The present study evaluates the water quality of Dez River, a river 23 km long, via QUAL2Kw model, based on simulation of DO and BOD5 p98arameters, through considering water quality standards during six months in three stations of Kashefieh, Pole-Panjom, and Hamidabad. To determine the model’s validity and compare the observational data, the paper uses the square mean square error (RMES) and the squared mean square error coefficient (CV). The achieved results of the model largely indicate the actual conditions of the river, which represent the ability of QUAL2Kw model to simulate qualitative parameters. The main contamination of Dez River comes from municipal wastewater, either directly imported by river residents or collected by urban canals. It, then, enters the river at a certain point. Based on the simulation and observational results of DO at two stations of 5th and Hamidabad Bridge in all months of sampling, it is below 5 mg/L, regarded a threat to aquatic life. In addition, BOD5 parameter goes beyond 6 mg/L in Hamidabad station, being a threatening factor for aquatic life in this station. Critical conditions of Dez River, low discharge, and high loading of pollutants have increased the concentration of water quality parameters. Given the results of RMSE and CV parameters, the model has had the best conformity for DO parameter, followed by BOD5.

The idea of systems analysis and mathematical modeling for formulating and resolving river pollution issues is of relatively recent vintage and has been applied widely in the last 3 decades. The present study illustrates the utility of Beck-modified Khanna–Bhutiani model (BMKB) to determine the pollution load due to the presence of organic matter in River Ganga from its course from Devprayag to Roorkee through the holy city of India, Haridwar. The study was conducted over a period of 3 years between 2010 and 2013. The study was aimed to verify the BMKB model for River Ganga. This model was simulated and calibrated through the data obtained by model by comparing it with the field data observed manually. Paired T-test were performed for dissolved oxygen (DO) and biochemical oxygen demand (BOD) between the titrated value and modelled value to determine if there was any statistically significant difference between the means of respective values. The results of T-test revealed statistically significant difference between DO and BOD, i.e., DO t (11)= 3.819, P= 0.003, BOD t(11)= 14.635, P= 0.000. The model presented with a good agreement between the calibrated and observed data, thereby actualizing the validity of the proposed model.

Xiangjiang (XJ) is a typical urban inland river that serves as a drinking water source, which may be affected by the currently used organochlorine pesticides (CUOCPs) originating from agricultural activities in the vicinity. On this basis, this study comprehensively explored the occurrence and distribution characteristics of CUOCPs in surface water and sediments under long-term precipitation and subsequent floods. Considering the low concentration of CUOCPs in water, a technique combining high-throughput organic analysis with high-volume solid phase extraction (High-throat/Hi-volume SPE) was introduced for effective analysis of CUCOPs. The results showed that the concentration of CUOCPs in the water and sediments of XJ ranged from 2.33 to 6.40 ng L⁻¹ (average of 3.93 ± 1.15 ng L⁻¹) and from 1.52 to 21.2 ng g⁻¹ (average of 6.60 ± 4.31 ng g⁻¹ dw), respectively. The distribution of CUOCPs in water was consistent throughout XJ, but that in sediments was not uniform, indicating a stronger impact of floods on water than on sediments. Water-sediment partition coefficients were generally >2 L g⁻¹, showing a tendency of CUOCP dominance in sediments. The results of principal component analysis and cluster analysis showed that the occurrence of CUOCPs is significantly affected by exogenous disturbance, which could be flood events; meanwhile, clusters of CUOCPs were found in both water and sediments in the source-limited middle reaches in urban areas. Redundancy analysis (RDA) showed that CUOCP occurrences were not positively correlated with nutrient elements (nitrogen and phosphorus), but related to pH and dissolved oxygen (DO), indicating complex sources.

Dissolved inorganic nitrogen (DIN) is considered the main factor that induces eutrophication in water, and is readily influenced by hydrodynamic activities. In this study, a 4-year field investigation of nitrogen dynamics in a turbulent river was conducted, and a laboratory study was performed in the approximately homogeneous turbulence simulation system to investigate potential mechanisms involved in DIN transformation under turbulence. The field investigation revealed that, contrary to NO⁻₃ dynamics, the NH⁺₄ concentrations in water were lower in flood seasons than in drought seasons. Further laboratory results demonstrated that limitation of dissolved oxygen (DO) caused inactive nitrification and active denitrification in static river sediment. In contrast, the increased DO levels in turbulent river intensified the mineralization of organic nitrogen in sediment; moreover, ammonification and nitrification were activated, while denitrification was first activated and then depressed. Turbulence therefore decreased NH⁺₄ and NO⁻₂ concentrations, but increased NO⁻₃ and total DIN concentrations in the overlying water, causing the total DIN to increase from 0.4 mg/L to maximum of 1.0 and 1.7 mg/L at low and high turbulence, respectively. The DIN was maintained at 0.7 and 1.0 mg/L after the 30-day incubation under low and high turbulence intensities (ε) of 3.4 × 10⁻⁴ and 7.4 × 10⁻² m²/s³, respectively. These results highlight the critical role of DO in DIN budgets under hydrodynamic turbulence, and provide new insights into the DIN transport and transformation mechanisms in turbulent rivers.

Many estuaries have undergone severe saltwater intrusion in addition to simultaneously experiencing serious heavy metal pollution. To explore the effect of water density stratification associated with saltwater intrusion on the behaviour of heavy metals (Cr, Co, Ni, Cu, Zn, As, Pb, and Cd) in water and sediments, a field survey was conducted in a typical estuary (Modaomen). The content, distribution, and mobility of heavy metals were investigated, as well as the influence of environmental factors on their future. The results showed that Modaomen estuary was characterised by a notable variation in salinity along the estuary, presenting total freshwater upstream, high salinity stratification water in the mouth, and saltwater offshore. Dissolved metals presented a prominent gradient vertically, with 1.2–2.1 times higher in bottom water than in surface water and the highest contents in the highly–stratified bottom water. Elevated salinity and restricted mixing induced by water stratification were likely the causes of this outcome. The distribution of heavy metals in sediments was greatly governed by grain size, Fe/Mn (hydr)oxides, total organic carbon, salinity, and dissolved oxygen. Comprehensive evaluation, combined with total contents and chemical fractions of heavy metals, indicated that internal release from sediments contributed a considerable part to the higher levels of heavy metals in bottom water, particularly for Zn and Pb, which was fully consistent with their status in water body, and elevated salinity and lack of oxygen were likely the primary driving factors. During the phase-partition processes between bottom water and sediments, partitioning coefficients were markedly lower in the highly stratified zone, implying that saltwater intrusion facilitated the mobility and repartitioning processes of metals. Because of increased levels and toxicity of heavy metals in water and extended residence time during saltwater intrusion, the potential damage to the estuarine ecosystem should receive more attention.

Pesticides are widely used to alleviate pest pressure in agricultural systems, and atrazine is a typical diffuse pollutant and serves a sensitivity index for environmental characteristics. Based on the physicochemical properties of parent substances, degradation products of pesticides may pose a greater threat to aquatic ecosystems than pesticides. Atrazine and three primary degradation products (deethylatrazine (DEA), deisopropylatrazine (DIA) and didealkylatrazine (DDA)) were investigated in a semienclosed bay of the western Pacific Ocean. Seasonal surface water and suspended particulate sediment (SPS) samples were collected from the estuary and bay in January, April, and August 2019. The level of pesticide contamination was lower in the bay than in the estuary, and the pesticide concentration in the dissolved phase was higher than that in the adsorbed phase. The average concentrations of atrazine and the three degradation products in the three seasons ranged from 2.42 to 328.46 ng/L in water and from 0.07 to 12.75 ng/L in SPS. The proportion of atrazine among the four detected pollutants decreased from 0.7 to 0.1 in surface water and from 0.3 to 0.1 in SPS over the seasons. As the main degradation products, the concentration proportions of DDA and DEA reached as high as 0.6 in August. The ratio of DEA to atrazine (DEA/ATR) increased from January to August, which indicated the progressive degradation process in the bay. Single-factor analysis of variance and principal component analysis indicated that atrazine degradation was sensitive to temperature, dissolved oxygen, and salinity. These three factors accounted for almost 70% of the seasonal variance in atrazine without a quantification assessment of photolysis or bacteria. The spatial distributions of DEA in the three seasons demonstrated that wind and currents also played important roles in pollutant redistribution. The seasonal temporal and spatial correlations between water and SPS demonstrated the degradation patterns of atrazine in marine conditions, supporting the need for future detailed toxicity studies.

Microbial community in wastewater treatment plants (WWTPs) are affected by various environmental factors. The microbial communities from different WWTPs around world were compared by meta-analysis of the published high-throughput sequencing data of 16S rRNA of these WWTPs, the various environmental factors considered. Community richness indexes showed significant difference between altitude groups, and there was no latitudinal diversity gradient in WWTPs’ microbiomes. Climate was the most important influential factor and process was the second factor, and latitude and altitude contributed 5.51% and 4.78% of the overall variance of the data separately. Three significantly enriched bacterial communities in latitude and altitude respectively were showed by ternary plots. Mantel test illustrated that microbial community was strongly correlated with dissolved oxygen, temperature and pollutants concentrations. The prediction of potential functions revealed that microbial function structures were more stable than community structures. Some dominant bacteria in WWTPs have potential pathogenicity may pose serious threat to the environment and human health.

The Sürgü Stream, located in the Euphrates River basin of Turkey, is used for drinking water source, agricultural irrigation and rainbow trout production. Therefore, water quality of the stream is of great importance. In this study, multivariate statistical techniques (MSTs) and water quality index (WQI) were applied to assess water quality of the stream affected by multiple stressors such as untreated domestic sewage, effluents from fish farms, agricultural runoff and streambank erosion. For this, 16 water quality parameters at five sites along the stream were monitored monthly during one year. Most of parameters showed significant spatial variations, indicating the influence of anthropogenic activities. All parameters except TN (total nitrogen) showed significant seasonal differences due to high seasonality in WT (water temperature) and water flow. The spatial variations in the WQI were significant (p < 0.05) and the mean WQI values ranged from 87.6 to 95.3, indicating “good” to “excellent” water quality in the stream. Cluster analysis classified five sites into three groups, that is, clean region, low polluted region and very clean region. Stepwise temporal discriminant analysis (DA) identified that pH, WT, Cl⁻, SO₄²⁻, COD (chemical oxygen demand), TSS (total suspended solids) and Ca²⁺ are the parameters responsible for variations between seasons, and stepwise spatial DA identified that DO (dissolved oxygen), EC (electrical conductivity), NH₄–N, TN (total nitrogen) and TSS are the parameters responsible for variations between the regions. Principal component analysis/factor analysis revealed that the parameters responsible for water quality variations were mainly associated with suspended solids (both natural and anthropogenic), soluble salts (natural) and nutrients and organic matter (anthropogenic).

Reservoirs are lentic man-made waterbodies resulting from river damming processes. Pollutants coming from adjacent areas can accumulate in the water and sediment of these modified freshwater environments. Fish are often found in reservoirs occupying several trophic niches. Biochemical biomarkers are early warning signals of environmental disturbance to an organism. It is essential to understand how pollutants, abiotic variables and biochemical biomarker responses behave throughout the seasons to implement biomonitoring programs. Loricariichthys anus and Geophagus brasiliensis were collected, and abiotic variables were seasonally measured for one year, at six sampling sites in Passo Real reservoir, in a subtropical region of Southern Brazil. Biochemical biomarkers were analyzed in four tissues of both fish species, as well as metal and pesticide concentrations in the reservoir’s water and sediment. Redundancy analysis (RDA) was carried out to find the temporal relationship between biomarkers and environmental variables. RDA has clearly shown the separation of seasons for both species. Azoxystrobin, simazine and propoxur were the pesticides mostly contributing to the variation, whereas metals had lesser contribution to it. Seasonality appears to be the main factor explaining biomarkers’ variability. PERMANOVA has confirmed the effect of temperature and dissolved oxygen on biomarkers of both fish species. Thus, it is hard to differentiate if the fluctuation in biomarkers’ responses only reflects the normal state of organisms or it is a biological consequence from negative effects of fish exposure to several types of pollution (sewage, pesticides, and fertilizers) entering this aquatic system. In this study, to circumvent the seasonality issue on biomonitoring, the analysis of biomarkers on these fish should not be carried out in organs directly affected by temperature (such as liver and gills), or during reproduction periods (mainly in Spring).

Increasing indirect nitrous oxide (N₂O) emission from river networks as a result of enhanced human activities on landscapes has become a global issue, as N₂O has been widely recognized as an important ozone-depleting greenhouse gas. However, indirect N₂O emissions from different rivers, particularly for those that drain completely different landscapes, are poorly understood. Here, we investigated the spatial-temporal variability of N₂O emissions among the different rivers in the Chaohu Lake Basin of Eastern China. Our results showed that river reaches in urban watersheds are the hotspots of N₂O production, with a mean N₂O concentration of ∼410 nmol L⁻¹, which is 9–18 times greater than those mainly draining forested (23 nmol L⁻¹), agricultural (42 nmol L⁻¹) and mixed (45 nmol L⁻¹) landscapes. Riverine dissolved N₂O was generally supersaturated with respect to the atmosphere. Such N₂O saturation can best be explained by nitrogen availability, except for those in the forested watersheds, where dissolved oxygen is thought to be the primary predictor. The estimated N₂O fluxes in urban rivers reached ∼471 μmol m⁻² d⁻¹, a value of ∼22, 13, and 11 times that in forested, agricultural and mixed watersheds, respectively. Averaged riverine N₂O emission factors (EF₅ᵣ) of the forested, agricultural, urban and mixed watersheds were 0.066%, 0.12%, 0.95% and 0.16%, respectively, showing different deviations from the default EF₅ᵣ that released by IPCC in 2019. This points to a need for more field measurements with wider spatial coverage and finer frequency to further refine the EF₅ᵣ and to better reveal the mechanisms behind indirect N₂O emissions as influenced by watershed landscapes.