A review of non-point source water pollution modeling for the urban-rural transitional areas of China: Research status and prospect

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.

Arsenic pollution concerning surface water and sediment of Jie River: A pilot area where gold smelting enterprises are concentrated

A comprehensive monitoring and risk assessment of arsenic (As) pollution concerning surface water and sediment is performed in the Jie River basin, where gold smelting enterprises are concentrated. The study area is divide into six regions, labeled as A, B, C, D, E, and F, from sewage outlets to downstream. Results shows that with far away from the sewage outlets, the total As concentrations in water and sediment gradually decrease from regions A to F. However, in region F, the concentration of bioavailable As significantly increases in the sediment due to the higher pH, leading to the transformation of As(V) into more mobile As(III). In sediment, Paracladius sp. exhibits strong resistance to As pollution in sediment, which can potentially elevate the risk of disease transmission. In water bodies, diatoms and euglena are the main phytoplankton in the Jie River while toxic cyanobacteria exhibits lower resistance to As pollution. Overall, measures should be taken to ecologically remediate the sediment in downstream while implementing appropriate isolation methods to prevent the spread of highly contaminated sediments from regions near sewage outlets.

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.

Assessing nutrient fate from terrestrial to freshwater systems using a semi-distributed model for the Fuxian Lake Basin, China

The growing and increasingly intensified agricultural sector exerts major pressures on the environment. Specifically, nitrogen (N) and phosphorus (P) runoff can induce eutrophication in freshwater ecosystems. To formulate environmental strategies for controlling eutrophication, decision-makers commonly consider the importance of pollutant contributors before developing sector-specific environmental policies. These types of science-based decisions benefit from nutrient models that quantify nutrient transport and fate. However, due to a lack of fertilizer application data, distributed models are generally not suitable for most rural regions with extensive agriculture, while lumped models cannot properly characterize the spatial variation of nutrient fate in these regions. To assess the nutrient contributions from different emission sources to freshwater, we developed a localized semi-distributed model to simulate total nitrogen (TN) and total phosphorus (TP) in 52 inflow rivers of Fuxian Lake Basin in China. The results show that diffuse sources contributed 82 % TN and 92 % TP loading to the inflow rivers. The highest eutrophication potentials (i.e., loading per area) is from the built environment, which is more than 10 times that of forests, but the contribution of the built environment to total diffuse loading is only the second-highest as it occupies 8.7 % of the surface area. Farmland is the main contributor, generating 49 % of diffuse TN and 57 % TP, respectively. Our results show that promoting a 10 % increase in nutrient use efficiency would reduce 5 % of N and 30 % of P diffuse loadings to the rivers. Through examining the impact of nutrient use efficiency, we emphasize the potential trade-offs between food productivity and environmental effects. This analysis workflow can be applied to other agricultural regions.

A novel approach to identify priority areas for optimal nutrient management in mixed land-use watersheds through nutrient budget assessment

Excessive nutrient supply in agricultural regions has led to various environmental issues, thereby requiring concentrated management owing to its persistent upward trend. Nutrient budgets (NBs), a vital agricultural environmental indicator, are employed for nutrient management in agricultural areas, using data surveyed by administrative agencies. However, the spatial extent of nutrient data for nutrient budgeting is limited by administrative boundaries according to the surveying organization, posing challenges in interpreting spatial patterns at the watershed level. In this study, a novel approach was developed to identify priority nutrient management areas by applying hot spot spatial analysis to watershed-level NBs, considering hydrological characteristics. This method was applied to approximately 850 subwatersheds across the Republic of Korea, where land cover characteristics are complex. Reassessing nutrient budgets at the watershed scale, accounting for overlapping administrative boundary areas and crop cultivation ratios, indicated similar levels between the two methods. Hot spot analysis revealed that watersheds with elevated NBs mirrored the spatial patterns of livestock excreta and cropland. The spatial distribution characteristics of watersheds with high nutrient levels in rivers corresponded with the concentration characteristics of industrial and commercial areas. Therefore, applying watershed-level NBs based on land cover ratios that consider nutrient input characteristics in agricultural regions is deemed appropriate for selecting priority nutrient management areas. Collectively, this study presents a method for selecting nutrient management priority areas by simultaneously considering the spatial characteristics of various environmental factors, such as land cover, livestock excreta, river water quality, and land area-based watershed-specific NBs. The proposed approach, considering mixed land cover characteristics, is anticipated to be valuable for selecting priority management areas in watersheds with diverse pollution sources. Future research is needed to explore nutrient budgets within watersheds, the influence of land use on pollution sources, and their correlation with water quality.

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.

Conflict between urbanization and water environmental protection: Lessons from the Xiangjiang River Basin in China

China, the largest developing country, has experienced rapid urbanization since its reform and opening-up. However, the increasing pollution load from urban areas has deteriorated urban river water quality, contradicting the concept of sustainable and green development promoted by the Chinese government. This situation elucidates governmental shortcomings in systematic environmental protection. Our study revealed that the current wastewater treatment plant (WWTP) discharge standards in urban areas are insufficient for attaining the desired urban river water quality and thus intensify the conflict between urbanization and water environmental protection. As urbanization continues, the urban population will grow, further exacerbating pollution and conflict. Our focus was the Xiangjiang River basin in Zunyi, a typical urbanized city in China. Using a validated one-dimensional mathematical model, we compared the water quality in the Xiangjiang River between current and upgraded WWTP discharge standards. The results showed that the water quality in the Xiangjiang River falls short of the standards, with more than 60 % of the river exceeding limits. However, upgrading WWTP discharge standards significantly reduces the proportion of river sections exceeding limits, with only 0.4 % exceeding standards during specific periods. This enhancement greatly improved the Xiangjiang River's water quality, aided in restoring the entire water environment in the basin, and supported water environmental protection goals. Our research findings offer crucial support for local governments in shaping comprehensive water environmental protection policies and insights for addressing similar environmental challenges caused by rapid urbanization in other developing regions.

Sustainable governance of drinking water conservation areas based on adaptive thresholds

Drinking water quality is integral to the Sustainable Development Goals framework. At the present, China's drinking water conservation faces a number of challenges that are partially brought on by strict conservation measures that don't fully take into account human-land conflict and sustainable development. Taking the idea of adaptive governance, this study seeks to identify adaptive thresholds and adaptive solutions for compatible drinking water conservation and local development. Pressure and resistance to drinking water quality in its status, future potential, and adaptive thresholds were explored to identify sustainable governance for the Baimei Conservation Area, Fujian Province. Field research, local governance forums, and the Soil and Water Assessment Tool (SWAT) model were utilized to explore the drinking water quality pressure and resistance to drinking water quality. In order to uncover potential future changes in pressure and resistance, suitability analyses and multi-scenario simulations were used to examine the status quo, pressure, and resistance scenarios. Adaptive thresholds were then identified through SWAT modeling of each scenario to guarantee the drinking water quality is greater than Class II in the Core Conservation Area and Class Ⅲ in 2nd-grade Conservation Area, respectively. The research finds that construction land development and farming are the key pressures on drinking water quality, and forests and wetlands are the primary resistances. The expansion of construction lands and the increased wetlands was centered on potential future scenarios because farming has no room for growth and forests are already heavily covered. The adaptive threshold of construction land expansion is identified to be 10% without new wetlands but can be 20% by adding 10% wetlands in subbasins, 5, 8, and 9. This study confirms the potential of adaptive sustainability for drinking water conservation areas. A similar analysis procedure can also be adapted to enhance adaptive governance for the sustainability of other conservation areas nationally and globally.

A critical review on the separation of heavy metal(loid)s from the contaminated water using various agricultural wastes

Wastewater contamination with heavy metal(loids)s has become a worldwide environmental and public health problem due to their toxic and non-degradable nature. Different methods and technologies have been applied for water/wastewater treatment to mitigate heavy metal(loid)-induced toxicity threat to humans. Among various treatment methods, adsorption is considered the most attractive method because of its high ability and efficiency to remove contaminants from wastewater. Agricultural waste-based adsorbents have gained great attention because of high efficiency to heavy metal(loids)s removal from contaminated water. Chemically modified biosorbents can significantly enhance the stability and adsorption ability of the sorbents. The two mathematical models of sorption, Freundlich and Langmuir isotherm models, have mostly been studied. In kinetic modeling, pseudo-second-order model proved better in most of the studies compared to pseudo-first-order model. The ion exchange and electrostatic attraction are the main mechanisms for adsorption of heavy metal(loid)s on biosorbents. The regeneration has allowed various biosorbents to be recycled and reused up to 4-5 time. Most effective eluents used for regeneration are dilute acids. For practical perspective, biosorbent removal efficiency has been elucidated using various types of wastewater and economic analysis studies. Economic analysis of adsorption process using agricultural waste-based biosorbents proved this approach cheaper compared to traditional commercial adsorbents, such as chemically activated carbon. The review also highlights key research gaps to advance the scope and application of waste peels for the remediation of heavy metal(loid)s-contaminated wastewater.

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.

Research on water quality improvement of plain irrigation area based on multi-scenario simulation

Water diversion projects have proven to be effective interventions to improve water quality in irrigation ditches. This study focused on quantifying the water quality improvement by utilizing a hydrodynamic water quality model in Funing County, Yancheng City. The model performed a spatial analysis of pollution concentrations across the study area. Various optimization scenarios were designed based on the diversion project and hydrological structure connectivity. The model was used to simulate changes in nutrient concentrations under different scenarios. The findings of this study were as follows: (1) Rural areas had lower nutrient concentrations and superior hydrological connectivity than urban areas. (2) The effect of water quality improvement correlated positively with increased flow rates introduced by the diversion project. Specifically, when the flow rate increased by 50%, the average reductions were 20% for NH4+, 5.2% for TN, and 5.1% for TP. Furthermore, introduced clean water led to more pronounced improvements in the overall regional water quality. (3) Although increasing the number of ditches improved water pollution concentration, the impact was not significant. (4) Model simulation results showed that 18 to 45% water diversion intensity effectively improved water quality, and the optimal water diversion intensity was 27 to 30%. The optimal water diversion intensities offered valuable insights for managing this region. The study's methods contributed to the promotion of sustainable development in regional water resources and the integrated management of the water environment.

Water quality improvement project for initial rainwater pollution and its performance evaluation

Efficiently addressing initial rainwater pollution is crucial for mitigating urban water pollution. However, the performance evaluation of initial rainwater pollution control project is rarely introduced. In this study, the architecture of effective comprehensive engineering measures for improving the water quality of initial rainwater in Anhui Province, China, was described. Three water quality indicators, ammonia nitrogen (NH3-N), chemical oxygen demand (COD), and total phosphorus (TP), were selected to explore the severity of urban pollution caused by initial rainwater under various rainfall scenarios. A single-factor evaluation method was used to contrast and assess the benefits of the initial rainfall interception project in terms of water quality enhancement. Results showed that initial rainfall pollution was gentler under light rainfall conditions but more prominent under moderate and heavy conditions. The percentages of NH3-N, COD, and TP in Lotus Pond that met the tertiary drinking water standard were 100%, 74.91%, and 100% with great improvement, and the average concentrations of NH3-N, COD, and TP in Fushan Road Drainage have decreased by 91.43%, 10.49%, and 57.33% respectively, after the construction of the interception project. These indicated that the nitrogen and phosphorus pollution were successfully controlled by the control techniques in both locations, but COD concentration has to be addressed with more specialized strategies. Overall, the water quality improvement project for initial rainwater pollution plays a great role in effectively governing initial rainwater pollution and improving river water quality, and provides an effective technical reference for urban water ecological environment management.

An assessment of approaches and techniques for estimating water pollution releases from aquaculture production facilities

The rapid expansion of the aquaculture industry raises concerns about water pollution from aquaculture production facilities (APFs). APFs release pollutants, including fish feed and feces, threatening the environment. The United Nations has introduced regulatory tools like the National Baseline Budget of pollutants (NBB) and Pollutant Release and Transfer Registers (PRTRs) to monitor pollution. However, these tools lack specific capabilities for estimating aquaculture-related pollution, especially from mariculture non-point sources (NPS). The United Nations Programme for the Assessment and Control of Marine Pollution in the Mediterranean (UNEP/MAP) stresses the need for an inventory and guidance document. Our comprehensive literature review focused on (1) NPS discharges of specific pollutants from APFs, (2) methods for estimating potential pollution releases from aquaculture, and (3) compiling information into a guidance document summarizing estimation methods. The geographical coverage of our study includes Europe, Australia, the USA, Canada, and East/Southeast Asia.

Integrated prediction of water pollution and risk assessment of water system connectivity based on dynamic model average and model selection criteria

In recent years, with the rapid development of economy and society, river water environmental pollution incidents occur frequently, which seriously threaten the ecological health of the river and the safety of water supply. Water pollution prediction is an important basis for understanding development trends of the aquatic environment, preventing water pollution incidents and improving river water quality. However, due to the large uncertainty of hydrological, meteorological and water environment systems, it is challenging to accurately predict water environment quality using single model. In order to improve the accuracy and stability of water pollution prediction, this study proposed an integrated learning criterion that integrated dynamic model average and model selection (DMA-MS) and used this criterion to construct the integrated learning model for water pollution prediction. Finally, based on the prediction results of the integrated learning model, the connectivity risk of the connectivity project was evaluated. The results demonstrate that the integrated model based on the DMA-MS criterion effectively integrated the characteristics of a single model and could provide more accurate and stable predictions. The mean absolute percentage error (MAPE) of the integrated model was only 11.1%, which was 24.5%-45% lower than that of the single model. In addition, this study indicates that the nearest station was the most important factor affecting the performance of the prediction station, and managers should pay increased attention to the water environment of the control section that is close to their area. The results of the connectivity risk assessment indicate that although the water environment risks were not obvious, the connectivity project may still bring some risks to the crossed water system, especially in the non-flood season.

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.

Assessing effect of best management practices in unmonitored watersheds using the coupled SWAT-BiLSTM approach

In order to enhance the simulation of BMPs (Best Management Practices) reduction effects in unmonitored watersheds, in this study, we combined the physically-based hydrological model Soil & Water Assessment Tool (SWAT) and the data-driven model Bi-directional Long Short-Term Memory (Bi-LSTM), using the very-high-resolution (VHR) Land Use and Land Cover (LULC) dataset SinoLC-1 as data input, to evaluate the feasibility of constructing a water environment model for the Ba-River Basin (BRB) in central China and improving streamflow prediction performance. In the SWAT-BiLSTM model, we calibrated the top five SWAT parameters sorted by P-Value, allowing SWAT to act as a transfer function to convert meteorological data into base flow and storm flow, serving as the data input for the Bi-LSTM model. This optimization improved the Bi-LSTM's learning process for the relationship between the target and explanatory variables. The daily streamflow prediction results showed that the hybrid model had 9 regions rated as "Very good," 2 as "Good," 2 as "Satisfactory," and 1 as "Unsatisfactory" among the 14 regions. The model achieved an NSE of 0.86, R2 of 0.85, and PBIAS of -2.71% for the overall daily streamflow prediction performance during the verification period of the BRB. This indicates that the hybrid model has high predictive accuracy and no significant systematic bias, providing a sound hydrodynamic environment for water quality simulation. The simulation results of different BMPs scenarios showed that in the scenarios with only one BMP measure, stubble mulch had the best reduction effect, with average reductions of 17.83% for TN and 36.17% for TP. In the scenarios with a combination of multiple BMP measures, the combination of stubble mulch, soil testing and formula fertilization, and vegetative filter strip performed the best, achieving average reductions of 42.71% for TN and 50.40% for TP. The hybrid model provides a novel approach to simulate BMPs' reduction effects in regions without measured hydrological data and has the potential for wide application in BMP-related decision-making.

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.

An advanced remote sensing retrieval method for urban non-optically active water quality parameters: An example from Shanghai

The optical insensitivity of non-optically active water quality parameters (NAWQPs) presents a significant challenge for remote sensing-based quantitative monitoring, which is an important tool for water quality assessment and management. Based on the analysis of the samples from Shanghai, China, it was found that the spectral morphological characteristics of the water body were obviously different under the combined effect of multiple NAWQPs. In view of this, in this paper, a machine learning method was proposed for the retrieval of urban NAWQPs by using multi-spectral scale morphological combined feature (MSMCF). The proposed method integrates both local and global spectral morphological features, and employs a multi-scale approach to enhance its applicability and stability, providing a more accurate and robust solution. To explore the applicability of the MSMCF method in retrieving urban NAWQPs, different methods were tested in terms of the retrieval accuracy and stability on the measured data and three different hyperspectral data. As can be seen from the results, the proposed method has good retrieval performance, which can be applied to hyperspectral data with different spectral resolutions with certain ability to suppress noise. Further analysis indicates that the sensitivity of each NAWQP to spectral morphological features varies. The research methods and findings in this paper can promote the development of hyperspectral and remote sensing technology in the prevention and treatment of urban water quality deterioration, and provide reference for related research.

Identifying critical regions for nitrogen and phosphorus loss management in a large-scale complex basin: The Jialing River

The determination of critical management areas for nitrogen (N) and phosphorus (P) losses in large-scale basins is critical to reduce costs and improve efficiency. In this study, the spatial and temporal characteristics of the N and P losses in the Jialing River from 2000 to 2019 were calculated based on the Soil and Water Assessment Tool (SWAT) model. The trends were analyzed using the Theil-Sen median analysis and Mann-Kendall test. The Getis-Ord Gi* was used to determine significant coldspot and hotspot regions to identify critical regions and priorities for regional management. The ranges of the annual average unit load losses for N and P in the Jialing River were 1.21-54.53 kg ha^-1 and 0.05-1.35 kg ha^-1, respectively. The interannual variations in both N and P losses showed decreasing trends, with change rates of 0.327 and 0.003 kg ha^-1·a^-1 and change magnitudes of 50.96% and 41.05%, respectively. N and P losses were highest in the summer and lowest in the winter. The coldspot regions for N loss were clustered northwest of the upstream Jialing River and north of Fujiang River. The coldspot regions for P loss were clustered in the central, western, and northern areas of the upstream Jialing River. The above regions were found to be not critical for management. The hotspot regions for N loss were clustered in the south of the upstream Jialing River, the central-western and southern areas of the Fujiang River, and the central area of the Qujiang River. The hotspot regions for P loss were clustered in the south-central area of the upstream Jialing River, the southern and northern areas of the middle and downstream Jialing River, the western and southern areas of the Fujiang River, and the southern area of the Qujiang River. The above regions were found to be critical for management. There was a significant difference between the high load area for N and the hotspot regions, while the high load region for P was consistent with the hotspot regions. The coldspot and hotspot regions for N would change locally in spring and winter, and the coldspot and hotspot regions for P would change locally in summer and winter, respectively. Therefore, managers should make specific adjustments in critical regions for different pollutants according to seasonal characteristics when developing management programs.

Output characteristics and driving factors of non-point source nitrogen (N) and phosphorus (P) in the Three Gorges reservoir area (TGRA) based on migration process: 1995-2020

Although physical models at present have made important achievements in the assessment of non-point source pollution (NPSP), the requirement for large volumes of data and their accuracy limit their application. Therefore, constructing a scientific evaluation model of NPS nitrogen (N) and phosphorus (P) output is of great significance for the identification of N and P sources as well as pollution prevention and control in the basin. We considered runoff, leaching and landscape interception conditions, and constructed an input-migration-output (IMO) model based on the classic export coefficient model (ECM), and identified the main driving factors of NPSP using geographical detector (GD) in Three Gorges Reservoir area (TGRA). The results showed that, compared with the traditional export coefficient model, the prediction accuracy of the improved model for total nitrogen (TN) and total phosphorus (TP) increased by 15.46 % and 20.17 % respectively, and the error rates with the measured data were 9.43 % and 10.62 %. It was found that the total input volume of TN in the TGRA had declined from 58.16 × 10⁴ t to 48.37 × 10⁴ t, while the TP input volume increased from 2.76 × 10⁴ t to 4.11 × 10⁴ t, and then decreased to 4.01 × 10⁴ t. In addition Pengxi River, Huangjin River and the northern part of Qi River were high value areas of NPSP input and output, but the range of high value areas of migration factors has narrowed. Pig breeding, rural population and dry land area were the main driving factors of N and P export. The IMO model can effectively improve prediction accuracy, and has significant implications for the prevention and control of NPSP.

A new paradigm of sewage collection in rural areas

Rural sewage collection networks play extremely important roles in rural sewage treatment, and the lack of a suitable collection model makes this task difficult. Hence, there is an urgent need to develop a new method to collect and deal with rural sewage. This paper establishes a rural sewage optimal collection model (RSOCM) with critical distance (d) and sewage quota per unit area (q_s) as the constraint factors. The implementation of critical distance for rural sewage collection pipeline networks was demonstrated for 38 rural areas in the Huicheng District, Huizhou City, Guangdong Province of China. The average critical distances of 22 m, 38 m, 29 m, 29 m, 41 m, and 55 m were demonstrated for Sandong Town, Ma'an Town, Luzhou Town, Ruhu Town, Hengli Town, and Shuikou Subdistrict, respectively. The q_s is used to create the best possible pipe network layout, determine the appropriate treatment method, and reduce construction costs. This model can be widely applied to sewage collection in rural areas of China, where the overall sewage collection system can implement different regional strategies to maximize rural pollution control and protect the environment.

The Eco-Agricultural Industrial Chain: The Meaning, Content and Practices

Lucid waters and lush mountains are invaluable assets. Resource-saving and environmentally friendly industrial structures, production, and living modes are pursued continuously for sustainable ecological development. According to the Second National Pollution-Source Survey, agricultural non-point pollution is still the most important source of the current water pollution. In order to improve the water environment and control the pollution, the meaning and content of the eco-agricultural industrial chain was introduced. Based on this conception, the eco-agricultural industrial chain, integrating a whole circular system with different sessions of crop farming, animal breeding, agricultural product processing, and rural living, was innovatively put forward to control the agricultural non-point pollution and protect the water environment systematically for the first time in this paper. The sustainable development was realized at a large scale from the reduction and harmlessness at the source, resource utilization in the process, and ecological restoration in the end. Core techniques were innovated based on the integration of agricultural industries to achieve the high-quality and green development of agriculture. The system included ecological breeding technologies, ecological cultivation technologies, as well as rural sewage treatment and recycling technologies, in the principle of reduce, reuse, and resource. Based on this, the agricultural production changed from the traditional mode of "resources-products-wastes" to the circulation pattern of "resources-products-renewable resources-products". Thus, the final aim could be achieved to realize the material's multilevel use and energy conversion in the system. The eco-agricultural industrial chain technology was proven to be efficient to achieve both the good control of agricultural non-point pollution and an effective improvement in the water quality.

Advances in microbial electrochemistry-enhanced constructed wetlands

Constructed wetland (CW) is an effective ecological technology to treat water pollution and has the significant advantages of high impact resistance, simple construction process, and low maintenance cost. However, under extreme conditions such as low temperature, high salt concentration, and multiple types of pollutants, some bottlenecks exist, including the difficulty in improving operating efficiency and the low pollutant removal rate. Microbial electrochemical technology is an emerging clean energy technology and has the similar structure and pollutant removal mechanism to CW. Microbial electrochemistry combined with CW can improve the overall removal effect of pollutants in wetlands. This review summarizes characterization methods of microbial electrochemistry-enhanced constructed wetland systems, construction methods of different composite systems, mechanisms of single and composite systems, and removal effects of composite systems on different pollutants in water bodies. Based on the shortcomings of existing studies, the potential breakthroughs in microbial electrochemistry-enhanced constructed wetlands are proposed for developing the optimization solution of constructed wetlands.

Improving the accuracy of nonpoint-source pollution estimates in inland waters with coupled satellite-UAV data

Quantitatively and accurately analyzing nonpoint-source (NPS) pollution is essential for efficiently preventing the input of NPS loads into inland waters. However, the accuracy of previous NPS pollution models is limited by the accuracy of ground parameter data. In addition, there are few effective methods that thoroughly verify modeling results at large scales. This paper presents a framework for accurate NPS pollution estimation by coupling satellite and unmanned aerial vehicle (UAV) monitoring data, and the results are verified by both field sampling and a newly developed inlet NPS pollution "observation" simulation method. Fractional vegetation coverage (FVC) data obtained by satellite were used to improve the accuracy of the runoff module of the framework. Satellite and UAV data were coupled to acquire livestock data, determine inlets, and identify reservoir buffer zones and vegetation types. These new data were then used to improve the accuracy of the livestock and runoff modules in the framework. The results show that the estimation accuracy of total nitrogen, total phosphorus, ammonia nitrogen, and chemical oxygen demand with FVC were improved by 39.96%, 69.29%, 54.05% and 47.22% (in relative error), respectively. The high-resolution livestock data acquisition improved the estimation accuracy of the NPS pollution load by 7-53%. The high-resolution inlet extraction improved the accuracy by 3-24%. The high-resolution buffer zone identification improved the accuracy with the estimated NPS pollutant concentration into reservoir decreasing by 60-99%. Finally, the high-resolution vegetation type identification improved the accuracy by 10-72%. The framework performs satisfactorily, which was verified based on the simulated NPS observations with an average relative error of 11.54-24.31%. We found that the FVC, livestock number, and inlet number are key parameters for NPS pollution modeling; the introduction of monthly variation in the FVC makes the modeled NPS pollution load much higher in areas with mature complex forested ecosystems or densely distributed vegetation but much lower in areas with sparsely distributed vegetation. The above methods provide a scientific reference for high-efficiency NPS pollution prevention in inland waters, laying a solid basis for decision-making regarding water quality management in data-scarce regions around the world.

Durable 3D Porous Superhydrophobic Composites for Versatile Emulsion Separation in Multiple Environments

Polydopamine as a multifunctional biomimetic polymer with nonselective strong adhesion properties has become a hot research topic in recent years. However, there are a few reports on the durable and effective emulsion separation of polydopamine composites from other materials. Therefore, it is necessary to construct durable polydopamine composites to achieve selective adsorption of materials. In this work, polypyrrole (PPy)-PDA was obtained on sponges by an in situ polymerization reaction, followed by the attachment of SiO₂ nanoparticles to the surface by polydimethylsiloxane to achieve superhydrophobicity. As a result, previously unreported selective superhydrophobic adsorbents for PPy-PDA coatings were obtained. The prepared sponges have an excellent adsorption capacity for oils and organic solvents. Not only can the sponges absorb 19-39 g of organic solvents per gram but they can also absorb oil from oil-in-water emulsions. The chemical oxygen demand value of the emulsion can be reduced to 219 mg/L after separation. More importantly, the performance remains good in the cycle test, and due to the construction of a durable superhydrophobic sponge, it can still maintain its relatively good performance in artificial seawater, acid-base environments, and can achieve relatively stable emulsion separation. At the same time, the potential of the polymer material composited with PDA in lasting and stable emulsion separation was also verified.

Spatiotemporal Pattern of Urban-Rural Integration Development and Its Driving Mechanism Analysis in Hangzhou Bay Urban Agglomeration

The quantitative analysis of the urban-rural integration development (URID) level and its driving factors is of great significance for the new-type urbanization of urban agglomerations. This study constructed a multidimensional framework in the perspective of a population–space–economy–society–ecology framework to measure the URID level from 2000 to 2020 and further explored the driving mechanism of the URID changes by a geographical detector model in the Hangzhou Bay urban agglomeration (HBUA). The results showed that the land-use change in the HBUA from 2000 to 2020 showed a typical characteristic of the transition between cultivated and construction land. The URID level in the HBUA improved from 0.294 in 2000 to 0.563 in 2020, and the year 2005 may have been the inflection point of URID in the HBUA. The URID level showed a significant spatial aggregation with high values. Hangzhou, Jiaxing, and Ningbo were hot spots since 2015, and the cold spots were Huzhou and Shaoxing. The population and spatial integration had more important impacts on URID levels in 2000, 2005, and 2020, while economic and social integration had more significant impacts on URID levels in 2010 and 2015. This study provided a deeper understanding of the evolution of URID in an urban agglomeration and could be used as a reference for decision makers.

Phenology–Gross Primary Productivity (GPP) Method for Crop Information Extraction in Areas Sensitive to Non-Point Source Pollution and Its Influence on Pollution Intensity

The excessive use of pesticides and fertilizers during agricultural production causes water pollution, which is an important type of non-point source pollution (NSP). Large amounts of harmful substances, such as nitrogen and phosphorus, flow into surface water along with farmland runoff, leading to eutrophication and other problems. However, the pollutant discharge capacity of different types of cultivated land varies greatly. Areas sensitive to NSP are areas with rich crop types, large spatial differences in crop growth, and complex planting patterns. These factors can cause different amounts of fertilizer used in and absorbed by the crops to influence the emission intensity of pollutants. NSP intensity mapping can reflect the spatial distribution of lands’ pollutant discharge capacity and it can provide a basis for pollution control. However, when estimating NSP intensity, existing methods generally treat cultivated land as a category and ignore how complex crop conditions impact pollution intensity. Remote sensing technology enables the classification and monitoring of ground objects, which can provide rich geographical data for NSP intensity mapping. In this study, we used a phenology–GPP (gross primary productivity) method to extract the spatial distribution of crops in the Yuecheng reservoir catchment area from Sentinel-2 remote sensing images and the overall accuracy reached 85%. Moderate resolution imaging spectroradiometer (MODIS) GPP data were used to simulate the spatial distribution of crop growth. Finally, a new model that is more suitable for farmland was obtained by combining this large amount of remote sensing data with existing mapping models. The findings from this study highlight the differences in spatial distributions between total nitrogen and total phosphorous; they also provide the means to improve NSP intensity estimations.

Quantification and Evaluation of Grey Water Footprint in Yantai

Problems such as water scarcity and pollution frequently occur in coastal zones. This study investigated the grey water footprint and the sustainability and intensity of grey water footprint in Yantai between 2014 and 2019 by taking both surface water and groundwater into consideration. The research results indicated that the Yantai grey water footprint firstly increased and then decreased between 2014 and 2019. The lowest grey water footprint in 2019 was 744 million m3. The agricultural grey water footprint accounted for a large proportion of the total grey water footprint. Although the sustainability of grey water footprint fluctuates in Yantai, it maintains well. The Yantai grey footprint intensity gradually decreased to <10 m3/10,000 CNY. The economic benefit of grey water footprint and utilization efficiency of water resources have been improved yearly. The quality of the water environment in Yantai has also been improved. The research of this paper provides some useful information for water resources protection and sustainable utilization in coastal cities.