Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
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Estimation of stream flow discharge using the satellite synthetic aperture radar images at the mid to small size streams

합성개구레이더 인공위성 영상을 활용한 중소규모 하천에서의 유량 추정

  • Seo, Minji (Department of Civil Engineering, Hongik University) ;
  • Kim, Dongkyun (Department of Civil Engineering, Hongik University) ;
  • Ahmad, Waqas (Department of Civil Engineering, Hongik University) ;
  • Cha, Jun-Ho (Han River Flood Control Office, Ministry of Environment)
  • 서민지 (홍익대학교 토목공학과) ;
  • 김동균 (홍익대학교 토목공학과) ;
  • ;
  • 차준호 (한강홍수통제소 수자원정보센터)
  • Received : 2018.08.02
  • Accepted : 2018.10.15
  • Published : 2018.12.31
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Abstract

This study suggests a novel approach of estimating stream flow discharge using the Synthetic Aperture Radar (SAR) images taken from 2015 to 2017 by European Space Agency Sentinel-1 satellite. Fifteen small to medium sized rivers in the Han River basin were selected as study area, and the SAR satellite images and flow data from water level and flow observation system operated by the Korea Institute of Hydrological Survey were used for model construction. First, we apply the histogram matching technique to 12 SAR images that have undergone various preprocessing processes for error correction to make the brightness distribution of the images the same. Then, the flow estimation model was constructed by deriving the relationship between the area of the stream water body extracted using the threshold classification method and the in-situ flow data. As a result, we could construct a power function type flow estimation model at the fourteen study areas except for one station. The minimum, the mean, and the maximum coefficient of determination ($R^2$) of the models of at fourteen study areas were 0.30, 0.80, and 0.99, respectively.

본 연구에서는 2015년에서 2017년 사이에 유럽항공우주국 Sentinel-1 위성이 촬영한 Synthetic Aperture Radar (SAR) 영상을 활용하여 한강 유역 내 하천의 유량을 추정하는 모형을 개발하였다. 한강 유역 내 15개 중소규모 하천을 연구지역으로 선정하였으며 SAR 인공위성 영상 자료와 수위 및 유량관측소에서 산정한 유량 자료를 모형 구축을 위하여 사용하였다. 우선, 오류 보정을 위해 다양한 전처리 과정을 거친 12장의 SAR 영상을 히스토그램 매칭 기법을 적용하여 이미지의 밝기 분포를 동일하게 만들었다. 이후 임계치 분류방식을 사용하여 추출된 하천 수체의 면적과 지상 관측유량자료와의 관계식을 도출하여 유량추정모형을 구축하였다. 그 결과, 1개소를 제외한 14개 관측소에서 인공위성에서 추출한 하천 면적을 입력 자료로 하는 멱함수 형태의 유량추정모형을 구축할 수 있었다. 14개 관측소의 최소, 평균, 최대 결정 계수($R^2$)는 0.3, 0.8, 0.99로 나타났다.

Keywords

SJOHCI_2018_v51n12_1181_f0001.png 이미지

Fig. 1. Study area of the Han river basin, the blue lines represent the river and the white circles represent the gauge station.(a) Gangchon Bridge, (b) Geoun Bridge, (c) Gurun Bbridge, (d) Daegok Bridge, (e) Daeseongri, (f) Bongsang Bridge, (g) Biryong Bridge, (h) Sarang Bridge, (i) Anheung Bridge, (j) Yeongwol Bridge, (k) Eunhyun Bridge, (l) Changhyun Bridge, (m) Jijeong Bridge, (n) Palgoe Bridge, (o) Paldang Bridge

SJOHCI_2018_v51n12_1181_f0002.png 이미지

Fig. 2. Schematic showing the overall methodology

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Fig. 3. Algorithm of finding an optimal target area and a maximum correlation coefficient

SJOHCI_2018_v51n12_1181_f0004.png 이미지

Fig. 5. Relationship between the average side slope and coefficient of determination for the 15 gauge stations

SJOHCI_2018_v51n12_1181_f0005.png 이미지

Fig. 6. A side slope of the cross section at the Sarang bridge and the Daegok bridge

SJOHCI_2018_v51n12_1181_f0006.png 이미지

Fig. 7. Sentinel-1 satellite imagery of (a) Anheung Bridge where water surface area-flow discharge relationship could not be derived and that of (b) Sarang Bridge where water surface area-flow discharge relationship could be clearly derived

SJOHCI_2018_v51n12_1181_f0007.png 이미지

Fig. 8. Relationship between the extracted water surface area (x) and the flow discharge (y) for the 15 gauge stations. The blue triangles represent data for constructing a model, The red lines represent a discharge estimation model and the circles represent validation data

SJOHCI_2018_v51n12_1181_f0008.png 이미지

Fig. 9. Cross section at the Daeseongri, Gapyeonggun. The green line represents maximum water level and the blue line represents minimum water level

SJOHCI_2018_v51n12_1181_f0009.png 이미지

Fig. 10. Relationship between discharge estimated from remotely sensed water surface area and the observed in situ discharge for the 14 gauged stations

SJOHCI_2018_v51n12_1181_f0010.png 이미지

Fig. 4. (a) Target areas for case 1 and case 2 at Sarang Bridge; (b) Correlation coefficient between the water area and discharge varying with different water extraction threshold. Two different curves correspond to different cases of target area (two polygons shown in Fig. 4(a)).; (c) Relationship between the extracted water surface area and discharge based on the target area case 1; (d) Relationship between the extracted water surface area and discharge based on the target area case 2

Table 1. Satellites observing river hydraulic variables currently in operation or in the future

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Table 2. Characteristics of Sentinel-1 IW mode

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Table 3. Correlation equation in water surface area and discharge

SJOHCI_2018_v51n12_1181_t0003.png 이미지

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