More than half of the world’s population now resides in cities and the amount of urban population is expected to further increase during the coming decades. Urbanization and the associated changes in land use/land cover can have a notable impact on the climate at local and regional scales. Specifically, several studies recently concluded that urbanization can modify the temporal and spatial properties of precipitation. On top of that, global warming is expected to enhance the magnitude and frequency of short-duration heavy precipitation, with consequential effects on the severity and frequency of urban pluvial flood events. Therefore, improving our understanding of the separate and combined effects of urbanization and climate change on short-duration precipitation is imperative for flood risk assessments and planning of future cities. To this end, we investigate the impact of climate change and urbanization on the space-time properties of precipitation by conducting current and future simulation scenarios over cities with different climates using the Weather Research and Forecasting (WRF) physically-based climate model. The results of this study elucidate the important role of urban land cover on the spatial stucture of precipitation under a changing climate.

How to cite: Koukoula, M., Torelló-Sentelles, H., and Peleg, N.: Impact of urbanization and climate change on spatial patterns of precipitation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1239, https://doi.org/10.5194/egusphere-egu23-1239, 2023.

Extreme rainfall is a critical “agent” driving flash floods in urban areas. In rainfall frequency analysis (RFA), however, storms are usually assumed to be uniform in space and fixed in time. Spatially and temporally uniform design storms and area reduction factors are oftentimes used in conjunction with RFA results in engineering practice for infrastructure design and planning. The consequences of such assumptions are poorly understood. This study examines how spatiotemporal rainfall heterogeneity impacts RFA, using a newly-introduced bivariate framework consisting of copula theory and stochastic storm transposition (SST). A large number of regionally-extreme storms with specific features—rainfall depth, duration, intensity, and level of intra-storm spatial organization—were collected. Rainfall intensity-duration-frequency (IDF) estimates exhibiting these bivariate features were then generated by synthesizing long records of rainfall via SST. The results show that dependencies exist among spatiotemporal storm characteristics. Bivariate frequency results exhibit smaller uncertainties but more complex physical meanings that the results from conventional methods. In particular, the highly spatially-organized storms play a leading role in frequency estimates.

How to cite: Zhuang, Q., Liu, S., Zhou, Z., and Wright, D.: A bivariate rainfall frequency analysis framework in urban areas by coupling copula theory and stochastic storm transposition, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2704, https://doi.org/10.5194/egusphere-egu23-2704, 2023.

Atmospheric limited-area models are superb tools built by atmospheric scientists, and can also be used by scientists from other disciplines. As hydrologists interested in urban rainfall hazard, we want to study possible changes in local-scale precipitation intensities and patterns under urban growth scenarios.

Unfortunately, the parameterization of ground properties appears scattered in many datasets. These differ by their spatial resolution, computational type (exclusive categories expressed as integers, categories expressed as percentages in the patchwork/tile approach, continuous parameters as real numbers, month-dependent real numbers), and of course by their semantic (land use/land cover, radiative properties such as LAI according to one or another sensor, orography, soil type according to one or another research institute).

From the above, the basic way to deal with expected land use changes in impact simulation changes would involve reading the scientific literature exhaustively - literally: to the point of exhaustion - to establish which parameter must be changed, and to hope that no inconsistencies will be introduced in the individual values or in their interdependence.

We propose another, easier, and above all safer strategy. The first step is to recognize the "ground properties" are not a list of individual parameters, but a compound object where many parameters are related in a hierarchy of aspects  : parameters related to land use, parameters related to orography, etc. The determination of this hierarchy is quite easy using multivariate statistics, individuals being locations sampled in the domain of interest and data being the parameters values at these locations. This approach helps to establish the list of parameters connected to the intended change.

Armed with this list, a "geographic cut-and-paste" strategy can be safely adopted to express intended land use change: the relevant parameter values of a representative (donor) location will be used at the target (modified) location, while leaving all other local parameters untouched.

We illustrate this approach with the specific case of prescribing variable levels of urban development for the city of Querétaro, Mexico, in the technical context of using WRF's UEMS distribution (89 datasets distributed as 25633 files distributed in 219 directories).

How to cite: Leblois, E., Salas Aguilar, S.-P., Anquetin, S., and Gonzalez Sosa, E.: How to consistently adapt soil parameters to express urban growth in physically based precipitation modeling ?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5619, https://doi.org/10.5194/egusphere-egu23-5619, 2023.

Urban flooding is a critical disaster resulting in the malfunction of the city and the loss of properties. Furthermore, urban flood prediction often requires a combined modeling process due to the complicated drainage system. In this study, the water levels and relevant inundation areas were estimated by the radar rainfall estimations and the SWMM model. Regarding the radar rainfall estimation, the joint relationship between reflectivity, phase (i.e, Z_H, Z_DR, K_DP) of dual-polarization radar and ground rainfalls was explored through the copula function. The copula is a function that effectively joins marginal distribution functions to form a multivariate distribution function. Finally, the water level and inundation areas of Gangnam district were estimated using hourly mean areal precipitation (MAP) through radar rainfall estimations and the coupled 1D/2D urban hydrological model. The coupled model consists of a 1D conduit network model based SWMM (i.e., the RUNOFF and EXTRAN modules) and a 2D overland flow model, which links the surcharging flows at the manholes of the 1D sewer network model.

Acknowledgement

This work was supported by Korea Environment Industry & Technology Institute (KEITI) through the Aquatic Ecosystem Conservation Research Program, funded by the Korea Ministry of Environment(MOE). (No. 2021003030001)

How to cite: Kim, H.-J., Jung, M.-K., Cho, H., and Kwon, H.-H.: Estimation of mean areal precipitation based on dual-polarization radar using copula function and Its use for urban drainage modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6299, https://doi.org/10.5194/egusphere-egu23-6299, 2023.

The accurate estimation of precipitation is still one of the major challenges in hydrology. One fairly new approach to improve rainfall quantification is the use of so-called opportunistic sensors (OS), i.e. sensors that were not designed to provide high-quality rainfall data at a larger scale, but can be used for that purpose. One type of OS are personal weather stations (PWS) that are owned by private users. They typically comprise one or a set of low-cost devices that record meteorological variables such as air temperature and rainfall. The number of PWS has increased over the past years and the high number of rain gauges offers potential to improve rainfall estimates. 
OS have also raised scientific interest in the recent years. In October 2021, the EU COST Action CA 20136 “Opportunistic Precipitation Sensing Network” (OPENSENSE) was launched with the aim to bring together researchers in the field of OS and to build a global opportunistic sensing community. Furthermore, EUMETNET recently released a dataset containing data of PWS in Europe for 2020 from MetOffice WOW and Netatmo to support the development of PWS quality control tools.
Compared to traditional rain gauge networks, PWS provide data in high temporal and spatial resolution but with low quality, since they are often not installed and maintained according to professional standards. Therefore, these data require a thorough quality control (QC) and filtering before they can be used for applications such as areal precipitation estimates. Two different QC algorithms have been published by de Vos et al. (2019) and Bárdossy et al. (2021). These are available in the OPENSENSE GitHub environment (https://github.com/OpenSenseAction). 
In this study, we apply these two aforementioned QC algorithms on four 24-hour periods, containing convective or homogeneous rain events, from the same PWS dataset for the Amsterdam Metropolitan Area, and validate the outcome using a gauge-adjusted radar product as reference. The characteristics and relative performance of the QC algorithms are presented, thus providing aid for prospective users to decide which of these QC algorithms is best suited for their purpose.

References:
Bárdossy, A., Seidel, J., & El Hachem, A. (2021). The use of personal weather station observations to improve precipitation estimation and interpolation. Hydrology and Earth System Sciences, 25(2), 583-601
de Vos, L. W., Leijnse, H., Overeem, A., & Uijlenhoet, R. (2019). Quality Control for Crowdsourced Personal Weather Stations to Enable Operational Rainfall Monitoring. Geophysical Research Letters, 46(15), 8820-8829.

How to cite: de Vos, L., El Hachem, A., Seidel, J., and Bárdossy, A.: Comparitive performance of two quality control algorithms for personal weather station rainfall data in Amsterdam Metropolitan Area, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9127, https://doi.org/10.5194/egusphere-egu23-9127, 2023.

Urban pluvial flooding is a modern, growing global disaster, particularly in developing countries with inadequate infrastructure. It remains a challenge to accurately model the runoff behavior in urban areas with a complex topography and to quantify the impact of spatial urban patterns on changing urban rainfall-runoff response. The question to be addressed is how varying the urban spatial configurations can quantitatively influence the overland flow response in relation to the spatiotemporal hydrodynamic variables such as water depth, velocity, and outflow discharge. We use a 2D shallow water model to indicate the influence of changing spatial urban factors (such as the orientation of streets and buildings, and adding sidewalks) in small idealized (synthetic) urban catchments during a single pluvial flood event. The domain layout extends over a size of 267.5m*267.5m with a 3% longitude slope. We differentiate mainly between two street networks: i) the two-way main street with of 14-m width with sidewalks, and ii) side streets of 10m width (Fig.1). We then define novel spatially integrated indicators over the domain at the steady state to analyze quantitatively runoff variables in correlation with the urban features (Fig.1). Additionally, local hotspot maps were created to assess the flood-risk thresholds, such as human stability and failure of buildings. Hotspots are defined as the places with the highest flow velocity magnitudes and water depths (> 90%). The results of the modeling showed that, with respect to the flow velocities in small-scale urban catchments, the main street layout is the dominant urban factor, followed by the side street widths, which were decisively determined by the geometry of the sidewalks. The comparison with real flood risk thresholds shows that the lower part of the main road is the most sensitive to flood risk in the domain with a high-risk hazard for human stability. However, the riskiest case is not corresponding to the fastest hydrograph response. Varying the spatial urban configurations, especially the rotation of the main roads, changes the flood risk thresholds and delays runoff. On the other hand, spatially integrated indicators of the flow variables in the domain are showing low sensitivity to the spatial urban features. Our findings offer a new important perspective on the development of urban flood risk assessment, especially for rapidly urbanizing cities, and provide a better understanding of the spatiotemporal rainfall-runoff generation in a small urban catchment considering the spatial layout of the urban structures.

Fig.1 Overview of the modelling approach and evaluation of the runoff data

How to cite: Shlewet, M., Caviedes-Voullième, D., Kästner, K., and Hinz, C.: Effects of urban structures on spatial and temporal flood distribution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9498, https://doi.org/10.5194/egusphere-egu23-9498, 2023.

Rainfall affects urban traffic flow. In rapidly urbanizing megacities in Asian countries, heavy rainfall causes roads to flood and traffic congestion to worsen due to weak drainage systems. This study statistically quantified the impact of rainfall on urban traffic speed in Bangkok, using probe vehicle data and rainfall data from 2018 to 2020. Traffic speeds are calculated based on the travel distance and travel time between districts, taking into account the detouring of flooded sections.

Results show that both the rainfall intensity at the time of driving as well as the amount of previous rainfall affect the traffic speed reduction. In particular, the impact of previous rainfall increases at times and areas where traffic is concentrated, such as during the weekday morning and evening peak hours and travel to/from the city center. The results of the analysis based on regional characteristics show that low-lying districts are more affected by the previous rainfall because the flood water tends to stay on the road surface, while districts with high vegetation index (NDVI) are less affected by the previous rainfall. In addition, the impact of previous rainfall increases with population density and the ratio of narrow streets. In Bangkok, urbanization has progressed while leaving behind a city block configuration with many narrow streets, called Soi, connecting to arterial roads. This result means that limited road space is prone to flooding, and once flooding occurs, combined with the concentration of traffic on adjacent roads, traffic congestion becomes more severe.

The results of this study showed the impact of rainfall on urban traffic in different areas and at different times of the day in the target site. Integrated improvements to the transport and drainage systems could have a greater benefit.

How to cite: Takano, T., Nakamura, S., Morita, H., Piamsa-nga, N., and Vichiensan, V.: Sensitivity Analysis of the Effect of Rainfall on Road Traffic Speed in Bangkok, Thailand, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10806, https://doi.org/10.5194/egusphere-egu23-10806, 2023.

The risk posed globally by surface water flooding to people and properties is growing due to rapid urbanisation and the intensification of rainfall due to climate change. Whilst tools to model urban flood risk have also been rapidly developing, there remains a knowledge gap around the sensitivity of urban hydraulic modelling methods to the temporal structure of rainfall. In the UK, the industry standard process considers rainfall events to always be symmetrical, and with a singular peak in intensity. Previous studies of observed UK extreme rainfall events suggests that loading of rainfall towards the start or end of events is in fact more common. In this study, the sensitivity of an urban catchment in the north of England is tested using fifteen realistic rainfall profiles derived from these observed extremes. Additionally, idealized systematic variations are made to the industry standard profile to shift the single peak towards the start or end of the event, and to split the rainfall volume over multiple peaks. We demonstrate that the positioning of the peak, as well as its magnitude, influences the severity, timing and nature of the associated flooding. The profile with the peak nearest the end of the event is associated with an 18% larger flooded area than the early peaking profile which is associated with the smallest flooded area.

How to cite: Asher, M., Trigg, M., Birch, C., Böing, S., and Villalobos-Herrera, R.: The sensitivity of urban surface water flood modelling to the temporal structure of rainfall, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12555, https://doi.org/10.5194/egusphere-egu23-12555, 2023.

Flood damage is not only caused by river floods. In particular, highly sealed urban areas are repeatedly affected by flooding as a result of convective heavy precipitation, regardless of their proximity to surface waters. Floods are often very localized due to the small spatial extent of the heavy precipitation cells. However, the spatial and temporal prediction of these precipitation cells is subject to great uncertainty due to the multitude of meteorological influences. In many cases, only the affected large areas in which convective heavy precipitation events can occur are known. The spontaneous implementation of safety measures by municipalities and residents is therefore rarely effective, which has already led to high damages in the past.

Hydrodynamic numerical (HN) models for simulating runoff, water levels and water velocity for heavy precipitation events require a high spatial and temporal resolution. Therefore, computational costs for pure HN models are high, so that a novel coupling approach with a hydrological rainfall-runoff (RR) model, which computes comparatively fast, is suggested. To represent the flooding events resulting from convective heavy precipitation events in highly heterogeneous inner-city areas, surface runoff can be simulated using RR models. Overloads of the existing drainage system are also identified. Averaging of, for example, sealing values, as is the case with conventional RR modelling, is dispensed with using high-resolution area information. A particularly detailed analysis of the study area at street level is thus possible as long as the flow directions are unambiguous. Subsequent coupling of the RR-simulated runoff to an HN model represents flooding of the area away from the fixed RR model runoff pathways. Due to the model concept developed for our study, runoff is represented with high temporal and spatial resolution and very short response times in the RR model. In the case of identified flooding of a road section, the flooding is then followed up with a non-uniform and transient HN model for the respective area. The combined approach reduces the model area of the HN model, which simulates dynamic flooding into the area, to the flood critical areas. In addition, this approach increases the accuracy of hindcasts compared to observations and delivers the opportunity to assess weak spots in the drainage system of complex urban areas. Municipalities may use the knowledge to create adapted and adequate risk management approaches for heavy precipitation events and make structural adjustments to reduce the now known risks.

How to cite: Sauer, C., Nagrelli, S., and Fröhle, P.: High-resolution modelling of heavy precipitation runoff behavior in urban areas using a coupled rainfall-runoff and hydrodynamic modelling approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14225, https://doi.org/10.5194/egusphere-egu23-14225, 2023.