HS7.5 | Hydro-meteorological Extremes and Hazards: Vulnerability, Risk, Impacts and Mitigation
EDI
Hydro-meteorological Extremes and Hazards: Vulnerability, Risk, Impacts and Mitigation
Co-organized by AS1/GM4/NH1/NP8
Convener: Francesco Marra | Co-conveners: Elena CristianoECSECS, Nadav Peleg, Efthymios Nikolopoulos, Giuliano Di Baldassarre
Orals
| Wed, 17 Apr, 10:45–12:30 (CEST), 14:00–15:45 (CEST)
 
Room B, Thu, 18 Apr, 16:15–18:00 (CEST)
 
Room B
Posters on site
| Attendance Thu, 18 Apr, 10:45–12:30 (CEST) | Display Thu, 18 Apr, 08:30–12:30
 
Hall A
Posters virtual
| Attendance Thu, 18 Apr, 14:00–15:45 (CEST) | Display Thu, 18 Apr, 08:30–18:00
 
vHall A
Orals |
Wed, 10:45
Thu, 10:45
Thu, 14:00
Extreme hydro-meteorological events drive many hydrologic and geomorphic hazards, such as floods, landslides and debris flows, which pose a significant threat to modern societies on a global scale. The continuous increase of population and urban settlements in hazard-prone areas in combination with evidence of changes in extreme weather events lead to a continuous increase in the risk associated with weather-induced hazards. To improve resilience and to design more effective mitigation strategies, we need to better understand the triggers of these hazards and the related aspects of vulnerability, risk, mitigation and societal response.
This session aims at gathering contributions dealing with various hydro-meteorological hazards that address the aspects of vulnerability analysis, risk estimation, impact assessment, mitigation policies and communication strategies. Specifically, we aim to collect contributions from academia, industry (e.g. insurance) and government agencies (e.g. civil protection) that will help identify the latest developments and ways forward for increasing the resilience of communities at local, regional and national scales, and proposals for improving the interaction between different entities and sciences.
Contributions focusing on, but not limited to, novel developments and findings on the following topics are particularly encouraged:
- Physical and social vulnerability analysis and impact assessment of hydro-meteorological hazards
- Advances in the estimation of socioeconomic risk from hydro-meteorological hazards
- Characteristics of weather and precipitation patterns leading to high-impact events
- Relationship between weather and precipitation patterns and socio-economic impacts
- Socio-hydrological studies of the interplay between hydro-meteorological hazards and societies
- Hazard mitigation procedures
- Strategies for increasing public awareness, preparedness, and self-protective response
- Impact-based forecast, warning systems, and rapid damage assessment.
- Insurance and reinsurance applications

Orals: Wed, 17 Apr | Room B

Chairpersons: Giuliano Di Baldassarre, Efthymios Nikolopoulos
10:45–10:50
Dynamics and societal impacts
10:50–11:10
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EGU24-21687
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HS7.5
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solicited
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Highlight
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On-site presentation
Mariana Madruga de Brito, Jan Sodoge, Alexander Fekete, Michael Hagenlocher, Elco Koks, Christian Kuhlicke, Gabriele Messori, Marleen de Ruiter, Pia-Johanna Schweizer, and Philip J. Ward

Hydro-meteorological extremes, such as droughts and floods, often trigger a series of compound and cascading impacts due to interdependencies between coupled natural and social systems. However, studies typically only consider one impact and disaster event at a time, ignoring causal chains, feedback loops, and conditional dependencies between impacts. Analyses capturing these complex patterns across space and time are thus needed to inform effective adaptation planning. Here, we present a collection of methods that can be used for assessing the dynamics of the multi-sector compound and cascading impacts (CCI) of hydro-meteorological extremes. We discuss existing challenges, good practices, and potential ways forward. Rather than pursuing a single methodological approach, we advocate for methodological pluralism. We see complementary or even convergent roles for analyses based on quantitative (e.g. data-mining, systems modeling) and qualitative methods (e.g. mental models, qualitative storylines). The data-driven and knowledge-driven methods provided here can serve as a useful starting point for understanding the dynamics of both high-frequency CCI and low-likelihood but high-impact CCI.

How to cite: Madruga de Brito, M., Sodoge, J., Fekete, A., Hagenlocher, M., Koks, E., Kuhlicke, C., Messori, G., de Ruiter, M., Schweizer, P.-J., and Ward, P. J.: Understanding the dynamics of multi-sector impacts of hydro-meteorological extremes: a methods overview, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21687, https://doi.org/10.5194/egusphere-egu24-21687, 2024.

11:10–11:20
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EGU24-82
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HS7.5
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ECS
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On-site presentation
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Clare Lewis

Atmospherically generated coastal waves labelled as meteotsunami are known to cause destruction, injury and fatality due to their rapid onset and unexpected nature. These progressive shallow water waves with a period of 2 to 120 minutes tend to be initiated by sudden pressure changes (±1 mb over a few tens of minutes) and wind stress from moving atmospheric systems out on the open water. As these waves arrive at the shoreline they are amplified by localised resonances. Unlike other related coastal hazards such as tsunami, there exists no standardised means of quantifying this phenomenon which is crucial for understanding its impacts and to establish a shared language and framework for meteotsunami analysis and comparison.

In this study, we present a new 5-level Lewis Meteotsunami Intensity Index (LMTI) primarily trialled in the United Kingdom (UK) but designed for global applicability. A comprehensive dataset of meteotsunami events recorded in the UK were verified and applied to the index which yielded results that identified a predominant occurrence of Level 2 or moderate intensity meteotsunamis (69%), with distinct hotspots identified in Southwest England and Scotland. Further trial implementation and calibration of the LMTI in a global capacity revealed its adaptability to other meteotsunami prone regions facilitating the potential for further research into preparedness and hazard mitigation strategies.

How to cite: Lewis, C.: Proposal for a new meteotsunami intensity index., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-82, https://doi.org/10.5194/egusphere-egu24-82, 2024.

11:20–11:30
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EGU24-20767
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HS7.5
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On-site presentation
Sonia Quiroga, Virginia Hernanz, Cristina Suarez, and Jose Evelio Aguiño

Rich in biodiversity, Tumaco is a focal point for REDD+ projects that aim to combat deforestation and promote sustainable land use. Cacao farming, vital to the local economy, offers an opportunity to reconcile livelihoods and conservation. However, challenges remain in reconciling cacao and forest conservation. This study explores the benefits of sustainable cacao practices, such as agroforestry, for economic development and environmental conservation. It also looks at the challenges farmers face and the implications for the success of REDD+. Perceptions of climate change profoundly influence farmers' perspectives and behaviours in the context of REDD+ initiatives, shaping the sustainability and effectiveness of such efforts. Therefore, fostering a robust understanding of climate change among local farmers is critical to improving the integration of sustainable cacao production into REDD+ frameworks. This research aims to provide insights for policy makers and project implementers to advance both conservation and development goals in the Tumaco region, by addressing potential synergies and trade-offs between cacao production and REDD+ initiatives. The farmers' lack of knowledge is particularly worrying, not only for the fight against climate change, but also because if the cacao farmers of Tumaco do not see the incentives of carbon credits as a sustainable source of income, they will be forced to return to illegal crops, and the socio-environmental development of these communities will be compromised.

How to cite: Quiroga, S., Hernanz, V., Suarez, C., and Aguiño, J. E.: Evaluating the merit of Carbon Credits: Is there a lack of effectiveness in transitioning from direct Payments for Ecosystem Services to REDD+ community-based incentives?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20767, https://doi.org/10.5194/egusphere-egu24-20767, 2024.

11:30–11:40
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EGU24-5774
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HS7.5
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On-site presentation
Anna Mapelli, Andrea Libertino, Giulia Ercolani, Mirko D'Andrea, Nicola Testa, Matteo Darienzo, Simone Gabellani, Marco Massabò, Rafatou Fofana, Salifou Dene, Boukary Niampa, Maxime Teblekou, and Ramesh Tripathi and the Voltalarm member states national agencies

The Volta Basin, spanning six countries in West Africa, faces significant challenges from both floods and extreme precipitation. To address these challenges, the myDewetra-VOLTALARM system was developed as a collaborative transboundary early warning system (EWS) through the joint efforts of an international Consortium, composed by the Volta Basin Authority (VBA), the Global Water Partnership for West Africa (GWP-WA) and the World Meteorological Organization (WMO), and national institutions of the six riparian countries.  

myDewetra-VOLTALARM embraces an impact-based forecasting approach, focusing on the potential consequences of severe hydrological events on vulnerable communities. This is achieved through state-of-the-art hydro-meteorological modelling chain generating precipitation and discharge forecast with lead times of up to five days, coupled with impact assessment tools that translate these forecasts into actionable warnings based on real-time risk information for sectors like civil protection, agriculture and livelihoods, protected areas. By focusing on potential impacts,  myDewetra-VOLTALARM empowers stakeholders to make risk-informed decisions and implement timely mitigation actions, thereby reducing vulnerabilities and enhancing community resilience. The strength of myDewetra-VOLTALARM hinges on the collaboration, built-up through the implementation process, among the riparian countries, fostering data exchange and enabling a comprehensive understanding of hydrological dynamics across the entire basin. Harmonized risk assessments lead to consistent warning products and mitigation strategies, while the publication of the results on the open-source  myDewetra-VOLTALARM platform ensures transparency and accessibility for all stakeholders. 

A cornerstone of myDewetra-VOLTALARM's impact is the co-produced flood and heavy rainfall impact bulletin, issued jointly by national and regional authorities twice per week. This bulletin provides critical information, enriching and validating the model results with the expertise and local information/measurements of the national institutions, on which the Volta Basin Authority bases its advisories, tailored to specific locations and sectors. The Flood and Heavy Rainfall Impact Bulletin ensures a consistent flow of information at the basin scale and it integrates in the existing national procedures for early warning and civil protection, allowing all the stakeholders to stay informed and adapt their preparedness measures as the hydrometeorological situation evolves. 

myDewetra-VOLTALARM serves as a model for effective early warning systems in shared river basins. Its impact-based forecasting, transboundary cooperation, and co-produced Flood and Heavy Rainfall Impact Bulletin hold the potential to significantly reduce the impacts of floods and extreme precipitation, contributing to a more resilient and sustainable future for the Volta Basin communities.

How to cite: Mapelli, A., Libertino, A., Ercolani, G., D'Andrea, M., Testa, N., Darienzo, M., Gabellani, S., Massabò, M., Fofana, R., Dene, S., Niampa, B., Teblekou, M., and Tripathi, R. and the Voltalarm member states national agencies: myDewetra-VOLTALARM: a transboundary impact-based early warning system increasing resilience of Volta basin communities against hydrometeorological hazards, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5774, https://doi.org/10.5194/egusphere-egu24-5774, 2024.

11:40–11:50
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EGU24-5587
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HS7.5
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ECS
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On-site presentation
Chi Vuong Tai, Dongkyun Kim, Soohyun Kim, Yongchan Kim, Hyojeong Choi, and Jeonghun Lee

Vulnerability is regarded as a crucial element in disaster risk reduction, garnering increasing attention from researchers. However, these assessments typically conclude with the spatial representation and analysis of vulnerability index values, with very few attempts made on vulnerability validation. This study has employed Principal Component Analysis (PCA) algorithm for the entire 38 selected socio-economic features, resulting in 9 principal components (or factors) to estimate Socio-Economic Vulnerability Index (SEVI). The results reveal consistent vulnerability levels in over half of the dongs (administrative units), compared with SEVI estimated from a subjective weighting scheme based on expert experience. Meanwhile, the remaining dongs exhibit a change in only one level of vulnerability. SEVI values and ranks from PCA were subsequently internally validated through global uncertainty and sensitivity analyses using Monte Carlo method. The vulnerability scores of all input features were randomly generated based on their fitted probability distribution functions, serving as input parameters for 39,936 Monte Carlo simulations. The median statistic was employed to evaluate the vulnerability uncertainty based on both bias of estimated SEVI values and ranks in comparison with simulated data. The findings from this analysis revealed that medium-low and medium vulnerability levels tend to be underestimated, while medium-high and high levels primarily witness an overestimation tendency. The bias in SEVI ranks was further employed to assess the vulnerability uncertainty. In the sensitivity test, a tornado diagram was created to illustrate the explanation of each feature to the overall SEVI variability. The results indicate that the feature with highest explanation of SEVI variability is the number of families with only children and a mother, accounting for more than 5%. The methodology employed in this study is applicable to areas with limited social and economic data sources. Based on our findings, we suggest that the areas with low bias on SEVI values or ranks are reliable for developing disaster risk mitigation strategies, while other areas require further consideration. Additionally, the results from the sensitivity test provide valuable support for future research when selecting input features for socio-economic vulnerability assessment.

Acknowledgement:

This study was supported by: (1) The National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2022R1A4A3032838) (50 % grant); (2) Korea Environment Industry & Technology Institute (KEITI) through R&D Program for Innovative Flood Protection Technologies against Climate Crisis Project, funded by Korea Ministry of Environment (MOE) (RS-2023-00218873) (50 % grant).

How to cite: Vuong Tai, C., Kim, D., Kim, S., Kim, Y., Choi, H., and Lee, J.: Socio-Economic Vulnerability assessment and validation in Seoul, South Korea , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5587, https://doi.org/10.5194/egusphere-egu24-5587, 2024.

11:50–12:00
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EGU24-8291
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HS7.5
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ECS
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On-site presentation
Tiangang Yuan, Amos P K Tai, and Jin Wu

Since the 1950s, global irrigated area has expanded dramatically, with complex effects on regional climate worldwide. The North China Plain (NCP) is among the most intensively irrigated regions in the world, but the effects of historical irrigation expansion on climate extremes over multi-decadal timescale are largely uncertain. Combining statistical methods with model simulations, we found that NCP experienced a decreasing trend of 0.2–0.25 ℃ decade−1 (p < 0.1) in daily maximum temperature (Tmax) during May-June of 1961–2000 along with irrigation expansion, which is distinct from other regions experiencing strong warming such as most of western China. The cooling effect on Tmax is 0.092 ℃ decade−1 (p < 0.01), relatively lower than that in California’s Central Valley but comparable to the trend in Northwest China and larger than the trend in Tibetan Plateau. The correlation coefficients between irrigation expansion and temperature change from 1960 to 2000 for Tmax and mean air temperature (Tmean) are –0.58 and –0.33 (p < 0.01), respectively, suggesting the ability of irrigation to alleviate regional warming and temperature extremes. Such effect varies over time, continuously strengthening from 1961 to 1980 because of intensive irrigation expansion, but then remaining relatively unchanged or weakening during 1980–2005 with moderate expansion. After 2005, the cooling effect is not detectable, which implies that it is completely canceled out by other forcings such as greenhouse gas warming, compensation of urban area expansion, small irrigation expansion rate and decline in irrigation water use. Despite that, irrigation is still able to reduce the number of extreme heat days after 1980. Compared with other factors, we found that irrigation expansion is the second most important contributor (27%) to the decrease in Tmax during the study period, after aerosol pollution (54%). This work emphasizes the ability of irrigation expansion to adapt agriculture to climate change over the past decades, and highlights the need for sustainable irrigation expansion in the future.

How to cite: Yuan, T., Tai, A. P. K., and Wu, J.: Irrigation expansion in North China Plain has historically decelerated regional warming and mitigated temperature extremes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8291, https://doi.org/10.5194/egusphere-egu24-8291, 2024.

12:00–12:10
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EGU24-9313
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HS7.5
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ECS
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On-site presentation
Shibo Cui and Jianshi Zhao

Flood insurance is an important non-structural measure for flood risk management. However, a significant protection gap in flood insurance exists in many countries and the high cost of flood insurance is a primary reason. Reducing the flood insurance costs for both policyholders and insurance companies is crucial for the effective implementation of flood insurance. Here, we use portfolio theory to derive fundamental principles of reducing overall insurance cost including premiums and risk reserves through geographic risk complementarity. Furthermore, we propose a reasonable premiums distribution approach among different risk agents to analyze the effect of geographic risk complementarity on individual cost, based on the cooperative game theory. We applied our method in China, which has a large territory but lacks a national flood insurance program. We show there is a low correlation of flood losses across most provinces in China. Compared to the separate insurance in each province, national flood insurance can reduce total premiums by 14.5% and total risk reserves by 61.0%. The regions with highest proportion of premium reduction are the middle and lower Yellow River reaches, which have a lower flood risk correlation with the portfolios of other regions. In conclusion, the geographic complementarity in flood risk has a significant effect on reducing flood insurance cost and the degree of cost reduction depends on the flood risk correlation among different entities. We recommend that China should utilize the geographic risk complementarity to implement a national-level flood insurance program. The method proposed can also provide references for catastrophe insurances around the world.

How to cite: Cui, S. and Zhao, J.: The Effects of Geographic Risk Complementarity on Reducing Flood Insurance Costs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9313, https://doi.org/10.5194/egusphere-egu24-9313, 2024.

12:10–12:20
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EGU24-11090
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HS7.5
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ECS
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On-site presentation
Rhoda Odongo, Hans De Moel, Marthe Wens, Natalia Limones, Dim Coumou, and Anne Van Loon

Over the past decade, the Horn of Africa (HoA) has been plagued by recurrent drought events that have had devastating impacts on the population. The frequency, duration and severity of these droughts are expected to increase in the wake of global warming, leading to higher losses and damages if the vulnerability of the population is not reduced. Monitoring and early warning systems for droughts are based on various drought hazard indicators. However, assessments of how these indicators are linked to impacts are rare. For adequate drought management, it is essential to understand and characterise the drivers of drought impacts, especially in the HoA, where most studies focus either on meteorological droughts, agricultural droughts or the propagation of droughts through the hydrological cycle, without considering the relationship between hazard and impact. Drought hazard indices alone cannot capture the vulnerability of the system. In this study, we identify meaningful indices for the occurrence of region- and sector-specific impacts. We assess the effectiveness of socio-economic clustering in categorising counties based on common characteristics and their correlation with historical drought impacts (malnutrition, milk production and trekking distances to water sources). Using Random Forest (RF) and Spearman correlation analyses, we examine the link between drought indices (Standardised Precipitation Index, Standardised Precipitation Evapotranspiration Index, Standardised Soil Moisture Index, Standardised Streamflow Index and Vegetation Condition Index) with different accumulation periods and the impact data. We find that clustering regions based on vulnerability proxies significantly improves the hazard-impact relationship, emphasising the importance of considering vulnerability factors in drought risk assessment. Our results indicate an impact-specific relationship that is strongly influenced by the vulnerability of the region. In particular, household and livestock distance to water is most strongly associated with medium- to long-term precipitation-based indices (2-10 months), while milk production can be associated with a variety of indices with different accumulation periods (5-24 months), and malnutrition is correlated with precipitation- and streamflow-based indices (5-24 months). Household and livestock distance to water is well modelled by clusters reflecting low access to improved sanitation and safe water sources, high poverty, aridity and gender disparities. Malnutrition was well modelled by clusters related to aridity, average precipitation, food consumption score, access to water sources, improved sanitation and poverty levels. The type of clustering used in modelling the impact of drought on milk production does not have a major impact on the performance of the models. We then apply this relationship to hindcast drought indices to obtain impact data on individual counties for periods when no impact monitoring was done yet. With that information we estimate the associated risk under specific climatic conditions. By recognising the drivers and vulnerability factors that influence the sensitivity of counties to drought, communities can better prepare and mitigate the impacts of drought.

How to cite: Odongo, R., De Moel, H., Wens, M., Limones, N., Coumou, D., and Van Loon, A.: From indices to impacts: Understanding the dynamics of drought impacts through socio-economic clustering, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11090, https://doi.org/10.5194/egusphere-egu24-11090, 2024.

12:20–12:30
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EGU24-677
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HS7.5
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ECS
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Highlight
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On-site presentation
Ni Li, Wim Thiery, Jakob Zscheischler, Gabriele Messori, Liane Guillou, Joakim Nivre, Olof Görnerup, Seppe Lampe, Clare Flynn, Mariana Madruga de Brito, and Aglae Jezequel

Storms, heat waves, wildfires, floods, and other extreme weather climate-related disasters pose a significant threat to society and ecosystems, which in many cases is being aggravated by climate change. Understanding and quantifying the impacts of extreme weather climate events is thus a crucial scientific and societal challenge. Disaster databases are extremely useful for establishing the link between climate events and socio-economic impacts. However, publicly available data on impacts is generally scarce. Apart from existing open disaster databases such as EM-DAT, robust data on the impacts of climate extremes can also be found in textual documents, such as newspapers, reports and Wikipedia articles. Here we present a new climate impact database that has been built based on multiple public textual entries using a pipeline of data cleaning, key information extraction and validation. In particular, we constructed the database by using the state-of-the-art generative artificial intelligence language models GPT4, Llama2 and other advanced natural language processing techniques. We note that our dataset contains more records in the early time period of 1900-1960 and in specific areas such as than the benchmark database EM-DAT. Our research highlights the opportunities of natural language processing to collect data on climate impacts, which can complement existing open impact datasets to provide a more robust information on the impacts of weather and climate events.

How to cite: Li, N., Thiery, W., Zscheischler, J., Messori, G., Guillou, L., Nivre, J., Görnerup, O., Lampe, S., Flynn, C., Madruga de Brito, M., and Jezequel, A.: A new climate impact database using generative AI, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-677, https://doi.org/10.5194/egusphere-egu24-677, 2024.

Lunch break
Chairpersons: Elena Cristiano, Efthymios Nikolopoulos
14:00–14:05
Precipitation extremes
14:05–14:15
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EGU24-3170
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HS7.5
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ECS
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On-site presentation
Yufan Chen, Shuyu Zhang, Deliang Chen, and Junguo Liu

In recent decades, the Central Plains Urban Agglomeration of China (CPUA) has faced recurring extreme precipitation events (EPEs), causing severe flood disasters, endangering residents, and inducing significant property losses. This study examines the spatiotemporal patterns of summer EPEs in the CPUA from 1961 to 2022. The Hybrid Single-Particle Lagrangian Integrated Trajectory model was used to trace the water vapor trajectories associated with these events and the atmospheric circulations linked to diverse moisture transports were identified. The findings reveal an overall increase in both the intensity and frequency of summer EPEs, particularly intensifying over urban areas while displaying more frequent yet weaker precipitation in mountainous regions. Moisture contributing to these events originates from sources including Eurasia, the northern and southern Western North Pacific, as well as the Bay of Bengal and South China Sea. Notably, contributions from Eurasia and the Northern Western North Pacific have increased, whereas those from the Bay of Bengal and the South China Sea have decreased. Events fueled by Western North Pacific moisture show intensified impacts on urban areas, driven by anomalous anticyclonic patterns and the formation of the Huang-Huai cyclone, inducing vigorous convective activity over the CPUA. The proliferation of the Western North Pacific Subtropical High facilitates warm air transport, converging with colder air from inland areas, resulting in extreme precipitation.

How to cite: Chen, Y., Zhang, S., Chen, D., and Liu, J.: Influences of moisture transport on changes in extreme precipitation in Central Plains Urban Agglomeration, China , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3170, https://doi.org/10.5194/egusphere-egu24-3170, 2024.

14:15–14:25
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EGU24-3951
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HS7.5
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ECS
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Virtual presentation
Tomás Gaspar, Ricardo M. Trigo, Alexandre M. Ramos, Akash Singh Raghuvanshi, Ana Russo, Pedro M.M. Soares, Tiago Ferreira, and Ankit Agarwal

The Indian subcontinent is characterized by a pronounced summer monsoon season with substantial rainfall from June to September and a less intense autumn monsoon, albeit both posing major challenges to the densely populated regions through flash floods and landslides. During monsoons, different regions of India are affected by extreme precipitation events with distinct durations and triggered by several mechanisms. Here, considering 10 different regions of India characterized by different climatic regimes, we apply an objective ranking of extreme precipitation events, across various time scales, ranging from 1 to 10 days, making use of a high-resolution daily precipitation dataset covering the entire Indian territory from 1951 to 2022. The results confirm that the method accurately detects and ranks the most extreme precipitation events in each region, providing information on the daily evolution of the magnitude (and spatial extent affected) of high precipitation values in each region. Moreover, results show that top rank events can be associated with different types of storms affecting the four main coastal regions of India. In particular, some top rank events can be critically linked to long duration events (e.g., 10 days), which can be missed in ranks for shorter duration (e.g., 1-3 days) periods, thus stressing the need to employ multi-day precipitation extremes ranking. Finally, an in-depth analysis of the large-scale atmospheric circulation and moisture transport is presented for the top 10-day events affecting four coastal regions of India. Overall, we are confident that our findings are valuable in advancing disaster risk reduction strategies, optimizing water resource management practices, and formulating climate change adaptation strategies specifically tailored for the Indian subcontinent.

 

R.M.T., A.R., S.P. and A.T.M. thank Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020). A.R. and R.M.T. thank also FCT (https://doi.org/10.54499/2022.09185.PTDC, http://doi.org/10.54499/JPIOCEANS/0001/2019, https://doi.org/10.54499/DRI/India/0098/2020). A.R. was supported by FCT through https://doi.org/10.54499/2022.01167.CEECIND/CP1722/CT0006.

 

How to cite: Gaspar, T., M. Trigo, R., M. Ramos, A., Singh Raghuvanshi, A., Russo, A., M.M. Soares, P., Ferreira, T., and Agarwal, A.: Multi-day precipitation extremes ranking and their association with atmospheric moisture fluxes over India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3951, https://doi.org/10.5194/egusphere-egu24-3951, 2024.

14:25–14:35
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EGU24-8564
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HS7.5
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On-site presentation
Hamidreza Mosaffa and Luca Brocca

Effective disaster prevention necessitates the production of high-resolution flood susceptibility maps (FSM) that accurately identify potential flood-prone areas. Conventional FSMs, however, provide static representations that overlook the inherent dynamicity of flood susceptibility, which is influenced by temporal variations, precipitation intensities, and other factors. Additionally, traditional FSMs often lack the high-resolution climate data required for precise risk assessment. To address these limitations, we propose a novel dynamic FSM approach that incorporates temporal variations and high-resolution climate data.

Our approach employs the Random Forest machine learning algorithm, trained on a comprehensive dataset of flooded and non-flooded areas (Global Flood Database v1). The algorithm considers seven critical factors influencing flooding events: elevation, slope, land cover, proximity to rivers, drainage density, soil moisture, and precipitation. This approach enables the generation of high-resolution (1 km) dynamic FSMs for the Mediterranean region, under varying seasonal conditions, precipitation intensities, and post-drought scenarios.

To assess and compare the model's performance, we employed both training and testing datasets, conducting evaluations using various metrics. The study results demonstrate the superior performance of the Random Forest model, establishing its efficacy as a robust tool for mapping dynamic flood susceptibility. The accuracy and reliability of the results obtained through this approach offer crucial insights for mitigating flood-related risks and enhancing disaster management strategies. This study is an integral part of the Open-Earth-Monitor Cyberinfrastructure (OEMC) project. As our next step, we aim to expand the application of our dynamic flood susceptibility mapping methodology to cover the European region.

How to cite: Mosaffa, H. and Brocca, L.: High-Resolution Dynamic Flood Susceptibility Mapping Across the Mediterranean Region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8564, https://doi.org/10.5194/egusphere-egu24-8564, 2024.

14:35–14:45
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EGU24-10245
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HS7.5
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ECS
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On-site presentation
Matteo Pesce, Eleonora Dallan, Francesco Marra, and Marco Borga

Time-dependent precipitation frequency analyses were often hampered by the availability of relatively short data records, which result in large uncertainty in the estimation of extremes. The recently developed non-asymptotic statistical methods, based on fitting ordinary events rather than extreme events only, represent a potential solution to the problem of data scarcity and are finding wide application in literature under assumptions of stationarity. Recent studies investigated the use of non-asymptotic methods under non-stationary conditions (e.g., Vidrio-Sahagún and He, 2022) and advocated their use over other methods for non-stationary frequency analysis of extreme precipitation. In this study we formalize a non-stationary time-dependent approach for the statistical analysis of multi-duration precipitation extremes using simplified metastatistical extreme value (SMEV) approach. The study focuses on a catchment in the Eastern Italian Alps, where trends in extreme precipitation where reported (Dallan et al., 2022) and which was impacted by the exceptional Vaia event in 2018. We provide an estimation of extreme return levels of precipitation in six stations in the neighborhood of the catchment and compare them with precipitation maxima observed during Vaia storm. The results show that using a non-stationary left-censored Weibull distribution, with both scale and shape parameters linearly dependent on time, allows to properly describe the observed trends of intense precipitation for different durations. Our results suggest that the probability of observing events like Vaia increased over the past decades, leading to the need for updating local adaptation measures.

 

References:

Dallan, E., Borga, M., Zaramella, M., & Marra, F. (2022). Enhanced summer convection explains observed trends in extreme subdaily precipitation in the eastern Italian Alps. Geophysical Research Letters49(5), e2021GL096727.

Vidrio-Sahagún, C. T., & He, J. (2022). Hydrological frequency analysis under nonstationarity using the Metastatistical approach and its simplified version. Advances in Water Resources166, 104244.

How to cite: Pesce, M., Dallan, E., Marra, F., and Borga, M.: A time-dependent non-asymptotic statistical analysis of extreme precipitation events, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10245, https://doi.org/10.5194/egusphere-egu24-10245, 2024.

14:45–14:55
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EGU24-21428
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HS7.5
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On-site presentation
Characterization of Frequency and Intensity Rainfall Distributions and their Relationship with Physical Drivers : Application to French Polynesia
(withdrawn)
Lydie Sichoix, Lionel Benoit, Tonin Bechon, and Garry Terii
14:55–15:05
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EGU24-10297
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HS7.5
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ECS
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On-site presentation
Petr Vohnicky, Eleonora Dallan, Francesco Marra, Giorgia Fosser, Matteo Pesce, and Marco Borga

In mountainous regions, temperature determines the state of precipitation (liquid or solid) and in turn significantly affects runoff formation and flood generation. Projected temperature increase due to global warming may therefore affect the rainfall/precipitation ratio during heavy storms, hence intensifying the flood regime. This study aims to assess the projected variations in liquid/solid fraction of precipitation during heavy precipitation events in the upper Adige River, Italy (Eastern Italian Alps). The study utilizes simulations from an ensemble of convection-permitting climate models (CPM), which are suitable to the task given their ability to explicitly represent deep convection and to resolve the mountainous topography. The CPM data provided by the CORDEX-FPS Convection project at 1-hour temporal and remapped to 3 km spatial resolution, cover historical and far-future (2090-2099) time periods under the extreme climate change scenario (RCP8.5). Observational data from the densely instrumented river system are utilized for bias evaluation. Lastly, the Simplified Metastatistical Extreme Value (SMEV) approach, known for the reduced uncertainty compared to conventional approaches, is incorporated for frequency analysis. This method proves particularly useful for analyzing extremes from short time periods, such as those in CPM simulations. The projected changes in both sub-daily mean areal precipitation and liquid rainfall return levels are examined at various spatial scales based on the sub-basins total area. Our preliminary results underscore the significance of leveraging advanced statistical techniques and high-resolution climate models to address emerging challenges in hydrology and climate science. The climate-induced shifts in return period of liquid precipitation identified in this study are expected to have implications for both water resources management and adaptation measures.

How to cite: Vohnicky, P., Dallan, E., Marra, F., Fosser, G., Pesce, M., and Borga, M.: Projected amplification of rainfall extremes due to warming-induced reduction of snow fraction: an assessment based on convection-permitting simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10297, https://doi.org/10.5194/egusphere-egu24-10297, 2024.

15:05–15:15
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EGU24-18244
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HS7.5
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ECS
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On-site presentation
Stergios Emmanouil, Andreas Langousis, Elizabeth Perry, Luke Madaus, Joshua Hacker, and Emmanouil N. Anagnostou

Climate adaptation strategies and vulnerability assessments over coastal areas require proper modeling of the interplay and nonstationary nature of the physical processes involved in compound flooding. As a result of the reported upward trajectories of rainfall intensity over the Contiguous United States, flood risk estimates are also expected to vary. However, given the systematic and random inconsistencies of traditional extreme rainfall estimation approaches and the increased uncertainty surrounding climate model projections, the effects of climate change on the estimation of flood risk from compound hazards remains an open question. In this effort we aim to: (a) combine the observed rainfall intensity trends from the past 40 years (i.e., from 1979 to 2020; see also Emmanouil et al., 2022) across various scales of temporal averaging, with storm surge and antecedent streamflow conditions, to estimate how flood inundation levels evolve, and (b) assess the effects of those trends on flood risk estimation within areas affected by compound hydrological events. In doing so, we use hydrodynamic simulations of reported flood occurrences over the Greater Boston area (MA, United States) for a period of 20 years (i.e., from 2000 to 2019), along with the parametric modeling scheme proposed by Emmanouil et al. (2023). The latter has been shown to properly weight and link the exceedance probabilities of the main flood-driving mechanisms to the return periods of the maximum inundation levels, thus providing a sufficient depiction of the conditions over the studied domain and allowing for estimation beyond the range covered by the available simulations. Assuming that the dependence structure of the driving mechanisms remains time-invariant, our findings aim to enhance the understanding of how flood risk from compound hazards has been affected by extreme rainfall trends induced by the changing climatic conditions and, therefore, support decision-making on the design and protection of critical infrastructure.

References

Emmanouil, S., Langousis, A., Nikolopoulos, E. I., & Anagnostou, E. N. (2022). The Spatiotemporal Evolution of Rainfall Extremes in a Changing Climate: A CONUS‐Wide Assessment Based on Multifractal Scaling Arguments. Earth’s Future, 10(3). https://doi.org/10.1029/2021ef002539

Emmanouil, S., Langousis, A., Perry, E., Madaus, L., Hacker, J., and Emmanouil, E.N. (2023) Decomposing the effects of compound mechanisms on flood risk estimation for urban environments: A case study over Greater Boston, UrbanRain23, 12th International Workshop on Precipitation in Urban Areas, Pontresina, Switzerland, 29 November – 2 December 2023.

How to cite: Emmanouil, S., Langousis, A., Perry, E., Madaus, L., Hacker, J., and Anagnostou, E. N.: The effects of extreme rainfall trends on compound flood risk: A case study over Greater Boston, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18244, https://doi.org/10.5194/egusphere-egu24-18244, 2024.

15:15–15:25
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EGU24-7026
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HS7.5
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ECS
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Virtual presentation
Chi-June Jung, Radiant Rong-Guang Hsiu, Yu-Cheng Kao, Mon-Liang Chiang, Wen-Bin Hung, Jing-Ting Wang, and Ben Jong-Dao Jou

The most challenging weather phenomenon for disaster response in Taipei City is localized short-duration heavy rainfall. The capacity of each administrative district to withstand rainfall intensity varies, leading to incidents of flooding even when the rainfall falls short of the designed protection standard of 78.8 mm/h for drainage systems. To enhance disaster response, the Taipei City Fire Department conducts investigations and reports based on rainfall conditions. By integrating the intelligence and reporting system and raising the dispatching standard from 20 to 40 mm/h, the "Heavy Rainfall Response Process Improvement" project has successfully reduced response operation time and alleviated service burdens, advocating for adopting higher standards.

This study explores the correlation between intense rainfall and disaster occurrences, examining thunderstorm events that caused significant flooding in over three administrative districts. The study compares the earliest reported flooding time in each district with the corresponding rainfall, revealing that several districts experienced flooding with less than 60 mm/h of rainfall at the onset, indicating heightened vulnerability. Additionally, the study delves into the relationship between rainfall patterns and disaster potentials. When it accumulates 40 mm of rainfall within 30 minutes, there is a 63% chance of reaching 60 mm accumulation in the following 10 to 20 minutes. This analysis underscores the potential application of cumulative rainfall within the first 30 minutes for predicting subsequent rainfall trends and issuing disaster warnings.

How to cite: Jung, C.-J., Hsiu, R. R.-G., Kao, Y.-C., Chiang, M.-L., Hung, W.-B., Wang, J.-T., and Jou, B. J.-D.: Characteristics of Disaster-causing Heavy Rainfall in Taipei City and Its Application, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7026, https://doi.org/10.5194/egusphere-egu24-7026, 2024.

15:25–15:35
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EGU24-9257
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HS7.5
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ECS
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Virtual presentation
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M. Josefina Pierrestegui, Miguel A. Lovino, Gabriela V. Müller, and Omar V. Müller

Extreme hydrometeorological events (EHE) negatively affect ecosystems, human settlements, food production, water resources, and public health worldwide. In southeastern South America (SESA), the frequency and intensity of temperature and precipitation extremes have increased over recent decades. SESA is particularly vulnerable to EHE due to its high population rates and an economy heavily reliant on agricultural activities; therefore, advancing towards a climate-resilient development is a key goal for the region. This study presents a multi-hazard analysis of EHE and their changes over SESA.

Our study assesses the frequency, duration, and intensity of short- and long-term EHE for the 1961-1990 and 1991-2020 periods. ERA5 precipitation, soil moisture, and temperature data at multiple time scales (from daily to monthly) are used, with a spatial resolution of 0.25°×0.25° latitude-longitude grid. Long-term EHE are studied using nonparametric standardized indices—specifically, the Standardized Precipitation Index (SPI) and Standardized Soil Moisture Index (SSI)—at 3- and 18-month timescales to analyze agricultural and hydrological impacts. Short-term EHE are characterized by heavy precipitation, flash droughts, and heat waves events to analyze immediate impacts in urban areas and in agriculture. Individual hazard components are derived by multiplying the frequency, duration, and intensity of the identified events, followed by a rescaling to a 0-1 range using range normalization (with minimum and maximum values). The long-term and short-term EHE hazard indices are formulated by aggregating the rescaled individual hazard components and dividing by the total number of components. Changes in observed EHE hazard components are determined by comparing the EHE hazard indices for the 1991-2020 and 1961-1990 periods.

Our findings underscore significant precipitation excess hazard, mainly concentrated in agriculture-prone areas spanning central-eastern Argentina, Uruguay, and southern Brazil across both 3- and 18-month timescales. In contrast, precipitation deficit hazard predominantly manifests in the western regions of SESA. Regarding short-term EHE, the highest hazard magnitudes are observed in northeastern Argentina, southern Brazil, and southeastern Paraguay. Heat waves occur frequently in the region, with hazardous intensities over the northern part of SESA. Additionally, heavy precipitation events constitute a significant hazard component for urban and rural infrastructure primarily in northeastern Argentina. Flash droughts also affect agriculture-prone areas, particularly with high intensity in southern Brazil, northeastern Argentina, and Uruguay.

Our results reveal that the most significant changes are observed in short-term hazard indices in northeastern SESA. This region, which includes eastern Paraguay, northeastern Argentina, southern Brazil, and Uruguay, has experienced an increase in heat wave hazard, primarily due to a significant rise in the frequency of heat waves. Hazards associated with heavy precipitation and flash drought events have also increased, with a rise in their frequency and duration observed mainly over northeastern Argentina and southern Brazil. In contrast, long-term hazard indices exhibit non-uniform patterns of change. Our findings suggest that weather-related hazards have undergone changes over the last decades. We expect that these findings provide valuable insights to enhance SESA's hydroclimatic risk management systems by identifying areas susceptible to both short- and long-term hazards.

How to cite: Pierrestegui, M. J., Lovino, M. A., Müller, G. V., and Müller, O. V.: Multi-hazard assessment of long- and short-term extreme hydrometeorological events in southeastern South America, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9257, https://doi.org/10.5194/egusphere-egu24-9257, 2024.

15:35–15:45
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EGU24-17412
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HS7.5
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Highlight
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On-site presentation
Sergiy Vorogushyn, Li Han, Heiko Apel, Viet Dung Nguyen, Björn Guse, Xiaoxiang Guan, Oldrich Rakovec, Husain Najafi, Luis Samaniego, and Bruno Merz

After a flood disaster, the question often arises: “What if the event had gone differently?” For example, what would be the effects of a flood if the path of a pressure system and thus the precipitation field had occurred taken a different trajectory? The analysis of such alternative scenarios of precipitation footprints (“counterfactuals”) is a valuable approach for flood risk management in addition to classical extreme value statistical analyses. It helps to think about and prepare for extremes that have not occurred in this way, but which appear quite plausible.

Here, we analyze the spatial alternative scenarios of the deadly July 2021 flood in the Ahr Valley, Germany. The hydrological model mHM is driven with precipitation fields systematically shifted in space. The resulting runoff is transformed into inundation and flood impact indicators using the high-resolution hydrodynamic model RIM2D.

The results show that even a slight shift of the precipitation field by 15-20 km, which does not seem implausible due to orographic conditions, causes an increase in peak flows at the Altenahr gauge of over 30% and at individual tributaries of up to 160%. Also, significantly larger flood volumes can be expected due to precipitation shifts. This results in markable differences in inundation depths in a number of areas along the Ahr river valley. The presented results should encourage critical thinking about precautionary measures and risk management plans for extreme and unprecedented events.

How to cite: Vorogushyn, S., Han, L., Apel, H., Nguyen, V. D., Guse, B., Guan, X., Rakovec, O., Najafi, H., Samaniego, L., and Merz, B.: It could have come worse –  an analysis of spatial counterfactual scenarios for the July 2021 flood in the Ahr Valley, Germany, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17412, https://doi.org/10.5194/egusphere-egu24-17412, 2024.

Orals: Thu, 18 Apr | Room B

Chairpersons: Francesco Marra, Elena Cristiano
16:15–16:20
Hydrological extremes: Floods and landslides
16:20–16:30
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EGU24-669
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HS7.5
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ECS
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On-site presentation
Clemence Idukunda, Caroline Michellier, Emmanuel Twarabamenye, Florence De Longueville, and Sabine Henry

North-Western Rwanda's hilly and mountainous topography, high elevation, frequent torrential rainfall, and high population density render it highly susceptible to landslides and floods. A comprehensive understanding of community vulnerability to these hazards is crucial for effective risk assessment and mitigation strategies. To address data scarcity in the region, this study is based on a household survey approach that incorporates hazard-specific variables to compare vulnerability across three hazard categories: landslides, floods, and a combination of both. The survey encompasses 904 households across 50 cells (local administrative units), purposively selected according to hazard susceptibility distribution. Principal Component Analysis (PCA) was applied to derive a contextualized Social Vulnerability Index (SoVI). Five principal components accounting for 73.2% of the variance were identified. The first component, contributing 23.4%, highlights the vulnerability associated with unplanned settlements and low income. The second component, representing 19.5% of the variance, emphasizes demographic and social factors. The third component (12.6% of the variance) points to the vulnerability of households solely reliant on agriculture for their income. The fourth component (9% variance) is associated with land ownership, with households lacking land assets experiencing lower vulnerability. The fifth component (8.7% variance) underlines the relevance of household structure variables, indicating the high vulnerability of single-person households. SoVI scores classified 19 cells in the very high or high vulnerability category, predominantly those prone to landslides. These highly vulnerable cells are concentrated in the Northern Province, emphasizing the need to prioritize interventions in this region, such as effective land use planning and livelihood improvement strategies. This study provides a comprehensive vulnerability assessment and valuable insights for prioritizing interventions. The inclusion of hazard-specific variables and a comparative vulnerability approach across areas susceptible to landslides, floods, and both hazard types enhances the specificity and applicability of the findings. These insights are invaluable for local policymakers and disaster prevention and management authorities, enabling them to develop context-specific strategies to improve community resilience and reduce vulnerability to natural hazards.

Keywords: Community Vulnerability, Landslides, Floods, Noth-Western Rwanda, Social Vulnerability Index

How to cite: Idukunda, C., Michellier, C., Twarabamenye, E., De Longueville, F., and Henry, S.: Assessing Local Community Vulnerability to Landslides and Floods: A Household Survey Approach in North-Western Rwanda , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-669, https://doi.org/10.5194/egusphere-egu24-669, 2024.

16:30–16:40
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EGU24-11733
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HS7.5
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ECS
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On-site presentation
Clara Hohmann, Christina Maus, Ahmad Awad, Dörte Ziegler, Hanna Leberke, Maram Al Naimat, Wafaa Abuhammour, and Katja Brinkmann

Jordan is one of the water scarcest regions worldwide, but regularly hit by severe flash floods caused by heavy rainfall events. Such events will likely intensify in future and increase flash flood damages, especially in rapidly developing urban areas. Therefore, flood vulnerability analysis and assessment are urgently needed to improve urban risk management and to protect the local population. To date, however, such analyses in Jordan, as in many other MENA regions, have been hampered by the lack of spatial and temporal high-resolution climate, economic and social data. Furthermore, conducted hydrological analyses have only considered physical parameters in assessing flash flood risk.

Our aim is to investigate the vulnerability in a data scarce urban region and find solutions to overcome the challenges by combining different disciplinary perspectives with local knowledge. Jordan’s capital, Amman was selected as study region, which is a prime example of a rapidly growing city in the MENA region.

To analyze and assess the vulnerability of people, infrastructure and ecosystem to flash flood events in a watershed of Amman, a mixed-method approach was applied within a transdisciplinary research project called CapTain Rain (Capture and retain heavy rainfall in Jordan). To gain insights into flash flood risks, we explore the vulnerability dimensions exposure and sensitivity from the hydrological, hydraulic and social perspectives, and the adaptive capacity of the local population. For the assessment of each vulnerability dimension, different physical, social and ecological indicators were used. Several indicators, such as damage potential, were adapted to local conditions based on focus group discussions with Jordanian stakeholders.

The vulnerability dimensions exposure, sensitivity and adaptive capacity were assessed for the current situation and several possible scenarios with changing future conditions in climate (intensity of rainfall) and land cover (urbanization trends). As one sensitivity indicator the damage potential was analyzed. The resulting damage potential map shows e.g. the locations of critical infrastructure, and also includes the word heritage sites, which were identified as vulnerable infrastructure of high importance by the Jordanian stakeholders. Regarding future scenarios our first hydrological and hydraulic modelling results show that a moderate climate change of 20% more intense rainfall has a stronger influence compared to land cover changes. Land cover changes with more sealed surfaces have little influence on the runoff caused by the low infiltration capacity of soils in the area according to the available data.

Through interdisciplinary collaboration and local stakeholder engagement, this work demonstrates a noteworthy strategy to addressing flash flood risks in situations where data is limited. The results of the integrated scenario analysis and vulnerability assessment serve as a decision-support tool for urban planning.

How to cite: Hohmann, C., Maus, C., Awad, A., Ziegler, D., Leberke, H., Al Naimat, M., Abuhammour, W., and Brinkmann, K.: Exploring vulnerability to flash floods in a water-scarce MENA city: Challenges and possible solutions , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11733, https://doi.org/10.5194/egusphere-egu24-11733, 2024.

16:40–16:50
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EGU24-14198
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HS7.5
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ECS
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On-site presentation
Kai-Lun Wei, Kuo-Wei Liao, Guan-Yu Lin, Poshuan Lin, and Tsungyu Hsieh

Taiwan is located at the boundary between the Philippine Sea Plate and the Eurasian Plate, characterized by steep terrain and high river gradients. Combined with frequent events such as typhoons leading to substantial rainfall, this has resulted in disasters like debris flows. Several available tools such as HEC-RAS two-dimensional hydraulic, SRH-2D, FLO-2D and FLOW-3D are used to analyze the area of flooding and the impact of debris flow in the watershed. The simulation results are compared with historical disaster data to validate the feasibility of model. Furthermore, the results are used to evaluate the suitability of current government-designated evacuation locations and routes.

Among several analysis tools, the debris flow modeling in HEC-RAS two-dimensional hydraulic is considered as the best platform to analyze debris risk. The results show the sections of evacuation routes on the left bank of the downstream area near the estuary pass through the debris flow impact area. However, there is no suitable evacuation facility in the vicinity. Therefore, during warning issuance, residents need to be cautious and evacuate promptly. On the other hand, collaboration with government authorities can be pursued to establish new shelters or activity centers nearby, serving as alternative evacuation sites.

How to cite: Wei, K.-L., Liao, K.-W., Lin, G.-Y., Lin, P., and Hsieh, T.: Assessing the Influenced Zone of Debris Flow Using Numerical Simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14198, https://doi.org/10.5194/egusphere-egu24-14198, 2024.

16:50–17:00
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EGU24-867
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HS7.5
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ECS
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On-site presentation
Katelyn Johnson and Admire Nyamwanza

Climate change, an increasing urban population, and poor urban planning have increased flood-risk and the accompanying solid waste challenge in many coastal urban areas in developing countries. These challenges are more pronounced in informal settlements because: (a) they are often built on environmentally fragile locations such as river banks and coastal shores with high exposure to floods, (b) high poverty levels among residents resulting in low adaptive capacity, and (c) marginalisation of these localities emanating from their non-recognition in the larger city framework. Against this background, flood-risk assessments and response initiatives in these areas have primarily been informed by scientific approaches such as geographical information systems, without adequate incorporation of other forms of knowledge. Using the case of the coastal city of Durban, South Africa, our project explores the benefits of combining perspectives from different knowledge systems in understanding flood-risk and the accompanying solid waste challenge in urban informal settlements, towards developing solutions that are based on contextual and experiential aspects. Methodological techniques used include interviews and workshops with key experts and with informal settlement residents, and extensive reviews of literature.  Emerging findings show that holders of scientific, practitioner, and local knowledge vis-à-vis flood risk and waste management are active in the selected case study informal settlement. They have, in isolated cases, collaborated particularly around a) generation and distribution of flood early warnings, b) river clean-up initiatives, and c) catchment rehabilitation projects, with clear benefits for flood resilience and solid waste management. We find that there is need for a clear framework for integrating knowledge systems towards flood resilience and solid waste management in these contexts and the project has developed a draft framework. Integrating knowledge systems will: i) ensure the participation of different actors in mapping flood risk thereby creating a sense of ownership and ensuring uptake of and support for solutions crafted to deal with flood risk and the solid waste challenge; and ii) open up opportunities for coordinated support from various actors for a range of decisions around flood risk response preparation, flood and waste infrastructural design and mitigation of waste-induced flood destruction of infrastructure.

How to cite: Johnson, K. and Nyamwanza, A.: Integrated knowledge systems towards flood resilience and sustainable solid waste management in South African urban informal settlements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-867, https://doi.org/10.5194/egusphere-egu24-867, 2024.

17:00–17:10
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EGU24-8389
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HS7.5
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ECS
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On-site presentation
Hsing-Jui Wang, Ralf Merz, and Stefano Basso

The occurrence probability of rare floods is linked to the right-tail behavior of flood frequency distributions. Specifically, heavy-tailed behavior of flood distributions often signals significant hazards due to the unexpected extremeness of event magnitudes. However, conducting reliable analyses of flood tail heaviness across regions remains challenging due to the varying record lengths of available data.

In this study, instead of relying solely on statistical methods to evaluate flood tail behavior, we adopt a physical-based approach—hydrograph recession analysis—to quantify the nonlinearity of catchment hydrological responses. This method has shown its efficacy in identifying heavy-tailed flood behavior across analyses with different data lengths. Our analysis covers 575 river gauges, spanning drainage areas from 4 to 40,504 km2, across Atlantic-influenced European areas, Northwestern European areas, and the Continental United States. We categorize these regions based on the Köppen climate classification to explore the relationship between physiographic/climatic conditions and heavy-tailed flood behavior, and distinguish regional characteristics using the aridity index and potential evapotranspiration.

Our findings reveal a prevalence of heavy-tailed flood propensity in Atlantic-influenced European areas, prevalent nonheavy-tailed flood propensity in Northwestern European areas, and a mixed distribution with a balanced propensity in the Continental United States. Generally, drier catchments exhibit higher nonlinearity in hydrological responses, facilitating heavy-tailed floods, while catchments in which snow dynamics dominate the flood generation process tend to present linear responses. Excessively dry catchments, however, are less likely to exhibit heavy-tail floods due to insufficient moisture. Moreover, around one-third of catchments display varying tail behavior across seasons, underscoring the potential underestimation of flood tail heaviness in annual analyses. The seasonality of flood tail behavior—where instances of heavy-tailed flood behavior increase from spring to autumn but decrease in winter—is influenced by the seasonal variation of potential evapotranspiration.

Our study contributes to advancing the understanding of the impact of inherent physiographic and climatic features on regional and seasonal patterns of heavy-tailed flood behavior, providing valuable insights into the emergence of a considerable occurrence probability associated with very large magnitudes of rare floods.

How to cite: Wang, H.-J., Merz, R., and Basso, S.: Physiographic and Climatic Controls on Heavy-Tailed Flood Behavior: Insights from Catchment Nonlinear Responses, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8389, https://doi.org/10.5194/egusphere-egu24-8389, 2024.

17:10–17:20
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EGU24-19393
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HS7.5
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ECS
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On-site presentation
Margherita Sarcinella, Jeremy S. Pal, and Jaroslav Mysiak

Heavy rainfall events occurred in the Emilia-Romagna region in Northern Italy as a result of two major storms on May 2nd and 17th that led to the overflow of 22 rivers and triggered over 250 landslides. This event claimed 15 lives, forced 10 thousand people to evacuate and caused over 400 road closures. Due to a prior long-lasting winter drought and poor land use management that hampered effective water drainage, floodwaters stagnated for over a month in some areas, exacerbating the crisis. Over 40% of regional agricultural land was flooded leading to irreversible crop damage, in some instances, entire harvest loss. The objective of this study is to build a consistent and replicable methodology to quantify the agricultural damages and economic loss resulting from stagnated floodwater over cropland using the Emilia Romagna floods as a case study. The study emphasises the use of remote sensing data as a tool to achieve accurate impact estimates. Sentinel-1 SAR imagery is used to derive 10-meter resolution flood extent and duration maps at a revisit time of 3 to 6 days. The maps are matched with crop data available for the region from the iColt database and damages are computed as a function of ponded water duration and crop type as well as resistance to oxygen deprivation. The data, comprised of crop type, growing season and sowing date, allow for the characterization of the growth state of each crop at the time of flooding, implicitly providing insights on the probability of plant survival. The use of satellite-derived vegetation indices as markers for post-disaster crop recovery, with a focus on identifying crop-specific recovery rates and patterns is highlighted. This study highlights the need for collaborative efforts with key regional entities and can provide factual-hazard-based agricultural loss estimates to local institutions. These findings can guide targeted adaptation strategies, improve the spatial accuracy of loss assessment, and improve our comprehension of the aftermath of prolonged floods on agricultural output.

How to cite: Sarcinella, M., Pal, J. S., and Mysiak, J.: Impact of long-lasting flood water on agricultural productivity: a case study of the May 2023 Emilia Romagna floods, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19393, https://doi.org/10.5194/egusphere-egu24-19393, 2024.

17:20–17:30
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EGU24-15556
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HS7.5
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On-site presentation
Francesca Perosa, Alastair Clarke, Punit Bhola, Caroline McMullan, Emma Lewington, and Bernhard Reinhardt

To contribute to a more resilient flood risk management in Italy, we employ the recently published Verisk Inland Flood Model for Italy to conduct climate stress testing. We focus on the sensitivity of modeled losses to precipitation and leverage the meteorological dataset obtained from the Climate Model Intercomparison Project Phase 6 (CMIP6) for identifying projected precipitation trends and analyzing the potential effects of climate change on inland flood losses in the future, exploring different Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). The methodology involves analyzing correlations between annual or seasonal precipitation and the corresponding annual loss cost, which is defined as annual loss divided by the total insured value. By exploring these relationships, we seek to enhance our understanding of how precipitation patterns influence the financial implications of flood events in various Italian regions. Additionally, we use the 10,000-year stochastic catalog embedded in the Verisk Inland Flood Model to explore the impact of expected climate change-related changes in annual precipitation for each Italian region, addressing the climate change-based precipitation targets. This enables us to run the fully probabilistic Verisk Inland Flood model and to assess whether anticipated alterations in precipitation levels correspond to expected changes in Annual Average Loss (AAL). This approach allows us to dynamically adapt our flood risk model to varying climate scenarios, providing valuable insights for the (re)insurance industry, as well as academia and government agencies that are seeking to navigate the evolving landscape of flood-related risks.

How to cite: Perosa, F., Clarke, A., Bhola, P., McMullan, C., Lewington, E., and Reinhardt, B.: Climate Stress Testing for Enhanced Understanding of the Flood Hazard and its Socioeconomic Impacts in Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15556, https://doi.org/10.5194/egusphere-egu24-15556, 2024.

17:30–17:40
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EGU24-14743
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HS7.5
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On-site presentation
Martin Kadlec

The insurance sector plays a critical role in promoting disaster resilience and recovery by providing financial protection, speeding up rebuilding and recovery, and managing the financial impact of natural disasters. To fulfill this role, insurance companies must meet the capital requirements imposed by regulators. For example, the European Solvency II regulatory framework requires insurers to hold enough capital to withstand a natural catastrophe loss with a return period of 1 in 200 years. As the historical loss data are scarce and incomplete, the insurance sector uses stochastic catastrophe models (cat models) to assess the potential cost of rare but devastating events like floods.

A stochastic event set is a crucial element of cat models. It is a collection of possible disasters with their likelihood and severity. One method to generate stochastic flood events is to use numerical models of the atmosphere to generate realistic precipitation fields, and then apply rainfall-runoff models to estimate how much water will flow into rivers and streams from precipitation and snowmelt. By running many simulations with different inputs and parameters, stochastic flood models can provide a range of possible outcomes, including floods with spatial patterns and magnitude missing in historical data.

Output of such simulations are spatio-temporal hazard grids: precipitation grids for pluvial risk and river discharge grids for fluvial risk. These grids are large as the models typically run over large geographies (countries or continents) and simulate 10,000 years or more. This contribution will (i) provide overview of existing methods how to identify flood events in such huge discharge and precipitation datasets (i.e. peak-over threshold method), (ii) show their limitations for identifying flood events, and finally (iii) propose a new methodology designed to address specific needs of reinsurance industry such as the hours-clause condition, which specifies the time period within which losses from a single event must occur in order to be covered.

As many severe floods are composed from several sub-waves (for example 2002 floods in Czech Republic), proper event identification and separation is highly relevant topic as it influences the amount of reinsurance payouts after some types of flood events and thus capital available for rebuilding and recovery. 

How to cite: Kadlec, M.: Identification of flood events in large discharge datasets - reinsurance industry perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14743, https://doi.org/10.5194/egusphere-egu24-14743, 2024.

17:40–17:50
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EGU24-8531
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HS7.5
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On-site presentation
Francesco Dottori, Matteo Darienzo, Giacomo Fagugli, Simone Gabellani, Tatiana Ghizzoni, Daria Ottonelli, Flavio Pignone, and Eva Trasforini

On 15 September 2022 a catastrophic flood event hit the Misa river basin in Central Italy. The magnitude of the event (intensity of precipitation, water discharge, debris and sediment transport) and the subsequent impacts were far more severe and extended than previous flood events in the same area, thus calling for a radical change in current practices of flood risk management. In this framework, the present study aims at 1) providing a comprehensive assessment of flood risk for the Misa river basin, and 2) designing appropriate risk reduction measures at river basin scale. We reconstructed the September 2022 event by integrating in-field surveys, hydrological data, hydraulic models, observations of the event (e.g. flood extent maps) and historical data of past flood events, taking into account the incompleteness and uncertainty of both models and observations. Moreover, we modelled exposure and vulnerability of population and economic activities in the area, using detailed surveys of observed impacts to inform the model set-up. The outcomes of these activities allowed to review the risk analysis tools currently available in the Misa river basin, and to design updated risk scenarios for present and future climate conditions. Finally, the risk scenarios have been used to explore different alternatives for flood risk reduction, in agreement with local authorities and stakeholders. We evaluated a range of structural measures (strengthening of dike systems, detention areas, river diversions) and non-structural measures (land-use planning, relocation, flood-proofing measures), considering existing risk management plans and new analyses carried out in this study (e.g. cost effectiveness of measures).

How to cite: Dottori, F., Darienzo, M., Fagugli, G., Gabellani, S., Ghizzoni, T., Ottonelli, D., Pignone, F., and Trasforini, E.: Appraising and reducing riverine flood risk: a case study from Central Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8531, https://doi.org/10.5194/egusphere-egu24-8531, 2024.

17:50–18:00
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EGU24-3076
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HS7.5
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ECS
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On-site presentation
Shahin Khosh Bin Ghomash, Heiko Apel, Kai Schroeter, and Max Steinhausen

Due to rapid urbanization and the increase of extreme precipitation events driven by climate change, urban areas have experienced more frequent and severe pluvial floods in recent years. This trend is anticipated to continue in the future. One of the causes of flooding in these urban zones is the limited effectiveness or temporary reduction in surface drainage capacity, even when storm sewers adhere to technical standards. A notable instance was the June 2023 flooding in Braunschweig, situated in Lower Saxony, Germany, where the city received 60 liters per square meter of rainfall within a short time span, largely excessing sewer system capacity and leading to widespread inundation.

This research investigates the impact of implementing diverse strategies aimed at expanding urban drainage capacity to mitigate pluvial flood risk in Braunschweig. To accomplish this, a moderately detailed hydrodynamic model for the city was set up using the RIM2D hydrodynamic model, allowing for quick computational processing times which enabled the exploration of various measures through sensitivity analysis. The setup involved employing a high-resolution digital elevation model and various remote sensing data for land classification. The model incorporated high-resolution precipitation radar data from the 2023 event and additional precipitation scenarios of varying occurrence probabilities. Validation of the model against available event data and existing flood hazard maps specific to Braunschweig was conducted.

The validated model was then utilized to assess the effectiveness of different surface de-sealing scenarios within the city. These scenarios aim to enhance drainage capacity by means of increased infiltration to complement the existing sewer drainage system. The evaluation of these de-sealing scenarios focused on reducing surface inundation and anticipated damage, serving as a foundational aspect for conducting a cost-benefit analysis and detailed planning. This analysis can contribute to future-oriented urban pluvial flood risk management plans for the city.

How to cite: Khosh Bin Ghomash, S., Apel, H., Schroeter, K., and Steinhausen, M.: Assessing Surface Drainage Efficiency in Urban Pluvial Flood Hazard and Risk Mitigation: A Case Study of Braunschweig City, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3076, https://doi.org/10.5194/egusphere-egu24-3076, 2024.

Posters on site: Thu, 18 Apr, 10:45–12:30 | Hall A

Display time: Thu, 18 Apr 08:30–Thu, 18 Apr 12:30
Chairpersons: Efthymios Nikolopoulos, Elena Cristiano, Francesco Marra
Dynamics and societal impacts
A.98
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EGU24-7770
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HS7.5
Olga Petrucci, Massimo Conforti, Giovanni Cosentini, and Graziella Emanuela Scarcella

The occurrence of extreme hydro-meteorological events is globally on the rise, due to the combined effects of climate change and increasing urban development in vulnerable areas. Each year, landslides, floods, urban flooding, storm surges, snow and thunderstorm events cause casualties, huge damage to urban areas, farmland, and communication infrastructures. This work presents the preliminary results of an historical research aiming to identify the series of geo-hydrological events which affected the municipality of Catanzaro (Calabria, South Italy), having an area of 112.7 km2 and a population density of 746.84 ab./km², throughout the latest two Centuries. The purpose is to implement a GIS-platform using the historical series of past events to realize density maps resulting is a zonation of municipal area which depict the vulnerability of municipal sectors per type of damaging phenomena and type of damaged elements, and their trends throughout the decades. We firstly extracted those events contained in the database named ASICal (Italian acronym of historically flooded areas), a catalogue collecting damaging geo-hydrological events occurred in Calabria in the latest centuries and maintained by CNR-IRPI researchers. Then, to improve and enrich our series, we performed an historical research throughout the documents of the State Archive of Catanzaro. As a total, we gathered data about around 270 events which occurred in the study area between 1830 to 2023, highlighting the strong territorial vulnerability of the selected area. Considering the average number of events per year as a proxy of events impact, we can observe as this value increases during the study period, moving from one event per year (in the period 1900 – 1950) to 3 events per year (in the period 1950 – 2023). To be uploaded in the GIS platform and mapped, the 270 events were split in around 1500 records, according to the kind of damaging phenomena (flood, landslide, urban flooding, storm surges, snow, thunderstorm) and the affected place. 44% of cases were widespread events, while the remaining 56% affected single sites. Urban flooding seems the most frequent damaging phenomena (68% of records), followed by landslides (21%), while the other phenomena show lower frequencies. As far as damaged elements, the most frequently affected were public and private buildings (64%) and road and railway network (26%), while people were affected in a few cases (5%). Data elaboration as multi-hazard maps, also crosschecked to either physical or anthropogenic data can be used to identify hazard-prone areas and to support the multi risk management in terms of monitoring, planning of remedial works, and realization/updating of civil protection plans, as far as in the realization of educational campaigns aiming to raise people awareness.

This work was funded by the Next Generation EU—Italian NRRP, Mission 4, Component 2, Investment 1.5, call for the creation and strengthening of ‘Innovation Ecosystems’, building ‘Territorial R&D Leaders’ (Directorial Decree n. 2021/3277)—project Tech4You—Technologies for climate change adaptation and quality of life improvement, n. ECS0000009. This work reflects only the authors' views and opinions, neither the Ministry for University and Research nor the European Commission can be considered responsible for them.

How to cite: Petrucci, O., Conforti, M., Cosentini, G., and Scarcella, G. E.: Historical database for multi-hazard zonation and damage trend analysis in a Mediterranean study area (southern Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7770, https://doi.org/10.5194/egusphere-egu24-7770, 2024.

A.99
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EGU24-10877
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HS7.5
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ECS
Mara Lucantonio, Elena Ridolfi, Patrizia Cicini, Fabio Russo, and Francesco Napolitano

Risk is given by the combination of exposure, hazard, and vulnerability, and it is perceived by individuals in different ways. Some people may be unaware of the potential occurrence of a given hazard, while others may misjudge their level of exposure, vulnerability, or both. The knowledge of the population’s risk perception is a fundamental aspect for the analysis of potentially catastrophic phenomena and for the development of prevention policies to intervene and mitigate the expected damage. Questionnaires are widely used in social science research to acquire information about the attitudes, social characteristics, beliefs, and behaviors of participants. This information when combined through a mixed method can provide robust, comprehensive, and quantifiable results, adding a valuable perspective for the development of appropriate hazard mitigation and adaptation strategies. Here we present a case study that involves the analysis of a data set based on a questionnaire submitted to around 300 citizens of the city of Rome (Italy) in spring 2023. The proposed questionnaire investigates specific areas, which are: experience and knowledge of the phenomena, probability of occurrence perceived by the respondent, potential impact, and preparedness to deal with the phenomena.The use of questionnaires to study citizens’ perception of both natural and man-made hazards enables the acquisition of valuable information for authorities dealing with emergency management. The resulting dataset has the potential to improve the communication efficiency between authorities and citizens in risk situations, and provide relevant information for future studies relying on the knowledge of citizens’ risk perception.

How to cite: Lucantonio, M., Ridolfi, E., Cicini, P., Russo, F., and Napolitano, F.: Exploring Diverse Perceptions of Multiple Risks among the Public in Rome, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10877, https://doi.org/10.5194/egusphere-egu24-10877, 2024.

A.100
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EGU24-18357
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HS7.5
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ECS
Konstantinos Karagiorgos, Lars Nyberg, Nikos Kavallaris, Jenni Koivisto, Tonje Grahn, Ruth Björkholm, Johanna Gustavsson, and Sven Fuchs

In recent decades, social vulnerability assessments have become a valuable tool for gaining a deeper understanding of the effects of natural hazards on societies. These assessments aim to quantify and map human characteristics that contribute to potential loss, enabling the development of capacities and capabilities to respond to the emerging threats. Assessment methods range from qualitative approaches to semi-quantitative, often spatially explicit, place-based approaches, many of them with empirical background in respective case studies around the world. Despite these efforts, it is still important to carefully examine the potential benefits and limitations of these assessments, particularly those that focus on mapping and place-based approaches, in order to fully understand their value.

The purpose of this study (Karagiorgos et al., 2023) was to systematically evaluate the Social Vulnerability Index in Sweden (SVIS) developed by Haas et al. (2022) using a sensitivity analysis approach. This evaluation focuses on the sensitivity around the impact of changing aggregation scale levels, the influence of different options in constructing the index, the weight/contribution of each factor to social vulnerability and the indicators set. The aim was to determine the influence of input factor variation on model response.

Concerning the influence of scale variations on assessment outcomes, the SVIS algorithm demonstrated robustness when employed across various scales. In contrast, the factor retention method utilized yielded considerable differences in the results. Likewise, the weights' effect exerted a noteworthy influence on the index formation. The consideration of different subsets of variables revealed a high impact in certain scenarios.

The sensitivity analysis conducted in the index construction outlined in this study, recommends that the development of indexes proceed cautiously, accompanied by expert guidance. This approach ensures that the portrayal of social vulnerability remains both reasonable and consistent. Furthermore, the existence of other dimensions of vulnerability, such as physical, economic, and institutional, suggests that the SVIS be integrated with these dimensions. This integration can offer a comprehensive perspective on vulnerability, helping to identify and comprehend the primary pillars for use in Disaster Risk Reduction (DRR). It also contributes to a deeper understanding of the connections between social vulnerability models and the outcomes of disasters.

Haas, J.; Karagiorgos, K.; Pettersson, A.; de Goër de Herve, M.; Gustavsson, J.; Koivisto, J.; Turesson, K. & L. Nyberg (2022): Social sårbarhet för klimatrelaterade hot. Delstudie 2: Generella och hotspecifika index för social sårbarhet i Sverige. Myndigheten för samhällsskydd och beredskap, (MSB) rapport nr 1978, Karlstad.

Karagiorgos, K.; Kavallaris, N.; Björnholm, R.; Koivisto, J. & S. Fuchs (2023): Evaluation of the Social Vulnerability Index (SVIS) in Sweden. Swedish Civil Contingencies Agency (MSB), MSB report nr 2185, Karlstad. 

How to cite: Karagiorgos, K., Nyberg, L., Kavallaris, N., Koivisto, J., Grahn, T., Björkholm, R., Gustavsson, J., and Fuchs, S.: Unveiling the complexity of social vulnerability: An analysis of the Social Vulnerability Index in Sweden (SVIS), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18357, https://doi.org/10.5194/egusphere-egu24-18357, 2024.

A.101
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EGU24-18414
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HS7.5
The extreme future of soil moisture in a Portugal: from the main drivers to impacts
(withdrawn)
Pedro M M Soares and Daniela C Lima
A.102
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EGU24-20988
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HS7.5
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ECS
Anju Vijayan Nair, Rahim Dobariya, Deo Raj Gurung, and Efthymios Nikolopoulos

Higher altitude regions like High Mountain Asia (HMA) are particularly affected by future climate change where the increasing temperature coupled with inconsistent precipitation results in rapid glacier melting during summers and less regeneration of glaciers in winters affecting the livelihoods of billions of people. Access to information on future climate change and related hazards is essential to significantly reduce the impacts on socio-economic systems in HMA. In this study, we focus on identifying the areas in northwest HMA where climate extremes are projected to increase in magnitude and/or frequency. For this, statistically downscaled climate projections (at 5km resolution) derived from a 30-member ensemble of GFDL SPEAR CMIP6 are used to evaluate the projected trends in precipitation and temperature (for years 2015 to 2100) over Afghanistan, Tajikistan, and northern Pakistan under SSP2-4.5 and SSP5-8.5 scenarios. Analysis of changes in precipitation and temperature with respect to the historic climate (1990 to 2014) is done to evaluate the vulnerability to climate hazards including droughts and heatwaves. Analysis of the changes in future climate revealed a rapid increase in the occurrence of droughts and heatwaves towards the end of the century, affecting several communities in the region. Following the methodology developed by the Implementation Platform of the EU Mission on Adaptation to Climate Change (MIP4Adapt), the climate risk and vulnerability of local communities in the region is quantified. The results of this study provide critical information to stakeholders and the local communities to proactively prepare for the anticipated climate risks in the future and to adopt appropriate mitigation measures.

How to cite: Vijayan Nair, A., Dobariya, R., Gurung, D. R., and Nikolopoulos, E.: Assessment of future climate risk and vulnerability of local communities in High Mountain Asia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20988, https://doi.org/10.5194/egusphere-egu24-20988, 2024.

Floods
A.103
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EGU24-2563
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HS7.5
Monique Fort, Narayan Gurung, Gilles Arnaud-Fassetta, and Rainer Bell

A severe and complex, polygenetic flood event occurred in Muktinath area of Mustang, Nepal on the evening of August 13, 2023 causing significant damage to property and infra-structures worth approximately of USD 7.4 million at Kagbeni Village, which is nestled along both banks of Kagkhola, a major left bank tributary of the Kali Gandaki River. About 29 houses, 1 motorable bridge, 1 steel truss bridge and 3 temporary bridges were destroyed, while more than 25 cows and other livestock were killed. Fortunately, human lives were spared because the community was warned to move to safety before the mud and sludge hit the village. A study was conducted in order to know what had caused this unusual flash-flood in Mustang. Kagbeni (2810 m) lies in the north Himalayan, rain-shadow area and normally receives few rainfall (<300 mm/yr). However, for several years, the trend (confirmed by local residents) has been towards increased rainfall, leading to more landslides and floods. Although rainfall data from the nearest monitoring station, Jomsom (2720 m), shows that rainfall was high, there is not detailed information about the rainfall amount at Jhong (3600 m), and Muktinath  (3760 m), source area of Kagbeni flood. From the video taken there (Jhong, Muktinath) during this flash-flood event (hyper-concentrated flow), it can be concluded that it was a landslide lake outburst flood. However due to the difficult terrain and inaccessible path, it has not yet been possible to visit the source area of the landslide in detail. Heavy rainfall over a short period and flash-flood-like disasters are becoming a trend in the mountain regions in Nepal. Furthermore, this part of Mustang is fragile (Spiti shales), and heavy rainfalls have an immediate impact, since there is little soil to absorb the excess water. Former studies have also shown that temperature in Mustang is rising which is causing the monsoon air to move northward and upward. As a result, more rainfall is taking place in Trans-Himalayan areas like Mustang and Manang (North of Annapurna Himal, 8091 m). Therefore, it is believed that climate change and the rise in temperature could be the significant reasons for heavy rainfall that caused such a flash-flood in Kagbeni, Mustang. On the other hand, people are inviting disaster in Kagbeni by settling on the very low terraces or in flood-plains and encroaching on the bed of the local Kagkhola. Given the fragile geology of upstream area of Kagkhola, ongoing anthropogenic activities (agriculture and tourism) and the effect of climate change, the possibility of flash floods reoccurring in the future at Kagbeni remains high. Sadly, locals at Kagbeni have already started rebuilding houses damaged by the recent Kagbeni flood and continue to live in potentially threatened flood plains.   

How to cite: Fort, M., Gurung, N., Arnaud-Fassetta, G., and Bell, R.: Retrospect of the polygenetic Kagbeni flood event (August 13, 2023) in Mustang, Nepal. Are rapid hydromorphological processes relays and sediment cascades in the catchment well taken into account in the risk equation?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2563, https://doi.org/10.5194/egusphere-egu24-2563, 2024.

A.104
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EGU24-17516
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HS7.5
Fabian Weidt, Rainer Bell, Lothar Schrott, Alexander Brenning, Michael Dietze, Lisa Burghardt, and Joshua Groeßer

The extreme flood event of July 14/15, 2021 caused massive geomorphological changes along the Ahr river in western Germany. The processes include mass movement and bank erosion, channel displacement and widening and deposition of material at the floodplains, all of which contributed to extreme damage. With the aim of gaining a more comprehensive understanding of the factors controlling these processes, spatial patterns of geomorphological changes on a regional scale are analyzed. A differential terrain model (DoD), calculated from digital terrain models (DTM) collected before and after the event using airborne laser scanning (ALS), serves as the data basis. The course of the river is divided into 120 m wide and 100 m long segments. Analyzing the cumulated volumetric loss per segment, which represents the explained variable proxying spatial variability in flood power, is conducted by using a multiple linear regression model. The independent variables considered in this investigation include peak discharge, valley floor width and river curvature. Additionally, a time series model, incorporating ARIMA and GARCH components, is applied to unravel patterns and anomalies along the course of the river while accounting for the autocorrelative and heteroscedastic structure of data. Both the native data and the residuals of all model types are used to examine effects of bridge failure and subsequent outburst waves on volumetric loss. The analysis shows that the strongest geomorphological changes are associated with high peak discharge and a small valley floor width. River segments containing destroyed arch bridges show significantly higher volumetric loss values than segments with destroyed slab bridges, intact bridges or no bridge at all. Spatially limited amplification of volumetric loss to 200 m downstream of destroyed slab bridges suggests a more rapid decrease in outburst wave power for those type of bridges in contrast to arch bridges. These findings provide evidence that there are construction types more appropriate than traditional arch bridges to prevent local augmentation of flood power caused by outburst waves resulting from bridge clogging and failure.

How to cite: Weidt, F., Bell, R., Schrott, L., Brenning, A., Dietze, M., Burghardt, L., and Groeßer, J.: Spatial patterns and determinants of severe geomorphological changes due to the extreme flood event in the Ahr valley, western Germany in July 2021, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17516, https://doi.org/10.5194/egusphere-egu24-17516, 2024.

A.105
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EGU24-6148
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HS7.5
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ECS
Ke He, Maria Pregnolato, Neil Carhart, Jeffrey Neal, and Raffaele De Risi

In the realm of critical infrastructure, the road network plays an indispensable role in facilitating daily activities, communication, and economic interactions. However, it remains susceptible to the persistent challenge of flood hazards, leading to both structural and non-structural damages (e.g., physical collapse and service interruption). In normal flood disasters, physical collapse may not occur, but service interruptions often occur. Such disruptions manifest in the form of increased travel distances, prolong the travel times, and, in severe cases, complete travel impossibility. This has resulted in a reduction in transportation efficiency, leading to an increase in the social cost of transportation.

This study presents a novel approach that integrated flood hazard, transportation network topology, and vehicle vulnerability to evaluate the functionality of road network. A severity factor is defined to assess the accessibility of expected links (roads and bridges), considering different vehicle types such as cars and SUVs. Then, this study analyses the overall road network functionality loss under varying flood return periods by evaluating the severity of each network link based on the different types of vehicles. Identification of links with the lowest functionality allows for the assessment of the entire network’s performance using topology-based measures, including the average node degree, average clustering, average shortest path, and reachable areas (isochrones). This research employs the transportation network of Bristol, UK, as a case study to investigate the dynamic relationship between the network status and vehicle typology in the context of flooding events. Findings reveal a discernible correlation, wherein the resilience of the network in influenced by the specific characteristics of different vehicle types. Notably, SUVs emerge as inherently more resistant to flood-related disruptions compared to conventional cars.

The insights presented in this paper hold significant implications for the development of robust mitigation strategies geared towards bolstering the resilience of road networks and optimizing the rerouting of emergency response vehicles in flood-prone areas. By elucidating the interplay between vehicle characteristics, network functionality, and flood impacts, the research provides a foundation for informed decision-making in the formulation and implementation of effective preparedness measures. The outcomes of this study offer a strategic roadmap for authorities and policymakers, enabling them to proactively address the challenges posed by future flood events and enhance the overall adaptability and responsiveness of road networks in emergency situations.

How to cite: He, K., Pregnolato, M., Carhart, N., Neal, J., and De Risi, R.: Functionality assessment of road network combining flood roadworthiness and graph topology, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6148, https://doi.org/10.5194/egusphere-egu24-6148, 2024.

A.106
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EGU24-8205
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HS7.5
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ECS
Alice Gallazzi, Daniela Molinari, Francesco Ballio, Marina Credali, Immacolata Tolone, Simona Muratori, and Panagiotis Asaridis

The study aims to provide the Lombardy Region, the primary stakeholder in the project, with a procedure for evaluating and classifying structural flood risk mitigation measures. The primary objective is to assist the regional authority in identifying priority interventions for public funding. A step-by-step procedure has been developed to assess and rank all projects submitted to the Region, selecting priority projects based on technical considerations—evaluating feasibility, effectiveness, and sustainability of the proposed measures—and the preferences of policymakers. The assessment procedure's conceptual structure was tested using case studies, including both feasibility studies and executive projects, to determine the level of technical insights required at each planning phase of public works. The methodology relies on Multiple Criteria Analysis (MCA) techniques, enabling the simultaneous consideration of various, non-directly comparable criteria in a complex decision-making context. These criteria encompass technical features of proposed works, potential territorial constraints, and interferences in the intervention area (feasibility); the effectiveness of measures in reducing flood risk and associated costs; and the environmental and social co-benefits and disbenefits of each intervention (sustainability). Specific indicators, either ad hoc defined for the study or referenced from current regulations and guidelines at national and regional levels, are employed to evaluate the criteria. Stakeholder participation, particularly from the Region, River District Authorities, and Municipalities, is crucial throughout the process, especially in the final phase of aggregating (weighting) all criteria. This aggregation produces an overall performance score for each option, enabling the derivation of a regional ranking of flood risk mitigation strategies. The collaboration between academia and public institutions is highlighted as essential for enhancing the efficiency of disaster risk reduction policies.

How to cite: Gallazzi, A., Molinari, D., Ballio, F., Credali, M., Tolone, I., Muratori, S., and Asaridis, P.: A Multi-Criteria Analysis procedure for the evaluation and classification of flood risk mitigation strategies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8205, https://doi.org/10.5194/egusphere-egu24-8205, 2024.

A.107
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EGU24-3602
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HS7.5
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ECS
Montserrat Llasat-Botija, Maria Carmen Llasat, Dimitri Marinelli, Raül Marcos, Carlo Guzzon, and Albert Díaz

Floods represent a complex natural hazard, influenced not only by meteorological factors but also by geophysical aspects such as terrain topography, social factors such as the value of exposed assets, and cultural factors like risk awareness. For this reason, the study of these phenomena requires a holistic approach. This requires the correct organization of the information. In addition, given that the information comes from different sources, the traceability of the data must also be contrasted and preserved in order to guarantee its quality and robustness. Databases make it possible to conserve and document historical information, to analyze it and to support smart flood risk management.

With this objective in mind, in 2000 the GAMA team developed the INUNGAMA flood database, following the example of other natural hazards databases. This communication will present the new version of this database, FLOODGAMA, and the main results of its analysis. FLOODGAMA contains information on 456 flood events that affected Catalonia (NE of Spain), between 1900 and 2020, which have caused 1,253 casualties. The events are classified according to the impacts. It includes linked tables with information on event dates, descriptions, fatalities, economic damages, affected municipalities, recorded rainfall and recorded flow. Other tables contain historical marks, codifications and the geographical information of municipalities, counties, basins and rivers, as well as meteorological stations. Its structure has been simplified and standardized with Python and migrated to PostgreSQL (PostGIS) from an ACCESS format. The new database allows for more general and straightforward analysis, introduces GIS tool compatibility, and simplifies the addition of new data and new data sources. This last point has been one of the key points in this transformation as it will provide the database with the flexibility to respond to the challenges posed by the digital transformation that is currently taking place and as a tool for the improvement of adaptation.

The contribution shows the structure of this flood database and the results obtained after its analysis that allows the characterization of flood events in Catalonia.

This research has been done in the framework of the C3Riskmed project, Grant PID2020-113638RB-C22 funded by MCIN/AEI/10.13039/501100011033 and Flood2Now project, Grant PLEC2022-009403 funded by MCIN/AEI/10.13039/501100011033 and by the European Union Next Generation EU/PRTR.

How to cite: Llasat-Botija, M., Llasat, M. C., Marinelli, D., Marcos, R., Guzzon, C., and Díaz, A.: FLOODGAMA: the new INUNGAMA. Beyond a flood events database for Catalonia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3602, https://doi.org/10.5194/egusphere-egu24-3602, 2024.

A.108
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EGU24-9209
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HS7.5
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ECS
Ester García Fernández, Juan Francisco Albaladejo-Gómez, Andrina Gincheva, Salvador Gil-Guirado, and Alfredo Pérez-Morales

Floods represent the most diverse, destructive and frequent natural hazard worldwide and are one of the most significant causes of loss of economic and social assets. In recent years, an increase in the quantity and intensity of this phenomenon can be observed. The factors are manifold, but two stand out: increased hazards as a consequence of anthropogenic climate change and increased exposure and vulnerability of the population and its economic assets. One of the most conflictive areas of the planet are the Mediterranean regions, due to the combination of both factors. Among the hot spots, the Southeast of Spain stands out, with a situation aggravated by a semi-arid climate, but with a highly irregular and torrential rainfall distribution.

These factors are particularly problematic in urban areas, making it necessary to precisely locate the areas at risk in order to establish effective adaptation measures. For this reason, this paper compiles historical information on the main flood events from 1900 to the present in the metropolitan area of Murcia, the main urban area in southeast Spain. The information collected comes from newspaper sources. Subsequently, this information has been geolocated and analyzed with Geographic Information Systems. The results reveal that, in general terms, the damage is concentrated mainly in the areas near the Segura River. Additionally, and to a lesser extent, there is a significant concentration in its main tributary, the Guadalentín River. However, it should be noted that during recent flooding episodes, the areas affected are being modified, involving new urbanized areas, far from the main riverbeds and located in flood zones due to the passage of secondary watercourses such as wadis. Finally, it is worth noting that there has been an increase in the number of low-intensity damage points. However, on a positive note, it has been observed that higher intensity damage is decreasing.

How to cite: García Fernández, E., Albaladejo-Gómez, J. F., Gincheva, A., Gil-Guirado, S., and Pérez-Morales, A.: Spatial analysis of catastrophic flooding in the metropolitan area of Murcia over the last 100 years, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9209, https://doi.org/10.5194/egusphere-egu24-9209, 2024.

A.109
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EGU24-14698
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HS7.5
Anna Rita Scorzini, Charlie Dayane Paz Idarraga, and Daniela Molinari

Quantitative flood risk assessments rely on damage models, which relate information on flood hazard and vulnerability of exposed assets to estimate expected losses. Differently from other sectors, crop damage depends not only on typical hazards variables (including water depth, flow velocity, inundation duration, water salinity, yield of sediments and/or contaminants) but also on the month of flood occurrence. Indeed, plant vulnerability changes over the different phenological phases that are strictly related to the seasonality of crop production. Considering the time of occurrence of the flood would imply a shift from the traditional representation of inundation scenarios based on annual probability to monthly-based hazard estimations. When risk assessment is carried out at large spatial scale, a detailed understanding of seasonal flood patterns is then required for the different sub-catchments of the basins, including un-gauged ones. In this study we present a clustering approach to flood frequency regionalization applied to the Po River District in Northern Italy, within the risk assessment process required by the European Floods Directive. The  area is characterized by complex climatic and topographic conditions, highlighting the representativeness of the case study for the implementation of the proposed approach in other geographical contexts. Utilizing observed monthly flow data from over 100 gauging stations, the approach combines both physical and statistical criteria to identify homogeneous regions in terms of flood generation mechanisms and seasonality. The process enables the assignment of distinct monthly flood probabilities to all catchments within the district, thereby supporting a comprehensive flood risk assessment for the agricultural sector.

How to cite: Scorzini, A. R., Paz Idarraga, C. D., and Molinari, D.: Monthly flood frequency regionalization for comprehensive flood damage assessment to crops, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14698, https://doi.org/10.5194/egusphere-egu24-14698, 2024.

A.110
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EGU24-20944
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HS7.5
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ECS
Mara Ruf and Daniel Straub

Floods are one of the most hazardous natural phenomena worldwide and they are predicted to increase both in intensity and frequency due to climate change. This necessitates comprehensive flood risk mitigation measures that are planned and controlled from a regional as well as a strategic trans-regional perspective.

Controlled flood detention basins can be effective measures for dealing with extreme flood events [1]. By temporally storing water in the detention basin, the discharge in a river is reduced. If the water is removed from the river at the optimal time, this should reduce the peak water level at downstream locations and hence the flood risk.

However, the identification of the optimal operation of flood detention basins is a non-trivial as well as non-deterministic problem. Flood forecast uncertainty, dilatation of the wave along the river channel and the uncertainty in the breaching process turns the polder operation into a stochastic optimization problem with multiple possible optimization targets. Hence, this optimization belongs to the class of sequential decision problems under uncertainty. In this contribution, we utilize a developed dynamic-probabilistic flood risk model [2] to analyze and optimize different control strategies as well as the effect of uncertainties on the optimality of the detention basin operation. We consider the case of a single detention basin as well as that of multiple detention basins that are arranged in series.

 

[1] De Kork, J.-L.; Grossmann, M. (2009): Large-scale assessment of flood risk and the effects of mitigation measures along the Elbe River. Natural Hazards (2010) 52:143-166.

[2] Ruf, M., Hoffmann, A., Straub, D. (2023): Application of a decision sensitivity measure for the cost-benefit analysis of a flood polder at the Bavarian Danube. 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP 14). Dublin, Ireland.

How to cite: Ruf, M. and Straub, D.: Towards optimizing the operation of controlled flood detention basins, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20944, https://doi.org/10.5194/egusphere-egu24-20944, 2024.

A.111
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EGU24-7347
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HS7.5
Morgane Terrier and Mathis Joffrain

The 2011 flood event in Thailand was devastating both in terms of lives and economic losses. Following this event, the (re)insurance industry have deeply transformed its underwriting practices and used new modeling tools, both external and internal.

A loss is linked both to hazard and sites characteristics. As an insurer's exposure changes, losses for the same event can differ greatly from past observations. Therefore, hazard maps representing a past event can be used to estimate losses as of today.

Building an internal flood risk model requires to create a large set of spatial grids of flood depth. The water depth spatialisation, based on the water level of identified rivers, is a crucial part of the modeling and called the hydraulic modeling.

This poster will :

(i) the use of two hydraulic models to obtain a flood footprint: The software Super-Fast Inundation of CoastS (SFINCS) (Leijnse et al., 2021), a 2D open-source fast numerical model, and LISFLOOD-FP (Bates, 2004).

(ii) calculate insured losses on a fictive portfolio in Thailand using these two models with the same inputs.

(iii) describe and explain the discrepancies steming from (ii).

How to cite: Terrier, M. and Joffrain, M.: Impacts comparison by using different hydraulic models on the 2011 flood in Thailand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7347, https://doi.org/10.5194/egusphere-egu24-7347, 2024.

Landslides
A.112
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EGU24-3285
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HS7.5
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ECS
Chun Wei Liang and Hsun Chuan Chan

When heavy rainfall occurs in mountainous areas, the water level in streams rises, and the flow velocity increases, result in the enhancement of erosive capacity. As the fast-flowing water approaches the riverbanks, the stability of the riverbank slopes may reduce due to toe scour. It may further lead to the occurrence of near-bank landslides. The deposition of soil and sediment in the riverbed caused by landslides can have a major impact on the safety of the nearby residents and communities.

The Erwanping landslide area in the upstream Ali Mountain watershed, Taiwan was selected as the research area. By the means of the CCHE-2D hydraulic model, flood simulations with return periods of 10, 25, 50, and 100 years were conducted in the river near the landslide areas. The scour of the riverbanks was analyzed. Subsequently, a slope stability model was established based on the post-flood bed elevation predicted by the CCHE-2D. The impact of toe scour of slopes on slope stability was evaluated through the changes of safety factor subjecting to floods of various return periods. The present approaches provide important information for development of disaster prevention and warning system in the riverbank areas.

 

Keywords: Riverbank, Landslide, Hydraulic model, Slope stability

How to cite: Liang, C. W. and Chan, H. C.: Evaluating the Effect of Toe Erosion on Slope Stability through the Integration of Hydraulic Model and Slope Stabilization, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3285, https://doi.org/10.5194/egusphere-egu24-3285, 2024.

A.113
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EGU24-10950
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HS7.5
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ECS
Rui Fagundes Silva, Rui Marques, and José Luís Zêzere

The São Miguel Island covers an area of 744.6 km² and has a total population of 133,390, distributed across six municipalities: Ponta Delgada, Ribeira Grande, Vila Franca do Campo, Povoação, Lagoa, and Nordeste. The island features two extinct volcanic systems and three active central volcanoes with calderas connected by two fissure volcanic systems. Two distinct seasons can be identified based on rainfall patterns: from October to March (wet season) and from April to September (dry season). Since the settlement of the island in the mid-15th century, there have been records of landslides, some with significant socio-economic impact. The analysis of the spatial distribution and temporal patterns of mortality associated to landslides was carried out using the NATHA (Natural Hazards in Azores) database for the period 1900–2020. Data collection involved the analysis of more than 55,500 newspaper specimens. A total of 236 landslides events were catalogued on São Miguel Island, which caused 82 fatalities. The municipality of Povoação accounted for 48 fatalities, approximately 59% of the total. Ponta Delgada reported 14 fatalities, Ribeira Grande eight, Vila Franca do Campo seven, Nordeste three, and Lagoa two. On São Miguel Island, an average of 0.7 fatalities per year were recorded, resulting in a landslide mortality rate of 0.35 (calculated as the ratio between deaths and total events). The events with the highest number of fatalities occurred on October 31, 1997 (29 fatalities) and on October 14, 1942 (7 fatalities). The annual mortality rate per decade reveals two distinct periods with higher values: 1930-1949 and 1990-1999. No fatalities were recorded from 1900 to 1929. The landslide mortality rate has a first increase in the 1930s and 1940s (≈0.1 fatalities/10,000 inhabitants). From 1950 to 1989, there was a decrease (≈0.02 fatalities/10,000 inhabitants), with a slight increase in the 1960s. The period from 1990 to 1999 has the highest mortality rate (≈0.26 fatalities/10,000 inhabitants). However, excluding the extreme event of October 31, 1997 from the analysis reveals that the 1990s had a mortality rate in line with the previous four decades (0.02 fatalities/10,000 inhabitants). Along the two first decades of the 21st century, the mortality rate increased again, maintaining a stable trend (≈0.05 fatalities/10,000 inhabitants). The data also indicates that males had a higher frequency of fatalities. The circumstances surrounding the incidents varied, with most fatalities occurring outdoors when individuals were on foot in rural areas. However, it is noteworthy that there were also fatalities inside houses in urban areas, emphasizing the diverse contexts in which these tragic events took place. This information provides valuable insights to temporal patterns and spatial distribution of landslide-induced fatalities on São Miguel Island.

How to cite: Silva, R. F., Marques, R., and Zêzere, J. L.: Temporal and spatial analysis of mortality associated with landslides on São Miguel Island (Portugal) from 1900 to 2020, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10950, https://doi.org/10.5194/egusphere-egu24-10950, 2024.

A.114
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EGU24-3288
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HS7.5
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ECS
Ti Ching Cheng and Hsun Chuan Chan

Near-bank landslide is the primary source of sediment in the mountain rivers. Scouring of slope toe may cause the near-bank landslide, resulting in slope materials collapsing into rivers. Collapsing materials accumulated on the riverbed obstruct the flow, forming barrier lake and greatly destabilizes the river channel, hence, post a threat to the safety of downstream residents and property.

The Alishan River watershed was selected as the research areas and utilized logistic regression analysis to assess the landslide susceptibility of near-bank areas. Models considered different factors, including geographical and hydraulic factors, were established. Model assessment used the area under the ROC curve (AUC) values to evaluate the performance. Results of the model with the highest AUC value was then produced the landslide susceptibility map to illustrate the effects of geographical and hydraulic factors in the landslide prediction. The results showed that concave banks and channel sinuosity index contribute to near-bank landslides significantly. Observations of landslide susceptibility map and satellite image revealed that concave banks and flow meandering are often the characteristics of near-bank landslide areas with high susceptibility. The results can serve as a reference for disaster prevention and management in the future.

Keywords: Alishan River, Near-bank Landslide, Landslide Susceptibility Analysis, Hydraulic Factors, Logistic regression

How to cite: Cheng, T. C. and Chan, H. C.: Effects of Hydraulic Factors on Near-bank Landslide Susceptibility Analysis in Alishan River Watershed, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3288, https://doi.org/10.5194/egusphere-egu24-3288, 2024.

A.115
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EGU24-15848
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HS7.5
Vincenzo Totaro, Simona de Sario, Francesco Chiaravalloti, and Olga Petrucci

Floods and landslides are common natural phenomena that threaten society and ecosystems causing significant losses in term of human lives and financial damages. An in-depth investigation about the past occurrences of these events is of paramount importance for providing advances in the knowledge of natural and anthropogenic factors responsible for their generation. Considering rainfall as one of the key drivers for triggering physical mechanisms responsible for the occurrences of floods and landslides, a proper description of its characteristics needs to contemplate the intrinsic spatial and temporal variability. Despite the importance of such elements, rainfall monitoring often relies on sparse rain gauges, which lead to uncertainty in the identification of real rainfall patterns, making difficult to link precipitation records with observed damages. Meteorological radar represents a relevant tool for detecting rainfall spatiotemporal variability and providing ancillary information about the evolution of the events.

Goal of the work is to develop a methodology that aims in reconcile records of landslides and floods events with the rainfall structures obtained by the joint use of data recorded by rain gauge network and radar data. The research has been carried out by moving from a consolidated catalogue of damaging events occurred in correspondence of floods and landslides in Calabria region (Italy) in 2019 and 2020. Rainfall was investigated integrating rain gauge data and maps of Surface Rainfall Intensity with resolution of 1x1 km2.

Exploiting the availability of an accurate spatiotemporal reconstruction of precipitation structures, our investigation allowed to improve the specific knowledge about dynamics responsible of selected floods and landslides events. Preliminary results are supportive of the use of the proposed approach for integrating different sources of information in the assessment of the real dynamics of damaging events and for enhancing the use of their joint scientific content in the framework of risk assessment and mitigation.

How to cite: Totaro, V., de Sario, S., Chiaravalloti, F., and Petrucci, O.: The use of radar information for improving the knowledge about landslides and floods events: an application to Calabria region (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15848, https://doi.org/10.5194/egusphere-egu24-15848, 2024.

Dry extremes
A.116
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EGU24-11493
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HS7.5
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ECS
Pedro Henrique Lima Alencar and Eva Nora Paton

Dry spells, characterized by consecutive days with little to no precipitation, pose significant challenges, particularly in agriculture, and can impact various sectors including health when compounded by high temperatures, increased evaporation rates, or pollution. However, defining the thresholds for what constitutes a significant lack of precipitation or the number of consecutive days to define a notable dry spell remains ambiguous. In this study, we investigate the occurrence of different types of dry spells across Germany using twelve diverse definitions. These definitions encompass not only the conventional criteria of low/no precipitation but also consider associations with other extreme weather conditions occurring simultaneously (such as high temperatures, and potential evapotranspiration) or following the dry spell (like intense precipitation events). Leveraging continuous weather station data spanning the last 50 years, we employ the Mann-Kendall test to analyse seasonal and regional trends in the duration and frequency of these various dry spell events across Germany. Our findings reveal positive trends in both the frequency and duration of dry spells in Germany, notably prominent in the southern regions. These trends are observed in conventional low-precipitation dry spells and compound heat-dry events. Additionally, to facilitate event identification, we have consolidated these diverse dry spell definitions into an R-package called DryER (Dry spell Events in R).

 

How to cite: Lima Alencar, P. H. and Paton, E. N.: Dry spell frequency and duration analysis using different spell definitions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11493, https://doi.org/10.5194/egusphere-egu24-11493, 2024.

A.117
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EGU24-19949
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HS7.5
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ECS
|
Tapash Mazumdar, Silvia Di Francesco, Francesca Giannone, and Monia Santini

Draught is one of the major climate related disaster that Italy has been fighting in the recent years .It is a complex multidimensional phenomenon that is dependent upon on a wide variety of parameters ranging from climatic to socioeconomic ones. In this study we are considering watershed area of lake Bolsena, which is one of the most important water resources in central Italy, to asses in drought vulnerability using Geographical Information System (GIS)  in combination with the Analytic Hierarchy Process (AHP). GIS is used for the spatial analysis of drought for Lake Bolsena watershed area for the year 2022 which was one of the worst draught affected year in the history for the country. Parameters such as Monthly rainfall, Land use/Landcover (LULC), elevation , soil type, Normalized difference vegetation index (NDVI), Normalized Difference turbidity Index (NDTI),Normalized differentiate chlorophyl index(NDCI), Normalized Difference Water Index (NDWI),Storm power index (SPI)  were chosen and considered for the study. AHP is used to calculate weightage factors of each criterion based on the pairwise comparison matrices. The thematic maps of all the parameters were analyzed and Drought Vulnerability Assessment (DVA) map was generated using GIS. The output DVA map will provide valuable information on drought severity in the area and vulnerability related to water availability.

How to cite: Mazumdar, T., Di Francesco, S., Giannone, F., and Santini, M.: Drought vulnerability assessment and mapping using Multi-Criteria decision making (MCDM) and application of Analytic Hierarchy process (AHP) for watershed area of Lake Bolsena of Central Italy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19949, https://doi.org/10.5194/egusphere-egu24-19949, 2024.

A.118
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EGU24-4355
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HS7.5
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ECS
Qi Liu and Shanshan Yang

The self-calibrating Palmer Severity Drought Index (scPDSI) and the multi-time-scale Standardized Precipitation Evapotranspiration Index (SPEI) are commonly employed to explore the impact of water availability on vegetation. However, their usage lacks clearly defined boundaries. This study presents a global-scale macroscopic assessment of the relationship between scPDSI and SPEI with vegetation water stress factors. Our findings reveal that, in comparison to meteorological conditions, scPDSI exhibits a stronger correlation with root-zone soil moisture (RSM). Among SPEI on various scales, SPEI at the 9-month scale (SPEI09) effectively captures RSM dynamics, while SPEI at the 1-month scale (SPEI01) is more responsive to variations in vapor pressure deficit. Moreover, the sensitivity analysis of vegetation activity response to scPDSI and multi-scale SPEI indicates higher sensitivity in drylands to scPDSI and SPEI09, while that in boreal regions of the Northern Hemisphere exhibit the highest sensitivity to SPEI01. This study will provide scientific reference for selecting scPDSI and different SPEI time scales as indicators of water availability conditions.

How to cite: Liu, Q. and Yang, S.: Macroscopic evaluation of scPDSI and SPEI links to vegetation water stress factors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4355, https://doi.org/10.5194/egusphere-egu24-4355, 2024.

Precipitation extremes
A.119
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EGU24-19552
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HS7.5
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Highlight
Hayley Fowler, Amy Green, Elizabeth Lewis, David Pritchard, Stephen Blenkinsop, Luis Patino Velasquez, and Anna Whitford

Precipitation extremes result in flooding and droughts, causing substantial damages and loss of life. Understanding the variability of precipitation extremes with climate change is challenging, as we do no fully understand processes causing extreme precipitation under current climate variability. The INTENSE project focuses on understanding of the nature and drivers of global sub-daily precipitation extremes and change on societally relevant timescales. As part of this a Global sub-daily precipitation dataset has been collected, containing hourly rainfall data from approximately 25,000 rain gauges across over 200 territories, from a wide range of sources. This has been quality controlled using a rule-based open-source methodology, combining a number of checks against neighbouring gauges, known biases and errors, and thresholds based on the Expert Team on Climate Change Detection and Indices (ETCCDI) Climate Change Indices.  

A set of global hydroclimatic indices have been produced, characterising key aspects of shorter duration precipitation variability, including intensity, duration and frequency properties. An analysis of the indices, trends and corresponding climatology is carried out, providing information on various sub-daily precipitation characteristics (including extremes) across large parts of the world. These indices are publicly available for as many gauges as possible, alongside a gridded dataset that also incorporates indices calculated for additional restricted-access gauge records. To progress further with this work, updates to the dataset are required, with work ongoing to update resources for 2016 onwards, and attempts to automate the process where open-source datasets are available. Any collaborations, information, suggested contacts and relevant resources for developing the dataset are welcomed. 

How to cite: Fowler, H., Green, A., Lewis, E., Pritchard, D., Blenkinsop, S., Patino Velasquez, L., and Whitford, A.: Unveiling global sub-daily precipitation extremes: Insights and development of the INTENSE Project , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19552, https://doi.org/10.5194/egusphere-egu24-19552, 2024.

A.120
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EGU24-14898
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HS7.5
Michalis Diakakis, Spyridon Mavroulis, Christos Filis, Yiannis Bantekas, Marilia Gogou, Katerina-Nafsika Katsetsiadou, Maria Mavrouli, Vasilis Giannopoulos, Andromachi Sarantopoulou, Panagiotis Nastos, Emmanuel Vassilakis, Aliki Konsolaki, Evelina Kotsi, Sotiris Moraitis, Eleftheria Stamati, Athanasia Bakopoulou, Emmanuel Skourtsos, Panayotis Carydis, and Efthymios Lekkas

On September 4, 2023, Storm Daniel moved inland from the Ionian Sea, intensifying due to the warmth of the post-summer Mediterranean Sea, resulting in intense rainfall and thunderstorms over the Balkans. Central Greece was particularly affected, experiencing the highest daily rainfall totals recorded in the region.

The storm caused widespread devastation, especially in the Thessaly region, with significant impacts including intense erosion, mass movement phenomena triggered by rainfall, damages from strong winds, inundation, agricultural land damage, loss of life and injuries, impacts on residences and businesses, as well as a substantial toll on the environment and cultural sites.

This study focuses on Storm Daniel and its effects in Thessaly, Greece, by creating a database of distinct impact elements based on field surveys and public records. Through this archive, the study explores the range of its impacts, developing a systematic categorization to provide an in-depth understanding of the types and mechanisms of these impacts.

Examining extreme storms through post-flood surveys and emphasizing their impacts can enhance our comprehension of associated risks. This knowledge will facilitate more accurate predictions and strategic planning for such events, contributing to improved emergency management and recovery efforts. Anticipating the impacts becomes crucial, particularly in the context of the projected increase in the frequency of such events due to climate change, thereby strengthening our preparedness.

How to cite: Diakakis, M., Mavroulis, S., Filis, C., Bantekas, Y., Gogou, M., Katsetsiadou, K.-N., Mavrouli, M., Giannopoulos, V., Sarantopoulou, A., Nastos, P., Vassilakis, E., Konsolaki, A., Kotsi, E., Moraitis, S., Stamati, E., Bakopoulou, A., Skourtsos, E., Carydis, P., and Lekkas, E.: The diverse impacts of extreme storms in the European South. The case of Storm Daniel (2023) in Greece., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14898, https://doi.org/10.5194/egusphere-egu24-14898, 2024.

A.121
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EGU24-6088
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HS7.5
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ECS
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Rohtash Saini and Raju Attada

Widespread and multi-day heavy rainfall events, recorded during 08-09 July 2023 in northwest India, significantly impacted Himachal Pradesh, Punjab, and the Chandigarh region. These events resulted in devastating floods and extensive landslides, causing a substantial loss of lives and properties. Understanding such extreme weather phenomena is imperative for enhancing predictive capabilities and mitigating associated impacts. However, due to the complex topography of the Himalayas and limited observational data, poses challenges for investigating precipitation extremes. Against the background, in this study, we employ the Weather Research and Forecasting (WRF) model to investigate the atmospheric processes that led to unprecedented extreme precipitation. The innermost domain is configured with a horizontal grid spacing of 3 km, successfully reproduces the observed extreme rainfall. To assess the performance of different microphysics schemes in capturing key characteristics associated with heavy rainfall events, sensitivity experiments were conducted with five distinct schemes. Preliminary findings reveal that the Goddard microphysics scheme demonstrates good agreement with observations, closely followed by the Thompson scheme. Statistical analyses, including skill scores, further suggest that the Goddard microphysics scheme skillfully simulates the observed rainfall, displaying robust reflectivity values exceeding 35 dBZ in the core regions. The strong reflectivity indicates substantial hydrometeor concentrations, suggesting potential locations of deep convective activity associated with heavy rainfall. Detailed results of simulating the rainfall extremes over northwest India, along with feasible mechanisms influencing atmospheric conditions during extreme will be comprehensively discussed.

How to cite: Saini, R. and Attada, R.: Modelling and Prediction of Unprecedented Heavy Rainfall Event Over North India , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6088, https://doi.org/10.5194/egusphere-egu24-6088, 2024.

A.122
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EGU24-2163
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HS7.5
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ECS
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Sarvarbek Eltazarov, Ihtiyor Bobojonov, and Lena Kuhn

Index insurance has been introduced as an innovative and potential solution to mitigate several challenges caused by climate change in the agricultural sector. Despite the promising potential of index insurance, dissemination in developing countries is slow due to a lack of reliable weather data, which is essential for the design and operation of index insurance products. The increasing availability of model- and satellite-based data could ease the constraints of data access. However, their accuracy and suitability have to undergo a thorough assessment. Therefore, this study statistically and financially analyzes and compares the risk reduction potential of index insurance products designed employing various in-situ-, model- and satellite-based precipitation products (e.g., CMOPH, CPC, IMERG, GSMaP, MERRA, GLDAS, ERA5, PERSIANN, MSWEP, and MERRA2). This study employed county-level spring wheat yield data between 1982 and 2018 from 56 counties overall in Kazakhstan and Mongolia. The results showed that in the majority of cases in both countries, the hedging effectiveness of index insurance products designed based on IMERG is the highest. Moreover, among other data sources, the index insurance products designed using the PERSIANN, GLDAS and FLDAS showed higher risk reduction potential. Overall, this study highlights that satellite- and model-based precipitation products have higher accuracy and potential for index insurance design and operation than in-situ-based precipitation data.

How to cite: Eltazarov, S., Bobojonov, I., and Kuhn, L.: Climate risk-reduction potential of gridded precipitation data for agricultural index-based insurance development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2163, https://doi.org/10.5194/egusphere-egu24-2163, 2024.

A.123
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EGU24-15286
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HS7.5
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ECS
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Maxime Trevisani

According to France Assureur (French insurance unions), 2022 hail damage in France is estimated at more than €6.5 billion, i.e. more than half of all climate-related damage in 2022, or 60% of all hail damage accumulated between 2013 and 2021. This record-breaking year is in line with the growing concern about hail in France among public and private stakeholders. Despite its increasing impact on society the hail hazard in France remains largely unknown or under investigated at the national level, with a single 20x20 km hail risk map produced up in 1998 by F. Vinet using economic data (insurance) and measurements (hailpad). Hail hazard is poorly studied in France due to the great difficulty of observing or modelling hailfall, which are highly localised in time and space. The emergence of social networks since the late 2000s has led to a proliferation of potential hail observers across France. These new data, combined with insurance data, make it possible to study hail at a level of resolution never seen before in France.

The main objectives of our study are therefore to update the geographical assessment of the hail hazard in France, while improving the granularity of the existing geographical hail assessment. To this end we studied the hail hazard in terms of frequency and maximum diameter at the municipal level (average 16 km²), using hail reports (Keraunos, European Sever Weather Database) and insurance data (Generali France, around 5% market share) over the period 2013-2022.

Our study thus provides a resolution 25 times finer than that of Vinet and reveals a southwest - northeast axis dividing France into two parts: the southern part is heavily affected by hail while the northern part is less affected. It also highlights 3 main geographical areas with the highest hail hazard. The Massif Central stands out as the main hail-prone area in France, with a notable maximum in its northern part. The Bordeaux-Paris axis comes second, with a local maximum in the southwest Atlantic coast. In third place comes the Provence-Alpes-Côte d'Azur region, particularly in the Pre-Alps and Pre-Atlantic massifs. There also seems to be a correlation between orography and areas of high hail hazard, particularly noticeable in the Massif Central and Pre-Alps regions, but this assumption needs to be further investigated.

How to cite: Trevisani, M.: A 10-Year climatology of hail in France: towards an estimate of the hail hazard, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15286, https://doi.org/10.5194/egusphere-egu24-15286, 2024.

Posters virtual: Thu, 18 Apr, 14:00–15:45 | vHall A

Display time: Thu, 18 Apr 08:30–Thu, 18 Apr 18:00
Chairperson: Nadav Peleg
vA.20
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EGU24-611
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HS7.5
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ECS
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Amit Kumar Maurya, Somil Swarnkar, and Shivendra Prakash

The Indian Ganga Basin (IGB) is a highly prominent socioeconomic region in the Indian subcontinent. The IGB supports about 500 million individuals by providing sufficient freshwater for agro-industrial activities, mainly through the contribution of Indian Summer Monsoon (ISM) rainfall, which accounts for around 85% of the total rainfall received throughout the IGB. Any modifications in ISM patterns would substantially impact the availability of freshwater, and consequently, the socio-economic activities of the IGB region will be affected. This study aims to evaluate the historical changes in the monsoon rainfall characteristics from 1901 to 2019. Here, we conducted a detailed rainfall analysis in different sub-basins of the IGB where changes in monsoon rain spells are most noticeable and examined the hydrological extremes. We found that monsoon rain spell peaks have significantly increased across the major sub-basins of the IGB after 1960, implying the increased probability of flash flood hazards. At the same time, the monsoon rain spell has been depleted across the IGB after 1960, especially in the lower Indo-Gangetic plains. These results imply a rise in the occurrence of droughts. In addition, our interpretations also indicate a growing potential for combined hydrological extremes in the IGB. Further, the continuous rise in temperature and human-induced perturbations might exacerbate the existing extreme hydrological conditions. Thus, the findings of this study will be beneficial in implementing river basin management methods to assess the complex patterns of major hydrological catastrophes in the IGB.

How to cite: Maurya, A. K., Swarnkar, S., and Prakash, S.: Hydrological Analysis of Monsoon Rain Spells in the Indian Ganga Basin over the Last Century, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-611, https://doi.org/10.5194/egusphere-egu24-611, 2024.

vA.21
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EGU24-830
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HS7.5
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ECS
Surya Harilal, Raji Pushpalatha, Cibin Raj, Balmukund Singh, Unni Narayanan, and Maneesha V Ramesh

The frequency of landslides has increased recently due to uneven patterns of weather distribution and climate change. Major landslide predictions are based on rainfall models, and only a few studies consist of hydrological models, leading to low accuracy.  On the other hand, using hydrological parameters has considerably increased the accuracy of landslide predictions. This study focuses on interlinking the climate, surface, and subsurface flows on the landslide events in the Cauvery River basin, Karnataka, India, using the Soil and Water Assessment Tool (SWAT). Relative humidity, solar irradiance, wind speed, temperature, and precipitation are needed for the model, along with slope, land use, and digital elevation model (DEM). Mann-Kendall trend analysis is carried out to detect trends in rainfall and temperature in the study area, as these parameters can directly influence the surface and subsurface flows.  Preliminary results of the study indicate a strong correlation between the surface and subsurface flows on landslides along with the changing climatic conditions. The study region witnessed a series of landslide events in 2018, which, in turn, can be associated with the heavy surface flows observed using the model output for the same period. The derived correlation can further be used to forecast the landslide events with the surface and subsurface flow information. As an outcome, the study also proposes sustainable solutions to mitigate the impact of climate change and land conservation practices to protect the community. 

How to cite: Harilal, S., Pushpalatha, R., Raj, C., Singh, B., Narayanan, U., and V Ramesh, M.: Interlinking climate change, surface and subsurface flows on landslides in the Cauvery River basin, India , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-830, https://doi.org/10.5194/egusphere-egu24-830, 2024.

vA.22
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EGU24-8741
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HS7.5
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ECS
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Ajay Devda and Vishal Verma

Floods impact natural and human systems from multiple dimensions. The vulnerability to flood consequences is intricately linked to the hydrogeomorphic and socio-economic properties of the region. In a long run flood control infrastructure such as embankments evolve with the hydrogeomorphic and socio-economic properties and co produce the new set of vulnerabilities. Assessment of maladaptive contribution of flood control infrastructure is crucial in adaptive decision making and building resilience.The study analyzed flood vulnerability of the population residing inside the embankment area of the Kosi River basin from multidisciplinary parameters. The Kosi River embankment area covers around 890 Sq Km area and is home to nearly 0.8 million people who are facing a trifecta of issues, including regular flooding, scarcity of basic amenities, and loss of livelihood. The basin went through numerous flood-related research based on geomorphology, hydrology, and other physical factors; however, the flood impact assessment of embankments and its role within the socioeconomic dimension still needs to be explored. The present study unpacks flood vulnerability in 283 villages located within the Kosi embankment. Drawing upon thirteen attributes—comprising eight socio-economic and five hydro-geomorphic parameters—the analysis incorporates data from Sentinel-2, IMD, FMIS, the 2011 census report, and other pertinent survey reports. The study utilized analytical hierarchical process (AHP) to obtain relative priority order of parameters. Through the application of GIS analysis, we systematically formulated exhaustive vulnerability maps encapsulating socio-economic, hydrogeomorphic, and composite dimensions based on the weightage assigned to the selected parameters. The analysis highlights that nearly the entire population in the embankment region is susceptible to the effects of flooding, with ∼66% of the region having high and very high flood risk and ∼26% in areas with moderate risk. Furthermore, the outcomes reveal the maladaptive consequences of infrastructure solutions, manifesting as socio-economic disparities and exclusionary effects. The population living inside the embankment region exhibit notably impoverished socio-economic characteristics,including 32 % female literacy, approximately 90 houses constructed by  around 90 percent of houses are Kachha ( mud house), and highly rely on farm labor activities, which is highly lower than the region outside the embankment. Additionally, the outcomes bring to light the maladaptive consequences of infrastructure solutions, manifesting as socio-economic disparities and exclusionary effects. Residents within the embankment area exhibit notably impoverished socio-economic indicators, including a 32% female literacy rate, approximately 90% of houses are Katchha ( made from mud and straw), and economic dependency on agriculture labor activities, which is significantly lower than outside of the embankment. Moreover, the annual flood and longer periods of waterlogging cut off the population from other parts of the state. Lastly, the study discussed the source of vulnerability and adaptation options, which could be useful in developing comprehensive flood adaptation programs, including socioeconomic considerations.

How to cite: Devda, A. and Verma, V.: Assessing Flood Vulnerability and Maladaptive Effects Associated with Embankment-Based Flood Control Infrastructure : Hydrogeomorphic and Socioeconomic Analysis Kosi River Embankment Region, Bihar, India., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8741, https://doi.org/10.5194/egusphere-egu24-8741, 2024.

vA.23
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EGU24-19140
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HS7.5
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ECS
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Syed Bakhtawar Bilal and Vivek Gupta

Drought is a natural phenomenon characterized by an extended period of insufficient rainfall for a particular area. These deficit in rainfall leads to shortage of water reserves across surface and sub-surface storages. Variations in these shortages arise from diverse factors such as regional climatic variations, geographical features, and land-use patterns. The primary objective of this study is to assess the sensitivity of agricultural and hydrological systems to rainfall deficits across different climatic zones. We aim to quantify the degree of responsiveness of agricultural and hydrological droughts to varying precipitation deficiencies using various statistical and modeling techniques. By examining the diverse responses in different regions, this research seeks to enhance our understanding of precipitation shortages on drought dynamics.

How to cite: Bilal, S. B. and Gupta, V.: Sensitivity analysis of agricultural and hydrological droughts to rainfall deficits across India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19140, https://doi.org/10.5194/egusphere-egu24-19140, 2024.