Seasonal Variation Of Water Quality Research Articles

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 CO2, 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 Bacillariophyta (44.08%) followed by Chlorophyta (17.20%), Euglenozoa (10.97%), Cyanobacteria (12.90%), Charophyta (10.75%) and Miozoa (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. Trachelomonas, Navicula, and Nitzschia were dominant genera during summer; Anagostidinema, Desmodesmus, and Pinnularia were dominant during rainy; and Trachelomonas, Tetradesmus, and Gomphonema 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.

Spatiotemporal variation of water quality in the context of suspended particulate matter in Laguna Mar Chiquita Lake, Argentina using ACOLITE

This study investigates seasonal variations in water quality at Laguna Mar Chiquita Lake, Argentina, by employing remote sensing techniques to analyze Suspended Particulate Matter (SPM) which offers valuable insights into the lake's environmental health. Landsat 8–9 OLI/TIRS data from 2014–2023 was utilized for spectral analysis of water quality, processed using ACOLITE software for accurate quantitative data. Results show SPM concentrations ranging from 0.823 to 44.172 mg/l, with significant seasonal variations. Higher SPM concentrations post-monsoon indicate increased anthropogenic influence, particularly in the northern area. Pollution from tourism and industrial activities is lower pre-monsoon but spikes post-monsoon and during monsoon, suggesting unfavorable conditions. Effective management and continuous monitoring are crucial for maintaining lake quality and ecosystem health.

Seasonal Variations and Assessment of Surface Water Quality Using Water Quality Index (WQI) and Principal Component Analysis (PCA): A Case Study

In recent decades, water pollution has become a major concern, threatening both humans and natural ecosystems. This study aims to analyze seasonal variations in the quality of surface water of the Nador Canal in Morocco, using the water quality index (WQI) and principal component analysis (PCA). Surface water samples from 22 sites along the canal were analyzed for physical, chemical, and heavy metal parameters. The results of the study revealed significant seasonal variations, with water quality decreasing in the summer months, while its quality generally improved in winter. The predominant water type was Na+-Cl− in summer, while it was the mixed Ca2+-Na+-HCO3− water type in winter. WQI values also varied seasonally, with an average of 113.04 in summer and 160.6 in winter, classifying the water as unsuitable for drinking but suitable for irrigation throughout the year. The results of the water quality index are consistent with the results of the principal component analysis of surface water in the Nador Canal, where the results of the principal component analysis showed that there are significant seasonal variations in water quality. In both summer and winter, major ions like magnesium, sodium, and calcium predominantly indicate influences from natural and anthropogenic sources. In winter, heavy metals and nutrients, signaling pollution from industrial and agricultural runoff, become especially prominent. These variations are influenced by rainfall patterns and agricultural runoff, emphasizing the need for adaptive water management practices to maintain crop and soil health. This study provides new insights into the dynamic interplay between seasonal factors and water quality, offering valuable guidance for local water resource management.

Exploring seasonal variability in water quality of Nyabarongo River in Rwanda via water quality indices and DPSIR modelling.

Understanding seasonal variations in water quality is crucial for effective management of freshwater rivers amidst changing environmental conditions. This study employed water quality index (WQI), metal index (MI), and pollution indices (PI) to comprehensively assess water quality and pollution levels in Nyabarongo River of Rwanda. A dynamic driver-pressure-state-impact-response model was used to identify factors influencing quality management. Over 4years (2018-2021), 69 samples were collected on a monthly basis from each of the six monitoring stations across the Nyabarongo River throughout the four different seasons. Maximum WQI values were observed during dry long (52.90), dry short (21.478), long rain (93.66), and short rain (37.4) seasons, classified according to CCME 2001 guidelines. Ion concentrations exceeded WHO standards, with dominant ions being and . Variations in water quality were influenced by factors such as calcium bicarbonate dominance in dry seasons and sodium sulfate dominance in rainy seasons. Evaporation and precipitation processes primarily influenced ionic composition. Metal indices (MI) exhibited wide ranges: long dry (0.2-433.0), short dry (0.1-174.3), long rain (0.1-223.7), and short rain (0.3-252.5). The hazard index values for Cu2+, Mn4+, Zn2+, and Cr3+ were below 1, ranging from 8.89E - 08 to 7.68E - 07 for adults and 2.30E - 07 to 5.02E - 06 for children through oral ingestion, and from 6.68E - 10 to 5.07E - 07 for adults and 6.61E - 09 to 2.54E - 06 for children through dermal contact. With a total carcinogenic risk of less than 1 for both ingestion and dermal contact, indicating no significant health risks yet send strong signals to Governmental management of the Nyabarongo River. Overall water quality was classified as marginal in long dry, poor in short dry, good in long rain, and poor again in short rain seasons.

Assessment of seasonal variations in water quality in the vicinity of Hathaikheda Reservoir, Bhopal, Madhya Pradesh

Assessment of seasonal variations in water quality in the vicinity of Hathaikheda Reservoir, Bhopal, Madhya Pradesh

A Comparative Physical Parameters of Sri Kurmanadha Temple Pond and Sri Maninageswara Temple Pond, Srikakulam District, Andhra Pradesh, India

Data collected on certain physical parameters of Sri Kurmanadha, Srikurmam and Sri Maninageswar, Kallepalli, Temple Ponds, Srikakulam District, Andhra Pradesh from May 2014 to April 2016. The seasonal variations in water quality were recorded on monthly basis for a period of two years and correlation studies were also conducted among different physical parameters of both temple ponds. Water samples were analyzed for Physical Parameters like air temperature (28.250 C, 27.40 C), water temperature (240C, 24.350 C), transparency (32.1cm., 20.35cm.), EC (621μs/cm., 513.5μs/cm.), TSS (27mg/l., 35.5mg/l.) TDS (367mg/l., 298mg/l), pH (7.35, 7.5), DO (6.75mg/l, 6.5mg/l), COD (10.63mg/l, 10.36mg/l), BOD (3.31mg/l., 2.86mg/l.) total alkalinity (132.5mg/l., 128.5mg/l.), total hardness (80mg/l., 87.5mg/l.). Inter relationship between physical parameters (Pearson’s Correlation matrix) was also recorded. In this observation temperature showed strong positive correlation with COD (r=0.91, r=0.88), BOD (r=0.96, r=0.89), and negative correlation with DO (r=-0.84, r=-0.97). EC showed significant positive correlation with TDS (r=0.85, 0.89), and negative correlation with DO (r= -0.82, r=-0..84), TDS showed positive correlation with pH (r=0.77, r=0.72), and total hardness (r=0.81, 0.78), pH showed positive correlation with COD (r=0.77, r=0.84), total alkalinity (r=0.94, r=0.86), total hardness (r=0.81, r=0.84), and negative correlation with DO (r= -0.87, r=-0.77), Dissolved Oxygen showed negative correlation with COD (r= -0.88, r=-0.93), BOD (r= -0.95, r=-0.93). Chemical Oxygen Demand showed positive correlation with BOD (r= 0.92, r=0.91) and total alkalinity (r= 0.75, r=0.79). Biological Oxygen Demand showed positive correlation with total alkalinity (r= 0.74, r=0.63). Total Alkalinity showed positive correlation with total hardness (r= 0.90, r=0.87). These observations could useful in the water quality monitoring and regulation in order to enhance the quality of water with better sustainable management of Sri Kurmanadha, Srikurmam and Srimaninageswar, Kallepalli, Temple Ponds.

Seasonal Variation of Water Quality of Taiping Lake in Eastern China

Lakes and reservoirs are an important sources of drinking water for human life. However, numerous water quality indexes show seasonal fluctuation under different climatic conditions. We conducted a one-year investigation of Taiping Lake in year 2022 to construct relationship between water quality parameters and water quality. High water temperature promotes the growth of algae, and the existence of N species could provide the essential nutrient substance for the growing of algae. Under the irradiation of sunlight, algae will consume carbon dioxide through photosynthesis and release oxygen which can raise oxygen levels in the water. However, the rapid growth of algae could influence the acid-base balance in water through the consumption of carbon dioxide; thus, resulting in the increasing of pH values. These pH changes may pose a threat to drinking water.

Estimation of Non-Optically Active Water Quality Parameters in Zhejiang Province Based on Machine Learning

Water parameter estimation based on remote sensing is one of the common water quality evaluation methods. However, it is difficult to describe the relationship between the reflectance and the concentration of non-optically active substances due to their weak optical characteristics, and machine learning has become a viable solution for this problem. Therefore, based on machine learning methods, this study estimated four non-optically active water quality parameters including the permanganate index (CODMn), dissolved oxygen (DO), total nitrogen (TN), and total phosphorus (TP). Specifically, four machine learning models including Support Vector Machine Regression (SVR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and K-Nearest Neighbor (KNN) were constructed for each parameter and their performances were assessed. The results showed that the optimal models of CODMn, DO, TN, and TP were RF (R2 = 0.52), SVR (R2 = 0.36), XGBoost (R2 = 0.45), and RF (R2 = 0.39), respectively. The seasonal 10 m water quality over the Zhejiang Province was measured using these optimal models based on Sentinel-2 images, and the spatiotemporal distribution was analyzed. The results indicated that the annual mean values of CODMn, DO, TN, and TP in 2022 were 2.3 mg/L, 6.6 mg/L, 1.85 mg/L, and 0.063 mg/L, respectively, and the water quality in the western Zhejiang region was better than that in the northeastern Zhejiang region. The seasonal variations in water quality and possible causes were further discussed with some regions as examples. It was found that DO would decrease and CODMn would increase in summer due to the higher temperature and other factors. The results of this study helped understand the water quality in Zhejiang Province and can also be applied to the integrated management of the water environment. The models constructed in this study can also provide references for related research.

Variaciones fisicoquímicas del agua de una gran presa Hidroeléctrica Mexicana, Región Centro semi-árida

The Zimapan hydropower plant built in 1995 was the first project to take advantage of Mexico's City wastewater for electric power generation. This tropical reservoir receives pollutants that affect water quality from municipal, agricultural, and industrial wastewater through the Tula and San Juan rivers. The study considered the changes in the physicochemical parameters (surface to 20 m depth) for May (wet warm), November (wet cold-after rains), and February (dry cold) in seven dam sites: two lotic, two transitional, and three lentic sites. Mean values ranges were temperature 20.71-24.38 °C, 1.59-7.56 mg/L dissolved oxygen, Secchi disk transparency 2.26-3.98 m, pH 7.12-8.40, electrical conductivity 48-1334 µS/cm, total nitrogen 14.20-30.74 mg/L, total phosphorus 10.45-15.83 mg/L, and dissolved organic carbon 9.11-20.63 mg/L. In November, all the reservoir surface water was hypoxic due to increased dissolved organic carbon by river input. Even though dissolved oxygen has a seasonal variation, this reservoir has a sustainable fishery of tilapia and black bass (~400 tons/y). The dam is meromictic and hypereutrophic, with seasonal water quality variations with no significant spatial variations. Water quality variation observed in this study can be useful to Mexican decision-makers on water and fisheries management, prevent massive fish kills, and be a support guide for commercial and sport fishers.

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.

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.

Analysis of the seasonal water quality variation at the hydraulic junction of a dual-source water distribution system.

The implementation of a dual-source water supply system offers an increased level of reliability in water provision; however, intricate hydraulic dynamics introduce apprehensions regarding water safety at the hydraulic junction. In this study, we gathered data of the water quality at the hydraulic junction of a dual-source water supply system (plant A and plant B, sampling site A10 was near plant A, and sampling site A12 was near plant B) for one year in Suzhou Industrial Park. Our findings indicated that seasonal variations and water temperature exerted significant influence on the composition and formation of disinfection byproducts (DBPs). Notably, during the warmer months spanning from June to September, the concentration of trihalomethanes was the highest at the hydraulic junction, whereas the concentration of residual chloride was the lowest. The analysis on DBPs revealed that more Br-containing precursors in water in plant A resulted in the accumulation of more Br-containing DBPs at A10, whereas the highest concentration of Cl-containing DBPs accumulated at A12. The analysis of the dissolved organic matter (DOM) composition indicated an increase in concentration at A10 and A12 compared with that in plant A and plant B. The highest concentration of humic acids was observed at A10, whereas A12 accumulated the highest concentration of aromatic proteins and microbial metabolites. Owing to the fluctuations in water consumption patterns at the hydraulic junction, the water quality was susceptible to variability, thereby posing an elevated risk. Consequently, extensive efforts are warranted to ensure the maintenance of water safety and quality at this critical interface.

Assessment of seasonal variation of water quality of Agartala City, Tripura through PCA, PcoA approach & Water Quality Index

Assessment of seasonal variation of water quality of Agartala City, Tripura through PCA, PcoA approach & Water Quality Index

Seasonal differences in water quality of highland lakes and its influencing factors: A case study of Dianchi Lake

Abstract Water quality is of great significance to human survival and development. It is of good theoretical value to study seasonal water quality variation and driving factors in plateau lakes. This paper studied the variation of water quality parameters in different seasons and their relationship with land use and climate factors in Dianchi Lake, Yunnan Province from 2001 to 2019. The results show that the factors restricting water environment in different seasons are different, but basically close. The water quality parameters of multiple water quality monitoring stations in different seasons showed a decreasing or insignificant trend. In the rainy season, the temperature and precipitation were positively correlated with most water quality parameters, while the driving effect of climate factors was not significant in the dry season. Different land types have different effects on water quality indexes in different seasons. The water quality score was higher in the rainy season than in the dry season. The scores of water quality stations in the south and middle of Dianchi Lake are higher than those in the north. In this study, the relationship between climate, land, and water quality is established, which provides a way for the research of water quality parameters.

Assessment of the Seasonal Variations of Lakes Water Quality in Bangladesh

The study was conducted to assess the seasonal variations of water quality in Hatirjheel Lake and Dhanmondi Lake during the period from August, 2019 to January, 2020. The water samples were collected monthly during the monsoon and postmonsoon seasons from five sampling stations of both lakes. Comparative analysis revealed that mean pH was near the standard level in both lakes where DO concentration was much lower in Hatirjheel Lake than Dhanmondi Lake which could be due to the direct dumping of nearby residential and commercial waste, and domestic sewages from the city drainage system as well. The BOD concentration in Hairjheel Lake water exceeded the standard in both seasons and there was no significant change over seasons. In contrast, the Dhanmondi Lake water showed relatively lower BOD concentrations in both seasons where mean concentration slightly exceeded the standard in some stations. The EC and TDS contents showed positive relations but exceeded the standard limit throughout seasons in both lakes. The nutrient contents (NO3 -, NO2 - and NH4 +) of Hatirjheel Lake water highly exceeded the standard during the study that tends the lake water prone to eutrophication. The study revealed that the physicochemical parameters and nutrient status of Dhanmondi Lake water were within the standard limit except EC indicating a rich habitat for aquatic organisms and sounds for recreational activities than Hatirjheel Lake which should be monitored throughout the year to maintain the productivity of lake water systems.

Effects of comprehensive landscape patterns on water quality and identification of key metrics thresholds causing its abrupt changes

Comprehensive landscape patterns influence water quality with multiple factors, complex processes, and scale dependence. However, studies identifying landscape thresholds causing abrupt water quality changes and characterizing the contribution of topography to water quality are still limited. Exploring the impact mechanisms of natural geographical and landscape characteristics on spatial and seasonal water quality variations is conducive to watershed water resource protection and ecosystem restoration. Based on water quality monitoring data of Minjiahe River in the typical headwater area of the upstream Dan River in China from 2019 to 2021, we employed redundancy analysis, partial redundancy analysis, and nonparametric change-point analysis to analyze the relationship between stream water quality and multi-spatial scale comprehensive landscape patterns, to obtain the interactive and independent contributions of different landscape categories at multi-spatial scales on water quality, and to find the key landscape threshold leading to abrupt changes in water quality. Results showed that landscape configuration, landscape composition, and topographic factors collectively explain over 89.1% of water quality variation. Most seasonal variations in water quality were primarily caused by landscape configuration. The landscape composition was mainly responsible for the differences in water quality variations among spatial scales. The topographic factors made the least independent contribution and had a potential impact on overall water quality variation. In order to protect the water quality of streams, it is more reasonable to regulate the landscape at different scales. At the sub-catchment scale, interspersion and juxtaposition index (IJI) and landscape shape index (LSI) should be controlled below 82% and 22. At the 100 m riparian scale, farmland, urban land, IJI, and LSI should be controlled below 29%, 6.5%, 92%, and 26, respectively. Our results provide important guidance for optimizing landscape patterns and water conservation in the watershed.

Seawater quality assessment of the marine ecosystem of Punta Galeta in Panama

Seawater quality was described in the Caribbean coast of Panama based on water physicochemical parameters and biological monitoring studies. Samples of water and benthic macroinvertebrates were collected near Punta Galeta, Province of Colón, Panama. The sampling area was sheltered from the action of waves and located between the coral reef and mangroves. Class Polychaeta was themost abundant with 90 % overall presence in Punta Galeta. Taxonomic classes of Bivalvia, Malacostraca and Ophiuroidea only represented 10 % altogether. Overall, seawater quality was suitable for the collected species of macroinvertebrates, even though concentrations of nitrateand phosphate were above the recommended value. Recorded values of temperature, pH and dissolved oxygen indicated that the site is far from reaching hypoxic conditions. Water quality index indicates a good water quality at Punta Galeta. Further studies with more robust and intense sampling programs are required to properly define the seasonal variations of water quality and its link to benthic macroinvertebrates. Similar studies in the Caribbean of Panama are scarce even though they offer valuable information for water resource administrators.

Evaluation of water quality of Mundeswari River in eastern India: a water quality index (WQI) based approach

The Mundeswari River is the western distributary of the Damodar River system in eastern India. The water of this river is extensively used for domestic purposes and agricultural irrigation. This study aimed to evaluate the spatial and temporal water quality variation of the Mundeswari River and assess the water quality status of this river using the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI). Water quality was monitored monthly at four selected sampling stations (M1, M2, M3, and M4) during 2020-2022, considering twelve selected water quality indicators. The obtained water quality data were analysed using different statistical techniques. Water quality at different monitoring stations was appraised through the use of CCME-WQI. The results revealed that the overall water quality of most of the monitoring stations based on CCME-WQI values was “marginal.” The highest WQI value (82.01) was observed at M1, and the lowest WQI (41.24) was recorded at M3. One-way ANOVA indicated a statistically significant difference in WQI values between sampling sites (P <0.05). The water quality of the M3 sampling station was found to be in degraded condition throughout the study period. Cluster analysis from the perspective of WQI values revealed two distinct clusters of the sampling stations. Substantial seasonal variation in water quality was also observed. This river had putrid water quality during the pre-monsoon period, and relatively better water quality was evident after the monsoon. This study revealed that the water of the Mundeswari River is utterly unsafe for human consumption and it requires significant treatments before it can be safely used for domestic purposes like cooking, washing etc.

Seasonal Variation in Water Quality of River Subin in Kumasi

Seasonal Variation in Water Quality of River Subin in Kumasi

Environmental isotopes (δ18O–δ2H, 222Rn) and electrical conductivity in backtracking sources of urban pipe water, monitoring the stability of water quality and estimating pipe water residence time

This study demonstrates the use of environmental tracers (Water isotopes-δ18O–δ2H, Radon-222Rn, and Electrical Conductivity-EC) as complementary tools for backtracking the water source, estimating pipe water residence time, and monitoring the instability of the water quality. Using the capital of Ethiopia, Addis Ababa, as a case study site, we demonstrate that water isotopes (δ18O andδ2H) effectively backtrack the tap water to its source (springs, reservoirs, shallow aquifers, or deep aquifers). 222Rn is shown to be effective for discriminating groundwater-sourced pipe networks from those that are dominated by surface waters. Our reconnaissance survey reveals that 222Rn, a tracer previously not considered to determine the pipe water residence time, can be used effectively to determine pipe water residence time in groundwater-sourced pipe networks. We recommend further research to explore the capability of 222Rn as a robust indicator of the pipe water residence time in an urban piped water network. The tracers reveal that 50% of the city obtains its water from groundwater and that the groundwater-sourced areas of the city show the highest water quality instability. The water quality in groundwater-sourced pipes varies depending on pumping stoppage owing to power interruptions. Surface water-sourced pipe water shows seasonal variations in water quality, with occasional large deviations from the normal trends following flow interruptions.