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Record W6959502731 · doi:10.1002/hyp.70126

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

2025· article· en· W6959502731 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHydrological Processes · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Regulatory Analysis
Canadian institutionsInstitut National de Santé Publique du QuébecUniversité LavalInstitut de Recherche et de Développement en Agroenvironnement
FundersMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsSurface runoffSoil conservationHydrology (agriculture)Soil waterWater qualitySoil compactionSurface waterTile drainageCover cropCrop rotation

Abstract

fetched live from OpenAlex

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 m 2 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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.139
GPT teacher head0.389
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it