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Record W4321502094 · doi:10.5194/egusphere-egu23-4054

Method to quantify hydrological alterations due to anthropogenic interventions: A case study of Peace River, Canada

2023· preprint· en· W4321502094 on OpenAlexaboutno aff
Maithili Mohanty, Vinod Tare

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHydropowerHydrology (agriculture)Environmental scienceStreamflowCanyonDrainage basinFlow (mathematics)GeographyGeologyEcologyCartography

Abstract

fetched live from OpenAlex

Hydrological alteration refers to any modification to different components of the natural flow regime of a river that human interventions may cause. The interventions are built to store excess water for different purposes, such as hydropower generation, irrigation, and domestic uses. The headwaters of the Peace River in Canada that flows from the Rocky Mountains of British Columbia became regulated by two large dams, the W. A. C. Bennett dam in 1968 and the Peace Canyon dam in 1980. The objective of the paper quantified the hydrological alterations caused by the cascade of dams across the Peace River. We have used a powerful tool 'River Flow Health Index' to quantify the alterations in different flow regime components on a 0-1 scale (0 means unaltered and one means completely altered). Historical hydrological data is obtained from the Water Survey of Canada (http://www.ec.gc.ca/rhc-wsc/) at a gauge station, Peace River near Taylor (coordinates: 56° 8'8.99"N, 120°40'13.01"W) for the years 1945-2015. 1945-1962 is chosen as the reference state because the dams were constructed after 1963. The altered period is referred to the period 1970-2015 after the operation of the dams started. We scrutinized 171 hydrologically relevant parameters grouped into seven components of the flow regime: magnitude, variability, duration, frequency, timing, rate of change, and others. The methodology for estimating the River Flow Health Index (RFHI) consists of four steps: (1) segregation of the flow data based on preimpact and postimpact periods, (2) identification of important hydrological parameters, (3) assessment of the alterations, and (4) development of an index indicating the health of the river flow during the altered period on a 0–1 scale. The flow health of the river changed significantly due to the dams, with an overall alteration of 0.897. The degree of alterations in different components of the flow regime is magnitude (0.646), variability (0.978), duration (0.941), frequency (1.000), timing (0.978), rate of change (0.801), and others (1.000).Daily flows at the downstream site during 1945–2015 reveal substantial reductions in flows after the construction of the W. A. C. Bennett and Peace Canyon dams. Homogenization of flows in the post-impact period altered the variability component of the flow regime. The duration and frequency of the extreme events are stunted post-dam regulation. This might result from water storage and release, and these multiple dams can store and attenuate all high-and low-pulse events. Alterations in the timing component resulted in the seasonal shift in streamflow by storing flood flows and releasing or utilizing them during lean seasons. Changes in Group 6, i.e., rate of change after the construction of the dams, indicate dam operations for energy production (i.e., peaking operations). Thus, the results indicate that the large dams across the Peace River can substantially change the natural flow regime. Our results may help upgrade the design and implementation of reservoir operation policies that consider downstream hydrological alterations.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.006
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.088
GPT teacher head0.370
Teacher spread0.281 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2023
Admission routes1
Has abstractyes

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