Han River Watershed Research Articles

A Study on Distribution of Characteristics of Microplastic in the Han-River Watershed

Microplastic pollution in the marine environment is a global issue. Recently, in South Korea, there has been active research on the establishment of testing methods and investigation of distribution characteristics of microplastics not only in marine environments but also in freshwater systems. In particular, it is necessary to study the distribution of microplastics such as rivers and lakes, which are drinking water sources, to affect the water quality environment, management, and countermeasures. This study identified the distribution of microplastics in the mainstream and tributary of the Han River water system. The freshwater, sediment, and biological species samples were pre-treated accordingly, and microplastics larger than 20 µm were analyzed using μ-FT-IR. As a result of the inter-laboratory study, in the same way as in this study, it was possible to confirm that the trusted recovery rate was 63.6%. The survey results indicated that the number of microplastics per location ranged from 1,173 to 8,940 particles/L in freshwater samples, 3,800 to 192,000 particles/kg in sediment samples, and 34 to 384 particles/individual in fish samples. The most commonly found microplastic materials were PP, PE, and PTFE. The size distribution of plastics appeared in the following order: 45~100 µm, 100~300 µm, 20~45 µm, and greater than 300 µm, with predominantly fragmented shapes observed.

A novel approach to a multi-model ensemble for climate change models: Perspectives on the representation of natural variability and historical and future climate

This study developed a novel approach that integrated climate model selection and multi-model ensemble (MME) construction to effectively represent model uncertainties and, consequently, improve consistency in the evaluation of changes to extreme rainfall in different scenarios. Our focus was to combine 10 regional climate model (RCM) simulations, forced by two global climate models (GCM), especially for estimation of design rainfall in a changing climate. We hypothesized that the natural variability and statistically higher moment attributes in the extreme rainfall simulations from RCMs were not fully preserved. Therefore, the MME approach could be more effective in climate change studies, largely due to the use of multiple climate models. First, an experimental study was proposed to validate the efficacy of the proposed modeling framework approach adopting L-moments to quantify relative importance among climate models and their use for representing natural variability in the MME construction. The proposed approach was then applied to climate change scenarios collected from multiple RCMs for the Han-River watershed during both historical (1981–2005) and future (2006–2 100) periods. The results showed that the climate model selection informed by natural variability demonstrated better performance, representing nearly identical distribution to the observed annual maximum rainfall (AMR) in the Han River watershed. The range of the selected scenario was relatively narrower than that of all the scenarios, and the change rate was more consistent with the limited zero crossing, reflecting improvement in both model performance and consistency over historical and future periods, respectively. The change rate of the MME under RCP8.5 appeared to be an approximately 20% increase for the near (2011–2040) and far (2071–2 100) future, and the degree of increase in the rate for the mid-future (2041–2070) was slightly lower than that for the other periods, with increase of approximately 10%.

Identifying sources of acid mine drainage and major hydrogeochemical processes in abandoned mine adits (Southeast Shaanxi, China).

Acid mine drainage (AMD) has resulted in significant risks to both human health and the environment of the Han River watershed. In this study, water and sediment samples from typical mine adits were selected to investigate the hydrogeochemical characteristics and assess the environmental impacts of AMD. The interactions between coexisting chemical factors, geochemical processes in the mine adit, and the causes of AMD formation are discussed based on statistical analysis, mineralogical analysis, and geochemical modeling. The results showed that the hydrochemical types of AMD consisted of SO4-Ca-Mg, SO4-Ca, and SO4-Mg, with low pH and extremely high concentrations of Fe and SO42-. The release behaviors of most heavy metals are controlled by the oxidation of sulfide minerals (mainly pyrite) and the dissolution/precipitation of secondary minerals. Along the AMD pathway in the adit, the species of Fe-hydroxy secondary minerals tend to initially increase and later decrease. The inverse model results indicated that (1) oxidative dissolution of sulfide minerals, (2) interconversion of Fe-hydroxy secondary minerals, (3) precipitation of gypsum, and (4) neutralization by calcite are the main geochemical reactions in the adit, and chlorite might be the major neutralizing mineral of AMD with calcite. Furthermore, there were two sources of AMD in abandoned mine adits: oxidation of pyrite within the adits and infiltration of AMD from the overlying waste rock dumps. The findings can provide deeper insight into hydrogeochemical processes and the formation of AMD contamination produced in abandoned mine adits under similar mining and hydrogeological conditions.

A Study on Paldang Reservoir Water Quality Improvement Effect by Pollutant Source Location Regulation Using Watershed-Reservoir Integrated Prediction

Objectives:Since the enactment of the 「Han-River Watershed Act」, comprehensive analysis about direct and indirect contributions and effects of various environmental policies and water quality improvement projects for the preservation of water quality in the Han-River watershed is insufficient. Especially, effect of pollutant source location regulation should be inferred and estimated through model prediction because it does not exist unregulated conditions. As development pressure in non-urban areas near the metropolitan area is increasing, it is necessary to analyze the effects of pollutant source location regulation.Methods:In this study, average pollutant density of Gangwon-do, Gyeonggi-do, and Chungcheongbuk-do, where the regulation areas located, and average pollutant density of water source management areas were compared and analyzed. After that changes in pollutant sources in regulation areas were estimated by assuming load of pollutant sources in unregulated areas that load of pollutant sources in regulation areas. Since many reservoirs are located in Han-river watershed, it is difficult to simulate the water quality of Paldang reservoir using only watershed model, BASINS/WinHSPF and EFDC-WASP were linked. Through this, change in water quality of Paldang Lake was tried to predict when the pollutant location regulation was not implemented, and to analyze the effect of the pollutant location regulation.Results and Discussion:Water quality improvement of Paldang reservoir was evaluated by applying the discharge load when the pollution source location regulation was not implemented to the calibrated model. As a result of the pollution source location regulation, discharge load in the location regulation area was analyzed to reduce by 53.90% and T-P by 48.58%, and the BOD and T-P improvement effect of Paldang Dam was analyzed 6.77% and T-P 6.62%. Since the water quality improvement effect of Paldang Lake is accumulated to the entire upstream, it is evaluated relatively less than pollutant load reducing effect.Conclusion:It was analyzed that pollutiont source location regulation has water quality improvement effect, despite the small area which only located in near Paldang reservoir compared to the total area of the Han-River watershed.

Water Quality, Source Identification, and Risk Assessment of Heavy Metals Using Multivariate Analysis in the Han River Watershed, South Korea

This study aimed to investigate the irrigation water quality, major pollution sources, and human health hazards by focusing on heavy metal concentrations in the surface water of the Han River watershed, South Korea that supplies water for consumption and irrigation. Here, Mn was found to have the highest mean concentration, with the maximum concentration recorded at IH-2. The heavy metal concentrations were higher during summer and fall than that during spring. The mean concentration of heavy metals was relatively high in the downtown area (1.8 times) and downstream of the wastewater treatment facilities (1.3 times), indicating that the wastewater treatment facilities (WTFs) may be the primary source of pollution. Water at most of the sites were found to be suitable for irrigation. However, the sodium absorption ratio and soluble sodium percentage indicated that IH-2 was unsuitable. The results of the principal component analysis indicated that anthropogenic (vehicle and industrial) activities were the primary sources of metal pollution. Ingestion was identified as the primary exposure pathway in terms of health risks. However, the hazard quotients and hazard index for all pathways were below the safety limit (<1) for children and adults.

Distribution of Heavy Metals and Organic Compounds: Contamination and Associated Risk Assessment in the Han River Watershed, South Korea

Given water pollution increases in aquatic ecosystems resulting from industrialization and rapid urbanization, appropriate treatment strategies to alleviate water pollution are crucial. The spatiotemporal distribution, sources, and potential risk of heavy metals and organic compounds were determined in surface water from the Han River watershed (n = 100) in wet and dry seasons. The inductively coupled plasma mass spectrometer (Cr and As), mercury analyzer (Hg), and ultra-high performance liquid chromatography tandem mass spectrometer (organic compounds) were used to analyze the target compounds. Total concentration and detection frequency were in the order: Cr (2.375 µg/L, 100%) > As (1.339 µg/L, 100%) > Hg (0.007 µg/L, 100%) for heavy metals, and carbofuran (0.051 µg/L, 75%) > bisphenol A (0.040 µg/L, 47%) > quinoline (0.020 µg/L, 32%) for organic compounds. The target compounds showed the highest concentration in the area near industrial facilities. High concentrations and risk levels of all target compounds, except quinoline, were observed during the wet season. Principal component analysis indicated anthropogenic activities were the primary source of pollution. Cr showed the most prominent environmental impact in the wet season, suggesting its ecological risk. Additional monitoring is required for clear risk pollutant assessments in aquatic ecosystems to aid policy implementation.

Characteristics, Possible Origins, and Health Risk Assessment of Trace Elements in Surface Waters of the Han River Watershed, South Korea.

To safeguard aquatic environments in and around the Han River watershed in South Korea, a multivariate statistical evaluation of trace elements, a trace element concentration analysis and source determination, and a human health risk assessment were conducted on 10 trace elements at 25 sites. The results demonstrated that the Han River watershed was mainly affected by anthropogenic activities (traffic/industrial activity). The range of concentrations was arranged in descending order: Fe (217.13 ± 301.03 µg/L) > Mn (102.36 ± 153.04 µg/L) > Zn (23.33 ± 79.63 µg/L) > Ba (29.05 ± 12.37 µg/L) > Ni (5.14 ± 11.57 µg/L) > Cu (3.80 ± 3.56 µg/L) > Pb (0.46 ± 0.52 µg/L) > Se (0.06 ± 0.04 µg/L) > Cd (0.01 ± 0.01 µg/L) > Ag (0.004 ± 0.013 µg/L). The hazard index values of trace elements in surface water for combined pathways (ingestion and dermal contact) were < 1.0 for both adults and children, indicating no possible human health hazards. The estimated total cancer risk did not exceed the acceptable limit (1 × 10-4) for adults and children. The findings of this study provide data-driven guidelines for water environment policy decisions in the study area.

Spatio-Temporal Distribution and Influencing Factors of Human and Veterinary Pharmaceuticals in the Tributary Surface Waters of the Han River Watershed, South Korea.

Human and veterinary pharmaceuticals are being increasingly used for disease treatment; hence, their distribution and factors influencing them in the aquatic environment need to be investigated. This study observed the effect of human and animal populations, usage, purchasing criteria (prescription vs. non-prescription), and land use to identify the spatio-temporal distribution of eight pharmaceuticals at twenty-four sites of the tributaries of the Han River watershed. In rural areas, the mean concentration (detection frequency) of non-prescription pharmaceuticals (NPPs) was higher (lower) compared to that of prescription pharmaceuticals (PPs); in urban areas, a reverse trend was observed. Pharmaceutical concentrations in urban and rural areas were mainly affected by wastewater treatment plants (WWTPs) and non-point sources, respectively; concentrations were higher downstream (4.9 times) than upstream of the WWTPs. The concentration distribution (according to the target) was as follows: human–veterinary > human > veterinary. Correlation between total concentration and total usage of the pharmaceuticals was high, except for NPPs. Most livestock and land use (except cropland) were significantly positively correlated with pharmaceutical concentrations. Concentrations were mainly higher (1.5 times) during cold seasons than during warm seasons. The results of this study can assist policymakers in managing pharmaceutical pollutants while prioritizing emerging pollutants.

Geographical Distribution and Risk Assessment of Volatile Organic Compounds in Tributaries of the Han River Watershed

Volatile organic compounds (VOCs), with negative impacts on the aquatic ecosystem, are increasingly released into the environment by anthropogenic activities. Water samples were collected from five areas of the Han River Watershed (HRW) tributaries, South Korea, to detect 11 VOCs, which were classified as halogenated aliphatic hydrocarbons (HAHs) and aromatic hydrocarbons (AHs). Among the 11 VOCs, 1,1-dichloroethylene, 1,1,1-trichloroethane, and vinyl chloride were undetected. The highest concentration compounds were chloroform (0.0596 ± 0.1312 µg/L), trichloroethylene (0.0253 ± 0.0781 µg/L), and toluene (0.0054 ± 0.0139 µg/L). The mean concentration (0.0234 µg/L) and detection frequency (37.0%) of HAHs were higher than those of AHs (0.0036 µg/L, 21.0%, respectively). The Imjin Hantan River area exhibited the highest mean concentration (0.2432 µg/L) and detection frequency (22.9%), because it is located near industrial complexes, thus, highlighting their role as important VOC sources. However, the detected VOCs had lower concentrations than those permitted by the EU, WHO, USA, and South Korea drinking water guidelines. Ecological risks associated with the VOCs were estimated by risk quotient (RQ); consequently, the predicted no-effect concentration was 0.0029 mg/L, and the toluene and styrene RQ values were &gt;1 and &gt;0.5, respectively. The findings may facilitate policymakers in designing pollution control strategies.

Characteristics of Fish Communities in Namyang Lake and its Tributaries in the Estuary of Han River Watershed, South Korea

Characteristics of Fish Communities in Namyang Lake and its Tributaries in the Estuary of Han River Watershed, South Korea

Identifying Key Watershed Characteristics That Affect the Biological Integrity of Streams in the Han River Watershed, Korea

Understanding the complex human and natural processes that occur in watersheds and stream ecosystems is critical for decision makers and planners to ensure healthy stream ecosystems. This study aims to characterize the Han River watershed in Korea and extract key relationships among watershed attributes and biological indicators of streams using principal component analysis (PCA) and self-organizing maps (SOM). This study integrated watershed attributes and biological indicators of streams to delineate the watershed and stream biological status. Results from PCA strongly suggested that the proportions of watershed and riparian land use are key factors that explain the total variance in the datasets. Forest land in the watershed appeared to be the most significant factor. Furthermore, SOM planes showed that the biological indicators of streams have strong positive relationships with forest land, well-drained soil, and slope, whereas they have inverse relationships with urban areas, agricultural areas, and poorly drained soil. Hierarchical clustering classified the watersheds into three clusters, exclusively located in the study areas depending on the degree of forest, urban, and agricultural areas. The findings of this study suggest that different management strategies should be established depending on the characteristics of a cluster to improve the biological condition of streams.

Applicability of Lindley Distribution for Hydroelectric Dam Operations in the Dry Season

The long-term low-flow data are necessary for efficient planning of water resources and for estimating accurate quantiles via runoff data analysis at point. However, the short recording time period, low confidence, inconsistent distribution model, and parameter estimation method, make it difficult to estimate a proper low-flow quantile for each return period. In this study, the Lindley distribution model, which is a mix of the exponential and the gamma distribution models and has been verified as efficient by previous studies, was used to analyze the low-flow frequency using dam inflow data. We studied its applicability via comparison with statistics of observed data and other models already used for low-flow frequency analysis. For this, we carried out a performance analysis through a low-flow frequency analysis of inflow data from the hydroelectric dam and the reappearance capacity assessment of observed data at the Han river watershed. As a result, the hydrological applicability of the Lindley distribution model and its relative qualitative and quantitative excellence compared to the existing model were verified.

Temporal-spatial variation and environmental risk assessment of pharmaceuticals in tributaries of the Han River watershed, South Korea

Eight compounds from three categories of pharmaceuticals [5 antibiotics, 2 non-steroidal anti-inflammatory drugs, and 1 anti-epileptics] were monitored at 24 sites in the tributaries of the Han River watershed in South Korea, 2016. The seasonal occurrence, temporal-spatial variation, potential compound source(s), and a risk assessment of this watershed, which is the largest drinking water source in the country, were investigated. Clarithromycin was detected most frequently (72.2%) with the greatest median concentration (0.151 ± 0.072 μg L−1), followed by carbamazepine and sulfamethoxazole. The seasonality of the pharmaceuticals was observed, with higher concentrations and detection frequencies in spring than in summer and autumn; this was possibly caused by lower levels of microbial activities associated with lower water temperatures than other seasons. In terms of geographical variation, urban areas had higher pharmaceutical concentrations than rural areas, which was attributed to the former's high population density and largest wastewater treatment plants (WWTPs) regardless of season. The total concentration and detection frequency of WWTPs were 12.4 and 2.5 times higher in downstream sites than upstream sites, thereby conveying that WWTPs were the main source for the presence of pharmaceuticals in tributaries. According to the results produced from calculations of the risk quotient (RQ) of aquatic organisms, clarithromycin and sulfamethazine were identified as posing relatively high ecological risk (RQ > 1) during the spring that was identified for this study. This study can provide policymakers with scientific support for prioritizing pollutant management and collections of global data on emerging pollutants.

Pharmaceutical compounds in tributaries of the Han River watershed, South Korea

The Han River watershed is the largest and most important source of drinking water for the residents of the Seoul metropolitan area and the Gyeonggi province in South Korea. The tributaries of the watershed are vulnerable to contamination by effluents from nearby wastewater treatment plants (WWTPs) and non-point sources. In this study, a one-year monitoring study was performed to investigate the occurrence of 13 pharmaceuticals in 24 tributaries of the Han River watershed in October 2015. From the 13 pharmaceuticals, 12 were found in at least one sample, with the exception of chlortetracycline, which was not detected. The three most frequently detected compounds were clarithromycin (95.8%), carbamazepine (66.7%), and lincomycin (62.5%). Compounds found in high concentrations included clarithromycin (5.2675 μg L−1), ibuprofen (1.9646 μg L−1), and carbamazepine (1.1009 μg L−1). The total concentration of 12 pharmaceuticals in the Seoul metropolitan area (0.7128 μg L−1) was higher than that in the Gyeonggi area (0.3177 μg L−1) possibly due to the large-scale WWTPs located upstream. However, in IHR-3, which is located at the very upstream of the tributary and is not impacted by a WWTP, pharmaceuticals were not detected. This can be explained by the fact that most pharmaceuticals derived from WWTPs are related to human activity. The risk quotients (RQs) for the target pharmaceuticals were calculated on the basis of their presence in tributaries, and all pharmaceuticals presented RQs < 0.01, indicating that potential environmental impacts should be low. These results will be useful to monitor and assess the potential environmental risks of pharmaceuticals in the surface water.

Evaluation of Watershed Scale Aquatic Ecosystem Health by SWAT Modeling and Random Forest Technique

In this study, we evaluated the aquatic ecosystem health (AEH) with five grades (A; very good to E; very poor) of FAI (Fish Assessment Index), TDI (Trophic Diatom Index), and BMI (Benthic Macroinvertebrate Index) using the results of SWAT (Soil and Water Assessment Tool) stream water temperature (WT) and quality (T-N, T-P, NH4, NO3, and PO4). By applying Random Forest, one of the machine learning algorithms for classification analysis, each AEH index was trained and graded from the SWAT results. For Han river watershed (34,418 km2) in South Korea, the 8 years (2008~2015) observed AEH data of Spring and Fall periods at 86 locations from NAEMP (National Aquatic Ecological Monitoring Program) were used. The AEH was separately trained for Spring (FAIs, TDIs, and BMIs) and Fall (FAIa, TDIa, and BMIa), and the AEH results of Random Forest with SWAT (WT, T-N, T-P, NH4, NO3, and PO4) as input variables showed the accuracy of 0.42, 0.48, 0.62, 0.45, 0.4, and 0.58, respectively. The reason for low accuracy was from the weak strength of the individual trees and high correlation between the trees composing the Random Forest due to the data imbalance. The AEH distribution results showed that the number of Grade A of total FAI, TDI, and BMI were 84, 0, and 158 respectively and they were mostly located at the upstream watersheds. The number of Grade E of total FAI, TDI, and BMI were 4, 50, and 13 and they were shown at downstream watersheds.

A Study on the Flora and Vegetation Changes in the Riparian Zones of Han River Watershed

A Study on the Flora and Vegetation Changes in the Riparian Zones of Han River Watershed

A local-regional scaling-invariant Bayesian GEV model for estimating rainfall IDF curves in a future climate

Future changes in rainfall patterns induced by climate changes will affect society and ecosystems, and quantifying these changes is of utmost importance for the management of hydroclimate risk. In particular, the estimation of intensity-duration-frequency (IDF) curves for rainfall data is a routine procedure in urban hydrology and hydraulic studies and should be revisited to reflect future changes in rainfall variability. In this work, we propose a novel methodology based on the scaling-invariant property of rainfall duration versus intensity to estimate parameters of a generalized extreme value (GEV) distribution at sub-daily scales. A Bayesian inference framework is developed so that uncertainties are reduced and can be easily propagated to IDF curves. The proposed model can be employed to: (i) improve local (at-site) GEV estimates for sites with limited rainfall records; (ii) estimate GEV parameters at sub-daily scales and construct IDF curves for sites where only daily rainfall records are available (partially gauged sites); (iii) construct regional IDF curves for homogeneous hydrologic regions; and (iv) update local and regional IDF curves from simulations of future daily rainfall. The model is tested using historical rainfall data from 18 gauges located in the Han River Watershed in South Korea, and projected climate change scenarios RCP 6 and RCP 8.5 from the Met Office Hadley Centre HadGEM2-AO model. When considering historical data, the results show that the model satisfactorily estimate IDF curves for both gauged and partially gauged sites. In future scenarios, the model reveals a substantial increase in rainfall events of rare intensity (large return periods), mostly due to changes in the rainfall variability rather than changes in the average rainfall. Particularly, for a 100-year return period event, we expect an increase of about 23% in scenario RCP 6 and about 30% under scenario RCP 8.5 when projected using regional IDF curves. To the best of our knowledge, this is the first statistical approach in the literature to assess future changes in regional IDF curves, which in our opinion is more suitable than evaluating local estimates only.

Key coastal landscape structures for resilient coastal green infrastructure to enhance the abundance of migratory birds on the Yellow Sea

The aim of this study was to investigate the key landscape structures of migratory bird habitats that affect abundance of migratory birds to promote resilient coastal green infrastructure planning on the Yellow Sea coast. We classified coastal areas into four watersheds of South Korea and conducted multivariate regression analysis between migratory bird populations and landscape structures including total class area (CA), patch area distribution (MN), patch density (PD), and edge density (ED). At the national level, sandbank MN, sandbank CA, water ED, and grasslands were derived as key landscape structures affecting the abundance of migratory birds. At the watershed level, key landscape structures were determined as follows: Urban area_MN for the Han River watershed, rice paddy MN for the Asan watershed, rice paddy CA for Saemangeum, and grassland MN for the Youngsan River watershed. Considering the multifunctionality, redundancy, and connectivity of the resilience strategy, we provide specific coastal infrastructure planning recommendations at the national and watershed scales.

Estimation of return period and its uncertainty for the recent 2013–2015 drought in the Han River watershed in South Korea

Abstract This study introduces an approach to copula model parameter estimation within a Bayesian framework. The model is applied to estimate the return periods of the 2013–2015 drought in the Han River watershed (South Korea) as observed through a network of 18 rainfall stations in the watershed. For the univariate return periods, some of the 2013–2015 drought durations (i.e., 9–24 months) have return periods of around 30 years while the drought severities (which range from about 400 to 1,400 mm) at certain stations might be regarded as extreme events with return periods in the hundreds of years. The recent drought is extraordinary at many stations in the Han River watershed although the associated uncertainty is quite large (e.g., for the Seoul station, a range of about 180 to 2,250 years). Moreover, it is clearly seen that the unprecedented joint return periods of the 2013–2015 drought at many stations are consistent with the very high drought severity. The joint return period of the drought duration and severity is above 100 years for many of the stations and upwards of 1,000 years for a few stations.

Drought Frequency Analysis Using Hidden Markov Chain Model and Bivariate Copula Function

This study applied a probabilistic-based hidden Markov model (HMM) to better characterize drought patterns. In addition, a copula-based bivariate drought frequency analysis was employed to further investigate return periods of the current drought condition in year 2015. The obtained results revealed that western Kangwon area was generally more vulnerable to drought risk than eastern Kangwon area using the 40-year data. Imjin-river watershed including Cheorwon area was the most vulnerable area in terms of severe drought events. Four stations in Han-river watershed showed a joint return period exceeding 1,000 years associated with the drought duration and severity in 2014-2015. Especially, current drought status in Northern Han-river and Imjin-river watershed is most severe drought exceeding 100-year return period.