Indicator Assessment

Crop water demand

Indicator Assessment

Prod-ID: IND-200-en

Also known as: CLIM 033

Published 20 Dec 2016 Last modified 18 Nov 2021

13 min read

Topics: Climate change adaptation

This page was archived on 18 Nov 2021 with reason: No more updates will be done

Climate change led to an increase in the crop water demand and thus the crop water deficit from 1995 to 2015 in large parts of southern and eastern Europe; a decrease has been estimated for parts of north-western Europe.
The projected increases in temperature will lead to increased evapotranspiration rates, thereby increasing crop water demand across Europe. This increase may partly be alleviated through reduced transpiration at higher atmospheric CO₂ levels.
The impact of increasing water requirements is expected to be most acute in southern and central Europe, where the crop water deficit and irrigation requirements are projected to increase. This may lead to an expansion of irrigation systems, even in regions currently without irrigation systems. However, this expansion may be constrained by projected reductions in water availability and increased demand from other sectors and for other uses.

Fig. 1: Trend in crop water deficit of grain maize during the growing season

Note: Annual rate of change of the crop water deficit of grain maize during the growing season for the period 1985-2014 in Europe. The crop water deficit is the difference between the crop-specific water requirement (in this case grain maize) and available water through precipitation. The simulation is based on the JRC-MARS gridded meteorological data at 25 km resolution. Red colours show an increase of the gap between crop water requirement and the available water, blue colours indicate a reduction of the deficit. Areas where the seasonal crop water requirement exceeds regularly (i.e. in more than 90 % of the years) the available water (through precipitation) have been marked by hatches. Areas without hatches experience both deficit and surplus or only a surplus of water in their crop water balance. In this case, red colours refer to a reduced surplus, while blue colours indicate an increasing surplus of available water.

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Fig. 2: Projected annual rate of change of the crop water deficit of grain maize during the growing season in Europe for the period 2015-2045 for two climate scenarios.

Projected annual rate of change of the crop water deficit of grain maize during the growing season in Europe for the period 2015-2045 for two climate scenarios.

Note: Projected annual rate of change of the crop water deficit of grain maize during the growing season in Europe for the period 2015-2045 for two climate scenarios. The crop water deficit is the difference between the crop-specific water requirement (in this case grain maize) and the water available through precipitation. The climate forcing of the two simulations is based on the two global climate models HadGEM2 and MIROC, taken from CMIP5 and bias-corrected by the ISI-MIP project (Warszawski et al., 2014). Crop model simulations have been done with the crop model WOFOST at 25 km resolution. Red colours show an increase of the gap between crop water requirement and water availability, blue colours indicate a reduction of the deficit. Areas where the seasonal crop water requirement exceeds regularly (i.e. in more than 90 % of the years) the water available through precipitation have been marked by hatches. Areas without hatches experience both deficit and surplus or only a surplus of water. In this case, red colours refer to a reduced surplus, while blue colours indicate an increasing surplus of water.

Data source:

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Past trends

Irrigation in Europe is currently concentrated along the Mediterranean, where in some countries more than 80 % of the total freshwater abstraction is used for agricultural purposes [i]. However, consistent observations of water demand and consumption for agriculture do not currently exist for Europe, partly because of unrecorded water abstractions and national differences in accounting and reporting. Modelling approaches can be used to compute net irrigation requirements. Two studies estimated the net irrigation requirements in Europe for 1995–2002 and for the year 2000 with a total of three different model systems [ii]. The results show an irrigation requirement of up to 21–40 km³ for Spain, which had the highest net irrigation requirement in the EU-27.

Crop water demand, defined as the water consumed during the growing season, depends on the crop type and the timing of the growing season. Water demand can be modelled using meteorological data and information on crop management, and the difference between crop water demand and rainfall constitutes the crop water deficit. Figure 1 shows the change in the crop water deficit for grain maize, which is a crop that is often grown under irrigated conditions because it is mostly grown during the summer season. The hatched areas in Figure 1 show the areas where crop water demand exceeds average rainfall and thus may have an irrigation demand. The trends for 1995–2015 show an increase in the crop water deficit for maize in large parts of southern and eastern Europe; a decrease has been estimated for parts of north-western Europe.

Some of the effects of estimated changes in the crop water deficit may also be related to the duration of the crop growing period, which is shortened under higher temperatures, thus leading to less water being consumed.

Projections

A multi-model study using seven global hydrological models driven by five global climate models under four RCP scenarios estimated changes in irrigation water demand (IWD) across regions during the 21st century. Under the low and low-to-medium emissions scenarios (RCP2.6 and RCP4.5, respectively), the simulated changes in IWD across Europe were small. For RCP6.0, the multi-model average suggests a substantial increase in IWD in most of Europe. For RCP8.5, the projected increase in IWD exceeds 25 % in most of the irrigated regions in Europe [iii]. Most hydrological models in this multi-model study did not consider the physiological effect of increased CO₂, which can increase the water-use efficiency of crop plants. The only available study using a hydrological and a crop model that considers the physiological effect of increased CO₂ still estimates that there is a high likelihood that IWD in southern Europe will increase by more than 20 % until 2080 [iv]. Regional case studies suggest much higher increases in IWD in some regions [v].

Climate change will also affect water availability. The Mediterranean area is projected to experience a decline in water availability, and future irrigation will be constrained by reduced run-off and groundwater resources, by demand from other sectors and by economic costs [vi]. Assuming that urban water demands would be prioritised over agricultural purposes, the proportional reduction of water availability for irrigation in many European basins is larger than the reduction in annual run-off [vii].

The projected changes in the crop water deficit for grain maize are shown in Figure 2 for two different climate models. The simulations are based on the WOFOST crop model, which considers the effect of increases in the CO₂ concentrations on the water use efficiency of maize. The simulations for both climate model projections for the 2030s show an increasing crop water deficit for large areas of Europe, in particular over central Europe. This will increase the water requirement for irrigation, including in areas not currently applying irrigation.

Adaptation measures and the integrated management of water, often at catchment scale, are needed to address future competing demands for water between agriculture, energy, conservation and human settlements. New irrigation infrastructure will be required in some regions [viii].

[i] EEA, ‘Water Resources across Europe — Confronting Water Scarcity and Drought’, EEA Report (European Environment Agency, 2009), http://www.eea.europa.eu/publications/water-resources-across-europe.

[ii] Gunter Wriedt et al., ‘Estimating Irrigation Water Requirements in Europe’,Journal of Hydrology 373, no. 3–4 (15 July 2009): 527–44, doi:10.1016/j.jhydrol.2009.05.018; T. aus der Beek et al., ‘Modelling Historical and Current Irrigation Water Demand on the Continental Scale: Europe’,Advances in Geosciences 27 (7 September 2010): 79–85, doi:10.5194/adgeo-27-79-2010.

[iii] Yoshihide Wada et al., ‘Multimodel Projections and Uncertainties of Irrigation Water Demand under Climate Change’,Geophysical Research Letters 40, no. 17 (16 September 2013): 4626–32, doi:10.1002/grl.50686.

[iv] Markus Konzmann, Dieter Gerten, and Jens Heinke, ‘Climate Impacts on Global Irrigation Requirements under 19 GCMs, Simulated with a Vegetation and Hydrology Model’,Hydrological Sciences Journal 58, no. 1 (2013): 88–105, doi:10.1080/02626667.2013.746495.

[v] R. Savé et al., ‘Potential Changes in Irrigation Requirements and Phenology of Maize, Apple Trees and Alfalfa under Global Change Conditions in Fluvià Watershed during XXIst Century: Results from a Modeling Approximation to Watershed-Level Water Balance’,Agricultural Water Management 114 (November 2012): 78–87, doi:10.1016/j.agwat.2012.07.006.

[vi] J.E. Olesen et al., ‘Impacts and Adaptation of European Crop Production Systems to Climate Change’,European Journal of Agronomy 34, no. 2 (February 2011): 96–112, doi:10.1016/j.eja.2010.11.003.

[vii] Ana Iglesias et al., ‘Water and People: Assessing Policy Priorities for Climate Change Adaptation in the Mediterranean’, inRegional Assessment of Climate Change in the Mediterranean, ed. Antonio Navarra and Laurence Tubiana, Advances in Global Change Research 51 (Dordrecht: Springer, 2013), 201–33, http://link.springer.com/chapter/10.1007/978-94-007-5772-1_11.

[viii] Marijn van der Velde, Gunter Wriedt, and Fayçal Bouraoui, ‘Estimating Irrigation Use and Effects on Maize Yield during the 2003 Heatwave in France’,Agriculture, Ecosystems & Environment 135, no. 1–2 (1 January 2010): 90–97, doi:10.1016/j.agee.2009.08.017.

Supporting information

Indicator definition

Trend in crop water deficit for grain maize during the growing period
Projected change in the crop water deficit for grain maize during the growing period

Units

Change in water deficit (m³/ha/a)

Rationale

Justification for indicator selection

Water is essential for plant growth and there is a relationship between plant biomass production and transpiration, with water-use efficiency (biomass production per unit of water transpired) being affected by crop species and management. The increasing atmospheric CO₂ concentration will lead to higher water-use efficiency through reductions in plant transpiration and increased photosynthesis. However, higher temperatures and lower relative humidity will lead to higher evaporative demands, which will reduce water-use efficiency. The resulting effect of climate change on water-use efficiency will therefore be the result of a combination of changes in climate and atmospheric CO₂ concentration, as well as changes in crop choice and management. The water demand by crops must be met through rainfall during the growing period, soil water storage or irrigation. In drought-prone areas, increasing demands for water by industrial and urban users intensify the competition for irrigation water, and managing this requires an integrated approach.

Scientific references

IPCC, 2014a: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1132 pp.
IPCC, 2014c: Europe. Kovats, R.S., R. Valentini, L.M. Bouwer, E. Georgopoulou, D. Jacob, E. Martin, M. Rounsevell, and J.-F. Soussana, 2014: Europe. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Barros, V.R., C.B. Field, D.J. Dokken, M.D. Mastrandrea, K.J. Mach, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1267-1326.

Policy context and targets

Context description

In April 2013, the European Commission (EC) presented the EU Adaptation Strategy Package. This package consists of the EU Strategy on adaptation to climate change (COM/2013/216 final) and a number of supporting documents. The overall aim of the EU Adaptation Strategy is to contribute to a more climate-resilient Europe.

One of the objectives of the EU Adaptation Strategy is Better informed decision-making, which will be achieved by bridging the knowledge gap and further developing the European climate adaptation platform (Climate-ADAPT) as the ‘one-stop shop’ for adaptation information in Europe. Climate-ADAPT has been developed jointly by the EC and the EEA to share knowledge on (1) observed and projected climate change and its impacts on environmental and social systems and on human health, (2) relevant research, (3) EU, transnational, national and subnational adaptation strategies and plans, and (4) adaptation case studies.

Further objectives include Promoting adaptation in key vulnerable sectors through climate-proofing EU sector policies and Promoting action by Member States. Most EU Member States have already adopted national adaptation strategies and many have also prepared action plans on climate change adaptation. The EC also supports adaptation in cities through the Covenant of Mayors for Climate and Energy initiative.

In September 2016, the EC presented an indicative roadmap for the evaluation of the EU Adaptation Strategy by 2018.

In November 2013, the European Parliament and the European Council adopted the 7^th EU Environment Action Programme (7^th EAP) to 2020, ‘Living well, within the limits of our planet’. The 7^th EAP is intended to help guide EU action on environment and climate change up to and beyond 2020. It highlights that ‘Action to mitigate and adapt to climate change will increase the resilience of the Union’s economy and society, while stimulating innovation and protecting the Union’s natural resources.’ Consequently, several priority objectives of the 7^th EAP refer to climate change adaptation.

Targets

No targets have been specified.

Methodology

Methodology for indicator calculation

The crop water deficit is the difference between the crop-specific water requirement (in this case grain maize) and available water through precipitation. The hindcast simulation is based on the Agri4Cast gridded meteorological dataset at 25 km resolution.

The projected changes in the crop water deficit for grain maize have been simulated using two different global climate models (HadGEM2 and MIROC). These delivered input data to the WOFOST (WOrld FOod STudies) crop model, which considers the effect of increases in the CO₂ concentrations on the water use efficiency of maize. The WOFOST model is maintained and further developed by Wageningen Environmental Research (Alterra) in co-operation with the Plant Production Systems Group of Wageningen University & Research and the Agri4Cast unit of the Joint Research Centre.

Methodology for gap filling

Not applicable

Methodology references

Biavetti et al. (2014): European meteorological data: contribution to research, development, and policy support. Irene Biavetti, Sotiris Karetsos, Andrej Ceglar, Andrea Toreti and Panos Panagos: ’European meteorological data: contribution to research, development, and policy support’, Proc. SPIE 9229, Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 922907 (August 12, 2014); doi:10.1117/12.2066286
Documentation WOFOST. Wageningen University and Research, 2016.

Uncertainties

Methodology uncertainty

Not applicable

Data sets uncertainty

Crop yield and crop requirements for irrigation are affected not only by climate change, but also by management and a range of socio-economic factors. The effects of climate change on these factors therefore have to be estimated indirectly using agrometeorological indicators and through statistical analyses of the interaction between climatic variables and factors such as crop yield (Caubel et al., 2015).

The projections of climate change impacts and adaptation in agriculture rely heavily on modelling, and it needs to be recognised that there is often a chain of uncertainty involved in the projections, which range from emissions scenarios, through climate modelling and downscaling, to assessments of impacts using an impact model The extent of all these uncertainties is rarely quantified, even though some studies have assessed uncertainties related to individual components. The crop modelling community has only recently started addressing uncertainties related to modelling impacts of climate change on crop yield and the effect of possible adaptation options. Recently, the effects of extreme climate events have also been included in impact assessments, but other effects such as those related to biotic hazards (e.g. pests and diseases) still need to be explored.