Factors Affecting Water Quality and the Structure of Zooplankton Communities in Wastewater Reservoirs of the Right-Bank Sorbulak Canal System (South-Eastern Kazakhstan)

: This work aims to assess the main factors that determined the variability of environmental and biological variables in wastewater reservoirs of the Right-Bank Sorbulak Canal system (South-Eastern Kazakhstan). We used standard methods for the collection and analysis of data, as well as the principal components analysis (PCA) to assess the relationship between environmental and biological indicators. The average depth of the surveyed reservoirs was 4.1–10.0 m, temperature— 21.7–25.7 ◦ C, pH—9.41–10.00, permanganate index—16.22–19.07 mgO/dm 3 , N-NO 2 —0.03–0.13, N-NO 3 —1.28–3.00, N-NH 4 —0.30–0.53, PO 4 —0.14–0.39, Si—3.69–8.26, Mn—0.03–0.07, Fe—0.34– 0.38 mg/dm 3 . The content of Cd, Co, Pb, Zn, and Cr was low, Cu—0.012–0.036 mg/dm 3 . The water quality is inﬂuenced by the wastewater composition, chemical interactions, morphometric and physical-chemical conditions of the reservoir, pollution of the coastal area, and secondary water pollution. Changes in the species composition and zooplankton abundance reﬂected the instability of external conditions. PCA showed the priority inﬂuence of carbonates, bicarbonates, magnesium, temperature, nutrients, and heavy metals on zooplankton structure. The results obtained demonstrate the indicator signiﬁcance of zooplankton, and the methodological approaches can be used to assess water bodies with the complex pollution located in other regions.


Introduction
The growth of the earth's population causes an annual increase in the volume of wastewater containing a complex set of organic and toxic compounds [1,2]. A significant part of wastewater is discharged into natural water bodies [3], causing considerable damage to biological resources and human health [4]. The growing practice of reusing wastewater in agriculture [5] and drinking water [6] increases environmental and human health risks.
Pollutants entering aquatic ecosystems with wastewater undergo transformation. These processes are determined by a complex of natural and climatic factors (temperature, current, mineralization, pH value) [7], chemical interactions [8], accumulation in bottom sediments [9], and living organisms [10]. Increased total dissolved solids (TDS) and an alkaline environment contribute to the transition of heavy metals into a sparingly soluble inactive form [7], with the reverse effect of temperature [11]. The transformation of pollutants largely depends on the morphometric characteristics of the water body [12]. Shallow water bodies warm up better; they have no or weakly expressed temperature stratification, higher nutrient turnover rate [13], and larger relative areas occupied by macrophytes [14]. The critical nutrient level for lakes to become turbid is higher for smaller lakes [15]. Macrophytes intensively absorb heavy metals [10], but after death, they could be a source of secondary pollution of a water body.
The impact of wastewater on aquatic ecosystems depends both on its origin (industrial, agricultural, livestock, domestic wastewater) and on the composition of biological communities [16,17]. In the lakes of the Kola Peninsula (Karelia, northwest Russia) polluted by industrial effluents, the biomass of phytoplankton and fish was higher, and that of macrozoobenthos was lower than in the reference lake of the same system [18]. In India, zooplankton of sewage-fed fishponds was more diverse but less variable than in natural fishponds [19]. Industrial effluents in three tributaries of the Calcasieu Estuary (Louisiana, USA) had a more significant negative impact on planktonic invertebrates than agricultural effluents [20].
Anthropogenic activities almost entirely subsidize wastewater reservoirs. The continuous influx of pollutants with wastewater causes differences between wastewater reservoirs and natural water bodies, characterized by a seasonal dependence on nutrient supply [21]. Toxic compounds in wastewater distort the natural processes of eutrophication of water bodies associated with organic matter accumulation. Toxicants suppress the primary producers [22] and disrupt the transformation of nutrients. As a result, the composition and structure of biological communities under conditions of toxic pollution do not reflect the level of accumulation of organic matter in the aquatic ecosystem, i.e., its trophic status.
Sorbulak (South-East Kazakhstan) is one of the largest wastewater reservoirs globally. Together with shallow ponds, Sorbulak stores wastewater from the Almaty and Almaty region, with about two million people [23]. The shortage of water resources in the region necessitates the reusing of wastewater, which is associated with risks to human health and natural ecosystems [4,5]. Due to the climatic conditions of South-Eastern Kazakhstan, the water of the Sorbulak system is used in the largest volumes from May to September [23], when the demand for water resources is maximum. It is necessary to constantly monitor water quality in wastewater reservoirs to reduce risks, especially during the six-month growing season. The literature provides information on the chemical composition of water and the structure of zooplankton communities in Sorbulak, less often in ponds, only for one of the summer months of 1985,1998,2000,2001, and 2017 [24][25][26][27]. This study is based on semi-annual data that allow us to assess the formation of the quality of water resources in wastewater reservoirs during the period of their most intensive use. Its purpose is to evaluate the main factors determining the spatial and temporal variability of environmental indicators and the structure of zooplankton communities under conditions of mixed pollution of the Sorbulak reservoir and two wastewater ponds from May to September 2021.

Description of Study Area
Sorbulak is located 50 km northwest of Almaty (South-Eastern Kazakhstan) at 620 m. It was created in 1973 specifically for the discharge of household and industrial wastewater from the city of Almaty and the Almaty region. The wastewater canal, originating at the wastewater treatment plant in Almaty, flows into the southeastern part of Sorbulak ( Figure 1). The depth of the canal does not exceed 0.8-1.0 m. The transparency of the water is to the bottom. The current is weak, and filamentous algae develop in large numbers (Figure 2a,b). Sorbulak has the shape of an irregular triangle, and it is divided into two parts by an island (Figure 1). Its area with maximum filling reaches 58 km 2 , the length of the coastline is 33.5 km, and the water volume is about 1000 million m 3 . The northern part of the reservoir is deep (19.0-25.0 m). The southern and southeastern parts are shallow, with 1.5-5.0 m. Depending on the water level, the average depth reaches 10.0-15.5 m. From the western bay of Sorbulak, part of the water is annually withdrawn for irrigation of fodder crops such as corn and alfalfa. With a decrease in the level, the shallow coastal zone of Sorbulak becomes swampy and covered with a crust of cyanobacteria (Figure 2c,d).
By the end of 1980, the filling of Sorbulak had reached a critical level, and there was a threat of a dam breakthrough. In 1995, an emergency Right-Bank Sorbulak Canal (RSC) was built, through which part of the wastewater, bypassing Sorbulak, can be discharged into shallow ponds (RSC ponds) and further, if it is necessary, to the Ili River. The emergency release of water threatens the Ili River and Balkhash, the largest fishery lake in Kazakhstan. In a chain, the ponds are located east of Sorbulak at 615-618 m. The ponds have a serial number by the distance from the inflowing canal (RSC No. [1][2][3][4][5][6][7][8]. The ponds have an indented coastline ( Figure 1). The largest of them is the penultimate one (RSC 7) and the last one (RSC 8), with an area of 3.5 and 0.4 km 2 , respectively. The water area of the ponds varies significantly as it depends on the volume of incoming effluents. The maximum depths do not exceed 7-8 m, with average depths of 2.7-6.0 m. Water transparency is most often low. The water color is green mainly because of the significant number of planktonic algae, especially in RSC 7 (Figure 2e,f). Sorbulak has the shape of an irregular triangle, and it is divided into two parts by an island (Figure 1). Its area with maximum filling reaches 58 km 2 , the length of the coastline is 33.5 km, and the water volume is about 1000 million m 3 . The northern part of the reservoir is deep (19.0-25.0 m). The southern and southeastern parts are shallow, with 1.5-5.0 m. Depending on the water level, the average depth reaches 10.0-15.5 m. From the western bay of Sorbulak, part of the water is annually withdrawn for irrigation of fodder crops such as corn and alfalfa. With a decrease in the level, the shallow coastal zone of Sorbulak becomes swampy and covered with a crust of cyanobacteria (Figure 2c,d).
By the end of 1980, the filling of Sorbulak had reached a critical level, and there was a threat of a dam breakthrough. In 1995, an emergency Right-Bank Sorbulak Canal (RSC) was built, through which part of the wastewater, bypassing Sorbulak, can be discharged into shallow ponds (RSC ponds) and further, if it is necessary, to the Ili River. The emergency release of water threatens the Ili River and Balkhash, the largest fishery lake in Kazakhstan. In a chain, the ponds are located east of Sorbulak at 615-618 m. The ponds have a serial number by the distance from the inflowing canal (RSC No. [1][2][3][4][5][6][7][8]. The ponds have an indented coastline ( Figure 1). The largest of them is the penultimate one (RSC 7) and the last one (RSC 8), with an area of 3.5 and 0.4 km 2 , respectively. The water area of the ponds varies significantly as it depends on the volume of incoming effluents. The maximum depths do not exceed 7-8 m, with average depths of 2.7-6.0 m. Water transparency is most often low. The water color is green mainly because of the significant number of planktonic algae, especially in RSC 7 (Figure 2e,f). Sorbulak has the shape of an irregular triangle, and it is divided into two parts by an island (Figure 1). Its area with maximum filling reaches 58 km 2 , the length of the coastline is 33.5 km, and the water volume is about 1000 million m 3 . The northern part of the reservoir is deep (19.0-25.0 m). The southern and southeastern parts are shallow, with 1.5-5.0 m. Depending on the water level, the average depth reaches 10.0-15.5 m. From the western bay of Sorbulak, part of the water is annually withdrawn for irrigation of fodder crops such as corn and alfalfa. With a decrease in the level, the shallow coastal zone of Sorbulak becomes swampy and covered with a crust of cyanobacteria (Figure 2c,d).
By the end of 1980, the filling of Sorbulak had reached a critical level, and there was a threat of a dam breakthrough. In 1995, an emergency Right-Bank Sorbulak Canal (RSC) was built, through which part of the wastewater, bypassing Sorbulak, can be discharged into shallow ponds (RSC ponds) and further, if it is necessary, to the Ili River. The emergency release of water threatens the Ili River and Balkhash, the largest fishery lake in Kazakhstan. In a chain, the ponds are located east of Sorbulak at 615-618 m. The ponds have a serial number by the distance from the inflowing canal (RSC No. [1][2][3][4][5][6][7][8]. The ponds have an indented coastline ( Figure 1). The largest of them is the penultimate one (RSC 7) and the last one (RSC 8), with an area of 3.5 and 0.4 km 2 , respectively. The water area of the ponds varies significantly as it depends on the volume of incoming effluents. The maximum depths do not exceed 7-8 m, with average depths of 2.7-6.0 m. Water transparency is most often low. The water color is green mainly because of the significant number of planktonic algae, especially in RSC 7 (Figure 2e  Wastewater treatment discharged into Sorbulak began in 1980. First, mechanical wastewater treatment is carried out, and then the water passes through sand traps. The next stage is biological treatment in special pools, where the air is injected. After biological treatment, the water enters the radial settling tanks and further through the canal Sorbulak and ponds. The main share falls on the sewerage of multi-apartment residential buildings (39.0-53.0%) and public utilities (26.8-30.4%). The share of industrial wastewater varies from 16.3 to 65.8%. Until the beginning of 2000, the leading suppliers of industrial wastewater were motor transport, locomotive depots, machine building, metalworking, printing, food, light, fuel, woodworking, chemical industries, etc. The closure of many industrial enterprises by the 2000s led to a significant decrease in the share of industrial wastewater to the above minimum value. The share of atmospheric precipitation does not exceed 19% (in dry years, it is much less), and groundwater-9% [23]. Pre-treated wastewater contains organic, biogenic, suspended solids, surfactants, metals, phenols, fats, dyes, oil products, cyanides, formaldehyde, etc. [28]. Until 2002, elevated concentrations of cadmium (up to 0.078 mg/dm 3 ), copper (up to 0.024 mg/dm 3 ), lead, and zinc (up to 0.047 mg/dm 3 ) were recorded in water [29]. By 2017, the share of industrial effluents decreased as the content of heavy metals [24].
Although Sorbulak and ponds are fed mainly by wastewater, many birds live on the islands and coastal zones (Figure 3a,b). The concentration of birds in this area is due to several reasons-the location of the reservoirs on the path of bird migration, a general shortage of water resources in the region, a good food supply, and a relatively low disturbance factor. Sorbulak and the entire system of wastewater reservoirs is a crucial ornithological area, and it is included in the list of wetlands of regional importance [30]. Carp species of fish live in the reservoirs, among which Cyprinus carpio Linnaeus reaches the largest number and larger mass than individuals from natural water bodies. Wastewater treatment discharged into Sorbulak began in 1980. First, mechanical wastewater treatment is carried out, and then the water passes through sand traps. The next stage is biological treatment in special pools, where the air is injected. After biological treatment, the water enters the radial settling tanks and further through the canal Sorbulak and ponds. The main share falls on the sewerage of multi-apartment residential buildings (39.0-53.0%) and public utilities (26.8-30.4%). The share of industrial wastewater varies from 16.3 to 65.8%. Until the beginning of 2000, the leading suppliers of industrial wastewater were motor transport, locomotive depots, machine building, metalworking, printing, food, light, fuel, woodworking, chemical industries, etc. The closure of many industrial enterprises by the 2000s led to a significant decrease in the share of industrial wastewater to the above minimum value. The share of atmospheric precipitation does not exceed 19% (in dry years, it is much less), and groundwater-9% [23]. Pre-treated wastewater contains organic, biogenic, suspended solids, surfactants, metals, phenols, fats, dyes, oil products, cyanides, formaldehyde, etc. [28]. Until 2002, elevated concentrations of cadmium (up to 0.078 mg/dm 3 ), copper (up to 0.024 mg/dm 3 ), lead, and zinc (up to 0.047 mg/dm 3 ) were recorded in water [29]. By 2017, the share of industrial effluents decreased as the content of heavy metals [24].
Although Sorbulak and ponds are fed mainly by wastewater, many birds live on the islands and coastal zones (Figure 3a,b). The concentration of birds in this area is due to several reasons-the location of the reservoirs on the path of bird migration, a general shortage of water resources in the region, a good food supply, and a relatively low disturbance factor. Sorbulak and the entire system of wastewater reservoirs is a crucial ornithological area, and it is included in the list of wetlands of regional importance [30]. Carp species of fish live in the reservoirs, among which Cyprinus carpio Linnaeus reaches the largest number and larger mass than individuals from natural water bodies. Due to the high level of toxic pollution of wastewater reservoirs, especially in the first twenty years of their existence, fishing and the use of Sorbulak and ponds water for irrigation (except for irrigation of industrial crops) were officially prohibited. However, there are currently about 70 farms around the Right-Bank Sorbulak Canal system, and wastewater is used to irrigate fodder crops (corn, alfalfa). Domestic animals (horses, cows, and sheep) from the same farmers use water for drinking ( Figure 3c). The meat of these animals and fish is sold in large quantities in Almaty, while the content of heavy metals in the liver and muscle tissue of the fish reaches a high level [24]. The authors link pathological changes in the internal organs of fish with exposure to toxic substances.

Field Sampling
Material sampling was carried out in Sorbulak and two ponds (RSC 7 and RSC 8) once a month from April to September 2021 using a grid of 15 stations (Figure 2, black Due to the high level of toxic pollution of wastewater reservoirs, especially in the first twenty years of their existence, fishing and the use of Sorbulak and ponds water for irrigation (except for irrigation of industrial crops) were officially prohibited. However, there are currently about 70 farms around the Right-Bank Sorbulak Canal system, and wastewater is used to irrigate fodder crops (corn, alfalfa). Domestic animals (horses, cows, and sheep) from the same farmers use water for drinking ( Figure 3c). The meat of these animals and fish is sold in large quantities in Almaty, while the content of heavy metals in the liver and muscle tissue of the fish reaches a high level [24]. The authors link pathological changes in the internal organs of fish with exposure to toxic substances.

Field Sampling
Material sampling was carried out in Sorbulak and two ponds (RSC 7 and RSC 8) once a month from April to September 2021 using a grid of 15 stations (Figure 2, black circles). In June, additional samples were taken in the wastewater canal, 6 km upstream of its confluence with Sorbulak. The pH and water temperature were measured using an AMTAST portable waterproof Pen pH meter. Water transparency was determined using a Secchi disk with a diameter of 30 cm. At each station, water samples were taken to analyze the chemical composition (Ca, Mg, Na + K, Cl, SO 4 , CO 3 , HCO 3 ), total dissolved solids (TDS), the content of nitrite-nitrogen (N-NO 2 ), nitrate-nitrogen (N-NO 3 ), ammonium nitrogen (N-NH 4 ), phosphates (PO 4 ), total iron (Fe), silicon (Si), manganese (Mn), oxygen, readily oxidizable organic substances (PI permanganate index), cadmium (Cd), lead (Pb), Zn (zinc), copper (Cu), chromium (Cr), cobalt (Co), as well as zooplankton samples. At depths of less than 5 m, hydrochemical samples were taken from the surface horizon. At depths of more than 5 m, samples were taken using a bathometer with a volume of 1 dm 3 at different horizons (at least three horizons). Water was poured into a container, mixed, and one integral sample was taken. Samples for TDS were taken in plastic containers with a volume of 1 dm 3 , heavy metals-0.5 dm 3 (conservation with concentrated chemically pure nitric acid), nutrients-in glass containers with a volume of 0.5 dm 3 (conservation with 1 cm 3 of chloroform), readily oxidizable organic substances (permanganate index PI)-in glass containers with a volume of 0.25 dm 3 (conservation with sulfuric acid), oxygen-in oxygen bottles with a ground stopper with a volume of 0.25 dm 3 (conservation with a solution of Mn chloride in an alkaline medium). Water samples were delivered to the laboratory for further analysis within 24 h. Zooplankton samples were collected using a small Juday plankton net (top length 12 cm, bottom length 45 cm, input diameter 12 cm, mesh size 64 µm) by pulling it from the bottom to the surface [31]. Samples were fixed with a 4% formaldehyde solution. A total of 84 water samples were taken for each type of analysis.

Laboratory Analysis
Conventional methods of chemical analysis of water samples were used [32]. The content of N-NO 2 , N-NO 3 , N-NH 4 , PO 4 , Si, Mn, and Fe was determined photometrically. We used Griess and Nessler reagents, metallic cadmium, and ammonium molybdate in combination with ascorbic and sulfosalicylic acids depending on the analysis. The content of readily oxidizable organic substances (PI) was determined under acidic conditions by Kubel's method. The total hardness of water was determined by the volumetric complexometric method with the eriochrome black indicator. The error in determining the main ions in water was 0.5-5.0%, depending on the analysis. Heavy metals were determined by inductively coupled plasma mass spectrometry using a plasma quadrupole mass spectrometer ELAN-9000, Waltham, Massachusetts, USA (ST RK ISO 17294-1-2011) in the low-background measurement laboratory, Institute of Nuclear Physics (Almaty). The detection limits for heavy metals are (in mg/dm 3 ): for Cd-0.00006, for Co-0.00007, for Cr-0.0004, for Cu-0.0005, for Pb-0.00005, for Zn-0.001.
Species identification of planktonic invertebrates was carried out using keys [33][34][35]. The abundance of organisms was calculated according to [31]. At the beginning, a sample was brought to a certain volume (150-500 cm 3 ). After thorough mixing, three sub-samples were taken from the sample using a 1 cm 3 stamp pipette. In this sub-sample, all encountered individuals and age stages of certain species (the most numerous) were counted in Bogorov's cell. Then the sample was concentrated to a volume of 125-150 cm 3 . Three sub-samples were retaken from it, where less abundant age stages or species were counted. The whole procedure was repeated once more while the sample was concentrated to a volume of 50 cm 3 . In the end, with its volume of 20-25 cm 3 , the sample was viewed in its entirety for counting large and rare species of planktonic invertebrates. The results of counting individuals are recalculated per 1 m 3 using the formula (separately for each sample dilution): where N-abundance (ind./m 3 ), n-number of individuals in a portion, V1-dilution volume (cm 3 ), V2-subsample volume (cm 3 ), and V3-filtered water volume (m 3 ). The filtered volume of water was calculated by the formula: where r is the radius of the inner ring of the Juday net, h is the length of the net pulling (water column height), m. Males, females, copepodites, and nauplii of Copepoda as well as cladoceran's females, females with eggs, males (if they were present), and juveniles were counted separately. The total abundance was found for each species of planktonic invertebrates; for each crustacean species, the total abundance was calculated by summing the abundance of individual age and size stages. The total abundance of zooplankton was determined by summing up the abundance of all species found in the sample. The mass of individuals/species was determined by the formulas of the dependence between mass and body length to calculate the biomass [36].
The average number of species per sample, Shannon Ab (bit/ind), Shannon Bi (bit/mg) [37], and average individual mass (mg) [38] were determined to characterize the zooplankton communities. Calculating the Shannon Ab leads to underestimating large species with low abundance. Shannon Bi considers the contribution of large species but underestimates the role of small species. Therefore, it is recommended to use both versions of the Shannon index to describe the structure of biological communities [39].
The calculation of the Shannon index based on log 2 was performed in the Primer 5 Software. The average mass of an individual in zooplankton communities was calculated by dividing the total biomass by the total abundance.

Statistical Analysis
Statistical analysis of the data was performed using the Statistica 12 and R programs. For all variables, mean values with the standard error were calculated. For the analysis, 27 environmental variables were used (depth, temperature, transparency, water pH, TDS, hardness, content of Ca, Mg, Na + K, Cl, SO 4 , CO 3 , HCO 3 , N-NO 2 , N-NO 3 , N-NH 4 , PO 4 , Fe, Si, Mn, PI, Cd, Pb, Zn, Cu, Cr, Co) and 12 biological variables (abundance and biomass of rotifers, cladocerans and copepods, total abundance and biomass, species number, Shannon Ab and Shannon Bi, the average mass of an individual). We checked the type of data distribution according to Kolmogorov -Smirnov and Lilliefors and Shapiro-Wilk's test [40] in Statistica 12 Software. After a statistical estimation of distribution, the data were transformed by taking their logarithm (if the distribution is shifted to the right) or taking the cube root (if the distribution is shifted to the left). Re-checking the transformed data showed their complete or almost complete compliance with the normal distribution, provided that the data were separated by water bodies.
Graphs of the seasonal dynamics of variables were built using the ggplot 2 package [41]. Principal component analysis (PCA) was carried out in the R program to reduce the data dimension with minimal loss of information [42]. The data were standardized using the scale.unit = TRUE function. The PCA results provided in the factoextra R package (FactoMineR library) were extracted and visualized. Eigenvalues were calculated using the fviz_eig () function to determine the contribution of each variable to the total variance of the principal components. The contribution of variables to the principal components PC1 (Dim.1) and PC2 (Dim.2) was estimated using the head(var$contrib) function. A correlation circle was built, and the quality of representation of variables was calculated using the head(var$cos2) function to visualize and evaluate correlations between variables. Their location within the correlation circle allows assessing the relationship between the variables. Positively correlated variables are located in the same quadrant. Variables with a negative correlation are located in opposite quadrants. A high cos2 indicates a good representation of the variable in the main component. In this case, the variable is located close to the circumference of the correlation circle and is colored red. A low cos2 indicates that the variable is not fully represented in the main component and is close to the center of the circle. To assess the factors influencing the zooplankton communities' structure, we considered the correlation of environmental variables and their contribution to the total variance and chose 17 environmental variables (TDS, Ca, SO 4 , Mg, HCO 3 , Hardness, pH, transparency, temperature, PO 4 , N-NO 2 , Zn, Pb, CO 3 , N-NO 3 , Si).

Hydrological Characteristic
From spring to autumn 2021, the coastline of Sorbulak receded by about 180-200 m (Figure 3c,d) and 10-30 m in ponds. The decrease in the water level was associated with a reduction in the volume of incoming wastewater from spring to autumn, which could be judged by the depth of the canal (visual observations). In addition to a decrease in inflow, the shallowing of Sorbulak occurred due to the withdrawal of water for irrigation.

Hydrophysical Characteristics
The average depth of Sorbulak is about twice that of ponds ( Table 1). The highest water transparency was recorded in RSC 7, and the lowest in RSC 8. All wastewater reservoirs are warm water, with a higher water temperature in the ponds. The water had an alkaline reaction, with the maximum pH values in the ponds. In the wastewater canal, the water temperature in summer reached 28.0 • C, at a pH of 9.8. Vertical stratification of water temperature and pH was recorded only in the northern bay of Sorbulak, with depths of more than 15-25 m. The average temperature of the bottom layers of water was 4.5-8.0 • C lower than on the surface. The difference in pH was 0.17-1.13. At depths of 6.0-10.0 m, the differences in these variables reached 0.2-3.3 • C and 0.04-0.31 • C, respectively. In shallow ponds, the temperature and pH of the water at the surface and the bottom practically did not differ.
Bottom sediments are black and gray silts, clay, in ponds with many detritus, in the deep part of Sorbulak with the smell of hydrogen sulfide. The thickness of the nearbottom hydrogen sulfide layer was 5-7 m. At the end of summer and autumn, the smell of hydrogen sulfide was also recorded in the near-bottom layers of some shallow areas of the water area (eastern bay).
The coastal zone of Sorbulak, especially the shallowest southern and western parts, is overgrown with comb pondweed Stuckenia pectinata L. With a seasonal decrease in water level, the area occupied by pondweed increased three to four times. There is no pondweed in the ponds. Along the banks of the canal connecting ponds No. 7 and 8, the common reed Phragmites australis (Cav.) Trin grows. ex Steud.

Hydrochemical and Toxicological Variables
In June 2021, the water in the wastewater canal had the following characteristics. TDS was equal to 557.6 mg/dm 3  The water in the ponds is slightly mineralized ( Table 1). In Sorbulak, the average value of TDS is more than twice as high as in the ponds and the canal. According to its chemical composition, the water belonged to the chloride class, the sodium group of the second type (Cl Na II ). Sulfates (S Na II ) prevail in Sorbulak only in April. Sorbulak water is of medium hardness, and it is soft in ponds. The oxygen content in the surface layers was at a high level. The highest average content of N-NO 2 , N-NO 3 , PO 4 , and Si was found in RSC 7, N-NH 4 -in RSC 8, and PI-in Sorbulak. The average Mn and Fe content in the ponds and Sorbulak did not differ significantly. The content of Zn, Cr, and Pb was at a low level, Cd, and in some cases Co below the detection limit. The Cu content was generally elevated, with a maximum in RSC 8.

Dynamics during the Six Warm Months
In Sorbulak, the temperature of surface water layers increased from 15. The seasonal dynamics of nitrogen and phosphorus compounds in Sorbulak and RSC 7 did not follow clear patterns, with a weakly expressed trend of decreasing from April to September (Figure 4). In RSC 8, the maximum N-NO 2 , N-NO 3 , and PO 4 were recorded in June, and N-NH 4 -in July. In Sorbulak, the highest amount of Cu was detected in June, in ponds in August. In August, an increased amount of Cr was registered in Sorbulak.
June, and N-NH4-in July. In Sorbulak, the highest amount of Cu was detected in June, in ponds in August. In August, an increased amount of Cr was registered in Sorbulak. According to the correlation coefficient values, changes in temperature, TDS, PI, N NO2, and partially PO4 were synchronous in all reservoirs ( Table 2). In Sorbulak, the sea sonal dynamics of N-NH4 and Cu were antiphase relative to the ponds. Most of the envi ronmental variables, except for N-NO3, N-NH4, and pH, changed synchronously in ponds

Spatial Distribution
We performed a principal component analysis (PCA) to assess the spatial distribu tion of environmental variables and their relationship with each other. The analysis wa According to the correlation coefficient values, changes in temperature, TDS, PI, N-NO 2 , and partially PO 4 were synchronous in all reservoirs (Table 2). In Sorbulak, the seasonal dynamics of N-NH 4 and Cu were antiphase relative to the ponds. Most of the environmental variables, except for N-NO 3 , N-NH 4 , and pH, changed synchronously in ponds.

Spatial Distribution
We performed a principal component analysis (PCA) to assess the spatial distribution of environmental variables and their relationship with each other. The analysis was performed on 82 individuals, described by 27 variables. According to the eigenvalues, the first two principal components accounted for 47.2% of the total variance; ten variables accounted for 88.7% of the total variance. According to cos2, TDS, SO 4 , Na + K, Hardness, Cl, Si, Mg, pH, Cu, Mn, and HCO 3 made the main contribution to the variability of the first principal component (orange and red colors) (Figure 5a). Temperature, Ca, PO 4 , N-NO 2 , CO 3 , Fe, Mg, and Pb were best represented in the second principal component.  (Figure 5a). Temperature, Ca, PO4, N NO2, CO3, Fe, Mg, and Pb were best represented in the second principal component. The biplot (Figure 5b) demonstrates that the environmental variables formed three clusters according to each wastewater reservoir. The geometric centers of the clusters (the most prominent circles of the corresponding color) did not coincide, which indicated the differences in environmental conditions in each of the wastewater reservoirs. The mos clearly identified environmental variables related to Sorbulak. They characterized mainly the chemical composition of water (bicarbonates, sulfates, chlorides, alkali and alkaline earth metals, hardness, TDS). The same quadrant contained PI, depth, and transparency The second and third clusters overlapped and pooled wastewater ponds variables. They were grouped in opposite quadrants, indicating a negative correlation with the variables of the first cluster. Environmental conditions in RSC 7 were characterized by increased Fe Zn, N-NH4, and N-NO3, and in RSC 8 by increased pH, Si, Cu, and Mn.

Species Composition
As part of zooplankton communities, 80 species were recorded, including 53 rotifers 16 cladocerans, 9 copepods, and 2 facultative inhabitants (Table 3).  The biplot (Figure 5b) demonstrates that the environmental variables formed three clusters according to each wastewater reservoir. The geometric centers of the clusters (the most prominent circles of the corresponding color) did not coincide, which indicated the differences in environmental conditions in each of the wastewater reservoirs. The most clearly identified environmental variables related to Sorbulak. They characterized mainly the chemical composition of water (bicarbonates, sulfates, chlorides, alkali and alkaline earth metals, hardness, TDS). The same quadrant contained PI, depth, and transparency. The second and third clusters overlapped and pooled wastewater ponds variables. They were grouped in opposite quadrants, indicating a negative correlation with the variables of the first cluster. Environmental conditions in RSC 7 were characterized by increased Fe, Zn, N-NH 4 , and N-NO 3 , and in RSC 8 by increased pH, Si, Cu, and Mn.

Quantitative Variables
The highest average zooplankton abundance was recorded in RSC 8, with the lowes value in RSC 7 ( Table 4). The average biomass of zooplankton did not differ in water bod ies. In Sorbulak, copepods dominated zooplankton abundance. Rotifers and Cladocera subdominated. Cladocerans dominated zooplankton biomass. The main part of the quan titative variables of zooplankton in RSC 7 was formed by cladocerans, and in RSC 8 by copepods.

Structural Variables
The zooplankton of RSC 8 was characterized by the highest species richness, high values of the Shannon index, and minimal values of the average individual mass (Table  4). Larger planktonic invertebrates dominated zooplankton in RSC 7, but their numbe was minimal relative to other ponds. In terms of species richness of planktonic inverte brates, Sorbulak occupied an intermediate position; Shannon index values were compa rable to those of RSC 8.

Dynamics during the Six Warm Months
The dynamics of the quantitative variables of zooplankton in all of the wastewate reservoirs have their features (Figures 7 and 8). In Sorbulak, after a high abundance o planktonic invertebrates in April, a decline followed in May and June, followed by a rise in July and a further decrease in September. In RSC 7, the quantitative variables of zoo plankton gradually increased from May to September. RSC 8 has two zooplankton abun dance peaks (May and September) and one biomass peak (June). Pearson's correlation coefficients in seasonal variability of biological variables between wastewater reservoir were not statistically significant.

Quantitative Variables
The highest average zooplankton abundance was recorded in RSC 8, with the lowest value in RSC 7 ( Table 4). The average biomass of zooplankton did not differ in water bodies. In Sorbulak, copepods dominated zooplankton abundance. Rotifers and Cladocera subdominated. Cladocerans dominated zooplankton biomass. The main part of the quantitative variables of zooplankton in RSC 7 was formed by cladocerans, and in RSC 8 by copepods.

Structural Variables
The zooplankton of RSC 8 was characterized by the highest species richness, high values of the Shannon index, and minimal values of the average individual mass (Table 4). Larger planktonic invertebrates dominated zooplankton in RSC 7, but their number was minimal relative to other ponds. In terms of species richness of planktonic invertebrates, Sorbulak occupied an intermediate position; Shannon index values were comparable to those of RSC 8.

Dynamics during the Six Warm Months
The dynamics of the quantitative variables of zooplankton in all of the wastewater reservoirs have their features (Figures 7 and 8). In Sorbulak, after a high abundance of planktonic invertebrates in April, a decline followed in May and June, followed by a rise in July and a further decrease in September. In RSC 7, the quantitative variables of zooplankton gradually increased from May to September. RSC 8 has two zooplankton abundance peaks (May and September) and one biomass peak (June). Pearson's correlation coefficients in seasonal variability of biological variables between wastewater reservoirs were not statistically significant.

Dominant Species
In Sorbulak, the rotifer Synchaeta kitina dominated in April, and Filinia major and Keratella quadrata in May. In the following months, dominance shifted to crustaceans, with a seasonal species change. In April and May, Daphnia (Daphnia) galeata formed the basis of quantitative variables; in June, D. (Ctenodaphnia) magna; in July, August, and September, Diaphanosoma mongolianum and D. (Daphnia) pulex (in July together with Bosmina longirostris). Among copepods from April to June, Acanthocyclops robustus and Cyclops vicinus dominated, from July to September A. robustus.
In the zooplankton of RSC 7, rotifers played a significant role in August (Hexarthra mira) and September (Keratella quadrata). Cladocerans Daphnia (Ctenodaphnia) magna and D. (Daphnia) pulex dominated zooplankton in May and June. In the following months, only

Dominant Species
In Sorbulak, the rotifer Synchaeta kitina dominated in April, and Filinia major and Keratella quadrata in May. In the following months, dominance shifted to crustaceans, with a seasonal species change. In April and May, Daphnia (Daphnia) galeata formed the basis of quantitative variables; in June, D. (Ctenodaphnia) magna; in July, August, and September, Diaphanosoma mongolianum and D. (Daphnia) pulex (in July together with Bosmina longirostris). Among copepods from April to June, Acanthocyclops robustus and Cyclops vicinus dominated, from July to September A. robustus.
In the zooplankton of RSC 7, rotifers played a significant role in August (Hexarthra mira) and September (Keratella quadrata). Cladocerans Daphnia (Ctenodaphnia) magna and D.
(Daphnia) pulex dominated zooplankton in May and June. In the following months, only the last species remained, in July and September, together with Chydorus sphaericus. Cyclops vicinus dominated among copepods in spring, and A.robustus dominated in subsequent months.
In the zooplankton of RSC 8, the set of dominant rotifer species was the most unstable. In April, it included Filinia major and F. terminalis; in May, Keratella quadrata; in July, Asplanchna brightwelli; in August, Brachionus forficula; in September, B. forficula and Asplanchna girodi. Cladocerans B. longirostris and Diaphanosoma cf. dubium played a notable role only in June and July. In months, there was also a change in the composition of the dominant species among the copepods. From April to May, the proportion of cyclops C. vicinus decreased. In May, the abundance of heat-loving A. robustus increased, and it retained its Pbing position in the community in the summer months. In July and August, the composition of the dominant species was replenished with diaptomus Sinodiaptomus sarsi, with cyclops Thermocyclops vermifer in August and September.
3.6. Impact of Environmental Variables on Zooplankton 3.6.1. Sorbulak Biplot PCA demonstrates the relationship between environmental and biological indicators and the season (Figure 9a,b). The first cluster combined April, the second-May and June, and the third-July, August, and September. April was characterized by the highest content of Ca, HCO 3 , PO 4 , Pb, Zn, high abundance of rotifers and copepods. In May and June, the lowest abundance of all groups of planktonic invertebrates, an increased amount of N-NO 2 , and a lower content of Ca and HCO 3 compared to April were recorded. The characteristic features of the months combined into the third cluster (July, August, September) were high values of TDS, Mg, hardness, transparency, temperature, and a high abundance of cladocerans.
the last species remained, in July and September, together with Chydorus sphaericus. Cyclops vicinus dominated among copepods in spring, and A.robustus dominated in subsequent months.
In the zooplankton of RSC 8, the set of dominant rotifer species was the most unstable. In April, it included Filinia major and F. terminalis; in May, Keratella quadrata; in July, Asplanchna brightwelli; in August, Brachionus forficula; in September, B. forficula and Asplanchna girodi. Cladocerans B. longirostris and Diaphanosoma cf. dubium played a notable role only in June and July. In months, there was also a change in the composition of the dominant species among the copepods. From April to May, the proportion of cyclops C. vicinus decreased. In May, the abundance of heat-loving A. robustus increased, and it retained its Pbing position in the community in the summer months. In July and August, the composition of the dominant species was replenished with diaptomus Sinodiaptomus sarsi, with cyclops Thermocyclops vermifer in August and September.

Sorbulak
Biplot PCA demonstrates the relationship between environmental and biological indicators and the season (Figure 9a,b). The first cluster combined April, the second-May and June, and the third-July, August, and September. April was characterized by the highest content of Ca, HCO3, PO4, Pb, Zn, high abundance of rotifers and copepods. In May and June, the lowest abundance of all groups of planktonic invertebrates, an increased amount of N-NO2, and a lower content of Ca and HCO3 compared to April were recorded. The characteristic features of the months combined into the third cluster (July, August, September) were high values of TDS, Mg, hardness, transparency, temperature, and a high abundance of cladocerans.  The location of the variables on the correlation circle demonstrates that rotifers were positively associated with bicarbonates and PO 4 ; negative associations were with TDS, Mg, temperature, and transparency. Cladocera were positively associated with Mg and temperature while negatively correlated with N-NO 2 , PO 4 , Ca, Zn, Pb, and depth. A positive relationship was found between copepods and HCO 3 , Ca, PO 4 , N-NO 2 , Pb, and Zn; a negative one with transparency, water temperature, TDS, and Mg.
The number of planktonic invertebrate species was positively associated with transparency, temperature, TDS, and Mg, inversely with HCO 3 , Ca, PO 4 , N-NO 2 , Pb, and Zn (Figure 9b). The values of the Shannon index changed in a similar way, which were positively associated with depth, transparency, temperature, TDS, and Mg, with a negative relationship with HCO 3 , Ca, PO 4 , and N-NO 2 . The same environmental variables influenced the average individual mass in zooplankton communities, with the maximum values in June.

Ponds RSC
In RSC 7, May was characterized by the highest concentrations of nutrients, Ca, and Zn, July-by elevated water temperatures; CO 3 and Mg were associated with August and September (Figure 10a). The relationship between environmental and biological variables was traced only to a weak extent. Rotifers were associated with CO 3 , cladocerans with CO 3 and Si, and copepods with temperature. For rotifers, negative associations were with nutrients and Ca. In RSC 8, May was associated with increased content of PO4, N-NO2, and pH value, June-with hardness, July-with temperature, hardness, transparency, N-NH4, August and September-with Mg (Figure 10b). Following the location of variables on the correlation circle, the biomass of rotifers was positively related to N-NH4, with a negative relationship between abundance and temperature, hardness, and PO4. Positive associations were recorded between Cladocera and the chemical water composition, PO4, transpar- In RSC 8, May was associated with increased content of PO 4 , N-NO 2 , and pH value, June-with hardness, July-with temperature, hardness, transparency, N-NH 4 , August and September-with Mg (Figure 10b). Following the location of variables on the correlation circle, the biomass of rotifers was positively related to N-NH 4 , with a negative relationship between abundance and temperature, hardness, and PO 4 . Positive associations were recorded between Cladocera and the chemical water composition, PO 4 , transparency, and temperature; negative relationships with Zn and Pb. Copepods were associated with N-NO 2 , pH, and HCO 3 ; a negative relationship was with temperature, water chemistry, and transparency. The number of planktonic invertebrate species was associated with temperature, N-NH 4 , and transparency; the average individual mass-with PO 4 , Mn, and hardness. Shannon index values were associated with temperature, Ca, and hardness, and they were in feedback with Mg and HCO 3 .

Factors Affecting the Water Quality in Wastewater Reservoirs
In June 2021, the content of nitrogen compounds, PO 4 , and Fe in the wastewater canal was higher, and PI values, Cu, and Pb were lower than in ponds and Sorbulak. A similar distribution of pollutants between different parts of the Sorbulak wastewater system was also recorded in previous periods [23,24,27].
The decline in nutrients in reservoirs relative to the wastewater canal is associated with their absorption by primary producers [44]. According to our unpublished data, in June 2021, the phytoplankton biomass in Sorbulak and ponds (4.6-11.0 g/m 3 ) was an order of magnitude higher than in the wastewater canal (0.8 g/m 3 ). In Sorbulak, a competitive consumer of nitrogen and phosphorus is comb pondweed, which, like other aquatic plants, uses them for its life activity [45].
The higher content of heavy metals in the reservoirs relative to the wastewater canal is due to their long-term accumulation in bottom sediments and subsequent release. The role of bottom sediments in shaping water quality is widely known [46]. Until 1980, the sewage discharged into Sorbulak was not treated. By 2000, the total content of suspended solids, Fe, Cu, Sr, and Cd, entering Sorbulak reached 85,000 tons [23].  [29]. The results obtained allow us to conclude that bottom sediments can be a source of secondary pollution of wastewater reservoirs.

TDS
In the Sorbulak depression, groundwater occurs at depths of 0.8-4.8 m and is characterized by increased TDS [23]. A twofold excess of water salinity in Sorbulak, compared to the canal, was recorded already in the initial period (1985) of its existence [25]. The almost threefold excess of TDS in Sorbulak relative to the canal and ponds may be due to the accumulation of salts in conditions of its weak flow and their additional supply from underlying rocks and groundwater. The low water salinity values in the canal and ponds are associated with their flow (the movement of water in the direction from the first to the eighth pond) and, presumably, the absence of underground runoff mineralized water.

pH Value
Differences in pH can be explained by the higher photosynthetic microalgae activity in ponds than in Sorbulak. According to our unpublished data, the peak pH values in the ponds (9.55-10.26) coincided with the highest phytoplankton biomass (10.0-11.0 g/m 3 ). The values of both variables in the ponds were higher than in Sorbulak (pH < 9.33, phytoplankton biomass 5.6-8.4 g/m 3 ). A negative correlation between pH and HCO 3 ( Figure 5) could reflect the absorption of carbon dioxide by rapidly reproducing microalgae [47]. It is known that carbon dioxide shifts pH value to the acid side [43].

Nutrients
Municipal, livestock, and agricultural effluents are the primary sources of nutrient supply to aquatic ecosystems [48]. Aquatic and semi-aquatic birds also enrich water bodies with nitrogen and phosphorus [49]. Primary producers consume nutrients for their growth [50]. Their death leads to the accumulation of these compounds in bottom sediments [45] and secondary pollution of water bodies [51]. Desorption of nitrogen is more active than phosphorus and depends on temperature. The solubility of iron phosphates is affected by Ca [52]. In turn, iron stimulates phosphorus binding in bottom sediments [53]. Positive relationships between Fe and PO 4 were established for the lakes of Northern Kazakhstan [54].
Differences in the average content of nutrients between Sorbulak and ponds are due to many reasons. In addition to wastewater, grazing and watering of animals (Figure 3c) is an additional source of nutrients for Sorbulak and, to a lesser extent, ponds. Colonial bird species (pelicans, cormorants, gulls) nesting on the islands contributed to the organic pollution of these water bodies (Figure 3a,b). Compared with ponds, the lower content of nitrogen in Sorbulak may be due to its absorption by combed pondweed in shallow waters and burial in bottom sediments of deep-water parts. Obviously, secondary pollution of ponds occurs due to intensive desorption from bottom sediments in shallow depths and high temperatures of the bottom layer. A particular contribution to the enrichment of ponds with nutrients caused by polluted runoff from overlying shallow ponds. In them and the ponds we examined, the desorption of pollutants from bottom sediments occurs due to high water temperatures in summer. Chemical interactions [52,53] also affect the accumulation of nutrients in the examined wastewater reservoirs. For Sorbulak, the Pearson correlation coefficient between PO 4 and Fe was 0.547, and between PO 4 and Ca was 0.641, at p < 0.05. For ponds, the relationship between PO 4 and Fe was not statistically significant; a more substantial relationship was noted between PO 4 and Ca (r = 0.840, p < 0.05).

Silicon, Iron, and Manganese
Silicon enters aquatic ecosystems due to chemical weathering and dissolution of silicon-containing minerals [43], with industrial wastewater, due to the death of plants and algae [55]. The content of Si in the surface waters of the humid zone correlates with organic matter [56]. Silicon contributes to water enrichment with Fe and Mn [57]. Manganese enters aquatic ecosystems through the leaching of ferromanganese ores, emissions, and effluents from industrial enterprises [43]. Inside the water body, the release of Mn occurs due to the decomposition of aquatic animals, algae, and higher aquatic plants. With a sufficient amount of oxygen, the formation of sparingly soluble MnO 2 contributes to its accumulation in bottom sediments [58]. The return of Mn to water most intensively occurs together with PO 4 under anaerobic conditions [59].
According to the references, the increased combined content of Si, Fe, and Mn in ponds may be associated with chemical interactions between these elements. In addition to wastewater, the sources of their receipt are the processes of secondary pollution of ponds, including the death of planktonic algae. A substantial amount of Si and PO 4 was recorded in RSC 7, where in summer, the water is a green suspension of planktonic algae (Figure 2e).

Heavy Metals
Heavy metals get into wastewater and further into Sorbulak and ponds, mainly with industrial wastewater. Due to socio-economic reasons, from the 1990s to 2005, the share of industrial effluents in the total volume of wastewater declined [23], which led to a decrease in the overall level of toxic pollution of wastewater reservoirs. In 2000-2002, the content of heavy metals varied within the following limits (mg/dm 3 ): Cd-from 0.005 to 0.078, Cu-from 0.002 to 0.024, Pb-from 0.006 to 0.047, Zn-from 0.014 to 0.047 [29]. In the summer of 2017, the content of Cd and Pb was below the detection limit; the content of Cu and Zn in Sorbulak and RSC 8 was significantly lower than the MPC, but high in RSC 7 (Zn was 0.037, Cu was 0.043 mg/dm 3 ) [24]. For six months of 2021, the concentrations of Cd, Cr, Co, Pb, and Zn in all water bodies were below the MPC. The widespread increase in Cu (up to 0.0115-0.0359 mg/dm 3 , with a maximum in ponds) may be associated with an increase in textile production in Almaty (from 5.0 to 23.7%) in recent years [60]. Copper, along with zinc, is used to manufacture paints and dyeing fabrics [23].
Differences in the spatial distribution of heavy metals in the surveyed wastewater bodies are determined by a complex of local physicochemical factors. The migratory of heavy metals depends on the form of their occurrence (cationic or anionic) and the physicochemical conditions of the water body [61]. The entry of heavy metals into the water from bottom sediments is stimulated by anaerobic conditions [62], high temperatures, and low water pH values [11]. Binding with CO 3 2− and Cl − leads to the formation of sparingly soluble complexes and the accumulation of heavy metals in bottom sediments [61]. Cu and Pb are almost completely precipitated under alkaline conditions (pH > 6); Zn binds with Mn and Fe oxides and precipitates more intensively with an increase in TDS [11]. Si contributes to water enrichment with Zn and Cu [57].
High pH values contribute to the accumulation of metals in bottom sediments and the purification of the water column in all wastewater reservoirs. In Sorbulak, in addition, the burial of heavy metals in bottom sediments occurs due to temperature stratification (in the deep part, the temperature of the bottom layers is 7-8 • C lower than on the surface) and a high concentration of complexing ions (CO 3 2− , Cl − ). In shallow ponds, the temperature of the bottom layers in summer reaches 25.5-26.0 • C, which can stimulate the desorption of heavy metals from sediments to water. Chemical interactions between Si, Zn, and Cu contribute to their joint accumulation in ponds. An additional influx of heavy metals into ponds can occur due to polluted runoff from overlying ponds (Figure 1).

Dynamic during Six Warm Months
For natural water bodies, the supply of nutrients is positively correlated with precipitation, with a maximum in the spring [63]. In the reservoirs examined, only four indicators (temperature, TDS, PI, N-NO 2 ) changed to one degree or another synchronously, which may indicate common predictors of their seasonal dynamics. These include natural and climatic factors (seasonal changes in air temperature and precipitation) and changes in the volume of incoming wastewater.
Differences in the seasonal dynamics of most of the environmental variables between Sorbulak and ponds are due to the specific conditions for transforming pollutants in each of them. As mentioned above, a significant factor determining water quality in reservoirs is the desorption of organic and toxic substances from bottom sediments. The rate of these processes, in addition to the complex and often non-linear influence of several other factors [8], positively depends on temperature [7,11]. Perhaps it is no coincidence that the highest content of heavy metals was recorded at the end of summer, against the background of maximum water heating in shallow ponds. In Sorbulak, a factor in reducing toxic pollution of the water column is increased TDS value. The Pb and Zn content in Sorbulak decreased statistically significantly with an increase in water salinity (r = −0.694 and r = −0.460, p < 0.05). There was a weak correlation between TDS and Pb content in ponds (r = −0.380). A lead deposition is enhanced in the presence of carbonates [61,63], the amount of which in the examined reservoirs was positively related to TDS. Thus, the hydrochemical conditions of reservoirs stimulate the purification of the water column and the accumulation of pollutants in bottom sediments; however, under certain conditions, it becomes the cause of secondary pollution of water bodies. It should also be taken into account that heavy metals, once entering the aquatic ecosystem, remain there indefinitely since they do not undergo biodegradation [11]. The removal of heavy metals from the surveyed reservoirs is carried out due to unauthorized catching of fish, in the organs and tissues of which there is an intensive accumulation of heavy metals [28].

Species Composition
Species of planktonic invertebrates, which are the most common in wastewater reservoirs, inhabit water bodies of various types, including those with an increased amount of readily oxidizable organic substances and nutrients [64]. D. (C.) magna, D. (Daphnia) pulex, and A. robustus dominated the zooplankton of Sorbulak starting from the first years of its existence when wastewater was not treated [25]. It also indicates their resistance to a wide gradient of environmental conditions. D. magna is morphologically adapted to trophic water bodies dominated by filamentous cyanobacteria due to the thickening of the bristles of the filter apparatus [65]. B. longirostris is also found in water bodies with a high abundance of cyanobacteria [66]. D. mongolianum prefers sulfate-chloride alkaline eutrophic waters [67]. Dominance in 2021 of this species, which was absent earlier [24][25][26][27], may be associated with a decrease in the toxic pollution of wastewater reservoirs. Cyclopoid copepods A. robustus (previously identified as A. trajani) and C. vicinus inhabit the water bodies of Kazakhstan with a high level of organic and toxic pollution [64]. In general, most species of planktonic invertebrates recorded in ponds prefer shallow water bodies with rapidly changing environmental conditions [34,36,68] and an increased level of organic pollution [39]. In Sorbulak, both thicket and planktonic species were encountered, which reflected the diversity of biotopes in this reservoir.
The dominance of large Daphnia in summer contributes to the purification of the water column of reservoirs from bacterioplankton and phytoplankton and an increase in water transparency [69]. A positive, statistically significant relationship between Daphnia biomass and water transparency was registered only in ponds (r = 0.681, p < 0.05).
The composition of dominant species in Sorbulak and ponds was variable, especially among rotifers, which may reflect dynamic changes in environmental conditions [70], including those not taken into account in this study. The number of planktonic invertebrate species in reservoirs decreased along the phosphorus load gradient. It was also noted in other urbanized water bodies [16].

Quantitative Variables
Higher quantitative variables of zooplankton in the surveyed wastewater reservoirs, compared with natural water bodies of Kazakhstan [71], are due to the constant influx of nutrients with wastewater. Favorable conditions for planktonic invertebrates in 2021 are also due to a significant decrease in the toxic pollution of wastewater reservoirs due to the closure in recent decades of most industrial enterprises previously located in Almaty [23]. According to our data, the ratio of the organic and toxic components in the total pollution level is the main factor in forming the species composition and structure of zooplankton communities in technical reservoirs of Kazakhstan [71]. This is because organic and nutrient substances determine the abundance of bacterioplankton and phytoplankton and, consequently, the trophic conditions of planktonic invertebrates; on the other hand, chemical interactions between heavy metals and organic substances can reduce the toxicity of the last one [11].

Dynamics during Six Warm Months
In temperate and arid water bodies, temperature and seasonal variability in precipitation [71] are among the main predictors of the intra-annual dynamics of the composition and structure of biological communities. In a tropical climate, a constant influx of nutrients into water bodies with wastewater causes a uniform distribution of biological variables throughout the year [16]. Still, in natural water bodies of the region, seasonal dynamics depend on the supply of nutrients from the catchment area during the monsoon period.
Differences in environmental variables (reasons discussed above) determined the asynchrony of the seasonal dynamics of zooplankton in wastewater reservoirs, despite their territorial proximity and feeding from the same source. In the surveyed wastewater reservoirs, the seasonal dynamics of zooplankton had pronounced maxima: in Sorbulak, in April and July; in RSC 7, in September; and in RSC 8, in May and September. Thus, the seasonal dynamics of biological variables were associated with the seasonal temperature gradient, but in each wastewater reservoir, it was determined by an additional set of environmental indicators.

Impact of Environmental Variables on Zooplankton Communities
Depending on the water body, the factors influencing planktonic invertebrates were somewhat different. The influence of the same environmental variables on taxonomic groups could be either positive or negative. The different nature of the relationship between biological and environmental variables is maybe due to the non-linear response of species to changes in environmental conditions. Previously, we found that the optimal values for planktonic invertebrates occupy the middle of the variation series when the gradient of ecological variables is relatively wide [54,71].
Almost all taxonomic groups of zooplankton were associated with CO 3 and/or HCO 3 . It could indirectly reflect the biotic relationships between zooplankton and phytoplankton, which are not considered in this study, and the significant role of anions in the formation of water alkalinity [43] and the transformation of heavy metals [61]. The positive effect of water temperature on the abundance of Cladocera, among which Bosmina, Daphnia, and Ceriodaphnia dominated, is due to their thermophilicity [72,73]. Freshwater cladocerans, except Polyphemidae, are sensitive to Mg [74]. The positive relationship between the abundance of cladocerans and Mg in wastewater reservoirs confirms our earlier conclusion [75] about the resistance of some Daphnia species to this cation. With a low level of toxic pollution of wastewater reservoirs in 2021, the relationship between cladocerans and Zn and Pb content was negative. It indicates that even low concentrations of heavy metals could have a negative effect on filter feeders species [76]. Cyclopoida is more resistant to toxic pollution [63], which is also confirmed in this work.
The obtained correlations between environmental and biological parameters cannot always be explained. This is due to the insufficiency of our knowledge about the ecological preferences of planktonic invertebrates and the influence of many multidirectional factors in the conditions of complex pollution of wastewater reservoirs.

Conclusions
Water quality in wastewater reservoirs is formed under the influence of a complex of interrelated factors. Organic matter and nutrients enter reservoirs with wastewater, polluted surface runoff, due to the vital activity of domestic animals and near-water bird species, and heavy metals mainly with wastewater. In turn, the toxic pollution of wastewater entering the reservoirs depends on the volume of industrial effluents and the efficiency of their treatment. The increase in the content of copper in the water against the backdrop of the growth of textile production in the past few years indicated insufficiently effective wastewater treatment from heavy metals. Further transformation of the pollutants was determined by the physicochemical conditions in each of the wastewater reservoirs. The participation of bottom sediments in the purification and secondary pollution of the water column largely depends on the prevailing depths. In shallow ponds, the desorption of heavy metals from bottom sediments occurs more intensively due to better heating of the bottom layers. In the deep-water Sorbulak, water purification is facilitated by temperature stratification, increased mineralization, and large areas occupied by macrophytes. The joint accumulation of some pollutants (Si, Mn, Zn, Cu) may be due to their chemical interaction. Zooplankton was represented mainly by eurybiont species enduring a wide gradient of environmental conditions. The change in the species composition of planktonic invertebrates during the semi-annual warm period reflected the instability of external conditions in wastewater reservoirs. The constant supply of nutrients with wastewater has led to a high abundance of zooplankton in wastewater reservoirs throughout the entire research period. Zooplankton communities were mainly affected by carbonates, bicarbonates, temperature, magnesium, nutrients, and heavy metals. The results obtained indicated that even low concentrations of heavy metals could harm the Cladocera, while Cyclopoida is more resistant to toxic pollution. In general, chemical and biological variables indicated a high level of organic pollution and relatively low toxic pollution of Sorbulak and ponds. Thus, at present, the reuse of wastewater is relatively safe, but constant monitoring of its quality is necessary.
Author Contributions: E.K. analyzed the data, wrote an article, prepared figures and tables; M.A. wrote part of the article, reviewed drafts of the article; S.R. performed hydrochemical analysis of samples, reviewed drafts of the article. All authors have read and agreed to the published version of the manuscript.
Funding: This work was funded by the Committee of Science, Ministry of Education and Science, Republic of Kazakhstan, Grant no. AP08855655 "Assessment of the ecological state of wastewater storages of the system of the Right-Bank Sorbulak Canal for the development of the scientific basis for wastewater disposal", Institute of Zoology. The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.

Data Availability Statement:
No new data were created or analyzed in this study. Data sharing is not applicable to this article.