A hybrid approach to improvement of watershed water quality modeling by coupling process-based and deep learning models.

Watershed water quality modeling to predict changing water quality is an essential tool for devising effective management strategies within watersheds. Process-based models (PBMs) are typically used to simulate water quality modeling. In watershed modeling utilizing PBMs, it is crucial to effectively reflect the actual watershed conditions by appropriately setting the model parameters.

Optimization of the Design Configuration and Operation Strategy of Single-Pass Seawater Reverse Osmosis.

The numerical study was conducted to compare process performance depending on the pump type and process configuration. The daily monitoring data of seawater temperature and salinity offshore from Daesan, Republic of Korea was used to reflect the site-specific seawater conditions. An algorithm for reverse osmosis in constant permeate mode was developed to simulate the process in time-variant conditions.

Theoretical Analysis of a Mathematical Relation between Driving Pressures in Membrane-Based Desalting Processes.

Osmotic and hydraulic pressures are both indispensable for operating membrane-based desalting processes, such as forward osmosis (FO), pressure-retarded osmosis (PRO), and reverse osmosis (RO). However, a clear relation between these driving pressures has not thus far been identified; hence, the effect of change in driving pressures on systems has not yet been sufficiently analyzed. In this context, this study formulates an actual mathematical relation between the driving pressures of membrane-based desalting processes by taking into consideration the presence of energy loss in each driving pressure.

The relative importance of water temperature and residence time in predicting cyanobacteria abundance in regulated rivers.

Despite a growing awareness of the problems associated with cyanobacterial blooms in rivers, and particularly in regulated rivers, the drivers of bloom formation and abundance in rivers are not well understood. We developed a Bayesian hierarchical model to assess the relative importance of predictors of summer cyanobacteria abundance, and to test whether the relative importance of each predictor varies by site, using monitoring data from 16 sites in the four major rivers of South Korea. The results suggested that temperature and residence time, but not nutrient levels, are important predictors of summer cyanobacteria abundance in rivers.

Modeling spatiotemporal bacterial variability with meteorological and watershed land-use characteristics.

Bacteria are a primary contaminant in natural surface water. The instream concentration of fecal coliform, a potential indicator of pathogens, is influenced by meteorological conditions and land-use characteristics. However, the relationships between these conditions and fecal coliforms are not fully understood.

Development of early-warning protocol for predicting chlorophyll-a concentration using machine learning models in freshwater and estuarine reservoirs, Korea.

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.

Developing a flow control strategy to reduce nutrient load in a reclaimed multi-reservoir system using a 2D hydrodynamic and water quality model.

Blocking the natural bi-directional flow in an estuarine system using an artificial dyke has commonly caused serious water quality problems. In the southwestern part of South Korea, a parallel triple-reservoir system was constructed by blocking the mouth of three different rivers (Yeongsan, Okcheon, and Kumja), which were then interconnected using two open channels. This system has experienced a deterioration in water quality due to pollutants accumulated from the upper watershed, and has continually discharged pollutant loads to the outer ocean.

Multi-level stressor analysis from the DNA/biochemical level to community levels in an urban stream and integrative health response (IHR) assessments.

The objectives of this study were to identify multi-level stressors at the DNA/biochemical level to the community level in fish in an urban stream and to develop an integrative health response (IHR) model for ecological health diagnosis. A pristine control site (S (c) ) and an impacted site (S (i) ) were selected from among seven pre-screened sites studied over seven years. Various chemical analyses indicated that nutrient enrichment (Nitrogen, Phosphorus) and organic pollution were significantly greater (t > 8.

The modified SWAT model for predicting fecal coliforms in the Wachusett Reservoir Watershed, USA.

This study assessed fecal coliform contamination in the Wachusett Reservoir Watershed in Massachusetts, USA using Soil and Water Assessment Tool (SWAT) because bacteria are one of the major water quality parameters of concern. The bacteria subroutine in SWAT, considering in-stream bacteria die-off only, was modified in this study to include solar radiation-associated die-off and the contribution of wildlife. The result of sensitivity analysis demonstrates that solar radiation is one of the most significant fate factors of fecal coliform.

Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network.

The arsenic (As) contamination of groundwater has increasingly been recognized as a major global issue of concern. As groundwater resources are one of most important freshwater sources for water supplies in Southeast Asian countries, it is important to investigate the spatial distribution of As contamination and evaluate the health risk of As for these countries. The detection of As contamination in groundwater resources, however, can create a substantial labor and cost burden for Southeast Asian countries.

Prevalence of season-specific Escherichia coli strains in the Yeongsan River Basin of South Korea.

Seasonal and spatial variation in the genotypic richness of 3480 Escherichia coli isolates obtained from the Yeongsan River basin in South Korea was investigated by using the horizontal fluorophore-enhanced rep-PCR (HFERP) DNA fingerprinting technique. The relationship between 60 E. coli isolates from each of 58 freshwater samples was determined by using multidimensional scaling (MDS) analysis and self-organized maps (SOMs).

Advancing assessment and design of stormwater monitoring programs using a self-organizing map: characterization of trace metal concentration profiles in stormwater runoff.

Stormwater runoff poses a great challenge to the scientific assessment of the effects of diffuse pollution sources on receiving waters. In this study, a self-organizing map (SOM), a research tool for analyzing specific patterns in a large array of data, was applied to the monitoring data obtained from a stormwater monitoring survey to acquire new insights into stream water quality profiles under different rainfall conditions. The components of the input data vectors used by the SOM included concentrations of 10 metal elements, river discharge, and rainfall amount which were collected at the inlet and endpoint of an urban segment of the Yeongsan River, Korea.

Factors dominating stratification cycle and seasonal water quality variation in a Korean estuarine reservoir.

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.

Evaluation of the relationship between two different methods for enumeration fecal indicator bacteria: colony-forming unit and most probable number.

Most probable number (MPN) and colony-forming unit (CFU) estimates of fecal indicator bacteria (FIB) concentration are common measures of water quality in aquatic environments. Thus, FIB intensively monitored in Yeongsan Watershed in an attempt to compare two different methods and to develop a statistical model to convert from CFU to MPN estimates or vice versa. As a result, the significant difference was found in the MPN and CFU estimates.

Use of barcoded pyrosequencing and shared OTUs to determine sources of fecal bacteria in watersheds.

While many current microbial source tracking (MST) methods rely on the use of specific molecular marker genes to identify sources of fecal contamination, these methods often fail to determine all point and nonpoint contributors of fecal inputs into waterways. In this study, we developed a new library-dependent MST method that uses pyrosequencing-derived shared operational taxonomy units (OTUs) to define sources of fecal contamination in waterways. A total 56,841 pyrosequencing reads of 16S rDNA obtained from the feces of humans and animals were evaluated and used to compare fecal microbial diversity in three freshwater samples obtained from the Yeongsan river basin in Jeonnam Province, South Korea.

Linking land-use type and stream water quality using spatial data of fecal indicator bacteria and heavy metals in the Yeongsan river basin.

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.

Spatial and temporal variability of fecal indicator bacteria in an urban stream under different meteorological regimes.

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.

High diversity and abundance of antibiotic-resistant Escherichia coli isolated from humans and farm animal hosts in Jeonnam Province, South Korea.

The spread of antibiotics resistance among bacteria is a threat to human health. Since South Korea uses approximately 1.5 times more antibiotics than do other OECD countries, this is likely to impact the numbers and types of antibiotic-resistant bacteria found in the environment.

Meteorological effects on the levels of fecal indicator bacteria in an urban stream: a modeling approach.

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.

Factors affecting metal exchange between sediment and water in an estuarine reservoir: a spatial and seasonal observation.

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.

Decadal and seasonal scale changes of an artificial lake environment after blocking tidal flows in the Yeongsan Estuary region, Korea.

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.

Absence of Escherichia coli phylogenetic group B2 strains in humans and domesticated animals from Jeonnam Province, Republic of Korea.

Multiplex PCR analyses of DNAs from genotypically unique Escherichia coli strains isolated from the feces of 138 humans and 376 domesticated animals from Jeonnam Province, South Korea, performed using primers specific for the chuA and yjaA genes and an unknown DNA fragment, TSPE4.C2, indicated that none of the strains belonged to E. coli phylogenetic group B2.

Effect of environmental flow management on river water quality: a case study at Yeongsan River, Korea.

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 (BOD(5)) 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.

Interpretation of seasonal water quality variation in the Yeongsan Reservoir, Korea using multivariate statistical analyses.

The Yeongsan (YS) Reservoir is an estuarine reservoir which provides surrounding areas with public goods, such as water supply for agricultural and industrial areas and flood control. Beneficial uses of the YS Reservoir, however, are recently threatened by enriched non-point and point source inputs. A series of multivariate statistical approaches including principal component analysis (PCA) were applied to extract significant characteristics contained in a large suite of water quality data (18 variables monthly recorded for 5 years); thereby to provide the important phenomenal information for establishing effective water resource management plans for the YS Reservoir.