• Title/Summary/Keyword: 수자원 관리

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Estimation of ecological flow and fish habitats for Andong Dam downstream reach using 1-D and 2-D physical habitat models (1차원 및 2차원 물리서식처 모형을 활용한 안동댐 하류 하천의 환경생태유량 및 어류서식처 추정)

  • Kim, Yongwon;Lee, Jiwan;Woo, Soyoung;Kim, Soohong;Lee, Jongjin;Kim, Seongjoon
    • Journal of Korea Water Resources Association
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    • v.55 no.12
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    • pp.1041-1052
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    • 2022
  • This study is to estimate the optimal ecological flow and analysis the spatial distribution of fish habitat for Andong dam downstream reach (4,565.7 km2) using PHABSIM (Physical Habiat Simulation System) and River2D. To establish habitat models, the cross-section informations and hydraulic input data were collected uisng the Nakdong river basic plan report. The establishment range of PHABSIM was set up about 410.0 m from Gudam streamflow gauging station (GD) and about 6.0 km including GD for River2D. To select representative fish species and construct HSI (Habitat Suitability Index), the fish survey was performed at Pungji bridge where showed well the physical characteristics of target stream located downstream of GD. As a result of the fish survey, Zacco platypus was showed highly relative abundance resulting in selecting as the representative fish species, and HSI was constructed using physical habitat characteristics of the Zacco platypus. The optimal range of HSI was 0.3~0.5 m/s at the velocity suitability index, 0.4~0.6 m at the depth suitability index, and the substrate was sand to fine gravel. As a result of estimating the optimal ecological flow by applying HSI to PHABSIM, the optimal ecological flow for target stream was 20.0 m3/sec. As a result of analysis two-dimensional spatial analysis of fish habitat using River2D, WUA (Weighted Usable Area) was estimated 107,392.0 m2/1000 m under the ecological flow condition and it showed the fish habitat was secured throughout the target stream compared with Q355 condition.

Hydrologic evaluation of SWAT considered forest type using MODIS LAI data: a case of Yongdam Dam watershed (MODIS LAI 자료를 활용하여 임상별로 고려한 SWAT의 수문 평가: 용담댐유역을 대상으로)

  • Han, Daeyoung;Lee, Jiwan;Kim, Wonjin;Baek, Seungchul;Kim, Seongjoon
    • Journal of Korea Water Resources Association
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    • v.54 no.11
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    • pp.875-889
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    • 2021
  • This study compares and analyzes the Soil and Water Assessment Tool (SWAT) and Terra MODIS (Moderate Resolution Imaging Spectroradiometer) as coniferous, deciduous and mixed forest with Yongdam Dam upstream (904.4 km2). The hydrologic evaluation period was set to 10 years from 2010 to 2019, and the applicability of the 8-day MOD15A2 Leaf Area Index (LAI) data, 3 TDR (Time Domain Reflectometry) (GB, JC, CC), and 1 Flux Tower (DU) evaporation volume (YDD) data was simulated. As a result, the R2 of coniferous forest, deciduous forest and mixed forest are 0.95, 0.89, 0.90, soil moisture and evaportranspiration stations R2 were analyzed at 0.50 to 0.55 and 0.51, respectively, with R2 at 0.74, RMSE 2.75 mm/day, NSE 0.70 and PBIAS 14.3% for Yongdam inflow. Based on the calibrated and validated watersheds, the annual average evaportranspiration was calculated as coniferous 469.7 mm, deciduous 501. mm and 511.5 mm mixed forest, total runoff were estimated at coniferous 909.8 mm, deciduous 860.6 mm and 864.2 mm mixed forest. In the case of annual average evaportranspiration, it was evaluated that deciduous were high, but in the case of streamflow, it was evaluated that coniferous were high. Unlike other hydrologic with similar patterns throughout the year, the average annual evapotranspiration was about 7% higher than coniferous due to the higher evapotranspiration of deciduous with high leaf area index in summer and fall. In addition, deciduous were 9% and 6% higher for surface runoff and lateral flow, but the groundwater of coniferous was 77% higher. Therefore, it was confirmed that the total runoff was in order of coniferous, mixed forest, and deciduous.

Analysis of the mixing effect of the confluence by the difference in water temperature between the main stream and the tributary (본류와 지류의 수온 차에 의한 합류부 혼합 양상 분석)

  • Ahn, Seol Ha;Lee, Chang Hyun;Kim, Kyung Dong;Kim, Dong Su;Ryu, Si Wan;Kim, Young Do
    • Journal of Korea Water Resources Association
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    • v.56 no.2
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    • pp.103-113
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    • 2023
  • The river confluence is a section in which two rivers with different topographical and hyrodynamic characteristics are combined into one, and it is a section in which rapid flow, inflow of sediments, and hydrological topographic changes occur. In the confluence section, the flow of fluid occurs due to the difference in density due to the type of material or temperature difference, which is called a density flow. It is necessary to accurately measure and observe the confluence section including a certain section of the main stream and tributaries in order to understand the mixing behavior of the water body caused by the density difference. A comprehensive analysis of this water mixture can be obtained by obtaining flow field and flow rate information, but there is a limit to understanding the mixing of water bodies with different physical properties and water quality characteristics of rivers flowing with stratigraphic flow. Therefore, this study attempts to grasp the density flow through the water temperature distribution in the confluence section. Among the extensive data of the river, vertical data and water surface data were acquired, and through this, the stratification phenomenon of the confluence was to be confirmed. It was intended to analyze the mixed pattern of the confluence by analyzing the water mixing pattern according to the water temperature difference using the vertical data obtained by measuring the repair volume by installing the ADCP on the side of the boat and measuring the real-time concentration using YSI. This study can supplement the analysis results of the existing water quality measurement in two dimensions. Based on the comparative analysis, it will be used to investigate the current status of stratified sections in the water layer and identify the mixing characteristics of the downstream section of the river.

Analysis of domestic water usage patterns in Chungcheong using historical data of domestic water usage and climate variables (생활용수 실적자료와 기후 변수를 활용한 충청권역 생활용수 이용량 패턴 분석)

  • Kim, Min Ji;Park, Sung Min;Lee, Kyungju;So, Byung-Jin;Kim, Tae-Woong
    • Journal of Korea Water Resources Association
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    • v.57 no.1
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    • pp.1-8
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    • 2024
  • Persistent droughts due to climate change will intensify water shortage problems in Korea. According to the 1st National Water Management Plan, the shortage of domestic and industrial waters is projected to be 0.07 billion m3/year under a 50-year drought event. A long-term prediction of water demand is essential for effectively responding to water shortage problems. Unlike industrial water, which has a relatively constant monthly usage, domestic water is analyzed on monthly basis due to apparent monthly usage patterns. We analyzed monthly water usage patterns using water usage data from 2017 to 2021 in Chungcheong, South Korea. The monthly water usage rate was calculated by dividing monthly water usage by annual water usage. We also calculated the water distribution rate considering correlations between water usage rate and climate variables. The division method that divided the monthly water usage rate by monthly average temperature resulted in the smallest absolute error. Using the division method with average temperature, we calculated the water distribution rates for the Chungcheong region. Then we predicted future water usage rates in the Chungcheong region by multiplying the average temperature of the SSP5-8.5 scenario and the water distribution rate. As a result, the average of the maximum water usage rate increased from 1.16 to 1.29 and the average of the minimum water usage rate decreased from 0.86 to 0.84, and the first quartile decreased from 0.95 to 0.93 and the third quartile increased from 1.04 to 1.06. Therefore, it is expected that the variability in monthly water usage rates will increase in the future.

Applicability evaluation of GIS-based erosion models for post-fire small watershed in the wildland-urban interface (WUI 산불 소유역에 대한 GIS 기반 침식모형의 적용성 평가)

  • Shin, Seung Sook;Ahn, Seunghyo;Song, Jinuk;Chae, Guk Seok;Park, Sang Deog
    • Journal of Korea Water Resources Association
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    • v.57 no.6
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    • pp.421-435
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    • 2024
  • In April 2023, a wildfire broke out in Gangneung located in the east coast region due to the influence of the Yanggang-local wind. In this study, GIS-based RUSLE(Revised Universal Soil Loss Equation) and SEMMA (Soil Erosion Model for Mountain Areas) were used to evaluate the erosion rate due to vegetation recovery in a small watershed of the Gangneung WUI(Wildland-Urban Interface) fire. The small watershed of WUI fire has a low altitude range of 10-30 m and the average slope of 10.0±7.4° which corresponds to a gentle slope. The soil texture was loamy sand with a high organic content and the deep soil depth. As herbaceous layer regenerated profusely in the gully after the wildfire, the NDVI (Normalized Difference Vegetation Index) reached a maximum of 0.55. Simulation results of erosion rates showed that RUSLE ranged from 0.07-94.9 t/ha/storm and SEMMA ranged from 0.24-83.6 t/ha/storm. RUSLE overestimated the average erosion rate by 1.19-1.48 times compared to SEMMA. The erosion rates were estimated to be high in the middle slope where burned pine trees were widely distributed and the slope was steep and to be relatively low in the hollow below the gully where herbaceous layer recovers rapidly. SEMMA showed a rapid increase in erosion sensitivity under at certain vegetation covers with NDVI below 0.25 (Ic = 0.35) on post-fire hillslopes. Gentle slopes with high organic content and rapid recovery of natural vegetation had relatively low erosion rate compared to steep slopes. As subsequent infrastructure and human damages due to sediment disaster by heavy rain is anticipated in WUI fire areas, the research results may be used as basic data for targeted management and decision making on the implementation of emergency treatment after the wildfire.

Study on water quality prediction in water treatment plants using AI techniques (AI 기법을 활용한 정수장 수질예측에 관한 연구)

  • Lee, Seungmin;Kang, Yujin;Song, Jinwoo;Kim, Juhwan;Kim, Hung Soo;Kim, Soojun
    • Journal of Korea Water Resources Association
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    • v.57 no.3
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    • pp.151-164
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    • 2024
  • In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH3, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.

An Equation to Estimate Steady-State Seepage Rate of Rockfill Dam (사력댐의 정상상태 침투량 예측식)

  • Lee, Jong-Wook;Lim, Heui-Dae
    • Journal of the Korean Geotechnical Society
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    • v.27 no.10
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    • pp.69-80
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    • 2011
  • In this study unsaturated seepage analysis of 8 large rockfill dam managed by Korea Water Resources Corporation, were carried out, and the seepage rate of rockfill dam was analyzed by changing reservoir water level, shape, saturated and unsaturated seepage properties of core zone to present an equation to estimate steady-state seepage rate of rockfill dam. This equation considers unsaturated seepage flow and is applicable to domestic large scale Rockfill dam with the height of more than 50m. Estimated values by the proposed equation are greater than those by the method of Sakamoto (1998), which does not consider unsaturated seepage flow. The difference of estimated values increases with the lower reservoir water level and decreases with the higher reservoir water level. We can be sure that the comparison between the measured seepage rate and the estimated seepage rate by the proposed equation for the existing rockill dam was well-matched. The proposed equation is close to the actual phenomenon compared with the existing equations (Sakamoto, 1998; Chapuis and Aubertin, 2001) because it is based on the results of unsaturated seepage analysis of dams, has upstream and downstream slopes in the range of 1Vertical: (0.2~0.3)Horizontal.

Selection of Optimal Band Combination for Machine Learning-based Water Body Extraction using SAR Satellite Images (SAR 위성 영상을 이용한 수계탐지의 최적 머신러닝 밴드 조합 연구)

  • Jeon, Hyungyun;Kim, Duk-jin;Kim, Junwoo;Vadivel, Suresh Krishnan Palanisamy;Kim, JaeEon;Kim, Taecin;Jeong, SeungHwan
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.3
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    • pp.120-131
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    • 2020
  • Water body detection using remote sensing based on machine interpretation of satellite image is efficient for managing water resource, drought and flood monitoring. In this study, water body detection with SAR satellite image based on machine learning was performed. However, non water body area can be misclassified to water body because of shadow effect or objects that have similar scattering characteristic comparing to water body, such as roads. To decrease misclassifying, 8 combination of morphology open filtered band, DEM band, curvature band and Cosmo-SkyMed SAR satellite image band about Mokpo region were trained to semantic segmentation machine learning models, respectively. For 8 case of machine learning models, global accuracy that is final test result was computed. Furthermore, concordance rate between landcover data of Mokpo region was calculated. In conclusion, combination of SAR satellite image, morphology open filtered band, DEM band and curvature band showed best result in global accuracy and concordance rate with landcover data. In that case, global accuracy was 95.07% and concordance rate with landcover data was 89.93%.

Application of groundwater-level prediction models using data-based learning algorithms to National Groundwater Monitoring Network data (자료기반 학습 알고리즘을 이용한 지하수위 변동 예측 모델의 국가지하수관측망 자료 적용에 대한 비교 평가 연구)

  • Yoon, Heesung;Kim, Yongcheol;Ha, Kyoochul;Kim, Gyoo-Bum
    • The Journal of Engineering Geology
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    • v.23 no.2
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    • pp.137-147
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    • 2013
  • For the effective management of groundwater resources, it is necessary to predict groundwater level fluctuations in response to rainfall events. In the present study, time series models using artificial neural networks (ANNs) and support vector machines (SVMs) have been developed and applied to groundwater level data from the Gasan, Shingwang, and Cheongseong stations of the National Groundwater Monitoring Network. We designed four types of model according to input structure and compared their performances. The results show that the rainfall input model is not effective, especially for the prediction of groundwater recession behavior; however, the rainfall-groundwater input model is effective for the entire prediction stage, yielding a high model accuracy. Recursive prediction models were also effective, yielding correlation coefficients of 0.75-0.95 with observed values. The prediction errors were highest for Shingwang station, where the cross-correlation coefficient is lowest among the stations. Overall, the model performance of SVM models was slightly higher than that of ANN models for all cases. Assessment of the model parameter uncertainty of the recursive prediction models, using the ratio of errors in the validation stage to that in the calibration stage, showed that the range of the ratio is much narrower for the SVM models than for the ANN models, which implies that the SVM models are more stable and effective for the present case studies.

Coupled Model Development between Groundwater Recharge Quantity and Climate Change Using GIS (GIS를 이용한 기후변화 연동 지하수 함양량 산정 모델 개발 및 검증)

  • Lee, Moung-Jin;Lee, Joung-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.14 no.3
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    • pp.36-51
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    • 2011
  • Global climate change is disturbing the water circulation balance by changing rates of precipitation, recharge and discharge, and evapotranspiration. Groundwater, which occupies a considerable portion of the world's water resources, is related to climate change via surface water such as rivers, lakes, and marshes. In this study, the authors selected a relevant climate change scenario, A1B from the Special Report on Emission Scenario (SRES) which is distributed at Korea Meteorological Administration. By using data on temperature, rainfall, soil, and land use, the groundwater recharge rate for the research area was estimated by periodically and embodied as geographic information system (GIS). In order to calculate the groundwater recharge quantity, Visual HELP3 was used as main model, and the physical properties of weather, temperature, and soil layers were used as main input data. General changes to water circulation due to climate change have already been predicted. In order to systematically solve problems of ground circulation system, it may be urgent to recalculate the groundwater recharge quantity and consequent change under future climate change. The space-time calculation of changes of the groundwater recharge quantity in the study area may serve as a foundation to present additional measures to improve domestic groundwater resource management.