Effects of land-use patterns on in-stream nitrogen in a highly-polluted river basin in Northeast China

Rainfall impacts on nonpoint nitrogen and phosphorus dynamics in an agricultural river in subtropical montane reservoir region of southeast China

The increased frequency and intensity of heavy rainfall events due to climate change could potentially influence the movement of nutrients from land-based regions into recipient rivers. However, little information is available on how the rainfall affect nutrient dynamics in subtropical montane rivers with complex land use. This study conducted high-frequency monitoring to study the effects of rainfall on nutrients dynamics in an agricultural river draining to Lake Qiandaohu, a montane reservoir of southeast China. The results showed that riverine total nitrogen (TN) and total phosphorus (TP) concentrations increased continuously with increasing rainfall intensity, while TN:TP decreased. The heavy rainfall and rainstorm drove more than 30% of the annual N and P loading in only 5.20% of the total rainfall period, indicating that increased storm runoff is likely to exacerbate eutrophication in montane reservoirs. NO3--N is the primary nitrogen form lost, while particulate phosphorus (PP) dominated phosphorus loss. The main source of N is cropland, and the main source of P is residential area. Spatially, forested watersheds have better drainage quality, while it is still a potential source of nonpoint pollution during rainfall events. TN and TP concentrations were significantly higher at sites dominated by cropland and residential area, indicating their substantial contributions to deteriorating river water quality. Temporally, TN and TP concentrations reached high values in May-August when rainfall was most intense, while they were lower in autumn and winter than that in spring and summer under the same rainfall intensities. The results emphasize the influence of rainfall-runoff and land use on dynamics of riverine N and P loads, providing guidance for nutrient load reduction planning for Lake Qiandaohu.

Riverine seasonal rainfall event tracing of organic pollution sources using fluorescence fingerprint difference spectrum

Elucidating the dynamics of dissolved organic matter (DOM) transport and transformation under seasonal rainfall events is essential for the conservation of riverine ecosystems, for mitigating the effects of climate change, and for crafting informed water management strategies. Therefore, this study aimed to investigate the evolutionary characteristics of organic pollution sources during consecutive rainfall events in early spring and to quantify their relative contributions to the process of surface water pollution. The results showed seasonal rainfall induces water quality exceedances in rivers due to the combined impacts of terrestrial inputs and endogenous releases. Humic acid (HA) (region V) and fulvic acid (FA) (region III) emerged as the predominant organic matter in the water column, with their fluorescence intensity altering as rainwater flushed the riverbed. Sources of pollution include agricultural and urban domestic sources (AS + DS) (72.29 %), industrial and urban domestic and microbial sources (IS + DS + MS) (37.71 %), and agricultural and industrial sources (AS + IS) (63.32 %), indicating that agricultural surface pollution discharges contribute significantly. The gas-chromatography-mass spectrometry (GC-MS) further confirmed that exogenous inputs were predominantly comprised of particulate pollutants. This study underscores the efficacy of fluorescence difference spectrometry in delineating the migration and transformation of river pollution sources during seasonal rainfall and facilitating the implementation of targeted management strategies for river ecosystems.

Impacts of land use on phosphorus and identification of phosphate sources in groundwater and surface water of karst watersheds

The thin soil layer with uneven distribution in karst areas facilitates the migration of phosphorus (P) to groundwater, threatening the safety of water sources seriously. To offer a scientific guidance for water pollution control and land use planning in karst areas, this study examined the relationships between land use and P in groundwater and surface water, and quantified the phosphate sources in Gaoping river basin, a small typical watershed in karst areas. Spatial distribution analysis revealed that the highest mean P concentrations in groundwater and surface water were in farmland and construction-farmland zones, respectively. Land use impact analysis showed that the concentration of P in groundwater was influenced positively by farmland but negatively by forest land. In contrast, the concentration of P in surface water was influenced positively by both farmland and construction land. The mixed end-element and Bayesian-based Stable Isotope Analysis in R (SIAR) model results showed that agricultural fertilizers were the main phosphate source for groundwater in farmland and forest-farmland zones, while urban sewage was the main source in the construction-farmland zone. For surface water, the main phosphate source was agricultural fertilizers in both farmland and construction-farmland zones. This study indicates that controlling P pollution in local water bodies should pay close attention to the management of land use related to human activities, including regulating sewage discharge from construction land and agricultural fertilizer usage.

Layer-specific mechanisms of perfluoroalkyl acid (PFAA) transport and partition in estuarine environments: Unveiling the depth-dependent differences

Understanding of characteristics and transport of perfluoroalkyl acids (PFAAs) in heterogeneous estuarine environments is limited. Furthermore, the role of suspended particles (SPS) in different layers remains unclear. This study explores the multiphase distribution process and mechanism of PFAAs controlled by SPS across surface and bottom layers in five small estuaries. Peaks in PFAA concentrations are consistently observed at strongly stratified sites. Concentrations of the PFAAs in both surface and bottom SPS decreased as the degree of mixing increased from strongly stratified levels to well-mixed levels. The water-SPS partitioning of some short-chain PFAAs (PFBS, PFHxA, and PFHpA) is influenced by environmental factors (pH, depth, temperature, and salinity) due to electrostatic interactions, while the sorption of some long-chain PFAAs (PFOA, PFOS, and PFNA) is controlled by SPS and dissolved organic carbon (OC), driven by hydrophobic interactions. Additionally, SPS dominates OC transport in estuarine systems, except in sandy sediment environments. SPS plays a dominant role in PFAA partitioning in both surface and bottom water-SPS systems (p < 0.05), and salinity only significantly affects PFBS in bottom layer (p < 0.01). These findings are critical for understanding the drivers of PFAA partitioning and the roles of SPS in different layers, underscoring the necessity of considering particle-associated PFAA fractions in future coastal environmental management.

Spatiotemporal drivers of urban water pollution: Assessment of 102 cities across the Yangtze River Basin

Effective management of large basins necessitates pinpointing the spatial and temporal drivers of primary index exceedances and urban risk factors, offering crucial insights for basin administrators. Yet, comprehensive examinations of multiple pollutants within the Yangtze River Basin remain scarce. Here we introduce a pollution inventory for urban clusters surrounding the Yangtze River Basin, analyzing water quality data from 102 cities during 2018-2019. We assessed the exceedance rates for six pivotal indicators: dissolved oxygen (DO), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), biochemical oxygen demand (BOD), total phosphorus (TP), and the permanganate index (CODMn) for each city. Employing random forest regression and SHapley Additive exPlanations (SHAP) analyses, we identified the spatiotemporal factors influencing these key indicators. Our results highlight agricultural activities as the primary contributors to the exceedance of all six indicators, thus pinpointing them as the leading pollution source in the basin. Additionally, forest coverage, livestock farming, chemical and pharmaceutical sectors, along with meteorological elements like precipitation and temperature, significantly impacted various indicators' exceedances. Furthermore, we delineate five core urban risk components through principal component analysis, which are (1) anthropogenic and industrial activities, (2) agricultural practices and forest extent, (3) climatic variables, (4) livestock rearing, and (5) principal polluting sectors. The cities were subsequently evaluated and categorized based on these risk components, incorporating policy interventions and administrative performance within each region. The comprehensive analysis advocates for a customized strategy in addressing the discerned risk factors, especially for cities presenting elevated risk levels.

Urbanization and agriculture intensification jointly enlarge the spatial inequality of river water quality

Rivers are severely polluted by multiple anthropogenic stressors. An unevenly distributed landscape pattern can aggravate the deterioration of water quality in rivers. Identifying the impacts of landscape patterns on the spatial characteristics of water quality is helpful for river management and water sustainability. Herein we quantified the nationwide water quality degradation in China's rivers and analyzed its responses to spatial patterns of anthropogenic landscapes. The results showed that the spatial patterns of river water quality degradation had a strong spatial inequality and worsened severely in eastern and northern China. The spatial aggregation of agricultural/urban landscape and the water quality degradation exhibits high consistency. Our findings suggested that river water quality would further deteriorate from high spatial aggregation of cities and agricultures, which reminded us that the dispersion of anthropogenic landscape patterns might effectively alleviate water quality pressures.

Assessing land use changes' effect on river water quality in the Dez Basin using land change modeler

Changes in land use due to urbanization, industrialization, and agriculture will adversely affect water quality at all scales. This study examined the possible effects of future land use on the water quality of the Dez River located in Iran. The QUAL2Kw dynamic model was used to simulate the water quality of the Dez River. Data and information available in July 2019 and 2013 were used for calibration and validation. According to the comparison of the RMSE, RMSE%, and percent bias error indices for the model during the calibration and validation period, the QUAL2Kw model of Dez River had high accuracy with acceptable values of errors. The land use changes in the Dez river basin were modeled and predicted by the LCM model after simulating water quality. The images from Landsat 8/OLI were used for 2013, 2016, and 2019, respectively. Based on the accurate evaluation of classified images, Kappa coefficients for 2013, 2016, and 2019 were 88.19, 87.46, and 89.91, respectively. Modeling land use and land cover changes was conducted to predict 2030. As a result of the study, agricultural and built-up areas and water bodies will increase in 2030. The possible effects of land use changes in 2030 on river water quality were examined as a final step. Based on the results of the water quality simulation in 2030, biochemical oxygen demand, chemical oxygen demand, and NO₃ parameters exceeded the maximum permissible level of drinking standard. This study recommends frequent water quality monitoring and LULC planning and management to reduce pollution in river basins.

Effects of changes in land use structure on nitrogen input in the Pingzhai Reservoir watershed, a karst mountain region

Optimizing land use composition to control nitrogen input into water bodies is one way to address surface source pollution in karst mountain regions. In this study, changes in land use, N sources, and spatial and temporal changes of N migration in the Pingzhai Reservoir watershed were evaluated from 2015 to 2021, and the relationship between land use composition and N input was elucidated. N was the main pollution in the water of the watershed; NO₃^- was the dominant form of N, and it did not react during migration. N came from soil, livestock manure or domestic sewage, and atmospheric deposition. Isolating the fractionation effects of source nitrogen is crucial to improve the accuracy of nitrogen and oxygen isotope traceability in the Pingzhai Reservoir. From 2015 to 2021, the grassland area in the Pingzhai Reservoir increased by 5.52%, the woodland area increased by 2.01%, the water area increased by 1.44%, the cropland decreased by 5.8%, unused land decreased by 3.18%, and construction land remained unchanged. Policies and reservoir construction were the main drivers of changes in land-use type in the catchment. Changes in land use structure affected nitrogen input patterns, with unused land having a highly significant positive correlation with inputs of NH₃-N, NO₂^-, and TN, and construction land having a significant positive correlation with the input of NO₂^-. The inhibitory effect of forest and grassland on nitrogen input in the basin was offset by the promoting effect of cropland and construction land on nitrogen input, with unused land becoming a new focus area for nitrogen emissions due to a lack of environmental management. Modifying the area of different land use types in the watershed can effectively control nitrogen input to the watershed.

Determination of nitrate sources in a karst plateau reservoir based on nitrogen and oxygen isotopes

Investigating the sources, migration and proportional contribution of nitrate is essential to effectively protect water quality. δ¹⁵N-NO₃^-, δ¹⁸O-NO₃^- and Stable Isotope Analysis in R (SIAR) were used to qualitatively and quantitatively analyse nitrate sources in the Pingzhai Reservoir water body. The values of δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- in water vary with season. Soil organic nitrogen and chemical fertilisers are the main sources of nitrate in autumn, while domestic sewage and livestock manure are the primary sources of nitrate in winter and spring. The SIAR results showed that chemical fertilisers, livestock manure, sewage, and soil organic nitrogen had the highest proportional contribution. In autumn, the proportional contribution of chemical fertilisers to river and reservoir were 47 and 51 %. During winter, the proportional contributions of livestock manure and sewage to river and reservoir were 53 and 68 %, respectively, and in spring 49 and 68 %, respectively. Considering the fragility of karst ecosystems, strict measures should be formulated for the use of chemical fertilisers and standards for sewage discharge should be raised. Control nitrogen input from agricultural activities and prevent water quality deterioration.

Exploring the canal environment in terms of water, bed sediments and vegetation in a reclaimed floodplain of Northern Italy

The Po plain (Italy) is one of the largest floodplains in Europe that needs environmental restoration. To achieve this goal, the knowledge of the 'environment' (water, bed sediments and vegetation) of the canals crossing such floodplain is necessary. The water flow of the canals was kept low for hydraulic safety purposes from October to March (NIR), and high for irrigation purposes from April to September (IR). Within this framework, this study aimed to assess in 9 sites of the east part of Po plain 1) the canals' environment quality in terms of vegetation diversity, and water and bed sediment physicochemical properties; and 2) how these features are influenced by canal managements and landscape properties. Water was monthly sampled both in NIR and IR periods, the bed sediments were sampled in summer and winter periods, while the vegetation was recorded in spring and autumn. The low water flow during NIR worsened the water quality by increasing the concentrations of nutrients and salts. A higher salt and nutrient concentrations were observed both in water and bed sediments of canals crossing areas with fine texture alluvial deposits than in those flowing through medium texture alluvial deposits. Further, higher nutrient and salt concentrations were observed for the canals used as collectors of the water coming from other canals. Despite the differences observed for the bed sediments and water quality, the vegetation type and biodiversity did not show differences among the study sites probably because affected by the land use of the surrounding landscape. Indeed, the canals cross agricultural land which limit the developments of natural vegetation and do not promote plant biodiversity. Overall, the present study found out the key role of landscape properties and canal managements on 'canal environment' quality which need to be considered to perform an appropriate reclamation of such environments.

Anthropogenic activities control the source dynamics of sediment organic carbon in the lower reach of an inland river

Sediment organic carbon (SeOC) sources with rich information can be used as a "historical archive" reflecting anthropogenic activities in the catchment, which is crucial to carbon management in the watershed. Anthropogenic activities and hydrodynamic conditions significantly influence the river environment and are reflected by the SeOC sources. However, the key drivers of the SeOC source dynamics are ambiguous, which restricts the behavior of regulating the carbon output of the basin. In this study, sediment cores from the lower reach of an inland river were selected to quantify the SeOC sources based on a centennial scale. A partial least squares path model was used to establish the relationship between anthropogenic activities and hydrological conditions with the SeOC sources. Findings showed that the exogenous advantage of SeOC composition was gradually significant (early period: 54.3%; middle period: 81%; later period: 82%) from the bottom layer to the surface layer of the sediments in the lower reach of the Xiangjiang River. Factors related to anthropogenic activities controlled the external input of SeOC (δ¹³C: r_∂ = -0.94, P < 0.001; δ¹⁵N: r_∂ = -0.66, P < 0.001). Different anthropogenic activities performed different effects. Land use change aggravated soil erosion and brought more terrestrial organic carbon to the downstream. The variation of grassland carbon input was the most obvious (from 33.6% to 18.4%). In contrast, the reservoir construction intercepted upstream sediments, which might have been the main reason for the slow growth of terrestrial organic carbon input in the downstream in the later period. This study provides a specific grafting for the SeOC records - source changes - anthropogenic activities in the lower reach of the river, which provides scientific basis for watershed carbon management.

Scale effects of land use on river water quality: a case study of the Tuojiang River Basin, China

Assessing the scale effects of land use on water quality is of great significance for effectively controlling nonpoint source (NPS) pollution in river basins. In this study, redundancy analysis (RDA) and stepwise multiple linear regression (SMLR) analysis were applied to assess the effects of land use on water quality across multiscales in the Tuojiang River Basin. All monitoring sections were classified into three groups according to the characteristics of land use and cluster analysis of water quality. Results showed that the improvement in water quality of rivers in the Tuojiang River Basin lies in the emphasis and protection of the small-scale scope. Concomitantly, the linkages between individual water quality parameter and land use were highly dependent on spatial scales and regional basis. For the upstream group A, urban land is the main source of COD and TN pollution, while industrial and rural residential land contributed the most to TP pollution. Water body exhibits favorable effects on ammonia nitrogen due to its absorption and degradation, together with the growth of phytoplankton within it. For group B in the middle-lower reaches, controlling the input of organic fertilizers in paddy field will effectively alleviate COD pollution. Increasing the proportion of grassland near the riparian zone can have a positive effect on TN and TP pollution. It should continue to strengthen the strict supervision of NH₃-N concentration in wastewater discharge from industrial enterprises. Our results can provide important information for land use planning and making multiple scale measures for water quality conservation.

Integrating source apportionment and landscape patterns to capture nutrient variability across a typical urbanized watershed

Effective integrated watershed management requires models that can characterize the sources and transport processes of pollutants at the watershed with multiple landscape patterns. However, few studies have investigated the influence of landscape spatial configuration on pollutant transport processes. In this study, the SPARROW_TN and SPARROW_TP models were constructed by combining direct pollution source data and landscape pattern data to investigate the source composition and nutrient transport processes and to reveal the influence of landscape patterns on nutrient transport in the urbanized Beiyun River Watershed. The introduction of landscape metrics significantly improved the simulation results of both models, with R² increasing from 0.89 to 0.85 to 0.93 and 0.91, respectively. Spatial variations existed in TN and TP loads and yields, as well as the source compositions. Pollution hotspots were effectively identified. Source apportionment showed that for the entire watershed, TN came from atmospheric nitrogen deposition (35.25%), untreated sewage (28.23%), agricultural sources (22.60%), and treated sewage (13.92%). In comparison, TP came from untreated sewage (44.94%), agricultural sources (40.22%), and treated sewage (11.51%). In addition, the largest patch index of grassland correlated positively with both TN and TP, whereas the largest shape index of buildup land and interspersion and juxtaposition index of forest were negatively correlated with TN and TP, respectively. The results of this study will provide insight into effective nutrient control measures that consider spatially varying nutrient sources and associated nutrient transport processes.

Evaluation of water quality using a Takagi-Sugeno fuzzy neural network and determination of heavy metal pollution index in a typical site upstream of the Yellow River

Assessment of river water quality is very important for understanding the impact of human activities on aquatic ecosystems. As the second-largest river in China, the Yellow River's water environment is closely related to the social development and water security of northern China. The Huangshui River is a major tributary of the upper Yellow River, and it supplies water to cities in the lower reaches. In this study, a Takagi-Sugeno (T-S) fuzzy neural network was used to evaluate water quality of the Huangshui River, and pollutant sources were analyzed. The heavy metal pollution index (HPI) was calculated to assess the heavy metal pollution level, and the health risks posed by heavy metal elements were assessed. The results indicated that the main contaminants in the Huangshui River were ammonia nitrogen (NH₃-N) and total phosphorus (TP), which was affected by various activities of industry, agriculture, and urbanization, and the maximum concentration of NH₃-N and TP was 5.90 mg/L and 0.36 mg/L, respectively. The T-S evaluation results of some points in the middle reaches were 3.317 and 3.197, which belonged to Level Ⅳ and the water quality was poor. The concentrations of Cu, Zn and Cr in the river were 0.57-44.58 μg/L, 10-122.50 μg/L and 2-28.67 μg/L, respectively, and they were relatively large. The T-S fuzzy neural network could evaluate water quality, avoiding extreme evaluation results by using fuzzy rules to reduce the influence of pollutant concentrations that are too high or too low. In addition to qualitative categorization of water quality, this approach can also quantitatively assess water quality within a single category. The results of water quality assessment could provide a scientific data support for river management.

Land use management recommendations for reducing the risk of downstream flooding based on a land use change analysis and the concept of ecosystem-based disaster risk reduction

Sustainable management of ecosystems can provide various socio-ecological benefits, including disaster risk reduction. Through their regulating services and by providing natural protection, ecosystems can reduce physical exposure to common natural hazards. Ecosystems can also minimize disaster risk by reducing social and economic vulnerability and enhancing livelihood resilience. To showcase the importance and usefulness of ecosystem-based disaster risk reduction (Eco-DRR), this study (1) analyzed the land use change in a watershed in central Japan, (2) applied the concept of Eco-DRR, and made land use management recommendations regarding the watershed scale for reducing the risk of downstream flooding. The recommendations that emerged from the application, based on the land use change analysis, are: the use of hard infrastructure and vegetation to store and retain/detain stormwater and promote evapotranspiration is recommended for downstream, urban areas; the sustainable management of upland forest ecosystems and secondary forest-paddy land-human systems, and proactive land use planning in the lowland delta, where built land is concentrated, are key to the watershed-scale landscape planning and management to reduce downstream flooding risks.

Identification of the control factors affecting water quality variation at multi-spatial scales in a headwater watershed

Understanding the effect of landscape characteristics on water quality can provide insight into mitigating water quality impairment. However, there is no consensus about the key controlling factors influencing water quality. This paper examined the combined effects of land use and topography on water quality across multi-scale, and identified the key controlling factors determining water quality variation in the headwater watershed of the Hengxi reservoir in Eastern China. Water quality impairment (WQI), expressed as a composite variable, was established to measure the overall water quality. We used the partial least squares (PLSR) method to explore the combination of landscape metrics and identify the key controlling factors. Results showed that the optimal PLSR model at 50-m, 100-m, and 150-m buffer scales and catchment scale explained 77%, 63%, 60%, and 56% of variability in WQI, respectively. At catchment scale, patch density, the percentage of paddy field, and hypsometric integral were the key controlling factors impacting water quality. At buffer scales, the slope gradient, the percentage of forest land, and topographic wetness index were more effectively determined WQI variation. Thus, the key controlling factors depend on spatial scales. Both spatial scales and corresponding key controlling factors should be considered in the adjustment of land use composition and planning of landscape configuration to better protect water quality.

A Multivariate and Spatiotemporal Analysis of Water Quality in Code River, Indonesia

The efficacy of a water quality management strategy highly depends on the analysis of water quality data, which must be intensively analyzed from both spatial and temporal perspectives. This study aims to analyze spatial and temporal trends in water quality in Code River in Indonesia and correlate these with land use and land cover changes over a particular period. Water quality data consisting of 15 parameters and Landsat image data taken from 2011 to 2017 were collected and analyzed. We found that the concentrations of total dissolved solid, nitrite, nitrate, and zinc had increasing trends from upstream to downstream over time, whereas concentrations of parameter biological oxygen demand, cuprum, and fecal coliform consistently undermined water quality standards. This study also found that the proportion of natural vegetation land cover had a positive correlation with the quality of Code River's water, whereas agricultural land and built-up areas were the most sensitive to water pollution in the river. Moreover, the principal component analysis of water quality data suggested that organic matter, metals, and domestic wastewater were the most important factors for explaining the total variability of water quality in Code River. This study demonstrates the application of a GIS-based multivariate analysis to the interpretation of water quality monitoring data, which could aid watershed stakeholders in developing data-driven intervention strategies for improving the water quality in rivers and streams.

Decadal patterns of anthropogenic salinisation in typical mountain streams in northeastern China: Increased rates and sources

Salt pollution and anthropogenic-accelerated weathering is globally shifting the ionic composition and increasing salinisation of fresh water. We analyzed a 40-year data set (1970s-2010s) to characterize the drastic change of dissolved ionic composition, conductivity and pH levels. We also identified causative factors in these highly polluted mountain streams in northeastern China. Dissolved salt ions (Ca²⁺, Mg²⁺ and SO₄^2-) increased by 3.02-5.21 fold and conductivity (a proxy for salinisation) increased by 3.09 fold. The average pH values increased from 7.08 to 8.49. The dominant ions, Ca²⁺, Mg²⁺, SO₄^2- and HCO₃^- + CO₃^2-, accounted for ∼90% of ionic composition based on mass concentration. Between the 1970s and 2010s, the dominant anion shifted from HCO₃^- + CO₃^2- to a mixture of SO₄^2- and HCO₃^- + CO₃^2-. Increasing mining and land development appear to be the primary driving factors for the change of Ca²⁺, Mg²⁺, SO₄^2- and HCO₃^- + CO₃^2- concentrations; whereas, agricultural land was the main driving factor for the variation in K⁺, Na⁺ and Cl^- concentrations. The source of ions has shifted from a more natural weathering of carbonate rocks to one of mineral dissolution that is affected by anthropogenic activities. Our study shows that freshwater mountain streams are at risk of long lasting anthropogenic salinisation and should be considered in future management and conservation plans.

Tracking riverine nitrate sources under changing land use pattern and hydrologic regime

It remains challenging to identify nitrate sources in streams due to complications associated with anthropogenic inputs and in-stream biogeochemical processes. We used dual isotopic analysis of nitrate and a Bayesian isotope mixing model to explore the dynamics of nitrate sources and their associated transformations among three types of headwater watershed with different dominant land use types during four seasons in Jiulong River Watershed, a coastal China watershed. Nitrogen sources were the primary determinant of the δ¹⁵N-NO₃ and seasonal differences in biogeochemical processes exhibited among watersheds. Nitrate was mostly derived from nitrification in spring and summer, whereas atmospheric deposition greatly influenced the isotopic composition in autumn and winter. Chemical fertilizer contributed the largest to the riverine nitrate, accounting for 36.9 ± 12.3%, followed by soil N (27.2 ± 4.4%), atmospheric deposition (23.9 ± 11.8%) and manure & sewage (12.0 ± 5.9%). This study reveals the seasonality of riverine nitrate sources under changing watershed land use patterns.

Landscape Characteristics Affecting Spatial Patterns of Water Quality Variation in a Highly Disturbed Region

Spatial patterns of water quality trends for 45 stations in control units of the Shandong Province, China during 2009–2017 were examined by a non-parametric seasonal Mann-Kendall’s test (SMK) for dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), permanganate index (COD_Mn), total phosphorus (TP) and ammonia nitrogen (NH₃-N). The DO concentration showed significant upward trends at approximately half of the stations, while other parameters showed significant downward trends at more than 40% of stations. The stations with downward trends presented significant spatial autocorrelation, and were mainly concentrated in the northwest and southwest regions. The relationship between the landscape characteristics and water quality was explored using stepwise multiple regression models, which indicated the water quality was better explained using landscape pattern metrics compared to the percentage of land use types. Decreased mean patch area and connectedness of farmland will promote the control of BOD, COD and COD_Mn, whereas the increased landscape percentage of urban areas were not conducive to the water quality improvement, which suggested the sprawling of farmland and urban land was not beneficial to pollution control. Increasing the grassland area was conducive to the reduction of pollutants, while the effect of grassland fragmentation was reversed.

Landscape patterns regulate non-point source nutrient pollution in an agricultural watershed

Landscape pattern critically affects hydrological cycling and the processes of non-point source nutrients pollution. However, little is known about the quantitative relationship between landscape characteristics and the river water quality, and very few studies have addressed the abrupt changes in river water quality with the gradient of landscape metrics. The present study was conducted in a typically intensive agriculture watershed of eastern China including 13 sub-watersheds with different landscape pattern metrics. We adopted redundancy analysis, nonparametric deviance reduction approach, bootstrap sampling and other statistical methods to reveal the quantitative relationship between landscape pattern metrics and water quality variables; then, the phenomenon of an abrupt change in river water quality was explored with different landscape pattern gradients. The results show that landscape pattern significantly affects river water quality, and this effect was quite different in dry and rainy seasons. In the studied watershed, landscape pattern metrics could respectively explain 71.1% and 55.3% of the total variance in the river water quality in dry and rainy seasons. The configuration metrics of landscape pattern had a stronger ability than their composition metrics to explain the variance in water quality. In the dry season, largest patch index of forestland (LPI_for), the most important landscape index, explained 37.9% of the total variance in water quality. While, in the rainy season, the most important landscape index was the largest patch index of farmland (LPI_far), and it could explain 32.4% of that variance. In the studied watershed, when the LPI_for was <35% or LPI_far was over than 50%, water quality would typically change abruptly, at which the probability of a change in river water would suddenly rise substantially.

Using multivariate statistical analyses to identify and evaluate the main sources of contamination in a polluted river near to the Liaodong Bay in Northeast China

Using multivariate statistical analysis, the study evaluated anthropogenic sources of river water contamination and their relationships with river water quality in the Haicheng River basin near to the Liaodong Bay in Northeast China. The results showed that nitrogen (N) and phosphorous (P) were identified as the main pollutants in the river water by factor analysis. Human population and elevational gradient were all significantly correlated with N, P, and other water quality variables in correlation analysis and explained chemical oxygen demand (COD), N, and P variables from 23.9% (TN) to 53.1% (NH₃⁺-N) of the total variances in regression analysis, indicating that population and its distribution were all responsible for river contaminations, especially for COD, N, and P contaminations. The excessive applications of fertilizers and pesticides were all positively correlated with nitrogen variables and nitrogen pollution factor in correlation analysis, suggesting that agricultural activities were contributed to the river nitrogen pollution. Due to inadequate or lack wastewater treatment facilities, huge amounts of domestic sewage and industrial effluents were released into the river, becoming the predominant anthropogenic sources for the river water deterioration of COD, N, and P. Multivariate statistical analysis provided useful tools to correlate sources of contamination with water quality data. This approach will provide a better management for river pollution control in a human-driven river ecosystem.

Application of Nitrogen and Oxygen Isotopes for Source and Fate Identification of Nitrate Pollution in Surface Water: A Review

Nitrate pollution in surface water has become an environmental problem of global concern. The effective way for controlling the nitrate pollution of surface water is to identify the pollution source and reduce the input of nitrate. In recent decades, nitrogen (δ15N) and oxygen (δ18O) isotopes of nitrate has been used as an effective approach for identifying the source and fate of nitrate pollution in surface water. However, owing to the complexity of nitrate pollution source and the influence of isotopic fractionation, the application of this method has some limitations. In this work, we systematically discussed the fundamental principle of using nitrogen and oxygen isotopes to trace the nitrate source, the fate identification of nitrate, and the major testing techniques. Subsequently, the applications of nitrogen and oxygen isotopes for source identification of surface water were illustrated. However, there are still significant gaps in the application of the source identification and transformation mechanisms to nitrate and many research questions on these topics need to be addressed.

Spatio-temporal dynamics of water quality and their linkages with the watershed landscape in highly disturbed headwater watersheds in China

The water quality of headwater streams is a worldwide concern because of their critical roles in supplying clean water for drinking and other consumptive uses. Here, we evaluate temporal trends and spatial dynamics of the permanganate index (COD), ammonia-nitrogen (AN), and total phosphorus (TP) for 31 sites in headwater watersheds of the Huai River Basin, China. The seasonal Mann-Kendall test and correlation and variance analyses were applied to long-term time series (2003-2010) of water quality data in order to investigate the patterns of water quality trends, as well as their linkages with the watershed landscape. The results indicated that (1) more than 1/3 of headwater monitoring sites have exhibited either significantly increasing or decreasing trends in COD, AN and TP, while only TP increased for most them; (2) obvious increasing concentration gradients were observed for all water quality parameters along the upstream to the downstream continuum. Such spatial patterns can be highly explained by land cover and landscape configuration metrics. The percent of urban land and urban-related landscape metrics (such as the Landscape Division Index) were the primary explanatory variables for AN, while the aggregation metrics of cropland and urban land cover were the main predictors of COD and TP; (3) historical dynamics of COD, AN, and TP were influenced by land cover transitions. The trends of COD and TP may be attributable to the change in the wetland landscape, while the trends of AN were likely related to changes in forestland area as well as environmental management. Overall, our study determined the spatial and temporal dynamics of water quality parameters in the headwater watersheds and interpreted the possible reasons behind their spatio-temporal dynamics, which can have important implications for sustainable landscape planning as well as headwater watershed management.

Effects of secondary salinisation on macroinvertebrate functional traits in surface mining-contaminated streams, and recovery potential

Secondary salinisation has become a hot spot internationally due to its adverse effects on freshwater ecosystems. Although its effects on ecosystem patterns has been broadly studied, its potential effect on ecosystem functions, in particular on the functional traits of freshwater organisms, and functional trait recovery are largely unknown. In this study, we conducted a field investigation at 405 sample sites from May 2009 to July 2016 in surface mining-contaminated streams, in order to evaluate the influence of secondary salinisation on macroinvertebrate functional traits and the recovery potential of dominant functional traits. Results of univariate models showed that sensitive, very tolerant, gill-breathers, cutaneous-breathers, shredders, predators and gatherers were the most responsive indicators to enhanced specific conductivity and sulfate loadings with sensitive, gill-breathers, shredders and predators demonstrating a reduction in abundance, whereas cutaneous-breathers and gatherers exhibiting an increase. Complicated relationships among different species indicated that co-exclusions would not occur because all macroinvertebrate taxa exhibited positive correlations. Results of relative recovery potential showed that omnivores and gatherers recovered quickly following improvements in water quality, whereas gill-breathers, pneumostome-breathers, filterers and scrapers would be expected to recover slowly due to their sensitivity to both specific conductivity and sulfate and low drift propensity. Overall, secondary salinisation has posed severely ecological risks to macroinvertebrate functional attributes in surface mining-contaminated streams, and their effects should be considered in future conservation plans.

Source identification and impact of landscape pattern on riverine nitrogen pollution in a typical urbanized watershed, Beijing, China

This study explored the sources of nitrate and the impact of landscape pattern on nitrogen pollution in the highly urbanized Beiyun River Watershed, China during 2016 by applying a dual stable isotope approach (δ¹⁵N-NO₃^-and δ¹⁸O-NO₃^-) combined with multiple statistical analyses. The sources of riverine nitrate principally originated from manure and sewage, nitrification of soil nitrogen, fertilizer nitrification, and atmospheric deposition. A Bayesian model was used to estimate the source contributions and results showed that manure and sewage were the major contributors to river nitrate with combined proportions of 77.59% and 89.57% in the rainy season and the dry season, respectively. Results from multiple stepwise regression indicated that the typical artificial land use types and landscape configuration metrics reflecting landscape fragmentation related well with riverine nitrogen variables for different seasons (R²>0.6). Industrial land, unused land and patch density of built-up land and road were positively correlated with riverine nitrogen over seasons, whereas the interspersion and juxtaposition index of forest land was negatively related with nitrate. Regulating built-up land and unused land, connecting forest land with other land use types and diminishing discharges of industrial and domestic wastewater would be effective ways to improve urban river water quality.

How sulfate-rich mine drainage affected aquatic ecosystem degradation in northeastern China, and potential ecological risk

Mining activity is an increasingly important stressor for freshwater ecosystems. However, the mechanism on how sulfate-rich mine drainage affects freshwater ecosystems is largely unknown, and its potential ecological risk has not been assessed so far. During 2009-2016, water and macroinvertebrate samples from 405 sample sites were collected along the mine drainage gradient from circum-neutral to alkaline waters in Hun-Tai River, Northeastern China. Results of linear regressions showed that sulfate-rich mine drainage was significantly positively correlated with the constituents typically derived from rock weathering (Ca²⁺, Mg²⁺ and HCO₃^-+CO₃^2-); the diversity of intolerant stream macroinvertebrates exhibited a steep decline along the gradient of sulfate-rich mine drainage. Meanwhile, stressor-response relationships between sulfate-rich mine drainage and macroinvertebrate communities were explored by two complementary statistical approaches in tandem (Threshold Indicator Taxa Analysis and the field-based method developed by USEPA). Results revealed that once stream sulfate concentrations in mine drainage exceeded 35mg/L, significant decline in the abundance of intolerant macroinvertebrate taxa occurred. An assessment of ecological risk posed by sulfate-rich mine drainage was conducted based on a tiered approach consisting of simple deterministic method (Hazard Quotient, HQ) to probabilistic method (Joint Probability Curve, JPC). Results indicated that sulfate-rich mine drainage posed a potential risk, and 64.62-84.88% of surface waters in Hun-Tai River exist serious risk while 5% threshold (HC₀₅) and 1% threshold (HC₀₁) were set up to protect macroinvertebrates, respectively. This study provided us a better understanding on the impacts of sulfate-rich mine drainage on freshwater ecosystems, and it would be helpful for future catchment management to protect streams from mining activity.

Dissolved trace elements in a nitrogen-polluted river near to the Liaodong Bay in Northeast China

Dissolved trace element concentrations (Ba, Fe, Mn, Si, Sr, and Zn) were investigated in the Haicheng River near to the Liaodong Bay in Northeast China during 2010. Dissolved Ba, Fe, Mn, and Sr showed significant spatial variation, whereas dissolved Fe, Mn, and Zn displayed seasonal variations. Conditions such as water temperature, pH, and dissolved oxygen were found to have an important impact on redox reactions involving dissolved Ba, Fe, and Zn. Dissolved Fe and Mn concentrations were regulated by adsorption or desorption of Fe/Mn oxyhydroxides and the effects of organic carbon complexation on dissolved Ba and Sr were found to be significant. The sources of dissolved trace elements were found to be mainly from domestic sewage, industrial waste, agricultural surface runoff, and natural origin, with estimated seasonal and annual river fluxes established as important inputs of dissolved trace elements from the Haicheng River into the Liaodong Bay or Bohai Sea.