Real time adjustment of slow changing flow components in distributed urban runoff models
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
In many urban runoff systems infiltrating water contributes with a substantial part of the total inflow and therefore most urban runoff modelling packages include hydrological models for simulating the infiltrating inflow. This paper presents a method for deterministic updating of the hydrological model states governing the infiltrating inflow based on downstream flow measurements. The fact that the infiltration processes follows a relative large time scale is used to estimate the part of the model residuals, at a gauged downstream location, that can be attributed to infiltration processes. This information is then used to update the states of the hydrological model. The method is demonstrated on the 20 km2 Danish urban catchment of Ballerup, which has substantial amount of infiltration inflow after succeeding rain events, for a very rainy period of 17 days in August 2010. The results show big improvements for regular simulations as well as up to 10 hour forecasts. The updating method reduces the impact of non-representative precipitation estimates as well as model structural errors and leads to better overall modelling results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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