A Systematic Review of Methods for Investigating Climate Change Impacts on Water-Energy-Food Nexus

被引:2
|
作者
Gao, Danyang [1 ]
Chen, Albert S. [1 ]
Memon, Fayyaz Ali [1 ]
机构
[1] Univ Exeter, Ctr Water Syst, Exeter EX4 4QF, England
关键词
PRISMA; Hydrology; Agriculture; Hydropower; Climate change; HYDROPOWER GENERATION; IRRIGATION WATER; DECISION-MAKING; INTEGRATED ASSESSMENT; CROP PRODUCTION; FUTURE CHANGES; GLOBAL FOOD; RIVER-BASIN; LAND-USE; RESOURCES;
D O I
10.1007/s11269-023-03659-x
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Water, energy and food are important for human survival and sustainable development. With climate change, investigating climate change impacts on Water-Energy-Food nexus has been a topic of growing interest in recent years. However, there is a lack of a systematic review of the current state and methodologies of Water-Energy-Food nexus studies under climate change. Here, we review research articles investigating climate change impacts on Water-Food, Water-Energy and Water-Energy-Food nexus over last seven years. The existing methods and tools, spatial scales, and future climate scenarios setting in these articles are summarised and analysed. We found that the analyses methods could be divided into four categories (physics-based modelling, statistical methods, supervised learning and operation optimisation), among them, physics-based modelling accounts for the largest proportion. The reviewed studies cover a range of scales from site scale to global, with most studies focusing on the regional scale. Models used for small to middle scale are mainly related to hydrology and water resource, while large-scale modelling is based on interdisciplinary models. Future climate scenarios setting include emission scenarios and global warming scenarios based on Global Climate Models (GCMs). A number of future research challenges have been identified. These include spatial scale and resolution, internal physical mechanism, application of novel artificial intelligence models, extreme climate events, potential competition in nexus systems as well as data and model uncertainty.
引用
收藏
页码:1 / 43
页数:43
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