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. 2021 Jan 17;50(6):1248–1258. doi: 10.1007/s13280-020-01470-1

Long-term changes in microbial water quality indicators in a hydro-power plant reservoir: The role of natural factors and socio-economic changes

Gunta Spriņġe 1,2,✉, Māris Bērtiņš 3, Lesya Gnatyshyna 4, Ilga Kokorīte 6, Agnese Lasmane 2, Valery Rodinov 6, Oksana Stoliar 5
PMCID: PMC8068751  PMID: 33454917

Abstract

Long-term changes, from 1984 to 2010, in the indicators of microbial pollution (total viable count, coliforms, Escherichia coli, enterococci, and Clostridium perfringens) are analysed in the Riga Hydropower Plant Reservoir, an essential source of drinking water for Riga, the capital of Latvia. Counts in microbial indicators fluctuated seasonally and were related to physicochemical parameters (nitrogen compounds, turbidity, temperature, and pH). The changes in microbial pollution were brought about by two major socio-economic developments. Firstly, Latvia’s independence from the USSR in 1991 which facilitated a distinct reduction in most microorganism counts due to a sharp decline in industrial and agricultural production. This resulted in a significant drop in point and nonpoint pollution in the river basin. A further development was Latvia joining the European Union in 2004. The corresponding focus on water management, including wastewater treatment, was a major priority of environmental investment and lead to improvements in microbial water quality.

Electronic supplementary material

The online version of this article (10.1007/s13280-020-01470-1) contains supplementary material, which is available to authorized users.

Keywords: Environmental policy, Microbial indicators, Physicochemical parameters, Reservoir, Seasonal changes

Introduction

Hydropower is the most widely used and economically efficient renewable energy source in the world, and its use as a source of green energy is essential in the context of a low-carbon economy (Bratrich et al. 2004; Chatzimouratidis and Pilavachi 2009). However, hydropower causes serious ecological impacts at the local level, such as the inundation of land, modifications of flow regimes, migration barriers, trapped nutrients or sediments, and the degradation of aquatic ecosystems (Bratrich et al. 2004). Water quality aspects are of special importance when a reservoir’s water is used as a source of drinking water, as is the case with the Riga Hydropower Plant (HPP) reservoir or Riga Reservoir.

Impacts caused by human pollution and habitat alteration in aquatic ecosystems are most evident at the microbial level as microorganisms react quickly to low levels of pollutants, in addition to other physical, chemical, and biotic environmental changes (Paerl et al. 2003). Microbial quality indicators for raw water generally follow standard EU drinking-water criteria. Such indicators are given in the EU Council Directive on the Quality of Water Intended for Human Consumption (European Commission 1998). In Latvia, the regulation entitled Regulations Regarding the Quality of Surface Waters and Groundwaters dictates drinking water standards (Republic of Latvia Cabinet 2002).

Broadly speaking, microbial indicators are divided into three groups. Process indicators are organisms that demonstrate the efficiency of a process, such as total heterotrophic bacteria or total coliforms for chlorine disinfection. Faecal indicators indicate the presence of faecal contamination, such as the bacterial groups as thermotolerant coliforms or Escherichia coli. While a group or species indicating a pathogen presence and behaviour belongs to the index and model organism category (Ashbolt et al. 2001).

Water bodies are affected by natural perturbations, including droughts, storms, and floods, the frequency and extent of which may be increasing, leading to a change in microbial parameters as a result of these events (Paerl et al. 2003). However, human impacts (increased pollution from industry and agriculture; untreated wastewater, hydromorphological changes) have significantly impacted the aquatic environment, and will continue to do so (Páll et al 2013). In the case of Latvia, after regaining independence in 1991, the quality of inland water improved mainly as a result of a decrease in nutrient loads from point and nonpoint sources, coupled with substantial efforts taken in the area of environmental protection (Juhna and Kļaviņš 2001). Furthermore, the socio-economic crisis in the early 1990s ushered in a dramatic reduction in industrial and agricultural production. For example, the number of livestock decreased four-fold, and fertilizer consumption 15-fold (Stålnacke et al. 2003). The amount of wastewater decreased substantially, due to both the collapse of big industrial enterprises and the introduction of water conservation measures (Juhna and Kļaviņš 2001). In the ensuing years, more than 848 million euros have been invested in the construction and reconstruction of wastewater treatment plants and sewerage networks, drinking water stations, and water supply systems in urban areas (UNECE 2019).

Having these developments as a unique backdrop, the aim of this study is to analyse changes in microbiological indicator organisms over the period of 1984 to 2010. The relevance of the study can be found in the fact that due to the aforementioned political and socio-economic changes that occurred in Latvia during this time period, the water quality of Riga Reservoir, as a source of drinking water, has been positively impacted.

This study has come to this result by analysing the total viable counts of heterotrophic bacteria as an indicator of organic pollution, while total and faecal coliforms, E. coli, intestinal enterococci, and Clostridium perfringens, were the specific indicators used to analyse faecal pollution.

Materials and methods

Riga Reservoir is situated 35 km from the mouth of the Daugava River. The river (total length 1005 km, 352 km in Latvia) begins in Russia and runs through Belarus and Latvia. Thus, the reservoir is affected by runoff from an exceptionally large catchment area: 84 100 km2 (27 062 km2 in Latvia). The Reservoir is the largest artificial water body in Latvia, with a total surface area of 42.3 km2, an average reservoir depth of 7.1 m, maximum depth of 17.4 m, length of 35 km, and volume of 339 million m3. It was built between 1966 and 1974 to fulfil the needs of the Riga Hydropower Plant (HPP), and as a drinking water source for the city of Riga. The total installed capacity of the Riga HPP is 402 MW. The Riga Reservoir is the last in a cascade of three Daugava HPPs in Latvia (Fig. 1). In order to ensure a permanent generation of electricity, Riga HPP’s operations alternate between peak and off-peak modes.

Fig. 1.

Fig. 1

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Study area and longitude profile of the River Daugava in the territory of Latvia

The water utility company Rīgas Ūdens supplied the microbial data for the Riga Reservoir for the period between March 1984 and December 2010.

For sampling, raw water was taken at 8 m depth in the Riga Reservoir (GPS coordinates 56° 49′ 18.7″ N; 24° 17′ 07.0″ E), as well as by two pipes supplying water to the Daugava Drinking Water Treatment Plant. In total, 9800 daily water samples were collected in sterile 0.5 L glass bottles from a tap designated for this purpose through which water from the Daugava continuously flows according to standard procedures (till 1994 ГOCT 18963-73, after 1994—ISO 5667 series of standards).

Throughout the study period, quality assurance measures (monitoring the sterility of the medium by the qualitative streaking method, working surfaces by RODAC plates, and air by exposure of a nonselective agar medium) were applied as standard procedures in the microbiological testing laboratory. This is in accordance with ISO standards for both total coliforms and faecal coliforms. Escherichia coli and intestinal enterococci positive and negative controls were performed. This included the qualitative streaking method, inoculation of the relevant reference culture (Escherichia coli ATCCO 25922 TM, Enterococcus faecalis ATCCO 29212 TM, Clostridium perfringens ATCCO 13124 TM) in the prepared medium, and incubation, followed by an assessment of the growth of the microorganisms.

Total viable counts (TVC; CFU mL−1) were estimated as colony counts after inoculation in the nutrient agar culture medium (till 1994: ГOCT 18963-73; after 1994: LVS EN ISO 6222:1988). For all samples, analysis was completed at the time of collection. Specifically, a total of 4896 samples were analysed from March 1984 to July 1997. The multiple tube (most probable number) method (till 1994: ГOCT 18963-73; Ū-71-94; after 1994: LV ISO 9308-2:1990) was used to determine the Coli Index (quantitative index of the faecal contamination of water, MPN L−1), total coliforms (MPN 100 mL−1), faecal coliforms (thermotolerant) (MPN 100 mL-1), and Escherichia coli (E. coli, MPN 100 mL−1). For the Coli index, 4892 samples were analysed from March 1984 to July 1997. For total coliforms, 4883 samples were analysed from August 1997 to December 2010. For faecal coliforms, 4178 samples were analysed from August 1997 to February 2009. While for E. coli, 4178 samples were analysed from May 1994 to December 2010. The membrane filtration method was used to detect intestinal enterococci (CFU 100 mL−1) (till 2001: LVS ISO 7899-2:1984, after 2001: LVS EN ISO 7899-2:2001; ISO 7899-2:2006) and Clostridium perfringens (including spores) (CFU 100 mL−1) (LVS EN 26461-2:1993). For intestinal enterococci, 161 samples were analysed from August 1997 to December 2010. For C. perfringens, 113 samples were analysed from September 2001 to December 2010.

Water temperature, pH, turbidity, water colour, chemical oxygen demand (COD), NH4+, NO2−, NO3−, and PO4− were analysed according to standard methods. An overview of the analytical methods of the water chemical composition in the Riga Reservoir is given in the Supplementary Material (Table S1).

Data analysis

Mean monthly values of microbial and physicochemical parameters were calculated from the daily data of analytical measurements which was provided by Rīgas Ūdens’s Daugava Drinking Water Treatment Plant laboratory.

The multivariate non-parametric Mann–Kendall test modified by Hirsch and Slack (1984) was used to analyse long-term and seasonal changes in the TVC and Coli index. The purpose of the test is to detect monotone trends in a time series that may contain missing values, outliers, serial, or seasonal variation, while not following a typical distribution. A trend was considered as statistically significant at the 95% confidence level when the test statistics showed a value greater than 1.96 or less than − 1.96. The MULTIMK/PARTMK programme was used to perform a trend analysis (Libiseller and Grimvall 2002). To assess the long-term trend to all other microbial indicators, the linear regression method was used in MS Excel 2013 (v15.0).

Spearman’s rho correlation was used to study the relationship between microbiological and physicochemical parameters. This was chosen as it does not require normal data distribution. R software (R Core Team 2016) packages Hmisc and ggplot2 were used to run correlation tests and create plots.

Results

Our results confirm that seasonal changes occurred for almost all the bacteriological parameters in the Riga Reservoir (Fig. 2).

Fig. 2.

Fig. 2

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Seasonal variations in the total viable count (TVC, 1984–1997), total coliforms (1997–2010), faecal coliforms (1997–2009), and E. coli (1994–2010)

As seen in Fig. 2, the highest mean TVC occurred in spring (April), and the largest fluctuations between the minimum and maximum values were also more commonly found in spring (March, April) and June. The highest total and faecal coliforms and E. coli average values, as well as the highest fluctuations of these indicators, were generally observed in winter and early spring (Fig. 2). However, the number of faecal coliforms never exceeded the target value (20 000 MPN mL−1) for water quality standards for surface water to be used for the abstraction of water intended for human consumption, as specified in the Republic of Latvia Cabinet Regulation No.118. (12 March 2002), Regulations Regarding the Quality of Surface Waters and Groundwaters.

Similarly, the amount of intestinal enterococci were relatively low (0–100 CFU 100 mL−1) throughout the study period (1997–2010) and were significantly below the target value (10 000 CFU mL−1), set out in the Republic of Latvia Cabinet Regulation No. 118. In most years, detectable levels of these faecal indicators were not observed from May to October. The numbers of C. perfringens varied from 1 to 68 CFU 100 mL−1, with no obvious seasonal trend detected.

The results of the correlation analysis revealed relationships between microbial and chemical parameters. Ammonium concentrations had the closest relationship with total (r = 0.43, p < 0.0) and faecal (r = 0.48, p < 0.01) coliforms and E. coli (r = 0.73, p < 0.01) when compared to other physicochemical parameters. TVC was positively related with water turbidity (r = 0.40, p < 0.01) and nitrate concentration (r = 0.36, p < 0.01). C. perfringens had the closest relationship with nitrate concentration (r = 0.48, p < 0.01). All microbial parameters had a weak negative relationship with temperature. Total and faecal coliforms, E. coli, and C. perfringens all had a weak positive relationship with phosphate concentrations (Table 1). Regarding relationships among microbial parameters, a strong correlation was found between the total and faecal coliforms and E. coli. The number of E. coli. was also correlated with the total viable count (Table 1).

Table 1.

Physico-chemical parameters and analytical methods used for water analyses in the Riga Reservoir

Parameter Analysis period; number of samples Basic principle Method before 2000 Method after 2000
Temperature 1987–2010; 288 Mercury glass thermometer or thermal resistivity thermometer Mercury glass thermometera Mercury glass thermometer and thermal resistivity thermometersa
pH 1987–2010; 288 Potentiometry Potentiometrya ISO 10523
Turbidity 1987–2010; 288 Turbidimetry ГОСТ 3351-74 ISO 7027
Color 1987–2010; 288 Visually by using Pt scale ГОСТ 3351-74 ISO 7887
Chemical oxygen demand (COD) 1990–2010; 243 Titrimetrically after oxidation of a sample with KMnO4 ГОСТ 23268.12-78 ISO 8467
NH4+ 1987–2010; 288 Photometrically according to the Nessler’s method ГОСТ 4192-82 ISO 7150/1
NO2− 1987–2010; 286 Photometrically following Griess reaction ГОСТ 4192-82 ISO 6777
NO3− 1987–2010; 272 Photometrically according to the salicylate method ГОСТ 18826-73 ISO 7890/3
PO43− 2001–2010; 80 Photometrically following molybdenum blue reaction ГОСТ 18309-72 ISO 6878
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aNo standard method available

A significant downward trend was observed in the Riga Reservoir in TVC (R2 = 0.11, p < 0.01, n = 160) and the Coli index (R2 = 0.33, p <0.01, n = 159) over a long-term period (1984–1997). The monthly mean concentrations of TVC reached more than 500 CFU mL−1 in 1986, and there was a gradual decrease to a range of 20 to 200 CFU mL−1. Monthly mean values from 1984 to 1990 of the Coli index fluctuated with peaks reaching up to more than 8000 MPN L−1, while from 1991 to 1997 in most cases, these values were not higher than 1000 MPN L−1.

The Mann–Kendall trend test results confirmed that the decrease in both TVC and the Coli index in the Riga Reservoir were statistically significant (for the coli index, MK-stat = − 3.4, p < 0.01; and for TVC, MK-stat = − 2.9, p < 0.01). A statistically significant decrease in TVC (MK-stat < − 1.96, p < 0.05) occurred mostly in late spring and summer as well as in November and January, while a statistically significant decrease in the Coli index was observed throughout the year, outside of June and July (Fig. 3).

Fig. 3.

Fig. 3

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The significance of trends in the total viable count (TVC) and the coli index, 1984–1997

The maximum values of E. coli occurred during the 1997–1998 period (up to 24 000 MPN 100 mL−1); however, later counts saw a significant decrease (did not exceed 625 MPN 100 mL−1; R2 = 0.16, p < 0.01, n = 199) (Fig. 4).

Fig. 4.

Fig. 4

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Changes in the numbers of E. coli, 1994–2010

Similar to the counts of E. coli the maximum values of total and faecal coliforms occurred from 1997 to 1998 (up to 7000 MPN 100 mL−1 for total coliforms, up to 2400 MPN 100 mL−1 for faecal coliforms). This was followed by a significant decrease in the counts of total and faecal coliforms (total coliforms did not exceed 1100 MPN 100 mL−1, R2 = 0.18, p < 0.01, n = 160; faecal coliforms did not exceed 500 MPN 100 mL−1, R2 = 0.29, p <0.01, n = 138).

The numbers regarding intestinal enterococci were generally low (0–100 CFU 100 mL−1) during the observation period from 1997 to 2010, while showing no definite trend during this period. The numbers of C. perfringens were also low and fluctuated without any trend from 2001 to 2010 (Fig. 5).

Fig. 5.

Fig. 5

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The number of Clostridium perfringens in the Riga Reservoir water, 2001–2010

Discussion

In general, the values of microbial indicators for water quality in the Riga Reservoir were not high compared to polluted waters in other countries e.g. Febros River in Portugal, the Gangetic river system in India, Sutla River in Croatia (Cabral and Marques 2006; Sood et al. 2008; Dragun et al. 2011). In the Riga Reservoir, microbiological water quality corresponds with the requirements of the EU Council Directive on the Quality of Water Intended for Human Consumption (European Commission 1998). At the same time, the Latvia regulation entitled Regulations Regarding the Quality of Surface Waters and Groundwaters has also been fulfilled (Republic of Latvia Cabinet 2002).

Microbial parameters in the reservoir water demonstrated both seasonal and long-term changes. Seasonal fluctuations in the values of microbial indicators in the Riga Reservoir water may have been caused by variable hydrological, climatic and meteorological conditions, water hydro-chemical composition, and water level regulation for the needs of the HPP. Typically, the Riga HPP can operate with full capacity only during the spring flood period when the major part of the total annual river runoff in Latvia is generated (39% on average), and the highest discharge is typically observed in April (17% on average) (Apsīte et al. 2013). The highest average values and fluctuations of total and faecal coliforms, E.coli, enterococci, and total viable counts in the Riga Reservoir were observed in early spring and winter. The increase in the numbers of indicator organisms can be attributed to high water flows from melting snow (Goyal et al. 1977; Lipp et al. 2001; An et al. 2002; Kistemann et al. 2002; An and Breidenbach 2005; Hill et al. 2005; Phanuwan et al. 2006) and rainfall (Goyal et al. 1977; Niewolak 1998; Kistemann et al. 2002; Brookes et al. 2004; Hill et al. 2006; Strathmann et al. 2016). As the water flow increases, water turbidity follows suit, along with both total viable count and coliform bacteria (Canosa and Pinilla 1999; Mallin et al. 2000; An et al. 2002).

The hydrological regime, as well as point and nonpoint pollution sources, determine the concentration of nutrients and organic matter in Latvian surface waters (Kļaviņš et al. 2001). On top of that, nutrient inputs and faecal pollution strongly affect the physicochemical and microbiological quality in general (Agbogu et al. 2006; Jordaan and Bezuidenhout 2016). Positive correlations between individual bacteriological and physicochemical parameters are found in a significant number of studies. For example, bacterial counts have a positive relationship with concentrations of nitrogen compounds in Colombian waterbodies (Canosa and Pinilla 1999), coastal watersheds of the United States (Mallin et al. 2000), the Febros River, Portugal (Cabral and Marques 2006), and in water storage reservoirs in China (Hong et al. 2010). Nitrogen enters the water as a result of both natural processes and, especially, anthropogenic sources such as agricultural fertilisers, municipal sewage, degradation of organic matter, and atmospheric deposition in the catchment area (Randall and Mulla 2001, Cabral 2010). The present study confirms a positive significant relationship between physicochemical (ammonium, nitrates, nitrites, turbidity, phosphates) and microbial parameters. The negative effect is the impact of an increase in temperature on the survival of faecal bacteria (McFetters and Stuart 1972; Faust et al. 1975; Lindström et al. 2005; Blaustein et al. 2013). Such a connection is also found in Riga Reservoir. In addition, strong relationships exist between groups of microbial indicators (E. coli and C. perfringens; total and faecal coliforms and E. coli, and between total viable count and E. coli).

The long-term changes in bacterial indicators show two critical periods. First, the average monthly total viable count and Coli index values showed a rapid decrease as well as lower fluctuations after 1991. This was followed by a significant drop in total coliforms, faecal coliforms, and E. coli (as well as in their fluctuations) between 1998 and 2000. Additionally, bacterial counts remained low throughout the remainder of the study period (2010).

This decrease in microbial indicators cannot be explained by the negative effects of the temperature or by reduced water flow rates. Analyses of the mean annual water discharge of the Daugava during the period from 1985 to 1997 show that the discharge in 1990 was 1.5–1.8 times larger than the mean of this period. Discharge was particularly high in autumn 1990 and winter 1991 (Environmental Consultancy and Monitoring Centre 1998). Although there was a significant upward trend in water temperature during the study period, the increase continued after 2000 (Latkovska and Apsite 2016) when microbiological indicators remained low and unchanged.

What can explain the significant decrease in the numbers of microbial indicators in the Riga Reservoir during the period studied are the political and socio-economic changes which occurred in Latvia during this timeframe (Fig. 6).

Fig. 6.

Fig. 6

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Political and socio-economic changes in Latvia, 1984–2010

Latvia regained independence in 1991, when the USSR collapsed. In comparison with the 1980s, there was a sharp decrease in the total volume of production in the industrial sector. The collapse of large industrial enterprises along with a decrease in water consumption by households (water meters and water charges were introduced) and the introduction of water-saving technology (e.g. aerators) led to a decrease in the wastewater volume in Latvia (Juhna and Kļaviņš 2001; Springe and Lukstina 2019). In addition, a reduction in the use of nitrogen and phosphorus fertilisers scaled down nonpoint pollution (Environmental Consultancy and Monitoring Centre 1998; Juhna and Kļaviņš 2001). Furthermore, in 1991, due to the economic downturn of the country, there was a decrease in the amount of livestock (Environmental Consultancy and Monitoring Centre 1998), an important non-point faecal contributor (Crowther et al. 2002; Tyrrel and Quinton 2003; Hill et al. 2005).

Data from the Latvian Environmental Data Centre show that the total amount of wastewaters discharged in the Daugava basin has drastically decreased since 1991, and in 1997 the amount of wastewater was only 35% of the 1991 level. The same trend was observed in untreated municipal wastewater discharges, which in 1997 was only 27% of the 1991 level (Environmental Consultancy and Monitoring Centre 1998). In the case of the Riga Reservoir, one of the largest Latvian industrial textile factories, located at its upper part, in the town of Ogre, rapidly cut its operations between 1996 and 1998. The number of workers was reduced by several thousand, and the production area was downsized nine-fold. In all likelihood, this significantly reduced point-source pollution to the Riga Reservoir, including domestic wastewater. These findings are supported by numerous studies which confirm that municipal wastewater and agricultural runoff are the main sources of bacterial pollution (e.g., Tyrrel and Quinton 2003; Brookes et al. 2004; Hill et al. 2005; Hill et al. 2006; Cabral 2010; Strathmann et al. 2016; Bojarczuk et al. 2018).

The period after 1997 was also associated with changes in the national environmental policy. Latvia joined the European Union in 2004 and to meet EU commitments, ambitious water management projects were launched in the mid-1990s. The national environmental policy, the action programmes for its implementation, and the investment strategies for specific environmental spheres were developed in accordance with the European Commission documents Accession Partnership and The Third National Programme for Latvia’s Integration in the EU. The resources to achieve the objectives of the projects were provided by the state budget, bilateral co-operation partner organizations, EU funds, and international financing institutions. Water protection was named as the first of the four environmental investment priorities (Investment Department of Ministry of Environmental Protection and Regional Development 1998). Its implementation was also facilitated by the signing of the HELCOM Convention in 1992. Riga and Daugavpils, both situated on the banks of the Daugava, were listed among the hot spots in the Baltic Sea joint comprehensive environmental action programme (HELCOM 2003). During this time, water management in Daugavpils and Riga saw major changes (Investment Department of Ministry of Environmental Protection and Regional Development 1998). For example, the reconstruction of sewage treatment plants in Daugavpils was completed in 2000 with the construction of a complex containing biological wastewater treatment plants and dewatering and sludge stabilisation auxiliaries. Studies have shown that coliform bacterial levels in rivers and reservoirs near urban and industrial areas are significantly higher due to point-source pollution, mainly sewage inflow (Hong et al. 2010, Strathmann et al. 2016; Bojarczuk et al. 2018). Between 1995 and 1998, the largest environmental investments were made with the objective to develop water management. The 800+ Programme was launched, which provided opportunities for the improvement of water supply and sewerage in small towns and rural areas in Latvia (Investment Department of Ministry of Environmental Protection and Regional Development of the Republic of Latvia 1998). These actions were in line with the guideline that a clean source of drinking water requires effective policies that identify, document, and reduce watershed risks. This also pertains to other countries where government and international agencies play a critical role in policy development (e.g. Davies and Mazumder 2003).

Conclusion

The majority of the microbial water pollution indicators selected (total viable count, Coli index, total and faecal coliforms) fluctuated seasonally in the Riga Reservoir. An increase in microbial indicator values was mainly observed in winter and the early spring period, while the lowest values occurred in summer. These results correspond with the water discharge changes in Latvian rivers (higher in spring). Ammonia, nitrate, and nitrite concentrations, and turbidity were the most important physicochemical parameters associated with an increase in microorganisms. While seasonal changes were unable to explain the sharp decline in the faecal pollution indicator organisms, and the total viable count, since 1991, socio-economic changes in Latvia could. Latvia regained independence from the USSR in 1991, and the economic downturn led to a significant decrease in industrial production, livestock, use of fertilisers, and discharge of domestic wastewater. The period after the mid-1990s was associated with the implementation of environmental policies and large European investments in the water sector. By analysing these important factors as a whole, it is possible to identify how political and socio-economic changes at the national level account for the downward trend in microbial indicators identified over the long-term.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 160 kb) (160KB, pdf)

Acknowledgements

We would like to thank the water company “Rīgas ūdens” for monitoring data. We are grateful to the two anonymous reviewers for their helpful input, useful comments and suggestions. The research of this paper was financially suppored by the Grant No. LV-UA/2017/5 and University of Latvia Grant No. AAp2016/B041//Zd2016/AZ03.

Biographies

Gunta Spriņġe

is an Associate Professor in environmental science at Faculty of Geography and Earth Science and senior researcher at Institute of Biology, University of Latvia. Her studies involve hydroecology and environmental quality of surface freshwaters.

Māris Bērtiņš

is a Researcher and a Ph.D. student in analytical chemistry at Faculty of Chemistry, University of Latvia. He is former employee of “Rīgas ūdens” Ltd. where he has gained significant experience on chemical and microbiological quality control of drinking water.

Lesya Gnatyshyna

is an Associate Professor of the Department of General Chemistry at I. Horbachevsky Ternopil State Medical University. Her research interests include biomonitoring studies in reservoirs and evaluation of the contaminants.

Ilga Kokorīte

is a senior researcher at Institute of Biology, University of Latvia. Her research interests are related to analysis of long-term changes of aquatic chemistry, pollution loads and factors affecting water quality.

Agnese Lasmane

is a graduate of Master Study programme at Faculty of Geography and Earth Science, University. Her interests are connected to bacteriological quality of drinking water sources.

Valery Rodinov

is a researcher at Institute of Biology, University of Latvia. His scientific interests cover hydrology, aquatic chemistry and influence of climate change on water ecosystems.

Oksana Stoliar

is professor at the Ternopil Volodymyr Hnatyuk National Pedagogical University. Ternopil, Ukraine. Her research interests include political ecology of power plants and the evaluation of their environmental relevance.

Footnotes

Publisher's Note

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Contributor Information

Gunta Spriņġe, Email: gunta.spinge@lu.lv.

Māris Bērtiņš, Email: maris.bertins@lu.lv.

Lesya Gnatyshyna, Email: gnatyshynall@tdmu.edu.ua.

Ilga Kokorīte, Email: ilga.kokorite@lu.lv.

Agnese Lasmane, Email: lasmani146@gmail.com.

Valery Rodinov, Email: valerijs.rodinovs@lu.lv.

Oksana Stoliar, Email: Oksana.Stolyar@tnpu.edu.ua.

References

  1. Agbogu VN, Umoh VJ, Okuofu CA, Smith SI, Ameh JB. Study of the bacteriological and physicochemical indicators of pollution of surface waters in Zaria, Nigeria. African Journal of Biotechnology. 2006;5:732–737. [Google Scholar]
  2. An Y-J, Breidenbach GP. Monitoring E. coli and total coliforms in natural spring water as related to recreational mountain areas. Environmental Monitoring and Assessment. 2005;102:131–137. doi: 10.1007/s10661-005-4691-9. [DOI] [PubMed] [Google Scholar]
  3. An Y-J, Kampbell DH, Breidenbach GP. Escherichia coli and total coliforms in water and sediments at lake marinas. Environmental Pollution. 2002;120:771–778. doi: 10.1016/S0269-7491(02)00173-2. [DOI] [PubMed] [Google Scholar]
  4. Apsīte E, Rudlapa I, Latkovska I, Elferts D. Changes in Latvian river discharge regime at the turn of the century. Hydrology Research. 2013;44:554–569. doi: 10.2166/nh.2012.007. [DOI] [Google Scholar]
  5. Ashbolt NJ, Grabow WOK, Snozzi M. Indicators of microbial water quality. In: Fewtrell L, Bartram J, editors. Water quality: Guidelines, standards and health: Assessment of risk and risk management for water-related infectious diseases. London: World Health Organization; 2001. pp. 289–301. [Google Scholar]
  6. Blaustein RA, Pachepsky Y, Hill RL, Shelton DR, Whelan G. Escherichia coli survival in waters: Temperature dependence. Water Research. 2013;47:569–578. doi: 10.1016/j.watres.2012.10.027. [DOI] [PubMed] [Google Scholar]
  7. Bojarczuk A, Jelonkiewicz Ł, Lenart-Boroń A. The effect of anthropogenic and natural factors on the prevalence of physicochemical parameters of water and bacterial water quality indicators along the river Białka, southern Poland. Environmental Science and Pollution Research. 2018;25:10102–10114. doi: 10.1007/s11356-018-1212-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Bratrich C, Truffer B, Jorde K, Markard J, Meier W, Peter A, Schneider M, Wehrli B. Green hydropower: A new assessment procedure for river management. River Research and Applications. 2004;20:865–882. doi: 10.1002/rra.788. [DOI] [Google Scholar]
  9. Brookes JD, Antenucci J, Hipsey M, Burch MD, Ashbolt NJ, Ferguson C. Fate and transport of pathogens in lakes and reservoirs. Environment International. 2004;30:741–759. doi: 10.1016/j.envint.2003.11.006. [DOI] [PubMed] [Google Scholar]
  10. Cabral JP. Water microbiology. Bacterial pathogens and water. International Journal of Environmental Research and Public Health. 2010;7:3657–3703. doi: 10.3390/ijerph7103657. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Cabral JP, Marques C. Faecal Coliform Bacteria in Febros river (Northwest Portugal): Temporal Variation, Correlation with Water Parameters, and Species Identification. Environmental Monitoring and Assessment. 2006;118:21–36. doi: 10.1007/s10661-006-0771-8. [DOI] [PubMed] [Google Scholar]
  12. Canosa A, Pinilla G. Bacteriological eutrophication indicators in four Colombian water bodies (South America) Lakes & Reservoirs: Research & Management. 1999;4:23–27. doi: 10.1046/j.1440-1770.1999.00079.x. [DOI] [Google Scholar]
  13. Chatzimouratidis AI, Pilavachi PA. Technological, economic and sustainability evaluation of power plants using the Analytic Hierarchy Process. Energy Policy. 2009;37:778–787. doi: 10.1016/j.enpol.2008.10.009. [DOI] [Google Scholar]
  14. Crowther J, Kay D, Wyer MD. Faecal-indicator concentrations in waters draining lowland pastoral catchments in the UK: Relationships with land use and farming practices. Water Research. 2002;36:1725–1734. doi: 10.1016/S0043-1354(01)00394-3. [DOI] [PubMed] [Google Scholar]
  15. Davies JM, Mazumder A. Health and environmental policy issues in Canada: The role of watershed management in sustaining clean drinking water quality at surface sources. Journal of Environmental Management. 2003;68:273–286. doi: 10.1016/S0301-4797(03)00070-7. [DOI] [PubMed] [Google Scholar]
  16. Dragun Z, Kapetanović D, Raspor B, Teskeredžić E. Water quality of medium size watercourse under baseflow conditions: The case study of river Sutla in Croatia. Ambio. 2011;40:391–407. doi: 10.1007/s13280-010-0119-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Environmental Consultancy and Monitoring Centre of Ministry of Environmental Protection and Regional Development of the Republic of Latvia. 1998. The hydroecological state of the River Daugava basin. National Report of the Republic of Latvia, 1998, Riga, Latvia (in Latvian).
  18. Commission European. Council Directive 98/83/EC of 3 November 1998 on the quality of water intended for human consumption. Official Journal of the European Communitie. 1998;41:32–54. [Google Scholar]
  19. Faust MA, Aotaky AE, Hargadon MT. Effect of physical parameters on the in situ survival of Escherichia coli MC-6 in an estuarine environment. Applied Microbiology. 1975;30:800–806. doi: 10.1128/AM.30.5.800-806.1975. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Goyal SM, Gerba CP, Melnick JL. Occurrence and distribution of bacterial indicators and pathogens in canal communities along the Texas coast. Applied and Environmental Microbiology. 1977;34:139–149. doi: 10.1128/AEM.34.2.139-149.1977. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. HELCOM. 2003. The Baltic Sea Joint Comprehensive Environmental Action Programme (JCP). Ten years of implementation. Baltic Sea Environmental. Proceedings No. 88.
  22. Hill DD, Owens WE, Tchounwou PB. Comparative assessment of the physico-chemical and bacteriological qualities of selected streams in Louisiana. International Journal of Environmental Research and Public Health. 2005;2:94–100. doi: 10.3390/ijerph2005010094. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hill DD, Owens WE, Tchounwou PB. The impact of rainfall on fecal coliform bacteria in Bayou Dorcheat (North Louisiana) International Journal of Environmental Research and Public Health. 2006;3:114–117. doi: 10.3390/ijerph2006030013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Hirsch RM, Slack JR. A nonparametric trend test for seasonal data with serial dependence. Water Resources Research. 1984;20:727–732. doi: 10.1029/WR020i006p00727. [DOI] [Google Scholar]
  25. Hong H, Qiu J, Liang Y. Environmental factors influencing the distribution of total and fecal coliform bacteria in six water storage reservoirs in the Pearl River Delta Region, China. Journal of Environmental Sciences. 2010;22:663–668. doi: 10.1016/S1001-0742(09)60160-1. [DOI] [PubMed] [Google Scholar]
  26. Investment Department of Ministry of Environmental Protection and Regional Development of the Republic of Latvia. 1998. Report on Environmental Investments, 1992–1998. Riga, Latvia.
  27. Jordaan K, Bezuidenhout CC. Bacterial community composition of an urban river in the North West Province, South Africa, in relation to physico-chemical water quality. Environmental Science and Pollution Research. 2016;23:5868–5880. doi: 10.1007/s11356-015-5786-7. [DOI] [PubMed] [Google Scholar]
  28. Juhna T, Kļavinš̆ M. Water-quality changes in Latvia and Riga 1980–2000: Possibilities and problems. Ambio. 2001;30:306–314. doi: 10.1639/0044-7447(2001)030[0306:wqcila]2.0.co;2. [DOI] [PubMed] [Google Scholar]
  29. Kistemann T, Claßen T, Koch C, Dangendorf F, Fischeder R, Gebel J, Vacata V, Exner M. Microbial load of drinking water reservoir tributaries during extreme rainfall and runoff. Applied and Environmental Microbiology. 2002;68:2188–2197. doi: 10.1128/aem.68.5.2188-2197.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Kļaviņš M, Rodinov V, Kokorīte I, Kļaviņa I, Apsīte E. Long-term and seasonal changes in chemical composition of surface waters in Latvia. Environmental Monitoring and Assessment. 2001;66:233–251. doi: 10.1023/A:1006352015230. [DOI] [PubMed] [Google Scholar]
  31. Latkovska I, Apsīte E. Long-term changes in the water temperature of rivers in Latvia. Proceedings of the Latvian Academy of Sciences. Section B. Natural, Exact, and Applied Sciences. 2016;70:78–87. doi: 10.1515/prolas-2016-0013. [DOI] [Google Scholar]
  32. Libiseller C, Grimvall A. Performance of partial Mann–Kendall tests for trend detection in the presence of covariates. Environmetrics. 2002;13:71–84. doi: 10.1002/env.507. [DOI] [Google Scholar]
  33. Lindström ES, Kamst-Van Agterveld MP, Zwart G. Distribution of typical freshwater bacterial groups is associated with pH, temperature, and lake water retention time. Applied and Environmental Microbiology. 2005;71:8201–8206. doi: 10.1128/aem.71.12.8201-8206.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Lipp EK, Vincent KR, Rodriguez-Palacios C, Farrah SR, Rose JB. The effects of seasonal variability and weather on microbial. Fecal pollution and enteric pathogens. Journal Estuaries and Coasts. Estuaries. 2001;24:266–276. doi: 10.2307/1352950. [DOI] [Google Scholar]
  35. Mallin MA, Williams KE, Esham EC, Lowe RP. Effect of human development on bacteriological water quality in coastal watersheds. Ecological Applications. 2000;10:1047–1056. doi: 10.1890/1051-0761(2000)010[1047:EOHDOB]2.0.CO;2. [DOI] [Google Scholar]
  36. McFetters GA, Stuart DG. Survival of coliform bacteria in natural waters, field and laboratory studies with membrane filter chambers. Applied Microbiology. 1972;245:805–811. doi: 10.1128/AM.24.5.805-811.1972. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Niewolak S. The evaluation of the contamination degree and the sanitary and bacteriological state of the waters in the Czarna Hańcza River in the region of Suwałki and the Wigry National Park. Polish Journal of Environmental Studies. 1998;7:229–241. [Google Scholar]
  38. Páll E, Niculae M, Kiss T, Şandru CD, Spînu M. Human impact on the microbiological water quality of the rivers. Journal of Medical Microbiology. 2013;62:1635–1640. doi: 10.1099/jmm.0.055749-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Paerl HW, Dyble J, Moisander PH, Noble RT, Piehler MF, Pinckney JL, Steppe TF, Twomey L, et al. Microbial indicators of aquatic ecosystem change: Current applications to eutrophication studies. FEMS Microbiology Ecology. 2003;46:233–246. doi: 10.1016/S0168-6496(03)00200-9. [DOI] [PubMed] [Google Scholar]
  40. Phanuwan C, Takizawa S, Oguma K, Katayama H, Yunika A, Ohgaki S. Monitoring of human enteric viruses and coliform bacteria in waters after urban flood in Jakarta, Indonesia. Water Science and Technology. 2006;54:203–210. doi: 10.2166/wst.2006.470. [DOI] [PubMed] [Google Scholar]
  41. R Core Team. 2016. R: A language and environment for statistical computing.
  42. Randall GW, Mulla DJ. Nitrate nitrogen in surface waters as influenced by climatic conditions and agricultural practices. Journal of Environmental Quality. 2001;30:337–344. doi: 10.2134/jeq2001.302337x. [DOI] [PubMed] [Google Scholar]
  43. Republic of Latvia Cabinet. 2002. Regulation regarding the quality of surface waters and groundwaters. Retrieved 8 May, 2020, from https://likumi.lv/ta/en/en/id/60829.
  44. Sood A, Singh KD, Pandey P, Sharma S. Assessment of bacterial indicators and physicochemical parameters to investigate pollution status of Gangetic river system of Uttarakhand (India) Ecological Indicators. 2008;8:709–717. doi: 10.1016/j.ecolind.2008.01.001. [DOI] [Google Scholar]
  45. Springe G, Lukstina G. Water services in Riga city in different socio-economic situation and changing population. In: Juutti P, Mattila H, Rajala R, Schwartz K, Staddon C, editors. Resilient water services and systems: The foundation of well-being. London: IWA Publishing; 2019. pp. 85–94. [Google Scholar]
  46. Stålnacke P, Grimvall A, Libiseller C, Laznik M, Kokorite I. Trends in nutrient concentrations in Latvian rivers and the response to the dramatic change in agriculture. Journal of Hydrology. 2003;283:184–205. doi: 10.1016/S0022-1694(03)00266-X. [DOI] [Google Scholar]
  47. Strathmann M, Horstkott M, Koch C, Gayer U, Wingender J. The River Ruhr–an urban river under particular interest for recreational use and as a raw water source for drinking water: The collaborative research project “Safe Ruhr”—microbiological aspects. International Journal of Hygiene and Environmental Health. 2016;219:643–661. doi: 10.1016/j.ijheh.2016.07.005. [DOI] [PubMed] [Google Scholar]
  48. Tyrrel SF, Quinton JN. Overland flow transport of pathogens from agricultural land receiving faecal wastes. Journal of Applied Microbiology. 2003;94:87–93. doi: 10.1046/j.1365-2672.94.s1.10.x. [DOI] [PubMed] [Google Scholar]
  49. UNECE 2019. Fourth reporting exercise under the Protocol on Water and Health. Summary report of Latvia in accordance with article 7 of the Protocol on Water and Health. Retrieved 8 May, 2020, from https://www.unece.org/fileadmin/DAM/env/water/Protocol_reports/reports_pdf_web/2019_reports/Latvia_Protocol_report_4th_cycle_3May19.pdf.

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