Water trade alternatives in the face of climate change
Bibliographic record
Abstract
Purpose: Prolonged drought and climate change uncertainty have created an urgent need to re-distribute water away from irrigators and back to environmental flows. Previous approaches to achieve this objective have had mixed results. The current approach focuses on purchasing water from irrigators to bolster river flows for ecosystem health. However, governments are purchasing entitlements, not allocations, which do not provide large amounts of water for the money that is spent. This paper aims to review the policies and events that have driven this process. Design/methodology/approach: Following a the review of the policies and events, the paper identifies how the regulatory/market-based approaches have resulted in a status quo or path dependent situation, to the detriment of achieving sustainable water use. Findings: Previous approaches have so far simply maintained path dependency, i.e. the consumptive pool at more or less existing levels. Government intervention to purchase entitlements from irrigators for the environment through water markets is meant to break the status quo, but questions whether this can be achieved from a solitary focus on entitlement recovery. Practical implications: It is suggested that both historical approaches offer less reform value, and that appropriate market intervention is warranted. However, entitlement water purchasing alone may limit provision of wet water to key environmental sites during critical periods and perpetuate a continuation of the path dependency arrangements. Originality/value: A suggested expansion of the water-purchasing programme that utilises allocation based products to meet adaptive environmental flow strategies is provided. Such an approach may offer a more suitable framework for dealing with the uncertain outcomes of climate change and ecosystem needs. © Emerald Group Publishing Limited.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 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 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".