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Record W7015013751

A Review of Canadian Prairie Hydrology: Principles, Modelling and Response to Land Use and Drainage Change

2023· report· en· W7015013751 on OpenAlexaffabout

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typereport
Languageen
Field
Topic
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSnowmeltHydrology (agriculture)Surface runoffWetlandSnowDrainageStreamflowPrecipitationLand cover
DOInot available

Abstract

fetched live from OpenAlex

This report reviews research on the hydrological cycle, runoff generation, hydrological modelling and the influence of changes to land cover and wetlands on the same for the Canadian Prairies. The purpose of this report is to identify and examine the major processes that are responsible for prairie hydrology as well as the impacts of land cover change such as wetland drainage on water storage and on the streamflow hydrograph. The objective of this report is to propose hydrological modelling techniques; these techniques can contribute to the development of a predictive tool in the form of a prairie hydrological model. It is intent to utilize such a hydrological model to evaluate the impacts of wetland drainage and restoration as well as changes in the surrounding upland land use on downstream hydrology. Hydrology in the Canadian Prairie region is complex and highly varied. Only one third of annual precipitation occurs over the winter and the surface snow water equivalent distribution is highly heterogeneous due to wind redistribution of snow during blowing snow storms. Blowing snow can transport and sublimate as much as 75% of annual snowfall from open prairie fields. The formation of drifts from windblown snow lengthens the spring runoff season and modulates the peak spring flows. The frozen state of mineral soils results in rapid snowmelt runoff in the springtime, which produces 80% or more of annual local runoff. The prairie region is characterized by glacially-formed depressions; these depressions fill with water to form pothole sloughs and wetlands and are very important to prairie hydrology due to their surface storage capacity. A fill-and-spill runoff mechanism is identifiable in prairie basins that are dominated by these surface depressions where flow does not commence until all storage in the depressions is filled. This results in an episodic and rapid increase in contributing area during peak runoff events. However outside of these events much of the prairie landscape is non-contributing to streamflow and even in the most extreme runoff events, some prairie basins are internally drained and never contribute to streamflow. This fill and spill phenomenon is in contrast to forms of hydrological storage found in temperate regions in which the flow rate is proportional to storage. Because of depressional storage and poorly and internally drained basins, most surface runoff in the prairie region does not contribute to the major river systems. Hydrological processes in the prairie region are sensitive to the land cover and climate change. Wetlands can be completely dried out when surrounded by native grassland rather than agricultural fields. Droughts are frequent on the Canadian Prairies. Lower precipitation and higher air temperature are the common characteristics of droughts; surface snowmelt runoff is largely suppressed and can even completely cease when warmer (e.g. 5 ºC increase of temperature) or drier (e.g. 50% decrease of precipitation) conditions develop. The Cold Regions Hydrological Model platform (CRHM) is a “state-of-the-art” physically-based hydrological model designed for the prairie region. CRHM is based on a modular, object-oriented structure in which component modules represent basin descriptions, observations, or physically-based algorithms for calculating hydrological processes. Preliminary tests show reasonable performance of CRHM in simulating the water balance and streamflow hydrograph for prairie regions. The model also shows capabilities to simulate impact of land use change and climate change on hydrological processes and streamflow. Further work in CHRM will be development of surface storage and surface routing models that are suitable for modelling hydrology in the prairie wetland region.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.003
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.094
GPT teacher head0.231
Teacher spread0.137 · 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.

Study designNot applicable
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

Citations4
Published2023
Admission routes2
Has abstractyes

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