Transboundary Aquifer Management Across the Americas: Hydro-Diplomacy as an Accelerator of Adaptive Groundwater Governance Amid Climate Change Challenges
Bibliographic record
Abstract
The management of transboundary aquifers across the Americas faces significant challenges, especially as climate change and population growth intensify groundwater stress. Groundwater use has increased to support domestic, industrial, and agricultural demands but has been extracted through unregulated withdrawals, leading to the severe degradation of aquifer health and transboundary frictions. This study focuses on how hydro-diplomacy can accelerate the adaptive governance of shared groundwater resources in three key regions: Canada–USA, USA–Mexico, and Mexico–Guatemala–Belize. We utilized a mixed methodology by integrating a transect approach, borrowed from ecology, into the field of geopolitics. To compare the hydro-diplomatic relations and groundwater governance across a continental gradient in the Americas, we conducted a literature review and employed the TWINS conflict–cooperation matrix to evaluate governance frameworks and hydro-diplomatic interactions across time. Our findings demonstrate that hydro-diplomacy plays a pivotal role in expediting agreements, fostering transboundary data sharing, and supporting participatory governance models. In particular, the presence of supranational bodies such as the International Joint Commission (IJC) between Canada and the USA has been effective in maintaining long-term collaboration through social learning and technical cooperation. Meanwhile, in regions like Mexico–Guatemala–Belize, the absence of robust institutions has hindered progress, with limited financial and knowledge-sharing networks. This study highlights the need for improved cross-border cooperation mechanisms and the establishment of common monitoring protocols to better manage aquifer resources under the pressures of climate change. The results support the development of more adaptive transboundary groundwater management strategies aligned with Sustainable Development Goal (SDG) 6.5.2 and call for broader geopolitical cooperation to address the complexities of groundwater governance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".