Search

Among the input data of the watershed model for simulating changes of flowrate in the watershed, weather input data, especially input data related to rainfall, are the most important. Therefore, it is important to ensure the accuracy of rainfall input data to increase the accuracy of the watershed model results. Securing rainfall measurements with finer spatial and temporal resolutions is important in predicting flowrate variations at a sub-catchment, especially as they relate to global and local climate changes in weather conditions such as rainfall depth, rainfall intensity, etc. In this study, adjusted radar-rainfall estimates were suggested as alternative input data for watershed modeling. Through a statistical analysis of the representativeness of a ground rainfall measurement (10 km × 10 km grid), the necessity of radar-rainfall estimates (2 km × 2 km grid) was identified. By applying calibration factors to initial radar-rainfall estimates and comparing adjusted radar-rainfall estimates with ground rainfall measurements, it was proven that adjusted radar-rainfall estimates could be used as input data for watershed simulations (NSE > 0.92; n = 12). Adjusted radar-rainfall estimates and ground rainfall measurements were used as input data of the Soil and Water Assessment Tool model to predict flowrate variations at the outlets of a tributary and the entire watershed. As a result, the accuracies of the simulation results were improved for the outlets of a tributary and the entire watershed (NSE: 0.33 to 0.48 and 0.19 to 0.55, respectively). To obtain more reliable rainfall data, radar images easily accessible to users were applied, and the accuracy of the data was increased by applying simple equations to numerical data extracted from radar image processing. Additionally, the applicability of the adjusted radar-rainfall estimates was demonstrated by comparing the modeling results using the suggested rainfall data and existing ground-based rainfall data. The suggested methodologies are expected to contribute to more accurately predict the possibility of flood disasters in other regions and countries lacking infrastructure related to rainfall measurements and to establish appropriate countermeasures.

When stormwater runoff flows into a constructed wetland, the water level changes inside, and the volume of the wetland changes accordingly. In this study, the relationship between pollutant removal and water depth flowrate changes was analyzed with velocity phase analysis, using the concepts of horizontal velocity and vertical velocity. A constructed wetland located in an agricultural area was used for the velocity phase analysis. Analysis results revealed that all four ponds and Phases I and III accounted for over 90% of the pollutant load. In particular, Phase III, where vertical and horizontal velocities were reduced, was responsible for approximately twice the load on average. The reason for the highest load in Phase III was due to the inflow of contaminants into the constructed wetland through the first flush effect occurred at the time when the flow rate decreased due to the difference in runoff strength. Therefore, it is necessary to maximize Phases I and III in the velocity phase when designing multi-stage wetlands to make the flow of water more natural. Furthermore, considering pollutant load levels, a design review is needed to expand the size of downstream wetlands, so that they can optimize water quality management functions.

Chlorophyll-a (Chl-a) is a direct indicator used to evaluate the ecological state of a waterbody, such as algal blooms that degrade the water quality in lakes, reservoirs and estuaries. In this study, artificial neural network (ANN) and support vector machine (SVM) were used to predict Chl-a concentration for the early warning in the Juam Reservoir and Yeongsan Reservoir, which are located in an upstream region (freshwater reservoir) and downstream region (estuarine reservoir), respectively. Weekly water quality data and meteorological data for a 7-year period were used to train and validate both the ANN and SVM models. The Latin-hypercube one-factor-at-a-time (LH-OAT) method and a pattern search algorithm were applied to perform sensitivity analyses for the input variables and to optimize the parameters of the two models, respectively. Results revealed that the two models well-reproduced the temporal variation of Chl-a based on the weekly input variables. In particular, the SVM model showed better performance than the ANN model, displaying a higher prediction accuracy in the validation step. The Williams-Kloot test and sensitivity analysis demonstrated that the SVM model was superior for predicting Chl-a in terms of prediction accuracy and description of the cause-and-effect relationship between Chl-a concentration and environmental variables in both the Juam Reservoir and Yeongsan Reservoir. Furthermore, a 7-day interval was determined as an efficient early warning interval in the two reservoirs. As such, this study suggested an effective early-warning prediction method for Chl-a concentration and improved the eutrophication management scheme for reservoirs.

This study reveals land-use factors that explain stream water quality during wet and dry weather conditions in a large river basin using two different linear models-multiple linear regression (MLR) models and constrained least squares (CLS) models. Six land-use types and three topographical parameters (size, slope, and permeability) of the watershed were incorporated into the models as explanatory variables. The suggested models were then demonstrated using a digitized elevation map in conjunction with the land-use and the measured concentration data for Escherichia coli (EC), Enterococci bacteria (ENT), and six heavy metal species collected monthly during 2007-2008 at 50 monitoring sites in the Yeongsan Watershed, Korea. The results showed that the MLR models can be a powerful tool for predicting the average concentrations of pollutants in stream water (the Nash-Sutcliffe (NS) model efficiency coefficients ranged from 0.67 to 0.95). On the other hand, the CLS models, with moderately good prediction performance (the NS coefficients ranged 0.28-0.85), were more suitable for quantifying contributions of respective land-uses to the stream water quality. The CLS models suggested that industrial and urban land-uses are major contributors to the stream concentrations of EC and ENT, whereas agricultural, industrial, and mining areas were significant sources of many heavy metal species. In addition, the slope, size, and permeability of the watershed were found to be important factors determining the extent of the contribution from each land-use type to the stream water quality. The models proposed in this paper can be considered useful tools for developing land cover guidelines and for prioritizing locations for implementing management practices to maintain stream water quality standard in a large river basin.

As a representative urban stream in Korea, the Gwangju (GJ) stream suffers from chronic fecal contamination. In this study, to characterize levels of fecal pollution in the GJ stream, the monthly monitoring data for seven years (from 2001 to 2007) and the hourly monitoring data from two field experiments were examined with respect to seasonal/daily variations and spatial distribution under wet and dry weather conditions. This research revealed that concentrations of fecal indicator bacteria strongly varied depending on the prevalent meteorological conditions. That is, during the dry daytime, fecal indicator bacteria concentrations decreased due to inactivation from solar irradiation, but rapidly increased in the absence of sunlight, suggesting external source inputs. In addition, bacterial concentrations substantially increased during rainfall events, due probably to a major contribution from combined sewer overflow. The observations in this study can be useful for implementing fecal pollution management strategies and for predicting fecal contamination as a function of meteorological conditions.

Gwangju Creek (GJC) in Korea, which drains a highly urbanized watershed, has suffered from substantial fecal contamination, thereby limiting the beneficial use of the water in addition to threatening public health. In this study, to quantitatively estimate the sinks and sources of fecal indicator bacteria (FIB) in GJC under varying meteorological conditions, two FIB (i.e., Escherichia coli and enterococci bacteria) were monitored hourly for 24 h periods during both wet and dry weather conditions at four sites along GJC, and the collected data was subsequently used to develop a spatiotemporal FIB prediction model. The monitoring data revealed that storm washoff and irradiational die-off by sunlight are the two key processes controlling FIB populations in wet and dry weather, respectively. FIB populations significantly increased during precipitation, with greater concentrations occurring at higher rainfall intensity. During dry weather, FIB populations decreased in the presence of sunlight in daytime but quickly recovered at nighttime due to continuous point-source inputs. In this way, the contributions of the key processes (i.e., irradiational die-off by sunlight, settling, storm washoff, and resuspension) to the FIB levels in GJC under different meteorological conditions were quantitatively estimated using the developed model. The modeling results showed that the die-off by sunlight is the major sink of FIB during the daytime in dry weather with a minor contribution from the settling process. During wet weather, storm washoff and resuspension are equally important processes that are responsible for the substantial increase of FIB populations.

The present study proposes a methodology for determining the effective dispersion coefficient based on the field measurements performed in Gwangju (GJ) Creek in South Korea which is environmentally degraded by the artificial interferences such as weirs and culverts. Many previous works determining the dispersion coefficient were limited in application due to the complexity and artificial interferences in natural stream. Therefore, the sequential combination of N-Tank-In-Series (NTIS) model and Advection-Dispersion-Reaction (ADR) model was proposed for evaluating dispersion process in complex stream channel in this study. The series of water quality data were intensively monitored in the field to determine the effective dispersion coefficient of E. coli in rainy day. As a result, the suggested methodology reasonably estimates the dispersion coefficient for GJ Creek with 1.25 m2/s. Also, the sequential combined method provided Number of tank-Velocity-Dispersion coefficient (NVD) curves for convenient evaluation of dispersion coefficient of other rivers or streams. Comparing the previous studies, the present methodology is quite general and simple for determining the effective dispersion coefficients which are applicable for other rivers and streams.

Water quality impairment from nonpoint source pollution is one of the critical causes of surface water eutrophication in rivers and lakes surrounding agricultural area, Korea. In the Songchon Constructed Wetland (SCW) located in Yeongsan (YS) watershed which has about 1,000 km2 (total watershed area: 3,471 km2) for agricultural area, 19 times of intensive field monitoring in 2010 were conducted with various rainfall patterns and about more 1,000 water samples were measured and analyzed in field and laboratory. To identify the relationship between meteorological conditions and removal efficiency of the constructed wetland, principal component analysis (PCA) and ternary plot analysis was used for 19 field experiment data. Mean treatment performance of TSS, BOD5, COD, TN, and TP was 16.4%, 42.1%, 43.7%, 36.6%, and 57.1%, respectively, as a method of pollutant load reduction for multiple tests of storm events. PCA results revealed that rainfall depth, rainfall intensity, and antecedent dry days (ADDs) can be major components as a representative in each component. Also, ternary contour plots results showed that the treatment performance of SCW in agricultural area during storm events can be affected by three meteorological conditions. These results and phenomena can be applicable to develop the NPS discharge model and to elucidate the relationship between rainfall and storm water runoff using rain radar in a drainage area.

This paper describes a management scheme to control river water quality using additional water discharges from upstream dams, which results in an increase environmental flow (EF) followed by an enhancement of water quality in a target river. To suggest a creditable management plan among a suite of ideal scenarios, the monthly averaged water quality monitoring data from 2001 to 2006 at the Yeongsan (YS) River, Korea were investigated with respect to seasonal variation and spatial distribution. From the analysis, it was found that while biochemical oxygen demand (BOD5) level in the YS River was extremely high during the dry/drought season (April, May, and June; AMJ), the level was subsequently decreased during the monsoon season (July, August, and September; JAS) due mainly to the dilution effect of rainfall. To improve the water quality in AMJ, we here suggested a scenario of increasing EF using surplus water discharges from upstream dams, which was examined by one dimensional riverine water quality model, QUAL2E model. Simulation result showed that additional discharge from the upstream dams could lead, on average, to a 36% of water quality improvement in mainstream with respect to BOD5. Model coefficients were validated by comparing the six year monitoring data to minimize a sum of squares error, and showed a good agreement with the observed data. Overall, the methodology developed in this paper appears to be quite clear and straightforward, and thus, can be applied to a wide range of the flow managements or water quality controls in a stream with artificial structures.

Artificial lakes, initially built in estuaries for positive purposes such as flood prevention and providing irrigation water, have been found to have negative impacts including blocking tidal cycles, disappearance of brackish water zones, sediment increase, water pollution, change of microbial diversity inhabiting patterns, and a decline in fish diversity. In this study, multidisciplinary field studies including physical, chemical, and biological analyses were performed to demonstrate decadal and seasonal scale changes in the ecological environment in Yeongsan Reservoir (YSR), Korea, since the construction of a 4.35 km-long dam in 1981. The results of the study show that the volume of sediment accumulated in YSR was 75.2 million m(3) since the dam was constructed, resulting in a 33.6% reduction of the total water storage capacity. Also, water quality in YSR was affected by complex physico-chemical and hydrological phenomena, including saline and thermal stratifications, and pollutant loadings leading to eutrophication. Subsequent sediment bacteria analyses showed microbial diversity according to different depths in sediment, indicating the environmental change of sediment ecology. Moreover, the fish diversity in this study (2006-2007) was found to be considerably reduced compared to a similar study in 1989 (42% reduction), and the ecological health was deemed to be in a "poor" condition based on the 10-metric Lentic Ecosystem Health Assessment (LEHA) model. Accordingly, these results indicate that aquatic ecosystems are detrimentally affected by estuarine dams that block tidal flows, and when applied to short/long-term management strategies for artificial lakes in estuaries, suggest that similar construction projects have to be suitably controlled.

A comprehensive water quality monitoring program was conducted in the Yeongsan (YS) River, Korea from 2005 to present to investigate wet and dry weather pollutant discharge in an attempt to establish point and non-point pollution management strategies. As part of this monitoring program, 11 heavy metal species were measured during dry and wet weather conditions in the YS River, where Gwangju City (GJ), a subcatchment of the YS River, was further monitored to clarify the responsibility of different metal species discharged into the mainstream. Monthly grab water samples showed that greater amounts of metals along the YS River were discharged during the wet summer months due largely to storm runoff. In addition, further monitoring results revealed that GJ, a highly urbanized area, was a significant contributor of the heavy metals being discharged into the YS River during both wet and dry weather. The most abundant metal species discharged from GJ were manganese, aluminum and iron with different contributions of wet and dry weather flows to the total discharge load. Wet weather flow was a significant contributor to the annual dissolved metal loads, accounting for 44-93% of the annual load depending on the metal species, with the exception of chromium and cadmium (9% and 27%, respectively). Mostly, metal loads during wet weather were shown to be proportional to the rainfall depth and antecedent dry period. A substantial fraction of metals were also associated with solids, suggesting that sedimentation might be an appropriate management practice for reducing the metal load generated in GJ. Overall, although dissolved metal concentrations in YS River were at an acceptable level for aquatic community protection, continual metal discharge throughout the year was considered to be a potential problem in the long-term due to gradual water quality degradation as well as continuous metal accumulation in the system.

A comprehensive monitoring program was conducted during 2005-2007 to investigate seasonal variations of hydrologic stability and water quality in the Yeongsan Reservoir (YSR), located at the downstream end of the Yeongsan River, Korea. A principal component analysis (PCA) was performed to identify factors dominating the seasonal water quality variation from a large suite of measured data--11 physico-chemical parameters from 48 sampling sites. The results showed that three principal components explained approximately 62% of spatio-seasonal water quality variation, which are related to stratifications, pollutant loadings and resultant eutrophication, and the advective mixing process during the episodic rainfall-runoff events. A comparison was then made between YSR and an upstream freshwater reservoir (Damyang Reservoir, DYR) in the same river basin during an autumn season. It was found that the saline stratification and pollutant input from the upstream contributed to greater concentrations of nutrients and organic matter in YSR compared to DYR. In YSR, saline stratification in combination with thermal stratification was a dominant cause of the longer period (for two consecutive seasons) of hypoxic conditions at the reservoir bottom. The results presented here will help better understand the season- and geography-dependent characteristics of reservoir water quality in Asian Monsoon climate regions such as Korea.

Water quality response in a reservoir has often been assessed using relatively restricted datasets that cannot provide sufficient information, thereby giving rise to a dramatic over- or underestimate of actual figures. In this paper we discuss how the levels of metallic elements between the sediment and overlying water in an estuarine reservoir can be influenced by aquatic parameters in response to spatial and seasonal conditions. To better elucidate the interfacial exchange between sediment and water, statistical analyses are employed to intensive data sets collected from the Yeongsan Reservoir (YSR), Korea, which has undergone widespread deterioration in water quality due to the continuous growth of anthropogenic sources. During three seasonal sampling campaigns, we found that oxygen deficiency at the bottom water layer promotes Fe and Ni accumulation in sediment, likely due to the formation of sulfide and oxide complexes under anoxic and suboxic environments, respectively. In addition, salinity levels as high as 11 per thousand in the bottom water layer during autumn substantially increase the release of Mn, restricting the use of YSR as a primary source of agricultural irrigation water. Although most dissolved metals are at acceptable levels for sustaining aquatic life, it is recommended that for long-term planning the elevated Fe and Mn levels in sediment should be controlled with oxygen deficiency during dry weather to ensure a sustainable water supply or, at a minimum, better coordinated operation of YSR.