BO-I-3: Rainfall erosivity

The legend comprises six categories for the rainfall erosivity (unit: kilojoules per square metre multiplied by millimetres per hour) as a district average for the years 2017 to 2021.Click to enlarge
Rainfall erosivity – district mean for 2017-2021

The legend comprises six categories for the rainfall erosivity (unit: kilojoules per square metre multiplied by millimetres per hour) as a district average for the years 2017 to 2021. The categories each comprise 15 units. The yellow-green colour spectrum ranges from yellow for values less than 70 to dark green for values greater than 130. There is also a category with black hatching on a white background for districts with insufficient data.

Source: Technical data: DWD (RADKLIM); Geodata: Geobasis-DE/BKG 2021

2023 Monitoring Report on the German Strategy for Adaptation to Climate Change

BO-I-3: Rainfall erosivity

In Germany, rainfall erosivity doubled over the past 50 years. High levels of rainfall intensity increase the risk of  soil loss. In years with violent heavy rainfall events such as 2002 or latterly 2021, the mean annual R-factors were  particularly high. Targeted anti-erosion measures taken on vulnerable soils and on steeply sloping terrain can help to  reduce soil loss even where high rainfall erosivity prevails.

The illustration contains an XY scatter diagram which indicates the mean annual R-factor in Newton per hour. The illustration covers the period 1962 to 2021.
BO-I-3: Rainfall erosivity
Source: literature research up until 2000 (Auerswald et al. 2019a and b); from 2001 onwards DWD (RADKLIM)

Climate change increases the risk of soil loss

Soils usable today is the result of thousands of years of development, because the formation of a soil layer of just one centimetre thickness, arising from the weathering of rock and the decomposition of organic matter, takes at least a hundred years. Soil losses, for instance resulting from erosion by water or wind, are therefore usually irreplaceable. They constitute severe ecological and economic damage.

The impacts of climate change increase the risk of soil loss. Erosive, extreme weather events as well as heavy rain events have been occurring more frequently and with greater intensity. Moreover, soil loss can be favoured by increasing precipitation in winter. When winter precipitation increasingly falls as rain, and when this rain falls on patchy vegetation cover on soils under agricultural use, the outcome may involve substantial soil losses. Furthermore, temperature increases lead to shifts in the development phases of plants, including agricultural crops (cf. Indicator LW-I-1). Presumably, any resulting changes in ground cover are likely to increase the risk of erosion even more. Gaps in the vegetation – apt to assist erosion – and desiccated topsoil are to be expected as a result of increased drought periods in spring and summer. This development also increases the risk of wind erosion. On the predominantly sandy soils in northern Länder near the coast, wind is one of the foremost causes of erosion.

Primarily, soil erosion signifies a reduction in soil depth and thus in the usable field capacity (cf. Indicators BO-I-1, and BO-I-2) It also signifies the loss of topsoil particularly rich in nutrients and humus. Eroded soil material is shifted to lower lying areas including housing estates and transport routes. In those locations the material inputs lead to siltation (colmation) thus producing undesirable pollution of water bodies with nutrients and pollutants. Such developments counteract the efforts to improve the condition of water in the spirit of the European Water Framework Directive (WWRL).

Erosion monitoring that would cover the whole of Germany contiguously is not yet available. So far, soil erosion monitoring conducted in existing BDF is the only measuring approach to cover all of Germany’s Länder for the purpose of long-term data collection on soil erosion nationwide. However, neither the procedures nor the intensity involved in those surveys have been adopting a homogeneous approach. Consequently, there is a lack of representative monitoring data on the actual erosion scenario. However, it is possible to calculate rainfall erosivity (the R-factor) on the basis of ombrometer and radar data thus facilitating an estimate of the risk potential. The R-factor is an input parameter contained in ABAG, the Allgemeine Bodenabtragsgleichung (General Soil Erosion Equation) which is used to illustrate climate-relevant influences on erosion. Rainfall erosivity results from the volume and intensity of erosive rain. It describes the ability of precipitation to detach particles from their aggregates (splash effect) by means of the rain’s kinetic energy, thus displacing these mparticles as a result of surface discharge.

The indicator shows the mean annual R-factor for Germany: from 1962 to 2016 on the basis of ombrometer data98, 98, from 2001 to 2021, additionally, on the basis of RADKLIM, radar-based precipitation data99. As is typical of time series characterised by extreme events, the development of the mean annual R-factors in Germany indicates a fluctuating course. Both the ombrometer data and the radar data indicate peak values of rainfall erosivity for the years of 2002 and 2007. Especially the year of 2002 was characterised by heavy rainfall events. In summer, violent precipitation led to severe flooding in eastern and western Germany. The year of 2021 had, according to RADKLIM data, the fourth highest mean rainfall erosivity so far. In that year, one of the most severe flood disasters in Germany’s history occurred in North Rhine-Westphalia and in the Rhineland-Palatinate as a result of heavy rainfall. The moving 5-year mean demonstrates that over the past 50 years, the R-factor has increased distinctly. In 2019, the 5-year annual mean was roughly 2.5 times higher than in 1975.

In Germany, rainfall erosivity is essentially in line with the distribution of precipitation. As far as the mean of 2017 to 2021 is concerned, the lowest R-values (RADKLIM radar data) were centred on Saxony-Anhalt and Lower Saxony, on North Rhine-Westphalia and on the coast of Mecklenburg-Western Pomerania. In the North German Plain, erosive precipitation volumes generally occur less frequently than in central Germany and the south of the country where, in orographical terms, the topography is more differentiated thus favouring elevating and convective processes in the atmosphere. Accordingly, the highest R-factor values occur in the ridges of upland areas and in the Alpine region.

Apart from precipitation, the slope of the terrain, the soil properties, and especially the ground cover play an important role in the erosion scenarios: Types of crops with a particularly high potential for soil loss include potatoes, maize and sugar beet as well as numerous special crops and vineyards on steep slopes. There is a diverse range of measures available for preventing erosion, in particular in arable fields. The options range from site-adapted crop rotation which ensures continuous ground cover for the entire year, to nurse crops and the use of mulches, to adapting the management direction as well as practising permanently ploughless, conservation-oriented soil tillage for the purpose of maintaining a natural soil structure and in order to achieve particularly thorough soil cover by leaving protective plant residues on the ground.

 

98 - Auerswald K., Fischer F., Winterrath T., Brandhuber R. 2019a: Rain erosivity map for Germany derived from contiguous radar rain data. Hydrol. Earth Syst. Sci., 23: 1819–1832. https://hess.copernicus.org/articles/23/1819/2019/.
98 - Auerswald K., Fischer F., Winterrath T., Elhaus D., Maier H., Brandhuber R. 2019b: Klimabedingte Veränderung der Regenerosivität seit 1960 und Konsequenzen für Bodenabtragsschätzungen. In: Bachmann G., König W., Utermann J. (Hg.) Bodenschutz, Ergänzbares Handbuch der Maßnahmen und Empfehlungen für Schutz, Pflege und Sanierung von Böden, Landschaft und Grundwasser (Loseblattsammlung), Berlin, 4090, 21. pp. https://mediatum.ub.tum.de/doc/1525847/document.pdf.

99 - Winterrath T., Brendel C., Hafer M., Junghänel T., Klameth A., Lengfeld K., Walawender E., Weigl E., Becker A. 2018: RADKLIM Version 2017.002: Reprocessed gauge-adjusted radar-data, one-hour precipitation sums (RW). doi: 10.5676/DWD/RADKLIM_RW_V2017.002.

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