Aquatic macroinvertebrate communities as indicators of water quality in the Raška River

In this work, a hydrodynamic and water quality model was developed for Lake Nubia based on a two-dimensional, laterally averaged and finite difference hydrodynamic and water quality code, CE-QUAL-W2. The model was calibrated and verified using data which were measured in the years of 2006 and 2007 during low flood periods, respectively. Measurements during the flood season are not available. The results of the presented model show a good agreement with the observed hydrodynamic and water quality records. Two water quality indices (WQIs), NSF WQI and CCME WQI, have been developed to assess the state of water quality in the investigated case study, Lake Nubia, during the first low flood period of January 2006. The CCME WQI has been modified to use the Egyptian standards (objectives) of raw water. Moreover, another two trophic status indices, Carlson TSI and LAWA TI, have been developed to evaluate the trophic status of Lake Nubia during the same period of January 2006. Results of the previously developed hydrodynamic and water quality model for Lake Nubia were used to validate the model. According to the developed water quality indices results, Lake Nubia has a good water quality state during the low flood period. The modified CCME WQI (based on measured data) indicates that the Lake Nubia water quality state is excellent according to the Egyptian standards of water quality for surface waterways. Results of the applied trophic status indices show that the Lake Nubia trophic status is eutrophic during the studied period. The effect of the global climate change on the hydrodynamic and water quality characteristics of Lake Nubia was conducted for the 21st century. To do that, the outputs of eleven global climate models for two global emissions scenarios combined with hydrological modeling were used. A theoretical process algorithm has been simplified, further developed and calibrated to modify the initial conditions of dissolved oxygen due to the global climate change effects. A sensitivity analysis has been conducted by using each of the predicted air temperature and inflow data separately in the model in order to investigate its effect on the characteristics of the hydrodynamic and water quality. Three hydrodynamic characteristics of the reservoir were investigated with respect to the climate change: water surface levels, evaporation water losses and thermal structure. In addition, eight water quality characteristics of the reservoir were investigated with respect to the climate change: dissolved oxygen, chlorophyll-a, ortho-phosphate, nitrate-nitrite, ammonium, total dissolved solids, total suspended solids and potential of hydrogen (pH). Moreover, the climate change effects on the water quality and trophic status indices have been studied. The results of the climate change study show partially significant impacts on the examined hydrodynamic and water quality characteristics, while the water quality and trophic status indices are slightly affected by the climate change scenarios.

This is the second aquatic biological monitoring report generated by Los Alamos National Laboratory's (LANL's) Water Quality and Hydrology Group. The study has been conducted to generate impact-based assessments of habitat and water quality for LANL waterways. The monitoring program was designed to allow for the detection of spatial and temporal trends in water and habitat quality through ongoing, biannual monitoring of habitat characteristics and benthic aquatic macroinvertebrate communities at six key sites in Los Alamos, Sandia, Water, Pajarito, and Starmer's Gulch Canyons. Data were collected on aquatic habitat characteristics, channel substrate, and macroinvertebrate communities during 2001 and 2002. Aquatic habitat scores were stable between 2001 and 2002 at all locations except Starmer's Gulch and Pajarito Canyon, which had lower scores in 2002 due to low flow conditions. Channel substrate changes were most evident at the upper Los Alamos and Pajarito study reaches. The macroinvertebrate Stream Condition Index (SCI) indicated moderate to severe impairment at upper Los Alamos Canyon, slight to moderate impairment at upper Sandia Canyon, and little or no impairment at lower Sandia Canyon, Starmer's Gulch, and Pajarito Canyon. Habitat, substrate, and macroinvertebrate data from the site in upper Los Alamos Canyon indicated severe impacts from the Cerro Grande Fire of 2000. Impairment in the macroinvertebrate community at upper Sandia Canyon was probably due to effluent-dominated flow at that site. The minimal impairment SCI scores for the lower Sandia site indicated that water quality improved with distance downstream from the outfall at upper Sandia Canyon.

HighlightsTreatment improved water quality at Densmore Pond but not Wilderness Ridge Pond.Macroinvertebrate populations showed context-dependent patterns from FTW treatment.FTWs acted as refugia for ponds with eutrophic conditions.Macroinvertebrate predator species diversification increased at Densmore Pond.Abstract. In urban landscapes, stormwater retention ponds provide an abundance of services such as nutrient cycling, erosion control, pollutant removal, habitat, and aesthetics. Aquatic macroinvertebrates play functional roles in habitat creation and predator-prey interactions and are tolerant of varying levels of pollution, making them suitable bioindicators for monitoring ecological treatments. Pollution is known to reduce habitat, niches, and overall biological diversity. However, the response of macroinvertebrates to water quality improvements has not been well documented. This study quantified changes in aquatic macroinvertebrate communities in two urban retention ponds receiving water quality treatments via floating treatment wetlands (FTWs) and slow-release lanthanum composites inside airlift pumps. We hypothesized FTWs would benefit aquatic macroinvertebrates directly, by providing unique habitat structure via suspended roots, and indirectly, by removing pollution from the water column to support aquatic vegetation growth. At Densmore Pond, three years of biological-chemical treatment effectively reduced nutrient and chlorophyll-a concentrations. This resulted in the expansion of aquatic vegetation communities and the diversification of macroinvertebrate predator species. At the Wilderness Ridge Pond, nutrient and chlorophyll-a concentrations remained unchanged, with minimal aquatic vegetation taking hold and macroinvertebrate communities dominated by the same families. Nevertheless, the Wilderness Ridge Pond FTWs acted as refugia by providing otherwise scant habitat for biota not observed within the broader ecosystem. Collectively, these findings provide divergent results but document the positive effects FTWs make on macroinvertebrate communities when water quality improves (i.e., Densmore Pond) or the refugia FTWs provide when water quality does not drastically improve (i.e., Wilderness Ridge Pond). Keywords: Aquatic macroinvertebrates, Bioassessment, Context-dependency, Ecology, Floating treatment wetland, Lanthanum, Novel ecosystems, Phytoremediation.

Issue By 2025, half of the world's population will be living in water-stressed areas. Managing water quality and quantity is a worldwide concern that will require investing in WATER Centers and monitoring systems to improve the safety of drinking water and contribute to water conservation worldwide. Without reliable water policy climate change will threaten human survival. Problem There is no single measure that can describe overall water quality for any one body of water, let alone at a global level. Seven assessment methods used to measure water quality either on a national or global level, were reviewed and indexed. This index was examined and compared by objective, use, distribution and global location. Water centers need to review community water process, outcomes and outputs and also provide user populations with a Water Quality and Water Quantity Index (WQQI). Results United Nations Environment Programme UNEP research has revealed that “although there is no globally accepted composite index of water quality, some countries and regions have used, or are using, aggregated water quality data in the development of water quality indices.” 'Most water quality indices rely on normalizing, or standardizing data by parameter according to expected concentrations and some interpretation of 'good' versus 'bad' concentrations”. Lessons The survival of the human population requires policy changes regarding water management. The feedback humans need to survive can best be described as a Water Quality and Quantity Index (WQQI). With the growing scarcity of drinking water worldwide, proactive strategic thinking and planning is necessary. Message: Investing in WATER Centers ensures that the public health and economic benefits for all things related to water is optimized. The WQQI could also be useful in longitudinal and cross-sectional epidemiological studies. Key messages The survival of the human population requires policy changes regarding water management. Mankind needs real-time feedback about water quality to respond to threats to the water supply.

In 1990, field studies of water quality and stream macroinvertebrate communities were initiated in Sandia Canyon at Los Alamos National Laboratory. The studies were designed to establish baseline data and to determine the effects of routine discharges of industrial and sanitary waste. Water quality measurements were taken and aquatic macroinvertebrates sampled at three permanent stations within the canyon. Two of the three sample stations are located where the stream regularly receives industrial and sanitary waste effluents. These stations exhibited a low diversity of macroinvertebrates and slightly degraded water quality. The last sample station, located approximately 0.4 km (0.25 mi) downstream from the nearest wastewater outfall, appears to be in a zone of recovery where water quality parameters more closely resemble those found in natural streams in the Los Alamos area. A large increase in macroinvertebrate diversity was also observed at the third station. These results indicate that effluents discharged into Sandia Canyon have a marked effect on water quality and aquatic macroinvertebrate communities.

Water quality assessment is an increasingly important area of environmental study. Assessment of water quality can be a process that includes multiple factors, which can have an influence on water quality. Researchers have developed many evaluation indices in order to display the results of water quality evaluations more intuitively. The water quality index has been an important field in sustainable water quality management. This research, based on the papers published of 20 years from the Web of Science, analyzed the data by using CiteSpace 5.0. The result shows the direction, frontiers, and hotspots of the water quality index. Research from institutes, research keywords, word frequency, quoted literature, and subjects The result shows that, in view of the world, India, China, the US, Brazil, and Iran are major countries. From the hotspots and frontiers of research, key words like "water quality management" and "drinking water quality" are the main research hotspots and frontiers of social network in the contamination of water and water quality problems in China and India. This study provides a method for scientists to keep up with the situation of the study on water quality management and puts forward suggestions for further research on sustainable water quality index.

Human societies rely on water to fulfill multiple needs. Paradoxically, our dependency on water has brought fundamental changes to freshwater ecosystems that may manifest as abrupt transitions in water quantity and quality indicators associated with conditions that can no longer fulfill human needs. Of particular concern amidst a time of environmental changes are tropical streams and their linked riparian zones, particularly in islands, given their role in the provisioning of water-derived ecosystem services. Focusing on a watershed that has become a key player in the water economy of Puerto Rico we investigated the spatiotemporal variation of water quality and socio-economic indicators, including links between them. The analyses of two unique datasets showed that 1) water quality indicators exhibited three distinctive behaviors, 2) in a small number of stations biological and chemical variables tended to decrease over time, 3) socio-economic indicators were spatially discontinuous, and 4) water quality and socio-economic indicators were related in counter-intuitive ways yet scale became a critical factor revealing the nature of the relationships. Our results raise questions about the causes underlying the observed variability in water quality and socio-economic conditions, the resilience of tropical watersheds, and ultimately the sustainable delivery of water-derived ecosystem services.

Productive activities such as agriculture and livestock have transformed the Andean basins in South America. In accordance with this statement, the objective of this study was to assess the water quality of “Las Piedras” river located in an Andean basin with 6626 ha in Colombian Highlands. This study analyzed nutrient inputs from agricultural production, spatial crops distribution, human activities and their influence on the ecological state of the river. The evaluation integrated physicochemical and biological parameters in the indexes of water quality, pollution and the aquatic macroinvertebrates community. Results showed that aggregated crop fields occupy 25.2 % in the basin and the biological water quality through the Biological Monitoring Working Party (BMWP) index denotes the presence of tolerant-pollution organisms, additionally the biodiversity was low (Shannon H ´ 1.1). The water quality in the river satisfies the Colombian regulation criteria for human consumption, even higher concentrations of nutrients in the lower area with 2.20 mg/L nitrates and 1.49 mg/L of phosphates, besides the loss of nutrients by runoff, which was 2.57 mg/L nitrates in the middle area and 0.18 mg/L phosphates in the upper area. In this sense, the nutrient concentration input increases toward the lower area of the basin because of the crop distribution. The agricultural land use modified the hydrological ecosystem services by decreasing the basin water regulatory capacity and nutrients input to the main stream.

Rivers and wetlands in Myanmar provide essential services to people in terms of transportation, agriculture, fisheries and a myriad of other ecosystem services, all of which are dependent on a healthy ecosystem. Irrigation channels are also an important part of the infrastructure for daily water use in Myanmar. The objective of this research is to describe the aquatic ecosystem of irrigation channels using aquatic macroinvertebrate communities. The research focused on the taxonomic composition of the aquatic macroinvertebrates of the Zawgyi River and the associated irrigation channels in central Myanmar, east of the city of Mandalay. Significant differences between the river and channels, and among individual channels, were shown using an analysis of similarity: Bray–Curtis similarity, a multivariate equivalent of the univariate statistical method of analysis of variance: ANOSIM and an analysis of similarity percentages: SIMPER by Plymouth Routines in Multivariate Ecological Research: PRIMER v6 software. The initial findings suggest that there is a clear separation between macroinvertebrate communities at the morpho-species level of identification between river and irrigation channels, while there is less separation between functional feeding groups (FFG) between them. The lower taxonomic level of discrimination at the family level using a water quality index showed no significant difference between river and channels. The preliminary field results indicate that a recently modified biomonitoring index method could be applied in Myanmar to assess the ecological water quality of the modified river, as well as human-made channels.

The article considered the ecological index of water quality, which is used for planning water protection activities, developing water protection measures, carrying out ecological and ecological and economic zoning, ecological mapping; water pollution index, which is determined by hydrochemical indicators; modified Horton water quality index models; the Water Quality Index is proposed by the Canadian Council of Ministers of the Environment; the Said index, which is used to assess the quality of water for general use; water quality index in the river subbasin in a certain year; The Nemerov Pollution Index, which is used to comprehensively assess water, precipitation, or soil quality, and the Oregon Water Quality Index. Advantages and disadvantages of water quality and pollution indices are determined.

Development of a submerged aquatic vegetation community index of biotic integrity for use in Lake Ontario coastal wetlands

Various pollutants have had a substantial impact on the quality of water in recent years. The quality of water directly impacts human health and the environment. The water quality index (WQI) is an indicator of effective water management. Water quality modelling and prediction have become essential in the fight against water pollution. The research aims to build an efficient prediction model for river water quality and to categorize the index value according to the water quality standards. The data has been collected from eleven sampling stations located in various locations across the Bhavani River, which flows through Kerala and Tamilnadu. The water quality index is determined by 27different parameters affecting water quality like dissolved oxygen, temperature, pH, alkalinity, hardness, chloride, coliform, etc. Data normalization and feature selection are done to construct the dataset to develop machine learning models. Machine learning algorithms such as linear regression, MLP regressor, support vector regressor and random forest has been employed to build a water quality prediction model. Support vector machines (SVM), naïve bayes, decision trees, MLP classifiers, have been used to develop a classification model for classifying water quality index. The experimental results revealed that the MLP regressor efficiently predicts the water Quality index with root mean squared error as 2.432, MLP classifier classifies the water quality index with 81% accuracy. The developed models show promising output concerning water quality index prediction and classification.

Evaluation of water quality and potential scaling of corrosion in the water supply using water quality and stability indices: A case study of Juja water distribution network, Kenya

Drinking water quality describes the conditions for water to be accepted as suitable for human consumption. Water quality index is characterized by including in the process of assessment, water quality parameters such as physical, chemical and micro-biological. Nowadays, the management of hazardous events has become a big problem for water utilities and leads to the increase of the rate of public health risk. Availability of adequate management strategy in order to maintain good quality water has been always a challenge for water utilities. To provide a solution to the problem, one needs to think of a simple and effective tool that can be used to easily assess the quality of the water. Water Quality Index (WQI) and Water Stability Index (WSI) are known as the most reliable tools for assessing water quality and aggressiveness. This study aims at assessing the water quality and potential scaling and corrosion of the water supply in the Juja water distribution network by using WQI and WSI based on Langelier Saturation Index (LSI). Five sampling locations were selected including the treatment plant outlet and consumption points for physical, chemical and bacteriological water quality analysis and determination of WQI and WSI. It was found that 100% of the collected water samples had Calcium concentrations within the World Health Organization (WHO) and Kenya Bureau of Standards (KEBS) acceptable ranges. Additionally, 100% of the collected water samples had TDS concentrations within the WHO and KEBS acceptable ranges. However, at time, water quality parameters such as Residual Chlorine, E. coli, Alkalinity, and Turbidity were out of the WHO and KEBS standards. pH values ranged from 6.29 to 8.06 and was generally within acceptable limits. The WSI ranged between – 3.04 to – 0.99, indicating that the water is generally corrosive and may pose a risk to water quality and shorten the lifespan of the network facilities. Generally, the water from the Treatment Plant was of good quality, while at consumption points JKUAT Main Gate, JKUAT Campus, High Point, and Juja Stage had fair water quality based on the calculated WQI. There was a slight drop of the water quality associated with the low concentrations of residual chlorine, and the presence of E. coli at all the stations. The water quality therefore deteriorates in the distribution network and is corrosive throughout the system right from the treatment plant based on the WQI and WSI. The water company needs to improve on the treatment process, and relook at management strategies of the network, provide better services to consumers.

Water Quality Index (WQI) is one of the most effective indicators assessing the water quality of the surface water. The Water Quality Index was used to determine the quality of raw water used for drinking purposes at the AL-Abbasia River. The water samples were taken from six stations along AL-Abbasia River for during a twenty - month period started from January to October in (2019) to (2020). fifteen parameters of water quality were evaluated including Temperature (C°), Hydrogen power (pH), Total Hardness (T.H), Turbidity (Turb.), Total Dissolved Solid (T.D.S), Chloride (Cl-), Calcium (Ca+2), Electrical Conductivity (E.C.), Magnesium (Mg+2), Sodium (Na+), Potassium (K+), Sulfate (SO4 -2), Total Suspended Solids (T.S.S), Aluminum (Al). Data analysis revealed that some of these parameters exceeded the World Health Organization (WHO) standards such as Total Hardness (T.H), Total Dissolved Solid (T.D.S), Magnesium (Mg+2) and Sulfate (SO4 -2). Other parameters were within the WHO standards. In this thesis three different methods were used to calculate WQI, the WAWQI, CWQI, and Nemerow’s Pollution Index. For WAWQI, the computed overall WQI value of all samples and stations along AL-Abbasia River was (64.5) which implies that the water was generally "poor". The computed monthly overall WQI along AL-Abbasia River for all samples and stations was (64.114). The monthly WQI variation ranged to a higher value of (78.42) in February 2019, due to high pollutants and heavy rainfall in this month and a lower value of (53.92) in July 2019 along AL-Abbasia River, and classified as (very poor) in terms of drinking water quality. The annual river water quality index variation along AL-Abbasia River ranged between (64.31) " Poor quality" at the upstream near station (A1) and (64.1) "poor" at the downstream near station (A6) which indicates that the ratio is very close between the river upstream and downstream. The water quality assessment was recorded as “poor” because of the high values of Total Hardness (T.H), sulfate and Total Dissolved Solid (T.D.S) where it exceeded the limits. If we excluded (T.H, sulfate and T.D.S) values from water assessment, the result will be changed from (64.5) to (48.86) and the quality of water will be changed from “Poor” to “Good”. According to CWQI, the result calculated by Canadian Water Quality Index method showed that the water quality was fair along the main stream of AL-Abbasia River. The annual average water quality index recorded during the two years was fair in the upstream at station A1 with a value of 74.57 and downstream at station A6 with a value of 61.6. The water quality index during 2019 ranged between fair at A1, A2, and A6 stations and good at A3, A4, and A5 stations with a value ranged between 61.04 at A2 and 82.83 at A3. The water quality index during 2020 year ranged between fair at A1, A2, A3, A4, and A6 stations and marginal at station A5 with values between 77.63 at station A1 and 58.23 at station A5. The Nemerow’s Pollution Index is another method used to calculate WQI. This method gives a statistical analysis to show the state of the river water quality for each parameter and each station along the river. When the value of NPI is greater than 1, then this means that there is a high concentration of this parameter, thus increasing the water pollution. The results obtained from this method indicate that high sulfate, T.H, and turbidity concentrations had a significant impact on water quality during the study period. In 2019, The high NPI was recorded for SO4 and T.H for all stations during the study period, while in 2020, the highest NPI was recorded for T.S.S, SO4, T.H, T.D.S, Mg, and turbidity.