An analysis of Italian damage data to economic activities

2021 ◽  
Author(s):  
Marta Galliani ◽  
Francesca Carisi ◽  
Alessio Domeneghetti ◽  
Giovanni Menduni ◽  
Daniela Molinari ◽  
...  
Keyword(s):  
Critical Role ◽  
Flood Damage ◽  
Flood Events ◽  
Economic Activities ◽  
Commercial Activities ◽  
Flood Impacts ◽  
Damage Modelling ◽  
Damage Data ◽  
Observed Damage

<p>The study of flood impacts on the different sectors that compose the built environment and the society is crucial to implement actions of prevention, mitigation, and cautious planning. In such a context, the sector of businesses assumes a critical role, both for its importance for the wellbeing of the society and because of the high losses it suffers in case of inundations. Nevertheless, flood damage modelling to businesses is still a challenging task: the large number of different commercial activities, their specific geographical and economic contexts and the few observed damage data are just some of the reasons for that. In Italy, for example, a shared methodology to assess damage to enterprises is not present; building knowledge about types and dimensions of impacts of flood events to economic activities is then even more impelling. This contribution presents the analysis of about a thousand observed damage records regarding industrial and commercial activities, collected by four research groups after different flood events in Italy: the inundation occurred in the town of Lodi (Lombardia Region) in 2002, the one in Sardegna Region in 2013, and the floods caused in the Emilia-Romagna Region by Secchia (2014) and Enza (2017) Rivers. Data retrieved from the local and regional authorities responsible for damage compensation present different levels of detail and aggregation, according to the case study investigated. In all cases, they refer to the direct damage only and, for each case study, they have been first organised according to the activity types (e.g. trade, manufacturing, construction, finance) and per affected components: i.e. structure, equipment and stock. Data analysis has been led by some questions, we identified as key to start developing knowledge for damage modelling:  are there similarities in the different case studies? Which are the more affected business sectors in case of flood? Which component suffers the highest damage among structure, equipment, and stock? Is there an empirical trend of damage with hazard parameters? Results were first compared with the socio-economic context of the affected area, to have a first confirmation of data quality and reliability; then, the analysis focused on searching information and relationships between damage and activity type, activity dimension and water level. Results support the identification of the more vulnerable elements within the business sector, orienting modellers’ and decision-makers’ choices.</p>

Flood damage assessment to economic activities: implementation and transferability of French methodology

2021 ◽  
Author(s):  
Frédéric Grelot ◽  
Marta Galliani ◽  
Pauline Bremond ◽  
Daniela Molinari ◽  
Lilian Pugnet ◽  
...  
Keyword(s):  
Residential Buildings ◽  
Flood Damage ◽  
Economic Activities ◽  
Damage Functions ◽  
Flood Prevention ◽  
Damage Modelling ◽  
French Case ◽  
Damage Data ◽  
The City

<p>Since 2010, a national method is available in France for multi-criteria analysis of flood prevention projects. The method uses national damage functions to estimate losses to the different exposed items, including economic activities. Despite the business sector suffers significant losses in case of flood, flood damage modelling to businesses is less advanced than for other exposed sectors, as e.g. residential buildings. Reasons are many and include: the high variability of activities types composing this sector and then the difficulty of standardisation (above all when contents are considered), and the lack of data to understand and quantify damage and validate existing modelling tools. The collection of damage data in two case studies, in France and in Italy, and the collaboration between two research groups in the two countries allowed to study the applicability, the validity, and the transferability of the French damage functions for economic activities to Italy. Firstly, the functions were tested and validated in a French case study, i.e. the flood that affected the Île-de-France Region in 2016. This validation exercise faced the problem of working with few information about the identity of the activities, and propose a solution; moreover, it allowed to verify the actual availability of input data to implement the functions in France and pointed out the paucity of information to validate the methodology. Testing the functions in a foreign case study, i.e. the flood occurred in 2002 in Italy in the city of Lodi, allowed instead to verify the transferability of the method.</p>

scholarly journals Reconstituting past flood events: the contribution of citizen science

2019 ◽  
Author(s):  
Bocar Sy ◽  
Corine Frischknecht ◽  
Hy Dao ◽  
David Consuegra ◽  
Gregory Giuliani
Keyword(s):  
Citizen Science ◽  
Local Community ◽  
Flood Hazard ◽  
Quantitative Information ◽  
Flood Events ◽  
Flood Impacts ◽  
Causative Factors ◽  
Instrumental Records ◽  
Different Parts

Abstract. Information gathered on past flood events is essential for understanding and assessing flood hazard. In this study, we present how citizen science can help retrieving this information, in particular in areas with scarce or no instrumental measurements on past events. The case study is located in Yeumbeul North (YN), Senegal, where flood impacts represent a growing concern for the local community. This area lacks instrumental records on flood extent and water depth as well as information on the chain of causative factors. We developed a framework using two techniques to retrieve information on past flood events by involving two groups of citizens who were present during the floods. The first technique targeted the part of the citizens’ memory, which records information on events, recalled through narratives, whereas the second technique focused on scaling past flood event intensities using different parts of the witnesses’ body. These techniques were used for 3 events, which occurred in 2005, 2009 and 2012. They proved complementary by providing quantitative information on flood extents and water depths, and by revealing factors that may have contributed in aggravating floods for 3 events which occurred in 2005, 2009 and 2012.

scholarly journals DamaGIS: a multisource geodatabase for collection of flood-related damage data

2018 ◽  
Author(s):  
Clotilde Saint-Martin ◽  
Pierre Javelle ◽  
Freddy Vinet
Keyword(s):  
New Media ◽  
Personal Information ◽  
Flood Damage ◽  
Online Media ◽  
Flood Events ◽  
Multiple Sources ◽  
Partial Data ◽  
Damage Data ◽  
Reproducible Method ◽  
The Impact

Abstract. The present paper introduces a new database for collection of flood-related damage and assessment at the local scale. Every year in France, recurring flood events result in several million Euros of damage, and reducing the heavy consequences of floods has become a high priority. However, actions to reduce the impact of floods are often hindered by the lack of damage data on past flood events. Even if partial data were available, data sharing within the research community is very limited and closely supervised to ensure the protection of individuals' personal information. In comparison, the growth of social and online media has provided access to broad information at the local and global scales. Therefore, the DamaGIS database offers an innovative bottom-up approach to gather and identify damage data from multiple sources, including new media. This paper also presents an easily reproducible method to assess the severity of flood damage. The DamaGIS database is available at doi:10.5281/zenodo.1186623.

scholarly journals Estimation uncertainty of direct monetary flood damage to buildings

2004 ◽  
Vol 4 (1) ◽  
pp. 153-163 ◽  
Author(s):  
B. Merz ◽  
H. Kreibich ◽  
A. Thieken ◽  
R. Schmidtke
Keyword(s):  
Water Depth ◽  
Flood Damage ◽  
Economic Losses ◽  
Damage Functions ◽  
Data Set ◽  
Large Variability ◽  
Flood Impacts ◽  
Inundation Depth ◽  
Damage Data ◽  
Damage Estimates

Abstract. Traditional flood design methods are increasingly supplemented or replaced by risk-oriented methods which are based on comprehensive risk analyses. Besides meteorological, hydrological and hydraulic investigations such analyses require the estimation of flood impacts. Flood impact assessments mainly focus on direct economic losses using damage functions which relate property damage to damage-causing factors. Although the flood damage of a building is influenced by many factors, usually only inundation depth and building use are considered as damage-causing factors. In this paper a data set of approximately 4000 damage records is analysed. Each record represents the direct monetary damage to an inundated building. The data set covers nine flood events in Germany from 1978 to 1994. It is shown that the damage data follow a Lognormal distribution with a large variability, even when stratified according to the building use and to water depth categories. Absolute depth-damage functions which relate the total damage to the water depth are not very helpful in explaining the variability of the damage data, because damage is determined by various parameters besides the water depth. Because of this limitation it has to be expected that flood damage assessments are associated with large uncertainties. It is shown that the uncertainty of damage estimates depends on the number of flooded buildings and on the distribution of building use within the flooded area. The results are exemplified by a damage assessment for a rural area in southwest Germany, for which damage estimates and uncertainty bounds are quantified for a 100-year flood event. The estimates are compared to reported flood damages of a severe flood in 1993. Given the enormous uncertainty of flood damage estimates the refinement of flood damage data collection and modelling are major issues for further empirical and methodological improvements.

scholarly journals Are interactions important in estimating flood damage to economic entities?

2020 ◽  
Author(s):  
David Nortes Martínez ◽  
Frédéric Grelot ◽  
Pauline Brémond ◽  
Stefano Farolfi ◽  
Juliette Rouchier
Keyword(s):  
Local Level ◽  
Significant Proportion ◽  
Flood Damage ◽  
Economic Activities ◽  
Production Chain ◽  
Agent Based ◽  
Flood Impacts ◽  
Flood Damage Estimation ◽  
Standard Practices ◽  
Indirect Impacts

Abstract. Estimating flood damage, although crucial for assessing flood risk and for designing mitigation policies, continues to face numerous challenges, notably the assessment of indirect damage. It is widely accepted that damage other than direct damage can account for a significant proportion of total damage. Yet due to more scarce data sources and lack of knowledge on links within and between economic activities, indirect impacts have received less attention than direct impacts. Furthermore, attempts to grasp indirect damage through economic models have not gone below regional levels. Even though local communities can be devastated by flood events without this being reflected in regional accounts, few studies have been conducted from a microeconomic perspective at local level. What is more, the standard practices applied at this level of analysis tackle entities but ignore how they may be linked. This paper addresses these two challenges by building a novel agent-based model of a local agricultural production chain (a cooperative winemaking system), which is then used as a virtual laboratory for the ex-ante estimation of flood impacts. We show how overlooking existing interactions between economic entities in production chains can result in either overestimation (double counting) or underestimation (wrong estimation of the consequences for the activity) of flood damage. Our results also reveal that considering interactions requires thorough characterization of their spatial configuration.Based on both the application of our method and the results obtained, we propose balanced recommendations for flood damage estimation at local level.

scholarly journals The object-specific flood damage database HOWAS21

2020 ◽  
Author(s):  
Patric Kellermann ◽  
Kai Schröter ◽  
Annegret H. Thieken ◽  
Sören-Nils Haubrock ◽  
Heidi Kreibich
Keyword(s):  
Flood Damage ◽  
Damage Estimation ◽  
Economic Sectors ◽  
Flood Impacts ◽  
Large Potential ◽  
Damage Data ◽  
Flood Analysis ◽  
Flood Damage Estimation ◽  
Estimation Models

Abstract. The Flood Damage Database HOWAS21 contains object-specific flood damage data resulting from fluvial, pluvial and groundwater flooding in Germany. The datasets incorporate various pieces of information about flood impacts, exposure, vulnerability, and direct tangible damage at properties from several economic sectors. The main purpose of development and design of HOWAS21 is to support forensic flood analysis and the derivation of flood damage estimation models. This paper highlights exemplary analyses to demonstrate the use of HOWAS21 flood damage data in these two application areas. The data applications indicate a large potential of the database for fostering a better understanding and estimation of the consequences of flooding. HOWAS21 recently enlarged its scope and is now also open for international flood damage data.

What is the value of a multi-decadal regional database of compensation claims for flood damage modelling and risk management?

2021 ◽  
Author(s):  
Axelle Doppagne ◽  
Pierre Archambeau ◽  
Jacques Teller ◽  
Anna Rita Scorzini ◽  
Daniela Molinari ◽  
...  
Keyword(s):  
Flood Damage ◽  
State Agency ◽  
Flow Depth ◽  
Flood Events ◽  
Explanatory Variables ◽  
Damage Models ◽  
Damage Modelling ◽  
Spatial Coverage ◽  
Compensation Claims ◽  
Building Level

<p>Flood damage modelling is a key component of flood risk modelling, assessment and management. Reliable empirical data of flood damage are essential to support the development and validation of flood damage models. However, such datasets remain scarce and incomplete, particularly those combining a large spatial coverage (e.g., regional, national) over a long time period (e.g., several decades) with a detailed resolution (e.g., address-level data).</p><p>In this research, we analysed a database of 27,000 compensation claims submitted to a Belgian state agency (Disaster Fund). It covers 104 natural disasters of various types (incl. floods, storms, rockslides …) which occurred in the Walloon region in Belgium between 1993 and 2019. The region extends over parts of the Meuse and of the Scheldt river basins. The registered amounts of damage at the building level were estimated by state-designated experts. They are classified in six categories. While roughly half of the registered disasters are pluvial flooding events, they account for less than a quarter of the total claimed damage. In contrast, riverine floods correspond to about one third of the registered events, but they lead to one half of the claimed damage.</p><p>A detailed analysis of the data was undertaken for a limited number of major riverine flood events (1993, 1995, 2002), which have caused a very large portion of the total damage. By geo-referencing the postal address of each individual building, it was possible to assign each claim to a specific river reach. This enabled pointing at the most flood prone river stretches in an objective way. Then, using cadastral data, each type and amount of damage could be attributed to a specific building.</p><p>To explore the value of the database for elaborating and validating damage models, the claimed damage data at the building level were related to estimates of hydraulic variables for the corresponding flood events. To do so, we used an existing database of results of 2D hydrodynamic modelling, covering 1,200+ km of river reaches and providing raster files at a spatial resolution ranging from 2 m to 5 m for computed flow depth and velocity in the floodplains. The attribution of flow depth to individual buildings was performed either by averaging the computed flow depths around the building footprint or by considering the maximum value.</p><p>The correlation between claimed damage at the building level and attributed flow depth is relatively low, irrespective of the flow depth attribution method. This may result from the high uncertainty affecting each of these variables. It also hints at the necessity of using multivariable damage models which account for a broader range of explanatory variables than the sole flow depth (flow velocity, characteristics of building material and equipment, building age, etc.). This will be discussed in the presentation and further explored in the next steps of this research.</p><p>Data for this analysis were provided by the Belgian regional agency SPW-IAS in July 2020. Due to privacy reasons, data at the address-level may not be disseminated in the scientific community; but results of data processing may be shared at an aggregated level.</p>

scholarly journals Calibration and validation of FLFA<sub>rs</sub> -- a new flood loss function for Australian residential structures

2016 ◽  
Vol 16 (1) ◽  
pp. 15-27 ◽  
Author(s):  
R. Hasanzadeh Nafari ◽  
T. Ngo ◽  
W. Lehman
Keyword(s):  
Loss Function ◽  
Extreme Event ◽  
Flood Damage ◽  
Damage Models ◽  
Flood Loss ◽  
Residential Structures ◽  
Damage Data ◽  
Historic Data ◽  
Flood Damage Estimation ◽  
Observed Damage

Abstract. Rapid urbanisation, climate change and unsustainable developments are increasing the risk of floods. Flood is a frequent natural hazard that has significant financial consequences for Australia. The emergency response system in Australia is very successful and has saved many lives over the years. However, the preparedness for natural disaster impacts in terms of loss reduction and damage mitigation has been less successful. In this paper, a newly derived flood loss function for Australian residential structures (FLFArs) has been presented and calibrated by using historic data collected from an extreme event in Queensland, Australia, that occurred in 2013. Afterwards, the performance of the method developed in this work (contrasted to one Australian model and one model from USA) has been compared with the observed damage data collected from a 2012 flood event in Maranoa, Queensland. Based on this analysis, validation of the selected methodologies has been performed in terms of Australian geographical conditions. Results obtained from the new empirically based function (FLFArs) and the other models indicate that it is apparent that the precision of flood damage models is strongly dependent on selected stage damage curves, and flood damage estimation without model calibration might result in inaccurate predictions of losses. Therefore, it is very important to be aware of the associated uncertainties in flood risk assessment, especially if models have not been calibrated with real damage data.

Analyzing the National Logistics System through Integrated and Efficient Logistics Networks: A Case Study of Container Shipping Connectivity in Indonesia

2017 ◽  
Vol 862 ◽  
pp. 238-243 ◽  
Author(s):  
Siti Dwi Lazuardi ◽  
Bart van Riessen ◽  
Tri Achmadi ◽  
Irmanto Hadi ◽  
Achmad Mustakim
Keyword(s):  
Network Flow ◽  
Critical Role ◽  
Maritime Transportation ◽  
Network Design Problem ◽  
Economic Activities ◽  
Logistics System ◽  
Logistics Networks ◽  
Basic Infrastructure

Indonesia, as the world’s largest archipelagic country, should take into account the critical role of maritime transportation as a basic infrastructure for connecting inter-island economic activities. According to the National Logistics System, Indonesia should have its own international hub port in the future, thus this study is required to analyse the connectivity between main domestic ports and international hub ports in Indonesia. A heuristics approach is applied by combining the Feeder Network Design Problem and Multiple Commodity Network Flow Problem to create the optimum routes as well as to allocate the cargo by minimizing the total transportation costs. Two scenarios are conducted in the calculation, in the first scenario, we analyze all international containers of six main domestic ports (with Belawan), while the second scenario does not consider on the international containers in Belawan (without Belawan). The second case corresponds to directly delivering all international containers to Belawan, without considering these for the connectivity network. In conclusion, each route will have the fewer legs and shorter distances if the larger ship capacity used, consequently, the lower total shipping costs will be gained on these routes.

scholarly journals Are flood damage models converging to “reality”? Lessons learnt from a blind test

2020 ◽  
Vol 20 (11) ◽  
pp. 2997-3017 ◽  
Author(s):  
Daniela Molinari ◽  
Anna Rita Scorzini ◽  
Chiara Arrighi ◽  
Francesca Carisi ◽  
Fabio Castelli ◽  
...  
Keyword(s):  
Flood Damage ◽  
Joint Effort ◽  
Blind Test ◽  
Research Teams ◽  
Damage Models ◽  
Damage Modelling ◽  
Blind Comparison ◽  
Building Level ◽  
Implementation Stage

Abstract. Effective flood risk management requires a realistic estimation of flood losses. However, available flood damage estimates are still characterized by significant levels of uncertainty, questioning the capacity of flood damage models to depict real damages. With a joint effort of eight international research groups, the objective of this study was to compare, in a blind-validation test, the performances of different models for the assessment of the direct flood damage to the residential sector at the building level (i.e. microscale). The test consisted of a common flood case study characterized by high availability of hazard and building data but with undisclosed information on observed losses in the implementation stage of the models. The nine selected models were chosen in order to guarantee a good mastery of the models by the research teams, variety of the modelling approaches, and heterogeneity of the original calibration context in relation to both hazard and vulnerability features. By avoiding possible biases in model implementation, this blind comparison provided more objective insights on the transferability of the models and on the reliability of their estimations, especially regarding the potentials of local and multivariable models. From another perspective, the exercise allowed us to increase awareness of strengths and limits of flood damage modelling, which are summarized in the paper in the form of take-home messages from a modeller's perspective.

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