Utilisation des technologies géomatiques pour spatialiser le facteur K d’érodabilité des sols du bassin versant de la rivière Chaudière, Québec
Bibliographic record
Abstract
Le système informatisé GIBSI utilise l’Équation Universelle de Pertes de Sol (EUPS) pour simuler l’érosion hydrique des sols. L’EUPS nécessite d’estimer le facteur d’érodabilité annuelle moyenne des sols (facteur K) du bassin versant étudié. Cette estimation peut s’avérer délicate, car elle dépend de l’information contenue sur les cartes pédologiques. Le recours aux technologies géomatiques s’avère alors un moyen à privilégier pour gérer les caractéristiques physico-chimiques des sols et leur localisation sur le bassin versant. Une procédure d’agrégation spatiale par polygones pédologiques a été élaborée afin de calculer le facteur K pour les sols du bassin versant de la rivière Chaudière (Québec, Canada). Une cartographie du facteur K a été réalisée afin d’étudier la distribution spatiale de l’érodabilité des sols du bassin versant. Les valeurs du facteur K calculées par polygone pédologique varient de 0,0043 à 0,0582 t h ha MJ–1 ha–1 mm–1 et présentent une moyenne de 0,0236 t h ha MJ–1 ha–1 mm–1. Cette cartographie a fait ressortir certaines discontinuités spatiales dans la délimitation des polygones situés à la frontière de cartes pédologiques appartenant à des comtés voisins. Certaines de ces discontinuités auraient pour origine la nature et la distribution des pédo-paysages sur le bassin versant et l’évolution des méthodes de cartographie et de classification des sols utilisées entre les années 1957 et 1996. \n \n Abstract \nThe integrated \nmodelling system GIBSI simulates soil erosion using the Universal Soil Loss Equation (USLE). The USLE requires the evaluation of the soil erodibility K factor for the studied watershed. This estimate can be difficult because it depends on information from soil maps. The use of geomatics technologies appears to be a good way to manage the physico-chemical characteristics of soils and their aerial distribution in the watershed. A method for the spatial aggregation of the physico-chemical soil parameters obtained from published soil surveys was developed and used to calculate, at the soil polygone level, the K factor for the Chaudière River watershed (Québec, Canada). The calculated values of K, for all the surveyed soil polygones, varied between 0.0043 and 0.0582 t h ha MJ–1 ha–1 mm–1, averaging 0.0236 t h ha MJ–1 ha–1 mm–1 for the watershed. The raster mapping of these values showed spatial discontinuities at the limits of adjacent soil counties. Some of these discontinuities were due to the nature and distribution of soil landscapes on watershed and to the evolution of soil survey techniques between 1957 and 1996.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".