MétaCan
Menu
Back to cohort
Record W2563956511 · doi:10.1002/2016wr019191

The integrated hydrologic model intercomparison project, <scp>IH‐MIP2</scp>: A second set of benchmark results to diagnose integrated hydrology and feedbacks

2016· article· en· W2563956511 on OpenAlexaff
Stefan Kollet, Mauro Sulis, R. M. Maxwell, Claudio Paniconi, Mario Putti, Giacomo Bertoldi, Ethan T. Coon, Emanuele Cordano, S. Endrizzi, Evgeny Kikinzon, Emmanuel Mouche, Claude Mügler, Youngjin Park, Jens Christian Refsgaard, Simon Stisen, Edward A. Sudicky

Bibliographic record

VenueWater Resources Research · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of WaterlooInstitut National de la Recherche Scientifique
FundersProvincia autonoma di Bolzano - Alto AdigeDeutsche ForschungsgemeinschaftNational Science Foundation
KeywordsSurface runoffBenchmark (surveying)Hydrology (agriculture)Environmental scienceHydrological modellingMeteorologyGeotechnical engineeringGeologyClimatologyGeography

Abstract

fetched live from OpenAlex

Abstract Emphasizing the physical intricacies of integrated hydrology and feedbacks in simulating connected, variably saturated groundwater‐surface water systems, the Integrated Hydrologic Model Intercomparison Project initiated a second phase (IH‐MIP2), increasing the complexity of the benchmarks of the first phase. The models that took part in the intercomparison were ATS, Cast3M, CATHY, GEOtop, HydroGeoSphere, MIKE‐SHE, and ParFlow. IH‐MIP2 benchmarks included a tilted v‐catchment with 3‐D subsurface; a superslab case expanding the slab case of the first phase with an additional horizontal subsurface heterogeneity; and the Borden field rainfall‐runoff experiment. The analyses encompassed time series of saturated, unsaturated, and ponded storages, as well as discharge. Vertical cross sections and profiles were also inspected in the superslab and Borden benchmarks. An analysis of agreement was performed including systematic and unsystematic deviations between the different models. Results show generally good agreement between the different models, which lends confidence in the fundamental physical and numerical implementation of the governing equations in the different models. Differences can be attributed to the varying level of detail in the mathematical and numerical representation or in the parameterization of physical processes, in particular with regard to ponded storage and friction slope in the calculation of overland flow. These differences may become important for specific applications such as detailed inundation modeling or when strong inhomogeneities are present in the simulation domain.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.503
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
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 head0.040
GPT teacher head0.304
Teacher spread0.264 · 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

Citations176
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueWater Resources ResearchSame topicHydrology and Watershed Management StudiesFrench-language works237,207