Heavy Rainfall and Flood Hazards 2024


Both maps are comprised of multiple layers that are distinct in terms of their subject matter and location. Some of these layers are self-contained. More specifically, the maps contain the following specialised layers:

Map 02.24.1 Heavy Rainfall Information Map

The heavy rainfall information map is primarily based on the following resources:

  1. Topographic depression analysis of the Berlin Waterworks (BWB) and
  2. Fire service operations of the Berlin Fire Brigade (Berliner Feuerwehr) for the State of Berlin.

The topographic depression analysis is based on the topographic analysis of the digital terrain model (ATKIS® DGM – Digital Terrain Model, 2021), incorporating information on building areas, passageways, and floors (ALKIS® – Official Real Estate Cadastre Information System, 2021), which was conducted by the BWB in 2022. A GIS analysis was performed to identify depressions, flow paths, and accumulated runoff based on the pre-smoothed DTM. Buildings were integrated into the DTM as barriers to runoff, which cannot be overcome by water. Depressions in enclosed courtyards were excluded. The following depression attributes were derived based on a zonal statistics analysis and are part of the factual data display:

  • Catchment area (DrainArea [m2]),
  • Depression area (FillArea [m2]),
  • Maximum depth of the depression (FillDepth [cm]),
  • Lowest elevation within the depression (BottomElev [m]),
  • Highest elevation within the depression (FillElev [m]) and
  • Depression volume (FillVolume [m3])

Relevant depressions were identified based on the following criteria:

  • Depression depth of at least 20 cm,
  • Depression area of at least 4 m2,
  • Depression volume of at least 2 m3,
  • Catchment area of the depression of at least 200 m2.

The dataset capturing fire service operations compiles ‘water’-related reports from the Berlin Fire Brigade, which indicate a connection to heavy rain and which were recorded on days with heavy rainfall. The dataset was collected by the Berlin Fire Brigade and processed by the Berlin Waterworks (BWB) (i.e. Flood Atlas). The BWB cross-referenced the fire service operations with precipitation data from the BWB for the day and location in question, assigning an expected return period (T) to the rainfall event. Duplicates were removed. The following attributes were derived and are part of the factual data display:

  • Date (created)
  • Return period (T)
  • District

The data was geocoded using the Berlin address file. The timeframe of the reports includes two periods, the years 2005 to 2017 and the years 2018 to 2021. These datasets were combined into one dataset, covering the period from May 2005 to September 2021. For the purpose of aggregation and presentation, the data was grouped and classified based on block segment areas and road areas of the Urban and Environmental Information System (ISU5 2021).

Map 02.24.2 Heavy Rainfall Hazard Map

In Berlin, heavy rainfall hazards are analysed based on a coupled 1D sewer network and a 2D surface runoff model (1D/2D coupled model). This approach integrates the calculation of runoff processes in the sewer network (1D) with the two-dimensional hydrodynamic modelling of surface runoff (2D). It allows for a bidirectional exchange of water volumes, i.e. an exchange in both directions, between the surface and the sewer network at manholes and road drains. Together, the Berlin Waterworks (BWB) and the Senate Department responsible for water management have developed a statement of work ‘Preparation of Heavy Rainfall Hazard Maps for Berlin’s Combined and Rainwater Catchment Areas’ (Erstellung von Starkregengefahrenkarten für Berliner Misch- bzw. Regenwassereinzugsgebiete). This document forms the basis for defining heavy rainfall hazards.

Prerequisites include data on topography, buildings, roads, impervious soil coverage, soil-scientific characteristics, and sewer networks. The current sewer network (combined or separate sewerage system) provided by the BWB is used for the 1D sewer network model. The drainage infrastructure is represented by a sewer network model and encompasses elements such as manholes, road drains, sewer sections between manholes and their catchment areas. A detailed and comprehensive 2D surface model without overlaps is created based on the Digital Terrain Model. Standardised roof shapes derived from the building data are then integrated into the model. Walls or curbs are represented by break lines. The formation and concentration of runoff is impacted by the surface of the investigated area. Distinctions are therefore made between building areas, roads, paths, bodies of water, and green spaces based on the relevant data sources (cf. Chapter Statistical Base). Walls, curbs, and other linear elements, although not represented in the DTM due to resolution limitations, may act as runoff obstacles. If they are significant for runoff, they are subsequently added in as break lines.

Key datasets for building areas include ALKIS building data and the green roof dataset (for allotment garden areas). When it comes to the runoff formation of roofs, a distinction is made between discharging and non-discharging roofs, based on the records of precipitation charges. The model considers discharging roofs as directly connected to the sewer system (1D runoff formation). For non-discharging roofs, the runoff is modelled using the surface runoff model. In this case, the effective precipitation is spread across the surrounding surface by applying the principle of marginal distribution. Roads and pathways include all paved areas, such as roads, pathways, squares, and private impervious areas. Runoff from these areas is modelled using the 2D surface runoff model, without distinguishing between discharging and non-discharging areas. All standing and flowing waters from the ALKIS dataset are considered bodies of water. The remaining areas are assumed to be green spaces. These areas receive appropriate runoff parameters based on relevant literature. The parameters include runoff loss through wetting and accumulation in depressions as well as initial and final curve numbers. The model reflects the precipitation intercepted by vegetation (interception), the soil infiltration capacity, and the surface roughness.

In the context of flood risk areas (SenUVK, 2018), Berlin has already developed flood hazard maps and defined flood risk areas as part of the Floods Directive. To prevent overlaps with the heavy rainfall hazard maps, the bodies of water are assumed to be fully operational hydraulically. Additionally, certain bodies of water (e.g. of the first order (navigable waters), Nordgraben) are considered to be able to hydraulically cope with brief heavy rainfall events. Only prolonged, extensive rainfall events are expected to be ‘triggering’. The model assumes that discharge, i.e. an overflow of these bodies of water is methodologically impossible. Moreover, these waters are assigned uniform pre-flood water levels for a moderate flood (for rare and extraordinary events) and for a 100-year flood (for extreme events). For rare and extraordinary events, the actual pipes and culverts are included in the model. For the extreme event, it is assumed that culverts are either partially obstructed (diameter > 0.5 m (>DN 500)) or fully obstructed (diameter ≤ 0.5 m (≤ DN 500)), unless a debris screen prevents obstruction.

The resulting model is used to calculate flooding for different precipitation scenarios with varying return periods, relying on the Coordinated Storm Rainfall Regionalisation Analysis (KOSTRA) of Germany’s National Meteorological Service (DWD) for precipitation volumes. The revised dataset KOSTRA-DWD-2020 was used for this purpose. The following scenarios have been defined for Berlin in regard to heavy rainfall risk management:

  • rare event: 30 or 50-year rainfall event (T = 30a or T = 50a) with a Euler Type II precipitation pattern,
  • extraordinary event: 100-year rainfall event (T = 100a) with a Euler Type II precipitation pattern, and
  • extreme event: 100 mm rainfall event (T extreme) with block rainfall.

The prevailing duration category of 180 minutes in Berlin was derived from a sensitivity analysis, with the highest water level being the most important factor. To model the timeline and intensity of the event, either the Euler Type II distribution (for rare and extraordinary events) or a 60-minute block rainfall (for an extreme event) was assumed. The model takes into account both the duration of the rainfall, i.e. the duration category of the analysed scenarios, and a one-hour time lag. A plausibility check is carried out based on the results of the exceptional event. On-site checks are executed to review any implausible runoff paths and accumulated water, while also recording any hydraulically relevant structures that may have been overlooked.

This method requires a large amount of data and computational power. It was therefore not applied to the whole city at once. Instead, it is carried out gradually for selected areas. Nevertheless, the method delivers rather accurate and sound results, providing insight into the formation and concentration of runoff. Coupled 1D/2D simulations continue to be run for additional areas and are subsequently published online. The table below illustrates the areas for which heavy rainfall hazard maps have already been created.

Table 1: Areas for which heavy rainfall hazard maps have already been created.