• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.919-928
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• 2023

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.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.213-213
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• 2023

하천의 합류부는 두 하천이 만나 형성되는 지역으로 복잡한 혼합 거동을 보인다. 합류부에서는 실제로 수리 특성이 유황에 따라 다양하게 변화하고 수환경 특성도 함께 변화하며, 이로 인해 본류와 지류에 비해 다양한 생태학적인 종이 분포하는 등 환경적으로 중요구간 중 하나이다. 합류부의 혼합 거동을 이해하기 위해서는 다양한 유황에 따른 수체 혼합 거동을 2차류를 통해 분석하는 것이 중요하다. 해외의 경우 2차류의 패턴을 통해 합류부에서의 혼합 거동을 공간적으로 분석한바 있으나(Riley and Rhoads, 2012), 대부분의 연구들은 중·소규모의 하천을 대상으로 진행되어 대규모 하천에서의 확인은 미흡한 상태이다. 또한, 실제 현장에서 계측을 통한 데이터 획득과 후 처리의 어려움으로 인해 현재 국내에서는 2차류 패턴을 통해 대규모 하천 합류부의 혼합 거동을 확인한 사례는 전무한 실정이다. 따라서, 본 연구에서는 Sontek사의 ADCP를 통해 계측된 수리 데이터를 Rozovskii의 방법을 기반으로 한 2차류로 나타내 낙동강-금호강 합류부에서의 공간적인 수체 혼합을 확인하였다. 혼합거리를 판단하기 위해 합류 이후 혼합의 경계면(Shear Layer)에서 나타나는 2차류의 특이한 패턴(Helical motion)을 주요 지표(Index)로 사용하였다. 그리고, 수질 센서인 YSI EXO2의 수표면 전기전도도의 분포를 통해 합류부에서 본류와 지류의 혼합거리를 산정하였으며, 2차류의 패턴과 비교하였다. 분석 결과, 대규모 하천에서 2차류의 특이한 패턴이 존재함을 명확히 확인하였다. 본류와 지류의 모멘텀 비에 따라 서로 다른 패턴의 혼합양상을 2차류를 통해 확인할 수 있었으며, 2차류의 혼합 패턴과 전기전도도의 분포를 비교 분석하여 합류부에서의 혼합을 3차원적으로 해석하였다.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.931-939
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• 2022

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.