ITS2.5/NH13.5 | Bridging natural and social sciences to study societal responses to extreme weather events
EDI
Bridging natural and social sciences to study societal responses to extreme weather events
Convener: Viktoria Cologna | Co-conveners: Simona Meiler, Roman Hoffmann, Joshua Ettinger, Chahan M. Kropf, Sonali Manimaran, Pui Man Kam
Orals
| Mon, 15 Apr, 08:30–12:30 (CEST)
 
Room N2
Posters on site
| Attendance Mon, 15 Apr, 16:15–18:00 (CEST) | Display Mon, 15 Apr, 14:00–18:00
 
Hall X4
Orals |
Mon, 08:30
Mon, 16:15
Extreme weather events such as tropical cyclones, heatwaves and floods threaten populations around the world. Climate change is increasing the frequency and intensity of many kinds of extreme weather events, which can combine with community exposure, inequalities and vulnerabilities to cause substantial harm. There is a growing literature at the intersection of the natural and social sciences studying the impacts of extreme weather events on populations as well as peoples’ behavioral, attitudinal, and emotional responses. For instance, studies have investigated how extreme weather and climatic changes influence food and water security, conflict and security risks, and health outcomes. Additionally, the field of environmental human mobility has witnessed remarkable progress in data collection, analytical methods, and modeling techniques. Further research has examined the responses of individuals and households to these threats, including climate-related emotions, environmental concerns, and climate policy support. These studies have been conducted in interdisciplinary settings, where social scientists closely collaborate with natural scientists to study populations that have been, or will be, impacted by extreme weather events.

Yet only few studies are currently harnessing the full potential of interdisciplinary collaborations in this space and several challenges pertaining to the choice of methods and the scale of analysis (e.g., regional, national) remain underexplored. This session aims to provide a platform for interdisciplinary work on extreme weather events and invites contributions from natural and social scientists interested in interdisciplinary studies on the societal impacts of and responses to extreme weather events. Furthermore, we highlight the topic of human (im)mobility with a perspective on addressing recent advancements, methodological innovations, novel use of data, challenges, or future prospects in modeling human mobility in the past, present, and future.

We invite contributions including but not limited to studies of:

- Environmental attitudes and behaviors influenced by extreme events
- Health and wellbeing effects of climate change and extreme events
- Migration and displacement due to extreme events
- Food production and security in relation to extreme weather
- The interplay between climate change, environment, and conflict
- Methodological challenges to interdisciplinary collaborations

Orals: Mon, 15 Apr | Room N2

Chairpersons: Viktoria Cologna, Simona Meiler
08:30–08:35
Economic, policy, and purchase preferences
08:35–08:45
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EGU24-21029
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Highlight
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On-site presentation
Sara M. Constantino, Giovanna d’Adda, Milica Vranic, and Elke U. Weber

Extreme weather events are increasing in frequency and severity, directly affecting economic growth and development, especially in low-income countries. Disasters may also have indirect effects through their impacts on economic preferences, including risk, time, and social preferences, which shape individual investment decisions and economic relationships. Using experimentally validated measures of six economic preferences in 64 countries, we find that recent exposure to natural disasters makes individuals on average more risk averse, less patient and less prosocial. The effects are strongest among individuals who are less resilient to shocks because they (a) live in countries with limited resources and inadequate social and institutional safety nets; or b) are in cultural contexts with “looser” social norms and lower social cohesion; or (c) are exposed to shocks against which it is hard to prepare. We also find that short- term exposure to natural disasters may hamper interpersonal relationships by decreasing negative reciprocity and social trust, but that higher lifetime exposure may actually increase trust and positive reciprocity over the long-term. Our results point to the importance of climate adaptation and mitigation policies and robust and rapid post-disaster relief measures that reduce the negative impacts of natural disasters, mitigating their indirect as well as direct impacts on economic growth and human development.

How to cite: Constantino, S. M., d’Adda, G., Vranic, M., and Weber, E. U.: Global Evidence of the Impacts of Natural Disasters on Economic Preferences , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21029, https://doi.org/10.5194/egusphere-egu24-21029, 2024.

08:45–08:55
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EGU24-14015
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ECS
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Highlight
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On-site presentation
Melissa Tier, Elke Weber, and Michael Oppenheimer

There is an increasing need for ex-ante climate adaptation policy planning and design. Moreover, meeting robust standards to minimize harm and environmental inequities will require innovative practices and foresight, but little is currently known regarding how such standards influence residents’ preferences for or against climate policies. One set of climate adaptation strategies ripe for such consideration is urban risk management for worsening flooding. These strategies are often complex and controversial (e.g., choices between protection, retreat, and relocation), and can vary widely in structure with regard to key justice components (e.g., types of distributive, procedural, and corrective justice).

 

This presentation will share results from a large-scale, international survey that examined a comprehensive set of justice values underlying residents’ urban flood policy preferences. The online survey was translated and administered in 5 cities globally (n=650 residents per city): Buenos Aires (Spanish), Johannesburg (Zulu & English), London (English), New York City (English, Spanish, & Korean), and Seoul (Korean). The survey explores which urban climate adaptation flood policies are generally preferred by residents, whether certain categories of policies are preferred over others, and whether certain characteristics of residents best predict their preferences. More specifically, analysis of survey data considers which variables are best predictors of differences in policy preferences: a) self-perceived vulnerability to flood risk; b) city of residence; c) political, economic, and psychological worldviews; or d) other common demographics. Preliminary analysis of survey results suggests that residents with higher self-perceived vulnerability to flood risk also have an increased likelihood of preferring more expansive adaptation strategies (i.e., not just homeowner-focused policies, not just protection strategies, and more reparative actions).

 

This survey was designed to integrate contemporary topics in environmental justice, climate adaptation, and urban planning. The hypothesis was that people who self-identify as more vulnerable to flood risk prefer policies that focus more on other vulnerable people – in other words, an empathy effect caused by higher salience of vulnerability. Moreover, this effect was expected to be stronger than that of city of residence, worldviews (e.g., political identities), and other demographic characteristics. The presentation will both review detailed statistical analysis of the survey data, as well as discuss recommendations for how to best frame risk management policies in order to increase support for policies aimed at minimizing environmental inequities.

 

This dissertation thesis project has been supported by the Princeton School of Public & International Affairs and the 2023 Young Scientists Summer Program at the International Institute of Applied Systems Analysis.

How to cite: Tier, M., Weber, E., and Oppenheimer, M.: Urban Residents’ Justice Preferences in the Design of Climate Adaptation Flood Policy, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14015, https://doi.org/10.5194/egusphere-egu24-14015, 2024.

08:55–09:05
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EGU24-13476
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On-site presentation
Ben Newell and Omid Ghasemi

An increasing number of organizations are providing climate risk information for real estate properties in the form of climate risk scores. We investigate individuals' attitudes toward the accuracy of such information and whether this information impacts participants' willingness to buy properties. In a series of online experiments, participants (N=612) were asked to rate the desirability of a range of properties based on different attributes, including price, size, and year built. These properties were paired with high, low, or no climate risk scores. Following these tasks, participants completed surveys measuring their beliefs and perceptions regarding climate risk. Experiment 1 manipulated risk-level between subjects and found that participants were less willing to buy high-risk properties than low-risk properties or properties with no risk information, with no significant differences between the last two. Experiment 2, manipulated risk scores within-subject and found that not only were the high-risk properties rated lower than no risk and low-risk ones, but participants were also more willing to buy the low-risk properties than those with no risk information. In Experiment 3, the same tendency to buy low-risk properties compared to high-risk ones was found among a sample of homeowners, regardless of the timeframe (12 months vs. 30 years) and the granularity (risk at the property-level vs. postcode-level) of the risk information. The findings also revealed that individual beliefs and perceptions of climate change did not impact willingness ratings for any of the property types, except in Experiment 3, in which the higher expected risk due to climate change was negatively related to willingness to buy high-risk properties. Together, the findings suggest that climate risk scores impact individuals' assessments of properties, regardless of their beliefs and experience with climate-related events. 

How to cite: Newell, B. and Ghasemi, O.: Evaluating the Impact of Climate Risk Scores on Property Purchase Decisions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13476, https://doi.org/10.5194/egusphere-egu24-13476, 2024.

09:05–09:10
Mobility, migration, and displacement
09:10–09:20
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EGU24-18203
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ECS
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Highlight
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On-site presentation
Kristina Petrova, Karim Zantout, Sandra Zimmermann, Katja Frieler, and Jacob Schewe and the the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP)

This study presents a novel approach to understanding the impact of climate extremes on human mobility by examining not only the immediate response to the occurrence of such events per se but also the effect of their duration and frequency over time. Utilizing the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) climate data in combination with recently released geo-located sub-national net migration data provided by Niva et al. 2023, we assess the influence of various climate-related events, including droughts, floods, crop failures, and tropical cyclones. Our analysis goes beyond the traditional binary assessment of whether climate extremes affect mobility, delving into the nuanced ways these recurrent events shape migration patterns in areas with different levels of socio-economic development and political inclusivity over time. We aim to capture the shifts in net migration at a granular level, providing insights into how populations respond to environmental stressors over short, medium, and long-term periods. This temporal aspect is crucial in understanding the resilience and adaptability of communities in the face of climate change. Our findings reveal significant variations in mobility responses depending on the nature and duration of climate extremes.  This study contributes to the broader discourse on climate change and human mobility by highlighting the importance of considering temporal dynamics in policy development and planning for climate resilience.

How to cite: Petrova, K., Zantout, K., Zimmermann, S., Frieler, K., and Schewe, J. and the the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP): Temporal Dynamics of Internal Mobility in Response to Climate Extremes: A Global Analysis., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18203, https://doi.org/10.5194/egusphere-egu24-18203, 2024.

09:20–09:30
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EGU24-7400
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Virtual presentation
Rachata Muneepeerakul

Migration is one of human’s most drastic adaptation strategies against unfavorable conditions. In this work, we developed a minimalistic mechanistic model for human migration, dubbed CHASE, is developed. The model is named after the factors it includes to capture human migration, namely CH = Changing mindset, A = Agglomeration, S = Social ties, and E = the Environment.  Numerical experiments were conducted by subjecting the human agents in the model to two different kinds of disturbances: sudden shocks and gradual changes. Model results revealed highly nonlinear interplay among diversity, distance barrier, and social ties. The results also showed distinct responses to sudden shocks and gradual changes, both in terms of dynamics of the populations and diversity patterns.  Some ongoing and future work will also be briefly discussed.

How to cite: Muneepeerakul, R.: Modeling human migration: a minimalistic mechanistic modelling approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7400, https://doi.org/10.5194/egusphere-egu24-7400, 2024.

09:30–09:40
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EGU24-16971
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On-site presentation
Eva Trasforini, Lorenzo Campo, Tatiana Ghizzoni, Andrea Libertino, Daria Ottonelli, Sylvain Ponserre, Lauro Rossi, and Roberto Rudari

The risk of displacement caused by natural hazards has been increasingly impactful and emerges as a topical issue point in the field of disaster risk management. Given the potential escalation of this phenomenon due to climate change, population growth and urbanization, enhancing displacement risk assessment through reliable models and data has become increasingly crucial. Different applications require approaches that can be adapted at different spatial scales, from local to global scale. In pursuit of this goal, we have devised a probabilistic procedure for estimating the potential displacement of individuals due to riverine floods. The methodology is based on a novel approach to vulnerability assessment which considers that people’s vulnerability depends on several physical and social factors such as direct impacts on houses, livelihoods and critical facilities (such as schools and hospitals). These concepts are seamlessly woven into a comprehensive probabilistic risk assessment. A modelling chain that incorporates climatic, hydrological, and hydraulic and exposure/vulnerability models can be run different resolution to predict impacts at different special scales, from local to global scale.

This approach already demonstrated its validity for in Fiji and Vanuatu, where the small size of the countries allows for the definition of a building scale exposure model. In the present study, our focus turns towards adjusting the methodology for large countries, where using a high-resolution exposure model becomes impractical.

For our case study, we selected three countries in the Horn of Africa—Ethiopia, Somalia, and Sudan—acknowledging their particular vulnerability to the challenges posed by recurrent floods and the resulting internal displacement.

To properly match the 90m resolution of riverine flood hazard maps and avoid distortions in the final risk computations, a specific procedure for downscaling global exposure dataset, such as the 1-km resolution Global Exposure Socio-Economic and Building Layer (GESEBL), was implemented using high-resolution population distribution products. The resulting exposure layers are a set of population distributions associated to different sectorial assets (residential, industrial and agricultural production, services), characterized in terms of physical vulnerability to floods.

Impacts of current and future flood scenarios on those assets may render them unable to provide their function, thus causing people to forcedly move. In this procedure we took special care to avoid double counting, i.e. those cases where people lose both habitual place of residence and livelihoods.

Displacement risk expressed in annual average displacement and probable maximum displacement was evaluated under current and future climate conditions with optimistic and pessimistic scenarios. The results indicate a potential 2 to 4 times increase in average annual displacement for optimistic scenarios compared to current conditions, with even higher risk for pessimistic scenarios.

The application of this methodology in larger countries paves the way for its implementation on a global scale.

How to cite: Trasforini, E., Campo, L., Ghizzoni, T., Libertino, A., Ottonelli, D., Ponserre, S., Rossi, L., and Rudari, R.: Regional probabilistic flood displacement risk assessment: the Horn of Africa case study, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16971, https://doi.org/10.5194/egusphere-egu24-16971, 2024.

09:40–09:50
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EGU24-18164
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ECS
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On-site presentation
Sandra Zimmermann, Katja Frieler, and Jacob Schewe and the ISIMIP Team

Every year, disasters force millions of people around the world to leave their homes. Disaster-induced displacement often leads to humanitarian hardship and imposes substantial costs on vulnerable, low-income societies in the Global South. With anthropogenic climate change increasing the intensity and number of extreme events in many regions globally, understanding and projecting disaster-induced displacement becomes increasingly important. Floods are among the main causes of disaster-induced displacements. However, the causes of variability in flood displacement over time and space are not well understood. Therefore, it is not known to what extent climate change has already affected displacement in the past, making it difficult to produce reliable estimates of future displacement risk.

In our study, we address the question of how much of the observed variability can be explained on the basis of process-based flood hazard modeling. We use the output of state-of-the-art global hydrological models forced with observational climate and direct human forcings to derive flood extents from the global hydrodynamic model CaMa-Flood. We first assess how well modelled flood hazards can explain annual variations in past displacement as recorded by the Internal Displacement Monitoring Center at a global as well as national scale, before also accounting for different vulnerabilities of communities by applying spatially-disaggregated vulnerability factors derived from comparing the simulated number of people affected by flooding to observational displacement data. We hence provide a comprehensive assessment of the explanatory power of the process-based fluvial flood hazard component concerning displacement.

How to cite: Zimmermann, S., Frieler, K., and Schewe, J. and the ISIMIP Team: Can we understand the variability in flood-induced displacement using process-based global flood modelling? , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18164, https://doi.org/10.5194/egusphere-egu24-18164, 2024.

09:50–10:00
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EGU24-18416
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ECS
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Virtual presentation
Eleonora Panizza, Yared Abayneh Abebe, Roberto Rudari, and Mauro Spotorno

The IGAD region in East Africa has experienced a rise in the occurrence and severity of floods over time, as a consequence of climate variability and change. Among member states, Sudan stands out as one of the most affected by recurrent floods, suffering significant damage to houses, livelihoods, infrastructure, and economic activities. Areas along the River Nile, in particular, are often affected by riverine flooding. These events continue to displace thousands of people annually in the country, while immobility in the face of disasters is also an issue. In response to this challenge, the design and implementation of effective flood risk mitigation policies have become paramount, addressing both physical and socio-economic perspectives. 

The aim of this research was to develop an agent-based model (ABM) to simulate human behavior and assess the impact of policies on flood displacement patterns in seven locations in Khartoum State, Sudan. To lay the groundwork for the ABM, a household survey was conducted to collect information about the socioeconomic characteristics, flood displacement experience, and risk perceptions of the resident population. The ABM operates as a tool for modeling the behavior of autonomous household entities in various 30-year hazard and policy scenarios. Policies, tested both individually and in combination, include the Early Warning System, the Awareness Programme, the Basic Income Programme, the House Repair Programme and the Build Back Better Programme. 

In the model, households’ actions and decisions within the different flood and policy scenarios depend on their personal characteristics. Elements that influence the decision to move or stay include risk perception, socioeconomic characteristics, and flood damage. This innovative model serves as an instrument for estimating the volume of displacement, evacuation, and immobility across different scenarios. It supports the identification of the most effective intervention strategy for the context under consideration. 

The focus of the presentation is on the results of the comparative policy analysis derived from the ABM simulations. These findings are also instrumental in supporting local and national decision-makers in mitigating the risk of flood displacement and immobility, thereby strengthening the resilience of communities to flood challenges.

How to cite: Panizza, E., Abebe, Y. A., Rudari, R., and Spotorno, M.: An agent-based model for testing the impact of policy options on flood displacement in Sudan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18416, https://doi.org/10.5194/egusphere-egu24-18416, 2024.

10:00–10:05
Coffee break
Chairpersons: Viktoria Cologna, Simona Meiler
10:45–11:05
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EGU24-14376
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solicited
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Highlight
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On-site presentation
Amanda Carrico

It is well known that the impacts of climate change to health and well-being are exacerbated by existing social inequality. Throughout the world, women face heightened vulnerability to climate stress due to pervasive power imbalances, gender norms, and economic marginalization. Interdisciplinary collaborations that carefully integrate social and physical data are critically needed to foster a deeper understanding of the processes that increase women’s exposure. In this talk, I share findings from recent work examining the effects of extreme weather on early and forced marriage, intimate partner violence, and social isolation of girls and women. I will discuss these trends in relation to recent progress in the opportunities available to women, and offer insights into the conditions that might support women’s well-being in the face of climate risk.

How to cite: Carrico, A.: Gendered Responses to Climate Change and the Well-Being of Girls and Women , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14376, https://doi.org/10.5194/egusphere-egu24-14376, 2024.

Gender, vulnerability, and preparedness
11:05–11:15
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EGU24-1005
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ECS
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On-site presentation
Akshita Choudhary, Anu Susan Sam, Harald Kaechele, and Pawan Kumar Joshi

Gender vulnerabilities to climate change are increasingly recognized in the global arena; however, attention to gender in the context of climate change in India is relatively recent. Agriculture is a crucial part of the country’s economy and the agricultural practices in the Indian Himalaya are highly influenced by gender dynamics due to traditional gender roles and various social and cultural constraints. This study provides empirical evidence on how gender plays a role in the susceptibility to climate change from a district of Central Himalaya in Uttarakhand. The study identifies the key indicators that affect vulnerability both within and between genders. Additionally, the gender data is categorized based on caste (social segregation) and lower and higher elevation in the hills (geographical segregation) for investigating gender-specific vulnerabilities - both inter and intra-gender - in agricultural households. The primary data were collected in the months, April - June 2022 from 298 sample households based on stratified sampling selected from 20 villages in the district, Almora, Uttarakhand. Categorical principal component analysis (Cat-PCA) was used to develop weights for adaptive capacity and sensitivity indicators. Based on the Inter-governmental Panel on Climate Change (IPCC) framework 2014 and the theory of intersectionality, an intrinsic gender vulnerability index is developed. A sensitivity analysis approach is further adopted to pinpoint the major indicators influencing gender intersectional vulnerabilities. The expected results go beyond the conventional gender paradigms by exploring the intersectional nature of vulnerability and recognizing the complex interplay of various socioeconomic factors such as caste, education, income, and access to resources that contribute to differential gender vulnerabilities.

Keywords: Gender vulnerability, intersectionality, climate change, Cat-PCA, Sensitivity analysis.

How to cite: Choudhary, A., Sam, A. S., Kaechele, H., and Joshi, P. K.: Identifying key indicators and exploring gender intersectional vulnerabilities to climate change in agricultural households: A study of Central Himalaya, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1005, https://doi.org/10.5194/egusphere-egu24-1005, 2024.

11:15–11:25
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EGU24-19508
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ECS
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On-site presentation
Julia Beier, Eva Preinfalk, and Susanne Hanger-Kopp

Climate change interacts with a multitude of socioeconomic characteristics (i.e. income, age, employment), determining individual risk and coping capacities. However, existing impact assessments of climate risk commonly focus on aggregate levels, leaving blind spots with respect to within-country distributional effects. Adhering to the concept of intersectionality, this study examines differential vulnerabilities and factors determining heterogeneities on a household level in the context of heat and flood related risks in Austria. 

We extend upon previous research by identifying differential vulnerabilities and the patterns determining heterogeneities among agents. To this end, we develop a mixed-methods approach, bringing together two ends of the spectrum: the generic representation of a single representative household and highly context specific individual risk determinants. Building on stakeholder involvement at different governance levels, qualitative insights from workshops and interviews are developed into narratives and storylines. These are vital for identifying key drivers of vulnerability and later integrated and combined with multivariate statistical analysis. Using the K-modes clustering algorithm, we combine geocoded socioeconomic data (e.g. age, sector and type of employment and income) with climate impact data (flood inundation level for different return periods, kysely days) on a 1kmx1km scale. Such development of archetypes aligns quantitative clusters with qualitative narratives, fostering mutual validation and a profound understanding of differential climate risk. Thus, the iterative exchange between quantitative and qualitative methods constitutes the backbone of this study. 

Through this approach, we identify reoccurring indicator combinations to disentangle the socioeconomic drivers of differential vulnerabilities and coping capacities in the context of flood- and heat-related climate risk. This sheds light on the within-country distributional implications of climate change, characterizing archetypical patterns of vulnerability and the constraints underlying adaptive capacities. Our findings contribute towards a more nuanced representation of society in climate impact assessments and enhance the understanding of the individual constraints limiting adaptive capacities, informing the development of targeted and just adaptation. 

How to cite: Beier, J., Preinfalk, E., and Hanger-Kopp, S.: Identifying archetypes of climate vulnerability: A mixed-methods approach for heat and flood related risk in Austria , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19508, https://doi.org/10.5194/egusphere-egu24-19508, 2024.

11:25–11:35
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EGU24-14059
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ECS
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On-site presentation
Isabella Hinks and Josh Gray

Despite feeding the majority of the global population, small (<2 ha) farmers are among the poorest and disproportionately vulnerable to climate changes. Their ability to improve yields amid increasingly severe and frequent climate shocks will largely determine the success of the UN’s Sustainable Development Goals (SDGs) to eliminate poverty and hunger. Because smallholder farmers play a central role in efforts to achieve global food security, many governmental and private institutions have influenced smallholders’ on-farm management practices through interventions. However, interventions led by different institutions have pushed communities of smallholders to adopt divergent adaptation strategies: Some communities have taken proactive measures by diversifying their crop rotations or implementing tree-based systems as natural climate solutions, while others have primarily used reactive measures, implementing adaptations that were directly informed by their recent experiences with extreme weather events (e.g., altering sow and harvest dates to avoid a period of extreme heat). Despite the deadly consequences of food shortages in smallholder communities, very little research has quantified the impact of specific adaptations on their sensitivity to inter-annual climate variability. Fortunately, the recent influx of satellite sensors has enabled us to remotely monitor changes in smallholder field-level cultivation practices and tree-based systems, and with high performance computing, we can scale these analyses across landscapes. Here, we integrated administrative yield data, multi-source satellite and weather data, and household and field survey data across India, Nepal, and Bangladesh in mixed-effect models to answer: Where, and how have smallholder communities adapted their cultivation practices? And, how have these adaptations impacted their resilience to weather shocks? The results of these findings were contextualized using household survey data of 2,000 smallholder farmers to understand the drivers of farmers’ decisions and their perspectives on climate-induced adaptations. Our findings can inform future interventions in the region, and the algorithms will be directly transferable to other regions of smallholder agriculture where farmers adopt distinct adaptations and experience other climate threats.

How to cite: Hinks, I. and Gray, J.: From Satellites to Soil: Integrating Satellite and Household Survey Data to Assess the Impacts of Adaptations on Smallholder Farmers’ Climate Resilience, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14059, https://doi.org/10.5194/egusphere-egu24-14059, 2024.

11:35–11:45
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EGU24-20639
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ECS
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Virtual presentation
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Md Abdullah Al Mamun, Jianfeng Li, Aihong Cui, Raihana Chowdhury, and Md Lokman Hossain

The coastal regions of Bangladesh have been struggling with extreme weather events, including frequent storm surges, heatwaves, droughts, and rising sea levels. These coastal regions provide the majority of the produced agricultural crops and sustain the lives and livelihoods of marginalized people of the country. Given the increasing frequency and intensity of extreme weather events, understanding the existing challenges in agriculture and the adaptive mechanisms in crop production is critical for ensuring agricultural sustainability and ensuring livelihoods in smallholder farmers in the coastal region. In this study, using qualitative and quantitative methods, we assessed the challenges and adaptive techniques in agriculture and the trajectory of climatic conditions in two agriculture-dominated but climate-vulnerable sub-districts in the southeastern coastal region of Bangladesh.

Using focus group discussions (FGDs) and key informant interviews (KIIs), we explored (i) the challenges faced by the farmers, and (ii) adaptive techniques farmers have adopted in addressing climate-induced stresses in two highly climate-vulnerable sub-districts in the southeastern coastal region of Bangladesh. Two drought indices (Standardized Precipitation Evapotranspiration Index: SPEI, and the Standardized Terrestrial water storage Index: STI) were used to assess the temporal trends of climatic conditions in the studied sub-districts. Qualitative information was analyzed by thematic and content analyses, while quantitative information was analyzed by the Kendall test.

Respondents in FGDs and KIIs identified untimely precipitation, droughts in crop growing seasons, limited irrigation water, and outbreaks of pests during flowering time are the major challenges in agriculture. Farmers have adopted resilient crop varieties to address these challenges. The prominent crop varieties are heat- and salt-tolerant rice, drought-tolerant vegetables, and pest-resistant crops. Notably, qualitative findings show that farmers are utilizing organic fertilizers (vermicompost) to improve soil health, mulching to keep the soil moist, storing rainwater in ponds to irrigate winter and summer crops, and growing shallow-rooted and short-rotation crops to better adjust to changing weather conditions. The study highlights the growing popularity of vermicompost in improving soil fertility and improving soil water holding capacity, indicating its potential as a nature-based solution in agricultural sustainability. Examination of the temporal trend of climatic conditions obtained from SPEI and STI values, we found that both of our studied sub-districts experienced increasing dry climatic conditions. The observed increasing growing season dry climatic conditions (obtained from 3- and 6-month SPEI and STI values) in both sub-districts support the documented responses of the respondents in FGDs and KIIs.

This study highlights the extensive problem of climate-induced stresses in coastal Bangladesh and its impact on crop production. It emphasizes the significance of adaptive practices, like stress-tolerant crop varieties, bio-fertilizers, rainwater harvesting, mulching, and cultivating short rotation and shallow-rooted crops to address the adverse impacts of climate change. The findings are of practical importance for the government, NGOs, and stakeholders for ensuring sustainable agriculture and food security in coastal Bangladesh.

How to cite: Mamun, M. A. A., Li, J., Cui, A., Chowdhury, R., and Hossain, M. L.: Integrating adaptive approaches in addressing climate-induced stresses: Evidence of a mixed-method study in coastal Bangladesh , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20639, https://doi.org/10.5194/egusphere-egu24-20639, 2024.

11:45–11:55
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EGU24-9975
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ECS
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On-site presentation
Yu Han and Cees van Westen

Hurricanes are among the most frequent and devastating natural disasters in tropical regions. These events often necessitate massive evacuations when warnings are issued, which often place a significant burden on transportation systems. The situation becomes even more complex and challenging when hurricanes coincide with other disruptive events, such as pandemics or compounded infrastructure damages. These compound scenarios not only dramatically increase community vulnerability but also add layers of complexity to emergency management, particularly in coastal communities with direct impacts. Understanding individual responses to such emergencies is vital for developing effective emergency management strategies. The focus of this study is to enhance our understanding of how individuals react and respond to emergencies in the face of such compound hazards. We concentrated specifically on the evacuation behaviors of residents in the state of Florida, U.S., during a major hurricane event. To this end, an activity-based model was developed. The model employs the Metropolis-Hastings algorithm, to generate a simulated population. The simulated population, characterized by diverse socioeconomic attributes, is designed to reflect the demographics and behaviors of the actual population in the study area. We integrated information from a local household hurricane evacuation survey and aggregated evacuation data to measure the evacuation decisions, timing, and destinations of individuals. We then applied the model to examine three distinct evacuation scenarios: a standalone hurricane, a hurricane coinciding with a pandemic, and a hurricane combined with storm surge flooding on the transportation systems. Our findings underscore the profound impact that compound hazards on transportation systems. We observed that the average travel time for evacuation could potentially double under compound hazard conditions. This highlights the potential inadequacy of current infrastructure resilience in handling complex emergency situations under compound hazards. This developed model offers valuable insights for assessing system-wide impacts of natural disasters in coastal regions and can be adapted for various scenarios to aid in disaster preparedness and response planning.

How to cite: Han, Y. and van Westen, C.: Modeling Evacuation Strategies in Response to Compound Hazards: Lessons Learned from a Major Hurricane Event in the US, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9975, https://doi.org/10.5194/egusphere-egu24-9975, 2024.

11:55–12:00
Text mining, information diffusion, and event attribution information
12:00–12:10
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EGU24-1695
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ECS
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On-site presentation
Jan Sodoge, Giuliano Di Baldassarre, Christian Kuhlicke, and Mariana Madruga de Brito

Historically, groundwater resources have been perceived as inexhaustible in Central Europe by policy-makers and the general public. However, recently increasing drought periods and user groups with competing interests caused conflicts about the usage of and access to groundwater resources. Groundwater-related conflicts, defined here as social issues resulting from divergent viewpoints among diverse stakeholders, have been extensively examined in regions with an extended history of water scarcity. Yet, there is limited research on the emergence of groundwater-related conflicts in Central Europe and the role of recent drought events in shaping these. Here, we study the emergence of groundwater-related conflicts in Germany since 2000 using a text-mining approach. Specifically, we investigate four research questions: (i) how are groundwater-related conflicts characterized, (ii) which influential stakeholders are shaping these conflicts, (iii) what are the spatio-temporal patterns of these conflicts and (iv) how do drought events and different socio-economic factors influence their occurrence? To address these questions, we use machine learning and text-mining techniques on more than one million newspaper articles to develop a spatio-temporal database of conflicts. We also extract and categorize involved stakeholders using a named entity recognition algorithm. Then, we use statistical modeling to link the occurrences of groundwater conflicts with drought indices and other additional explanatory variables. Our results reveal the growing diversity and geographical spread of groundwater-related conflicts in Germany. Also, our results shed light on the role of the recent drought events’ influence on conflicts. Our findings contribute to mapping the evolving landscape of groundwater-related conflicts in Germany and the effects of drought events. The proposed methods have the potential to enable large-scale studies of environmental conflicts using vastly available text data.

How to cite: Sodoge, J., Di Baldassarre, G., Kuhlicke, C., and Madruga de Brito, M.: Emergent vulnerabilities: exploring the role of drought for increasingly diverse groundwater conflicts in Germany , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1695, https://doi.org/10.5194/egusphere-egu24-1695, 2024.

12:10–12:20
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EGU24-14972
|
ECS
|
On-site presentation
Jiam Song and Jonghun Kam

Social network plays a critical role in risk communication diffusing information in near real time. Disaster-affected communities utilize their social network to report catastrophic damages and increase the perceived risk of the ongoing disaster by non-affected communities, which enhance their willingness to donate and support emergency aids to the affected communities. Previous studies have focused on social network structure or information diffusion separately. This study strives to reproduce the social response to natural disasters aims integrating the two aspects of social network structure and information diffusion. This study focuses on two classical and catastrophic U.S. disasters, such as 2012 flash drought and wildfire, to establish the social network during these two disasters and understand difference in the patterns of the risk communication within the data-driven social network and random social network (e.g., (the equal chance/importance of a nodes). Random social network is made from the LFR benchmark algorithm using the properties of the data-driven network, including node number, degree distribution, community distribution, and average degree. This study leverages over 120,000 (53,000) tweets that contains a term, drought (wildfire). In this study, a Susceptible-Infected-Recovered (SIR) model is employed to simulate the information diffusion patterns using the data-driven and random social network. After fitting SIR model with the Twitter data using these two social network-based simulations, this study aims to assess 1) the impact of the structure difference on risk communication and 2) the impact of influential users in different social network structures. Result shows that the trained SIR model using the data-driven social network reproduced the observed information diffusion patterns for the 2012 drought and wildfires but with relatively higher uncertainty in the information diffusion pattern for wildfires. The SIR model simulation with data-driven social network shows a faster information diffusion pattern with a higher information reach rate than that with the random social network. In closing, this study discusses limitations and opportunities of next-generation social dynamic modeling for natural disaster risk communication. This study highlights the value of an interdisciplinary approach in improving risk communication and developing a more efficient and effective mitigation policies for not only droughts and wildfires and other natural disasters.

How to cite: Song, J. and Kam, J.: Understanding the dynamics of information diffusion through data-driven social network modeling for the 2012 U.S. drought and wildfire, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14972, https://doi.org/10.5194/egusphere-egu24-14972, 2024.

12:20–12:30
|
EGU24-5601
|
ECS
|
On-site presentation
Sabine Undorf and Monika Undorf

Event attribution science quantifies the influence of anthropogenic climate change on the occurrence of extreme weather events. One incentive for such research is an assumed motivational effect on people’s climate change mitigation and adaptation efforts, but little empirical evidence exists regarding this. While subjective attribution has been shown to matter, the few studies concerned with scientific attribution were gathered in societies polarised above average. Moreover, scientists and stakeholders have suggested that intellectual and communicative obstacles hinder motivational effects. They also questioned any effect on adaptation (rather than mitigation) intentions.

Here, we present results using the high-impact flood in July 2021 in Germany to empirically test the motivational effect of scientific attribution on mitigation and adaptation intentions. Data from a nationally representative sample and oversamples from the two flood-affected federal states in a control (n=663) and an attribution (n=611) group were collected in March 2022. Both groups learned about the consequences and immediate causes of the flood. The attribution group additionally learned about the World Weather Attribution's result that climate change to date had made the associated heavy rainfall more likely and more intense and that this influence would increase further in future. Groups did not differ in socioeconomic factors; mediation analyses and ordinary least squares linear regressions were applied.

Results showed that learning about event attribution results increased people’s subjective attribution of the event to climate change and their mitigation and adaptation intentions. It also increased their belief that the climate is changing and that this is due to human activities. Subjective attribution, but not personal flooding experience, mediated these effects. The effect on adaptation but not mitigation intentions was positively related to low education and to far-right political orientation. We set the results in the context of related evidence, highlight methodological caveats, and discuss implications for climate/impact attribution science.

How to cite: Undorf, S. and Undorf, M.: Increased climate change mitigation and adaptation intentions through learning about an event attribution result for the 2021 European floods, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5601, https://doi.org/10.5194/egusphere-egu24-5601, 2024.

Posters on site: Mon, 15 Apr, 16:15–18:00 | Hall X4

Display time: Mon, 15 Apr 14:00–Mon, 15 Apr 18:00
Chairpersons: Viktoria Cologna, Simona Meiler
X4.97
|
EGU24-2160
|
ECS
Ann-Christine Link and Roman Hoffmann

Climate change is associated with increasing frequencies and intensities of extreme weather events. These can, directly and indirectly, shape human (im)mobility. While most research on migration in the context of climate change focuses on climate as a migration driver in origin areas, there is a gap in knowledge on the role of migration for climate resilience in the destination areas. This paper studies differences in resilience (resistance and recovery) to climatic shocks between migrant and non-migrant households in Ethiopia, a country that is highly exposed and vulnerable to climate change. We use longitudinal data from the Living Standards Measurement Study (LSMS) conducted by the World Bank to construct a comprehensive Well-Being Index, which is used to analyze the impacts of climatic shocks and identify households that are more or less able to resist and recover from shocks. We use fixed effect panel regression approaches to model the impacts of climatic shocks on well-being over time for migrant and non-migrant households. Further explorative mediation analyses yield insights into mechanisms explaining differences between households. We find that migrant households have an overall lower climate resistance as they experience double as high well-being impacts when exposed to climatic shocks compared to non-migrant households. Climatic shocks significantly reduce the food security of all affected households and, in addition, negatively impact access to basic infrastructures and health for migrant households. Mediation analyses suggest that these differential climatic impacts are mainly driven by characteristics of migrant-origin regions, including poverty. Migrant households originating from less prosperous regions still face disadvantages even if they now reside in more prosperous regions. This contrasts the experience of non-migrant households whose resilience benefits from increased prosperity in their region of residence. While migrant households show a lower resistance to climate shocks, they recover faster from climatic shocks, which can be associated with diversified livelihoods and remittances that take time to unfold. This research is highly relevant to policy as it improves the understanding of underlying factors shaping differential vulnerability to climate change impacts and supports targeted interventions to increase the resilience of affected households.

How to cite: Link, A.-C. and Hoffmann, R.: The Tail End of Migration: Assessing the Climate Resilience of Migrant Households in Ethiopia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2160, https://doi.org/10.5194/egusphere-egu24-2160, 2024.

X4.98
|
EGU24-3460
|
ECS
Karina Löffler, Andrea Damm, Heinz Gallaun, Judith Köberl, Dominik Kortschak, Petra Miletich, Lena Oberhuber, and Manuel Strohmaier

Climate change is causing temperatures around the globe to rise, leading to an increase in the frequency and intensity of hot days and heatwaves. In urban areas, this trend is further exacerbated by urban characteristics, such as the high building density and degree of sealing, the high concentration of anthropogenic heat sources or the reduced outgoing radiation. Extreme heat puts a strain on health, especially for elders and people with pre-existing illnesses. For effective and targeted prevention of heat-related morbidity and mortality, information on the spatial variance of people’s exposure and sensitivity, but also their adaptability towards heat can be of great importance.

A common practice for determining the distribution of vulnerable population groups within a city or an area is to construct a spatial Heat Vulnerability Index (HVI) based on findings and data from natural and social sciences, including e.g. socio-economic data, health data, remote sensing data, and climate data. However, there is no standardized workflow but a variety of approaches for the construction of an HVI, which may lead to significant differences in the calculated index ranks. In order to assess the impact of changes in the method design on the resulting index, we test different input data sets, weighting methods and spatial scales for the construction of a spatial HVI for the city of Graz (Austria). The input parameters for the HVI include temperature data, derived from satellite data and weather stations, as well as spatial socio-economic data that describe the population’s sensitivity towards heat and the capability to adapt to high temperatures. By conducting an uncertainty analysis and a global variance-based sensitivity analysis, the partial contribution of changing input variables, chosen weighting methods and different spatial scales to the output’s variance is determined. In addition, a local sensitivity analysis compares the application of land surface temperature derived from thermal satellite imagery to the use of station temperature data for the construction of an HVI.

How to cite: Löffler, K., Damm, A., Gallaun, H., Köberl, J., Kortschak, D., Miletich, P., Oberhuber, L., and Strohmaier, M.: Using data and findings from natural and social sciences to assess urban heat vulnerability: a comparison of different methodologies., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3460, https://doi.org/10.5194/egusphere-egu24-3460, 2024.

X4.99
|
EGU24-4419
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ECS
Complex Dynamics of Human Migration: Beyond Linear Thinking
(withdrawn)
Woi Sok Oh
X4.100
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EGU24-4576
|
ECS
muhadaisi airiken and ShuangCheng Li

Drought, flood, hail and low temperature frost (LTF) are the main agrometeorological disasters in China. However, a comprehensive and quantitative study on the long-term trend of farmland and economic damage across the country is still lacking and needs to be carried out urgently. Based on historical statistical data from yearbooks and bulletins, the overall characteristics of the impacts of provincial meteorological disasters on population, economy and farmland during 1989-2022 were analyzed by using Mann-Kendall trend test at yearly and provincial scales in China. The results showed that the proportion of direct economic losses caused by meteorological disasters to GDP showed a decreasing trend. The SGD13.1 index, based on the number of deaths and the value of disaster losses, shows that there are abrupt years on the time scale under the Mann-Kendall trend test. In the past 30 years, crop loss in China has increased first and then decreased under natural disasters, and drought is the most serious type of disaster that causes farmland loss. The Person correlation analysis combining disaster intensity index and multiple factors shows that agricultural economic output has a significant negative correlation with disaster intensity, SDG13.1 and total precipitation, and a positive correlation with average annual temperature. There was a significant positive correlation between SDG13.1 and disaster intensity index. The results of this study systematically reveal the damage characteristics of meteorological disasters to socio-economic system in China, which are critical and necessary for disaster risk reduction and adaptive strategy development.

How to cite: airiken, M. and Li, S.: Spatiotemporal variations in damages to socio-economic system from meteorological disasters in mainland China during 1989–2022, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4576, https://doi.org/10.5194/egusphere-egu24-4576, 2024.

X4.101
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EGU24-8637
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ECS
Stewart Jennings, Andrew Challinor, Jennie Macdiarmid, Edward Pope, Thomas Crocker, Weston Anderson, Richard King, Stephen Whitfield, Rebecca Sarku, Christian Chomba, Masiye Nawiko, Lucas Rutting, and Marieke Veeger

Achieving climate-smart nutrition security in sub-Saharan Africa is an urgent challenge due to increasing climate risks to agricultural production, population growth and food price volatility This necessitates an integrated evidence base that takes into account not only future food system modelling but wider academic expertise and stakeholder knowledge and the plausible and desirable transformations that these information streams can provide. Accordingly, we use the integrated Future Estimator for Emissions and Diets (iFEED) to explore scenarios of food system transformation towards nutrition security. iFEED integrates climate, crop and land use modelling to explore scenarios of relevance to the policy landscape, as informed by stakeholders, assessing the adequacy of energy and nutrient supplies to meet dietary requirements at a population level. Our results show that calories are not always sufficient at the population level in extremely hot and dry years by mid-century in Zambia, even when maximising food production on available land. The majority of micronutrients also remain below population requirements. An alternative scenario where crops for population level nutrition security are prioritised shows that there are larger calorie shortfalls in extremely hot and dry years, although more micronutrient requirements are met than in the production-focused scenario. Both scenarios show benefits, and we point to ways forward that address the challenges to achieving climate-resilient nutrition security in the region. We also introduce our latest thinking on a new inclusive assessment framework that aims to expand iFEED to incorporate bottom-up disruptive seeds work and top-down modelling across spatial scales to deliver socially-equitable nutrition security in Kenya.

How to cite: Jennings, S., Challinor, A., Macdiarmid, J., Pope, E., Crocker, T., Anderson, W., King, R., Whitfield, S., Sarku, R., Chomba, C., Nawiko, M., Rutting, L., and Veeger, M.: An inclusive assessment framework for exploring climate-resilient nutrition security in sub-Saharan Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8637, https://doi.org/10.5194/egusphere-egu24-8637, 2024.

X4.102
|
EGU24-14994
David Lallemant, Sonali Manimaran, Thannaletchimy Housset, and Sylvain Ponserre

Coastal communities are expected to be highly exposed to rising sea levels and more frequent and intense tropical storms in the coming decades, with forced migration (or displacement) highly likely in many of these places. The exposure to these hazards is driven not just by climate change, but also by growing populations and rapid urbanisation of coastal cities. However, the extent of forced migration will be highly variable, and will be dependent on pre-existing physical and social vulnerabilities present in each location. Therefore, in order to reliably forecast future forced migration due to sea-level rise and tropical storms, it is necessary to construct spatially explicit displacement curves that link hazard levels to the migratory response of communities. This study has calibrated displacement curves through regression analysis for the Philippines based on historical internal migratory movements due to coastal flooding and tropical storms. The data for calibration was obtained from the Internal Displacement Monitoring Centre and governmental disaster reports, and the calibration was performed at the level 3 administrative boundaries. With the displacement curves, critical thresholds of flood and wind damage, at which point forced migration occurs, are identified. Subsequently, these displacement curves are combined with projections of future sea-levels and tropical storms in order to forecast the forced migration of communities under climate change. The displacement curves can be used by researchers, planners and policymakers to understand the varied migratory response of communities to sea-level rise and its associated hazards. This will allow for effective adaptation plans to be devised in advance in order to manage such forced migration in a manner that allows communities, including vulnerable ones, to relocate and avoid the adverse impacts of a changing climate.

How to cite: Lallemant, D., Manimaran, S., Housset, T., and Ponserre, S.: Calibrating Displacement Curves to Forecast Forced Migration due to Sea-Level Rise and Tropical Storms, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14994, https://doi.org/10.5194/egusphere-egu24-14994, 2024.

X4.103
|
EGU24-20205
Michael Friesenecker, Thomas Thaler, Monika Mayer, Harald Rieder, Herbert Formayr, Christian Schmidt, and Lehner Fabian

Assessing the spatio-temporality of risks associated with climate change have become dominant in disaster risk research. However, integrated assessments of spatio-temporal aspects combing hazard, exposure and social vulnerability is still under-researched, especially in the fields extreme heat events and heightened ozone concentrations. Studies frequently tend to concentrate either solely on the hazard dimension, such as heatwaves and ozone exceedances, neglecting their interactions (Feron et al. 2023), or solely on isolated spatio-temporal assessments of social vulnerability and exposure (Santos et al. 2022). Using the recent risk conception of the latest IPCC report, we analyze risk as the cumulative interaction of hazard, exposure and vulnerability for historical trends and near future scenarios.

A novel data set allows for an integrated assessment of historic spatio-temporal trends as well as near-future trends using different SSP-RCP combinations (SSP2-4.5 & SSP3-8.5) at census tract level. To assess the combined impact of temperature and ozone extremes, we utilize bias-corrected model fields from high resolution runs of the coupled chemistry-climate model WRF-Chem. Population data was projected until 2050 by combining historical growth rates for selected indicators with national change rates from the Shared Socio-economic Pathways (SSP) database by IIASA (Riahi et al. 2017). Regional variations in national SSP change rates are weighted with regionalized projections for population and age groups, and historic data on income and education from the Eurostat Database.

Methodologically, we use the Adjusted Mazziotta-Pareto Index (AMPI) normalization method to overcome the limitations of comparing z-scored values over time as reported by Santos et al. (2022). This has the advantaged that all values across all periods of time are considered in normalization (Mazziota & Pareto 2022). Bases on the integration into a composite indicator, we, first, performed a multivariate analysis of how sub-indicators for hazard, exposure and social vulnerability relate to each other for Austria. Second, we applied global and local Moran’s I statistics to analyze if the spatial patterns have changed in terms of spatial heterogeneity or spatial clustering over time.

The paper concludes by highlighting the needs of integrated risk assessments and discusses the potentials and limitations of our assessment approach. Finally, possible benefits of the interdisciplinary and small-scale use of SSP-RCP combinations for a more comprehensive formulation of informed policy guidelines.

 

Feron, S., Cordero, R. R., Damiani, A., Oyola, P., Ansari, T., Pedemonte, J. C., ... & Gallo, V. (2023). Compound climate-pollution extremes in Santiago de Chile. Scientific Reports13(1), 6726.

Mazziotta, M., & Pareto, A. (2022). Normalization methods for spatio‐temporal analysis of environmental performance: Revisiting the Min–Max method. Environmetrics33(5), e2730.

Riahi, K., Van Vuuren, D. P., Kriegler, E., Edmonds, J., O’neill, B. C., Fujimori, S., ... & Tavoni, M. (2017). The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global environmental change42, 153-168.

Santos, P. P., Zêzere, J. L., Pereira, S., Rocha, J., & Tavares, A. O. (2022). A novel approach to measuring spatiotemporal changes in social vulnerability at the local level in Portugal. International Journal of Disaster Risk Science13(6), 842-861.

How to cite: Friesenecker, M., Thaler, T., Mayer, M., Rieder, H., Formayr, H., Schmidt, C., and Fabian, L.: An integrated assessment of future risks of climate change for Austria: spatio-temporal trends of ozone, heat, and social vulnerability , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20205, https://doi.org/10.5194/egusphere-egu24-20205, 2024.

X4.104
|
EGU24-19158
|
ECS
|
Highlight
Marthe Wens, Hans de Moel, Anne van Loon, Michel Isabellon, Daria Ottonelli, Sylvain Ponserre, and Lauro Rossi

The characterization of drought hazards remains a complex endeavor, primarily due to the absence of a universally accepted definition for a "drought event." Different deficits across various parts of the water cycle contribute to a spectrum of drought consequences, rendering the definition contingent upon the impacts incurred. Moreover, quantifying drought vulnerability poses challenges given the intricate interplay among socioeconomic, political, and environmental factors that influence the relationship between a drought event and its impacts on exposed production systems, people and nature. 
Our work addresses these challenges by introducing a novel data-driven methodology employing an array of drought indices and several datasets on observed drought impacts. Applying decision tree-based AI techniques, this method identifies combinations of hydrometeorological conditions known to generate societal consequences, and as such is able to estimate probabilistic drought disaster risk.

The presented impact-based approach is generalizable and impacts evaluated include energy production losses, internal displacement, crop and livestock damage, malnutrition, ecosystem health degradation, and strains on drinking water utilities. Illustrated through a case study in the Horn of Africa, this contribution exemplifies the quantification of expected annual drought impact, whereby impact is measured as the number of drought-induced internally displaced persons (IDPs). Drawing on the latest IDMC Displacement Tracking Matrix data, we assessed drought displacement risks under current and projected climate scenarios for Somalia and Ethiopia. Both countries grapple with complex human mobility dynamics, driven by a multitude of push and pull factors. Our findings reveal average annual IDPs up to 2% in some regions in Ethiopia, rising to 3% with unmitigated climate change. In Somalia, the majority of regions are anticipated to experience on average >10,000 drought-induced IDPs annually, under all future projections. Our model demonstrates proficiency in distinguishing prolonged and flash droughts as drivers for displacement. Furthermore, it facilitates the identification of hotspot areas, thereby supporting drought disaster risk reduction decisions and proactive policies.

How to cite: Wens, M., de Moel, H., van Loon, A., Isabellon, M., Ottonelli, D., Ponserre, S., and Rossi, L.: A data-driven approach to predict water security and societal impacts: the risk of drought-induced internal displacement in the Horn of Africa., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19158, https://doi.org/10.5194/egusphere-egu24-19158, 2024.

X4.105
|
EGU24-20362
|
ECS
Local adaptation practices to climate change in relation to food availability and production in Amazonia
(withdrawn after no-show)
Julia Menin and Ryuji Soma
X4.106
|
EGU24-16735
|
ECS
Steffen Lohrey, Pui Man Kam, Bianca Biess, Tabea Cache, Sabrina Di Vincenzo, Radley M. Horton, and Lisa Thalheimer

The 2022 Pakistan floods have been unprecedented in their extent. They affected around 33 million people, caused about 15 billion USD in damages, and took the lives of more than 1,800 persons, dominantly in the southern parts of the country.

Effective disaster response requires fast assessments of likely impacts from hazardous weather to inform decision-makers and guide relief efforts for early action. Displacement modeling is a key technique towards these goals. However, displacement modeling which accounts for socio-economic components and uncertainties is methodologically challenging, and quantitative evidence largely remains limited and fragmented. Much work is needed to resolve these.

This study aims at providing a case study for disaster displacement modeling by using the open-source impact assessment platform CLIMADA to investigate the extent by which flood-related hazards can be used to quantify displacement numbers in a data-limited region. Here, we estimate displacement from the 2022 Pakistan floods in Sindh province as a case study. We combine data on flood depth, exposed population, and provide impact functions that relate vulnerability of people likely to be displaced. We further use published numbers of affected people as target data for our model. The centerpiece of our analysis is the choice of impact functions. We test different forms of impact functions as well as assumptions about critical flood depths to proxy the number of displaced people, first using ex-ante assumptions, and then a numerically optimized version.

With ex-ante assumptions, our model predicts a range of 1.94 to 5.65 million of displaced people in Sindh province, as compared to a total number of 6.76 million as reported by government sources. When we apply numerically optimized impact functions, the results closely resemble those obtained using the ex-ante assumptions, indicating that the current methods underestimate the extent of displacement. Additionally, we have evaluated the relationship between local vulnerability and the level of urbanization, and our findings reveal a negative correlation.

We use this model to explain different displacement estimates for the 2022 floods across Pakistan and thereby contribute a case study to the growing field of displacement models, and towards the development of more refined ones. It highlights opportunities as well as limitations, and is a quantitative contribution to an existing discussion on how much disaster-related displacement can be modelled, and in how far assumptions can be generalized. These insights also support a better understanding of displacement and migration from future climate risks.

How to cite: Lohrey, S., Kam, P. M., Biess, B., Cache, T., Di Vincenzo, S., Horton, R. M., and Thalheimer, L.: Modeling human displacement in the 2022 Pakistan floods: Current gaps and opportunities., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16735, https://doi.org/10.5194/egusphere-egu24-16735, 2024.

X4.107
|
EGU24-13023
Nina Nikolova and Simeon Matev

The water footprint of maize production is an indicator that provides information not only about direct water use for crop yields but also about indirect water use and virtual water trade. The general aim of the present research is to enlarge the knowledge about climate variability's impact on agriculture concerning improving sustainable water use for crop production. The accent of the proposed work will be on the assessment and analysis of green (rainfed production) and blue (irrigation water) water used for growing maize crops in the Danube Plain (Bulgaria).

The investigation is based on the following data: climatic data (air temperature, precipitation, wind speed, relative humidity); statistical data from agriculture, local authorities, and farmers (data about crop parameters and yields, and irrigation), and geographical data (climatic maps, maps about land use, soil maps, maps of main agricultural plants dissemination). The calculation and assessment of the water footprint of growing maize is done by the application of Cropwat software. The water needed for irrigation under various crop management options is determined. The main investigated period is 1961-2022 but special attention is given to water footprints of maize production during the extreme dry and extreme wet years. The results of the present work allow us to identify the hotspots regarding water use and water scarcity. The knowledge about the water footprint and climate-agriculture relationship could be used in water resources management and for effectively coping with the environmental and economic problems related to water scarcity and drought.

Acknowledgments: This study has been carried out in the framework of the project “The Nexus Approach in Agriculture. The water-food nexus in the context of climate change”, supported by the Ministry of Education and Science (MES) of Bulgaria (Agreement № КП-06-КОСТ-2/17.05.2022 and is based upon work from COST Action NEXUSNET, CA20138, supported by COST (European Cooperation in Science and Technology).

How to cite: Nikolova, N. and Matev, S.: Water Footprints of Growing Maize Crops in the Danube Plain (Bulgaria), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13023, https://doi.org/10.5194/egusphere-egu24-13023, 2024.

X4.108
|
EGU24-4863
|
ECS
Dezhen Yin and Fang Li

Extreme weather and climate events, such as extreme temperatures, droughts, and floods, cause significant yield losses and threaten global food security. Their frequency and intensity have increased in recent decades, a trend expected to continue. China is the world's largest grain producer and also a country where extreme events occur frequently. Nevertheless, the influence of extreme weather and climate events on crop yields in China is not yet well understood. This study quantified the impact of heat waves, frost, droughts, and floods on the yields of wheat, maize, rice, and soybean in China from 1970 to 2019, using the superposed epoch analysis (SEA) method, agricultural statistics collected from the National Bureau of Statistics of China, and crop calendar reanalysis dataset. Furthermore, the performance of 13 global gridded crop models (GGCMs) in simulating these impacts is evaluated. The results show that heat waves, frost events, droughts, and floods significantly decrease crop yields by 2.1%, 1.0%, 2.2%, and 1.7% for wheat, maize, rice, and soybean, respectively, accounting for 23.6%, 10.5%, 21.4%, and 18.9% of the interannual variability. Yields of different crop types in China are sensitive to specific extreme weather events. The GGCMs effectively capture the impact of droughts, with nine out of thirteen models detecting a significant effect, yet they struggle to accurately simulate the effects of heat waves, frost events, and floods, with only five, two, and two models detecting these impacts, respectively.

How to cite: Yin, D. and Li, F.: Influence of Extreme Weather and Climate Events on Crop Yields in China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4863, https://doi.org/10.5194/egusphere-egu24-4863, 2024.

X4.109
|
EGU24-18736
|
ECS
Mercè Cisneros, Josep Barriendos, Mariano Barriendos, Agustí Esteban i Amat, Cristina Simó, Claudi Aventín-Boya, and Javier Sigró

The unequivocal global warming of the climate system and the clear influence of human activities underscore the urgency of addressing the present challenge of Earth's warming. The exploration of past climate patterns presents significant opportunities in this regard.

Past climate information in high-mountain-areas, such as the Catalan or Aranese Pyrenees, is often still scarce. This is attributed to various reasons. On one hand, instrumental data series for these regions during the 20th century are not abundant and/or frequently start only from the 1960s. On the other hand, concerning climate information derived from historical documents for the past centuries in some of these regions, although its potential has been demonstrated in previous studies, it remains largely unexplored. Given all of this, it is not difficult to realize that these high-mountain-regions may exhibit a particular vulnerability in the face of current conditions of global warming. At the same time, its reactivity allows for the swift documentation of changes, as observed in the rapid regression of permanent Pyrenean glaciers over the past 50 years.

It is important to note that, given the strategic position of many of these locations as passages and border areas, especially from the mid-17th century onward, with the consolidation of European nation-states, there comes the implementation of the concept of political borders, various events throughout history (such as fires, wars, etc.) have led to the total or partial destruction of numerous documents. Frequently, the history of certain events is only preserved through oral accounts passed down from generation to generation.

Life in the Pyrenees has often been challenging, sustained by those individuals who have remained faithful, resisted, and persevered. The people of the Pyrenees have relied on the forest, pastures, and rather lean lands for their livelihood, and transportation has consistently posed difficulties. Additionally, sporadic phenomena of various kinds, whether historical, economic, or natural (avalanches, floods, earthquakes...), the latter strongly impacting the natural hazards in mountainous areas, have triggered changes in the villages or, in the worst cases, their abandonment and/or disappearance. The impact on these communities has often resulted from a combination of phenomena that is challenging to disentangle.

Here, we present an initial exploration of abandoned villages in the Catalan and Aranese Pyrenees during the Little Ice Age and the 20th century. The developed methodology includes the classification of depopulated areas based on various attributes: moment of disappearance, cause, altitude, and location. We have examined the climatic trends that could have affected the regions of the depopulated areas at different times. Causes include natural phenomena such as avalanches and landslides, as well as other factors like epidemics or plagues. The combination of these physical and biological factors can produce strong economic crisis at different scales. In extreme cases, this deterioration leds to the abandonment of specific villages. It is worth noting the centrifugal effect of large industrial and service agglomerations located in proximity, which have significantly contributed to the depopulation of Pyrenean settlements, whether seasonally (especially in the 19th century) or permanently (particularly in the 20th century).

How to cite: Cisneros, M., Barriendos, J., Barriendos, M., Esteban i Amat, A., Simó, C., Aventín-Boya, C., and Sigró, J.: Abandoned villages in the Catalan and Aranese Pyrenees during the Little Ice Age and the 20th Century: exploration of climate forcings through historical documents, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18736, https://doi.org/10.5194/egusphere-egu24-18736, 2024.

X4.110
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EGU24-17120
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ECS
Sinne van der Veer, Raed Hamed, Hande Karabiyik, and Jamal Roskam

Recent studies that address the impacts of extreme weather on crop yields, are predominantly focused on expansive geographical scales and generally ignore the role of management practices in modulating the dynamics of weather-crop sensitivities. In our study, a unique dataset containing data from the Dutch Minerals Policy Monitoring Program and the Farm Accountancy Data Network (FADN) is used to explore the relationship between extreme weather and crop yields at farm level in the Netherlands. The dataset consists of unbalanced panel data from the years 2006 to 2021 including an average of about 1,500 farms. The Standardized Precipitation Evapotranspiration Index (SPEI) is used to reflect weather anomalies, both extreme wet and dry conditions. The climatological variables necessary to compute the SPEI are estimated at field-level using data gathered by the Royal Netherlands Meteorological Institute from 277 precipitation stations and 18 climate stations. In total, ten types of crops are covered and the role of soil type, irrigation and nutrient application in modulating the relationship between extreme weather and crops is elucidated. Distinction is made between drought and excessive precipitation during the planting-, growing- and harvesting period. The results show substantial impacts from drought during the growing- and harvesting period and excessive precipitation during the planting- and growing period. Severe droughts show statistically significant (p≤0.05) reductions in yield for nine crops, and lead to yield reductions ranging from 10 to 25 percent when only occurring during the growing period. Meanwhile, eight crops show statistically significant (p≤0.05) reductions in yield due to severe precipitation excess, with reductions ranging from 5 to 20 percent from excessive precipitation during the planting period. Soils such as sand or loess amplify the negative impact of drought on crop yield, while softening the impact of excessive precipitation. Furthermore, irrigation and nutrient application (both nitrogen and phosphate) are shown to moderately decrease the impact of extreme weather on crop yield, with substantial differences depending on crop type and the period in which the extreme weather event occurred. The findings of this study provide valuable insights to guide local adaptation priorities which are critical given the projected increase in the intensity and frequency of extreme weather under climate change.

How to cite: van der Veer, S., Hamed, R., Karabiyik, H., and Roskam, J.: Investigating the Effects of Extreme Weather and their Interactions with Farm Management on Crop Yields in the Netherlands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17120, https://doi.org/10.5194/egusphere-egu24-17120, 2024.

X4.111
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EGU24-4065
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ECS
Ola Ali, Elma Dervic, Rainer Stütz, Ljubica Nedelkoska, and Rafael Prieto-Curiel

The global surge in displacement, with nearly 110 million people uprooted due to violence, underscores the pressing need to comprehend the challenges faced by refugees. Population growth, environmental crises, and political instability contribute to this crisis, projecting an escalating trend in the decades ahead. While hosting countries strive to address concerns related to labour markets, state provisions, and cultural integration, understanding the well-being of refugees upon entry needs to be more adequately explored. This study focuses on refugee stability and integration, employing Austria as a case study. Utilising comprehensive administrative data spanning November 2022 to November 2023, we examine residence movements as a proxy for stability. Our findings reveal a stark contrast in the stability of refugees compared to other migrant groups. Analysing movement profiles, we establish that refugees exhibit significantly higher rates of residential mobility than their counterparts, especially among male refugees. This imbalance persists even when comparing refugees to migrants from top refugee-sending countries without official refugee status. This study contributes valuable insights into the intricate dynamics of refugee stability, shedding light on the enduring challenges faced by this population. By examining movement patterns as a key indicator, we provide a nuanced understanding of the residential experiences of refugees, that can inform targeted policies and interventions for enhanced refugee well-being and integration.

How to cite: Ali, O., Dervic, E., Stütz, R., Nedelkoska, L., and Prieto-Curiel, R.: Quantifying the Stability of Refugee Populations: A Case Study in Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4065, https://doi.org/10.5194/egusphere-egu24-4065, 2024.

X4.112
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EGU24-3565
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ECS
Dariya Ordanovich, Ana Casanueva, Aurelio Tobías, and Diego Ramiro

Nowadays, the rise in the global temperatures are a source of concern, particularly in the Mediterranean region, where Spain is already witnessing notable consequences for its aging population. Predictions for the end of the XXI century reveal a persistent increase in air temperatures along with an increment of extreme episodes. Abnormal heat, once considered an 'environmental accident', is now a serious public threat. This contribution endeavors to quantify the added effects of heat wave exposure on mortality by demographic and socioeconomic strata during the period of 45 years in Spain at the provincial level. Moreover, we aim to explore the temporal evolution in these effects and variations in its spatial patterns, especially focusing on the inequality aspects that shape the health outcomes in an increasingly aging population.

Here we leverage daily individual mortality data and other contextual data on population from the National Institute of Statistics of Spain and air temperature estimates from the ERA5 global reanalysis. We also use the historical settlement data as a proxy for population distribution from 1975 onward. To estimate the main and added effects of heat waves we fit a quasi-Poisson time-series regression model using a distributed lag non-linear model with 10 days of lag, controlling for trends and day of the week.

We analyze approximately 15.8 million of deaths registered in Spain between 1975 and 2019. During the selected time window, we expect to see a shift in the temperature-mortality association from a V-shape in the first decades of the observation to a U-shape by the end of the period all across the provinces, thus revealing a progressive flattening of the exposure-response curve. We also expect to observe an overall reduction in the mortality burden associated with the temperatures. In particular, we anticipate more significant and rapid decline in the cold-related risks and attributable fractions in comparison with the heat-related ones, with some latitudinal variations across the country.

On the other hand, we witness a steady increase in the incidence of the heat wave episodes with time all over the country. We expect to see a positive added effect of heat wave on mortality, however this effect is assumed to be smaller than the primary effect. In addition, we anticipate observing variations in the effect depending on the heat wave order, duration, intensity, geographic location and demographic strata. The largest added effects are expected for the longest and strongest heat waves in the oldest-old population in the less accustomed to extreme heat areas.

How to cite: Ordanovich, D., Casanueva, A., Tobías, A., and Ramiro, D.: The lethal grip of heat: mapping the heat wave-mortality nexus in Spain (1975-2019), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3565, https://doi.org/10.5194/egusphere-egu24-3565, 2024.