Assessing the real impact of inter-provincial grain trade on water and land resources within China via a modified framework
Bibliographic record
Abstract
A rational evaluation of the virtual land and water resource flows within the grain trade can potentially serve: ( i) to mitigate regional resource scarcity, ( ii ) as the basis for agricultural water and land resource management, and ( iii ) to support policymakers in making strategic choices for resource redistribution and sustainable resource development. Failing to reflect real-world agricultural production systems and irrigation-driven resource management practices, existing evaluation frameworks consider only the virtual water and land content embedded in traded grain, neglecting irrigation’s marginal productivity enhancement effect under cropland constraints. Applied to empirical analyses of interprovincial grain transfers within China, where arable land resources are strictly constrained, a modified framework was developed to incorporate irrigation effects into virtual water and land resource accounting. China's land and water productivity under irrigated agriculture is 2.18- and 1.32-fold greater than under rainfed agriculture, respectively. However, the irrigation provision rate is less than 50 %. From 2005–2015, interprovincial virtual water flows increased from 45.94 × 10 9 m³ to 98.80 × 10 9 m³ , and virtual land flows increased from 3.64 × 10 6 ha to 9.35 × 10 6 ha. A benefits evaluation showed that, over the same period, virtual water wastage decreased from 8.24 × 10 9 m³ to 3.79 × 10 9 m³ , and virtual land wastage increased from 1.81 × 10 6 ha to 4.22 × 10 6 ha. Therefore, failure to consider the role of irrigation can lead to erroneous grain virtual water and land trade evaluations. In altering the perspective of virtual water and land resource assessment, this study provides a basis for agricultural layout optimisation, irrigation development and water resource management policies. • Expanded irrigation boosts grain production despite arable land constraints. • Irrigation enhances the efficiency of water and land use in grain production. • Ignoring irrigation's role leads to the underestimation of virtual blue water flows and arable land savings. • Incorporating grain production processes into trade evaluations enhances policy relevance.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".