A process‐based approach to attribution of historical streamflow decline in a data‐scarce and human‐dominated watershed
Bibliographic record
Abstract
Abstract Human activities have resulted in rapid hydrological change around the world, in many cases producing shifts in the dominant hydrological processes, confounding predictions, and complicating effective management and planning. Identifying and characterizing such changes in hydrological processes is therefore a globally relevant problem, one that is particularly challenging in sparsely monitored environments. We develop a novel, process‐based approach for attribution of hydrological change in such scenarios and apply the approach to the TG Halli watershed outside Bangalore, India, where streamflow has declined considerably over the last 50 years. The approach consists of (a) employing a range of field instrumentation and experiments to identify contemporary streamflow generation mechanisms, (b) using these observations to constrain our understanding and generate hypotheses pertaining to historical changes, and (c) evaluating these hypotheses with a range of evidence including proxies for historical hydrological processes. The body of evidence in the TG Halli watershed indicates the historical presence and subsequent loss of a shallow groundwater table that previously discharged to the stream, meaning that groundwater depletion is the most likely driver of streamflow decline. These findings present a viable path towards improved predictions of future water resources and sustainable water management within the watershed. Our process‐based approach to attribution has the potential to improve understanding of human‐driven hydrological change in regions with poor monitoring of hydrological systems.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".