Tracking nitrate sources in agricultural-urban watershed using dual stable isotope and Bayesian mixing model approach: Considering N transformation by Lagrangian sampling.

A dual isotopes approach and the Bayesian isotope mixing model were applied to trace nitrogen pollution sources and to quantify their relative contribution to river water quality. We focused on two points to enhance the applicability of the method: 1) Direct measurement on the end-members to distinguish "sewage" and "manure" which used to be grouped in one pollution source as their isotope ranges overlap; 2) The Lagrangian sampling method was applied to consider the transport of nitrogen pollutants in a long river so that any fractionation process can be dealt with in the given Bayesian modeling framework. The results of the analysis confirmed the NO3- isotope composition in the river of interest to be within the range of NO3- with origins in "NH4+ in fertilizer", "Soil N", and "Manure and sewage" pollution. This suggests that nitrogen pollution is mostly attributed to anthropogenic sources. The δ18O NO3 value follows the range +2.5∼+15.0‰, implying that NO3- in the river is mainly derived from nitrification, and possible nitrification in groundwater or waterfront other than surface water. The ratio of the concentration of δ15N NO3 to that of δ18O NO3, and the corresponding regression equation indicates that the denitrification effect in surface water was insignificant during the study period. From the results of the contribution ratio of each source, improving the water quality of the discharge from the sewage treatment plants was proved to be the key factor to reduce nitrogen pollution in the river.

Organic matter and heavy metal in river sediments of southwestern coastal Korea: Spatial distributions, pollution, and ecological risk assessment.

This study identifies the impact of river sediments on coastal ecosystems in the southwestern coastal region of Korea. Surface sediments were analyzed for their spatial distributions of organic matter, nutrients, and heavy metal concentrations. Furthermore, pollutants were identified according to the pollution load index (PLI) and potential ecological risk index (RI). Concentrations did not show serious pollution levels compared to generalized guidelines; however, some sites exceeded the PLI pollution standard, and were also identified as potential ecological risks. Through cluster analyses the sediment sites were classified into three groups: rivers with relatively high concentrations of organic matter and nutrients, rivers affected largely by artificial heavy metal pollution, and rivers with low levels of pollution by organic matter, nutrients, and heavy metals. It is evident that continuous monitoring and management are required to prevent major pollution from industrial complexes, agriculture, and commercial activities in the regions near these rivers.

Nitrogen Stimulates Microcystis-Dominated Blooms More than Phosphorus in River Conditions That Favor Non-Nitrogen-Fixing Genera.

Despite the implementation of intensive phosphorus reduction measures, periodic outbreaks of cyanobacterial blooms in large rivers remain a problem in Korea, raising the need for more effective solutions to reduce their occurrence. This study sought to evaluate whether phosphorus or nitrogen limitation is an effective approach to control cyanobacterial (Microcystis) blooms in river conditions that favor this non-nitrogen-fixing genus. These conditions include nutrient enrichment, high water temperature, and thermal stratification during summer. Mesocosm bioassays were conducted to investigate the limiting factors for cyanobacterial blooms in a river reach where severe Microcystis blooms occur annually. We evaluated the effect of five different nitrogen (3, 6, 9, 12, and 15 mg/L) and phosphorus (0.01, 0.02, 0.05, 0.1, and 0.2 mg/L) concentrations on algae growth. The results indicate that nitrogen treatments stimulated cyanobacteria (mostly Microcystis aeruginosa) more than phosphorus. Interestingly, phosphorus additions did not stimulate cyanobacteria, although it did stimulate Chlorophyceae and Bacillariophyceae. We conclude that phosphorus reduction might have suppressed the growth of Chlorophyceae and Bacillariophyceae more than that of cyanobacteria; therefore, nitrogen or at least both nitrogen and phosphorus control appears more effective than phosphorus reductions alone for reducing cyanobacteria in river conditions that are favorable for non-nitrogen-fixing genera.

Analysis of spatiotemporal variation in river water quality using clustering techniques: a case study in the Yeongsan River, Republic of Korea.

Herein, cluster analysis was applied to evaluate the spatiotemporal variations in water quality variables of a river. The analysis was performed using the data obtained from 15 monitoring stations during 2007-2018 in the Yeongsan River, Republic of Korea. The spatiotemporal analysis successfully clustered the annual water quality variables temporally into years of poor water quality (2007-2012) and good water quality (2013-2018), and spatially into stations observing bad water quality (midstream) and good water quality (upstream and downstream). For the spatial cluster analysis results before and after a large river engineering project, the water quality was grouped into four clusters according to regional effects and water pollutant sources. The clustering analysis results clearly reflected changes in the water quality along the river due to the project. Overall, this study demonstrates that cluster analysis can be effectively used for evaluating spatiotemporal variations in river water quality.