1. Wilfried Mirschel, Ralf Wieland, Karin Luzi
Simulated additional crop yields due to irrigation of agricultural fields throughout Brandenburg, Germany, for
- Оценка допольнителного урожая сельско-хозяйственных культур из-за орошения для пашни земли Бранденбурга за 1975 – 2075 годы -
Wilfried Mirschel, Ralf Wieland, Karin Luzi
Leibniz-Centre for Agricultural Landscape Research (ZALF), Institute of Landscape Systems Analysis, Eberswalder Str. 84, D Müncheberg, Germany;

2. Content 1. Introduction and aim 2. Methodology
● ZUWABE - model for spatial irrigation water demand and additional yield due to irrigation
● Input map information
● Simulation tool
3. Assumptions for scenario simulations
4. Results for Brandenburg
● Climate changes
● Irrigation water demand between 1975 and 2075
● Additional yield due to irrigation between 1975 and 2075
5. Conclusions

3. Introduction and aim (1)
Climate change is going on with increasing temperatures especially during winter and decreasing precipitation amounts during the main growing season of crops.
In Brandenburg there are low annual precipitation sums today already
Brandenburg
Annual precipitation for Germany
(source: DWD, Offenbach)

4. Introduction and aim (2)
Federal state of Brandenburg:
+ temperature increase up to 2100: > 4 K
+ annual precipitation in 2100: < 450 mm
+ annual climatic water balance in 2100: < mm
+ soil: - mainly morainic sand (diluvial sand) with low soil water capacity
- low soil quality index
Situation for agriculture in future:
+ limitations in plant available water during spring and summer months
+ increase of cropping risk (especially for spring crops)
+ decrease of crop yields and yield stability
Most effective adaptation measure of agriculture to climate change is the irrigation (!), using ground water, surface water and cleaned waste water
But attention !
Irrigation in agriculture must be in accordance with the regional water availability and the landscape water balance.

5. Introduction and aim (3)
For development of climate adaptation strategies in agriculture on a regional scale better information about long-term effects of irrigation water demands of agricultural crops are necessary.
The usage of well validated models for crop yield and irrigation water demand in agriculture is the only possibility for assessing the impact of climate change on irrigation water demand.
For the climate change impact assessment on spatial scale regional models with an intermediate complexity (REMICs) are favoured which are robust and solid, and which have realistic input data demands in space and time.
For the regional assessment of irrigation water demand on arable land in different regions of Brandenburg the statistical based model ZUWABE (ZUsatzWAsserBEdarf) - a REMICs model - was developed.

6. Introduction and aim (4)
At present in the Federal State of Brandenburg only 2.6 % of arable land are irrigated, i.e. vegetables, potatoes, sugar beet, silage maize, winter wheat, fodder plants.
In future the arable land irrigated will be increase significantly.
The aim of this contribution is to estimate the additional yield due to irrigation for different agricultural crops for all arable land in Brandenburg.
Distribution of soil quality-based productivity classes in Brandenburg (source: GEMDAT)

7. - IRRIWATER - statistical based model for irrigation water demand -
Methodology (1)
- IRRIWATER - statistical based model for irrigation water demand -
ZUWABE
IWDCrSi – crop-specific irrigation water demand (mm)
CR – agricultural crop
IP – crop-specific irrigation period
IWBCrSi – crop- and site-specific irrigation water benchmark according to Roth (1993)
PrIP(LL) – precipitation average ( ) for the East German lowlands, calculated for IP
PrIP(SS) – precipitation average ( ) for the concrete site, calculated for IP
CWB – 30-year average of climatic water balance for
CWB30ySP – 30-year average of climatic water balance for concrete simulation period
CO2 – atmospheric CO2-content (ppm)
FCO2 – factor for CO2-induced reduction of plant transpiration

8. - IRRIWATER - statistical based model for irrigation water demand -
Methodology (2)
- IRRIWATER - statistical based model for irrigation water demand -
Irrigation water benchmark (IWBCrSi; mm)
Soils: D – diluvial, V – weathered, Al – alluvial, Lö – loess, K – tip; t – clayey, l - loamy

9. - IRRIWATER - statistical based model for irrigation water demand -
Methodology (3)
- IRRIWATER - statistical based model for irrigation water demand -
Climatic water balance (CWB, mm)
N – precipitation (mm), G – global radiation (J m-2), C – constant (=30 near the Baltic Sea, = 93 in land), T – temperature (°C)
Influence of atmospheric CO2 content on irrigation water demand
Data source: Free Air Carbon Enrichmenten (FACE) experiment, Braunschweig

10. - IRRIWATER - statistical based model for irrigation water demand -
Methodology (4)
- IRRIWATER - statistical based model for irrigation water demand -
Additional crop yield due to Irrigation (YIrri)

11. - Input map information for Brandenburg - Site type for arable land
Methodology (5)
- Input map information for Brandenburg -
Productivity classes
Soil quality-based productivity classes (source: GEMDAT)
Site type for arable land

12. YIELDSTAT – Interactive Software
Methodology (6)
- Simulation tool -
Maps
YIELDSTAT – Interactive Software
Soil index
Altitude
Data base (Weather/Climate, Parameter, Management)
Hydromorphy
Climate zoning
Soil type
Model
YIELDSTAT
Szenario simulations for winter wheat in 2075
Additional crop yield
Irrigation water demand
IRRIWAT

13. Assumptions for climate scenario simulations
Climate data:
+ Global Climate Model ECHAM5/MPI – OM (MPI Hamburg, Germany)
+ SRES IPCC emission szenario A1B
(economic growth, population increase up to 2050 then decrease, using different sources of energy)
+ Climate data regionalisation: WETTREG 2010 with 100 equiprobabli realizations
+ Realizations taken into account, №´s: 0,11, 22, 33, 44, 55, 66, 77, 88, 99
+ Climate data taken from the DWD-station Potsdam
Climate levels taken into account:
+ 1975, 2000, 2025, 2050, 2075
Agro-management:
+ recent crop rotations for all simulation periods
+ conventional soil tillage with plough for all simulation periods
+ only winter wheat as precrop
+ crops with irrigation: winter wheat, winter barley, winter rye, oat, spring barley, triticale, winter rape, sugar beet, potatoes, silage maize, alfalfa-grass-mix, clover-grass-mix
+ dry matter content of extra crop yields: 86% (cereals), 91% (winter rape), 28% (silage maize)

14. Results for Brandenburg (1)
- Climate changes for WETTREG (A1B), DWD station Potsdam -
Annual average temperature
circa K
Annual precipitation
circa mm
(WETTREG 2010, emission szenario: A1B)

15. Results for Brandenburg (2)
- Climate changes for WETTREG (A1B), DWD station Potsdam -
Climatic water balance
circa mm
Length of vegetation period
circa 115 days longer
(WETTREG 2010, emission szenario: A1B)

16. Results for Brandenburg (3)
- Irrigation water demand averaged for Brandenburg -

17. Results for Brandenburg (4)
- Irrigation induced extra yield averaged for Brandenburg -

18. Results for Brandenburg (5)
- Irrigation water demand for soil quality-based productivity areas -
Productivity areas
Irrigationn water demand [mm]
Potatoes
Clover-grass
Silage maize
Winter barley
Winter rape
Winter wheat
Sugar beets
Potatoes
Clover-grass
Silage maize
Winter barley
Winter rape
Winter wheat
Sugar beets
Potatoes
Clover-grass
Silage maize
Winter barley
Winter rape
Winter wheat
Sugar beets
Potatoes
Clover-grass
Silage maize
Winter barley
Winter rape
Winter wheat
Sugar beets
Potatoes
Clover-grass
Silage maize
Winter barley
Winter rape
Winter wheat
Sugar beets

19. Results for Brandenburg (6)
- Additional crop yield due to irrigation for soil quality-based productivity areas -
Productivity areas
Additional crop yield due to irrigation [dt ha-1]
Potatoes
Clover-grass
Silage maize
Winter barley
Winter rape
Winter wheat
Sugar beets
Potatoes
Clover-grass
Silage maize
Winter barley
Winter rape
Winter wheat
Sugar beets
Potatoes
Clover-grass
Silage maize
Winter barley
Winter rape
Winter wheat
Sugar beets
Potatoes
Clover-grass
Silage maize
Winter barley
Winter rape
Winter wheat
Sugar beets
Potatoes
Clover-grass
Silage maize
Winter barley
Winter rape
Winter wheat
Sugar beets

20. Results for Brandenburg (7)
- Winter wheat -
Irrigation water demand (mm)
62 mm
116 mm
Additional crop yield due to irrigation (dt ha-1)
9.3 dt ha-1
17.5 dt ha -1

21. Results for Brandenburg (8)
- Sugar beet -
Irrigation water demand (mm)
53 mm
161 mm
Additional crop yield due to irrigation (dt ha-1)
50 dt ha-1
153 dt ha -1

22. Results for Brandenburg (9)
- Potatoes -
Irrigation water demand (mm)
74 mm
102 mm
Additional crop yield due to irrigation (dt ha-1)
74 dt ha-1
102 dt ha -1

23. Results for Brandenburg (10)
- Silage maize -
Irrigation water demand (mm)
72 mm
220 mm
Additional crop yield due to irrigation (dt ha-1)
87 dt ha-1
264 dt ha -1

24. Conclusions (1)
Climate change is going on especially also in Brandenburg
 Long-term measurements and climate data show:
+ a continuously increase of annual temperature
+ a decrease in annual precipitation
+ an increase in climatic water balance deficit
+ a longer vegetation period up to 115 days in 2100
For stabile crop yields under climate change irrigation will be an important adaptation measure of agriculture. Up to 2075 the irrigation water demand will increase significantly but with big differences within the arable land of Brandenburg.
Compared to the irrigation water demand at present it will be increase significantly in Brandneburg up to 2075 – for winter wheat in average by 50 mm (in all: 116 mm), for spring barley by 37 mm (in all: 93 mm), for sugar beet by 96 mm (in all: 161 mm) and for silage maize by 130 mm (in all: 220 mm). Within Brandenburg there will be big differences.
Variations of irrigation water demand and additional crop yield due to irrigation between years will increase up to 2075.
The additional crop yields due to irrigation also will increase – for winter wheat in average by 0.8 t ha-1 (in all by 1.8 t ha-1), for spring barley by 0.6 t ha-1 (in all by 1.4 t ha-1), for sugar beets by 9.1 t ha-1 (in all by 15.3 t ha-1) and for silage maize by 15.6 t ha-1 (in all by 26.4 t ha-1)
Actions for regional water storage as prerequisit for an expansion of the irrigation area should be more in focus of attention.

25. „Не так важно предсказать будущее точно – важнее быть подготовленным для будущего”
(„It is not a matter of correctly predicting the future, but of being prepared for it”)
Периклес, греческий политический деятель (500 до н.э.)

26. Спасибо Вам за внимание !