JAMES BUTTLE REVIEW: A resilience framework for physical hydrology
Bibliographic record
Abstract
Abstract Hydrological systems across the globe are increasingly subjected to pressures from a warming climate and anthropogenic disturbance. Responses to stress can be nonlinear and variable; therefore, it is imperative to improve understanding of resilience and tipping points of these systems. Previous applications of resilience concepts to physical hydrology have been disconnected, and an increasing range of definitions and approaches has often led to improper applications. Here, upon synthesizing relevant literature, we define physical hydrological resilience as the ability of a watershed to maintain hydrological function while exposed to a stressor or perturbation, thus remaining within the same regime. From this definition a new framework for physical hydrological resilience is forwarded which includes four key traits that must be part of a robust application of resilience for physical hydrology. Any evaluation of resilience should (1) identify and justify a baseline regime; (2) evaluate hydrological function, one or more of collection, storage and release; (3); assess physical hydrological systems for both resistance and latitude and (4) evaluate important perturbations and processes and how they interact to manifest into resistance, latitude, and tipping points. The framework is applied to the example of the Elbow River in Alberta, Canada, using baseline (1979–2015) and future (2050–2080) conditions. Two key hydrological processes, snow accumulation and streamflow, are found to have low resistance to winter duration and late spring precipitation, respectively. The collection function is resilient to a warmer, wetter climate due to a large latitude in relation to air temperatures, while the release function is not resilient, shifting from a streamflow‐ towards an evapotranspiration‐dominated regime in the future. The successful application of the concepts of resilience to this complex catchment demonstrates how the framework could be applied across a diversity of catchments. Results of resilience studies can improve environmental monitoring and evaluation programs and complement social‐ecological resilience frameworks and water management strategies.
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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 | 0.002 |
| 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 | 0.001 |
| 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 | 0.002 |
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".