Objectives:A large-scale freshwater lake is a freshwater lake with a storage of 5,000,000 tons or more among freshwater lakes. It is located at the end of the basin, so complex and various pollutants flow in from a wide basin, and it has a characteristic of longer retention and greater accumulation for a long time in the lake. Since the continuous inflow and accumulation of non-point pollution sources for agricultural purpose occurred due to the repeated reuse of agricultural water near freshwater lakes, and the complex water use and occurred drainage structure, water pollution is aggravating. In this study, the main pollution sources of large-scale freshwater lakes were derived through multivariate statistical analysis using various water quality factors for efficient freshwater lake management. The analysis is performed out to predict the future Chlorophyll-<i>a</i>(Chl-<i>a</i>) and to identify major factors affecting algal growth, and to use them as establish effective countermeasures to improve water quality based on the characteristics of freshwater lakes algal growth the future.Methods:In the case of GanWol(GW), GeumGang(GG), GeumHO(GeH), NamYang(NY), DaeHo(DH), BuNam(BN), SapGyo(SG), ASan(AS), YoungSan(YS), YoungAm(YA) in the water environment information system operated by the Ministry of Environment, water quality data on a monthly basis for 10 years from January, 2011 to December, 2020 were collected from three point measurement located in the lake. In the case of GoHeung(GoH), GunNae(GN), Busa(BS), SeokMoon(SM), and HaeNam(HN), water quality data were collected on a quarterly basis for 5 years from April 2015 to March 2019 from one point measurement located in the lake.Results and Discussion:As a result of Korean trophic state index (TSI_ko) analysis, most of the large-scale freshwater lakes in the central region of the West Sea were classified as Hypertrophic, and all of the large-scale freshwater lakes in the southern region of the West Sea were classified as Eutrophic. Based on the results from factor analysis and principal component analysis, countermeasures against organic matters, nutrients, and algal bloom in terms of type of large-scale freshwater lake should be prepared. As a result of multiple linear regression analysis for Chl-<i>a</i> prediction, large-scale freshwater lakes in the central region of the West Sea had higher explanatory rates than large-scale freshwater lakes in the southern region of the West Sea, but all were analyzed below 0.8, suggesting that the accuracy was not high.Conclusions:BOD, COD, TOC, T-N, and T-P concentration of freshwater lakes in the central region of the West Sea have more deterioating water quality than freshwater lakes in the southern region of the West Sea, suggesting that organic pollutants and nutrients need to be managed. As a result of the factor analysis, it is judged that organic matter & algae type nutrient type, and complex type classification, and appropriate water quality management measures for each type are required. All regression models used for prediction of Chl-<i>a</i> were analyzed as <i>p</i><0.05, and the independent variables of each prediction formula were meaningful in explaining Chl-<i>a</i>. Chl-<i>a</i> is changed by the complex effects of various water quality factors, and it is also judged that the influence of water quality external products such as precipitation, sunshine time, and flow rate should also be considered. In the future, if the regression is performed by integrating the water quality factors and external factors of a longer period, it is possible to create a model with a slightly higher explanatory rate by increasing the R² value.

Objectives : In this study, the characteristics of stormwater runoff from agricultural nonpoint pollution sources investigated under various experimental conditions were evaluated among different land use types (e.g., paddy, field, field (alpine), and vinyl house), and event mean concentrations (EMCs) for each water quality parameter were statistically analyzed. These results can be used in calculating the contribution of stormwater runoff to water quality of receiving water body by performing quantitative and qualitative analysis. The unit loads calculated were compared with Ministry of Environment TMDL (2019) to secure the reliability of the calculated unit loads.Methods : EMCs and unit loads investigated in various studies were classified in terms of paddy, field, field (alpine), and vinyl house. Among various land use types, EMCs and unit loads were statistically analyzed quantitatively and qualitatively. For EMCs, a null hypothesis is that ‘EMCs of water quality parameters among different land use types are not different at a statistically significant level (α=0.05)’. Based on the results of statistical analysis, heteroscedasticity (p<0.05) and Welch-test method were consequently applied, and post hoc test was performed using the Games-Howell method. Finally, unit loads was compared and reviewed against the TMDL (2019) unit loads of the Ministry of Environment.Results and Discussion : Various EMCs in all water quality parameters were found among different land use types (i.e., paddy, field, field (alpine) and vinyl house). For most water quality parameters, EMCs tended to decrease in the order of field (alpine) > field > vinyl house > paddy. The coefficient of variance (CV) values of all water q uality parameters were 0.5 or greater. Based on these results, EMCs in agricultural nonpoint source pollution are very diverse and deviated due to the combination of natural and artificial factors. Post hoc test results indicated different statistical significance among all water quality parameters. In addition to the land use types, both natural factors (i.e., season, rainfall, antecedent rainfall day, and, rainfall runoff rate) and artificial factors (i.e., cultivator manipulation, emission route, type of crop, and amount of compost) affect the characteristics of stormwater runoff. In particular, in the case of field (alpine) with prominent topographical feature of slope, and EMCs were statistically greater than those from other land use types in all water quality categories (p<0.05).Conclusions : Countermeasures for field (alpine)with greater EMCs than paddy, field and vinyl house, should be performed priority. EMCs were affected by a complex interaction between natural factors (i.e., season, rainfall, antecedent rainfall day, and, rainfall runoff rate) and artificial factors (i.e., cultivator manipulation, emission route, type of crop, and amount of compost), and additional data and research are required for further study to elucidate these complex interactions.