Can urban pluvial flooding be predicted by open spatial data and weather data?

2016 ◽  
Vol 85 ◽  
pp. 156-171 ◽  
Author(s):  
S. Gaitan ◽  
N.C. van de Giesen ◽  
J.A.E. ten Veldhuis
Keyword(s):  
Spatial Data ◽  
Weather Data ◽  
Pluvial Flooding ◽  
Urban Pluvial Flooding

scholarly journals Towards identification of critical rainfall thresholds for urban pluvial flooding prediction based on crowdsourced flood observations

2018 ◽  
Author(s):  
Christian Bouwens ◽  
Marie-Claire ten Veldhuis ◽  
Marc Schleiss ◽  
Xin Tian ◽  
Jerôme Schepers
Keyword(s):  
Spatial Data ◽  
Strong Dependence ◽  
Management Strategies ◽  
Drainage System ◽  
Threshold Value ◽  
Early Warning Systems ◽  
Threshold Values ◽  
Urban Flood ◽  
Pluvial Flooding ◽  
Urban Pluvial Flooding

Abstract. Urban drainage systems are challenged by both urbanization and climate change, intensifying urban pluvial flooding impacts. Urban pluvial flooding impacts can be reduced by improving infrastructure and operational urban flood management strategies. This study investigated the relation between heavy rainfall and urban pluvial flooding in Rotterdam with the aim to identify parameters and thresholds that can be used as predictors of urban pluvial flooding. The focus of the investigation was on an area of 16 km2. Datasets for this research included historical crowdsourced flooding reports, overflow pumping volumes, open spatial data and rainfall data at different temporal and spatial resolutions. Threshold values, (which can be used as part of early warning systems), were derived from historical flooding data and rainfall depths over sub daily durations. Threshold values of rainfall depth were found to be 6 mm (±3 mm) in 15 min and 11 mm (±6 mm) in 60 min. Surprisingly, the derived thresholds are only approximately half of the theoretical drainage system design capacity. Furthermore, a threshold value of 70 % (±4 %) imperviousness was found above which flooding incidents significantly increase. Results also suggested a strong dependence on spatial aggregation scale, as it highly influences correlation coefficients and parameter density values. Elevation differences did not appear to contribute to urban pluvial flooding, based on a flow path analysis for the study area. Finally, we showed that antecedent rainfall does not explain additional variance in reports, meaning it is not an influential urban pluvial flooding predictor, at least not on a daily temporal resolution.

Influence of urban forms on surface flow in urban pluvial flooding

2020 ◽  
Vol 582 ◽  
pp. 124493 ◽  
Author(s):  
Martin Bruwier ◽  
Claire Maravat ◽  
Ahmed Mustafa ◽  
Jacques Teller ◽  
Michel Pirotton ◽  
...  
Keyword(s):  
Surface Flow ◽  
Urban Forms ◽  
Pluvial Flooding ◽  
Urban Pluvial Flooding

scholarly journals A Vulnerability Assessment of Urban Emergency in Schools of Shanghai

2019 ◽  
Vol 11 (2) ◽  
pp. 349 ◽  
Author(s):  
Jie Yin ◽  
Yameng Jing ◽  
Dapeng Yu ◽  
Mingwu Ye ◽  
Yuhan Yang ◽  
...  
Keyword(s):  
Emergency Services ◽  
Response Times ◽  
Flood Hazard ◽  
Hot Spot ◽  
Hazard Analysis ◽  
Rescue Service ◽  
Traffic Conditions ◽  
Pluvial Flooding ◽  
Urban Pluvial Flooding ◽  
The City

Schools and students are particularly vulnerable to natural hazards, especially pluvial flooding in cities. This paper presents a scenario-based study that assesses the school vulnerability of emergency services (i.e., Emergency Medical Service and Fire & Rescue Service) to urban pluvial flooding in the city center of Shanghai, China through the combination of flood hazard analysis and GIS-based accessibility mapping. Emergency coverages and response times in various traffic conditions are quantified to generate school vulnerability under normal no-flood and 100-y pluvial flood scenarios. The findings indicate that severe pluvial flooding could lead to proportionate and linear impacts on emergency response provision to schools in the city. Only 11% of all the schools is predicted to be completely unreachable (very high vulnerability) during flood emergency but the majority of the schools would experience significant delay in the travel times of emergency responses. In this case, appropriate adaptations need to be particularly targeted for specific hot-spot areas (e.g., new urbanized zones) and crunch times (e.g., rush hours).

Where's the fire? Quantifying uncertainty in a wildfire threat model

2004 ◽  
Vol 13 (1) ◽  
pp. 17 ◽  
Author(s):  
S. D. Jones ◽  
M. F. Garvey ◽  
G. J. Hunter
Keyword(s):  
Spatial Data ◽  
Uncertainty Assessment ◽  
Weather Data ◽  
Fuel Load ◽  
Wildfire Management ◽  
Minimal Impact ◽  
Threat Model ◽  
Digital Elevation ◽  
Input Dataset ◽  
Land Cover Maps

Models of wildfire threat are often used in the management of fire-prone areas for purposes such as planning fire education campaigns and the deployment of fire prevention and suppression resources. While the use of spatial or geographic data is common to all wildfire threat models, the key question arises: Is the accuracy of the spatial data used in wildfire threat models sufficient for the intended decision-making purpose? To help answer this question, a quantitative uncertainty assessment technique was applied to a wildfire threat model used by the Country Fire Authority in Victoria, Australia. The technique simulates known or estimated spatial data error by modifying data values to represent the range of all probable errors present in the input dataset. The wildfire threat model is then run multiple times using these modified ‘error’ layers in order to simulate and observe the effect these errors have on the model outputs. For the model concerned, the results suggest that errors in digital elevation surfaces have only minimal impact upon the outputs, resulting in relatively stable wildfire management decisions. On the other hand inaccuracies in land cover maps (with implied differences in fuel load estimations) result in larger changes in the model outputs, whereas changes in fire weather data can result in highly unstable outputs. Knowledge of these effects can facilitate better wildfire management since any improvements that are to be made to the model’s accuracy can be focussed directly upon the problem datasets.

scholarly journals Visualizing 3D Terrain, Geo-Spatial Data, and Uncertainty

2016 ◽  
Author(s):  
Steve Dübel ◽  
Martin Röhlig ◽  
Christian Tominski ◽  
Heidrun Schumann
Keyword(s):  
Spatial Data ◽  
Information Needs ◽  
Three Dimensional ◽  
Weather Data ◽  
Use Case ◽  
3D Terrain ◽  
Visualization Strategy ◽  
Design Options ◽  
High Degree ◽  
Uncertainty Information

Visualizing geo-spatial data embedded into a three-dimensional terrain is challenging. The problem becomes even more complex when uncertainty information needs to be presented as well. This paper addresses the question of how to visually communicate all three aspects: the 3D terrain, the geo-spatial data, and the data-associated uncertainty. We argue that visualizing all aspects with a high degree of detail will likely exceed the visual budget. Therefore, we propose a visualization strategy based on prioritizing a selected aspect and presenting the remaining two with less detail. We discuss various design options that allow us to obtain differently prioritized visual representations. Our approach has been implemented as a tool for rapid visualization prototyping in the context of avionics applications. Practical solutions are described for a use case related to the visualization of 3D terrain and uncertain weather data.

Early warning system for detection of urban pluvial flooding hazard levels in an ungauged basin

2018 ◽  
Vol 92 (2) ◽  
pp. 1237-1265 ◽  
Author(s):  
Melisa Acosta-Coll ◽  
Francisco Ballester-Merelo ◽  
Marcos Martínez-Peiró
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Ungauged Basin ◽  
Flooding Hazard ◽  
Pluvial Flooding ◽  
Urban Pluvial Flooding ◽  
Hazard Levels

scholarly journals A methodical framework for analysing the cause of urban pluvial flooding in a hillside settlement

2019 ◽  
Vol 79 (9) ◽  
pp. 1798-1807
Author(s):  
Lena Simperler ◽  
Florian Kretschmer ◽  
Thomas Ertl
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Evaluation Criteria ◽  
Sewer System ◽  
Systematic Analysis ◽  
Surface Drainage ◽  
Methodical Approach ◽  
Pluvial Flooding ◽  
Urban And Rural Areas ◽  
Urban Pluvial Flooding

Abstract Pluvial flood risk is increasing in urban and rural areas due to changes in precipitation patterns and urbanization. Pluvial flooding is often associated with insufficient capacities of the sewer system or low surface drainage efficiency of urban areas. In hilly areas, hillside runoff additionally affects the risk of pluvial flooding. This article introduces a methodical approach and related evaluation criteria for a systematic analysis of potential causes of urban pluvial flooding. In the presented case study, the cause of pluvial flooding at two selected sites in a hillside settlement is investigated based on a coupled 1D/2D model of the whole hydrological catchment. The results show that even though bottlenecks in the sewer system are important, the effect of low surface drainage efficiency and hillside runoff greatly influence pluvial flooding. The knowledge of different causes of flooding can be further used for selecting and positioning appropriate adaption measures. The presented approach proved its practicability and can thus serve as a guidance and template for other applications to gain better understanding and knowledge of local specific pluvial flooding events.

scholarly journals Agro-Climatic Data by County: A Spatially and Temporally Consistent U.S. Dataset for Agricultural Yields, Weather and Soils

Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 66
Author(s):  
Seong Do Yun ◽  
Benjamin M. Gramig
Keyword(s):  
Spatial Data ◽  
Crop Yields ◽  
Original Data ◽  
Data Sources ◽  
Weather Data ◽  
Climatic Data ◽  
Soil Characteristic ◽  
Growing Seasons ◽  
Aggregation And Disaggregation ◽  
Agricultural Yields

Agro-climatic data by county (ACDC) is designed to provide the major agro-climatic variables from publicly available spatial data sources to diverse end-users. ACDC provides USDA NASS annual (1981–2015) crop yields for corn, soybeans, upland cotton and winter wheat by county. Customizable growing degree days for 1 °C intervals between −60 °C and +60 °C, and total precipitation for two different crop growing seasons from the PRISM weather data are included. Soil characteristic data from USDA-NRCS gSSURGO are also provided for each county in the 48 contiguous US states. All weather and soil data are processed to include only data for land being used for non-forestry agricultural uses based on the USGS NLCD land cover/land use data. This paper explains the numerical and geo-computational methods and data generating processes employed to create ACDC from the original data sources. Essential considerations for data management and use are discussed, including the use of the agricultural mask, spatial aggregation and disaggregation, and the computational requirements for working with the raw data sources.

scholarly journals A Methodological Approach to Municipal Pluvial Flood Risk Assessment Based on a Small City Case Study

2020 ◽  
Vol 12 (24) ◽  
pp. 10487
Author(s):  
Felix Julian Othmer ◽  
Dennis Becker ◽  
Laura Miriam Schulte ◽  
Stefan Greiving
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Urban Areas ◽  
Heavy Rainfall ◽  
Methodological Approach ◽  
Flood Risk Assessment ◽  
Methodical Approach ◽  
Pluvial Flooding ◽  
Research Procedure ◽  
Urban Pluvial Flooding

Urban flooding caused by heavy rainfall confronts cities worldwide with new challenges. Urban flash floods lead to considerable dangers and risks. In cities and urban areas, the vulnerability to pluvial flooding is particularly high. In order to be able to respond to heavy rainfall events with adaptation strategies and measures in the course of urban development, the spatial hazards, vulnerabilities and risks must first be determined and evaluated. This article shows a new, universally applicable methodical approach of a municipal pluvial flood risk assessment for small and medium-sized cities. We follow the common approaches to risk and vulnerability analyses and take into account current research approaches to heavy rainfall and urban pluvial flooding. Based on the intersection of the hazard with the vulnerability, the pluvial flood risk is determined. The aim of the present pluvial flood risk assessment was to identify particularly affected areas in the event of heavy rainfall in the small German city of Olfen. The research procedure and the results have been coordinated with the city’s administration within the framework of a real laboratory. In the course of the science–policy cooperation, it was ensured that the results could be applied appropriately in urban developments.

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