Showing papers on "Nonpoint source pollution published in 2020"

Recent advances in control technologies for non-point source pollution with nitrogen and phosphorous from agricultural runoff: current practices and future prospects

Abstract: Eutrophication of natural water is a universal problem. Nitrogen (N) and phosphorus (P) from agricultural runoff are the main sources of nutrient input, provided that emissions from industrial point sources (IPS) are under control. Therefore, it is of great environmental importance to reduce pollution associated with agricultural runoff as a means of regulating eutrophication levels in natural water. Numerous methods proposed for treating agricultural runoff can be classified into three categories: source control, process control, and end treatment. In this review, major technologies for N and P control from agricultural runoff are summarized along with discussion of newly proposed technologies such as biochar biomimetics and microbial catalyst. Because agricultural runoff (from farmlands to receiving waters) is a complicated pollution process, it is difficult to regulate the nutrients discharged via such process. This review will thus offer a comprehensive understanding on the overall process of agricultural runoff and eutrophication to help establish control strategies against highly complicated agricultural non-point sources.

Review of Watershed-Scale Water Quality and Nonpoint Source Pollution Models.

Abstract: Watershed-scale nonpoint source (NPS) pollution models have become important tools to understand, evaluate, and predict the negative impacts of NPS pollution on water quality. Today, there are many NPS models available for users. However, different types of models possess different form and structure as well as complexity of computation. It is difficult for users to select an appropriate model for a specific application without a clear understanding of the limitations or strengths for each model or tool. This review evaluates 14 more commonly used watershed-scale NPS pollution models to explain how and when the application of these different models are appropriate for a given effort. The models that are assessed have a wide range of capacities that include simple models used as rapid screening tools (e.g., Long-Term Hydrologic Impact Assessment (L-THIA) and Nonpoint Source Pollution and Erosion Comparison Tool (N-SPECT/OpenNSPECT)), medium-complexity models that require detail data input and limited calibration (e.g., Generalized Watershed Loading Function (GWLF), Loading Simulation Program C (LSPC), Source Loading and Management Model (SLAMM), and Watershed Analysis Risk Management Frame (WARMF)), complex models that provide sophisticated simulation for NPS pollution processes with intensive data and rigorous calibration (e.g., Agricultural Nonpoint Source pollution model (AGNPS/AnnAGNPS), Soil and Water Assessment Tool (SWAT), Stormwater Management Model (SWMM), and Hydrologic Simulation Program Fortran (HSPF)), and modeling systems that integrate various sub-models and tools, and contain the highest complexity to solve all phases of hydrologic, hydraulic, and chemical dynamic processes (e.g., Automated Geospatial Watershed Assessment Tool (AGWA), Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) and Watershed Modeling System (WMS)). This assessment includes model intended use, components or capabilities, suitable land-use type, input parameter type, spatial and temporal scale, simulated pollutants, strengths and limitations, and software availability. Understanding the strengths and weaknesses of each watershed-scale NPS model will lead to better model selection for suitability and help to avoid misinterpretation or misapplication in practice. The article further explains the crucial criteria for model selection, including spatial and temporal considerations, calibration and validation, uncertainty analysis, and future research direction of NPS pollution models. The goal of this work is to provide accurate and concise insight for watershed managers and planners to select the best-suited model to reduce the harm of NPS pollution to watershed ecosystems.

Factors driving nutrient trends in streams of the Chesapeake Bay watershed

Abstract: Despite decades of effort toward reducing nitrogen and phosphorus flux to Chesapeake Bay, water-quality and ecological responses in surface waters have been mixed. Recent research, however, provides useful insight into multiple factors complicating the understanding of nutrient trends in bay tributaries, which we review in this paper, as we approach a 2025 total maximum daily load (TMDL) management deadline. Improvements in water quality in many streams are attributable to management actions that reduced point sources and atmospheric nitrogen deposition and to changes in climate. Nutrient reductions expected from management actions, however, have not been fully realized in watershed streams. Nitrogen from urban nonpoint sources has declined, although water-quality responses to urbanization in individual streams vary depending on predevelopment land use. Evolving agriculture, the largest watershed source of nutrients, has likely contributed to local nutrient trends but has not affected substantial changes in flux to the bay. Changing average nitrogen yields from farmland underlain by carbonate rocks, however, may suggest future trends in other areas under similar management, climatic, or other influences, although drivers of these changes remain unclear. Regardless of upstream trends, phosphorus flux to the bay from its largest tributary has increased due to sediment infill in the Conowingo Reservoir. In general, recent research emphasizes the utility of input reductions over attempts to manage nutrient fate and transport at limiting nutrients in surface waters. Ongoing research opportunities include evaluating effects of climate change and conservation practices over time and space and developing tools to disentangle and evaluate multiple influences on regional water quality.

Review on uncertainty of the first-flush phenomenon in diffuse pollution control

Abstract: Several definitions and criteria of the first-flush are being used to assess and control the nonpoint source (diffuse) pollution. The common consensus is that the first-flush is generally noticed in the small catchments (e.g. 10 ha) without on-site monitoring being conducted. However, it is also recommended to come up with a simplistic approach of designing the best management practices (BMPs) to capture and treat certain depth of the initial storm runoff (e.g. first 20 mm), which will help reduce the effect of nonpoint source (NPS) pollution.

Response of Non-point Source Pollution Loads to Land Use Change under Different Precipitation Scenarios from a Future Perspective

Abstract: To optimize the management of non-point source (NPS) pollution in a changing environment, the cellular automata (CA) and Hydrological Simulation Program-Fortran (HSPF) models were used to study the response mechanism of NPS pollution loads to land use change and different precipitation scenarios. Taking the Dongjiang River Basin as a case study, the land use situation and its spatial distribution patterns in 2020, 2030 and 2050 were predicted by the logistic regression-based CA model. The trends of the NPS pollution loads under different land use and precipitation scenarios were quantitatively evaluated. The results show that the total accuracy of the land use change simulated by the CA model was 81%. Both the HSPF model and the CA model were highly applicable to this basin. Precipitation is proven to be the main driving force of NPS pollution. From 2020 to 2050, the annual load, average monthly load, maximum and minimum monthly load of the BOD and TP show an upward trend. TN shows a slight downward trend, which is related to the reduction in cultivated land area and the use of nitrogen fertilizer. In view of the future trend of NPS pollution, the basin should continue to control TN pollution and focus on strengthening BOD and TP control to achieve high-quality management of the water environment.

Spatiotemporal analysis of water quality using multivariate statistical techniques and the water quality identification index for the Qinhuai River basin, East China

Abstract: Monitoring water quality is indispensable for the identification of threats to water environment and later management of water resources. Accurate monitoring and assessment of water quality have been long-term challenges. In this study, multivariate statistical techniques (MST) and water quality identification index (WQII) were applied to analyze spatiotemporal variation in water quality and determine the major pollution sources in the Qinhuai River, East China. A rotated principal component analysis (PCA) identified three potential pollution sources during the wet season (mixed pollution, physicochemical, and nonpoint sources of nutrients) and the dry season (nutrient, primary environmental, and organic sources) and they explained 81.14% of the total variances in the wet season and 78.42% of total variances in the dry season. The result of redundancy analysis (RDA) showed that population density, urbanization, and wastewater discharge are the main sources of organic pollution, while agricultural fertilizer consumption and industrial wastewater discharge are the main sources of nutrients such as nitrogen and phosphorus. The water quality of the Qinhuai River basin was determined to be mainly Class III (slightly polluted) and Class IV (moderately polluted) based on WQII. Temporally, the change trend of WQII showed that water quality gradually deteriorated between 1990 and 2005, improved between 2006 and 2010, and then deteriorated again. Spatially, the WQII distribution map showed that areas with more developed urbanization were relatively more polluted. Our results show that MST and WQII are useful tools to help the public and decision makers to evaluate the water quality of aquatic environment.

Spatiotemporal variations of nitrate sources and dynamics in a typical agricultural riverine system under monsoon climate.

Abstract: Nitrogen pollution is a serious environmental issue in the Danjiangkou Reservoir region (DRR), the water source of the South-to-North Water Diversion Project of China. In this research, seasonal surveys and a bi-weekly time series survey were conducted in the Qihe River Basin, one of the most densely populated agricultural basins in the DRR. Hydrochemical compositions (NO3− and Cl−), dual isotopes (δD-H2O, δ18O-H2O, δ15N-NO3−, and δ18O-NO3−), and a Markov Chain Monte Carlo isotope mixing model were jointly applied to unravel the sources, migrations, and transformations of the nitrate (NO3−) in the basin. It was revealed that the mixing between different sources was the main process controlling the isotopic compositions of the riverine NO3− in the upper-middle reaches. In contrast, denitrification occurred in the lower reaches. For the first time, the sources of NO3− were quantified at a basin scale in the DRR. Overall, the river transported 484.2 tons/year of NO3-N to the reservoir, of which 32.6%, 36.4%, 28.0%, and 3.0% was from soil organic nitrogen, chemical fertilizer, residential sewage and atmospheric precipitation, respectively. The NO3-N fluxes of the different sources were regulated by the monsoon climate and anthropogenic activities. For example, high precipitation and intense fertilization resulted in severe nonpoint source pollution. Denitrification thrived in soils and reservoirs in wet seasons. Temperature could regulate the migration, nitrification and denitrification processes. Based on the results, we suggest that the management strategies dealing with nitrogen pollution issue in the DRR should follow the specific spatiotemporal characteristics of NO3− sources, migration and transformation mechanisms.

An Evolutionary Game Model for the Multi-agent Co-Governance of Agricultural Non-Point Source Pollution Control under Intensive Management Pattern in China.

Abstract: This paper focuses on the sustainable development dilemma of agricultural production in China under the pattern of intensive management, which is seriously challenged by agricultural non-point source pollution. The key to effectively break through the dilemma is to promote the co-governance of agricultural non-point source pollution control by stakeholders including local governments, new agricultural operators and traditional farmers. Accordingly, this paper discusses the interactive decision-making relationships between new agricultural operators and traditional farmers under the guidance of local governments, by constructing a trilateral evolutionary game model, as well as analyzing evolutionary cooperative stability strategies and realizing the simulation of evolution processes in different scenarios by MATLAB. The results show that new agricultural operators play a leading role in agricultural non-point source pollution control, whose strategies have effects such as technology spillover. The rewards from the superior government will support local governments in taking proactive action in the co-governance of agricultural non-point source pollution control, and then local governments can offer technical support and subsidies to new agricultural operators and traditional farmers for reducing their costs. Furthermore, this paper also finds that there are green synergy effects among the groups, where the variations of parameters and strategies by one group would affect the two others. Additionally, agricultural land operation rights transfers would cause traditional farmers to take more time to cooperate in the co-governance of agricultural non-point source pollution control. In order to promote the multi-agent co-governance of agricultural non-point source pollution control under intensive management pattern, this paper suggests that it should be necessary to reduce their costs and improve incentives, as well as to increase the common interests among groups and enhance their green synergy effects.

Assessment of Rain Garden Effects for the Management of Urban Storm Runoff in Japan

Abstract: Storm runoff is a growing concern against a background of increasing urban densification, land-use adaptation and climate change. In this study, a storm water management model was used to analyze the hydrological and water-quality effects of rain gardens (also known as bioretention cells) as nonpoint source control solutions in low-impact development (LID) practices for an urban catchment in the Nakagyo Ward area of Kyoto in Japan. The results of simulations with input involving Chicago hyetographs derived for different rainfall return periods (referred to as 3 a, 5 a, 10 a, 30 a, 50 a and 100 a) indicated the effectiveness of this arrangement, in particular for rainstorm 3 a, which exhibited the maximum contaminant reduction ratio (Total Suspended Solids (TSS) 15.50%, Chemical Oxygen Demand (COD) 16.17%, Total Nitrogen (TN) 17.34%, Total Phosphorus (TP) 19.07%) and a total runoff reduction volume of 46.56 × 106 L. With 5 a, the maximum number of flooding nodes was reduced to 87, demonstrating that rain gardens handle rainfall effectively over a five-year return period. There was a one-minute delay for 100 a, which again indicates that rain gardens support control of urban runoff and mitigate flooding. Such gardens were associated with reduced stormwater hazards and enhanced resistance to short-term rainstorms at the research site, and should be considered for urban planning in Kyoto and other cities all over the world.

Water quality attribution and simulation of non-point source pollution load flux in the Hulan River basin.

Abstract: Surface water is the main source of irrigation and drinking water for rural communities by the Hulan River basin, an important grain-producing region in northeastern China. Understanding the spatial and temporal distribution of water quality and its driving forces is critical for sustainable development and the protection of water resources in the basin. Following sample collection and testing, the spatial distribution and driving forces of water quality were investigated using cluster analysis, hydrochemical feature partitioning, and Gibbs diagrams. The results demonstrated that the surface waters of the Hulan River Basin tend to be medium-weakly alkaline with a low degree of mineralization and water-rock interaction. Changes in topography and land use, confluence, application of pesticides and fertilizers, and the development of tourism were found to be important driving forces affecting the water quality of the basin. Non-point source pollution load fluxes of nitrogen (N) and phosphorus (P) were simulated using the Soil Water and Assessment Tool. The simulation demonstrated that the non-point source pollution loading is low upstream and increases downstream. The distributions of N and P loading varied throughout the basin. The findings of this study provide information regarding the spatial distribution of water quality in the region and present a scientific basis for future pollution control.

Assessment of the Soil Vulnerability Index and comparison with AnnAGNPS in two Lower Mississippi River Basin watersheds

Abstract: There is an increasing need to quickly and accurately identify areas where agricultural conservation practices can provide the greatest reduction in nutrient and sediment runoff. Geographic information systems (GIS)-based tools and indices are promising for identifying critical areas that are significant contributors of nonpoint source pollution loads with limited data. One such tool, the Soil Vulnerability Index (SVI), is tested here in Beasley Lake and Goodwin Creek watersheds in Mississippi. The SVI runoff component results are compared against aerial images and long-term land use histories in the watershed to determine if a higher SVI score is related to visibly degraded land or land removed from cultivation. SVI results are also compared to sediment yield estimates generated with the Annualized Agricultural Non-Point Source pollution model (AnnAGNPS) to determine the degree of agreement. The SVI runoff score demonstrated agreement with imagery and land use histories in both watersheds. The SVI categories and corresponding AnnAGNPS-predicted sediment yield also had moderate agreement, with 45% and 68% of watershed area in agreement in Beasley Lake and Goodwin Creek watersheds, respectively. In general, the tool is a quick way to assess spatial areas potentially contributing to nonpoint source pollution, which can then be combined with field-based knowledge and/or imagery to provide valuable insight for placement of conservation practices.

Characteristics of Non-Point Source Pollution under Different Land Use Types

Abstract: Non-point source pollution (NPSP) is a major challenge for current global water resources. The output characteristics of pollutants under different land use types are very important for controlling NPSP. In this study, long-term positioning monitoring and an analysis of rainfall runoff from different land use types were used to evaluate a typical watershed in the water source area of the middle route of the South-to-North Water Diversion Project (MR-SNWDP). The results show significant differences in nitrogen and phosphorus content in the runoff water bodies of various land use types. The nitrogen and phosphorus content in the MR-SNWDP was directly related to rainfall intensity and the fertilization period in the runoff following fertilization of farmland and vegetable plots. This nitrogen and phosphorus content was also observed to be significantly higher in the fertilization period than in other periods. The loss of nitrogen and phosphorus in forestland was greatly affected by rainfall intensity. Nitrogen in runoff comes primarily from farmland and vegetable fields, where its main form is nitrate nitrogen (NN). Vegetable fields are the main source of phosphorus, where its primary form is soluble phosphate (PO43−-P). Nitrogen and phosphorus have a defined incubation period during the dry season. Farmland and vegetable fields receive less rainfall during the dry season and it is difficult to form effective runoff; this allows nitrogen and phosphorus deposition. The runoff formed by the first rainfall at the beginning of the flood season (April or May) will carry a large amount of nitrogen and phosphorus from the soil into water bodies. Therefore, it is crucial to pay careful attention to the season when attempting to control NPSP.

Currents Status, Challenges, and Future Directions in Identifying Critical Source Areas for Non-Point Source Pollution in Canadian Conditions

Abstract: Non-point source (NPS) pollution is an important problem that has been threatening freshwater resources throughout the world. Best Management Practices (BMPs) can reduce NPS pollution delivery to receiving waters. For economic reasons, BMPs should be placed at critical source areas (CSAs), which are the areas contributing most of the NPS pollution. The CSAs are the areas in a watershed where source coincides with transport factors, such as runoff, erosion, subsurface flow, and channel processes. Methods ranging from simple index-based to detailed hydrologic and water quality (HWQ) models are being used to identify CSAs. However, application of these methods for Canadian watersheds remains challenging due to the diversified hydrological conditions, which are not fully incorporated into most existing methods. The aim of this work is to review potential methods and challenges in identifying CSAs under Canadian conditions. As such, this study: (a) reviews different methods for identifying CSAs; (b) discusses challenges and the current state of CSA identification; and (c) highlights future research directions to address limitations of currently available methods. It appears that applications of both simple index-based methods and detailed HWQ models to determine CSAs are limited in Canadian conditions. As no single method/model is perfect, it is recommended to develop a ‘Toolbox’ that can host a variety of methods to identify CSAs so as to allow flexibility to the end users on the choice of the methods.