River Nitrate Research Articles

Intensive short-term sampling with long-term consequences: characterizing pollutant transport with implications for developing monitoring.

Riverine sampling of pollutants is commonly used to understand pollutants' transport pathways, relationships with hydrology, and overall presence in a waterbody. However, temporal gaps between sample collection introduce errors to these efforts, and guidance prescribing sampling frequency remains sparse. The magnitude of error often depends on a contaminant's transport mechanisms and local hydrologic conditions, making the creation of comprehensive sampling guidance difficult. This study analyzed a unique dataset that measured 18 analytes, including pesticides, nutrients, and pathogens, in three Iowa rivers for 90 consecutive days (May 4-August 1, 2000). This dataset provided a novel opportunity to relate pollutants to local hydrology and quantify errors associated with recurring sampling. Pesticide concentrations followed the spring flush phenomenon, where values were greatest during high streamflow in May and June but often depleted by July. Fecal coliform and total phosphorus (TP) also coincided with high flow, but unlike pesticides, their concentrations never diminished. Nitrate exhibited more complex behavior; concentrations were diluted during high flows and then increased as streamflow receded. Autocorrelations were significant for nitrate and atrazine in larger rivers but negligible for fecal coliform and TP. Loads were calculated for four pollutants with minimal non-detects (atrazine, fecal coliform, nitrate, and TP). We simulated intermittent sampling by selecting evenly spaced subsets of measured values to estimate loads, which were compared to the loads calculated using every daily sample to quantify error. This method typically overestimated nitrate loads but underestimated other pollutants, and errors often decreased in larger watersheds. Nitrate generally had the lowest error, while fecal coliform had the highest. We used these results to approximate the sampling frequency needed to bind errors within a certain threshold.

Effect of Eco-enzyme on Water Quality Parameters in Some Rivers Disembogued at Ambon Bay

Due to the increasing population in Ambon City, the high volume of organic waste in rivers that empties into Ambon Bay can impact the marine ecosystem. On the other hand, processing organic waste in the form of eco-enzymes has been widely applied and has benefits, for instance, as a cleaning liquid. This study aimed to analyze the effect of eco-enzyme concentrations on water quality parameters, such as pH, ammonia, detergent, coliform, nitrate, phosphate, BOD, COD, and DO in several rivers flowing into Ambon Bay. The research was conducted from May to November 2022. Water samples were collected from four rivers that flow into Ambon Bay. Production of ecoenzyme was carried out at the Marine Science Laboratory at Pattimura University for three months. Eco-enzyme derived from banana peels obtained from tourist areas on Ambon Island. The research applied the method of observation and experiment. The data of each parameter obtained from the treatments (sample before and after treatment using 10% and 20% of eco-enzyme) were then compared with Second-Class of River Water Quality Standards. The results showed that eco-enzyme could neutralize the pH value. The DO, ammonia, detergent and coliform concentration decreased after adding 10% and 20% of the eco-enzyme. By contrast, adding eco-enzyme to the river watercan increase the concentration of nitrate, phosphate, BOD, and COD.

Tracing nitrogen sources and transformation characteristics in a large basin with spatially heterogeneous pollution distribution

This study used dual stable isotopes to examine nitrate sources and geographical distribution in the Liao River Basin (LRB), one of China's seven major river basins. During a normal hydrological season in April 2021, water samples were taken from the main streams of the Liao River (MLR), Shuangtaizi River (STR), Hun River (HR), Taizi River (TZR), and Daliao River (DLR). Monitoring results indicated that 93% of the water samples had a total nitrogen level exceeding the Class IV limit (1.5 mg/L) of the ‘Environmental Quality Standards (EQS) for surface water’, indicating a serious nitrogen pollution status. 71.3% of the total nitrogen on average was in the form of nitrate. The scatterplots of δD-H2O and δ18O-H2O showed that water in TZR and DLR were mainly affected by precipitation, while MLR, STR and HR were additionally impacted by evaporation and groundwater. The overall δ15N and δ18O of NO3− varied from 7.7‰ to 17.9‰ and 0.6‰–11.2‰, respectively. The correlations between δ15N-NO3- and δ18O-NO3-, along with attribution results from the Bayesian isotopic mixing model, indicated a predominant role of manure/sewage (MS) pollution in affecting river nitrate, accounting for 78% of total nitrate in MLR and 72% in DLR. A positive correlation between δ15N-NO3- and δ18O-NO3- in MLR indicated the occurrence of denitrification process. Overall, attribution results showed that the primary nitrate sources varied in different river systems within such a large basin, mainly due to spatially varied land use and human activities. Tailored nitrogen management strategies should be implemented to address the main anthropogenic pressures.

Pollution, spatial distribution, and health risks assessment of nutrient concentration in surface water resources of Maroon-Jarahi Basin in southwestern Iran.

Nowadays, the introduction of nutrients caused by human activities is considered an environmental issue and a significant problem in river basins and coastal ecosystems. In this study, the concentration of nutrients ( and ) in the surface water sources of the Maroon-Jarahi watershed in the southwest of Iran was determined, and the pollution status and health risk assessment were done. The average concentration of nitrate and phosphate in Ludab, Maroon, Zard, Allah, Jarahi rivers, and Shadegan wetland were obtained at 2.25-0.59, 4.59-1.84, 4.07-2.02, 5.40-2.81, 11.51-4.67, 21.63 and 6.20 (mg/l), respectively. A comparison of the results with the World Health Organization (WHO) limit showed that nitrate was lower than in all stations, but phosphate was higher than the limit in some stations of the Maroon, Allah, Jarahi rivers, and Shadegan wetland. Calculation of linear regression analysis showed significant positive relationships between nitrate and phosphate in all surface water sources (except Ludab) and based on the N/P ratio, nitrogen was estimated as the limiting factor in phytoplankton growth (N/P < 16). The evaluation of the status of the Nutrient pollution index (NPI) was observed as: Shadegan > Jarahi > Allah > Maroon > Zard > Ludab that the Jarahi River and Shadegan wetland were in the medium pollution class (1 < NPI ≤ 3) and other waterbodies were in the non-polluted to low pollution state (NPI < 1). Calculation of the chronic daily intake (CDI) showed that water body nutrients cause more non-carcinogenic health risks through the oral route than dermal exposure, and according to HI, children's health is more at risk than adults. Findings showed that surface water resources especially downstream of the Maroon-Jarahi watershed are at eutrophication risk, and to control the nearby human activities and as a result increase the nutrients in these water resources, measures should be taken.

Toxicity threshold and ecological risk of nitrate in rivers based on endocrine-disrupting effects: A case study in the Luan River basin, China

Nitrate, as a crucial nutrient, is consistently targeted for controlling water eutrophication globally. However, there is considerable evidence suggesting that nitrate has endocrine-disrupting potential on aquatic organisms. In this study, the sensitivity of various adverse effects to nitrate nitrogen (nitrate-N) was compared, and a toxicity threshold based on endocrine-disrupting effects was derived. The spatiotemporal variations of nitrate-N concentrations in the Luan River basin were investigated, and the associated aquatic ecological risks were evaluated using a comprehensive approach. The results showed that reproduction and development were the most sensitive endpoints to nitrate, and their distribution exhibited significant differences compared to behavior. The derived threshold based on endocrine-disrupting effects was 0.65 mgL−1, providing adequate protection for the aquatic ecosystem. In the Luan River basin, the mean nitrate-N concentrations during winter (4.4 mgL−1) were significantly higher than those observed in spring (0.7 mgL−1) and summer (1.2 mgL−1). Tributary inputs had an important influence on the spatial characteristics of nitrate-N in the mainstream, primarily due to agricultural and population-related contamination. The risk quotients (RQ) during winter, summer, and spring were evaluated as 6.7, 1.8, and 1.1, respectively, and the frequency of exposure concentrations exceeding the threshold was 100 %, 64.3 %, and 42.5 %, respectively. At the ecosystem level, nitrate posed intermediate risks to aquatic organisms during winter and summer in the Luan River basin and at the national scale in China. We suggest that nitrate pollution control should not solely focus on water eutrophication but also consider the endocrine disruptive effect on aquatic animals.

Spatio-Temporal Variations in Nitrate Sources and Transformations in the Midstream of the Yellow River Determined Based on Nitrate Isotopes and Hydrochemical Compositions

Nitrate pollution is a major environmental problem threatening rivers, and nitrogen and oxygen isotopes have proved to be an effective means of analyzing the sources and transformations of nitrate in rivers. However, a low monitoring frequency cannot accurately reflect the changes in nitrate. In this study, the sources and transformations of nitrate in the middle reaches of the Yellow River and its tributaries during the dry season and the wet season were analyzed based on water quality parameters and nitrate isotopes. Stable isotope analysis conducted using the R (SIAR) model was used to estimate the proportions of different nitrate sources. The results showed that the main nitrate sources in the main stream were soil nitrogen (40.95–45.83%) and domestic sewage and manure (30.93–32.60%), respectively, with little variation between the dry season and wet season because of the large flow of the Yellow River. During the dry season, the nitrate sources of the two tributaries were mainly domestic sewage and manure (45.23–47.40%), followed by soil nitrogen (31.35–34.00%). However, the primary nitrate source of T2 (Qin River) became soil nitrogen (40.05%) during the wet season, a phenomenon that was mainly caused by the significant increase in river discharge and in soil erosion in the basin. During the wet season, the concentrations of total nitrogen (TN) and nitrate (NO3−) significantly decreased in the main stream and tributaries, and nitrification and denitrification processes occurred in both the main stream and tributaries of the Yellow River. In addition, the T2 tributary (Qin River) was also significantly affected by mixed dilution. High-frequency sampling can reflect the isotopic information of nitrate in the river more comprehensively, which helps us to understand the conversion process of nitrate more accurately.

A framework model to integrate sources and pathways in the assessment of river water pollution

Metal and nutrient pollution, soil erosion, and alterations in climate and hydrology are prevalent issues that impact the water quality of riverine systems. However, integrated approaches to assess and isolate causes and paths of river water pollution are scarce, especially in the case of watersheds impacted by multiple hazardous activities. Therefore, a framework model for investigating the multiple sources of river water pollution was developed. The chosen study area was the Paraopeba River basin located in the Minas Gerais, Brazil. Besides multiple agriculture, industrial, and urban pollution sources, this region was profoundly affected by the rupture of the B1 tailings dam (in January 2019) at the Córrego do Feijão mine, resulting in the release of metal-rich waste. Considering this situation, thirty-nine physicochemical and hydromorphological parameters were examined in the Paraopeba River basin, in the 2019–2023 period. The analysis involved various statistical techniques, including bivariate and multivariate methods such as correlation analysis, principal component analysis, and clustering. The Paraopeba River was mainly impacted by metal contamination resulting from the dam collapse, whereas nutrient contamination, mainly from urban and industrial discharges, predominantly affected its tributaries. Additionally, the elevated concentrations of aluminum, iron, nitrate, and sulfate in both main river and tributaries can be attributed to diffuse and point source pollution. In terms of hydromorphology and soil type, the interaction between woody vegetation and erosion-resistant soils, especially latosols, contributes to the stability of riverbanks in the main river. Meanwhile, in the tributaries, the presence of neosols and sparse vegetation in urbanized areas promoted riverbank erosion potentially amplifying pollution. While the study was conducted in a particular watershed, the findings are based on a methodology that can be applied universally. Hence, the insights on surface water quality from this research can be a valuable resource for researchers studying watersheds with diverse pollution sources.

Climate and landform interact to control the source and transport of nitrate in Pacific Northwest rivers

The hydrological effects of climate change are documented in many regions; however, climate-driven impacts to the source and transport of river nutrients remain poorly understood. Understanding the factors controlling nutrient dynamics across river systems is critical to preserve ecosystem function yet challenging given the complexity of landscape and climate interactions. Here, we harness a large regional dataset of nitrate (NO3–) yield, concentration, and isotopic composition (δ15N and δ18O) to evaluate the strength of hydroclimate and landscape variables in controlling the seasonal source and transport of NO3–. We show that hydroclimate strongly influenced the seasonality of river NO3–, producing distinct, source-dependent NO3– regimes across rivers from two mountain ranges. Riverine responses to hydroclimate were also constrained by watershed-scale topographic features, demonstrating that while regional climate strongly influences the timing of river NO3– transport, watershed topography plays a distinct role in mediating the sensitivity of river NO3– dynamics to future change.

Seasonal and Tidal variations of DO, BOD, and Nutrients in Major Rivers within Eastern Niger Delta, Nigeria

River channels within the Oil producing Area of Nigeria are highly impacted by the activities of the Oil Companies. This work examined the Dissolved oxygen (DO), Biochemical oxygen demand (BOD), Nitrate (NO3-), Phosphate (PO43-), and sulphate (SO42-) in Calabar, Cross River, Imo, Great Kwa, and Qua-Iboe Rivers using standard procedures. Results showed that, DO, BOD, NO3-, and SO42- were within their limits by NESREA whereas, PO43- was higher than the limit. Mean levels of NO3-, PO43-, and SO42- were higher during the dry season and low tidal regime while DO and BOD showed higher levels in wet season and high tidal regime. Results also indicated that, DO belong to the slightly polluted class, BOD, NO3-, and SO42- belong to the non-polluted class whereas, PO43- varied between moderately polluted and the severely polluted classes in the studied aquatic channels. Generally, the relationships among the parameters varied from one parameter to the other. Principal component analysis (PCA) identified mainly the anthropogenic factor and moderately the natural factor as being responsible for the levels of the parameters assessed in the studied rivers. Hierarchical clusters analysis (HCA) recorded common associations and sources for the DO and BOD, PO43- and SO42- while NO3- had a separate and personal cluster. The study revealed the existing relationships among the studied parameters and their related impact on the health of the aquatic ecosystems investigated.

A century of nitrogen dynamics in agricultural watersheds of Denmark

Intensive agriculture has been linked to increased nitrogen loads and adverse effects on downstream aquatic ecosystems. Sustained large net nitrogen surpluses have been shown in several contexts to form legacies in soil or waters, which delay the effects of reduction measures. In this study, detailed land use and agricultural statistics were used to reconstruct the annual nitrogen surpluses in three agriculture-dominated watersheds of Denmark (600–2700 km2) with well-drained loamy soils. These surpluses and long-term hydrological records were used as inputs to the process model ELEMeNT to quantify the nitrogen stores and fluxes for 1920–2020. A multi-objective calibration using timeseries of river nitrate loads, as well as other non-conventional data sources, allowed to explore the potential of these different data to constrain the nitrogen cycling model. We found the flux-weighted nitrate concentrations in the root zone percolate below croplands, a dataset not commonly used in calibrating watershed models, to be critical in reducing parameter uncertainty. Groundwater nitrate legacies built up in all three studied watersheds during 1950–1990 corresponding to ∼2% of the surplus (or ∼1 kg N ha yr−1) before they went down at a similar rate during 1990–2015. Over the same periods active soil nitrogen legacies first accumulated by approximately 10% of the surplus (∼5 kg N ha yr−1), before undergoing a commensurate reduction. Both legacies appear to have been the drivers of hysteresis in the diffuse load at the catchments’ outlet and hindrances to reaching water quality goals. Results indicate that the low cropland surpluses enforced during 2008–2015 had a larger impact on the diffuse river loads than the European Union’s untargeted grass set-aside policy of 1993–2008. Collectively, the measures of 1990–2015 are estimated to have reset the diffuse load regimes of the watersheds back to the situation prevailing in the 1960s.

Unexpectedly high nitrate levels in a pristine forest river on the Southeastern Qinghai-Tibet Plateau

River nitrate (NO3–) pollution is a global environmental issue. Recently, high NO3– levels in some pristine or minimally-disturbed rivers were reported, but their drivers remain unclear. This study integrated river isotopes (δ18O/δ15N-NO3– and δD/18O-H2O), 15N pairing experiments, and qPCR to reveal the processes driving the high NO3– levels in a nearly pristine forest river on the Qinghai-Tibet Plateau. The river isotopes suggested that, at the catchment scale, NO3– removal was prevalent in summer, but weak in winter. The pristine forest soils contributed more than 90 % of the riverine NO3–, indicating the high NO3– backgrounds. The release of soil NO3– to the river was “transport-limited” in both seasons, i.e., the NO3– production/stock in the soils exceeded the capacity of hydrological NO3– leaching. In summer, this regime and the NO3–-plentiful conditions in the soils associated with the strong NO3– nitrification led to the high riverine NO3– levels. While the in-soil nitrification was weak in winter, the leaching of legacy NO3– resulted in the consistently high NO3– levels. This study provides insights into the reasons for high NO3– levels in pristine or minimally-disturbed rivers worldwide and highlights the necessity to consider NO3– backgrounds when evaluating anthropogenic NO3– pollution in rivers.

Riverine nitrate source and transformation as affected by land use and land cover

A mixed land use/land cover (LULC) catchment increases the complexity of sources and transformations of nitrate in rivers. Spatial paucity of sampling particularly low-resolution sampling in tributaries can result in a bias for identifying nitrate sources and transformations. In this study, high spatial resolution sampling campaigns covering mainstream and tributaries in combination with hydro-chemical parameters and dual isotopes of nitrate were performed to reveal spatio-temporal variations of nitrate sources and transformations in a river draining a mixed LULC catchment. This study suggested that point sources dominated the nitrate in the summer and winter, while non-point sources dominated the nitrate in the spring and autumn. A positive correlation was observed between proportions from sewage and land use index (LUI). However, negative correlations between soil nitrogen/nitrogen fertilizer and LUI were observed. With an increase of urban areas, the increased contribution from domestic sewage resulted in an increase of NO3− concentrations in rivers. Both urban and agricultural inputs should be considered in nitrate pollution management in a mixed LULC catchment. We concluded that the seasonal variations of nitrate sources were mainly affected by flow velocity conditions and agricultural activities, while spatial variations were mainly affected by LULC. In addition, we found a novel underestimation of dominated sources from Bayesian model because of mixing effect of isotope values from the tributaries to mainstream, however, high spatial resolution sampling can make up for this shortcoming. δ15N and δ18O values of nitrate indicated that nitrate originated from nitrification in soils. The nitrate concentrations and correlation between δ15N and 1/[NO3−] suggested little contribution of nitrate removal by denitrification. Thus, the nitrate reduction in the Yuehe River basin needs to be strengthened. The study provides new implications for estimation of nitrate sources and transformations and basis for nitrate reduction in the river with mixed LULC catchment.

Land use as a major factor of riverine nitrate in a semi-arid farming-pastoral ecotone: New insights from multiple environmental tracers and molecular signatures of DOM

The nitrogen contamination in rivers has become significant concern in arid and semiarid areas due to water resource shortage and extensive anthropogenic activities in relation to land-use changes in China. As a major nitrogen species, identifying driving factors, transformation and sources of nitrate is crucial for managing nitrogen pollution in rivers. In this study, nitrate sources and transformations were deciphered using physicochemical variables, molecular signature of dissolved organic matter and coupled isotopes of nitrate under different land use types in the Yang River, a typical farming-pastoral ecotone in the semi-arid area of North China. The results of river water showed a significant positive correlation between NO3− concentrations, δ15N-NO3− values and percentage of urban land and cropland, which confirmed the critical role of land use in the variations of riverine nitrate. The correlation between dissolved organic matter composition (aliphatic and lignin-like compounds) and NO3−/Cl− ratios as well as Cl− concentrations verified the effect of agricultural activities on nitrate source and transport. The variation in water chemical variables and dual isotopes of nitrate in river and soil extracts (δ15N-NO3− and δ18O-NO3−) was indicative of the concurrence of in-soil nitrification process and assimilation, whereas denitrification was inhibited under aerobic conditions in the semiarid area. The Bayesian model revealed that about 60% of nitrate was derived from non-point sources (manure, soil organic nitrogen and chemical fertilizer) and 36% from sewage. Although urban is not the major land-use type in the farming-pastoral ecotone, sewage contributed to about 36% of nitrate. The source identification of nitrate stresses the importance of the management of non-point pollution and demand for sewage treatment facilities in the farming-pastoral ecotone. This multiple-tracer approach will help gain deeper insights into nitrogen management in semi-arid areas with extensive human disturbance.

Hydrological connectivity affects nitrogen migration and retention in the land‒river continuum

Land use change and excessive nitrogen (N) loading threaten the health of receiving water bodies worldwide. However, the role of hydrological connectivity in linking watershed land use, N biogeochemistry and river water quality remain unclear. In this study, we investigated 15 subwatersheds in the Jiulong River watershed (southeastern China) during a dry baseflow period in 2018, combined with 3‒year (2017–2019) nutrient monitoring in 5 subwatersheds to explore river N dynamics (dissolved nutrients, dissolved gases and functional genes) and their controlling factors at three hydrological connectivity scales, i.e., watershed, hydrologically sensitive areas (HSAs) and riparian zone. The results show that land use at HSAs (less than 20% of watershed area) and watershed scales contributed similarly to river N variation, indicating that HSAs are hotspots for transporting land N into river channels. In particular, the agricultural land was the main factor affecting river nitrate and nitrous oxide (N2O) concentrations, while the built–up land significantly affected river ammonium and nitrite. At the riparian zone scale, soils and sediments substantially influenced river N retention processes (i.e., nitrification and denitrification). Management and protection measures targeting HSAs and riparian zones are expected to efficiently reduce river N loading and improve water quality.

Exploring the relations between sequential droughts and stream nitrogen dynamics in central Germany through catchment-scale mechanistic modelling

Like many other regions in central Europe, Germany experienced sequential summer droughts from 2015 to 2018. As one of the environmental consequences, river nitrate concentrations have exhibited significant changes in many catchments. However, catchment nitrate responses to the changing weather conditions have not yet been mechanistically explored. Thus, a fully distributed, process-based catchment Nitrate model (mHM-Nitrate) was used to reveal the causal relations in the Bode catchment, of which river nitrate concentrations have experienced contrasting trends from upstream to downstream reaches. The model was evaluated using data from six gauging stations, reflecting different levels of runoff components and their associated nitrate-mixing from upstream to downstream. Results indicated that the mHM-Nitrate model reproduced dynamics of daily discharge and nitrate concentration well, with Nash-Sutcliffe Efficiency ≥ 0.73 for discharge and Kling-Gupta Efficiency ≥0.50 for nitrate concentration at most stations. Particularly, the spatially contrasting trends of nitrate concentration were successfully captured by the model. The decrease of nitrate concentration in the lowland area in drought years (2015–2018) was presumably due to (1) limited terrestrial export loading (ca. 40 % lower than that of normal years 2004–2014), and (2) increased in-stream retention efficiency (20 % higher in summer within the whole river network). From a mechanistic modelling perspective, this study provided insights into spatially heterogeneous flow and nitrate dynamics and effects of sequential droughts, which shed light on water-quality responses to future climate change, as droughts are projected to be more frequent.

Seasonal Variation and Driving Factors of Nitrate in Rivers of Miyun Reservoir Watershed, North China

In order to identify the seasonal variations and dominant driving factors of NO3-N in rivers, investigations of five consecutive years were conducted in seven rivers of the Miyun Reservoir Watershed. Significant seasonal variation of NO3-N in rivers was separately found in the dormant season (non-growing season) and the growing season. Furtherly, the V-shaped, W-shaped, and indistinct seasonal patterns of NO3-N accounted for 53.0%, 38.7%, and 8.3%, respectively. They were remarkably affected by stream flow, and their significant quadratic function was discovered. The annual maxima and minima of NO3-N corresponded to medium flow in the dormant season and low flow or flood in the growing season, respectively. On one hand, flood mainly played a role in the diluent for the Chao River with high NO3-N, and on the other hand, it acted as a nitrogen source for the Bai River with low NO3-N. The NO3-N was closely correlated with human activities, and this correlation had obvious seasonal change trend. In the dormant season, significant and mostly extremely significant high correlation coefficient (R) values were determined, while partly non-significant with low R values were found in July, August, September, and October. Increasing seasonal variation index of NO3-N from upstream to downstream was found that was gentle for large rivers and sharp for small tributaries. The seasonality of NO3-N was more affected by natural factors, especially flood, than human factors.

Non-parametric analysis of nitrogen trends in the form of nitrate and nitrite in rivers and streams of the contiguous United States for 1990–2019

ABSTRACT Nitrogen and phosphorous support the ecosystem by supplying nutrients to algae and aquatic plants. Having them in excess results in the eutrophication of waters creating quality problems. In the past, nitrogen has been widely investigated for wells in the context of groundwater flow. However, a national-scale nitrogen assessment in rivers and streams has not received enough attention. In this study, the Wilcoxon rank-sum test, a non-parametric hypothesis testing method, has been applied to nitrogen concentration in the form of nitrate-nitrogen and nitrite-nitrogen in rivers and streams of the Contiguous United States. This approach was particularly chosen because of the non-normal and positively skewed nitrogen levels occurring in the surface flow. This method was able to identify the impaired body of waters as well as quantify the confidence, significance, and errors involved. The Northern Appalachians (NAP), Northern Plains (NPL), and Xeric (XER) ecoregions were identified as the ecoregions worsening in the nitrogen-nitrate condition with NAP, and XER needed immediate action. The nitrite-nitrogen condition did not pose an immediate threat, so mitigation efforts should focus more on nitrate-nitrogen remediation. It was shown that the method was superior to the two-sample t-test by yielding lower type II errors.

Sources and transformations of nitrate in Qixiangcuo Lake and its inflow rivers in the northern Tibetan Plateau.

Human activities and climate change input more reactive nitrogen into alpine lakes. Alpine saline lakes are usually located in endorheic watersheds at high-altitude areas, with no other drainage methods than evaporation, and are prone to accumulate nutrients. Meanwhile, alpine saline lakes are usually oligotrophic and sensitive to reactive nitrogen inputs, and even modest reactive nitrogen inputs may have significant effects on them, such as eutrophication. Nitrate is the main form of reactive nitrogen in lakes; therefore, clarifying the sources and transformations of nitrate in alpine saline lakes is important to prevent or mitigate eutrophication in alpine saline lakes. In this study, the sources and transformations of nitrate in Qixiangcuo Lake and its inflow rivers in the northern Tibetan Plateau were identified using dual nitrate isotopes and hydrochemistry. The results show that (1) the ranges of NO3- concentrations, δ15N - NO3-, and δ18O - NO3- values were 3.6 ~ 26.1μg/L, - 10.5 to + 6.0‰, and - 10.4 to + 9.2‰ in Qixiangcuo Lake and 194.4 ~ 728.1μg/L, + 5.8 ~ + 8.8‰, and - 1.9 to + 2.4‰ in its inflow rivers, respectively. The NO3- concentrations and δ15N - NO3- values were significantly lower in Qixiangcuo Lake than in its inflow rivers (P < 0.05). (2) The main sources of nitrate in both surface water and bottom water of Qixiangcuo Lake were ammonium in atmospheric deposition (mean probability estimate (MPE) 41.0% and 32.2%, respectively) and livestock manure (MPE 28.9% and 21.7%, respectively). The main sources of nitrate in the inflow rivers of Qixiangcuo Lake were domestic sewage (MPE 35.7%) and livestock manure (MPE 29.6%). (3) The main nitrogen transformation process in Qixiangcuo Lake was nitrification. The conservative mixing of multiple sources controlled the nitrate concentration and isotopic composition of Qixiangcuo Lake. Improvement in grazing area planning and the installation of sewage treatment facilities are effective measures to prevent eutrophication in Qixiangcuo Lake and its inflow rivers.

Assessment of Water Quality Indicators in the Orla River Nitrate Vulnerable Zone in the Context of New Threats in Poland

Currently, one of the most serious threats to the environment in rural areas is industrial livestock production, which generates a significant amount of chemical and biological pollution. It causes pollution of waters, affects biodiversity, and has an impact on the climate. Research was carried out in the Orla River (Poland) with a catchment area of 1.546 km2. Studies were concentrated on pH, dissolved oxygen, alkalinity, and other factors. Analyses were conducted on the area of livestock buildings in two buffer zones, 1 and 3 km wide, respectively, and included the abundance of phosphorus and potassium in soil as well as its potential impact on the quality of river water. Seasonal variability was observed for nutrients. In the winter period the highest concentrations of nitrates were observed, while in the summer this was the case for phosphates and total phosphorus. The highest concentrations of nutrients occurred in 2012, particularly total and ammonium nitrogen. There was a positive correlation between livestock building area and parameters such as ammonium, organic, and total nitrogen in the 1 km buffer, as well as organic and total nitrogen, potassium and dissolved oxygen in the 3 km buffer. Negative correlation in the case of pH was observed in both buffer zones. Relationships were found between the area of livestock buildings and parameters analyzed during seasons.

Evaluation of the Groundwater and Irrigation Quality in the Zhuoshui River Alluvial Fan between Wet and Dry Seasons

The Zhuoshui River alluvial fan is one of the most important groundwater and agricultural areas in Taiwan. Abundant groundwater resources are the main source of domestic water supply and irrigation water. However, groundwater recharge and groundwater quality have been greatly affected under extreme climate and hydrological conditions. Hence, the quality of groundwater has been a topic of concern to the public. In this study, groundwater level and groundwater quality data of the Zhuoshui River alluvial fan from 2008 to 2020 were used to divide the wet and dry season groups according to the sampling dates. An independent samples t-test was used to evaluate the differences in the mean groundwater level and the mean concentration between the wet and dry seasons. The test results show that there was no statistically significant difference in the mean groundwater level between the wet and dry seasons. This may result from the time lag effects of groundwater recharge. Except for groundwater temperature, bicarbonate, and total organic carbon (TOC), there were no significant differences among the mean concentrations of other groundwater quality parameters in Aquifer 1 and Aquifer 2 between the wet and dry seasons. In terms of the alluvial fan location, although the soil texture, land utilization, cropping systems, and hydrogeology of the proximal, mid-, and distal fan may affect groundwater quality variations, it seems that only Aquifer 1 is affected by surface water infiltration, resulting in significant differences in mean groundwater temperature, mean concentrations of major ions, and nitrate between the wet and dry seasons, whereas Aquifer 2 is less affected. At the same time, owing to the geological conditions and intensive cultivation in the Zhuoshui River alluvial fan, nitrate and arsenic could represent a high risk to the public’s health if groundwater is used as a source for domestic water supply or irrigation water in the distal fan area, whether in the wet season or dry season. Meanwhile, due to global climate change and uneven droughts and floods, the hydrological conditions of the so-called “wet season” and “dry season” are obviously different from those in the past. Compared with precipitation, groundwater level may be a better indicator for understanding variations in groundwater quality.