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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. Although the two predictors were of similar significance across the sites, the residence time was marginally better in accounting for the variation in cyanobacteria abundance. The model with spatial hierarchy demonstrated that temperature played a consistently significant role at all sites, and showed no effect from site-specific factors. In contrast, the importance of residence time varied significantly from site to site. This variation was shown to depend on the trophic state, indicated by the chlorophyll-a and total phosphorus levels. Our results also suggested that the magnitude of weir inflow is a key factor determining the cyanobacteria abundance under baseline conditions.

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. Furthermore, the sources of large variability in fecal coliform counts, e.g., temporal or spatial sources, remain unexplained, especially at large scales. This study proposes the use of Bayesian overdispersed Poisson models, whereby the combined effects of temperature, rainfall, and land-use characteristics on fecal coliform concentration are quantified with predictive uncertainty, and the sources of variability in fecal coliform concentration are assessed. The models were developed using 8-year weekly observations of fecal coliforms obtained from the Wachusett Reservoir watershed in Massachusetts, USA. The results highlight the importance of interactions among meteorological and land-use characteristics in controlling the instream fecal coliform concentration; the increase in fecal coliform concentration with temperature increase was more drastic when rainfall occurred. Also, the responses of fecal coliforms to temperature increases were more pronounced in forest-dominated than in urban-dominated areas. In contrast, the fecal coliform concentration increased more rapidly with rainfall increases in urban-dominated than in forest-dominated areas. The models also demonstrate that among the sources of variability, the monthly component made the most significant contribution to the variability in fecal coliform concentrations. Our results suggest that seasonally dependent processes, including surface runoff, are critical factors that regulate fecal coliform concentration in streams.

Providing high-resolution monitoring data is essential in promoting decision-making activities for surface water quality protection such as scientific modeling and data analysis. In this study, statistical models using multiple linear regression (MLR) were developed to estimate Chlorophyll-a (Chl-a) and total suspended solid (TSS) concentrations in a mesotrophic reservoir, the Yeongam Reservoir in Korea, from satellite observations. Two types of satellite data that covered different spectral regions, for wavelengths in 412–865 nm (for the Geostationary Ocean Color Imager) and those in 405–14,385 nm (for the Moderate Resolution Imaging Spectroradiometer), were used as inputs for statistical models, after bias correction. The MLR models for Chl-a and TSS were initially constructed and evaluated with 39 image data-sets obtained during 2011–2014. Subsequently, they compared with their corresponding algorithms that were developed under different environmental settings as well as the CE-QUAL-W2 model, a...

Reverse osmosis (RO) desalination of 35,000 ppm seawater consisting of sodium and chlorine ions with water was simulated using molecular dynamics. In this study, RO simulations were performed at different pressures using carbon nanotube (CNT) membranes having varying pore diameters (8–14 A). Results showed that a CNT membrane allowed high water fluxes because of the presence of a low energy barrier for water–carbon interactions, with continuous and ordered water chains observed inside the CNTs. The investigations into the ion rejection capability of CNT membranes revealed that (6, 6) CNTs could provide high rejection rates (>95%). The rejection of ions was mainly due to the presence of a high energy barrier caused by removing the hydrating water molecules necessary for ions to pass through the narrow CNT pore. The desalination performance of (6, 6) CNT membranes and conventional polymeric membranes was then compared. It was found that CNT membranes have a higher normalized flux and comparable ion ...

Statistical models play an important role in elucidating the dynamic behaviors of surface water quality, given limited data on a large scale. In this study, we examine alternative approaches to develop regression models that predict fecal coliform (FC) concentrations in a river using different methods for selecting important variables provided by a self-organizing map (SOM). The raw data used as input to the SOM included 11 water quality, 6 meteorological, and 7 land use parameters that were monitored along the Yeongsan River in Korea on various time scales (from daily to half a decade) during 1996–2008. In both test and validation data sets, (multiple) regressions using backward elimination were compared against regression models via forced entry, which included a set of ranked variables simultaneously based on four indices in the SOM (i.e. structuring index, relative importance, cluster description, and Spearman’s rank correlation). Results showed that the SOM effectively illustrated the complex...

A transient model of seawater reverse osmosis (SWRO) system enables systematic assessment of membrane performance in response to changes in time-series parameters, operating conditions, or ancillary equipment. In this study, we describe the effects of energy recovery device (ERD) and feed pressure control on the SWRO plant in terms of energy consumption (reduced) and water quantity (increased) using a numerical model at pilot scale. In the simulation, two types of isobaric ERD, i.e. pressure exchanger (PX) and dual work exchanger energy recovery (DWEER), were used to quantify changes of the mass flow rates of inflow and outflow in the system. Also, temporal variation in the raw feedwater quality was addressed in the model with adaptive feed pressure control to maintain the amount of produced water under fouled membrane conditions. Results showed that the observed recovery and rejection rates in the pilot-scale plant had an excellent agreement with their predicted values under different seawater fe...

Groundwater contamination with arsenic (As) is one of the major issues in the world, especially for Southeast Asian (SEA) countries where groundwater is the major drinking water source, especially in rural areas. Unfortunately, quantification of groundwater As contamination is another burden for those countries because it requires sophisticated equipment, expensive analysis, and well-trained technicians. Here, we collected approximately 350 groundwater samples from three different SEA countries, including Cambodia, Lao PDR, and Thailand, in an attempt to quantify total As concentrations and conventional water quality variables. After that, two machine learning models (i.e. artificial neural network (ANN) and support vector machine (SVM)) were applied to predict groundwater As contamination using conventional water quality parameters. Prior to modeling approaches, the pattern search algorithm in MATLAB software was used to optimize the ANN and SVM model parameters, attempting to find the best param...

Pressure retarded osmosis (PRO) is a promising membrane-based process for producing clean and renewable energy. Since the major driving force is the salinity gradient between the feed and draw solutions, PRO can operate without a large environmental footprint. However, the performance of PRO can be severely limited by fouling, with organic fouling commonly deemed the main factor influencing PRO performance, since even a small amount of organic foulants can cause a significant flux decline. In spite of its importance, however, few studies have focused on PRO fouling. Therefore, the objectives of this study were to investigate the effect of hydraulic pressure as an influencing factor and to adjust the feed solution pH in order to alleviate fouling in the PRO process. Alginate was chosen as the model foulant due to its common existence in feed water. Based on our results, a higher hydraulic pressure caused an increase in the reverse solute flux, such that organic fouling became aggravated. In additio...

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 paper presents a desalination process powered by a microgrid. Desalination is critically important for many countries demanding potable water beyond that available in nature. The desalination process requires a stable power supply system. As the stable power supply system, microgrid, which is a distributed small capacity power system integrating renewable energy with energy storage, has become important. In this paper, small capacity desalination plant powered by a microgrid is implemented and its features are described. The desalination plant is operated by electricity provided from either renewable energy resource such as solar cell or power grid. Overall control of the desalination plant is carried out by a programmable logic controller and status of water production is monitored by energy management system. The implemented desalination plant consumes 5 kW and produces 1 m3/h of fresh water.

This paper describes the effects of weir construction on water quality in the Yeongsan (YS) River. In general, weirs affect aquatic environments of rivers and streams by interrupting natural water flow. To identify changes in water quality before and after weir construction, analysis of variance and autocorrelation tests were conducted on data from four monitoring stations. Seasonal variations in suspended solids (SS), biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and pH were analyzed using data from six years of monitoring. No significant changes in mean BOD5 or COD followed the construction of weirs. However, mean TN and TP were changed significantly during and after construction. Moreover, SS and pH changed significantly during construction, and TN and TP concentrations were slightly improved after weir construction. However, continuous monitoring and analysis of water quality changes in each weir are required to prevent environmenta...

This study introduces a schematic methodology for smart water grids (SWGs) for use in water management platforms, which integrates information and communication technology (ICT) into a single water management scheme. SWG technology is seen as a promising solution for resolving recent critical global water problems. To ensure the security of water quantity, safety of water quality, and ICT-based water management solutions, SWG technology should integrate five prime research areas: (1) platform configuration in both water and ICT networks, (2) guarantee water resources including both natural and manufactured water, (3) intelligent control of water flow using bi-directional communication in water infrastructure, (4) better management scheme dealing with risk-minimization for assets in the water infrastructure, and (5) energy efficiency in operating and maintaining water infrastructure. Two platforms (i.e. water and ICT platforms) are introduced as examples of well-designed platforms for the managemen...

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. Therefore, the objective of this study is to establish an effective dam operation plan for reducing nutrient loads released from the integrated reservoir. In this study, the CE-QUAL-W2 model, which is a 2-dimentional hydrodynamic and water quality model, was applied to predict the pollutant load released from each reservoir in response to different flow scenarios for the interconnecting channel. The model was calibrated using two novel methods: a sensitivity analysis to determine meaningful model parameters, and a pattern search to optimize the parameters. From the scenario analysis using flow control, it was determined that the total nitrogen (TN) and total phosphorus (TP) loadings could be reduced by 27.2% and 6.6%, respectively, under the optimal channel flow scenario by regulating the chlorophyll-a concentration in the reservoir. The results confirm that effective dam operation could contribute to a decrease in pollutant loads in the receiving seawater body. As such, this study suggests operational strategies for a multi-reservoir system that can be used to reduce the nutrient load being discharged from reservoirs.

In this study, unlike the previous researches, the pretreatment equipment composed of a 40- μm disk filter and a hollow fiber ultra-filtration (UF) membrane was constructed. The performances of the pretreatment facilities were analyzed on the basis of 5-week-long continuous experiments using sea water. The results confirmed that the newly constructed pretreatment equipment could be used for the pretreatment of sea water reverse osmosis as evidenced by silt density index15 values below two for a long period and measured turbidities of about 0.4 NTU. The membrane fouling could be removed by using chemical enhanced backwash. Trans-membrane pressure and the permeability could be returned to the initial conditions. It reveals that UF membrane performances of the pretreatment were dependent on the sea water conditions and operating conditions.

Nonpoint source (NPS) pollution is widely recognized as a major source affecting the water quality deterioration in rivers, lakes, and marine environments. Many studies about the relations between NPS pollutants and solid matters from drainage area have been carried out in the area of stormwater management. This study collected stormwater and soil samples from a drainage area in Korea; the particle size distributions (PSDs) were then analyzed during four storm events. The results indicate that the PSDs of fine and medium silt in the stormwater are related to the soil component of the drainage area. In addition, solid matter was strongly related to NPS pollutant discharges such as total nitrogen and total phosphorus during stormwater runoff. Therefore, to design an NPS management facility, the PSD from the drainage area should be considered. It is expected that this study can be applied to the designs of settling ponds used to remove particles from stormwater runoff.

Nonpoint source pollutions discharged with stormwater runoff during rainfall events degrade public waterbodies. Because combined sewer overflows (CSOs) especially affect public waterbodies, necessary measures must be taken for CSOs. Therefore, this study treated CSOs using the ultra-rapid coagulation (URC) process. More than 50% of the study site was comprised of an industrial area, followed by forest, farmland and residential areas at 21.3, 2.6, and 23.5%, respectively. The 30,000 ton capacity URC process was used to treat CSOs generated from the catchment. Monitoring was conducted over 8 rainfall events, and the samples were analyzed for pollutant parameters such as total suspended solids (TSS), biochemical oxygen demand (BOD), chemical oxygen demand (CODcr), total nitrogen (TN), total phosphorus (TP), and heavy metals. At the beginning of the rainfall, the first flash effect was observed, but was not observed 20 min later. The concentration of TSS and BOD increased as the rainfall intensity be...

Finding a suitable osmostically active solute is the most important problem in forward osmosis (FO). Even though there are a number of osmotically active compounds that exist, the major problem occurs during the separation of product water from the solute. Osmotically active macromolecules (polyethylene glycol [PEG] and humic acid [HA]) were investigated in this research as possible draw solutes for FO. Cellulose triacetate FO membranes (Hydration Technology Innovations, LLC) and several ultrafiltration and nanofiltration membranes were used in osmosis and filtration steps of the system, respectively. Molecular weights (MW) of PEG were selected as 2 k, 10 k, and 20 kDa for 400 and 600 g/L concentrations. HA solutions were prepared in concentrations ranging from 200 to 800 g/L. Increased MW resulted in higher water permeation when PEGs were used. The relationship between the reflection coefficient and the viscosity was investigated for PEG/water separation by membrane filtration. The combined effe...

The fouling behavior of seawater reverse osmosis membranes has yet to be definitively investigated due to the complexity of seawater compositions. In this study, a time-series image analysis (TSIA) was performed to investigate the fouling mechanism using scanning electron microscopy (SEM) and atomic force microscopy (AFM). The fouling experiments were conducted with synthetic seawater (SS) and SS mixed with humic acid substances (SHA). The effect of operational time was investigated for 2, 4, 6, 8, 12, and 20 h. According to the TSIA results, different fouling characteristics between SS and SHA experiments were observed. In the SS case, the fouling mechanism is the interaction between inorganic particles and the membrane surface as well as interaction between inorganic particles and the deposited foulants. Then, increased accumulation of deposited foulants was observed with respect to the operational time. However, in the presence of humic acid, the fouling mechanism was significantly influenced ...

The development and exploitation of sustainable and environment-friendly energy resources are required in order to resolve global energy shortages. Recently, salinity gradient power (SGP) has been considered a feasible candidate, with high potential to become a substitute for the current use of fossil fuels due to benefits such as less periodicity, abundance and no emission of carbon dioxide. In this paper, one SGP, pressure-retarded osmosis (PRO) system, was reviewed in terms of its mechanism, limitations and available applications. In the PRO system, water permeates through a semipermeable membrane from the feed solution to the draw solution, and energy is generated by depressurizing the permeated flow through a hydro turbine. Models for understanding its mechanism and for improving of its performance were reviewed. In addition, applications of sea water reverse osmosis (SWRO), wastewater treatment (WWT) and PRO hybrid process were introduced in order to develop new water-energy nexus processes...

A lab-scale vortex separator, based on a swirling motion to remove settleable particles, was used to remove suspended solids in urban stormwater runoff. However, the treatment is limited to the removal of large settleable particles. The synthesized stormwater runoff was made with tap water and the addition of road sediment. The vortex separator has internal components designed to enhance vortex separation by minimizing the turbulence, increasing the efficiency, and preventing captured pollutants from washout. As the flow continues to spiral down around the inlet baffle, a low energy vortex motion directs settleable particles into the protected sediment storage zone. Advanced vortex separation provided an extendable and stabilized flow path while protecting the captured pollutants for a wide range of flow rates. The range of the inflow rate was 30–115 l/m, and the size of the influent particles varied from 75 to 200 μm. Overall removal efficiencies of 51.8% for SS, 26.6% for COD, 70.5% for TP, and...

Membrane filtration is lately becoming a popular process for the pre-treatment of seawater in reverse osmosis (SWRO) desalination. The common practiced method of controlling membrane fouling and reducing the treatment costs usually involves a short coagulation step prior to the membrane filtration. In this work, a study of the feasibility of a coagulation free microfiltration (MF) as pre-treatment for SWRO desalination from a technical, economical and environmental point of view was performed. The experimental part included filtration of seawater from the Yellow Sea in Korea both with and without granular activated carbon (GAC) pre-treatment using a laboratory scale MF plant and different constant fluxes in outside-in dead-end mode. The results show that a coagulant and GAC free, stand-alone microfi ltration using low fluxes and intense chemical cleanings is technically possible. When compared to a state of the art coagulation-MF, such a process could be economically and environmentally favourabl...

To manage and control the nonpoint source (NPS) pollution and to improve the water quality of impaired streams, rivers and lakes, practices including constructed wetlands, permeable pavement, swales and others are being attempted in the world. Before applying these techniques, an analysis of stormwater runoff characteristics should be understood due to the complexity in estimating system design factors for best management practices (BMPs). This study investigates the stormwater discharge from an agricultural area in Korea. Based on this investigation, pollutant and flow coefficient of variation (PFCoV) values were developed in an attempt to explain the stormwater runoff in the agricultural area. Four field studies categorized by rainfall type were then employed to assess the PFCoV values. The results show that the physical meaning of PFCoV values indicates the variation of NPS pollutants during a storm event. As such, this simple and meaningful result can be applied to a wide range of stormwater ...

A four-year monitoring study was conducted to determine the diffuse pollutant unit loads for the six representative transportation landuses (i.e., highway, parking lot, bridge, service area and toll gate) in urban areas in Korea. Pollutant event mean concentrations (EMCs) were calculated from 123 storm events at eleven sites and the average annual rainfall and runoff coefficients were determined to estimate the unit loads using the National Institute of Environmental Research (NIER) method. Apparent differences in the unit load values existed among landuses as explained by the high variability of EMCs for different rainfall events. The study has found that runoff from bridges and highways contained the highest loadings of TSS and COD while service areas are the primary sources of nutrients and metals. The results of this study could be used by the Ministry of Environment (MOE) to separate the unit loads of transportation landuses from the urban area category in the current unit load system. The v...

Different numerical schemes for the fate and transport models of fecal indicator bacteria (FIB) were used to predict the concentration of FIB in a creek, which were then compared to a steady state model (QUAL2E). Escherichia coli (EC) and enterococci bacteria (ENT) were selected as representative FIB to compare the model performance under different flow and weather conditions in the Gwangju Creek in Korea. The results revealed that model accuracy of the forward time centered space (FTCS) scheme is the highest compared to the upstream, Dufort-Frankel, Crank-Nicolson methods and steady state model (QUAL2E) under dry weather conditions. In wet weather conditions, however, the upstream scheme shows the best performance among the five models. The upstream scheme thus represented a potential method for predicting the fate and transport of FIB originating from nonpoint sources during the rainy season. This study demonstrates that prediction results could vary in response to different numerical schemes a...

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. In this study we examined feces from domesticated animals and humans for the diversity and abundance of antibiotic-resistant Escherichia coli. Abundant antibiotic-resistant E. coli were isolated from all the tested animals and humans and were examined by horizontal, fluorophore-enhanced, rep-PCR (HFERP) DNA fingerprint analysis. A total of 793 unique, non-clonal, E. coli isolates were obtained from the 513 human and animal hosts examined. Antibiotic resistance analysis, done using 14 antibiotics, indicated that 72.3% of the isolates (573 of 793) were found resistant to more than one antibiotic. The E. coli isolated from swine were resistant to the greatest number of antibiotics. Tetracycline resistant E. coli were routinely isolated from all animal hosts (36 to 77% per host), except for dairy cattle (9.3%). Twenty nine E. coli isolates from all hosts, except for duck, were resistant to more than 10 antibiotics. Gene transfer and southern hybridization studies revealed that resistance to 13 of the antibiotics was self-transmissible, and likely mediated by plasmids and integrons. Since genetically diverse and numerically abundant antibiotic-resistant E. coli were consistently recovered from chicken, swine and other domesticated animals in South Korea, our results suggest that the use of sub-therapeutic levels of antibiotics for disease prophylaxis and growth promotion should be curtailed.

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.

Scale formation of soluble salts is one of the major factors limiting the performance of reverse osmosis (RO) membranes for desalination. However, it is difficult to predict membrane fouling due to scale formation in a complicated feed water containing dissolved organics such as humic substances. This study aims at prediction of the complicated fouling phenomenon by scale formation in the presence of dissolved organic matters. Experimental studies with model solutions were conducted in a small batch filtration device. Humic acid and calcium sulfate were used as model dissolved organic matters and scale-forming salts. A genetic programming technique was applied to predict the effect of dissolved organic matters on scale formation.

Seawater reverse osmosis (SWRO) desalination is considered one of the most promising technologies for supplying freshwater to the regions suffering from water scarcity. Although a considerable amount of research has been conducted in attempts to improve SWRO desalination technology, reducing the cost of producing freshwater is still required. In Korea, this effort is already been being carried out by the Seawater Engineering & Architecture of High Efficiency Reverse Osmosis (SeaHERO) project. Core Technology 2 (CT2), one of the most important sub-projects out of four CTs under SeaHERO, pursues two main goals: optimization of processes for low energy consumption/high efficiency and localization of core parts/equipments of the SWRO plant. Four unit technologies (UTs) are then incorporated into CT2 and each UT has its own technical target; UT1 focuses on the development of SWRO desalination system integration and optimization technology in terms of energy saving; UT2 and 3 work to develop high performance RO...

Forward osmosis (FO) is a membrane-based desalination technique using an osmotic pressure gradient as a driving force. FO enables lower energy consumption to produce water than reverse osmosis (RO) because it does not require high transmembrane pressure. However, FO needs to be combined with other processes such as RO or evaporation because the draw salts in the FO products should be removed. This paper focused on theoretical investigation of combined systems with FO and RO for seawater desalination. A theoretical model to predict the performance of the combined systems was developed based on the solution—diffusion model and the modified film theory. The effect of internal concentration polarization on FO efficiency was also considered in the model. A pilot-scale system of FO and RO was assumed for model calculations. Results showed that the combinations of FO with seawater reverse osmosis (SWRO) have potential for desalination with high recovery (up to 80%). It was also found that FO may be incorporated ...

In the present study, the feasibility of a tri-hybrid desalination system for the production of electricity, energy for heating and cooling and water was studied. The tri-hybrid desalination system is a combination of a cogeneration and a desalination system. The system is composed of a generator driven by a gas engine, a gas boiler, a turbo-refrigerator, an absorption refrigerator for cogeneration, and an RO and an MED for the desalination system. The excess heat was calculated based on the electrical, heating and cooling load data and assumed that would be used for the production of water. The quantitative analysis of the product water and the energy consumption rate was compared on a month-by-month basis, and the feasibility of the tri-hybrid desalination system is explained.

The model of salt transport through the membrane in multi-component system was developed with the irreversible thermodynamics theory considering the effect of the interaction between the salt ions. With the proposed transport model, the model for spiral-wound module was built based on the mass conservation law and concentration polarization derived by film theory. Through the parameter estimation, the frictional coefficients related to permeability of water and each ion was determined and then phenomenological analysis was conducted. The simulation results show that the salt rejection is increasing as the applied pressure and feed flow rate increasing. Also, the predictions by present model are in good agreement with the experimental data in the literature.

To date, over 80 papers on transport modeling and natural organic matter (NOM) relating to seawater reverse osmosis (SWRO), have been reviewed. As a result of such focus, NOM, one of the main foulants related to reverse osmosis (RO) membranes, has been shown to possess intrinsic chemical complexities and ambiguities, necessitating further investigation. Consequently, since such NOM fouling and transport mechanisms associated with SWRO are not fully understood, a summation of previous studies has been included in the paper in question to systematize information, not only as to RO membrane transport modeling, but NOM fouling characteristics, as well. Accordingly, RO transport models in the review are classified into three categories: diffusion-based, pore, and irreversible thermodynamic models. In addition, specific features, unique assumptions, and applications for each model are examined. The paper consists of the following components towards meaningful understanding of NOM fouling model development durin...

A seawater reverse osmosis (SWRO) desalination process has become an alternative technology to solve water shortage problem in the world. Although SWRO is an advanced and useful technology for humanity, there is still unsettled cost effective issue. Therefore, the estimation of operation and maintenance (O&M) costs should be significantly considered before a new construction of SWRO desalination plant. The objective of this feasibility study is to estimate total annual profits (TAP) according to O&M for a new construction of SWRO desalination plant at 9 candidate sites along the shoreline in Korea. The cost estimation model was developed and validated with Fujairah SWRO plant operation data in 2005. As a result, TAPs for the 9 candidate sites were estimated and compared with that of Fujairah SWRO plant. The result reflects that the cost estimation model in this study is able to propose a reasonable range of TAP for a new construction project of SWRO desalination plant in Korea.

The successful operation of a seawater reverse osmosis desalination plant depends greatly on the performance of the pretreatment step. The start-up of a pretreatment filtration process usually begins with a dynamic part called ripening, during which the filter media increases its adsorption ability and improves the removal of foulants from the seawater. In that period (typically lasting 30–60 min, depending on the system's conditions) the effluent often does not meet the quality requirements of the RO membranes and must often be disposed of. An observation and analysis of the ripening phenomena was performed using lab scale acrylic filter columns containing granular activated carbon. The seawater originated from the Yellow Sea in Korea and an inline coagulation was performed prior to filtration using an optimal dose of FeCl3 based on a jar test. The turbidity, total suspended solids concentration and dissolved organic carbon were measured before and after filtration with the goal of assessing the filtrati...

Recovery and salt rejection rate, which are directly related to the membrane properties and operating conditions (i.e., feed flow rate, pressure, temperature, and TDS concentration), are two main indicators for evaluating the performance of a reverse osmosis (RO) membrane process. A simple and rapid test with minimum data is inevitably requested to diagnose membrane performance at a certain operating conditions, because experiments at all operating conditions are inefficient and consumable work in the view of cost as well as man-hour. In this study, permeate flow rate and TDS concentration of three kinds of commercial RO membranes were carefully examined under various operating conditions [i.e., feed pressure (45–65 kgf/cm2) and temperature (5–30°C)]. Based on the experimental data, membrane resistance models including temperature and pressure correction factors were developed for the rapid diagnosis of SWRO membrane performances. As a result, the models developed in this study have good agreements betwee...

Reverse osmosis (RO) membranes have high rejection for most of solutes in seawater except for boron. Therefore, boron rejection should be considered in the design and operation of the RO process for seawater desalination. In this paper, we investigated boron rejection and its relation to salt rejection using an irreversible thermodynamic model. Permeability constants for commercially-available RO membranes were obtained using theoretical model and the simulation data from membrane performance test program provided by membrane manufacturers. The effect of pH and concentration of the feed water on the boron rejection was also theoretically investigated under various operating conditions. The model calculations revealed that the rejection of boron follows a different mechanism from those of other ionic solutes and could not be readily correlated with ion rejections. To overcome the limit of mechanistic models, we explored an alternative approach for predicting boron permeability from membrane properties and ion permeability. It appears that this alternative approach can aid to achieve a better understanding of boron rejection by seawater RO membranes.

Desalination offers one of the reasonable alternatives as a solution to water scarcity. Among the desalination technologies, seawater reverse osmosis (SWRO) process becomes increasingly attractive for freshwater supply with comparatively low energy consumption and cost-effective operation. In this study, a benchmark of operating Fujairah SWRO desalination plant in the United Arab Emirates is applied to assess the relative performance of a new and large plant construction in other sites. A process model was developed to simulate the performance of SWRO desalination process and to estimate its operating cost. The developed model was validated using one-year SWRO operation data obtained from Fujairah SWRO desalination plant. Temperature and salinity data were collected from World Ocean Atlas 2005, and then applied to the model to estimate the operating cost under the site-specific conditions of 9 different countries. The results of this study present that the performance of the SWRO desalination process was significantly influenced by feed water concentration (i.e., mainly salinity) and temperature, and that the total operating cost is significantly dependent of the local electricity costs. As a conclusion, World Ocean Atlas data and the benchmark provide a method of comparing the performance of various SWRO desalination systems among different countries. Furthermore the methodology is applicable to simulate the process model with site-specific water quality data and to estimate the operating cost before a new construction of SWRO desalination plant at a target area elsewhere.

At the time being there are several technological designs of membrane-based seawater reverse osmosis (SWRO) pretreatment systems on the desalination market. The abundance of different membrane materials and configurations (pressurized/submerged/inside-out/outside-in etc.) combined with site specific conditions make the unbiased assessment of their general performance a difficult task. In this paper we suggest a data mining method based on the principal component analysis (PCA) to serve as a more systematically logical regression tool on currently available literature data. PCA is a multivariate statistical method that uses a linear transformation for dimension reduction and pattern recognition. The results show how this method can be used effectively in the case of SWRO membrane based pretreatment for both literature data reconciliation and reconstruction, as well as for future data prediction.

This study focused on the analysis of As levels in human hair samples collected from six villages in the Kandal Province of Cambodia. Of interest were the influence of, and interactions among, certain factors affecting As intake into the human body: As concentrations in groundwater, period of groundwater consumption, age and gender. The results revealed As levels in human hair ranging from 0.06 to 30 μg g −1 with median and arithmetic mean values of 0.61 and 3.20 μg g −1 ( n = 68), respectively. Furthermore, a linear relationship was found between As concentrations in human hair and in the local groundwater. Arsenic (III) is the dominant species in Kandal groundwater, constituting in most cases at least 60% of the total As. Arsenic concentration ranged from 5 to 1543 μg L −1 , with the median value 348 μg L −1 and arithmetic mean 454 μg L −1 . In large rural, poor areas holding most of Kandal’s 1.1 million people, up to 2 in 1000 people are believed to be at risk of cancer through the As-enriched water they drink. A toxicity risk assessment provides a hazard quotient (HQ) equaling 5.12, also a clear indication of non-carcinogenic exposure risk. On the authors’ visit to Kampong Kong commune, Kandal Province, cases of arsenicosis were diagnosed in patients as a result of drinking As-enriched groundwater.

Statistical regression models involve linear equations, which often lead to significant prediction errors due to poor statistical stability and accuracy. This concern arises from multicollinearity in the models, which may drastically affect model performance in terms of a trade-off scenario for effective water resource management logistics. In this paper, we propose a new methodology for improving the statistical stability and accuracy of regression models, and then show how to cope with pitfalls in the models and determine optimal parameters with a decreased number of predictive variables. Here, a comparison of the predictive performance was made using four types of multiple linear regression (MLR) and principal component regression (PCR) models in the prediction of chlorophyll-a (chl-a) concentration in the Yeongsan (YS) Reservoir, Korea, an estuarine reservoir that historically suffers from high levels of nutrient input. During a 3-year water quality monitoring period, results showed that PCRs could be a compact solution for improving the accuracy of the models, as in each case MLR could not accurately produce reliable predictions due to a persistent collinearity problem. Furthermore, based on R2 (goodness of fit) and F-overall number (confidence of regression), and the number of explanatory variables (R-F-N) curve, it was revealed that PCR-F(7) was the best model among the four regression models in predicting chl-a, having the fewest explanatory variables (seven) and the lowest uncertainty. Seven PCs were identified as significant variables, related to eight water quality parameters: pH, 5-day biochemical oxygen demand, total coliform, fecal indicator bacteria, chemical oxygen demand, ammonia–nitrogen, total nitrogen, and dissolved oxygen. Overall, the results not only demonstrated that the models employed successfully simulated chl-a in a reservoir in both the test and validation periods, but also suggested that the optimal parameters should cautiously be considered in the design of regression models.

Spatio-temporal variations of biochemical oxygen demand (BOD) and total coliform (TC) in the Han River, Korea, were investigated in terms of concentration- based and mass loading-based approaches. Considering the river water quality criteria regulated by the Ministry of Environment in Korea, the tributaries linked to the main- stream of the Han River were found to be highly contaminated with respect to both BOD and TC and, in fact, most of the tributaries exceeded the maximum water quality criteria. To evaluate the pollution impact of tribu- taries on the mainstream, the monthly water quality monitoring data for six years (from 1995 to 2000) were collected from the Han River basin, and statistically ana- lyzed using Pearson's correlation coefficient. The results revealed that mass loading-based approach was superior to the concentration-based approach for effective Han River watershed management. Overall results supported that the mass loading-based approach associated with total maxi- mum daily loads (TMDL) management would be a useful and suitable protocol in watershed management for improving the water quality of the Han River and pro- tecting public health. Therefore, this study supporting TMDL management can be applicable to a wide array of contaminants and watershed settings in Korea.

The coastal waters at many beaches in California and the United States are afflicted with fecal pollution, which poses a health risk for people exposed to the water through recreational activities such as swimming, surfing, and diving. Identifying sources of pollution is complicated by oceanographic transport/mixing processes and the nonconservative behavior of microorganisms exposed to sunlight and hostile marine conditions. This article investigates the variation of fecal indicator bacteria (FIB) concentrations in the surf zone and the adjacent coastal marsh by applying autocorrelation and cross-correlation analyses that illustrate solar and tidal modulations. A steady state bioreactor model was developed to explain solar inactivation in the surf zone, whereas a dynamic model was applied to explain tidally influenced disturbances in the coastal marsh. These models applied to intensive monitoring datasets on FIB and environmental variables have provided insights into the biologic and physical processes controlling coastal water quality, specifically the influence of sunlight and tides on bacterial levels.

To characterize fluorescent dissolved organic matter (FDOM) in Yeongsan River in Korea, 110 water samples were acquired from March 2008 to November 2009 around the watershed. Excitation emission matrix data of fluorescence was obtained using spectrophotometric analysis and parallel factor (PARAFAC) model was used to characterize FDOM. The spatiotemporal variation and effect on FDOM were studied using an exploratory analysis and analysis of variance (ANOVA). According to the spatial and seasonal characteristics, we used post hoc analysis to identify significantly different sites and season. The PARAFAC results identified three most important PARAFAC components explaining 95.32% of total variance of original data-set. Seasons and sites had a significant effect on PARAFAC Components I and II (p ≤ 0.05), whereas season had a significant effect on Component III (p ≤ 0.05). There was no significant interaction between seasons and sites for all the three PARAFAC components (p > 0.05). For Components I and II, summer season was significantly different from other seasons (p ≤ 0.05), whereas for Component III, the fall season was significantly different from winter and summer seasons (p ≤ 0.05). These results indicate that ANOVA and post hoc analysis in our study not only confirmed the results of previous studies, but also revealed differences in seasons and sites for identified FDOMs as a new information. The methodology proposed in this paper can be a useful tool for finding sources and sinks of FDOMs in a riverine system influenced by natural organic matter impairment.

The surf zone is the unique environment where ocean meets land and a place of critical ecological, economic, and recreational importance. In the United States, this natural resource is increasingly off-limits to the public due to elevated concentrations of fecal indicator bacteria and other contaminants, the sources of which are often unknown. In this paper, we describe an approach for calculating mass budgets of pollutants in the surf zone from shoreline monitoring data. The analysis reveals that fecal indicator bacteria pollution in the surf zone at several contiguous beaches in Orange County, California, originates from well-defined locations along the shore, including the tidal outlets of the Santa Ana River and Talbert Marsh. Fecal pollution flows into the ocean from the Santa Ana River and Talbert Marsh outlets during ebb tides and from there is transported parallel to the shoreline by wave-driven surf zone currents and/or offshore tidal currents, frequently contaminating >5 km of the surf zone. The methodology developed here for locating and quantifying sources of surf zone pollution should be applicable to a wide array of contaminants and coastal settings.

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. A water temperature-associated function to represent the contribution of beaver activity in the watershed to fecal contamination improved prediction accuracy. The modified SWAT model provides an improved estimate of bacteria from the watershed. Our approach will be useful for simulating bacterial concentrations to provide predictive and reliable information of fecal contamination thus facilitating the implementation of effective watershed management.

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. Therefore, modeling approaches for As concentration using conventional on-site measurement data can be an alternative to quantify the As contamination. The objective of this study is to evaluate the predictive performance of four different models; specifically, multiple linear regression (MLR), principal component regression (PCR), artificial neural network (ANN), and the combination of principal components and an artificial neural network (PC-ANN) in the prediction of As concentration, and to provide assessment tools for Southeast Asian countries including Cambodia, Laos, and Thailand. The modeling results show that the prediction accuracy of PC-ANN (Nash–Sutcliffe model efficiency coefficients: 0.98 (traning step) and 0.71 (validation step)) is superior among the four different models. This finding can be explained by the fact that the PC-ANN not only solves the problem of collinearity of input variables, but also reflects the presence of high variability in observed As concentrations. We expect that the model developed in this work can be used to predict As concentrations using conventional water quality data obtained from on-site measurements, and can further provide reliable and predictive information for public health management policies.

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. From the study, it was found that the SOM displayed significant variability in trace metal concentrations for different monitoring sites and rainfall events, with a greater impact of stormwater runoff on stream water quality at the upstream site than at the downstream site, except under low rainfall conditions (≤ 4 mm). In addition, the SOM clearly determined the water quality characteristics for "non-storm" and "storm" data, where the parameters nickel and arsenic and the parameters chromium, cadmium, and lead played an important role in reflecting the spatial and temporal water quality, respectively. When the SOM was used to examine the efficacy of stormwater quality monitoring programs, between 34 and 64% of the sample size in the current data set was shown to be sufficient for estimating the stormwater pollutant loads. The observed errors were small, generally being below 10, 6, and 20% for load estimation, map resolution, and clustering accuracy, respectively. Thus, the method recommended may be used to minimize monitoring costs if both the efficiency and accuracy are further determined by examining a large existing data set.