The Impact of Virtual Water on Sustainable Development in Gansu Province
Bibliographic record
Abstract
The concept of virtual water, as a new approach for addressing water shortage and safety issues, can be applied to support sustainable development in water-scarce regions. Using the input-output method, the direct and the complete water use coefficients of industries categorized as primary, secondary, or tertiary, and the spatial flow patterns of the inter-provincial trade in the Gansu province region of China, were explored. The results show that in 2007, 2010, and 2012 the direct and complete water use coefficients of the primary industries were the greatest among the three industry categories, with direct water use coefficients of 1545.58, 882.28, and 762.16, respectively, and complete water use coefficients of 1692.22, 1005.38, and 873.44, respectively; whereas, the direct and complete water use coefficient values of the tertiary industry category were the lowest, with direct water use coefficients of 16.65, 7.74, and 66.89 for 2007, 2010, and 2012, respectively, and complete water use coefficients of 65.46, 66.89, and 72.81 for 2007, 2010, and 2012, respectively. In addition, study results suggest that the volume of virtual water supplied to Gasnu province’s local industries has decreased annually, while virtual water exports from the province have increased annually, with the primary industry accounting for 95% of virtual water output. Overall, the virtual water of Gansu province in 2010 showed a net output trend, with a total output of 0.506 billion m3, while in 2007 and 2012 it showed a net input trend with a total input of 0.104 and 1.235 billion m3, respectively. Beijing, Shanghai, Guangdong, Ningxia and other water-scarce areas were the main input, or import source for Gansu’s virtual water; during the years studied, these provinces imported more than 50 million m3 individually. Based on these results, it is clear that under the current structure, virtual water is mainly exported to the well-developed coastal areas and their adjacent provinces or other water-abundant regions. Therefore, Gansu province should (1) adjust the industrial structure and develop water-saving and high-tech industries; (2) adjust the current trade pattern to reduce virtual water output while increasing its input to achieve balanced economic development and water resource security.
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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 | 0.000 | 0.001 |
| 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".