The 2018 drought in Sweden prompted questions about climate-adaptation and -mitigation measures – especially in the agricultural sector, which suffered the most. This study applies a water–food–energy nexus modelling framework to evaluate drought impacts on irrigation and agriculture in Sweden using 2018 and 2019 as case studies. A previous water–food–energy nexus model was updated to facilitate an investigation of the benefits of data-driven irrigation scheduling as compared to existing irrigation guidelines. Moreover, the benefits of assimilating earth observation data in the crop model have been explored. The assimilation of leaf area index data from the Copernicus Global Land Service improves the crop yield estimation as compared to default crop model parameters. The results show that the irrigation water productivities of the proposed model are measurably improved compared to conventional and static irrigation guidelines for both 2018 and 2019. This is mostly due to the advantage of the proposed model in providing evapotranspiration in cultural condition (ET_c)-driven guidelines by using spatially explicit data generated by mesoscale models from the Swedish Meteorological and Hydrological Institute. During the drought year 2018, the developed model showed no irrigation water savings as compared to irrigation scenarios based on conventional irrigation guidelines. Nevertheless, the crop yield increase from the proposed irrigation management system varied between 10% and 60% as compared to conventional irrigation scenarios. During a normal year, the proposed irrigation management system leads to significant water savings as compared to conventional irrigation guidelines. The modelling results show that temperature stress during the 2018 drought also played a key role in reducing crop yields, with yield reductions of up to 30%. From a water–food–energy nexus, this motivates the implementation of new technologies to reduce water and temperature stress to mitigate likely negative effects of climate change and extremes. By using an open-source package for Google Earth®, a demonstrator of cost-effective visualization platform is developed for helping farmers, and water- and energy-management agencies to better understand the connections between water and energy use, and food production. This can be significant, especially during the occurrence of extreme events, but also to adapt to the negative effects on agricultural production of climate changes.

瑞典 2018 年的干旱引发了有关气候适应和减缓措施的问题，尤其是在遭受最严重影响的农业部门。本研究使用 2018 年和 2019 年的案例研究，应用水-食物-能源关系建模框架来评估干旱对瑞典灌溉和农业的影响。更新了之前的水-食物-能源关系模型，以促进调查数据驱动的灌溉调度与现有灌溉指南相比的优势。此外，还探讨了在作物模型中同化地球观测数据的好处。与默认作物模型参数相比，来自哥白尼全球土地服务的叶面积指数数据的同化改进了作物产量估计。等_{_}) 驱动的指南，使用瑞典气象水文研究所的中尺度模型生成的空间显式数据。在 2018 年干旱年，与基于传统灌溉指南的灌溉方案相比，开发的模型显示没有灌溉用水节约。尽管如此，与传统灌溉方案相比，拟议灌溉管理系统的作物产量增加在 10% 到 60% 之间。在正常年份，与传统灌溉指南相比，拟议的灌溉管理系统可显着节水。建模结果表明，2018 年干旱期间的温度胁迫在降低作物产量方面也发挥了关键作用，减产幅度高达 30%。从水-食物-能源的关系中，这促进了新技术的实施，以减少水和温度压力，以减轻气候变化和极端事件可能产生的负面影响。通过使用 Google Earth® 的开源软件包，开发了一个具有成本效益的可视化平台演示器，以帮助农民、水和能源管理机构更好地了解水和能源使用以及粮食生产之间的联系。这可能意义重大，尤其是在极端事件发生期间，还要适应气候变化对农业生产的负面影响。以及水和能源管理机构，以更好地了解水和能源使用以及粮食生产之间的联系。这可能意义重大，尤其是在极端事件发生期间，还要适应气候变化对农业生产的负面影响。以及水和能源管理机构，以更好地了解水和能源使用以及粮食生产之间的联系。这可能意义重大，尤其是在极端事件发生期间，还要适应气候变化对农业生产的负面影响。