Assessing spatiotemporal risks of nonpoint source pollution via soil erosion: a coastal case in the Yellow River Delta, China.

Nonpoint source pollution (NPSP) has always been the dominant threat to regional waters. Based on empirical models of the revised universal soil loss equation and the phosphorus index, an NPSP risk assessment model denoted as SL-NPSRI was developed. The surface soil pollutant loss was estimated by simulating the rain-runoff topographic process, and the influence of path attenuation was quantified. A case study in the Yellow River Delta and corresponding field surveys of soil pollutants and water quality showed that the established model can be applied to evaluate the spatial heterogeneity of NPSP. NPSP usually occurs during high-intensity rainfall periods and in larger estuaries. Summer rainfall increased pollutant transport into the sea from late July to mid-August and caused estuarine dilution. Higher NPSP risks often correspond to coastal areas with lower vegetation coverage, higher soil erodibility, and higher soil pollutant concentrations. Agricultural NPSP originating from cropland significantly increase the pollutant fluxes. Therefore, area-specific land use management and vegetation coverage improvement, and temporal-specific strategies can be explored for NPSP control during source-transport hydrological processes. This research provides a novel insight for coastal NPSP simulations by comprehensively analyzing the soil erosion process and its associated pollutant loss effects, which can be useful for targeted spatiotemporal solutions.

From field soil sampling to watershed model: Upscaling by integrating information entropy and interpolation method.

Soil property data plays a crucial role in watershed hydrology and non-point source (H/NPS) modeling, but how to improve modeling accuracy with affordable soil samplings and the effects of sampling information on H/NPS modeling remains to be further explored. In this study, the number of sampling points and soil properties were optimized by the information entropy and the spatial interpolation method. Then the sampled properties were parameterized and the effects of different parameterization schemes on H/NPS modeling were tested using the Soil and Water Assessment Tool (SWAT). The results indicated that the required sampling points increased successively for soil bulk density (SOL_BD), soil saturated hydraulic conductivity (SOL_K) and soil available water capacity (SOL_AWC). Compared to the traditional database (Harmonized world soil database), the NSE and R2 performance by new scheme increased by 22.8% and 10.5%, respectively. The entropy-based optimization reduced the sampling points by 13.2%, indicating a more cost-effective scheme. Compared to hydrological simulation, sampled properties showed greater effects on NPS modeling, especially for nitrogen. This proposed method/framework can be generalized to other watersheds by upscaling field soil sampling information to the watershed scale, thus improving H/NPS simulation.

Exogenous mobile genetic elements and their associated integrons drive the enrichment of antibiotic-resistant genes in the river of a valley basin city (Lanzhou, China).

River is a unique source of drinking water in valley-type cities, affecting local urban development and human lifestyles. However, the key driving factors for dissemination of antibiotic-resistant genes (ARGs) in valley-type urban environments remain unclear. This study aimed to investigate the distribution of ARGs in the Yellow River and to clarify the driving factors of ARGs in a typical valley basin city (Lanzhou, China). The seven selected ARGs with higher abundances including tetracycline resistance genes (tetM, tetX), macrolide resistance genes (ermB, ermF, ereA), and sulfonamide resistance genes (sul1, sul2) were detected. The results showed that the total absolute abundance of all the selected ARGs varied from 9.97 × 1012 to 1.04 × 1015 copies/L in the water body, with higher abundances in the wet season, relative to the dry season. Among these, sulfonamide resistance genes (sul1, sul2) displayed the highest absolute abundance in the river and soil. The ARGs and mobile genetic elements (MGEs) were significantly correlated with bacterial abundance, dissolved organic carbon (DOC), ammonia nitrogen (NH4+), and total nitrogen (TN) levels in the water environment (Mantel test, P < 0.01). Structural equation modeling revealed the direct input of point-source and nonpoint-source ARGs in this area contributed less to the overall level of the ARGs in the water. Among the multiple drivers, the MGEs derived from wastewater treatment plant and anthropogenic nonpoint area positively and directly affected the ARG profiles in water (P < 0.01), rather than the factors of bacterial abundance and physicochemical properties. According to this study, the exogenous MGEs from anthropogenic activities are the main driver for the enrichment of ARGs in the valley-type urban river environment.

Functional keystone taxa promote N and P removal of the constructed wetland to mitigate agricultural nonpoint source pollution.

Characterized by irregular spatial and temporal variations of pollutant loading and complex occurrence mechanisms, agricultural nonpoint source pollution (ANPSP) has always been a great challenge in field restoration worldwide. Returning farmlands to wetlands (RFWs) as an ecological restoration mode among various constructed wetlands was selected to manage ANPSP in this study. Triarrhena lutarioriparia, Nelumbo nucifera and Zizania latifolia monocultures were designed and the water pollutants was monitored. N. nucifera and Z. latifolia could reach the highest TN (53.28 %) and TP (53.22 %) removal efficiency, respectively. By 16s high-throughput sequencing of rhizosphere bacteria, 45 functional species were the main contributors for efficient N and P removal, and 38 functional keystone taxa (FKT) were found with significant ecological niche roles and metabolic functions. To our knowledge, this is the first study to explore the microbial driving N and P removal mechanism in response to ANPSP treated by field scale RFWs.

Agricultural nonpoint source pollutant loads into water bodies in a typical basin in the middle reach of the Yangtze River.

Phosphorus and nitrogen pollution from agricultural nonpoint sources heavily burden the water environment, and a scientific calculating system is needed to calculate the pollutant loads under the water pollution treatment. This study established a system to calculate the coefficients of agricultural nonpoint source pollutants into water bodies in the subregion in Poyang Lake basin in the middle reach of the Yangtze River combining with multiple driving factors. Validation results showed that the errors of the typical unit were 30.58% for total phosphorus (TP), 13.43% for total nitrogen (TN) and 33.93% for ammonia nitrogen (NH3-N), respectively. The errors of the subregion were 26.92% for TP, 31.83% for TN and 29.15% for NH3-N, respectively. Besides, there were higher TP and TN loads in the east area of subregion in both units and county scales, which indicated the heavy phosphorus and nitrogen burden on water environment. In contrast, higher NH3-N loads occurred in the north area of subregion. The establishment of coefficient system for agricultural pollutants into water bodies and the pollutant loads calculation would provide enlightenment for water pollution treatment and agricultural nonpoint source pollution controlling.

Differences in nonpoint source pollution load losses based on hydrological zone characteristics: a case study of the Shaying River Basin, China.

Agricultural nonpoint source (NPS) pollution loss is closely related to hydrological processes. Understanding the differences in NPS pollution load loss under hydrological processes is useful for the management and prevention of NPS pollution. In this paper, hydrological and water quality data from 2016 to 2018 and monitoring data of physical and chemical indicators in 1347 field soil samples in the Shaying River Basin (SYRB) were used to analyze spatiotemporal variations in NPS pollution using the Soil and Water Assessment Tool and multifactor analysis of variance. The intensities and differences in NPS pollution losses for different soil types and land use patterns were evaluated under different hydrological zones. The annual rainfall in the SYRB decreased gradually from 1136.50 to 404.04 mm, showing a significant zoning. Areas with high loss intensities were mainly distributed in areas with steep slopes and in the 800-1000 mm rainfall zone. Cultivated land had the largest loss of NPS pollution, followed by forest land and rural residential land. Fluvo-aquic soil had the largest loss of NPS pollution, followed by cinnamon soil and lime concretion black soil. A nonlinear regression model was established for rainfall and the NPS pollution loss intensity and had a correlation coefficient of 0.60-0.99 at a 95% confidence level. Slope and rainfall were the main factors influencing the nitrogen and phosphorus losses. In the 800-1000 mm rainfall zone, the soil background nitrogen and phosphorus load was also a major factor influencing the nitrogen and phosphorus loss intensities.

Investigating the Relationship between Surface Water Pollution and Onsite Wastewater Treatment Systems.

Onsite wastewater treatment systems (OWTSs) are important nonpoint sources (NPSs) of pollution to consider in watershed management. However, limited OWTS data availability makes it challenging to account for them as an NPS of water pollution. In this study, we succeeded in obtaining OWTS permits and integrated them with environmental data to model the pollution potential from OWTSs at the watershed scale using GIS-based multicriteria decision analysis. Then, in situ water quality parameters─Escherichia coli (E. coli), total nitrogen, total phosphorus, temperature, and pH─were measured along the main tributary at base-flow conditions. Three general linear models were developed to relate E. coli to water quality parameters and OWTS pollution indicators. It was found that the model with the OWTS pollution potential had the lowest corrected Akaike information criterion (AICc) value (35.01) compared to the models that included classified OWTS pollution potential input criteria (AICc = 36.76) and land cover (AICc = 36.74). These results demonstrate that OWTSs are a significant contributor to surface water pollution, and future efforts should be made to improve access to OWTS data (i.e., location and age) to account for these systems as an NPS of water pollution.

Factors in homeowners' willingness to adopt nitrogen-reducing innovative/alternative septic systems.

When environmental mitigation requires individual adoption, engagement approaches centered on cost effectiveness and technological efficiency alone are often insufficient. Through focus groups with adopters and prospective adopters, this research identifies factors influencing homeowners' willingness to adopt Innovative/Alternative (I/A) septic systems for nitrogen reduction. We apply concepts from technology adoption and behavior change models as a framework for illustrating the homeowner decision-making process around I/A adoption. The perceived needs to replace an old/failing septic system, comply with local regulations, and protect local water quality synergistically catalyzed adoption. Adoption was further influenced by the larger context within which it is taking place, perceived characteristics of I/A systems and the installation process, system aesthetics concerns, and homeowners' attitudes and beliefs. Considering how these factors affect adoption could enable resource managers to design more targeted interventions to encourage adoption through behavior change strategies such as social marketing, and to improve how these systems are communicated. If I/A systems are to be used as a tool to achieve water quality goals, the considerations influencing homeowners' willingness to install these systems will be critical to incentivizing voluntary adoption. Many of these factors are relevant to the adoption of other individual-level environmental management strategies, which are being increasingly deployed in response to complex, nonpoint source pollution issues.

Study on the planning and influential factors of the safe width of riparian buffer zones in the upper and middle reaches of the Ziwu River, China.

In this study, we employed the random forest model to identify the riparian buffer zone in the upper and middle reaches of the Ziwu River, used the Soil and Water Assessment Tool (SWAT) to simulate and calculate the nonpoint source pollution load in the riparian buffer zone, and used empirical formulas to estimate the pollutant concentration when surface runoff passes the edge of the riparian buffer zone. Moreover, through correlation analysis, we identified the main factors that affect the safe width of the riparian buffer zone. By combining these factors with the characteristic parameters of the riparian buffer zone and the water quality demand, we analyzed and calculated the safe width of the riparian buffer zone. Our findings are as follows: ① the simulated values of the SWAT model were highly consistent with the measured values. Specifically, the calibration and verification results of the hydrological station achieved Ens ≥ 0.65, RE < ± 15%, and R2 ≥ 0.85, while the overall total nitrogen and total phosphorus loads achieved Ens ≥ 0.65, RE < ± 15%, and R2 > 0.65. ② We found that the total nitrogen (TN) and total phosphorus (TP) loads in the riparian buffer zone gradually increased from upstream to downstream. Among these loads, the normal season had the largest TN and TP concentrations reaching the edge of the riparian buffer zone, while the dry season had the minimum concentrations. ③ The factors affecting the safe width of the riparian buffer zone included the connectivity, slope of the buffer zone, cultivated land area, and regional population density. For the effective protection of water quality, it is recommended that the upstream, midstream, and downstream buffer zones be at least 77.9 m, 33.37 m, and 60.25 m wide, respectively.

Towards implementing precision conservation practices in agricultural watersheds: A review of the use and prospects of spatial decision support systems and tools.

Agricultural nonpoint source (NPS) pollution leads to water quality degradation. While agriculture is faced with the challenge of feeding a growing population in a changing climate, farmers must also strive to minimize adverse impacts of agriculture on the environment. As a result, policies, and agri-environmental programs to promote agricultural conservation practices for controlling NPS pollution have been emerging. Despite progress, reducing NPS is a complex challenge that requires ongoing innovation and investment. A major challenge is to achieve an optimal spatial trade-off between the economic costs and positive environmental outcomes of conservation practices on complex agricultural landscapes. Geospatial systems and tools can help to address this challenge and enhance the effectiveness and efficiency of conservation efforts. However, using these tools for precision conservation is underexamined. This review paper aims to address this gap through a critical exploration of spatial decision support systems and tools to provide synthesized knowledge for implementing precision conservation practices. This paper proposes a conceptual framework to guide the implementation of precision conservation and identifies areas for further development of geospatial systems and tools on planning and assessment of precision conservation efforts. All of which will be helpful for decision-makers and watershed managers in determining the most effective approaches for precision conservation. Furthermore, this review highlights the need for further research and development towards establishing an integrated spatial decision support system framework, which can improve socio-economic, environmental, and ecological outcomes.

River Basin Export Reduction Optimization Support Tool; a tool to screen options for reducing nutrient loads while minimizing cost.

Excess loading of nitrogen and phosphorus to river networks causes environmental harm, but reducing loads from large river basins is difficult and expensive. We develop a new tool, the River Basin Export Reduction Optimization Support Tool (RBEROST) to identify least-cost combinations of management practices that will reduce nutrient loading to target levels in downstream and mid-network waterbodies. We demonstrate the utility of the tool in a case study in the Upper Connecticut River basin in New England, USA. The total project cost of optimized lowest-cost plans ranged from $18.0 million to $41.0 million per year over 15 years depending on user specifications. Plans include both point source and non-point source management practices, and most costs are associated with urban stormwater practices. Adding a 2% margin of safety to loading targets improved estimated probability of success from 37.5% to 99%. The large spatial scale of RBEROST, and the consideration of both point and non-point source contributions of nutrients, makes it well suited as an initial screening tool in watershed planning.

Assessing and improving the outcomes of nonpoint source water quality trading policies in urban areas: A case study in Virginia.

Nonpoint source (NPS) water quality trading (WQT) is a market-based approach to improving water quality. Past work has shown that these programs could increase localized pollutant loadings, in part by exporting water quality controls from urban to rural areas. Virginia's NPS WQT program has enabled thousands of transactions and may provide a model for other programs, but its impacts on urban water quality have not been thoroughly assessed. We quantify the impact of NPS WQT purchases in Virginia on water quality and hydrology in an urban catchment. We go on to assess outcomes of a policy alternative where buyers and sellers are collocated in the urban catchment. Simulation results show that NPS WQT increased total phosphorus (TP) loading by an average of 0.8 lbs TP/year for each 1.0 offsite credits purchased in the analyzed catchment. The TP loading increased in years with greater rainfall, such that TP loads were increased by up to 1.2 lbs TP/year for each offsite credit purchased. These loading increases may or may not be acceptable, depending on the cumulative number of purchases within an urban catchment and existing local water quality issues. In our policy alternative with buyers and sellers collocated in the catchment, we found that the TP increase from development was completely offset at the catchment scale, with a decrease of 4.3 lbs TP/year for each 1.0 credits purchased. This suggests that credits awarded for urban mitigation practices are undervalued compared with water quality requirements for credit purchasers. This undervaluation is a result of the Virginia trading program using one approach to compute the credit value for buyers and a different approach to compute the credit value for sellers. We demonstrate how using a single model to determine both buyer and seller credit values in urban areas could provide greater transparency and mitigate the risk of urban pollution hot spots. This work demonstrates the importance of consistency in the scale of pollutant load calculations between buyers and sellers for NPS WQT, and contributes novel insight into the implications of WQT for urban NPS pollution.

Tire-Derived Transformation Product 6PPD-Quinone Induces Mortality and Transcriptionally Disrupts Vascular Permeability Pathways in Developing Coho Salmon.

Urban stormwater runoff frequently contains the car tire transformation product 6PPD-quinone, which is highly toxic to juvenile and adult coho salmon (Onchorychus kisutch). However, it is currently unclear if embryonic stages are impacted. We addressed this by exposing developing coho salmon embryos starting at the eyed stage to three concentrations of 6PPD-quinone twice weekly until hatch. Impacts on survival and growth were assessed. Further, whole-transcriptome sequencing was performed on recently hatched alevin to address the potential mechanism of 6PPD-quinone-induced toxicity. Acute mortality was not elicited in developing coho salmon embryos at environmentally measured concentrations lethal to juveniles and adults, however, growth was inhibited. Immediately after hatching, coho salmon were sensitive to 6PPD-quinone mortality, implicating a large window of juvenile vulnerability prior to smoltification. Molecularly, 6PPD-quinone induced dose-dependent effects that implicated broad dysregulation of genomic pathways governing cell-cell contacts and endothelial permeability. These pathways are consistent with previous observations of macromolecule accumulation in the brains of coho salmon exposed to 6PPD-quinone, implicating blood-brain barrier disruption as a potential pathway for toxicity. Overall, our data suggests that developing coho salmon exposed to 6PPD-quinone are at risk for adverse health events upon hatching while indicating potential mechanism(s) of action for this highly toxic chemical.

[Simulation of Pollution Apportionment and Optimization of Control Methods in Watershed Scale: A Case Study of the Shun'an Watershed in Tongling City].

The protection of the Yangtze River is an important national strategy in China, but it faces many problems such as difficult water environment protection, unclear pollution sources, and low integration of measures. Aimed at addressing watershed scale multi-source pollution together with facing the bottleneck method, by combining research data analysis, mechanism model, and intelligent algorithm optimization, this study built the framework for accurate pollution apportionment, measures evaluation, and overall measure optimization. Shun'an watershed in Tongling City of Anhui Province was set as an example for the application. The results showed that the new method could accurately quantify the impacts of planting industry, rural life, livestock and poultry breeding, aquaculture, industrial sewage, and domestic sewage in the watershed and evaluate the overall effects of various measures. The multi-objective optimization algorithm provided a cooperative multi-source pollution control scheme with higher cost performance and better environmental benefit by comparing the cost effectiveness of various schemes systematically. The optimization scheme showed that total nitrogen could be reduced by 1274.24 t·a-1 in wet years, 855.24 t·a-1 in normal years, and 381.96 t·a-1 in dry years. Total phosphorus was reduced by 321.42 t·a-1 in wet years, 159.80 t·a-1 in normal years, and 42.93 t·a-1 in dry years, such that the water quality reached the surface class Ⅲ water quality standard. These research results can be extended to other watersheds and provide a method reference for water environment protection under the background of the high-quality development of watersheds.

[Estimation of Cropland Nitrogen Runoff Loss Loads in the Yangtze River Basin Based on the Machine Learning Approaches].

A quantitative understanding of cropland nitrogen (N) runoff loss is critical for developing efficient N pollution control strategies. Using correlation analysis, a structural equation model, variance decomposition, and machine learning methods, this study identified the primary influencing factors of total N (TN) runoff loss from uplands (n=570) and paddy (n=434) fields in the Yangtze River Basin (YRB) and then developed a machine learning-based prediction model to quantify cropland N runoff loss load. The results indicated that runoff depth, soil N content, and fertilizer addition rate were the major influencing factors of TN runoff loss from uplands, whereas TN runoff loss rate from paddy fields was mainly regulated by runoff depth and fertilizer addition rate. Among the four used machine learning methods, the prediction models based on the random forest algorithm presented the highest accuracy (R2=0.65-0.94) for predicting upland and paddy field TN runoff loss rates. The random forest algorithm based model estimated a total cropland TN loss load in the YRB of 0.47 Tg·a-1 (upland:0.25 Tg·a-1; paddy field:0.22 Tg·a-1) in 2013, with 58% of TN runoff loss load derived from the midstream and downstream regions. The models predicted that TN runoff loss loads from croplands in YRB would decrease by 2.4%-9.3% for five scenarios, with higher TN load reductions occurring from scenarios with decreased runoff amounts. To mitigate cropland N nonpoint source pollution in YRB, it is essential to integrate efficient water, fertilizer, and soil nutrient managements as well as to consider the midstream and downstream regions as the high priority area. The machine learning-based modeling method developed in this study overcame the difficulty of identifying the functional relationships between cropland TN loss rate and multiple influencing factors in developing relevant prediction models, providing a reliable method for estimating regional and watershed cropland TN loss load.

Effects of biochar on runoff generation, soil and nutrient loss at the surface and underground on the soil-mantled karst slopes.

The effects of biochar (BC) on soil erosion and nutrient output have attracted widespread attention; however, the role of BC in soil and water conservation remains debated. In particular, the effect of BC on underground erosion and nutrient output in soil-mantled karst areas has not been clearly determined. The objective of this study was to investigate the effects of BC on soil and water conservation and nutrient output in surface-underground dual erosion structures in soil-mantled karst areas. Eighteen runoff plots (2 m × 1 m) were established at the Guizhou University research station. Two BC treatments (T1 = 30 t/ha; T2 = 60 t/ha) and a control treatment (CK = 0 t/ha) were used. The BC material was produced from corn straw. The experiment ran from January to December 2021 and a total of 1132.64 mm of rainfall was measured. Runoff and soil and nutrient loss at the surface and underground were collected during natural rainfall. The results showed that 1) compared to CK, the BC application significantly increased surface runoff (SR, P < 0.05) and reduced subsurface runoff (SF, P < 0.05), and underground fissure runoff (UFR) decreased in general but did not reach a significant level (P > 0.05). The total amount of SR collected in each treatment during the test period accounted for 51 %-63 % of the total amount of all collected outlet runoff (SR, SF and UFR); 2) total organic carbon (TOC), total nitrogen (TN) and total phosphorus (TP) were mainly exported through the UFR, and total potassium (TK) was mainly exported through the SR; and 3) compared to CK, the BC reduced TOC, TN and TP output through runoff but had no significant effect on TK output regardless of surface runoff or underground runoff. Thus, BC application reduces nonpoint source (NPS) pollution, and more importantly, it can inhibit TN and TP flow into groundwater through bedrock fissures. Our results provide further evidence for evaluating the soil and water conservation benefits of BC. Therefore, BC in soil-mantled karst agricultural areas can prevent groundwater pollution in karst regions. In general, BC enhances surface erosion and inhibits underground runoff and nutrients loss on soil-mantled karst slopes. This shows that the process through which BC application affects erosion in karst areas is complex, and further research is needed to investigate the long-term effects of BC application in this area.

Influence of concrete material of runoff collection containers on monitoring of nitrogen and phosphorus pollutants.

The accurate monitoring of N and P surface runoff losses from farmland is crucial to control agricultural nonpoint source pollution. A pond constructed with concrete material (CM) is a common collection container used during field experiments in China, but the adsorption characteristics of concrete may cause a considerable underestimation of surface runoff losses from farmland. To characterize any neglected error caused by the collection container material, a laboratory experiment was conducted comparing the N and P contents of runoff samples collected from CM and plastic material (PM) containers. The results indicated that CM containers significantly lowered N and P sample contents compared with PM containers, which was attributed to the adsorption capacity of pollutants by CM containers. This was confirmed by scanning electron microscopy (SEM) images of particles retained in CM containers. In an attempt to alleviate this error, three common water-repellent materials were applied to CM containers that significantly limited the pollutant adsorption of CM containers. Moreover, it was shown that there was no significant difference between the calculated concentration of runoff losses and the total amount of pollutants. To calibrate the observational error from CM containers, stepwise multiple regression models of different forms of N and P pollutants were developed. The results of this study suggest that treating CM containers with water repellent is an effective measure for improving the accuracy of new-built monitor points of agricultural nonpoint source pollutants. In addition, the calibration of observational error from CM containers and delayed sampling is essential to estimate agricultural nonpoint source pollution load via the surface runoff from farmland based on data from monitor points.

Evaluating the impacts of sustainable land management practices on water quality in an agricultural catchment in Lower Austria using SWAT.

Managing agricultural watersheds in an environmentally friendly manner necessitate the strategic implementation of well-targeted sustainable land management (SLM) practices that limit soil and nonpoint source pollution losses and translocation. Watershed-scale SLM-scenario modeling has the potential to identify efficient and effective management strategies from the field to the integrated landscape level. In a case study targeting a 66-hectare watershed in Petzenkirchen, Lower Austria, the Soil and Water Assessment Tool (SWAT) was utilized to evaluate a variety of locally adoptable SLM practices. SWAT was calibrated and validated (monthly) at the catchment outlet for flow, sediment, nitrate-nitrogen (NO3-N), ammonium nitrogen (NH4-N), and mineralized phosphorus (PO4-P) using SWATplusR. Considering the locally existing agricultural practices and socioeconomic and environmental factors of the research area, four conservation practices were evaluated: baseline scenario, contour farming (CF), winter cover crops (CC), and a combination of no-till and cover crops (NT + CC). The NT + CC SLM practice was found to be the most effective soil conservation practice in reducing soil loss by around 80%, whereas CF obtained the best results for decreasing the nutrient loads of NO3-N and PO4-P by 11% and 35%, respectively. The findings of this study imply that the setup SWAT model can serve the context-specific performance assessment and eventual promotion of SLM interventions that mitigate on-site land degradation and the consequential off-site environmental pollution resulting from agricultural nonpoint sources.

Integrated assessment of land-to-river Cd fluxes and riverine Cd loads using SWAT-HM to guide management strategies.

In 2011, China invested US$9.8 billion to combat the severe heavy metal pollution in the Xiang River basin (XRB), aiming to reduce 50% of the 2008 industrial metal emissions by 2015. However, river pollution mitigation requires a holistic accounting of both point and diffuse sources, yet the detailed land-to-river metal fluxes in the XRB remain unclear. Here, by combining emissions inventories with the SWAT-HM model, we quantified the land-to-river cadmium (Cd) fluxes and riverine Cd loads across the XRB from 2000 to 2015. The model was validated against long-term historical observations of monthly streamflow and sediment load and Cd concentrations at 42, 11, and 10 gauges, respectively. The analysis of the simulation results showed that the soil erosion flux dominated the Cd exports (23.56-80.14 Mg yr-1). The industrial point flux decreased by 85.5% from 20.84 Mg in 2000 to 3.02 Mg in 2015. Of all the Cd inputs, approximately 54.9% (37.40 Mg yr-1) was finally drained into Dongting Lake; the remaining 45.1% (30.79 Mg yr-1) was deposited within the XRB, increasing the Cd concentration in riverbed sediment. Furthermore, in XRB's 5-order river network, the Cd concentrations in small streams (1st order and 2nd order) showed larger variability due to their low dilution capacity and intense Cd inputs. Our findings highlight the need for multi-path transport modeling to guide future management strategies and better monitoring schemes to restore the small polluted streams.

New method for scaling nonpoint source pollution by integrating the SWAT model and IHA-based indicators.

Nonpoint source (NPS) pollution shows spatial scaling effects because it is affected by topography, river networks, and many other factors. Currently, the lack of an integrated methodology for quantifying the scaling effect has become a crucial barrier in evaluating NPS pollution. In this study, a new method was proposed for scaling NPS pollution by integrating hydrological model and hydrological alteration indicators. Nested catchments were delineated by eight-direction algorithm, and a semidistributed hydrological model was used to simulate the interannual process within the drainage area and to obtain data series of runoff, sediment, and total phosphorus (TP) at different spatial scales. In addition, the average, the extrema, the change rate and feature variables of each type of indicators were proposed to quantitatively describe the pattern of NPS pollution at different spatial scales. The results show the coefficients of variation (CVs) of most runoff and TP indicators are 0.6-0.8, while those of sediment vary greatly from 0.4 to 1.6 with the threshold of those indicators being 0.33. With the increase in drainage area, the NPS load-related indicators show an increasing trend, while load intensity indicators show a decreasing trend and their changing patterns are affected by the heterogeneity of topographic or hydrological information included. Based on logarithmic variance of the change rate, 825 km2 was identified as the turning point for scaling transformation where the slope changes dramatically. The proposed methodology comprehensively describes features of the NPS scaling effect that could be utilized for targeted monitoring and control of NPS pollution in other watersheds.