A Comparison Study of Runoff Characteristics of Non-Point Source Pollution from Three Watersheds in South Korea

Critical review on toxic contaminants in surface water ecosystem: sources, monitoring, and its impact on human health

Surface water pollution is a critical and urgent global issue that demands immediate attention. Surface water plays a crucial role in supporting and sustaining life on the earth, but unfortunately, till now, we have less understanding of its spatial and temporal dynamics of discharge and storage variations at a global level. The contamination of surface water arises from various sources, classified into point and non-point sources. Point sources are specific, identifiable origins of pollution that release pollutants directly into water bodies through pipes or channels, allowing for easier identification and management, e.g., industrial discharges, sewage treatment plants, and landfills. However, non-point sources originate from widespread activities across expansive areas and present challenges due to its diffuse nature and multiple pathways of contamination, e.g., agricultural runoff, urban storm water runoff, and atmospheric deposition. Excessive accumulation of heavy metals, persistent organic pollutants, pesticides, chlorination by-products, pharmaceutical products in surface water through different pathways threatens food quality and safety. As a result, there is an urgent need for developing and designing new tools for identifying and quantifying various environmental contaminants. In this context, chemical and biological sensors emerge as fascinating devices well-suited for various environmental applications. Numerous chemical and biological sensors, encompassing electrochemical, magnetic, microfluidic, and biosensors, have recently been invented by hydrological scientists for the detection of water pollutants. Furthermore, surface water contaminants are monitored through different sensors, proving their harmful effects on human health.

Investigation of microplastics in urban rivers of Eastern China in summer: abundance, characteristics and ecological risk assessment

Microplastics (MPs) are increasingly becoming recognized as worldwide environmental contaminants, exerting a substantial impact on the safety of city rivers. This study explored the abundance and characteristics of MPs in summer 2023, including June and August, representing plum rain and typhoon rain seasons. The Qinhuai River exhibits more spatial fluctuations in six sampling sites with average concentrations of 470 ± 119.56 items per L, and the abundance increases with the water flows in the river. Downstream had the highest MP abundance of 484 ± 121.34 items per L, which were positive with the concentration of suspended solids (SS). Transparent and green MPs were more even in the sampling sites, and the shapes of fragments were predominant in the summer. Interestingly, the proportion of fiber and small-sized (38-75 μm) microplastics was predominant in the plum rain seasons, while the percentage of large-sized (270-5000 μm) and polymers of PE occurred in the typhoon rain seasons. The index of hazard scores of plastic polymers (H) revealed that the studied river had a severe pollution level (IV), which was highly influenced by PVC and PC. Besides, the pollution load index PLI value of different rain seasons was slightly polluted (I), while the PLI in autumn rain seasons was relatively higher than that in other seasons due to the higher variance of MPs. Therefore, the ecological risk of microplastics of PVC and PC in the Qinhuai River during varying seasons should be seriously considered. Our research is expected to provide valuable assistance in improving the management of urban rivers.

Pollutant transport model with large time-scale and estimation of land-use export coefficients at a watershed level

The pollutant transport equilibrium in a watershed can be analyzed on a large time scale, and land-use export coefficients can be calculated directly under certain hydrologic and transport conditions, by ignoring hydrologic and transport processes at small space and time scales on hydrologic response units. In this study, the water environment system of a watershed was deconstructed into three parts (source, source-sink, and runoff transport) to construct a pollutant transportation equilibrium model on a large time scale. A watershed with an annual source-sink accumulation of zero was defined as a completely transported watershed; therefore, we derived a completely transported equilibrium equation. The problem of seeking the land export coefficient was converted into a problem of seeking the optimal solution of linear programming, which can be estimated according to the variation in pollutant output processes. The feasibility of the solution can be analyzed using multi-year stochastic rainfall processes. The model was used to analyze the transport equilibrium of chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) upstream of the monitored cross-sections in a watershed, which covered 3145.66 km2. The land export coefficients were calculated according to the model. The model calculations indicated that the watershed was completely transported during perennial years. The calculated export coefficients of COD, TN, and TP for farmland, primary vegetation, and urban land were within the range of general empirical values. The calculated maximum accumulations of COD, TN, and TP were 0.19 × 107, 0.063 × 107, and 0.049 × 106 kg, respectively, for perennial rainfall. PRACTITIONER POINTS: A completely transported watershed was defined, and a model of pollutant transportation equilibrium with large time-scale was constructed. A problem of seeking the optimal solution of a linear programming was designed to estimate the land export coefficient of COD, TN, and TP. The runoff transport and accumulation processes of COD, TN, and TP in a watershed was analyzed.

1 to 1000 Policy: Controlling Phosphorous Pollution from Tea Farms with Bioretention Cells

When implementing nonpoint source pollution control plans, the size or number of required controlling facilities is a very practical issue. However, quantifying nonpoint source pollution is difficult because it is generated by variable and random rainfall events. This study develops a two-stage optimization process to demonstrate the determination of the optimal bioretention cell size for tea farm pollution control. The optimization process was based on a verified watershed-scale model and a verified site-scale model. The verified watershed model was used to obtain total phosphorous (TP) reduction loads. Once the goal of watershed management was decided, the reduction loads were then allocated and the unit reduction loads were determined. Using the unit reduction loads, the verified tea farm model was used to assess the optimal bioretention cell size for tea farms. A case study using the Jinggualiao stream in the Feitsui Reservoir watershed, Taipei, Taiwan was presented. The results showed that the unit tea farm TP reduction loads were 270 g/ha-year and 326 g/ha-year to reach two water quality goals, and a total of 350 m2 and 600 m2 of bioretention cells were needed, respectively. A 1 to 1000 ratio of the standard bioretention cell area to the tea farm area is recommended as a general control rule.

Dynamization of Urban Runoff Pollution and Quantity

At present, the annual loads from long-term series simulations are mostly used for the evaluation of rainwater management and treatment measures although the relevance of the temporal distribution of both pollution and quantity has a recognizable influence on the performance of the treatment. With the idea of dynamizing the simulation output values in relation to (i) single rainfall events, (ii) specific catchment characteristics, and (iii) the duration of the dry period between two rainfall events measurement devices and scenario studies were established in a joint research project in Lower Saxony. First measurement results of surface runoff qualities of an urban sub-catchment in Braunschweig/Germany are presented in a high temporal definition for several pollution parameters. A correlation analysis was performed identifying additional explanatory parameters that have an influence on the first flush effect, such as rainfall characteristics or antecedent dry period. First calculations of the possible reduction in the decentralized storm water treatment by disconnecting the first flush showed values of 42–65%, depending on the pollution parameters. The comparative evaluation of the data with different statistical methods shows that the uncertainties in the calculation of rainwater pollution, or the duration of the first flush, are still very high and do not yet allow researchers to derive a pollution forecast for, e.g., a throttle control solely from the recording of the rain and area characteristics.

An Urban Water Pollution Model for Wuhu City

An in-depth study of the temporal and spatial distribution of pollution loads can assist in the development of water pollution remediation. The research scope of this paper was the highly developed Wuhu City located south of the Yangtze River. Chemical oxygen demand (COD), NH3-H, and total phosphorus (TP) were chosen as the pollutant research objects of this study. Then, by combining the natural and social conditions within the scope of the study, a balanced system of pollution load generation and migration was described. A pollution load model of Wuhu City based on Load Calculator, MIKE 11, and ArcGIS was established. The results indicate that, in terms of the time distribution, the changes in the influx of the different pollutants were consistent. In terms of the spatial distribution, the major contributions to the annual pollution load were domestic pollution, urban surface runoff pollution, and poultry breeding pollution. The major contributors to the annual pollution load into the river were domestic pollution, urban surface runoff pollution, and sewage plant tail water pollution. This analysis provides references for the comprehensive management of local water environments.

Assessment of Pollutants from Diffuse Pollution through the Correlation between Rainfall and Runoff Characteristics Using EMC and First Flush Analysis

Urban stormwater runoff is an important source of pollution in receiving water bodies, mainly in cities in development. However, strategies to deal with the impacts caused by the runoff discharges, such as implementing a sustainable urban drainage system (SUDS) with optimized management, need information usually obtained through monitoring studies. Brasília is a city that has one of the highest urban growth rates in Brazil, with significant impacts on urban water resources, including diffuse pollution, generated by new unregulated urban developments that initially start being built with precarious sanitation infrastructure. The Vicente Pires (VP) watershed is highly urbanized and comprises two areas that have been intensively occupied more recently, at a fast pace, and do not have yet basic sanitation systems fully implemented. Stormwater quality at the outlet of the VP watershed was analyzed by monitoring the rainfall, runoff flows, and pollutant concentration. Event Mean Concentration (EMC) and first-flush (FF) phenomenon were calculated, and hydrologic characteristics were compared for different events through correlation analysis. During dry periods the flow varied between 0.5 and 1.29 m3/s, while in flood periods the maximum value was 72.17 m3/s, forming floods with great volume. Nitrate during dry periods stands out with its high concentration; the maximum was 1.49 mg/L, while the maximum concentration during the flood events was 0.43 mg/L, probably due to dilution. Ammonia results showed very low values, probably because nitrification is occurring up to the collection point. The EMC values of solids in flood events were higher and can be attributed to river bed scour along the VP watershed. The EMC SS values for the VP watershed are also similar to areas in the initial stages of building development. The EMC values in the dry season indicate strong correlations between some water quality parameters such as NH+3-N and SS, TS and NO−3-N; NO−3-N, and COD. These correlations indicate that these pollutants are probably being generated by the same source, probably sewage discharges. During flood events, the correlation between pollutant loads and peak flow can be associated with the scouring during surface washing off, because greater concentrations of solids and organic matter occur in events with greater flow rates. For the first 30% of the initial runoff volume, about 29% of SS, 38% of NH+3-N, and 35% of reactive P were carried during flood events. It was verified that large values of maximum or mean rainfall intensity are related to the occurrence of First Flush (FF) for most pollutants. Antecedent dry days (ADD) did not influence build-up processes in this watershed; however, they are related to FF occurrence. Data indicate that the sewage and stormwater collection networks were being installed caused a high impact on observed water quality, with high concentrations of solids during flood events. On the other hand, the wastewater collection after the sewer network installation led to a decrease in COD concentrations over time. For sustainable management of diffuse pollution, the adoption of distributed SUDS to enhance runoff volume reduction is a recommended solution for the case.

Organics removal and microbial interaction attributes of zeolite and ceramsite assisted bioretention system in copper-contaminated stormwater treatment

Bioretention has been increasingly used recently to treat heavy metals contaminated stormwater. However, less is known about how metal accumulation influences microbial performance and organics removal mechanisms in different layers of the bioretention system. Two lab-scale bioretention columns (i.e., control and Cu treatment) were designed and filled with soil and fillers (zeolite and ceramsite). The results obtained from the time-series experiment of 121 days showed that the removal of organics markedly affected by Cu accumulation and microbial activities, varied between soil and filler layers of bioretention system. The overall organics removal rate was higher in filler than soil. However, at the individual level, the chemical oxygen demand (COD) removal rate was higher than total organic carbon (TOC) in the soil, while the opposite trend was observed in fillers. Mixed media (soil + fillers) significantly reduced the bio-available and labile fractions of Cu from 33.5 to 8% and 67.5 to 33.4%, respectively. The bioretention column treated with Cu lost 14% more microbial biomass in soil than filler over the 121 days study period. Therefore mixed media in bioretention system can offset the substantial negative impacts of long-term metal accumulation on pollutant removal and microbial degradation function in the bioretention. The present study advanced our understanding to resolve the complex metals-impacted microbial pollutant biodegradation mechanisms and highlight importance of mixed media in the long-term maintenance of the bioretention system, which is imperative for developing effective and stormwater-specific remediation strategies.

Prediction of Water Level and Water Quality Using a CNN-LSTM Combined Deep Learning Approach

A Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM) combined with a deep learning approach was created by combining CNN and LSTM networks simulated water quality including total nitrogen, total phosphorous, and total organic carbon. Water level and water quality data in the Nakdong river basin were collected from the Water Resources Management Information System (WAMIS) and the Real-Time Water Quality Information, respectively. The rainfall radar image and operation information of estuary barrage were also collected from the Korea Meteorological Administration. In this study, CNN was used to simulate the water level and LSTM used for water quality. The entire simulation period was 1 January 2016–16 November 2017 and divided into two parts: (1) calibration (1 January 2016–1 March 2017); and (2) validation (2 March 2017–16 November 2017). This study revealed that the performances of both of the CNN and LSTM models were in the “very good” range with above the Nash–Sutcliffe efficiency value of 0.75 and that those models well represented the temporal variations of the pollutants in Nakdong river basin (NRB). It is concluded that the proposed approach in this study can be useful to accurately simulate the water level and water quality.

Effects of lead (Pb) in stormwater runoff on the microbial characteristics and organics removal in bioretention systems

Bioretention systems have been proved to be a natural approach for effectively reducing stormwater runoff pollution loads. However, the effects of heavy metals in stormwater runoff on microbial characteristics and organics removal in bioretention systems are unclear. In this study, two lab scale bioretention columns including the control and lead (Pb) treatment with the soil and filler layer were established. The changes of organic matter and lead in the effluent water and the soil (or fillers) were monitored during 121 operation days. The soil (or fillers) microbial characteristics were also analyzed. The results showed that most of Pb was intercepted by soil, while a small amount accumulated in fillers after 121 days. The long-term Pb accumulation in the biorentention system negatively affected the microbial biomass and microbial activity, while positively affected the community diversity. Pb accumulation killed some microorganisms, but simultaneously stimulated the growth of some Pb-tolerance microorganisms. The abundance of bacteria with COD degradation function in soil layer decreased, while that in fillers increased, indicating the effect of Pb on the community structure of these two layers was different. The COD removal in the soil and filler layer was promoted and inhibited by Pb contamination respectively. Moreover, Pb affected the removal of organic matter by chelating organic matters and changing their composition. The results suggested that the long-term accumulation of heavy metals in bioretention system would affect microbial degradation function and pollutants removal, causing our concern for the long-term maintenance of the bioretention system.

Performance Assessment of Sub-Daily and Daily Precipitation Estimates Derived from GPM and GSMaP Products over an Arid Environment

Precipitation is a critical variable for comprehending various climate-related research, such as water resources management, flash flood monitoring and forecasting, climatic analyses, and hydrogeological studies, etc. Here, our objective was to evaluate the rainfall estimates obtained from Global Precipitation Mission (GPM), and Global Satellite Mapping of Precipitation (GSMaP) constellation over an arid environment like the Sultanate of Oman that is characterized by a complex topography and extremely variable rainfall patterns. Global Satellite-based Precipitation Estimates (GSPEs) can provide wide coverage and high spatial and temporal resolutions, but evaluating their accuracy is a mandatory step before involving them in different hydrological applications. In this paper, the reliability of the Integrated Multi-satellitE Retrievals for the GPM (IMERG) V04 and GSMaP V06 products were evaluated using the reference in-situ rain gauges at sub-daily (e.g., 6, 12, and 18 h) and daily time scales during the period of March 2014–December 2016. A set of continuous difference statistical indices (e.g., mean absolute difference, root mean square error, mean difference, and unconditional bias), and categorical metrics (e.g., probability of detection, critical success index, false alarm ratio, and frequency bias index) were used to evaluate recorded precipitation occurrences. The results showed that the five GSPEs could generally delineate the spatial and temporal patterns of rainfall while they might have over- and under-estimations of in-situ gauge measurements. The overall quality of the GSMaP runs was superior to the IMERG products; however, it also encountered an exaggeration in case of light rain and an underestimation for heavy rain. The effects of the gauge calibration algorithm (GCA) used in the final IMERG (IMERG-F) were investigated by comparison with early and late runs. The IMERG-F V04 product did not show a significant improvement over the early (i.e., after 4 h of rainfall observations) and late (i.e., after 12 h of rainfall observations) products. The results indicated that GCA could not reduce the missed precipitation records considerably.