ITS1.5/NP8.6 | Urban Geo-sciences: modelling and monitoring complex urban systems; from the state of the art to planning challenges
EDI
Urban Geo-sciences: modelling and monitoring complex urban systems; from the state of the art to planning challenges
Co-organized by ERE6
Convener: Maider Llaguno-Munitxa | Co-conveners: Tim Kearsey, Francesco La Vigna, Danlu CaiECSECS, Daniel Schertzer, Gabriele Manoli, Ting Sun
Orals
| Wed, 17 Apr, 08:30–12:25 (CEST), 14:00–15:45 (CEST)
 
Room 2.24
Posters on site
| Attendance Thu, 18 Apr, 10:45–12:30 (CEST) | Display Thu, 18 Apr, 08:30–12:30
 
Hall X3
Posters virtual
| Attendance Thu, 18 Apr, 14:00–15:45 (CEST) | Display Thu, 18 Apr, 08:30–18:00
 
vHall X3
Orals |
Wed, 08:30
Thu, 10:45
Thu, 14:00
Cities are complex multi-scale systems, composed of multiple sub-components (e.g. for population, energy, transport, climate) that interact with each other on various time scales (e.g. hourly, seasonal, annual). Urban models and digital twins for urban planning applications and policies aimed at shaping healthier and more sustainable urban environments should account for such complex interactions as they regulate the growth and functioning of cities, often resulting in emergent large-scale phenomena. Yet our ability to quantitatively describe city behaviour is still limited due to the variety of processes, scales, and feedbacks involved.
In this session we welcome modelling and monitoring studies that focus on multi-sector dynamics and city-biosphere interactions. These include – but are not limited to – demography, urban transport networks, energy consumption, anthropogenic emissions, urban climate, pollution, urban hydrology and ecology.
The aim is to elucidate complex urban dynamics, identify strategies and methods for the development of models and digital twins of cities, and understand how the form and function of urban environments can improve liveability and well-being of their citizens.
This session welcomes concepts, methodologies and disruptive models to overcome current scientific bottlenecks, to better deal with non-linearities, multi-component systems and extremes over a wide range of scales in geophysical and urban systems.

Orals: Wed, 17 Apr | Room 2.24

Chairpersons: Maider Llaguno-Munitxa, Gabriele Manoli, Ting Sun
08:30–08:35
session1
08:35–08:45
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EGU24-2965
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ITS1.5/NP8.6
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On-site presentation
Jiyun Song, Dachuan Shi, and Qilong Zhong

Urban blue (water) and green (vegetation) spaces are natural refuges of cool spots for citizens to escape from the extreme heat outdoors and have been widely used in traditional and modern urban designs called ‘water towns’ (i.e., buildings are sited along rivers and trees), particularly in Southern China with rich water resources. This study represents the first comprehensive investigation into the cooling effect of urban river networks at different climatic scales in Shanghai, a Chinese megacity characterized by a significant presence of water towns. At the neighborhood scale, we conducted fine-resolution street-level monitoring of microclimatic data along various rivers during the 2022 heatwave periods in central Shanghai and applied an advanced spatial regression algorithm to quantify the synergistic effect of river and vegetation. At the city scale, we quantified the cooling buffer zones and cooling intensities of urban river networks by integrating fine-resolution urban river network maps with multi-source remotely sensed datasets. We found that the width of rivers, coverage ratio, density, and morphology of river networks are the key factors affecting the cooling potential. The confluence or proximity of river tributaries can also bring an enhanced cooling effect than standalone ones. In a diurnal cycle, rivers can lead to an averaged cooling intensity of 0.4–0.8 °C in air temperature with a maximum value of 3.5 °C in the afternoon, as well as a cooling distance ranging from 100 m to 700 m at various riverside neighborhoods. On the other hand, city-scale results show that river networks can provide a considerable cooling buffer zones covering 36.9% of Shanghai and a maximum cooling intensity of 5.5 °C in surface temperature. Our study implies that urban river networks cannot be neglected in urban climatic studies and should be incorporated into a new conceptualization of water-included urban local climate zone classifications in the world urban database.

How to cite: Song, J., Shi, D., and Zhong, Q.: How do urban river networks regulate city climate? A case study in Shanghai, China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2965, https://doi.org/10.5194/egusphere-egu24-2965, 2024.

08:45–08:55
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EGU24-9413
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ITS1.5/NP8.6
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ECS
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On-site presentation
Yizhen Yan, Bo Huang, Weixi Wang, Linfu Xie, Renzhong Guo, and Yunxiang Zhao

Building heights play a crucial role in various urban research fields, including 3D modeling, urban environmental analysis, sustainable development, and urban planning and management. Numerous methods have been developed to derive building heights from different data sources, including street view imagery, which offers detailed, ground-level perspectives of buildings. However, occlusions from street elements such as trees and vehicles present significant challenges, especially in densely built or complex urban areas. To address this challenge, we propose the use of advanced deep learning models for occlusion reduction, enhancing building height estimation from street view images. As trees typically cause the most occlusion, we employ an open-set detector and a large segmentation deep neural network to create tree masks in the images. Subsequently, we use a stable diffusion model for image inpainting, restoring parts of buildings occluded by trees. These inpainted images are then processed through building instance segmentation, yielding clearer building boundaries for height estimation. Moreover, we integrate a single-view metrology-based height estimation method with a building footprint auxiliary approach, leveraging their respective strengths and mitigating the impact of varying distances between street view cameras and buildings. Our methodology is validated using a dataset comprising 954 buildings and 3814 images. Experimental results demonstrate that our approach increases the percentage of height estimates within a two-meter error margin by approximately 7%, confirming its effectiveness. This work offers a cost-effective solution for large-scale building height mapping and updating, and it opens new avenues for urban research requiring accurate building height data.

How to cite: Yan, Y., Huang, B., Wang, W., Xie, L., Guo, R., and Zhao, Y.: Enhancing Building Height Estimation through Occlusion Reduction with Advanced Deep Learning Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9413, https://doi.org/10.5194/egusphere-egu24-9413, 2024.

08:55–09:05
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EGU24-13309
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ITS1.5/NP8.6
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ECS
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Highlight
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On-site presentation
Chenghao Wang, Janet Reyna, Henry Horsey, and Robert Jackson

Residential and commercial buildings jointly account for 39% of energy consumption and 28% of greenhouse gas emissions in the U.S. In densely populated urban areas, the share of energy use and emissions attributable to buildings can be even higher. The future evolution of building energy use and associated carbon emissions is uncertain, with potentially substantial variations in climate conditions, socioeconomic development, and power sector trajectories; accounting for these in future projections is often compounded by limited data availability and resolution of conventional modeling approaches. To address these challenges, in this study, we employed a bottom-up, high-resolution modeling approach and evaluated city-scale building energy consumption and CO2 emissions across 277 urban areas in the U.S. under various mid-21st century scenarios. Our findings reveal substantial spatial and temporal variations in future changes in building energy use and CO2 emissions among U.S. cities under a variety of climate, socioeconomic, and power sector evolution scenarios. On average, a 1°C warming at the city scale projects a 13.8% increase in building energy use intensity for cooling, accompanied by an approximately 11% decrease in energy use intensity for heating, albeit with notable spatial disparities. Collectively, driven by global warming and socioeconomic development, mid-century city-level building energy use is projected to rise on average by 17.5–39.8% under all scenarios except for SSP3-7.0 when compared with the last decade. In contrast, city-level building CO2 emissions are projected to decrease in most urban areas (averaging from 10.6% to 66.0% under different scenarios), with spatial variations primarily influenced by climate change and power sector decarbonization.

How to cite: Wang, C., Reyna, J., Horsey, H., and Jackson, R.: Urban energy futures: Unraveling the dynamics of city-scale building energy use and CO2 emissions under mid-century scenarios, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13309, https://doi.org/10.5194/egusphere-egu24-13309, 2024.

09:05–09:15
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EGU24-14606
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ITS1.5/NP8.6
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ECS
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On-site presentation
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Xiaotian Ding, Yongling Zhao, Dominik Strebel, Yifan Fan, Jian Ge, and Jan Carmeliet

Evaluation of the outdoor thermal comfort and comprehension of the impact of urban morphology are essential for assessing heat-related risks and implementing urban planning strategies that enhance the resilience of urban populations to extreme heat events. However, the challenge lies in achieving city-wide thermal comfort mapping at high spatial and temporal resolutions, which requires consideration of the complex urban morphology (urban geometry and land cover) at a microscale, as well as the background meteorological factors at larger scale. Here, we introduce an effective framework for city-scale thermal comfort mapping at high spatial-temporal resolution that integrates WRF-UCM and SOLWEIG model, aiming to achieve fine-grained thermal comfort mapping at the city scale and to explore the impact of urban morphology on these thermal conditions.

In the proposed framework, we employ the WRF-UCM model (The Weather Research and Forecasting model coupled with the urban canopy model) to establish the background meteorological condition at local-scale (500m resolution). Additionally, we utilize the SOLWEIG (Solar and Longwave Environmental Irradiance Geometry) model for the simulation of mean radiant temperature at a finer micro-scale (10m resolution), a critical determinant of thermal comfort. These simulations are performed using detailed 3D urban morphological data and land cover information. Subsequently, the Universal Thermal Climate Index (UTCI) is calculated on hourly basis, integrating the aforementioned factors.

A case study conducted for a Chinese city with a population of 15 million demonstrates a significant correction between the rise in the UTCI during daytime and an increase in impervious surface area, evidenced by a maximum correlation coefficient of 0.80. Furthermore, our findings emphasize the significance of tree canopy coverage in mitigating heat, demonstrating that an implementation of 40% tree cover could diminish daytime UTCI by approximately 1.5 to 2.0 ºC. This methodological framework is not only instrumental in assessing heat-related risks and human thermal discomfort within intricate urban environments but also offers pivotal insights for the adoption of climate-resilient urban planning strategies.

How to cite: Ding, X., Zhao, Y., Strebel, D., Fan, Y., Ge, J., and Carmeliet, J.: A cross-scale methodological framework for the quantification of the impact of urban features on intra-city microclimate, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14606, https://doi.org/10.5194/egusphere-egu24-14606, 2024.

09:15–09:25
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EGU24-18963
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ITS1.5/NP8.6
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ECS
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Highlight
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On-site presentation
How much data do we need to assess future flood risk in data-scarce mega-cities?
(withdrawn)
Veronika Zwirglmaier and Matthias Garschagen
09:25–09:35
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EGU24-20304
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ITS1.5/NP8.6
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ECS
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On-site presentation
Alistair Ford, Yimeng Liu, Richard Dawson, and Saini Yang

Extreme rainfall causes disruption and damage to urban transport networks through flooding, resulting in economic impacts for residents and businesses. The impact of such extreme weather events is the result of a complex interaction between the hazard (shaped by the nature of the rainfall and urban characteristics such as topography and land-use), exposure (the spatial and temporal intersection of the flood footprint with urban infrastructure and assets), and vulnerability (the ability of those assets and their users to cope with the level of flooding).

This paper demonstrates a complex systems approach to understand the role of these three components of the impact on urban transport systems by dynamically coupling a hydrodynamic flood model (such as CADDIES 2D or CityCAT) with an agent-based transport model (SUMO). By simulating a range of extreme rainfall events at a range of times of day, the modelling approach allows quantification of the scale of the impact (both direct and indirect) and assessment of adaptation options to reduce the disruption. Inclusion of coupled dynamic models allows the exploration of both hard, including engineered and nature-based approaches, and soft measures such as early warning and home working. This allows for a more-complete cost-benefit analysis of interventions and understanding of their effectiveness.

The modelling approach is demonstrated for a range of extreme rainfall events on commuting journeys on the road network in the city of Beijing, China. The results show that whilst grey and green approaches to adaptation can reduce the impact of extreme rainfall on the transport network, the benefits of soft measures, such as demand reduction by increased home working, are greater. Such soft measures also have additional co-benefits for reduction in emissions from transport, and potentially a lower implementation cost. Only by considering these interactions in a complex systems approach can such an assessment be undertaken.

 

How to cite: Ford, A., Liu, Y., Dawson, R., and Yang, S.: Asssessing the impacts of extreme rainfall on urban transport: a complex systems approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20304, https://doi.org/10.5194/egusphere-egu24-20304, 2024.

09:35–09:45
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EGU24-9349
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ITS1.5/NP8.6
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ECS
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On-site presentation
Developing a global building morphology dataset for urban hydroclimate simulation
(withdrawn)
Ruidong Li, Ting Sun, Saman Ghaffarian, Michel Tsamados, and Guang-Heng Ni
09:45–09:55
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EGU24-15532
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ITS1.5/NP8.6
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ECS
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On-site presentation
Marwa Alfouly and Thomas Hamacher

Urban areas are major contributors to climate change, accounting for 71 to 76% of CO2 emissions from global final energy use [1]. Nevertheless, cities are growing in both size and number. By 2030, it is projected that 730 million people will live in megacities (cities with at least 10 million inhabitants) compared to 500 million people in 2016 [2]. The number of megacities will also increase from 29 to 43 [3]. On the other side, solar radiation is an important component in the energy balance of urban areas. Urban form impacts the production of building-integrated photovoltaics, solar heat gains and heating/cooling demand of buildings. Relevant urban form characteristics include urban layout, population density, and individual building characteristics, such as height, wall orientation, roof slope, and construction material. Optimization of the urban form design can contribute to better energy performance of buildings. However, optimization is a large multivariable problem that is computationally intensive. A good understanding of the urban form impact can guide the optimization. In this work, the influence of shadow from surrounding buildings on solar radiation incident on buildings is studied provided a three-dimensional (3D) model of an area.

Open Access 3D models for many cities are made available by local authorities. Standardized data formats for 3D modelling are well-established. The scientific community has been working towards understanding urban forms, their impact on energy demand, and the potential for realizing sustainable urban forms. So far, the available work relied on different tools to analyze the impact of urban form on space heating/cooling demand for a specific city making reproducibility difficult. 

This work shows the advantage of using the standardized CityJSON format to establish an open-source Python-based framework to calculate hourly solar irradiance on building facades, considering the shadow of surrounding buildings, generate a thermal model of building envelopes, and calculate heat losses, gains, and the heating load of a building. The proposed methodology involves three phases. First is data collection and pre-processing. Second is the calculation of direct solar radiation on building facades and roofs. For that, hourly sun positions have been determined.  Maximum shadow length is calculated for each sun position. The geometry of buildings is analyzed, shared walls are excluded, and exemplary window vertices are allocated on the free walls such that the window-to-wall ratio ranges between 15% and 25%. Orientations of walls and slopes of tilted roofs were identified. Hyper-points are deployed on each surface in a 0.5m grid. With that, shadow height at each hyper-point and direct solar radiation were calculated. Third is the estimation of the heating or cooling load.

An exemplary neighborhood in Munich is presented as a real case study. Preliminarily results confirm that urban form is influencing the energy performance of buildings. Less shadowing on a building implies higher solar exposure but not necessarily reduced heating demand despite identical thermal properties of buildings’ envelope.

 

 

References:

[1] United Nations. (2017). Urban Environment. https://unfccc.int/resource/climateaction2020/media/1308/Urban_Environment_17.pdf

[2] United Nations. (2016). The World’s cities in 2016: data booklet. http://digitallibrary.un.org/record/1634928

[3] European Commission. (2020). Urbanisation worldwide. https://knowledge4policy.ec.europa.eu/foresight/topic/continuing-urbanisation/urbanisation-worldwide_en

How to cite: Alfouly, M. and Hamacher, T.: Evaluating Urban Form Influence on Solar Exposure and Corresponding Building Energy Demands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15532, https://doi.org/10.5194/egusphere-egu24-15532, 2024.

09:55–10:05
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EGU24-1502
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ITS1.5/NP8.6
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ECS
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Highlight
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Virtual presentation
Antonis Papantoniou, Chris Danezis, and Diofantos Hadjimitsis

Cities play a crucial role in climate neutrality because although they occupy only 4% of the EU land area, they host 75% of its population. In addition, they consume over 65% of global energy and account for more than 70% of global CO2 emissions. As climate change mitigation depends on urban action, the EU has decided to support cities in accelerating their green and digital transformation. The EU Mission on Climate-Neutral and Smart Cities aims to make the participating cities climate neutral and smart by 2030, in areas such as energy, waste management, transport, and buildings, to improve the quality of life. A WEBGIS Smart City Geospatial Framework has been developed for the Limassol Municipality in Cyprus. The establishment of a Smart City Geospatial Framework is imperative for several reasons. Firstly, it enables data-driven decision-making, allowing city officials to make informed choices about urban planning and resource allocation. Secondly, it enhances the efficiency of public services, such as transportation and emergency response, by leveraging real-time spatial data. Moreover, the framework promotes sustainability by providing insights into environmental factors, contributing to eco-friendly urban development. Lastly, the integration of geospatial technologies fosters citizen engagement, transparency, and overall improvement in the quality of life for urban residents. Under this WEBGIS smart city framework, the authors explore the importance of supporting the Limassol Municipality under the EU Mission for climate-neutral and smart cities by 2030 initiative, using the proposed WEBGIS smart city framework.  Results are presented using the GIS dashboard.

How to cite: Papantoniou, A., Danezis, C., and Hadjimitsis, D.: Exploring the importance of using a novel Smart City Geospatial Integrated Framework for supporting Cities participating in EU Mission for climate-neutral and smart cities by 2030: the case study of Limassol in Cyprus., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1502, https://doi.org/10.5194/egusphere-egu24-1502, 2024.

10:05–10:15
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EGU24-9711
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ITS1.5/NP8.6
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On-site presentation
Luca Guerrieri, Marzia Rizzo, and Roberto Passaquieti

A full access to high-quality geological data is fundamental to address all different aspects of land management, such as adapting to existing geohazard and ensuring the availability of georesources (e.g. critical raw materials and geothermal energy). This is particularly relevant in urban areas, where a multidisciplinary and integrated approach to diverse geological issues is imperative.

GeoSciences IR is a geological research infrastructure currently being implemented through NextGenerationEurope funds, with the aim of meeting the needs of Regional Geological Surveys (RGS), the local technical offices having a specific mandate on geological topics at regional and local level, including the urban environment.

Through the GeoSciences IR platform, it will be possible to access data, services, tools, and training modules developed in accordance with the FAIR principles and the INSPIRE Directive, which require fully open accessibility, interoperability, and reusability.

The priority topics of GeoSciences IR have been selected according to the RGS'needs and encompass various geological themes, including 2D and 3D geological mapping, marine geology, geoheritage conservation, geohazard mapping and monitoring, sustainable mining, and land consumption.

Among datasets under preparation, some will be of more specific interest for the urban environment, including i) stratigraphies from boreholes; ii) characterization of local geohazard related to landslides, sinkholes, active and capable faulting; iii) structural works for the mitigation of hydrogeological risk; iv) ground motion mapping and monitoring for low-velocity slope movements and subsidence; v) soil sealing and land consumption monitoring.

Users will also benefit from the full interoperability among services and will be able to access innovative tools based on specific algorithms available for cloud data processing.

Furthermore, a specific section of GeoSciences IR will be dedicated to e-learning modules built to increase the transfer of knowledge from scientists to end-users of GeoSciences IR. These modules have mainly focused on the methodological approach for data collection and on the use of available datasets and tools.

GeoSciences IR is under implementation by a large consortium composed by 13 Italian universities and 3 research institutes, coordinated by ISPRA, Geological Survey of Italy. The infrastructure will open to the public in 2025 and will be maintained for at least 10 years.

In this long-term perspective, a dialogue with external stakeholders (from institutions and the private sector) has already started with the aim of building a reference infrastructure for geological data in Italy, taking into account also their feedback and, in some cases, including additional contributions in terms of data, services and tools. Meanwhile, a constant interaction has been established with other existing research infrastructures available at European level (e.g. EPOS ERIC, EGDI) to ensure their complementarity and identify eventual gaps and overlaps.

How to cite: Guerrieri, L., Rizzo, M., and Passaquieti, R.: GeoSciences IR: a geological research infrastructure for land management in urban areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9711, https://doi.org/10.5194/egusphere-egu24-9711, 2024.

Coffee break
Chairpersons: Daniel Schertzer, Klaus Fraedrich, Maider Llaguno-Munitxa
10:45–10:55
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EGU24-18781
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ITS1.5/NP8.6
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ECS
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On-site presentation
Yue Zeng, Jianhua Guo, and Xiao Xiang Zhu

The urban heat island effect is a well-documented phenomenon in cities, particularly in metropolitan areas, with recognized environmental consequences. Mitigating this effect through urban green space planting strategies has been widely acknowledged. However, the extent of the spatial heterogeneity of the cooling effect across different urban functional zones remains insufficiently explored at a fine scale of urban green space.

In this study, we employed a robust semi-supervised deep learning method to precisely segment urban green spaces from high-resolution remote sensing images and developed a 0.5 m fine-scale urban green space product tailored for the Beijing metropolitan area. Leveraging the fine-grained urban green space segmentation results, we modeled cooling efficiency through a nonlinear relationship, quantified as the temperature reduction for a 1% urban green space cover increase. We also conducted a comprehensive assessment of differential cooling efficacy, considering both reference temperature and urban green space cover levels, across diverse urban functional zones at the scale of 300 m × 300 m urban grids.

The results revealed substantial disparities in cooling efficiency among different urban functional zones and different levels of urban green space coverage in Beijing. To be specific, with a 1% increase in urban green space, the commercial zone, residential zone, industrial zone, transportation zone, and public zone can achieve a cooling effect with a mean of 0.095 ± 0.075°C, 0.075 ±0.065°C, 0.075±0.065°C, 0.070±0.060°C and 0.055±0.045°C respectively. By uncovering spatial variations and heterogeneity in cooling effects, our study underscores the critical need for customized strategies in urban green space planning based on functional zone characteristics and offers valuable insights into urban planning and sustainable development practices.

How to cite: Zeng, Y., Guo, J., and Zhu, X. X.: Differential Cooling Efficacy of Fine-Grained Urban Green Spaces Across Diverse Functional Zones: A Case Study in the Beijing Metropolitan Area, China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18781, https://doi.org/10.5194/egusphere-egu24-18781, 2024.

10:55–11:05
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EGU24-20502
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ITS1.5/NP8.6
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ECS
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On-site presentation
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Eduardo Rico Carranza

Recently, we have seen an increase in models that combine powerful technical simulations with efficient visualizations and user interfaces that support decision-making in environmental and urban policies. These tools, known as Digital Twins (DTs) have been currently applied to water management and cities, however, their use tends to be limited to reduced groups of technical experts, policymakers and city officials, with the models behind these tools not being openly available, even though they may be publicly funded. Simultaneously developers, who may be interested in using these models to assess their proposals, cannot access them and must develop their local models, in many cases trying to catch up with new legislation.  A more efficient and open method could be implemented based on sharing evidence-based models through the planning application process. We call this an Integrated Water Planning Portal (IWPP), which consists of a web platform that gives developers access to a water systems model to test their proposals and use this work in the planning application process, which can be done through the same platform. In parallel to this, planners can use the portal to review this work, comment on it or give a final planning verdict. For such a system to work, robust data-sharing and model deployment protocols need to be implemented to strike a balance between accuracy, understandability and data protection. We present work on the feasibility of IWPP, based on prototype development and semi-structured interviews with stakeholders in the UK water management field. Evidence from this work suggests a targeted approach to modelling and data collection which is presented in a model framework. This approach satisfies the requirements of different stakeholders and provides a robust base for further development of tools such as IWPP.

How to cite: Rico Carranza, E.: Integrated Water Planning Portal: Feasibility study for a development-oriented digital twin to facilitate integrated water management through targeted data and model sharing., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20502, https://doi.org/10.5194/egusphere-egu24-20502, 2024.

11:05–11:15
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EGU24-21264
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ITS1.5/NP8.6
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Highlight
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Virtual presentation
Interactive City Information Model for Urban Environmental Assessments
(withdrawn)
Konstantina Ntassiou, Chiara Cavalieri, Elena Agudo-Sierra, Alexandre Bossard, and Maider Llaguno-Munitxa
session2
11:15–11:25
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EGU24-16662
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ITS1.5/NP8.6
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Highlight
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On-site presentation
Ioulia Tchiguirinskaia, Yangzi Qiu, and Daniel Schertzer

This work has benefited from a multidisciplinary scientific and technical contributions geared by the HM&Co Lab of the Ecole des Ponts ParisTech (hmco.enpc.fr) towards the sustainable, desirable, and resilient city. The deepening of the Universal Multifractal (UM) concepts and the encouragement of their operational applications have been linked to several initiatives launched in recent years to better integrate the heterogeneity/intermittency into public policy practices. Considering the complex, dynamic interactions between geophysical and anthropogenic fields within a conurbation such as the Ile de France region, a transition towards the shared value economy has been considered to best stimulate sober and collaborative development, and there exist at least 3 ways to approach today’s discussions about future transformations. Their intercomparison is the core of this presentation.

Following the United Nations 2030 Agenda, the first most conventional approach is based on notions of sustainable development, supported by appropriate adaptation and mitigation of climate change.

Combining the notions of extreme variability and complexity would require linking together geophysical and urban scales within extreme variability, and therefore considering geosciences, and not just geophysics! Such a synergistic and integrative approach would help move beyond traditional silo thinking, addressing the complexity of data- and/or theory-driven urban geosciences.

Finaly, combining the notions of scaling and nonlinear variability would ultimately require linking cascades, multiplicative chaos, and multifractals. This would initiate a break with linear stochastic models towards stronger heterogeneity / intermittency, which would in turn lead to a plausible clustering of field and activity fluctuations. The appearance of multifractal phase transitions then becomes possible, considerably amplifying the impact of any action, and would make future transformations fully efficient, effectively imitating the way in which Nature acts. This will be finally illustrated using several examples of so-called Nature Based Solutions (NBS).

How to cite: Tchiguirinskaia, I., Qiu, Y., and Schertzer, D.: Different Approaches to the Impacts of Climate Change, with a Common Goal: a Healthy Planet, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16662, https://doi.org/10.5194/egusphere-egu24-16662, 2024.

11:25–11:35
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EGU24-14334
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ITS1.5/NP8.6
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Virtual presentation
Le Duc, Juyoung Jo, and Yohei Sawada

Urban drainage models have been used in many cities for analysis, prediction, and control related to urban flooding. Many sources of uncertainties exist in these models comprising model parameters, meteorological forcings, and surface conditions. Thus, it is necessary to calibrate models before using them in reality. A common choice in calibration is to fit the model outputs with observations through many cases. This strategy is known as the offline mode in calibration and works on the stationary assumption of model parameters. If parameters vary in time, this method usually yields the climatological range of the parameters, which are not necessarily optimal in specific cases. In this study, instead of the offline model we follow the online mode in estimating model parameters by using an ensemble Kalman filter (EnKF). Furthermore, we estimate not only model parameters but also model states simultaneously utilizing the EnKF. Note that originally, EnKF is a data assimilation technique that is based on sampling in estimating any system states given observations, and later is used for the purpose of parameter estimation. The combination of EnKF and an urban drainage model is expected to lead to a real-time monitoring system for urban flooding similar to reanalysis systems in numerical weather prediction.

How to cite: Duc, L., Jo, J., and Sawada, Y.: Realtime monitoring of urban flooding by ensemble Kalman filters, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14334, https://doi.org/10.5194/egusphere-egu24-14334, 2024.

11:35–11:45
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EGU24-11021
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ITS1.5/NP8.6
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ECS
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Virtual presentation
Arun Ramanathan, Pierre-Antoine Versini, Daniel Schertzer, Ioulia Tchiguirinskaia, Remi Perrin, and Lionel Sindt

Abstract

Temporal structure functions are usually defined as the q-th order statistical moment of the absolute fluctuation in a time series over a temporal lag at a given resolution. However, applying this in analyzing a temperature time series results in the possibility of simulating only a similar fluctuation over a temporal lag at a resolution and not the temperature directly. Since the aim is to simulate a temperature time series this simulated fluctuation series can be added to an assumed mean temperature to obtain a temperature time series. However, proceeding this way seems to necessitate some ad-hoc moving average technique that seems difficult to be physically reasoned. Secondly but more importantly both diurnal and seasonal periodicity have to be forcibly introduced once again in a non-rigorous manner. A drastic yet reasonably useful alternative would be to modify the definition of the structure-function instead. For order of statistical moment q  the modified structure function is now defined here as

Sq(Δt)=⟨ΙTλ - Tλ/2,2Ιq

Where the scale ratio λ∝1/ΙΔtΙ; 2m/2m=1≤λ≤Λ=2m/20 and ΙΔtΙ is the time lag, whereas 2m is the largest possible scale out of the scales analyzed that can be represented as a power of 2. While Tλ is the temperature at scale ratio λ or scale l, Tλ/2,2 is the upscaled (by a scale ratio of 2) temperature at scale ratio λ/2 or scale 2l, and the subscript ‘2’ indicates that each element of  Tλ/2 (upscaled temperature) is repeated twice consecutively. It should be noted that Tλ/2,2 is not the same as Tλ because the former is an upscaled series, twice repeated (consecutively) of the latter. The largest scale ratio considered in the analysis is Λ. By defining the structure-function in this way temperature at a larger scale after being repeated a sufficient number of times can be directly added to the fluctuation at a smaller scale to result in the temperature at a smaller scale. The universal multifractal parameters obtained from the modified structure-function analysis are not necessarily equal to those obtained from the usual structure-function analysis (i.e. the two different structure functions follow two different scaling laws). An iterative curve fitting technique is used to estimate the values of Universal Multifractal (UM) parameters C1, H, and a  while the value of α  is estimated using a normalized form of the modified structure function along with the un-normalized one. A simulation procedure that utilizes the aforementioned modified structure function definition is proposed here to generate temperature scenarios. Finally, reference evapotranspiration is estimated based on the simulated temperature using a simple empirical power law function. The actual evapotranspiration is estimated using the reference evapotranspiration and water content via a different, simpler empirical function. The tentative methodology proposed here when used along with simulated reference rainfall scenarios could help design zero-emission green roof solutions.

 

Keywords

Multifractals, Non-linear geophysical systems, Cascade dynamics, Scaling, Hydrology, Meteorology.

How to cite: Ramanathan, A., Versini, P.-A., Schertzer, D., Tchiguirinskaia, I., Perrin, R., and Sindt, L.: Simulating Temperature and Evapotranspiration using a Universal Multifractal approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11021, https://doi.org/10.5194/egusphere-egu24-11021, 2024.

11:45–11:55
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EGU24-8391
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ITS1.5/NP8.6
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On-site presentation
Charalampos Ntigkakis, Stephen Birkinshaw, Ross Stirling, and Brian Thomas

Groundwater flooding within the urban infrastructure can play a major role in determining the resilience of urban environments. Urban groundwater models can be used to simulate the complex interactions between surface water and groundwater within the urban system and can be developed to jointly account for groundwater-surface water processes and subsurface characterization. They can be used to simulate potential groundwater flooding and help understand the role of groundwater in urban resilience to climate change. However, urban groundwater is a component of the wider urban water system that has traditionally been overlooked, and the complex interactions between surface water and groundwater may obscured by urban infrastructure and its influence on groundwater flow. Furthermore, the subsurface characterisation is an integral part of any groundwater model, however it’s influence on model performance is not yet fully understood. Therefore, the inherent complexities of the urban environment, combined with the scarcity of appropriate groundwater and subsurface data, can lead to increased model uncertainty. It is argued that robust urban groundwater modelling depends on a strong conceptual understanding of the groundwater system, and constraining the uncertainty in the subsurface characterisation.

This project aims to assess model sensitivity to the geological interpretation in simulating groundwater dynamics that represent regions of groundwater flooding. It accounts for uncertainty in the subsurface information to develop an ensemble of different geological interpretations and evaluate the influence of the subsurface characterisation on groundwater flow model performance, within the Ouseburn watershed in the greater Newcastle upon Tyne area.

How to cite: Ntigkakis, C., Birkinshaw, S., Stirling, R., and Thomas, B.: Urban hydrogeologic uncertainty characterisation to evaluate risk of groundwater flooding, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8391, https://doi.org/10.5194/egusphere-egu24-8391, 2024.

11:55–12:05
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EGU24-7877
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ITS1.5/NP8.6
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ECS
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On-site presentation
Yangzi Qiu, Pierre-Antoine Versini, Nathanaël Mifsud-Couchaux, and Ioulia Tchiguirinskaia

The infrastructures of Régie Autonome des Transports Parisiens (RATP) system are significant for the transportation of the Île-de-France region, providing essential social and economic services. In order to assess and mitigate the negative impact of climate change, this study aims to characterise the flood and heat wave risks of RATP infrastructures under climate change on multiple scales. Extreme flood events and heat wave events may result in the functional disruptions to the RATP infrastructures by interrupting circulation for more or less long periods. Therefore, a better understanding of the multi-scales risk (combining hazard, exposure and vulnerability indicators) of RATP infrastructures could enhance their resilience to climate change. With this respect, a multi-scale analysis of flood and heat wave risks of RATP infrastructures is presented by integrating the Universal Multifractal (UM) framework and analytic hierarchy process (AHP). The UM framework is a stochastic method that allows analysis of the natural hazards (extreme precipitation and temperature) and risks under three future climate scenarios (RCP2.6, RCP4.5, RCP8.5) across a range of scales. The AHP method is applied for quantifying the various risks by weighting hazard, exposure and vulnerability indicators based on experts’ knowledge. The results show that a certain number of RATP stations and lines are prone to flood and heat waves under climate change, especially in the RCP8.5 scenario. By undertaking the multiple scales of flood and heat wave risks of RATP infrastructures, this study seeks to contribute valuable insights that will inform strategic planning and resilience-building initiatives for RATP infrastructures under climate change (adaptation measures). It provides a theoretical basis for multiple risk assessments in other metropolitan areas worldwide.

How to cite: Qiu, Y., Versini, P.-A., Mifsud-Couchaux, N., and Tchiguirinskaia, I.: Multiscale characterisation of varied risks for transportation infrastructures under climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7877, https://doi.org/10.5194/egusphere-egu24-7877, 2024.

12:05–12:15
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EGU24-1003
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ITS1.5/NP8.6
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ECS
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On-site presentation
Rui Deng, Ziqi Li, and Mingshu Wang

Machine learning (ML) and Artificial Intelligence (AI) models have been increasingly adopted for geospatial tasks. However, geospatial data (such as points and raster cells) are often influenced by underlying spatial effects, and current model designs often lack adequate consideration of these effects. Determining the efficient model structure for representing geospatial data and capturing the underlying complex spatial and contextual effects still needs to be explored. To address this gap, we propose a Transformer-like encoder-decoder architecture to first represent geospatial data with respect to their corresponding geospatial context, and then decode the representation for task-specific inferences. The encoder consists of embedding layers that transform the input location and attributes of geospatial data into meaningful embedding vectors. The decoder comprises task-specific neural network layers that map the encoder outputs to the final output. Spatial contextual effects are measured using explainable artificial intelligence (XAI) methods. We evaluate and compare the performance of our model with other model structures on both synthetic and real-world datasets for spatial regression and interpolation tasks. This work proposes a generalizable approach to better modeling and measuring complex spatial contextual effects, potentially contribute to efficient and reliable urban analytic applications that require geo-context information.

How to cite: Deng, R., Li, Z., and Wang, M.: A Transformer-Based Model for Effective Representation of Geospatial Data and Context, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1003, https://doi.org/10.5194/egusphere-egu24-1003, 2024.

12:15–12:25
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EGU24-1223
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ITS1.5/NP8.6
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ECS
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Virtual presentation
Charunika Sandamini Arambegedara, Yu Lijun, Danlu Cai, Jianfeng Zhu, Asanga Venura Ranasinghe, and Ambepitiyawaduge Pubudu De Silva

In recent years, Sri Lanka has experienced a high prevalence of chronic kidney disease (CKDu) in certain regions, especially in the North Central Province (NCP). The etiology of this disease is not yet clearly understood, although several hypotheses involving environmental and occupational factors have been proposed. To better understand the patterns of CKDu incidence and its potential relationship to environmental factors, a spatial and temporal analysis was conducted using geographic information system (GIS) tools. In this study, we identified the geographical hotspots of CKDu incidence over a period of eleven years (from 2010 to 2020) in the NCP, of Sri Lanka. The analysis was done for the districts of Anuradhapura and Polonnaruwa in NCP. Furthermore, we analysed the temporal trends of CKDu incidence by comparing the disease burden between different years. Finally, we examined the association between river basins and CKDu incidence by overlaying the spatial layers of the disease incidence and river basins. Our results showed that there were significant spatial and temporal variations in CKDu incidence in the region over the study period. The disease is characterized by a fluctuating trend. Also, the number of hotspots has decreased over time, and the number of CKDu-affected patients has also decreased. Similarly found that CKDu hotspots were concentrated around the mainly 4 river basins in the region, indicating a possible link between water resources and the disease. By identifying CKDu hotspots and understanding the disease's movement over time, public health officials can target their efforts more effectively, reducing the disease's impact on affected communities. This study provides important insights into the spatial and temporal patterns of CKDu and suggests the need for further research to investigate the potential environmental risk factors contributing to this disease.

 

Key Words: Chronic Kidney Disease of Unknown Etiology (CKDu), Hotspots Analysis, Spatial and Temporal Variation, Geographical Information System (GIS)

How to cite: Arambegedara, C. S., Lijun, Y., Cai, D., Zhu, J., Ranasinghe, A. V., and Silva, A. P. D.: Spatial and Temporal Analysis for Identifying the Movement of Chronic Kidney Disease (CKDu) Hotspots; in Reference to River Basins in North Central Province, Sri Lanka, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1223, https://doi.org/10.5194/egusphere-egu24-1223, 2024.

Lunch break
Chairpersons: Francesco La Vigna, Tim Kearsey, Maider Llaguno-Munitxa
14:00–14:10
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EGU24-821
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ITS1.5/NP8.6
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ECS
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On-site presentation
Jiaqi Qian and Danlu Cai

Urbanization induced carbon dioxide (CO2) emissions have attracted widespread attention.

A comprehensive attribution analysis model is designed to understand the inherent uncertainties in diagnosing the effects of urban expansion dynamics and modes on carbon dioxide (CO2) emissions. First, 68 selected cities across China are categorized into three types, including expanding, contracting, and staying cities, through developing an evaluation indicator system by integrating population, economy, construction, and social information. Next, the carbon dioxide (CO2) emissions of the cities were quantified. The Lasso method was employed to select the factors influencing CO2 emissions. For cities with different development modes, the XGBoost regression model with SHAP algorithm was employed to calculate the contribution rate of various factors to carbon emissions in different types of cities. Additionally, the analysis considered the temporal changes of these factors.

The main conclusions are as follows:

(i)Comparing urban built-up areas extracted from the nighttime light dataset with China's national land use and cover change dataset, the results reveal a minimum correlation of 0.72-0.82 and an average overall accuracy of 78%.

(ii)The urbanization process of 68 cities exhibits a predominant pattern of normal fluctuations, with a coexistence of expansion and contraction. The results indicate that over the past 20 years, expanding cities have been concentrated mainly in coastal regions such as the Yangtze River Delta and the Pearl River Delta, while contracting cities are primarily found in inland areas characterized by traditional industrial cities. It is observed that the development processes of most cities involve an initial phase of intensive expansion (or contraction), followed by a gradual trend towards stability in the later stages.

(iii)The factors influencing carbon emissions in expanding and contracting cities share commonalities and differences. Population and energy efficiency both have significant impacts on carbon emissions in different types of cities. For expanding cities, the impact of green area on carbon emissions is more pronounced. Conversely, in contracting cities, the influence of foreign trade is more significant.

How to cite: Qian, J. and Cai, D.: The impact of the expansion and contraction of China’s cities on CO2 emissions,2002-2021,evidence from integrated nighttime light data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-821, https://doi.org/10.5194/egusphere-egu24-821, 2024.

session3
14:10–14:20
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EGU24-20734
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ITS1.5/NP8.6
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On-site presentation
Fredrik Mossmark, Jenny Norrman, Paula Lindgren, Emrik Lundin Frisk, Lorena Melgaço, Marilu Melo Zurita, Victoria Svahn, Tore Söderqvist, Olof Taromi Sandström, and Yevheniya Volchko

Geosystem services (GS) can be defined as the contributions humans derive from the subsurface: the use of the subsurface to build and construct within and on top, groundwater, energy and material extraction, storing of e.g. water, energy and carbon dioxide, providing habitats for diverse species and support for surface life, and serving as an archive of cultural and geological heritage. Sectorial management and lack of consequent consideration of subsurface geosystem services and competing or complementary subsurface uses promote the first-come-first-served principle, potentially hindering a sustainable management of the subsurface and compromising inter- and intra-generational equity. The research project “UNDER: Geosystem services underneath for sustainable communities and improved spatial planning practices” has the overall goal to develop a framework for systematic and structured consideration of geosystem services in Swedish planning practices that can support a path towards sustainable cities and communities. The specific objectives of the UNDER project are to: i) advance the concept of GS by identifying and mapping associated societal values (social, environmental and economic), ii) identify methods to assess societal values and investigate possibilities for integration in existing tools, iii) identify structures of governance and develop a broader and practice-informed understanding of the different societal actors in subsurface planning, and iv) create a participative learning environment, extended beyond the project implementation period leading to transformative processes in planning practice. The project is case study driven and works in collaboration with Swedish municipalities. Four ongoing spatial planning processes in Swedish municipalities have been selected as case studies, which will provide a variety of spatial planning contexts and objectives. The project is a multi-disciplinary, international project with funding from the Swedish research council Formas, running during 2021 - 2025. The presentation of the project will focus on the project activities, preliminary results, and future work.

How to cite: Mossmark, F., Norrman, J., Lindgren, P., Lundin Frisk, E., Melgaço, L., Melo Zurita, M., Svahn, V., Söderqvist, T., Taromi Sandström, O., and Volchko, Y.: UNDER: Geosystem services underneath for sustainable communities and improved spatial planning practices, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20734, https://doi.org/10.5194/egusphere-egu24-20734, 2024.

14:20–14:30
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EGU24-22240
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ITS1.5/NP8.6
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On-site presentation
Rouwen Lehne, Sonu Roy, Heiner Heggemann, and Christoph Schueth

While 3D city models are now available for many large and medium-sized cities and are increasingly being used, the urban subsurface (= urban geology) continues to be neglected in such models in most cases. The reasons for this are both inhomogeneous and complex geological/hydrogeological information, which at the same time is not assembled in a context-specific way, as well as a lack of standards, interfaces and exchange formats.

To overcome these barriers, geological and hydrogeological 2D and 3D content is currently being elaborated for several urban areas in the federal state of Hesse in close cooperation with the municipal cooperation partners using all available input data (in particular, however, boreholes, geological cross sections and groundwater level measurements), which are being assembled with a view to defined "urban geoparameters".

In addition, an attempt will be made to visualize the urban underground infrastructure (man-made objects) in 3D space and thus bring it into a synopsis with the geological and hydrogeological 2D and 3D content.

The synopsis, in turn, should be carried out in the respective working environments as far as possible, i.e. using the software solutions operated by the cooperation partners. To ensure this, both suitable interfaces and a suitable exchange format are required in the 3D data management systems for geological/hydrogeological models. The OGC API 3D GeoVolume and Styles interfaces and the 3D Tiles exchange format are considered to be the solution here.

With this presentation, we would like to present the current state of work with a focus on the parameterisation and packaging of geological and hydrogeological 2D and 3D data for urban areas.

How to cite: Lehne, R., Roy, S., Heggemann, H., and Schueth, C.: Urban geology as part of 3D city models - challenges and solutions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22240, https://doi.org/10.5194/egusphere-egu24-22240, 2024.

14:30–14:40
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EGU24-20648
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ITS1.5/NP8.6
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ECS
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Highlight
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Virtual presentation
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Azzurra Lentini, Jorge Pedro Galve, Moreno Beatriz Benjumea, Stephanie Bricker, Xavier Devleeschouwer, Paolo Maria Guarino, Timothy Kearsey, Gabriele Leoni, Romeo Saverio, Guri Venvik, and Francesco La Vigna

The Urban Geo-climate Footprint (UGF) project has been developed in the context of the Urban Geology Expert Group of Euro Geo Surveys, aimed to define a new methodology to classify and cluster cities by geological and climatic point of view.

The basic assumption of the UGF approach is that cities with similar geological-geographical settings should have similar challenges to manage, due to both common geological issues and climate change subsoil-related effects. Following this approach, a holistic tool consisting in a complex spreadsheet has been developed and applied to more than 40 European cities, in collaboration with several Geological Surveys of Europe.

It is demonstrated as the Urban Geo-climate Footprint tool is currently capable of providing a semi-quantitative quick representation of the pressures driven by geological and climatic complexity in the analysed cities, providing for the first time such classification for the urban environment.

Through the wide application of this methodology several benefits could be reached as the general awareness increase of non-experts and the enhanced reading-the-landscape capacity of decision makers about the link between geological setting and the increase in pressures due to climate change and anthropogenic activity.

Furthermore, the UGF approach would facilitate the possibility to exchange best practices among similar cities for planning purposes, and it would support the decision processes to define and differentiate policies and actions, also supporting policy and cooperative geoscience and climate justice.

 

How to cite: Lentini, A., Galve, J. P., Benjumea, M. B., Bricker, S., Devleeschouwer, X., Guarino, P. M., Kearsey, T., Leoni, G., Saverio, R., Venvik, G., and La Vigna, F.: Current status of the Urban Geo-climate Footprint project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20648, https://doi.org/10.5194/egusphere-egu24-20648, 2024.

14:40–14:50
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EGU24-18610
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ITS1.5/NP8.6
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Highlight
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On-site presentation
Sophie O'Connor and Beatriz Mozo Lopez

Communicating the subsurface is a challenge. Geoscientists are trained to visualise what is underneath them and to see the subsurface in 3D, whereas planners, policy makers and the people impacted by both (i.e., the public) are not.

Over many years, Geological Survey Ireland has developed several services in different formats to help pull together information about the subsurface, to present it in an organised manner and to portray it in three dimensions. Underpinned by the organisation’s commitment to open data and re-use of public sector information, these services are:

  • National Geotechnical Borehole Database
  • Geotechnical Viewer
  • 3D models and model viewer

Assembled over several decades, the National Geotechnical Borehole Database has expanded with the submission of ground investigations that have been carried out ahead of development projects by the private and public sectors. It acts as a secure, national repository and is a valuable resource for:

  • planning and optimising future ground investigations;
  • understanding the subsurface and urban geology;
  • for helping construct 2D and 3D models.

For ease of access, data and reports from the National Geotechnical Borehole Database are published on the Geotechnical Viewer, freely available to all.  The online Geotechnical Viewer displays ground investigations as digitised, georeferenced polygons, with an associated downloadable report in .pdf format. Several thousands of ground investigations projects are presented.

With time and technical and software advances, Geological Survey Ireland has produced urban 3D geological models using the National Geotechnical Borehole Database. A primary function of these models is visual communication of the subsurface to geoscientists, professionals from other disciplines, researchers, students and members of the public.

Our urban 3D models can assist with:

  • Resource (water and geothermal) mapping;
  • Understanding and characterising urban geology, with potential relevance for basement impact assessment, Sustainable Drainage Systems (SuDS), flooding and, subsurface management;
  • Optimising geotechnical investigation, design and construction;
  • De-risking human activities from impact of our subsurface environment;
  • Investigating impact of human activities on environment around and beneath us, e.g., dewatering;
  • and informing policy, planning, protective and climate adaptation measures.

3D geological models allow everyone to visualise the subsurface and can be used to communicate the geoscience behind policy, thereby making defensible decisions visible. To ensure the 3D models are easily accessible by all, Geological Survey Ireland have a 3D model viewer where no software or zip file downloads are needed. The 3D model viewer has Interactive and Augmented Reality functionality.

Recognising the importance of freely available, accessible data for non-geoscientists, Geological Survey Ireland has created and smoothed pathways for stakeholders to access and visualise geological data in urban settings.

How to cite: O'Connor, S. and Mozo Lopez, B.: From paper reports to 3D models for all – Irish geodata in urban settings, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18610, https://doi.org/10.5194/egusphere-egu24-18610, 2024.

14:50–15:00
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EGU24-17225
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ITS1.5/NP8.6
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On-site presentation
Beatriz Benjumea, Carlos Marín-Lechado, Beatriz Gaite, Ana Ruíz-Constán, Martin Schimmel, Fernando Bohoyo, and Zack J. Spica

This work focuses on two case studies carried out in Spain, where urban geophysics plays an important role in subsurface characterization. The application of geophysical methods in urban scenarios faces several challenges related to environmental noise (seismic or electromagnetic) or logistical constraints (lack of open space, complexity of instrumentation setup). In order to overcome these problems, research efforts are needed on both acquisition and processing aspects. The first case study presents the use of an innovative technology to acquire seismic data in the city of Granada. Distributed Acoustic Sensing (DAS) is based on the measurement of strain rate along a buried optical fiber that provides seismic measurements in a dense array of sensors. In our study, the fiber is a pre-existing underground telecommunications cable that crosses the city from northwest to southeast. We used 10 hours of ambient noise recordings to obtain subsurface reflection images that provide critical information for ground motion studies and seismic hazards in the metropolitan area. The second case study is located in the autonomous city of Melilla (North Africa). In this work, a gravimetric survey was carried out over the urban area with the aim of delineating the bedrock using 3D gravimetric inversion. We integrated the resulting geophysical model with surface geological observations, electrical resistivity tomography sections and borehole data to produce a 3D geological model of the city. Both studies highlight the suitability of geophysical information to complement the urban geological and geotechnical dataset to characterize and image the city underground.

How to cite: Benjumea, B., Marín-Lechado, C., Gaite, B., Ruíz-Constán, A., Schimmel, M., Bohoyo, F., and Spica, Z. J.: Geophysics for urban subsurface characterization: Two case studies from Spain, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17225, https://doi.org/10.5194/egusphere-egu24-17225, 2024.

15:00–15:10
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EGU24-15561
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ITS1.5/NP8.6
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On-site presentation
Tim Kearsey, Stephanie Bricker, Ricky Terrington, Holger Kessler, Helen Burke, and Steve Thorpe

The UK Government Office for Science has recently commissioned a Foresight Project on the ‘Future of the Subsurface’. The project draws on experts across different government departments and industry - including representative from the geological and environmental community, planning specialists, infrastructure and service providers, city authorities and energy specialists - to understand the future demands that will be placed on the subsurface to deliver our sustainable development goals; What are the high-value future societal subsurface uses? What climatic and environmental pressures are expected? What policy interventions will be required to protect and enhance the value of the subsurface in the longer-term? We present outcomes from the Foresight project's subsurface issues paper, alongside recommendations from the National and Regional level expert elicitation. Drawing on our research in urban geosciences and subsurface assessment we highlight how geological surveys can, and are, responding to the issues and recommendations highlighted by the Foresight project.  Some common themes emerge for which the geological survey has a role, for example, ensuring coordinated and interdisciplinary approaches to planning; Assessing opportunities to update or streamline subsurface governance and regulation; Improving the coverage, quality, availability and interoperability of data.

In addition to these overarching principles, the variability of regional geology in the UK and its impact on subsurface issues is a prominent outcome of the Foresight project and necessitates place-based approaches, tailored to distinct geologies and geographies, to define a hierarchy of subsurface need.  The UK has a particularly varied geology spanning the whole Phanerozoic this means that there are very different geological problems in different cities. Taking this placed-based approach we show how the evolution of 3D geology mapping and geospatial tools at the British Geological Survey (BGS), has shifted towards multi-assessment to appraise the diverse integrated and competing subsurface uses. We highlight the practical applications of 3D models in improving data availability and accessibility e.g. by updating geological maps, enhancing data products, and facilitating user accessibility through tools like model viewers. The paper concludes by emphasizing the importance of geological information to help facilitate dialogue and stakeholder consultation, and support evidence-based policymaking.

How to cite: Kearsey, T., Bricker, S., Terrington, R., Kessler, H., Burke, H., and Thorpe, S.: How do geological surveys respond to evolving uses and interaction in the urban subsurface?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15561, https://doi.org/10.5194/egusphere-egu24-15561, 2024.

15:10–15:20
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EGU24-8476
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ITS1.5/NP8.6
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On-site presentation
Cecile Le Guern, Fabien Prézeau, Pierre Chrétien, and Blandine Clozel

Desealing appears as an option to disartificialise soils. It embraces several territorial issues like water management, adaptation to climate change, the well-being of inhabitants and biodiversity. In practice, many desealing operations are carried out. The areas to be desealed are most often linked to opportunities such as development projects or target actions (like school playgrounds). There are in fact few potential maps to support desealing strategies. Existing methods systematically take certain criteria into account (e.g. water infiltration). Environmental criteria are however more or less considered.

The DésiVille project (2021-2024) aims to provide decision-making tools to support desealing strategies. In particular, it is preparing a methodological guide to map the potential for desealing, in order to propose a harmonized and concerted framework. The methodology considers 4 thematics: i) the characteristics of the sealed surfaces, ii) the potential of infiltration of soils, iii) the environmental risks and the protection of resources, and iv) the benefits of desealing.

The thematics linked to the potential of infiltration of soils and to the environmental risks consider information on the subsurface. In particular the presence of clay and the groundwater depth feed the potential of infiltration. The environmental risks and protection of resources integrate the presence of soluble rocks, the risk of soil pollution, the risk of flooding due to groundwater rise, the geotechnical risk, area of protection of the water resource. A multicriteria spatial analysis crosses the information per thematic on one side, and among thematics on the other side. The study case of Nantes Métropole (France) illustrates the influence of the potential of infiltration and of the environmental risks and protection of resource on the global potential of desealing maps.

The subsurface needs to be considered to build desealing strategies. More generally, it is essential to consider it in urban planning and development. Although out of sight, it must not be out of mind.

How to cite: Le Guern, C., Prézeau, F., Chrétien, P., and Clozel, B.: Subsurface in territorial soil desealing strategies, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8476, https://doi.org/10.5194/egusphere-egu24-8476, 2024.

15:20–15:30
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EGU24-6045
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ITS1.5/NP8.6
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Highlight
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On-site presentation
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Jeroen Schokker and Joris Dijkstra

The urban subsurface is increasingly disturbed by human activity and/or covered by anthropogenic deposits. This is particularly true for city centres, with thick and heterogeneous subsurface archives related to historical urban development, as well as for modern residential and industrial areas, that are often built on extensive sheets of filling sand. The anthropogenic deposits may be very diverse in nature, ranging from natural aggregates (crushed rock, gravel, sand or clay) to various types of novel anthropogenic materials (e.g. steelworks slags, concrete and rubble), as well as mixtures of these.

Although anthropogenic deposits could be represented on subsurface maps and in 3D models, these deposits are often omitted. Their lateral extent and thickness are not well constrained and relevant information on the lithological properties of the deposits is generally lacking. At the same time, the demand for complete and detailed subsurface information in the built environment is increasing and relates to anything from building stability and ground heat extraction to preserving cultural heritage and mitigating the effects of climate change.

This presentation therefore focusses on the lithological characterisation and stratigraphical subdivision of anthropogenic deposits in order to improve their representation in 3D geological subsurface models. We will evaluate current lithological standards and stratigraphic approaches and present the principles of the approach that we are developing in the Netherlands. We will discuss the practical consequences and give examples of bringing our approach into practice. Ultimately, a well-thought lithological description and classification system of anthropogenic deposits is a prerequisite to produce reliable subsurface and coupled surface-subsurface models. In that way, we can address the many challenges related to the ever-increasing use of  urban space and thus improve the wellbeing of our citizens.

How to cite: Schokker, J. and Dijkstra, J.: Improved representation of anthropogenic deposits in 3D urban geological subsurface models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6045, https://doi.org/10.5194/egusphere-egu24-6045, 2024.

15:30–15:40
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EGU24-1818
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ITS1.5/NP8.6
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Highlight
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On-site presentation
Sebastian Pfleiderer

Information on urban groundwater in Vienna is important not only to secure a sustainable use and supply but also to protect groundwater quality. Here, we provide a compilation of available information and data to cover all relevant aspects of hydrogeology within the city in order to improve planning and policy making with regard to water extraction, geothermal use and groundwater protection.

We propose a grouping of the Quaternary and Neogene sediments as well as of the underlying sedimentary rocks of the Flysch zone and the Calcareous Alps, into hydrogeological units with distinct properties. Each unit is described regarding lithology, aquifer type, groundwater occurrence and yield. Additionally, the area percentage of sealed ground surface and the conditions of groundwater recharge are defined. Finally, the types of groundwater use, withdrawal rates, hydrochemical signatures and heavy metal contents are characterized.

Limestones and dolomites of the Calcareous Alps represent high yield karst aquifers with calcium-magnesium-bicarbonate-type hydrochemistry, used as spa water drawn from 800 m deep, artesian wells.

Within the Flysch zone, clay- and marlstones act as aquitards while sandstones constitute fractured or double-porosity aquifers which are partially confined, of low yield and used locally for drinking water, industrial water and irrigation. At the surface, the zone occurs in the Vienna Woods, where groundwater recharge through rain water can be high within sandstone areas.

Where Neogene silts and clays contain sand and gravel layers, these represent porous aquifers of low to medium yield, used mainly for irrigation, industrial water and geothermal purposes. Groundwater recharge from the surface is impeded by a thick loess cover. In the eastern part of the city, groundwater in a conglomerate layer of 300 m thickness and 3000 m below ground, reaches temperatures of up to 100°C and is considered Vienna’s future geo-energy reservoir.

Pleistocene terraces are made of gravel and, with decreasing age, show decreasing amounts of sand and silt intercalations, while the groundwater shows increasing yield, increasing mineralisation and major ion contents shifting from Ca and Mg dominance towards more Na and K. The terraces’ occurrence coincides with intense urban land use, sealing of the ground surface, low recharge and potential infiltration of leaking sewage water.

Within the Danube plain, 60 % of the land is used for agriculture and recreation where rain water can infiltrate easily into Holocene gravel. Recharge also happens partially through river bank filtrate of the Danube, partially through artificial recharge. Among all groundwater units in Vienna, this continuous aquifer shows the highest yield and the most intense use for irrigation and groundwater heat pumps. During peak periods of water demand, groundwater is also used as drinking water.

Vienna’s water consumption amounts to 200 litres per person per day approximatively. In periods of normal demand, drinking water is provided exclusively by Alpine karst springs captured up to 120 km southwest of the city.

How to cite: Pfleiderer, S.: The hydrogeological units of Vienna - land use, groundwater use and groundwater chemistry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1818, https://doi.org/10.5194/egusphere-egu24-1818, 2024.

15:40–15:45

Posters on site: Thu, 18 Apr, 10:45–12:30 | Hall X3

Display time: Thu, 18 Apr 08:30–Thu, 18 Apr 12:30
X3.51
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EGU24-20103
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ITS1.5/NP8.6
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ECS
An analytical urban temperature model with building heterogeneity using geometric optical theory
(withdrawn)
Zunjian Bian and Hua Li
X3.52
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EGU24-165
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ITS1.5/NP8.6
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ECS
|
Rakibul Ahasan and Burak Güneralp

Urban growth and infrastructure development, especially road network growth, are two interactive, coevolving processes, and to understand long-term urban growth dynamics, it is crucial to model these two processes codependently. Hence, in this study, we present a modeling framework that is capable of capturing the feedback between urban land and road network in forecasting the amount and spatial patterns at large regional scales. While this proposed model with road length as a model parameter forecasts up to 1.2 times new urban areas globally under different scenarios, traditional models with no road length consideration forecasted 1.5–3.7 times more urban areas in 2050. We also forecasted the growth in road network length and pattern considering urban areas as the attraction point. Our model forecasted a substantial amount of new roads to be added to existing global road inventory by 2050– ranging between 1.67 million km and 3.37 million km under five Shared Socio-economic Pathways (SSPs) scenarios. We present Nigeria, Brazil and Bangladesh as case studies where significant new road development is forecasted in currently underdeveloped areas. The overall output from this codependent modeling process will inform the updated connectivity pattern along with an urban growth forecast. This approach enables us to capture the influence of transportation development and the ongoing large-scale transportation infrastructure development projects on urban growth at large, regional- and global- levels for more realistic assessments of the impacts of these projects on the environment.

How to cite: Ahasan, R. and Güneralp, B.: An integrated, scale-invariant model to forecast global urban growth and transportation network development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-165, https://doi.org/10.5194/egusphere-egu24-165, 2024.

X3.53
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EGU24-444
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ITS1.5/NP8.6
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ECS
Pedro Henrique Dias Kovalczuk, Daniel Schertzer, and Ioulia Tchiguirinskaia

Despite efforts to obtain consistent results, the prediction of patterns in the behavior of geophysical fields still faces many uncertainties. However, these analyses are important for studying the effects of human action on the environment and the effects reflected in climate change. There is much evidence that Multifractals are capable of describing intermittent behavior and statistical data of all orders and over a wide range of scales. Therefore, this work consists of using the multifractal framework to analyze recent precipitation projection data in France, verifying the evolution of its parameters over a relatively long period of time (from 1951 to 2100) and over space, using 12 points on French territory with a resolution of 2.8º x 2.8º. For this, the Double Trace Moment technique was applied to determine the mean intermittency codimensions, the multifractality indexes and the maximum probability singularities. These results were compared to the article by J.-F. Royer et al., C. R. Geoscience 340 (2008) to verify if projections remained consistent with changes in data and economic scenarios. Despite the differences found in the range of parameter values ​​and scaling behavior, recent data also indicated an increase in intermittency over time and presented spatial behavior similar to old projections, which reinforces the expectation of an increase in precipitation extremes in the coming decades.

How to cite: Dias Kovalczuk, P. H., Schertzer, D., and Tchiguirinskaia, I.: Multifractal analysis of recent precipitation projections in the context of climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-444, https://doi.org/10.5194/egusphere-egu24-444, 2024.

X3.54
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EGU24-531
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ITS1.5/NP8.6
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ECS
|
Hai Zhou, Daniel Schertzer, and Ioulia Tchiguirinskaia

Precipitation nowcasting, referring to short-term forecasting ahead for 0 to 6 hours, is an important aspect of many urban meteorological and hydrological studies. This is due to the fact that reliable nowcasting can serve as an early warning of massive flooding and a guide for water-related risk management, making it highly significant in urban areas from a socio-economic perspective. Precipitation exhibits extreme variability over a wide range of space-time scales, so nowcasting is essentially a spatiotemporal sequence forecasting. Convolutional long short-term memory (ConvLSTM) models are frequently used to capture the spatiotemporal correlation, but they often struggle with an issue that produces blurry predictions. Therefore, generative adversarial network (GAN) architecture is employed to achieve more detailed and realistic predictions. The framework of universal multifractal (UM) with only three scale-independent parameters (α, C1, H) is also introduced in the deep learning model to characterize the extreme variability of precipitation. The developed hybrid approach using stochastic models physically based on the cascade paradigm ensures that intermittency is directly taken into account, including in the generation of uncertainty. In addition to the common evaluating metrics, like mean absolute error (MAE), root mean squared error (RMSE), critical success index (CSI), probability of detection (POD), power spectral density (PSD) and UM are also introduced to evaluate nowcasting performance in the spectrum space. This ongoing work is based on the previous research about combining recurrent neural networks with variational mode decomposition and multifractals to predict rainfall time series in Paris area.

How to cite: Zhou, H., Schertzer, D., and Tchiguirinskaia, I.: Combining Generative Adversarial Networks with Multifractals for Urban Precipitation Nowcasting , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-531, https://doi.org/10.5194/egusphere-egu24-531, 2024.

X3.55
|
EGU24-3246
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ITS1.5/NP8.6
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen Ward, Zhiwen Luo, and Sue Grimmond

We present the coupling of the Surface Urban Energy and Water Scheme (SUEWS) into the Weather Research and Forecasting (WRF) model, which includes pre-processing to capture spatial variability in surface characteristics. Fluxes and mixed layer height observations from southern UK were utilised to assess the WRF-SUEWS system over two-week periods across different seasons. Mean absolute errors are lower in residential Swindon compared to central London for turbulent sensible and latent heat fluxes (QH, QE), with increased accuracy on clear days at both locations. The model's performance exhibits clear seasonality, showing enhanced precision for QH and QE during autumn and winter due to more frequent clear days than in spring and summer. Using the coupled system, we explored how anthropogenic heat flux emissions affect boundary layer dynamics by contrasting areas with varying human activities within Greater London; higher emissions not only raise mixed layer heights but also create a warmer, drier near-surface atmosphere. Future updates will align the coupled system with the latest SUEWS version, focusing on detailed surface-layer diagnostics that can support various urban climate applications such as building energy modelling and human thermal comfort assessments.

How to cite: Sun, T., Omidvar, H., Li, Z., Zhang, N., Huang, W., Kotthaus, S., Ward, H., Luo, Z., and Grimmond, S.: WRF-SUEWS Coupled System: Development and Prospect, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3246, https://doi.org/10.5194/egusphere-egu24-3246, 2024.

X3.56
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EGU24-8492
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ITS1.5/NP8.6
Paolo Maria Guarino, Antonino Barba, Fausto Marra, Fabio Pascarella, and Mauro Roma

Naples is the third largest Italian city by size and population. Over 75% of its area is urbanized and the development of the city, often disorderly over the centuries, have occurred despite that the city is exposed to numerous geological hazards, namely: the volcanic and seismic hazard associated with a possible reactivation of Vesuvius and Phlegraean Fields volcanic centres; the seismic hazard connected with the  Apennine seismic activity; the landslide hazard due to the geologically immature landscape and the sinkhole hazard associated with the anthropic use of the subsoil. The studies undertaken and commissioned in the past by the Municipal Administration of Naples, starting from those aimed at facing the so-called Naples’ Subsoil Emergency in the early 2000s, have allowed the acquisition of a large amount of geological information relating to the subsoil, which requires a new and more modern data management structure. For this purpose, the Ufficio Servizio Difesa Idrogeologica del Territorio of the Municipality of Naples has started a project aimed at valorising and updating the enormous amount of data in its possession, through the creation of an digital platform aimed at representing the subsoil of the municipal territory. In this work the preliminary results of the project are presented. The objective of the project is to build a dataset of the geological subsoil information, structured by means of a system of coherent and organic relationships, which will concern not only the geological features (stratigraphic logs, geotechnical parameters etc.) but also the anthropic features (man-made cavities, underground services, tunnels etc.) and that will be included, in the future, within a broader digital  platform concerning the housing and underground public facilities. ISPRA, via the Department for the Geological Survey of Italy, has carried out numerous studies in the Neapolitan area in recent years, also in collaboration with the Municipality of Naples. In this context, ISPRA will provide scientific support and data in its possession for the construction of an updated geological model of the subsoil and the revision of the city’s geological map. With the accomplishment of the project, the digital platform of the subsoil of the city of Naples will become the reference geo-informatics tool of the municipal GIS; it will also have a strong participatory value open to all stakeholders, with the possibility of activating exchanges between citizens and institutions aimed at a continuously updating the acquired knowledge.

How to cite: Guarino, P. M., Barba, A., Marra, F., Pascarella, F., and Roma, M.: The subsoil of the city of Naples: accomplishment of a digital platform for its representation, management and protection, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8492, https://doi.org/10.5194/egusphere-egu24-8492, 2024.

X3.57
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EGU24-8678
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ITS1.5/NP8.6
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ECS
Ping Zhang, Hao Wu, Hao Chen, and Qiangqiang Sun

Understanding and accurate identification of long-term urban greening dynamics in China are critical for the sustainable urban management (Sustainable Development Goals, SDG11) and living environment of humans. But it was often challenging because a lack of continuous high-frequent data at high spatial resolution and over large time scales. Here, we proposed a framework for identifying detailed evolution processes and regime shifts in relation to urban greening based on characterization of urban greenness in continuous fields over space and time. We utilized annual, fractional estimates of urban green vegetation (GV) endmember time series from per-pixel Landsat composites, using a standardized spectral mixture Vegetation-Impervious surface-Soil (VIS) model in China over the past three decades. A Google Earth Engine platform-based non-linear model (logistic curves) was developed to derive the magnitude, timing and duration of urban greening at a per-pixel basis during these time series records. These parameters were combined to characterize heterogeneous pattern of urban greening throughout the entire China in 1990-2019. We found that the unmixed fractions of urban GV exhibited a generally consistent agreement with estimated fractions from high-spatial-resolution Google earth images (RMSE =11.30%), demonstrating its high suitability and reliability. Using detailed geographic process model with logistic trajectory fitting curves, our findings indicate that the ratio of the area with significant greening trends during 1990-2019 account for nearly 3.0% to the overall urbanized area in China. These greening changes are predominantly distributed in eastern coastal region and northeast Plain. In particular, the Jing-jin-ji, Ha-Chang and Middle-Southern Liaoning are the top three urban agglomerations contributing the greening for this period. Notably, Urumqi, the capital city in north-western China, has the highest ratio of the area with significant increasing GV relative to the urbanized space of the entire city, due to great achievements of urban green construction (i.e., the newly established parks or street plants), and relatively low greenness before 1990. Based on the derived change parameters, our results also reveal the economic impacts on the timing of urban greening are prevalent. For instance, the timing of turning points for urban greening in three major highly-urbanized and developed urban agglomerations, that is, the Jing-jin-ji, Yangtze River Delta, Pearl River Delta showed 2-3 years earlier than other regions. Compared to the state-of-the-art approaches, this framework has the potential to detect high-frequent urban greening process as continuous spatial and time fields with multi-dimensional thematic, thus could help support sustainable urban management practices.

How to cite: Zhang, P., Wu, H., Chen, H., and Sun, Q.: Remotely sensed monitoring of urban greening in China from 1990-2019 to support SDG11, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8678, https://doi.org/10.5194/egusphere-egu24-8678, 2024.

X3.59
|
EGU24-18514
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ITS1.5/NP8.6
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ECS
|
Pranav Pandya, Maider Llaguno-Munitxa, Martin Edwards, Emilie Lacroix, and Gabriele Manoli

As cities grapple with the multifaceted challenges posed by climate change, the Brussels Capital Region (BCR) stands at the forefront of fostering sustainable urban mobility, particularly through the development of cycling infrastructure aimed at bolstering public health and well-being. Policy initiatives implemented in BCR such as 'Good Move' and 'Ville 30' have acted as catalysts, prompting a paradigm shift towards specialized cycling lanes and facilities, thereby enhancing the safety and convenience of cycling as a viable transportation alternative. However, the growing recognition of urban heat stress and thermal discomfort as significant public health concerns, particularly for users of urban soft mobility means, highlights the pressing need for immediate and targeted interventions from urban stakeholders. While it is widely recognized that weather conditions, especially during very hot and cold days, influence cycling behavior, as do urban environmental features like the urban fabric and the presence of green infrastructure in a street, there remains a need to establish quantifiable metrics for assessing the impact of thermal comfort on cycling behavior. This study aims to address this gap, offering a nuanced examination of the cycling routes and cycling behavior of the BCR. We propose a multidisciplinary approach that integrates geospatial, psychological, and environmental sciences to examine the complex interplay between cycling path planning, urban design, micrometeorology, and thermal comfort. Data spanning from 2019 to 2022 has been sourced from multiple channels, including Brussel Mobility, Google Street View (GSV) with semantic image classification, Local Climate Zone (LCZ) maps, and meteorological stations. Geospatial data for Elsene and Etterbeek has been collected. The initial findings reveal that creating green pathways in urban areas can lessen heat stress and enhance comfort for cyclists. Moreover, cyclists are inclined to steer clear of extremely hot or cold weather conditions. Integrating urban microclimatological conditions into the framework of urban cycling design, this research aims to steer policy development towards creating urban soft mobility solutions that are more comfortable, climate-adaptive, and prioritize health considerations.

How to cite: Pandya, P., Llaguno-Munitxa, M., Edwards, M., Lacroix, E., and Manoli, G.: Modeling the Interplay between Urban Environmental Characteristics and Cyclist Route Preferences, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18514, https://doi.org/10.5194/egusphere-egu24-18514, 2024.

X3.60
|
EGU24-18749
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ITS1.5/NP8.6
Lennart Schmidt, Felix Weiske, Manfred Schütze, Phillip Grimm, Julius Polz, and Jan Bumberger

Waste water networks constitute a crucial element of urban infrastructure that are influenced by an observed increase in urban flooding events. To ensure regular network operation and minimal environmental impact, anomaly detection of urban waste water networks timeseries can serve as a real-time monitoring tool to detect a) sensor defects and b) system anomalies such as leaks or blockages. However, setting up such a monitoring system in practice can face significant challenges. These include limited amounts of labeled anomalies, heterogenous data quality, inconsistent measurement frequencies as well as instationarity of the system (sensor displacement and drop-out, changes in network layout). For the waste water network of a medium-sized German city, we set up machine learning based anomaly detection and present strategies to tackle aforementioned challenges. Our results show that autoencoder-based model architectures are valuable tools in such a context where only a minimal fraction (<0.01%) of the data is labeled. Both a well-parametrized interpolation strategy and a model architecture that is largely robust to missing values are essential prerequisites for adequate model performance. Based on our results, we derive general strategies to aid in setting up anomaly detection systems in real-world use cases.

How to cite: Schmidt, L., Weiske, F., Schütze, M., Grimm, P., Polz, J., and Bumberger, J.: Tackling practical challenges in anomaly detection for real-time monitoring of urban waste water networks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18749, https://doi.org/10.5194/egusphere-egu24-18749, 2024.

X3.61
|
EGU24-20495
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ITS1.5/NP8.6
Gabriele Leoni, Giovanni De Caterini, Marco D'Antona, Stefano De Corso, Claudia Delfini, Marco Di Leginio, Massimo Diaco, Giovanni Finocchiaro, Fiorenzo Fumanti, Luca Guerrieri, Mauro Lucarini, Ines Marinosci, Michele Munafo', Nicolo' Giovanni Tria, and Daniele Spizzichino

The concept of georesources, within the framework of the new environmental strategies of the European Union's (EU) Green Deal, has gained an expanded perspective, beyond the traditional approach linked to the mining industry. Georesources are defined as natural resources or elements of the landscape, physical space, and territory, to which economic, environmental, or social value is attributed. This definition encompasses raw materials, water resources, soil conservation, as well as intangible elements such as geoheritage, natural landscape, and ecosystem balance.

The concept of sustainability integrates with a technical principle that promotes the improvement of land conditions in natural, ecological, social, economic, and cultural terms. This perspective acknowledges that the European territory is the result of millennia of transformations by humans, with activities such as agriculture, land exploitation, and the use of natural resources that have altered environments.

The EU action plan aims to promote sustainability as a central element of economic growth, guiding capital flows towards a more sustainable economy. A priority is to define a classification of sustainability for georesources cultivation, based on technical-scientific and industrial standards, to which the sustainability of investments in the sector can be referred.

The Green Deal aims to address challenges related to climate change by promoting a new economy based on sustainable development, ecosystem protection, biodiversity conservation, and climate change mitigation. EU economic strategies are oriented towards assigning 'value' to environmental aspects, stimulating innovation and competitiveness in a dynamic market.

The concept of environmental value extends to various areas such as energy efficiency, renewable energy, sustainable agriculture, green mobility, and new technologies. This includes the creation of green jobs to ensure a fair transition to a new sustainable economy and reduced inequalities.

In the context of georesources, traditionally associated with the exploitation of non-renewable and renewable resources, an analytical approach is proposed to assess sustainability not only in the extractive field but also in the context of land planning within a broader geographic context.

For the quantitative assessment of the value of georesources in the policies outlined in the Green Deal, a parametric method based on the integrated analysis of the following themes is proposed: Geography, Hydrography, Environment, Sociology, Nature, and Economics to characterize the intrinsic value of georesources.

The use of GIS as a multidisciplinary analysis tool for integrating environmental and socio-economic data allows for a dynamic approach in identifying the intricate relationships of various themes, simplifying the representation of land status.

For each area identified through the comparison of indicators, a "georesource sustainability" index - the GIASONE index - is calculated by a weighted sum of the indices related to each theme. The use of the parametric method also allows for the comparison of different scenarios under varying environmental and socioeconomic conditions, useful for planning decisions.

How to cite: Leoni, G., De Caterini, G., D'Antona, M., De Corso, S., Delfini, C., Di Leginio, M., Diaco, M., Finocchiaro, G., Fumanti, F., Guerrieri, L., Lucarini, M., Marinosci, I., Munafo', M., Tria, N. G., and Spizzichino, D.: Giasone: a method to assess sustainability of georesources cultivation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20495, https://doi.org/10.5194/egusphere-egu24-20495, 2024.

Posters virtual: Thu, 18 Apr, 14:00–15:45 | vHall X3

Display time: Thu, 18 Apr 08:30–Thu, 18 Apr 18:00
vX3.3
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EGU24-4483
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ITS1.5/NP8.6
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ECS
|
Dachuan Shi and Jiyun Song

Urban overheating is becoming an increasingly pressing concern under the dual challenges of global warming and urban heat island effect. One effective way to mitigate urban overheating problems is to create urban cool spots via urban blue-green spaces (BGS).  To investigate the synergistic cooling effect of urban BGS, we proposed a new urban BGS coupling system by integrating a new urban water module with the state-of-the-art urban vegetation module in the framework of an urban canopy model (UCM). This coupled BGS system can represent complicated radiative exchanges between building, tree, and water, and simulate dynamic variations of shadow length, temperature, humidity, as well as energy and water fluxes within the urban street canyon. The new urban BGS model has been evaluated in typical neighborhoods with building and trees siting along rivers (also named ‘water towns’) in two Chinese megacities, i.e., Shanghai and Hong Kong. Based on this model, we investigated the synergistic cooling effect of BGS in different ‘water town’ design scenarios with different combinations of BGS characteristics (e.g., tree crown radius and height, river width, the distance between tree and river) and street canyon characteristics (e.g., geometries and orientations). Our study emphasizes the importance of optimizing 'water town' design to offer more effective cool spots for urban citizens facing escalating heat stress.

How to cite: Shi, D. and Song, J.: Investigating the synergistic cooling effect of urban blue and green spaces via an advanced urban canopy model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4483, https://doi.org/10.5194/egusphere-egu24-4483, 2024.