Spatiotemporal variation of nitrogen and phosphorus and its main influencing factors in Huangshui River basin

Stochastic process is main factor to affect plateau river fish community assembly

Plateau river ecosystems are often highly vulnerable and responsive to environmental change. The driving mechanism of fish diversity and community assembly in plateau rivers under changing environments presents a significant complexity to the interdisciplinary study of ecology and environment. This study integrated molecular biological techniques and mathematical models to identify the mechanisms influencing spatial heterogeneity of freshwater fish diversity and driving fish community assembly in plateau rivers. By utilizing environmental-DNA metabarcoding and the null model, this study revealed the impact of the stochastic process on fish diversity variations and community assembly in the Huangshui Plateau River of the Yellow River Basin (YRB) in China. This research identified 30 operational taxonomic units (OTUs), which correspond to 20 different fish species. The findings of this study revealed that the fish α-diversity in the upstream region of Xining is significantly higher than in the middle-lower reach (Shannon index: P = 0.017 and Simpson: P = 0.035). This pattern was not found to be related to any other environmental factors besides altitude (P = 0.023) that we measured. Further, the study indicated that the assembly of fish communities in the Huangshui River primarily depends on stochastic ecological processes. These findings suggested that elevation was not the primary factor impacting the biodiversity patterns of fish in plateau rivers. In plateau rivers, spatial heterogeneity of fish community on elevation is mainly determined by stochastic processes under habitat fragmentation, rather than any other physicochemical environmental factors. The limitations of connectivity in the downstream channel of the river could be taken the mainly responsibility for stochastic processes of fish community in Huangshui River. Incorporating ecological processes in the eDNA approach holds great potential for future monitoring and evaluation of fish biodiversity and community assembly in plateau rivers.

Response of stream water quality to the vegetation patterns on arid slope: a case study of Huangshui River basin

Vegetation patterns on slopes strongly affect the water cycle processes in a basin, especially the water yield and confluence in arid areas. Quantifying and evaluating the effects of hydrological change on the migration and transformation of pollutants are challenging. Based on 4-year stream water quality data of 13 monitoring sites in the Huangshui River basin, a typical arid watershed of the Chinese Loess Plateau, the redundancy analysis (RDA) and structural equation modeling (SEM) analysis tools were used to quantify its relationship with vegetation patterns. In the study, land use and the enhanced vegetation index (EVI) were used as a metric of vegetation patterns; accordingly, the 13 catchments were divided into three groups via the cluster analysis, including large (over 80%), medium (70 ~ 80%), and small (below 70%) proportion vegetation patterns (LVP, MVP, SVP). The results of the LVP group showed that vegetation patterns negatively affected the contamination of total phosphorus (TP), ammonia nitrogen (NH3-N), permanganate index (CODMn), and biochemical oxygen demand (BOD5) in the stream water, and the contribution rates were - 0.57. While the proportion of urban area positively correlated with stream water quality in the groups of MVP and SVP, the contribution rates were 0.46 and 0.36, respectively. Moreover, the precipitation in the groups of MVP and SVP negatively correlated with pollutants (- 0.24 and - 0.26). Those results revealed the response of stream water quality to vegetation patterns on the slope with the consideration of precipitation, land use, and socio-economic factors for the regional water and land resource allocation. This study has important management implications for vegetation patterns on slope of fragile ecosystems in arid areas.

Characteristics of nitrogen flow and its environmental effects in the Yellow River Basin, China

In large river basins, the nitrogen (N) cycle is largely regulated by complicated interactions between human and natural elements. Nevertheless, the origins, fate and driving forces of reactive nitrogen (Nr) flows in the basins are still not clear. An estimation model of N flux was established for evaluating the Nr flow and its environmental effects in the Yellow River Basin of Henan Province (HYRB) by means of material flow analysis. Total N input and output of HYRB were calculated at 4090.9 and 3948.8 Gg N yr-1, causing 142.0 Gg yr-1 of N stored in the basin. Industry, cropland and residential activities, respectively occupied for 42.2%, 23.2% and 12.3% of the whole input, as well as 43.6%, 25.1% and 12.3% of the whole output, which were central to HYRB's N cycle. Anthropogenic activities regulated above 95.0% of total inputs, and 49.5% of N outputs was emitted into the air and 4.5% into hydrosphere. High N input, energy intensive, imperfect sewage disposal facilities and low N utilization efficiency were the main reasons of contaminate. How to effectively regulate the input of high-strength N pollutant associated with insufficient N cycling and Nr elimination is the main issue in the Yellow River Basin. In present research also put forward corresponding control measures according to the evaluation of N flow and Nr release of HYRB. The research can supply science foundation for coordinating the human-environment relationship in large basins, and also has important reference significance for the formulation of Nr emission reduction strategies.

Pollution source identification and abatement for water quality sections in Huangshui River basin, China

Accurately obtaining the pollution sources and their contribution rates is the basis for refining watershed management. Although many source analysis methods have been proposed, a systematic framework for watershed management is still lacking, including the complete process of pollution source identification to control. We proposed a framework for identification and abatement of pollutants and applied in the Huangshui River Basin. A newer contaminant flux variation method based on a one-dimensional river water quality model was used to calculate the contribution of pollutants. The contributions of various factors to the over-standard parameters of water quality sections at different spatial and temporal scales were calculated. Based on the calculation results, corresponding pollution abatement projects were developed, and the effectiveness of the projects was evaluated through scenario simulation. Our results showed that the large scale livestock and poultry farms and sewage treatment plants were the largest sources of total nitrogen (TP) in Xiaoxia bridge section, with contribution rates of 46.02% and 36.74%, respectively. Additionally, the largest contribution sources of ammonia nitrogen (NH3-N) were sewage treatment plants (36.17%) and industrial sewage (26.33%). Three towns that contributed the most to TP were Lejiawan Town (14.4%), Ganhetan Town (7.3%) and Handong Hui Nationality town (6.6%), while NH3-N mainly from the Lejiawan Town (15.9%), Xinghai Road Sub-district (12.4%) and Mafang Sub-district (9.5%). Further analysis found that point sources in these towns were the main contributor to TP and NH3-N. Accordingly, we developed abatement projects for point sources. Scenario simulation indicated that the TP and NH3-N could be significantly improved by closing down and upgrading relevant sewage treatment plants and building facilities for large scale livestock and poultry farms. The framework adopted in this study can accurately identify pollution sources and evaluate the effectiveness of pollution abatement projects, which is conducive to the refined water environment management.

Unraveling the rate-limiting step in microorganisms' mediation of denitrification and phosphorus absorption/transport processes in a highly regulated river-lake system

River-lake ecosystems are indispensable hubs for water transfers and flow regulation engineering, which have frequent and complex artificial hydrological regulation processes, and the water quality is often unstable. Microorganisms usually affect these systems by driving the nutrient cycling process. Thus, understanding the key biochemical rate-limiting steps under highly regulated conditions was critical for the water quality stability of river-lake ecosystems. This study investigated how the key microorganisms and genes involving nitrogen and phosphorus cycling contributed to the stability of water by combining 16S rRNA and metagenomic sequencing using the Dongping river-lake system as the case study. The results showed that nitrogen and phosphorus concentrations were significantly lower in lake zones than in river inflow and outflow zones (p < 0.05). Pseudomonas, Acinetobacter, and Microbacterium were the key microorganisms associated with nitrate and phosphate removal. These microorganisms contributed to key genes that promote denitrification (nirB/narG/narH/nasA) and phosphorus absorption and transport (pstA/pstB/pstC/pstS). Partial least squares path modeling (PLS-PM) revealed that environmental factors (especially flow velocity and COD concentration) have a significant negative effect on the key microbial abundance (p < 0.001). Our study provides theoretical support for the effective management and protection of water transfer and the regulation function of the river-lake system.

Assessment of water quality parameters in Muthupet estuary using hyperspectral PRISMA satellite and multispectral images

The continuous availability of spatial and temporal distributed data from satellite sensors provides more accurate and timely information regarding surface water quality parameters. Remote sensing data has the potential to serve as an alternative to traditional on-site measurements, which can be resource-intensive due to the time and labor involved. This present study aims in exploring the possibility and comparison of hyperspectral and multispectral imageries (PRISMA) for accurate prediction of surface water quality parameters. Muthupet estuary, situated on the south side of the Cauvery River delta on the Bay of Bengal, is selected as the study area. The remote sensing data is acquired from the PRISMA hyperspectral satellite and the Sentinel-2 multispectral instrument (MSI) satellite. The in situ sampling from the study area is performed, and the testing procedures are carried out for analyzing different water quality parameters. The correlations between the water sample results and the reflectance values of satellites are analyzed to generate appropriate algorithmic models. The study utilized data from both the PRISMA and Sentinel satellites to develop models for assessing water quality parameters such as total dissolved solids, chlorophyll, pH, and chlorides. The developed models demonstrated strong correlations with R² values above 0.80 in the validation phase. PRISMA-based models for pH and chlorophyll displayed higher accuracy levels than Sentinel-based models with R² > 0.90.

Diagnostic strategy for the combined effects of microplastics and potentially toxic elements on microbial communities in catchment scale

Combined effects of potentially toxic materials (PTMs) released from production activities on microbial communities in environmental flimsy area are poorly recognised. Microplastics (MPs) and potentially toxic elements (PTEs) were investigated in soils and river sediments in a headwater catchment from the Qinghai-Tibet Plateau. Their co-effects on microbial communities and the controlling factors affecting communities were further explored. Results showed that MPs and PTEs significantly accumulated in soils and sediments. Among which fragment-shaped MPs and copper (Cu) dominated, with mean contents of 1.11 × 10⁴ and 1.81 × 10⁴ items kg^-1 and 13.80 and 7.33 mg kg^-1 in soils and sediments, respectively. Distribution index (0.54) suggested that fiber-shaped MPs preferred to transport into rivers and deposited in sediments. The film mulching contributed significantly to the occurrence of fragment-shaped MPs, while Cu may be derived from industrial wastewater. The antagonistic effect between fiber-shaped MPs and zinc (Zn) on soil microbial structure was found based on their obtuse angle in canonical correlation analysis. While the synergistic effect between total phosphorus (TP) and Cu on diversity was detected by interaction detector model (q(TP ∩ Cu) >q(TP) >q(Cu), p < 0.05). Soil TP and Cu were identified as controlling factors influencing diversity through random forest model and factor detector (q(TP) = 0.49, q(Cu) = 0.36, p < 0.05), which may be related to direct nutrient supply and microbial resistance, respectively. The negative effects of MPs on structure might be counteracted by increasing Zn content, while the co-existence of TP and Cu further increased diversity. A diagnostic framework, which involves background data collection, sampling analysis, characterisation and relationship investigation, was proposed to explore the co-effects of complex pollution and factors on communities. This study may provide strategies to mitigate the negative effects on microorganisms in the environment.

Predicting phosphorus and nitrate loads by using SWAT model in Vamanapuram River Basin, Kerala, India

Evaluations of probable environmental impacts of point and diffuse source pollution at regional sizes are essential to achieve sustainable development of natural resources such as land and water. This research focused on how nitrate and phosphorus load varied over time and space in the Vamanapuram River Basin (VRB). Phosphorus and nitrate loads have been evaluated in the VRB using the semi-distributed Soil and Water Assessment Tool (SWAT) hydrological model. SWAT Calibration and Uncertainty Programs (SWAT-CUP) have simulated the developed model using the Sequential Uncertainty Fitting, version 2(SUFI-2). The developed model was simulated for 2001 to 2008, and it was split into two-phase calibration and validation phases. Model performance was evaluated by the percentage of bias (PBAIS) and Nash-Sutcliffe efficiency coefficient (NSE). The simulated performance of nitrate was indicated as NSE = 0.22-0.59 and PBIAS = 51.86-65.88. The simulated performance of phosphorus showed NSE = 0.06-0.33 and PBIAS = 15.14-33.97. Total Phosphorus load was most sensitive to the organic Phosphorus enrichment ratio (ERORGP) and CH_N2 for streamflow simulation. This study concluded that the South-western region was a high potential for nutrient loads. This study will explain the nutrient load and guidelines for land management practice in the study area.

Comammox biogeography subject to anthropogenic interferences along a high-altitude river

The recent discovery of comammox Nitrospira performing complete ammonia oxidation to nitrate has overturned the long-held dogma of two-step nitrification on Earth, yet little is known about the effect of urbanization interference on their distribution. Using gene-centric metagenomics, we provided the first blueprints about comammox community, biogeography, and environmental drivers along a high-elevation (> 2000 m) river flowing through the largest city on the vulnerable Qinghai-Tibetan Plateau. Our study confirmed a wide presence and diversity of yet-uncultured comammox clade B across wet and dry seasons, with average 3.0 and 2.0 times as abundant as clade-A amoA genes in water and sediments, respectively. Species identified from freshwater and drinking water treatment plants dominated the comammox guilds (58∼100%), suggesting this plateau river shared a similar comammox assemblage with the above habitat types. Compared with the urban area harboring more abundant canonical Nitrospira identified in wastewater (average 24%), the upstream suburban reach had a smaller human population but larger proportions of comammox in ammonia-oxidizing prokaryotes (24∼72% of abundances) and Nitrospira sublineages I/II. Higher contents of nitrate and nitrite in water, and antibiotics in water and sediments, may restrain comammox niches in nitrifiers over the urban area. Further random forest analysis revealed that lincosamides and quinolones were the most important antibiotic predictors for the niche differentiations between comammox and canonical nitrifiers in water, while macrolides for those in sediments. Finally, by incubation experiments, we demonstrated higher activity contributions of benthic comammox in the suburban area (36.2∼92.8% of potential ammonia-oxidation rates) than in the urban reach, and that the contribution variation had significant negative relations with macrolides and their major components. Overall, this study highlighted that anthropogenic activities hampered the advantage of riverine complete nitrifiers over the canonical two-step ones.

Random forest-based modeling of stream nutrients at national level in a data-scarce region

Nutrient runoff from agricultural production is one of the main causes of water quality deterioration in river systems and coastal waters. Water quality modeling can be used for gaining insight into water quality issues in order to implement effective mitigation efforts. Process-based nutrient models are very complex, requiring a lot of input parameters and computationally expensive calibration. Recently, ML approaches have shown to achieve an accuracy comparable to the process-based models and even outperform them when describing nonlinear relationships. We used observations from 242 Estonian catchments, amounting to 469 yearly TN and 470 TP measurements covering the period 2016-2020 to train random forest (RF) models for predicting annual N and P concentrations. We used a total of 82 predictor variables, including land cover, soil, climate and topography parameters and applied a feature selection strategy to reduce the number of dependent features in the models. The SHAP method was used for deriving the most relevant predictors. The performance of our models is comparable to previous process-based models used in the Baltic region with the TN and TP model having an R² score of 0.83 and 0.52, respectively. However, as input data used in our models is easier to obtain, the models offer superior applicability in areas, where data availability is insufficient for process-based approaches. Therefore, the models enable to give a robust estimation for nutrient losses at national level and allows to capture the spatial variability of the nutrient runoff which in turn enables to provide decision-making support for regional water management plans.

Effects of Agriculture and Animal Husbandry on Heavy Metal Contamination in the Aquatic Environment and Human Health in Huangshui River Basin

Huangshui River (HSR) is the mother river of Qinghai province. Croplands and grasslands cover more than 76% of the total area, and highland agriculture and animal husbandry are the dominant industries. The use of pesticides, fertilizers, and feed additives increases the risk of heavy metal (HM) contamination. In this study, the concentration of HMs in the main stream and tributaries of HSR were investigated. The Positive Matrix Factorization model was used for source apportionment, and Health Risk Assessment method was used to assess the human health risks. To further analyze the effect of agriculture and animal husbandry on aquatic environment and human health, we considered agriculture and animal husbandry as two factors in the source apportionment process, defined the effect of the factors, established the calculation formula, and quantified the effects. The results show that the overall situation of aquatic environment in HSR is good; natural processes, traffic tail gas and atmospheric deposition, agricultural planting, industrial wastewater discharge, and animal husbandry are the main sources of HMs in the water. These HMs present noncarcinogenic and carcinogenic risks for infants. A total effect of agricultural and animal husbandry on HMs or HI in HSRB is approximately 20%, while on TCR is 40%. However, the effects of agriculture on the hazard quotient of arsenic, carcinogenic risk of nickel and lead, and that of animal husbandry on carcinogenic risk of cadmium were significant. This study can provide a theoretical basis for local managers of agriculture and animal husbandry to perform their work effectively.

Perfluorinated compounds in a river basin from QingHai-Tibet Plateau: Occurrence, sources and key factors

The occurrence of perfluorinated compounds (PFCs) in different environmental media in the QingHai-Tibet Plateau has been limitedly investigated. In this study, the water, sediments, soils and agricultural product samples were collected in the Huangshui River basin, and contents of the PFCs and values of water parameters were determined. This study investigated dominantly regulating factors of the distribution of PFCs in the water emphatically, explored the sources and assessed potential risks of the PFCs integrally. The results showed that perfluorohexanesulfonic acid, perfluorooctanesulfonic acid, perfluorobutanoic acid (PFBA) and perfluorooctanoic acid presented high maximum concentrations of 3207.42, 3015.96, 1941.89 and 826.4 ng L-1 in the water, respectively. There were 12 PFCs detected in crops, with the maximum concentration of 5206.86 ng g-1 for PFBA. The significantly positive correlation (p < 0.05) was observed between the concentrations of PFBA in crops and that in adjacent rivers, indicating that the irrigation most likely contributed to the accumulation of PFBA in the studied crops. The occurrence of the PFCs in the water during the dry season was dominantly regulated by fluorescent dissolved organic matters via the hydrophobic interaction, while it was primarily regulated by the total nitrogen and electrical conductivity via electrostatic interaction during the wet season. The PFCs in the water were mainly from the wastewater discharged from wastewater treatment plants and carpet factories, while the resuspension of the PFCs in sediments was also an important contribution especially in wet season. The PFCs in the river has posed sustained risk to the public health, especially children.

Farmland Changes and Their Ecological Impact in the Huangshui River Basin

The Huangshui River Basin (HRB) is the main grain production and key implementation region of the “Grain for Green Program” (GGP) of Qinghai Province, and has experienced a quick urbanization during the last 20 years. Therefore, identifying the farmland change and its ecological effects is significant for farmland and ecological protection in the HRB. To this end, this study analyzed the farmland change between 2000 and 2018, based on 1 m spatial resolution farmland data visually interpreted from Google Earth high-resolution images, and then estimated its ecological impact based on the Normalized Difference Vegetation Index (NDVI) data of MODIS, using an ecological impact index of farmland change. The study found that: (1) The farmland area in the HRB decreased from 320.15 k ha in 2000 to 245.01 k ha in 2018, reduced by 23.47% or 1.48% per year, as mainly caused by ecological restoration and built-up land occupation; (2) from 2000 to 2018, the natural environment showed a greening trend in the HRB, with the mean NDVI increasing by 0.74% per year; (3) the farmland changes had a positive ecological effect, contributing 6.67% to the regional increase in the NDVI, but had a negative impact on grain production; (4) it is suggested to strengthen farmland protection by strictly controlling the urban land occupation and over-conversion of farmland in the HRB.