Impacts of rainfall events on runoff water quality in an agricultural environment in temperate areas

Enhancing machine learning models for total organic carbon prediction by integrating geospatial parameters in river watersheds

This study utilizes machine learning (ML) algorithms to develop a robust total organic carbon (TOC) prediction model for river waters in the Geumho River sub-basins, South Korea, considering both non-rain and rain events. The model incorporates geospatial parameters such as land use, slope, flow rate, and basic water quality metrics including biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and suspended solids (SS). A key aspect of this research is examining how land use information enhances the model's predictive accuracy. We compared two ML algorithms-extreme gradient boosting (XGBoost) and deep neural networks (DNN)-with a traditional multiple linear regression (MLR) approach. XGBoost outperformed the others, achieving an R2 value between 0.61 and 0.68 in the test dataset and demonstrating significant improvement during rain events with an R2 of 0.77 when including land use data. In contrast, this enhancement was not observed with the MLR model. Feature importance analysis using Shapley values highlighted COD as the primary predictor for non-rain events, while during rain events, COD, TP, TN, SS and agricultural land collectively influenced TOC levels. This study significantly advances understanding of TOC variability across different land use scenarios in river systems and underscores the importance of integrating geospatial and water quality parameters to enhance TOC prediction, particularly during rain events. This methodology provides a valuable framework for developing river management strategies and monitoring long-term TOC trends, especially in scenarios with gaps in essential monitoring data.

Identification of pollution source and prediction of water quality based on deep learning techniques

Semi-arid rivers are particularly vulnerable and responsive to the impacts of industrial contamination. Prompt identification and projection of pollutant dynamics are crucial in the accidental pollution incidents, therefore required the timely informed and effective management strategies. In this study, we collected water quality monitoring data from a typical semi-arid river. By water quality inter-correlation mapping, we identified the regularity and abnormal fluctuations of pollutant discharges. Combining the association rule method (Apriori) and characterized pollutants of different industries, we tracked major industrial pollution sources in the Dahei River Basin. Meanwhile, we deployed the integrated multivariate long and short-term memory network (LSTM) to forecast principal contaminants. Our findings revealed that (1) biological oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen, total phosphorus, and ammonia nitrogen exhibited high inter-correlations in water quality mapping, with lead and cadmium also demonstrating a strong association; (2) The main point sources of contaminant were coking, metal mining, and smelting industries. The government should strengthen the regulation and control of these industries and prevent further pollution of the river; (3) We confirmed 4 key pollutants: COD, ammonia nitrogen, total nitrogen, and total phosphorus. Our study accurately predicted the future changes in this water quality index. The best results were obtained when the prediction period was 1 day. The prediction accuracies reached 85.85%, 47.15%, 85.66%, and 89.07%, respectively. In essence, this research developed effective water quality traceability and predictive analysis methods in semi-arid river basins. It provided an effective tool for water quality surveillance in semi-arid river basins and imparts a scientific scaffold for the environmental stewardship endeavors of pertinent authorities.

Effect of solar radiation on natural organic matter composition in surface waters and resulting impacts on drinking water treatment

Solar radiation experiments showed a shift in the composition of natural organic matter (NOM). Due to irradiation, the concentration of high molecular weight (HMW) molecules decreased, and that of the low molecular weight (LMW) fraction increased. Microbiological analyses showed that biodegradation was neglectable. To assess the consequences for water treatment processes, coagulation jar tests were performed by comparing the removal effectivity for NOM fractions from irradiated and unirradiated raw water. The degree of dissolved organic carbon (DOC) removal by coagulation was lower for irradiated waters. As primarily HMW organic compounds are removed by coagulation, the decrease in coagulation performance is attributed to the increase in the LMW concentration due to photochemical reactions induced by solar radiation. Flocs were about 15% larger for irradiated water. Possibilities to adapt water treatment to respond to changes in DOC composition and concentration are outlined. Ozonation-biofiltration is judged as the most promising treatment process to cope with climate change-related challenges in drinking water treatment.

Trends and influential factors of high ecological status mobility in Irish Rivers

The decline in high ecological water status in rivers is a significant concern in European countries. It is thus important to investigate the factors that cause sites to lose high status in order to undertake measures to protect and restore high status water quality. Analysis of 20 years of water quality data reveals strong mobility between high status and non-high status (especially good status) rivers. Associations between this mobility and socio-economic and physical environmental variables were estimated by multinomial logistic regression at national scale and regional scale. Based on reported changes in water quality status cross across 1990, 2000 and 2010, four classes of the mobility of high status were defined in this study: those sites that maintain high status (maintain), enter high status (enter), fluctuate between high and non-high status (fluctuate) and exit from high status (exit). The national results indicate that agricultural activity as indicated by variables representing intensity of livestock farming (organic nitrogen) and tillage farming (cereal share) and elevation had significant negative impacts on high status rivers. Meanwhile, significant differences in population density and septic tank density between 'exit', 'maintain', 'fluctuate' and 'enter' classes indicate that these factors played important roles in the stability of high status rivers. The regional outcomes reveal differential significant pressures across regions. For example, rainfall and elevation had positive impacts on high status rivers in the north-west region, while organic nitrogen had a negative effect in the south-west. This paper demonstrates the challenge in achieving the Water Framework Directive goal of maintaining high status rivers, given the sensitive and highly differentiated nature of areas that have lost high status or fluctuated in and out of high status. This paper also suggests the necessity for localised policies and mitigation measures.

Temporal and spatial variability of water quality in an urban wetland and the effects of season and rainfall: a case study in the Daguan Wetland, China

Urban wetlands provide multiple functions including water treatment, recreation, and education, but they are also highly vulnerable, so it is important to monitor wetland water quality to ensure wetland health. In this study, water quality parameters of an urban wetland and rainfall were monitored at 6 sites for 1 year. The correlation analysis of water quality parameters and spatial-temporal variability analysis of water quality were carried out. Besides, the effects of season and rainfall on the wetland water quality were evaluated by the comprehensive water quality identification index (CWQII). These results have shown that there is a significant correlation between nutrient pollutants and Chl-a. Wetland water quality changed with the seasons, but it also varied due to changes in rainfall and location. The water quality of the shallow areas both had high susceptibility and response to seasonal changes and rainfall, but the water quality of the deepwater area was relatively stable. The CWQIIs in different seasons were ranked: Winter (5.98) > spring (4.67) > autumn (4.66) > summer (4.26), and the CWQIIs of different rainfall intensities were ranked: torrential rain (5.09) > heavy rain (4.88) > light rain (4.50) > no rain (4.39) > moderate rain (3.95). The results of this study distinctly explained the effects of season and rainfall on water quality in an urban wetland in a subtropical monsoon climate zone and would be helpful to the policymakers and concerned authorities in developing better water quality management strategies for these wetlands.

Biogeochemical impacts of sewage effluents in predominantly rural river catchments: Are point source inputs distinct to background diffuse pollution?

Discharge of treated sewage effluent to rivers can degrade aquatic ecosystem quality, interacting with multiple stressors in the wider catchment. In predominantly rural catchments, the river reach influence of point source effluents is unknown relative to complex background pressures. We examined water column, sediment and biofilm biogeochemical water quality parameters along river transects (200 m upstream to 1 km downstream) during summer at five wastewater treatment works (WWTW) in Scotland. Treated sewage effluent (subset, n = 3) pollutant concentrations varied between sites. Downstream concentration profiles of water and sediment biogeochemical parameters showed complex spatial changes. A hypothesised point source signature of elevated concentrations of pollution immediately downstream of WWTW then a decaying pollution 'plume' did not commonly occur. Instead, elevated soluble reactive phosphorus (SRP), ammonium and coliforms (maximum 0.23 mgP/l, 0.33 mgN/l and >2 × 106 MPN/100 ml) occurred immediately downstream of two WWTW, whereas some downstream pollutant concentrations decreased. Microbial substrate respiration responses only differed 1 km downstream. Significantly greater concentrations of sediment metal occurred >500 m downstream, likely due to the redeposition of historic contaminated sediments. Significantly lowered chlorophyll-a downstream of one WWTW coincided with elevated metals, despite water SRP and sediment P increases. Overall, stress caused to microbes and algae by effluent contaminants outweighed the subsidy effect of WWTW nutrients. We observed variable effluent flows to the rivers limited localised pollution downstream of WWTW and overall influence of arable land cover on river water quality. Together, this challenges views of consistently discharging point sources impacting low dilution sensitive rivers in summer contrasting with 'diffuse' sources. Thus, river water column and benthic compartments are altered at varying scales by point source effluents in combination with rural catchment pollution sources, both discrete (e.g. farmyards and septic tanks) and diffuse.

Real-time measurement of total nitrogen for agricultural runoff based on multiparameter sensors and intelligent algorithms

Real-time monitoring of non-point source (NPS) pollution is challenging owing to the minute-scale change in runoff flow and concentration under rainfall condition. In this study, we proposed a real-time measurement method for total nitrogen (TN) by combining the timeliness of sensor detection and the accuracy of intelligent algorithms, based on the physical and chemical relationships between TN and sensor-measured indexes. Extra tree regression was selected as the TN inversion algorithm, which has high precision, high computational efficiency, and better ability in over-fitting control. The results show that: (1) the real-time inversion algorithm of TN can achieve the monitoring frequency at the minute scale (<5 min); (2) the method performs well (R²>0.9) when the training and testing datasets are from similar environmental backgrounds (fields or ditches); (3) in the case of partial variable missing, this method can still realize TN inversion, and the prediction accuracy is acceptable (R²>0.7) under the number of missing variables (n) ≤ 2, which makes up for the flaws of missing or abnormal data caused by sensor malfunctions. Overall, the proposed real-time measurement method of TN has stable data acquisition, high precision, and high monitoring frequency. In addition, the method is not limited by cloudy, rainy, or nighttime conditions. Compared with methods such as laboratory test, remote sensing inversion, and water quality automatic monitoring station, our method has obvious advantages in runoff monitoring of NPS pollution, which mainly occurs in small and micro water bodies. The new real-time measurement of TN for runoff may provide important technological support for pre-warning and emergency control of NPS pollution.

Adaptive monitoring approach to assess dissolved organic matter dynamics during rainfall events

Rainfall events induce water quality transformation in river systems influenced by the watershed land use and hydrology dynamics. In this context, an adaptive monitoring approach (AMA) is used to assess non-point sources (NPS) of pollution events, through dissolved organic matter (DOM) contribution. The case study is a monitoring site in a semi-urban watershed characterized by NPS contribution. An integrated quali-quantitative method for DOM based on dissolved organic carbon (DOC) content, spectroscopic techniques of excitation-emission fluorescence (EEF), and UV-visible absorbance is proposed. The results indicate a mix of allochthonous and autochthonous DOM characteristics from NPS sources associated to vegetation area influence (A₂₈₅/DOC of 15.43 L (g cm)^-1 and SUVA₂₅₄ of 2.11 L (mg m)^-1). The EEF signals showed more humic-like than protein-like characteristics with peaks A and C (approximately 5.72 r.u.) more intense than peaks B, T₁, and T₂ (approximately 4.33 r.u.), indicating NPS from the soil leachate. The absorbance ratio values indicate a mix of organic compounds with greater proportion of refractory characteristics with high aromaticity and molecular weight (approximately A₃₀₀/A₄₀₀ of 4.15 and A₂₅₀/A₃₆₅ of 4.48), associated with the surface wash-off of accumulated residual and subsurface soil erosion, which contribute to complex organic matter structures. The fluorescence indexes, overall, indicated allochthonous sources with intermediate humic characteristics (FI ≈ 1.43, BIX ≈ 0.65, and HIX ≈ 7.98). The proposed integrated optical property strategy represents an opportunity for better understanding of DOM dynamic assessment for identifying potential mitigation techniques for organic pollution control and improving water quality conditions.

Extreme Hydro-Meteorological Events Influence to Water Quality of Small Rivers in Urban Area: A Case Study in Northeast Poland

This paper presents an impact of hydro-meteorological extreme events and urban catchment to water quality in small rivers in Białystok (Poland). The results from a five-year study have taken into account droughts, continuous precipitation, and storm precipitation causing flash floods. Extreme hydro-meteorological events has a different impact on the physical and chemical parameters of water. It was found that the largest change in water quality occurs on the 2nd day after the rainfall and changed concentration of some chemical parameters persists for a long time. The majority but, what’s important, not all of them are diluted after floods and concentrated after droughts. Flash flooding results in a large increase concentrations of DOC and selected forms of phosphorus. Higher values of EC, Eh, Mg²⁺, HCO₃^-, Cl^-, SiO₃^2-, NO₃^-N, TN were observed during drought compared to the average values from 2014–2018. A high degree of naturalness of the river valley and increased water retention results in a decreased concentration of NH₄⁺-N, DOC and phosphorus forms. The buffer zone plays an important role in limiting the inflow of pollutants and nutrients from the catchment area. That is why it is worth undertaking restoration of river valleys in urban areas.

Quantitative assessment of background pollutants using a modified method in data-poor regions

Heavy background pollutant loads pose a difficult problem for the assessment and management of regional water quality, especially in areas where surface water quality is less affected by anthropogenic pollution. Deducting background values from those derived from water quality monitoring is a new method for evaluating surface water environments in areas with heavy background loads. In this study, river source reserves in Heilongjiang province were evaluated with an export coefficient model (ECM) that considers the rainfall influence factor, has an improved timescale, and is based on synchronous rainfall monitoring data and concentrations. Moreover, the ECM was combined with a mechanism model. The chemical oxygen demand, ammonia nitrogen, and other water quality indices are affected by background environment, and therefore, suitable export coefficients for the study area were determined and a regression equation between the rainfall influence factor and precipitation was established. By combining the ECM and mechanism model, the concentrations entering the river during eight rainfall events in 2018 were predicted, and the background value was calculated to evaluate surface water quality. The predicted values were found to approximate the monitored values. Therefore, this study is of great significance for water quality assessment and management in areas with heavy background pollutant loads.

Spatiotemporal Relationships of Phytoplankton Blooms, Drought, and Rainstorms in Freshwater Reservoirs

Algal blooms, especially those composed of toxic phytoplankton, are a global threat to eutrophic and mesotrophic freshwater reservoirs. While extreme hydrologic events such as flooding and drought have been shown to control bloom onset and success, the spatiotemporal dynamics of these relationships are still unclear for mesotrophic reservoirs. In this study, the relationships between hydrologic events and phytoplankton in Lake Allatoona and Lake Lanier, Georgia, United States, were characterized using historical and satellite datasets from 2008 to 2017 and statistical modeling. Results showed that the impact of stormflow and rainstorm events varied systematically from riverine to lacustrine reaches of the two reservoirs on weekly and monthly scales. Precipitation duration and stormflow were the most significant and best-fitting predictors of algal bloom biomass in deeper reaches of the two reservoirs, suggesting that algal blooms in more lacustrine environments may be better equipped for wet and stormy regimes than has been previously hypothesized.

Water quality dynamic during rainfall episodes: integrated approach to assess diffuse pollution using automatic sampling

Diffuse pollution caused by rainfall events potentially affects water quality in rivers and, therefore, must be investigated in order to improve water quality planning and management recovery strategies. For these, a quali-quantitative approach was used to monitor the water quality parameters in a river located in a semi-urban watershed area based upon automatic sampling. Thirteen water quality parameters were measured during five rainfall events. Events ranged from 2.3 to 56.8 mm and water peak flows from 3.3 to 4.5 m³/s. The pollutographs measured showed a standard pattern for total suspended solids (TSS). However, for the other chemical parameters, as total phosphorous (TP) and dissolved organic carbon (DOC), the dilution effects were more evident. It was possible to observe the rainfall influence mainly for physical parameters indicating a mass transport pattern for diffuse pollutants, which increased, for example, the amount of TSS in the river. Furthermore, hydrological characteristics were relevant considering the pollutant behavior. Antecedent dry periods, ranging from 1.3 days to 21.4 days, and critical time, from 2.0 to 10.4 h, are determinants to evaluate non-traditional water quality impacts in the river. In general, each rainfall episode has its own characteristics, which produces distinct mass contribution and temporal behavior, being challenging in making generalization. Therefore, the results indicate that diffuse pollution has to be considered to establish future decision-making strategies to water resources management.

A Revised Method of Surface Water Quality Evaluation Based on Background Values and Its Application to Samples Collected in Heilongjiang Province, China

In China, the use of certain standards to evaluate surface water quality in areas with high background values due to natural factors rather than to human activities results in water quality underestimation and thus affects regional water quality management and decision-making. Herein, we examined river source water function zones of the Heilongjang province characterised by high background values and analysed the corresponding water quality data acquired in 2011–2016. The examined samples featured elevated chemical oxygen demand (COD), permanganate index (CODMn), and ammonia nitrogen (NH3-N) levels, which indicated that water quality was affected by the natural environment. The concentrations of background pollutants almost exceeded the limits stipulated by regional surface water quality standards and exhibited strong spatiotemporal variability. A three-step discrimination method including single index recognition, limiting factors, and a synthetic index was proposed to distinguish the background area among these zones for determining background values, and 10 complete background areas were identified. The background values of COD, CODMn, and NH3-N for the entire area were determined based on the data acquired during background area monitoring. Finally, considering the present procedure of water quality evaluation in China (single factor exponential method), a revised method based on background values was suggested. Thus, the evaluation results objectively and accurately reflect the regional water quality situation and therefore provide a scientific basis for the development of a better water quality assessment and management system in China.

Assessing Hydrological Modelling Driven by Different Precipitation Datasets via the SMAP Soil Moisture Product and Gauged Streamflow Data

To compare the effectivenesses of different precipitation datasets on hydrological modelling, five precipitation datasets derived from various approaches were used to simulate a two-week runoff process after a heavy rainfall event in the Wangjiaba (WJB) watershed, which covers an area of 30,000 km2 in eastern China. The five precipitation datasets contained one traditional in situ observation, two satellite products, and two predictions obtained from the Numerical Weather Prediction (NWP) models. They were the station observations collected from the China Meteorological Administration (CMA), the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG), the merged data of the Climate Prediction Center Morphing (merged CMORPH), and the outputs of the Weather Research and Forecasting (WRF) model and the WRF four-dimensional variational (4D-Var) data assimilation system, respectively. Apart from the outlet discharge, the simulated soil moisture was also assessed via the Soil Moisture Active Passive (SMAP) product. These investigations suggested that (1) all the five precipitation datasets could yield reasonable simulations of the studied rainfall-runoff process. The Nash-Sutcliffe coefficients reached the highest value (0.658) with the in situ CMA precipitation and the lowest value (0.464) with the WRF-predicted precipitation. (2) The traditional in situ observation were still the most reliable precipitation data to simulate the study case, whereas the two NWP-predicted precipitation datasets performed the worst. Nevertheless, the NWP-predicted precipitation is irreplaceable in hydrological modelling because of its fine spatiotemporal resolutions and ability to forecast precipitation in the future. (3) Gauge correction and 4D-Var data assimilation had positive impacts on improving the accuracies of the merged CMORPH and the WRF 4D-Var prediction, respectively, but the effectiveness of the latter on the rainfall-runoff simulation was mainly weakened by the poor quality of the GPM IMERG used in the study case. This study provides a reference for the applications of different precipitation datasets, including in situ observations, remote sensing estimations and NWP simulations, in hydrological modelling.

Aquatic Bacterial Communities Associated With Land Use and Environmental Factors in Agricultural Landscapes Using a Metabarcoding Approach

This study applied a 16S rRNA gene metabarcoding approach to characterize bacterial community compositional and functional attributes for surface water samples collected within, primarily, agriculturally dominated watersheds in Ontario and Québec, Canada. Compositional heterogeneity was best explained by stream order, season, and watercourse discharge. Generally, community diversity was higher at agriculturally dominated lower order streams, compared to larger stream order systems such as small to large rivers. However, during times of lower relative water flow and cumulative 2-day rainfall, modestly higher relative diversity was found in the larger watercourses. Bacterial community assemblages were more sensitive to environmental/land use changes in the smaller watercourses, relative to small-to-large river systems, where the proximity of the sampled water column to bacteria reservoirs in the sediments and adjacent terrestrial environment was greater. Stream discharge was the environmental variable most significantly correlated (all positive) with bacterial functional groups, such as C/N cycling and plant pathogens. Comparison of the community structural similarity via network analyses helped to discriminate sources of bacteria in freshwater derived from, for example, wastewater treatment plant effluent and intensity and type of agricultural land uses (e.g., intensive swine production vs. dairy dominated cash/livestock cropping systems). When using metabarcoding approaches, bacterial community composition and coexisting pattern rather than individual taxonomic lineages, were better indicators of environmental/land use conditions (e.g., upstream land use) and bacterial sources in watershed settings. Overall, monitoring changes and differences in aquatic microbial communities at regional and local watershed scales has promise for enhancing environmental footprinting and for better understanding nutrient cycling and ecological function of aquatic systems impacted by a multitude of stressors and land uses.

Can the watershed non-point phosphorus pollution be interpreted by critical soil properties? A new insight of different soil P states

The physicochemical properties of surface soil play a key role in the fate of watershed non-point source pollution. Special emphasis is needed to identify soil properties that are sensitive to both particulate P (PP) pollution and dissolved P (DP) pollution, which is essential for watershed environmental management. The Chaohu Lake basin, a typical eutrophic lake in China, was selected as the study site. The spatial features of the Non-point Source (NPS) PP loads and DP loads were calculated simultaneously based on the integration of sediment delivery distributed model (SEDD) and pollution loads (PLOAD) model. Then several critical physicochemical soil properties, especially various soil P compositions, were innovatively introduced to determine the response of the critical soil properties to NPS P pollution. The findings can be summarized: i) the mean PP load value of the different sub-basins was 5.87 kg, and PP pollution is regarded to be the primary NPS P pollution state, while the DP loads increased rapidly under the rapid urbanization process. ii) iron-bound phosphorus (Fe-P) and aluminum-bound phosphorus (Al-P) are the main components of available P and showed the most sensitive responses to NPS PP pollution, and the correlation coefficients were approximately 0.9. Otherwise, the residual phosphorus (Res-P) was selected as a sensitive soil P state that was significantly negatively correlated with the DP loads. iii) The DP and PP concentrations were represented differently when they were correlated with various soil properties, and the clay proportion was strongly negatively related to the PP loads. Meanwhile, there is a non-linear relationship between the DP loads and the critical soil properties, such as Fe and Total Nitrogen (TN) concentrations. Specifically, a strong inhibitory effect of TN concentration on the DP load was apparent in the Nanfei river (NF) and Paihe (PH) river basins where the R² reached 0.67, which contrasts with the relatively poor relationship within the other five basins. In addition, the degree of correlation between the Fe and DP loads severely degraded in the basins that were mostly covered by construction land or those that underwent a rapid urbanization process. The findings indicate that land use/cover change (LUCC), especially the distribution of agricultural land and construction land, as well as the soil background information (TN, Fe and Soil organic matters, etc.) can be considered as factors that influence NPS P pollution.

High frequency monitoring of pesticides in runoff water to improve understanding of their transport and environmental impacts

Rainfall-induced peaks in pesticide concentrations can occur rapidly. Low frequency sampling may therefore largely underestimate maximum pesticide concentrations and fluxes. Detailed storm-based sampling of pesticide concentrations in runoff water to better predict pesticide sources, transport pathways and toxicity within the headwater catchments is lacking. High frequency monitoring (2min) of seven pesticides (Dimetomorph, Fluopicolide, Glyphosate, Iprovalicarb, Tebuconazole, Tetraconazole and Triadimenol) and one degradation product (AMPA) were assessed for 20 runoff events from 2009 to 2012 at the outlet of a vineyard catchment in the Layon catchment in France. The maximum pesticide concentrations were 387μgL^-1. Samples from all of the runoff events exceeded the legal limit of 0.1μgL^-1 for at least one pesticide (European directive 2013/39/EC). High resolution sampling used to detect the peak pesticide levels revealed that Toxic Units (TU) for algae, invertebrates and fish often exceeded the European Uniform principles (25%). The point and average (time or discharge-weighted) concentrations indicated up to a 30- or 4-fold underestimation of the TU obtained when measuring the maximum concentrations, respectively. This highlights the important role of sampling methods for assessing peak exposure. High resolution sampling combined with concentration-discharge hysteresis analyses revealed that clockwise responses were predominant (52%), indicating that Hortonian runoff is the prevailing surface runoff trigger mechanism in the study catchment. The hysteresis patterns for suspended solids and pesticides were highly dynamic and storm- and chemical-dependent. Intense rainfall events induced stronger C-Q hysteresis (magnitude). This study provides new insights into the complexity of pesticide dynamics in runoff water and highlights the ability of hysteresis analysis to improve understanding of pesticide supply and transport.

Zeolite Combined with Alum and Polyaluminum Chloride Mixed with Agricultural Slurries Reduces Carbon Losses in Runoff from Grassed Soil Boxes

Carbon (C) losses from agricultural soils to surface waters can migrate through water treatment plants and result in the formation of disinfection by-products, which are potentially harmful to human health. This study aimed to quantify total organic carbon (TOC) and total inorganic C losses in runoff after application of dairy slurry, pig slurry, or milk house wash water (MWW) to land and to mitigate these losses through coamendment of the slurries with zeolite (2.36-3.35 mm clinoptilolite) and liquid polyaluminum chloride (PAC) (10% AlO) for dairy and pig slurries or liquid aluminum sulfate (alum) (8% AlO) for MWW. Four treatments under repeated 30-min simulated rainfall events (9.6 mm h) were examined in a laboratory study using grassed soil runoff boxes (0.225 m wide, 1 m long; 10% slope): control soil, unamended slurries, PAC-amended dairy and pig slurries (13.3 and 11.7 kg t, respectively), alum-amended MWW (3.2 kg t), combined zeolite and PAC-amended dairy (160 and 13.3 kg t zeolite and PAC, respectively) and pig slurries (158 and 11.7 kg t zeolite and PAC, respectively), and combined zeolite and alum-amended MWW (72 and 3.2 kg t zeolite and alum, respectively). The unamended and amended slurries were applied at net rates of 31, 34, and 50 t ha for pig and dairy slurries and MWW, respectively. Significant reductions of TOC in runoff compared with unamended slurries were measured for PAC-amended dairy and pig slurries (52 and 56%, respectively) but not for alum-amended MWW. Dual zeolite and alum-amended MWW significantly reduced TOC in runoff compared with alum amendment only. We conclude that use of PAC-amended dairy and pig slurries and dual zeolite and alum-amended MWW, although effective, may not be economically viable to reduce TOC losses from organic slurries given the relatively low amounts of TOC measured in runoff from unamended slurries compared with the amounts applied.

Agricultural runoff pollution control by a grassed swales coupled with wetland detention ponds system: a case study in Taihu Basin, China

The performance of a field grassed swales (GSs) coupled with wetland detention ponds (WDPs) system was monitored under four typical rainfall events to assess its effectiveness on agricultural runoff pollution control in Taihu Basin, China. The results indicated that suspended solids (SS) derived from the flush process has significant influence on pollution loads in agricultural runoff. Determination of first flush effect (FFE) indicated that total suspended solids (TSS) and total phosphorus (TP) exhibited moderate FFE, while chemical oxygen demand (COD) and total nitrogen (TN) showed weak FFE. Average removal efficiencies of 83.5 ± 4.5, 65.3 ± 6.8, 91.6 ± 3.8, and 81.3 ± 5.8 % for TSS, COD, TN, and TP were achieved, respectively. The GSs played an important role in removing TSS and TP and acted as a pre-treatment process to prevent clogging of the subsequent WDPs. Particle size distributions (PSDs) analysis indicated that coarse particles larger than 75 μm accounted for 80 % by weight of the total particles in the runoff. GSs can effectively reduce coarse particles (≥75 μm) in runoff, while its removal efficiency for fine particles (<75 μm) was low, even minus results being recorded, especially for particles smaller than 25 μm. The length of GSs is a key factor in its performance. The WDPs can remove particles of all sizes by sedimentation. In addition, WDPs can improve water quality due to their buffering and dilution capacity during rainfall as well as their water purification ability during dry periods. Overall, the ecological system of GSs coupled with WDPs is an effective system for agricultural runoff pollution control.

Tracking the behavior of different size fractions of dissolved organic matter in a full-scale advanced drinking water treatment plant

In this study, five different dissolved organic matter (DOM) fractions, defined based on a size exclusion chromatography with simultaneous detection of organic carbon (OCD) and ultraviolet (UVD), were quantitatively tracked with a treatment train of coagulation/flocculation-sand filtration-ozonation-granular activated carbon (GAC) filtration in a full-scale advanced drinking water treatment plant (DWTP). Five DOM samples including raw water were taken after each treatment process in the DWTP every month over the period of three years. A higher abundance of biopolymer (BP) fraction was found in the raw water during spring and winter than in the other seasons, suggesting an influence of algal bloom and/or meltwater on DOM composition. The greater extent of removal was observed upon the coagulation/flocculation for high-molecular-weight fractions including BP and humic substances (HS) and aromatic moieties, while lower sized fractions were preferentially removed by the GAC filtration. Ozone treatment produced the fraction of low-molecular-weight neutrals probably resulting from the breakdown of double-bonded carbon structures by ozone oxidation. Coagulation/flocculation was the only process that revealed significant effects of influent DOM composition on the treatment efficiency, as revealed by a high correlation between the DOM removal rate and the relative abundance of HS for the raw water. Our study demonstrated that SEC-OCD-UVD was successful in monitoring size-based DOM composition for the advanced DWTP, providing an insight into optimizing the treatment options and the operational conditions for the removal of particular fractions within the bulk DOM.

Impact of catchment geophysical characteristics and climate on the regional variability of dissolved organic carbon (DOC) in surface water

Dissolved organic carbon (DOC) is a recognized indicator of natural organic matter (NOM) in surface waters. The aim of this paper is twofold: to evaluate the impact of geophysical characteristics, climate and ecological zones on DOC concentrations in surface waters and, to develop a statistical model to estimate the regional variability of these concentrations. In this study, multilevel statistical analysis was used to achieve three specific objectives: (1) evaluate the influence of climate and geophysical characteristics on DOC concentrations in surface waters; (2) compare the influence of geophysical characteristics and ecological zones on DOC concentrations in surface waters; and (3) develop a model to estimate the most accurate DOC concentrations in surface waters. The case study involved 115 catchments from surface waters in the Province of Quebec, Canada. Results showed that mean temperatures recorded 60 days prior to sampling, total precipitation 10 days prior to sampling and percentages of wetlands, coniferous forests and mixed forests have a significant positive influence on DOC concentrations in surface waters. The catchment mean slope had a significant negative influence on DOC concentrations in surface waters. Water type (lake or river) and deciduous forest variables were not significant. The ecological zones had a significant influence on DOC concentrations. However, geophysical characteristics (wetlands, forests and slope) estimated DOC concentrations more accurately. A model describing the variability of DOC concentrations was developed and can be used, in future research, for estimating DBPs in drinking water as well evaluating the impact of climate change on the quality of surface waters and drinking water.

Revealing organic carbon-nitrate linear relationship from UV spectra of freshwaters in agricultural environment

A strong non linear relationship between nitrate and organic matter (assessed by dissolved organic carbon, DOC) has been recently demonstrated by Taylor and Townsend (2010), namely for freshwaters. In this context, our study explores this relation from the behavior of sets of normalized UV spectra (same area under each spectrum) of different water samples showing a hidden isosbestic point (HIP) around 225 nm. This HIP is linked to the existence of a simple relation between nitrate and DOC, the proportions of which vary according to the sampling location and environmental factors. In a second step, a simple linear model is proposed for nitrate-DOC relationship (α⋅NO3+β⋅DOC=1) and a validation is proposed for more than 150 samples of different Brittany rivers and lakes. For samples of the largest watershed, a complementary exploitation from data acquired during the different campaigns confirmed the seasonal evolution between spring (high nitrate/low DOC) and autumn (high DOC/low nitrate). Further investigation on other freshwater samples is needed in order to improve the limits of this linear model.

Microbial contamination detection in water resources: interest of current optical methods, trends and needs in the context of climate change

Microbial pollution in aquatic environments is one of the crucial issues with regard to the sanitary state of water bodies used for drinking water supply, recreational activities and harvesting seafood due to a potential contamination by pathogenic bacteria, protozoa or viruses. To address this risk, microbial contamination monitoring is usually assessed by turbidity measurements performed at drinking water plants. Some recent studies have shown significant correlations of microbial contamination with the risk of endemic gastroenteresis. However the relevance of turbidimetry may be limited since the presence of colloids in water creates interferences with the nephelometric response. Thus there is a need for a more relevant, simple and fast indicator for microbial contamination detection in water, especially in the perspective of climate change with the increase of heavy rainfall events. This review focuses on the one hand on sources, fate and behavior of microorganisms in water and factors influencing pathogens' presence, transportation and mobilization, and on the second hand, on the existing optical methods used for monitoring microbiological risks. Finally, this paper proposes new ways of research.

Evaluating spatial interaction of soil property with non-point source pollution at watershed scale: the phosphorus indicator in Northeast China

To better understand the spatial dynamics of non-point source (NPS) phosphorus loading with soil property at watershed scale, integrated modeling and soil chemistry is crucial to ensure that the indicator is functioning properly and expressing the spatial interaction at two depths. Developments in distributed modeling have greatly enriched the availability of geospatial data analysis and assess the NPS pollution loading response to soil property over larger area. The 1.5 km-grid soil sampling at two depths was analyzed with eight parameters, which provided detailed spatial and vertical soil data under four main types of landuses. The impacts of landuse conversion and agricultural practice on soil property were firstly identified. Except for the slightly bigger total of potassium (TK) and cadmium (Cr), the other six parameters had larger content in 20-40 cm surface than the top 20 cm surface. The Soil and Water Assessment Tool was employed to simulate the loading of NPS phosphorus. Overlaying with the landuse distribution, it was found that the NPS phosphorus mainly comes from the subbasins dominated with upland and paddy rice. The linear correlations of eight soil parameters at two depths with NPS phosphorus loading in the subbasins of upland and paddy rice were compared, respectively. The correlations of available phosphorus (AP), total phosphorus (TP), total nitrogen (TN) and TK varied in two depths, and also can assess the loading. The soil with lower soil organic carbon (SOC) presented a significant higher risk for NPS phosphorus loading, especially in agricultural area. The Principal Component Analysis showed that the TP and zinc (Zn) in top soil and copper (Cu) and Cr in subsurface can work as indicators. The analysis suggested that the application of soil property indicators is useful for assessing NPS phosphorus loss, which is promising for water safety in agricultural area.