Earticle

초록

영어

In this study, Mike11 will be used as the numerical model where a data assimilation method will be applied to it. This paper aims to gain an insight and understanding of data assimilation in flood forecasting models. It will start with a general discussion of data assimilation, followed by a description of the methodology and discussion of the statistical error forecast model used, which in this case is the linear regression. This error forecast model is applied to the water level forecast simulated by MIKE11 to produced improved forecast and validated against real measurements. It is found that there exists a phase error in the improved forecasts. Hence, 2 general formula are used to account for this phase error and they have shown improvement to the accuracy of the forecasts, where one improved the immediate forecast of up to 5 hours while the other improved the estimation of the peak discharge.

목차

Abstract
 1. Introduction
 2. Model Description
  2.1 WEKA
  2.2 M I KE11 model
 3. Data Assimilation
 4. Methodology
  4.1 Statistics
  4.2 Accounting for Errors
 5. Case Study
  5.1 Overview of the River Networks
  5.2 Rainfall Runoff Model
  5.3 Data
  5.4 Analysis Results
 6. Conclusion
 References

키워드

저자

• Lian Guey Ler [ International Center for Urban Water Hydroinformatics Research & Innovation ] Corresponding author
• Byung Sik Kim [ Korea Institute of Construction Technology ]
• Gye Woon Choi [ Inchen University ]
• Byung Hwa Kang [ National Emergency Management Agency ]
• Jung Jae Kwang [ Green & Clean Engineering ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국습지학회지 [韓國濕地學會誌]

• 간기

  계간

• pISSN

  1229-6031

• eISSN

  2384-0056

• 수록기간

  1999~2026

• 등재여부

  KCI 등재,SCOPUS

• 십진분류

  KDC 472 DDC 570