Characteristics and influencing factors of flash floods in Bavaria (Germany) – an analysis using a hydrological-hydraulic model ensemble

2020 ◽  
Author(s):  
Johannes Mitterer ◽  
Karl Broich ◽  
Thomas Pflugbeil ◽  
Fabian von Trentini ◽  
Florian Willkofer ◽  
...  
Keyword(s):  
Water Balance ◽  
Hydrodynamic Model ◽  
Flash Flood ◽  
Flash Floods ◽  
Individual Characteristics ◽  
Runoff Generation ◽  
Retention Capacity ◽  
Index Method ◽  
Area Of Interest ◽  
Water Balance Models

<p>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.</p><p>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.</p><p>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.</p><p>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.</p>

Assessing the benefits of coupling hydrological and hydrodynamic model approaches for an improved simulation of flash floods

2020 ◽  
Author(s):  
Thomas Pflugbeil ◽  
Karl Broich ◽  
Johannes Mitterer ◽  
Fabian von Trentini ◽  
Florian Willkofer ◽  
...  
Keyword(s):  
Simulation Model ◽  
Hydrodynamic Model ◽  
Catchment Area ◽  
Flash Flood ◽  
Flash Floods ◽  
Hydrological Processes ◽  
Good Representation ◽  
Flood Events ◽  
Runoff Generation ◽  
Hydrodynamic Models

<p>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.</p><p>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.</p><p>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:</p><ul><li>Runoff generation: SCS-CN value method (TELEMAC-2D), Green Ampt method (LARSIM), layer-resolving Richards method (WaSiM)</li> <li>Runoff concentration: Strickler roughness approach (TELEMAC-2D), Kalinin-Miljukov method (LARSIM), flow time index method (WaSiM)</li> </ul><p>In this study, we examine three different types of couplings:</p><ul><li>(1) The runoff concentration is calculated using the hydrodynamic model, the runoff generation is carried out using the CN value method.</li> <li>(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.</li> <li>(3) The runoff concentration in the upper catchment area is also calculated using hydrological methods, only the urban area is calculated hydrodynamically.</li> </ul><p>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.</p>

scholarly journals The Ensemble Framework For Flash Flood Forecasting (EF5) v1.2: description and case study

2020 ◽  
Vol 13 (10) ◽  
pp. 4943-4958
Author(s):  
Zachary L. Flamig ◽  
Humberto Vergara ◽  
Jonathan J. Gourley
Keyword(s):  
Water Balance ◽  
Flash Flood ◽  
Flood Forecasting ◽  
Ensemble Forecasts ◽  
Routing Schemes ◽  
Catchment Areas ◽  
The Us ◽  
Water Balance Models ◽  
Flash Flood Forecasting

Abstract. The Ensemble Framework For Flash Flood Forecasting (EF5) was developed specifically for improving hydrologic predictions to aid in the issuance of flash flood warnings by the US National Weather Service. EF5 features multiple water balance models and two routing schemes which can be used to generate ensemble forecasts of streamflow, streamflow normalized by upstream basin area (i.e., unit streamflow), and soil saturation. EF5 is designed to utilize high-resolution precipitation forcing datasets now available in real time. A study on flash-flood-scale basins was conducted over the conterminous United States using gauged basins with catchment areas less than 1000 km2. The results of the study show that the three uncalibrated water balance models linked to kinematic wave routing are skillful in simulating streamflow.

Which event produces the largest flash flood? Considering rainfall characteristics, initial soil moisture, retention and run-on infiltration

2020 ◽  
Author(s):  
Markus Weiler ◽  
Hannes Leistert ◽  
Andreas Steinbrich
Keyword(s):  
Soil Moisture ◽  
Return Period ◽  
Overland Flow ◽  
Flash Flood ◽  
Joint Probability ◽  
Flash Floods ◽  
Runoff Generation ◽  
Runoff Formation ◽  
Initial Soil Moisture ◽  
Initial Soil

<p>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.</p><p>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.</p><p>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.</p>

Hydrodynamic rainfall-runoff modeling using different approaches for runoff creation

2020 ◽  
Author(s):  
Karl Broich ◽  
Thomas Pflugbeil ◽  
Johannes Mitterer ◽  
Markus Disse
Keyword(s):  
Water Depth ◽  
Surface Runoff ◽  
Flash Flood ◽  
Flash Floods ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Hydrodynamic Models ◽  
Additional Advantage ◽  
Runoff Modeling ◽  
Scs Cn

<p>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.</p><p>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 1<sup>st</sup> 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.</p><p>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.</p>

scholarly journals An Operational High-Performance Forecasting System for City-Scale Pluvial Flash Floods in the Southwestern Plain Areas of Taiwan

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 405
Author(s):  
Tzu-Yin Chang ◽  
Hongey Chen ◽  
Huei-Shuin Fu ◽  
Wei-Bo Chen ◽  
Yi-Chiang Yu ◽  
...  
Keyword(s):  
Hydrodynamic Model ◽  
High Performance ◽  
Flash Flood ◽  
Wrf Model ◽  
Flash Floods ◽  
Soil Conditions ◽  
Two Dimensional ◽  
Weather System ◽  
Forecasting System ◽  
Performance Forecasting

A pluvial flash flood is rapid flooding induced by intense rainfall associated with a severe weather system, such as thunderstorms or typhoons. Additionally, topography, ground cover, and soil conditions also account for the occurrence of pluvial flash floods. Pluvial flash floods are among the most devastating natural disasters that occur in Taiwan, and these floods always /occur within a few minutes or hours of excessive rainfall. Pluvial flash floods usually threaten large plain areas with high population densities; therefore, there is a great need to implement an operational high-performance forecasting system for pluvial flash flood mitigation and evacuation decisions. This study developed a high-performance two-dimensional hydrodynamic model based on the finite-element method and unstructured grids. The operational high-performance forecasting system is composed of the Weather Research and Forecasting (WRF) model, the Storm Water Management Model (SWMM), a two-dimensional hydrodynamic model, and a map-oriented visualization tool. The forecasting system employs digital elevation data with a 1-m resolution to simulate city-scale pluvial flash floods. The extent of flooding during historical inundation events derived from the forecasting system agrees well with the surveyed data for plain areas in southwestern Taiwan. The entire process of the operational high-performance forecasting system prediction of pluvial flash floods in the subsequent 24 h is accomplished within 8–10 min, and forecasts are updated every six hours.

scholarly journals The Ensemble Framework For Flash Flood Forecasting (EF5) v1.2: Description and Case Study

2020 ◽  
Author(s):  
Zachary L. Flamig ◽  
Humberto Vergara ◽  
Jonathan J. Gourley
Keyword(s):  
Water Balance ◽  
Flash Flood ◽  
Flood Forecasting ◽  
Streamflow Prediction ◽  
Ensemble Forecasts ◽  
Routing Schemes ◽  
Catchment Areas ◽  
Water Balance Models ◽  
Flash Flood Forecasting

Abstract. The Ensemble Framework For Flash Flood Forecasting (EF5) was developed specifically for improving hydrologic predictions to aid in the issuance of flash flood warnings by the U.S. National Weather Service. EF5 features multiple water balance models and two routing schemes which can be used to generate ensemble forecasts of streamflow, streamflow normalized by upstream basin area (i.e., unit streamflow), and soil saturation. EF5 is designed to utilize high resolution precipitation forcing datasets now available in near real time. A study on flash flood scale basins was conducted over the conterminous United States using gauged basins with catchment areas less than 1,000 km2. The results of the study show that the three uncalibrated water balance models linked to kinematic wave routing are skillful in streamflow prediction.

scholarly journals A Survey of Remote Sensing and Geographic Information System Applications for Flash Floods

2021 ◽  
Vol 13 (9) ◽  
pp. 1818
Author(s):  
Lisha Ding ◽  
Lei Ma ◽  
Longguo Li ◽  
Chao Liu ◽  
Naiwen Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Flash Flood ◽  
Flash Floods ◽  
Geographic Information ◽  
Flood Disaster ◽  
Future Research ◽  
Time Zone ◽  
Gis Technologies

Flash floods are among the most dangerous natural disasters. As climate change and urbanization advance, an increasing number of people are at risk of flash floods. The application of remote sensing and geographic information system (GIS) technologies in the study of flash floods has increased significantly over the last 20 years. In this paper, more than 200 articles published in the last 20 years are summarized and analyzed. First, a visualization analysis of the literature is performed, including a keyword co-occurrence analysis, time zone chart analysis, keyword burst analysis, and literature co-citation analysis. Then, the application of remote sensing and GIS technologies to flash flood disasters is analyzed in terms of aspects such as flash flood forecasting, flash flood disaster impact assessments, flash flood susceptibility analyses, flash flood risk assessments, and the identification of flash flood disaster risk areas. Finally, the current research status is summarized, and the orientation of future research is also discussed.

Using convection-permitting climate models and a high-resolution distributed hydrological model to assess future changes in Alpine flash floods.

2021 ◽  
Author(s):  
Marjanne Zander ◽  
Pety Viguurs ◽  
Frederiek Sperna Weiland ◽  
Albrecht Weerts
Keyword(s):  
High Resolution ◽  
Natural Hazards ◽  
Climate Models ◽  
Flash Flood ◽  
Regional Climate ◽  
Flash Floods ◽  
Flood Frequency ◽  
Climate Dynamics ◽  
Future Climate ◽  
European Climate

<p>Flash Floods are damaging natural hazards which often occur in the European Alps. Precipitation patterns and intensity may change in a future climate affecting their occurrence and magnitude. For impact studies, flash floods can be difficult to simulate due the complex orography and limited extent & duration of the heavy rainfall events which trigger them. The new generation convection-permitting regional climate models improve the intensity and frequency of heavy precipitation (Ban et al., 2021).</p><p>Therefore, this study combines such simulations with high-resolution distributed hydrological modelling to assess changes in flash flood frequency and occurrence over the Alpine terrain. We use the state-of-the-art Unified Model (Berthou et al., 2018) to drive a high-resolution distributed hydrological wflow_sbm model (e.g. Imhoff et al., 2020) covering most of the Alpine mountain range on an hourly resolution. Simulations of the future climate RCP 8.5 for the end-of-century (2096-2105) and current climate (1998-2007) are compared.</p><p>First, the wflow_sbm model was validated by comparing ERA5 driven simulation with streamflow observations (across Rhone, Rhine, Po, Adige and Danube). Second, the wflow_sbm simulation driven by UM simulation of the current climate was compared to a dataset of historical flood occurrences (Paprotny et al., 2018, Earth Syst. Sci. Data) to validate if the model can accurately simulate the location of the flash floods and to determine a suitable threshold for flash flooding. Finally, the future run was used to asses changes in flash flood frequency and occurrence. Results show an increase in flash flood frequency for the Upper Rhine and Adige catchments. For the Rhone the increase was less pronounced. The locations where the flash floods occur did not change much.</p><p>This research is embedded in the EU H2020 project EUCP (EUropean Climate Prediction system) (https://www.eucp-project.eu/), which aims to support climate adaptation and mitigation decisions for the coming decades by developing a regional climate prediction and projection system based on high-resolution climate models for Europe.</p><p> </p><p>N. Ban, E. Brisson, C. Caillaud, E. Coppola, E. Pichelli, S. Sobolowski, …, M.J. Zander (2021): “The first multi-model ensemble of regional climate simulations at the kilometer-scale resolution, Part I: Evaluation of precipitation”, manuscript accepted for publication in Climate Dynamics.</p><p>S. Berthou, E.J. Kendon, S. C. Chan, N. Ban, D. Leutwyler, C. Schär, and G. Fosser, 2018, “Pan-european climate at convection-permitting scale: a model intercomparison study.” Climate Dynamics, pages 1–25, DOI: 10.1007/s00382-018-4114-6</p><p>Imhoff, R.O., W. van Verseveld, B. van Osnabrugge, A.H. Weerts, 2020. “Scaling point-scale pedotransfer functions parameter estimates for seamless large-domain high-resolution distributed hydrological modelling: An example for the Rhine river.” Water Resources Research, 56. Doi: 10.1029/2019WR026807</p><p>Paprotny, D., Morales Napoles, O., & Jonkman, S. N., 2018. "HANZE: a pan-European database of exposure to natural hazards and damaging historical floods since 1870". Earth System Science Data, 10, 565–581, https://doi.org/10.5194/essd-10-565-2018</p>

scholarly journals Modelling monthly runoff generation processes following land use changes: groundwater–surface runoff interactions

2004 ◽  
Vol 8 (5) ◽  
pp. 903-922 ◽  
Author(s):  
M. Bari ◽  
K. R. J. Smettem
Keyword(s):  
Land Use ◽  
Water Balance ◽  
Surface Runoff ◽  
Land Use Changes ◽  
Annual Rainfall ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Mean Annual Rainfall ◽  
Monthly Runoff ◽  
Stream Bed

Abstract. A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall–runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, "Ernies" (control, fully forested) and "Lemon" (54% cleared) are in a zone of mean annual rainfall of 725 mm, while "Salmon" (control, fully forested) and "Wights" (100% cleared) are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall–runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i) immediately after clearing due to reduced evapotranspiration, and (ii) through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i) an upper zone unsaturated store, (ii) a transient stream zone store, (ii) a lower zone unsaturated store and (iv) a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and predicted monthly hydrographs. The observed and predicted monthly runoff for all catchments matched well with coefficients of determination (R2) ranging from 0.68 to 0.87. Predictions were relatively poor for: (i) the Ernies catchment (lowest rainfall, forested), and (ii) months with very high flows. Overall, the predicted mean annual streamflow was within ±8% of the observed values. Keywords: monthly streamflow, land use change, conceptual model, data-based approach, groundwater

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