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Record W4392596994 · doi:10.5194/egusphere-egu24-1587

Transforming river morphology over 60 years of urban development 

2024· preprint· en· W4392596994 on OpenAlexaffabout
Peter Ashmore, Barlow Victoria, McDonald John

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsWestern University
Fundersnot available
KeywordsMorphology (biology)GeographyBiologyZoology

Abstract

fetched live from OpenAlex

Urban land development causes changes to river channel form and function and to community relationships and visions of rivers. The story of urbanization of Highland Creek, Toronto, Canada involves the transformation of the 100km2 watershed from rural to almost 100% urban land-use over 6-7 decades. The unusually rich documentation of the watershed changes allows for understanding of the long-term trajectory of transformation of the channels based on geomorphic principles. It also shows the evolving institutional responses to managing and redesigning the river channels and valleys, and mitigating risks, which can be seen as part of the urbanization of rivers along with the physical response of the river channels. Urbanization has transformed the main channels to an extremely energetic state more like mountain streams despite the low relief terrain of the Toronto region with total stream power increasing by up to 10 times following urbanization. Measurements from historical air photos for multiple epochs over 60 years show that channels have widened progressively by a factor of 4 or 5, with accompanying changes in planform, triggered, in particular, by two or three large flood events, and consistent with hydraulic geometry predictions. The time trajectory and spatial pattern of changes to morphology of reaches that were free to adjust to the increased stream power are well-predicted by land-cover based predictions of stream power using the SPIN watershed analysis tool (Stream Power Index for Networks) which provides a means of predicting possible future changes as well as explaining historical change. Increases in specific stream power show potentially large increases in bed material particle mobility consistent with observed morphology changes. Freedom to evolve to a new state is partly the result of institutional decisions and vision to set aside valley land in the 1950s to reduce flood damage. In other places the process of urbanization has involved progressive engineering of the channel, reflecting approaches in 1960s and 70s to protect infrastructure and institute an engineering vision of river control which has eliminated fluvial processes of channel development and adjustment. Recent moves to channel restoration using geomorphic design approaches reflect create novel river morphology. Urbanization of channels does not end with land cover change and its physical hydro-geomorphic effects, nor is there a clear end-point and time-span of response that is often claimed in studies of urban fluvial change. Understanding urbanization as an ongoing process of ‘re-storying’ river channels within a socio-geomorphic system is essential to understanding urban river histories and futures, explaining urban river morphology, and recognising the entwined physical and socio-political power and processes that transform urban rivers.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.452

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.015
GPT teacher head0.237
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2024
Admission routes2
Has abstractyes

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