Testing the Predictive Power of Hydro-Economic Supply-Side Input–Output Models Under Different Water Availability and Economic Conditions Over Time in a Transboundary River Basin
Bibliographic record
Abstract
Although the temporal transferability of input–output (IO) models has been examined before, no study has investigated the impacts of changing water availability conditions over time, e.g., due to climate change, on the predictive power of water-inclusive IO models. To address this gap, we investigate the performance of inter-regional supply-side input–output (ISIO) models that incorporate precipitation and water intake under varying climates over time in a transboundary water management context. Using the Saskatchewan River Basin in Western Canada as a case study, we develop four ISIO models based on available economic and hydrological data from years with different climatic conditions, i.e., two dry and two wet years. Accounting for price changes over these years, our findings indicate that the joint impact of changes in water availability and economic structural changes on economic output can be considerable. The results furthermore show that each model performs particularly well in predicting the economic output for similar climatic years. The models remain reliable in predicting economic outputs over several years as long as changes in water availability are within the range observed in the water-inclusive base year ISIO model.
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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".