Rainfed winter wheat cultivation in the North German Plain will be water limited under climate change until 2070
© Svoboda et al. 2015
Received: 19 May 2015
Accepted: 29 October 2015
Published: 10 November 2015
We analysed regionalised ECHAM6 climate data for the North German Plains (NGP) in two time slots from 1981 to 2010 and 2041 to 2070.
The annual mean temperature will increase significantly (by about 2 °C) that will result in shorter growing periods since the sum of degree days until harvest will be reached earlier. Even if the amount of total precipitation does not change there appears to be a shift towards increased winter precipitation and thus noticeable reduced summer precipitation.
Through the example of winter wheat we show a future limitation of water availability if yields are to be maintained or even increase.
Is there a relevant change by comparing the status quo with current climate projections?
Is there a shift towards winter rainfall in the NGP, and in particular in the study regions, as predicted in the literature?
Is there a trend to decreased and less steady rainfall during the summer growing period of winter wheat visible when evaluating current climate projections?
Winter wheat is the most important crop in the NGP and, matching with Boogaard et al. , the dominant crop of Europe in terms of acreage. In DH, 16 % of all cropping area is winter wheat (WW). In OS, the share is 7 %. The sowing date (JD s) is September 15 as common in the NGP. Due to temperature as the main driver for physiological processes , the harvest date of winter wheat is essentially determined by cumulated temperature (heat sum), expressed in degree days (DD) . Growth of winter wheat depends strictly on the air temperature .
Modelling the harvest date and growing period
Iterators are j and n.
Time period analysed within this study is from 1981 until 2070. Within this period we selected two representative time slots of 30 years each. First slot is from 1981 to 2010 representing the status quo and delineates the reference period. The second slot is from 2041 to 2070 representing the future. Differences between the time slots indicate a possible climate change.
Scenario weather data for representative weather stations are available with daily values for the model regions in the NGP. These data are the result of fitting “Statistical regionalization model: STAR”  to recent measured data of the appropriate weather stations. STAR scenario data (SCEN: 1981–2010) then match the observed values for each study area in terms like mean monthly precipitation, temperature and solar radiation. To exclude model bias when comparing status quo with future climate data, all following evaluations of the status quo were based on the scenario (SCEN) climate data.
Climate—climate change (CC) scenarios for future climate prediction
The results for the current condition were compared to projected weather data driven by the output of general circulation models (GCM) run under representative concentration pathway 8.5 (RCP 8.5). Collective climate models were used for analysis and prediction of climate change. Collective climate models include 21 GCM; all were driven by the scenario RCP 8.5. For the present study, we have selected 3 out of 21 GCM on the basis of their temperature gradient: (a) Minimum mean temperature increase (T min → INM-CM4, Russia, +1 °C until 2070). (b) Medium mean temperature increase (T med → ECHAM6, MPI Hamburg, Germany, +2 °C). (c) Maximum mean temperature increase (T max → ACCESS1.0, CSIRO-BOM, Australia, +3 °C). The regionalisation of the GCM output was realised by the STAR model.
First of all, we need to define which aspects of climate change are relevant concerning crop production in general. Thus, in this study, the relevant climate change intends relevant for cropping winter wheat and includes in particular evaluations during the growing period and this period in parts.
Winter rainfall in our context is defined by DIN 4049 where the hydrological year (H a) runs from 1 November of year one to 31 October of the following year. The winter season includes the months of November to April; the summer season includes the months of May to October. The second benefit is the start and end of hydrological winter (H W) that reflects start and end of leaching period in the NGP. Calculating this way enables us to analyse the winter rainfall during the typical leaching period and the summer rainfall from the end of the leaching period during summer until the harvest date, respectively.
Since rainfall during the growing period (P veg) is not a meaningful parameter for analysing possible water deficit of winter wheat, we introduced the precipitation during main growing period (P m-veg) as a parameter of interest (beginning of possible water deficit due to emptying the soil water storage with the beginning of hydrological summer); P m-veg is defined by the amount of precipitation measured from May 1 (assumed end of leaching period due to the beginning of significant transpiration) until harvest date.
All data were evaluated using the R software package R Core Team .
Shift towards winter rainfall
Precipitation in the study regions Diepholz (DH) and Oder-Spree (OS) differentiated according to annual precipitation (1.1.–31.12.), precipitation during hydrological year (1.10.–31.9.), hydrological winter (1.10.–31.4.) and the share of precipitation during hydrological winter (H W)
Share of H W
Growing period (days) of winter wheat (V per) as defined by the delimiters sowing and harvest date for the study regions Diepholz (DH) and Oder-Spree (OS)
Rainfall during main growing period and potential drought
Precipitation during main growing period (P m-veg)
P m-veg (mm)
P m-veg (mm)
When comparing the data from the weather stations during the reference period with the modelled STAR outcome no significant differences are noticed. This is in good agreement of Gerstengarbe et al.  who compared STAR with the current climatology of selected regions all over Germany. Gallardo et al.  show similar results while analysing an ensemble of 15 regional climate models nested into six GCM. They found differences depending on the region and the investigated model. Our simple model for calculating the harvest date reasonably well predicts the mean harvest date over a long period of 30 years. For some years the prediction is less precise. For this reason, we have based all results to the long term.
Shift towards winter rainfall
The shift towards winter rainfall with +7 % in DH and +9 % in OS is less pronounced than reported in many studies [9, 11, 12]. That may be because of the different period (hydrological vs. calendric) selected on the one hand and the different period of time (1981–2010) in total. Badeck et al.  suggested that a fraction of uncertainty may arise due to the time frame analysed. Comparing the mean annual precipitation of calendric against hydrologic year in the present time period, DH shows with 709 mm compared to 711 mm only little difference. However, OS reflects similar results on a lower level (572 to 566 mm). Kozuchowski and Degirmendizc  analysed long time weather data in different regions in Poland and found that regional differences are widespread. Following this, it may be possible, that the regions investigated in the present study may have a different shift than the mean of the NGP. Further studies should clarify the situation.
Patil et al.  found evidence that increased temperature led to earlier harvest date; the same effect we discovered for both regions. Depending on the scenario (T min, T med, T max) the harvest date will be three (T min), five (T med) or six (T max) weeks earlier than today. For Southern Sweden, Eckersten  has also found earlier harvest dates for winter wheat along with rising temperatures, while the yields stayed the same or decreased.
Growing period and rainfall during growing period
While comparing the growing period of winter wheat (V per) in SCEN (1981–2010) with the V per in T max (2041–2070), there is a reduction of 45 (14 %) days in both regions. These findings correspond with Brown and Rosenberg  who calculated the length of the growing season of winter wheat in North America with different GCM. They pointed out that with increasing temperature the potential of water stress may arise. Reciprocal to the growing days we calculated the so-called cold days, with less than 2.5 °C, during the growing period. The amount of cold days decreased by >60 % to 19 days in the T max scenario. Walther et al.  discovered a comparable trend for frost days when analysing recent data of southern Switzerland. This could be relevant for vernalisation. Porter and Gawith  reported the optimal temperature for vernalisation process of winter wheat is between 3.8 and 6.0 °C, while in this study 2.5 °C  was taken to define cold days. Further regional adopted climate evaluations have to take care of optimal parameters. Under current conditions, 32 % (DH) to 36 % (OS) of the precipitation within the growing period comes during the main growing period from beginning of hydrological summer to harvest date. We observed a distinct shift of the precipitation towards the period in which the wheat plant does not require a lot of water (sowing until 1 March).
Conclusion and outlook
It became clear that there is a relevant difference comparing the status quo with current climate projections for the NPG. We found clear indications that the available precipitation during main growing period of winter wheat will decrease. Effects on yield have to be investigated using an appropriated plant soil model. While total annual rainfall does not change significantly a strong shift towards winter precipitation becomes evident. Possible consequences (e.g. nutrient leaching, erosion, need of introduction of catch crops) have to be evaluated in further studies.
NS developed the design of the model and the study in total, evaluated the results and drafted the manuscript. JH participated in the study, coordinated and helped to draft the manuscript. MS participated in the design of the study and performed R coding. All authors read and approved the final manuscript.
This project was supported by the German Ministry of Research (BMBF). Project: NaLaMa-nT, FKZ 033L029. The PIK (Potsdam Institute for Climate Impact Research) is gratefully acknowledged for providing the climate data.
The authors declare that they have no competing interests.
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