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2025 Vol.58, Issue 10 Preview Page

Research Article

Development and application of a data-driven prediction model for real-time flood response in small streams

소하천의 실시간 홍수 대응을 위한 데이터 기반 예측모형 개발 및 적용

Tae Sung Cheonga
,
Hosun Kangb
,
SungJe Yec*
정 태성a
,
강 호선b
,
예 성제c*
aSenior Research Officer, National Disaster Management Research Institute, Ulsan, Korea
bResearch Officer, National Disaster Management Research Institute, Ulsan, Korea
cPrincipal Research, National Disaster Management Research Institute, Ulsan, Korea
a국립재난안전연구원 연구관
b국립재난안전연구원 연구사
c국립재난안전연구원 책임연구원
*Corresponding Author
31 October 2025. pp. 869-881
PDF XML Citation
Abstract

The increasing frequency of localized torrential rainfall due to climate change has exacerbated flood damage in small streams, where steep slopes and irregular channel geometries cause rapid fluctuations in water level and flow rate. These dynamic conditions limits the accuracy and responsiveness of conventional flood forecasting systems. The research develops a real-time flood prediction model tailored to the hydrologic and hydraulic characteristics of small streams. The model integrates smart monitoring and management systems, the Automated Weather Stations, and the MAPLE forecast rainfall data to enhance prediction accuracy. A four-parameter nonlinear nomograph and the Manning equation has been employed to enable flood water surface elevation estimation even in ungauged sections. The roughness coefficient is optimized in real-time using the Levenberg-Marquardt algorithm to improve model reliability. The proposed model has been applied to nine pilot small stream sites, demonstrating strong correlation with observed data and no overflow of embankment levels, thereby confirming its predictive performance. The research provides a data-driven, integrated modeling approach that strengthens preemptive flood response capabilities and holds potential for broader application in small to mid-sized river basins.

Keywords
Small stream flood forecasting
Real-time prediction modeling
Data-driven prediction model
Smart monitoring and management system
Manning equation optimization

최근 기후 변화로 인한 국지성 집중호우의 빈도 증가로 소하천에서의 홍수 발생 및 피해가 심화되고 있으나, 지형적 특성상 짧은 시간 내 수위와 유량이 급변하여 수치모형에 기반한 기존의 홍수 예측 시스템으로는 정밀한 대응이 어려운 실정이다. 본 연구는 소하천의 수문·수리학적 특성을 반영한 실시간 예측 기법을 제안하고, 이를 위해 행정안전부의 스마트 계측관리 시스템과 기상청의 방재기상관측장비, MAPLE 예측 강우 데이터를 연계한 데이터 기반 예측모형을 개발하였다. 연구에서는 4변수 비선형 노모그래프와 Manning 방정식을 활용하여 미계측 구간에서도 홍수위를 예측할 수 있도록 하였으며, 조도계수의 실시간 최적화를 통해 예측의 정확성과 안정성을 확보하였다. 제안된 예측모형을 9개 시범 소하천에 적용한 결과 실제 수위 자료와 높은 상관성을 보였고, 제방고를 초과하는 범람이 나타나지 않아 신뢰성 있는 결과를 도출하였다. 본 연구는 실측 기반 융합모델을 통한 선제적 대응 역량을 제고함으로써, 향후 소하천뿐 아니라 다양한 중소하천의 재해예방 및 실시간 홍수 예·경보 체계 구축에 기여할 수 있을 것으로 기대된다.

키워드
소하천 홍수 예측
실시간 수문 모형화
데이터 기반 예측모형
스마트 계측관리 시스템
매닝방정식 최적화
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Information
  • Publisher :KOREA WATER RESOURECES ASSOCIATION
  • Publisher(Ko) :한국수자원학회
  • Journal Title :Journal of Korea Water Resources Association
  • Journal Title(Ko) :한국수자원학회 논문집
  • Volume : 58
  • No :10
  • Pages :869-881
  • Received Date : 2025-05-13
  • Revised Date : 2025-08-27
  • Accepted Date : 2025-09-05
  • DOI :https://doi.org/10.3741/JKWRA.2025.58.10.869
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