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Record W2025945116 · doi:10.3741/jkwra.2010.43.10.865

An Analysis of the Effect of Climate Change on Flow in Nakdong River Basin Using Watershed-Based Model

2010· article· en· W2025945116 on OpenAlexaboutno aff
Tae-Seok Shon, Sang‐Do Lee, Sangdan Kim, Hyun-Suk Shin

Bibliographic record

VenueJournal of Korea Water Resources Association · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceWatershedSWAT modelClimate changePrecipitationStructural basinDrainage basinHydrology (agriculture)StreamflowSurface runoffSoil and Water Assessment ToolGeologyMeteorologyGeographyEcology

Abstract

fetched live from OpenAlex

미래기후에 대한 수환경 평가는 기후자료를 입력 값으로 요구하는 강우-유출모형을 이용하거나 유량 이외에 유사, 영양물질과 같은 수질인자를 동시에 모의할 수 있는 유역모형을 이용하여 평가하는 것이 일반적이다. 따라서 본 연구에서는 유역 모형으로 SWAT를 선정하고 낙동강 유역을 대상 유역으로 하여 기후변화로 인한 하천 유량의 영향을 분석하였다. 전지구기후모형(GCM: Global Climate Model)중 비교적 한반도의 기후 특성을 잘 재현하고 있는 호주(CSIRO: Mk3.0, 즉 CSMK) 모형과 캐나다(CCCma: CGCM3-T47, 즉 CT47) 모형의 A2, B1, A1B 시나리오를 SWAT 모형의 입력 자료로 활용하였다. 각 시나리오의 미래의 기온과 강우의 증가율을 분석하고 현재와 미래기후변화 시나리오에 따른 유량과 유량변동성을 연, 계절, 중기간으로 나누어 비교, 분석하였으며, 대부분의 지점에서 기온 및 유량이 증가하였으며 기후변화는 하천 및 호소의 수온상승과 유량변화에 큰 영향을 줄 것으로 예상되기 때문에 향후 본 연구의 결과를 토대로 기후변화에 따른 낙동강 유역의 유출량 증대로 인한 수공 구조물의 치수능력 증대 방안을 세워야 할 것이다. To evaluate influence of the future climate change on water environment, it is necessary to use a rainfall-runoff model, or a basin model allowing us to simultaneously simulate water quality factors such as sediment and nutrient material. Thus, SWAT is selected as a watershed-based model and Nakdong river basin is chosen as a target basin for this study. To apply climate change scenarios as input data to SWAT, Australian model (CSIRO: Mk3.0, CSMK) and Canadian models (CCCma: CGCM3-T47, CT47) of GCMs are used. Each GCMs which have A2, B1, and A1B scenarios effectively represent the climate characteristics of the Korean peninsula. For detecting climate change in Nakdong river basin, precipitation and temperature, increasing rate of these were analyzed in each scenarios. By simulation results, flow and increasing rate of these were analyzed at particular points which are important in the object basin. Flow and variation of flow in the scenarios for present and future climate changes were compared and analyzed by years, seasons, divided into mid terms. In most of the points temperature and flow rate are increased, because climate change is expected to have a significant effect on rising water temperature and flow rate of river and lake, further on the basis of this study result should set enhancing up water control project of hydraulic structures caused by increasing outer discharge of the Nakdong River Basin due to climate change.

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)0.002
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 score0.041
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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

Citations10
Published2010
Admission routes1
Has abstractyes

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