An approach to maintaining hydrological networks in the face of land use change
Bibliographic record
Abstract
Ephemeral drainage patterns in the prairie pothole region of southern Alberta are not well understood at the landscape level. Municipal land use planning generally places very few constraints on development, which can leave the existing landscape topography and drainage patterns highly modified and engineered. Few if any features that exist within the pre-development landscape remain post-development. Part of the residential or industrial land development process is the creation of master drainage plans which focus on collecting and moving precipitation or snow melt away from roads and buildings through drainage ponds and piping systems. However, in prairie pothole landscapes, there is a landscape hydrology system that connects wetlands and sub-surface soil moisture flows and involves significant ephemeral components. These existing landscape flow systems provide ecosystem services in both flood and drought conditions. However, conventional land conversion processes do not generally recognize existing landscape processes like hydraulic connectivity in the development process. This creates a gap between the standard engineering approach and landscape structure and function which puts landscape processes and services at risk of being lost over time. The method demonstrated in this paper has been designed to bridge pre-development and post-development conditions for hydrologic flow systems. This method can be used as an additional cross-scalar information “layer” for use in the planning process to identify how utilities, roads and building sites can be spatially organized to complement rather than conflict with existing landscape flow systems in areas with minimal topographic relief and specifically in Prairie Pothole Region landscapes. This relatively simple technique can help reduce infrastructure costs and enables development to maintain natural flow systems and cross-scalar hydraulic connectivity.
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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 | 0.000 | 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".