• Title/Summary/Keyword: Non-point Pollution Source

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Mathematical Description of Soil Loss by Runoff at Inclined Upland of Maize Cultivation (옥수수 재배 경사지 밭에서 물 유출에 따른 토양유실 예측 공식)

  • Hur, Seung-Oh;Jung, Kang-Ho;Ha, Sang-Keon;Kwak, Han-Kang;Kim, Jeong-Gyu
    • Korean Journal of Soil Science and Fertilizer
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    • v.38 no.2
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    • pp.66-71
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    • 2005
  • Soil loss into stream and river by runoff shall be considered for non-point source pollution management as national land conservation. The purpose of this study was to develop the mathematical equation to predict soil loss from inclined uplands of maize cultivation due to the runoff by rainfall which mainly converges on July and August. Soil loss was concentrated on May because of low canopy over an entire field in 2002 and on June and July because of heavy rainfall in 2003. By regression analysis the relation between runoff and soil loss can be represented by a linear equation of y =1.5291x - 3.4933, where y is runoff ($Mg\;ha^{-1}$) and x is soil loss ($kg\;ha^{-1}$). The determination coefficient of this equation was 0.839 (P<0.001). Therefore, the mathematical equation derived from the practical experiment at the inclined upland can be applicable to predict soil loss accompanied by runoff due to periodic rainfall converging on short periods within a couple of months.

A Study on Field Compost Detection by Using Unmanned AerialVehicle Image and Semantic Segmentation Technique based Deep Learning (무인항공기 영상과 딥러닝 기반의 의미론적 분할 기법을 활용한 야적퇴비 탐지 연구)

  • Kim, Na-Kyeong;Park, Mi-So;Jeong, Min-Ji;Hwang, Do-Hyun;Yoon, Hong-Joo
    • Korean Journal of Remote Sensing
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    • v.37 no.3
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    • pp.367-378
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    • 2021
  • Field compost is a representative non-point pollution source for livestock. If the field compost flows into the water system due to rainfall, nutrients such as phosphorus and nitrogen contained in the field compost can adversely affect the water quality of the river. In this paper, we propose a method for detecting field compost using unmanned aerial vehicle images and deep learning-based semantic segmentation. Based on 39 ortho images acquired in the study area, about 30,000 data were obtained through data augmentation. Then, the accuracy was evaluated by applying the semantic segmentation algorithm developed based on U-net and the filtering technique of Open CV. As a result of the accuracy evaluation, the pixel accuracy was 99.97%, the precision was 83.80%, the recall rate was 60.95%, and the F1-Score was 70.57%. The low recall compared to precision is due to the underestimation of compost pixels when there is a small proportion of compost pixels at the edges of the image. After, It seems that accuracy can be improved by combining additional data sets with additional bands other than the RGB band.

Evaluation of Runoff Prediction from a Coniferous Forest Watersheds and Runoff Estimation under Various Cover Degree Scenarios using GeoWEPP Watershed Model (GeoWEPP을 이용한 침엽수림 지역 유출특성 예측 및 다양한 식생 피도에 따른 유출량 평가)

  • Choi, Jaewan;Shin, Min Hwan;Cheon, Se Uk;Shin, Dongseok;Lee, Sung Jun;Moon, Sun Jung;Ryu, Ji Cheol;Lim, Kyoung Jae
    • Journal of Korean Society on Water Environment
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    • v.27 no.4
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    • pp.425-432
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    • 2011
  • To control non-point source pollution at a watershed scale, rainfall-runoff characteristics from forest watersheds should be investigated since the forest is the dominant land use in Korea. Long-term monitoring would be an ideal method. However, computer models have been utilized due to limitations in cost and labor in performing long-term monitoring at the watersheds. In this study, the Geo-spatial interface to the Water Erosion Prediction Project (GeoWEPP) model was evaluated for its runoff prediction from a coniferous forest dominant watersheds. The $R^2$ and the NSE for calibrated result comparisons were 0.77 and 0.63, validated result comparisons were 0.92, 0.89, respectively. These comparisons indicated that the GeoWEPP model can be used in evaluating rainfall-runoff characteristics. To estimate runoff changes from a coniferous forest watershed with various cover degree scenarios, ten cover degree scenarios (10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%) were run using the calibrated GeoWEPP model. It was found that runoff increases with decrease in cover degree. Runoff volume was the highest ($206,218.66m^3$) at 10% cover degree, whereas the lowest ($134,074.58m^3$) at 100% cover degree due to changes in evapotranspiration under various cover degrees at the forest. As shown in this study, GeoWEPP model could be efficiently used to investigate runoff characteristics from the coniferous forest watershed and effects of various cover degree scenarios on runoff generation.

Accuracy Evaluation of Open-air Compost Volume Calculation Using Unmanned Aerial Vehicle (무인항공기를 이용한 야적퇴비 적재량 산정 정확도 평가)

  • Kim, Heung-Min;Bak, Su-Ho;Yoon, Hong-Joo;Jang, Seon-Woong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.3
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    • pp.541-550
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    • 2021
  • While open-air compost has value as a source of nutrients for crops in agricultural land, it acts as a pollution that adversely affects the environment during rainfall, and management is required. In this study, it was intended to analyze the accuracy of calculating open-air compost volume using fixed-wing UAV (unmanned aerial vehicle) capable of acquiring a wide range of images and automatic path flights and to identify the possibility of utilization. In order to evaluate the accuracy of calculating the three open-air compost volume, ground LiDAR surveys and precision surveys using a rotary UAV were performed. and compared with the open-air compost volume acquired through a fixed-wing UAV. As a result of comparing the calculation of open-air compost volume based on the ground LiDAR, the error rate of the rotary-wing was estimated to be ±5%, and the error rate of fixed-wing was -15 ~ -4%. one of three open-air compost volume calculated by fixed-wing was underestimated as about -15 %, but the deviation of the open-air compost volume was 2.9 m3, which was not significant. In addition, as a result of periodic monitoring of open-air compost using fixed-wing UAV, changes in the volume of open-air compost with time could be confirmed. These results suggested that efficient open-air compost monitoring and non-point pollutants in agricultural for a wide range using fixed-wing UAV is possible.

Research on Design Capacity Evaluation of Low Impact Development according to Design Criteria (저영향개발 시설 설계 기준에 따른 용량 평가 방법 연구)

  • Im, Jiyeol;Gil, Kyungik
    • Journal of Wetlands Research
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    • v.24 no.1
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    • pp.59-67
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    • 2022
  • The interest in LID facilities is increasing worldwide for recovery of natural water cycle system to destroy by urbanization. However, problems are raised when installation of LID because comprehensive analysis about design capacity adequacy of LID facilities was not conducted completely. In this research, removal efficiency and design volume adequacy of LID facilities were analyzed based on rainfall monitoring data in four LID facilities(Vegetated Swale, Vegetative Filter Strip, Bio-Retention and Permeable Pavement). As a result, group of LID facility designed on WQV was shown higher flow(37%) and pollutants(TSS, BOD, TN and TP) removal efficiencies(20 ~ 37%) than group of LID facility designed on WQF. SA/CA graph was drawn for evaluation of design volume adequacy based on rainfall monitoring data. In this SA/CA graph, coefficient of determination show over 0.5 in all parameter, especially, Flow and TP were show over 0.95. And, 'SA/CA & L/CA' graph considering difference of structure mechanism in LID facility suggested in this research was confirmed that improved coefficient of determination in flow, TSS and TP than SA/CA graph. According to this research results, feasibility of applying 'SA/CA & L/CA' graph for evaluation of design volume adequacy in LID facility, and it is necessary to follow up research for generalization and normalization.

Heavy Metals in Road Deposited Sediments and Control of Them in Urban Areas: A Review (문헌고찰에 의한 도시 지역 도로퇴적물의 중금속 특성 및 적정 관리방안)

  • Kim, Do Gun
    • Land and Housing Review
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    • v.13 no.3
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    • pp.125-140
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    • 2022
  • Road Deposited Sediment (RDS) is the solids formed from the wear of road, wear of vehicles, exhausts, and the input of the emissions from various sources out of the roads. RDS is seriously polluted by organic matter, nutrients, and metals. RDS plays an important role as the sink and the transport medium of the associated pollutants because RDS can be carried to the adjacent water system via stormwater runoff. In this regard, the heavy metals in RDS were investigated based on the publications. The contents of the metals in RDS were highly variable. The concentration of Cr, Ni, Cu, Fe, Zn, As, Cd, and Pb in urban RDS in various regions was in a range of 3.16-3,410, 1.15-1,382, 20.2-9,069, 2,980-124,853, 81-2,550, 2.3-214, 0.19-21.3, and 15.21-1,125 mg/kg, respectively. The anthropogenic enrichment of the metals in RDS was confirmed by the high concentration of Cu, Zn, Cd, and Pb. The contents of the metals were higher in industrial and traffic areas than in residential areas, while they were generally increased with decreasing particle size. It is believed that this study's results would contribute to quantifying the metals' load via RDS and establishing control strategies.

Derivation of Data Demand through Analysis of Agreed Terms and Conditions on Environmental Impact Assessment - Focusing on the Water Environment - (환경영향평가 협의 내용 분석을 통한 데이터 수요 도출방안 - 수환경 분야를 중심으로 -)

  • Jinhoo Hwang;Yoonji Kim;Seong Woo Jeon;Yuyoung Choi;Hyun Chan Sung
    • Journal of Environmental Impact Assessment
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    • v.32 no.1
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    • pp.29-40
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    • 2023
  • The need for improvement is raised due to limitations with environmental impact assessment, and the importance for data-based environmental impact assessment is increasing. In this study, data demand was derived by analyzing Agreed Terms and Conditions in the Water Environment field (Water Quality, Hydraulic & Hydrologic Conditions, and Marine Environment) of environmental impact assessment. Agreed Terms and Conditions on environmental impact assessment in the water environment field were classified and categorized by environmental impact assessment stage (addition to status survey, impact prediction and evaluation, establishment of reduction measures, post-environmental impact survey), and data demand for each type of consultation opinion was linked. As a result of the categorization of Agreed Terms and Conditions, it was classified into 18 types in the water quality, 15 types in the hydraulic & hydrologic conditions, and 17 types in the marine environment. As a result of linking data demand, the total number of data demand was 236 in the water quality, 98 in the hydraulic & hydrologic conditions, and 73 in the marine environment. The highest number of Agreed Terms and Conditions and data demands were found in the water quality for the evaluation item and establishment of reduction measures, specifically establishment of non-point source pollution reduction measures, for the stage. The numbers were judged to be linked to the relative importance of the items and the primary purpose of environmental impact assessment. The derivation of data demand through the analysis of Agreed Terms and Conditions in the environmental impact assessment can contribute to the advancement of the preparation of environmental impact assessment reports and is expected to increase data utilization by various decision-makers by establishing a systematic database.

Analysis of Non-point source Pollution by Rainfall Runoff Characteristics in Songya-stream of Downstream of Andong Dam (안동댐 하류 송야천 유역의 강우시 비점오염물질 유출 특성 분석)

  • Kang, Tae Seong;Yu, Na Yeong;Shin, Min Hwan;Park, Bae Kyung;Kim, Jong Gun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.282-282
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    • 2021
  • 강우시 농경지와 축산시설로부터 유출되는 비점오염물질은 하류 수계의 수질과 수생태계에 악영향을 미친다. 이에 따라 환경부에서는 비점오염원관리지역을 지정하고 다양한 비점오염 저감 대책을 시행하고 있다. 본 연구에서는 비점오염원관리지역으로 지정된 안동댐 하류 중 송야천 유역을 대상으로 강우유출수 모니터링을 수행하였으며, 모니터링 결과를 바탕으로 강우시 비점오염물질 유출 특성을 분석하였다. 모니터링 기간은 2020년 6월부터 11월까지 총 5회의 강우사상에 대하여 상·하류와 유입하천을 포함한 총 8개의 모니터링 지점을 대상으로 강우사상별 유량가중평균농도(Event Mean Concentration, EMC), 오염부하, 단위면적당 오염부하를 산정하였으며, 오염원 그룹별 비점배출부하를 산정하여 오염 기여도를 분석하였다. 강우유출수 조사결과를 이용한 EMC 농도 산정 결과 유입하천인 오산천 지점이 SS와 TOC 항목을 제외한 모든 수질항목의 EMC 농도가 가장 큰 것으로 나타났다. 단위면적당 오염부하를 산정하여 비교 분석한 결과 T-P 항목의 단위면적당 오염부하는 물한천 지점(0.69 kg/ha)과 오산천 지점(0.69 kg/ha)이 크게 나타났다. 결과와 같이 오산천 지점과 물한천 지점이 오염정도가 큰 것으로 나타났으며, 이에 따른 상류 오염원 현장 정밀조사를 수행하였다. 조사 결과 강우발생시 상류에 위치한 농경지와 축사에서 발생하는 오염원이 하천으로 유입되고 있었으며, 여러 축사에서 배출되고 있는 유입수를 채취하여 분석한 결과 T-P 농도가 평균 0.935 mg/L로 높게 나타났다. 전국오염원조사자료(국립환경과학원, 2017) 내용을 참조하여 송야천 유역의 오염원 그룹별 비점배출부하를 산정해 오염 기여도를 분석한 결과, T-P 항목의 경우 축산계와 토지계의 비점배출부하가 전체 비점배출부하의 약 63%와 37%를 차지해 비점배출부하 기여도가 큰 것으로 나타났다. 이와 같이 송야천 유역의 경우 강우시 농경지와 축산시설에서 배출되는 오염물질이 하천 수질오염에 상당한 기여를 하고 있는 것으로 보여지며, 비점오염원 발생에 대한 대책 마련이 필요할 것으로 사료된다. 본 연구 결과는 송야천 유역의 비점오염 저감 대책 수립을 위한 기초자료로 활용할 수 있을 것으로 판단된다.

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The Analysis of Future Land Use Change Impact on Hydrology and Water Quality Using SWAT Model (SWAT 모형을 이용한 미래 토지이용변화가 수문 - 수질에 미치는 영향 분석)

  • Park, Jong-Yoon;Lee, Mi Seon;Lee, Yong Jun;Kim, Seong Joon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.2B
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    • pp.187-197
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    • 2008
  • This study is to assess the impact of future land use change on hydrology and water quality in Gyungan-cheon watershed ($255.44km^2$) using SWAT (Soil and Water Assessment Tool) model. Using the 5 past Landsat TM (1987, 1991, 1996, 2004) and $ETM^+$ (2001) satellite images, time series of land use map were prepared, and the future land uses (2030, 2060, 2090) were predicted using CA-Markov technique. The 4 years streamflow and water quality data (SS, T-N, T-P) and DEM (Digital Elevation Model), stream network, and soil information (1:25,000) were prepared. The model was calibrated for 2 years (1999 and 2000), and verified for 2 years (2001 and 2002) with averaged Nash and Sutcliffe model efficiency of 0.59 for streamflow and determination coefficient of 0.88, 0.72, 0.68 for Sediment, T-N (Total Nitrogen), T-P (Total Phosphorous) respectively. The 2030, 2060 and 2090 future prediction based on 2004 values showed that the total runoff increased 1.4%, 2.0% and 2.7% for 0.6, 0.8 and 1.1 increase of watershed averaged CN value. For the future Sediment, T-N and T-P based on 2004 values, 51.4%, 5.0% and 11.7% increase in 2030, 70.5%, 8.5% and 16.7% increase in 2060, and 74.9%, 10.9% and 19.9% increase in 2090.

Evaluation of Runoff‧Peak Rate Runoff and Sediment Yield under Various Rainfall Intensities and Patterns Using WEPP Watershed Model (다양한 강우강도 및 패턴에 따른 WEPP 모형의 유출‧첨두유출‧토양유실량 평가)

  • Choi, Jae-Wan;Ryu, Ji-Chul;Kim, Ik-Jae;Lim, Kyoung-Jae
    • Journal of Korea Water Resources Association
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    • v.45 no.8
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    • pp.795-804
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    • 2012
  • Recently, changes in rainfall intensity and patterns have been causing increasing soil loss worldwide. As a result, the water ecosystem becomes worse and crops yield are reduced with soil loss and nutrient loss with it. Many studies have been proposed to estimate runoff and soil loss to predict or decrease non-point source pollution. Although the USLE has been used for many years in estimating soil losses, the USLE cannot reflect effects on soil loss of changes in rainfall intensity and patterns. The WEPP, physically based model, is capable of predicting soil loss and runoff using various rainfall intensity. In this study, the WEPP model was simulated for sediment yield, runoff and peak runoff using data of 5, 10, 30, 60 minute term rainfall, Huff's method and design rainfall. In case of rainfall interval of 5 minutes and 60 minutes, the sediment and runoff values decreased by 24% and 19%, respectively. The peak rate runoff values decreased by 16% when rainfall interval changed from 5 minutes to 60 minutes, indicating the peak rate runoff values are affected by rainfall intensity to some degrees. As a result of simulating using Huff's method, all values (sediment yield, runoff, peak runoff) were found to be the greatest at third quartile. According to the analysis under various design rainfall conditions (2, 3, 5, 10, 20, 30, 50, 100, 200, 300 years frequency), sediment yield, runoff, and peak runoff of 906.2%, 249.4% and 183.9% were estimated using 2 year to 300 year frequency rainfall data.