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Stratonovitch, P., & Semenov, M. A. (2015). Heat tolerance around flowering in wheat identified as a key trait for increased yield potential in Europe under climate change. J. Experim. Bot., 66(12), 3599–3609.
Abstract: To deliver food security for the 9 billon population in 2050, a 70% increase in world food supply will be required. Projected climatic and environmental changes emphasize the need for breeding strategies that delivers both a substantial increase in yield potential and resilience to extreme weather events such as heat waves, late frost, and drought. Heat stress around sensitive stages of wheat development has been identified as a possible threat to wheat production in Europe. However, no estimates have been made to assess yield losses due to increased frequency and magnitude of heat stress under climate change. Using existing experimental data, the Sirius wheat model was refined by incorporating the effects of extreme temperature during flowering and grain filling on accelerated leaf senescence, grain number, and grain weight. This allowed us, for the first time, to quantify yield losses resulting from heat stress under climate change. The model was used to optimize wheat ideotypes for CMIP5-based climate scenarios for 2050 at six sites in Europe with diverse climates. The yield potential for heat-tolerant ideotypes can be substantially increased in the future (e.g. by 80% at Seville, 100% at Debrecen) compared with the current cultivars by selecting an optimal combination of wheat traits, e.g. optimal phenology and extended duration of grain filling. However, at two sites, Seville and Debrecen, the grain yields of heat-sensitive ideotypes were substantially lower (by 54% and 16%) and more variable compared with heat-tolerant ideotypes, because the extended grain filling required for the increased yield potential was in conflict with episodes of high temperature during flowering and grain filling. Despite much earlier flowering at these sites, the risk of heat stress affecting yields of heat-sensitive ideotypes remained high. Therefore, heat tolerance in wheat is likely to become a key trait for increased yield potential and yield stability in southern Europe in the future.
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Zhai, R., & Tao, F. (2017). Contributions of climate change and human activities to runoff change in seven typical catchments across China. Sci. Tot. Environ., 605, 219–229.
Abstract: Climate change and human activities are two major factors affecting water resource change. It is important to understand the roles of the major factors in affecting runoff change in different basins for watershed management. Here, we investigated the trends in climate and runoff in seven typical catchments in seven basins across China from 1961 to 2014. Then we attributed the runoff change to climate change and human activities in each catchment and in three time periods (1980s, 1990s and 2000s), using the VIC model and long-term runoff observation data. During 1961-2014, temperature increased significantly, while the trends in precipitation were insignificant in most of the catchments and inconsistent among the catchments. The runoff in most of the catchments showed a decreasing trend except the Yingluoxia catchment in the northwestern China. The contributions of climate change and human activities to runoff change varied in different catchments and time periods. In the 1980s, climate change contributed more to runoff change than human activities, which was 84%, 59%,-66%,-50%, 59%, 94%, and -59% in the Nianzishan, Yingluoxia, Xiahui, Yangjiaping, Sanjiangkou, Xixian, and Changle catchment, respectively. After that, human activities had played a more essential role in runoff change. In the 1990s and 2000s, human activities contributed more to runoff change than in the 1980s. The contribution by human activities accounted for 84%,- 68%, and 67% in the Yingluoxia, Xiahui, and Sanjiangkou catchment, respectively, in the 1990s; and -96%,-67%,-94%, and -142% in the Nianzishan, Yangjiaping, Xixian, and Changle catchment, respectively, in the 2000s. It is also noted that after 2000 human activities caused decrease in runoff in all catchments except the Yingluoxia. Our findings highlight that the effects of human activities, such as increase in water withdrawal, land use/cover change, operation of dams and reservoirs, should be well managed. (C) 2017 Elsevier B.V. All rights reserved.
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Doro, L., Jones, C., Williams, J. R., Norfleet, M. L., Izaurralde, R. C., Wang, X., et al. (2017). The Variable Saturation Hydraulic Conductivity Method for Improving Soil Water Content Simulation in EPIC and APEX Models. Vadose Zone Journal, 16(13).
Abstract: Soil water percolation is a key process in the life cycle of water in fields, watersheds, and river basins. The Environmental Policy Integrated Climate (EPIC) and the Agricultural Policy/Environmental eXtender (APEX) are continuous models developed for evaluating the environmental effects of agricultural management. Traditionally, these models have simulated soil water percolation processes using a tipping-bucket approach, with the rate of flow limited by the saturated hydraulic conductivity. This simple approach often leads to inaccuracy in simulating elevated soil water conditions where soil water content (SWC) levels may remain above field capacity under prolonged wet weather periods or limited drainage. To overcome this deficiency, a new sub-model, the variable saturation hydraulic conductivity (VSHC) method, was developed for simulating soil water percolation processes using a nonlinear equation to estimate the effective hydraulic conductivity as a function of the SWC and soil properties. The VSHC method was evaluated at three sites in the United States and two sites in Europe. In addition, a numerical solution of the Richards equation was used as a benchmark for SWC comparison. Results show that the VSHC method substantially improves the accuracy of the SWC simulation in long-term simulations, particularly during wet periods. At the watershed scale, results on the Riesel Y2 watershed indicate that the VSHC method enhances model performance in the high-flow regime of channel peak flows because of the improved estimation of SWC, which implies that the improved SWC simulation at the field scale is beneficial to hydrologic modeling at the watershed scale.
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Vilvert, E., Lana, M., Zander, P., & Sieber, S. (2018). Multi-model approach for assessing the sunflower food value chain in Tanzania. Agric. Syst., 159, 103–110.
Abstract: Sunflower is one of the major oilseeds produced in Tanzania, but due to insufficient domestic production more than half of the country’s demand is imported. The improvement of the sunflower food value chain (FVC) understanding is important to ensure an increase in the production, availability, and quality of edible oil. In order to analyse causes and propose solutions to increase the production of sunflower oil, a conceptual framework that proposes the combined use of different models to provide insights about the sunflower FVC was developed. This research focus on the identification of agricultural models that can provide a better understanding of the sunflower FVC in Tanzania, especially within the context of food security improvement. A FVC scheme was designed considering the main steps of sunflower production. Thereafter, relevant models were selected and placed along each step of the FVC. As result, the sunflower FVC model in Tanzania is organized in five steps, namely (1) natural resources; (2) crop production; (3) oil processing; (4) trade; and (5) consumption. Step 1 uses environmental indicators to analyse soil parameters on soil-water models (SWAT, LPJmL, APSIM or CroSyst), with outputs providing data for step 2 of the FVC. In the production step, data from step 1, together with other inputs, is used to run crop models (DSSAT, HERMES, MONICA, STICS, EPIC or AquaCrop) that analyse the impact on sunflower yields. Thereafter, outputs from crop models serve as input for bio-economic farm models (FSSIM or MODAM) to estimate production costs and farm income by optimizing resource allocation planning for step 2. In addition, outputs from crop models are used as inputs for macro-economic models (GTAP, MAGNET or MagPie) by adjusting supply functions and environmental impacts within steps 3, 4, and 5. These models simulate supply and demand, including the processing of products to determine prices and trade volumes at market equilibrium. In turn, these data is used by bio-economic farm models to assess sunflower returns for different farm types and agro-environmental conditions. Due to the large variety of models, it is possible to assess significant parts of the FVC, reducing the need to make assumptions, while improving the understanding of the FVC.
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Biewald, A., Rolinski, S., Lotze-Campen, H., Schmitz, C., & Dietrich, J. P. (2014). Valuing the impact of trade on local blue water. Ecol. Econ., 101, 43–53.
Abstract: International trade of agricultural goods impacts local water scarcity. By quantifying the effect of trade on crop production on grid-cell level and combining it with cell- and crop-specific virtual water contents, we are able to determine green and blue water consumption and savings. Connecting the information on trade-related blue water usage to water shadow prices gives us the possibility to value the impact of international food crop trade on local blue water resources. To determine the trade-related value of the blue water usage, we employ two models: first, an economic land- and water-use model, simulating agricultural trade, production and water-shadow prices and second, a global vegetation and agricultural model, modeling the blue and green virtual water content of the traded crops. Our study found that globally, the international trade of food crops saves blue water worth 2.4 billion US$. This net saving occurs despite the fact that Europe exports virtual blue water in food crops worth 3.1 billion US$. Countries in the Middle East and South Asia profit from trade by importing water intensive crops, countries in Southern Europe on the other hand export water intensive agricultural goods from water scarce sites, deteriorating local water scarcity. (C) 2014 Elsevier B.V. All rights reserved.
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