Water Quality Risk Assessment Research Articles

A holistic water quality risk assessment and key parameter identification approach coupling comparative water quality index (WQI) models: a six-year monitoring study in Danjiangkou Reservoir, China

A holistic water quality risk assessment and key parameter identification approach coupling comparative water quality index (WQI) models: a six-year monitoring study in Danjiangkou Reservoir, China

Purification Resistance Index: A new water quality assessment method toward drinking water production

Water quality assessment plays a significant role in ensuring the availability of clean and safe water. The Water Quality Index (WQI) model method has been developed to provide a basis for assessing water quality by integrating various water quality parameters. However, existing WQIs do not “actively” consider the difficulty of water treatment from raw water to specific water use scenarios. This study proposes a novel model framework, named as Purification Resistance Index (PRI), quantitatively evaluating not only the exceedance of pollutants but also how difficult they can be removed in the water treatment process. The framework is built based on the conventional drinking water treatment processes, with sub-indices for coagulation-sedimentation (rc), filtration (rf), disinfection (rd), and advanced treatment (ra). The model considers appropriate weights assigned to each sub-index to calculate the purification resistance, resulting in a comprehensive index for water quality evaluation. Case studies on nationwide and citywide water source reservoirs demonstrated the applicability of PRI approach. PRI breakthrough the traditional water quality risk assessment paradigm and extents to engineering region and provide useful tools for water source supervision, drinking water treatment plant planning and updating, operation control, and other purposes. Water authority, water utility and municipal design institute will all benefit. It is open for more localized practices validation and discussion.

An onsite risk assessment of water quality and heavy metal contamination in Kandal Kampong Speu and Kampong Chhnang Province of Cambodia

An onsite risk assessment of water quality and heavy metal contamination in Kandal Kampong Speu and Kampong Chhnang Province of Cambodia

Misjudging drinking water quality risk: Adopting a barrier approach for meaningful risk assessment to address latent risks.

The water quality risk assessment is the foundation for every drinking Water Safety Plan. The need to conform with a 'Corporate' risk assessment model commonly dominated by asset management frequency data can cause misjudgement of microbial risk. Well-performed risk assessments should identify potential risks. Risk assessments which place too much emphasis on historical evidence to demonstrate 'likelihood' of microbial contamination are unsuitable for drinking water quality because they fail to recognise 'latent' risks associated with absent or underperforming barriers to contamination. Most outbreaks occur when these 'latent' factors align to create a failure. Good risk assessments need to provide foresight. This is achieved if drinking water quality risk assessments are based on a 'barrier' approach. Where adequate and reliable multiple barriers to contamination are present the likelihood of a hazardous event should then be categorised as rare. Where barriers are absent, inadequate, or unreliable, then a higher likelihood is appropriate, depending on the nature and extent of the barrier shortfall. Practical examples show how the 'barrier' approach can be applied. The barrier risk assessment directly informs the operational monitoring programme, enabling regular confirmation that the challenge and barrier performance are consistent with the predictions of the risk assessment.

Operational reliability of urban drainage systems under uncertainties

Water quality risks from overflows have attracted significant research attention, and the reliability of urban drainage systems (UDS) is in urgent need of assessment and improvement. The overflow volume and concentration of critical pollutants are generally used as assessment indicators, which is quite time consuming and cumbersome especially under continuous rainfall. Simplifying the water quality risk assessment indicators for the UDS reliability is intractable. For this purpose, this study proposes the detention tank emptying time as a new reliability evaluation indicator, which greatly reduces the calculation burden by converting water quality risk into hydraulic risk. On this basis, the effects of rainfall, dry weather flow (DWF), actuators and their interactions on reliability are quantified by massive scenarios. It shows that the DWF affects the emptying process via weekly and daily seasonality and its interaction with rainfall is mainly responsible for unreliability. Further, the engineering facility linkage controlled by the actuator to cope with the interaction is the key. Particularly, the Prophet algorithm is innovatively applied to mine the patterns and generate the DWF series for the challenge of sparse DWF data. In conclusion, the indicator proposed expands the connotation of UDS reliability assessment, prompting a small investment in replacing actuators with better controllability and greatly improving reliability. It guides the engineering planning and enhancement from a new perspective of whole-chain optimization from the global to the detailed level.

Specificality, Quality Variation, Assessment and Treatment of Estuarine Water in the Pearl River Delta, South China

The Pearl River Delta (PRD) is a major economic and manufacturing area in South China. Using the comprehensive and authoritative monitoring data, this study conducted a systematic review of the regularity of marine disasters (e.g., storm surges, saltwater intrusions, and red tides), water quality variations, water quality risk assessments and wastewater treatment in seven sections of the Pearl River Estuary (PRE). The total water resources in the PRD have been a decreasing in recent years. Seasonal marine disasters occur frequently, causing loss of life and economic damage. A monitoring and early-warning system was constructed to provide a scientific basis for dealing marine disasters response. Based on the water quality monitoring data from the seven main PRE sections from 2015 to 2020, chemical properties, heavy metal concentrations and comprehensive pollution indices were selected as indicators. The water quality of the seven PRE sections, flowing westward into the South China Sea improved over time. According to a water quality risk assessment, Yamen the estuary nearest the sea is at the highest risk. The PRD had a wastewater treatment rate of 97.37%, which was equal to the average of Guangdong Province. These findings can be used to predict future trends in estuarine water, quality and inform future studies of water quality variations in the PRD.

Dynamic Analysis of Risk to Water Quality in the Baimei Reservoir Conservation Area, Fujian Province, China

The security of drinking water resources is an important concern for human survival. The extensive use of geographic information system and remote sensing data in risk assessments of water quality from a spatiotemporal perspective can complement water resource management. In this study, we investigated Baimei reservoir conservation area, Fujian Province, China. The quantitatively inversed leaf area index was used to represent the vegetation growth condition in simulations of the hydrological process using soil and water assessment tool. According to the simulation results, the spatial distribution of the risk to water quality was mainly related to the land-use condition, and the temporal distribution of the risk to water quality was mainly related to the precipitation dynamics. Single factor analysis of various scenarios showed that uncontrolled expansion of agricultural land (scenario A) would lead to an overall average increase of 231.9% in the total nitrogen (TN) load in the basin. By contrast, if agricultural lands are all transformed into forests (scenario B), then the overall TN load in the basin would decrease by an average of 20.8%. In practical terms, conversion of sloping agricultural lands to forests (scenario C) could reduce the overall TN load by 17.0%. Thus, moderate conversion of agricultural lands to forests can reduce the pollution load effectively. The simulation results obtained for scenarios with adjustments to the fertilization time and amount showed that applying fertilizer on rainy days would increase the risk to water quality compared with days without rain. The method developed in this study can be applied for dynamic analysis in water quality risk assessments of water conservation areas and can provide a scientific reference for promoting ecological management strategies and sustainable development at the regional scale.

Risk assessment of sectional water quality based on deterioration rate of water quality indicators: A case study of the main canal of the Middle Route of South-to-North Water Diversion Project

The Middle Route of South-to-North Water Diversion Project of China (MRSNWDPC) is the most important inter-basin water diversion project. This study screened out 8 water quality indicators, including pH, ammonia nitrogen (NH3-N), fecal coliform (F. coli), dissolved oxygen (DO), permanganate index (PI), five-day biochemical oxygen demand (BOD5), fluoride (F-), sulfate (SO42-), which were from monthly monitoring data of 29 sections between January 2016 and December 2018, and analyzed the probability distribution characteristics of water quality deterioration rate (WQDR) samples, compared the advantages of three kinds of probability density function parameter optimization method, then the probability density model of each water quality indicator is constructed. By defining the section water quality risk and setting the threshold, the risk level of harmful water quality events (“ degradation ”or“ standard exceedance ”) in the next one month was calculated based on the real-time monitoring data. The main conclusions include: (1) The probability density of WQDR samples in the MRSNWDPC basically corresponded to the p-III distribution, and the optimum line method can be used as the parameter optimization method of the distribution function. (2) The water quality risk assessment method proposed in this paper could calculate sectional risk based on real-time monitoring data of water quality and play an early warning role in the occurrence of harmful water quality events in the next one month. (3) From 2016 to 2018, water quality deterioration existed in the MRSNWDPC, and the probability of pH, DO and BOD5 with higher risk level was higher than other indicators. However, further research is needed to confirm whether a stable trend of water quality deterioration exists. This study redefines the concept of risk of sectional water quality from the perspective of the probability of occurrence of harmful events and sets the threshold value of risk level in combination with the water body function, so as to predict the future water quality risk level in the next month, which plays a good warning role in the water quality management of the MRSNWDPC and can help relevant management departments to make response plans in advance. It is worth mentioning that the method proposed in this paper has been applied to the water quality monitoring and early warning integrated management platform of the main canal of the MRSNWDPC.

Infrared thermographic investigation of the oxidation behaviour of sulfide minerals from antimony-bearing rocks exemplified by the Podkozara deposit, Bosnia-Herzegovina

To date, prediction of the drainage chemistry of geologic materials at mine sites commonly relies upon well-established mineralogical and geochemical test work. Antimony (Sb) deposits require water quality risk assessments that consider the contaminant's solubility and mobility behaviour. To investigate the oxidation reaction of sulfides, a newly designed infrared (IR) thermographic test protocol was used to visualise oxidising sulfide minerals and to classify the rock types from the Podkozara Sb project, Bosnia-Herzegovina according to their oxidation reactivity. Furthermore, the sample materials were geochemically and mineralogically analysed using pXRF, powder XRD, ICP-AES, ICP-MS and NAGpH techniques. Four rock types have been recognised in the deposit: (i) stibnite mineralised quartz veins (SMQV); (ii) stibnite mineralised carbonate rocks (SMCR); (iii) pyritic phyllites; and (iv) mylonitic marbles. As indicated by the defined rock types, stibnite and pyrite are the only two sulfide minerals detected in the sample materials, causing reactions of varying intensities during IR testing. The intensity and duration of the oxidation reaction depends on various factors, including the sulfide mineral itself, the ore content and galvanic reactions between the sulfide minerals. Based on IR testing, it could be demonstrated that SMQV and SMCR are highly reactive and have a high risk for sulfide oxidation and associated Sb release into waters in any pH environment. Pyritic phyllites and tailings show less oxidation reaction intensities and no oxidation reactions could be recorded for marbles. Tailings pose a low risk and pyritic phyllites as well as marbles do not show a risk at all for Sb deportment. For pyritic phyllites, however, a release of Fe must be considered. In addition, underground mine and local surface waters were analysed for their pH, Eh as well as dissolved metal, metalloid and sulfate contents. The mine waters possess especially strongly elevated Sb values (5–244 μg/L) at neutral to alkaline pH values (7.0–8.1). Thus, in the Podkozara deposit, there is a general excess of neutralising carbonate minerals that result in adequate buffering of generated sulfuric acid, limiting mobility of base metal cations in solution but this supports the mobilisation of Sb into mine waters. In this study, complementary conventional mineralogical and geochemical testing as well as novel IR visualisation of possible sulfide oxidation have revealed useful information on the likelihood of different rock types causing metalliferous drainage issues. In particular, IR thermographic testing provides valuable insights on the presence of oxidising Sb- and Fe-sulfides in ores and wastes. This information can be used to prepare suitable mitigation strategies for Sb-rich neutral mine drainage waters and serves as a sample pre-selection for long-term environmental studies and tests. Furthermore, this analysis shows that different management and separate disposal plans will be needed for different lithological wastes.

The Impact of Time-Integrating Active or Passive Sampling Methods on Bioanalytical Water Quality Risk Assessment

Since traditional chemical analytical methods only consider a minor fraction of substances present in the water cycle, biological effect monitoring (BEM) is required for a more reliable assessment of the chemical status. BEM integrates the effects of all micropollutants that may trigger adverse outcome pathways. For reliable risk assessment it is important that substances are efficiently recovered from the water matrix by the environmental sampling and extraction methods. The present study compares the performance of five time-integrated sampling and extraction methods for large effluent volumes at three wastewater treatment plants (WWTPs). Both chemical and bioassay data are evaluated to select the best suited method for bioanalytical monitoring. Large volumes of WWTP effluents, collected for three weeks by flow-proportional active sampling, were extracted with XAD resins and large-volume solid-phase extraction (SPE). Simultaneously, three types of passive samplers (silicon rubber, POCIS and Speedisk) were deployed in the effluent channels. Clear differences were observed between both chemical and bioanalytical profiles for the five time-integrated sampling/extraction methods. Higher levels of extracted chemicals did not always lead to higher responses in the bioassays. If the total amount of extracted substances reflects the overall bioactivity, this may be since both agonistic and antagonistic compounds are extracted more efficiently. The best of the investigated active sampling methods seems to be SPE, that concentrated more compounds and at higher concentrations than XAD. The results obtained with passive samplers are highly dependent on estimations of average extracted water volumes, which are difficult to predict for complex environmental mixtures. POCIS seems to be the most efficient passive sampler for concentration of polar organic micropollutants. The preference between SPE and POCIS depends on the application. Since differences in sampling and extraction will affect the assessments of environmental risks, effect-based trigger values need to be adjusted for each method.

Early warning of water quality degradation: A copula-based Bayesian network model for highly efficient water quality risk assessment

In the context of global climate change and increasingly severe environmental pollution, drinking water quality risk assessments to provide crucial early warnings have become essential routine work. At present, traditional water quality assessment methods are commonly used without considering the correlation among different indicators and the substantial uncertainty from multiple sources, which limit their applications. To address this issue, a copula-based Bayesian network (CBN) method was proposed in this study to concretely evaluate the water quality risk with multiple environmental risk indicators in a large drinking water reservoir in Tianjin city, China. Taking rainfall and water temperature (WT) as external environmental risk indicators and pH, ammonia nitrogen (NH3–N), total nitrogen (TN), total phosphorus (TP), and permanganate index (CODMn) as internal environmental risk indicators, the CBN model was constructed to investigate the interaction between the indicators and water quality state and assess the contingent risk. Our results showed that TN and NH3–N should be considered key risk indicators. Additionally, we performed forward and backward risk analyses to assess water quality risk during different seasons and determined the distributions of key indicators under different water quality risk grades. From a time perspective, the reservoir's water quality risk is much higher in winter and spring than in other seasons affected by winter snowfall. From a spatial perspective, the water quality risk is much higher at the reservoir's entrance than at other locations affected by water diversion. Furthermore, we found that the probability of water quality risk events may be relatively high when the TN concentration is 3.6 mg/L to 6.4 mg/L at the reservoir's entrance. The results reveal that the CBN method could be an invaluable decision-support tool for reservoir managers and scientists, which could provide an early warning of water quality degradation by only inputting monitoring data.

Passive sampling with suspect screening of polar pesticides and multivariate analysis in river catchments: Informing environmental risk assessments and designing future monitoring programmes

Pollution of surface water by polar pesticides is a major environmental risk, particularly in river catchments where potable water supplies are abstracted. In these cases, there is a need to understand pesticide sources, occurrence and fate. Hence, we developed a novel strategy to improve water quality management at the catchment scale using passive sampling coupled to suspect screening and multivariate analysis. Chemcatcher® passive sampling devices were deployed (14 days) over a 12 month period at eight sites (including a water supply works abstraction site) in the Western Rother, a river catchment in South East England. Sample extracts (n = 197) were analysed using high-resolution liquid chromatography-quadrupole-time-of-flight mass spectrometry and compounds identified against a commercially available database. A total of 128 pesticides from different classes were found. Statistical analysis of the qualitative screening data was used to identify clusters of pesticides with similar spatiotemporal pollution patterns. This enabled pesticide sources and fate to be identified. At the water supply works abstraction site, spot sampling and passive sampling were found to be complementary, however, the passive sampling method in conjunction with suspect screening detected 50 pesticides missed by spot sampling combined with targeted analysis. Geospatial data describing pesticide application rates was found to be poorly correlated to their detection frequency using the Chemcatcher®. Our analysis prioritised 61 pesticides for inclusion in a future water quality risk assessment at the abstraction site. It was also possible to design a seasonal monitoring programme to effectively characterise the spatiotemporal pesticide profiles within the catchment. A work flow of how to incorporate passive sampling coupled to suspect screening into existing regulatory monitoring is proposed. Our novel approach will enable water quality managers to target the mitigation (non-engineered actions) of pesticide pollution within the catchment and hence, to better inform drinking water treatment processes and save on operational costs.

Method for a new risk assessment of urban water quality: IFN-SPA

Water quality is one of the most essential factors to influence human daily life and environment health. Risk assessment of water quality has critical significance to sustainable development of human society and natural systems. Set pair analysis (SPA) methods are widely used in risk assessment, especially in water resources. The essence of SPA is to classify assessment samples consider the uncertainties exist in risk assessment system based on the viewpoints of unity, difference, and opposition. The existing SPA methods are classified into two types, including (i) original SPA and (ii) comprehensive SPA. Both the original and comprehensive SPA methods have the following limitations: (i) it is need to judge whether the assessment factor belongs to type I or type II; (ii) it is need to judge whether the assessment factor is positive or negative. This method article gives a detailed description of the application of the existing SPA method. The method article is a companion paper with the original article [1].• Description of SPA methods.• Application of SAP methods in risk assessment of water quality.• Calculate the weights of assessment factors.

A flow-weighted ensemble strategy to assess the impacts of climate change on watershed hydrology

Evaluation of hydrological response to future climate change is essential for water quality risk assessment and adaptive management implementation within a watershed context. In this study, we present a modeling framework that integrates a hydrological model with projections of General Circulation Models (GCMs). Temperature and precipitation projections of six GCMs with two downscaling methods are used to force the Soil and Water Assessment Tool (SWAT) model in the Hamilton Harbour watershed in Ontario, Canada. A flow-based weighting strategy was developed to integrate the projections of multiple GCMs based on their ability to recreate empirical flow frequency distributions in multiple monitoring sites. Our study renders support to the ability of the weighted model ensemble to draw meaningful hydrological forecasts. Nonetheless, we also note that the ensemble strategy understates the frequency and magnitude of flow extremes, and therefore the domain that is collectively delineated by individual GCMs can still provide complementary planning information. Climate change is projected to trigger a distinct increase in air temperature and precipitation during the late winter-early spring period, which in turn will likely result in an earlier snowmelt and changes in the magnitude and timing of peak flow events. Analysis of the water cycle shows that the sensitivity of the individual hydrological components to climate change may vary along the urban-to-agriculture gradient. The projected declining soil–water content in agricultural catchments highlights the likelihood of more intensified drought conditions in the croplands. Evapotranspiration rates will likely increase across the entire watershed, whereas surface runoff could be reduced but less so in urbanized locations. Overall, our findings suggest that any future planning exercise to ameliorate the prevailing water quality conditions will only be insightful if we consider the interplay between climate change and urbanization processes in the area.

Water quality risk assessment for drought conditions: A case study of the Korean Nakdong River basin

As the frequency of drought from climate change increases and the severity of drought become worse, it is imperative to prepare appropriate countermeasures against severe droughts. Despite the severe impacts of droughts on coupled humans and environmental systems, we do not fully understand the consequences of severe droughts affecting the environment. Therefore, the present study proposed a quantitative assessment index for water quality risk for extreme droughts to improve the safety of water environment management by providing flows to areas vulnerable to the drought. The application of this study is the Nakdong River basin in Korea, which has assessed the vulnerability of water quality to severe droughts as water quality deterioration problems continue to be experienced event after the river restoration project was completed. The results of this study are expected to provide scientific environmental drought monitoring information in a changing climate.

Seeing is Predicting: Water Clarity-Based Nowcast Models for E. coli Prediction in Surface Water

Given the 24–48 h turn-around time of conventional surveillance approaches, methods are needed that improve the timeliness and accuracy of recreational water quality risk assessments. Although one useful approach is to combine existing monitoring programmes with predictive faecal indicator bacteria (FIB) models, these models are largely ‘top-down’ in their approach to safeguarding public health. Beyond being simply ‘advised when to avoid swimming’, there is an increasing awareness amongst the general public regarding the role they can play in water quality monitoring. Using quantile, maximum value and optimized incremental modelling approaches, this study reports on the possibility of developing intuitive, public-friendly models that are based on the physical appearance of water (clarity), to estimate 8103 nation-wide E. coli concentrations in rivers, and to assess whether water is safe to swim in. If swimmers were to avoid river waters with <1.1 m black disc visibility during autumn and summer, and river waters with values <0.5 m black disc visibility during spring and winter, they would also avoid microbial hazards that are associated with exceedances of the 540 CFU/100 mL single sample bathing water standard. Regardless of the climatic season, stream order classification, catchment land cover or geology of streams considered, the clarity-based E. coli models performed well as they presented with sensitivity, specificity and accuracy values of at least 72%. The developed models offer the benefit of providing a faster method for estimating E. coli concentration, potentially engaging the public in water monitoring, and allowing them to make informed decisions on whether it is safe to swim.

Risk assessment of water quality in the vicinity of a large-scale farm specializing in laying hens

Risk assessment of water quality in the vicinity of a large-scale farm specializing in laying hens

Microfluidic Preconcentration Chip with Self-Assembled Chemical Modified Surface for Trace Carbonyl Compounds Detection.

Carbonyl compounds in water sources are typical characteristic pollutants, which are important indicators in the health risk assessment of water quality. Commonly used analytical chemistry methods face issues such as complex operations, low sensitivity, and long analysis times. Here, we report a silicon microfluidic device based on click chemical surface modification that was engineered to achieve rapid, convenient and efficient capture of trace level carbonyl compounds in liquid solvent. The micro pillar arrays of the chip and microfluidic channels were designed under the basis of finite element (FEM) analysis and fabricated by the microelectromechanical systems (MEMS) technique. The surface of the micropillars was sputtered with precious metal silver and functionalized with the organic substance amino-oxy dodecane thiol (ADT) by self-assembly for capturing trace carbonyl compounds. The detection of ppb level fluorescent carbonyl compounds demonstrates that the strategy proposed in this work shows great potential for rapid water quality testing and for other samples with trace carbonyl compounds.

Understanding human infectious Cryptosporidium risk in drinking water supply catchments

Treating drinking water appropriately depends, in part, on the robustness of source water quality risk assessments, however quantifying the proportion of infectious, human pathogenic Cryptosporidium oocysts remains a significant challenge. We analysed 962 source water samples across nine locations to profile the occurrence, rate and timing of infectious, human pathogenic Cryptosporidium in surface waters entering drinking water reservoirs during rainfall-runoff conditions. At the catchment level, average infectivity over the four-year study period reached 18%; however, most locations averaged <5%. The maximum recorded infectivity fraction within a single rainfall runoff event was 65.4%, and was dominated by C. parvum. Twenty-two Cryptosporidium species and genotypes were identified using PCR-based molecular techniques; the most common being C. parvum, detected in 23% of water samples. Associations between landuse and livestock stocking characteristics with Cryptosporidium were determined using a linear mixed-effects model. The concentration of pathogens in water were significantly influenced by flow and dominance of land-use by commercial grazing properties (as opposed to lifestyle properties) in the catchment (p < 0.01). Inclusion of measured infectivity and human pathogenicity data into a quantitative microbial risk assessment (QMRA) could reduce the source water treatment requirements by up to 2.67 log removal values, depending on the catchment, and demonstrated the potential benefit of collating such data for QMRAs.

Water Quality Risk Assessment for the Laoguanhe River of China Using a Stochastic Simulation Method

The Laoguanhe River is a major tributary of the Danjiang River, which is the source water source for the Danjiangkou Reservoir (i.e., the source reservoir for the middle route of the South-to-North Water Diversion Project in China). This study was intended to provide scientific decision support to help manage the water environment in the Laoguanhe River and maintain high water quality levels for the water diversion project. Risk assessment based on water quality simulation was undertaken in this research. The QUAL2Kw model was used to improve the simulations of the water quality of the Laoguanhe River under sparse data conditions. Latin hypercube sampling (LHS) was used to improve flow inputs for QUAL2Kw. The model was used to calculate the water quality risks under several scenarios based on a Markov stochastic process to reflect uncertainty. The simulation results indicated that the water quality of the downstream section of the Laoguanhe River could meet the basic requirements for exporting water to the Danjiangkou Reservoir.