Water Quality Parameters Research Articles

Water Quality Impact on Fish Behavior: A Review From an Aquaculture Perspective

ABSTRACTChanges in water quality significantly shape fish behavior, a crucial index reflecting the growth and welfare status of fish. Given the centrality of this relationship to aquaculture practices, a comprehensive understanding of how water quality dynamics influence fish behavior is imperative. While there have been some summaries of the effects of water quality parameters on fish physiology and growth, few reviews on their effects on fish behavior have been reported yet. This article reviews several water quality parameters which are of great concern in aquaculture from multiple facets of actual production, including physical parameters (water temperature and turbidity), chemical parameters (dissolved oxygen, salinity, pH, and inorganic nitrogen), and chemical pollutants (microplastics and crude oil), which have gained increasing attention from the researchers and aquaculture practitioners over the past decades. Variations in these water quality parameters can exert profound effects on fish physiology, metabolism, internal tissues and organs, and sensory perception, which influences fish behaviors such as swimming, schooling, feeding, predation, anti‐predation, aggression, courtship, as well as adaptive and stress‐related behaviors such as exploration, avoidance response, and anxiety‐like behavior. By synthesizing the behavioral changes caused by specific water quality parameters, this review aims to provide strong support for further water quality‐related research, thereby fostering environments conducive to both fish welfare and aquaculture productivity.

Water quality estimates using machine learning techniques in an experimental watershed

ABSTRACT Estimation of the water quality parameters is important to enhance time and cost-effectiveness to that of the conventional approach. This study is aimed to identify the best machine learning (ML) approach to predict concentrations of biochemical oxygen demand (BOD), nitrate, and phosphate. Four ML techniques including decision tree, random forest, gradient boosting, and XGBoost were compared to estimate the water quality parameters based on biophysical (i.e., population, basin area, river slope, water level, and stream flow) and physicochemical properties (i.e., conductivity, turbidity, pH, temperature, and dissolved oxygen) as input parameters. The data were split into training and test sets, and the model performances were evaluated using coefficient of determination (R2), Nash–Sutcliffe efficiency coefficient (NSE), and root mean squared error (RMSE). The mean squared error (MSE) was used as the optimization target. The robust fivefold cross-validation, along with hyperparameter tuning, achieved R2 values of 0.76, 0.67, and 0.71 for phosphate, nitrate, and BOD, and NSE values of 0.73, 0.67, and 0.66, respectively. XGBoost yielded the lowest RMSE across all parameters, showcasing superior performance when considering all metrics performed. In conclusion, ML techniques, particularly with a robust cross-validation technique and hyperparameter optimization, showed good results in water quality parameter prediction.

Delineation and Mapping of Groundwater Quality Assessment in Salem District, Tamil Nadu, India using GIS Techniques

Groundwater is a crucial natural resource with significant economic importance, supporting industrial activities, irrigation, and drinking water supplies. However, its extensive use for these purposes depletes water tables, which diminishes its future availability and leads to increased salinity, stream depletion, and land subsidence. A study was conducted to evaluate and map groundwater quality across different blocks in Salem district viz., Salem, Gangavalli, Thalaivasal, Attur, Pethanaickenpalayam, Valappady, Ayothiyapattinam, Yercaud, Panamarathupatty, Veerapandi, Edappadi, Sankari, Kadayampatti, Kolathur, Konganapuram, Magudanchavadi, Mecheri, Nangavalli, Omalur, and Tharamangalam. Sampling was conducted in February 2024, during which a total of 200 samples were collected and examined for pH, electrical conductivity, cations like Ca2+, Mg2+, Na+ and K+, anions like CO32-, HCO3-, SO42-, and Cl-. Based on the ionic concentration, the water quality parameters are derived such as Sodium Adsorption Ratio(SAR) and Residual Sodium Carbonate (RSC). The pH and EC values were ranged from 7.08 to 8.58 and 0.74 to 2.75 dS/m, respectively. The residual sodium carbonate (RSC) concentration ranged from -7.3 to 10.1 meq/L, while the sodium adsorption ratio (SAR) ranged from 0.7 to 9.7 meq/L. According to the CSSRI, Karnal Water Quality Classification, approximately 66.5 % of the samples fit into the good quality category, approximately 13% of the samples fit into the alkaline water category, and 20% of the samples fit into the saline water category in the Salem district. Using this classification, thematic maps depicting groundwater quality in the Salem district were generated with ArcGIS software. The study concludes that the majority of the samples are classified as good-quality water, while saline and alkali water emerge as the next major concern. Using this saline water for irrigation can change the soil's physical properties and lower agricultural productivity. Thus, it's crucial to apply soil amendments like gypsum and provide proper drainage to avoid long-term soil damage.

Uncovering the Anthropogenic Influences on Water Quality: A Case of Lake Victoria Shores, Entebbe, Uganda

Lakes serve as vital ecosystems, providing freshwater resources and habitats for diverse species. However, human activities, particularly around lakeshores, have led to significant environmental degradation, including heavy metal contamination. Lake Victoria, the second-largest freshwater lake globally, has been severely impacted by pollution from industrial, agricultural, and urban sources. This research aims at examining the influence of the anthropogenic activities on the water quality of Lake Victoria. Specifically, the study tried to determine the activities undertaken at the Lake shores of Lake Victoria; determined the physico-chemical parameters of the water from the shores and the heavy metal concentration in the water samples obtained from the shores of Lake Victoria. This study utilized a cross-sectional and experimental research designs to assess water quality and anthropogenic influences around Lake Victoria. A total of 150 residents from selected communities were surveyed using a semi-structured questionnaire to gather demographic information, perceptions of water quality and the activities carried out within the shores of Lake Victoria. Water samples were collected from multiple sites along the lake shores for analysis of heavy metals using the Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Water quality parameters were determined In-situ using a multi-parameter water testing kit and Hanna instrument. Results showed that the anthropogenic activities that could have contributed to water degradation include: fishing, transport, agriculture and construction among others. Apart from pH which was outside the permissible limits, all the other water parameters were within the WHO permissible limits. Considering the heavy metal concentration, all the sampled sites apart from one inlet, had the concentrations above the WHO permissible levels an indication of significant heavy metal contamination in the Lake Victoria shores. These findings highlight the urgent need for targeted pollution control measures and regular monitoring to mitigate further environmental degradation. Effective interventions, including stricter regulations and sustainable land use practices within the Victoria shores are essential for safeguarding the lake's ecosystem and the health of surrounding communities.

Machine Learning Based Inversion of Water Quality Parameters in Typical Reach of Rural Wetland by Unmanned Aerial Vehicle Images

Rural wetlands are complex landscapes where rivers, croplands, and villages coexist, making water quality monitoring crucial for the well-being of nearby residents. UAV-based imagery has proven effective in capturing detailed features of water bodies, making it a popular tool for water quality assessments. However, few studies have specifically focused on drone-based water quality monitoring in rural wetlands and their seasonal variations. In this study, Xiangfudang Rural Wetland Park, Jiaxin City, Zhejiang Province, China, was taken as the study area to evaluate water quality parameters, including total nitrogen (TN), total phosphors (TP), chemical oxygen demand (COD), and turbidity degree (TUB). We assessed these parameters across summer and winter seasons using UAV multispectral imagery and field sample data. Four machine learning algorithms were evaluated and compared for the inversion of the water quality parameters, based on the situ sample survey data and UAV multispectral images. The results show that ANN algorithm yielded the best results for estimating TN, COD, and TUB, with validation R2 of 0.78, 0.76, and 0.57, respectively; CatBoost performed best in TP estimation, with validation R2 and RMSE values of 0.72 and 0.05 mg/L. Based on spatial estimation results, the average COD concentration in the water body was 16.05 ± 9.87 mg/L in summer, higher than it was in winter (13.02 ± 8.22 mg/L). Additionally, mean TUB values were 18.39 Nephelometric Turbidity Units (NTU) in summer and 20.03 NTU in winter. This study demonstrates the novelty and effectiveness of using UAV multispectral imagery for water quality monitoring in rural wetlands, providing critical insights into seasonal water quality variations in these areas.

Comparative growth performance of Nile tilapia (Oreochromis niloticus) sex groups intank culture: A hormone-free approach for sustainable aquaculture in Dodoma, Tanzania

Male tilapia are globally preferred in aquaculture for their superior growth and uniform harvest sizes. However, hormonal sex reversal techniques used to produce all-male populations can pose health and environmental risks. This study investigated the growth performance of manually separated monosex males, monosex females, and mixed-sex groups of Nile tilapia in tank culture as a sustainable and hormone-free alternative. Over six weeks, the study measured various morphometric parameters, weight gain, specific growth rates, water quality parameters, and condition factors. The fish were fed isonitrogenous commercial feed, and the feeding regime was adjusted based on their weight. Results revealed that monosex tilapia groups attained higher growth rates than mixed-sex groups, with males achieving an average final weight of 56.5 g, followed by females at 53.3 g, and mixed-sex groups at 43.3 g. Males had higher morphometric values compared to females and mixed-sex groups. The water quality parameters remained optimal across all groups, indicating that sex composition does not impact water management. Monosex females and mixed-sex groups exhibited better condition factors. The study concludes that tilapia farming can be effectively conducted with either mono-sex male or mono-sex female tilapia, as their growth rates do not differ significantly. Further research and development of techniques to ease the separation of sexes and enhance the growth rates of monosex female tilapia are recommended as a viable, hormone-free alternative for sustainable aquaculture.

Water Quality Analysis of a 300 Mvar Large-Scale Dual Internal Water Cooling Synchronous Condenser External Cooling System and Exploration of Optimal Water Treatment Agent Dosage at Different Temperatures

The external cooling water system of a 300 Mvar dual internal water cooling synchronous condenser at a certain ultra-high voltage converter station continued to exhibit significant scaling and corrosion, even with regular addition of scale and corrosion inhibitors. To solve this problem, the external cooling water of the synchronous condenser was sampled and tested periodically, with the main test items including conductivity, pH value, turbidity, hardness, alkalinity, and other water quality parameters directly related to corrosion and scaling. The trends of these parameters over time were also analyzed. The results showed that as the operation time increased, the cooling water became concentrated during multiple circulation cycles, and the various dissolved or suspended substances underwent a certain degree of enrichment. However, the addition of scale and corrosion inhibitors did not dynamically adjust according to the changes in water quality, and there was always an excessive dosage. Thus, using the external cooling water as the experimental sample, static scale inhibition tests and rotating coupon corrosion tests were conducted to evaluate the scale and corrosion inhibition performance of the commercial AS-582 scale and corrosion inhibitor used at this ultra-high voltage converter station under different conditions. Considering the more obvious corrosive tendency of this water sample, the focus was on testing its corrosion inhibition performance. When the dosage was 600 ppm, the scale inhibition effect was optimal, with an inhibition rate of 92.15%. The corrosion inhibition effect of this scale and the corrosion inhibitor were significantly related to water temperature. At 25 °C, when the dosage was 500 ppm, the corrosion inhibition effect was optimal, with an inhibition rate of 86.79%. However, when the temperature increased to 40 °C, the corrosion inhibition effect under each dosage was significantly worse, unable to meet the requirements, and the use of other corrosion inhibitors in combination was necessary. This work will provide a reference for the scientific use of scale and corrosion inhibitors.

Unveiling the potential of parasites as proxy bioindicators for water quality assessment in river Jhelum Kashmir, India.

This study aimed to evaluate the effects of deteriorated physicochemical conditions in the river Jhelum on parasitic infestations and to investigate the potential of fish parasites as bioindicators of water quality. All the physicochemical parameters exhibited statistically significant differences based on both site and season (p < 0.01).The interaction term (Site × Season) was also kept in the model since it was statistically significant (p < 0.01). A parasitological survey of 360 schizothoracine fish revealed a 30.3% prevalence (109/360) of endohelminth infection. The study identified four predominant parasitic taxa across two distinct classes: Cestoda, including Adenoscolex oreini and Schyzocotyle acheilognathi, and Acanthocephala, comprising Pomphorhynchus kashmirensis and Neoechinorhynchus manasbalensis. For the assessment of parasitic load, we calculated the prevalence, mean intensity, mean abundance, and index ofinfection for each sampling period. Correspondence analysis identified associations between parasite occurrence and specific water quality parameters. Regression analysis, including R2 and p values, demonstrated a positive correlation between the number of parasites and both the proportion of infected fish and the ratio of infected to examined fish. Given that parasitic load is significantly influenced by a range of water quality parameters, fish parasites can serve as a robust indicator of declining water quality. Fish parasites are highly sensitive to water quality changes such as pollutants, toxins, and fluctuations in pH, temperature, and oxygen levels. Deteriorating water quality can stress fish, compromising their immune systems and increasing their susceptibility to parasitic infections. Additionally, complex life cycles of parasites can be disrupted by poor water conditions, making them indicators of water quality issues.

Evaluating the potability of domestic water supply sources using water quality index in Kilombero district, Tanzania

ABSTRACT The decline in water quality in various bodies of water has led to significant health risks for individuals relying on these sources for drinking and domestic use. The prevalence of waterborne diseases in some areas is attributed by inadequate water quality assessments of supply sources. This study focused on evaluating the potability of domestic water sources in the Kilombero district of Tanzania, where approximately 70% of the population depends on untreated natural sources. Two models were utilized: the Weighted Arithmetic Water Quality Index (WAWQI) and the Canadian Council of Ministers of Environment Water Quality Index (CCME WQI), analysing 15 water quality parameters. The WAWQI identified three groundwater sources as poor quality for consumption, while indicating seasonal improvements in water quality – from 12 in the wet season to 13 in the dry season. Conversely, the CCME WQI classified all 15 sources as potable, with an increase in ‘Excellent’ ratings from 9 to 13 between seasons. The findings showed that all surface water sources were deemed potable, while 67% of groundwater sources met quality standards. The remaining 33% of boreholes were categorized as having poor quality. Overall, both models indicated better water quality during the dry season, with surface water generally exhibiting higher quality than groundwater.

Retrieve water quality parameters of urban rivers from hyperspectral images through feature interaction based two-stage method fused with spectral unmixing and spatial relatedness

Monitoring water quality through efficient quantification of water quality parameters (WQPs) is of paramount importance to environmental management of urban rivers. Unmanned aerial vehicle (UAV) remote sensing techniques posed a great opportunity for visualizing spatial distributions of WQPs concentrations with higher flexibility and monitoring frequency compared to satellite remote sensing techniques, assisting to trace potential contamination sources and prevent water quality from degradation. However, current methods of water quality monitoring usually involved large masses of water samples as training data to keep calculation accuracy every time their study area changed, increasing financial cost and incurring time delay in monitoring and evaluating water quality. This study proposed a UAV-based two-stage multidirectional fusion with probabilistic matrix factorization (TSMF-PMF) method in unified framework, to effectively quantify WQPs including chemical oxygen demand (COD), biochemical oxygen demand (BOD), and turbidity from UAV hyperspectral images. TSMF-PMF established feature interaction and outlier feedback module, ensuring relatively high calculation stability with less training samples. The experimental results showed that TSMF-PMF achieved good performance on predicting concentrations of WQPs with coefficient of determination (R2) and mean absolute percentage error (MAPE) ranging from 0.82 to 0.91 and from 5.35 % to 10.23 %. This study established theoretical and technical foundation to optimize environmental management scheme of urban rivers and provided an application demonstration.

Assessment of the water quality pollution index and ecological risk of microplastic pollution along the Tambakoso River in Surabaya, Indonesia

Increasing human activities and improper waste disposal will cause microplastic pollution in surface water. This study analyzed the abundance and characteristics of microplastics, pollution index based on water quality and its relationship with microplastic pollution, and the potential ecological risk of microplastics along the Tambakoso River which is influenced by various land uses of housing, industry, agriculture, and ponds from 16 sampling points. The average abundance of microplastics in the river was 91.80 particles/L. The Kruskal Wallis test showed that there were significant differences between microplastic pollution at each sampling location (Pvalue <0.05). In general, microplastics were mostly found in the form of fragments (48.36 %), transparent color (73.81 %), SMP size (<1 mm) (81.6 %), and dominated by PVC and nylon polymers. However, the characteristics of microplastics at each sampling location varied. The water quality pollution index value showed a slightly polluted category at most points. Redundancy analysis (RDA) showed that the characteristics of the shape and color of microplastics correlated with water quality parameters. The potential ecological risk based on microplastic pollution showed minor, moderate, and high categories at points with industrial land use. This indicates that the distribution of microplastics is closely related to human activities in the area. The level of ecological risk from microplastics depends on the percentage of each plastic polymer, along with its abundance in the environment. This study offers an important basis for designing efficient countermeasures to reduce microplastic pollution and improve water quality in surface waters.

The Potential Role of Phytoplankton Functional Groups Under Anthropogenic Stressed Wetlands: Characterizing The Environmental Sensitivity.

Anthropogenic and climatic changes are continuously altering the freshwater plankton, necessitating an evaluation of the complex structure of plankton communities to understand and mitigate these impacts. In this context, the present study focuses on evaluating the structure of plankton communities, specifically Phytoplankton Functional Groups (FGs) for assessing the environmental sensitivity of wetlands under changing scenario. These FGs are defined by shared adaptive features rather than taxonomic traits. Over the period from 2016 to 2018, two ecologically distinct wetlands were examined, analysing their phytoplankton FGs and their relationship with water quality parameters. Ecohydrological data revealed significant seasonal variations (p ≤ 0.05) in key parameters such as water depth, temperature, pH, electrical conductivity, dissolved oxygen, total alkalinity, total hardness, NO3-N, and PO4-P. Notably, there were no significant differences observed among the sampling stations within each wetland. A total of 125 phytoplankton genera/species were classified into 23 FGs in the open wetland and 22 FGs in the closed wetland. Spatial and seasonal analyses of dominant FGs suggested both wetlands were experiencing pollution pressures. This study highlights the powerful role of phytoplankton functional groups (FGs) as bioindicators of wetland health, uncovering pollution pressures. In open wetlands, 15 phytoplankton FGs with 36 key taxa (Indicator Value ≥ 40%) emerged as critical indicators, while in closed wetlands, only 10 FGs with 17 taxa were identified. To assess eutrophication, the occurrence of these indicator species was evaluated using BVSTEP function analysis. The study recommends pollution reduction in catchment areas and restoration of riverine connectivity to enhance FG diversity. Phytoplankton FG methodologies are deemed effective for assessing the environmental sensitivity of wetlands significantly impacted by human activities. This research offers a scientific foundation for the evaluation and restoration of wetland ecosystems.

Wastewater Management as a Part of Solution for Water Resources Problem in Erbil City

In Erbil City, municipal wastewater (MWW) is disposed directly without any treatment processes in the natural environment water body and in some places used for irrigation purposes. Untreated MWW causes problems for the environment, and people's health. Water quantity and quality variation produce complications for water sources in Erbil City, Kurdistan Region-Iraq. There is a lack of performing MWW management fundamentals in the area as well. This research aimed to study the MWW management in Erbil City, presenting water resource difficulties and bringing about suitable solutions for the water resource problems, and also to highlight the risk for the poor Management. MWW Data on Erbil municipal (EMWW) water quality parameters were collected and analyzed for the study period (four months), beginning in October 2022 and ending in March 2023. Twelve EMWW quality parameters were captured and tested in the Laboratory, arranged, and compared with MWW disposal criteria and local standards. The following MWW parameters include pH, electrical conductivity (EC), total dissolved salts (TDS), chloride (CL), total solids (TS), total alkalinity, total acidity, chemical oxygen demand (COD), and colour. The results showed that Erbil's MWW characteristics in terms of temperatures ranged between 11-23 °C and in turn, affected biological species activities. Maximum PH value was 7.7. Total alkalinity found in the range from 140 to 178 mg/l. Chloride concentration results showed for October was 62 mg/l and the maximum value was 80 mg/l in November due to the increment in temperature and evaporation. The range of the COD values of sewage water for five months was 246 -773 mg. Erbil's MWW's moderate to medium strength may be treated and utilized for landscaping, fountains, and irrigation, minimizing the need for fresh water from resources like wells and surface water in the Greater Zab River.

Assessment of Groundwater Quality for Irrigation Suitability in Rajangaon Shenpunji and Surrounding Area, Aurangabad, Maharashtra, India.

The quality of irrigation water available to farmers has a significant impact on crop yield. Hence, it is need to better understand irrigation water quality. The present study mainly emphasizes the assessment of the suitability of 30 water samples from dug wells, bore wells and surface water bodies in Rajangaon Shenpunji and surrounding areas, Aurangabad, Maharashtra, India. The groundwater sample datasets of post-monsoon 2013 season were collected. The water quality parameters, viz. sodium adsorption ratio (SAR), percent sodium (%Na), residual sodium carbonate (RSC), residual sodium bicarbonate (RSBC), Kelly’s ratio (KR), magnesium adsorption ratio (MAR), permeability index (PI) have been calculated. Based on these calculated parameter results, prepared spatial distribution maps in Arc GIS 10.3 software. These parameters were correlated with standard permissible/desirable limits for irrigation use for the prevailing crops. Based on these factors, most of the samples fall into the category of water suitable for irrigation. A few samples that exceeded permissible limits were discovered in various geological and anthropogenic activities near the water samples in the study area. A complete investigation of groundwater quality may be suitable remedial action. Artificial recharge techniques are developed to increase the chemical concentrations in groundwater or suitable crops are working to continue the present water quality.

Analysis of the water quality of the Wiringtasi River, Barru Regency, Indonesia, in relation to fish cultivation

Objective: This research aims to determine the quality of water along the Wiringtasi River, Barru Regency, Indonesia in relation to the development of fish cultivation. Material and method: Sampling was carried out by random sampling by selecting three research locations, namely location 1 is a river location close to rice fields, location 2 is a location close to pond areas and beaches, and location 3 is a location around the mouth of the Wiringtasi River. The data collected is water quality parameter data, which includes temperature, dissolved oxygen, pH, and salinity. The data obtained is then processed and linked to fish cultivation needs. The data was then analyzed using descriptive analysis. Results: The research results show that the water temperature in the Wiringtasi river is in the average range of 29.4–30.4 oC. The average dissolved oxygen at the research location is in the range of 4.31–5.08 ppm. The average value of water pH at the research location is in the range of 6.33-7.17, while the average value of water salinity at the research location is in the range of 12.67-36.83 ppt. Conclusion: All water quality parameters measured in the Wiringtasi River, Barru Regency, Indonesia, are still in accordance with the growth and survival needs of fish.

Spatial Distribution of Water Quality Parameters in a Mineralized Region of Rajasthan

Water quality parameters, anionic concentrations and uranium levels were measured in groundwater samples collected from Rohil, Sikar District, Rajasthan as a part of radiological baseline survey. This region hosts disseminated uranium deposits. The uranium concentration in water samples showed a mean value of 107 ± 141 μg/L and more than 40% samples crossed the AERB limit. The mean conductivity and TDS of samples were 2221 ± 1513 μS/cm and 1583 ± 1085 ppm, respectively. The mean value of fluoride, chloride, nitrate and sulphate were 2.4 ± 1.4 ppm, 414 ± 466 ppm, 33.70 ± 37.2 ppm and 140 ±133 ppm, respectively. Measured parameters in many samples were above the respective limits set by BIS, AERB and WHO. No particular trend was observed for any of the parameters with increasing distance from the proposed site and no correlation was evident in the measured parameters.

Deriving water quality index using site-specific water quality parameter guidelines for real-time water quality stations

ABSTRACT The Newfoundland and Labrador real-time water quality (RTWQ) monitoring program operates a network of surface water monitoring stations, measuring physical water quality parameters in near real time. The network generates vast amounts of data that are too complex for many stakeholders to interpret. While the Canadian Council of Ministers of the Environment water quality index (WQI) has been a valuable tool to simplify and summarize the ambient quality of water, its usage in RTWQ is virtually non-existent. This is largely due to the lack of alignment/congruency between the limited number of parameters from real-time networks and the availability of aquatic water quality guidelines. This paper is the first attempt to outline a method of utilizing real-time water quality data to generate site-specific water quality guidelines using the background concentration method. Using these guidelines, we compute weekly WQI scores for select monitoring stations and examine various influences on the scores, including precipitation. The influence of each parameter on the WQI score is also plotted in the computation of the RTWQ WQI. Comparison is made between the yearly scores of the Canadian Environmental Sustainability Indicators WQI and RTWQ WQI. The paper also discusses the challenges and benefits of using this methodology as well as the sensitivity of WQI scoring at stations with various anthropogenic influences.

Comparative analyses on nitrogen removal microbes and functional genes within anaerobic–anoxic–oxic and deoxidation ditch sewage-treating processes in Wuhan and Xi’an cities, China

IntroductionAnaerobic–anoxic–oxic (A2/O) and deoxidation ditch (DOD) processes are being increasingly preferred owing to their effectiveness in treating various wastes in wastewater treatment plants (WWTPs). Considering seasonal variations is crucial in optimizing treatment processes, ensuring compliance with regulations, and maintaining the overall efficiency and effectiveness of WWTPs. This study aimed to determine the influence of seasonality on nitrogen removing microbes and functional genes within A2/O and DOD processes in the humid Wuhan and semi-arid Xi’an cities, China.MethodsThe physicochemical parameters of water quality were determined, and molecular and bioinformatic analyses of the bacterial community and nitrogen metabolism functional genes in the two different treatment processes of two WWTPs were performed over four seasons.Results and discussionOur analyses revealed a significant difference in all physicochemical parameters across all experimental groups (p &amp;lt; 0.05). At the genus level, the abundance of Dokdonella, one unidentified genus of Nitrospiraceae, Terrimonas, and one unidentified genus of Chloroflexi was the highest in all groups. Generally, warmer seasons exhibited higher biodiversity indices. The A2/O system exhibited higher values in terms of most nitrogen metabolism functional genes than those of the DOD sewage treatment system. In both WWTPs, the abundance of most genes in spring and summer were higher than that of autumn and winter seasons. Taken together, changes in temperature, caused by seasonal changes, may contribute to changes in abundance of nitrogen metabolic functional genes.

A Novel Approach for Ex Situ Water Quality Monitoring Using the Google Earth Engine and Spectral Indices in Chilika Lake, Odisha, India

Chilika Lake, a RAMSAR site, is an environmentally and ecologically pivotal coastal lagoon in India facing significant emerging environmental challenges due to anthropogenic activities and natural processes. Traditional in situ water quality monitoring methods are often labor intensive and time consuming. This study presents a novel approach for ex situ water quality monitoring in Chilika Lake, located on the east coast of India, utilizing Google Earth Engine (GEE) and spectral indices, such as the Normalized Difference Turbidity Index (NDTI), Normalized Difference Chlorophyll Index (NDCI), and total suspended solids (TSS). The methodology involves the integration of multi-temporal satellite imagery and advanced spectral indices to assess key water quality parameters, such as turbidity, chlorophyll-a concentration, and suspended sediments. The NDTI value in Chilika Lake increased from 2019 to 2021, and the Automatic Water Extraction Index (AWEI) method estimated the TSS concentration. The results demonstrate the effectiveness of this approach in providing accurate and comprehensive water quality assessments, which are crucial for the sustainable management of Chilika Lake. Maps and visualization are presented using GIS software. This study can effectively detect floating algal blooms, identify pollution sources, and determine environmental changes over time. Developing intuitive dashboards and visualization tools can help stakeholders engage with data-driven insights, increase community participation in conservation, and identify pollution sources.

Enhancing Aquaculture Productivity through Integrated Farming Systems: A Comparative Study of Fish-Pig and Fish-Duck Systems

Integrated farming systems involving fish-animal are of high relevance in current scenario. Studies like this asses the suitability of such systems in improving the aquaculture productivity and overall benefits to the ecosystem. It plays a crucial role in optimizing the use of small water resources in rural areas to enhance animal production. Given the potential of pig and duck manure as nutrient inputs in fish culture, a grow-out trial was conducted in a 0.1 ha earthen pond located in Elangitampatty, Kezhisenkattupatti, and Asakkattuppatti villages of Kollihills Taluk in Namakkal district, Tamil Nadu. The pond was stocked with four carp species: Catla, Rohu, Mrigal, and Grass carp in a ratio of 40:20:30:10 at a density of 7500 fish per hectare. Three treatments were employed: (1) Control (T0), where fish were fed with commercial feed, (2) Integrated fish-duck farming (T1), and (3) Integrated pig-fish farming (T2). In the control group (T0), fish were fed commercial fish feed (24% crude protein, 4 mm pellet size) at 4% of body weight, while in T1 and T2, fish received 50% of the commercial feed and were supplemented with duck and pig excreta, respectively. After an 8-month grow-out period, fish weights and total production in each group were recorded. Water quality parameters, such as pH, dissolved oxygen, free carbon dioxide, alkalinity, and hardness, were measured using standard methods (APHA, 2019). Results showed that pond fertilization with pig and duck excreta promoted the growth of algae, phytoplankton, and zooplankton, providing a natural food source for the fish. Total fish production was highest in the fish-pig integration system (T2), with a recorded yield of 4960.09 kg. Catla (Catla catla) had the highest individual species yield, with a total harvested weight of 2225.98 kg, followed by Grass carp (Ctenopharyngodon idella) at 1490.37 kg. The final average weight of Grass carp in T0, T1, and T2 was 1047 ± 13.27 g, 1151.10 ± 12.85 g, and 1490.37 ± 13.52 g, respectively. For Catla, the final average weight in T0, T1, and T2 was 910 ± 9.45 g, 960 ± 10.26 g, and 980 ± 12.20 g, respectively. Similarly, Rohu in T0, T1, and T2 weighed 850 ± 7.98 g, 900 ± 11.23 g, and 910 ± 11.16 g, respectively, while Mrigal in T0, T1, and T2 weighed 600 ± 6.04 g, 720 ± 8.50 g, and 730 ± 10.56 g, respectively. The results highlight that the fish-pig system outperformed the fish-duck system in terms of fish productivity, which may be due to the better nutrient composition in pig manure and the genetic potential of the fish species. An economic analysis revealed that the fish-pig integration system generated the highest net income (Rs. 555,353.90) and benefit-cost ratio (2.12), indicating that integrated fish-pig farming is more profitable than both fish-duck farming and the control group without integration.