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Kersebaum, K. C., & Nendel, C. (2014). Site-specific impacts of climate change on wheat production across regions of Germany using different CO2 response functions. European Journal of Agronomy, 52, 22–32.
Abstract: Impact of climate change on crop growth, groundwater recharge and nitrogen leaching in winter wheat production in Germany was assessed using the agro-ecosystem model HERMES with a downscaled (WETTREG) climate change scenario A1B from the ECHAM5 global circulation model. Three alternative algorithms describing the impact of atmospheric CO2 concentration on crop growth (a simple Farquhar-type algorithm, a combined light-use efficiency – maximum assimilation approach and a simple scaling of the maximum assimilation rate) in combination with a Penman-Monteith approach which includes a simple stomata conduction model for evapotranspiration under changing CO2 concentrations were compared within the framework of the HERMES model. The effect of differences in regional climate change, site conditions and different CO2 algorithms on winter wheat yield, groundwater recharge and nitrogen leaching was assessed in 22 regional simulation case studies across Germany. Results indicate that the effects of climate change on wheat production will vary across Germany due to different regional expressions of climate change projection. Predicted yield changes between the reference period (1961-1990) and a future period (2021-2050) range from -0.4 t ha(-1), -0.8 t ha(-1) and -0.6 t ha(-1) at sites in southern Germany to +0.8 t ha(-1), +0.6 t ha(-1) and +0.8 t ha(-1) at coastal regions for the three CO2 algorithms, respectively. On average across all regions, a relative yield change of +0.9%, +3.0%, and +6.0%, respectively, was predicted for Germany. In contrast, a decrease of -11.6% was predicted without the consideration of a CO2 effect. However, simulated yield changes differed even within regions as site conditions had a strong influence on crop growth. Particularly, groundwater-affected sites showed a lower vulnerability to increasing drought risk. Groundwater recharge was estimated to change correspondingly to changes in precipitation. The consideration of the CO2 effect on transpiration in the model led to a prediction of higher rates of annual deep percolation (+16 mm on average across all sites), which was due to higher water-use efficiency of the crops. In contrast to groundwater recharge, simulated nitrogen leaching varied with the choice of the photosynthesis algorithm, predicting a slight reduction in most of the areas. The results underline the necessity of high-resolution data for model-based regional climate change impact assessment and development of adaptation measures. (C) 2013 Elsevier B.V. All rights reserved.
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Zhang, S., Tao, F., & Zhang, Z. (2016). Changes in extreme temperatures and their impacts on rice yields in southern China from 1981 to 2009. Field Crops Research, 189, 43–50.
Abstract: Extreme temperature impacts on field crop are of key concern and increasingly assessed, however the studies have seldom taken into account the automatic adaptations such as shifts in planting dates, phenological dynamics and cultivars. In this present study, trial data on rice phenology, agro-meteorological hazards and yields during 1981-2009 at 120 national agro-meteorological experiment stations were used. The detailed data provide us a unique opportunity to quantify extreme temperature impacts on rice yield more precisely and in a setting with automatic adaptations. In this study, changes in an accumulated thermal index (growing degree day, GDD), a high temperature stress index (>35 degrees C high temperature degree day, HDD), and a cold stress index (<20 degrees C cold degree day, CDD), were firstly investigated. Then, their impacts on rice yield were further quantified by a multivariable analysis. The results showed that in the past three decades, for early rice, late rice and single rice in western part, and single rice in other parts of the middle and lower reaches of Yangtze River, respectively, rice yield increased by 5.83%, 1.71%, 8.73% and 3.49% due to increase in GDD. Rice yield was generally more sensitive to high temperature stress than to cold temperature stress. It decreased by 0.14%, 0.32%, 0.34% and 0.14% due to increase in HDD, by contrast increased by 1.61%, 0.26%, 0.16% and 0.01% due to decrease in CDD, respectively. In addition, decreases in solar radiation reduced rice yield by 0.96%, 0.13%, 9.34% and 6.02%. In the past three decades, the positive impacts of increase in GDD and the negative impacts of decrease in solar radiation played dominant roles in determining overall climate impacts on yield. However, with climate warming in future, the positive impacts of increase in GDD and decrease in CDD will be offset by increase in HDD, resulting in overall negative climate impacts on yield. Our findings highlight the risk of heat stress on rice yield and the importance of developing integrated adaptation strategies to cope with heat stress.
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Tao, F., Zhang, Z., Zhang, S., & Rötter, R. P. (2015). Heat stress impacts on wheat growth and yield were reduced in the Huang-Huai-Hai Plain of China in the past three decades. European Journal of Agronomy, 71, 44–52.
Abstract: Heat stress impacts on crop growth and yield have been investigated by controlled-environment experiments, however little is known about the impacts under field conditions at large spatial and temporal scales, particularly in a setting with farmers’ autonomous adaptations. Here, using detailed experiment Observations at 34 national agricultural meteorological stations spanning from 1981 to 2009 in the Huang-Huai-Hai Plain (HHHP) of China, we investigated the changes in climate and heat stress during wheat reproductive growing period (from heading to maturity) and the impacts of climate change and heat stress on reproductive growing duration (RGD) and yield in a setting with farmers’ autonomous adaptations. We found that RGD and growing degree days above 0 degrees C (GDD) from heading to maturity increased, which increased yield by similar to 14.85%, although heat stress had negative impacts on RGD and yield. During 1981-2009, high temperature (>34 degrees C) degree days (HDD) increased in the northern part, however decreased in the middle and southern parts of HHHP due to advances in heading and maturity dates. Change in HDD, together with increase in GDD and decrease in solar radiation (SRD), jointly increased wheat yield in the northern and middle parts but reduced it in the southern part of HHHP. During the study period, increase in GDD and decrease in SRD had larger impacts on yield than change in HDD. However, with climate warming of 2 degrees C, damage of heat stress on yield may offset a large portion of the benefits from increases in RGD and GDD, and eventually result in net negative impacts on yield in the northern part of HHHP. Our study showed that shifts in cultivars and wheat production system dynamics in the past three decades reduced heat stress impacts in the HHHP. The insights into crop response and adaptation to climate change and climate extremes provide excellent evidences and basis for improving climate change impact study and designing adaptation measures for the future. (C) 2015 Elsevier B.V. All rights reserved.
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Toscano, P., Genesio, L., Crisci, A., Vaccari, F. P., Ferrari, E., La Cava, P., et al. (2015). Empirical modelling of regional and national durum wheat quality. Agricultural and Forest Meteorology, 204, 67–78.
Abstract: The production of durum wheat in the Mediterranean basin is expected to experience increased variability in yield and quality as a consequence of climate change. To assess how environmental variables and agronomic practices affect grain protein content (GPC), a novel approach based on monthly gridded input data has been implemented to develop empirical model, and validated on historical time series to assess its capability to reproduce observed spatial and inter-annual GPC variability. The model was applied in four Italian regions and at the whole national scale and proved reliable and usable for operational purposes also in a forecast ‘real-time’ mode before harvesting. Precipitable water during autumn to winter and air temperature from anthesis to harvest were extremely important influences on GPC; these and additional variables, included in a linear model, were able to account for 95% of the variability in GPC that has occurred in the last 15 years in Italy. Our results are a unique example of the use of modelling as a predictive real-time platform and are a useful tool to understand better and forecast the impacts of future climate change projections on durum wheat production and quality.
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Nendel, C., Wieland, R., Mirschel, W., Specka, X., Guddat, C., & Kersebaum, K. C. (2013). Simulating regional winter wheat yields using input data of different spatial resolution. Field Crops Research, 145, 67–77.
Abstract: The success of using agro-ecosystem models for the high-resolution simulation of agricultural yields for larger areas is often hampered by a lack of input data. We investigated the effect of different spatially resolved soil and weather data used as input for the MONICA model on its ability to reproduce winter wheat yields in the Federal State of Thuringia, Germany (16,172 km(2)). The combination of one representative soil and one weather station was insufficient to reproduce the observed mean yield of 6.66 +/- 0.87 t ha(-1) for the federal state. Use of a 100 m x 100 m grid of soil and relief information combined with just one representative weather station yielded a good estimator (7.01 +/- 1.47 t ha(-1)). The soil and relief data grid used in combination with weather information from 14 weather stations in a nearest neighbour approach produced even better results (6.60 +/- 1.37 t ha(-1)); the same grid used with 39 additional rain gauges and an interpolation algorithm that included an altitude correction of temperature data slightly overpredicted the observed mean (7.36 +/- 1.17 t ha(-1)). It was concluded that the apparent success of the first two high-resolution approaches over the latter was based on two effects that cancelled each other out: the calibration of MONICA to match high-yield experimental data and the growth-defining and -limiting effect of weather data that is not representative for large parts of the region. At the county and farm level the MONICA model failed to reproduce the 1992-2010 time series of yields, which is partly explained by the fact that many growth-reducing factors were not considered in the model. (C) 2013 Elsevier B.V. All rights reserved.
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