of Downscaling of climate change scenarios for a high-resolution, site-speciﬁc assessment of drought stress risk for two viticultural regions with heterogeneous landscapes

Abstract. Extended periods without precipitation, observed for example in central Europe including Germany during the seasons from 2018 to 2020, can lead to water deficit and yield and quality losses for grape and wine production. Irrigation infrastructure in these regions to possibly overcome negative effects is largely non-existent. Regional climate models project changes in precipitation amounts and patterns, indicating an increase in frequency of the occurrence of comparable situations in the future. In order to assess possible impacts of climate change on the water budget of grapevines, a water balance model was developed, which accounts for the large heterogeneity of vineyards with respect to their soil water storage capacity, evapotranspiration as a function of slope and aspect, and
viticultural management practices. The model was fed with data from soil
maps (soil type and plant-available water capacity), a digital elevation
model, the European Union (EU) vineyard-register, observed weather data, and
future weather data simulated by regional climate models and downscaled by a
stochastic weather generator. This allowed conducting a risk assessment of
the drought stress occurrence for the wine-producing regions Rheingau and
Hessische Bergstraße in Germany on the scale of individual vineyard
plots. The simulations showed that the risk for drought stress varies
substantially between vineyard sites but might increase for steep-slope
regions in the future. Possible adaptation measures depend highly on local
conditions and are needed to make targeted use of water resources, while
an intense interplay of different wine-industry stakeholders, research,
knowledge transfer, and local authorities will be required.


RCM data: Daily data of 10 climate simulations from the ENSEMBLES project.
Observational data: Observed daily data of 10 weather stations of the regions Rheingau and Hessische Bergstraße from 1959-1988 (baseline climate).
Deriving sets of WG-parameters representing the observed station data for each weather station.

Weather generator:
Construction of a synthetic time series representing the baseline climate for each weather station (used to validate the WG).
Deriving RCM-based climate change scenarios from changes in the basic WG-parameters. The changes are based on comparison of WGparameters derived from RCMsimulated data from 2058-2087 and 1961-1990 for each grid cell.
Selecting the four closest grid cells for each weather station.
Interpolation of RCM-based climate change scenarios (changes in climate statistics) into station locations based on inverse distance weighting of the four closest grids for each weather station.
Weather generator: Construction of synthetic transient time series for each station and climate simulation. WG parameters of the observed climate were modified using the station-specific RCM-based climate change scenarios derived in the previous step, scaled by a factor k depending on the year and the selected emission scenario (see Fig. S2). Final time series consisted of observed data from 1961-1988 followed by synthetic series from 1989-2100 representing the emission scenarios RCP8.5 and RCP4.5. Spatial data of vineyard plots: Spatial polygons of the European Union vineyard register.
Weather data: Time series consisting of observed daily data from 1961-1988 followed by climate simulations from 1989-2100 for 10 weather stations across the vinegrowing regions (see Fig. S1 for details).

For each vineyard plot:
Selecting the nearest weather station to use the corresponding weather data.

For each vineyard plot:
Calculation of mean slope and aspect based on the digital elevation model.

For each vineyard plot and climate simulation:
Calculating reference evapotranspiration as a function of slope and aspect.

For each vineyard plot and climate simulation:
Calculating daily water balance with a vineyard water balance model.

Digital elevation model:
Digital elevation model at 1 m resolution, provided by the Hessian Agency for Soil Management and Geoinformation.
Soil data: Soil database of the official state map series BFD5W, based on soil mappings in 20 m x 20 m, respectively 25 m x 25 m resolution.
Linking each vineyard plot to soil data to determine the mean available water capacity at 1 m and 2 m depth (AWC1m, AWC2m) and the mean total evaporable water (TEW) of the soil surface layer.

Vineyard geometry and soil cultivation:
Uniform geometry representing a standard vertical shoot positioning system with 2 m row spacing. Soil cultivation and cover crops in alternating rows for the Rheingau region, complete green cover for the Hessische Bergstraße.     S1: Monthly means of the weather variables daily maximum temperature (Tmax), daily minimum temperature (Tmin), relative humidity (Rh), vapour pressure deficit (VPD), solar radiation (Rs), wind speed (u2, at 2 m above ground) based on recordings of the weather station in Geisenheim (Rheingau, Germany) for the periods 1961-1990 and 1991-2020. Reference evapotranspiration (ET0) was calculated from the monthly values according to FAO56 guidelines (Allen et al., 1998)     Following the calculation procedure of the FAO56 guidelines, the vapour pressure deficit was calculated from monthly means of temperature and relative humidity data. Regarding the calculation of ET0 the variables relative humidity and vapour pressure deficit are interchangeable and lead to the same results. The changes in the annual means of the weather variables shown in the table do not take into account seasonal shifts, which are, however, included in the changes in reference Winter (DJF) -10 to +24 +2 to +9 -12 to +20 Year -45 to +118 0 to +108 -150 to +93