The Role of Water Balance Modelling in the Transition to Low Impact Development
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Low impact development (LID) is increasingly being viewed by local governments and developers alike as a viable approach to stormwater management that can effectively protect aquatic habitat and water quality. LID relies on distributed runoff management measures that seek to control stormwater volume at the source by reducing imperviousness and retaining, infiltrating and reusing rainwater at the development site. Early conventional stormwater management practices tended to focus on stormwater quantity and controlling a few extreme rainfall events, whereas the more frequent storms, which represent the majority of total runoff volume, carry most of the pollutants, and control the geomorphology of streams, were addressed in stormwater quality design practiced during the last decade. These frequent events are most effectively managed with a volume control approach, often described as stormwater source control or Low impact development (LID). Such an approach is described in this paper, demonstrating how water balance modelling can be an effective tool for evaluating and supporting implementation of LID options such as bioretention, pervious paving, numerous types of infiltration systems, rainwater reuse and green roofs. It also discusses recently developed water balance modelling software, including an Internet-based planning tool and a design optimization tool.
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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 | 0.009 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it