1. Introduction
Water is a vital liquid for living organisms and it is used in different human activities; the increasing population and consequent economic activities are leading to water quality deteriorations and water quantity reductions. These changes generate negative impacts on living organisms, ecosystems, and their interactions [
1]. Pollution issues have been observed in river water, mainly in the least developed countries. Scarcity problems and social inequalities worsen the situations, and authorities are trying to preserve the natural water quality. For example, the rapid growth of urban areas and the associated economic activities in some regions of Latin America and Asia have increased so much that governments are no longer able to develop water treatment facilities or even keep the existing ones operating.
One of the main problems involves discharges in superficial eater bodies [
2,
3]. Discharge sources are factors that influence the water quality composition, making it susceptible to pollution, and, therefore, reducing water’s capacity to attenuate or degrade waste and contaminants, changing the composition of water components. The natural origin of the discharge shows that water is affected by weather, minerals present in the soil, and atmospheric depositions of compounds, such as dust, wind, etc. [
1]. Human origins of the discharges are mainly due to human discharges that contain chemicals used in agricultural households and industrial activities, such as pesticides, herbicides, fertilizers, organic solvents, and degreasing/disinfecting compounds. These human-originated discharges have altered water quality worldwide, leading to quality depletion of shallow water [
1,
4].
The influence of human activities and natural effects impact water quality in surface bodies and the quality measurements are not static values. Due to their systemic nature, water quality changes with time and space; therefore, constant monitoring activity is essential. Water quality depends on physical, chemical, and biological properties; thus, it is crucial to monitor such changes, enabling the detection of temporal and spatial variabilities [
1,
5,
6]. Water quality can be associated with changes in different parameters, such as nutrient concentrations, pH values, sediment loads, dissolved oxygen levels, and the addition of compounds, such as oil, grease, mercury, trace metals, pesticides, and nonmetallic toxins that harm humans and wildlife, which depend on these resources. The water quality index (WQI), is a powerful parameter that is helpful in the evaluation [
1,
5,
7].
Information about water quality can be evaluated with different parameters, such as nutrient concentrations, pH values, sediment loads, dissolved oxygen levels, and the presence of to toxic compounds. Even when most of the microorganisms present in the environment are favorable for the environment, microbial pollution mainly originates from urban contamination and agriculture. The presence of these organisms induces diseases or premature death in humans and livestock. In most downstream communities, people near these polluted areas, whether due to housing or recreational or work activities, are exposed to microbial pathogens [
8]. In these cases of microbial contamination, and due to variations in time or in different sites within the same water body, some parameters are employed and analyzed using different methodologies to test the water quality. The most common method is to detect fecal contaminants; coliforms are used as the primary indicators of pathogenic microorganisms [
1,
9,
10].
It is essential to monitor water quality to estimate the impact of activities and discharges on water bodies, or to determine their possible usages. Nevertheless, common values of the individual parameters are not sufficient or easy to understand and provide information about the global water quality [
11,
12,
13]. There are tools that can be used to determine water quality trends and values, but some are dynamic modeling methods or implement multivariate statistics. Cluster analyses are used to order variables or data in similar groups, and factor analyses are practical [
14].
Authorities and researchers have recommended the use of an expression that is able to provide information about the global quality of water; this parameter is called the WQI [
11,
15]. The WQI is a powerful parameter, proposed by Horton in 1965, which represents water quality with a single value. It englobes a large number of physicochemical and biological parameters, ranging from 3 to 20, and it eases their interpretations as they are converted into a simple value (formed by weights assigned to the employed variables) [
8,
11,
16]. The WQI value is basically a number that allows contrasting the values in general; therefore, it is commonly used to classify, assign, and determine water pollution [
14,
17,
18], and is adapted and improved according to the application or the region [
13]. When the parameters are selected adequately, they can help to prevent repetitive and unnecessary information, making it easier to estimate and use WQI [
13,
19].
However, toxicity information is not included in WQI studies because water-containing substances that are harmful to aquatic life, animals, and humans are excluded for this measurement [
8]. Some researchers have addressed the problem of the evaluation of water quality by using ecological indicators or the use of bioindicators, based on the fact that physical and chemical properties do not always offer entire perspectives of the water quality [
9,
11,
20,
21,
22]. Water quality, which is also known or related to ecological health, can also be represented, such as the responses of different types of aquatic organisms. Special attention is given to those that demonstrate more sensitivity to the conditions in the environment, such as the most employed diatoms, zooplankton, and macroinvertebrates [
23]. Bioindicators are sometimes used by sampling the population of the species from the analyzed place; for example, coral [
24], diatoms [
25],
Allocapnia,
Glossosoma, and
Hesperoperla [
21], or by taking water samples ex situ for further evaluation with sensitive organisms.
Bioassays are widely employed to evaluate surface water and even discharges. They are used as complex or multiparametric assays because they comprise a series of parameters, and because they are affordable, easier to perform, and take little time [
26]. One of the most common organisms employed for evaluating toxicity is
Daphnia magna [
27], due to its sensitivity to toxic substances, short reproduction span, adaptability, and small space required for maintenance and lab tests [
26]. Several studies have evaluated the responses of bioindicators and their responses to factors. For example,
Daphnia’s death or immobility has been tested for pH [
28], conductivity, salinity [
27], and potassium dichromate [
29]. However, the combination of factors also influences the ecological impacts of biological indicators, mainly in complex waters; for example, in surface water where there are discharges that make a complex mixture of compounds, such as in seawater, lakes, or rivers.
This study analyzed and characterized pollution in the El Pueblito River, which is located in Corregidora, Queretaro, Mexico. In 2008, a hydrological and environmental diagnostic was performed, and a program focused on recovering the river was created (with the diagnostic results as the basis). One of the strategies to recover the space and avoid pollution was to deliver environmental education to the population that inhabited areas near the river. In 2011, a project that focused on planning and mitigating pollution on El Pueblito River was implemented. Several important milestones were achieved: the installation of biofilters, the placing of some structural works, such as rock traps for stabilization, restoration of the sinuosity of the river, and the use of deflectors [
30].
In this sense, the main objective of this work was to compare the water quality obtained by physicochemical parameters with bioassays. The monitoring of water quality employing physicochemical parameters of El Pueblito River will be translated to WQI. Bioassays, such as the Daphnia magna survival rate and Sorghum bicolor seed germination rates, were carried out. Finally, an analysis of the data was performed to establish the interrelations between physicochemical parameters, the relationship between physicochemical parameters and bioindicators, and the relationship between WQI and bioindicators throughout the river.
5. Conclusions
The results of this study indicate that the upstream analyzed sites (MAN, BAT, and STA) in El Pueblito River presented good water quality, but downstream of RAS, PIR, BAR, and PUE, the water quality decreased slightly. The results of the analysis at the last point downstream (PUE) showed a slight natural attenuation of pollution, but it did not affect water quality. Due to the high pollution levels, even with attenuation, the water quality remained poor. The physicochemical parameters at different sites of the El Pueblito River showed evidence of higher levels of contamination downstream after the discharge points of water into the river (at PIR and RAS). Parameters, such as COD, BOD, PT, TS, and TDS, are evidence of this pollution. The same behavior was observed with the results of LC50 with Daphnia magna and the global parameter WQI, with both methods confirming the results obtained by individual factors. Furthermore, sorghum germination did not correlate with the rest of the values, perhaps due to the presence of PT and other compounds that were employed as substrates to the germination and growth of seeds (promoting the growth). Thus, in this case, it was not a good bioindicator to correlate with the pollution of the river. There is a correlation between individual parameters, e.g., COD, BOD, VSS, PT, showing consistency, and the same tendency between them and biological indicators, such as LC50 and total coliforms. We also determined that in the El Pueblito River, for WQI with very bad quality, LC50 values were under 18% dilution. With this evidence, it is important to communicate that LC50 is a good, fast, and affordable indicator that can be associated with higher or lower pollution in El Pueblito River. Otherwise, in the conditions of our experiments, there was no good numerical correlation index to associate WQI values with LC50; perhaps a clear correlation could be performed by increasing the number of dilutions at the LC50 assays, allowing to obtain more information. One of the limitations of this work is that the sampling was performed in the rainy season; for future research, it will be important to consider the whole year.