Nonpoint Source Pollution Control Research Articles

Comparative assessment of pollution control measures for urban water bodies in urban small catchment by SWMM

Under the current increasingly serious water pollution situation in urban, the comprehensive treatment and protecting measures in urban small catchment are the necessary step to the water pollution treatment, not only focus on the water bodies themself. In this paper, the Luojiagang river channel and its catchment in Wuhan, which has been heavily impacted by water pollution, are taken as an example for the comparative assessment of pollution control measures in order to explore the effective and sustainable schemes including the LID (Low Impact Development---LID) by using SWMM model (Storm Water Management Model---SWMM). Through the comparison of pollution treatment measures based on scenarios simulation with the baseline scenarios, it was found that the reduction effects of pollutant peak concentrations at the outlet node of Luojiagang River had the decreasing order of: the combined measures (COS) > LID control > the water diversion from Donghu Lake (WAD) > the sewage treatment (SET) > the sediment dredging (SED), and the reduction effects of total pollutant load had the decreasing order of: LID > COS > SET > SED > WAD. The results show that the control of non-point source pollution is the key for the improvement of water quality in Luojiagang River, and LID plays important role in the reduction of both pollutant peak concentrations and load. This study has the implication for the decision making of the water pollution controlling schemes in urban small catchment.

Innovative upcycling gabions with coal bottom ash for nonpoint source pollution control against climate change

Climate change accelerates extreme temperature fluctuations and rainfall volatility, and shifts in rainfall patterns, rapidly increasing nonpoint source pollution originated from turbid water and soil erosion. The climate changes also pose serious threats to the agricultural environment and food security. This study innovates the conventional control facilities of turbid water and soil erosion in the sloping field, using coal bottom ash as a harmful waste of thermal power generation. Typical gabion and side modified gabion are designed in consideration with geographical characteristics. The adsorption capacity of coal bottom ash for turbidity, suspended solids (SS), total nitrogen (T-N), and total phosphorus (T-P) were increased as the amounts of coal bottom ash increase. At the rate of 20-g coal bottom ash, the turbidity, SS, T-N, and T-P were absorbed by 84.0%, 80.2%, 40.2%, and 53.2%, respectively. The typical gabion (TG) and side modified gabion (SMG) installed in the sloping field also decreased the turbidity, SS, T-N, and T-P by up to 98.1%, 99.4%, 77.6%, and 84.0%, respectively, during the natural rainfall events. The use of coal bottom ash cannot only be an effective upcycling way to control nonpoint source pollution but also be an ecofriendly approach against climate change.

The Impact of Green Finance on Agricultural Non-Point Source Pollution: Analysis of the Role of Environmental Regulation and Rural Land Transfer

This study evaluates the impact of green finance on agricultural non-point source pollution control and emission reduction in 30 Chinese provinces from 2005 to 2022. Utilizing the entropy value method and the unit survey inventory method, the research measures the levels of green finance development and agricultural non-point source pollution. It employs a mediation effect model to empirically assess the pollution control efficacy of green finance and to elucidate the mechanisms underlying its influence. The findings indicate that green finance development significantly curtails agricultural non-point source pollution emissions. This conclusion is still valid after a series of robustness tests. The results of mechanism analysis show that environmental regulation and land transfer are important channels for green finance to reduce agricultural non-point source pollution. However, the slowing effect of green finance is stronger in provinces where the economic development level is still in the catch-up zone. Consequently, this study suggests strengthening green finance infrastructure in rural areas, coordinating green finance and environmental regulation policies, optimizing land transfer systems to promote scale management, and developing differentiated green finance policies based on regional economic development levels. These measures aim to augment the role of green finance in pollution treatment and emission reduction, thereby optimizing the green financial system, advancing environmental protection, and fostering sustainable development in China’s agricultural sector.

Innovative approach for assessing nitrogen loss risk to surface waters from crop production in a watershed scale through nitrogen surplus index method

Although various measures are applied to control farmland nitrogen loss at the field scale, effective control strategies at the watershed scale are still lacking due to poor understanding of nitrogen loss risks across different scales. Therefore, an innovative approach to assess the risk of nitrogen loss to surface waters from crop production at the watershed scale was established, with nitrogen surplus, a more accurate indicator, as a major source factor introduced to the traditional index method. Furthermore, this approach was applied in the Baiyangdian Lake Watershed, a typically agricultural-dominated watershed in China, and the control strategies for farmland nitrogen loss reduction were investigated with scenario analysis. The major results included: (1) Areas with high (2–4 for risk to river, 1.6–3.2 for risk to lake) and very high (>4 for risk to river, >3.2 for risk to lake) risks of nitrogen loss in crop production were relatively small. For example, in the wheat-maize rotation system, these areas accounted for only 2.1–3.5 % and 0.9–1.8% of the total study area, respectively. Additionally, the critical source areas of nitrogen loss were concentrated around the receiving water bodies. (2) The nitrogen surplus in wheat season increased the nitrogen loss to surface waters. Compared to the maize season, the area with high and very high risk for nitrogen loss to the nearby river in wheat-maize rotation system increased by 58.3% and 141.4%. Furthermore, the areas with high and very high risk for nitrogen loss to the lake in wheat-maize rotation system were 129.6% and 220.6% more than that during maize season. (3) Nitrogen loss risk to the nearby rivers was correlated with nitrogen surplus, but nitrogen loss risk to the lake was related to the transport coefficient. (4) The optimized scenario for nitrogen loss reduction in crop production was the combination of nitrogen surplus being less than 20 kg/ha and 500 m banning area around the river with no fertilizer application, which reduced the nitrogen loss risk to the nearby river and to the lake by 94–95% and 89–95%. The results of this study provide a scientific basis for nutrient resource management and non-point source pollution control.

Study on Non-Point Source Pollution Prevention and Control System in Nansi Lake Basin Based on System Dynamics Approach

Agriculture, as an important activity on which human beings depend for their livelihood, brings serious environmental problems while meeting the needs of human survival, among which agricultural non-point source (NPS) pollution is one of the most urgent environmental problems. This study quantitatively assessed the loading characteristics spatial and temporal evolution patterns of two agricultural NPS pollutants, chemical oxygen demand (COD) and ammonia nitrogen (NH3-N), from 2010 to 2020 in the Nansi Lake Basin as an example, and constructed a system dynamics (SD) simulation model to simulate and analyze agricultural NPS pollution under different development and treatment scenarios, based on an investigation of the regional prevention and control strategy of agricultural NPS pollution and the technological system. The results show that the current status of agricultural NPS pollution load in the Nansi Lake Basin is poor, and the level of pollution load is high, showing obvious geographical differences. In terms of temporal changes, the pollution loads of the two pollutants showed a decreasing trend from 2010 to 2020, among which the pollution load of NH3-N showed the largest change. Spatially, the spatial distribution of each type of pollutant has some similarities, with smaller pollution loads in Jining and Zaozhuang and relatively larger pollution loads in Heze and Ningyang. The main source of COD pollution in the Nansi Lake Basin is rural life, with an emission proportion of 52.85%, and the main sources of NH3-N pollution from agricultural NPS pollution in the area are rural life and livestock and poultry farming, with emission proportions of 47.55% and 35.36%, respectively. Under the status quo continuum scenario, the pollution load values for COD are consistently higher than those for NH3-N, so the relative impact of COD is greater. In this study, the principles and methods of SD in system science are adopted to deal with the agricultural NPS pollution of Nansi Lake Basin, and the evolution of its behavioral characteristics are simulated, forecasted, and predicted, and policy experiments are conducted, with a view to providing references for the prevention and control of agricultural NPS pollution in Nansi Lake Basin and further research.

Spatio-temporal characteristics and multi-scale risk identification of pollution load based on sensitivity analysis in small watersheds located in Tuojiang River Basin, China.

High-quality development of water resources supports high-quality socio-economic development. High-quality development connects high-quality life, and clarifying the key management contents of small watersheds plays an important role in building ecologically clean small watersheds and promoting regional production and life. Previous research on pollution loads has focused on examining the impact of various external drivers on pollution loads but still lacks research on the impact of changes in pollution sources themselves on pollution loads. In this study, sensitivity analysis was used to determine the impact of changes from different sources on the total pollution loads, which can recognize the critical pollution sources. We first employed the pollutant discharge coefficient method to quantify non-point source pollution loads in the small watershed in the upstream Tuojiang River basin from 2010 to 2021. Then, combination sensitivity analysis with Getis-Ord Gi* was used to identify the critical sources and their crucial areas at the global, districts (counties), and towns (streets) scales, respectively. The results indicate: (1) The pollution loads of COD, NH3-N, TN, and TP all show a decreasing trend, reducing by 18.3%, 16.2%, 18.6%, and 28.1% from 2010 to 2021, respectively; (2) Livestock and poultry breeding pollution source is the most critical source for majority areas across watershed; (3) High-risk areas are mainly concentrated in Jingyang district and its subordinate towns (streets). There is a trend of low-pollution risk areas transitioning to high-pollution risk areas, with high-risk areas predominantly concentrated in the southeast and exhibiting a noticeable phenomenon of pollution load spilling around. This study can promote other similar small watersheds, holding significant importance for non-point source pollution control in small watersheds.

Linking terrestrial biogeochemical processes and water ages to catchment water quality: A new Damköhler analysis based on coupled modeling of isotope tracers and nitrate dynamics

Catchment-scale nitrate dynamics involve complex coupling of hydrological transport and biogeochemical transformations, imposing challenges for source control of diffuse pollution. The Damköhler number (Da) offers a dimensionless dual-lens concept that integrates the timescales of exposure and processing, but quantifying both timescales in heterogeneous catchments remains methodologically challenging. Here, we propose a novel spatio-temporal framework for catchment-scale quantification of Da based on the ecohydrological modeling platform EcH2O-iso that coupled isotope-aided water age tracking and nitrate modeling. We examined Da variability of soil denitrification in the heterogeneous Selke catchment (456 km2, central Germany). Results showed that warm-season soil denitrification was of catchment-wide significance (Da >1), while its high spatial variations were co-determined by varying exposure times and removal efficiencies (e.g., channel-connected lowland areas are hotspots). Moreover, Da seasonally shifted from processing-dominance to transport-dominance during the wet-spring season (from >1 to <1), implying important linkages between summer terrestrial denitrification and subsequent winter river water quality. Under the prolonged 2018–2019 droughts, denitrification removal generally reduced, resulting in further accumulation in agricultural soils. Moreover, the space-time responses of Da variability indicated important implications for catchment water quality. The older water in lowland areas exhibited extra risks of groundwater contamination, whilst agricultural areas in the hydrologically responsive uplands became sensitive hotspots for export and river water pollution. Importantly, the lowland pixels intersecting river channels exhibited high removal efficiencies, as well as high resilience to the disturbances (wet-spring Da shifted to >1 under drought conditions). The proposed catchment-wide Da framework is implied by mechanistic modeling, which is transferable across various environmental conditions. This could shed light on understanding of catchment N processes, and thus providing site-specific implications of non-point source pollution controls.

Spatial and Temporal Scale Effects of Landscape Pattern on Riverine Nitrogen and Phosphorus Nutrients in the Qingshan Lake Watershed

The influences of landscape pattern on water quality are dependent on spatial-temporal scales. However, the effects of landscape composition, landscape configuration, and landscape slope metrics on seasonal water quality at different spatial scales remain unclear. Based on the total nitrogen, total phosphorus, nitrate-N, and ammonium-N data from 26 sampling sites in the Qingshan Lake watershed, this study coupled landscape pattern analysis, redundancy analysis, and partial redundancy analysis to quantify the spatiotemporal scale effects of landscape pattern on riverine nitrogen （N） and phosphorus （P） concentrations. The results showed that： ① The explanatory ability of landscape pattern at the sub-watershed scale on riverine N and P concentrations was 6.8%-8.4% higher than that at the buffer scale, and this effect was more obvious in the dry season. ② At the sub-watershed scale, the percentage of forestland and the interspersion and juxtaposition degree of residential land had a greater influence on riverine N and P concentrations. At the buffer scale, the slope of farmland and residential land and the aggregation degree of forestland patches were the key factors affecting riverine N and P concentrations. ③ The contribution rate of landscape configuration to riverine N and P concentration variations （20.1%-36.5%） was the highest. The sensitivity of the effect of landscape configuration on riverine N and P concentrations to seasonal changes was the highest, and the effect of landscape slope on riverine N and P concentrations had the highest sensitivity to spatial scale changes. Therefore, landscape pattern-regulated non-point source pollution should be considered from a multi-scale perspective. These results can provide scientific basis for the formulation of landscape pattern optimization measures aiming at non-point source pollution control.

Tripartite evolutionary game and simulation analysis of agricultural non-point source pollution control

Tripartite evolutionary game and simulation analysis of agricultural non-point source pollution control

Can the best management practices resist the combined effects of climate and land-use changes on non-point source pollution control?

Climate and land-use changes have an overlying impact on non-point source (NPS) pollution in river basins. However, the control effect of Best Management Practices (BMPs) for NPS pollution is not yet clear under future scenarios. The Soil and Water Assessment Tool (SWAT) model was coupled with the entropy-weighted method, global climate patterns and land-use data to explore the dynamic variations in total nitrogen (TN) and total phosphorus (TP) loads in the Jing River Basin during the baseline (2000−2020) and future periods (2021–2065), evaluate the pollution reduction effectiveness of individual and combined BMPs, and propose practical BMP configurations. Results indicate that a future trend of urban land expansion, particularly in the economic scenario (LU_SSP585), leads to weakened environmental ecosystems, while the sustainable scenario (LU_SSP126) exhibits more balanced land development. The MIROC-ES2L model demonstrates higher Taylor skill scores, forecasted significant increases in precipitation, maximum, and minimum temperatures under the SSP585 scenario. Spatial heterogeneity in TN and TP loads is notable, showing an upward trajectory in the future. The interaction between land-use and climate change has complex effects on TN and TP loads, with land-use-induced TN changes being relatively small (4.6 %) and TP changes substantial (24.3 %). The spatial distribution, under overlying effects, leans towards the influence of climate change, emphasizing its dominant role in TN and TP load variations. Distinct differences exist in the reduction of NPS pollution loads among different BMPs, with combined BMPs demonstrating superior effectiveness. The environmental-cost effectiveness trends of BMPs remain consistent across various future scenarios. RG (Return agricultural land to grass), RG + TT (Terracing), and RG + FR10 (Fertilizer reduction: 10 %) + GW (Grassed waterway) + FS (Filter strip) + TT emerge as the most effective single, double, and multiple BMP combinations, respectively. The results offer valuable insights for preventing and mitigating future NPS pollution risks, optimizing land-use layouts, and enhancing watershed management decisions.

Effects of Biochar-loaded Ammonia Nitrogen on Soil Carbon Emissions, Enzyme Activity, and Microbial Communities

The form of soil nitrogen input significantly affects soil CO2 emission. As a new form of nitrogen input, biochar-loaded ammonia nitrogen not only reduces the input of chemical nitrogen fertilizer in farmland but also reduces the cost of environmental treatment. It is of great significance to promote the zero growth of national chemical fertilizer, the prevention and control of farmland non-point source pollution, and the realization of the national goal of "carbon peak" and "carbon neutralization." Through an indoor culture experiment, the effects of different nitrogen input forms on soil carbon emission, enzyme activity, and microbial community were studied through four treatments:no fertilization (CK), single application of chemical nitrogen fertilizer (CF), biochar combined application of chemical nitrogen fertilizer (BF), and biochar-loaded ammonia nitrogen (BN). The results showed that compared with that in CF, BF significantly increased cumulative carbon emissions (66.24 %), whereas BN had no significant difference. It is worth noting that the cumulative carbon emissions were significantly reduced by 35.28 % compared with that in BF and BN. Compared with those in CF and BF, the activities of β-glucosidase, peroxidase, and polyphenol oxidase treated with BN significantly increased by 20.25 % and 5.20 %, respectively. Compared with that in CF, the BF treatment increased microbial community richness and community diversity, whereas the BN treatment decreased microbial community richness. Compared with that in BF, the relative abundance of Proteobacteria decreased by 11.16 %, and the relative abundance of Actinobacteria and Bacteroidota increased by 8.12 % and 5.83 %, respectively, in which xylosidase activity was the most important soil factor affecting microbial community structure. The relative abundance of Chloroflexi was significantly correlated with cellobiose hydrolase activity, and the relative abundance of Gemmatimonadetes was significantly correlated with β-glucosidase activity. There was a very significant correlation between the relative abundance of Proteobacteria and cumulative carbon emissions. To summarize, compared with those under biochar combined with chemical nitrogen fertilizer, biochar loaded with ammonia nitrogen significantly reduced cumulative carbon emissions, and its emission reduction effect was better. The results of this study will be beneficial to the landing of the national "double carbon strategy," the healthy development of the biological natural gas industry, the construction of the national green cultivation circular agriculture system, and the realization of the national zero growth strategy of chemical fertilizer.

Long-term water quality variations and influencing factors in Dianchi Lake, China – Insights from 30-year data

ABSTRACT Changes in water quality in Dianchi Lake over a long temporal scale have been significantly influenced by climate change and policy issuance. This study utilized the Mann -Kendall test and Theil -Sen estimation to examine water quality trends at 10 monitoring sites within Dianchi Lake from 1989 to 2018. The corresponding impacts of policies, including point source (PS) and non-point source (NPS) pollution control, ecological restoration (ER), and enforcement and supervision (ES), along with climatic conditions, were evaluated. Analysis of regression curves of water quality indexes indicates a slight increase in ammonia (NH4+-N) and total nitrogen (TN), while total phosphorus (TP), biochemical oxygen demand (BOD5), permanganate index (CODMn), and chlorophyll-a (Chl-a) decreased from the baseline time (year 1989). During the mid-phase (2001 -2006) of the study period, the impacts of policies on water quality were inconspicuous, with water temperature affecting Chl-a concentration variations. During the 11th Five-Year Plan, pollutants like NH4+-N, TN, TP, and CODMn peaked and then significantly declined between 2009 and 2015, likely due to comprehensive issuance of NPS and ER policies. This study can provide a reference for water quality management in eutrophic lakes.

Spatial Layout of Vegetation Buffer Zones around Water Bodies to Avoid Non-Point Source Pollution in a Mining Area

The riparian vegetation buffer zone plays an important role in the prevention and control of non-point source pollution, and consideration should be given to selecting one with a lower cost and better effect. The SWAT model was used to simulate the regulation ability of riparian vegetation buffer zone layout on runoff, nitrogen, and phosphorus in the Jiawang Basin, and five different vegetation buffer zone layout scenarios were set up. The results showed that (1) the SWAT model has good applicability in simulating runoff and water quality in the Jiawang Basin; (2) the reduction rates of runoff, total nitrogen, and total phosphorus in continuous forest riverbank buffer zones reached 2.46%, 6.63%, and 9.18%, and their regulatory effects were better than those in grasslands; (3) there is not much difference in the inhibitory effect of forest and grassland on total nitrogen, but the discontinuous forest buffer zone has a better reduction effect on total phosphorus than grassland. Therefore, in the actual arrangement of vegetation buffer zones, it should be tailored to local conditions to achieve ideal non-point source pollution prevention and control effects at a lower cost.

“Period-area-source” hierarchical management for agricultural non-point source pollution in typical watershed with integrated planting and breeding

Agricultural non-point source (NPS) pollution threatens the aquatic environments significantly. Insufficient attention to the migration characteristics of multiple sources of pollution as well as the variability of anthropogenic interference hinders effective pollution control, particularly in watersheds with integrated planting and breeding (IPB). In this study, we proposed a distributed dual-structure empirical export model for IPB (DSEEM-IPB) that optimizes hydrological processes in pollutant transport and refines NPS load estimation from animal breeding sources to simulate agricultural NPS pollution in a typical IPB watershed. Based on the estimated NPS load, a “period-area-source” management approach for NPS pollution is proposed with a co-analysis of critical periods (CPs), critical source areas (CSAs), and critical source types (CSTs). The results show that (1) the CPs of only two months (June and July) contributed 62.9% and 56.2% of the total nitrogen (TN) and total phosphorus (TP) load respectively; (2) the CSAs in the CPs contributed 17.6% of the TN load within 14.0% of the area and 16.2% of the TP load within 13.4% of the area; (3) planting (74.4%) is the primary source of nitrogen loss while breeding (58.3%) is the primary source of phosphorus loss; and (4) optimal control measures should target planting sources in CSAs and sub-CSAs within CPs (yielding 32.4% of annual TN loads) and breeding sources in CSAs within non-CPs (yielding 22.1% of annual TP loads). This study indicates that prioritizing pollution management of critical sources from critical areas or periods can achieve efficient and targeted control of agricultural NPS pollution.

Editorial: Advances in ecotechnologies for the control of non-point source pollution in agricultural and urban watersheds

Editorial: Advances in ecotechnologies for the control of non-point source pollution in agricultural and urban watersheds

Deep groundwater irrigation altered microbial community and increased anammox and methane oxidation in paddy wetlands of Sanjiang Plain, China.

The over-utilizing of nitrogen fertilizers in paddy wetlands potentially threatens to the surrounding waterbody, and a deep understanding of the community and function of microorganisms is crucial for paddy non-point source pollution control. In this study, top soil samples (0-15 cm) of paddy wetlands under groundwater's irrigation at different depths (H1: 6.8 m, H2: 13.7 m, H3: 14.8 m, H4: 15.6 m, H5: 17.0 m, and H6: 17.8 m) were collected to investigate microbial community and function differences and their interrelation with soil properties. Results suggested some soil factor differences for groundwater's irrigation at different depths. Deep-groundwater's irrigation (H2-H6) was beneficial to the accumulation of various electron acceptors. Nitrifying-bacteria Ellin6067 had high abundance under deep groundwater irrigation, which was consistent with its diverse metabolic capacity. Meanwhile, denitrifying bacteria had diverse distribution patterns. Iron-reducing bacteria Geobacter was abundant in H1, and Anaeromyxobacter was abundant under deep groundwater irrigation; both species could participate in Fe-anammox. Furthermore, Geobacter could perform dissimilatory nitrate reduction to ammonia using divalent iron and provide substrate supply for anammox. Intrasporangium and norank_f_Gemmatimonadacea had good chromium- and vanadium-reducting potentials and could promote the occurrence of anammox. Low abundances of methanotrophs Methylocystis and norank_f_Methyloligellaceae were associated with the relatively anoxic environment of paddy wetlands, and the presence of aerobic methane oxidation was favorable for in-situ methane abatement. Moisture, pH, and TP had crucial effects on microbial community under phylum- and genus-levels. Microorganisms under shallow groundwater irrigation were highly sensitive to environmental changes, and Fe-anammox, nitrification, and methane oxidation were favorable under deep groundwater irrigation. This study highlights the importance of comprehensively revealing the microbial community and function of paddy wetlands under groundwater's irrigation and reveals the underlying function of indigenous microorganisms in agricultural non-point pollution control and greenhouse gas abatement.

A stochastic simulation-based chance-constrained programming model for optimizing watershed best management practices for nonpoint source pollution control under uncertainty

In this study, a stochastic simulation-based chance-constrained programming (SSCP) model is developed by integrating soil and water assessment tool (SWAT), generalized likelihood uncertainty estimation (GLUE), chance-constrained programming (CCP) and genetic algorithm (GA) for managing non-point source (NPS) pollution under uncertainty. The SSCP model improves upon conventional simulation-based optimization methods by effectively (i) reflecting the propagation of stochastic uncertainties from the SWAT to the optimization framework by the joint GLUE and CCP (GLUE-CCP) approach, and (ii) identifying the optimal implementation levels of best management practices (BMPs) under different constraint-violation risk levels. The SSCP is solved using a GA with parallel sampling technique after conversion into the corresponding deterministic version. The model is applied to determine the optimal types, sizes and locations of BMPs for NPS pollution control in the Hanjiang River basin, China. The results indicate that, under low-risk conditions, grassed waterways and filter strips should be implemented in the northern part of the basin and larger detention ponds of about 637.8 ∼ 850.4 ha should be installed in the northern and eastern parts of the basin; whereas under high-risk conditions, filter strips should be installed in the northeastern part of the basin and larger detention ponds of about 562.1 ∼ 749.5 ha should be installed in the northern and southwestern parts of the basin. Moreover, as the risk level decreases, stricter control of constraint violations leads to higher BMP implementation costs in order to mitigate the risk of excessive NPS pollution loads. Thus, the proposed model provides valuable insights into the selection of BMP placement schemes at various risk levels, facilitating the reduction of NPS pollution at the outlet of the Hanjiang River basin to acceptable levels while considering the tradeoff between system cost and risk.

Estimation, Management, and Control of Non-Point Source Pollution from Livestock Runoff: A Literature Review

Los nutrientes, como el nitrógeno y el fósforo generan, entre otros impactos, la eutrofización en los cuerpos de agua. Estos impactos son principalmente causados por actividades agrícolas como la ganadería, debido a la aplicación de fertilizantes y/o al estiércol de las vacas. Los nutrientes transportados por la escorrentía llegan a los cuerpos de agua y generan contaminación. Esta problemática ha sido abordada desde la década de los 60, no obstante, se ha logrado poco avance en este tema. Los avances están relacionados con la estimación del aporte de nutrientes de forma teórica y a través de simulaciones, debido a los altos costos que implica tomar datos en el campo. También se han realizado esfuerzos en la implementación de Buenas Prácticas de Gestión para el manejo de las fuentes no puntuales, pero existe poca evidencia de la eficiencia de cada una de estas prácticas. Por otro lado, pese a la falta de información científica necesaria para formular políticas, se ha demostrado que la vía normativa puede ser el mejor mecanismo para controlar la contaminación por fuentes no puntuales. En este artículo, se presenta una revisión de estos tres componentes luego del análisis bibliométrico, estableciendo lo que se conoce actualmente y las brechas de información. Primero, se abordan los avances en la estimación del aporte de las fuentes no puntuales, segundo se presentan las Buenas Prácticas de Gestión, y tercero, se exponen los avances en materia de políticas para el control de la contaminación no puntual.

Factors Influencing Willingness of Farmers to Pay for Agricultural Non-point Source Pollution Control Based on Distributed Cognitive Theory

The analysis of the willingness of individual farmers to cover costs is an important basis for measuring the economic value of agricultural non-point pollution management， and determining the ecological and economic value of rural surface pollution control is a necessary measure to internalize the externalities of agricultural production. Based on the analysis of the hierarchy of factors influencing the cognition of farmers， this study constructed a theoretical framework based on distributed cognition theory to analyze their willingness to pay for agricultural non-point source pollution control from the perspective of individual farmers. On the basis of this framework， we used the Double-Hurdle model to empirically test the overall process of farmers'willingness to pay and their willingness to pay the amount for agricultural non-point source pollution control by combining 531 microscopic research datapoints in Guanzhong， Shaanxi Province. The results showed that： ① the number of farmers with willingness to pay for agricultural non-point source pollution control was 267， accounting for 50.30% of the total sample， and the average value of willingness to pay was 1 469.77 yuan·hm-2； the total economic value of agricultural non-point source pollution control in Shaanxi Province in 2020 was estimated to be 5.791 billion yuan based on the expected value of the willingness to pay level of the research sample. ② Farmers'willingness to pay for agricultural non-point source pollution control was influenced by the combined effects of personal， regional， and cultural forces， and the effects of each dimension were similar； farmers' willingness to pay for agricultural non-point source pollution control was mainly influenced by the cultural force factor， and the effects of personal and regional forces were very limited. ③ The results of the regressions by income level showed that personal and cultural strengths had a significant impact on the willingness to pay among the low-income group but did not contribute to the increase in the willingness to pay.

Implication of self-organizing map, stable isotopes combined with MixSIAR model for accurate nitrogen control in a well-protected reservoir

Nitrogen pollution and eutrophication in reservoirs is a global environmental geochemical concern. Occasional algal blooms still exist in reservoirs that have undergone pollution treatment. The lack of quantitative evidence of nitrogen sources and fate limits long-term stable ecological safety management. This work applied an approach integrated zonal mapping, stable isotopes (δ18OH2O, δ15Nnitrate, δ18Onitrate, and δ13C-DIC) and a Bayesian isotope model to analyze regional and seasonal differences in the contribution and sources of nitrogen to a well-protected reservoir. The values of δ18Onitrate and the positive relationship between NO3− and δ13C-DIC suggested that nitrification was the primary NO3− production in the rivers. While Denitrification was present at only a few sites. Results of the MixSIAR model coupled the NO3−/Cl− indicator revealed that the domestic sewage contributed high riverine NO3− loading (68.6 ± 10.6 %) in the dry season. In the wet season, the main nitrate sources of upper watershed were ammonia and carbamide fertilizers (47.5 % and 40.3 %). While the domestic sewage was still the major contributor of downstream region (a dense residential area), indicating possible problems with rainwater and sewage drainage networks. The results implied that the colleting and treatment of sewages were the priority in downstream region, and non-point source pollution control and wastewater treatment plant upgrading were essential to control nitrate pollution in the two upstream regions. These findings provide new insights into precise nitrogen pollution traceability and identification of treatment priorities in the sub-region, and promote the management other well-protected watershed in similar need of further nitrogen contamination control.