Identifying critical source areas of non-point source pollution to enhance water quality: Integrated SWAT modeling and multi-variable statistical analysis to reveal key variables and thresholds.

By integrating soil and water assessment tool (SWAT) modeling and land use and land cover (LULC) based multi-variable statistical analysis, this study aimed to identify driving factors, potential thresholds, and critical source areas (CSAs) to enhance water quality in southern Alabama and northwest Florida's Choctawhatchee Watershed. The results revealed the significance of forest cover and of the lumped developed areas and cultivated crops ("Source Areas") in influencing water quality. The stepwise linear regression analysis based on self-organizing maps (SOMs) showed that a negative correlation between forest percent cover and total nitrogen (TN), organic nitrogen (ORGN), and organic phosphorus (ORGP), highlighting the importance of forests in reducing nutrient loads. Conversely, Source Area percentage was positively correlated with total phosphorus (TP) loads, indicating the influence of human activities on TP levels. The receiver operating characteristic (ROC) curve analysis determined thresholds for forest percentage and Source Area percentage as 37.47 % and 20.26 %, respectively. These thresholds serve as important reference points for identifying CSAs. The CSAs identified based on these thresholds covered a relatively small portion (28 %) but contributed 47 % of TN and 50 % of TP of the whole watershed. The study underscores the importance of considering both physical process-based modeling and multi-variable statistical analysis for a comprehensive understanding of watershed management, i.e., the identification of CSAs and the associated variables and their tipping points to maintain water quality.

Facilitating mitigation of agricultural non-point source pollution and improving soil nutrient conditions: The role of low temperature co-pyrolysis biochar in nitrogen and phosphorus distribution.

The current study generated co-pyrolysis biochar by pyrolyzing rice straw and pig manure at 300 °C and subsequently applying it in a field. Co-pyrolysis biochar demonstrated superior efficiency in mitigating agricultural non-point source pollution compared to biochar derived from individual sources. Furthermore, it displayed notable capabilities in retaining and releasing nutrients, resulting in increased soil levels of total nitrogen, total phosphorus, and organic matter during the maturation stage of rice. Moreover, co-pyrolysis biochar influences soil microbial communities, potentially impacting nutrient cycling. During the rice maturation stage, the soil treated with co-pyrolysis biochar exhibited significant increases in available nutrients and rice yield compared to the control (p < 0.05). These findings emphasize the potential of co-pyrolysis biochar for in-situ nutrient retention and enhanced soil nutrient utilization. To summarize, the co-pyrolysis of agricultural waste materials presents a promising approach to waste management, contributing to controlling non-point source pollution, improving soil fertility, and promoting crop production.

Comprehensive effects of climate, land use/cover and management practices on runoff and nutrient variations in a rapidly urbanizing watershed.

As non-point source pollution has emerged as a significant global and regional concern, climate change (CC), land use/cover transformation (LUCT), and management practices (MP) play vital roles in addressing nutrient pollution. However, current studies lack comprehensive quantification and consistent conclusions on the response to these factors, especially for management practices. To quantify and elucidate the impact of representative environmental factors on rapidly urbanizing regions, this study focused on the Shenzhen River, which serves as the most typical urbanizing watershed. Using a process-based distributed hydrological model with a factor-controlled simulation method, we identified significant differences in nutrient concentrations and the impacts of climate variability, land use/cover changes, and anthropogenic interventions from 2003 to 2020. Moreover, effective measures greatly improved water quality in the Shenzhen River during study period, as evident from trend and cluster analysis. However, ecological water supplements implemented since 2016 have led to a slight reduction in simulated runoff performance, and CC may amplify the synergistic effects of precipitation and temperature on the river system. While the implemented practices have been effective in reducing total nitrogen (TN) and total phosphorus (TP) loads, strong TN pollution control is still needed in rapidly urbanizing areas due to the results of land use/cover type changes. Our findings emphasize the intricate interplay among CC, LUCT, and MP in shaping water quality and hydrological processes in rapidly urbanizing watersheds, and clarify the independent effects of these factors on nutrients. This study contributes to a better understanding of the complex interactions between multiple factors in watersheds and provides guidance for sustainable watershed management.

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.

A spatial optimal allocation method considering multi-attribute decision making and multiple BMPs random combination in sub-watersheds.

Best management practices (BMPs) have been extensively employed in effective watershed management for non-point source pollution. The weights of objective functions and the restrictive conditions of combined BMPs are the vital requirements for BMPs allocation. Therefore, it is more beneficial to explore that a spatial optimal allocation method considering multi-attribute decision making and multiple BMPs random combination. Here is the novel framework based on Soil and Water Assessment Tool (SWAT) and the Non-dominated Sorting Genetic Algorithm II (NSGA-Ⅱ), which considers multiple objectives in deriving watershed-scale pollution control practices by considering BMPs cost and combined reduction rates of total nitrogen (TN) and total phosphorus (TP). The framework also integrates combined Entropy Weight method (EWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to solve the weights of TN and TP, and considers the attributes of the sub-basin itself, which is more local suitability. Four categories of BMPs, tillage management, nutrient management, vegetative filter strips, and landscape management, were evaluated in the Jing River Basin (JRB) and resulted in reduction rates of 9.77%, 10.53%, 16.40%, and 14.27% averagely, respectively. BMP allocation schemes, derived from multi-objective optimization, are stratified into three financial scenarios. Low-cost scenario, costing up to 2 billion RMB, primarily targets the grain for green program in 28.81% of sub-basins. Medium-cost scenario, between 2 and 6 billion RMB, predominantly utilizes the grain for green in areas with a slope greater than 15°, accounting for 20.00% of sub-basins. High-cost scenario exceeds 6 billion RMB, mainly due to the implementation of multiple combination measures. The three configuration scenarios can provide decision-makers with a trade-off between measure costs and reduction efficiency. Overall, the innovative framework not only facilitates cost-effective implementation but provides a beneficial methodology for selecting cost-effective conservation practices in other regions.

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.

Distribution characteristics of non-point source pollution of TP and identification of key source areas in Nanyi Lake (China) Basin: based on InVEST model and source list method.

The Nanyi Lake basin, located in the middle and lower reaches of the Yangtze River, is a crucial component of the Yangtze River ecosystem. Excessive phosphorus levels lead to eutrophication in rivers and lakes. This study aims to enhance the identification efficiency of key source areas for non-point source pollution of total phosphorus (TP) in the Nanyi Lake Basin and improve decision-making regarding the treatment of these areas. The study employs the InVEST model and utilizes GIS spatial hot spot analysis to identify key source areas of agricultural TP non-point source pollution. The accuracy of the InVEST model's simulation results was verified using the source list method. The findings indicate that paddy fields serve as the primary pollution source. TP non-point source pollution in Nanyi Lake is influenced by pollution sources, pollution load filtration rate, and potential TP runoff mass concentration. Different pollution sources correspond to distinct key source areas, and the pollution generated by these sources in different administrative regions, ultimately affecting the lake, varies as well. The InVEST model demonstrates great applicability in regions where agricultural TP is the primary pollution source. For the Nanyi Lake basin, which predominantly experiences agricultural TP non-point source pollution, a combination of the InVEST model and the source list method is recommended. The InVEST model serves as the primary tool, while the source list method supplements it. This approach not only compensates for any limitations of the InVEST model's simulation results but also avoids unnecessary economic waste. The outcomes of this study contribute to a deeper scientific understanding of TP pollution in the Nanyi Lake Basin. They also aid in effectively identifying key source areas and formulating appropriate measures based on the pollution characteristics, thereby providing guidance for non-point source pollution control in the basin.

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.

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

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

Agricultural non-point source pollution and rural transformation in a plain river network: Insights from Jiaxing city, China.

Recently, agricultural non-point source pollution (ANPSP) has gained increasing attention in China. However, using a uniform paradigm to analyze ANPSP in all regions is difficult, considering their geographical, economic, and policy differences. In this study, we adopted the inventory analysis method to estimate the ANPSP of Jiaxing City, Zhejiang Province as a representative region of the plain river network area from 2001 to 2020 and analyzed it in the framework of policies and rural transformation development (RTD). The ANPSP showed an overall decreasing trend over 20 years. Compared to 2001, total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) decreased by 33.93%, 25.77%, and 43.94%, respectively, in 2020. COD accounted for the largest annual average (67.02%), whereas TP contributed the most to the equivalent emissions (50.9%). The highest contribution of TN, TP, and COD, which fluctuated and decreased over the past 20 years, originated from livestock and poultry farming. However, the contribution of TN and TP from aquaculture increased. The overall trend of RTD and ANPSP showed an inverted "U" shape with time, and the evolution of both showed similar stage characteristics. With the gradual stabilization of RTD, ANPSP successively went through three stages: high-level stabilization (2001-2009), rapid-decreasing (2010-2014), and low-level stabilization (2015-2020). Additionally, the relationships between pollution loads from different agricultural sources and indicators of different dimensions of RTD varied. These findings provide a reference for the governance and planning of ANPSP in the plain river network area and a new perspective for investigating the relationship between rural development and the environment.

Applying water environment capacity to assess the non-point source pollution risks in watersheds.

Comprehension of the spatial and temporal characteristics of non-point source (NPS) pollution risk in watersheds is essential for NPS pollution research and scientific management. Although the concept of water functional zones (WFZ) has been considered in the NPS pollution risk assessment process. However, no comprehensive study of the NPS pollution risk has been conducted to effectively protect water quality in watersheds with different water environment capacity. Therefore, this study proposes a new NPS pollution risk assessment method that integrates water functional zoning, receiving water body environmental capacity, and space-time distribution of pollution load for quantifying the impact of pollution discharge from sub-catchment on nearby water body quality. Based on the NPS nutrient loss process modeled by the Soil and Water Assessment Tool (SWAT), this method was used to assess the NPS pollution risk in the Le 'an River Watershed at annual and monthly scales. The results showed that the NPS pollution risk is characterized by seasonal and spatial variability and is influenced clearly by the water environment capacity. High NPS pollution loads are not necessarily high pollution risks. Conversely, a low NPS nutrient pollution load does not represent a low regional risk sensitivity. In addition, NPS risk assessment based on the water environment capacity could also distinguish the differences in risk levels that were masked by similar NPS pollutant loss and the same water function zoning to achieve accurate control of NPS pollution management in watersheds.

Contribution of non-point source pollution that migrated with underground runoff process based on the SWAT model and a digital filter algorithm.

Non-point source (NPS) pollution has always been the focus of research worldwide, and understanding the migration process is the basis for effective control of NPS pollution. In this study, the SWAT model and digital filtering algorithm were combined to explore the contribution of NPS pollution that migrated with underground runoff (UR) process to the Xiangxi River watershed. The results showed that the surface runoff (SR) was the main migration process of NPS pollution, while the contribution of NPS pollution that migrated with the UR process only accounted for 30.9%. With the decrease in annual precipitation among the three selected hydrological years, the proportion of NPS pollution that migrated with the UR process for TN decreased, whereas the proportion for TP increased. The contribution of NPS pollution migrated with UR process varied remarkably during different months. Although the maximum total load and the load of NPS pollution that migrated with the UR process for TN and TP all appeared in the wet season, due to the hysteresis effect, the load of NPS pollution that migrated with the UR process for TP appeared 1 month later than the total load of NPS pollution. With an increase in precipitation from the dry season to the wet season, the proportion of NPS pollution that migrated with the UR process for TN and TP decreased gradually, and the degree of decrease in NPS pollution that migrated with the UR process for TP was more evident than that for TN. Besides, being affected by topography, land use, and other factors, the proportion of NPS pollution that migrated with the UR process for TN decreased from 80% in upstream areas to 9% in downstream areas, while that for TP reached a maximum of 20% in downstream areas. Based on the research results, the contribution of soil and groundwater cumulative nitrogen and phosphorus should be considered, and different managements and control measures for different migration routes should be adopted in controlling pollution.

Strategy for cost-effective BMPs of non-point source pollution in the small agricultural watershed of Poyang Lake: A case study of the Zhuxi River.

In recent years, Poyang Lake has been affected by severe agricultural non-point source (NPS) pollution, a global water pollution problem. The most recognized and effective control measure for agricultural NPS pollution is the strategic selection and placement of best management practices (BMPs) for critical source areas (CSAs). The present study employed the Soil and Water Assessment Tool (SWAT) model to identify CSAs and evaluate the effectiveness of different BMPs in reducing agricultural NPS pollutants in the typical sub-watersheds of the Poyang Lake watershed. The model performed well and satisfactorily in simulating the streamflow and sediment yield at the outlet of the Zhuxi River watershed. The results indicated that urbanization-oriented development strategies and the Grain for Green program (returning the grain plots to forestry) had certain effects on the land-use structure. The proportion of cropland in the study area decreased from 61.45% (2010) to 7.48% (2018) in response to the Grain for Green program, which was mainly converted to forest land (58.7%) and settlements (36.8%). Land-use type changes alter the occurrence of runoff and sediment, which further affect the nitrogen (N) and phosphorus (P) loads since sediment load intensity is a key factor affecting the P load intensity. Vegetation buffer strips (VBSs) proved the most effective BMPs for NPS pollutant reduction, and the cost of 5-m VBSs proved the lowest. The effectiveness of each BMP in reducing N/P load ranked as follows: VBS > grassed river channels (GRC) > 20% fertilizer reduction (FR20) > no-tillage (NT) > 10% fertilizer reduction (FR10). All combined BMPs had higher N and P removal efficiencies than the individual measures. We recommend combining FR20 and VBS-5m or NT and VBS-5m, which could achieve nearly 60% pollutant removal. Depending on the site conditions, the choice between FR20+VBS and NT + VBS is flexible for targeted implementation. Our findings may contribute to the effective implementation of BMPs in the Poyang Lake watershed and provide theoretical support and practical guidance for agricultural authorities to perform and direct agricultural NPS pollution prevention and control.

Identifying the critical areas and primary sources for agricultural non-point source pollution management of an emigrant town within the Three Gorges reservoir area.

Agricultural non-point source pollution is threatening water environmental health of the Three Gorges reservoir. However, current studies for precision management of the agricultural non-point source pollution within this area are still limited. The objective of this study was identifying the critical areas and primary sources of agricultural non-point source pollution for precision management. Firstly, the inventory analysis approach was used to estimate the discharge amount of total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) from farmland fertilizer, crop residues, livestock breeding, and daily activities. Afterwards, the deviation standardization method was applied to evaluate the emission intensity of TN, TP, and COD, as well as calculating the comprehensive pollution index (CPI) of each village, based on which the critical areas for agricultural non-point source pollution management could be distinguished. Moreover, the equivalence pollution load method was conducted to identify the primary pollution sources within each critical zone. The above methods were implemented to an emigrant town within the Three Gorges reservoir area named Gufu. Results showed that agricultural non-point source pollution in Gufu town has been alleviated to a certain extent since 2016. Nevertheless, in four areas of the town (i.e., Longzhu, Fuzi, Shendu, and Maicang), the agricultural non-point source pollution still deserved attention and improvement. For the mentioned critical areas, farmland fertilizer and livestock breeding were the primary sources causing agricultural non-point source pollution. The emission amount of TN and TP from farmland fertilizer accounted for 60% and 48% of the total, respectively. And those from livestock breeding were 29% and 46%. Our research could provide definite targets to relieve agricultural non-point source pollution, which had great significance to protect water environment while coordinating regional economic growth after emigrant resettlement.

Study on non-point source pollution characteristics under different spatial scales: a case study of Hanjiang River Basin, China.

In recent years, the research on non-point source (NPS) pollution has been deepening, but it is focused on the large-scale watershed or region. There are a few studies on the scales of small watershed and runoff plot, and it is even less to analyze the characteristics and mechanism of non-point source pollution in certain watershed by combining three different scales. Based on the combination of natural rainfall monitoring and MIKE model simulation, the Shaanxi section of Hanjiang River Basin in China was taken as an example to study the characteristics of NPS pollution at different spatial scales. The results showed that there was an obvious correlation between rainfall and runoff/sediment yield. The order of runoff yield/sediment yield per unit area was as follows: woodland > forested and grassy land > arable land. There was a significant relationship between the loss of total phosphorus and the sediment yield in the runoff plots. The total nitrogen pollution was serious, with an average concentration of 3.8 mg/L. The nutrient loss was in the form of nitrate nitrogen, with an average proportion of 63.06%. For small watershed scale, the characteristics of rainfall runoff pollution generation were like runoff plot scale, both have obvious initial scour phenomenon. However, compared with runoff plot scale, the pollutant loss concentration increases with a strong lag. The MIKE model based on the coupling of hydrology, hydrodynamics, and pollution load had a strong applicability in the basin. The critical source areas of NPS pollution were identified, and five scenarios were laid out in the areas for the control of NPS pollution. Centralized livestock and poultry farming had the best reduction effect.

Load quantification and effect evaluation of urban non-point source pollution in the Licun River based on SWAT model.

With the gradual control of point source pollution, the impact of urban nonpoint source pollution on river water quality is becoming more prominent. Regarding the current problem that nonpoint source pollution loads in urban basins are difficult to quantify and the impact on water quality is difficult to analyze, the Licun River basin in Qingdao was selected as the research object. Through the field survey and surface accumulation sampling analysis of the basin, the evaluation model of urban nonpoint source pollution was constructed by revising the land type data of the basin and the urban database of the SWAT model. The results showed that concentration of nitrate in precipitation was most sensitive to the simulation of nitrogen loading; organic P in baseflow was most sensitive to the simulation of phosphorus loading. The Nash-Sutcliffe efficiency coefficient (ENS) and the coefficients of determination (R2) of the SWAT model for runoff, total phosphorus (TP), and total nitrogen (TN) in the simulation validation period meet the model requirements,indicating a good model fit. In addition, the spatial and temporal distribution characteristics of urban nonpoint source pollution of TN and TP in 2021 were analyzed. In July, rainfall-runoff from the Licun River basin was the most polluted.

Comparing critical source areas for the sediment and nutrients of calibrated and uncalibrated models in a plateau watershed in southwest China.

Controlling non-point source pollution is often difficult and costly. Therefore, focusing on areas that contribute the most, so-called critical source areas (CSAs), can have economic and ecological benefits. CSAs are often determined using a modelling approach, yet it has proved difficult to calibrate the models in regions with limited data availability. Since identifying CSAs is based on the relative contributions of sub-basins to the total load, it has been suggested that uncalibrated models could be used to identify CSAs to overcome data scarcity issues. Here, we use the SWAT model to study the extent to which an uncalibrated model can be applied to determine CSAs. We classify and rank sub-basins to identify CSAs for sediment, total nitrogen (TN), and total phosphorus (TP) in the Fengyu River Watershed (China) with and without model calibration. The results show high similarity (81%-93%) between the identified sediment and TP CSA number and locations before and after calibration both on the yearly and seasonal scale. For TN alone, the results show moderate similarity on the yearly scale (73%). This may be because, in our study area, TN is determined more by groundwater flow after calibration than by surface water flow. We conclude that CSA identification with the uncalibrated model for TP is always good because its CSA number and locations changed least, and for sediment, it is generally satisfactory. The use of the uncalibrated model for TN is acceptable, as its CSA locations did not change after calibration; however, the TN CSA number changed by over 60% compared to the figures before calibration on both yearly and seasonal scales. Therefore, we advise using an uncalibrated model to identify CSAs for TN only if water yield composition changes are expected to be limited. This study shows that CSAs can be identified based on relative loading estimates with uncalibrated models in data-deficient regions.

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.

Assessing the effectiveness of potential best management practices for science-informed decision support at the watershed scale: The case of the Mar Menor coastal lagoon, Spain.

Coastal lagoons are ecosystems of high environmental importance but are quite vulnerable to human activities. The continuous inflow of pollutant loads can trigger negative impacts on the ecological status of these water bodies, which is contrary to the European Green Deal. One example is the Mar Menor coastal lagoon in Spain, which has experienced significant environmental degradation in recent years due to excessive external nutrient input, especially from non-point source (NPS) pollution. Mar Menor is one of the largest coastal lagoons of the Mediterranean region and a site of great ecological and socio-economic value. In this study, the highly anthropogenic and complex watershed of Mar Menor, known as Campo de Cartagena (1244 km2), was modelled with the Soil and Water Assessment Tool (SWAT) to analyse potential options for recovery of this unique system. The model was used to simulate several best management practices (BMP) proposed by recent Mar Menor regulations, such as vegetative filter strips, shoreline buffers, contour farming, removal of illegal agriculture, crop rotation management, waterway vegetation restoration, fertiliser management and greenhouse rainwater harvesting. Sixteen scenarios of individual and combined BMPs were analysed in this study. We found that, as individual measures, vegetative filter strips and contour farming were most effective in nutrient reduction: approximately 30 % for total nitrogen (TN) and 40 % for total phosphorus (TP). Moreover, waterway vegetation restoration showed the highest sediment (S) reduction at approximately 20 %. However, the combination of BMPs demonstrated clear synergistic effects, reducing S export by 38 %, TN by 67 %, and TP by 75 %. Selecting the most appropriate BMPs to be implemented at a watershed scale requires a holistic approach considering effectiveness in reducing NPS pollution loads and BMP implementation costs. Thus, we have demonstrated a way forward for enabling science-informed decision-making when choosing strategies to control NPS contamination at the watershed scale.

Distribution of antibiotic resistance genes in the sediments of Erhai Lake, Yunnan-Kweichow Plateau, China: Their linear relations with nonpoint source pollution discharges from 26 tributaries.

Erhai Lake, a typical plateau deep water lake, experienced long-term nonpoint source (NPS) pollution discharge from 26 tributaries, which significantly affected the abundance and spread of resistance genes. In this study, 25 antibiotic resistance genes (ARGs), classified into six types, and NPS pollution discharges were investigated throughout around the Erhai basin. FCA (mexF) and sulfonamide resistance genes (sul1, sul2 and sul3) were the most common. Although the absolute overall abundance of ARGs there was low so far, the individual gene like sulfonamide resistance gene was high. Regression analysis using an ordinary least squares model (OLS) showed that the discharge of NPS pollution into Erhai Lake would have an obvious effect on the distribution of ARGs. And the relations between them were linear. Concretely speaking, the total nitrogen (TN) pollution input from tributaries could significantly correlated with the increasing of ARG abundance, while the total phosphorus (TP) pollution input showed the opposite correlation, and ultimately affect the distribution of ARGs. Moreover, the effect of TP on ARG distribution was more significant than TN. This study provides a geographical profile of ARG distribution in a subtropical deep lake on Yunnan-Kweichow Plateau. The results are beneficial for predicting the distribution characteristics of ARGs and controlling their pollution in plateau lakes.