particular economic sector or company.</p><p>Finally, the risk assessment is discussed based on applications for the impacts of floods on European roads and the potential to extend to multi-hazard assessments (landslides, earthquakes, pluvial flooding) and other types of critical networks is discussed.  </p><p> </p><p>This paper has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 776479 for the project CO-designing the Assessment of Climate CHange costs. https://www.coacch.eu/</p><p> </p>

scholarly journals Uncertainties in Coastal Flood Risk Assessments in Small Island Developing States

2019 ◽  
Author(s):  
Matteo U. Parodi ◽  
Alessio Giardino ◽  
Ap van Dongeren ◽  
Stuart G. Pearson ◽  
Jeremy D. Bricker ◽  
...  
Keyword(s):  
Flood Risk ◽  
Input Data ◽  
Flood Damage ◽  
Small Island ◽  
Small Island Developing States ◽  
Damage Functions ◽  
Current Time ◽  
Coastal Flood ◽  
Coastal Flood Risk ◽  
The Impact

Abstract. Considering the likely increase of coastal flooding in Small Island Developing States (SIDS), coastal managers at the local and global level have been developing initiatives aimed at implementing Disaster Risk Reduction (DRR) measures and adapting to climate change. Developing science-based adaptation policies requires accurate coastal flood risk (CFR) assessments, which are often subject to the scarcity of sufficiently accurate input data for insular states. We analysed the impact of uncertain inputs on coastal flood damage estimates, considering: (i) significant wave height, (ii) storm surge level and (iii) sea level rise (SLR) contributions to extreme sea levels, as well as the error-driven uncertainty in (iv) bathymetric and (v) topographic datasets, (vi) damage models and (vii) socioeconomic changes. The methodology was tested through a sensitivity analysis using an ensemble of hydrodynamic models (XBeach and SFINCS) coupled with an impact model (Delft-FIAT) for a case study at the islands of São Tomé and Príncipe. Model results indicate that for the current time horizon, depth damage functions (DDF) and digital elevation model (DEM) dominate the overall damage estimation uncertainty. We find that, when introducing climate and socioeconomic uncertainties to the analysis, SLR projections become the most relevant input for the year 2100 (followed by DEM and DDF). In general, the scarcity of reliable input data leads to considerable predictive error in CFR assessments in SIDS. The findings of this research can help to prioritise the allocation of limited resources towards the acquisitions of the most relevant input data for reliable impact estimation.

scholarly journals Connections between regional economic growth and motor transport infrastructure

2018 ◽  
Vol 19 (6) ◽  
pp. 936-940
Author(s):  
Piotr Pawlak
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Road Network ◽  
Short Description ◽  
Transport Infrastructure ◽  
Regional Economic Growth ◽  
General State ◽  
Road Infrastructure ◽  
Motor Transport ◽  
The Road

The article presents, in the short description, a link between the economic development of the region and the condition of its road infrastructure. The region selected for comparisons and analysis of this compounds is Eastern Poland. First, the characteristics of the selected region were discussed. Next, the general state of transport development of the country was described, in aspect of road infrastructure. The last part of the article discusses the issues of the region's economic growth in relation to its infrastructure situation, in connection with the condition and development of the road network. The presented material was concluded with a summary, which emphasized the existence of the tested compounds.

Large Scale Flood Damage Mapping: the case study of Romania Country

2020 ◽  
Author(s):  
Raffaele Albano ◽  
Aurelia Sole ◽  
Salvatore Manfreda ◽  
Caterina Samela ◽  
Iulia Craciun ◽  
...  
Keyword(s):  
Machine Learning ◽  
Land Use ◽  
High Resolution ◽  
Flood Risk ◽  
Large Scale ◽  
Flood Damage ◽  
Emergency Operations ◽  
Hazard Exposure ◽  
Cost Efficient ◽  
Damage Mapping

<p>A large-scale flood risk analysis that properly evaluates and quantifies the three components of risk (hazard, exposure and vulnerability) is essential in order to support national and global policies, emergency operations and land use management. For example, governments can use risk information for the prioritisation of investments to implement measures for flood damage reduction, for emergency operations and for land-use policies, while reinsurance companies can improve the estimation of the flood risk-based insurance premiums.</p><p>Nevertheless, limits in time and data represent significant limitation this kind of applications: i) the significant amount of data and parameters required for the calibration and validation of traditional model; ii) the moderate/coarse resolution of data available at global scale and the sparse availability of high-resolution data that may affect the accuracy of analysis results; iii) the high cost and computational demand of hydraulic models. However, the growing availability of data from new technologies of Earth observation (EO) and environmental monitoring combined with the advances in newly developed algorithms (e.g. machine learning) have extended the range of possibilities for geoscientists, updating and re-inventing the way highly resource- and data-intensive processes, such as risk management and communication, are carried out.</p><p>The present study proposes a cost-efficient method for large-scale analysis and mapping of direct economic flood damage at medium resolution in data-scarce environments. The proposed methodological framework consists of three main stages. The first step concerns the derivation of a water depth map through a Digital Elevation Model (30m resolution)-based geomorphic method that uses supervised linear binary classification. The second step aims to realize an exposure map on the basis of a supervised land use classification through the use of a machine learning technique: the information extracted from Landsat-8 remotely sensed optical images were utilized in combination with the discontinuous (i.e. available for a few large cities in Europe) existing high-resolution Urban-Atlas land use maps in order to obtain a land-use map with a resolution of 30 m. Finally, the flood economic damage mapping was carried out using the results of the two previous steps in a GIS algorithm, developed by authors, based on the vulnerability (depth-damage) curves method. The proposed integrated framework has been tested in Romania for a 100-years return time event. The resulting map (at 30 m resolution) covers the entire Romanian territory including minor order rivers, which are often neglected in large-scale analyses.</p><p>The demonstrative application shows how the description of flood risk may particularly benefit from the integrated use of geomorphic methods, machine learning algorithms and EO freely available monitoring data. The ability of the proposed cost-efficient model to carry out high-resolution and large-scale analyses in data-scarce environments allows performing future risk assessments keeping abreast of temporal and spatial changes in terms of hazard, exposure and vulnerability.</p><p><em>Acknowledgement: This work was carried out during the tenure of an ERCIM ‘Alain Bensoussan’ Fellowship Programme.</em></p>

Flood vulnerability assessment: A critical comparison between site derived, national and international depth-damage functions and their use in assessing flood risk in Malaysia

2021 ◽  
Author(s):  
Balqis M. Rehan ◽  
Paul Sayers ◽  
A. Ulwan M. Alayuddin ◽  
M. Fadhil M. Ghamrawi ◽  
James D. Miller ◽  
...  
Keyword(s):  
Flood Risk ◽  
Flood Hazard ◽  
Flood Damage ◽  
Damage Function ◽  
Kuala Lumpur ◽  
Investment Planning ◽  
Damage Functions ◽  
Flood Vulnerability ◽  
Site Specific ◽  
Flood Vulnerability Assessment

<p>Damage functions are widely used to determine flood losses. National and international published damage functions are often used with little scrutiny or validation at local scales; a lack of understanding that unquestionably adds uncertainty to national flood risk assessment and investment planning. This paper examines the differences in aggregate flood damage estimates based on damage functions derived locally using local surveys and questionnaires, published national sector-based damage functions and land-use based damage functions published for Malaysia in the international literature. The paper is presented in two parts: firstly, the construction of a damage function from site-specific post-event flood surveys (covering a range of building types and flood hazard variables) and secondly, the comparison of these locally derived function with available national and international functions. A 0.05 km<sup>2</sup> residential area located in Kuala Lumpur, Malaysia, which consists of sparsely located houses was selected for the study. It was used to drive the site-specific damage function and an associated estimate of flood damage for a range of observed and modelled flood events. The results show that at higher depths, the use of the site-specific function suggest an aggregate damage of approximately twice than an estimate based on national functions but much less (less than 100%) than would be estimated based on international published functions. The paper concludes that the international published damage functions should be used with care and condition using local (where possible) or national understanding of flood damages to avoid a significant over estimation of losses.</p>

scholarly journals Rapid urban flood damage assessment using high resolution remote sensing data and an object-based approach

2020 ◽  
Vol 11 (1) ◽  
pp. 906-927 ◽  
Author(s):  
Sergio Iván Jiménez-Jiménez ◽  
Waldo Ojeda-Bustamante ◽  
Ronald Ernesto Ontiveros-Capurata ◽  
Mariana de Jesús Marcial-Pablo
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Damage Assessment ◽  
Remote Sensing Data ◽  
Flood Damage ◽  
Urban Flood ◽  
Sensing Data ◽  
Object Based ◽  
Flood Damage Assessment

scholarly journals Enhancement of large-scale flood damage assessments using building-material-based vulnerability curves for an object-based approach

2019 ◽  
Author(s):  
Johanna Englhardt ◽  
Hans de Moel ◽  
Charles K. Huyck ◽  
Marleen C. de Ruiter ◽  
Jeroen C. J. H. Aerts ◽  
...  
Keyword(s):  
Land Use ◽  
Built Environment ◽  
Rural Areas ◽  
Flood Risk ◽  
Building Material ◽  
Large Scale ◽  
Flood Damage ◽  
Risk Assessments ◽  
Object Based ◽  
Coarse Information

Abstract. In this study, we developed an enhanced approach for large-scale flood damage and risk assessments that uses characteristics of buildings and the built environment as object-based information to represent exposure and vulnerability to flooding. Most current large-scale assessments use an aggregated land-use category to represent the exposure, treating all exposed elements the same. For large areas where previously only coarse information existed such as in Africa, more detailed exposure data is becoming available. For our approach, a direct relation between the construction type and building material of the exposed elements is used to develop vulnerability curves. We further present a method to differentiate flood risk in urban and rural areas based on characteristics of the built environment. We applied the model to Ethiopia, and found that rural flood risk accounts for about 22 % of simulated damages; rural damages are generally neglected in the typical land-use-based damage models particularly at this scale. Our approach is particularly interesting for studies in areas where there is a large variation in construction types in the building stock, such as developing countries. It also enables comparison across different natural hazard types that also use material-based vulnerability, paving the way to the enhancement of multi-risk assessments.

scholarly journals Comparing Different Equipment and Applications in Pavement Data Collection as Part of Road Management System

2019 ◽  
Vol 3 (3) ◽  
pp. 39
Author(s):  
Arjol Lule ◽  
Shkelqim Daja
Keyword(s):  
Data Collection ◽  
Asset Management ◽  
Management System ◽  
Road Network ◽  
Road Transport ◽  
Transport Infrastructure ◽  
Management Systems ◽  
Road Infrastructure ◽  
The Road ◽  
Road Management

National roads are the main arteries in road transport infrastructure. Therefore, all agencies or authorities responsible of road infrastructure, pay attention to road management systems. Albania is experiencing an increase in road infrastructure investments and maintenance of this road network. There have been some attempts to establish national and secondary road management systems. These systems attempt to achieve different objectives, such as the provision of an adequate level of service, the preservation of the road infrastructure, etc. A good Road Asset Management System (RAMS), helps to carry out all the actions of inventory, storage and maintenance of road assets as well as, supports the decision-making process. At present, there are several data collection devices and applications that carry out the job efficiently. The purpose of this paper is to present the analysis of the use and comparison of some equipment and Cell Phone Based Systems (MiniROMDAS, PaveProf-V2 and RoadLab_Pro) used for the road pavement data collection, necessary in the calculation of the International Roughness Index (IRI), along the national road network in Albania. The comparison is made, by analyzing the data and results obtained along a 20 km long road segment in Albania, using the various above-mentioned technologies. Also, an overview of the currently available technologies providing information that could assist managers in establishing an appropriate data collection program is given.

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