HS7.5

In a world of increasing global flood hazards, vulnerable populations (very young and elderly) are disproportionately affected by flooding due to their low self-reliance, weak political voice and insufficient inclusion into climate adaptation and emergency response plans. These individuals account for most flood casualties and often rely on emergency services due to flood induced injuries, exacerbated medical conditions, and requiring evacuative assistance. However, emergency service demand often exceeds the potential capacity whilst flooded roads and short emergency response timeframes decrease accessibility, service area, and population coverage; but how does this compare across the globe and what will the future hold?

To answer this question, a global analytical framework has been created to determine the spatial, temporal, and demographic variability of emergency service provision during floods. This is based on global fluvial and coastal flooding (at 10-year and 100-year return periods), and present and future flood conditions (present-day and 2050, under RCP 4.5 and RCP 8.5 climate scenarios). The framework includes a hotspot analysis to identify the extent and distribution of flood hazards and at-risk vulnerable populations, an accessibility analysis to identify emergency service accessibility to vulnerable populations based on restrictions of flood barriers and response-time frameworks, and a vulnerability analysis to compare the environmental injustice of emergency service provision between key demographic groups.

The highlighted geographical and temporal differences in emergency service provision globally and between regions, in addition to the framework itself, can be used by national and international organisations to inform strategic planning of emergency response operations and major investments of infrastructure, services, and facilities to maximise the benefit to the disproportionately affected vulnerable populations. This includes the production of more detailed flood hazard and evacuation maps that highlight vulnerability hotspots, the prioritisation of vulnerable population groups in emergency response plans to minimise geographic and population disparities of flood injuries and fatalities, and the allocation of emergency service hubs in regions of high vulnerability but low emergency response provision.

How to cite: Johnson, S., Wilby, R., Yu, D., and Matthews, T.: Global analysis of emergency service provision to vulnerable populations during floods of various magnitude under climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5214, https://doi.org/10.5194/egusphere-egu22-5214, 2022.

The Intensity and frequency of extreme storms have been increasing due to possible climate change, making it challenging to manage stormwaters in highly urbanized areas. Without an adequate and appropriate stormwater system, these storms may cause significant damage and losses to live and properties. Low Impact Development (LID) is a recent but widely accepted alternative for managing the increased stormwater. However, limited research is available to understand their effectiveness and optimize the mix of LIDs and conventional stormwater systems. This study evaluates the performance of several LIDs under current and future storm conditions, identify the best performing mixes of LIDs and convention stormwater system and provide a decision-making tool for urban stormwater management. The methodologies will be tested for Renton City, which is part of the Seattle Metropolitan Area.

In order to achieve our objective, first, a statistical rainfall-runoff model will be developed to assess the current stormwater system and estimate runoff for the current and future periods. The final results indicate a significant increase in runoff due to the increased rainfall in the future (2020-2040) compared to the past (1995-2014). The Stormwater Management Model (SWMM) will then be used to simulate the rainfall-runoff under conventional and LIDs (e.g., bio-retention, rain barrels, rain gardens, infiltration trenches, and permeable pavement) stormwater system. The final results show that the performance of LIDs in reducing total runoff volume varies with the types and combinations of LIDs. A 30% to 75% reduction in runoff was achieved for the past and future 50-year and 100-year storms. A Genetic Algorithm (GA) is used to optimize the LID and conventional stormwater system considering the reduction in runoff, installation and maintenance costs. The type, size, location, and number of different LIDs will be considered as decision variables for the GA. Finally, the study aims at developing a comprehensive framework to evaluate the performance of LIDs under present and future storms and identify cost and performance effective LIDs in a given urban area. The framework introduced in this study will help local authorities and practitioners to implement appropriate climate change adaptation strategies by maximizing the benefit from LIDs and ensure sustainable stormwater management for the current and future climates.

How to cite: Abduljaleel, Y. and Demissie, Y.: Evaluation and Optimization of Low Impact Development Designs for Sustainable Stormwater Management in a Changing Climate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13, https://doi.org/10.5194/egusphere-egu22-13, 2022.

Flash floods are related to short duration and high intensity rainfalls, they are common phenomena in many parts of Europe as well as Italy. These events can result in debris flow, debris flood or water flood. The main differences are in the triggering, propagation, and depositional phases and more importantly in terms of velocity, impact forces and associated damage.
In Campania Region (Southern Italy) these phenomena historically involved the catchments several times, with an increase in frequency in the last decade. They are associated to small watershed – fan systems that fall in the southern Apennines characterized by intermittent flow. The alluvial fans in the outlet zones are highly urbanized, hence the population living in the deposition areas is exposed to high risk. 
In this study, the geomorphic response to flash floods is assessed through magnitude evaluation of some flash floods recently occurred in heterogeneous geological and geomorphological settings in both coastal and inland areas. Each scenario is reconstructed through the mapping of areal extent, water heights, particle sizes and estimate of volumes and built damage aiming at vulnerability definition, a relevant topic considering the global climate changes.
In this study, an approach aimed at developing vulnerability curves is proposed. It is based on a application of a typical method widely adopted in the earthquake engineering that in this case assume as intensity parameter the water height measured in post-event surveys. 
The results are expressed as vulnerability curves at different damage scenarios that can be valuable tools for local authorities, emergency, and disaster planners since they can assist decision making analysis of protection measures for future events.

How to cite: Forte, G., De Falco, M., Santangelo, N., and Santo, A.: Vulnerability scenarios for flash floods occurred in Campanian Apennines (South Italy), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4716, https://doi.org/10.5194/egusphere-egu22-4716, 2022.

Recent evidences suggest that in Europe, flood frequency and precipitation frequencies are often not aligned. Beside other factors pre-storm conditions exert a significant impact on flood generation thus their knowledge is paramount for a proper flood forecasting. A number of predictors have been used in the past to understand how much precipitation is transformed into runoff (i.e., runoff coefficient, RC). Notable examples are the antecedent precipitation index (API), the prestorm river discharge and soil moisture. On top of these new products potentially available from satellite observations like surface soil moisture and total water storage anomalies (TWSA), root zone soil moisture from reanalysis and hydrological models can be used along with precipitation to predict in advance the severity of the storm runoff.Our goal here is to provide an objective description of the role played by different predictors for hydrologic forecasting in Europe. In particular, we aim at answering the following research questions:

• How variable is runoff coefficient across the European catchments?
• How much are surface and root zone soil moisture, river discharge, antecedent precipitation and total water storage anomalies able to explain the RC variability across European floods?
• Under which conditions (climate period, location and flood magnitude) are the different pre-storm indices able to predict this runoff coefficient variability?

We answered these questions using long term (1980-2016) precipitation and river discharge observations from more than 100 basins covering different European regions. Results demonstrated that root zone soil moisture and TWSA are the best predictors of prestorm conditions under a variety of climatic and geographic features and thus their correct representation in land surface and hydrological models is strategic for an effective flood forecasting.

How to cite: Massari, C., Marra, F., Tramblay, Y., Crow, W., Camici, S., Modanesi, S., Brocca, L., and Gruendemann, G.: Prestorm root zone soil moisture conditions critical for flood forecasting in Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1830, https://doi.org/10.5194/egusphere-egu22-1830, 2022.

 The probabilistic assessment of risk due to landslides for Disaster Risk Reduction (DRR) purposes in terms of absolute and quantitative metrics (e.g., number of expected fatalities, economic damage) is still quite challenging. If, on the one side, landslide susceptibility models based on the combined statistical analysis of observed events and geomorphological predisposing factors can be efficiently implemented, they must be integrated by further hypothesis and information to capture the complexity of landslides hazard and be efficiently used for the assessment of risk. For instance, most susceptibility models are static and do not formally account for main triggering conditions (e.g., rainfall or seismic activity). Furthermore, they do not include any probabilistic information on the frequency/magnitude relationships of the related events, hence conveying relative and partial information. In this contribution, a simplified framework for probabilistic landslides risk assessment is presented and its application for multi-hazard risk assessment in Burundi is discussed. The proposed approach is based on the integration of multi-temporal susceptibility models accounting for monthly average precipitation patterns into a heterogeneous Poisson point process model. The occurrence process model is used to generate a large portfolio of events, each associated with a feature representing its magnitude whose distribution is modelled by a simple power law. These events can be combined with exposure and fragility/vulnerability information to obtain a probabilistic assessment of risk of different adverse consequences on people, assets and infrastructure.

The proposed approach has been exemplified in the context of a multi-hazard risk assessment at national scale for Burundi and has proved successful in providing spatialised absolute and relative risk estimates that could be compared and combined with risk assessments related to other hazards (e.g., earthquakes and floods) with different characteristics and return periods.

 The practical implementation was based on the available data for the targeted region, which is limited, and relies on several assumptions and hypothesis that are accompanied by a significant level of uncertainty. The results have been preliminarily assessed using the data provided by the IOM Emergency Tracking Tool (ETT) from the period 2018-2021. The results indicate that the framework is flexible and can be used to obtain actionable information on risk due to landslides at different temporal and spatial scales. Our findings further highlight the importance of addressing landslide risk from a larger, interdisciplinary perspective, fostering the systematic collection of risk-oriented data (e.g., event inventories including information on damage and loss) and the synergies among different actors involved in DRR and Climate Change Adaptation. The potential and limitations of the proposed approach for regional landslide risk and for multi-hazard risk assessment will be discussed. The described research activities have been carried out within the framework of an international project funded by the European Union, implemented by the International Organization of Migration (IOM) and coordinated by IDOM (Spain).

How to cite: Pittore, M., Steger, S., Moreno, M., Campalani, P., Renner, K., Villacis, C., Piñón, J., Pérez, E., Rincón de la Rosa, L., Achour, I., and Noel, E.: Towards a quantitative spatiotemporal assessment of probabilistic landslide risk for large-area applications: challenges and perspectives.  , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11082, https://doi.org/10.5194/egusphere-egu22-11082, 2022.

In this work a multi-relaxation time (MRT) Lattice Boltzmann model based on the use of non-conventional collision operator is used to simulate the flood event in Venice Lagoon.

Numerical methods (finite difference, finite volume and finite element methods) that solve the macroscopic equations of fluid mechanics (Navier Stokes equations), are usually employed for these aims. Most of these methods put in evidence that the application of bed slope and friction forces can lead to inaccurate solutions due to numerical errors.

In addition, the extension of these schemes to complex geometries is not straightforward and some of these approaches are very computational expensive if applied to real flows. Since the problems are posed at a large scale, it should be the aim to develop a simple and accurate representation of the source term to simulate realistic shallow water flows.

The LBM approach is a versatile method and it has been extensively applied in different fields.

Non-conventional Lattice Boltzmann models based on central moments and cumulants collision operators allows to simulate large-scale hydraulic problems such as flooding events and the use of a GIS environment allows to set the information related to topography, initial conditions (water depth and velocity values distribution), boundary conditions (position and type of solid and inlet/outlet boundaries), external force (value and distribution of roughness coefficients, obstacles position) and to make this data available for the execution of the numerical model.

In order to validate the correctness of the proposed mathematical model for Venice Lagoon, the real flood event that took place on November 12, 2019 is simulated: several field data are available for this test case; the results, in terms of water level and velocity field are compared with recorded data, verifying the accordance. Moreover, technical solutions for hydraulic risk evaluation and mitigation, taking account of the expected sea level rise, due to climate change, are proposed.

How to cite: Padrone, J., Di Francesco, S., and Venturi, S.: Modelling flood events in Venice Lagoon with a cumulant CO lattice Boltzmann shallow water model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2474, https://doi.org/10.5194/egusphere-egu22-2474, 2022.

Future scenarios of climate change foresee an increase in frequency, duration, and severity of droughts, especially in arid and semiarid regions. This predictions require an intensive study of drought mechanics, starting with how past and present droughts behave, and continuing with the study of future droughts.
In this research, it has been studied how a precipitation decrease that causes a meteorological drought is related to hydrological drought, caused by a decrease in river streamflow. The area of study is located in the Guadalquivir River basin, south of the Iberian Peninsula, which serves as an example of semiarid region. Two different sources of streamflow data are used: observational data obtained from the Spanish Centre for Public Work Experimentation and Study (CEDEX), which takes into consideration regulation from reservoirs, and modelled data obtained with the Variable Infiltration Capacity (VIC) model. The use of two data sources allows for a comparison of results, serving as a validation for future projects that will rely on the use of modelled data to study the behaviour of droughts in the near future.
The numerical description and correlation of droughts is performed by means of drought indices, such as the Standardized Precipitation Evapotranspiration Index (SPEI) or the Standardized Streamflow Index (SSI), each describing one drought type, respectively meteorological and hydrological.

Keywords: Drought indices, Hydrological model, Observational data, Guadalquivir basin.

Acknowledgements
This work was funded by FEDER/Junta de Andalucía-Consejería de Economía y Conocimiento, project B-RNM-336-UGR18, by the Spanish Ministry of Economy and Competitiveness project CGL2017-89836-390 R with additional support from FEDER Funds, and by FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades (project P20_00035).

How to cite: Romero-Jiménez, E., García-Valdecasas Ojeda, M., Yeste, P., Rosa-Cánovas, J. J., Esteban-Parra, M. J., Castro-Díez, Y., and Gámiz-Fortis, S. R.: Correlation of Meteorological and Hydrological Droughts using Observational and Modelled Data in the Guadalquivir River Basin, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10067, https://doi.org/10.5194/egusphere-egu22-10067, 2022.

The entire strait is the base of the port aquatorium and a vital shipping artery from the Baltic Sea to the Curonian Lagoon as well as a complex water system connecting two water basins of different sizes and depths and nature: differing considerably in salinity and density. Although the quays are well protected from the waves of the open sea, dangerous water level fluctuations still occur in the port area, the origin of which is not yet well understood. This study aims to identify the occurrence and main characteristics of the long waves, with the period from minutes to several hours, to identify their origin and impact.

Analysis of the spectral composition of these oscillations is based on continuous pressure recordings at a frequency of 4 Hz in Klaipėda harbour during the stormy season 2016-2017 and repeated during calm and stormy seasons in 2021. Most of the oscillation energy is concentrated in two frequency bands. Significant water level changes occurred due to infragravity motions with periods of 30 s (0.03 Hz) and disturbances with the typical periods of wind waves on the Lithuanian coast with periods of 3-10 s (0.1-0.3 Hz). The highest peak in the wind wave frequency band corresponds to typical storm conditions in the Baltic Sea with periods of 5-9 s. While the typical amplitudes of the oscillations in this range were modest, hazardous changes in water level occurred at lower frequencies with amplitudes of 0.5 m. The record shows the presence of harbour oscillations with periods of 30-200 s (0.005-0.03 Hz) and seiches of the Curonian Lagoon with periods of 1200 s (0.0008 Hz).

The largest oscillations are created by a combination of wind waves and infragravity waves with periods that roughly match the natural seiche periods of Klaipėda Strait and harbour oscillations and seiches can be observed not only during the stormy season.

How to cite: Nesteckytė, L., Klepšaitė-Rimkienė, L., and Myrberg, K. A.: Long waves in the Port of Klaipėda, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4011, https://doi.org/10.5194/egusphere-egu22-4011, 2022.

The subject of this presentation is the assessment of the occurrence, intensity, and impact severity of weather-related events with socio-economic implications during the period 2000-2020 in Greece. The aim is to draw critical conclusions through the distribution of events at the temporal and spatial level and in relation to their societal impact as measured by a qualitative impact-severity index. The data derived from the High Impact Weather Events (HIWE) database that has been developed by the METEO Unit at the National Observatory of Athens (NOA), is systematically updated and publicly available. The analysis includes events related to floods, lightning activity, hail, snow/frost, windstorms, and tornados having caused impacts on life (injury or death) and/or infrastructure. The presentation provides an overview of the data used and methodology applied for assessing weather-related hazards, and the results of their analysis that include the evolution of events, the most damaging phenomena, and the areas most exposed to each phenomenon. This work was conducted in the frame of CLIMPACT – National Νetwork on Climate Change and its Impacts, a flagship initiative on climate change to coordinate a Pan-Hellenic network of institutions.

How to cite: Papagiannaki, K., Kotroni, V., Lagouvardos, K., and Bezes, A.: High-impact weather events in Greece: Analysis of the period 2000-2020, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4523, https://doi.org/10.5194/egusphere-egu22-4523, 2022.

The northeastern area of Italy, and specifically of Friuli Venezia Giulia region (FVG), is characterized by the heaviest precipitation annual totals in the country. Effects of both prolonged and extreme precipitation can be particularly damaging in this area, causing debris flow, flash floods, avalanches. Due to the very short times of concentration and hydrological response of the mountain watersheds of the analyzed area, extreme and short events are of particular interest. The region has a dense ground-station network which is managed by the regional Civil Protection Agency, constituted by 2 main rain-gauges networks, based on CAE and Micros-SIAP technology, respectively; this last is co-managed by the OSMER-ARPA (OSservatorio MEteorologico Regionale-Agenzia Regionale per la Protezione dell’Ambiente) FVG. The networks count a total of about 200 rain-gauges; for some stations, data at 5-minute resolution are available since the 1996 (CAE network), whereas Micros-SIAP works continuously and at high resolution since the early 2000s. Over the last two decades, the temporal resolution of stations has been progressively increased up to 1-minute step.

This work presents a comprehensive analysis of the available dataset at high temporal resolution (i.e. 30 min, 5 min and 1 min) to verify whether trends in very short rainfall duration are underway. The continuous time series of data recorded by a sample of rain-gauges by the two networks are first analyzed. A preliminary analysis aims at verifying the consistency of the dataset at the higher resolutions. Statistical trends are then assessed by comparing two methods, i.e., the classical Mann-Kendall and the quantile regression at different thresholds and durations. Differently than the traditional methods that require a subset of data (e.g., the rainfall annual maxima), the quantile regression method allows to detect changes in the tails of the rainfall distributions and to screen the whole rainfall time series.

How to cite: Arnone, E., Treppiedi, D., and Noto, L.: Preliminary analysis of high-resolution precipitation in Friuli Venezia Giulia region, Italy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6434, https://doi.org/10.5194/egusphere-egu22-6434, 2022.

The analysis of short-duration precipitation extremes is of foremost importance as heavy precipitation is directly related to many hazards, e.g. flash floods, landslides and crop damage. Here, we adopt an extreme value framework based on the concept of ordinary events, defined as independent realizations of the process of interest. In particular, we aim at investigating the link between the characteristics of ordinary storms (e.g. seasonality, average duration, autocorrelation) and the statistics of the emerging extremes at sub-daily durations (1-24 h). We used the Global Sub-Daily Rainfall (GSDR) dataset, which provides quality controlled hourly precipitation data from rain gauges over the Contiguous United States (CONUS). 

First, we tested the hypothesis that a Weibull distribution can describe the tail of ordinary events and independently reproduce the annual maxima. Then, we quantified the portion of ordinary events, termed tail hereinafter, which share the statistical properties with annual maxima. Analysis of the storm characteristics show shorter average duration storms (< 12h) in the central portion of CONUS, between latitudes 90ºW and 105ºW. Seasonality analysis showed predominance of summer events in all central and eastern areas, with exception to a region encompassing the northwestern areas of the southern US states, which are dominated by spring events. On the western coast, winter events dominate the tail of the distribution of the ordinary events. The majority of these events happened in the afternoon (12PM to 6PM) or night (6PM to 12AM). The parameters describing our extreme value distribution revealed insightful features. The scale parameter of the Weibull distribution describing the tail followed the local climatology, with higher values over the southeast of CONUS (region characterized for high intensity precipitation), and small values over the northwest. The shape parameter indicates heavier-tailed distributions on the north and central regions of the US, as opposed to the majority of stations CONUS-wide. On average, the number of events per year is larger in the east (50 to 100 events per year) when compared to the west (0 to 50 events per year) . 

Further analyses include investigating the influence of storm properties in the parameters of our extreme value distribution. This link, if proven significant, can be used to establish predictors for extreme precipitation statistics that stem from characteristics of ordinary storm events.

How to cite: Araujo, D., Marra, F., Ali, H., Fowler, H., and Nikolopoulos, E.: Storm characteristics and extreme sub-daily precipitation statistics over CONUS, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10722, https://doi.org/10.5194/egusphere-egu22-10722, 2022.

The compounding evidence on the aberrant behavior of extreme precipitation has drawn attention of hydrometeorologists towards re-evaluating the existing hydraulic design criteria for protection of large structures (e.g., spillways of dams, nuclear power plants) in changing climate. Traditionally, design flood estimates for those structures were based on Probable Maximum Precipitation (PMP) to minimize or avert the risk of failure and consequent catastrophic damage to mankind and the environment. PMP, as defined by the World Meteorological Organization (WMO), does not account for long-term climatic trends. However, in recent decades, there has been an increase in frequency and magnitude of extreme precipitation events in different parts of the globe. This necessitates devising potential strategies to arrive at effective PMP estimates to re-assess the existing design criteria.  Against this backdrop, researchers have been actively developing new methods or modifying the existing ones to adapt to changing climate. The majority of these methods are physics-based whose application demands voluminous data on various hydrometeorological variables and computationally intensive systems to run simulations on weather models. In comparison, statistical approaches are simple and not data intensive. Among available statistical approaches, Hershfield method is widely used due to its ease of application. There is a dearth of attempts to extend it for use in climate change scenarios.

In the present study, a new variant of Hershfield method is proposed which yields reliable PMP estimates by accounting for long-term trends in precipitation data for better estimation of at-site frequency factor in the climate change scenario. The applicability of the proposed method is illustrated over India considering 119 years (1901-2019) long 0.25-degree gridded precipitation records from IMD (India Meteorological Department). The country has more than 5000 dams, and currently PMP estimates are being considered for risk analyses of several ageing dams through the aid of the World Bank, under DRIP (Dam Rehabilitation and Improvement Project). The proposed methodology is applied to arrive at PMP estimates for sites/grids in homogeneous precipitation regions delineated in the country using cluster analysis. The overall impact of increasing/decreasing trend of precipitation on the regional estimate of frequency factor and one-day PMP estimates is clearly demonstrated using the proposed and conventional Hershfield methods.

How to cite: Bhatt, J. and Srinivas, V. V.: Accounting for long-term climatic trends in Probable Maximum Precipitation estimation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11993, https://doi.org/10.5194/egusphere-egu22-11993, 2022.

The economic loss associated with natural hazards has drastically increased over the past decades, reaching over $210 billion dollars worldwide in 2020. The explication of regional-scale climate change effects with the tendency to exacerbate local climate criticalities has long jeopardized disaster resilience and the coping capacity of many communities. There is a lack of a robust operational linkage between the pre-disaster and post-disaster segments when a disaster occurs. This hampers an effective emergency response often leading to delayed humanitarian intervention and unplanned evacuations. Moreover, the great amount of openly available impact information on past events is commonly discarded and the forecast potential which the data yields has yet to be fully explored. In this context, the Impact-based Forecasting (IbF) approach aims to interconnect pre-emptive planning for early action with post-disaster impacts while taking advantage of historical data. The underlying principle of IbF is that the magnitude of an event is translated to site-specific impact information. Therefore, a paradigm shift from the conventional magnitude-likelihood relationship to impact-likelihood is proposed. This research develops a method to fully exploit the potential of IbF while overcoming the typical site-specificity of emergency response through remote sensing and automation. While the IbF framework allows for a multi-hazard approach, here we present a method targeting the ex-ante impact assessment of riverine floods. The analysis consists of two main components: i) the delineation of the flood extent from Sentinel-1 SAR imagery and ii) the definition of the event impact on the population, land and built environment. The IbF impact-likelihood relationship is ultimately derived by matching the two components for a historical event series. A fully automated Google Earth Engine algorithm for flood extent mapping with a 10 m spatial resolution has been developed to detect floodwater with a single-scene classification based on an automated thresholding method. The flood magnitude is then matched with open-access geodata such as human settlements, population density, land cover and infrastructure from the OpenStreetMap catalogue to generate the impact assessment. Once trained on several site or region specific past events, it can automatically forecast the impact associated with a given event magnitude. Here we apply the technique to three case studies including the flooding associated with the Tropical Cyclone Idai, which made landfall in Mozambique in March 2019 causing over 1200 fatalities and $2 billion worth of damage. The performance of the flood mapping algorithm has been evaluated as satisfactory for the impact application and further validation at two additional sites is ongoing. Therefore, local triggers can be set to ensure a valuable temporal window to promptly plan and estimate the cost of intervention on the field. This work is a first step to providing a consistent and regionally transferable disaster preparedness tool that allows for multi-hazard impact forecasts.

How to cite: Sarcinella, M., Pagán, B. R., Pal, J. S., Essenfelder, A. H., Landuyt, L., and Mysiak, J.: Impact-based Forecasting: Bridging the gap between forecast and post flood impact with remote sensing, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12046, https://doi.org/10.5194/egusphere-egu22-12046, 2022.