• Journal of Korean Society on Water Environment
• /
• v.26 no.5
• /
• pp.796-801
• /
• 2010

Water quality index (WQI) can be a great tool that allows experts to translate large amount of complex water quality data into a format more easily understood by the public and policy makers. Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) can be calculated with the three factors (Scope: $F_1$, Frequency: $F_2$, Amplitude: $F_3$). After all, the WQI for a specific site is produced as a number between 0 to 100; the scale is also divided into five categories, i.e., Excellent, Good, Fair, Marginal and Poor. The WQI was found to be highly related to Chl-a, pH, temperature among the collected items. When the more input parameters were used, the range of variation generally became smaller. $F_3$ among the factors of WQI was influenced by algae. It showed a similar variation tendency between WQI and algal bloom in 2008.

• Journal of Korean Society on Water Environment
• /
• v.21 no.5
• /
• pp.470-476
• /
• 2005

The Korean Water Quality Index (K-WQI) was applied to the rivers located in the watershed of Daecheong Lake to assess the status of river water quality, and propose potential target constituents for better water quality management in the watershed. The estimated K-WQI value for each river was varied from 70 to 90, and Youngdongcheon showed the worst score while Mujunamdeachen showed the best score. The total nitrogen (TN) and total coliform bacteria were identified as the most significant constituents that degrade the K-WQI values in the rivers. The correlation coefficients (r) were determined between K-WQI and the delivered specific load ($kg/km^2/yr$) of BOD, TN, and TP to justify potential target constituents that have a great influence on the improvement of K-WQI values. The results showed that TN (r=-0.86) and TP (r=-0.85) have a strong negative relationships with K-WQI, but BOD have almost no effect. This implies that BOD, the surrogate parameter for organic pollutants, is no more a feasible water quality variable for the water quality management in the study site.

• Korean Journal of Ecology and Environment
• /
• v.46 no.2
• /
• pp.225-233
• /
• 2013

We examined the effect of different field temperatures on water quality improvement (WQI) of natural domestic plant-mineral composites (PMCs). This method was previously used by Kim et al. (2011), to monitor the restoration of water quality of a eutrophic lake, Lake Shingal (Korea). Results indicate that PMCs on phytoplankton, BOD and phosphorus showed more than 70% WQI below $20^{\circ}C$, and less than 40% WQI over $25^{\circ}C$, respectively. The WQIs of PMCs on blue-green algae were gradually decreased with the increase of temperature, whilst diatoms exhibited more than 90% higher WQIs, regardless of water temperature. Additionally, the WQIs on bacterial biomass and total nitrogen were low at all temperatures. These results collectively indicate that water quality improvement activity of plant-mineral composites was dependent on the water temperature, and that the field application of above chemical during temperatures over $25^{\circ}C$, would be less effective in treating a cyanobacteria bloom dominated by Microcystis aeruginosa, than by diatoms.

• Journal of Environmental Health Sciences
• /
• v.31 no.5 s.86
• /
• pp.398-403
• /
• 2005

This study is undertaken to find the optimal method to make the decision on the degree of water pollution by comparison of K-WQI, KOE-WQI that is made for index with the water quality index and water quality environment standard of the Frame Act on Environment Policy as the result of survey for water quality reality on the major point of the Yeongsan river from 2002 to 2004. The water quality of major rivers has some differences depending on seasons. however, under the water quality standard by the $BOD_5$ density, most of rivers displayed the water quality level of $II{\sim}III$ grading, and on K-WQI that is classified by indexing for 10 categories of pH, DO, $BOD_5,\;COD,\;SS,\;T-N,\;NH_3-N,\;NO_{3^-}$ N, T-P, and E-Coli and classified into 5 groups from 100 points to 40 points, they displayed the score distribution of the first grade in water quality for $85{\sim}100$ points to the second grade in water quality for $70{\sim}84$ points. On KOE-WQI that is classified by indexing for 5 categories of pH, DO, $BOD_5$, COD and T-coli and classified into 5 groups from 90 points or above for outstanding and 29 points or below for very bad, and the water quality distribution is made ranged from the first grade in water quality for 90 points or more to the third grade in water quality for $69{\sim}50$ points. In addition, for the contribution of the water quality decline, the Environmental standard has significant dependency on the $BOD_5$ density, with K-WQI contributing in various water quality decline depending on the environment around the river area of $BOD_5,\;T-N,\;NH_3-N,\;NO_3-N,\;T-P$, and E-Coli, and KOE-WQI acting os the factor contributing to lower the water quality decline by $BOD_5$, COD, and T-coli. As such, the current water quality environment standard has high dependency on $BOD_5$ and KOE-WQI excludes some nitrogen and phosphorus that considers the river environment that the grade in water quality is set by some category, and K-WQI reflected well of the ecology environment of rivers with the diversity of the assessment factor as well as to have the low dependency of specific factor to be objective.

• Journal of Korean Society on Water Environment
• /
• v.22 no.5
• /
• pp.748-756
• /
• 2006

Accurate and timely information on status and trends in the environment is necessary to shape sound water quality management policy and to implement water quality improvement programs efficiently. One of the most effective ways to communicate information on water quality trends to policy-makers, scientists, and the general public is with comprehensive water quality indices. The derivation and structure of a water quality index (WQI) for the classification of surface water quality is discussed. The WQI generally developed through the selection, transformation and weighting of determinants with rating curves based on legal standards and quality directives or guidelines. The representative pollutants should be included in the index, and the relationship between the quantity of these pollutants in the water and the resulting quality of the water should be based on scientific results. The WQI be simply and meaningfully formulated that nonscientifically trained users can easily become familiar with the framework of the system and use the output data to evaluate their own pollution problems.

• Korean Journal of Remote Sensing
• /
• v.32 no.3
• /
• pp.221-234
• /
• 2016

In Korea, most industrial parks and major cities are located in coastal areas, which results in serious environmental problems in both coastal land and ocean. In order to effectively manage such problems especially in coastal ocean, water quality should be monitored. As there are many factors that influence water quality, the Korean Government proposed an integrated Water Quality Index (WQI) based on in situmeasurements of ocean parameters(bottom dissolved oxygen, chlorophyll-a concentration, secchi disk depth, dissolved inorganic nitrogen, and dissolved inorganic phosphorus) by ocean division identified based on their ecological characteristics. Field-measured WQI, however, does not provide spatial continuity over vast areas. Satellite remote sensing can be an alternative for identifying WQI for surface water. In this study, two schemes were examined to estimate coastal WQI around Korea peninsula using in situ measurements data and Geostationary Ocean Color Imager (GOCI) satellite imagery from 2011 to 2013 based on machine learning approaches. Scheme 1 calculates WQI using estimated water quality-related factors using GOCI reflectance data, and scheme 2 estimates WQI using GOCI band reflectance data and basic products(chlorophyll-a, suspended sediment, colored dissolved organic matter). Three machine learning approaches including Random Forest (RF), Support Vector Regression (SVR), and a modified regression tree(Cubist) were used. Results show that estimation of secchi disk depth produced the highest accuracy among the ocean parameters, and RF performed best regardless of water quality-related factors. However, the accuracy of WQI from scheme 1 was lower than that from scheme 2 due to the estimation errors inherent from water quality-related factors and the uncertainty of bottom dissolved oxygen. In overall, scheme 2 appears more appropriate for estimating WQI for surface water in coastal areas and chlorophyll-a concentration was identified the most contributing factor to the estimation of WQI.

• Korean Journal of Ecology and Environment
• /
• v.50 no.1
• /
• pp.46-56
• /
• 2017

The Youngsan River estuary was physically changed by the construction of a sea embankment at near the mouth of estuary. Weirs were also constructed recently in the freshwater zone and it was reported that algal blooms occur more frequently. The freshwater introduced into saltwater zone from sluice gates of the embankment affects water quality but it has not been addressed that how the freshwater inputs influence the health of marine ecosystem. In this study, we used the data of water properties and phytoplankton communities collected at three stations for 4 days including before the freshwater discharge, during the discharge and after 1 and 2 days of discharge events. WQI(water quality index), TRIX (trophic status index) and P-IBI(phytoplankton index of biotic integrity) were used to evaluate the ecosystem health and long-term data were also utilized to determine the criteria for P-IBI. The results showed that grades of the ecosystem health assessed by the indices were low at the station near the gates and increased as downstream. However, the temporal pattern of grades was different depending on methods. Grades of WQI and TRIX decreased during the discharge and restored after the discharge whereas the grades of P-IBI decreased slightly even after the discharge. This suggests that P-IBI is more applicable to estuarine systems where experience extreme change of water properties than WQI and TRIX since P-IBI includes phytoplankton that can respond quickly to the change.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.16 no.2
• /
• pp.102-114
• /
• 2013

The basin of Lake Shihwa is one of highly industrialized region of Korea and a current environmental issue of study area is the operation of tidal power plant (TPP) to improve water quality. The application of water quality index (WQI) which integrates five physiochemical parameters (transparency, DO, DIN, DIP and chlorophyll-a) of water quality in Lake Shihwa and outer sea during 2011~2012 were performed not only to evaluate the spatial and temporal distribution of the water quality but also to assess the effect of water quality improvement by the operation of tidal power plant. The higher WQI values were observed in monitored sites near the industrial complexes in Lake Shihwa and the outfall of wastewater treatment plants (WWTPs) in outer sea. This indicates that the quality of seawater is influenced by diffuse non-point sources from industrial, municipal and agricultural areas in Lake Shihwa and by point sources from the effluence of municipal and industrial wastewater throughout WWTPs in outer sea. Mean WQI value decreased from 53.0 in 2011 to 42.8 in 2012 of Lake Shihwa. Water quality has improved significantly after TPP operation because enhancement of seawater exchange between Lake Shihwa and outer sea leads to improve a hypoxic condition which is primarily a problem in Lake Shihwa. Mean WQI of outer sea showed similar values between 2011 and 2012. However, the results of hierarchical cluster analysis and the deterioration of water quality in summer season indicate that the operation of tidal power plant was not improved the water quality in the upper most area of Lake Shihwa. To successfully improve overall water quality of Lake Shihwa, it is urgently necessary to manage and reduce of non-point pollution sources of the basin of Lake Shihwa.

• Journal of Environmental Science International
• /
• v.29 no.6
• /
• pp.659-672
• /
• 2020

Water and sediment qualities were investigated in the Oncheon Stream and at the Wondong bridge of the Suyoung River, during the summer rainy season, 2019. Dissolved oxygen (DO) showed the lowest levels at 4.7 and 5.0 m/L, and biogeochemical oxygen demand (BOD) showed the highest at 5.3 mg/L downstream where the tributary flows into the main river. Chemical oxygen demand (COD) increased from 2.0 to 5.9 mg/L on average as it flowed downstream, The COD/BOD ratio decreased gradually as it flowed downstream, reaching 1.0. However, COD/BOD ratio at the Wondong bridge was 5.8-22.2, indicating that easily biodegradable and non-biodegradable organic matter flows into the Oncheon Stream and Suyoung River, respectively. Total nitrogen (T-N) / total phosphorus (T-P) ratio tended to decrease from 72 to 21 as it flowed downstream, measuring 71 to 86 at the Wondong bridge. The water quality index (WQI) generally improved better than grade IV after heavy rainfalls. However, DO and T-P were the parameters that deteriorated the WQI. Ignition loss (IL), COD, T-N, and T-P of sediments had distribution of 1.44 ± 1.01%, 0.35 ± 0.16%, 43 ± 63 mg/kg, and 10.9 ± 21.9 mg/kg, respectively. These were several times lower than the annual averages of IL, T-N, and T-P in 2017 before the dredging project was conducted in the first half of 2018.

• Journal of Wetlands Research
• /
• v.19 no.3
• /
• pp.311-317
• /
• 2017

In this study, the water quality index was calculated using the water quality monitoring data in the Nakdong River water system and the water quality status was compared with the living standard. The water quality index was selected by the RWQI method CCME-WQI currently used by the Ministry of Environment. The water quality items were selected as 7 items for pH, DO, EC, water temperature, TOC, T-N and T-P. The evaluation period was selected from the last three years (2013~2015) and water quality monitoring data measured within the period were used. As a result of the evaluation, the results of the previous evaluation showed similar tendency to the index of living environment, but the monthly evaluation showed different BOD and T-P results. Therefore, it is concluded that it is more reliable that more complex evaluation than single water quality evaluation is needed for efficient river management.