Journal of Korean Society of Environmental Engineers
/
v.33
no.4
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pp.289-299
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2011
We studied the characteristics of pollutant concentrations in 9 streams that flow into Shihwa Lake in order to provide the scientific data for effective implementation of total pollution loads management system (TPLMS) of the Lake. Suspended solid (SS), chemical oxygen demand (COD), dissolved nutrients ($NO_2$, $NO_3$, $NH_4$, $PO_4$ and $SiO_2$), total phosphorus (TP) and total nitrogen (TN) in stream water from industrial complexes, urban and agricultural regions were determined. Pollutant concentrations in December were higher than that in other sampling periods. COD concentration from industrial complex region with average of 12.6 mg/L was 2 times higher those from urban region (6.6 mg/L) and agricultural region (5.9 mg/L). TP concentration from industrial region also showed higher concentration than other regions. TN concentration in stream water was 5.89 mg/L for industrial region, 3.02 mg/L for urban region and 5.27 mg/L for agricultural region, respectively, suggesting inflow of TN due to fertilizer usage in agricultural field. Relative percentage of nitrogen compounds in TN follows the sequence: $NH_4$ (35.1%) > $NO_2$ (20.0%) > DON (22.8%) > PON (8.9%) > $NO_2$ (3.2%). Concentrations of dissolved nutrients, TP and TN in stream water were 3.2~37.2 times higher than that in Shihwa Lake seawater, therefore large amount of pollutants may be directly entered into Shihwa Lake without any treatment. For Gunja stream of industrial region, pollutants at midstream showed relatively higher concentration compared to upstream and downstream. It is necessary to manage the illegal discharging of sewage and waste water. Our results provide valuable informations on the estimation and reduction of total pollutant loads in the process of establishing adequately strategic and implemental plan of Shihwa Lake TPLMS.
This study was conducted to evaluate the influence of pollutant loads on the water quality in the Dongjin River area from January 2003 to December 2004. The average value of BOD and T-N showed the highest peak in Yongho, Dukcheon watershed among Dongjin River. Concentrations of BOD, T-N and T-P in Jeongeup watershed were 2.29 mg $L^{-1}$, 4.40 mg $L^{-1}$ and 0.27 mg $L^{-1}$, respectively. Concentration of BOD in Chilbo was 1.19 mg $L^{-1}$ which would be in the grade I according to water quality criteria by Ministry of Environment. The BOD level in Wonpeung and Sinpeung watershed ranged from 4.06 to 7.35 mg $L^{-1}$. The T-N effluent loads of non-point pollutants were high in Wonpeung, Gobu, Yongho Dukcheon, Jeongeup and Sinpeung watershed in order. The major sources of BOD, T-N and T-P effluent loads were Livestock. The T-P effluent load of non-point pollutant was 68 kg $day^{-1}$ in Wonpeung, 58 kg $day^{-1}$ in Yongho Dukcheon and 45 kg $day^{-1}$ Jeongeup watershed. The delivered loads of BOD was high in Gobucheon, while both T-N and T-P were high in Yongho Dukcheon. The delivery ratio of BOD and T-N at dry season was below 100% in all watershed of Dongjin River. The delivery ratio of T-N at raining season was high in Yongho Dukcheon and Chilbo watershed
Kyoung-Seok Lee;Dong Hoon Lee;Youngmi Ahn;Joo-Hyon Kang
Journal of Wetlands Research
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v.25
no.2
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pp.99-110
/
2023
Non-point source (NP) pollutants in an agricultural landuse are discharged from a large area compared to those in other land uses, and thus effective source control measures are needed. To develop appropriate control measures, it is necessary to quantify discharge load of each source and evaluate the degree of water quality improvement by implementing different options of the control measures. This study used Hydrological Simulation Program-FORTRAN (HSPF) to quantify pollutant discharge loads from different sources and effects of different control measures on water quality improvements, thereby supporting decision making in developing appropirate pollutant control strategies. The study area is the Gyeseong river watershed in Changnyeong county, Gyeongsangnam-do, with agricultural areas occupying the largest proportion (26.13%) of the total area except for the forest area. The main pollutant sources include chemical and liquid fertilizers for agricultural activities, and manure produced from small scale livestock facilities and applied to agriculture lands or stacked near the facilities. Source loads of chemical fertilizers, liquid fertilizers and livestock manure of small scale livestock facilities, and point sources such as municipal wastewater treatment plants (WWTPs), community WWTPs, private sewage treament plants were considered in the HSPF model setup. Especially, NITR and PHOS modules were used to simulate detailed fate and transport processes including vegitation uptake, nutrient deposition, adsorption/desorption, and loss by deep percolation. The HSPF model was calibrated and validated based on the observed data from 2015 to 2020 at the outlet of the watershed. The calibrated model showed reasonably good performance in simulating the flow and water quality. Five Pollutants control scenarios were established from three sectors: agriculture pollution management (drainge outlet control, and replacement of controlled release fertilizers), livestock pollution management (liquid fertilizer reduction, and 'manure management of small scale livestock facilities) and private STP management. Each pollutant control measure was further divided into short-term, mid-term, and long-term scenarios based on the potential achievement period. The simulation results showed that the most effective control measure is the replacement of controlled release fertilizers followed by the drainge outlet control and the manure management of small scale livestock facilities. Furthermore, the simulation showed that application of all the control measures in the entire watershed can decrease the annual TN and TP loads at the outlet by 40.6% and 41.1%, respectively, and the annual average concentrations of TN and TP at the outlet by 35.1% and 29.2%, respectively. This study supports decision makers in priotizing different pollutant control measures based on their predicted performance on the water quality improvements in an agriculturally dominated watershed.
Park, Su Jeong;Kwon, Oh Sang;Tanaka, Hiroaki;Kim, Chang Soo;Kim, Eun Seok;Kim, Ji Hye;Jang, Seok Jea;Ahn, Kyung Hee
Journal of Korean Society on Water Environment
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v.29
no.6
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pp.847-851
/
2013
This study describes the results of an investigation conducted in order to characterize the quantity and quality of individual gray water streams. The highest pollutants concentrations were found in gray water originating from kitchen and laundry with $BOD_5$ concentrations in the order of several hundreds $mgl^{-1}$. In contrast to this, bathroom was regarded as a major contributor of Escherichia coli. Laundry gray water has higher pH, sodium, sulfate, anionic surfactants. Individual gray water types had different contribution to the overall daily discharge and relative pollutants loads. Kitchen, although accounting for only 13% of the total volume, was identified as a major source of microorganisms with Total coliforms, Escherichia coli, Fecal streptococcus taking up 82%, 74% and 54% of their relative daily load, respectively. The laundry gray water, although being responsible for 36% of the total daily discharge, was established as a significant contributor of sodium, sulfate, anionic surfactants and TOC (70%, 72%, 84% and 52%, respectively). But the laundry gray water was a minor source of microorganisms. Bathroom was found to be a major gray water producer, making up 51% of the flow, but constituted less than 50% of the relative daily load in most cases.
In order to assess the influences of bottom sediment on water quality, following measurement were made. (1) Estimations of pollutant loads from the bottom sediment based on mass balance concept, (2) measurements of pollutant concentrations in the sediment to assess the pollution level and influence potential, (3) in situ and laboratory measurements of Sediment Oxygen Demants (SOD) and pollutant load (sediment release) from bottom sediment. Analyses of inflow and outflow loadings using simple mass balance show that there are some variations found according to the pollutants. However, there is no consistent evidence that the sediment can be a source of pollutants. Pollutant concentrations in the sediment range 16~724.8 mg/kg (COD), 1.68 ~12.64 mg/kg (T-P), 5.6~76.8 mg/kg (T-N), 0.32~21.6 mg/kg ($NH_3$-N), 0.092~0.544 mg/kg ($NO_2$-N), 4.8~18.4 mg/kg ($NO_3$-N), and 1.59~11.23 mg/kg ($PO_4$-P). Measured SOD ranges $0.190{\sim}0.802g{\cdot}m^{-2}{\cdot}d^{-1}$ and measured release rate ranges $-1618.42{\sim}10mg/m^2{\cdot}d$(COD), $-12{\sim}16mg/m^2{\cdot}d$(T-P), $-197.37{\sim}140mg/m^2{\cdot}d$(T-N), $0.4{\sim}74.32mg/m^2{\cdot}d$($NH_3$-N), $-2.04{\sim}0.8mg/m^2{\cdot}d$ ($NO_2$-N), $-70{\sim}40mg/m^2{\cdot}d$ ($NO_3$-N), and $-26.11{\sim}28.55mg/m^2{\cdot}d$($PO_4$-P). All study results indicate that bottom sediments in the Seoha weir show only limited effects on the water quality. It implies that sediment dredging is not an effective option or management measure to reduce pollutant loading.
Lee, Yong Jun;Park, Jong Yoon;Park, Min Ji;Kim, Seong Joon
KSCE Journal of Civil and Environmental Engineering Research
/
v.28
no.6B
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pp.653-663
/
2008
The purpose of this study is to establish a database of weather, hydrology, point source pollution management, reservoir release and tillage management for SWAT model evaluation of Anseongcheon watershed ($370.1km^2$, the upstream of Gongdo water level gauging station), and to use them for the following research of future climate and land use change impact on streamflow and stream water quality. It is expected that the database can achieve the practical analysis of current watershed hydrologic and environmental condition. The model calibration and validation were conducted using the constructed database. The model results showed that the tillage management affected the temporal shift of pollutant loads, and changed the flow pattern of pollutant transport through cultivation area. It was identified that the April and May irrigation water supply from the agricultural reservoir also affected the streamflow of downstream. The data application of pollutants treatment facilities and tillage management of cultivation area showed about 10% difference in the simulation results of stream water quality. The data establishment of agricultural reservoir operation, the tillage management of cultivated area within the watershed and the attributes inclusion of pollutants treatment facilities were proved to be important in SWAT model evaluation. The results of model setup in this study are expected for more reliable model application in the following research of future climate and land use change impact on hydrology and stream water quality of the study watershed.
Journal of Korean Society of Environmental Engineers
/
v.39
no.3
/
pp.140-148
/
2017
The effectiveness of the first flush treatment system using settling process was evaluated to reduce urban nonpoint source pollutant loads to surface water during storm events. A pilot scale system was constructed and tested in the field and surface runoff samples were collected automatically according to pre-defined conditions. Nine rainfall events were tested and average removal efficiencies of TSS (Total Suspended Solid), TP (Total Phosphorus) and TN (Total Nitrogen) were evaluated as 87.4%, 75.3%, and 43.6%, respectively. Concentration and removal efficiency of pollutants were found to be affected by an amount of rainfall and rainfall intensities of the respective events. This seemed to be caused by the greater particulate fractions of first flushed samples than the samples collected in later time periods during the same rainfall events. The study showed that it is possible to remove a significant portion of the nonpoint source pollutant loads in initial rainfall runoff by using a simple settling process for TSS and TP without requiring additional power or chemicals.
In this study, non-point source(NPS) contribution was investigated based on flow rates and water qualities of streams into the lake during rainfall events. Event mean concentration(EMC) and the pollution loads were calculated to establish a database for NPS control measurement in the survey area, and so on. The runoff characteristics of NPS were investigated and estimated on the basis of the ratio of an agricultural to forest area in the stream of sub-catch basin during rainfall events. Non-point source pollution loads were also calculated to establish a database for NPS control measure in the upstream lake Chinyang. At a rainfall event, BOD concentrations rise sharply at the early peak time of runoff, however, peaks of TSS concentration were observed at the similar time of peak flow. This was a phenomenon shown at the watersheds caused by forest and geological types. The discharged EMC range was 2.9-4.8 mg/L in terms of BOD. The discharged EMC range was 6.2-8.2 mg/L in terms of SS. The discharged EMCs of T-N and T-P were 1.4-2.5 mg/L and 0.059-0.233 mg/L, respectively. Total BOD loading rate through the 3 tributaries to the lake Chinyang was 1,136 kg/d during dry weather. The upper watershed area of the Nam-river dam in this study was divided into 14 catchment basins based on the Korean guideline for total maximum daily load(TMDL) of water quality pollutants. The higher the agricultural land-use ratio, the more NPS loading rate discharged, but the more occupied a forest area, the lower more NPS loading rate discharged. In an agricultural land-use area more than 20%, the increase of NPS loadings might be dramatically diffused by increasing the integrated complex-use like vinyl-house facilities and fertilizer use etc. according to the effective land-use utilization. The NPS loading rates were BOD 0.3 $kg/ha{\cdot}day$, SS 0.21 $kg/ha{\cdot}day$, TN 0.02 $kg/ha{\cdot}day$, TP 0.005 $kg/ha{\cdot}day$ under less than 10% agricultural land-use. In agricultural land-use of 20%-50%, these values were investigated in the range of 0.32 $kg/ha{\cdot}day$-0.73 $kg/ha{\cdot}day$ for BOD, 0.92 $kg/ha{\cdot}day$-3.32 $kg/ha{\cdot}day$ for SS, 0.70 $kg/ha{\cdot}day$-0.90 $kg/ha{\cdot}day$ TN, 0.03 $kg/ha{\cdot}day$-0.044 $kg/ha{\cdot}day$ for TP.
An integrated system of GIS and water quality model was suggested including the pollutant loads from the watershed. The developed system consists of two parts. First part is the GIS module. The geographic information system of the study area was built to provide the information on landuse and several surface factors concerning the overland flow processes of water and pollutants. Second part is the modeling modules which include storm event pollutant load model(SEPLM)., non-storm event pollutant load model(NSPLM), and river water quality simulation model(RWQSM). Models can calculate the pollutant load from the study area. The databases and models are linked through the interface modules resided in the overall system, which incorporate the graphical display modules and the operating scheme for the optimal use of the system. The developed system was applied to the Chungju multi-purpose reservoir to estimate the pollutant load during the four selected rainfall events between 1991 and 1993,. based upon monthly basis and seasonal basis in drought flow, low flow, normal flow and wet flow.
This study was conducted to evaluate the characteristics of nonpoint source pollutants discharge from a small rural watershed. A typical rural area in Gongju City, Korea, was selected as the research site. Water quality and quantity in streams and rainfall samples were analyzed periodically from May to October 2005. Pollutant loads were estimated from a nonpoint source pollution model (AvSWAT, Arcview Soil and Water Assessment Tool). During the rainy season, from June 26 to 30 September 2005 and the dry season, before 26 June and after 30 September 2005, biological oxygen demands and chemical oxygen demands accounted for 91.3% and 93.7% of annual load, respectively, while total-N and total-P were 97.1% and 91.1% of annual load, respectively. The observed stream flow was $66.5m^3sec^{-1}$, while simulation stream flow was $66.2m^3sec^{-1}$. That can be assumed that simulation can be used to estimate the stream flow without practical measurement. However, the runoff trend following the occurrence of a storm event was not recorded properly.
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