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.

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.

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-21^st 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.

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.

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.

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.

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.

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.

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.

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.

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

S_q(Δt)=⟨ΙT_λ - T_λ/2,2Ι^q⟩

Where the scale ratio λ∝1/ΙΔtΙ; 2^m/2^m=1≤λ≤Λ=2^m/2⁰ and ΙΔtΙ is the time lag, whereas 2^m is the largest possible scale out of the scales analyzed that can be represented as a power of 2. While T_λ is the temperature at scale ratio λ or scale l, T_λ/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  T_λ/2 (upscaled temperature) is repeated twice consecutively. It should be noted that T_λ/2,2 is not the same as T_λ 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.