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기계학습모형을 이용한 다분광 위성 영상 기반 낙동강 부유 물질 농도 계측 기법 개발
권시윤,서일원,백동해,Kwon, Siyoon,Seo, Il Won,Beak, Donghae 한국수자원학회 2021 한국수자원학회논문집 Vol.54 No.2
Suspended Solids (SS) generated in rivers are mainly introduced from non-point pollutants or appear naturally in the water body, and are an important water quality factor that may cause long-term water pollution by being deposited. However, the conventional method of measuring the concentration of suspended solids is labor-intensive, and it is difficult to obtain a vast amount of data via point measurement. Therefore, in this study, a model for measuring the concentration of suspended solids based on remote sensing in the Nakdong River was developed using Sentinel-2 data that provides high-resolution multi-spectral satellite images. The proposed model considers the spectral bands and band ratios of various wavelength bands using a machine learning model, Support Vector Regression (SVR), to overcome the limitation of the existing remote sensing-based regression equations. The optimal combination of variables was derived using the Recursive Feature Elimination (RFE) and weight coefficients for each variable of SVR. The results show that the 705nm band belonging to the red-edge wavelength band was estimated as the most important spectral band, and the proposed SVR model produced the most accurate measurement compared with the previous regression equations. By using the RFE, the SVR model developed in this study reduces the variable dependence compared to the existing regression equations based on the single spectral band or band ratio and provides more accurate prediction of spatial distribution of suspended solids concentration.
센서 기반 모니터링 자료를 활용한 임하댐 저수지 탁수 예측 정확도 개선
김종민,이상웅,권시윤,정세웅,김영도,Kim, Jongmin,Lee, Sang Ung,Kwon, Siyoon,Chung, Se Woong,Kim, Young Do 한국수자원학회 2022 한국수자원학회논문집 Vol.55 No.11
In Korea, about two-thirds of the precipitation is concentrated in the summer season, so the problem of turbidity in the summer flood season varies from year to year. Concentrated rainfall due to abnormal rainfall and extreme weather is on the rise. The inflow of turbidity caused a sudden increase in turbidity in the water, causing a problem of turbidity in the dam reservoir. In particular, in Korea, where rivers and dam reservoirs are used for most of the annual average water consumption, if turbidity problems are prolonged, social and environmental problems such as agriculture, industry, and aquatic ecosystems in downstream areas will occur. In order to cope with such turbidity prediction, research on turbidity modeling is being actively conducted. Flow rate, water temperature, and SS data are required to model turbid water. To this end, the national measurement network measures turbidity by measuring SS in rivers and dam reservoirs, but there is a limitation in that the data resolution is low due to insufficient facilities. However, there is an unmeasured period depending on each dam and weather conditions. As a sensor for measuring turbidity, there are Optical Backscatter Sensor (OBS) and YSI, and a sensor for measuring SS uses equipment such as Laser In-Situ Scattering and Transmissometry (LISST). However, in the case of such a high-tech sensor, there is a limit due to the stability of the equipment. Therefore, there is an unmeasured period through analysis based on the acquired flow rate, water temperature, SS, and turbidity data, so it is necessary to develop a relational expression to calculate the SS used for the input data. In this study, the AEM3D model used in the Water Resources Corporation SURIAN system was used to improve the accuracy of prediction of turbidity through the turbidity-SS relationship developed based on the measurement data near the dam outlet.
초분광영상 기반 탁수 모니터링에서의 탁도-SS 관계식 적용성 검토
김종민,김광수,권시윤,김영도,Kim, Jongmin,Kim, Gwang Soo,Kwon, Siyoon,Kim, Young Do 한국수자원학회 2023 한국수자원학회논문집 Vol.56 No.12
우리나라의 강우 특성은 여름철 홍수기에 집중되어있다. 특히 이상강우 및 기상이변에 의한 집중강우의 증가 추세로 다량의 탁수가 댐 내에 유입될 시 전도현상으로 인해 탁수 장기화 현상이 발생하게 된다. 이러한 문제를 해결하기 위한 탁수 예측을 통한 선제적 조치 방안 또는 댐 운영방안 마련에 많은 연구가 진행되고 있다. 탁수 예측을 위해서는 상류 유입부의 탁수 자료를 필요로 하지만 현재 시·공간적인 데이터 해상도는 부족한 실정이다. 시간적 해상도 개선을 위해서는 탁도-SS 관계식에 대한 개발을 필요로 하며 공간적 해상도 개선을 위해 다항목수질측정기(YSI), 레이저부유사측정기(Laser In-Situ Scattering and Transmissometry, LISST), 초분광 센서 등의 센서 기반 측정을 통해 선, 면 단위 데이터 측정을 통해 탁수에 대한 공간적 해상도를 개선할 수 있다. 또한 LISST-200X의 경우 입경 크기 등에 대한 자료 수집이 가능함에 따라 분율(Clay : Silt : Sand)에 대한 탁도-SS 관계식에 활용될 수 있다. 또한 최근 원격탐사 방안 중 다른 탑재체에 비해 공간해상도 및 시간해상도가 높은 UAV와 분광·방사 해상도가 높은 초분광 센서를 활용 시 탁수 발생에 대한 공간적인 분포를 제시할 수 있다. 따라서, 본 연구에서는 LISST-200X 및 YSI-EXO를 활용하여 실험실 분석을 통해 분율(Clay : Silt : Sand)에 따라 탁도-SS 관계식을 산정하였으며 UAV (Matrice 600), 초분광센서(microHSI 410 SHARK)를 포함한 센서 기반 현장 측정을 통해 탁도와 부유사 농도, 측정된 부유사농도 기반 탁도-SS 관계식을 이용하여 산정한 탁도에 대하여 공간적 분포를 제시하였다. 이를 통해 탁도-SS 관계식에 대한 적용성 검토 및 탁수 발생 현황에 대하여 파악하고자 하였다. Rainfall characteristics in Korea are concentrated during the summer flood season. In particular, when a large amount of turbid water flows into the dam due to the increasing trend of concentrated rainfall due to abnormal rainfall and abnormal weather conditions, prolonged turbid water phenomenon occurs due to the overturning phenomenon. Much research is being conducted on turbid water prediction to solve these problems. To predict turbid water, turbid water data from the upstream inflow is required, but spatial and temporal data resolution is currently insufficient. To improve temporal resolution, the development of the Turbidity-SS conversion equation is necessary, and to improve spatial resolution, multi-item water quality measurement instrument (YSI), Laser In-Situ Scattering and Transmissometry (LISST), and hyperspectral sensors are needed. Sensor-based measurement can improve the spatial resolution of turbid water by measuring line and surface unit data. In addition, in the case of LISST-200X, it is possible to collect data on particle size, etc., so it can be used in the Turbidity-SS conversion equation for fraction (Clay: Silt: Sand). In addition, among recent remote sensing methods, the spatial distribution of turbid water can be presented when using UAVs with higher spatial and temporal resolutions than other payloads and hyperspectral sensors with high spectral and radiometric resolutions. Therefore, in this study, the Turbidity-SS conversion equation was calculated according to the fraction through laboratory analysis using LISST-200X and YSI-EXO, and sensor-based field measurements including UAV (Matrice 600) and hyperspectral sensor (microHSI 410 SHARK) were used. Through this, the spatial distribution of turbidity and suspended sediment concentration, and the turbidity calculated using the Turbidity-SS conversion equation based on the measured suspended sediment concentration, was presented. Through this, we attempted to review the applicability of the Turbidity-SS conversion equation and understand the current status of turbid water occurrence.