Unified Guidelines for Drought Condition Monitoring in Local Dams and Rivers in South Korea
Bibliographic record
Abstract
Drought assessment is a critical component of water resource management, ensuring the stability of water supplies and minimizing the impacts of droughts. Focusing on percentile-based criteria and available water supply duration, the United States Drought Monitor (USDM) employs a five-tiered drought assessment ranging from abnormally dry conditions (D0) to exceptional drought (D4), with percentiles delineating each stage. Camrose City in Canada monitors drought conditions in four stages: watch, warning, critical, and emergency based on the number of days water can be supplied to the population. These monitoring schemes highlight the importance of hydrological and statistical data in identifying drought conditions and guiding proactive responses.Considering the practices of drought monitoring in Building on these international practices, this study proposes a unified guideline for drought condition monitoring schemes for dams and rivers in South Korea. The guideline incorporates percentile thresholds (30%, 20%, 10%, 5%) for indicators such as reservoir storage rates and river levels. For reservoir management, thresholds are set based on water availability durations (90, 60, 30, 20 days).The drought monitoring guideline is further validated using two methods for a testbed, the Dongbok Dam; the supply-based criteria defined thresholds as 25.6-17.1-8.5-5.7 million m³ for reservoir volume and 28-19-9-6% for reservoir rates. Alternatively, the percentile-based method yielded thresholds of 52.8-44.2-32.3-25.4%. The Pyeongchang River was selected as a representative case for rivers where supply-based criteria are inapplicable. The 10-day percentile-based criteria showed higher thresholds during the flood season (April–September) and lower thresholds during the non-flood season (October–February).This research emphasizes integrating global best practices into localized drought monitoring systems. By adopting standardized and scientifically robust methods, water resource managers can improve resilience against droughts and ensure sustainable water availability for future generations.Acknowledgment: This work was supported by the 2023-2024 K-water through research on improving dam operation strategies to respond to drought, funded by the Korea Ministry of Environment(MOE)(grant number).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".