[논문]실측유량 자료를 활용한 홍수량 빈도해석 기법 평가

김태정; 김장경; 송재현; 김진국; 권현한

doi:10.3741/jkwra.2022.55.5.333

[국내논문] 실측유량 자료를 활용한 홍수량 빈도해석 기법 평가
Evaluation of flood frequency analysis technique using measured actual discharge data 원문보기

Journal of Korea Water Resources Association = 한국수자원학회논문집, v.55 no.5, 2022년, pp.333 - 343

김태정 (한국수자원조사기술원 전략기획실) , 김장경 (베이지안웍스) , 송재현 (인하대학교 토목공학과) , 김진국 (한국건설기술연구원 수자원하천연구본부) , 권현한 (세종대학교 공과대학 건설환경공학과)

초록
AI-Helper

수자원의 계획 및 설계에 활용되는 홍수량 산정 방법은 홍수량 빈도해석 방법과 강우-유출모형에 의한 방법이 사용된다. 홍수량 빈도해석 방법은 홍수량 자료를 직접 빈도해석 하여 확률홍수량을 산정하며 이론적으로 가장 정확한 방법으로 평가된다. 기존의 홍수량 해석은 자료의 제약으로 인하여 실측유량의 직접 빈도해석은 한계가 있었으나 과거부터 국가적으로 수문조사를 수행하여 10년 이상의 실측유량 자료를 확보할 수 있는 수준에 도달하였다. 본 연구는 수위-유량 관계곡선식을 통하여 안정적으로 확보된 실측유량 자료를 활용하여 홍수량 빈도해석을 수행하였다. 홍수량 빈도해석을 위하여 Bayesian 기법을 적용하여 매개변수를 산정하고 빈도별 홍수량의 불확실성을 정량화하였다. 확률홍수량 산정 결과는 장기간의 강우량 자료를 적용하여 강우-유출모형으로 산정된 홍수량과 근접한 것을 확인하였다. 수문조사를 통하여 장기간의 실측유량 자료를 활용하여 다각적인 관점으로 수문해석이 가능할 것으로 판단된다.

Abstract ▼ AI-Helper

For water resource management, the design flood is calculated using the flood frequency analysis technique and the rainfall runoff model. The method by design flood frequency analysis calculates the stochastic design flood by directly analyzing the actual discharge data and is theoretically evaluated as the most accurate method. Actual discharge data frequency analysis of the measured flow was limited due to data limitations in the existing flood flow analysis. In this study, design flood frequency analysis was performed using the measured flow data stably secured through the water level-discharge relationship curve formula. For the frequency analysis of design flood, the parameters were calculated by applying the bayesian inference, and the uncertainty of flood volume by frequency was quantified. It was confirmed that the result of calculating the design flood was close to that calculated by the rainfall-runoff model by applying long-term rainfall data. It is judged that hydrological analysis can be done from various perspectives by using long-term actual flow data through hydrological survey.

Keyword

표/그림 (13)

그림 Fig. 1. Hydrological survey method conducted by KIHS
표 Table 1. Current status of streamflow measurement stations performed by KIHS
그림 Fig. 2. Development of rating curve at seoulsi (Jungranggyo) by KIHS Hydrological survey annual report
표 Table 2. Current status of data duration at streamflow stations each river basin (accrued)
표 Table 3. 6 Station information and control flood by rating curve (unit : m³/s)
그림 Fig. 3. Visualization of discharge data. (a): Yeongwolgun (Yeongwoldaegyo) station, (b): Guryegun (Guryegyo) station
그림 Fig. 4. Goodness-of-fit test based in gumbel probability plot and empirical CDF at water level station Yeoncheongun (Saranggyo)
그림 Fig. 5. A comparison of Gumbel distribution parameters using Bayesian model and ML
표 Table 4. Station information and control flood by rating curve (unit : m³/s)
표 Table 5. Parameter estimation result using Bayesian model and ML
표 Table 6. The estimated design flood according to Bayesian-based return periods (unit : m³/s)
표 Table 7. The estimated design flood according to ML-based return periods (unit : m³/s)
그림 Fig. 6. Uncertainty bounds associated with design flood and comparison between bayesian and ML based frequency analysis

참고문헌 (26)

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