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Record W2951803885 · doi:10.3390/w11061232

Rooting Depth and Extreme Precipitation Regulate Groundwater Recharge in the Thick Unsaturated Zone: A Case Study

2019· article· en· W2951803885 on OpenAlexaff
Jin Shao, Bingcheng Si, Jiming Jin

Bibliographic record

VenueWater · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of Saskatchewan
FundersNational Natural Science Foundation of China
KeywordsGroundwater rechargePrecipitationHydrology (agriculture)Vegetation (pathology)Environmental scienceGroundwaterDepression-focused rechargeVadose zoneGeologySoil scienceSoil waterAquiferGeography

Abstract

fetched live from OpenAlex

Many modeling efforts have been made for shallow soil, but little has been done in deep-rooted ecosystems, especially on the long-term impact of deep-rooted vegetation to understand the impact of vegetation type on hydrological processes. In this study, we used the Community Land Model (CLM) version 4.0 to simulate the soil water dynamics and groundwater recharge with shallow-rooted and deep-rooted vegetation cover in the critical soil zone of 100 m thickness. We selected winter wheat and summer maize to represent shallow-rooted vegetation and apple trees as deep-rooted vegetation growing in the semi-humid Loess Plateau of China over the period of 1901–2015. Our results show that the rooting depth and precipitation dictate the occurrence of disconnected recharge. This occurred in soil depths that were below 75 m in wet years with annual precipitation of over 650, 730, and 1000 mm for the winter wheat field, summer maize field, and apple orchard, respectively. Connected recharge was the major component of groundwater recharge for all three crop fields. The transit time of precipitation ranged from several to hundreds of years via the disconnected recharge that is caused by extreme precipitation and the connected recharge that is generated by other precipitation. Therefore, both rooting depth and growth period of vegetation affect the groundwater recharge and transit time, as well as precipitation.

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 score0.031
Threshold uncertainty score0.553

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 head0.022
GPT teacher head0.235
Teacher spread0.213 · 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

Citations19
Published2019
Admission routes1
Has abstractyes

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