Sociohydrological Impacts of Water Conservation Under Anthropogenic Drought in Austin, TX (USA)
Bibliographic record
Abstract
Abstract Municipal water providers increasingly respond to drought by implementing outdoor water use restrictions to reduce urban water withdrawals and maintain water availability. However, restricting urban outdoor water use to support watershed‐scale drought resilience may generate unanticipated cross‐scale interactions, for example, by altering drought response and recovery in urban vegetation or urban streamflow. Despite this, urban water conservation is rarely conceptualized or modeled as endogenous to the water cycle. Here we investigate cross‐scale interactions among urban water conservation and water availability, water use, and sociohydrological response in Austin, TX (USA) during a recent anthropogenic (human‐influenced) drought. Multiscalar statistical analyses demonstrated that outdoor water conservation for reservoir management at the municipal scale produced responses that can cascade both “upward” from the city to the watershed (e.g., decoupling streamflow patterns upstream and downstream of Austin at the watershed scale) and “downward” to exert heterogeneous effects within the city (e.g., redistributing water along a socioeconomic gradient at submunicipal scales, with effects on terrestrial and aquatic ecosystems). We suggest that adapting to anthropogenic drought through irrigation curtailment requires sustained engagement between hydrology and social sciences to integrate socioeconomic status and political feedbacks within and among irrigator groups into the water cycle. Findings from this cross‐disciplinary study highlight the importance of a multiscalar and spatially explicit perspectives in urban sociohydrology research to uncover how water conservation as adaptation to anthropogenic drought links hydrological processes with issues of socioeconomic inequality and spatiotemporal scale in the Anthropocene.
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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 | 0.001 | 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) | 0.001 | 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 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".