1,721,099 research outputs found
Observe to Predict, Predict to Prevent: Cooperation and Technology Transfer between Science and Public Administrations for Civil Protection
No full textInitial assessments of topographic variability effects on urban pluvial flood modelling accuracy
No full textPluvial flooding is a growing concern due to climate change and urbanization. Accurate flood modeling requires high-resolution topographic data, but data availability, inconsistencies, and computational constraints pose challenges. This study examines the sensitivity of pluvial flood models to digital terrain model (DEM) resolution using HEC-RAS 2D in a frequently flooded Genoa neighborhood. Simulations with 5m, 1m, and 0.5m resolutions assess flood extent, depth, and computational efficiency. Results highlight the importance of high-resolution data for accurate predictions. The research informs urban flood risk management by balancing data granularity with resource efficiency, advocating for microtopographic integration and DEM-DSM comparisons
Scenes and Scenarios: Managing natural disasters by using satellite images to their full potential
No full textThe Impact of Input Data on the Modelling of Pluvial Flooding
No full textThis poster summarizes the last two years of doctoral research, with a particular focus on the most recent results. Climate change has intensified the impacts on environmental systems and increased the frequency of extreme events, making them more difficult to predict and manage. Pluvial flooding in urban areas has become a major concern, driven both by climate change and rapid urbanization. To address this issue, a variety of modeling tools have been developed, including one-dimensional (1D) and two-dimensional (2D) hydrodynamic methods, as well as integrated hydrological-hydraulic approaches that couple sewer and surface flows. Nevertheless, challenges remain, particularly regarding the quality of input data such as topographic resolution and its integration with urban drainage networks. The research presented here advances this discussion by examining these challenges and presenting new findings from the most recent stage of the doctoral work
Cross fertilisation between traditional regionalization of rainfall extremes and remotely sensed data
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Sampling strategies and assimilation of ground temperature for the estimation of surface energy balance components
No full textAssessing the Sensitivity of Pluvial Flood Modelling to the Topographic Description of Urban Areas
No full textThe rising frequency of pluvial flooding, driven by climate change and rapid urbanization, has increased the vulnerability of urban communities to flood-related hazards. Urban expansion intensifies this issue by reducing soil permeability and altering natural drainage patterns, resulting in more severe flood events that impact larger populations. Consequently, pluvial flooding has become a pressing concern in urban flood risk management.
While advanced models have been developed to simulate pluvial flood scenarios, persistent challenges related to input data limit their effectiveness. These challenges fall into four main categories:
Data Availability and Integration: Urban flooding involves interconnected systems that require diverse datasets, including topography, land use, and hydraulic characteristics. Accessing accurate and complete data on urban drainage systems is often difficult. Moreover, integrating data from multiple sources and ensuring compatibility across formats adds complexity
Data Acquisition and Homogeneity: Continuous data collection using consistent instrumentation is essential. Disruptions or inconsistencies in acquisition can compromise model accuracy and decision-making. Addressing this requires robust maintenance and sensor networks
Data Quality, Accuracy, and Uncertainty: Data from various platforms may contain random errors, biases, and uncertainties. Rigorous validation and calibration are necessary to enhance the reliability of simulation outputs and the effectiveness of flood mitigation strategies
Spatial and Temporal Resolution: Urban flood dynamics depend on variables such as rainfall intensity, land surface properties, and drainage network behavior. However, acquiring data with sufficient resolution remains challenging, as conventional datasets often lack the granularity needed for accurate modelling
These limitations affect a range of input data, including rainfall, sewer systems, and terrain descriptions.
This study focuses on the influence of spatial resolution and detail in Digital Terrain Models (DTMs) and Digital Surface Models (DSMs) on the performance of pluvial flood simulations. Using geospatial data processing and 2D flood modelling, the research assesses how different resolutions impact simulation outcomes. The subsurface drainage network is excluded, as the sewer data from the Municipality of Genoa and the local water utility are outdated, shifting the focus to terrain representation
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