Ponds and Their Potential for Agricultural Sustainability in Punjab; Insights from a Century of Surface Water Change in the Granary of India
Bibliographic record
Abstract
Ponds are one of the most basic landscape features that humans can use to manage water, and were important landscape features common especially in periods before people began extracting groundwater using fossil-fuels. In this article we use historical cartography and geospatial methods to analyse a century of change in pond distribution in the Indian state of Punjab, part of a larger area colloquially known as the ‘Granary’ of India. We ask how the changing spatial distribution of ponds over the last century reflects shifts in water management over a period that also includes the Green Revolution (1968 onwards), when agriculture intensified and groundwater levels declined. We find that ponds were prevalent in the past, suggesting they contributed to more adaptive forms of water use. Pond numbers and area have declined over the last century, which leads us to suggest that pond restoration may provide a pathway to sustainable water governance in the region today.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".