Water-limited crop productivity

Assessment versions

Published (reviewed and quality assured)

• Water-limited crop productivity (CLIM 032) - Assessment published Nov 2012

Justification for indicator selection

Crop biomass production derives from the capture and conversion of solar energy through the process of photosynthesis. However, this process may be restricted by low (or high) temperatures or by water limitations. A simple index can be used by which the effective annual radiation for plant growth is estimated by summing daily contributions of solar radiation on days with mean temperature above 5 ºC, minimum temperature above 0 ºC and sufficient soil water for supporting crop transpiration. In practice the response depends on soil type that may have large differences in capacity for storing soil moisture and on possibilities for supplementary irrigation. Crop yield also depends on the timing of the crop growth and yield formation. Yields in cereal and oilseed crops respond particularly to the duration of the grain filling period. The impacts of unfavourable meteorological conditions and extreme events vary considerably, depending on the timing of occurrence and the development stage of the crops. Changes in the occurrence of extreme events such as heat waves, droughts, heavy precipitation and floods will greatly affect crop yield leading to increased variability and economic consequences.

Scientific references:

• IPCC, 2007. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 2007; M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson (eds); Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Indicator definition

• Projected changes in effective solar radiation

• Projected changes in water-limited crop yield

• Projected change in water-limited wheat production

Units

• MJ/m²
• %
• tons/NUTS-2 region

Policy context and targets

Context description

Targets

No targets have been specified.

Related policy documents

• Climate-ADAPT: Mainstreaming adaptation in EU sector policies
  Overview of EU sector policies in which mainstreaming of adaptation to climate change is ongoing or explored
• Climate-ADAPT: National adaptation strategies
  Overview of activities of EEA member countries in preparing, developing and implementing adaptation strategies
• DG Climate Action: What is the EU doing about climate change?
  Activities of the EU regarding climate change (both mitigation and adaptation)
• White paper - Adapting to climate change: towards a European framework for action
  EU framework for adaptation to climate change, leading to a comprehensive EU adaptation strategy by 2013

Methodology

Methodology for indicator calculation

Projected changes in effective solar radiation are taken from two climate models, which is an indicator for water limited crop productivity, for the period 2031-2050 compared with 1975-1994 for the KNMI and Hadley Centre (HC) climate model projections under the A1B emission scenario.

The mean relative changes in water-limited crop yield are simulated by the ClimateCrop model for the 2050s compared with 1961–1990 for 12 different climate models projections under the A1B emission scenario. The ClimateCrop model was applied to explore the combined effects of projected changes in temperature, rainfall and CO2 concentration across Europe, considering effects of adaptation. The mean projected changes show a pattern of decreases in yields along the Mediterranean and large increases in Scandinavia. However, throughout large parts of western and central Europe mean changes in crop yields are likely to be small.

The simulated change in water-limited wheat production for 2030 compared with 2000 was estimated for the A1B emission scenario using a cold (ECHAM5) (left) and a warm (HADCM3) (right) climate change projection. The production changes are shown for 25x25 km grids assuming current area of wheat cropping. 

Methodology for gap filling

Not applicable

Methodology references

• Donatelli et al. 2012: Assessing agriculture vulnerabilities for the design of effective measures for adaption to climate change (AVEMAC project) Donatelli, M., Duveiller, G., Fumagalli, D., Srivastava, A., Zucchini, A., Angileri, V., Fasbender, D., Loudjani, P., Kay, S., Juskevicius, V., Toth, T., Haastrup, P., M’barek, R., Espinosa, M., Ciaian, P. and Niemeyer, S., 2012, Assessing agriculture vulnerabilities for the design of effective measures for adaption to climate change (AVEMAC project), European Commission, Joint Research Centre, Luxembourg.
• Iglesias et al. 2011: Looking into the future of agriculture in a changing climate. Iglesias, A., Quiroga, S. and Diz, A. (2011)  European Review of Agricultural Economics 38(3), 427 –447. doi:10.1093/erae/jbr037

Data specifications

EEA data references

• No datasets have been specified here.

External data references

• Assessing agriculture vulnerabilities for the design of effective measures for adaption to climate change (AVEMAC project)
• Looking into the future of agriculture in a changing climate

Data sources in latest figures

Uncertainties

Methodology uncertainty

Not applicable

Data sets uncertainty

Effects of climate change on the growing season and crop phenology can be monitored directly, partly through remote sensing (growing season) and partly through monitoring of specific phenological events such as flowering. There is no common monitoring network for crop phenology in Europe, and data on this therefore has to be based on various national recordings, often from agronomic experiments. Crop yield and crop requirements for irrigation are not only affected 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 between climatic variables and factors such as crop yield.

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 going from emission scenario, through climate modelling, downscaling and 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 effect of possible adaptation options, and so far only few studies have involved livestock systems. Future studies also need to better incorporate effects of extreme climate events as well as biotic hazards (e.g. pests and diseases).

Further information on uncertainties is provided in Section 1.7 of the EEA report on Climate change, impacts, and vulnerability in Europe 2012 (http://www.eea.europa.eu/publications/climate-impacts-and-vulnerability-2012/)

Rationale uncertainty

No uncertainty has been specified