MétaCan
Menu
Back to cohort
Record W7119426217

Árvizek és belvizek a 21. századi Magyarországon = Floods and inland waters in 21st century Hungary

2025· article· hu· W7119426217 on OpenAlexaboutno aff
L. Szlávik

Bibliographic record

VenueRepository of the Academy's Library (Library of the Hungarian Academy of Sciences) · 2025
Typearticle
Languagehu
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsFlash floodFlood mythCurrent (fluid)Water sourceHydrology (agriculture)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

A 21. században nem tartható fenn a jelenlegi vízgazdálkodási gyakorlat, ezért a víz lesz századunk egyik legnagyobb kihívása. A vízválság egyik tényezője a sok víz” problémája, amely három területen jelentkezik: a folyók árvizeinél, a települések úgynevezett helyi vízkárainál és hazai sajátosságként a belvizeknél. A tanulmány áttekinti az elmúlt negyedszázad szélsőséges hidrológiai eseményeit (árvizeket, villámárvizeket és belvizeket), megfogalmazza az ezekből leszűrhető tapasztalatokat, és bemutatja a kezelésükre alkalmazott újszerű műszaki megoldásokat. | Current water management practices cannot be sustained in the 21st century, so water will be one of the greatest challenges of our century. One factor in the water crisis is the problem of “too much water”, which occurs in three areas: river floods, water damage to settlements, and inland waters, which are a Hungarian specialty. The study reviews the extreme hydrological events (floods, flash floods and inland waters) that have occurred in the past quarter century, formulates the lessons learned from them, and presents innovative technical solutions applied to their management. In the period after 1998 – until today – 11 significant floods have occurred on Hungarian rivers (Fig. 1), which – based on their various parameters – can be classified as extraordinary. Flash floods were registered on several occasions on small watercourses in Hungary between 2005 and 2023. The protection strategy against them requires a complex series of measures, the most important element of which is the retention of water in reservoirs. In the last 100–180 years, new and higher flood levels have developed on the Tisza River and its tributaries. Fig. 4 illustrates their succession and increase. In the last few decades, the intensity of the flood level rise has increased in several sections. The strategic issues for the development of domestic flood protection are the causes, expected pace and extent of this water level increase. To improve flood protection of the Tisza River, lowland flood reservoirs were designed and built. A total of seven such reservoirs were completed between 2004 and 2022. These reservoirs are capable of retaining 771 million m3 of water over an area of 273 km2 (Fig. 5). Hungary’s inland water vulnerability is unique worldwide. The area threatened by inland water in our country is approximately 44,000 km2, 47% of the country’s territory. Extremely large inland waters threaten 400–500 thousand hectares in Hungary; under average conditions, 80–100 thousand hectares are flooded (Fig. 6). Hungary has a unique protection organization, expertise and experience in the world for flood and inland water protection. In the past 25 years, numerous novelties, new technical solutions and innovations have been introduced and applied in flood and inland water protection. The study reviews the most important developments.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueRepository of the Academy's Library (Library of the Hungarian Academy of Sciences)Same topicFlood Risk Assessment and ManagementFrench-language works237,207