1. Introduction
The link between extreme weather events and waterborne disease outbreaks is well established in the literature [
1,
2,
3,
4]. With the imminent threat of changing climate variables on the quality of freshwater resources, water treatment plants that are heavily dependent on surface water bodies are particularly vulnerable. Microbial deterioration of surface water sources occurring during extreme precipitation events and the resulting impact on the integrity of water treatment plants and disease outbreaks have been widely investigated [
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16]. Furthermore, increasing numbers of natural organic matter in surface water sources due to changes in precipitation patterns and catchment attributes [
17] may challenge the efficacy of water treatment processes, enhance regrowth of bacteria in the water distribution network, and result in waterborne disease outbreaks [
18,
19,
20,
21].
The impact of these extreme events on water supply systems is likely to be more pronounced in temperate countries, such as Norway, where seasonal variations and increases in temperature and precipitation are expected in the future. According to the Norwegian Green Paper on Climate Change Adaptation, the mean annual temperature in Norway is expected to increase from 2.3 °C to 4.6 °C by 2100, with the highest and lowest increases expected in the winter and summer months, respectively. During the same period, annual precipitation is expected to increase from 5% to 30% with major seasonal variations and increased the frequency of torrential rains [
22]. These future changes in precipitation events and temperature will lead to significant changes in water quality parameters, including the presence of microbial pathogens [
23]. A study on the microbial quality of Norwegian surface water bodies showed an association between rainfall and increased loads of fecal indicator organisms into surface waters [
24]. A recent study has also shown a significant association between microbial organisms in Norwegian raw water sources and changes in land use, and rainfall in the catchment [
25].
Apart from rainfall, water temperature variations have been shown to affect the growth and survival dynamics of microbial organisms in raw water sources [
26,
27,
28,
29]. Variations in water temperature, which is controlled by factors such as air temperature, cloud cover, solar radiation and other geomorphometric factors [
30,
31], affect the hydrodynamic distribution of microorganisms through increased stratification [
30,
31,
32,
33]. In addition, the onset of heavy rains causes destratification, altering the movement of microbial organisms-bearing particles within the waterbody [
34]. Short term and long-term stratification and destratification mainly resulting from temperature changes may lead to water quality deterioration [
35,
36,
37]. Accordingly, the development of resilient and adaptable management strategies necessary for the provision of safe drinking water in Norway requires a quantitative estimation of the potential impact of local projections of weather parameters, such as temperature and precipitation, on the quality of raw water sources.
There is increasing reliance on models and forecasts for planning and decision-making for effective management of drinking water facilities [
38,
39,
40]. Among the variety of models, properly calibrated hydrodynamic and water quality models provide reliable means of tracking primary sources of microbial contamination in drinking water sources [
41,
42,
43]. In addition, these models can describe the transport of contaminants within watershed and their fate once in the waterbody [
44,
45,
46,
47]. When calibrated, hydrodynamic models can provide reliable information about the sources of microbial pathogens within catchment of a water source as well as help in identifying which source has the potential of posing the greatest threat to the microbial quality of drinking water source at the intake point. For effective planning of measures to mitigate potential health risks associated with microbial contamination of raw water sources, an assessment of potential levels of fecal indicator organisms, such as
E. coli, in various sections of the waterbody at a particular time is imperative.
The overall aim of this study was to apply hydrodynamic modeling to assess the impact of climate change on the microbial quality of the raw water source of a water treatment plant in Norway. The specific objectives were (1) to determine the impact of discharge from the main tributaries of the lake on occurrence of E. coli at the raw intake point of the water treatment plant; (2) to assess the distribution of temperature in the lake and the effect on E. coli; (3) to evaluate how changes in climatic variables in 2045 and 2075 can affect the mixing conditions and temperature in the lake; and (4) to evaluate the effects of changes in the mixing conditions on the occurrence of E. coli at the raw water intake point. Developing a climate-driven microbial quality hydrodynamic model will not only provide insight into potential effects of climate change on the microbial quality of raw water, but also help managers of the water treatment plants adequately plan long-term mitigation strategies necessary for the provision of safe drinking water to the public. Further, as water treatment plants are usually designed and built with a long-life span ranging from 25 to 30 years, understanding climate impacts is critical to developing appropriate management strategies. Similar water treatment plants can, therefore, apply the method to assess the impact of climate change on their drinking water sources.
4. Discussion
The hydrodynamic model simulation showed the overall effect of the E. coli discharged from the streams on the E. coli level throughout the lake. The observed E. coli numbers used as input to the model resulted in a much lower level at the water intake when compared to the measured numbers at the water treatment plant. The key sources of E. coli load to the lake identified during the sampling were the Brusdalen and Slettebakk streams. However, the results of the model suggest that together with the four smaller streams and the additional discharge points created in the unsampled sections, discharge from the tributaries of the lake may have a low effect on the numbers of E. coli at the raw water intake in the lake. It is, therefore, likely that other unidentified sources of E. coli discharge into the lake are more dominant. For instance, households located on the western section of the lake (where the intake zone of the water treatment plant is located) could be important sources, although no overland streams were identified in this section of the catchment area during the sampling period. In addition, sewage pipes traverse this section of the lake, and there is the possibility of leakages from these pipes. It is, therefore, necessary to closely examine the pipes for potential leakages.
The model results also showed that circulation occurring in the lake in the spring and autumn increased the chances of
E. coli reaching greater depths in the lake. Moderate rainfall at the turn over the period following the long summer season partly account for the sudden rise in the numbers of
E. coli towards the end of November, since they favor the accumulation and transport of organic and inorganic matter into the lake through elevated stream flows. This result is consistent with a related study that reported high numbers of
E. coli in a lake in Sweden during the same period and lowest levels in summer [
65]. Further, the temperature distribution in the lake (
Figure 5) indicates that considerable amount of vertical mixing of the lake water occurred during this period, thereby increasing the transport of the bacteria to the water intake point of 35 m below surface. Moreover, high-velocity wind currents, which characterize this season, enhance the circulation of water in the lake and this could increase the likelihood of contaminants reaching the intake depth.
Despite the overall very low
E. coli numbers predicted at raw water intake zone in summer, the cross-sections indicate higher numbers potentially occurring at the same depth in the eastern section of the lake close to the dominant contamination sources identified in the sampling (Slettebakk and Brusdalen streams) as shown in
Figure 5B2. The high numbers in that part may be a reflection of the high levels in the tributaries. Potential sources of
E. coli, such as wild animals and birds in the catchment of the lake, are more active in this season and may have contributed to the observed numbers in the streams. Further, although the inactivation rates of microbial organisms in surface water generally occurs faster with increasing temperature, this dependency can be affected by site-specific conditions and can vary among different water sources [
28,
66]. It is, therefore, possible that typical surface water temperatures in summer in the study region create favorable conditions for the survival of
E. coli in the streams. While high numbers of
E. coli in the streams may be associated with catchment precipitation through increased flows and high sediment loads in spring and autumn, low flows in summer could lead to shorter travel distance and longer settling time in the streams and these may affect the numbers of microorganisms in surface water [
67]. Nonetheless, the output time series indicated generally very low numbers in the lake during the summer period (
Figure 6F). This also agreed with the observation in 2017. It has been reported that other factors including lower loading of fecal materials into surface water occurring during the summer season as well as potentially less viability of fecal indicator organisms at higher water temperatures may contribute to this observed trend [
68]. In addition, increased solar radiation in summer is reported as an important contributor to the inactivation of indicator bacteria in large freshwater bodies, such as lakes [
69,
70]. Moreover, the thermoclines in the lake during this season separate the epilimnion from the hypolimnion, restricting water circulation and the spread of contaminants in lakes [
71].
The model results generally indicate the pattern of water temperature and
E. coli in 2045 and 2075 is similar to the base year (2017). However, an increasing trend of water temperature was observed across all the seasons. Water temperature at the intake depth in spring, summer, autumn and winter rises by an average of 0.43 °C, 1.2 °C, 1.34 °C, 0.89 °C, respectively, by 2075 relative to 2017. The numbers of
E. coli at the water intake point in future may remain at levels close to the numbers presently observed in summer. The numbers in spring and autumn may, however, be higher than present levels, with the possibility of higher numbers in winter due to the late start of the autumn circulation in the future. It is worth noting that the predicted numbers of
E. coli at the raw water intake shown in
Figure 6F only indicate the changes in the numbers relative to the present levels due to projected changes in the weather variables (air temperature and precipitation) and/stream flow. This is because the model already indicated that the discharge from the sampled streams has low effect on the occurrence of the fecal indicator bacteria at the raw water intake point (
Figure 4). Thus, based on current projections of precipitation and air temperature in the study region, plans regarding the management of the drinking water facility should take into account the possibility of higher
E. coli levels occurring in the water.
The results of this study provide useful assessments of the effect of climate change on the microbial quality of the raw water source for the treatment plant. However, the extensive use of climate data introduces considerable limitations in the use of the results, therefore management decisions that will be taken based on the results should consider such limitations. The major sources of uncertainties include the historical observations of the weather variables used in both the previous hydrological models and the hydrodynamic model, the climate projections, as well as the model formulations and their calibrations in this study. While uncertainties in the predicted stream flow and
E. coli numbers were accounted for in the previous hydrological model [
49] that provided additional inputs for this study, the number of discharge points (streams) included in the model was only a small fraction of the tributaries, most of which are either transient or cannot be easily assessed for regular sampling due to the steep topography. Thus, discharges from those sections could be higher both presently and, in the future, potentially affecting the numbers that reach the raw water intake zone. In addition, the method applied in this study only accounts for the status quo scenarios that assume all other things in the catchment of the lake will remain the same in the future. Although the water treatment plant managers plan to maintain current regulations to limit further development and recreational activities within the catchment, incidents, such as extreme precipitation events, combined sewer overflows, or bursting of sewer pipes, could potentially lead to sudden increases in the numbers of microorganisms discharged into the lake. However, such scenarios have not been accounted for in the present study.