Water Quality Variables Research Articles

Prediction enhancement for surface water sodium adsorption ratio using limited inputs: Implementation of hybridized stacked ensemble model with feature selection algorithm

The Sodium Adsorption Ratio (SAR) is a widely used variable in water quality research, particularly in agriculture and environmental studies. In many cases, the key variables required for SAR calculation, namely Na+, Mg+2, and Ca+2, are not available. Consequently, the potential to calculate SAR using a limited number of water quality variables becomes critically important. The study implemented the Multilayer Perceptron Neural Network (MLPNN), Support Vector Regression (SVR), and K-Nearest Neighbors (KNN) models at level-0 for prediction purposes, along with the Boruta model for variable selection. A stacked ensemble learning model at level-1 enhanced the prediction accuracy. The discharge and water quality dataset from the Zarrin-Gol River in northern Iran was utilized to implement the modeling procedure. Results obtained from the variable selection process using the Boruta model revealed that using a limited number of water quality variables can effectively predict SAR even without the principal variables. Further investigation of the input combinations for the level-0 models demonstrated that, for the MLPNN, KNN, and SVR models, 4, 3, and 1 input variables, respectively, yielded optimal predictions. Among the level-0 models, the MLPNN model exhibited the highest accuracy, with RMSE = 0.54, MBE = 0.26, MAE = 0.44, R = 0.84, IA = 0.67, and KGE = 0.79. Implementing the stacked ensemble learning model at level-1 significantly improved the SAR prediction compared to the level-0 models. The ensemble-NN model yielded the best performance in estimating SAR within the range of recorded data, with RMSE = 0.53, MBE = 0.29, MAE = 0.41, R = 0.87, IA = 0.70, and KGE = 0.82. Residual analysis further confirmed the superior predictive capability of the level-1 models compared to the level-0 models. The generalized-logistic probability distribution function is used to estimate the extreme values data. The Ensemble-KNN model best predicted extreme values data, with RMSE = 0.69, MBE = −0.61, MAE = 0.61, R = 0.61, IA = 0.26, and KGE = 0.37. The findings underscore the substantial advancements achieved through stacked ensemble methods in enhancing the modeling of SAR across various aspects, including total data, extreme values, and models' residuals.

Bayesian Network Analysis for Shoreline Dynamics, Coastal Water Quality, and Their Related Risks in the Venice Littoral Zone, Italy

The coastal environment is vulnerable to natural hazards and human-induced stressors. The assessment and management of coastal risks have become a challenging task, due to many environmental and socio-economic risk factors together with the complex interactions that might arise through natural and human-induced pressures. This work evaluates the combined effect of climate-related stressors on low-lying coastal areas by applying a multi-risk scenario analysis through a Bayesian Network (BN) approach for the Venice coast. Based on the available open-source and remote sensing data for detecting shoreline changes, the developed BN model was trained and validated with oceanographic variables for the 2015–2019 timeframe, allowing us to understand the dynamics of local-scale shoreline erosion and related water quality parameters. Three “what-if” scenarios were carried out to analyze the relationships between oceanographic boundary conditions, shoreline evolution, and water quality parameters. The results demonstrate that changes in sea surface height and significant wave height may significantly increase the probability of high-erosion and high-accretion states. Moreover, by altering the wave direction, the water quality variables show significant changes in the higher-risk class. The outcome of this study allowed us to identify current and future coastal risk scenarios, supporting local authorities in developing adaptation plans.

Water Quality Prediction of Small-Micro Water Body Based on the Intelligent-Algorithm-Optimized Support Vector Machine Regression Method and Unmanned Aerial Vehicles Multispectral Data

Accurate prediction of spatial variation in water quality in small microwaters remains a challenging task due to the complexity and inherent limitations of the optical properties of small microwaters. In this paper, based on unmanned aerial vehicles (UAV) multispectral images and a small amount of measured water quality data, the performance of seven intelligent algorithm-optimized SVR models in predicting the concentration of chlorophyll (Chla), total phosphorus (TP), ammonia nitrogen (NH3-N), and turbidity (TUB) in small and micro water bodies were compared and analyzed. The results show that the Gray Wolf optimized SVR model (GWO-SVR) has the highest comprehensive performance, with R2 of 0.915, 0.827, 0.838, and 0.800, respectively. In addition, even when dealing with limited training samples and different data in different periods, the GWO-SVR model also shows remarkable stability and portability. Finally, according to the forecast results, the influencing factors of water pollution were discussed. This method has practical significance in improving the intelligence level of small and micro water body monitoring.

Impact of source water quality on total organic carbon and trihalomethane removal efficiency in a water treatment plant: A case study of Upper Awash, Ethiopia.

This study addresses the limited understanding of factors affecting the efficiency of water treatment plants in reducing trihalomethane (THM) formation through total organic carbon (TOC) removal, highlighting significant challenges in improving treatment effectiveness. The aim of this study was to examine the influence of water quality on the efficiency of water treatment plants to remove TOC and reduce THM formation. Linear regression and correlation analyses were conducted to examine the relationship between water quality parameters and THM concentrations. The results showed that there was a negative relationship between turbidity, metals, and TOC concentration with TOC removal efficiency. Positive correlations were found between parameters and the formation of THMs in water. Of these parameters, water temperature was observed to have relatively less influence on THM formation. It was observed that seasonal variations in water quality affect the efficiency of TOC removal and THM content in treated water. THM levels in chlorinated water were found to be within the permissible range of the World Health Organization's drinking water quality guidelines. However, it is still important to maintain continuous monitoring and take measures to reduce THMs. The model demonstrated a strong correlation (R2 = 0.906) between predicted and measured THM values.

Three-dimensional augmentation for hyperspectral image data of water quality: An Integrated approach using machine learning and numerical models

This research introduces a comprehensive methodology to enhance hyperspectral image data (HSD) utility, specifically focusing on the three-dimensional (3-D) augmentation of Chlorophyll-a (Chl-a). This study comprises three significant steps: (1) the augmentation of limited field water quality data in terms of time interval and number of variables using neural network models, (2) the generation of 3-D data using numerical models, and (3) the extension of the hyperspectral image data into 3-D data using machine learning models. In the first phase, Multilayer Perceptron (MLP) models were developed to train water quality interactions and successfully generated high-frequency water quality data by adjusting biased measurements and predicting detailed water quality variables. In the second phase, high-frequency data generated by MLP models were applied to develop two numerical models. These numerical models successfully generated 3-D data, thereby demonstrating the effectiveness of integrating numerical modeling with neural networks. In the final phase, ten machine learning models were trained to generate 3-D Chl-a data from HSD. Notably, the Gaussian Process Regression model exhibited superior performance, effectively estimating 3-D Chl-a data with robust accuracy, as evidenced by an R-square value of 0.99. The findings align with theories of algal bloom dynamics, further validating the effectiveness of the approach. This study demonstrated the successful integrated development for HSD extension using machine learning models, numerical models, and original HSD, highlighting the potential of such integrated methodologies in advancing water quality monitoring and estimation. Notably, the approach leverages readily accessible data, allowing for the swift generation of results and bypassing time-consuming data collection processes. This research marks a significant step towards more robust, comprehensive water quality monitoring and prediction, thereby facilitating better management of aquatic ecosystems.

Factors Influencing the Variation in Phytoplankton Functional Groups in Fuchunjiang Reservoir

To explore the distribution characteristics, blooming risk mechanism and driving factors of phytoplankton community structure in Fuchunjiang Reservoir. The variation characteristics of phytoplankton, zooplankton and physicochemical indicators in Fuchunjiang Reservoir and its upper and lower reaches were investigated in 2020 and 2021. Based on the phytoplankton functional groups, non-metric multidimensional scale analysis, redundancy analysis and other statistical methods, the seasonal succession characteristics and driving factors of phytoplankton functional groups were analyzed. A total of 18 phytoplankton functional groups were identified, in of which 10 were predominant. The composition of phytoplankton functional groups in the Fuchunjiang Reservoir was significant different. Spatially, the upstream were dominated by group C and P while the represent species were Cyclotella and Aulacoseira,reflecting the mixed meso-eutrophic environments. However, group P was the main group in Fuchunjiang reservoir, and the dominance decreased gradually along the stream direction. Meanwhile, in the downstream, MP has an absolute advantage at Qiantang River estuary. It reflected the environmental characteristics of frequent disturbance and high turbidity of tide-sensing rivers. In addition, the predominant functional groups demonstrated strong seasonal variations. The dominant functional groups were diverse in summer and consisted of P+L0+J+M+S1+H1+MP. In addition to group P (Aulacoseira), which was dominant throughout the year, it also included several groups represented by cyanobacteria and chlorophyta, reflecting the environmental characteristics of changeable habitats and vigorous productivity. In autumn, the succession was dominated by H1 group represented by Dolichospermum and the representative function groups were P and H1, reflecting the hydrological background of reduced flow and static flow. In winter, the increase of Cyclotella led to the predominance of group C, which was dominated by P+C, reflecting the changing conditions of weakened water exchange and intensified eutrophication problems. In spring, the dominant functional groups were gradually enriched and were composed of C, D, P, and MP, which also reflected the changing environmental habitat characteristics which caused by increasing rainfall and air temperature. According to the results of the C-R-S growth strategy, the Fuchunjiang Reservoir has been in the R strategy for a long time, which was consistent with the habitat characteristics of Fuchunjiang Reservoir and its upper and lower reaches with high disturbance and low stress. In addition, C strategy and S strategy appeared in some reaches, reflecting the variability of water quality and hydrology. RDA analysis showed that water temperature, discharge, zooplankton biomass, permanganate index, total nitrogen and total phosphorus were significantly correlated with the seasonal succession of phytoplankton functional groups (P < 0.05), and temperature and flow pattern were probably the most critical factors for the succession. Studies have shown that the impact of hydrometeorological processes on phytoplankton in the Fuchunjiang Reservoir is crucial:high temperature and changing discharge during the summer may lead to cyanobacterial blooms in the Fuchunjiang reservoir; To reduce the risk of algal blooms, it is still necessary to increase the control of nitrogen and phosphorus load in rivers, and fully consider the coordination of water conservancy dispatch methods.

Evaluation of Spatiotemporal Variations in Water Quality Along the Chungnam Province Coast and Inner Estuary (West Coast of Korea)

Evaluation of Spatiotemporal Variations in Water Quality Along the Chungnam Province Coast and Inner Estuary (West Coast of Korea)

Variation in macroinvertebrate assemblages and water quality as a test for different levels of ecological impairment across an Ethiopian highland river system

ABSTRACT The Ethiopian highlands is an area under high anthropogenic pressure. Despite being a hotspot for freshwater biodiversity, the ecological status of local rivers is not monitored. Physicochemical and nutrient water quality parameters and macroinvertebrate assemblages were sampled monthly from the Megech River and its tributaries from January to March 2021. Sampling locations were designated as either upstream or downstream of the Gondar City urban area. We tested for temporal (monthly) and spatial (location, river) variation in water quality and spatial (location, river) variation in macroinvertebrate assemblage structure to examine which water quality parameters were most associated with patterns in macroinvertebrate assemblages. Water quality varied significantly between locations and months but not between rivers. Water quality differences were particularly driven by higher nutrient, salinity, dissolved solids, and conductivity levels downstream, and higher pH and dissolved oxygen levels upstream. Despite the more abundant and diverse macroinvertebrate assemblages downstream, biotic index scores generally indicated slightly increased ecological impairment downstream. A clear spatial pattern emerged in macroinvertebrate assemblages between locations; we detected a significant difference between rivers, with pairwise differences between sampling locations, particularly due to high dissimilarity between the upstream and downstream locations of the Angereb, Shinta, and Qeha rivers. BIO-ENV Pearson correlations indicated that variation in macroinvertebrate assemblages were mostly explained by dissolved oxygen, salinity, and nutrient parameters including nitrate, ammonium, and sulphate. Our findings confirm the need for more rigorous monitoring of Ethiopian highland rivers and improved management of nutrient inputs.

Seasonal Variations in Household Water Use, Microbiological Water Quality, and Challenges to the Provision of Adequate Drinking Water: A Case of Peri-urban and Informal Settlements of Hosanna Town, Southern Ethiopia.

Several studies have been conducted on household water use and microbial water quality globally. However, studies that considered seasonal variability of household water use and microbial water quality were limited. Therefore, this study investigated the seasonal variability of household water use, microbiological water quality, and challenges to the provision of adequate water in the peri-urban and informal settlements of Hosanna town, Southern Ethiopia. A longitudinal study was conducted on 288 households. The data was gathered using a pretested structured questionnaire, laboratory-analysis, interviews, storage-container inventories, focus group discussions, key-informant interviews, and an observational checklist. The data was analyzed using stepwise-multiple linear regression, bivariate and multivariable logistic regression, thematic-analysis, t-tests, and non-parametric-tests. Households were visited for 7 consecutive days during the dry and rainy seasons to account for changes in daily and seasonal variation of water use. 440 stored water and 12 source samples were analyzed for E. coli presence during dry and rainy seasons. The prevalence of stored water contamination with E. coli was 43.2% and 34.5% during the dry and rainy seasons, respectively. The per capita water consumption was 19.4 and 20.3 l during the dry and rainy seasons, respectively. Piped water on-premises, small family size, volume, and number of water storage containers were significant predictors of per capita water consumption in both seasons. Piped water off-premises, storing water for more than 3 days, uncovered, and wide-mouthed water storage containers were significantly associated with the presence of E. coli in water in both seasons. Seasonal variability of household water use and microbiological water quality was statistically significant, which is a significant public health concern and needs intervention to enhance water quantity and quality to mitigate the risk of waterborne diseases. Findings also suggest seasonal monitoring of the safety of drinking water to ensure that the water is safe and healthy.

Effect of Water Storage Tank Material on Quality of Water with Storage Period

Quality drinking water is of prime importance for human need. Potable water comes from surface water and groundwater sources and it is acceptable for human consumption. The method of storing water plays a crucial role in maintaining its purity and safety for human consumption. Due to lack of continuous water supply, storage tanks are necessary to store water and storage tank material may affect the quality of potable water. The objective of this study is to investigate the variation in water quality during storage for some particular time period in different types of storage containers. 40 days (six weeks) is considered to determine potable water quality variation during storage in different container materials and materials used for containers are plastic tanks, clay pot and Reinforced Cement Concrete. To find the water quality parameters, samples are to be collected at five days interval. During the period of storage, physical, chemical and biological water quality parameters are to be determined. Parameters obtained from above tests are analyzed to understand the effect of age and container material on the quality of potable water. This analysis is useful to choose the material of storage container to store water for a particular period of time.

Alterations in Immunology in Three Sizes of Black Jaw Tilapia (Sarotherodon melanotheron) Exposed to Dimethoate in the Laboratory

Three different sizes of Black Jaw Tilapia (Sarotherodon melanotheron) were subjected to dimethoate exposure in the laboratory, and changes in their immunology were observed. The fish were treated with the chemical for 15 days at five different concentrations: 0.00 (control), 0.05, 0.10, 0.15, and 0.20 mg/L. The trial involved the assessment of six water quality variables, including temperature, pH, salinity, dissolved oxygen, nitrite, and ammonia. After the experiment, blood samples from the fish were obtained, and standard laboratory procedures were used to look for immunological profiles in them. Based on all the parameters evaluated, the findings indicated that the chemical had a detrimental effect on the organism even at the lower concentration (0.05 mg/L) over the duration of time (15 days). The findings also showed that the values for ammonia and nitrite increased in proportion to the chemical’s concentration. At the same time, the dissolved oxygen levels dropped (P<0.05). While temperature, pH and salinity were all within the same range for every chemical concentration. However, the chemical significantly distorted the immunological profiles of S.melanotheron, with increasing leucocytosis. Following exposure to this chemical, there are substantial decreases (monocytopenia) and significant increases (P<0.05) in the number of each cell type as well as in the number of lymphocytes (lymphocytosis), eosinophils (eosinophilia), and neutrophils (neutropenia). The study showed that the chemical has a dose-dependent effect on the fish’s immune system. Therefore, care should be exercised when applying this chemical in close proximity to an aquatic environment.

Relationship between Water Quality Parameters and Parasite Infestation in Farmed Oreochromis niloticus in Selected Rift Valley Counties, Kenya

Globally, parasitic infections hinder aquaculture productivity and sustainability. Improper water quality parameters reduce fish immunity, make them susceptible to parasites, and enhance parasitic proliferation in culture systems. Subsequently, this study aimed to determine the prevalence and intensity of ecto‐ and endo‐parasite infesting Oreochromis niloticus in varying water quality in aquaculture systems in Kericho, Bomet, and Nakuru counties. A total of 220 Oreochromis niloticus samples were captured from 11 liner ponds, eight earthen ponds, two concrete ponds, and one plastic tank from 22 farms in the three counties. External and internal organs were examined for parasite infestation. Skin scrapings and squash preparation of fish eyes were also examined to reveal the organisms through microscopic examination. A Pearson’s correlation analysis between physicochemical parameters and parasitic prevalence was used to determine the strength and direction of correlation coefficients with significance at 95%. Overall parasitic prevalence infestation was 39.6% (87/220). Ten parasite genera were recovered, with Dactylogyrus species dominating overall at 15.9% (35/220), followed by Trichodina spp. (7.7%; 17/220). Epistylis species had the highest mean intensity of 12.8 ± 35.7 (total number of Epistylis parasites (141)/total of infested fish (11)). Earthen ponds had a significantly higher (36.2%, 29/80) prevalence of Dactylogyrus sp. than liner ponds (3.6%, 4/110) (p < 0.001). Dissolved oxygen levels were 16.9 ± 0.7 mgL−1 in Bomet, 14.9 ± 0.3 mgL−1 in Kericho, and 12.5 ± 0.5 mgL−1 in Nakuru which were above desirable range for fish culture. The electrical conductivity in Bomet was 76 ± 5 µS/cm and Kericho 52 ± 4 µS/cm below the desirable range. Temperature, pH, phosphate, nitrates, and nitrites were within the desirable limit for fish farming. Electrical conductivity and pH had positive correlation of 1 and 0.97, respectively, with the prevalence of Acanthocephalus, Euclinostomum, and Trichodina species. Temperature and nitrate positively correlated between 0.80–0.89 and 0.90–0.99, respectively, with the prevalence of Dactylogyrus, Riboscyphidia, Epistylis, Camallanus, and Paracamallanus species. The study demonstrates that water quality significantly influences parasitic prevalence in aquaculture systems. Therefore, it is crucial for farmers to monitor water quality parameters to mitigate parasitic infestations.

Assessment of drinking water quality based on trace elements concentrations in the semi-arid region, Morocco

Human health and sustainable socio-economic growth are closely linked to water quality. Due to increasingly intense human activity, pollutants, and in particular trace elements, are entering the aquatic system and harming humans. The main objective of this study is to analyse and compare the impact of the trace elements on the water quality of natural springs. The concentrations of ten trace elements in 12 spring water samples collected in 2022 were analyzed using ICP-MS to determine the spatial variability of natural water quality in the Ouislane watershed. Nine major trace elements (boron, cobalt, chromium, copper, manganese, nickel, lead, zinc, and vanadium) were measured using the inductively coupled plasma mass spectrometry (ICP-MS) technique. The average values of these elements followed the descending trend: B > Ni > Cr > Co > Zn > Mn > V > Cu > Pb in spring water samples. Some trace elements measured in certain water samples exceed the upper limits set by Moroccan drinking water quality standards (NM) and the World Health Organization (WHO). From the principal components analysis (PCA), 83% of the variation is explained by the first three main components. B, Co, Cr and Ni have a strongly impact on water quality explain by their strong correlation with CP1 (R2 > 0.70). The calculated water quality index (WQI) values ranged from 61.18 to 95.11, with an average of 78.47. Approximately 17% of the water samples were categorized as excellent quality water (WQI < 50), with the remaining 83% classified as good quality water (50 < WQI < 100). According to the WQI index, all the natural spring waters investigated are deemed suitable for human consumption.

Ensuring microbial water quality for on-site water reuse: Importance of online sensors for reliable operation

A growing number of cities and regions are promoting or mandating on-site treatment and reuse of wastewater, which has resulted in the implementation of several thousand on-site water reuse systems on a global scale. However, there is only limited information on the (microbial) water quality from implemented systems. The focus of this study was on two best-in-class on-site water reuse systems in Bengaluru, India, which typically met the local water quality requirements during monthly compliance testing. This study aimed to (i) assess the microbial quality of the reclaimed water at a high temporal resolution (daily or every 15 min), and (ii) explore whether measurements from commercially available sensors can be used to improve the operation of such systems. The monitoring campaign revealed high variations in microbial water quality, even in these best-in-class systems, rendering the water inadequate for the intended reuse applications (toilet flushing and landscape irrigation). These variations were attributed to two key factors: (1) the low frequency of chlorination, and (2) fluctuations of the chlorine demand of the water, in particular of ammonium concentrations. Such fluctuations are likely inherent to on-site systems, which rely on a low level of process control. The monitoring campaign showed that the microbial water quality was most closely related to oxidation–reduction potential (ORP) and free chlorine sensors. Due to its relatively low cost and low need for maintenance, the ORP emerges as a compelling candidate for automating the chlorination to effectively manage variations in chlorine demand and ensure safe water reuse. Overall, this study underscores the necessity of integrating treatment trains, operation, and monitoring for safe on-site water reuse.

Variáveis ambientais como preditoras da assembleia de peixes em sistemas aquáticos semiáridos

Abstract Aim To understand the distribution of fish species and their use of habitat, a range of environmental variables were evaluated as predictors of fish assemblage composition and richness in tropical semiarid aquatic systems. Methods We surveyed the species composition of fish assemblages in semiarid aquatic systems and established their degree of association with the structure of the aquatic habitat. Sites consisted of stream reaches with surface water flow, isolated temporary pools, and man-made reservoirs. Fish sampling was conducted on four occasions during the wet (April and June 2006) and dry seasons (September and December 2006). The correlation between richness and abundance with the habitat structure was evaluated using stepwise multiple regression. Patterns of variation in fish assemblage composition across sites were evaluated using Nonmetric Multidimensional Scaling, and the Indicator Species Analysis was used to determine which species were significant indicators of sites. To establish multivariate correlations and test the hypothesis of local fish composition being associated with the environmental variables we used a Canonical Correspondence Analysis. Results Morphometric variables, stream reach width, stream length and elevation explained 75.6% of the variation in fish richness. Macrophyte cover and overhanging vegetation added to the predictive power of the model equation, where the final model explained 86.9% of the variation in fish richness. Canonical Correspondence Analysis showed a significant relationship between fish composition data and site morphology (altitude, bank slope and littoral depth). Among the water quality, habitat composition and substrate variables, temperature, sand, and gravel showed higher correlation with the CCA axes. Conclusions These results indicated that fish communities assume different structures and compositions across different habitat types following the environmental heterogeneity in dryland aquatic systems.

Assessing the Seasonal Variability of Water Quality and Heavy Metals Concentration in Sediment, Water, and Fish Muscles of Korotoa River in Bangladesh

Assessing the Seasonal Variability of Water Quality and Heavy Metals Concentration in Sediment, Water, and Fish Muscles of Korotoa River in Bangladesh

Algal Diversity and its Relationship with Seasonal Variation of Water Quality in Gajedi Lake, Rupandehi District, Nepal

The current study focuses on the algal diversity of Gajedi Lake in different seasons in connection to the lake's water quality indicators. Algae and water samples were collected from eight peripheral sites of the lake in summer, rainy, and winter seasons in 2021. The water temperature, conductivity, total dissolved solids, hardness, alkalinity, phosphorus, free CO<sub>2</sub>, and dissolved oxygen were recorded as high during the summer season while water pH was high during the rainy season. Altogether 93 species of algae were reported under 52 genera, 30 families, 7 classes and 6 phyla in this study. The largest phylum was <i>Bacillariophyta </i>(44.08%) followed by <i>Chlorophyta </i>(17.20%), <i>Euglenozoa </i>(10.97%), <i>Cyanobacteria </i>(12.90%), <i>Charophyta</i> (10.75%) and <i>Miozoa </i>(1.07%). The Shannon-Weiner diversity index indicated high abundance during the summer season, with more evenly distributed algal species. More algal species were recorded in the winter season. <i>Trachelomonas, Navicula</i>, and <i>Nitzschia </i>were dominant genera during summer; <i>Anagostidinema, Desmodesmus</i>, and <i>Pinnularia</i> were dominant during rainy; and <i>Trachelomonas, Tetradesmus</i>, and <i>Gomphonema </i>were dominant during winter. The redundancy analysis ordination showed that the algal composition varied along with the seasonal changes in physico-chemical parameters. Temperature, pH, and conductivity were thus identified as significant factors influencing species richness.

Qualidade da água e uso e cobertura do solo na bacia do Ribeirão Ipanema (Bacia do Rio Doce/Brasil): efeitos da urbanização

ABSTRACT We evaluated the water quality conditions and their relationships with the land cover/use throughout the entire Ipanema Stream Watershed (ISW), also considering temporal differences. Thirteen water quality variables were evaluated in fourteen sampling stations located in rural, peri-urban, and urban zones in both dry and rainy seasons from 2015 to 2018. A PCA was performed to detect which variables explain most of the data variability and to detect spatial and/or temporal trends in ISW water quality. The four PCs explained 74% of the data variability, but strong relationships with environmental variables were only observed in the two main components. PC1 was related to nutrients, alkalinity, BOD, electrical conductivity, DO, and pH, while PC2 was related to total suspended solids (TSS) and chlorophyll-a. A spatial pattern related to sampling stations and land uses was observed, but no temporal pattern was identified. Ammoniacal-N and TSS were most important variables (loading values >│0.75│), and showed higher values in urban zone probably due to inadequate sewage discharge. Ipanema Stream did not show a self-purification capacity, and the high TSS concentrations in rural mainstream ask for riparian zone restoration. These management actions for water quality improvement would even contribute to the recovery of Doce River.

Perfil hemato-bioquímico do tambaqui (Colossoma macropomum Cuvier, 1816) comparando diferentes fases de crescimento em cultivo aquapônico

Abstract The aim of this study was to evaluate the haemato-biochemical parameters of tambaqui Colossoma macropomum in different growth phases in an integrated culture with açai Euterpe oleracea. For this, 240 juvenile tambaqui with initial average weight and length of 21.8 ± 7.74 g and 11.28 ± 6.88 cm were cultured in an aquaponic system integrated with açai for 180 days. During the period, 108 healthy tambaquis were sampled and categorized into five distinct growth phases. At each growth phase blood aliquots were collected. The first phase being fish with an average weight of 103.1 ± 5.27 g; second phase with 823.4 ± 42.6 g; third phase with 1087.75 ± 16.38 g; fourth phase with 1402.0 ± 76.6 g and fifth phase with 1815.0±65.1 g. Water quality variables remained within acceptable parameters for both cultures. Erythrocyte was significantly lower in the first and second phase. Haemoglobin was significantly lower in fish in the first phase. Haematocrit remained the same from the second phase onwards. MCV was significantly lower in fish with 1815.0 ± 65.1 g. Plasma glucose levels were significantly lower in the first and second phases. Cholesterol, triglycerides, and total proteins were significantly higher in fish of the fifth phase. AST was significantly lower in fish from the third phase when compared to fish from the first and fifth phases. ALT was significantly higher in fish from the first phase when compared to fish from the third, fourth, and fifth phases. The results are important tools for assessing the health and well-being of tambaqui in future research involving aquaponic cultures.

Oceanographic Analysis for Optimal Lobster Artificial Reef Placement in Prigi Bay, East Java

Oceanographic states are closely related to marine biota’s distribution and breeding patterns, especially in the intertidal zone. This study analyses the water quality variability and their relationship in the water of Prigi Bay. Water quality data was collected in situ using a Water Quality Checker. The statistical analyses were performed by applying PAST software version 4.11. The suitable waters with the best tendency value for the placement of lobster artificial reefs are stations 2 (Karang Gongso) and 4 (Damas). It is not only explained by salinity and turbidity but also by the ORP role, which has the solution potential to transfer electrons from oxidants to reductants, thus affecting the chemical processes. The high potential suitability at 2 locations is due to the concentration of a supportive environment with variability in ORP concentrations, having more potential for electron transfer, which significantly affects the attached benthic life as a pioneer for the reef. Salinity stability is safer from the impact of water mixing from the estuary. Parameter concentrations are more stable according to water temperature standards for coralline algae growth and are affected by turbidity and dissolved oxygen. In addition, other research is needed, such as social factors and fishermen’s activities.