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Record W1480412753 · doi:10.18172/cig.2649

Assessment of soil redistribution at catchment scale by coupling a soil erosion model and a sediment connectivity index (central spanish pre-pyrenees)

2015· article· en· W1480412753 on OpenAlexaff
Manuel López‐Vicente, Laura Quijano, Leticia Gaspar, Ana Navas

Bibliographic record

VenueCuadernos de Investigación Geográfica · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsUniversity of Northern British Columbia
FundersMinisterio de Economía y Competitividad
KeywordsSurface runoffDrainage basinHydrology (agriculture)ErosionEnvironmental scienceSedimentMediterranean climateSoil waterGeologySoil scienceGeomorphologyGeographyEcologyCartography

Abstract

fetched live from OpenAlex

The study and quantification of soil redistribution is a complex and difficult task and even a non-solved question at catchment scale both in field and numerical simulation studies. In this study we tackle this topic by coupling two different predicting models and a sound field-based dataset to assess the potential soil redistribution in a Mediterranean rain-fed agricultural and mountainous catchment (La Reina gully catchment, Cinco Villas region, NE Spain): the enhanced Modified-RMMF-2014 version of the “Modified Revised Morgan, Morgan and Finney” model (Morgan, 2001; López-Vicente and Navas, 2010) of soil erosion and the IC (Index of Connectivity; Borselli et al., 2008) model of sediment connectivity. In a cereal experimental plot (1.9 ha; 1 x 1 m of cell size), located in the lowlands of the La Reina gully catchment, we firstly ran the IC model under six different scenarios of runoff pathways and results were compared with field observations of soil redistribution. The best performance was obtained with the IC model when the map of geomorphic features (rills, ephemeral gullies and fan deposits) was used in the simulation. Predicted rates of both models were correlated at 613 control points and three areas where identified at the plot: erosive-, stable- and depositional- prone areas, affecting 30%, 22% and 48% of the soil surface, respectively. The average erosion rates in each area were 3.3, 1.5 and 1.1 Mg ha-1 yr-1 with standard deviation values of 20.3, 19.0 and 8.3 Mg ha-1 yr-1. Then, the IC model was run at La Reina gully catchment (231 ha; 5 x 5 m) and the IC values were analysed following the first approach. Stable areas and those mainly affected by processes of soil loss and deposition were identified. Results showed clear differences in the index of connectivity along the catchment though the extension of the areas with predominant processes of soil loss was under predicted (11% of the catchment area). Further research should be focused on the adjustment of the IC model to catchment scale. Our approach offers a simple and alternative method to assess spatially distributed processes of soil redistribution at catchment scale that can be of interest in ungauged catchments where calibration task of numerical models is difficult to be done.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.244
Teacher spread0.219 · 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 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

Citations65
Published2015
Admission routes1
Has abstractyes

Explore more

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