Water Quality Monitoring Programs Research Articles

Prediction of stream nitrogen and phosphorus concentrations from high-frequency sensors using Random Forests Regression

Stream nutrient concentrations exhibit marked temporal variation due to hydrology and other factors such as the seasonality of biological processes. Many water quality monitoring programs sample too infrequently (i.e., weekly or monthly) to fully characterize lotic nutrient conditions and to accurately estimate nutrient loadings. A popular solution to this problem is the surrogate-regression approach, a method by which nutrient concentrations are estimated from related parameters (e.g., conductivity or turbidity) that can easily be measured in situ at high frequency using sensors. However, stream water quality data often exhibit skewed distributions, nonlinear relationships, and multicollinearity, all of which can be problematic for linear-regression models. Here, we use a flexible and robust machine learning technique, Random Forests Regression (RFR), to estimate stream nitrogen (N) and phosphorus (P) concentrations from sensor data within a forested, mountainous drainage area in upstate New York. When compared to actual nutrient data from samples tested in the laboratory, this approach explained much of the variation in nitrate (89%), total N (85%), particulate P (76%), and total P (74%). The models were less accurate for total soluble P (47%) and soluble reactive P (32%), though concentrations of these latter parameters were in a relatively low range. Although soil moisture and fluorescent dissolved organic matter are not commonly used as surrogates in nutrient-regression models, they were important predictors in this study. We conclude that RFR shows great promise as a tool for modeling instantaneous stream nutrient concentrations from high-frequency sensor data, and encourage others to evaluate this approach for supplementing traditional (laboratory-determined) nutrient datasets.

Evaluation of a multivariate analysis modeling approach identifying sources and patterns of nonpoint fecal pollution in a mixed use watershed

Surface waters listed on impaired waters (303 d) lists due to pathogen contamination pose a significant environmental and public health burden. The need to address impairments through the Total Maximum Daily Load (TMDL) process has resulted in method developments that successfully identify nonpoint fecal pollution sources by maximizing available resources to improve water quality. However, the ability of those methods to effectively and universally identify sources of fecal pollution requires further evaluation. The objective of this research was to assess the usefulness of a previously described multivariate statistical approach to identify common patterns influencing fate and transport of fecal pollutants from sources to receiving streams using the Tuckasegee River watershed in Western North Carolina as a test watershed. Two streams were routinely monitored using a targeted sampling approach to assess fecal pollution extent and identify nonpoint sources using canonical correlation and canonical discriminant analyses. Fecal pollution in the watershed varied spatially and temporally with significantly higher fecal coliform concentrations observed in Scott Creek (f = 9.49, p = 0.002) and during the summer months (f = 14.8, p < 0.0001). Canonical correlations described 62–67% of water quality variability and indicate that fecal pollution in portions of the watershed are influenced by stormwater runoff and fecal indicator bacteria resuspension from sediment, while fecal pollution in other portions are influenced by soil erosion and surface runoff. Canonical discriminant analyses indicate that LULC significantly influences the nature and extent of fecal pollution. These results demonstrate that chemical parameters are useful predictors of fecal pollution and can help identify nonpoint fecal pollution sources in relation to land use patterns and land management practices. This approach to water quality monitoring program design and data analysis may effectively and efficiently identify parameters that best predict fecal pollution to aid in development and implementation of effective TMDLs to remediate impaired waters.

Methodological Approaches to Organization of Drinking Water Quality Monitoring Programs

Summary. Introduction: Drinking water is one of the most important environmental factors sustaining life and determining human health. The goal of the Russian Federal Clean Water Project is to improve drinking water quality through upgrading of water treatment and supply systems using advanced technologies, including those developed by the military-industrial complex. The most informative and reliable sources of information for assessing drinking water quality are the results of systematic laboratory testing obtained within the framework of socio-hygienic monitoring (SGM) and production control carried out by water supply organizations. The objective of our study was to formulate approaches to organizing quality monitoring programs for centralized cold water supply systems. Materials and methods: We reviewed programs and results of drinking water quality laboratory tests performed by Rospotrebnadzor bodies and institutions within the framework of SGM in 2017–2018. Results: We established that drinking water quality monitoring in the constituent entities of the Russian Federation differs significantly in the number of monitoring points (566 in the Krasnoyarsk Krai vs 10 in Sevastopol) and measured indicators, especially sanitary and chemical ones (53 inorganic and organic substances in the Kemerovo Region vs one indicator in the Amur Region). Discussion: For a more complete and objective assessment of drinking water quality in centralized cold water supply systems, monitoring points should be organized at all stages of water supply with account for the coverage of the maximum number of people supplied with water from a particular network. Thus, the number of points in the distribution network should depend, inter alia, on the size of population served. In urban settlements with up to 10,000 inhabitants, for example, at least 4 points should be organized while in the cities with more than 3,000,000 inhabitants at least 80 points are necessary. We developed minimum mandatory lists of indicators and approaches to selecting priority indices to be monitored at all stages of drinking water supply.

Nutrient limitation of phytoplankton in Chesapeake Bay: Development of an empirical approach for water-quality management

Understanding the temporal and spatial roles of nutrient limitation on phytoplankton growth is necessary for developing successful management strategies. Chesapeake Bay has well-documented seasonal and spatial variations in nutrient limitation, but it remains unknown whether these patterns of nutrient limitation have changed in response to nutrient management efforts. We analyzed historical data from nutrient bioassay experiments (1992–2002) and data from long-term, fixed-site water-quality monitoring program (1990–2017) to develop empirical approaches for predicting nutrient limitation in the surface waters of the mainstem Bay. Results from classification and regression trees (CART) matched the seasonal and spatial patterns of bioassay-based nutrient limitation in the 1992–2002 period much better than two simpler, non-statistical approaches. An ensemble approach of three selected CART models satisfactorily reproduced the bioassay-based results (classification rate = 99%). This empirical approach can be used to characterize nutrient limitation from long-term water-quality monitoring data on much broader geographic and temporal scales than would be feasible using bioassays, providing a new tool for informing water-quality management. Results from our application of the approach to 21 tidal monitoring stations for the period of 2007–2017 showed modest changes in nutrient limitation patterns, with expanded areas of nitrogen-limitation and contracted areas of nutrient saturation (i.e., not limited by nitrogen or phosphorus). These changes imply that long-term reductions in nitrogen load have led to expanded areas with nutrient-limited phytoplankton growth in the Bay, reflecting long-term water-quality improvements in the context of nutrient enrichment. However, nutrient limitation patterns remain unchanged in the majority of the mainstem, suggesting that nutrient loads should be further reduced to achieve a less nutrient-saturated ecosystem.

Application of indexes to evaluate the water quality of the Continguiba/Pindoba Irrigated Perimeter in Sergipe, Brazil

Irrigation makes food production viable, but the quality and quantity of water may be compromised as a result of inadequate management, which may lead to an increase in the concentration of nutrients, heavy metals and agrochemicals. This study aimed to characterize and monitor the water quality of the Continguiba/Pindoba Irrigated Perimeter in Sergipe, Brazil. Secondary data from the Water Quality Monitoring Program were used through the reports of monitoring campaigns carried out between 2013 and 2014. The Water Quality Index (WQI) and the Trophic State Index (TSI) were used in the water quality assessment. The results showed that there is an influence of seasonality, where the best indices were obtained in the rainy season, with the WQI characterized as regular to good, and the TSI characterized as oligotrophic. There was interference from the drainage of rice lots in the dry season, contributing to the increase of nutrients. There was no spatial influence for WQI, which may be related to the eclipse effect, which attenuated the negative impact of a certain variable given the aggregation of several variables. The TSI suffered spatial influence, the waters added to agricultural and fish lots were classified as oligotrophic or ultraoligotrophic, already in the drainage were found indexes of super-utrophic state.

From data to decisions: understanding information flows within regulatory water quality monitoring programs

Most countries maintain regulatory requirements for testing of drinking water supplies to guide treatment procedures and ensure safe water delivery to consumers. It is unclear, however, if water quality data are always used effectively, particularly in low-resource settings. Efforts to improve the use of water quality data will benefit from a comprehensive understanding of existing systems for managing and sharing information. This study evaluates the methods used to organize, analyze, and transmit drinking water quality data among 26 water supplier or surveillance institutions and two regulatory agencies in six countries of sub-Saharan Africa. Following extensive qualitative and quantitative data collection, we developed data flow diagrams to map formal and informal water quality networks. We found high levels of similarities between the information systems established by different institutions operating under different regulatory structures. We determined that the key barriers to information flows were the limited aggregation and analysis of data and the poor enforcement of data sharing requirements. Our results suggest that broad reforms are necessary to improve the use of these water quality data to manage water safety. These measures could include strengthening enforcement of testing and reporting, building staff capacity for managing and using data, and integrating collection of water quality data with other information systems.

Water and Sediment Quality in the Coastal Zone Around the Mouth of Doce River After the Fundão Tailings Dam Failure.

Fundão dam (Minas Gerais, Brazil) breached on 5 November 2015, releasing 50 million m³ of Fe ore tailings and dam materials into the upper Doce River system. The tailings travelled 670 km along the river system to the ocean. Starting on 17 November 2015, 6 days before the tailings reached the Doce River mouth, a water quality monitoring program with a daily sampling schedule was implemented by Samarco Mineração S.A. (Samarco) to assess the impacts on marine water and sediment quality. Between November 2015 and August 2017 water and sediment quality were monitored at 28 locations offshore from the Doce River mouth. The sampling areas were grouped by hydrological and metocean season (i.e., rainy and dry seasons and wave and wind climates), distance from the river mouth (<5 km, >5 km and within a Marine Protected Area), and water depth. The data were compared to the Brazilian water quality standards and prebreach conditions. Statistical tests were conducted to evaluate temporal and spatial trends and patterns. For the water quality parameters of relevance (total suspended solids, turbidity, total and dissolved Fe, Al, and Mn), pulses of concentration increases were observed right after the arrival of the plume in the coastal zone and during the subsequent rainy seasons. Exceedances of prebreach conditions were more frequent closer to the Doce River mouth. During the dry season, concentrations tended to decrease, reaching prebreach levels for a number of parameters, with small short-term pulses associated with metocean factors. For sediment quality parameters of relevance (particle size, Fe, Al, and Mn), Fe was the only one that clearly resulted from the dam breach, which was mediated by river influence and oceanographic factors affecting particle size distribution. Results indicated that the Fundão dam failure did affect water and sediment quality in the Atlantic Ocean, with greater impacts closer to the river mouth and immediately after the arrival of the tailings plume, with concentrations gradually returning to preevent levels over time. Integr Environ Assess Manag 2020;16:643-654. © 2020 SETAC.

Intelligent decision-support system to plan, manage and optimize water quality monitoring programs: design of a conceptual framework

This paper presents the conceptual framework of a holistic, intelligent decision-support system (IDSS) to plan, manage and optimize water quality monitoring programs (WQMPs) for surface waters. WQMPs are a crucial component of water management because information on water quality is essential when taking action such as legislative compliance, environmental projects, urban and infrastructure development. Planning, managing and optimizing WQMPs is a complex process and requires multiple variables, rules and subject matter expert knowledge. The specific goals of this paper were to (1) assess to what extent the subject domain (WQMPs) is deemed appropriate for an IDSS; (2) describe the design process of the conceptual framework; (3) present the main elements of the system architecture; (4) present two case studies that served as potential end users; (5) illustrate the applicability of the IDSS and (6) describe subsequent steps to further test the IDSS. The IDSS was developed on the premise that the proposed system could (1) improve quality, (2) capture undocumented expertise that is perishable or in short supply (tacit knowledge), (3) provide accessible expertise to novice users, (4) have a training effect on users, and (5) show that the system, even partially complete, could still be useful. Our initial assumptions regarding these points were validated through interviews with subject matter experts. The conceptual framework was designed based on a literature review, interviews with 44 subject matter experts from Europe, Canada and the United States, interaction with end users from two case studies in the Province of Quebec, Canada, and five information technology experts from Canada and Germany. The IDSS presented in this paper will facilitate the planning, management and optimization of WQMPs. It will be exportable to various watersheds and consider the WQMP planner’s need to update the network rapidly if changes occur in human, financial and technical resources. HIGHLIGHTS Holistic and adaptable decision-support system to plan, manage and optimize surface water quality monitoring programs Management and decision support system for knowledge acquisition processes on water quality System integrates tacit and explicit knowledge on water quality monitoring challenges Management and decision support system based on tacit knowledge from 44 experts and two case studies Adapted design methodology for an Intelligent decision-support system

Macroalgae transplant to detect the occurrence of anthropogenic nutrients in seawater of highly tourist beaches in Mediterranean islands

In the Mediterranean region, islands are among the most important tourist destinations, being sites of considerable naturalistic, historical and cultural importance. This is highly beneficial for local economies, but may also represent a threat for the environment, especially during the peak season (i.e. summer). Indeed, the sharp demographic increase concentrated in a relatively short period may negatively affect the quality of coastal marine systems and the provision of ecosystem services, producing in turn negative feedbacks on tourism industry. Nevertheless, the assessment of the environmental impact of tourism on coastal seawater has been seldom addressed. Here, we show the results of the biomonitoring approach adopted in the tourist Island of Rhodes (Greece), in the context of the Interreg Med BLUEISLANDS project. The study involved short-term macroalgae transplantation and incubation, and, through the analysis of nitrogen stable isotopes, provided a time-integrated picture of the occurrence of anthropogenic nutrients, which are indicators of water quality and might be missed by routine water quality monitoring programs. Main findings ruled out a marked input of anthropogenic nutrients potentially threatening the functioning of coastal ecosystems and highlighted overall good environmental conditions. In addition, this approach provided spatial data useful to produce GIS maps, useful tools that may help the decisional process of policy-makers, for adopting management practices to mitigate the environmental impact and foster sustainable tourism.

Influence of Fundão Tailings Dam Breach on Water Quality in the Doce River Watershed.

The Fundão dam (Minas Gerais, Brazil) breach resulted in the transport and deposition of Fe mine tailings and debris for approximately 670 km along the Doce River watershed. Following the event, an extensive water quality monitoring program was implemented. The results generated by this program were used to assess the temporal and spatial impacts of the event on water quality. Data from several sampling sites situated along affected watercourses collected from 6 November 2015 to 27 September 2017 were evaluated. The sampling area was grouped into 4 zones delineated by hydropower plant dams located along the Doce River watershed and divided into 5 distinct time periods related to hydrological seasonality. Data were also compared to the Brazilian standards of water quality and available pre-event conditions. Principal component analysis followed by analysis of variance (ANOVA) tests were performed to evaluate the observed temporal and spatial trends and patterns. The results indicated that concentrations of 58 water quality parameters increased with the arrival of the tailings wave released by the breach, generally exceeding pre-event and regulatory levels. Persistent or seasonally recurring concentrations were observed for 30 water quality parameters. Concentrations of total and dissolved forms of Fe, Al, Mn, total P, total suspended solids, and turbidity tended to increase during the wet season and decrease during the dry season, this trend being more pronounced close to the dam. The water quality changes were more pronounced immediately after the arrival of the tailings wave, gradually decreasing over time and returning prebreach conditions, but fluctuated seasonally in response to the natural variation in river flow. Integr Environ Assess Manag 2020;16:583-595. © 2020 SETAC.

Tryptophan-like fluorescence as a high-level screening tool for detecting microbial contamination in drinking water

Regular monitoring of drinking water quality is vital to identify contamination of potable water supplies. Testing for microbial contamination is important to prevent transmission of waterborne disease, but establishing and maintaining a water quality monitoring programme requires sustained labour, consumables and resources. In low resource settings such as developing countries, this can prove difficult, but measuring microbial contamination is listed as a requirement of reaching the UN's Sustainable Development Goal 6 for water and sanitation. A nine-month water quality monitoring programme was conducted in rural Malawi to assess the suitability of tryptophan-like fluorescence (TLF), an emerging method for rapidly detecting microbial contamination, as a drinking water quality monitoring tool. TLF data was compared with thermotolerant coliforms (TTCs, E. coli) and inorganic hydrochemical parameters. A large (n = 235) temporal dataset was collected from five groundwater drinking water sources, with samples collected once or twice weekly depending on the season. The results show that TLF can indicate a broader contamination risk but is not as sensitive to short term variability when compared to other faecal indicators. This is likely due to a broad association of TLF with elevated DOC concentrations from a range of different sources. Elevated TLF may indicate preferential conditions for the persistence of TTCs and/or E. coli, but not necessarily a public health risk from microbial contamination. TLF is therefore a more precautionary risk indicator than microbial culturing techniques and could prove useful as a high-level screening tool for initial risk assessment. For widespread use of TLF to be successful, standardisation of TLF values associated with different levels of risk is required, however, this study highlights the difficulties of equating TLF thresholds to TTCs or E. coli data because of the influence of DOC/HLF on the TLF signal.

Evaluating the impact of sampling design on drinking water quality monitoring program outcomes

Drinking water suppliers around the world are required by regulations to sample and test water quality in their distribution systems with the intention of generating information that can be used to protect human health. Requirements for where samples must be collected can vary and guidance on how to select locations to meet these requirements is limited. There is a need to better define and evaluate the meaning of representative in the context of selecting locations for collecting grab samples while considering the regulatory context and resources available to suppliers. We develop sampling programs for monitoring disinfectant residual concentrations and compare the results and efficacy of these programs using synthetic water quality data for two example distribution systems. Results showed that achieving accurate estimates of worst quality conditions in a network was more likely than achieving accurate estimates of systemwide conditions, and that using constant locations makes it difficult to accurately represent systemwide conditions. Results also showed that timing of sample collection is likely important depending on factors such as consumer demand patterns, and that it is inappropriate to make conclusions about systemwide conditions when few samples are taken over an evaluation period. This research has implications for developing recommendations that water suppliers and regulators can use to design and evaluate effective sampling programs.

Hydrogeochemical evaluation, suitability, and health risk assessment of groundwater in the watershed of Godavari basin, Maharashtra, Central India

In this investigation, the geochemical progression of a total of 31 groundwater samples of pre-monsoon season was assessed with categorization based on entropy weight water quality index and risk assessment on public health in the semi-arid area of Godavari basin, Maharashtra, Central India. Graphically, the major groundwater types identified were Ca-HCO3, mixed Ca-Mg-Cl, and mixed Ca-Na-HCO3. Based on [Mg2+/Na+] with [Ca2+/Na+] and [HCO3-/Na+] with [Ca2+/Na+] plots, carbonate and silicate weathering were identified as a major geochemical process governing groundwater chemistry. The presence of reverse ion exchange process was authenticated by (Ca2+ + Mg2+) vs. (HCO3- + SO42-) and Na+ + K+-Cl- vs. (Ca2+ + Mg2+)-(HCO3- + SO42-) plots. The saturation index values for calcite and dolomite showed that these minerals were in dissolution state. The dissolution of gypsum, dolomite, and anhydrite increased Ca2+ load in groundwater which accelerated the precipitation of calcite. The high toxic level of NO3- (> 45mg/L) was identified in 64.5% of the 31 groundwater samples, whereas F- concentration exceeded the threshold value in 12.9% of samples. Based on the entropy weight water quality index values, 70% of the samples were found to have moderate quality for drinking. In addition, health risk evaluation showed that the total hazard, due to fluoride and nitrate through oral pathways, was much higher than that through the dermal pathway. Children were found to be at high risk due to the consumption of NO3- and F- contaminated water. The calculated irrigation water quality index (IWQI) diverge from 7.4-89.2, expressing excellent to good quality for irrigation. Based on the irrigation water quality index, 90.3% of samples were found excellent for irrigation and 6.4% of good quality for irrigation. Authors recommend that continuous water quality monitoring programs along with effective management practices should be developed to avoid excessive extraction of groundwater.

Challenges in Quantifying Air-Water Carbon Dioxide Flux Using Estuarine Water Quality Data: Case Study for Chesapeake Bay.

Estuaries play an uncertain but potentially important role in the global carbon cycle via CO2 outgassing. The uncertainty mainly stems from the paucity of studies that document the full spatial and temporal variability of estuarine surface water partial pressure of carbon dioxide ( pCO2). Here, we explore the potential of utilizing the abundance of pH data from historical water quality monitoring programs to fill the data void via a case study of the mainstem Chesapeake Bay (eastern United States). We calculate pCO2 and the air‐water CO2 flux at monthly resolution from 1998 to 2018 from tidal fresh to polyhaline waters, paying special attention to the error estimation. The biggest error is due to the pH measurement error, and errors due to the gas transfer velocity, temporal sampling, the alkalinity mixing model, and the organic alkalinity estimation are 72%, 27%, 15%, and 5%, respectively, of the error due to pH. Seasonal, interannual, and spatial variability in the air‐water flux and surface pCO2 is high, and a correlation analysis with oxygen reveals that this variability is driven largely by biological processes. Averaged over 1998–2018, the mainstem bay is a weak net source of CO2 to the atmosphere of 1.2 (1.1, 1.4) mol m−2 yr−1 (best estimate and 95% confidence interval). Our findings suggest that the abundance of historical pH measurements in estuaries around the globe should be mined in order to constrain the large spatial and temporal variability of the CO2 exchange between estuaries and the atmosphere.

Severe western Canadian wildfire affects water quality even at large basin scales

Wildfires can have severe and lasting impacts on the water quality of aquatic ecosystems. However, our understanding of these impacts is founded primarily from studies of small watersheds with well-connected runoff regimes. Despite the predominance of large, low-relief rivers across the fire-prone Boreal forest, it is unclear to what extent and duration wildfire-related material (e.g., ash) can be observed within these systems that typically buffer upstream disturbance signals. Following the devastating 2016 Fort McMurray wildfire in western Canada, we initiated a multi-faceted water quality monitoring program that suggested brief (hours to days) wildfire signatures could be detected in several large river systems, particularly following rainfall events greater than 10 mm. Continuous monitoring of flow and water quality showed distinct, precipitation-associated signatures of ash transport in rivers draining expansive (800–100,000 km2) and partially-burned (<1–22 percent burned) watersheds, which were not evident in nearby unburned regions. Yields of suspended sediment, nutrients (nitrogen, phosphorus) and metals (lead, others) from impacted rivers were 1.2–10 times greater than from those draining unburned regions. Post-fire suspended sediment concentrations in impacted rivers were often larger than pre-fire 95% prediction intervals based on several years of water sampling. These multiple lines of evidence indicate that low-relief landscapes can mobilize wildfire-related material to rivers similarly, though less-intensively and over shorter durations, than headwater regions. We propose that uneven mixing of heavily-impacted tributaries with high-order rivers may partially explain detection of wildfire signals in these large systems that may impact downstream water users.

Assessment of nutrient contamination in the waters of the El Fuerte River, southern Gulf of California, Mexico.

This study assessed the spatial and temporal nutrient variability in the El Fuerte River basin in northwestern Mexico, considering its effects on the water trophic status as well as the nutrient loading to the Gulf of California. Physicochemical parameters, inorganic species of nitrogen, phosphate, total nitrogen, total phosphorus, and chlorophyll-a (chl-a) were quantified at 16 selected sites along the river in April (dry season) and October (rainy season) 2017. Mean concentrations of nutrients during dry and rainy seasons were 36.3 ± 24.1 and 55.1 ± 74.6 μg L-1 of total ammonia nitrogen, 3.4 ± 3.6 and 4.5 ± 3.5 μg L-1 of NO2--N, 190.8 ± 256.0 and 163.6 ± 261.0 μg L-1 of NO3--N, 42.4 ± 44.2 and 104.9 ± 76.2 μg L-1 of PO43--P, 1.0 ± 1.3 and 691 ± 2242 mg L-1 of TN, 0.06 ± 0.06 and 0.08 ± 0.09 mg L-1 of TP, and 0.9 ± 0.6 and 2.0 ± 0.9 μg L-1 of chl-a with significant differences (p < 0.05) between sites and seasons. When waters are transported downstream, nutrient levels are enriched by 4 to 35 times compared to those upstream due to increased population and agriculture downstream, confirming the hypothesis of the study. The calculated TN and TP fluxes were 1.23 × 104 and 3.57 × 101 ton year-1, respectively. Factor analysis indicated that inorganic nitrogen species and phosphorus are the main factors affecting the river water quality. Despite N excess during the rainy season, the river reached mesotrophic waters due to phosphorus limitation. This suggests the need to establish a water quality monitoring program to understand the vulnerability of the river course to changes in its trophic state.

Economic and efficiency based optimisation of water quality monitoring network for land use impact assessment

The evaluation of the importance of having accurate and representative stations in a network for river water quality monitoring is always a matter of concern. The minimal budget and time demands of water quality monitoring programme may appear very attractive, especially when dealing with large-scale river watersheds. This article proposes an improved methodology for optimising water quality monitoring network for present and forthcoming monitoring of water quality under a case study of the Selangor River watershed in Malaysia, where different monitoring networks are being used by water management authorities. Knowing that the lack of financial resources in developing countries like Malaysia is one of the reasons for inadequate monitoring network density, to identify an optimised network for cost-efficiency benefits in this study, a geo-statistical technique coupled Kendall's W was first applied to analyse the performance of each monitoring station in the existing networks under the monitored water quality parameters. Second, the present and future changes in non-point pollution sources were simulated using the integrated Cellular Automata and Markov chain model (CA–Markov). Third, Station Potential Pollution Score (SPPS) determined based on Analytic Hierarchy Process (AHP) was used to weight each station under the changes of non-point pollution sources for 2015, 2024, and 2033 prior to prioritisation. Finally, according to the Kendall's W test on kriging results, the weights of non-point sources from the AHP evaluation and fuzzy membership functions, six most efficient sampling stations were identified to build a robust network for the present and future monitoring of water quality status in the Selangor River watershed. This study proposes a useful approach to the pertinent agencies and management authority concerned to establish appropriate methods for developing an efficient water quality monitoring network for tropical rivers.

Considerations on the monitoring of water quality in urban streams: a case study in Portugal

Monitoring water quality in urban stream is of utmost importance for water resources managers, who are pressured to optimize monitoring schemes in order to reduce costs. The present study aims to use the results of a 2-year-long water quality monitoring program of an urban stream in Portugal to identify improvement opportunities. The urban stream under study was subjected to wastewater treatment plants effluent discharges, leachates from a major sealed landfill, low-class housing effluents, and nonpoint sources of pollution. Contributing watersheds are mostly artificial surfaces and agricultural land, which irrigate directly from the river. River water quality was evaluated on 11 sampling locations for 24months from October 2013 to September 2015. The present paper describes statistical analysis of the results obtained for 12 physicochemical parameters in order to optimize the monitoring scheme. Cluster analysis detected a seasonal variation in the water quality and a spatial pattern based on the major point sources of pollution. A factor analysis showed that the parameters that mostly contribute to water quality assessment in this urban river are alkalinity, ammonia, electrical conductivity, pH, temperature, and dissolved oxygen. Results suggest that the monitoring efforts-and associated costs-may be reduced by decreasing monitoring frequency, sampling points, and monitored parameters. The statistical analysis described in this study may be replicated in other water quality monitoring programs, providing useful and important information for the systematic and iterative assessment of the adequacy of water quality sampling programs towards a sustainable management of water quality surveillance.

Capacity challenges in water quality monitoring: understanding the role of human development

Monitoring the qualitative status of freshwaters is an important goal of the international community, as stated in the Sustainable Development Goal (SDGs) indicator 6.3.2 on good ambient water quality. Monitoring data are, however, lacking in many countries, allegedly because of capacity challenges of less-developed countries. So far, however, the relationship between human development and capacity challenges for water quality monitoring have not been analysed systematically. This hinders the implementation of fine-tuned capacity development programmes for water quality monitoring. Against this background, this study takes a global perspective in analysing the link between human development and the capacity challenges countries face in their national water quality monitoring programmes. The analysis is based on the latest data on the human development index and an international online survey amongst experts from science and practice. Results provide evidence of a negative relationship between human development and the capacity challenges to meet SDG 6.3.2 monitoring requirements. This negative relationship increases along the course of the monitoring process, from defining the enabling environment, choosing parameters for the collection of field data, to the analytics and analysis of five commonly used parameters (DO, EC, pH, TP and TN). Our assessment can be used to help practitioners improve technical capacity development activities and to identify and target investment in capacity development for monitoring.

Applying Quantitative Microbial Risk Assessment Model in Developing Appropriate Standards for Irrigation Water.

This study aimed to apply a quantitative microbial risk assessment (QMRA) model to estimate the annual risk probability of Salmonella infection associated with the consumption of crops, which were irrigated with raw wastewater abstracted by farmers without official permission. Data generated from the model were used to propose realistic standards for Salmonella in irrigation water needed for safe crop production. Results demonstrated the presence of total coliforms, fecal coliforms, fecal streptococci, and Salmonella in wastewater samples. Salmonella was recorded on lettuce and spinach in 3 different harvesting events, although it was not found in data obtained for parsley plant. The QMRA scenario included surface irrigation, consumption of raw crops, and 1-day withholding period before harvest. The annual risk probability of Salmonella infection for consumers exceeded the target tolerable risk (7.7 × 10-4 ) for investigated crops. The Pearson's correlation coefficient between different annual risk probabilities showed significant correlation (p < 0.05). The levels of risk posed from spinach and lettuce were roughly similar, although they tended to be higher for lettuce. The optimum concentrations of Salmonella in irrigation water needed to satisfy the World Health Organization guidelines of disease burden (disability-adjusted life years 10-6 ) per person per year ranged from 34 to 119 via multiple-tube fermentation technique/100 mL, for spinach and lettuce plants, respectively. The study concluded that unofficial reuse of wastewater in irrigation is a principle route for crop contamination. Water quality monitoring programs should be integrated with QMRA investigations for better estimation of risk level. The fit parameters used could be tailored to cover a wide array of local situations in different countries. Models applied for viruses, helminths, and bacteria other than Salmonella are encouraged in future studies. Integr Environ Assess Manag 2020;16:353-361. © 2019 SETAC.