The historical footprint and future challenges of water-energy-food nexus research: a bibliometric review towards sustainable development
Bibliographic record
Abstract
The water–energy–food (WEF) nexus has emerged as a frontier issue in interdisciplinary research and is one of the most complex sustainability challenges that the world is faced with today. In this review, we ask: (i) how can the interdependent relationships among water, energy, and food resources be identified? (ii) what methods have been applied to understand these relationships? and (iii) what are the future opportunities and challenges for the WEF nexus development? To answer these questions, we provide a critical assessment of the relevant literature from Web of Science database on WEF nexus published between 2008 and 2019 using a bibliometric analysis. Using the resulting 396 published articles, we systematically reviewed the concept and the bibliometric characteristics of the WEF nexus research to assess the development footprint. Based on the most popular topics and research methods found in these publications, we discussed the major research limitations as well as future opportunities and challenges for WEF research. An examination of internal and external relationships among topics showed that the three most recent hot areas of WEF nexus research include (i) water, energy, and food, (ii) policy-making and resource management, and (iii) system models and methods. Specifically, considering that no one method can solve all problems, we innovatively summarized the application scope and the advantages and disadvantages of each method, with a particular focus on the WEF nexus models. This was undertaken to support readers in choosing a scientific method to analyze the specific WEF nexus related issues. We anticipate that complex interdependence mechanisms, data uncertainty, analytical model development, and in-depth policy implementation will pose the greatest challenges for future WEF nexus research; however, these challenges will also generate better research opportunities. This bibliometric review highlights that to increase understanding of complex WEF systems and formulating optimal strategies to manage them is of great significance for environmental and social sustainability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".