• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.5
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• pp.29-40
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• 2018

Even if a small amount of arsenic (As) is entering to small agricultural reservoir from upper streams, small agricultural reservoir becomes sensitive to changes in arsenic concentration depending on the water level in case of accumulation continuously because of its scale. If we want to manage arsenic concentration in small agricultural reservoir, it is very important to understand arsenic changes in agricultural reservoir. In spite of the fact that modeling is the most accurate method for analyzing arsenic concentration changes in small agricultural reservoirs, but, it is difficult to monitor arsenic change everyday. So, if data is prepared for modeling arsenic changes, water quality modeling is more effective than monitoring. Therefore, in this study, arsenic concentration changes was simulated and arsenic concentration change mechanism in small reservoir was analyzed using hydrological and water quality monitoring data and by conducting EFDC (Environment Fluid Dynamics Code)-WASP (Water Quality Analysis Simulation Program) linkage. EFDC-WASP coupling technique was very useful for modeling arsenic changes because EFDC can consider hydrodynamic and WASP can perform arsenic concentration simulation, separately. As a results of this study, during dry season, As concentration was maintained relatively high arsenic concentrations. Therefore, water level control will be needed for managing As concentration of reservoir.

• Environmental and Resource Economics Review
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• v.22 no.3
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• pp.521-545
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• 2013

This study applied choice experiment(CE) method(which is included in the stated preference method) to estimate values of some important attributes(i.e. type of estuary, water quality of river in estuary, water quality of sea in estuary, biodiversity level of estuary) of 4 major river(Hangang, Guemgang, Yeongsangang, Nakdonggang) estuaries in Korea. Although the multinomial logit model(MNL) is generally applied to analyse the CE data, testing for IIA assumption with the Hausman and McFadden test in MNL model shows that the IIA assumption in our data is rejected. Therefore, the heteroscedastic extreme value model(HEV) and the multinomial probit model(MNP) which are not based on the IIA assumption are used to analyse our CE data. As results, the coefficients and the elicited economic values of MNL model are seriously distorted if the IIA assumption is not satisfied in MNL model. The estimation results of MNP model show that the economic values are elicited as 352.3 billion won(95% C.I. 261.1 - 477.8 billion won) for natural estuary, 411.5 billion won(95% C.I. 338.5 - 525.5 billion won) for one grade improvement of river water quality in estuary, 358.9 billion won(95% C.I. 292.5 - 457.0 billion won) for one grade improvement of sea water quality in estuary, and 151.9 billion won(95% C.I. 99.0 - 218.6 billion won) for one grade improvement of biodiversity level of estuary. Therefore, the value of estuary is reached to 2,197.0 billion won(95% C.I. 1,721.0 - 2,879.9 billion won) if any natural estuary in 4 major rivers has good water quality of river in estuary(i.e. 2nd grade), good water quality of sea in estuary(i.e. 1st grade), and good biodiversity level of estuary.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.4
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• pp.177-188
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• 1993

Model parameters of the WASP4 applied to Lake Paldang were estimated. The methodology is based on grouping water quality constituents and relevant parameters and successively estimating each group of parameters by a trial-and-error procedure. Chlorophyll a, nitrogen cycles, phosphorus cycles, BOD and DO were simulated at the complexity level 4. A water budget analysis using the monthly records of reservoir inflows and outflows in 1989 and 1990 was made to determine seasonally-averaged flowrates at model boundaries. Estimated flowrates were used, together with the seasonal average of water quality measurements in 1989 and 1990 for the calibration and verification, respectively, of the model. Grouping water quality constituents and associated parameters proved to be efficient in estimating a number of model parameters. From the results of model calibration and verification, it was found that quantitative evaluations of nonpoint and benthic sources of organic matters are essential. Benthic sources near the entrance of the Kyeongancheon were the most significant.

• Korean Journal of Environmental Agriculture
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• v.31 no.2
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• pp.113-121
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• 2012

BACKGROUND: The Doam watershed in Korea has been managed for the reduction and the prevention of non-point source pollution since 2007. Especially, the water quality of the Doam reservoir is a primary issue related to the Doam dam reoperation. We have carried out the modeling to evaluate the water quality based on suspended solids (SS) of the Doam watershed and the Doam reservoir. Two powerful hydrological and water quality models (HSPF and CE-QUAL-W2) were employed to simulate the combined processes of water quantity and quality both in the upland watershed of the Doam reservoir and the downstream waterbody. METHODS AND RESULTS: The HSPF model was calibrated and validated for streamflow and SS. The CE-QUAL-W2 was calibrated for water level, water temperature, and SS and was validated for the only water level owing to data lack. With the parameters obtained through the appropriate calibration, SS concentrations of inflow into and in the Doam reservoir were simulated for three years (2008, 2004 and 1998) of the minimum, the average, and the maximum of total annual precipitation during recent 30 years. The annual average SS concentrations of the inflow for 2008, 2004, and 1998 were 8.6, 10.9, and 18.4 mg/L, respectively and those in the Doam reservoir were 9.2, 13.8, and 21.5 mg/L. CONCLOUSION(s): The results showed that more intense and frequent precipitation would cause higher SS concentration and longer SS's retention in the reservoir. The HSPF and the CE-QUAL-W2 models could represent reasonably the SS from the Doam watershed and in the Doam reservoir.

• Journal of Environmental Science International
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• v.12 no.8
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• pp.841-846
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• 2003

The ecosystem model was applied to estimate the regional distribution of the net production(or consumption) of phytoplankton and the net uptake(or regeneration) rate of nutrients in Masan Bay for scenario analysis to find a proper management plan. At the surface level, net production of phytoplankton is 200 mgC/㎡/day at the entrance of the bay, and 400∼1000 mgC/㎡/day at the center of the bay. The inner area of the bay showed more than 2000 mgC/㎡/day. All areas of the bottom level have a net consumption, with the center of the bottom level showing more than 600 mgC/㎡/day. For dissolved inorganic nitrogen, the results showed a net uptake rate of 100∼900 mg/㎡/day at the surface level. It showed that the net regeneration is above 50 mg/㎡/day at the bottom level. For dissolved inorganic phosphorus, the net uptake rate showed 10.0∼80.0 mg/㎡/day at the surface level, and the regeneration rate showed 0∼20.5 mg/㎡/day at the bottom level. Therefore, in order to control the water quality in Masan Bay, it is important to consider the re-supplement of nutrients regenerated in the water column.

• Journal of Environmental Science International
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• v.23 no.5
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• pp.839-852
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• 2014

The Ministry of Environment (MOE) has made more effort in managing point source pollution rather than in nonpoint source pollution in order to improve water quality of the four major rivers. However, it would be difficult to meet water quality targets solely by managing the point source pollution. As a result of the comprehensive measures established in 2004 under the leadership of the Prime Minister's Office, a variety of policies such as the designation of control areas to manage nonpoint source pollution are now in place. Various action plans to manage nonpoint source pollution have been implemented in the Soyang-dam watershed as one of the control areas designed in 2007. However, there are no tools to comprehensively assess the effectiveness of the action plans. Therefore, this study would assess the action plans (especially, BMPs) designed to manage Soyang-dam watershed with the WinHSPF and the CE-QUAL-W2. To this end, we simulated the rainfall-runoff and the water quality (SS) of the watershed and the reservoir after conducting model calibration and the model validation. As the results of the calibration for the WinHSPF, the determination coefficient ($R^2$) for the flow (Q, $m^3/s$) was 0.87 and the $R^2$ for the SS was 0.78. As the results of the validation, the former was 0.78 and the latter was 0.67. The results seem to be acceptable. Similarly, the calibration results of the CE-QUAL-W2 showed that the RMSE for the water level was 1.08 and the RMSE for the SS was 1.11. The validation results(RMSE) of the water level was 1.86 and the SS was 1.86. Based on the daily simulation results, the water quality target (turbidity 50 NTU) was not exceeded for 2009~2011, as results of maximum turbidity in '09, '10, and '11 were 3.1, 2.5, 5.6 NTU, respectively. The maximum turbidity in the years with the maximum, the minimum, and the average of yearly precipitation (1982~2011) were 15.5, 7.8, and 9.0, respectively, and therefore the water quality target was satisfied. It was discharged high turbidity at Inbuk, Gaa, Naerin, Gwidun, Woogak, Jeongja watershed resulting of the maximum turbidity by sub-basins in 3years(2009~2011). The results indicated that the water quality target for the nonpoint source pollution management should be changed and management area should be adjusted and reduced.

• Journal of Korean Society on Water Environment
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• v.31 no.2
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• pp.181-195
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• 2015

Algal blooms in lakes are one of major environmental issues in Korea. A three-dimensional, hydrodynamic and water quality model was developed and tested in Lake Euiam to assess the performance and limitations of numerical modeling with multiple algal groups using field data commonly collected for algal management. In this study, EFDC was adopted as the basic model framework. Simulated vertical profiles of water temperature, dissolved oxygen and nutrients monitored at five water quality monitoring stations from March to October 2013, which are closely related to algal dynamics simulation, showed good agreement with those of observed data. The overall spatio-temporal variations of three algal groups were reasonably simulated against the chlorophyll-a levels of those estimated from the limited monitoring data (chlorophyll-a level and cell numbers of algal species) with the RMSEs ranging from 2.6 to $17.5mg/m^3$. Also, note that $PO_4-P$ level in the water column was a key limiting factor controlling the growth of three algal groups during most of simulation period. However, the algal modeling results were not fully attainable to the levels of observation during short periods of time showing abrupt increase in algae throughout the lake. In particular, the green algae/cyanobacteria and diatom simulations were underestimated in late June to early July and early October, respectively. The results shows that better understanding of internal algal processes, neglected in most algal modeling studies, is necessary to predict the sudden algal blooms more accurately because the concentrations of external $PO_4-P$ and specific algal groups originated from the tributaries (mainly, dam water releases) during the periods were too low to fully capture the sharp rise of internal algal levels. In this respect, this study suggests that future modeling efforts should be focused on the quantification of internal cycling processes including vertical movement of algal species with respect to changes in environmental conditions to enhance the modeling performance on complex algal dynamics.

• Journal of Environmental Science International
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• v.7 no.6
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• pp.833-843
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• 1998

It is noted that the red tides and the oxygen-deficient water mass are extensively developed in Masan Bay during summer. The nutrients mass balance was calculated in Masan Bay, using the three-dimensional numerical hydrodynamic model and the material cycle model. The material cycle model was calibrated with the data obtained on the field of the study area in June 1993. The nutrients mass balance calculated by the combination of the residual currents and material cycle model results showed nutrients of surface and middle levels to be transported from the inner part to the outer part of Masan Bay, and nutrients of bottom level to be transported from outer part to inner part of Masan Bay. The uptake rate of DIN in the box A1(surface level of inner part) was found to be 337. 5mg/$m^3$ㆍday, the largest value in all 9 boxes and that of DIP was found to be 18.6mg/$m^3$ㆍday in box A1, and the regeneration rate of DIN was found to be 78.2mg/$m^3$ㆍday in the box A3(bottom level of inner part), and that of DIP was found to be 18.6mg/$m^3$ㆍday in box A1. The regenerations of DIN and DIP in the water column of the entire Bay were found to be 7.66ton/day and 760kg/day, respectively. And the releases of DIN and DIP from the sediments of the entire Bay were found to be 2.86ton/day and 634kg/day, respectively. The regeneration rate was 2.5 times as high as the release rate in DIN, and 1.2 times in DIP. The results of mass balance calculation showed not only the nutrients released from the sediments but the nutrients regenerated in water column to be important in the control and management of water quality in Masan Bay.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.3
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• pp.535-546
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• 2000

Juam lake is a major water resource for the industrial and agricultural activities as well as the resident life of Kwangju and Chonnam area. However, the water quality of the lake is getting worse due to a large quantity of pollutant inflowing to the lake. As a preliminary step in making the countermeasure to achieve the water quality goal of the lake. it is necessary to understand how the water quality of the lake will be in future. Several computer programs can be used to predict the water quality of lake. Each of these programs requires a number of input data such as hydrological and meteorological data. and the quantity of the pollutant inflowed. but some or most of the input data contain uncertainty. which eventually results in the uncertainty of prediction value (future level of water quality). Generally. the uncetainty stems from the lack of information available. the randomness of future situation. and the incomplete knowledge of expert. Thus. the purpose of this study is to present a method for representing the degree of the uncertainty contained in input data by applying fuzzy theory and incorporating it directly into the water quality modeling process. By using the method. the prediction on the future water quality level of Juam lake can be made that is more appropriate and realistic than the one made without taking uncertainty in account.

• Journal of Wetlands Research
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• v.22 no.2
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• pp.106-112
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• 2020

Wetlands play an important function and role in hydrological, environmental, and ecological, aspects of the watershed. Water level in wetlands is essential for various analysis such as for the determination of wetland function and its effects on the environment. Since several wetlands are ungauged, research on wetland water level prediction are uncommon. Therefore, this study developed a water level prediction model using multiple regression analysis, principal component regression analysis, artificial neural network, and DNN to predict wetland water level. Geumjeong-Mountain Wetland located in Yangsan-city, Gyeongsangnam-do province was selected as the target area, and the water level measurement data from April 2017 to July 2018 was used as the dependent variable. On the other hand, hydrological and meteorological data were used as independent variables in the study. As a result of evaluating the predictive power, the water level prediction model using DNN was selected as the final model as it showed an RMSE value of 6.359 and an NRMSE value of 18.91%. This research study is believed to be useful especially as a basic data for the development of wetland maintenance and management techniques using the water level of the existing unmeasured points.