Assessing the costs of the overall economic impacts of natural hazards, costs of prevention and costs of emergency response, the supply of information on costs and benefits is crucial for decision-making in disaster risk reduction, hazard and risk management and climate change adaptation planning. This session aims to review current methodological approaches for assessing individual cost types and aims to show how these methods are used in the context of various natural hazards. We welcome submissions in the areas of assessing these various types of damage induced by any kind of natural hazard. Also, we are interested in contributions that focus on the cost-effectiveness or efficiency of risk reduction measures to natural hazards and adaptation to increasing weather risks due to climate change or other developments.
Additionally, this session aims at the better understanding of vulnerability of the built environment (building envelope, building content and infrastructure) to different types of natural hazards. The main focus herein is to present different models and approaches to bridge the gap between ex-post loss and damage assessment and ex-ante predictive models. Studies on loss, damage and vulnerability often address different scales and spatial patterns obstructing the comparison and transfer of results and methods. Moreover, although existing models (matrices, indices and functions) demonstrate high variance, analysis of the associated uncertainties remains fragmentary. We invite contributions addressing vulnerability, loss, damage assessment and we provide a platform for scientific exchange and implementation for successful disaster risk reduction strategies focusing on building back better, mitigation and adaptation.
vPICO presentations: Fri, 30 Apr
Modelling societal, ecological, and economic costs of natural hazards in the context of climate change is subject to both strong aleatoric and ethical uncertainty. Dealing with these is challenging on several levels – from the identification and the quantification of the sources of uncertainty to their proper inclusion in the modelling, and the communication of these in a tangible way to both experts and non-experts. One particularly useful approach is global uncertainty and sensitivity analysis, which can help to quantify the confidence in the output values and identify the main drivers of the uncertainty while considering potential correlations in the model. Here we present applications of global uncertainty analysis, robustness quantification, and sensitivity analysis in natural hazard modelling using the new uncertainty module of the CLIMADA (CLIMate ADAptation) platform.
CLIMADA is a fully open-source Python program that implements a probabilistic multi-hazard global natural catastrophe damage model, which also calculates averted damage (benefit) thanks to adaptation measures of any kind (from grey to green infrastructure, behavioral, etc.). With the new uncertainty module, one can directly and comprehensively inspect the uncertainty and sensitivity to input variables of various output metrics, such as the spatial distribution of risk exceedance probabilities, or the benefit-cost ratios of different adaptation measures. This global approach does reveal interesting parameter interplays and might provide valuable input for decision-makers. For instance, a study of the geospatial distribution of sensitivity indices for tropical cyclones damage indicated that the main driver of uncertainty in dense regions (e.g. cities) is the impact function (vulnerability), whereas in sparse regions it is the exposure (asset) layer.
(1) Aznar-Siguan, G. et al., GEOSCI MODEL DEV. 12, 7 (2019) 3085–97
(2) Bresch, D. N. and Aznar-Siguan., G., GEOSCI MODEL DEV. (2020), 1–20.
How to cite: Kropf, C. M., Ciullo, A., Meiler, S., Otth, L., McCaughey, J. W., and Bresch, D. N.: Uncertainty and sensitivity analysis for natural risk and adaptation appraisal modeling with CLIMADA, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1773, https://doi.org/10.5194/egusphere-egu21-1773, 2021.
Adaptive policy-making on drought risk management requires integrated assessment of uncertain future developments, policy actions and combinations of those. Preferably, such an assessment is based on quantified drought risks, defined as the integral of drought probability and economic consequences for all relevant sectors impacted by drought. The investment costs of proposed policy measures and strategies (various measures combined) can then be compared with the expected risk reduction.
We developed a method and assessment instrument to explore drought risk in the Netherlands, now and in the future, as well as in response to policy actions. By quantifying the amount of risk reduction in euro’s/year, we were able to assess costs and benefits of the investments proposed by various stakeholders. The method has been applied in support of the Netherlands drought risk management strategy as part of the National Delta Program which has to prepare the Netherlands for climate change. Drought risks were quantified by carrying out simulations with the National Water Model and coupled impact modules for five water users: agriculture, shipping, drinking water, industry water, and nature areas. A qualitative approach was taken for the drought effects on nature areas.
With the approach taken, we were able to assess costs and benefits of the investment strategy proposed by various stakeholders. The risk reduction of a measure differs per scenario, per year and per combination of measures, while the annual costs are the same. Results showed that the strategy was cost-effective under a scenario with ongoing climate change, in which the combined probability of precipitation deficits and low river flows increases. The method also provided insight into the most opportune time to implement the measures, considering uncertainty about future climate change. This provided relevant input for adaptive policy planning on the national scale.
How to cite: Mens, M., Rhee, van, G., Schasfoort, F., and Kielen, N.: Societal cost-benefit analyses based on quantified drought risks to assess Dutch Delta Program investments, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15268, https://doi.org/10.5194/egusphere-egu21-15268, 2021.
Drought economic impacts, even if non-structural, are a significant threat for those sectors highly dependent on water resources. Agricultural production is highly sensitive to extreme weather events such as droughts and heatwaves. Climate change is expected to exacerbate the frequency and the severity of droughts, as stated by the Intergovernmental Panel on Climate Change (IPCC), which raises concerns about food security for the next decades.
The Food and Agriculture Organization (FAO) estimated that between 2005 and 2015, 83% of all drought-related losses were absorbed by agriculture. The huge monetary losses are mainly due to crop yield reduction because of high temperatures and reduced precipitation, which are linked to additional expenses for field irrigation.
This study aims at estimating the economic impacts of drought on the agricultural sector. The investigation has been carried out for a specific case study area within the Po river basin (Northern Italy). The Po valley is the largest agricultural area in Italy and accounts for 35% of Italian agricultural production. It has experienced multiple droughts over the past 20 years, with the long and severe drought from 2003 to 2008 that caused relevant impacts to the agricultural sector. The total economic impact of the 2005-2007 drought was estimated to be around 1.850M€. Climate change projections over the Italian peninsula from the PRUDENCE regional experiments showed that the frequency and the severity of droughts in Northern Italy will increase in the next century due to a decrease in precipitation during critical crop growing seasons (spring and summer).
The proposed methodology consists of two steps. At first, farmers have been subjected to surveys for assessing the monetary losses they experienced during past drought events and the cost associated with the mitigation strategies implemented to reduce the economic impacts of the extreme event, with special attention to irrigation practices.
Secondly, the crop growing season and yields have been estimated using the Agricultural Production Systems sIMulator (APSIM), calibrated with local yields retrieved from the Italian National Institute for Statistics (ISTAT) over the period from 2006 to 2020. Weather parameters for simulations in APSIM were derived from remote-sensing images. The comparison between the average growing season and the ones with low yields allows the identification of the crop growing stages that experienced stress. Among the identified stresses, the ones related to water shortages are considered. The economic costs associated with agricultural practices are computed to obtain an estimation of farmers' expenses. Besides, farmers' income is computed based on crop prices and simulated yield. The reduced income obtained by farmers during the previously identified water-related stresses represents their loss due to drought.
Results reveal that the use of the developed methodology to identify drought stress in combination with the information coming from surveys helps in quickly assessing the economic impacts of past and present droughts in the Po river basin and represents a useful tool to evaluate which cultivations and which areas suffered the highest economic impacts of droughts.
How to cite: Borzì, I., Monteleone, B., Bonaccorso, B., and Martina, M.: Estimating the economic impacts of drought on agriculture through models and surveys in the Po river basin (Northern Italy), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12066, https://doi.org/10.5194/egusphere-egu21-12066, 2021.
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).
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.
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.
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.
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.
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.
How to cite: Doppagne, A., Archambeau, P., Teller, J., Scorzini, A. R., Molinari, D., Erpicum, S., Pirotton, M., and Dewals, B.: What is the value of a multi-decadal regional database of compensation claims for flood damage modelling and risk management?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6226, https://doi.org/10.5194/egusphere-egu21-6226, 2021.
The Flood Damage Database HOWAS 21 (https://doi.org/10.1594/GFZ.SDDB.HOWAS21) contains object-specific flood damage data resulting from fluvial, pluvial and groundwater flooding. The 8329 datasets (as at January 2021) incorporate various variables of flood hazard, exposure, vulnerability and direct tangible damage at properties from several economic sectors. The sectors comprise private households, commercial and industrial sector, agricultural and forested land, public thoroughfare (including roads and transport infrastructure) and watercourses and hydraulic structures. Although it currently almost exclusively contains datasets from Germany, it is still unique in respect to amount of data and detail of contained variables. HOWAS 21 mainly supports forensic flood analysis and the derivation of flood damage models. HOWAS 21 was first developed for Germany in 2007 but has recently been enhanced to an international flood damage database. This presentation shows the recent advancements of HOWAS 21 and highlights exemplary the use of HOWAS 21 flood damage data. HOWAS 21 is available at https://howas21.gfz-potsdam.de/howas21/
The use of HOWAS 21 follows a community-based concept, i.e. institutions that provide a defined amount and quality of data to HOWAS 21 get full access to the entire database. Thus, HOWAS 21 depends on the cooperation and commitment of the (scientific) community. The empirical flood damage database can only continuously grow, and as such increase its value for the whole community, if collected flood damage data are provided to HOWAS 21. Therefore, if flood damage data are or become available, we expressly encourage data owners to include them in HOWAS 21 for their own benefit and for the benefit of the whole community.
How to cite: Kreibich, H., Krahn, A., and Schröter, K.: The international flood damage database HOWAS 21, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8835, https://doi.org/10.5194/egusphere-egu21-8835, 2021.
Flooding is one of Australia’s more prevalent natural disasters, causing injury to people, damage to property and infrastructure, losses to business earnings, increases to the costs of providing government services, and intangible impacts such as environmental or social damages.
Australia’s National Strategy for Disaster Resilience (2011) and Queensland’s Strategy for Disaster Resilience (2017) provide the overarching framework to build disaster resilient communities in Queensland and Australia. Within this, Government has the role of identifying and implementing strategies to manage the disaster risks. The National Strategy recognises that consistent information on the costs and benefits of risk management options, which considers the full impacts on the social, built, economic and natural environments, is required to support this.
In Australia economic assessments for flood management projects have traditionally focused on the tangible damages of flooding, particularly to property. Other impacts of flooding, such as environmental or social impacts, are typically considered qualitatively or assessed through a multi-criteria assessment. The absence of state and/or national guidance on undertaking such assessments has also led to a wide variety of approaches, methodologies, data and results. This creates an unnecessary layer of complexity when seeking to compare and prioritise projects, within states and across Australia. It can also lead to the underestimation of the return on investment resulting from flood risk management projects, due to the incomplete capture of benefits.
The Brisbane River Strategic Floodplain Management Plan (SFMP) was publicly released in 2019 and includes 52 actions aimed to improve the resilience, safety and prosperity of the community and businesses in the Brisbane River floodplain, and Queensland more widely. The Queensland Reconstruction Authority (QRA) was allocated the lead to implement Action FM7 ‘Extend the economic framework established in the Strategic Plan and Technical Evidence Report to include community awareness and resilience, disaster management and land use planning.’
The Economic Assessment Framework for Flood Risk Management Projects is due for publication in early 2021. It was developed through a collaborative process with other state governments, universities, private practitioners, and key stakeholders to road test a number of approaches and develop the guideline to support a consistent methodology for economic assessments, which also quantify the impacts from non-structural options such as community awareness and resilience, building and development controls, and emergency management.
The new framework promotes consistent, comparable and complete economic assessments, and forms a key component of Queensland’s toolkit towards greater investment in risk mitigation and fostering disaster resilient communities.
How to cite: Moon, B. and Harrison, E.: Queensland’s New Framework for Flood Risk Management Economic Assessments, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1926, https://doi.org/10.5194/egusphere-egu21-1926, 2021.
Research on natural hazards has increasingly become concerned with compound events, i.e. multiple hazards that may coincide in space and time or happen sequentially. Such events may lead to unexpected or unwanted amplifications of the impacts compared to those of individual hazards. To what extent the co-occurrence of hazards exacerbates impacts and losses is largely undocumented.
Fluvial, pluvial, and coastal floods are commonly understood as distinct hazards. However, floods can be further differentiated, for example, into river floods, urban floods or flash floods. Most flood-loss models follow such a distinction of flood pathways, assuming that the damaging processes are also different and disconnected from each other. Recent studies have shown that vulnerability varies between distinct flood pathways. But loss modelling under the co-occurrence of distinct flood pathways has not yet been further examined.
Germany has faced severe floods since 2002, including preconditioned events (e.g. the rain-on-snow floods of 2006 and 2011; the excessive rainfall on already saturated soil of 2013), co-occurrence of multiple/consecutive hazards in the same geographical region, and spatially compound floods (such as in 2002, 2010 and 2016). Survey data collected after floods in Germany between 2002 and 2016 show that around 60% of 1150 surveyed households reported having been affected by more than one flood pathway indicating the process complexity at flooded properties.
With these survey data, we learned a model for estimating residential flood losses. We used Bayesian multilevel models that probabilistically incorporate uncertainty and allow for partial pooling of the data. Such models are capable of differentiating parameters for different flood pathways, but learn the parameters from all data simultaneously. One missing piece of information, however, is the contribution of each individual flood pathway to the overall financial impact. Although we cannot separate the magnitude of each flood pathway in our data, they are understood as distinct processes.
Bayesian inference is data driven and explicitly includes prior knowledge or beliefs. Our model thus assigns a prior belief of the extent to which co-occurrent pathways contribute to an increased loss. Therefore, five weight sets spanning a reasonable range, from averaged weighed to a total sum of effects, are implemented here in order to find eventual differences in the vulnerability of residential buildings to the different pathways and determine how they combine together into a single (potentially synergetic) impact.
This contribution introduces five model variants, their components, and shows the first differences across the model parameters. With this we also highlight the need to engage with the procedure of defining the weights sets, which still remains a challenge for the study of compound event' impacts.
How to cite: Samprogna Mohor, G., Korup, O., and Thieken, A.: Learning to estimate losses of compound inland flooding with Bayesian multilevel models, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3060, https://doi.org/10.5194/egusphere-egu21-3060, 2021.
The European Floods Directive (2007/60/EC) requires that Member States develop flood hazard and risk maps, to be used as the information basis for the development of Flood Risk Management Plans, and to update them every 6 years. To support such a process, the Po River District Authority signed in May 2020 an agreement with 20 Italian Universities and the Italian National Research Council (CNR) with the aim of transferring the state of the art about hydrology (including climate change), hydraulics and damage modelling into the production of the new maps, to be delivered by December 2021. This contribution describes the activities done so far by the damage modelling group, composed by 8 Universities and CNR. The objective of the group is to provide an Information System able to perform a quantitative estimation of flood damage, overcoming the limitations of present maps where the evaluation of risk remains highly qualitative and subjective. Proper damage assessment tools were identified for all the five categories of exposed elements included in the Directive: population, infrastructures, economic activities, environmental and cultural heritage, and na-tech sites. These tools are thought to address specific requirements: (i) being valid/applicable for the whole area of the District, (ii) being based on standardised and institutional data, available at national level, (iii) being calibrated (and possibly validated) in the Italian context. A dedicated Geographical Information System is currently under development to support technicians in the application of proposed tools and in the visualisation and processing of damage assessment results. The work done so far suggests that a quantitative estimation of damage is not yet possible for all the categories, rather three different levels of damage knowledge can be reached depending on the category and available data: quantitative, qualitative or descriptive (the latter being based on a deep investigation of historical data). Therefore, in order to get a total damage figure, the need arises of (i) comparing damage data with different metrics and (ii) comparing and weighting damage to different exposed categories, whose values may depend on objectives at stakes. A participatory process with final users will be then set up in the next year, to guarantee the usability and applicability of developed tools.
How to cite: Molinari, D. and Ballio, F. and the Flood damage group - Po River District's updating maps project: On the update of flood hazard and risk maps in the Po River District: results obtained for flood damage modelling, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4087, https://doi.org/10.5194/egusphere-egu21-4087, 2021.
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.
How to cite: Grelot, F., Galliani, M., Bremond, P., Molinari, D., Pugnet, L., Richert, C., and Ballio, F.: Flood damage assessment to economic activities: implementation and transferability of French methodology, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10049, https://doi.org/10.5194/egusphere-egu21-10049, 2021.
Today, flood risk management practices incorporate non-structural measures that take into account the potential of ecosystems to prevent, regulate and reduce water-related hazards. However, the implementation of non-structural measures, such as floodplains and water retention areas, increases the exposure of rural and farming areas for better protection of urban and industrial areas. Since agricultural enterprises are closely linked to land productivity, this exposure trade-off directly affects farm incomes, and thus the long-term sustainability of agricultural activities in floodplain and water retention areas. In addition, local businesses are increasingly interconnected in production networks and supply chains and impacts on local business can quickly have further consequences.
We propose to consider these supply networks as complex systems, i.e. a set of heterogeneous entities interacting with each other according to a given topology.In these systems, the upstream and downstream links that govern the interactions of the entities may allow the appearance of indirect effects that are reflected through the network of links. In our work, we focus on a cooperative winemaking system (CWS). A CWS is conceptualized as a supply chain in which a cooperative winery and a set of vinegrowers interact. The basic product of the system (the grape) is supplied by the vinegrowers, which the cooperative finishes processing (carrying out the winemaking, bottling and marketing stages).
We propose to analyze the extent to which individual winegrowers in financial difficulty may pose a threat to the sustainability of the system in the event of flooding. To carry out this analysis, we adopt a bottom-up approach. We use an agent-based model (the COOPER model) to simulate the production dynamics of the CWS. The COOPER model is used as a virtual laboratory to explore the behavior of the system under various flood scenarios, varying according to the spatial extent of the event and the season of occurrence. We test the influence of 4 parameters on financial viability at both the individual and system levels: the rigidity of the cost structure of the winery, the location of the winery, the individual business cessation criteria and the individual initial treasury.
Our results show that winery-related parameters influence the capacity of both system and individuals to absorb flood impacts more than individual parameters. The analysis of financial flows shows that, indeed, contrary to standard hypotheses in cost-benefit analyses and business resilience studies, return to pre-disaster states might not be possible. Furthermore, without financial support, some businesses may never recover and bussines dismissal due to financial presures and harvest variations threats the survival of the CWS (hence theating the long term viability of farming activities). In addition, we unveil a mechanism to graduate the degree of damage spreading in case of productions losses within the CWS hidden in the revenue-cost sharing rules and the structure of costs. From a managerial point of view, this type of result has strong implications: managers can influence the capacity of the CWS to absorb shocks and prevent damage propagation by keeping cost structures from becoming too rigid.
How to cite: Nortes Martínez, D., Grelot, F., Brémond, P., Farolfi, S., and Rouchier, J.: Effects of flood-induced individual businesses' financial distress over complex cooperative productive systems, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10226, https://doi.org/10.5194/egusphere-egu21-10226, 2021.
Estimating damage is crucial to evaluate flood management policies and to choose between different alternatives. In Cost-Benefit Analysis, the benefits of the policies are most of the time evaluated by avoided damage. One of the underlying assumptions of damage estimation is that the impacted assets come back quickly to their initial state, which justifies the assumption to focus on short term damage. So far, little research has questioned this assumption. However, recent work (Nortes Martinez, 2019) showed that flooding can critically disrupt farming systems in the long term. The vulnerability of agricultural activities to flooding has received so far less attention because they represent less damage proportionally compared to other economic sectors. However, better characterizing impacts on such assets is key to evaluating the efficiency and sustainability of flood management policies which relies on increasing exposure on agriculture. In this article, we propose to address the issue of long term field surveys to improve the assessment of flood-related damage to agricultural activities. To do so, we carried out interviews in 2015 with farmers impacted in 2014 by a flood, and which was repeated in 2019 and 2020. The case study is the “Étang de l’Or” watershed, located in the South of France in the Occitanie Region. It was impacted by an extreme flood in September 2014. 70 impacted farms were identified representing a total area of 3 044 ha of which 340 ha were affected. The main specialization of these farms were viticulture (27 farms) and market gardening and horticulture (27 farms). In 2015, a first round of surveys was carried out. A questionnaire aimed at having a global vision of the impacts on farms was used. 41 farms responded to the interviews (14 in viticulture and 16 in marketing gardening horticulture), which were carried out face-to-face. In 2019 and 2020, a second round of surveys was carried out with the farms specialised in viticulture and in market gardening and horticulture. A questionnaire was designed to investigate impacts that have occurred since 2014 as well as the potential adaptions implemented. 10 farms specialised in viticulture and 11 specialised in market gardening participated to the second round respectively 4 and 5 years after the first interviews. Long term surveys revealed that few biophysical impacts have persisted after the 2014 flood, for example long term loss of yield or impact on quality of the products. However, financial impacts were still present 5 years after: repayment of loans, replenishment of the cash fund. Although a full correlation cannot be established, some farms have gone bankrupt. In conclusion, we present methodological recommendations for the implementation of a long-term observation framework for flood impacts.
How to cite: Bremond, P., Balzergue, P., Garcia, P., Kechichian, L., Perret, N., Pouillet, A., and Grelot, F.: What do long term field surveys tell us about the economic impacts of flooding on agricultural activities?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9985, https://doi.org/10.5194/egusphere-egu21-9985, 2021.
In recent years in mountain areas, natural hazards such as rockfalls, avalanches and mudflows, triggered by ongoing climate change have increased in both frequency and magnitude. Hazards that, accompanied by increasing demographic pressure, socio-economic and land-use changes, especially in the Alpine region, have called for a greater need for human protection. This demand can be met with artificial structures, such as rockfall nets and avalanche fences, or with natural solutions, such as forests if properly managed. However, the protection service provided by forests, against natural hazards is difficult to value because it has no target market. Therefore, providing a value for this service would allow it to be integrated into risk management plans and programs. In this work, we analyzed from a qualitative and quantitative point of view the most widely used economic methods for estimating the protection service provided by forests against natural hazards, providing a decision support tool for stakeholders involved in risk management. The main results indicate that, depending on the resources and time available, as well as the spatial and temporal scale required, some methods are preferable to others. The Replacement Cost method is well suited to most operational contexts in which stakeholders may find themselves, as it is replicable, cost-effective and results are reliable and easily communicated. Although the Avoided Damages method refers to market data and is also capable of estimating indirect costs, it has the limitation of being site-specific. While the stated preference methods are suited for long-term evaluations on a large spatial scale, they require a high level of expertise and are costly in terms of both time and resources. From our analysis, we can conclude that the provided decision support tool should not replace the human ability to analyze complex situations, but rather be an aid to this process. The combination of this tool with others, such as frameworks and guidelines, provides a flexible support system aimed at improving the design and implementation of future ecosystem service assessments and management, as well as related decision-making.
How to cite: Bruzzese, S., Blanc, S., and Brun, F.: The forest protection service: a risk management decision support tool, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10655, https://doi.org/10.5194/egusphere-egu21-10655, 2021.
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 km2 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.
How to cite: M. Rehan, B., Sayers, P., M. Alayuddin, A. U., M. Ghamrawi, M. F., D. Miller, J., A. Kabirzad, S., Kaelin, A., C. Penning-Rowsell, E., H. Basri, B., A. Bell, V., Zulkafli, Z., and J. Stewart, E.: Flood vulnerability assessment: A critical comparison between site derived, national and international depth-damage functions and their use in assessing flood risk in Malaysia, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12731, https://doi.org/10.5194/egusphere-egu21-12731, 2021.
The selection of vulnerability models has a significant influence on the overall uncertainty when quantifying flood loss. Several scholars reported a limited spatial transferability of available vulnerability functions to case studies other than those they have been empirically deduced from. As a result, there is a need for computation and validation of regionally specific vulnerability functions. As in many data-scarce regions this option is not feasible, the physical processes of flood impact model chains can be developed using synthetic vulnerability function and validating them by expert opinion. The function presented in our study is based on expert heuristics using a small sample of representative buildings. We applied the vulnerability function in a meso-scale river basin and evaluated the new function by comparing the resulting flood damage with the damage computed by other approaches, (1) an ensemble of vulnerability functions available from the literature, (2) an individual vulnerability function calibrated with region-specific data, and (3) the vulnerability function used in flood risk management by the Swiss government. The results show that synthetic information can be a valuable alternative for developing flood vulnerability models in regions without any data or only few data on flood loss.
How to cite: Keiler, M., Zischg, A., and Fuchs, S.: Evaluating synthetic vulnerability functions in flood risk modelling – a case study from Switzerland, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13222, https://doi.org/10.5194/egusphere-egu21-13222, 2021.
The importance of assessing the physical vulnerability of assets to natural hazards is indisputable. Recent extreme events have shown that the severity of natural hazards is strongly linked to the vulnerability of the population and the built environment. Physical vulnerability, in particular, is directly connected to monetary damages and interruptions that are in the centre of the interests of several stakeholders including governments, authorities, insurance companies, engineers, and homeowners. A plethora of different approaches is available in the literature, nevertheless, two categories of approaches are the most prominent: vulnerability curves and vulnerability indicators. In this study, both are put to the test by using data from two relatively recent dynamic flood events. In more detail, a physical vulnerability index (PVI) and a Beta model based on damage data from Italy and Austria are validated using recent damage data from an event in Dimaro Folgarida (Trento, Italy) in 2018 and an event in Schallerbach (Tirol, Austria) in 2015. The study does not just validate the methods but also investigates remaining uncertainties related to the assessment of the process intensity on buildings and the calculation of the building value by conducting a sensitivity analysis.
How to cite: Papathoma-Koehle, M., Dosser, L., Roesch, F., Schlögl, M., Borga, M., Erlicher, M., and Fuchs, S.: Validation of methods for the assessment of physical vulnerability to dynamic flooding, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2010, https://doi.org/10.5194/egusphere-egu21-2010, 2021.
Coastlines across the globe have been experiencing threats due to rising sea-level. The global average rise in the annual sea level is projected to be 2 -3 mm putting the coastlines across the globe into a threat. South-East Asian countries would experience sea-level variation from 1.5 mm to 4.4 mm per year, exacerbating inundation risk due to tidal anomalies. Many of these countries bear relatively higher population density and fall under developing economy – hence under-equipped to follow proactive strategies for adaptation.
Recurring flood hazard incapacitates regional sustainability. Rapidly changing climate scenarios further add to the climate-hazard sensitivity by increasing the frequency of extremes. The coastal communities experience multiple threats of such climate sensitivity due to rising sea-level and high tide anomalies In the form of loss of life and livelihood, overbearing losses from disaster-related damages to the infrastructure damages. Particularly those associated with residential building impose significant liability on marginal groups, presenting ‘disaster recovery’ nearly an impossible target to achieve. Therefore, damage reduction becomes an inevitable parameter for disaster risk reduction (DRR).
This research presents a methodology for the assessment of vernacular building typology in coastal areas of Sundarbans in eastern India. The area adjoining the Bay of Bengal is the part of largest Mangrove delta in the world The case area, Sagar Island has 75 percent of its population residing within traditional housing system that is now under potential economic stress due to reoccurring floods. The process begins with probing insight on the damage and failure pattern induced by floodwater to the housing and helps in the development of a systematic framework for ‘damage preventing intervention’ for primary building typology. The study categorizes damage stages associated with the high tide flooding levels using the synthetic method of data collection. This is followed by damage cost calculation for the flood levels considering the available remedies. Therefore, suggesting a proactive approach for disaster resilient design depending on robustness and cost-effectiveness of the chosen remedies. As the vernacular buildings are still a popular habitat choice in various parts of developing/ urbanizing South Asia, the research finds a generic application for upgrading vernacular housing design standards for regional sustainability.
Keywords: flood hazard, high tide flooding, climate change, vernacular housing, damage assessment
How to cite: Narendr, A., Das, S., and H. Aithal, B.: Damage-cost assessment of vernacular buildings against coastal flooding, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-829, https://doi.org/10.5194/egusphere-egu21-829, 2021.
Recent events worldwide have clearly shown that wildfires pose a serious threat to people and buildings located in the WUI (Wildland-Urban-Interface). In Europe, due to climate change, wildfires are expected to continue affecting areas not only in the Mediterranean but also in other European regions (e.g. alpine and Scandinavian context). A wide range of tools is available for the assessment of physical vulnerability of buildings to different hazard types including floods, landslides and earthquakes. Yet, to date, vulnerability of buildings to wildfire still remains under-researched. Research gaps in this respect are pointed out in this study and a well-established approach for vulnerability assessment of buildings already used for tsunamis and dynamic flooding is adapted in order to be used for wildfires. The method is based on the development of a vulnerability index using building characteristics (indicators) that contribute to wildfire vulnerability, including construction material, surroundings, building design and surrounding vegetation. The index may be used as a basis for strategies for vulnerability reduction (reinforcement of buildings, building codes), evacuation planning, insurance purposes and resilient reconstruction of affected areas. Preliminary results of an application in Mati (Attica, Greece) based on the data of a wildfire occurred in July 2018 resulting in the death of more than 100 people are presented
How to cite: Garlichs, C., Diakakis, M., Mavroulis, S., Fuchs, S., and Papathoma-Köhle, M.: Vulnerability of buildings to wildfire, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1173, https://doi.org/10.5194/egusphere-egu21-1173, 2021.
Cultural heritage is universally recognized as an essential part of the socio-cultural and economic capital of a country. Current policies emphasize the strong contribution and cross-cutting nature of cultural heritage to achieve strategic goals for a smart, sustainable and inclusive growth. Furthermore, the important role that cultural heritage plays in creating and enhancing social capital has been particularly highlighted, as well as its economic impact. Nevertheless, natural hazards cause serious threats to cultural heritage, and severe damage and losses are recurrently seen to affect it due to these types of events. While such impacts can be seen to stem from a variety of sources, their physical characteristics play a significant role in their vulnerability to natural hazards. Therefore, it is imperative to explicitly consider cultural heritage in natural hazard risk reduction and management initiatives, from local to national and global scales, supported by rational and knowledge-based vulnerability and risk assessment studies.
However, the development of such assessments for a large number of cultural heritage assets in a region presents several challenges. Firstly, there is a shortage of methodological approaches to model the vulnerability and risk of cultural heritage assets to different natural hazards. Secondly, performing detailed vulnerability/risk analyses for every cultural heritage asset on a large scale (i.e. across a region or a country) would require resources that are unavailable in most cases. Finally, adequate post-disaster damage and loss data to support the development of methodologies is almost inexistent in this sector, namely due to a lack of approaches to do so, and to the difficulties in expressing intangible losses in quantitative terms.
In this context, this presentation will showcase recent advances in these fields developed within the ongoing research project RIACT (Risk Indicators for the Analysis of Cultural Heritage under Threat). These include the development of simple but robust approaches for the analysis of the vulnerability and risk of cultural heritage at various scales and their application in pilot case studies, the development of a database for collecting disaster damage and loss data in the cultural heritage sector, and the development of methodologies for cultural heritage disaster damage valuation and value-based post-disaster recovery prioritization. Ultimately, these research efforts aim to support stakeholders responsible for cultural heritage management and preservation in improving their adaptive capacity to plan for and respond to natural hazards.
How to cite: Romão, X., Figueiredo, R., Paupério, E., Salazar, G., and Tikhonova, O.: Natural hazard risk management for cultural heritage assets: advances in the context of the RIACT research project, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14743, https://doi.org/10.5194/egusphere-egu21-14743, 2021.
Linear critical infrastructures are fundamental for functioning of the society and for generating everyday economic activities. Maintenance of these infrastructures, as well as quick restoration of the services after service disruption are important and challenging tasks. Extreme weather events and related hazards (e.g. floods, erosion, landslides, and forest fires) may lead to a malfunctioning of these infrastructures, resulting in social and economic consequences.
A wide variety of methods are applicable for consequence assessment of linear infrastructure. A review and summary of existing methodologies has been made and recommendations for their use are provided. The review encompasses semi-quantitative approaches (e.g. multi-criteria analysis and indicator-based scoring approaches) and quantitative approaches, using damage assessment and economic impact tools. The approaches might be hazard specific, addressing the interaction between the hazard and the infrastructure assets or focus on the societal consequences of the malfunctioning infrastructure. In this work, special attention is paid to the assessment of the infrastructure service disruption as well as of physical damage to the linear infrastructures.
A framework for risk assessments of adverse weather-related events affecting terrestrial transportation lines has been established. The framework can be also applied to other linear infrastructure, such as water and electric power supply. The framework encompasses risk identification and assessment of hazard, exposure, vulnerability and consequences. In the risk identification, modes of malfunctioning of the infrastructure service are identified, as well as natural triggering events initiating the malfunctioning. Hazard encompasses frequency and intensity of the triggering events and is assessed at the location of the exposed infrastructure assets. The event intensity, is a parameter (single or composite) characterizing the damaging potential of a natural event, e.g. the water depth or velocity for flood. Vulnerability models represent the functional loss, the damage degree or the exceedance probability of damage levels pertinent to an infrastructure asset, expressed in terms of event intensity. For further consequence assessment, the criticality of assets need to be assessed, e.g. by using an event tree approach to analyse the relation between asset damage and service disruption. The indirect consequences depend on redundancy (multiple paths of supply) and robustness, but also on the capacity to restore functionality in a timely way (rapidity) as well as on the resources available to restore functionality (resourcefulness). Economic consequences (direct and indirect losses) due to weather-related events have been evaluated for transportation infrastructures, considering material damage caused by flooding as well as consequences for the users stemming from the interruption of the transportation service.
The described work receives funding from the European Community’s H2020 research and innovation program under grant agreement No 769255 (SAFEWAY). The sole responsibility for the content of this abstract lies with the authors. It does not necessarily reflect the opinion of the European Union. The work is also funded by the Research Council of Norway through the Centre for Research-based innovation KLIMA2050.
How to cite: Eidsvig, U. and Piciullo, L.: Consequence assessment of linear infrastructure exposed to hazardous weather-related events, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2253, https://doi.org/10.5194/egusphere-egu21-2253, 2021.
An Mw 6.9 (Ml 6.6) earthquake occurred at an estimated focal depth of 12 km in the Aegean Sea on October 30th, 2020. 115 people died in Turkey in the devastating earthquake, it left more than one thousand people injured and several hundreds of families in need of a shelter. The strong ground shaking further amplified by local site effects caused building collapses and substantial damages throughout the city of Izmir (Turkey) as well as in Samos Island (Greece). In the aftermath of the event, an intensity-based damage analysis was conducted for the rapid estimation of number of damaged buildings at regional scale. For this purpose, first, spatial distributions of PGA, PGV values and instrumental intensities were computed by also incorporating the recorded ground motion data made available by several institutions. Numbers of damaged buildings at each EMS-98 damage grade were then estimated using the intensity-based, regionally adjusted structural vulnerability relationships. This paper presents the geographical distributions of rapid damage estimations and compares them to the observational damage data.
How to cite: Hancilar, U., Dede, S. O., Sesetyan, K., Cakti, E., Dar, E., Erturk, S. O., Kafadar, N., Koca, C., Korkmaz, A., Malcioglu, F. S., Suleyman, H., Tetik, T., Uncu, G., Yenihayat, N., and Yolcu, A.: Rapid Estimation of Spatial Distributions of Building Damages in the 30 October 2020 Aegean Sea Earthquake, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16186, https://doi.org/10.5194/egusphere-egu21-16186, 2021.
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