Quantify phosphorus transport distinction of different reaches to estuary under long-term anthropogenic perturbation

Enhancing phosphorus source apportionment in watersheds through species-specific analysis

Phosphorus (P) is a pivotal element responsible for triggering watershed eutrophication, and accurate source apportionment is a prerequisite for achieving the targeted prevention and control of P pollution. Current research predominantly emphasizes the allocation of total phosphorus (TP) loads from watershed pollution sources, with limited integration of source apportionment considering P species and their specific implications for eutrophication. This article conducts a retrospective analysis of the current state of research on watershed P source apportionment models, providing a comprehensive evaluation of three source apportionment methods, inventory analysis, diffusion models, and receptor models. Furthermore, a quantitative analysis of the impact of P species on watersheds is carried out, followed by the relationship between P species and the P source apportionment being critically clarified within watersheds. The study reveals that the impact of P on watershed eutrophication is highly dependent on P species, rather than absolute concentration of TP. Current research overlooking P species composition of pollution sources may render the acquired results of source apportionment incapable of assessing the impact of P sources on eutrophication accurately. In order to enhance the accuracy of watershed P pollution source apportionment, the following prospectives are recommended: (1) quantifying the P species composition of typical pollution sources; (2) revealing the mechanisms governing the migration and transformation of P species in watersheds; (3) expanding the application of traditional models and introducing novel methods to achieve quantitative source apportionment specifically for P species. Conducting source apportionment of specific species within a watershed contributes to a deeper understanding of P migration and transformation, enhancing the precise of management of P pollution sources and facilitating the targeted recovery of P resources.

Predictive modeling of nitrogen and phosphorus concentrations in rivers using a machine learning framework: A case study in an urban-rural transitional area in Wenzhou China

Rapid urbanization in China since 1980 generated environmental pressures of non-point source pollution (NPSP) and increased wide public concerns. Excessive quantities of nitrogen (N) and phosphorus (P) is a significant source of aquatic pollution, despite of their roles as essential nutritional elements for aquatic life processes. In this study, we present a new framework using random forest (RF) as a powerful machine learning algorithm driven by geo-datasets to estimate and map the concentration of total nitrogen (TN) and phosphorus (TP) at a spatial resolution for the Wen-Rui Tang River (WRTR) watershed, which is a typically urban-rural transitional area in east coastal region of China. A comprehensive GIS database of 26 in-house built environmental variables was adopted to build the predictive models of TN and TP in open waters over the watershed. The performances of the RF regression models were evaluated in comparison with in-situ measurements, and the results indicated the ability of RF regression models to accurately predict the spatiotemporal distribution of N and P concentration in rivers. Charactering the explanatory variable importance measures in the calibrated RF regression model defined the most significant variables impacting N and P contaminations in open waters across the urban-rural transitional area, and the results showed that these variables are aquaculture, direct domestic sewage, industrial wastewater discharges and the changing meteorological variables. Besides, mapping of the TN and TP concentrations across the continuous river at high spatiotemporal resolution (daily, 1 km × 1 km) in this study were informative. The results in this study provided the valuable data to various different stakeholders for managing water quality and pollution control where similar regions with rapid urbanization and a lack of water quality monitoring datasets.

Discharge dynamics of agricultural diffuse pollution under different rainfall patterns in the middle Yangtze river

Rainfall plays a crucial role in influencing the loss of agricultural diffuse pollution. The middle Yangtze River region is well-know for its humid climate and numerous agricultural activities. Thus, this study quantitatively analyzed the concentration and distribution of nitrogen (N) and phosphorus (P) load and loss in a major tributary of the middle Yangtze River under different rainfall patterns by using sampling analysis and SWAT model simulation. The total nitrogen (TN) and nitrate-nitrogen (NO3-) concentrations were 1.604-3.574 and 0.830-2.556 mg/L, respectively. The total phosphorous (TP) and Soluble Reactive Phosphorus (SRP) were 2-148 and 2-104 μg/L, respectively. The modeling results demonstrated that higher rainfall intensity led to greater load and loss flux of diffuse pollutant at the outlet. Organic nitrogen (ORGN) is the main nitrogen form transported from the subbasin to the reach, while organic phosphorus (ORGP) and inorganic phosphorus (INORGP) were transported at similar amounts. Under the condition of conventional rainfall, the outlet reaches mainly transported NO3-, and ORGN gradually increased when rainstorm events occurred. The ratio of INORGP to ORGP was relatively stable. During extreme rainfall event, rainfall is the dominant element of agricultural diffuse pollution. A strong positive correlation exists between rainfall intensity and pollution loss during rainstorms. Storm rain events were the main source of TN and TP losses. Few storm rain days generated pollutants that accounted for a large proportion of the total loss, and their impact on TP loss was significantly greater than that of TN. The influence of storm rain on TN is mainly the increase in runoff, while TP is sensitive to the runoff and sediment transport promoted by rainfall. By setting different precipitation scenarios, it was confirmed that under the same rainfall amount, short-term storm rain has the most significant impact on the TN load, whereas TP load may be influenced more by the combined effects of rainfall duration and intensity. Therefore, to reduce the impact of agricultural diffuse pollution, it is important to take targeted measures for the rainstorm days.

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.

A multiscale analysis of the spatially heterogeneous relationships between non-point source pollution-related processes and their main drivers in Chaohu Lake watershed, China

A better understanding of the relationships between non-point source (NPS) pollution-related processes and their drivers will help to develop scientific watershed management measures. Although various studies have explored the drivers' impact on NPS pollution-related processes, quantitative knowledge of the properties within these relationships is still needed. This study uses the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to produce three related processes of NPS pollution, quick flow (QF), nitrogen export (NE), and sediment export (SE), in the upstream watershed of Chaohu Lake, China. The spatial distributions of QF, NE, and SE and their responses to multiple natural-socioeconomic drivers at nine spatial scales (1 km2, 10 km2, 20 km2, 30 km2, 50 km2, 75 km2, 100 km2, 200 km2, and town) were compared. The results showed that the spatial scale has little impact on the spatial distributions of NPS pollution-related processes. Across the nine scales, the socioeconomic drivers related to agricultural activities, area proportions of cultivated land (cultivated) and paddy field (paddy), have dominant impacts on NE, while the topographical drivers, the connectivity index (IC) and slope, have dominant impacts on both SE and QF. The magnitudes of single and paired natural-socioeconomic drivers' impacts on NPS pollution-related processes increase logarithmically or linearly with increasing spatial scale, but they tend to reach a stable threshold at a certain coarse scale. Our results emphasized the necessity and importance of embracing spatial scale effects in watershed water environmental management.

The evaluation of N/P fate using the SPARROW model: a case study in an arid and semi-arid region, northern China

The assessment of nutrients' fate from source to sink is critical to water quality control. As an important ecological reserve in the arid and semi-arid regions of China, the Luanhe River Basin (LRB) has suffered from the deterioration of water quality, thus leading to the urgent management and control. However, few studies have devoted to exploring the fate of N/P contaminations for the entire watershed, due possibly to the large drainage area and heterogeneous watershed composition. Here, we attempt to illustrate N/P contaminations delivery and retention processes using the SPAtially Referenced Regression On Watershed attributes (SPARROW) model. The model reveals 97% of the spatial variability in the TN load and 81% in the TP load, verifying its availability and credibility. The results indicate that anthropogenic sources are dominating the N/P load, which account for 68.5% of N and 74.6% of P inputs. The results highlight the significant retention effects of streams and reservoirs, with 16.4% of N and 13.4% of P removals by streams and 24.3% of N and 10.7% of P removals by reservoirs, respectively. Ultimately, only 49,045.2 t yr^-1 (or 16.9%) of N and 1668.7 t yr^-1 (or 17.1%) of P being transported to the Bohai Sea. In addition, the analysis of influencing factors showed that regional characteristics (e.g., topography, rainfall), stream size, and delivery distance are potential factors affecting the riverine transport, whereas flow rate and surface area are primarily affecting the reservoirs attenuation. In the future, the watershed water quality management should pay more attention to source management and pollution legacy risks to achieve sustainable and healthy watershed development.

Study on the sediment and phosphorus flux processes under the effects of mega dams upstream of Yangtze River

The upper Yangtze River (UYR) plays an important role in water supply, hydropower generation, environmental and ecological protection. Constructions of Mega cascade reservoirs have significantly affected the transport of sediment and P, but the evolution of sediment and P in the mega cascade reservoirs of the UYR is unclear. This study investigated the variations in sediment load and total P (TP) flux based on the flow and sediment data from 1990 to 2019 and TP concentrations from 2005 to 2019. In addition, the proportion of sediment load and TP flux from tributaries, variations in the concentrations of particulate P (PP) and dissolved P, trapping effect of dams, and statistical uncertainties were analyzed and discussed. The main results are as follows: (1) the sediment load and TP flux evidently decreased after the impoundment of reservoirs in the UYR and Jinsha River, and the contribution rate of TP flux from main tributaries (except Wu River) to mainstream increased by 3.82-24 %; (2) the error of TP flux calculated by daily and monthly data is within 30 %, which shows that the uncertainty range is clear at some degree attributed to the different monitoring frequency, and the concentration of PP in flood season is greater than that in non-flood season; (3) the total retention rates of sediment and TP in the Three Gorges Reservoir and Gezhouba were 86.78 %, and 49.83 % (2009-2012), respectively, but decreased to 82.85 % and 15.26 % (2013-2019), and the values in Xiangjiaba and Xiluodu were 97.83 % and 60.27 % (2013-2019). The retention rates of newly built reservoirs (Wudongde and Baihetan) were predicted using an empirical method, and the results revealed that new dams would facilitate long-term reduction in sediment downstream.

Occurrence, geochemical characteristics, enrichment, and ecological risks of rare earth elements in sediments of "the Yellow river-Estuary-bay" system

Recent studies have suggested that rare earth elements (REEs) are contaminants of emerging concern. Moreover, the understanding of the occurrence and risks of REEs in river-estuary-bay systems is limited. The present study investigated the distributions, geochemical characteristics, and ecological risks of Y and 14 REEs (La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu) in sediments from the Yellow River to its estuary and adjacent Laizhou Bay. The average total concentrations of Y and REEs in the sediments generally increased from the Yellow River (149 mg/kg) to the estuary (165 mg/kg) and Laizhou Bay (173 mg/kg). In the estuarine core sediments, the concentrations of Y, light REEs (LREEs), and heavy REEs (HREEs) were in the ranges of 19.5-31.4 mg/kg, 58.6-156 mg/kg, and 12.3-19.1 mg/kg, respectively, from the 1700s to 2018, showing no obvious increasing or decreasing trends. The surface and core sediments from the river to the bay were characterized by obvious fractionation between LREEs and HREEs. In sediments, Fe minerals and clay are believed to promote the accumulation of REEs, especially HREEs. The enrichment levels of REEs generally increased from the middle reaches of the Yellow River to the bay, and Gd, Tb, Dy, Ho, Yb, and Lu were the most enriched elements in the sediments. Lu had moderate potential ecological risks in sediments of "the Yellow River-estuary-bay" system, and other REEs had relatively low ecological risks. The potential ecological risk indices of Y and REEs ranged from 78.7 to 144, showing increasing trends from the Yellow River to its estuary and adjacent bay, which should raise concerns regarding emerging contaminant management around estuarine and coastal regions.

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.

Forest leaf litter nutrient discharge patterns in snowmelt surface runoff and watershed scale remote sensed simulation

The leaf litter decomposition is the important chain for the nutrient cycle in forest ecosystem, but its degradation dynamics and pulse discharge patterns in freeze-thawing watershed needed complete understanding. By integrating field observations and MODIS data, the temporal-spatial distributions of snow coverage and forest leaf litter biomass were analyzed. The critical period for snowmelt runoff under warming temperature and the relatively slow degradation patterns were identified. The on-site observations snowmelt runoff showed discharge concentration and fraction dynamics of typical forest leaf litter nutrients (carbon, nitrogen, and phosphorus) in thawing period. The snowmelt runoff flow and nutrient flux observed the linear regressions with the increased temperature from -8 °C to 6 °C (r2 = 0.443-0.987). The concentration of TOC, TN, and TP reached summit value around 50.0, 6.0, and 0.5 mg L^-1 in the snowmelt runoff, respectively. The fraction analysis proved that the much high composition of dissolved organic fraction and the biggest organic phosphorus percentage was 94%. The comparison experiments of forest soil with or without leaf litter cover demonstrated that the leaf litter caused a lower discharge load in the snowmelt flow, and the leaf litter cover can decease the potential transport capability of the snowmelt runoff. Coupled with remote sensing data, the watershed leaf litter nutrient discharge model was developed with snowmelt hydrological process mode. The watershed averaged discharge of TOC, TN, and TP from deciduous broad-leaved forest leaf litter was around 851.99, 75.05, and 9.78 mg·m^-2, respectively. The yearly simulation showed the spatial distribution variance of the nutrient discharge loads were held by different forest types, elevations, and slopes. The critical loss area identification provided new mitigations solution. The findings suggested that seasonal discharge of forest leaf litter nutrient in thawing period acted as a key contributor to watershed water pollution.

Spatial characteristics of nutrient budget on town scale in the Three Gorges Reservoir area, China

Accurately quantifying nutrient budget is an essential step toward sustainable nutrient management in large watersheds increasingly disturbed by human activity. A town-scale nutrient budget framework based on the Soil and Water Assessment Tool was developed for 2010-2012 in the Three Gorges Reservoir area in China (TGRA). Moran's I spatial correlation test and Geodetector spatial heterogeneity test were employed to systematically analyze the spatial characteristics of the resulting nutrient budget. The Moran's I value of total nitrogen (TN) and total phosphorus (TP) gradually increased from input to output in the range of 0.091-0.232 and 0.102-0.484, respectively. Towns with higher TN and TP inputs were largely concentrated in the main urban area of Chongqing because of its high population density. By contrast, towns with higher TN and TP outputs were concentrated in the head of the TGRA. The Moran's I values of the TN and TP retention coefficients (R) were 0.433 and 0.524, respectively, demonstrating clear spatial consistency. Towns with a "High-high" spatial consistency pattern and positive R value were concentrated in the tail and hinterland, while those with a "Low-low" spatial consistency pattern and negative coefficient value were located mainly in the head of the TGRA. This phenomenon was mostly caused by differences in regional elevation, the normalized difference vegetation index, and soil erosion factor. The interaction effect between any two of these three factors on nutrient retention (Geodetector q-value) was greater than 60%. Therefore, future nutrient management should be based on a full understanding of regional biophysical conditions, especially in large areas. These findings provide a new perspective on fine nutrient management.

Ammonium Nitrogen Streamflow Transport Modelling and Spatial Analysis in Two Chinese Basins

Ammonium nitrogen (NH4+-N), which naturally arises from the decomposition of organic substances through ammonification, has a tremendous influence on local water quality. Therefore, it is vital for water quality protection to assess the amount, sources, and streamflow transport of NH4+-N. SPAtially Referenced Regressions on Watershed attributes (SPARROW), which is a hybrid empirical and mechanistic modeling technique based on a regression approach, can be used to conduct studies of different spatial scales on nutrient streamflow transport. In this paper, the load and delivery of NH4+-N in Poyang Lake Basin (PLB) and Haihe River Basin (HRB) were estimated using SPARROW. In PLB, NH4+-N load streamflow transport originating from point sources and farmland accounted for 41.83% and 32.84%, respectively. In HRB, NH4+-N load streamflow transport originating from residential land and farmland accounted for 40.16% and 36.75%, respectively. Hence, the following measures should be taken: In PLB, it is important to enhance the management of the point sources, such as municipal and industrial wastewater. In HRB, feasible measures include controlling the domestic pollution and reducing the usage of chemical fertilizers. In addition, increasing the vegetation coverage of both basins may be beneficial to their nutrient management. The SPARROW models built for PLB and HRB can serve as references for future uses for different basins with various conditions, extending this model’s scope and adaptability.