MétaCan
Menu
Back to cohort
Record W7066526733

Impacts of Dredging and Brush Cutting of Paired Agricultural Drainage Ditches on GHG Emissions and Nutrient Filtration Capacity

2022· dissertation· en· W7066526733 on OpenAlexaboutno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2022
Typedissertation
Languageen
FieldMaterials Science
TopicClay minerals and soil interactions
Canadian institutionsnot available
Fundersnot available
KeywordsDitchDrainageGreenhouse gasDredgingNutrientAgricultureVegetation (pathology)Nutrient pollutionSurface runoffWater pollution
DOInot available

Abstract

fetched live from OpenAlex

Agriculture provides many beneficial and essential ecosystem services. Along with these 
\nbeneficial services, the conversion of natural ecosystems into heavily modified agricultural 
\necosystems is also a source of disservice, including being a major source of global greenhouse 
\ngas (GHG) emissions and pollution of downstream waterways due to increased nutrient runoff. 
\nCarbon (C), Nitrogen (N) and Phosphorus (P) applied to agricultural fields as fertilizer are a 
\nsource of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions. Nutrient 
\nrunoff can lead to excess P in surface water bodies causing algae blooms, and excess N can lead 
\nto excess nitrate (NO3) in rural groundwater (GW) wells. There is a need to establish beneficial 
\nmanagement practices (BMPs) to take into account agriculture-derived pollution with all 
\nagricultural practices. This thesis informs the development of BMPs by examining the 
\nenvironmental pollution aspects of both: 1) GHG emissions; and 2) nutrient export; resulting from
\nthe common practices of brush cutting and dredging of ditches to enhance drainage.
\nRiparian vegetation in agricultural drainage ditches has been shown to decrease 
\ninsolation, which decreases soil and water temperatures. This vegetation also hinders drainage 
\nby restricting flow, thus raising water levels, which decreases CO2 emissions and increases CH4
\nand N2O emissions. However, no previous studies have examined in detail the effects of 
\nremoving drainage ditch vegetation. This study examines the GHG emissions from four ditch 
\nmicroplots in the South Nation Watershed in southern Ontario, Canada following the removal 
\nof riparian vegetation from two microplots. The trials took place over three field seasons, and 
\nthe intervention methods were selected to observe the effects of brush cutting and of dredging 
\non GHG emissions between years. The Control Shrub and Control Tree microplot sites were 
\nleft unaltered. The Brush Cut Shrub and Brush Cut Tree sites were brushed in Spring 2018 and 
\nDredged in Fall of 2018, with observations at all sites taking place over 2018-2020 growing 
\nseasons. Brushing increased CO2 emissions at the treed site but had little effect on the shrub 
\nsite. Dredging decreased CH4 emissions.
\nRiparian vegetation has also been shown to obstruct the path for water flow, decreasing 
\nwater velocities and raising water levels, which increases the ability of ditches to filter and retain 
\nnutrients. Simultaneously with the GHG research above, this study also examines the N, P, and C 
\nv
\nexport from two adjacent watersheds within the South Nation Watershed following the removal 
\nof riparian vegetation from one of them. The trials took place over two field seasons and the 
\nintervention methods were selected to observe the effects of brush cutting and dredging on N and 
\nP export over two years. The southern watershed (Brush Cut) was brushed + dredged in 2018 
\nand the northern watershed (Control) was left intact before flow monitoring took place in 2019 
\nand the Fall of 2020. Tile drain discharge containing DOC, N and P, occurred during the Spring 
\nand Fall when the water table is higher, but was not observed during the summer. Brush cutting 
\nand dredging increased hydraulic outflow and reduced or eliminated NO3 retention capacity of 
\nagricultural drainage ditches by 320% in 2019 and 68% in Fall 2020. This increase in NO3
\nexport may negatively affect rural water supplies. Lack of O2 and increased retention of DOC 
\nand SO4 in the Control watershed suggests that significant NO3 reduction occurred. Differences 
\nin P export between Brush Cut and Control in 2019 were small. There are more signs of P 
\ntransformation in the Control watershed, but brush cutting and dredging may not significantly 
\naffect eutrophication.
\nThis thesis will help inform stakeholders about the environmental geochemical costs and 
\nbenefits of brushing and dredging so that they can develop BMPs that minimize GHG production 
\nand maximize nutrient filtration. Future research is needed to determine how many years the 
\neffects of these intervention methods remain, and also determine other environmental impacts 
\nsuch as their effects on biodiversity.

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.

How this classification was reachedexpand

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.216
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueUWSpace (University of Waterloo)Same topicClay minerals and soil interactionsFrench-language works237,207