• Journal of Korea Water Resources Association
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• v.39 no.1 s.162
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• pp.79-88
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• 2006

An accurate prediction of inflow water temperature is essentially required for real-time simulation and analysis of rainfall-induced turbidity 烈os in a reservoir. In this study, water temperature data were collected at every hour during the flood season of 2004 at the upstream of Daecheong Reservoir to justify its characteristics during rainfall event and model development. A significant drop of river water temperature by 5 to $10^{\circ}C$ was observed during rainfall events, and resulted in the development of density flow regimes in the reservoir by elevating the inflow density by 1.2 to 2.6 kg/$m^3$ Two types of statistical river water temperature models, a logistic model(DLG) and regression models(DMR-1, DMR-2, DMR-3) were developed using the field data. All models are shown to reasonably replicate the effect of rainfall events on the water temperature drop, but the regression models that include average daily air temperature, dew point temperature, and river flow as independent variables showed better predictive performance than DLG model that uses a logistic function to determine the air to water relation.

• Journal of Korean Society on Water Environment
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• v.29 no.6
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• pp.832-841
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• 2013

In recent years, eutrophication in the Paldang Lake has become one of the major environmental problems in Korea as it may threaten drinking water safety and human health. Thus it is important to understand the phenomena and predict the time and magnitude of algal blooms for applying adequate algal reduction measures. This study performed seasonal water quality assessment and chlorophyll-a prediction using Bayseian simple/multiple linear regression analysis. Bayseian regression analysis could be a useful tool to overcome limitations of conventional regression analysis. Also it can consider uncertainty in prediction by using posterior distribution. Generally, chlorophyll-a of a P2(Paldang Dam 2) site showed high concentration in spring and it was similar to that of P4(Paldang Dam 4) site. For the development of Bayseian model, we performed seasonal correlation. As a result, chlorophyll-a of a P2 site had a high correlation with P5(Paldang Dam 5) site in spring (r = 0.786, p<0.05) and with P4 in winter (r = 0.843, p<0.05). Based on the DIC (Deviance Information Criterion) value, critical explanatory variables of the best fitting Bayesian linear regression model were selected as a $PO_4-P$ (P2), Chlorophyll-a (P5) in spring, $NH_3-N$ (P2), Chlorophyll-a (P4), $NH_3-N$ (P4) in summer, DTP (P2), outflow (P2), TP (P3), TP (P4) fall, COD (P2), Chl-a (P4) and COD (P4) in winter. The results of chlorophyll-a prediction showed relatively high $R^2$ and low RMSE values in summer and winter.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.422-422
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• 2018

우리나라의 간척사업은 고려시대 중엽부터 서남해안에 다수 산재되어 있는 천혜적인 간척 적지를 대상으로 지속적으로 추진되어 국토확장 및 식량 자급달성에 기여하여 왔다. 그러나, 최근 들어 쌀 수급 등 농업정책의 변화, 비용에 대한 경제성 평가의 변화, 개발과 보전에 관한 이해당사자간의 대립 등으로 신규 간척사업의 추진이 어려워지고 기존 간척지의 토지이용 목적 변화와 이치수 기능개선을 목적으로 배수갑문을 확장하는 등의 사업이 추진되고 있다. 본 연구에서는 방조제 상류지역 및 지천에서 이상홍수 유입에 따른 방조제 안정성 검토를 실시하였다. 호내로 유입되는 빈도별 홍수량에 따른 각 지점별 수위변화를 이용하여 방조제 비상대처계획에 대한 재난관리 지표로 활용할 수 있는지를 확인한다. 이를 위해 선정된 방조제를 중심으로 빈도별 홍수량을 산정하여 수문학적 안정성을 검토하고, 빈도별 홍수량에 따른 호내의 홍수위 변화를 통하여 비상대처계획 시나리오를 구성하고자 한다. 새만금 유역의 수치모델링에 필요한 범위를 설정하고, 모델 구성 및 자료를 입력한 후 검 보정을 통하여 모델의 신뢰성을 검증한 후 모델운영 조건을 설정하였다. 새만금 종합개발계획(MP)이 완료되었을 경우를 가정하여 통합운영을 실시하였다. 호내 관리수위에 따른 100, 200, 500, PMF 홍수량 유입시에 호내 홍수위 모의를 수행하였다. 또한, 비상단계 중 초기단계인 '관심단계'를 "이상홍수 발생부터 관리수위 EL-1.5m까지"로 설정한다면 방조제 초기 재난대응이 유리해 질 것으로 판단된다. 또한, '주의단계'는 "관리수위 EL-1.5m부터 호내 관리홍수위 EL+1.5m까지"로 '경계단계'를 "호내 관리홍수위 EL+1.5m부터 제당 내측사석보호공 홍수위까지", '심각단계'를 "제당 내측사석보호공(만경유역 EL+4.5m, 동진유역 EL+2.5m) 이상의 홍수위"로 설정한다면 방조제 관리자에게 세부화된 정보 및 지표를 제공해 줄 것이라 판단된다. 방조제 비상상황 단계별 분류에서 이상홍수위 발생후의 시간을 수치모의를 통해 구분하였으며 정성적인 위기상황 판단이 아닌 구체적인 수치로 된 지표들을 방조제 위기상황 재난지표로 활용한다면 상황 관리자의 위기상황 판단과 대처를 위한 의사결정에 도움이 될 것으로 기대한다.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.5
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• pp.323-334
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• 2021

Pilot-scale coagulation and sedimentation processes were operated to investigate the T-P (Total phosphorus) removal efficiency. A multiple regression model was also derived to predict the water quality improvement effect with river water characteristics. The inflow rates for the pilot-scale facility were 157-576 m³/day, and the coagulant doses were in the range of 13.7-58.5 mg/L (average 38.9 mg/L) for PAC (Poly alum chloride) and 16.5-62.1 mg/L (average 36.0 mg/L) for alum. The results found that the influent BOD (Biochemical oxygen demand) and T-P concentrations were 4.9 mg/L and 0.115 mg/L, and the removal efficiencies were 52.7% and 59.4%, respectively. T-P removal efficiencies on wet weather days were higher by 10% than dry weather days because influent solids influenced T-P's coagulation process. The pH of river water was 6.9-7.8, and the average pH was 7.3. Although the pH variation was not significant, the trend showed that the treatment efficiency of T-P and PO₄-P removal increased. Thus, the pH range considered in this study seems to be appropriate for the coagulation process, which is essential for phosphorous removal. The T-P removal efficiencies were 19.6-93.3% (average 59.2%) for PAC and 16.4-98.5%(average 55.9%) for alum; thus, both coagulants showed similar results. Furthermore, the average coagulant doses were similar at 42.4 mg/L for PAC and 41.3 mg/L for alum. When the T-P concentration of the effluent was compared by the [Al]/[P] ratio, the phosphorus concentration of the treated water decreased with an increasing [Al]/[P] ratio, and the lowest T-P concentration range appeared at the [Al]/[P] ratio of 10-30. A seasonal multiple regression analysis equations were derived from the relationships between 10 independent and dependent variables (T-P concentration of effluent). This study could help lake water quality maintenance, reduce eutrophication, and improve direction settings for urban planning, especially plans related to developing waterfront cities.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.6
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• pp.417-424
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• 2021

Algal bloom is an ongoing issue in the management of freshwater systems for drinking water supply, and the chlorophyll-a concentration is commonly used to represent the status of algal bloom. Thus, the prediction of chlorophyll-a concentration is essential for the proper management of water quality. However, the chlorophyll-a concentration is affected by various water quality and environmental factors, so the prediction of its concentration is not an easy task. In recent years, many advanced machine learning algorithms have increasingly been used for the development of surrogate models to prediction the chlorophyll-a concentration in freshwater systems such as rivers or reservoirs. This study used a light gradient boosting machine(LightGBM), a gradient boosting decision tree algorithm, to develop an ensemble machine learning model to predict chlorophyll-a concentration. The field water quality data observed at Daecheong Lake, obtained from the real-time water information system in Korea, were used for the development of the model. The data include temperature, pH, electric conductivity, dissolved oxygen, total organic carbon, total nitrogen, total phosphorus, and chlorophyll-a. First, a LightGBM model was developed to predict the chlorophyll-a concentration by using the other seven items as independent input variables. Second, the time-lagged values of all the input variables were added as input variables to understand the effect of time lag of input variables on model performance. The time lag (i) ranges from 1 to 50 days. The model performance was evaluated using three indices, root mean squared error-observation standard deviation ration (RSR), Nash-Sutcliffe coefficient of efficiency (NSE) and mean absolute error (MAE). The model showed the best performance by adding a dataset with a one-day time lag (i=1) where RSR, NSE, and MAE were 0.359, 0.871 and 1.510, respectively. The improvement of model performance was observed when a dataset with a time lag up of about 15 days (i=15) was added.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.499-508
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• 2011

We analyzed the variations of water quality with flow regime alterations to determine the characteristics of the stream where the stream management is considerably difficult due to the high variability of the flow rates. In this study, both flow rates and water qualities were monitored at the tributaries, 34 in count, of both Geum River and Sabgyo Lake Basins. The variation of water qualities were divided into 2 types, based on their stream flow rates, known as Type I and Type II. If the water quality of a stream increases during low flow rate periods compared with high flow rate periods, it is classified as Type I; if the water quality of the stream increases during high flow rate periods compared with low flow rate periods, it falls under Type II. The analysis for the variations of water qualities, of all 43 basins, resulted to 24 basins under Type I and Nineteen 19 basins under Type II. The variations of water qualities were analyzed first by using Regression Analysis followed by Statistical Analysis. The average slope of the variations of water qualities and the slope of the standard deviations were 0.00135 and 0.00477, respectively. The Probability Distributions of both Type I and Type II basins were 61.1% and 38.9%, respectively. The basin having a probability distribution of 61.1% and is also known as Type I, increases during periods of low flow rates, due to the presence of point sources. Therefore, the basin should be enforced with stream management. Before the stream management can be implemented in all streams falling under Type II, the sources of contaminants should first be estimated. These contaminants can be classified into two parts, the first is Point source pollution and the second is Non-point source pollution, where the Non-Point source pollution can be sub-divided into two types, with storm runoff and without storm runoff.

• Journal of The Geomorphological Association of Korea
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• v.20 no.4
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• pp.15-28
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• 2013

This paper was made on the basis of geotourism to explain morphological characteristics of Patagonia and Atacama region in the Andes through 10-day fieldwork. The Patagonian landscape was focused on the Torres del Paine National Park, Chile and the Los Glacier National Park, Argentina; on the other hand, the Atacama morphological landscape was investigated around the San Pedro de Atacama. Many geomorphological features such as uplift, semiarid and glacier landscapes can be found in Patagonia, so it is strongly recommended to have an opportunity to enjoy these landforms by geotourism. Massive intrusive rock bodies of granite can be shown in those two National Parks declared a Biosphere Reserve by UNESCO. And, the Atacama Desert located on the forearc depression in the Andes, Chile has also many geomorphological destinations of arid and volcanic landforms; badland, pediplain, pediment, salt lake and geyser. Especially, huge pediplain is one of the greatest view points in the Atacama Desert. Patagonia and Atacama are the best geographical tourism sites to know diverse tectonic landforms made by the conflict between South American and Pacific plates.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.27-33
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• 2023

Recently, water shortages have occurred due to climate change, and the need for water management of agricultural water has increased due to the occurrence of algal blooms in reservoirs. Existing algae prevention is operated by putting many people on site and misses the optimal spraying time due to movement through boats. In order to solve this problem, it is necessary to block contamination in advance and move within time to uniformly spray complex microorganisms uniformly. Control drones are used for pesticide spraying and can be applied to algae prevention work by utilizing control drones. In this paper, basic research for the establishment of a marine control system was conducted for application to the reservoir environment, and as one of the results, the characteristics of a drone nozzle, a core technology that can be used for control drones, were calculated. In particular, it was found that the existing agricultural control drones had a disadvantage that the concentration was non-uniform within the suggested spraying interval, and to compensate for this, nozzle positioning and nozzle spraying uniformity were calculated. Based on the experimental results, we develop a core algorithm for establishing an algal bloom monitoring system in the reservoir environment and propose a precision control technology that can be used for marine control work in the future.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.139-150
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• 2024

This study introduced a method of estimating water surface evaporation using the physical-based Penman combination equation (PCE) and the Penman wind function (PWF). A set of regression parameters in the PCE and PWF models were optimized by using the observed evaporation data for the period 2016-2017 in the Yongdam Dam watershed, and their effectiveness was explored. The estimated evaporation over the Deokyu Mountain flux tower demonstrated that the PWF method appears to have more improved results in terms of correlation, but both methods showed overestimation. Further, the PWF method was applied to the observed hydro-meteorological data on the surface of Yongdam Lake. The PWF method outperformed the PCE in the estimation of water surface evaporation in terms of goodness-of-fit measure and visual evaluation. Future studies will focus on a regionalization process which can be effective in estimating water surface evaporation for the ungauged area by linking hydrometeorological characteristics and regression parameters.

• Korean Journal of Heritage: History & Science
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• v.53 no.1
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• pp.52-63
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• 2020

This study was conducted in order to evaluate the characteristics of air temperature fluctuation inside the Daegeumgul, Ondaldonggul, and Seongnyugul Caves, which are the most representative limestone caves in Korea, and also to assess the effects of air temperature on cave temperature. Temperature was measured hourly at three sites in Daegeumgul, Ondaldonggul, and Seongnyugul Caves from April 13 to June 25, 2019. Additionally, air temperature data for the areas around the caves was provided by the Meteorological Administration. Using this collected data, the basic statistical measure of fluctuation characteristics over time was ascertained, and time series analyses were performed. Wide variation of temperature was exhibited in the order of the cave entrance, the cave water inflow point, and the midpoint. Cave temperature was observed to increase gradually during the study period. There was a vast range in temperature at the Daegeumgul station located approximately 150 m outside the cave, but it remained nearly constant beyond the midpoint. Although the effect of air temperature was not significant due to the influence of visitors, the effect of air temperature on cave temperature gradually decreased from the entrance to the interior. At Ondaldonggul, there was a wide range in temperature recorded at the entrance due to the influence of air temperature, but it stayed almost constant in the interior. However, at the site where cave water flows into the cave, temperature was influenced by the cave water temperature. At Seongnyugul, there was a distinct fluctuation in temperature recorded at the cave entrance, while the middle of the cave remained nearly constant. Temperature fluctuated due to the air temperature at the entrance, while at the middle of the cave, measurements were expected to be affected to a greater extent by the lake water temperature than by the air temperature. However, this pattern was not observed. According to the time series analysis results, in all caves, fluctuations of air temperature affected cave temperature after approximately one hour. Cave size and structure, water presence, the entrance's size and shape, air flow, and visitor patterns can all influence cave temperature. Therefore, consideration of these factors is very important in the pursuit to clearly understand cave temperature characteristics.