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Semenov, M. A., & Stratonovitch, P. (2016). Local-scale CMIP5-based climate scenarios for MACSUR2 (Vol. 8).
Abstract: Climate sensitivity of GCMs was used to select 5 GCMs from the CMIP5 ensemble for impact studies in MACSUR2. Selected GCMs for MACSUR2 are EC-EARTH (7), GFDL-CM3 (8) HadGEM2-ES (10), MIROC5 (13), and MPI-ESM-MR (15). These GCMs are evenly distributed among CMIP5 (Fig 1) and should capture, in principal, climate uncertainty of the CMIP5 ensemble. Using 5 GCMs will enable us to assess uncertainties in impacts related to uncertainty in climate projections. The selection of GCMs in MACSUR2 has a good overlap with selections of GCMs used in CORDEX and AgMIP projects. We used the LARS-WG generator to construct local-scale CMIP5-based climate scenarios for Europe (Semenov & Stratonovitch, 2015). Fifteen sites were selected in Europe for MACSUR2. For each site and each selected GCM, 100 yrs climate daily data were generated by LARS-WG for RCP4.5 and RCP8.5 emission scenarios and for baseline and 3 future periods: near-term (2021-2040), mid-term (2041-2060) and long-term (2081-2100).
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Gabaldón-Leal, C., Lorite, I. J., Mínguez, M. I., Lizaso, J. I., Dosio, A., Sanchez, E., et al. (2015). Strategies for adapting maize to climate change and extreme temperatures in Andalusia, Spain. Clim. Res., 65, 159–173.
Abstract: Climate projections indicate that rising temperatures will affect summer crops in the southern Iberian Peninsula. The aim of this study was to obtain projections of the impacts of rising temperatures, and of higher frequency of extreme events on irrigated maize, and to evaluate some adaptation strategies. The study was conducted at several locations in Andalusia using the CERES-Maize crop model, previously calibrated/validated with local experimental datasets. The simulated climate consisted of projections from regional climate models from the ENSEMBLES project; these were corrected for daily temperature and precipitation with regard to the E-OBS observational dataset. These bias-corrected projections were used with the CERES-Maize model to generate future impacts. Crop model results showed a decrease in maize yield by the end of the 21st century from 6 to 20%, a decrease of up to 25% in irrigation water requirements, and an increase in irrigation water productivity of up to 22%, due to earlier maturity dates and stomatal closure caused by CO2 increase. When adaptation strategies combining earlier sowing dates and cultivar changes were considered, impacts were compensated, and maize yield increased up to 14%, compared with the baseline period (1981-2010), with similar reductions in crop irrigation water requirements. Effects of extreme maximum temperatures rose to 40% at the end of the 21st century, compared with the baseline. Adaptation resulted in an overall reduction in extreme T-max damages in all locations, with the exception of Granada, where losses were limited to 8%.
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Siebert, S., Webber, H., Zhao, G., Ewert, F., Siebert, S., Webber, H., et al. (2017). Heat stress is overestimated in climate impact studies for irrigated agriculture. Environ. Res. Lett., 12(5), 054023.
Abstract: Climate change will increase the number and severity of heat waves, and is expected to negatively affect crop yields. Here we show for wheat and maize across Europe that heat stress is considerably reduced by irrigation due to surface cooling for both current and projected future climate. We demonstrate that crop heat stress impact assessments should be based on canopy temperature because simulations with air temperatures measured at standard weather stations cannot reproduce differences in crop heat stress between irrigated and rainfed conditions. Crop heat stress was overestimated on irrigated land when air temperature was used with errors becoming larger with projected climate change. Corresponding errors in mean crop yield calculated across Europe for baseline climate 1984-2013 of 0.2 Mg yr(-1) (2%) and 0.6 Mg yr(-1) (5%) for irrigated winter wheat and irrigated grain maize, respectively, would increase to up to 1.5 Mg yr (1) (16%) for irrigated winter wheat and 4.1 Mg yr (1) (39%) for irrigated grain maize, depending on the climate change projection/GCM combination considered. We conclude that climate change impact assessments for crop heat stress need to account explicitly for the impact of irrigation.
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Dono, G., Cortignani, R., Doro, L., Giraldo, L., Ledda, L., Pasqui, M., et al. (2013). An integrated assessment of the impacts of changing climate variability on agricultural productivity and profitability in an irrigated Mediterranean catchment. Water Resource Manage., 27(10), 3607–3622.
Abstract: Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ETN), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ETN may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy.
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Elsgaard, L., Børgesen, C. D., Olesen, J. E., Siebert, S., Ewert, F., Peltonen-Sainio, P., et al. (2012). Shifts in comparative advantages for maize, oat and wheat cropping under climate change in Europe. Food Addit. Contam. Part A, 29(10), 1514–1526.
Abstract: Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45-65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45-55°N, oat had its maximum at 55-65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops.
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