• 제목/요약/키워드: real-time water level

검색결과 199건 처리시간 0.03초

실시간 범람위험도 예측을 위한 수리학적 모형의 개발 (Hydraulic Model for Real Time Forecasting of Inundation Risk)

  • 한건연;손인호;이재영
    • 한국수자원학회논문집
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    • 제33권3호
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    • pp.331-340
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    • 2000
  • 본 연구의 목적은 하천에서의 실시간 범람위험도 해석을 위해서 DAMBRK 모형과 Kalman filter를 연계한 수치모형을 개발하는데 있다. 본 모형은 1차원 동역학 방정식의 비선형 유한차분 근사해인 음해법을 기본으로 하고 있다. 추계학적 추정법으로서 최적의 갱신 예측치를 얻기 위해 확장된 Kalman filter 기법을 사용하였다. 이 과정은 확정론적 모형에 의한 예측치를 Kalman filter gain factor에 의해 보정된 실시간 관측치와 조합함으로써 수행되었다. 홍수범람위험도는 하도단면의 기하형상과 Manning 조도계수의 변동성을 고려하여 Monte Carlo 모의를 적용하여 예측되었다. 본 모형은 1990년 9월과 1995년 8월의 남한강 홍수에 적용하여 검증하였다. Kalman filter에 의한 해석은 이 기간 동안에 확정론적 해석결과와 비교하여 실측자료와 잘 일치되는 양상이 나타났으며, 이에 따라 제방의 월류위험도를 모의된 홍수위와 제방고를 비교함으로써 얻을 수 있었다.

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무선센서 네트워크 계측을 이용한 저수지 및 제방 계측시스템 구축에 관한 기초연구 (Basic Study on Monitoring System of Reservoir and Leeve Using Wireless Sensor Network)

  • 유찬호;김익훈;이승주;황정순;백승철
    • 한국지반환경공학회 논문집
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    • 제19권1호
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    • pp.25-30
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    • 2018
  • 저수지 및 제방에서의 계측은 가장 높이가 높은 구간을 선정하여 계측기를 매설하고 측정하는 집중계측 방식으로 최근에는 자동화 계측기술이 발달되어 실시간으로 계측결과가 관리사무소로 전달 및 수집, 저장되고 있다. 실시간 계측기술이 발달되었음에도 불구하고 계측결과가 시설물 관리와는 직접적으로 이용되지 못하고 있다. 최근 사물인터넷 기반의 무선 센서 네트워크 계측기술이 발달함에 따라 본 연구에서는 저수지 및 제방 구조물에 무선센서 네트워크 기술을 기반의 실시간 계측 및 평가시스템을 제안하였다. 적용성 평가를 위한 침투해석 결과 저수위 변화에 따라 제체 내부의 침윤선 변화와 함께 토체의 체적함수비가 함께 변화하여 체적함수비를 센서 노드로 설정한 계측시스템의 적용성을 확인하였다.

IoT를 사용한 센서 네트워크 기반의 실시간 토양 습도 모니터링 (Real-Time Soil Humidity Monitoring Based on Sensor Network Using IoT)

  • 김경헌;김희동
    • 한국전기전자재료학회논문지
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    • 제35권5호
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    • pp.459-465
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    • 2022
  • This paper reports a method to use a wireless sensor network deployed in the field to real-time monitor soil moisture, warning when the moisture level reaches a specific value, and wirelessly controlling an additional device (LED or water supply system, etc.). In addition, we report all processes related to wireless irrigation system, including field deployment of sensors, real-time monitoring using a smartphone, data calibration, and control of additional devices deployed in the field by smartphone. A commercially available open-source Internet of Things (IoT) platform, NodeMCU, was used, which was combined with a 9V battery, LED and soil humidity sensor to be integrated into a portable prototype. The IoT-based soil humidity sensor prototype deployed in the field was installed next to a tree for on-site demonstration for the measurement of soil humidity in real-time for about 30 hours, and the measured data was successfully transmitted to a smartphone via Wifi. The measurement data were automatically transmitted via e-mail in the form of a text file, stored on the web, followed by analyses and calibrations. The user can check the humidity of the soil real-time through a personal smartphone. When the humidity of a soil reached a specific value, an additional device, an LED device, placed in the field was successfully controlled through the smartphone. This LED can be easily replaced by other electronic devices such as water supplies, which can also be controlled by smartphones. These results show that farmers can not only monitor the condition of the field real-time through a sensor monitoring system manufactured simply at a low cost but also control additional devices such as irrigation facilities from a distance, thereby reducing unnecessary energy consumption and helping improve agricultural productivity.

임계치 모형과 인공신경망 모형을 이용한 실시간 저수지 수위자료의 이상치 탐지 (Outlier Detection of Real-Time Reservoir Water Level Data Using Threshold Model and Artificial Neural Network Model)

  • 김마가;최진용;방재홍;이재주
    • 한국농공학회논문집
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    • 제61권1호
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    • pp.107-120
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    • 2019
  • Reservoir water level data identify the current water storage of the reservoir, and they are utilized as primary data for management and research of agricultural water. For the reservoir storage management, Korea Rural Community Corporation (KRC) installed water level stations at around 1,600 agricultural reservoirs and has been collecting the water level data every 10 minutes. However, various kinds of outliers due to noise and erroneous problems are frequently appearing because of environmental and physical causes. Therefore, it is necessary to detect outlier and improve the quality of reservoir water level data to utilize the water level data in purpose. This study was conducted to detect and classify outlier and normal data using two different models including the threshold model and the artificial neural network (ANN) model. The results were compared to evaluate the performance of the models. The threshold model identifies the outlier by setting the upper/lower bound of water level data and variation data and by setting bandwidth of water level data as a threshold of regarding erroneous water level. The ANN model was trained with prepared training dataset as normal data (T) and outlier (F), and the ANN model operated for identifying the outlier. The models are evaluated with reference data which were collected reservoir water level data in daily by KRC. The outlier detection performance of the threshold model was better than the ANN model, but ANN model showed better detection performance for not classifying normal data as outlier.

도시하천방재를 위한 지능형 모니터링에 관한 연구 (Monitoring Technology for Flood Forecasting in Urban Area)

  • 김형우;이범교
    • 한국방재학회:학술대회논문집
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    • 한국방재학회 2008년도 정기총회 및 학술발표대회
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    • pp.405-408
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    • 2008
  • Up to now, a lot of houses, roads and other urban facilities have been damaged by natural disasters such as flash floods and landslides. It is reported that the size and frequency of disasters are growing greatly due to global warming. In order to mitigate such disaster, flood forecasting and alerting systems have been developed for the Han river, Geum river, Nak-dong river and Young-san river. These systems, however, do not help small municipal departments cope with the threat of flood. In this study, a real-time urban flood forecasting service (U-FFS) is developed for ubiquitous computing city which includes small river basins. A test bed is deployed at Tan-cheon in Gyeonggido to verify U-FFS. It is found that U-FFS can forecast the water level of outlet of river basin and provide real-time data through internet during heavy rain. Furthermore, it is expected that U-FFS presented in this study can be applied to ubiquitous computing city (u-City) and/or other cities which have suffered from flood damage for a long time.

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조간대에서 조위에 따른 기온과 수온 변화 : 여수 오도섬 (Variations in Air Temperature and Water Temperature with Tide at the Intertidal Zone : Odo Island, Yeosu)

  • 조원기;강동환;김병우
    • 한국환경과학회지
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    • 제31권12호
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    • pp.1027-1038
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    • 2022
  • The intertidal zone has both land and marine characteristics and shows complex weather environments. These characteristics are suited for studying climate change, energy balance and ecosystems, and may play an important role in coastal and marine weather prediction and analysis. This study was conducted at Odo Island, approximately 300m from the mainland in Yeosu. We built a weather observation system capable of real-time monitoring on the mud flat in the intertidal zone and measured actual weather and marine data. Weather observation was conducted from April to June 2022. The results showed changes in air temperature and water temperature with changes in the tide level during spring. Correlation analysis revealed characteristic changes in air temperature and water temperature during the day and night, and with inundation and exposure.

영산호 운영을 위한 홍수예보모형의 개발(III) -배수갑문 조절에 의한 홍수파의 전달- (River Flow Forecasting Model for the Youngsan Estuary Reservoir Operation(III) - Pronagation of Flood Wave by Sluice Gate Operations -)

  • 박창언;박승우
    • 한국농공학회지
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    • 제37권2호
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    • pp.13.2-20
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    • 1995
  • An water balance model was formulated to simulate the change in water levels at the estuary reservoir from sluice gate releases and the inflow hydrographs, and an one-di- mensional flood routing model was formulated to simulate temporal and spatial varia- tions of flood hydrographs along the estuarine river. Flow rates through sluice gates were calibrated with data from the estuary dam, and the results were used for a water balance model, which did a good job in predicting the water level fluctuations. The flood routing model which used the results from two hydrologic models and the water balance model simulated hydrographs that were in close agreement with the observed data. The flood forecasting model was found to be applicable to real-time forecasting of water level fluc- tuations with reasonable accuracies.

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Abundance of the Toxic Dinoflagellate Alexandrium catenella in Jinhae Bay, Korea as Measured by Specific Real-time PCR Probe

  • Park, Tae-Gyu;Kang, Yang-Soon;Park, Young-Tae
    • Fisheries and Aquatic Sciences
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    • 제12권3호
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    • pp.227-235
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    • 2009
  • The marine toxic dinoflagellate Alexandrium catenella has been implicated in numerous paralytic shellfish poisoning (PSP) events in many countries. Due to difficulties in rapidly identifying A. catenella, field-based study of this species has been problematic. The present study developed a TaqMan format A. catenella-specific probe for real-time PCR assay (specific to Korean genotype) based on LSU rDNA sequence information for studying geographic and temporal distribution of the species in surface sediments and water columns of Jinhae Bay, Korea. The field survey from 2007 to 2008 revealed that A. catenella occurred in most seasons at low densities, mostly below 1 cell $mL^{-1}$, and was more abundant in spring (maximum cell density of 2 cells $mL^{-1}$) when shellfish exceed the quarantine toxin level for PSP toxins in Jinhae Bay.

청계천 실시간 홍수예보를 위한 Flow Nomograph 개발 및 평가 (Development and Assessment of Flow Nomograph for the Real-time Flood Forecasting in Cheonggye Stream)

  • 배덕효;심재범;윤성심
    • 한국수자원학회논문집
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    • 제45권11호
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    • pp.1107-1119
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    • 2012
  • 본 연구의 목적은 도시하천으로 복원된 청계천유역의 실시간 홍수예보를 위한 flow nomograph를 개발하고, 실측자료를 통해 flow nomograph의 적용성을 검토하는데 있다. 본 연구의 적용대상 지역인 청계천 유역은 높은 불투수율, 짧은 도달시간 및 복잡한 수문학적 특성을 갖고 있어 기존 강우-유출 모형에 의한 홍수예측 방법의 선행시간 확보 측면에서 실효성을 거두지 못하고 있는 실정이다. 이에 본 연구에서는 홍수예보 선행시간을 확보하기 위해 강우정보만으로도 홍수예보가 가능한 flow nomograph를 개발하였다. Flow nomograph는 강우강도, 강우지속시간 등의 강우변수와 유량, 수위간의 상관관계를 구한 것이다. 본 연구에서는 Flow nomograph 개발과정에서 예보 기준 설정을 위해 홍수예보 지점을 선정하여 지점별 기준 홍수위를 산정하였으며, 다양한 홍수사상을 반영하기 위해 가상 강우시나리오를 설정하여 강우조건별 강우강도와 강우지속시간을 산정하였다. 또한 수위-유량관계 곡선식을 이용하여 기준 홍수위에 따라 홍수량 범위를 결정하고, SWMM모형을 이용하여 강우조건에 따른 지점별 홍수량을 산정하여 예보지점별로 기준홍수 위에 따른 홍수량을 산정하였다. 산정된 강우 시나리오에 따른 강우정보와 기준 홍수위에 따른 홍수량을 이용하여 flow nomograph를 개발하였으며, 이를 실제 홍수사상에 적용하여 평가하였다. 평가 결과 청계천 유역에 대해 flow nomograph의 적용성이 높은 것으로 나타났다. 향후 청계천과 같은 도시하천유역의 홍수예측 방법으로 활용도가 높을 것으로 판단된다.

수중 방사선 감시체계 구축을 위한 실시간 방사선 준위 모니터링 센서 개발 (Development of a Real-time Radiation Level Monitoring Sensor for Building an Underwater Radiation Monitoring System)

  • 박혜민;주관식
    • 센서학회지
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    • 제24권2호
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    • pp.96-100
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    • 2015
  • In the present study, we developed a real-time radiation-monitoring sensor for an underwater radiation-monitoring system and evaluated its effectiveness using reference radiation sources. The monitoring sensor was designed and miniaturized using a silicon photomultiplier (SiPM) and a cerium-doped-gadolinium-aluminum-gallium-garnet (Ce:GAGG) scintillator, and an underwater wireless monitoring system was implemented by employing a remote Bluetooth communication module. An acrylic water tank and reference radiation sources ($^{137}Cs$, $^{90}Sr$) were used to evaluate the effectiveness of the monitoring sensor. The underwater monitoring sensor's detection response and efficiency for gamma rays and beta particles as well as the linearity of the response according to the gammaray intensity were verified through an evaluation. This evaluation is expected to contribute to the development of base technology for an underwater radiation-monitoring system.