Assessing the Impacts of Soil Conservation Practices on Surface Runoff and Water Quality Using an Agricultural Experimental Setup, Generalised Additive Mixed Models, and Hydrologic Modelling
Bibliographic record
Abstract
ABSTRACT Soil compaction and degraded soil structure can decrease water infiltration, increase surface runoff, and impact surface water quality. Soil conservation practices aim to protect soils from erosion and can restore soil physical and hydrological properties; however, their effect on restoring hydrological conditions at the field level is unknown. An agricultural experimental setup was established in 2020 in Saint‐Lambert‐de‐Lauzon (near Quebec City, Canada) to assess the impact of soil conservation practices and soil compaction on surface runoff and water quality. The field site is composed of twelve 624 m2 experimental plots in which the following are monitored: surface runoff and tile drainage, water quality (suspended solids, total phosphorus, nitrate and nitrite, dissolved metals), soil physical and chemical properties, and crop yields. The experimental design allows the comparison of four agricultural treatments: two compaction treatments (with and without soil compaction) and two conservation treatments (conventional and soil conservation agricultural practices). Each treatment is replicated three times. After a 3‐year rotation cycle, analyses of monitored variables using Generalised Additive Mixed Models (GAMM) confirmed moderate but significant short‐term capacity of soil conservation practices to reduce loads of suspended solids and nitrate and nitrite. Loads of total phosphorus were, however, not reduced significantly. Moreover, soil conservation practices were related to an unexpected increase in surface runoff during the spring flood. No effect was observed on soil properties and crop yields. An innovative methodological framework was explored to assess the long‐term impacts of soil conservation practices on hydrology. The Soil and Water Assessment Tool model was set up and calibrated for each experimental plot to simulate water budgets and was run using restored soil physical conditions based on measurements conducted on surrounding unperturbed sites. Despite limitations in flow partitioning, simulations suggested that a restoration of soil physical properties could moderately reduce surface runoff at the plot scale in the long term. The study enhances understanding of local soil health, quantitative hydrology, and water quality processes, and demonstrates the potential of a new methodological framework to quantify the long‐term benefits of soil conservation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".