Displays

HS4.1

Heavy precipitation events in small and medium size catchments can trigger flash floods, which are characterized by very short response times and high specific peak discharges, and often occur in ungauged basins. Under appropriate geomorphological conditions, such rainstorms also cause debris flows or shallow landslides mobilizing large amounts of unconsolidated material. Although significant progress has been made in the management of these different hazards and related risks, they remain poorly understood and their predictability is affected by large uncertainties, due to the fast evolution of triggering rainfall events, the lack of appropriate observations, the high variabilities and non-linearities in the physical processes, and the high variability and complexity of societal vulnerability.

This session aims to illustrate current advances in monitoring, understanding, modelling, and forecasting flash floods and associated geomorphic processes, and documenting and anticipating the societal impacts and social responses.

Contributions on the following scientific themes are more specifically expected:
- Development of new measurement techniques adapted to flash floods monitoring (including remote sensing data, weather radar, and lightning), and quantification of the associated uncertainties,
- Identification of processes leading to flash flood events and/or rainfall-induced geomorphic hazards from data analysis and/or modelling, and of their characteristic space-time scales
- Possible evolutions in hazard characteristics and frequency related to climate change.
- Development of short-range (0-6h) rainfall forecasting techniques adapted to heavy precipitation events, and representation of associated uncertainties
- Development of hydro-meteorological forecasting chains for predicting flash floods and/or rainfall-induced geomorphic hazards in gauged and ungauged basins
- Development of inundation mapping approaches specifically designed for an integration in flash floods forecasting chains.
- Use of new criteria such as specific “hydrological signatures” for model and forecast evaluation
- Observation, understanding and prediction of the societal vulnerability and social responses to flash floods and/or associated hydro-geomorphic hazards.

Share:
Co-organized by NH1
Convener: Olivier Payrastre | Co-conveners: Jonathan Gourley, Marcel Hürlimann, Pierre Javelle, Massimiliano Zappa
Displays
| Wed, 06 May, 16:15–18:00 (CEST)

Files for download

Download all presentations (104MB)

Chat time: Wednesday, 6 May 2020, 16:15–18:00

Chairperson: Olivier Payrastre
D112 |
EGU2020-20206
| Highlight
Marc Berenguer, Shinju Park, and Daniel Sempere-Torres

Radar rainfall estimates and nowcasts have been used in Catalonia (NE Spain) for real-time flash flood hazard nowcasting based on the basin-aggregated rainfall for several years. This approach has been further developed within the European Projects ERICHA (www.ericha.eu) and ANYWHERE (www.anywhere-h2020.eu), where it has been demonstrated to monitor flash floods in real time in several locations and at different spatial scales (from regional to Continental coverage).

The work summarizes the main results of the recent projects, analysing the performance of the flash flood nowcasting system. The results obtained on recent events  show the main advantages and some of the limitations of the system.

D113 |
EGU2020-9682
Nicola Surian, Andrea Brenna, Marco Borga, Marco Cavalli, Francesco Comiti, Lorenzo Marchi, and Mattia Zaramella

Although channel dynamics (i.e. channel lateral mobility, intense sediment and wood transport) are commonly dominant processes in mountain streams during high-magnitude floods, hazard assessment still mostly focuses on water flooding only. Therefore, there is a need to include river geomorphological hazard to produce reliable flood hazard mapping and define effective mitigation measures. This work deals with the “Vaia” storm that occurred in the Eastern Alps (Italy) on 27-30 October 2018. Our aims are (i) to improve the understanding of geomorphic processes in response to large floods and (ii) to improve the prediction capability of the reaches more prone to undergo intense channel dynamics (e.g. channel widening, in-channel sedimentation) during such events.

An integrated approach was deployed to study the flood event in the Cordevole river catchment (876 km2). The approach includes (i) analysis of geomorphological processes, by comparing remote sensing data acquired before and after floods and field survey (e.g. recognition of different flow types); (ii) hydrological and hydraulic analysis (collection of rainfall and streamflow data, estimation of peak discharges at multiple sites in ungauged streams, and model-based consistency check of rainfall and discharge data); (iii) landslide mapping and analysis of sediment delivery to the channel network.

Intense sediment and wood transport took place. A wide range of transport processes (i.e. debris, hyperconcentrated and water flows) was recognized in the channel network and notable channel aggradation occurred at specific location (e.g. in channelized reaches). Channel widening was the most relevant geomorphic response along the fluvial network. Width ratio (i.e. channel width after / channel width before the flood) reached up to 2.1 and 4.4, respectively in the Cordevole and in its tributaries. Locally, the valley slopes were eroded (e.g. slope retreat up to 14 m). This means that the lateral channel dynamics affected not only large portions of the valley floor (e.g. forested floodplain) but also the valley slopes, especially if made of Quaternary deposits or soft bedrock.

These results have several implications in terms of flood hazard assessment in mountain streams. Since channel widening is a major process (streams may take up the whole floodplain and, locally, erode the valley slopes), so-called “river morphodynamic corridors” need to be defined and integrated into flood hazard maps. During high-magnitude floods the sediment mobilization may take place through mechanisms (e.g. hyperconcentrated flows) that can be different from those expected for ordinary water floods. Since major channel changes commonly occur during large floods, their prediction is needed and should accompany flood hydraulic modelling to obtain reliable flood event scenarios.

D114 |
EGU2020-18172
Markus Weiler, Hannes Leistert, and Andreas Steinbrich

Local heavy precipitation regularly causes great damage resulting from flash floods in small catchments. Appropriate discharge records are usually unavailable to derive an extreme value statistics and regionalization approaches predicting peak discharge from discharge records of larger basins cannot consider the small-scale effects and local processes. In addition, forecasting flash floods from rainfall forecast requires to identify the event conditions under which a catchment is most prone to trigger flash floods. Therefore, factors influencing runoff formation and concentration need to be identified based on catchment characteristics in order to predict flood hydrographs, geomorphic processes and flood inundation.

We have developed a framework depending on the joint probability of soil moisture and rainfall and used the distributed, processed-based rainfall-runoff model RoGeR to predict the spatial explicit probability of soil moisture and linking this to overland-flow and subsurface flow generation assuming different scenarios of soil moisture and rainfall characteristics. Selected combinations result in a joint probability with a specified return period (e.g. 100 year), but are based on different probabilities for rainfall amount, duration and initial soil moisture. From this, the combination of a precipitation event and initial soil moisture condition can be determined which generates the largest runoff generation. In addition, we found, that accounting for the spatially and temporally controlled superimposition of runoff formation and runoff concentration, including the possible infiltration of overland flow (run-on infiltration) along the flow path and the retention in depression can have considerable influence on modelled peak discharge and discharge volume for a given catchment. For this purpose, various methods were developed and tested considering the effects of run-on infiltration and retention, from complex 2D hydraulic models coupled with RoGeR to simpler approaches considering run-on infiltration only locally or based on the difference between actual and potential infiltration. These approaches were tested in different catchments with different soils, geologies and land use. Also, the sensitiviy of surface roughness was considered.

We developed an interactive spatial explicit method, which combines the joint probability of soil moisture and rainfall for runoff formation with hydraulic assumptions to determine runoff concentration and thus the corresponding design hydrographs and the specific conditions a catchment can trigger flash floods. This information can on the one side help to generate flash flood risk maps, but should also be considered in order to provide adequate catchment specific information for heavy precipitation risk management. We could clearly demonstrate that only the combined consideration of factors affecting flood formation and concentration and its implementation into a statistical framework allows to predict floods for a specific return period (which is not equal to the return period of precipitation) for small catchments where different runoff generation mechanisms occur simultaneously.

D115 |
EGU2020-13267
Johannes Mitterer, Karl Broich, Thomas Pflugbeil, Fabian von Trentini, Florian Willkofer, Markus Disse, and Ralf Ludwig

In recent years, heavy precipitation and flash flood events frequently occurred in Germany. The project HiOS (reference map for surface runoff and flash floods) focusses on the analysis of these events using conceptual lumped precipitation runoff models, distributed raster-based water balance models (LARSIM and WaSiM), as well as a hydrodynamic model internally coupled with infiltration routines (TELEMAC-2D). The objective of our research is to analyze which factors and processes foster flash floods, and how they may be represented in models. We show a comprehensive methodological comparison using simulation results of some events in Bavaria. These do not include erosion and log jam scenarios.

The catchments distributed across whole Bavaria considering a variety of catchment characteristics and varying in size between 1.2 and 164km². All models are driven by 5 minute pseudo-calibrated radar precipitation data of the German Weather Service (YW product), which are available for entire Germany in a 1km² raster. The distributed water balance models are available using high-resolution cell grids. WaSiM uses a regular grid size of 50m, whereas LARSIM is run using 100m cells and an embedded hydrological response unit scheme. All TELEMAC-2D meshes are built with a standard mesh size of 5m in the catchment and 2m in the settled area of interest, while important hydrodynamic structures are resolved more in detail.

We want to highlight the variety of applied hydrological and hydrodynamic model approaches of runoff generation and concentration, whereby both, simple conceptual and complex physical methods are included. Runoff generation processes are represented using the SCS-CN method, a modified Lutz-Südbayern approach, a Xinjiang-bucket model combined with a Green&Ampt infiltration routine, as well as a layer-resolving Richards model. Beyond that, some of these consider silting up and soil crack formation. Runoff concentration processes are assessed by constant translation, Strickler flow time index method, a combination of Williams and Kalinin-Miljukov method, as well as finally with two-dimensionally resolved shallow water equations.

As expected, runoff generation is influenced by land use and soil parametrization. However, the amount of created runoff differs a lot changing the method of simulation. Furthermore, the runoff volume reacts quite sensitive to small changes in the preceding saturation conditions. Runoff concentration is influenced by slope, retention capacity of the flood plain, the network of drainages, as well as the formation of polders by water-crossing structures such as traffic infrastructure. Our results therefore clearly show the individual characteristics of extreme events depending on the catchment properties, which are reflected by the demands concerning the modelling techniques. The findings of this study illustrate the importance of improved radar-derived precipitation observations as well as the need for a spatially distributed and layered soil moisture product to enhance flash flood modelling using hydrological models.

D116 |
EGU2020-1969
Ngoc Tu Nguyen, Wei He, and Haishen Lü

Rainfall-runoff (RR) models play a critical role in water resource management and flood risk mitigations. Accurate depiction of soil moisture (SM) state in hydrological processes is very crucial for flash flood simulations with RR models. Satellite SM data offers a great opportunity to improve flood simulations by providing more accurate information about the SM state. However, how to make full use of satellite SM data to constrain flood model behavior is an important but tricky research issue, which is not fully solved. Here we propose a method to employ both satellite surface and root-zone soil moisture from the Global Land Evaporation Amsterdam Model (GLEAM) data to determine initial condition, a key parameter, using a two-layer RR model named as “MISDc-2L”. The flood simulations were performed at an hourly time step at small to medium catchments in China over 2010-2015. Results show that the MISDc-2L model satisfactorily simulates flash floods, and its performance varies with flood magnitude. Specifically, the model generally performs better for high-magnitude floods than medium and small ones. The GLEAM soil moisture data was found to be helpful to determine the initial conditions of the MISDc-2L model and thus substantially improved flood simulations. Furthermore, accounting for the different effects of surface SM and root-zone SM on the quantification of initial conditions clearly improves flood simulations. We conclude that satellite SM data is beneficial to flash flood simulations.

D117 |
EGU2020-15216
Qing Lin, Jorge Leandro, Markus Disse, and Daniel Sturm

The quantification of model structure uncertainty on hydraulic models is very important for flash flood simulations. The choice of an appropriate model structure complexity and assessment of the impacts due to infrastructure failure can have a huge impact on the simulation results. To assess the risk of flash floods, coupled hydraulic models, including 1D-sewer drainage and 2D-surface run-off models are required for urban areas because they include the bidirectional water exchange, which occurs between sewer and overland flow in a city [1]. By including various model components, we create different model structures. For example, modelling the inflow to the city with the 2D surface-runoff or with the delineated 1D model; including the sewer system or use a surrogate as an alternative; modifying the connectivity of manholes and pumps; or representing the drainage system failures during flood events. As the coupling pattern becomes complex, quantifying the model structure uncertainty is essential for the model structure evaluation. If one model component leads to higher model uncertainty, it is reasonable to conclude that the new component has a large impact in our model and therefore needs to be accounted for; if one component has a less impact in the overall uncertainty, then the model structure can be simplified, by removing that model component.

In this study, we set up seven different model structures [2] for the German city of Simbach. By comparison with two inflow calculation types (1D-delineated inflow or 2D-catchment), the existence of drainage system and infrastructure failures, the Model Uncertainty Factor (MUF) is calculated to quantify the model structure uncertainties and further trade-off values with Parameter Uncertainty Factor (PUF) [3]. Finally, we can obtain a more efficient hydraulic model with the essential model structure for urban flash flood simulation.

 

    1. Leandro, J., Chen, A. S., Djordjevic, S., and Dragan, S. (2009). "A comparison of 1D/1D and 1D/2D coupled hydraulic models for urban flood simulation." Journal of Hydraulic Engineering-ASCE, 6(1):495-504.
    2. Leandro, J., Schumann, A., and Pfister, A. (2016). A step towards considering the spatial heterogeneity of urban, key features in urban hydrology flood modelling. J. Hydrol., Elsevier, 535 (4), 356-365.
    3. Van Zelm, R., Huijbregts, M.A.J. (2013). Quantifying the trade-off between parameter and model structure uncertainty in life cycle impact assessment, Environ. Sci. Technol., 47(16), pp. 9274-9280.

 

D118 |
EGU2020-1563
Nadav Peleg, Chris Skinner, Simone Fatichi, and Peter Molnar

Spatial characteristics of extreme rainfall are expected to change with increasing temperatures. Extreme rainfall directly affects streamflow and sediment transport volumes and peaks, yet the effect of climate change on the small-scale spatial structure of extreme rainfall and subsequent impacts on hydrology and geomorphology remain largely unexplored. Motivated by this knowledge gap, we conducted a numerical experiment in which synthetic rainfall fields representing extreme rainfall events of two types, stratiform and convective, were simulated using a space-time rainfall generator model (AWE-GEN-2d). The rainfall fields were modified to follow different spatial rainfall scenarios, associated with increasing temperatures, and used as inputs into a landscape evolution model (CAESAR-Lisflood). We found that the response of the streamflow and sediment yields are highly sensitive to changes in total rainfall volume and to a lesser extent to changes in localized peak rainfall intensities. The morphological (erosion and sediment transport) components were found to be more sensitive to changes in rainfall spatial structure in comparison to the hydrological components, and more sensitive to convective rainfall than stratiform rainfall because of localized runoff generation and erosion production. In addition, we showed that assuming extreme rainfall events to intensify with increasing temperatures without introducing a change in the rainfall spatial structure might lead to over-estimation of future climate impacts on basin-wide hydro-geomorphology.

D119 |
EGU2020-18229
Maria Laura Poletti, Martina Lagasio, Francesco Silvestro, Antonio Parodi, Flavio Pignone, and Nicola Rebora

The use of the best input for an hydrometeorological chain is one of the key elements to improve the discharge prediction in the framework of early warning system. This fact gains in importance in a region such as Liguria Region , where the presence of many catchments with very small drained area and response time in the order of few hours make the prediction of severe events a critical point.

The work main scope is to exploit both observations and modelling sources to improve the discharge prediction in small catchments with lead time of 2-8 hours. To pursue this aim in this study the output from the nowcasting technique PhaSt, a spectral-based nowcasting procedure, is used together with the rainfall prediction of WRF NWP model with an hourly cycling 3DVAR data assimilation procedure to produce rainfall scenarios; the continuous distributed hydrological model Continuum, transforms these latter in streamflow scenarios. The connection between the forecasting models outputs is performed through the so called blending  technique, that tries to combine the rainfall fields according to their reliability function of the lead time. The blending has been modified with respect to the standard application using the information retrieved from the NWPS about the total volume on the domain considered and in terms of location of the rainfall structures. The whole chain is applied on some case events of 2014 all over Liguria Region, northern Italy.

D120 |
EGU2020-15139
Tommaso Piacentini, Enrico Miccadei, Cristiano Carabella, Fausto Boccabella, Silvia Ferrante, Tommaso Pagliani, Alessandro Pacione, and Carlo Gregori

Urban and small catchments flooding is a common type of natural hazard caused by intense rainfall, which may cause inundation to roads, buildings, and infrastructure, interrupting transportation, power lines and, other critical urban infrastructure systems, damaging properties and threatening people’s lives. The expansion of urban areas and infrastructure over the last 50 years has led to a marked increase in flood risk.

The coastal and hilly areas of Central Italy have been largely affected by heavy rainfall and flood/flash-flood events in recent times. The Apennine hilly piedmont and the coastal hills of Abruzzo have been affected by moderate to heavy events (rainfall >35 mm/h and 100-220 mm/d), which caused damages to minor and major urban areas. In this study, the Feltrino Stream area and the Lanciano town were investigated for the realization of a local early warning system for heavy rainfall events and flooding. The project is funded by the Abruzzo Region within the frame of a regional Project named “Communicate to protect” and developed in collaboration with the Lanciano Municipality and with the Regional Civil Protection office.

The Feltrino Stream basin is located in the hilly area of southeastern Abruzzo, in the eastern piedmont of the Maiella massif (Central Apennines). The basin ranges from about 400 m a.s.l. to sea level, with an overall morphology characterized by a mesa and plateau relief and SW-NE elongated valleys. The Lanciano Town is developed on a mesa relief carved by minor valleys, largely modified and filled by anthropic activities.

In this work, the Feltrino Stream was investigated through a drainage basin scale geomorphological analysis incorporating (i) the morphometry of orography and hydrography, (ii) temperature and rainfall data analysis, (iii) acquisition of available geological, geomorphological, and hazard data, (iv) detail urban hydrography analysis and geomorphological field mapping, for the definition of a geodatabase of the geo-hydrological critical areas. The analysis allowed defining the arrangement of a rainfall, hydrometry and flood monitoring system integrating at local scale the existing regional monitoring network. The integration of the monitoring system and the critical areas in a web cloud digital system allowed to plan and realize an early warning system, based on the use of a digital app for smartphone. The warning system is being calibrated for the effectiveness during heavy rainfall events. After calibration, the system will support the local civil protection activities of the Lanciano Municipality. Moreover, under the supervision of the civil protection responsible, it is expected to be implemented as an automatic system for smartphone-based early warning of people exploiting the inbuilt geolocalization features of the recent smartphone.

D121 |
EGU2020-18088
Emmanuel Skourtsos, Michael Diakakis, Christos Filis, Haralambos Kranis, Spyridon Mavroulis, and Efthymios Lekkas

During the late afternoon and early morning hours of September 7, 2016, an intense storm hit the wider area of the Kalamata Municipality, Greece, affecting large parts of SW and SE Peloponnese. The storm caused three deaths, dozens of homeless people, damages to hundreds of homes and cars, huge losses in agricultural production and livestock, as well as effects on the road network, on schools and water and electricity utilities. The settlements of Pidima and Thouria and the city of Kalamata itself, situated on the interface between the flat and mountainous terrain of Messenia region were particularly affected by the overflow of local streams.

Rainfall intensity reached up to 162.2mm in one and a half hour at Arfara station of the National Athens Observatory, 15 km north of Kalamata City, while Kalamata and Kardamili stations received 102 mm and 107.8 mm in 50 minutes respectively.

The rainfall that had preceded the storm the previous day had been two to three times the average monthly values of the stations for September. This event caused the saturation of the surficial part of the geological formations, which combined with the high intensity of precipitation of the second day of rainfall and the high morphological gradients of the mountainous area, led to an increase in surface runoff with high proportion of solid materials.

The storm caused multiple flash floods in the region affecting mostly small catchments drained by ephemeral torrents that caused flooding and severe damages in the city of Kalamata as well as the settlements of Pidima and Thouria and others. The phenomena and their impacts clustered notably near the border between the mountainous and flat terrain affecting heavily the towns situated along it. Larger rivers in the area (Ari and Pamisos Rivers) as well as the formerly swampy areas were affected but phenomena and impacts recorded notably less intensity. Small debris flows triggered by the storm were also limited to the border between the two types of terrains and caused damages mostly on the infrastructure developed there.

Overall, the distribution of impacts as well as the characteristics of the floods and debris flow phenomena showed that regions on the interface between mountainous terrain with steep slopes and flat regions present particularly high levels of hazard at the border between the two, whereas the intensity tends to reduce gradually downstream.

D122 |
EGU2020-18668
Mattia Zaramella, Lorenzo Marchi, Francesco Marra, Francesco Comiti, Stefano Crema, Mattia Marchio, and Marco Borga

Between the morning of 27 October 2018 and the evening of 29 October 2018, heavy precipitation over the Eastern Italian Alps led to damaging flooding. The event, which occurred at the end of a climatic anomaly of prolonged drought, developed into two phases, with a first phase (October 27-28) dominated by more stratiform orographically-enhanced precipitation. After a short lull, a second and more intense phase of the event took place on the 29th, when a cold front from the Gulf of Lion entered the Mediterranean basin triggering explosive cyclogenesis. A characteristic of the second phase of the storm is the rainfall organization in well-defined convective bands, some of which persisted at the same location for up to 3 hours. The bands, aligned from southeast to northwest, were initially located downstream of the pre-alpine region.

The work aims to investigate the impact of the stationary convective bands and of the dry antecedent conditions on the flood response to the storm. The availability of high-resolution rainfall estimates from weather radar and of dense rain gauge network data, along with flood response observations from stream gauge data and post-event surveys, enables to study the hydrometeorological and hydrological mechanisms associated with this extreme storm and the consequent flood response.

Observational and model analyses of the hydrologic runoff in two areas heavily impacted by the storm (Noce river basin, in the Trentino Province, and upper Cordevole river basin, in the Veneto Region) illustrate how the structure and evolution of the stationary convective bands translate into scale dependent flood response. For the upper Cordevole river basin, the event envelope curve shows two peculiar behaviors: (a) basin scale ranging from 1 to 200 km2, with peak unit discharges decreasing from 10 to 4 m3s-1km-2; (b) basin scale ranging from 200 to 2000 km2, with smaller peak unit discharges. The spatial extent of the first region is controlled by the structure of the central convective band. Moreover, the spatial moments of catchment rainfall are exploited to identify the impact of the convective cells motion along the stationary band on the flood response.

D123 |
EGU2020-8250
Josep Carles Balasch, Jordi Tuset, Xavier Castelltort, Mariano Barriendos, Llanos Valera-Prieto, Giorgi Khazaradze, Glòria Furdada, Jaume Calvet, and David Pino

On the 22nd and 23rd of October 2019 a severe rainfall produced floods in the basins of the Catalan Coastal Range-Ebro Depression border (Francolí, Set, Femosa rivers) that affected various towns such as L'Espluga de Francolí, Montblanc, l'Albi, Vinaixa, among others, causing 6 deaths and material damages that exceeded 100 million euros. According to historical records, this rainfall episode would exceed the maximum rainfall estimates expected for 500 years in this region and the maximum heights reached by the water are comparable to, or exceed, those of the remembered Santa Tecla flash flood on September 1874, which would have a recurrence of more than 250 years.

This rain was caused by a S-SE warm and wet Mediterranean air mass over the Catalan Coastal System (Prades and Llena Ranges). The area of maximum rainfall was located at the headwaters of the rivers Set, Francolí and Montsant rivers, with rain depths above 200 mm. The hourly distribution at El Vilosell and Prades rain gauges shows 50 mm from 6 to 14 UTC and maximum intensity of 10 to 15 mm h-1, followed by a second pulse of 180-220 mm from 16 to 01 UTC and maximum intensity of 65 mm h-1 (maximum 3.1 mm min-1). 

Soil moisture content was low at the time of the rain after a dry summer. Early precipitation saturated the topsoil, therefore the soil surface was very wet at the beginning of the second rainfall event and it generated a hortonian overland flow. The highest rainfall intensity occurred around 19 UTC and the peak flow response was immediate, around an hour later, depending on the location.

Despite the similarity of rainfall and initial soil moisture conditions, the hydrological response in the two analyzed basins was markedly different. The flows generated in the Set River basin at l'Albagès reservoir produced a peak flow of 245 m3 s-1 (1.5·m3·s-1·km-2) and a very low flood runoff ratio of only 8%. In the basin of the Francolí River, at L'Espluga de Francolí, the peak flow was 1,300 m3 s-1 (13 m3·s-1·km-2) and the runoff ratio was of the order of 70%. The Set river basin is basically agricultural with terraced slopes that retained much of the precipitation, only released after the flood as baseflow. The Francolí river basin has steeper slopes and channels and is dominated by an extensive tree cover but very poorer soils that caused little water retention, giving rise to a major hydrological response, an order of magnitude larger than that of the Set River.

D124 |
EGU2020-10393
Llanos Valera-Prieto, Sergi Cortés, Glòria Furdada, Marta González, Jordi Pinyol, Josep Carles Balasch, Giorgi Khazaradze, Jordi Tuset, and Jaume Calvet

On October 22, 2019, intense rains took place in Catalonia (292,6 mm in 24 hours at Prades), associated with a meteorological isolated depression at high atmospheric level (DANA in Spanish language). These rains caused a sudden discharge increase and a major flash-flood in the Francolí river (Tarragona, Catalonia, Spain). As a result, the river swept along a large quantity of vegetation, crops and infrastructures, such as bridges, roads, and houses. Unfortunately, the flood caused a considerable economic damage (exceeding 100 million euros), and a loss of six human lives. This area was also affected by the 1994 flood, which produced 10 fatalities and losses worth 17,000 million euros.

The Francolí river watershed has an area of 853 km2 and a length of 59 km. The study area stretches for ~20 km along the upper basin, without regulatory infrastructures. It covers the localities of Vimbodí, L´Espluga de Francolí, Montblanc and Vilaverd, with a population of 12,463 people. Downstream Vilaverd, the river crosses the strait of La Riba at the west of the Prades mountains. The Francolí River has low water levels much of the year and a strong seasonal regime. It presents high sediment mobility and large transportation capacity.

Orthophotographs, LiDAR and field work data, including GNSS-RTK data of river sections, are fundamental for this hydro-geomorphic analysis. It is performed mostly through classical and stereo-anaglyph photo-interpretation and comparison of the 2019 (post-flood event), 2016 (pre-flood event), 1995 (after the 1994 flood) and 1945-56 orthophotographs (provided by the Geological and Cartographic Institute of Catalonia). The main effects considered are: a) channel migration, cuts or changes in the sinuosity of meanders; b) significant bank erosion; c) pull up and dragging of vegetation; d) channel widening and braiding; e) development of secondary active channels during the flood; f) significant erosive and sedimentary morphologies; g) extension of the flooded areas through ephemeral evidence. From the geomorphological effects of the 2019 and 1994 floods, the Active Band is determined and mapped. This characterization highlights that the Francolí river is, geomorphologically, very active. In consequence, when defining flood hazard zones, hydraulic modelling would not be able to capture the complexity of this system and would produce biased results.

Once the Active Band is determined and with the estimation of peak flows in crucial localities, the Preferential Flow Zone (PFZ) can be defined. PFZ is the envelope of the areas where the flow concentrates during major floods or, also, the most frequently flooded areas in minor floods. This zoning allows us to discriminate areas with high and low flow energies, and to identify the margins most prone to erosion. Accordingly, varying levels of flood hazard can be mapped, and flood areas classified.

This combined analysis of indicators allows us to characterize the flood hazard more precisely in the studied stretch. The method can serve to better understand and predict the flash-floods associated hydro-geomorphic hazards in these kind of geomorphologically active rivers.

The authors thank the financial support from PROMONTEC project (CGL2017-84720-R AEI/FEDER, UE), Spanish MINEICO.

D125 |
EGU2020-5501
Christos Filis, Nafsika Ioanna Spyrou, Michalis Diakakis, Vassiliki Kotroni, Konstantinos Lagouvardos, Katerina Papagiannaki, Emmanuel Vassilakis, Dimitrios Milios, and Efthymios Lekkas

During the period 24-25 November 2019 a low pressure system with organised convective storms has affected Greece as it crossed the country from west to east. The system, which was name Gyrionis, after a name used in the Greek mythology, has produced heavy rainfall, with increased lightning activity and local hailstorms. In the area of western Attica the maximum rainfall has been reported with 92 mm of on 24 November and additional 115 mm in 25 November, adding to a storm total of 206 mm, which caused flash floods in the town of Kineta. The storm caused overflowing of local torrents draining the south slopes of Geraneia Ori, inducing significant damages in property and infrastructure mainly within the town and across the coastal zone.

Field surveys showed that a wildfire that burned through almost the entire catchment of the main torrent (named Pikas) on 2018, played a crucial role in flooding and its impact on the town. At critical locations along the river, vegetation debris and eroded material of various grain sizes, including boulders, diminished dramatically the hydraulic capacity of the river, intensifying flooding in the downstream areas, which formed an alluvial fan.

Based on comparison of pre- and post-flood aerial photography of the burned area, a major source of this deposited material was identified as burned trees still standing after the fire, uprooted from the river banks of the main channel and carried away together with additional soil debris. The material was jammed at a crucial location near the apex of the alluvial fan causing floodwaters to overflow and inundate significant parts of the fan’s apron, a geomorphological setting that increased the extent and impact of flooding further.

Overall, the case of Kineta, is a characteristic case of post-wildfire flash flooding, in which the fire effects are critical in the enhancement of subsequent flooding phenomena.

D126 |
EGU2020-17845
Nafsika Ioanna Spyrou, Eirini Spyridoula Stanota, Michalis Diakakis, Emmanuel Andreadakis, Efthymios Lekkas, and Emmanuel Vassilakis

Unmanned Aircraft Systems (UAS) can be used to enhance monitoring of a wide range of environmental parameters, including acquiring data on various types of hydro-geomorphic phenomena.

Their capabilities to provide on demand images and videos of high resolution, are particularly useful in the case of flash flood phenomena, which occur in spatial and temporal scales that do not favor traditional monitoring processes.

In this work, flow velocity is estimated using aerial imaging acquired by means of an Unmanned Aircraft Vehicle (UAV) as well as ground observations during the catastrophic flash flood event of November 2017 in Mandra, Greece.

In these imaging detailed tracing of various floating objects and particles such as light trash, debris etc. was carried out using multiple high-resolution video frames with specific time marks. Water velocity estimations were also cross-examined using flood mark-derived velocity hydraulic heads extracted by ground observations after the flood.

The analysis was applied at a variety of locations across the study area, leading to a map of velocities for parts of the floodplain. Velocity values varied significantly depending on location, reaching up to 10m/s.

The UAS proved to be very useful for the collection of important information for an extended area during the flood since a large portion of it was inaccessible due to road closures and safety issues. Nevertheless, the approach comes with certain limitations, including flight regulations, safety precautions and that rainfall is at a level that allows the deployment of a UAV during a flash flood.

The findings show that the integration of aerial with ground observations in post-flood analysis contributes the completeness and accuracy of datasets regarding specific flash flood parameters and in the future could become a useful source of information, especially in data-poor regions.

D127 |
EGU2020-1042
Elena Grek and Sergey Zhuravlev

The previous research had shown that change of rainfall structure is taking place over Russia which increases the probability of occurrence of hazardous hydrological phenomena such as flash rainfall floods. Thus, the relevance and significance of the study is determined by the necessity of taking into account the structural changes of precipitation for reliable estimates of rainfall runoff characteristics in terms of climate change. The data of this study are comprehensive and consist of various sources of hydrometeorological information, including ground-based observations of precipitation and runoff, radar data. The assessment of the changes occurred in the maximum rainfall runoff and daily rainfall depth within the Russian part of the Baltic Sea basin was carried out in this study. The majority of the basins in our study showed positive trends in maximum discharge. The results of the work describe the experience of using different types of meteorological information of precipitation for rainfall floods modeling. The open-source SWAT (Soil and Water Assessment Tool) hydrological model was utilized. Small catchment (631 km2) situated in the Polomet’ River basin were chosen as the object of test modeling. The simulation efficiency is assessed using the coefficient of determination R2, Nash–Sutcliffe model efficiency coefficient (NSE), by comparing the mean values to standard deviations for the calculated and measured values of water discharge. This study was supported by RFBR, grant 19-35-90123 “Rain floods in the North-West Russia: assessment of variability and development of new forecasting methods”.

D128 |
EGU2020-8866
Pelagiya Belyakova, Ekaterina Vasil'eva, Andrey Aleksyuk, Vitaly Belikov, Boris Gartsman, and Andrey Bugayets

In the Russian part of Western Caucasus heavy rainfall episodes frequently occur, leading to flash floods that often cause fatalities and severe damage. As soon as climate change is expected to increase the risk of flash floods it is necessary to improve flood forecasting and flood risk mapping as well as other precautionary measures. For this scope the better knowledge of catchment response on heavy precipitation is needed using rainfall-runoff simulation and further hydrodynamic modelling of inundation of urbanized areas.

There is a number of models used for flash flood simulation. In this study we used an available unit hydrograph model KW-GIUH [1] and a hydrodynamic model STREAM 2D CUDA [2]. KW-GIUH model only schematically describes overland flow over the catchment, nonlinear character of response is introduced via kinematic-wave approximation of the travel time. STREAM 2D CUDA is based on numerical solution of shallow water equations in a two-dimensional formulation according to the original algorithm using the exact solution of the Riemann problem [2], due to which the calculation is performed for the entire catchment without special allocation of the channel network. Models were tested on several flash flood events on the river Adagum (6-7 July 2012, catastrophic flood in the Krymsk town) and the Zapadny Dagomys river (25 June 2015, 24-25 October 2018, Sochi).

Comparison of simulation results was done as the same input data set was used. Input data included DEM HydroSHEDS, measured hourly precipitation and runoff volumes observed on gauges and estimated after high-water marks. Also 10-min water levels from a regional automated flood monitoring system of the Krasnodar Territory were applied. Simulated runoff volumes and peak timing were analyzed. For the Zapadny Dagomys river a forecasting calculation was done using precipitation forecast from COSMO-Ru. For the Adagum river STREAM 2D CUDA allowed to conduct an experiment to assess possible effect from potential reservoir-traps in the tributaries. The results of the rainfall-runoff simulation by the KW-GIUH model can be used as inflow to the boundary of the area for hydrodynamic modeling using STREAM 2D CUDA, also for operational use. Scenario calculations with changing hydraulic conditions at the catchment can be simulated using the STREAM 2D CUDA model itself.

The flood simulation was supported by the Russian Science Foundation under grant №17-77-30006. Data processing from an automated flood monitoring system in the Krasnodar Territory is funded by Russian Foundation for Basic Research and the Krasnodar Territory, grant № 19-45-233007.

References:

  1. Lee K.T., Cheng N.K., Gartsman B.I., Bugayets A.N. (2009): A current version of the model of a unit hydrograph and its use in Taiwan and Russia, Geography and Natural Resources, Volume 30, issue 1, pp. 79–85. https://doi.org/10.1016/j.gnr.2009.03.015
  2. Aleksyuk A.I., Belikov V.V. (2017): Simulation of shallow water flows with shoaling areas and bottom discontinuities, Computational Mathematics and Mathematical Physics, Volume 57, issue 2, pp. 318–339. https://doi.org/10.1134/S0965542517020026
D129 |
EGU2020-4376
Minyeob Jeong, Jongho Kim, and Dae-Hong Kim

A method to predict runoff based on the instantaneous unit hydrograph and dynamic wave approximation is proposed. The method is capable of generating IUH of a watershed without the need of observed rainfall and runoff data, and only topography and surface roughness of a watershed are needed. IUHs were generated using a dynamic wave model and S-hydrograph method, and IUH generated was a function of both watershed and rainfall properties. The ordinate of IUH depends on the rainfall intensities, and the peak value of IUH was proportional to the rainfall intensity while the time to peak of the IUH was inversely proportional to the rainfall intensity.  Corresponding IUHs for different rainfall intensities were used to generate runoff hydrographs. Since the IUH is generated using a dynamic wave model, it can be a tool to physically simulate the rainfall-runoff processes. Also, nonlinear rainfall-runoff relationship can be taken into account by expressing IUH as a function of rainfall excess intensity. Several test results in ideal basins and in a real watershed show that the proposed method has a good capability in predicting runoff, while several limitations remain.

Keywords: rainfall-runoff, instantaneous unit hydrograph, dynamic wave model

D130 |
EGU2020-19680
Franziska Villinger, Ralf Loritz, and Erwin Zehe

In the last decade, several small-scale flash floods in south-west Germany have shown that there is great danger due to quickly rising water levels and soil erosion (BRONSTERT ET AL., 2018). Flash floods are triggered by high intensity rainfall events, where rapid surface (Horton) or shallow subsurface flows dominate runoff generation. Especially surface runoff can result in great damage as it is a highly localized process with large potential to perform physical work on the landscape and on infrastructure. Model characteristics can vary greatly in space and time, reliable predictions remain challenging, especially if hydrological models are applied, based on empirical rainfall-runoff relationships. It is hence a long-standing vision to use models which are more physically based and rely on less empirical relations, to be able to improve our ability to predict the occurrence and dimension of flash floods.

In this study we use the physically based model CATFLOW, which is firstly setup to simulate flash floods for a small rural catchment. We perform virtual experiments to test a) if the model is capable to predict two observed flash floods caused by two convective rainfall extremes and b) which model landscape characteristics are the most sensitive. Thirdly, we provide evidence that different standardized temporal rainfall patterns used in flood design strongly affect simulated flooding when being compared to simulations with the real observed pattern. Last, we discuss why the two observed flash floods differed strongly in peak and volume, although the two convective events were similar in depth, duration and mean intensity and antecedent wetness was similar as well. We assume that due to the lower degree of plant cover during the earlier first event, the likelihood for raindrops hitting bare soil was higher, causing more surface sealing and hence more surface runoff occurred. Plant cover influencing soil resistance and soil texture are besides meteorological forcing a main control of flash floods.

D131 |
EGU2020-17388
Petr Kavka, Luděk Strouhal, Romana Kubínová, and Marek Kaspar

It this contribution partial results of the project, which is focused on hydrological modelling as a tool for designing small water management construction and soil conservation measure and in the landscape are presented. For the hydrological response, design rainfall and the initial condition, the current state of the river basin as well as the characteristics of the area under consideration are important. For the hydrological response, design rainfall, the current conditions of the catchment area as well as the characteristics of the solved area are important. 

Design precipitation in relation to initial conditions (soil moisture and surface condition) is one of the project goals. This data are important for hydrological modelling that is a tool for designing water management measures on small watercourses and in river basin areas is relevant for catchment size where long-term measurements and possible analogy cannot be used. The design of small hydrotechnical buildings based on hydrological modelling is used for catchments up to the area of ​​5 km2.

Basic categorization of small catchments in the Czech Republic is presented. At present, the Czech catchments are categorized into four levels. From the main river catchment to the catchment of the category IV. order (small catchments). There are considerable differences in size in the fourth category. From catchment areas of over 20 km2 to supplementary catchment areas of less than 1 km2. The categorization of these catchments in terms of their potential hydrological response is described in the past. For the categorization of the territory of the Czech Republic at the level of small catchment areas in terms of hydrological response, the different size of the area is one of the hardly definable parameters.

For these reasons, the project addresses also the delimitation of small catchments in the Czech Republic, which fall into the category of areas up to 5 km2 and significant areas outside the watercourse and their subsequent classification in terms of possible hydrological response. The activities were in this ongoing project focused on delimitation of these catchments and research of suitable data for their classification.

Detailed model of terrain in the resolution 5x5 m and watercourse layer were used as input data for delimitation of small catchments. ArcGIS tools and Python scripting language were used for processing. As it is a relatively large data set, the following analyses were gradually repeated for the catchment III. order with the extension of the boundary, so as to ensure possible discrepancies between the delimitation of the basin and the distribution boards defined on the basis of a detailed terrain model.

Nine categories were selected as significant areas ranging from contributing areas of 0,3 to 5,5 km2. In the category of the smallest catchments (categories from 0,3 to 0,7 km2) there are over 70 thousand areas defined in the Czech Republic. In the category from 4,5 to 5,5 km2 there are over 4 thousand catchments. A categorization both for individual classes and overall for the territory of the Czech Republic according to the largest contributing area is presented.

D132 |
EGU2020-6604
Mingfu Guan

Landslide natural dams are commonly formed in a river valley of mountainous areas due to heavy rainfall or earthquake, which can be a complete or partial blockage. Different from conventional man-made dams, natural dams typically comprise unconsolidated and poorly sorted material, and are vulnerable to failure and breaching in short period due to overtopping or seepage. For those small sediment blockage in a river valley, their failures frequently occur during high intense rainfalls, which will induce a large flash flood with high-concentrated sediment downstream in a short period, and the magnitude is likely to be amplified along the flow direction due to the inclusion of a large amount of sediment. This can result in significant and sudden debris flow or high sediment-charged flash flood in the downstream for human life and property. Cascade failures of a series of natural dams in a gully have been considered to be a primary reason for the enlargement of high sediment-laden flash flood. In general, cascading natural dams can be formed along the sloping channel due to the randomness and unpredictability of landslides, which complexes the hydraulics of landslide dam failures.

This study evaluates the formation and development of sediment-charged flash floods due to cascading failure of natural dams through detailed hydro-morphodynamic modelling. The model used is based on shallow water theory and it has been successful in predicting the flow and morphological process during sudden dam-break, as well as full and partial dyke-breach.  The study first calibrates the model with experiemntal data of a cascade of partical blockage dam failures. Then the calibrated model is applied to two types of natural dam failure cases: (1) straight steep slope channel with a series of small partial blockage dams; (2) bend channel with steep slope including a series of partical blockage dams. For both cases, various scenarios are modelled, including: (1) failure of a single dam in a sloping channel, (2) failure of two dams in a sloping channel, (3) failure of multiple landslide dams (four) in a sloping channel. Based on the detailed model results, the study systematically explores the tempo-spatial evolution of sediment-charged flash floods (discharge, flow velocity, and flow concentration) and geomorphic properties along the steep sloping channel.  The effects of in-channel erosion and flow-driven sediment from dams on the evolution of flood dynamic process are analysed.  The results improve the understanding of the formation and development mechanism of flash floods due to cascading landslide dam failures.  The findings are beneficial for downstream flood risk assessment and developing control strategies for landslide-induced floods.

D133 |
EGU2020-20502
Maryse Charpentier-Noyer, François Bourgin, Geoffroy Kirstetter, Olivier Delestre, and Pierre Brigode

The vulnerability of the French Riviera to hydro meteorological hazards has been dramatically illustrated by the flash floods of October 3, 2015: 20 people were killed and the cost of the direct damages were higher than 600 million euros. Due to their fast dynamics, flash floods are difficult to predict and leave little time for forecasting. In this context, it is needed to improve real-time simulations to enable a short-range anticipation of the consequences of these phenomena. The main goal of this work was to test a hydrologic-hydraulic coupling in order to assess whether this coupling can be used for real-time forecasting purposes. The coupling is composed for the hydrological part of the event-based spatially distributed rainfall-runoff model Cinecar and for the hydraulic part of the Basilisk software, which is based on 2D hydraulic modelling (finite volume methods for shallow water equations) with adaptive grid refinement. The main interest of this coupling method is the compromise obtained between calculation time and precision. The rainfall-runoff model is run on the upstream part of the domain and feeds the hydraulic model applied in the downstream part. The rainfall-runoff model makes it possible to estimate very quickly the streamflow temporal evolution, while the hydraulic model, although much slower when applied at high spatial resolution (up to 4m), makes it possible to have water level and velocity at any point of the downstream area. The application of this coupling approach is presented for three basins severely affected by the October 2015 flash floods: the Brague (68 km²), the Frayère (22 km²) and the Riou de l’Argentière (48 km²) catchments. The results obtained for the three basins are compared with information gathered from post-event surveys, particularly the high water level marks. A particular attention is also put on computation times in order to evaluate the possibilities of real-time simulation. The results show promising performances both in terms of calculation time but also in terms of accuracy of the simulated flood areas and water levels.

D134 |
EGU2020-19429
Thomas Pflugbeil, Karl Broich, Johannes Mitterer, Fabian von Trentini, Florian Willkofer, Ralf Ludwig, and Markus Disse

Heavy rainfall and resulting flash flood events have been in the focus of research and the public in recent years. The relevance of the topic will become more prominent with increasing temperatures due to climate change. Extreme rainfall events in Germany like 2014 in Münster (North Rhine-Westphalia) or 2016 in Simbach am Inn (Bavaria) and Braunsbach (Baden-Wurttemberg) have also raised public awareness.

Hydrodynamic models for the simulation of fluvial events have been developed for a long time and are often used. However, the question arises to what extent these methods can be used for pluvial events. Hydrodynamic models allowing precipitation input are therefore well suited for the simulation of pluvial events, as they can display flow paths, depths, and velocities in high resolution. Nevertheless, defining precipitation without infiltration leads to an overestimation of the surface runoff. For this problem, an improved event simulation can be achieved by nesting hydrological processes into the hydrodynamic simulation procedure. In this study, we are using TELEMAC-2D as a hydrodynamic model because it uses precipitation in a spatially and temporally distributed manner and can be used very well by high-performance computing. LARSIM (Large Area Runoff Simulation Model) and WaSiM (Water Flow and Balance Simulation Model) are used as hydrological models.

The methodology for simulating flash floods can be divided into two important processes: runoff generation and runoff concentration. These are divided according to the strength of the respective model types:

  • Runoff generation: SCS-CN value method (TELEMAC-2D), Green Ampt method (LARSIM), layer-resolving Richards method (WaSiM)
  • Runoff concentration: Strickler roughness approach (TELEMAC-2D), Kalinin-Miljukov method (LARSIM), flow time index method (WaSiM)

In this study, we examine three different types of couplings:

  • (1) The runoff concentration is calculated using the hydrodynamic model, the runoff generation is carried out using the CN value method.
  • (2) The runoff generation in the entire catchment is calculated using the hydrological processes (LARSIM/WaSiM). The runoff concentration is still generated by the hydrodynamic model.
  • (3) The runoff concentration in the upper catchment area is also calculated using hydrological methods, only the urban area is calculated hydrodynamically.

We compare the different coupling types with each other using some real flash flood events. The results are presented with the aim to identify which approach is necessary for a good representation of the flash flood event. This depends mainly on the local conditions in the catchment area (e.g.  culverts, land use) and the rainfall event (e.g. rainfall intensity and duration). The findings from this study will be transferred to unobserved catchments in the further course.

D135 |
EGU2020-21732
Karl Broich, Thomas Pflugbeil, Johannes Mitterer, and Markus Disse

After extreme flash floods events 2016 in Bavaria, the cooperation project HiOS (reference map for surface runoff and flash floods) was started aiming at the detailed analysis of risk generated by flash floods using GIS methods as well as hydrological and hydrodynamic models. Part of the risk analysis is done using hydrodynamic rainfall-runoff modeling (HDRRM). HDRRM gets more and more popular since hydrodynamic models are able to accept rainfall as input. But most of the known hydrodynamic models have no integrated precipitation modules and therefore cannot be used uniquely for rainfall-runoff modeling. In this study, TELEMAC-2D is used for HDRRM because it already contains the SCS-CN-method and offers the possibility to implement new precipitation modules due to its open source license. An additional advantage of TELEMAC-2D is the good scaling on HPC cluster systems.

In this study, two different approaches for runoff creation will be compared. (1) The well-proven SCS-CN method calculates effective rain. Due to its simple structure, the process of runoff generation is completely decoupled from runoff concentration. Consequently, SCS-CN cannot account for re-infiltration due to surface runoff. (2) However, the Green-Ampt infiltration (GAI) is coupled to surface runoff as long as the water depth is non-zero. GAI is implemented recently and thus will be described in more detail. Both approaches are first tested using a simple model setup. The general model performance of the enhanced hydrodynamic rainfall-runoff modeling (EHDRRM) is verified using the case study Simbach/Triftern in Bavaria. This extreme flash flood event from 1st June 2016 hit the townships Simbach am Inn and Triftern. It is well documented and all necessary data is available in good quality. The main setup for the catchment area of 47 km² resp. 90 km² is built on a 1x1 m DEM, land use data, hydrological soil group data and 5 min-RADOLAN precipitation data. The calculated catchment outflow can be verified by measured data at the gauging stations in Simbach am Inn resp. Triftern. All comparisons include as reference results for precipitation without losses by infiltration.

The hydrodynamic precipitation runoff modeling HDRRM has proven to be a useful method for calculating flow paths, depths and velocities with a high spatial resolution during flash flood events. If the process of runoff generation is performed by the hydrodynamic model EHDRRM then the quality of results is improved significantly while keeping the modeling procedure simple. Concerning infiltration, EHDRRM allows for a physically correct representation taking the actual local water depth into consideration.

D136 |
EGU2020-13330
Yu-Chang Chen and Jiing-Yun You

Recently, urban flooding has become an important issue due to heavy rainfall and rapid urbanization. For urban flooding, the drainage of stormwater is essential in inundation analysis, including the concentration of overland flow and the transportation in sewer system. However, in the past, the concentration of overland flow has not been well examined, especially under the influence of building structures. In the past, the overland flow in urban area is hard to calculate and causing lots of computation time. Currently, two-dimensional hydraulic models become an important tool for flood planning and management. In this study, we compare two hydraulic numerical models based of grid cell. So, we can flow pattern of overland flow in urban area for better understanding. First one is FLO-2D, which uses full dynamic wave momentum equation to predict the progression of a flood hydrograph. The second model is GSSHA, a physically-based, distributed model, which uses diffusive wave equation as governing equation to execute numerical simulation. With these two hydraulic models, this study focuses on how the constructions affect the water flow during the flood and whether they can be an important factor to influence the drainage system in urbanized area.

Keywords: urban flooding simulation, two-dimensional hydraulic model, influence of buildings, rainfall-runoff model, FLO-2D, GSSHA

D137 |
EGU2020-18773
Robert Sämann, Thomas Graf, and Insa Neuweiler

Early warning systems for floods in urban areas should forecast water levels and damage estimation to protect vulnerable regions. To estimate the danger of a flood for buildings and people, the energy of the flood has to be taken into account additionally to the water level. The energy is related to the flow velocity. For directing rescue workers or trace spreading of contaminants through flooded streets, a high resolution of the water’s energy in space and time is required. Direct numerical run-off calculation is too slow for a flood forecast in time. Therefore a database with pre-calculated events is needed and a method to select the water levels and velocity fields that are similar to a forecasted rain event.

We present a method, how to create a real-time forecast based on pre-calculated data. The selection and weighting of the pre-calculated data is based on the precipitation pattern in the flood region. A nearest neighbor approach is applied to find water levels and velocity fields from a database that are similar to the forecasting event. For the ranking of similarity, different new metrics are compared against each other. The quality of the metrics is tested with a new approach of comparing velocity fields on the surface and in the pipe system. Considering both domains is crucial for understanding the complex dynamic flow paths on the surface. An urban catchment of 5 km² with high resolution (~3 m³) triangular surface mesh and connected drainage system is used for a hydrodynamic run-off simulation. The 1D-2D coupled software HYSTEM EXTRAN is used to generate the water levels and velocity fields for strong rainfall events of the past 20 years. More than 900 events with a duration between 15 minutes and 24 hours and return periods between 10 and 100 years were calculated and stored as the “pre-calculated” dataset.

For comparing two events, the mean square error is calculated between the precipitation patterns with different approaches to select the start index and number of intervals. This number depends on the hydraulic response time, the temporal resolution and the length of the reference pattern. The quality of the nearest neighbor selection is quantified using the Nash–Sutcliffe model efficiency coefficient of pipe flow and the root mean square error of water level and velocity in significant surface cells. Additionally, the transport paths of artificial contamination spills are compared between the events to show the reproducibility of velocity fields for each metric.

Results show that the reaction time and the wetting state of the surface is very important. Single cell values correspond well between a forecasted and a dataset event. However, complex transport paths have a very high variability that is not reproducible with similar events. Further research is required to clarify if this is a result of the random walk approach or of the injection time of the particles.

D138 |
EGU2020-9429
Francesco Cioffi, Lorenzo Tieghi, Sergio pirozzoli, mario giannini, and vincenzo scotti

Recent disasters stress the demand of fast and reliable tools for flooding forecasting, where the real-time prediction of extreme events becomes essential to avoid potential hazards for the population. In this work, we focus on the flash flooding phenomenon, given by the combination of temporally concentrated rainfall and steep slopes. Such configuration is typical in the St. Lucia island, in the eastern Caribbean Sea, that we exploit as a case study. It is possible to simulate the full evolution of rainfall by numerically solving the Shallow Waters equations (SW) on a computational domain. A preliminary comparison with historical events proved that an accurate solution is achieved only when the Digital Elevation Model (DEM) presents a resolution equal or inferior to 5 meters. With this grid resolution the whole island is discretized in over 60M cells at best, forbidding a real-time application of the SW solvers in flash flooding events.

 In this work we present a machine-learning surrogate model for a SW solver to estimate the level of the flooding danger. It is evaluated through a synthetic parameter, hereafter referred as flag, that takes in account both the water depth and its velocity. Therefore, flooding patterns in the island are represented through high-resolution maps with discrete values of flags, varying from 0 – safe to 4 – extremely dangerous.

The final aim is to solve a supervised regression, training a Multi-Layer Perceptron Neural Network (MLPNN) to map sequences of time- and spatial-varying rainfall (input features) to the corresponding previsions of flags (output features) shifted ahead of time. To do so, we first generate a rough database by simulating more than 30 flash flooding events, using an in-house validated code, whose input is the temporal and spatial rainfall distribution obtained by radar measurements of events occurred in the past. DEM resolution is set to 5 meters and SW solver solutions is sampled every 6 mins. Given the high dimensionality of the problem, both the inputs and the outputs of the simulations are preprocessed using an Incremental Principal Component Analysis (IPCA) to extract the scores and loadings. The elbow charts indicate the correct number of principal components, set to 8, that explains the 95% of the cumulative explained variance. The scores given by IPCA processing of rainfall are built into sequences of five elements, endowing the algorithm a memory. The min/max regularization are applied to the database. The MLPNN training phase is fastened through batch feeding and monitored to prevent overfitting, relying on Tensorflow library. To test the generalization capability of the synthetic model was verified by forwarding events that were not included in the original database.

D139 |
EGU2020-4836
Development of Heavy Rain Damage Risk Class and Prediction Function
(withdrawn)
DongHyun Kim, Jongsung Kim, and Hung Soo Kim
D140 |
EGU2020-10062
Andreas Huber, Simon Lumassegger, David Leidinger, Stefan Achleitner, Herbert Formayer, and Bernhard Kohl

In recent years the topic of flash flooding away from rivers and permanent watercourses has attracted increasing attention from the scientific community, public authorities and affected parts of the general public. Not only urban areas with a high proportion of sealed surfaces, but also rural areas have been adversely affected by pluvial flash floods (PFFs) or surface water floods (SWFs) in the recent past. Empirical evidence suggests that amongst others pre-Alpine areas (e.g. in Austria, Germany, Switzerland, ...) might be especially susceptible to this type of flooding. From a water-management perspective knowledge about potentially endangered areas is important for involved stake-holders as a basis for informed decisions on a variety of topics ranging from protection of existing infrastructure and adaptation of current land use practices to future settlement development. In the light of changing climatic conditions also information on projected future developments is highly desirable. With respect to the latter, an increasing number of datasets from national and pan-European climate-services has become publicly available. Also a growing proportion of two-dimensional hydrodynamic models supports direct rainfall as a boundary condition, thus addressing the special requirements for modeling of PFFs/SWFs.

We utilize different two-dimensional hydrodynamic models (unstructured-mesh, raster-based) in combination with an event-based hydrological approach to simulate the spatial distribution of surface runoff in response to heavy precipitation events for present conditions and under projected future conditions for small rural areas (< 2km²) in Upper Austria. The general applicability of the used modeling approach is demonstrated. However, also a number of remaining challenges related to the limited quantity and quality of observational data for model calibration and the definition of representative future scenarios is identified and discussed.

D141 |
EGU2020-17883
James Cooper, Xiaorong Li, and Andy Plater

Climate change is projected to cause considerable pressure on our environment and communities. In particular, an increase in flooding and extreme erosion events is foreseeable as a result of anticipated increase in the frequency and severity of storms (Gorman et al., 2009). In the absence of timely and strategic intervention, climate change is taking us closer to more uncertain (non-linear, stochastic) and potentially more catastrophic climatic impacts. This research aims to 1) based on the combined application of the ‘Reach’ and ‘Catchment’ modes of Caesar-Lisflood, quantify the uncertainty in the risk posed by flooding and erosion hazards for current climate conditions and for two future epochs (2021-2040 & 2061-2080) using the UKCP18 projections; 2) to assess the economic impact of erosion hazards on critical infrastructure such as buildings, transport networks (roads and bridges), agricultural land, etc; and 3) evaluate the vulnerability and resilience of these assets to differing storm regimes. The above-mentioned storm-related hazards and economic impacts are integrated in a web-based geospatial decision-support tool for visualization which ultimately supports sustainable and resilient decision making for a changing climate.