Cross-sectoral impacts of the 2018-2019 Central European drought and climate resilience in the German part of the Elbe River basin

Abstract

The 2018-2019 Central European drought was probably the most extreme in Germany since the early sixteenth century. We assess the multiple consequences of the drought for natural systems, the economy and human health in the German part of the Elbe River basin, an area of 97,175 km² including the cities of Berlin and Hamburg and contributing about 18% to the German GDP. We employ meteorological, hydrological and socio-economic data to build a comprehensive picture of the drought severity, its multiple effects and cross-sectoral consequences in the basin. Time series of different drought indices illustrate the severity of the 2018-2019 drought and how it progressed from meteorological water deficits via soil water depletion towards low groundwater levels and river runoff, and losses in vegetation productivity. The event resulted in severe production losses in agriculture (minus 20-40% for staple crops) and forestry (especially through forced logging of damaged wood: 25.1 million tons in 2018-2020 compared to only 3.4 million tons in 2015-2017), while other economic sectors remained largely unaffected. However, there is no guarantee that this socio-economic stability will be sustained in future drought events; this is discussed in the light of 2022, another dry year holding the potential for a compound crisis. Given the increased probability for more intense and long-lasting droughts in most parts of Europe, this example of actual cross-sectoral drought impacts will be relevant for drought awareness and preparation planning in other regions.

Supplementary information: The online version contains supplementary material available at 10.1007/s10113-023-02032-3.

Keywords: Central European drought; Cross-sectoral; Drought impacts; Drought indices; Eastern Germany; Elbe River basin.

Fig. 1

Map of the research domain. Basin boundaries (red brown) with the Havel River subbasin (hatched) extracted from BfG (2020). Data available for administrative units only are regularly analyzed for an aggregate of five federal states (green boundaries): Berlin, Brandenburg (BB), Saxony (SN), Saxony-Anhalt (ST) and Thuringia (TH)

Fig. 2

Meteorological drought indices (SPI and SPEI) for the GEB, calculated for 3- and 12-month time scales. The orange and red threshold levels are at −1.0 and −2.0 indicating drought and extreme drought, respectively

Fig. 3

Seasonal cycles of available soil water modelled with AMBAV for a standard soil (sandy loam) of 1 m depth. Regional averages for the GEB (a) and the Havel area (b). The green areas and dashed lines indicate the 10–90 percentile ranges and median of the years 1991–2020. Data basis: DWD-CDC (2021d)

Fig. 4

Drought indices for the decade of 2011–2020 for GEB and Havel area. From top to bottom, the 3- and 12-month meteorological SPEI, the Z-score rescaled German Drought Monitor’s Soil Moisture Index (SMI*), the GRACE-based Groundwater Index (GGI), the Standardized Streamflow Index (SSI) and Z-scores of the Plant Phenology Index (PPI-Z; dots denoting winter dormancy period with PPI < 0.05) are depicted. Red and orange colours indicate drought and extreme drought thresholds as in Fig. 2. The 2020 gap in the SSI of the GEB is due to missing runoff data

Fig. 5

Crop yields in 2018 relative to the 2012–2017 averages in German district-level administrative units; grey areas indicate missing data. GEB and Havel area are outlined in black. Data source: Statistische Ämter (2022b). Map geometries © GeoBasisDE/BKG

Fig. 6

Recent annual wood harvests in the five-state aggregate separated by species groups. Indicated are also cutting volumes caused by actual damages. Data source: DESTATIS (2022a)

Fig. 7

a) Relative developments of the gross value added for the narrower service sector and the entire economy in the five-state aggregate. Index values, chained and corrected for inflation. b) Share of the narrower service sector in the total GVA of the five-state aggregate, calculated from absolute GVA figures in actual prices. Data source: Statistische Ämter (2022a)