Search

With the increase in both rainfall and intensity due to climate change, the risk of debris flows is also increasing. In Korea, the increasing damage caused by debris flows has become a social issue, and research on debris-flow response is becoming increasingly important. Understanding the rainfall that induces debris flows is crucial for debris-flow response, and methods such as the I-D method have been used to evaluate and predict the risk of debris flows. However, previous studies on debris flow-induced rainfall analysis have been limited by the subjective decision of the researcher to select the impact meteorological stations, which greatly affects reliability. In this paper, in order to establish an objective standard, various maximum allowable distances between debris-flow disaster areas and meteorological stations were adjusted to 1, 3, 5, 7, 9, 11, 13, and 15 km using the CTRL-T automatic calculation algorithm, and the optimal maximum allowable distance suitable for Korean terrain was derived through parameter sensitivity analysis. Based on this, we developed a nomogram for sediment disaster risk prediction and warning in Gangwon-do, and applied it to past disaster cases, and found that, although the prediction time for each stage varies depending on the maximum allowable distance, on average, it is possible to predict the risk of sediment flows 4 to 5 h in advance. It is believed that the results of this study can be used to reduce sediment flow damage in advance. [ABSTRACT FROM AUTHOR]

Recognizing how human activities affect hydrological systems is vital for the sustainable preservation and effective management of water resources in the watershed. Hence, this paper focuses on the hydrological response to land use and land cover (LULC) change scenarios in the Anyang watershed, South Korea. We obtained LULC data maps for the years 2000, 2013, and 2022 from the local government, revealing significant changes over the years. Agricultural lands experienced a 6.2% increase from 2000 to 2022, and pastureland expanded by 8.67% over two decades. The SWAT model was utilized to assess the impact of LULC on the hydrological components of the study watershed. Model calibration and validation for each LULC change were carried out using the SWAT-CUP program, considering the recorded streamflow information of the region. An excellent agreement was reached between the simulated and measured streamflow in both the calibration and validation stages under various LULC conditions. The Nash–Sutcliffe model efficiency (NSE), the objective function, demonstrated values of 0.9, 0.89, and 0.89 during the calibration for 2000, 2013, and 2022, respectively, in the LULC scenario, while for the validation, we obtained values of 0.82, 0.78, and 0.80 for 2000, 2013, and 2022, respectively. Our findings indicate that the surface runoff rise contributed much to the water yield increase over the two decades compared to the other components in terms of the water yield, while the contribution of evapotranspiration (ET) to the watershed hydrological cycle declined by 1.66% from 2000 to 2022. The southeastern sub-basin part showed a high groundwater recharge distribution due to agricultural land, rice area, and forest area changes. [ABSTRACT FROM AUTHOR]

This paper presents an innovative digital twin dam and watershed management platform, K-Twin SJ, that utilizes real-time data and simulation models to support decision-making for flood response and water resource management. The platform includes a GIS-based geospatial digital twin of the entire Sumjin dam and river water system in Korea, with high-precision geospatial topography and facility information for dams and rivers (watershed area 4913 km2, river length 173 km, and 91 water infrastructures). The platform synchronizes real-time data such as rainfall, dam and river water levels, flow rate, and closed-circuit television (CCTV), and incorporates three hydraulic and hydrological simulation models for efficient dam operation considering the river conditions. AI technology is also used to predict the river water level and suggest optimal dam discharge scenarios. Additionally, the platform includes a geotechnical safety evaluation module for river levees, advanced drone monitoring for dams and rivers, and an AI CCTV video surveillance function. The digital-twin-based platform supports efficient decision-making for smart flood responses and contributes to reducing flooding damage and optimal operation through better smart water management. [ABSTRACT FROM AUTHOR]

The water cycle in watersheds is vulnerable due to climate change; hence, the need for sustainable watershed management is increasing. This paper suggests a framework for a healthiness assessment of the water cycle to provide a guideline for systematic watershed management considering the previous and current states. The suggested framework aims to prioritize restoration and enhancement plans based on the graded healthiness of the water cycle elements by the watersheds. The framework is composed of two assessment procedures: a problem-focused assessment to identify problems such as flood, drought, and river depletion in the watershed and the highest priority assessment to select the watershed for enhancement and restoration plans. The healthiness assessment method for each metric is suggested based on the Korean Framework Act on Water Management. The framework was applied to four different watersheds in South Korea. The framework is proven to be an effective method to identify practical emerging problems for the water cycle in each watershed. The framework can contribute to providing technical information to detect the water problem of the watershed by objectively diagnosing the watersheds with various potential water problems via the healthiness assessment. [ABSTRACT FROM AUTHOR]

Implemented by a national law, the National Aquatic Ecological Monitoring Program (NAEMP) has been assessing the ecological health status of surface waters, focusing on streams and rivers, in Korea since 2007. The program involves ecological monitoring of multiple aquatic biota such as benthic diatoms, macroinvertebrates, fish, and plants as well as water quality and habitat parameters. Taking advantage of the national scale of long-term aquatic ecological monitoring and the standardization of protocols and methods, the datasets in NAEMP provide many opportunities for various advanced comparative and synthetic studies, policy-making, and ecological management. In order to realize these potentials and opportunities, we have developed a RESTful API-based data management system called OSAEM (the Open, Sharable and Extensible Data Management System for Aquatic Ecological Monitoring), which is designed to be open, sharable, and extensible. In this paper, we introduce the RESTful API-based data management approach, present the RESTful API for the OSAEM system, and discuss its applicability. An OSAEM prototype system is currently available on a commercial cloud service (Amazon EC2) but the system remains under active development. [ABSTRACT FROM AUTHOR]

The decline in walleye pollock (Gadus chalcogrammus) stocks in Korean waters is a major concern for fishery conservation and management. However, the causes and mechanisms of this collapse remain unclear. This study investigated the complex dynamics influencing the abundance of walleye pollocks in the East Sea of Korea over several decades, by analyzing data from long-term changes in biological factors including composition of length and sex, catch, and oceanographic condition. Prior to the mid-1980s, the catch ratio of juveniles was higher than that of adults, with a higher proportion of females in both juvenile and adult catches compared to males. Especially, high fishing pressure on female individuals can be an important factor contributing to declining reproduction. Consequently, after the mid-1980s, there was a sudden decline in juvenile pollock catches. In the late 1980s, there was a rapid increase in sea surface temperature (SST) in the spawning grounds, resulting in a decrease in both the duration of suitable temperature for spawning and the regional proportion for suitable spawning conditions. Consequently, the decline in pollock stocks after the late 1980s due to overfishing of pollock in the mid-1980s was further exacerbated by the effects of SST warming after the late 1980s. These findings highlight the impact of overfishing and environmental factors on pollock stocks and indicate the need for appropriate fishery management practices to ensure the sustainable use of fishery resources. [ABSTRACT FROM AUTHOR]

This study aims to provide an opinion on the state-of-the-art of changes and reforms of water policies in South Korea, as well as the challenges along with their implications for sustainable water governance and management. In parallel with change in water resource characteristics generated by physical, environmental and socio-economic challenges such as: (1) uncertainties about climate change (flooding and drought) including seasonal and regional variation in precipitation; (2) significant increase in water use caused by rapid urbanization and population growth in industrialized urban areas; (3) inadequate water pricing mechanism which covers only around 80% of the production cost and makes it harder to maintain water systems; and (4) recursive water quality degradation and conflicts over water rights between regions resulting from non-point source pollution in highland versus lowland areas, Korean water policies have been developed through diverse reforms over 100 years. Nevertheless, new challenges for sustainable water management are continuously emerging. To meet those challenges we provide two ideas: (i) provider-gets-principle (payment for ecosystem services) of cost-benefit sharing among stakeholders who benefit from water use; and (ii) water pricing applying full-cost pricing-principle internalizing environmental externalities caused by the intensive water use. Funds secured from the application of those methods would facilitate: (1) support for upstream (rural) low income householders suffering from economic restrictions; (2) improvement in water facilities; and (3) efficient water use and demand management in South Korea's water sectors. We expect that this paper can examine the lessons relevant to challenges that South Korea faces and offer some implications on the formulation of new integration and further reforms of the institutions, laws and organizations responsible for managing water resources in South Korea. [ABSTRACT FROM AUTHOR]

According to a 2015 study conducted by the Ministry of Environment of Korea, municipal water is supplied to 96.1% of the total Korean population, but 3.9% of the total population (~2.14 million people) in rural myeon or villages, drink groundwater from old and/or unregistered wells that are not a part of themunicipalwater system. Additionally, accurate statistics are not reported without regular water quality tests, so safety measures alone are insufficient to improve water quality. In this situation, the Korean government is responsible for verifying the quality of groundwater and identifying the cause of groundwater contamination in areas with no municipal water supply. The National Institute of Environmental Research (NIER) under the Ministry of Environment of Korea, conducted the ‘Safe Groundwater Supply Project (SGSP)’ between 2012 and 2016 to secure groundwater quality stability in areas without the benefit of municipal water. This survey identified groundwater quality using a detailed water quality survey and gave recommendations for supplying safe groundwater and providing future improvements and countermeasures in cases of groundwater pollution. This paper presents the SGSP and consists of water quality analysis, the exploration and exploitation of drinking water facilities, the selection of a pilot project area among high-pollution areas, and improvement measures for water quality in the pilot project area. [ABSTRACT FROM AUTHOR]

Parallel pipeline projects can contribute to ensuring a safe and stable water supply and preventing or mitigating losses caused by water pipeline accidents. However, because these projects require a significant investment, feasibility tests are essential prior to their implementation. Considering the public nature of the water supply, the direct beneficiaries of the project and people from other regions can place value on such projects. Thus, this study estimates the value of parallel pipeline projects using the contingent valuation method (CVM) and the swing weighting technique. We constructed two contingent valuation surveys: one asking about the willingness to pay (WTP) for a parallel pipeline project within the respondent's region and the other asking about the WTP for a project outside the region. The results show that the annual WTP per household for projects within and outside the region was 113,669 KRW (87.98 USD) and 5493 KRW (4.25 USD), respectively. These results indicate that the value perceived by people from outside the region should be considered. Additionally, the results from the swing weighting technique and WTP analysis show that the values that respondents generally consider important and those that can leverage the overall project value are distinct. This study's results provide insights into the implementation of parallel pipeline projects in South Korea. Furthermore, this study's analytical framework can be used for the valuation of other public infrastructure projects. [ABSTRACT FROM AUTHOR]

This study accounted for the importance of daily expansion flow data in compensating for insufficient flow data in a watershed. In particular, the 8-day interval flow measurement data (intermittent monitoring data) could cause uncertainty in the high- or low-flow conditions that have been used to estimate the flow duration curve (FDC) and the load duration curve (LDC) used in Total Maximum Daily Load (TMDL) evaluation in Korea. Thus, this study developed a method to expand the 8-day interval flow data (missing data) to daily flow data in order to evaluate the Total Maximum Daily Load (TMDL) appropriately in a watershed. We employed the machine learning technique (the gradient descent method provided by the Google TensorFlow package) to develop a regression for expanding the 8-day interval flow data. The method was applied in the Nakdong River basin located in Korea to collect the 8-day interval and daily flow data from a number of gauging stations. The results of the expanded daily flow were evaluated through the RMSE, MAE, IOA, and NSE, and the valid expanded daily flow data were obtained for the 29 TMDL gauging stations (IOA 0.84~0.99, NSE −0.18~0.99). A good performance in the creation of daily flow data (continuous data) from the 8-day interval flow data (intermittent data) was shown using the proposed method. In addition, the Web GIS-based pollutant load assessment system was developed to evaluate the TMDL; it included the daily data expansion method and provided the pollution load characteristics objectively and intuitively. This system will help decision makers, such as environmental regulators, researchers, and the general public, and support their decision making for pollution source management with accessible and efficient tools for understanding and addressing water quality issues. [ABSTRACT FROM AUTHOR]

In South Korea, the use of hydroponic cultivation has been on the rise. However, this system produces a large amount of wastewater. In this study, the amount of wastewater generated by hydroponic tomato cultivation is identified, and a management plan is proposed. Based on the analysis of 103 tomato HWW samples, it was found that the electrical conductivity (EC) was 4.25 ± 1.01 dS/m, the nitrogen (N) content was 411.21 ± 122.64 mg/L, and the phosphorus (P) content was 47.74 mg/L, which caused eutrophication. Therefore, agricultural reuse and HWW treatment were proposed. Regarding the annual HWW load, 1 ha of hydroponics discharges 964.26 kg/ha of N, 111.95 of P, 937.46 of K, 795.14 of Ca, 313.83 of Mg, and 405.40 of S. The trace elements were heavy metals, which were calculated as Fe—4.03, Mn—0.77, Zn—1.08, B—2.25, Cu—0.38, and Mo—0.05 kg/ha. Since wastewater is a national source of drinking water, it needs to be collected and treated. Inter-item correlation analysis showed that most of the fertilizer components were correlated with the EC concentrations. This study can be used to determine the concentrations required for agricultural reuse and to determine the treatment capacity in HWW management. [ABSTRACT FROM AUTHOR]

In this study, we analyzed the impact of model spatial resolution on streamflow predictions, focusing on high-resolution scenarios (<1 km) and flooding conditions at catchment scale. Simulation experiments were implemented for the Geumho River catchment in South Korea using Weather Research and the Forecasting Hydrological Modeling System (WRF-Hydro) with spatial resolutions of 100 m, 250 m, and 500 m. For the estimation of parameters, an automatic calibration tool based on the Model-Independent Parameter Estimation and Uncertainty Analysis (PEST) method was utilized. We assessed the hydrological predictions across different spatial resolutions considering calibrated parameters, calibration runtime, and accuracy of streamflow before and after calibration. For both Rainfall Events 1 and 2, significant improvements were observed after event-specific calibration in all resolutions. Particularly for 250 m resolution, NSE values of 0.8 or higher were demonstrated at lower gauging locations. Also, at a 250 m resolution, the changes in the calibrated parameter values ( R E F K D T ) were minimized between Rainfall Events 1 and 2, implicating more effective calibration compared to the other resolutions. At resolutions of 100 m and 500 m, the optimal parameter values for the two events were distinctively different while more computational resources were required for calibration in Event 2 with drier antecedent conditions. [ABSTRACT FROM AUTHOR]

In this work, a method of simultaneously analyzing pesticide concentration and assessing its risks was developed. Assessments were conducted to evaluate the distribution characteristics and risks to human health of pesticides in shallow groundwater in agricultural areas. We developed multi-residue analytical methods using liquid chromatography (LC-MS/MS) and gas chromatography–tandem mass spectrometry (GC-MS/MS) to analyze 57 pesticides in groundwater. In addition, risk assessments were performed by setting scenarios considering the routes of pesticide infiltration into groundwater. For the simultaneous analysis of 57 pesticides, the liquid–liquid extraction method was applied twice using dichloromethane under acidic and alkaline conditions. The extract was concentrated and analyzed using LC-MS/MS (41 pesticides) and GC-MS/MS (16 pesticides). The precision and accuracy ranges of the analytical methods were 0.1~12.9% (within ±15%) and 80.3~113.6% (within ±20%), respectively. The limit of quantification was found to range from 0.0004 to 0.0677 μg/L. In total, 57 pesticides were monitored in 200 groundwater wells from 2019 to 2020. Twenty-six pesticides, including metolachlor and imidacloprid, were detected, with an average concentration of 0.0008 μg/L in groundwater. The pesticide types and detection levels differed depending on the survey period and surrounding land. When the risks associated with alachlor, metolachlor, and carbofuran were assessed, their health risks when found in groundwater were evaluated to be negligible (non-carcinogenic risk: less than 10−3, carcinogenic risk: less than 10−6). [ABSTRACT FROM AUTHOR]

This study investigated the effects of nonpoint source (NPS) pollution reduction and pollutant dynamics in a highland agricultural watershed in Korea. We employed the SWAT model to simulate hydrological processes and pollution transport within the watershed. The model incorporates future climatic scenarios derived from downscaled climate projections to assess their impacts on NPS pollution and pollutant reduction methods. These changes lead to heightened surface runoff and erosion rates, resulting in elevated sediment and nutrient concentrations. The projection indicates an anticipated increase in the annual average temperature by 1.3 to 2.1 °C by the mid-century, under scenarios SSP126 and SSP585. Additionally, precipitation levels are projected to increase by 31 to 61 mm from the baseline to the end of the century. Variations in hydrological components such as evapotranspiration, streamflow, and soil moisture are expected to range from +3.2 to +17.2%, −9.1 to +8.1%, and 0.1 to 0.7%, respectively, during the years 2040 and 2080. Fluctuations in TN, SS, and TP loading are estimated to range from −4.5 to +2.3%, −5.8 to +29.0%, and +3.7 to +17.4%, respectively. This study emphasizes the importance of adaptive management options for stakeholders and the need for adaptive management options to reduce nonpoint source pollution and protect water quality to maintain sustainable water supplies and conserve the environment in this watershed. [ABSTRACT FROM AUTHOR]

The increasing intensity of rainfall resulting from climate change is projected to worsen the inundation of urban areas by floods. As a viable alternative, stormwater harvesting presents an opportunity to enhance water supply reliability while reducing pressure on both water resources and urban stormwater drainage systems. The stored rainwater can be supplied with a radius of one kilometer around the storage facility, so less pumping energy is consumed compared to supplying the stored rainwater far away from the storage facilities. To visually depict the characteristics of the selected storage facility, land cover maps were created using ArcGIS. These maps were created for a circular region with a radius of one kilometer around each studied storage facility. In this study, a daily water balance model was formulated using spreadsheets to assess the potential of harvesting stormwater and rainwater for various pre-existing storage facilities. Five different types of storage facilities were selected for this study. The term "SRWH facility evaluation criteria" as a whole is used for the storm or rain (SR) water supply satisfaction rate, the SR guarantee rate, and the SR utilization rate. The results provide evidence that, for each selected studied storage facility, the SR water guarantee rate can potentially surpass 70% under conditions of low water demand. Moreover, we investigated the potential of the existing storage facilities to work as multifunctional resources, while the original purpose for which each facility was constructed remains un-affected. [ABSTRACT FROM AUTHOR]

Effective management of nitrate loading in complex river systems requires quantitative estimation to trace different nitrogen sources. This study aims to validate an integrated framework using soluble nitrogen isotope ratios (δ15N–NH4 and δ15N–NO3) and hydrological modeling (hydrological simulation program SPARROW) of the main stream and tributaries in the Yeongsan River to determine anthropogenic nitrogen fluxes among different land-use types in the complex river watershed. The δ15N–NH4 and δ15N–NO3 isotopic compositions varied across different land-use types (4.9 to 15.5‰ for δ15N–NH4 and −4.9 to 12.1‰ for δ15N–NO3), reflecting the different sources of nitrogen in the watershed (soil N including synthetic fertilizer N, manure N, and sewage treatment plant effluent N). We compared the soluble nitrogen isotopic compositions (δ15N–NH4 and δ15N–NO3) of the river water with various nitrogen sources (soil N, manure N, and sewage N) to assess their contribution, revealing that N from sewage treatment plant effluent as a point source was dominant during the dry season and N from forest- and soil-derived non-point sources was dominant due to intensive rainfall during the wet season. The coefficient of determination (R2) between the measured pollution load and the predicted pollution load calculated by the SPARROW model was 0.95, indicating a high correlation. In addition, the EMMA-based nitrogen contributions compared to the SPARROW-based nitrogen fluxes were similar to each other, indicating that large amounts of forest- and soil-derived N may be transported to the Yeongsan River watershed as non-point sources, along with the effect of sewage treatment plant effluent N as a point source. This study provides valuable insights for the formulation of management policies to control nitrogen inputs from point and non-point sources across different land-use types for the restoration of water quality and aquatic ecosystems in complex river systems. Given the recent escalation in human activity near aquatic environments, this framework is effective in estimating the quantitative contribution of individual anthropogenic nitrogen sources transported along riverine systems. [ABSTRACT FROM AUTHOR]

Agricultural land is an important ecosystem that is essential for human life, and rice paddies, in particular, provide many ecosystem services such as food production and the maintenance of biodiversity. Although the value of rice paddy wetlands is high, they are rapidly disappearing due to urbanization and development. This study aims to estimate the monetary value of the rice paddy wetland ecosystem and investigate the proportion of benefits for each rice paddy wetland function to provide policy implications for rice paddy wetland management. To this end, this study conducted a survey with 988 South Korean citizens regarding rice paddy wetlands and adopted the contingent valuation method (CVM) with various approaches (double-bounded dichotomous choice pooled model, double-bounded dichotomous choice panel model, pseudo referendum model, open-ended question model, etc.). Considering the characteristics of each approach, the present value of the total willingness to pay (WTP) per household was estimated to range from 327 to 347 USD. When extrapolated to the entire country, the total WTP of all households in South Korea is estimated from 6.7 to 7.1 billion USD. This study also finds that households have an average WTP distribution ratio by paddy wetlands function as follows: food supply 33.8%, biodiversity 27.2%, disaster and pollution control 24.2%, and cultural services 14.8%. These findings have policy implications by providing valuable insights for decision-making in determining the priority and allocation levels of financial resources in the future design of policies related to paddy wetlands. [ABSTRACT FROM AUTHOR]

High concentrations of 2-methylisoborneol (2-MIB) were reported during winter in the Paldang reservoir and North Han River, South Korea. The causes of the unusual taste and odor problems in the regulated river-reservoir system were not understood; however, a short-term solution is to flush out 2-MIB-rich water to secure water sources for over 20 million people. Approximately 150 million tons of water was released from upstream dams for 12 days (late November to early December 2018) to reduce the elevated levels of 2-MIB. Simultaneously, the spatio-temporal variations of the measured concentration of sample 2-MIB from five sites were simulated using a multi-dimensional hydrodynamics-based solute transport model to monitor the flushing effect. A modified environmental fluid dynamics code (EFDC) was adopted as the primary model framework. Five scenarios on the kinetic constants related to the characteristics of 2-MIB transport and behavior, such as conservative, net decay, and net production, were applied, and the results were compared. We found that the simulation errors on the elapsed times to satisfy the Korean drinking water monitoring standard (≤20 ngL−1) were smallest with the conservative dye transport option, indicating that the physical and biochemical characteristics of 2-MIB may not play an essential role. [ABSTRACT FROM AUTHOR]

In the context of hydrological model calibration, observational data play a central role in refining and evaluating model performance and uncertainty. Among the critical factors, the length of the data records and the associated climatic conditions are paramount. While there is ample research on data record length selection, the same cannot be said for the selection of data types, particularly when it comes to choosing the climatic conditions for calibration. Conceptual hydrological models inherently simplify the representation of hydrological processes, which can lead to structural limitations, which is particularly evident under specific climatic conditions. In this study, we explore the impact of climatic conditions during the calibration period on model predictive performance and uncertainty. We categorize the inflow data from AnDong Dam and HapCheon Dam in southeastern South Korea from 2001 to 2021 into four climatic conditions (dry years, normal years, wet years, and mixed years) based on the Budyko dryness index. We then use data from periods within the same climatic category to calibrate the hydrological model. Subsequently, we analyze the model's performance and posterior distribution under various climatic conditions during validation periods. Our findings underscore the substantial influence of the climatic conditions during the calibration period on model performance and uncertainty. We discover that when calibrating the hydrological model using data from periods with wet climatic conditions, achieving comparable predictive performance in validation periods with different climatic conditions remains challenging, even when the calibration period exhibits excellent model performance. Furthermore, when considering model parameters and predicted streamflow uncertainty, it is advantageous to calibrate the hydrological model under dry climatic conditions to achieve more robust results. [ABSTRACT FROM AUTHOR]

Herein, we conducted surveys during the 2018–2022 summers to investigate the impact of climate change-related changes in the phytoplankton community structure on the marine ecosystem in the South Sea of Korea. The average surface water temperature increased by ~1.07 °C at 0.0195 °C·yr−1 between 1968 and 2022. During the summers, the rate was 0.0211 °C·yr−1, with a total increase of ~1.16 °C, indicating a stronger increase in summer surface water temperature. Over the last 30 years, nutrient levels in the South Sea have decreased, particularly at the surface. Moreover, 29.3–90.0% of the phytoplankton community structure was dominated by nanoflagellates (≤20 μm). Based on the size of the phytoplankton chl-a, the average contribution rate of picophytoplankton was the highest (60.1%). Redundancy analysis revealed negative correlations between nutrients and water depth, excluding NH4. Increased stratification due to climate change is causing reduced nutrient availability at the surface mixed layer, and the size of the phytoplankton structure is progressively reducing. These changes are expected to manifest in a complex microbial food web centered on smaller phytoplankton with low primary productivity. This can reduce the efficiency of carbon transfer to higher consumer levels, suggesting a potential decrease in marine productivity. [ABSTRACT FROM AUTHOR]

Multiscale forecasting of groundwater levels (GWLs) is essential for ensuring the sustainable management of groundwater resources, particularly considering the potential impacts of climate change. Such forecasting requires a model that is not only accurate in predicting GWLs but also computationally efficient, ensuring its suitability for practical applications. In this study, a temporal convolutional network (TCN) is implemented to forecast GWLs for 17 monitoring wells possessing diverse hydrogeological characteristics, located across South Korea. Using deep learning, the influence of meteorological variables (i.e., temperature, precipitation) on the forecasted GWLs was investigated by dividing the input features into three categories. Additionally, the models were developed for three forecast intervals (at 1-, 3-, and 6-month lead times) using each category input. When compared with state-of-the-art models, that is, long short-term memory (LSTM) and artificial neural network (ANN), the TCN model showed superior performance and required much less computational complexity. On average, the TCN model outperformed the LSTM model by 24%, 21%, and 25%, and the ANN model by 24%, 37%, and 47%, respectively, for 1-, 3-, and 6-month lead times. Based on these results, the proposed TCN model can be used for real-time GWL forecasting in hydrological applications. [ABSTRACT FROM AUTHOR]

Pesticides are beneficial in protecting crops from pests and improving agricultural productivity; however, concerns on pesticide pollution in water have increased due to their indiscriminate use and lack of adequate regulations. Many studies have focused on the risks of pesticides considering the limited number and types of pesticide residues in crops and soils, and duration, and very few have focused on surface water throughout the year. Therefore, this study comprehensively identified 308 pesticides in surface water samples collected monthly over one year in the Saemangeum Basin, Korea. Both targeted and non-targeted analyses were used to identify 171 and 24 pesticides, respectively. Results highlight the extensive extent of pesticide contamination. Among the quantified pesticides, bromobutide and pretilachlor consistently exhibited high concentrations and risk levels, as indicated by their elevated risk quotient (RQ) values. Seasonal variations in pesticide concentrations revealed distinct patterns with intensified herbicide use during summer and increased insecticide concentrations during autumn. This study highlights the presence, distribution, and associated ecological risks of pesticides in surface waters, emphasizing the necessity of comprehensive monitoring and regulatory measures to protect aquatic ecosystems. The high RQ values identified for specific pesticides underscore the urgent need to implement effective strategies to mitigate these environmental risks. [ABSTRACT FROM AUTHOR]

This study aims to collect water samples from two tributaries within the Geum River basin in South Korea, where large-scale livestock complexes are located, to quantify the measured environmental concentration (MEC) of pharmaceutical residues using a multiresidue analytical method developed with liquid chromatography–tandem mass spectrometry (LC-MS/MS), and to evaluate the environmental risks posed by the detected pharmaceuticals to aquatic organisms. The water samples were collected at a total of 17 points, including up-, middle-, and downstream of the Seoksong and Nonsan-Gangkyoung streams connected to the Geum River, from October 2018 to March 2019. A multiresidue analytical method using LC-MS/MS was developed to quantify 49 pharmaceuticals with hydrophilic lipophilic balance using solid phase extraction. The recovery rates varied between 67.23% and 136.98%, while the limits of quantification were from 3.99 to 46.32 ng/L. Ecotoxicological information on acute and chronic effect endpoints (e.g., EC50, NOEC, etc.) was obtained from the U.S. EPA ECOTOX Knowledgebase. Considering the worst-case scenario, the lowest observed effect endpoint (mainly NOEC) of the most sensitive species was selected, and predicted no effect concentration (PNEC) values were calculated by dividing the endpoint by an assessment factor (AF). The mean, minimum, and maximum MECs of pharmaceuticals were divided by PNECs to calculate risk quotient (RQ). Caffeine was detected in all sampling sites with a detection frequency of 100%. High levels of pharmaceuticals (9.212 μg/L of sulfathiazole, 8.479 μg/L of acetaminophen, and 5.885 μg/L of florfenicol) were detected. The RQ values exceeded 1 and reached up to 84.79 (high risk category) for acetaminophen, and were between 0.11 and 0.83 (moderate risk) for carbamazepine, etc. The RQs for the rest of the 15 substances were below 1 (low risk). In the future, further studies should be conducted to monitor other micropollutants, including industrial chemicals, pesticides, etc., at different locations of the Geum River basin, including livestock farms, pharmaceutical manufacturing facilities, wastewater treatment plants, and other facilities, for long-term period. [ABSTRACT FROM AUTHOR]

This study examines whether the fluvial flood defense system of Korea is appropriate for risk reduction. Using spatial socioeconomic data and remote sensing, we estimated the potential economic damage that can be caused by the flooding of local streams and rivers along the Nakdong River (the longest river in Korea). For the analysis, a river risk map including return periods (50, 80, 100, and 200 years) and spatial inventories (residential, agricultural, industrial assets, and human lives) was employed to determine flood-prone areas and assess the damage within the inundation areas. A quantitative flood analysis was conducted using an object-based method to estimate the expected annual damage. We then compared the estimated damage for each tributary within the designed return periods and found no correlation. Numerous tributaries with low-defense targets were considered high-risk, while those with high-defense targets were assessed as low-risk. The dataset used in this study covered four damage categories. Among them, flood damage to residential assets appeared to have the highest value, whereas flood damage to industrial assets had the lowest value. The results demonstrate that the Korean government needs to tailor its flood defense policy based on quantitative risk assessments to effectively manage flood risks, especially given the increasing risk of climate change. [ABSTRACT FROM AUTHOR]

Floods are highly perilous and recurring natural disasters that cause extensive property damage and threaten human life. However, the paucity of hydrological observational data hampers the precision of physical flood models, particularly in ungauged basins. Recent advances in disaster monitoring have explored the potential of social media as a valuable source of information. This study investigates the spatiotemporal consistency of social media data during flooding events and evaluates its viability as a substitute for hydrological data in ungauged catchments. To assess the utility of social media as an input factor for flood prediction models, the study conducted time-series and spatial correlation analyses by employing spatial scan statistics and confusion matrices. Subsequently, a long short-term memory model was used to forecast the outflow volume in the Ui Stream basin in South Korea. A comparative analysis of various input factor combinations revealed that datasets incorporating rainfall, outflow models, and social media data exhibited the highest accuracy, with a Nash–Sutcliffe efficiency of 94%, correlation coefficient of 97%, and a minimal normalized root mean square error of 0.92%. This study demonstrated the potential of social media data as a viable alternative for data-scarce basins, highlighting its effectiveness in enhancing flood prediction accuracy. [ABSTRACT FROM AUTHOR]

Recently, Korea has been affected by various disasters caused by climate change and the resulting changes in weather, which have been taking an increasing toll on the country. A review of weather phenomena and their socioeconomic impact identified weather disasters as one of the most damaging categories of disasters. As such, this study suggests a method for calculating the rainfall threshold to predict the impact of heavy rain. In order to calculate the rainfall threshold based on the multi-method, the entire territory of South Korea was divided into 1 km by 1 km grids, and a method for calculating the rainfall threshold was proposed by grouping them into four categories: standard watershed, urban areas, rivers, and inundation traces. This study attempted to verify the results of the rainfall threshold in standard watersheds and urban areas. The results were verified using the data from events during the heavy rain in Seoul in 2022 and 2018, the heavy rain in Busan in 2020, and Typhoon Mitag in October 2019. As a result of the verification and calculation, a rainfall threshold was found on the grid where the actual flooding damage occurred in Busan, where heavy rain caused a large amount of urban flooding in July 2020. The application of the rainfall threshold on the grid caused enough damage to flood vehicles. After this application, it was found that flooding of more than 0.2 m affected vehicles. During early September in the Gangneung grid, flooding damage was caused by Typhoon Haishen, which affected traffic. In this damaged grid, it was also found that flooding of more than 0.2 m occurred according to the rainfall impact limit. In this study, since there were no quantitative data, verification was performed using qualitative data such as news and SNS. Therefore, quantitative verification methods using flooding sensors and CCTVs need to be carried out in the future. After verification using qualitative data, we found that the time when the actual flooding damage occurred and the flooding patterns were well ascertained. The rainfall threshold calculation method and the rainfall prediction information developed in this study are expected to be applicable to impact forecasting, which can provide people affected by heavy rainfall with information on how the rainfall will affect them, as well as simple rainfall forecasts. [ABSTRACT FROM AUTHOR]

Early and accurate flood forecasting and warning for urban flood risk areas is an essential factor to reduce flood damage. This paper presents the urban flood forecasting and warning process to reduce damage in the main flood risk area of South Korea. This process is developed based on the rainfall-runoff model and deep learning model. A model-driven method was devised to construct the accurate physical model with combined inland-river and flood control facilities, such as pump stations and underground storages. To calibrate the rainfall-runoff model, data of gauging stations and pump stations of an urban stream in August 2020 were used, and the model result was presented as an R2 value of 0.63~0.79. Accurate flood warning criteria of the urban stream were analyzed according to the various rainfall scenarios from the model-driven method. As flood forecasting and warning in the urban stream, deep learning models, vanilla ANN, Long Short-Term Memory (LSTM), Stack-LSTM, and Bidirectional LSTM were constructed. Deep learning models using 10-min hydrological time-series data from gauging stations were trained to warn of expected flood risks based on the water level in the urban stream. A forecasting and warning method that applied the bidirectional LSTM showed an R2 value of 0.9 for the water level forecast with 30 min lead time, indicating the possibility of effective flood forecasting and warning. This case study aims to contribute to the reduction of casualties and flood damage in urban streams and accurate flood warnings in typical urban flood risk areas of South Korea. The developed urban flood forecasting and warning process can be applied effectively as a non-structural measure to mitigate urban flood damage and can be extended considering watershed characteristics. [ABSTRACT FROM AUTHOR]

In this study, we investigate the distribution of calanoid copepod eggs in the sediments of Masan Bay (South Sea, Korea), in which hypoxic conditions occur every summer. In August (2011), hypoxia was observed at all stations, while normoxia was observed in April (2012). The pH and hydrogen sulphide concentration at the sediment-water interface in the inner bay during August were 7.7 and >20 mol L−1, respectively, and there was no significant difference between the stations in April. The abundance of eggs in the sediment ranged from 0.69 to 1.49 × 106 eggs m−2 in August, and from 0.59 to 1.08 × 106 eggs m−2 in April. Notably, the proportion of abnormal eggs was high (a maximum of 77.1%) in August, and a uniform distribution of normal eggs (>80%) was observed in April. A generation of abnormal eggs hatched with deformed nauplii in Masan Bay during the summer, and a failure to hatch was likely due to the high H2S concentration and low pH caused by hypoxia. In this paper, we discuss the effects of hypoxia and seabed environments on the hatching success of calanoid copepod eggs. [ABSTRACT FROM AUTHOR]

Most of Korea's precipitation is concentrated between June and September, and 65% of the country's territory is covered with mountains, which means there is less time for rainfall to reach the surface. These hydrological characteristics pose challenges in securing and managing water resources. Moreover, the Yeongdong Area of Gangwon Province does not easily allow the construction of reservoirs and dams, which adds to the difficulty of developing structural measures to address water shortage caused by water supply restrictions. One measure proposed for addressing damage to residents, as well as social conflicts caused by water shortages, is to use underground dams and other high-capacity underground facilities to secure water for Korea's eastern coastal areas. Unlike dams and reservoirs above the ground, underground dams are not affected by floods and offer an eco-friendly way to address the continuous water demand growth by storing water in underground spaces. This study prioritizes underground dam sites in six areas in the Yeongdong Area of Gangwon Province (Goseong, Sokcho, Yangyang, Gangneung, Donghae, and Samcheok) by conducting an expert survey and analyzing the results with the analytic hierarchy process (AHP) and fuzzy AHP. The findings indicate that the Sangcheon River in Sokcho, where an underground dam already exists, satisfies the criteria proposed in this study. We expect the study's findings and methods to be used to determine suitable dam sites and water resource management plans. [ABSTRACT FROM AUTHOR]

This study aims to develop a straightforward and practical formula to estimate transverse dispersion coefficients in meandering natural rivers, a critical factor for predicting solute transport. We present a novel expression for the transverse dispersion coefficient based on dispersion and hydraulic data sets obtained from tracer experiments conducted in natural rivers. A distinctive feature of the formula is its reliance on one dimensionless hydraulic parameter, u ¯ u * h R c . To assess the effectiveness and accuracy of our proposed formula, we compare it with previously established equations commonly employed in the field. Furthermore, we apply the formula to natural river bends situated in the Nakdong River of Korea. This equation serves to estimate the initial value of the dispersion coefficient in two-dimensional solute transport modeling. As a result, the calibrated value of the dimensionless transverse dispersion coefficient is 0.97, which is only a 16% difference between the initial value of 0.81 as obtained from the formula. The formula presented in this study, simplifying and utilizing the dimensionless hydraulic parameter, offers a promising approach to estimating transverse dispersion in natural meandering rivers in cases where tracer and secondary flow data are unavailable. Additionally, the formula can be refined with more recent dispersion data, leading to a clearer, more straightforward, and validated formulation that captures the intricate interplay between topography and transverse dispersion. [ABSTRACT FROM AUTHOR]

We investigated the spatio-temporal variations in three key biomolecular compounds (carbohydrates, proteins, and lipids) in particulate organic matter (POM) in the Yellow Sea (YS), South Sea of Korea (SS), East China Sea (ECS), and East Sea (Sea of Japan; ES) in order to estimate the regional annual calorie production rates based on the seasonal data obtained in each region. Carbohydrates were found to be most dominant, followed by lipids across all seas. The euphotic-integral calorie contents of POM during the study period were determined as 53.5 ± 12.6 Kcal m−2 in the YS; 54.2 ± 7.5 Kcal m−2 in the SS; 35.7 ± 9.2 Kcal m−2 in the ECS; and 58.7 ± 6.2 Kcal m−2 in the ES. Utilizing seasonal carbon conversion factors and primary production rates, we estimated the annual calorie productions, which were highest in the ES (1705 Kcal m−2 y−1) and lowest in the ECS (403 Kcal m−2 y−1). This can be attributed to the significantly higher energy efficiency of phytoplankton and faster turnover rate of calorie content. However, caution must be taken when comparing these estimates regionally, considering potential variations in developmental phases among the four regions during the sampling period in 2018. The calorie production rates in this study provide valuable insights into the physiological condition of phytoplankton within specific regions. [ABSTRACT FROM AUTHOR]

Flooding has the ability to severely reduce the capacity of a transportation network. The closure of even a single bridge, which often acts as a critical link in transportation networks, can have a severe impact on the entire network. This impact can lead to significant economic costs resulting from increased travel distances for drivers. Despite the significance of these costs, however, notably few studies have been conducted to determine the societal economic cost that would be incurred due to bridge closures. One possible reason for the lack of studies investigating bridge closures due to flooding could stem from the difficultly in collecting data. To address this issue, the methodology presented in this paper uses modeling and data resources that are available for major cities in most developed countries, including those in South Korea. We evaluate the economic impact of the bridge closures using the new administrative capital of North Gyeongsang Province, South Korea as a case study. Scenarios for the closure of bridges are derived from channel surveys and hydraulic analyses. These methods are used to overcome a lack of adequate data on historical floods in the new city. Traffic is forecasted to estimate the number of road users that would be forced to take detours due to inundated bridges. Contrasting travel distances when bridges are and are not operational, economic costs incurred by bridge closures due to flooding are estimated. The results indicated that bridge closures would result in an economic cost of 1563 USD to 44,180 USD per day, depending on how many bridges are closed and how many people are living in the new city. The estimates from this study will act as guidelines for identifying cost-effective mitigation and preparedness strategies aimed at reducing the frequency and impact of bridge closures due to flooding. [ABSTRACT FROM AUTHOR]

For the first time, the results of a comprehensive assessment study on agricultural reservoirs in Korea were obtained. In this study, four agricultural reservoirs in Korea, namely, Songgo, Idam, Nohong, and Jukryang reservoirs, were investigated to establish a quantitative assessment system based on the water quantity and quality of the agricultural reservoirs, and present ratings. The research method involves selecting an indicator framework to evaluate water quantity and quality, using the statistical package for the social sciences statistics analysis program to verify compliance with standards and suitability of the indicator system, and selecting the final indicators to calculate their weights. The Jukryang and Nohong reservoirs have good water quality based on the average grade whereas the Songgo and Idam reservoirs have water quality that requires improvement as per Korean agricultural water standards. The weights of 0.5 were applied to water quantity and quality. Comparison between the entropy method and the principal component analysis showed that the former is suitable as it showed a smaller deviation from the average than the latter one. Thus, the Jukryang reservoir showed the highest integrated soundness index, while the Songgo reservoir showed a lower index. Analysis of all reservoirs might help in establishing a rating system with absolute standards to provide grounds for agricultural reservoirs and diagnose the condition of reservoirs. [ABSTRACT FROM AUTHOR]

Recharge is a crucial section of water balance for both surface and subsurface models in water resource assessment. However, quantifying its spatiotemporal distribution at a regional scale poses a significant challenge. Empirical and numerical modeling are the most commonly used methods at the watershed scales. However, integrated models inherently contain a vast number of unknowns and uncertainties, which can limit their accuracy and reliability. In this work, we have proposed integrated SWAT-MODFLOW and Transient Water Table Fluctuation Method (TWTFM) to evaluate the spatiotemporal distribution of groundwater recharge in Anyang watershed, South Korea. Since TWTFM also uses SWAT model percolation output data, calibration was performed for individual models and a coupled model. The coupled model was calibrated using daily streamflow and hydraulic head. The SWAT-MODFLOW model performed well during the simulation of streamflow compared to the SWAT model. The study output showed that the study watershed had significant groundwater recharge variations during the simulated period. A significant amount of recharge happens in the wet season. It contributes a significant amount of the average annual precipitation of the region. The direct flow components (surface and lateral) showed significant contributions when the water balance components were evaluated in the region. TWTFM showed a glimpse to estimate recharge, which requires representative monitoring wells in the study region. Comprehensively, the SWAT-MODFLOW model estimated groundwater recharge with reasonable accuracy in the region. [ABSTRACT FROM AUTHOR]

We investigated the changes of main climate factors and their relationships with the catches of offshore fisheries of the Republic of Korea over the past 30 years (1981 to 2010), using a trend analysis and Pearson's correlation analysis. This study focused on seven fish species that have been preferred in Korean cuisine for centuries. Not only the air temperature, but also the sea surface temperature (SST) on the coast of Korea has risen (p < 0.05) in the period. The rise in SST over 30 years is significantly correlated with the rise in temperature (p < 0.01), but not with precipitation. Over the past 30 years, catches of anchovies and squid have increased significantly, while Alaska/walleye pollock has become almost extinct (p < 0.01). The analysis of this study indicates that cold water fish species have decreased or disappeared in Korean fisheries and have been replaced by warm water fish species. Our findings suggest that the fish species caught in Korean offshore fisheries have changed due to climate change, especially global warming. These results also suggest that there may be a threat to the food security of Koreans, so it is necessary to take measures to protect this food resource. [ABSTRACT FROM AUTHOR]

We investigated the potential impact of observation error on the calibration performance of an integrated watershed model. A three-dimensional integrated model was constructed using HydroGeoSphere and applied to the Sabgyo watershed in South Korea to assess the groundwater–surface water interaction process. During the model calibration, three different weighting schemes that consider observation error variances were applied to the parameter estimation tool (PEST). The applied weighting schemes were compared with the results from stochastic models, in which observation errors from surface discharges were considered a random variable. Based on the calibrated model, the interactions between groundwater and surface water were predicted under different climate change scenarios (RCP). Comparisons of calibration performance between the different models showed that the observation-error-based weighting schemes contributed to an improvement in the model parameterization. Analysis of the exchange flux between groundwater and surface water highlighted the significance of groundwater in delaying the hydrological response of integrated water systems. Predictions based on different RCP scenarios suggested the increasing role of groundwater in watershed dynamics. We concluded that the comparison of different weighting schemes for the determination of error covariance could contribute to an improved characterization of watershed processes and reduce the model uncertainty arising from observation errors. [ABSTRACT FROM AUTHOR]

South Korea's National Institute of Environmental Research (NIER) operates an algae alert system to monitor water quality at public water supply source sites. Accurate prediction of dominant harmful cyanobacterial genera, such as Aphanizomenon, Anabaena, Oscillatoria, and Microcystis, is crucial for managing water source contamination risks. This study utilized data collected between January 2017 and December 2022 from Juam Lake and Tamjin Lake, which are representative water supply source sites at the Yeongsan River and Seomjin River basins. We performed an exploratory data analysis on the monitored water quality parameters to understand overall fluctuations. Using data from 2017 to 2021 as training data and 2022 data as test data, we compared the dominant algal classification accuracy of 11 statistical machine learning algorithms. The results indicated that the optimal algorithm varied depending on the survey site and evaluation criteria, highlighting the unique environmental characteristics of each site. By predicting dominant algae in advance, stakeholders can better prepare for water source contamination accidents. Our findings demonstrate the applicability of machine learning algorithms as efficient tools for managing water quality in water supply source systems using monitoring data. [ABSTRACT FROM AUTHOR]

Perfluoroalkyl substances (PFASs) in shallow groundwater are increasingly being studied due to the global occurrence, environment persistence, bioaccumulation, and potential human health risk. In this research, 16 PFAS (11 perfluorinated carboxylic acids and 5 perfluorinated sulfonic acids) concentrations in groundwater were quantified to obtain information on geographical distribution and PFAS detection pattern for 4 years in South Korea. In the results, groundwater PFAS concentration ranged from non-detectable to average 45.2 ng/L (sum of PFASs). The major PFAS compounds were perfluorooctanoic acid (PFOA), perfluoropentanoic acid (PFPeA), perfluorohexanoic acid (PFHxA), perfluorohexane sulfonate (PFHxS), and perfluorooctane sulfonate (PFOS). The short chain (C < 8) PFASs were more prevalent than long chain (C > 8) PFASs in shallow groundwater. However, the detection patterns of 15 PFASs were different for each aquifer. Subsequently, through a health risk assessment, a non-carcinogenic risk level through ingestion, inhalation, and dermal contact for PFOA and PFOS was determined at 10−1, and it presents the need for PFAS management of groundwater. [ABSTRACT FROM AUTHOR]

Groundwater salinization in coastal aquifers because of seawater intrusion has raised serious concerns worldwide since it deteriorates the quality of drinking water and thereby threatens sustainable economic development. In particular, this problem has been a cause of growing concern in the western coastal regions of South Korea. In this paper, we review studies of seawater intrusion in western coastal regions of South Korea conducted over the past 20 years, particularly focusing on studies reported in international journals. We summarize the study locations, methods used, and major findings from individual and regional-scale studies. General methods used to identify and interpret seawater intrusion and subsequent geochemical processes are also presented. On the basis of insights gleaned from the previous studies, future research needs are discussed. [ABSTRACT FROM AUTHOR]

A Transient Storage Model (TSM), which considers the storage exchange process that induces an abnormal mixing phenomenon, has been widely used to analyze solute transport in natural rivers. The primary step in applying TSM is a calibration of four key parameters: flow zone dispersion coefficient ( K f ), main flow zone area ( A f ), storage zone area ( A s ), and storage exchange rate (α); by fitting the measured Breakthrough Curves (BTCs). In this study, to overcome the costly tracer tests necessary for parameter calibration, two dimensionless empirical models were derived to estimate TSM parameters, using multi-gene genetic programming (MGGP) and principal components regression (PCR). A total of 128 datasets with complete variables from 14 published papers were chosen from an extensive meta-analysis and were applied to derivations. The performance comparison revealed that the MGGP-based equations yielded superior prediction results. According to TSM analysis of field experiment data from Cheongmi Creek, South Korea, although all assessed empirical equations produced acceptable BTCs, the MGGP model was superior to the other models in parameter values. The predicted BTCs obtained by the empirical models in some highly complicated reaches were biased due to misprediction of A f . Sensitivity analyses of MGGP models showed that the sinuosity is the most influential factor in K f , while A f , A s , and α , are more sensitive to U / U * . This study proves that the MGGP-based model can be used for economic TSM analysis, thus providing an alternative option to direct calibration and the inverse modeling initial parameters. [ABSTRACT FROM AUTHOR]

This paper reviews a conceptual rainfall-runoff model called Tank which has been widely used over the last 20 years in Korea as a part of a water resource modelling framework for assessing and developing long-term water resource polices. In order to examine the uncertainty of model predictions and the sensitivity of model's parameters, Monte Carlos and Markov chain-based approaches are applied to five catchments of various Korean geographical and climatic conditions where the catchment sizes are ranged from 83 to 4786 km2. In addition, three optimization algorithms—dynamically dimensioned search (DDS), robust parameter estimation (ROPE), and shuffled complex evolution (SCE)—are selected to test whether the model parameters can be optimized consistently within a narrower range than the uncertainty bounds. From the uncertainty analysis, it is found that there is limited success in refining the priori distributions of the model parameters, indicating there is a high degree of equifinality for some parameters or at least there are large numbers of parameter combinations leading to good solutions within model's uncertainty bounds. Out of the three optimization algorithms, SCE meets the criteria of the consistency best. It is also found that there are still some parameters that even the SCE method struggles to refine the priori distributions. It means that their contribution to model results is minimal and can take a value within a reasonable range. It suggests that the model may be reconceptualized to be parsimonious and to rationalize some parameters without affecting model's capacity to replicate historical flow characteristics. Cross-validation indicates that sensitive parameters to catchment characteristics can be transferred when geophysical similarity exists between two catchments. Regionalization can be further improved by using a regression or geophysical similarity-based approach to transfer model parameters to ungauged catchments. It may be beneficial to categorize the model parameters depending on the level of their sensitivities, and a different approach to each category may be applied to regionalize the calibrated parameters. [ABSTRACT FROM AUTHOR]

Water transmission pipelines, which transport bulk water into storage facilities, usually have a tree-type configuration with large dimensions; thus, the breakage of a pipeline may cause a catastrophic service interruption to customers. Although drain efficiency is closely related to the number of washout and control valves and their locations, there is no useful guideline. This paper proposes a valve locating method by introducing numerical analyses to enumerate drainage time and zone. A time integration method, combined with the Newton–Raphson algorithm, is suggested to resolve drainage time, while considering the friction loss in gravitational flow. A drain direction matrix, which shows drain direction and coverage, is derived using a network searching algorithm. Furthermore, a feasible practical approach is presented by introducing a critical horizontal slope, a major washout valve, drainage indices, and control valve embedment. The developed method is first applied to simple pipes to validate the drainage time module. Subsequently, the model is expanded to the CY transmission line, which is one of the BR water supply systems in South Korea currently in operation. The results reveal that three drain valve locations have been neglected, and the addition of control valves guarantees consistent drain time below the operational criteria. [ABSTRACT FROM AUTHOR]

This research covers existing planning theory and possible ways to improve the decision-making process in Korean stream restoration. First, it attempts to recognize what extent the Korean stream restoration case follows Western environmental decision-making models. Additionally, key concepts and factors of environmental decision-making are discussed to build a foundation of planning theory. This research reveals key works in the broad and changing field of stream restoration that provides the foundation for understanding Korean water resource planning. To recognize the challenges and achievements of this planning, this paper first notes that, while technical perspectives of the engineering field have historically dominated stream restoration, current thinking recognizes the much greater complexity of stream restoration requires more than only engineering perspectives. After reviewing the literature in related areas, this research considers what the planning field has to offer. In the conclusion, this author argues that the application of citizen-oriented decision-making approaches could lead to better water resource management. Admittedly, this may still be hindered by political uncertainty and power conflicts caused by science-dominant environmental planning. [ABSTRACT FROM AUTHOR]

Estimating the groundwater recharge rate is essential in all groundwater-related fields, including groundwater development, use, management, modeling, and contamination analysis. In this study, we proposed a combined method of water budget and climate change scenario for estimating the net groundwater recharge rate in the Nakdong River watershed (NRW), South Korea. For the climate change scenario method, the representative concentration pathway (RCP) 4.5 and 8.5 climate scenarios were adopted. First, using the water budget method from 2009 to 2018, the net groundwater recharge rate (NGRR) of 12.15–18.10% relative to annual precipitation (AP) was obtained, subtracting direct runoff (DR) of 21.18–25.32% relative to AP, evapotranspiration (EP) of 40.53–52.29% relative to AP, and baseflow of 12.42–17.84% relative to AP, from the AP (865–1494 mm). The average annual NGRR of the NRW was 200 mm (15.59%). Second, the mean NGRRs from 2009 to 2100 under the RCP 4.5 and RCP 8.5 scenarios were anticipated as 8.73% and 7.63%, respectively. The similarity between the water budget and climate change scenarios was confirmed using data from 2009 and 2018. According to the simple climate change scenario, it is predicted that annual precipitation will increase over the years while the groundwater level and net groundwater recharge rate will decrease. Nonetheless, the estimated NGRR by the water budget method in this study possesses uncertainty due to using potential ET instead of actual ET which should be estimated by considering soil water content. [ABSTRACT FROM AUTHOR]

This study determined the PAH contamination variations in the subtidal surface sediment with oil fingerprinting in the Wu Yi San oil spill in Yeosu, Korea, in January 2014. The ∑16 PAHs and ∑alkyl PAHs were investigated in surface sediment and seawater 1 month after the oil spill for 1 year at 3-month intervals in the accident (St. A-F) and adjacent areas (St. 1-20). The averaged ∑16 PAHs and ∑alkyl PAH concentration in the five samplings were 42.2–171.7 ng/g and 211.5–221.8 ng/g, respectively. Comparing the PAH levels in St.E and St.17 indicated a decreased tendency, from 357.9 to 31.1 ng/g dw. in ∑16 PAHs, and from 1900.9 to 211.5 ng/g dw. in ∑alkyl PAHs. The PAHs were not statically correlated between surface sediment and seawater (p > 0.05), implying that the fate of PAHs was rapidly dispersed toward adjacent coasts and beaches. Pyrogenic origin was predominant in 16 PAHs, and petrogenic origin in alkylated PAHs. Notably, C2-D/C2-P and C3-D/C3-P ratios in the accident area during the first sampling were similar to accident oil, but the similarity was not shown in other samplings. Only the C2-naphthalene (St.A), C1-phenanthrene (St.A and St.B), and C2-phenanthrene (the entire accident area points) concentrations were higher than the ERL SQG. [ABSTRACT FROM AUTHOR]

Algal blooms have been observed worldwide and have had a serious impact on industries that use water resources, which is a problem for people and the environment. For this reason, an algae warning system is used to count the number of cyanobacterial cells and the concentration of chlorophyll-a. Several studies using multispectral or hyperspectral data to estimate chlorophyll concentration have recently been carried out. In the present study, a comparative approach was applied to estimate the concentration of chlorophyll-a at Paldang Dam, South Korea using hyperspectral data. We developed a framework for estimating chlorophyll-a using dimension reduction methods, such as principal component analysis and partial least squares, and various machine learning algorithms. We analyzed hyperspectral data collected during a field survey to locate peaks in the chlorophyll-a spectrum. The framework that used support vector regression achieved the highest R2 of 0.99, a mean square error (MSE) of 1.299 μg/cm3, and showed a small discrepancy between observed and real values relative to other frameworks. These findings suggest that by combining hyperspectral data with dimension reduction and a machine learning algorithm, it is possible to provide an accurate estimation of chlorophyll-a. Using this, chlorophyll-a can be obtained in real time through hyperspectral sensor data input from drones or unmanned aerial vehicles using the learned machine learning algorithm. [ABSTRACT FROM AUTHOR]

South Korea currently lacks a real-time monitoring and anomaly detection system for detecting continuous tap water quality changes from the water source to faucet and pre-diagnosing hazards that threaten tap water safety. In this study, we constructed an accurate water quality prediction model that could comprehensively cover all water treatment facilities supplying tap water nationwide and verified the model using an integrated approach. To address the uncertainty of continuously changing water quality, we collected five years (2017–2021) of hourly water quality data from 33 large water purification plants and applied various deep learning techniques to construct an optimal prediction model. We repeated water quality prediction and evaluation over the following 24 h through a time series cross-validation of an untrained dataset of the previous five months. The optimized deep learning model achieved average and maximum prediction accuracy of 98.78 and 99.98%, respectively, and showed excellent performance in terms of the root mean squared error (0.0006), mean absolute error (0.0003), and Nash–Sutcliffe efficiency (0.9894). Thus, deep learning technology greatly improved the accuracy and efficiency of water quality prediction. The proposed model could provide prompt and accurate water quality information for large-scale water supply facilities nationwide and improve public health through the early diagnosis of water quality anomalies. [ABSTRACT FROM AUTHOR]

A sand dam is an old technology used to trap sand materials and store water in dry riverbeds. Besides the volume of sand stored, the water storage and supply capacity of the sand dam depends principally on material properties including hydraulic conductivity (K) and the specific yield (Sy). In this study, the water supply capacity of a sand dam, applied in South Korea with a modified scheme, was analyzed. Imported sand materials were placed in three layers, and perforated drain pipes were installed to abstract the water to a collection tank. Using a Modular Finite-Difference Groundwater Flow (MODFLOW) model, the drain pipe discharge related to aquifer properties and supply capacity of a sand dam was evaluated. Using the model, the productivity of the sand storage with several cases of inflow conditions was assessed. For the period from 9 March 2020 to 16 May 2022, the results of calculation of water supply for the installation and operation of new sand dam are as follows. Regarding the actual inflow condition, compared to the average water supply of the existing water intake source, the sand dam installation increased water supply by 61.6%, and the sand dam installation showed an effect of improving the water supply by 36.0% for the minimum water supply. The calculated water supply for the condition where the inflow was reduced by 50% showed an effect of improving water supply by over 70% on average due to the installation of the sand dam. The findings would be a benchmark for future expansions of the scheme in related places, and management and maintenance of the system. [ABSTRACT FROM AUTHOR]

This paper proposes a new approach to consider the uncertainties for constructing flood hazard maps for levee failure. The flood depth, velocity, and arrival time were estimated by the 2-Dimensional model and were considered as flood indices for flood hazard mapping. Each flood index predicted from the 2-D flood analysis based on several scenarios was fuzzified to reflect the uncertainties of the indices. The fuzzified flood indices were integrated using the Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), resulting in a single graded flood hazard map. This methodology was applied to the Gam river in South Korea and confirmed that the Fuzzy MCDM (Multiple Criteria Decision Making) technique can be used to produce flood hazard maps. The flood hazard map produced in this study compared with the current flood hazard map of MOLIT (Ministry of Land, Infrastructure and Transports). This study found that the proposed methodology was more advantageous than the current methods with regard to the accuracy and grading of the flood areas, as well as in regard to an integrated single map. This report is expected to be expand upon other floods, including dam failure and urban flooding. [ABSTRACT FROM AUTHOR]

In this study, the distribution of giant N. jellyfish by the echo counting method was investigated in the East China Sea, where giant N. jellyfish are known to breed and migrate to the coastal waters of Korea mainly in summer. In addition, the distribution densities by the survey method were compared with the sighting and trawl surveys. In the case of the East China Sea area and the Gijang coastal area, a split beam type scientific echosounder (EK60, Simrad, Norway) and Acoustic data at 38 and 120 kHz were collected while moving at 6–7 kts. In the coastal waters of Korea, acoustics data at 38 and 120 kHz were collected with a split beam type scientific echosounder (EK80, Simrad, Norway) attached to the bottom of the R/V Tamgu No. 21. In the East China Sea, the average distribution densities of acoustic, sighting, and trawl surveys were 8355.7 (10−6 ind/m3), 162.2 (10−6 ind/m3), and 792.5 (10−6 ind/m3), respectively. The average densities in the coastal waters of Korea of acoustic, sighting, and trawl surveys were 2238.7 (10−6 ind/m3), 664.9 (10−6 ind/m3), and 432.9 (10−6 ind/m3), respectively. The average distribution density of the acoustic survey conducted on 21 July 2020 in the coastal waters of Gijang was 1024.5 (10−6 ind/m3), and the sighting survey showed 48.8 (10−6 ind/m3). The sighting surveys conducted on 22 July 2020 were 393.3 (10−6 ind/m3) and 19.6 (10−6 ind/m3). The average distribution density for the acoustic survey performed on 23 July 2020 was 99.0 (10−6 ind/m3), and for the sighting survey was 197.2 (10−6 ind/m3). When comparing the results of the acoustic survey with the results of the sighting and the trawl surveys, all surveys except for the survey conducted on 23 July 2020 showed that the acoustic survey was higher than other survey methods. [ABSTRACT FROM AUTHOR]