NH9.5 | Interaction of urban expansion with natural hazards
EDI
Interaction of urban expansion with natural hazards
Convener: Ugur Ozturk | Co-conveners: Roopam Shukla, Elisa BozzolanECSECS, Caroline Michellier, Viktor RözerECSECS, Ankit Agarwal, Olivier Dewitte
Orals
| Tue, 25 Apr, 16:15–18:00 (CEST)
 
Room 1.31/32
Posters on site
| Attendance Tue, 25 Apr, 10:45–12:30 (CEST)
 
Hall X4
Posters virtual
| Attendance Tue, 25 Apr, 10:45–12:30 (CEST)
 
vHall NH
Orals |
Tue, 16:15
Tue, 10:45
Tue, 10:45
The UN projects that the urban population will increase from 55% to 68% by 2050. The largest increase is projected to occur in low- and lower-middle-income countries. This trend will expand urban areas from coastal and mountainous terrain to flood plains and steeper hillslopes. This expansion will increase the population's exposure to natural hazards, especially landslides and floods. Rapid urbanisation also fosters the development of informal settlements in peri-urban areas. This type of housing is structurally more vulnerable to earthquakes or volcanic hazards. Additionally, informal urbanisation could also aggravate some natural hazards such as landslides by, for instance, poorly managing rainwater.
This session is dedicated to contributing national, regional, and local perspectives about urban expansion's interaction with natural hazards. We intend to bring together experts from science and practice to offer a discussion platform to increase awareness of this problem and provide possible solutions. We seek to discuss the following questions and several others during the session:

- Are there changes in natural hazard frequency due to urbanisation?
- Does informal settlement alter natural hazard susceptibility?
- What is the impact of natural hazards given the population concentration in specific regions?
- What is the role of climate change in natural hazards in urban spaces?

Orals: Tue, 25 Apr | Room 1.31/32

Chairpersons: Elisa Bozzolan, Caroline Michellier, Viktor Rözer
16:15–16:25
16:25–16:35
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EGU23-15196
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solicited
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Highlight
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On-site presentation
Faith Taylor

This presentation aims to set the scene for the session and promote debate about how we as a scientific community can better address the issue of risk in low-income neighbourhoods (also referred to as ‘slums’ and ‘informal settlements’).

Low- and middle-income countries are experiencing rapid urbanisation, often with limited capacity to manage the rapid growth and associated accumulation of risk. One billion people currently live in low-income neighbourhoods. For many cities in the Global South, this means that large proportions (up to 60%) of the urban population live in very small proportions of the urban land which are not formally planned/monitored and are often exposed to a range of single and multi-hazards. This creates challenges in compiling records of hazards, their impacts and feedbacks as many methods are not of sufficient resolution to record high-frequency low-magnitude hazard events that chronically affect these settlements and erode capacity to cope. Additionally, although low-income neighbourhoods often appear as one homogeneous unit on maps, this masks the fact that these areas often act as urban centres within their own right, with high levels of heterogeneity in terms of infrastructure, land use and demographics. This creates challenges in understanding exposure and vulnerability. Overall, these issues mean that our ability to understand single and multi-hazards in low-income neighbourhoods is limited, and resultantly we may miss large proportions of the population in city-wide risk assessments.

Based on my work on a number of projects in low-income neighbourhoods, I will discuss some ways of addressing these challenges and their associated strengths and weaknesses. This includes: (a) Whatsapp focus groups to map social networks of resilience, (b) low-cost smartphone GPS mapping to document the bottom-up response to shocks and stresses within low-income neighbourhoods, (c) exploration of novel ‘big’ and 'medium' data sources. These techniques are participatory and designed to support both residents and city-level stakeholders in better understanding the complexities of risk in slums. The results of this work document that residents of low-income neighbourhoods are not passive but often the first or only responders in dealing with risk in these areas.

How to cite: Taylor, F.: Assessing Risk and Resilience in Urban Low-Income Neighbourhoods, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15196, https://doi.org/10.5194/egusphere-egu23-15196, 2023.

Vulnerability & Exposure
16:35–16:45
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EGU23-10235
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ECS
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On-site presentation
Cassiano Bastos Moroz, Tobias Sieg, and Annegret Thieken

The last IPCC report highlighted that the urban expansion to areas exposed to climate-driven natural hazards might significantly increase disaster risk in the near future. Understanding risk as the combination of hazard, exposure and vulnerability, these increased trends will be more expressive among the economically and socially marginalized urban residents, particularly in informal settlements. A major cause of this process is spatial intraurban inequalities. The urban poor are not only more vulnerable to natural hazards, e.g., due to a lack of resources; they are also often driven towards the less valuable areas, including hazardous locations such as flood plains and steeper hillslopes, which likely increase their exposure. However, disaster risk research still lacks more holistic tools to simulate and better understand the interrelations among urban expansion, intraurban inequalities, and exposure to natural hazards. We aim to develop an urban growth model that incorporates different socioeconomic groups to investigate the impact of these inequalities on their hazard exposure. We developed our model following the multilevel modeling framework for urban growth. First, a demand module quantifies the amount of urban growth that is expected for each socioeconomic group. Then, a spatial allocation module determines where this growth will take place to fulfill these demands. In the allocation, the most probable locations of future urban areas are individually determined for each group as a function of driving forces. These include biophysical and socioeconomic factors such as terrain slope, elevation, and distance to infrastructure. We applied the model in the municipality of Rio de Janeiro, Brazil, while accounting for three different income groups. Preliminary results indicate that the characteristics of new urban areas change significantly as a function of the income class, with a strong pattern of spatial segregation. Low-income households were found to have a higher probability of being located on steeper terrain than middle- and high-income households. In addition, new low-income urban areas were also found to be more distant from the city center, the coastline, and the main city infrastructure including subway and train stations. These results demonstrate the relevance of incorporating existing inequalities into urban growth models, especially in developing spatial planning policies in accordance with existing risks to natural hazards.

How to cite: Bastos Moroz, C., Sieg, T., and Thieken, A.: The inclusion of intraurban inequalities in urban growth models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10235, https://doi.org/10.5194/egusphere-egu23-10235, 2023.

16:45–16:55
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EGU23-15281
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On-site presentation
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Jean Nsabimana, Sabine Henry, Aloys Ndayisenga, François Kervyn, Olivier Dewitte, and Caroline Michellier

In urban areas, networks and life-support systems, such as roads, power lines and drinking water pipes, are key infrastructures which contribute to the functioning of the city. Their damaging or destruction can lead to harmful consequences for the population. Such situation has already occurred in several African cities following the impact of a hazard of natural or human-induced origin. Bujumbura, the economic capital of Burundi, is no exception to such scenario, particularly as a result of geo-hydrological hazards which regularly affect various neighborhoods of the city: floods, flash-floods, river bank collapse, large urban gullies. For instance, the February 2014 flash flood damaged several key infrastructures in the north of Bujumbura, including the National Road number 1, a medium-voltage line and drinking water pipes.

The goal of this study is to show how, in an urban system like the city of Bujumbura, the vulnerability of these key infrastructures to geo-hydrological hazards can lead to the fragility of a large territory. This vulnerability is influenced by weaknesses related to their wear or age, their construction technique, and their dependence on external systems for their effective functioning. In addition to their own weaknesses, these key infrastructures are exposed to several natural hazards that can lead to their damage or destruction. In Bujumbura, the geo-hydrological hazards that regularly impact the city are accentuated by the lack or outdated rainwater drainage facilities and the inadequacy of the urban development plan.

After listing, locating and characterizing all the infrastructures that play a role in the life of the population in the urban environment, a classification, based on a participatory approach, was developed to select those on which the vulnerability assessment focused. Six forms of vulnerability (intrinsic, dependency, hazard exposure, control capacity, alternative operation, and crisis management) were assessed for each key infrastructure. To assess each form of vulnerability, interviews were conducted with facility managers (28) to supplement the data from the literature and field collection. Geometric weighting was performed to highlight the most vulnerable infrastructure that could disrupt the functioning of others and, by extension, that of the city.

The results of this study show that several road sections in the center and at the exit points of Bujumbura, as well as the drinking water treatment plant and the pumping stations, stand out among the most vulnerable infrastructures. Continued efforts are required to maintain, protect, and strengthen these networks and life-support systems in the face of geo-hydrological hazards, as their damage or destruction due to cascading effects caused by dependence on, or wear and tear of, infrastructure can affect a much wider area than just the hazard impact zone.

How to cite: Nsabimana, J., Henry, S., Ndayisenga, A., Kervyn, F., Dewitte, O., and Michellier, C.: Vulnerability of key urban infrastructures to geo-hydrological hazards: how endangered is the city of Bujumbura?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15281, https://doi.org/10.5194/egusphere-egu23-15281, 2023.

Flood Hazard/Risk
16:55–17:05
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EGU23-1072
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ECS
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On-site presentation
Conor Lamb, Maria Pregnolato, Francesca Pianosi, and Paul Bates

In previous assessments of UK flood risk, flood hazard has often been poorly represented by low skill models. Meanwhile, assessments of future flood risk have lacked a detailed representation of future flood exposure. This study represents a significant step forward in both flood hazard and future exposure representation. Using a state-of-the-art climate-conditioned hydrodynamic model for fluvial, pluvial and coastal flooding paired with the latest UK shared socioeconomic projections of population (UK-SSP), we explore how climate-induced changes in flood hazard interact with increasing exposure due to population changes. Using a detailed exposure dataset, we are also able to explore discrepancies in current and future flood risk between residential property types.

Our model values current yearly residential economic floods losses at £894 million, with fluvial flooding accounting for approximately 75% of these. This flood risk is not borne equally between the devolved British nations, however. In Scotland and Wales approximately 30% of local authorities have over £100 of annual flood losses per property, whereas only 4% of local authorities in England experience such levels. There are also significant discrepancies in flood risk by property type. Flats and terraced housing experience almost twice the rate of yearly inundations than detached and semi-detached housing. Under a high emissions climate scenario (RCP 8.5), by 2070 we estimate flood risk will increase by 29% whilst under a low emissions scenario (RCP 4.5) flood risk will increase by 10%. Similarly to current flood risk, these increases too are not borne equally across regions and property types.

Whilst climate change is set to drive an increase in flood risk over the next 50 years, our study suggests that population dynamics may have potential for offsetting relative flood risk rises. In all SSP projections studied here (SSP1, SSP2 and SSP5), an increase in population drives an increase in the yearly rate of property inundations. As such, the highest increases in flood risk due to population change are seen in SSP5 (+50%). However, due to population growth predominantly occurring in low flood risk areas, relative flood risk decreases most in SSP5 (-10%). Similar changes, although smaller in magnitude, are seen under SSP1 and SSP2. Despite these decreases in relative flood risk due to population change, when paired to climate change, we still see significant increase in flood risk over the next 50 years. Consequently, low emissions scenarios, such as SSP1/RCP2.6, see the lowest increases in flood risk by 2070 (+5%). These results show a clear need for climate change mitigation actions in order to limit flood risk increases. However, this study presents a promising signal where population growth may limit the burden of increased flood risk, due to climate change.

How to cite: Lamb, C., Pregnolato, M., Pianosi, F., and Bates, P.: Drivers of present and future residential flood risk in Britain, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1072, https://doi.org/10.5194/egusphere-egu23-1072, 2023.

17:05–17:15
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EGU23-60
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ECS
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On-site presentation
Pulipati Yaswanth, Balaji Narasimhan, and Chakravarthy Balaji

Chennai is the fourth largest metropolitan city in India and being a coastal city, this region receives extreme precipitation events, especially during the North-East monsoon season. Rapid urbanization has led to profound changes in the city's land-use land cover, which has the potential to impact the local microclimate. The 2015 December Chennai flood resulted in the loss of lives and an economy of 2.5 billion $. Hence a reliable forecast system for the city helps for better preparedness. It is well acknowledged that urbanization affects rainfall distribution, but several limitations exist in past studies. The discrepancies between climatological and numerical investigations have not been addressed. To understand the impact of urbanization on the rainfall space-time distribution, it is also essential to choose rainfall events that originated from distinct synoptic conditions. Hence in this study, the Weather Research Forecast (WRF) model and advanced statistical analysis are used to examine the effects of urbanization on rainfall modification over Chennai city. The present investigation considers satellite estimations and observed station data due to the absence of a dense rain-gauge network. From ECMWF reanalysis ERA5 data, large-scale weather predictors are selected to create weather patterns using a fuzzy clustering method, with Chennai as the domain center. Subsequently dividing the observational rainfall data into two equal periods, the changes in the rainfall quantiles (80th to 99.9th) are obtained for each cluster.  Since large-scale circulation patterns are similar, these shifts show the likely impact of urbanization on rainfall.  Extreme value theory combined with regional frequency analysis is implemented to understand the changing rainfall statistics in the past 50 years. Numerous WRF simulations are performed at convection-permitting scales with varied domain and physics configurations for three extreme precipitation events from different synoptic conditions. The study also investigates the ability of scale-aware convective schemes to describe precipitation processes in high-resolution simulations for the study domain. Then, the WRF simulations are conducted with optimal physics combinations with default USGS land cover data (1991-1992) and high-resolution land-use data (2017) with Local Climatic Zone (LCZ) classifications, that represents the present urbanization. The simulations with recent land cover data coupling with Building Energy Parameterization (BEP) in the WRF model significantly improved the rainfall prediction skill in the spatial-temporal domain minimizing the bias. Interestingly, an intense convective rainfall event which was neither detected by the regional meteorological department nor WRF simulations with the default LULC map has been forecasted by representing the current urbanization scenario in the model. Further, this study also explains the dynamic and thermodynamic responses influencing rainfall distribution due to urbanization. The study advances the role of urbanization in a coastal city and provides pathways for better urban planning and design. The improved ensemble forecasts help for better preparedness during extreme rainfall events.

How to cite: Yaswanth, P., Narasimhan, B., and Balaji, C.: Urban effects on the Extreme Precipitation: Advanced Statistical Analysis and Numerical Weather Prediction Model at Convective Scales, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-60, https://doi.org/10.5194/egusphere-egu23-60, 2023.

17:15–17:25
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EGU23-5489
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ECS
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On-site presentation
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Alessio Gatto, Federico Martellozzo, Stefano Clo', and Samuele Segoni

Climate change and urban expansion are contributing to a considerable increase in catastrophic atmospheric and hydro-geological events, which cause significant damage to the urban and social fabric.

This work takes Italy as a nation-wide case of study with a twofold objective: first, we compiled a dataset of recent hydro-geological disasters for which a state of emergency was declared; second, we focused on the interconnections between urban expansion and occurrence of disasters at the municipality level.

The dataset was built thanks to the collaboration with the Italian National Civil Protection Department, from which the data relating to national states of emergency and the surveys carried out were obtained. We discovered that in Italy, during the last ten years, there had been more than one hundred events that have required the intervention of national Civil Protection, with the declaration of the national state of emergency and the funding of interventions for first aid and restoration. The dataset consists of sets of municipalities and provinces that were included in the national state of emergency that suffered damage and obtained subsidies for reconstruction. Furthermore, information was collected regarding the beginning and end of the state of emergency, the days on which the event occurred, and the funds disbursed for recovery.

This database was the basis for subsequent analyses (at the municipality level and at the province level) aimed at quantifying the correlations between the occurrence of disasters and state-of-the-art indicators like soil consumption, extension of mapped hazardous zones, and buildings in areas at risk.

How to cite: Gatto, A., Martellozzo, F., Clo', S., and Segoni, S.: Tracking a decade of hydro-geological emergencies in Italy and their interplay with urban expansion, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5489, https://doi.org/10.5194/egusphere-egu23-5489, 2023.

Landslide Hazard/Risk
17:25–17:35
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EGU23-153
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On-site presentation
Martin Brook, Matt Cook, and Murry Cave

Land surface changes resulting from human activities have emerged as a factor of equal, if not greater importance than climate change in affecting landslide occurrence. Gisborne is a remote city on the northeast North Island of New Zealand, close to the Hikurangi Subduction Zone, and is vulnerable to natural hazards, such as tsunami, earthquakes, coastal erosion, flooding, and particularly landslides. Vulnerability is also characterised by a suite of social, economic, and infrastructural issues which uniquely culminate in Gisborne. Gisborne has the highest percentage of indigenous Māori people for a New Zealand city and experiences a high degree of socio-economic disadvantage. The city is remote from other urban centres, taking >3 hours to reach the nearest adjacent city via rural roads that are vulnerable to closure during and following natural hazard events.  In particular, landslide risk in recent years has been exacerbated by urban and suburban expansion of residential development into sub-optimal terrain, on steep hill slopes surrounding the city. The hills are underlain by weak Neogene sediments and uplifted Pleistocene estuarine deposits. Gisborne District Council has previously attempted to delineate landslide risk areas but has been hampered by the lack of detailed empirical data. Based on observational data from Sentinel-1 imagery, this study used interferometric synthetic aperture radar (InSAR) to reveal the pattern of slope deformation across Gisborne’s steepland periphery from January 2016 to December 2021. Velocities in the line of sight were obtained from the stack of interferograms and projected along the direction of maximum slope, to extract the true displacement on the slopes. The ascending and descending data sets were combined to reveal the vertical and horizontal components of the deformation. The results were combined with a regional LiDAR dataset, aerial imagery and field observations to delineate areas of slope deformation. Finally, slope deformation time series data was compared with rainfall records to identify seasonal changes, as well as shrink-swell of expansive soils. Results identified 132 unstable slopes within the study area, affected by soil creep, slumping and earthflows. Despite clear evidence of the effects of tree removal, loading of slopes by construction activity, and installation of unconsented, inadequate retaining walls contributing to slope failure, such practises unfortunately continue.

How to cite: Brook, M., Cook, M., and Cave, M.: City expansion, land-use change and slope failures in Gisborne, New Zealand: déjà vu all over again, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-153, https://doi.org/10.5194/egusphere-egu23-153, 2023.

17:35–17:45
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EGU23-16148
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ECS
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Virtual presentation
Shreyasi Choudhury, Bruce D. Malamud, and Amy Donovan

This study applies a belief-based probabilistic approach to find the relative influence of environmental conditions and human actions on the probability of occurrence of landslides in the Darjeeling Himalayas, India. Subjective (belief-based) probabilistic methods are an approach to model complex relationships in regions with low or no data. Here, we use two subjective probabilistic methods: expert elicitation and Bayesian belief network. Expert elicitation (EE) is a technique to quantify the knowledge of experts based on their theoretical or practical experience on a topic of interest. A Bayesian belief network (BBN) takes into consideration and represents the experts’ knowledge (and other data, if available) to give a probabilistic, rational outcome under the influence of uncertainty. BBNs are represented as a graph consisting of a set of random variables (called ‘nodes’) that are interconnected via edges (called ‘arcs’). BBN follow the Bayes’ theorem.

We first use expert judgement and secondary literature to determine 20 prominent variables that influence landsliding, divided into 2 triggering variables (earthquake, rainfall), 11 geomorphic variables (e.g., soil type, flood depth, elevation), and 6 anthropogenic variables (e.g., infrastructure development, machinery vibration). We then conduct EE with ten landslide experts, to find the prior and conditional probabilities of each of these 20 landslide-related variables. Prior probability is the probability of occurrence of the variables (A) that influence or trigger landslides (P(A)) and conditional probability is the probability of occurrence of landslide(s) given P(A)). Using BBN modelling, we then provide a comparison of answers across all ten experts per variable and across all variables per expert. Finally, we examine single and multiple combinations of variables and their relative influence on landsliding in the study area. We finally list suggestions, challenges faced, and limitations on designing and carrying out belief-based probabilistic procedures.

How to cite: Choudhury, S., Malamud, B. D., and Donovan, A.: Bayesian belief network modelling for landslide hazard assessment using probabilistic estimates from experts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16148, https://doi.org/10.5194/egusphere-egu23-16148, 2023.

Ecological Aspect
17:45–17:55
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EGU23-11871
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solicited
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Highlight
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On-site presentation
Jagdish Krishnaswamy, Denzil Daniel, Sumit Sen, and Jaya Khanna

The Himalayas are at the forefront of hazards related to climate change as well as other global change drivers such as land-use and land-cover change including complex interactions between diverse drivers.

Scientists, civil society organizations and local communities have identified key issues related to how specific Himalayan ecosystems are responding to these drivers including episodes of greening and browning of vegetation as well spread of Pine and the retreat of Oak forests, higher incidence of forest fire due to changes in winter rainfall and summer heat.

Using evidence from multi-decadal time-series of remotely sensed data on state of vegetation combined with climate data and measurements and observations from instrumented catchments we now have insights on the greening and browning of vegetation at larger scales and the comparative ecohydrological response of Pine and Oak dominated catchments at finer scales.   The Himalayas show elevation specific patterns of greening and browning trends that differ across the Himalayas from west to east.  Pine dominated catchments seem to have lower levels and temporally homogeneous soil moisture profiles as well as higher evapotranspiration and lower discharge regimes compared to Oak dominated catchments.  We discuss the implications of the evidence for biodiversity and ecosystem services under emerging and future climate change.

 

How to cite: Krishnaswamy, J., Daniel, D., Sen, S., and Khanna, J.: Emerging ecological and environmental hazards in the Himalayas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11871, https://doi.org/10.5194/egusphere-egu23-11871, 2023.

17:55–18:00

Posters on site: Tue, 25 Apr, 10:45–12:30 | Hall X4

Chairpersons: Ugur Ozturk, Olivier Dewitte
X4.52
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EGU23-2524
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ECS
Jeong Ah Um, Sungsu Lee, Byungjo Kim, Seunghun Shin, and Jongyeol Woo

As urbanization progresses worldwide, the number of high-rise buildings is rapidly increasing, especially in large cities, and the damages from building wind are expected to increase further. In particular, strong winds in urban canyon frequently damage doors, windows and signboards, etc. There also is a risk of building exterior materials scattering due to delamination at the edges of buildings, vortex generation, and gust. Among the damage caused by the building wind, the damage by the exterior material that has been removed due to strong wind can cause not only property damage but also personal damage. Recently, concerns about the damage of building winds in urban areas on pedestrian safety and living environment are increasing, but there is very little consideration in domestic architecture and urban planning procedures. Therefore, it is very essential to reduce the possibility of delamination of exterior materials by strong wind and consequent low pressure. The purpose of this study is to develop mitigation device attached to the edges of the buildings to lower the maximum peak pressure to reduce the potential detachment of building envelope. Using CFD and experimental approach, it was found that developed device can reduce the maximum peak pressure up to 20%.

This research was supported by a grant (RS-2022-00155691) of Disaster-Safety Industry Technology Commercialization R&D Program, funded by Ministry of Interior and Safety (MOIS, Korea).

How to cite: Um, J. A., Lee, S., Kim, B., Shin, S., and Woo, J.: Development of Mitigation Device to Wind Risk on Urban Region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2524, https://doi.org/10.5194/egusphere-egu23-2524, 2023.

X4.53
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EGU23-14078
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ECS
Shobhana Lakhera, Michel Jaboyedoff, Marc-Henri Derron, Ajanta Goswami, and Anil Kumar Maletha

Joshimath lies in the Chamoli district of Indian Himalayas, at an elevation of around 2000 m. It is reportedly located on old landslide debris with a very high slope of 60º, which marginally stabilized during the geologic past. Positioned in the vicinity of active Vaikrita thrust, Joshimath has been intermittently sinking for quite many decades and records incidences of slope failures even during the dry seasons (Valdiya et al., 2014). The lithology of the area is characterized by banded gneiss with interbedded schists and localized calc-silicate gneiss lenses with plunging folds and many minor faults (Valdiya et al., 1983). Topographically it is influenced by long-term river incision with Dhauliganga and Alaknanda, sharply incising the toes of the hill slopes in Joshimath, draining along NW direction, and cutting sharply around the curvatures mainly near Vishnuprayag and Maarwadi village. The 2021 debris flow and 2013 flash floods, resulted in noticeable increase in river undercutting and sediment load with changes in the river flow regimes resulting from deposition of mid-channel and side-channel bars, from the flow sediments and landslides along the toe region, respectively. Thus, this increase in fluvial undercutting may cause the large-scale destabilization of mountain slopes and induce deep-seated gravitational slope deformation (DGSD) that can eventually lead to catastrophic failures (Tsou et al., 2015).

A study on the impacts of 2013 flash flood by the Geological Survey of India (GSI) revealed, reactivated and newly activated landslides mainly occurred, either in river terraces or in slope debris material on steep slopes. The main causative factor responsible for triggering these landslides was toe-erosion by the river, accompanied by increased overburden due to heavy rainfall, during the 2013 flash flood (Sharma et al., 2014). Similarly, reactivated landslides can be spotted on google earth images post 2021 event, these are in and around the Joshimath town at the hill toe, thus implying high incision. Currently, land subsidence is being reported in almost 561 buildings across the Joshimath town, with severe cracks along with some muck water seepage. Many news reports have pointed on the breached and blocked natural drainage systems, from rapid urbanization which may be a reason for water seepage in the subsiding buildings. The maximum damage has been so far reported at the JP colony which lies in the rim area of the hill slope, thus being more susceptible to undercutting (Tsou et al., 2015). Many speculations on probable reasons, from the impact of tunneling for the Tapovan-Vishnugad project, blasting and mountain cutting for road construction, increased urbanization, improper drainage, and increased toe erosion have been listed. In this study, we try to analyze if any, the impacts of increased toe-incision induced by the 2021 flash floods, using geological and remote sensing techniques under the changing climate regimes, on the subsidence in Joshimath town. 

Keywords: Deep-Seated Gravitational Slope Deformation (DGSD), Subsidence, Incision, Undercutting, Landslides

How to cite: Lakhera, S., Jaboyedoff, M., Derron, M.-H., Goswami, A., and Kumar Maletha, A.: Preliminary Assessment: 2021 Debris Flow Impact on River Incision and Land Subsidence in Joshimath Town, Garhwal Himalayas, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14078, https://doi.org/10.5194/egusphere-egu23-14078, 2023.

X4.54
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EGU23-781
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ECS
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Hariom Gupta, Akash Singh Raghuvanshi, and Ankit Agarwal

Variations in precipitation characteristics have an impact not only on human society but also on the natural environment. In addition, precipitation events may have detrimental effects on human health and cause severe socioeconomic losses, as well as, in the worst situation, the loss of human life. Therefore, it becomes essential to characterize extreme events and understand the atmospheric dynamics driving them. In this study, we ranked multi-day precipitation events using 63 years (1959 to 2021) of daily precipitation data. The ranking was done based on the intensity as well as the spatial extent of the event. Further, we used integrated vapor transport (IVT) to quantify moisture transport during identified top-ranked precipitation events. Our preliminary analysis showed that the IVT variability is significant during these events, indicating substantial moisture accumulation before these events. Indeed, quantifying the connection of extreme to moisture movement might help in the early prediction of extreme events and lower the associated risks.

How to cite: Gupta, H., Singh Raghuvanshi, A., and Agarwal, A.: Moisture transport associated with multi-day precipitation events in India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-781, https://doi.org/10.5194/egusphere-egu23-781, 2023.

X4.55
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EGU23-5580
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ECS
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Highlight
Viktor Rözer, Mohammad Alsahli, and Sara Mehryar

The discovery of oil in the middle of the 20th century has triggered an unprecedented economic boom and urban expansion in countries of the Gulf region such as Kuwait, Qatar, or the UAE. Kuwait’s population has increased 7-fold since the 1950s – mostly driven by immigration - creating the need for large scale housing and urban development projects. With a strong focus on the provision of housing and a car-centric planning approach the environmental consequences of these large developments were often not fully evaluated. In combination with changing rainfall patterns in the region as a result of climate change, severe flash floods have caused significant damage in recent years.

Based on data from previous flash flood events and a high-resolution digital elevation model, a new flash flood susceptibility map for Kuwait has been developed. In combination with a detailed property level reconstruction of Kuwait’s urban expansion since the 1950s, we analyse how flash flood risk has developed in the Gulf state over time and which urban planning decisions have led to the recent jump in flash flood occurrences. Together with information about recent flash flood risk management plans, the study explores how Kuwait’s projected urban expansion until 2040 will contribute to its future flash flood risk.

How to cite: Rözer, V., Alsahli, M., and Mehryar, S.: Rapid urbanisation and flash flood risk in desert regions: the example of Kuwait, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5580, https://doi.org/10.5194/egusphere-egu23-5580, 2023.

X4.56
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EGU23-11038
Ajanta Goswami, Tapas Nahak, and Shashi Gaurav Kumar

India has 20 river basins, 12 major and 8 medium and small, with 1869 b.c.m of annual water resource potential. River basins have unequal water resources. Brahmaputra and Barak rivers provide 586 bcm of India's 1869 bcm annual water resource potential (which is roughly 32% of the total potential). These 'Water Tower of India' contains one-third of India's water. Brahmaputra basin, which covers India's NE, has the most water per person. The region has over 13000 cu.m./year per capita, well above Falkenmark's 1700 cu.m. Above the national average of 1544 cu. m.

Region has most hydropower potential. Only 3% of the NER's 31,857 MW hydropower potential has been used for human purposes (Brahmaputra Board, 2000), compared to 16% nationally. The NE's hydropower potential is 80% in Arunachal Pradesh (32 percent of the national potential).

The Indian government proposed 162 new hydroelectric projects in 16 states, 62 of which are in the Northeast. Most rivers are interstate. This water resource's sustainability is important for population and biodiversity. High-altitude glacial lakes can unleash fury downstream.

These Indian water bodies pose many dangers to the region's ethnic tribes. Between 1990 and 2009, climate change increased glacial lake area in the eastern Himalaya. Only China, Nepal, Pakistan, and Bhutan have recorded more than 50 glacial lake outbursts in the HKH.

Arunachal Pradesh has 1600 high-altitude lakes. 60 hydropower projects downstream of glacial lakes have been commissioned or proposed.

This study maps the glacial lakes of Arunachal Himalaya from the 1980s to the present and examines their dynamism. Morphometric and morphotectonic analysis is used to study the basin's response to flash floods and other hydrometeorological hazards. The interesting results obtained out of glacial lakes dynamics study and the morphometry/morphotectonic analysis of the Brahmaputra basins will be presented in the conference, which is completed new and unreported.

 

How to cite: Goswami, A., Nahak, T., and Kumar, S. G.: Analysis Of Glacial Lake And Basinal Topographic Dynamics And Associated Hazards In Brahmaputra Basin, The Water Tower Of India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11038, https://doi.org/10.5194/egusphere-egu23-11038, 2023.

Posters virtual: Tue, 25 Apr, 10:45–12:30 | vHall NH

Chairpersons: Roopam Shukla, Ankit Agarwal
vNH.9
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EGU23-2663
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ECS
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Altaf Hussain, Susanne Schmidt, and Marcus Nüsser

Small and medium-sized towns in the high mountain regions of South Asia are characterized by rapid and mostly unplanned urbanisation processes resulting in increased risk to natural hazards, such as flash floods, landslides and earthquakes. Due to rapid urban expansion, the case study of Kargil, the second largest city of the Union Territory of Ladakh is chosen to identify risk-prone areas. Based on multi-temporal approach using high resolution satellite imagery (Corona, ASTER and PlanetScope), statistical data and repeated field surveys, urban landscape changes are analysed since the 1960s. The population of Kargil town increased from 1,681 in 1961 to 16,338 in 2011, while total population of the entire Kargil district multiplied from 45,064 to 140,802 over the same period. The built-up area of Kargil town has grown from 0.25 km² to 2.30 km² between 1965 and 2020. The mountain region of Kargil is particularly vulnerable to natural disasters such as landslides, cloudbursts, and flash floods. The main highways (NH-1D and NH-301) connecting Kargil with adjacent regions are prone to landslides. Recurring flash floods in the surrounding of Kargil town was observed in the years 2006, 2010, 2013, 2014, 2016 and 2018, which caused massive damages to roads, buildings, and agricultural area. Most recent flash floods occurred in Kargil town (Baroo and Titichumik) and in different rural villages of Chiktan, Suru and Drass in 2022. These settlements are either located along the streams or on low lying banks of the main rivers, Suru, Drass and Wakha; examples include hazard prone areas such as the new bus stand, and Kabadi Nallah on the banks of Suru river and several other new settlements like Silmo colony or Andoo colony in Kargil town. Urban expansion does not only cover the most suitable areas but increasingly sprawls across steep slopes; examples include the new residential areas of Silmo colony, Andoo colony, and Haidery Mohalla. These new urban settlements are extremely prone to natural hazards and question the sustainability of town planning in this mountain region. The central old town, Baroo colony and Poyen colony are already saturated due to unplanned buildings and infrastructural development. The drivers of the urbanization include increasing of urban population, rural-urban migration to the administrative capital of Kargil district, and an increasing mountain tourism sector which led to new constructions of hotels, guesthouses, and arrival of tourists.

How to cite: Hussain, A., Schmidt, S., and Nüsser, M.: Urban Landscape Change in the Trans-Himalayan Town of Kargil, Ladakh, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2663, https://doi.org/10.5194/egusphere-egu23-2663, 2023.

vNH.10
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EGU23-10252
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ECS
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Badal Pokharel, Massimiliano Alvioli, and Samsung Lim

Slope units, defined by the portions of terrain bounded by drainage and divide lines, are specific mapping units that can be used to prepare landslide susceptibility maps, as they have better geomorphological content than grid cells. Researchers have progressed in delineating and optimizing slope unit maps in the past decades [1, 2], and in landslide susceptibility and hazard assessment [3,4]. We present a slope unit map delineated and published for the first time in the Himalayas [5], containing 112,674 polygons in a geographic extent that cover central Nepal and some sections of Tibet, China. We used this map to (i) compare landslide inventories, and their corresponding landslide susceptibility [6] and (ii) generate a rockfall susceptibility map along a highway [7]. We compared five inventories from different authors after the Gorkha earthquake in 2015, adopting statistical and geospatial techniques. The outcome shows differences in the geospatial clustering of the susceptibility maps corresponding to different inventories. We prepared a potential source map of earthquake-triggered rockfall along a highway in Rasuwa district, Nepal. Then, we ran STONE [8,9], a physically based application, to a grid map with a rockfall trajectory map based on which we generated a segment-wise rockfall susceptibility map. Results helped to identify areas with high susceptibilities, such as Dandagaun and Syaprubesi. The findings could be helpful for rockfall hazard and risk assessment and land use planning. Through these studies, we stress that slope-unit-based studies are an excellent alternative to grid cells for large-scale studies as they help select specific slopes for further hazard assessment. 
References:
[1]    M. Alvioli, F. Guzzetti, and I. Marchesini, “Parameter-free delineation of slope units and terrain subdivision of Italy”. Geomorphology 358, 107124 (2020). DOI: 10.1016/j.geomorph.2020.107124
[2]    M. Alvioli et al., “Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling”. Geosci Model Dev, 9, 3975–3991 (2016). DOI: 10.5194/gmd-9-3975-2016
[3]    M. Alvioli et al., “Rockfall susceptibility and network-ranked susceptibility along the Italian railway”. Engineering Geology 293, 106301 (2021). DOI: 10.1016/j.enggeo.2021.106301
[4]    M. Alvioli et al., “Seismically Induced Rockfall Hazard from Ground Motion Scenarios in Italy”. SSRN Electronic Journal (2022). DOI: 10.2139/ssrn.4156514
[5]    M. Alvioli, I. Marchesini, B. Pokharel, K. Gnyawali, and S. Lim, “Geomorphological slope units of the Himalayas”. J. Maps (2022). DOI: 10.1080/17445647.2022.2052768
[6]    B. Pokharel, M. Alvioli, and S. Lim, “Assessment of earthquake-induced landslide inventories and susceptibility maps using slope unit-based logistic regression and geospatial statistics,” Sci Rep 11, 21333 (2021). DOI: 10.1038/s41598-021-00780-y
[7]         B. Pokharel, S. Lim, T.N. Bhattarai, and M. Alvioli, “Rockfall susceptibility along Pasang Lhamu and Galchhi-Rasuwagadhi highways, Rasuwa, Central Nepal”. (under review)
[8]    F. Guzzetti, G. Crosta, R. Detti, F. Agliardi, “STONE: a computer program for the three-dimensional simulation of rock-falls”. Computers & Geosciences 28, 1079-1093 (2002). DOI: 10.1016/S0098-3004(02)00025-0
[9]     M. Alvioli, A. De Matteo, R. Castaldo, P. Tizzani, P. Reichenbach, “Three-dimensional simulations of rockfalls in Ischia, Southern Italy, and preliminary susceptibility zonation”. Geom Nat Haz and Risk, 2712-2736 (2022). DOI: 10.1080/19475705.2022.2131472 

 

 

How to cite: Pokharel, B., Alvioli, M., and Lim, S.: Slope-unit-based assessment of landslide susceptibility in Central Nepal, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10252, https://doi.org/10.5194/egusphere-egu23-10252, 2023.

vNH.11
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EGU23-14640
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ECS
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Ratan Kumar, Deepika Mann, and Roopam Shukla

Rapid rate of urban growth are being reported, urbanization is recommended, but at what environmental, health, and equity costs? Phenomena such as the  Urban heat island are resulting in  increased risk of heat-related mortality and morbidity, unequal benefits, and exclusionary planning. It is becoming increasing critical that we understand and address the challenges arising due to unplanned and rampant urbanization. The current study aims to characterize SUHII in 80 cities of India and correlate its impacts on migration using Google Earth Engine. 4 different pathways in which migration and urbanization are summarized based on the evidences gathered from the remote sensing based analysis. The results of the study will assist in deriving quantitative evidence will notably support the design of urban risk reduction practices at a pan- India level.

How to cite: Kumar, R., Mann, D., and Shukla, R.: Demystifying urbanization and migration interaction pathways – Evidences from 80 cities of India., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14640, https://doi.org/10.5194/egusphere-egu23-14640, 2023.

vNH.12
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EGU23-15976
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ECS
Shagun Garg, Vamshi Karanam, and Mahdi Motagh

Joshimath - a small hilly village in Uttarakhand, India is facing severe land subsidence. More than 600 houses and roads and roads have developed cracks, and the government has ordered the immediate evacuation of families in the area.

Joshimath has seen significant urbanization in recent years due to its strategic location and the increasing popularity of tourism and adventure sports in the region. There has been a growing demand for infrastructure and services to accommodate the influx of tourists, leading to the development of new hotels, resorts, and other facilities. Over the years, several hydroelectric, road, and tunnel construction projects have also been undertaken in the region. 

In order to better understand and mitigate the risk of landslides in this area, it is important to implement a robust monitoring system. Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technique that has been used successfully in the past to monitor landslides and other ground deformation events. In this study, we used InSAR to monitor land subsidence in Joshimath over a period of 20 months (May 2021 - Jan 2023). We collected radar data from Sentinel-1 and performed PSInSAR analysis. Our preliminary analysis revealed continuous deformation of the order of 4cm/year in the region. Specific locations are selected for further detailed analysis, and field work is being carried out to provide additional information such as effects of subsidence and vulnerability of the area. This information can be used to develop a comprehensive understanding of the subsidence problem in Joshimath. 

How to cite: Garg, S., Karanam, V., and Motagh, M.: Monitoring and Understanding Land Subsidence in Joshimath: An InSAR and Ground-based Study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15976, https://doi.org/10.5194/egusphere-egu23-15976, 2023.

vNH.13
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EGU23-16763
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ECS
Srikrishnan Siva Subramanian, Sumit Sen, and Ali. P Yunus

Increasing occurrences of landslides as compound events under extreme-rainfall demand the development of landslide early warning systems at the territorial scale. Traditionally, rainfall Intensity-Duration (ID) thresholds are adopted in these Territorial Landslide Early Warning Systems (Te-LEWS). However, the usage of complex rainfall thresholds in Te-LEWS has proven successful across the globe since these thresholds account for the terrain conditions in direct or indirect ways, unlike the ID thresholds which consider only the rainfall characteristics. In Japan, the Soil Water Index (SWI), a complex rainfall threshold, is implemented successfully to predict rainfall-induced sediment disasters. Implementing such complex thresholds in new geological settings is very challenging. Here, we present a framework to test the SWI threshold to predict shallow landslides and debris flows in the Himalayas. By analysing the landslides' historical occurrences and their corresponding triggering rainfall intensities from satellite-derived hourly precipitation data, we determine the critical threshold of SWI. The framework considers the SWI calculation within the desired region at every 5 km * 5 km grid. The approach is found applicable for selected rainfall-induced landslides and debris flows in the Himalayas, especially in Uttarakhand, India. This framework may be useful for establishing complex rainfall threshold-based Te-LEWS in new geological settings. 

How to cite: Siva Subramanian, S., Sen, S., and Yunus, Ali. P.: Applicability of complex rainfall thresholds for Territorial Landslide Early Warning Systems (Te-LEWS) in the Himalayas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16763, https://doi.org/10.5194/egusphere-egu23-16763, 2023.

vNH.14
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EGU23-16849
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ECS
Alka Kumari, Akash Singh Raghuvanshi, and Ankit Agarwal

Numerous reanalysis products have been released worldwide. Indeed, the latest generation of reanalysis exhibit less bias and inaccuracy due to significant advancements in model physics and data assimilation methodologies. The applicability of these data sets for various parts of the world must be carefully examined. Therefore, numerous initiatives have been conducted to investigate the validity of reanalysis on a global and regional basis. Reanalysis products have been used to examine a range of hydrological concerns, such as floods, droughts, and the balance of energy and water, among others. In this study, we investigate how well various reanalysis products simulate the spatiotemporal precipitation patterns over India. We have collected precipitation data from 1980 to 2021 for pan India using different reanalysis precipitation products such as ERA5 (Fifth generation of ECMWF global atmospheric reanalysis), CFSR (Climate Forecast System Reanalysis), MERRA2 (Modern Era Retrospective Analysis for Research and Application, version-2), JRA55 (Japanese global atmospheric reanalysis project), MSWX (Multi-Source Weather) and IMD (India Meteorological Department) dataset. Comparison of different precipitation reanalysis products with the IMD dataset using various descriptive and categorial indices showed that ERA5 was a better representative of IMD data than other reanalysis products. We infer that ERA5 can be utilized in various climatic studies and hydrological modelling for those areas or river basins having no or missing data.

How to cite: Kumari, A., Singh Raghuvanshi, A., and Agarwal, A.: Evaluation of different Precipitation Products with IMD dataset emphasizing on Hydrological Modelling., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16849, https://doi.org/10.5194/egusphere-egu23-16849, 2023.