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Record W3110791666 · doi:10.3390/rs12244084

Wetland Hydroperiod Change Along the Upper Columbia River Floodplain, Canada, 1984 to 2019

2020· article· en· W3110791666 on OpenAlexafffundabout
Chris Hopkinson, Brendon Fuoco, Travis Grant, Suzanne E. Bayley, Brian Brisco, Ryan J. MacDonald

Bibliographic record

VenueRemote Sensing · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsGovernment of CanadaNatural Resources CanadaUniversity of AlbertaUniversity of Lethbridge
FundersU.S. Geological SurveyEnvironment and Climate Change Canada
KeywordsFloodplainWetlandHydrology (agriculture)Thematic MapperEnvironmental scienceFlood mythDrainage basinSatellite imageryOpen waterRemote sensingPhysical geographyGeologyGeographyCartographyEcologyOceanography

Abstract

fetched live from OpenAlex

Increasing air temperatures and changing hydrological conditions in the mountainous Kootenay Region of British Columbia, Canada are expected to affect floodplain wetland extent and function along the Columbia River. The objective of this study was to determine the seasonally inundated hydroperiod for a floodplain section (28.66 km2) of the Upper Columbia River wetlands complex using time series satellite image observations and binary open water mask extraction. A mid pixel resolution (30 m) optical satellite image time series of 61 clear sky scenes from the Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) sensors were used to map temporal variations in floodplain open water wetland extent during the April to October hydrologically active season from 1984 to 2019 (35 years). The hydroperiod from the first 31 scenes (T1: 18 years) was compared to the second 30 (T2: 16 years) to identify changes in the permanent and seasonal open water bodies. The seasonal variation in open water extent and duration was similar across the two time periods but the permanent water body extent diminished by ~16% (or ~3.5% of the floodplain). A simple linear model (r2 = 0.87) was established to predict floodplain open water extent as a function of river discharge downstream of the case study area. Four years of Landsat Multi-Spectral Scanner (MSS) data from 1992 to 1995 (12 scenes) were examined to evaluate the feasibility of extending the hydroperiod record back to 1972 using lower resolution (60 m) archive data. While the MSS hydroperiod produced a similar pattern of open water area to duration to the TM/OLI hydroperiod, small open water features were omitted or expanded due to the lower resolution. While MSS could potentially extend the TM/OLI hydroperiod record, this was not performed as the loss of features like the river channel diminished its value for change detection purposes. Radarsat 2 scenes from 2015 to 2019 were examined to evaluate the feasibility of continued mountain valley hydroperiod monitoring using higher spatial and temporal resolution sensors like the Radarsat Constellation Mission (RCM). From the available horizontal transmit/receive (HH) single polarization sample set (8 scenes), the hydroperiod pattern of open water extent to duration was similar to the longer Landsat time series and possessed greater feature detail, but it was significantly reduced in seasonal inundation area due to the systematic omission of open water areas containing emergent vegetation. However, accepting that differences exist in sensor-based hydroperiod attributes, the higher temporal resolution of RCM will be suited to mountain floodplain inundation monitoring and open water hydroperiod analysis.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.526

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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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 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

Citations17
Published2020
Admission routes3
Has abstractyes

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