• Title/Summary/Keyword: Reservoir Park

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A Study on the Development of "Bufo gargarizans" Habitat Suitability Index(HSI) (두꺼비 서식지 적합성 지수(HSI) 모델개발을 위한 연구)

  • Cho, Gun-Young;Koo, Bon-Hak
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.25 no.2
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    • pp.23-38
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    • 2022
  • This study investigates the characteristics and physical habitat requirements for each Bufo gargarizans life history through a literature survey. After deriving variables for each component of Bufo gargarizans, in order to reduce regional deviations from eight previously studied literature research areas for deriving the criteria for variables, a total of 12 natural habitats of Bufo gargarizanss are selected as spatial ranges by selecting four additional sites such as Umyeonsan Ecological Park in Seoul, Wonheungibangjuk in Cheongju in the central region, Changnyeong Isan Reservoir in the southern region, and Mangwonji in Daegu. This study presents Bufo gargarizans SI, a species endemic to Korea, whose population is rapidly declining due to large-scale housing site development and road development, and develops a Bufo gargarizans HSI model accordingly to improve the function of the damaged Bufo gargarizans habitat and to present an objective basis for site selection of alternative habitat. At the same time, it provides basic data for adaptive management and follow-up monitoring. The three basic habitat requirements of amphibians, the physical habitat requirements of Bufo gargarizans, synthesized with shelter, food, and water, and the characteristics of each life history, are classified into five components by adding space and threats through literature research and expert advice. Variables are proposed by synthesizing and comparing the general characteristics of amphibians, among the previously studied single species of amphibians, the components of HSI of goldfrogs and Bufo gargarizans, and the ecological and physical environmental characteristics of Bufo gargarizans. Afterwards, through consultation with an amphibian expert, a total of 10 variables are finally presented by adjacent forest area(ha), the distance between spawning area and the nearest forest land(m), the soil, the distance from the wetland(m), the forest layered structure, the low grassland space, the permanent wetland area(ha), shoreline slope(%), PH, presence of predators, distance from road(m), presence or absence of obstacles. n order to derive the final criteria for each of the 10 variables, the criteria(alternative) for each variable are presented through geographic information analysis of the site survey area and field surveys of the previously studied literature research area. After a focus group interview(FGI) of 30 people related to the Bufo gargarizans colony in Cheongju, a questionnaire and in-depth interviews with three amphibians experts are conducted to verify and supplement the criteria for each final variable. Based on the finally developed Bufo gargarizans HSI, the Bufo gargarizans habitat model is presented through the SI graph model and the drawing centering on the Bufo gargarizans spawning area

Prediction of cyanobacteria harmful algal blooms in reservoir using machine learning and deep learning (머신러닝과 딥러닝을 이용한 저수지 유해 남조류 발생 예측)

  • Kim, Sang-Hoon;Park, Jun Hyung;Kim, Byunghyun
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1167-1181
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    • 2021
  • In relation to the algae bloom, four types of blue-green algae that emit toxic substances are designated and managed as harmful Cyanobacteria, and prediction information using a physical model is being also published. However, as algae are living organisms, it is difficult to predict according to physical dynamics, and not easy to consider the effects of numerous factors such as weather, hydraulic, hydrology, and water quality. Therefore, a lot of researches on algal bloom prediction using machine learning have been recently conducted. In this study, the characteristic importance of water quality factors affecting the occurrence of Cyanobacteria harmful algal blooms (CyanoHABs) were analyzed using the random forest (RF) model for Bohyeonsan Dam and Yeongcheon Dam located in Yeongcheon-si, Gyeongsangbuk-do and also predicted the occurrence of harmful blue-green algae using the machine learning and deep learning models and evaluated their accuracy. The water temperature and total nitrogen (T-N) were found to be high in common, and the occurrence prediction of CyanoHABs using artificial neural network (ANN) also predicted the actual values closely, confirming that it can be used for the reservoirs that require the prediction of harmful cyanobacteria for algal management in the future.

A study on environmental flow release through flood control reservoir (담양·화순 홍수조절지 환경대응용수 활용방안 연구)

  • Dong Gue Choe;Jong Duk Park;Dong Jin Kim;Seon Woong Ryu;Soo Jin Lee
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.371-371
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    • 2023
  • 담양 및 화순 홍수조절지는 홍수 시 본류에 계획방류량만 흘러가도록 제수문을 운영하고, 계획방류량을 초과하는 홍수량은 하도 및 조절지 내에 저류하여 홍수를 지체시킨 후 저류된 홍수량은 첨두홍수가 지나간 이후 방류하는 방법으로 영산강 유역의 홍수를 방어하기 위해 '12년 건설되었다. 그러나 홍수조절지는 200년 빈도의 홍수량을 저감 시키도록 설계됨에 따라 준공 이후 10년간 '20년 8월 홍수 등 3회만 홍수방어용으로 활용되었다. 영산강은 오염부하량 대비 유출량 부족 등으로 수질관리에 취약하고 하천유지용수를 공급하는 다목적댐이 없는 등 수자원 확보가 어려우므로, 비홍수기 홍수조절지에 환경대응용수를 담수 및 방류하여 영산강의 유량확보 및 수질개선 등 활용 다변화 방안을 모색하고자 한다. 이와 관련하여 '16년 및 '19년에 시범담수를 실시하였으나, 담수 수질 관리의 어려움, 방류 전후 강우 등 제한적 여건으로 인해 하류 유량증가 및 수질 개선 효과의 확인은 어려웠으며, 제방 물비침 등을 발견하여 시설 안정성 확보가 필요한 것으로 확인되었다. '21년 안정성 확보를 위한 보강 그라우팅을 시행했으며, '19년부터 '21년 2월까지 「홍수조절지를 활용한 영산강 수질개선 방안」연구용역을 실시하여, 비홍수기 활용방안을 수립하였다. '21년 4/4분기 댐과 보 등의 연계운영협의회에 '시범담수 계획' 안건 상정 및 의결을 거쳤고, '22년 3월 25~26일까지 담양 74mm, 화순 61mm 비가 내려 담양 63만m3, 화순 151만m3를 담수하고 18~19일간 저류 후 담양은 평균 3.0m3/초로 25시간 동안, 화순은 평균 5.0m3/초로 32시간 동안 하류로 방류하였다. 방류 후 담양·화순 모두 가까운 하류 수위국 수위 상승을 확인했으며, 화순의 경우 하류 수질에 일부 영향이 있음을 확인하였다. 다만, 초기유출수 배제 등을 고려하지 않아 담수의 수질이 본류보다 좋지 않았으며, 이에 따라 수질 영향의 인과관계 확인이 어려웠다. 기존 연구용역에서 제시한 비홍수기 활용방안의 검증·보완을 위한 연구용역이 '22.5월부터 '23.12월까지 진행될 예정이며, 초기유출수 배제를 위한 조건 재수립, 수질 모니터링지점 확대 등 보완된 '시범담수 계획'을 '23.3월 댐과 보 등의 연계운영협의회에 보고하였다. 연말까지 연구용역과 연계한 시범담수·방류 시행 및 모니터링·효과분석을 통해 비홍수기 홍수조절지 최적운영방안을 마련할 계획이다.

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Habitat Suitability Models of Endangered Wildlife Class II Mauremys reevesii in Gurye-gun, the Republic of Korea (전라남도 구례군에 서식하는 멸종위기 야생생물 II급 남생이의 서식지 적합성 모델 개발)

  • Chang-Deuk Park;Jeongwoo Yoo;Kwanik Kwon;Nakyung Yoo;Moon Seong Heo;Ju-Duk Yoon
    • Journal of Environmental Impact Assessment
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    • v.32 no.2
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    • pp.83-93
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    • 2023
  • This study was conducted to clarify the environmental variables that affect the appearance of Mauremys reevesii and to understand the relationship between M. reevesii and the variables. Habitat environmental survey was implemented by selecting 17 environmental variables considering ecological characteristics of M. reevesii in the main reservoir in Gurye-gun, the Republic of Korea. And the habitat data on the presence and absence of M.reevesii were analyzed statistically. The habitat suitability model of M. reevesii was described in following equation : logit (p) = -3.68 + (0.17 × leaf litter depth) + (1.55 × vegetation coverage of overstory on land) + (0.71 × coverage of midstory on land) + (0.96 × vegetation coverage of understory on water). This information gained is valuable for better understanding the distribution and how to conserve and promote populations of M. reevesii occurring in the Republic of Korea.

Water temperature prediction of Daecheong Reservoir by a process-guided deep learning model (역학적 모델과 딥러닝 모델을 융합한 대청호 수온 예측)

  • Kim, Sung Jin;Park, Hyungseok;Lee, Gun Ho;Chung, Se Woong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.88-88
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    • 2021
  • 최근 수자원과 수질관리 분야에 자료기반 머신러닝 모델과 딥러닝 모델의 활용이 급증하고 있다. 그러나 딥러닝 모델은 Blackbox 모델의 특성상 고전적인 질량, 운동량, 에너지 보존법칙을 고려하지 않고, 데이터에 내재된 패턴과 관계를 해석하기 때문에 물리적 법칙을 만족하지 않는 예측결과를 가져올 수 있다. 또한, 딥러닝 모델의 예측 성능은 학습데이터의 양과 변수 선정에 크게 영향을 받는 모델이기 때문에 양질의 데이터가 제공되지 않으면 모델의 bias와 variation이 클 수 있으며 정확도 높은 예측이 어렵다. 최근 이러한 자료기반 모델링 방법의 단점을 보완하기 위해 프로세스 기반 수치모델과 딥러닝 모델을 결합하여 두 모델링 방법의 장점을 활용하는 연구가 활발히 진행되고 있다(Read et al., 2019). Process-Guided Deep Learning (PGDL) 방법은 물리적 법칙을 반영하여 딥러닝 모델을 훈련시킴으로써 순수한 딥러닝 모델의 물리적 법칙 결여성 문제를 해결할 수 있는 대안으로 활용되고 있다. PGDL 모델은 딥러닝 모델에 물리적인 법칙을 해석할 수 있는 추가변수를 도입하며, 딥러닝 모델의 매개변수 최적화 과정에서 Cost 함수에 물리적 법칙을 위반하는 경우 Penalty를 추가하는 알고리즘을 도입하여 물리적 보존법칙을 만족하도록 모델을 훈련시킨다. 본 연구의 목적은 대청호의 수심별 수온을 예측하기 위해 역학적 모델과 딥러닝 모델을 융합한 PGDL 모델을 개발하고 적용성을 평가하는데 있다. 역학적 모델은 2차원 횡방향 평균 수리·수질 모델인 CE-QUAL-W2을 사용하였으며, 대청호를 대상으로 2017년부터 2018년까지 총 2년간 수온과 에너지 수지를 모의하였다. 기상(기온, 이슬점온도, 풍향, 풍속, 운량), 수문(저수위, 유입·유출 유량), 수온자료를 수집하여 CE-QUAL-W2 모델을 구축하고 보정하였으며, 모델은 저수위 변화, 수온의 수심별 시계열 변동 특성을 적절하게 재현하였다. 또한, 동일기간 대청호 수심별 수온 예측을 위한 순환 신경망 모델인 LSTM(Long Short-Term Memory)을 개발하였으며, 종속변수는 수온계 체인을 통해 수집한 수심별 고빈도 수온 자료를 사용하고 독립 변수는 기온, 풍속, 상대습도, 강수량, 단파복사에너지, 장파복사에너지를 사용하였다. LSTM 모델의 매개변수 최적화는 지도학습을 통해 예측값과 실측값의 RMSE가 최소화 되로록 훈련하였다. PGDL 모델은 동일 기간 LSTM 모델과 동일 입력 자료를 사용하여 구축하였으며, 역학적 모델에서 얻은 에너지 수지를 만족하지 않는 경우 Cost Function에 Penalty를 추가하여 물리적 보존법칙을 만족하도록 훈련하고 수심별 수온 예측결과를 비교·분석하였다.

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Temperature Effect on the Growth and Odorous Material (2-MIB) Production of Pseudanabaena redekei (온도가 남조류 Pseudanabaena redekei의 성장과 냄새물질(2-MIB) 생산에 미치는 영향)

  • Jaehyun Kim;Keonhee Kim;Chaehong Park;Hyunjin Kim;Soon-Jin Hwang
    • Korean Journal of Ecology and Environment
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    • v.56 no.2
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    • pp.151-160
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    • 2023
  • Cyanobacteria Pseudanabaena strains are known to produce 2-MIB(odorous material) in freshwater systems, thereby causing problems in water use. However, their physiological responses to environmental factors in relation with 2-MIB production is not well explored. This study was conducted to evaluate the effect of temperature on the growth and 2-MIB production of Pseudanabaena redekei. The experimental cyanobacteria strains were separated from the Uiam Reservoir (North Han River) and cultured in the BG-11 medium. Temperature was set to 10, 15, 20, 25, and 30℃ for the experiment, in the reflection of the seasonal water temperature variation in situ. For each temperature treatment, cyanobacterial biomass(Chl-a) and 2-MIB concentration (intra-cellular and extra-cellular fractions) were measured every 2 days for 18 days. Both maximal growth and total 2-MIB production of P. redekei appeared at 30℃. While intra-cellular 2-MIB contents were similar (26~29 ng L-1) regardless of treated temperatures, extra-cellular 2-MIB concentration was higher only in high temperature conditions (25~30℃), indicating that the extents of 2-MIB biosynthesis and release by P. redekei vary with temperature. The 2-MIB productivity of P. redekei was much higher in low-temperature conditions (10~15℃) than high temperature conditions (25~30℃). This study demonstrated that temperature was a critical factor contributing to 2-MIB biosynthesis and its release in cell growth (r=0.605, p<0.01). These results are important to understand the dynamics of 2-MIB in the field and thereby provide basic information for managing odorous material in drinking water resources.

A Estimation Study on Water Integration Management Model using Water-Energy-Food-Carbon Nexus - Focused on Yeongsan River - (물-에너지-식량-탄소 넥서스를 이용한 통합물관리 모델 평가 연구 - 영산강 수계를 중심으로 -)

  • Na, Ra;Park, Jin-hyeon;Joo, Donghyuk;Kim, Hayoung;Yoo, Seung-Hwan;Oh, Chang-Jo;Lee, Sang-hyun;Oh, Bu-Yeong;Hur, Seung-oh
    • Journal of Korean Society of Rural Planning
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    • v.29 no.1
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    • pp.37-49
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    • 2023
  • Active attention and effort are needed to develop an integrated water management system in response to climate change. In this study, it proposed models for cross-use of agricultural water and river maintenance water using sewage treatment water as an integrated water management system for the Yeongsan River. The impact of the integrated water management models was assessed by applying the concept of Nexus, which is being presented worldwide for sustainable resource management. The target year was set for 2030 and quantitatively analyzed water, energy, land use and carbon emissions and resource availability index by integrated water management models was calculated by applying maximum usable amount by resource. An integrated water management system evaluation model using the Nexus concept developed in this study can play a role that can be viewed in a variety of ways: security and environmental impact assessment of other resources. The results of this research will be used as a foundation for the field of in the establishment of a policy decision support system to evaluate various security policies, as we analyzed changes in other factors according to changes in individual components, taking into account the associations between water, energy, food, and carbon resources. In future studies, additional sub-models need to be built that can be applied flexibly to changes in the future timing of the inter-resource relationship components.

Relationship between Grain Size and Organic Carbon Content of Surface Sediments in the Major Estuarine Areas of Korea (국내 주요 하구역 표층퇴적물의 입도와 유기탄소 함량 관계)

  • BOO-KEUN KHIM;JU-YEON YANG;HYUK CHOI;KWANGKYU PARK;KYUNG HOON SHIN
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.28 no.4
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    • pp.158-177
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    • 2023
  • An estuary is a transitional water area that links the land and sea through rivers and streams, transporting various components from the land to the sea, which plays an important role in determining primary productivity in the coastal environment, and this coastal ecosystem captures a huge amount of carbon into biomass, known as blue carbon, which mitigates climate change as a potential carbon reservoir. This study examined the variation of mean grain size and organic carbon content of the surface sediments for 6 years and analyzed their relationship in the western and southern estuarine areas (Han River Estuary, Geum River Estuary, Yeongsan River Estuary, Seomjin River Estuary, and Nakdong River Estuary) and the East Sea upwelling area. During the sampling period (2015 to 2020), seasonal variation of both properties was not observed, because their variations might be controlled by diverse oceanographic environments and hydrographic conditions within each survey area. However, despite the synoptic problem of all samples, the positive relationship was obtained between the averages of mean grain size and organic carbon content, which clearly distinguishes each survey area. The unique positive relationship in all estuarine areas implies that the same process by sediment clay particles is important in the organic carbon accumulation. However, additional important factor may be expected in the organic carbon accumulation in the East Sea upwelling area. Further necessary data (sedimentation rate, dry bulk density etc) should be required for the estimation of carbon stock to evaluate the major estuaries in Korea as potential carbon reservoirs in the coastal environment.

A Review of Enhanced Oil Recovery Technology with CCS and Field Cases (CCS와 연계한 석유회수증진 기술 동향 및 현장사례 분석)

  • Park Hyeri;Hochang Jang
    • Journal of the Korean Institute of Gas
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    • v.27 no.3
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    • pp.59-71
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    • 2023
  • Carbon capture, and storage (CCS) is important for the reduction of greenhouse gases and achieving carbon neutrality. CCS focuses on storing captured CO2 permanently in underground reservoirs. CO2-enhanced oil recovery (CO2-EOR) is one form of CCS, where CO2 is injected into the underground to enhance oil recovery. CO2-EOR not only aids in the extraction of residual oil but also contributes to carbon neutrality by storing CO2 underground continuously. CO2-EOR can be classified into miscible and immiscible methods, with the CO2-water alternating gas (CO2-WAG) technique being a representative approach within the miscible method. In CO2-WAG, water and CO2 are alternately injected into the reservoir, enabling oil production and CO2 storage. The WAG method allows for controlling the breakthrough of injection fluids, providing advantages in oil recovery. It also induces hysteresis in relative permeability during the injection and production process, expanding the amount of trapped CO2. In this study, the effects of enhancing oil recovery and storing CO2 underground during CO2-EOR were presented. Additionally, cases of CO2-EOR application in relation to CCS were introduced.

A Research on Applicability of Drone Photogrammetry for Dam Safety Inspection (드론 Photogrammetry 기반 댐 시설물 안전점검 적용성 연구)

  • DongSoon Park;Jin-Il Yu;Hojun You
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.5
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    • pp.30-39
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    • 2023
  • Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.