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Article

Coastal Bathing Water Evaluation Under Contrasting Tourism Pressures at Herradura Bay (S-W Mediterranean)

by
Miguel María Granados-Fernández
1,
Salvador Arijo
2,
Andreas Reul
1,*,
Francisco Guerrero
3,
Juan Diego Gilbert
3,
Jorge García-Márquez
2,
Begoña Bautista
1 and
María Muñoz
4
1
Departamento de Ecología y Geología, Universidad de Málaga, Campus de Teatinos, s/n, 29071 Malaga, Spain
2
Departamento de Microbiología, Universidad de Málaga, Campus de Teatinos, s/n, 29071 Malaga, Spain
3
Departamento de Biología Animal, Biología Vegetal y Ecología, Universidad de Jaén, Campus de Las Lagnillas, s/n, 23071 Jaen, Spain
4
Departamento de Didáctica de la Matemática, de las Ciencias Sociales y de las Ciencias Experimentales, Universidad de Málaga, Campus de Teatinos, s/n, 29071 Malaga, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(21), 9792; https://doi.org/10.3390/su17219792
Submission received: 12 September 2025 / Revised: 21 October 2025 / Accepted: 30 October 2025 / Published: 3 November 2025
(This article belongs to the Special Issue Biodiversity, Biologic Conservation and Ecological Sustainability—2nd Edition)
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Versions Notes

Abstract

Coastal water quality is crucial for ecosystem services, supporting biodiversity and tourism. However, high tourist influxes often overwhelm wastewater treatment plant (WWTP) capacities, leading to untreated discharge and eutrophication, which severely impacts bathing water. Water quality monitoring is currently limited to selected points at the beach and oceanographic sampling, which requires depths >20 m offshore, leaving a gap of measurements between 1 and 50 m from the beach. To resolve this gap, our study proposes a low cost-effective sampling and monitoring method by using a kayak with a submersible fluorometer FlowCAM, as well as fecal bacteria detection and quantification. The kayak sampling was carried out during high- and low-tourism seasons in coastal bathing waters surrounded by Marine Protected Areas. The results show a patchy phytoplankton distribution, with chlorophyll a concentration up to 5.5 μg/L, indicating local fertilization. The observed floating organic matter patches were fecal bacteria free, while effluents of the WWTP to the Jate river and shore exceeded the legal limits for bathing water. These results suggest that wastewater treatment was overwhelmed during the high-tourism season, likely discharging wastewater into the river that flows into the shore. These findings are discussed in a sustainable development and socioeconomical context.

1. Introduction

Coastal zones are universally recognized as important ecological and socio-economic interfaces, serving as hotspots of biodiversity, economic activity, and homes to a significant portion of the global population for centuries [1,2]. Nevertheless, these areas exhibit high vulnerability to the effects of environmental changes [3,4] and other types of disturbances derived from human development [5]. The increasing human footprint in coastal urban areas severely degrades environmental quality and diminishes biodiversity [6], posing a significant threat to socioeconomic sectors, particularly maritime and coastal tourism, which support the economies and livelihoods of these regions. This tourism, inherently reliant on the natural environment and its resources, is paradoxically a major contributor to environmental deterioration, such as resource depletion, water and air pollution, plastic pollution, light and sound pollution, and subsequent species disturbance and extinction [6,7]. This is particularly true for the Mediterranean basin, a region recognized for its unique biodiversity, rich cultural heritage, and important role in the regional economies. However, the long-term conservation of these natural and economical important coastal ecosystems is increasingly jeopardized. Therefore, understanding and mitigating these impacts are crucial for the sustainable future of coastal regions, requiring effective management strategies to ensure the health and productivity of these vital areas.
The tourism sector leads to economic growth, development, and job creation worldwide. In Spain, tourism contributes 12.8% to GDP, with the sun and sand pairing sector being the most important. Tourism development led to coastal construction and extensive urban development on the Andalusian coast, which has been significant over the last 50 years. In fact, the European Commission launched an investigation into more than 250 urban projects that received a negative opinion from the competent authorities in water management and river basins, placing the projects in violation of the Water Framework Directive, 2000/60/EC [8]. However, concerns about the compatibility between tourism and the environment have been evidenced by the United Nations’ Environment Programs [9,10] and recently in the 2030 Agenda [11]. Coastal tourism requires bathing water to have a minimum quality standard to guarantee users’ health [12,13]. Regulation of water quality levels by controlling the limits of a set of physical, chemical, and microbiological parameters (specifically fecal enterococci and Escherichia coli) is necessary to control water quality and protect coastal waters from deterioration [14]. Along the Spanish and Mediterranean coastlines, Andalusia (southern Spain) has the highest number of contaminated beaches with illegal constructions [15]. Tourism analysis from 2019 to 2025 shows that the coastal population increased by a factor of three during the high season. This increase in the population usually exceeds the wastewater treatment plant (WWTP) capacity of the coastal villages, causing environmental problems in the coastal water. Nutrient discharge from the WWPT into the marine environment can significantly contributes to eutrophication and algae blooms in the coastal waters [16] and red tides [17].
The present study aims to evaluate sewage effluents in a coastal area in the south of Spain (La Herradura, Andalusia) using an analysis of key environmental variables, including chlorophyll-a concentration, heterotrophic bacteria, and Escherichia coli. Sampling was carried out at two distinct periods: (1) before and (2) during the period of high-tourism affluence.

2. Materials and Methods

The research was carried out in the Bay of La Herradura (Granada), which is located next to the MPAs of Maro-Cerro Gordo and Punta de la Mona (Figure 1).
Two types of sampling strategies were developed. The first consisted of bi-weekly sampling of fixed coastal stations (Stn 1, Stn 2, and Stn 3; Figure 1) during seven months, starting in winter (18 January 2019) and ending in summer (24 July 2019). The second sampling was conducted using a kayak, encompassing surface water sampling in stations throughout the entire bay of La Herradura (Stn 4, Stn 5, Stn 6, Stn X1, and Stn X2, as shown in Figure 1). This last sampling occurred during two consecutive weeks: before the Easter holydays (12 April 2019) and during the Easter holydays (20 April 2019). This timing was chosen to assess the effects of the increased tourism pressure. During the kayak survey, the phytoplankton concentration and composition were continuously measured (kayak transect; Figure 1).

2.1. Phytoplankton Sampling

To locate algal blooms at the shoreline, bi-weekly samplings were carried out during seven months at three coastal stations (Stn 1, Stn 2, and Stn 3; Figure 1) distributed along La Herradura beach (36°44′06″ N, 3°44′14″ W) (southern Spain). The water temperature and phytoplankton composition were measured and analyzed at each sampling station using a submersible fluorometer with five-point excitation spectra (BBE-Moldaenke FluoroProbe, Schwentinental, Germany [18]). The submersible fluorometer discriminated between four main phytoplanktonic groups (i.e., diatoms and dinoflagellates together, cyanobacteria, green algae, and cryptophytes) based on the relative fluorescence intensity of Chl a at 680 nm, following sequential light excitation by 5 Light-Emitting Diodes (LEDs) emitting at 450, 525, 570, 590, and 610 nm [18,19]. Accordingly, Total Chlorophyll a (TChl a) was subdivided in relative contribution of the phytoplankton groups to TChl a. Additionally, the fluoroprobe measured yellow substances (Dissolved Organic Matter, primarily leached from decaying detritus).
To estimate phytoplankton abundance and size, 1 L water samples were taken and transported within 3 h in cold and dark to the lab. In the laboratory, phytoplankton was concentrated on a 20 µm mesh and recovered in 20 mL. Immediately afterwards, each sample was passed through a FlowCAM (Benchtop VS4C/488/DSP; Fluid Imaging, Scarborough, ME, USA) equipped with a 100 μm flow cell and a 100-fold magnification (10 × objective). The analysis was performed in the auto-image mode, where individual pictures of each particle in the vision field were taken. Afterwards, phytoplankton abundance, size, and biovolume were estimated by manual reprocessing of the original data fields [20,21,22] and size spectra, with size classes log2 constructed according to Reul et al. 2014 [22].
For the kayak sampling, zig-zag surveys were also conducted using a kayak towing the immersive fluorometer (Figure 1) to determine the relative contribution of different phytoplankton groups and the patchy distribution of phytoplankton in the bay.

2.2. Bacterial Sampling

To assess the potential contamination of coastal waters by urban wastewater discharged into the surrounding environment, aliquots of seawater were collected at four coastal stations (Stn 1, Stn 2, Stn 3, and Stn 4; see Figure 1). Two sampling periods were selected to determine fecal contamination: one during the low-touristic season (12 April 2019) and another during the high-touristic season in Easter (20 April 2019).
The samples were transported in cold and dark conditions until they were processed in the laboratory. Different volumes of water (1, 10, and 100 mL) were filtered through sterile nitrocellulose filters (47 mm diameter, 0.45 µm pore size; Millipore Corp., Bedford, MA, USA). For the determination of Escherichia coli concentration in the water, the filters were placed on plates with Chromocult agar (Merck-Millipore, Darmstadt, Germany) and incubated at 37 °C for 24 h (according to ISO 9308-1:2014 [23]). To determine the fecal streptococci concentration in the water, the filters were placed on Slanetz–Bartley agar (Merck-Millipore, Darmstadt, Germany) and incubated at 37 °C for 48 h (according to ISO 7899-2:2000 [24]). After incubation, blue colonies were counted in Chromocult agar plates (corresponding to Escherichia coli), while red colonies were counted in Slanetz–Bartley agar plates (corresponding to fecal streptococci).
In addition to the coastal stations, other offshore stations were sampled for bacteria. During the kayak sampling, Stn 5, Stn 6, Stn X1, and Stn X2 were added, and aliquots of seawater were collected (Figure 1). The location of Stn 5 and Stn 6 were chosen to cover the entire bay, in accordance with the Bathing Water Directive [25] and the Spanish Regulation [14], which requires sampling to be performed at the exit of the spillway. Two stations were sampled between the beach and the submarine wastewater outfall (Stn. 5 and Stn. 6; see Figure 1) and two other stations were sampled offshore, west and east of the outfall (Stn X1 and Stn X2; see Figure 1). The sampling stations X1 and X2 coincided with the floating organic material detected during zig-zag sampling with the kayak. In addition, two other samples were taken: one from the spillway of the wastewater treatment plant (WWTP) into the Jate stream (Appendix A, Figure A1), and another at the Jate river mouth (Figure 1).
Additionally, information on fecal bacteria was downloaded from the Nayade [26] database at the sampling stations (Nayade1 and Nayade2, Figure 1).

2.3. Statistics

The data obtained for bacterial concentration and Chl a underwent statistical analysis using ANOVA after assuring normality and homogeneity of variance by log transformation. Additionally, a post hoc Tukey test (with a p-value of 0.05 as reference), which, according to [27], finds and separates family groups, subjected the sampling data by pairwise comparison.

3. Results

3.1. Temporal Evolution of Temperature and Phytoplankton at the Coastal Stations

During the coastal sampling, water temperature oscillated between 14 °C and 16 °C from January to June and increased up to 21 °C from June to the end of July.
TChl a concentration showed high variability, ranging between 1 and 5.5 µg/L. The highest TChl a concentration was obtained on the 9th of July at Stn 2. The mean TChl a concentration over the whole period was highest at Stn 2 (2.43 ± 1.17 µg/L), followed by Stn 3 (1.88 ± 0.80 µg/L) and Stn 1 (1.82 ± 0.73 µg/L).
The mean relative contribution of the four phytoplanktonic groups was not different among the sampling stations (ANOVA p > 0.05). Thus, the mean relative contribution to TChl a concentration was always the highest for green algae (59.47 ± 20.31%), followed by diatoms and dinoflagellates (24.51 ± 28.89%), cyanobacteria (14.89 ± 18.52%), and cryptomonads (1.12 ± 2.03%).
High TChl a concentration peaks were obtained at Stn 1 (4 ± 0.38 µg/L) at the beginning of the sampling period (1 February 2019) and Stn 2 (5.5 ± 0.05 µg/L) at the end of the sampling period (9 July 2019) (Figure 2A). In the first case, the high TChl a concentration was associated with an increase in cyanobacteria (Figure 2B, 1 February 2019) and in the second case to the proliferation of diatoms (Figure 2C, 9 July 2019). At sampling station 3, TChl a peaks larger than 3 µg/L were observed both on 12 April 2019 and 17 May 2019, coinciding with the increasing contribution of diatoms to total Chl a (Figure 2D).

3.2. Spatial Distribution of Phytoplankton During the First Kayak Sampling

A patchy distribution of the TChl a concentration was observed during the kayak zig-zag survey through the bay. The values ranged between 0.7 and 1.6 TChl a µg/L, with the highest concentration obtained in the southwestern part of the bay (circle in Figure 3) and in the middle of the bay, where the marine outfall was located (Figure 1 and Figure 3). Temperature showed an opposite distribution to TChl a, whereas cyanobacteria were more abundant in warmer coastal waters (square in Figure 3).
The main contributors to the TChl a concentration were green algae (ranging between 0.36 and 1.36 Chl a (μg/L) followed by dinoflagellates and diatoms (0.02 and 0.45 μg Chl a μg/L). Both groups were positively correlated with the TChl a concentration (Table 1). However, TChl a concentration correlated negatively with the yellow substances.
In contrast, cyanobacteria were negatively correlated with green algae, cryptophytes, and diatoms and dinoflagellates (Table 1). On the other hand, the total TChl a, green algae and diatoms and dinoflagellates correlated negatively with temperature and positively with transmittance.

3.3. Microphytoplankton Biovolume, Abundance, and Size Structure During First Kayak Sampling

In addition to the changes in the taxonomic groups of phytoplankton (diatoms and dinoflagellates, green algae, cyanobacteria, and cryptomonads), changes in the abundance, biovolume, and size structure of microphytoplankton of 20–100 μm Equivalent Spherical Diameter (ESD) were also observed (Figure 4).
According to the low TChl a concentration at the river mouth in Stn 4 and Stn 1, the abundance and biovolume of microphytoplankton were also very low. Stn 2 showed high abundance and relatively low biovolume, Stn 3 was characterized by high abundance and biovolume, while at Stn 6, lower abundance of cells coincided with higher biovolume (Figure 4).
Thus, the phytoplankton communities at these sampling stations were different in terms of size distribution, as observed in the Size-Abundance-Spectra (SAS) in Figure 5. The community at Stn 4 had the lowest abundance among all size classes. The community at Stn 2 had higher abundances in the smaller size classes, but lower abundances in the larger size classes than the communities at Stn 3 and Stn 6. Therefore, at Stn 3 and Stn 6, the increased abundance was accompanied by a relatively low biovolume (Figure 4). Stn 6 was characterized by higher abundance of large-sized cells, but lower abundances of smaller-sized phytoplankton than at Stn 3 and Stn 2. Thus, at station Stn 6, we observed a high biovolume with relatively low abundance (Figure 4). Finally, the microphytoplankton at Stn 3 showed high abundance throughout the whole SAS and exhibited the highest biovolume and abundance of all sampling stations.
The results of the ANOVA and Tukey post hoc test among the six classes of the different SAS showed significantly lower abundances of cells in the 20–25 µm ESD size class (Biovolume Log10 = 3.6–3.9 μm3) for Stn 4 and Stn 6 compared to Stn 2 and Stn 3. In the 31–79 µm ESD size class (Biovolume Log10 = 4.2–5.41 μm3), only Stn 4 had less abundant cells than Stn 2, Stn 3, and Stn 6. Finally, in the 79–100 µm ESD size class (Biovolume Log10 = 5.41–5.71 μm3), only three size spectra remained.

3.4. Bacteriological Analysis

The bacterial quantification changed according to the sampling stations and between the low- and high-tourism seasons. At the Spillway and Stn 4 sampling stations, the bacterial counts (E. coli and fecal streptococci) were higher during the high season than during the low season. In Stn 4, E. coli and fecal streptococci counts were ten and thirty-three times higher during the high season with respect to the low-season values. At the spillway, E. coli and fecal streptococci counts were sixty-six and four times higher during the high season than during the low season, respectively (Table 2). The legal threshold [25,26] was exceeded for fecal streptococci at Stn 4 during the high-tourism season and for both fecal streptococci and E. coli counts at the spillway during the high-tourism season.
In the case of fecal streptococci, there were average concentrations of 270 CFU/100 mL in the low-tourism season at Stn 4, this value being higher than the maximum value established for discharge to coastal and transitional waters (250 CFU/100 mL). There was also a higher concentration of this bacterium (8966 CFU/100 mL) at the same point (Stn 4) and at the point where water is discharged from the WWTP (spillway) with 863 CFU/100 mL in periods of high influx of tourism (being at this point the maximum established threshold of 200 CFU/100 mL for inland waters). These concentrations are above the results for fecal streptococci detected in the Nayade series [26] between 1 January 2016 and 1 January 2021 (Figure 6).
For E. coli, in the low-tourism season, the concentrations did not exceed the established threshold [14]. However, in the high-tourism season, the concentration amounted to 5466 CFU/100 mL at the point of the spillway, being above the threshold established (500 CFU/100 mL) for inland waters.

4. Discussion

Phytoplankton distribution is generally patched and fragmented in space and time [28,29] due to physical processes [29] such as turbulence [30], lateral stirring [31], and biochemical processes and trophic interactions [22], among others. The presence of phytoplankton itself enhances flocculation [32]. Phytoplankton proliferation depends on nutrients, light availability [22], and turbulence/stratification. Margalef’s mandala shows that, under turbulent conditions, diatoms dominate the phytoplankton composition, while red tides occur under high-nutrient-availability and stratified conditions [33]. In addition, cell size plays an important role, as larger (heavier) cells settle and grow faster; however, they have a lower surface/volume ratio, which negatively affects nutrients’ affinity, being less effective in incorporating nutrients at low concentrations in the environment. Our time series analysis of coastal waters along the shore of La Herradura Bay revealed high variability of TChl a concentration at the shoreline, with peaks of TChl a higher than 5 μg/L. TChl a concentration higher than 5 μg/L and the strong positive increase in the TChl a concentration over time are considered indicators of eutrophication [34]. Our TChl a measurement along the shoreline showed five peaks with Chl a concentration higher than 3 μg/L, indicating episodic nutrient inputs and successive TChl a peaks, which can reach eutrophic conditions (>5 μg Chl a/L). However, the mean Chl a concentration over the whole sampling period was between 1.88 and 2.4 μg/L, and the short time period did not reveal any trend. Thus, an eutrophication process could not be detected, but episodic phytoplankton blooms suggested occasional nutrient inputs.
The spatial phytoplankton distributions detected during the kayak surveys indicated different stages of the Margalef’s Mandala [33]. Larger-sized cells, such as green algae and diatoms and dinoflagellates, were more abundant in cooler, less stratified, nutrient-rich waters offshore, whereas elevated cyanobacteria concentration was associated (positive correlated) with warmer waters close to the beach, which might cause the increase in coastal water turbidity [35]. The increase in turbidity negatively affects macroalgae growth on the seafloor [36]. Moreover, sloppy feeding by grazers, viral lysis, and the excretion of metabolites by bacteria and zooplankton are sources of yellow substances [37]. However, in our case, yellow substances was positively correlated to coastal waters, suggesting the implication of nearshore processes on the generation of yellow substances.
The kayak transects showed a patchy distribution of phytoplankton in general (T Chl a), but phytoplankton groups showed an opposite distribution of green algae and cyanobacteria.
The different patchy distribution of the phytoplankton groups affects the abundance and biovolume of the phytoplankton community, their size structure, and the consequent pathway of biomass through the food web [38,39]. The presence of fresh water runoff from the WWTP at the mouth of the Jate River (Stn 4) negatively affected the biovolume and abundance of phytoplankton. In fact, the lowest values of biovolume and abundance of phytoplankton in all size classes were observed at Stn 4. Consequently, the SAS also showed the lowest and shortest spectrum of all sampling stations, being different from the SAS in the marine environment.
As shown in Table 2, at Stn 4 and Spillway, we obtained bacterial concentrations above the maximum threshold established in Spanish law [14]. During the low-tourism season, the E. coli values were below the threshold established by the European Union and Spanish law in all sampling stations, and fecal streptococci counts were higher than the limit values only at Stn 4 (Table 2). During the second week, with high tourism pressure, the values of these two indicators exceeded the limits established by Spanish law [14]. In one week, at Stn 4, the enumeration of E. coli and fecal streptococci multiplied by 10 and 33, respectively, being the concentration of fecal streptococci 48 times higher than the stipulated as “sufficient”. At the spillway of the WWTP to the Jate river. E. coli and fecal streptococci counts were six and four times higher in the second week than in the first week, respectively. At this point, the concentrations of E. coli and fecal streptococci were 6 and 2.5 times higher than the threshold contemplated in Spanish law [14], respectively. These results showed that the bathing waters on the beach at Stn 4 were unhealthy both during the low- and high-tourism seasons.
In contrast, the national information system of bathing water quality (Nayade) sampling [26] did not detect any “insufficient” water quality between 1 January 2016 and 1 January 2021. This was striking because, during the prolonged high-tourism season (summer), the WWTP might be overcome several times and the spill to the Jate River would contaminate the water at Stn 4, which is close to one of the Nayade sampling stations (Nayade 2, in Figure 1). The reason for this may be that the contamination diluted quickly, and, at a short distance, the bacterial abundance was below the legal threshold. Another factor might be that our sampling was not in the official time window of national bathing water control of Nayade standard sampling. WWTP spill might also be enhanced during the period of low water quality control and retained during the control periods (season and hours).
For Escherichia coli, during the low-tourism season, the concentrations did not exceed the established threshold contemplated in Spanish law [14]. However, during high tourism, the concentration amounted to 5466 CFU/100 mL at the point of the spillway, being above the threshold established (500 CFU/100 mL) for inland waters.
The population census of La Herradura village is approximately 4200 people [40]. During summer holidays, the population triples that of the permanent population, which means that La Herradura reaches around 13,000–15,000 people in the high-tourism season. Although the WWTP of La Herradura has a capacity for 20,000 inhabitants, it is only provided with the primary (removing coarse solids, sands, fats, and some settleable organic matter) and secondary (degrading dissolved organic matter using aerobic bacteria in biological reactors) treatments, but it lacks the tertiary treatment, whose objective is the reduction in heterotrophic bacteria (i.e., chlorination UV treatment, ozone, advanced filtration membranes, activated carbon, etc.) [41]. Thus, during the high-tourism season, heterotrophic fecal bacteria of 13,000–15,000 people would spill into La Herradura Bay, negatively affecting human health and the environment.
However, on the other hand, in 2019, tourism provided 2.473.804 jobs and EUR 91.911.973.022 to the Spanish economy [42]. Particularly in La Herradura, tourism accounts for 57.4% of the local income and generates more than 180 jobs in the area [43]. Thus, tourism is the main economic driver of the village. La Herradura Bay is surrounded by two marine protected areas (MPA), with picturesque views and seascapes that offer attractive seawater activities for tourism, such as diving, kayaking, and snorkeling. Although the WWTP capacity is designed for the high-tourism season population, its “Achilles’ heel” seems to be the lack of tertiary treatment, a problem that could be resolved easily by inverting the benefits of tourism to improve local water treatment.

5. Conclusions

La Herradura Bay shows patchy and very variable phytoplankton distribution in space and time, which affects the phytoplankton composition and size structure. Although peaks of very high TChl a concentration could be observed during the time series sampling along the shore, no eutrophication process could be detected in the short time series.
This study suggests that the carrying capacity of the coastal infrastructure of wastewater treatment can be exceeded during high-tourism seasons. The lack of tertiary wastewater treatment at villages with elevated tourism pressure, even outside the peak summer season, results in acute episodes of fecal contamination that suppose a risk to public health. Bacterial contamination in La Herradura Bay was originated primarily from the overflow of a WWTP into the Jate River and not through its official outfall.
Our findings underscore the limitations of standardized monitoring programs (Nayade) and highlight the need to implement more flexible, high-resolution surveillance strategies, especially during the periods of high tourism pressure. In this sense, additionally to the established Nayade sampling stations, any river which flow into the sea should be sampled at the shoreline, in order to detect potential fecal bacteria contamination from inland spills to the rivers. Therefore, the protection of people health and the sustainability of tourism, a key sector for the economy, both depends on effective year-round wastewater management and a control system that could detect and mitigate these episodic pollution events. Based on the socioeconomic analysis, the inclusion of the tertiary wastewater treatment, for reducing the spill of fecal bacteria in coastal water, is urgently proposed.

6. Outlook

This study shows that coastal waters are not monetarized well enough. For future work, we recommend locating the NAYADE sampling station next to the river mouth and elaborating the local index of the trophic state of coastal waters, which will serve as baseline for future works.

Author Contributions

Conceptualization, M.M.G.-F., M.M. and A.R.; methodology, J.G.-M., J.D.G., S.A.; software, A.R.; validation, F.G., B.B. and M.M.; formal analysis, M.M.G.-F.; investigation, A.R., M.M., F.G.; resources, F.G., A.R., S.A.; data curation, M.M.G.-F.; writing—original draft preparation, M.M.G.-F., M.M.; writing—review and editing, A.R., S.A., M.M., B.B., F.G.; visualization, J.D.G.; supervision, M.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Sustainability 17 09792 g0a1
Figure A1. WTTP spill to the Jate River.
Figure A1. WTTP spill to the Jate River.
Sustainability 17 09792 g0a1

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Figure 1. Sampling site and sampling stations. Red circles = nearshore biweekly sampling stations (Stn 1, Stn 2, Stn 3); beige circles = discreet water sampling stations during Herradura Bay survey sampling by kayak (Stn 4, Stn 5, Stn 6, Stn X1, and Stn X2). White triangle = localization of Nayade sampling stations; white straight line = emissary of the Herradura wastewater treatment plant. Beige triangle (on land) WWTP spill to the Jate River. (figure was made with ArcGisPro 3.4.0, backround: Gobierno de España, Microsoft, Vantor.)
Figure 1. Sampling site and sampling stations. Red circles = nearshore biweekly sampling stations (Stn 1, Stn 2, Stn 3); beige circles = discreet water sampling stations during Herradura Bay survey sampling by kayak (Stn 4, Stn 5, Stn 6, Stn X1, and Stn X2). White triangle = localization of Nayade sampling stations; white straight line = emissary of the Herradura wastewater treatment plant. Beige triangle (on land) WWTP spill to the Jate River. (figure was made with ArcGisPro 3.4.0, backround: Gobierno de España, Microsoft, Vantor.)
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Figure 2. Temporal variability in temperature (mean of the three samples at each sampling station), Total Chlorophyll a (TChl a) (A), and the relative contribution of algae groups to TChl a at the three coastal stations: Stn 1 (B), Stn 2 (C), and Stn 3 (D).
Figure 2. Temporal variability in temperature (mean of the three samples at each sampling station), Total Chlorophyll a (TChl a) (A), and the relative contribution of algae groups to TChl a at the three coastal stations: Stn 1 (B), Stn 2 (C), and Stn 3 (D).
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Figure 3. Total chlorophyll a concentration (μg/L), temperature, and cyanobacteria (μg/L) recorded during the kayak sampling (12 April 2019).
Figure 3. Total chlorophyll a concentration (μg/L), temperature, and cyanobacteria (μg/L) recorded during the kayak sampling (12 April 2019).
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Figure 4. Abundance (cell/mL) and biovolume (μm3/mL) of phytoplankton 20–100 μm ESD at the six sampling stations during the first kayak sampling (12 April 2019).
Figure 4. Abundance (cell/mL) and biovolume (μm3/mL) of phytoplankton 20–100 μm ESD at the six sampling stations during the first kayak sampling (12 April 2019).
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Figure 5. Size abundance spectra of microphytoplankton communities (Sampling date: 12 April 2019).
Figure 5. Size abundance spectra of microphytoplankton communities (Sampling date: 12 April 2019).
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Figure 6. Time series of fecal streptococci abundance registered during standard sampling of the national information system of bathing water quality Nayade [26] between 1 January 2016 and 1 January 2021, and fecal streptococci registered at sampling station 4 during low (12 April 2019) and high (20 April 2019) tourism seasons.
Figure 6. Time series of fecal streptococci abundance registered during standard sampling of the national information system of bathing water quality Nayade [26] between 1 January 2016 and 1 January 2021, and fecal streptococci registered at sampling station 4 during low (12 April 2019) and high (20 April 2019) tourism seasons.
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Table 1. Spearman rank order correlation among temperature (Temp.), total chlorophyll a (TChl a) phytoplankton groups (Green algae, cyanobacteria (Cyanobact.), diatoms and dinoflagellates (Diat.&Dinof.), Cryptomonads (Crypt.), Yellow Substances, and Transmittance during the Kayak survey. n.s not significant, * p < 0.05, ** p < 0.01, *** p < 0.001, n = 127. Bold indicates significant differences.
Table 1. Spearman rank order correlation among temperature (Temp.), total chlorophyll a (TChl a) phytoplankton groups (Green algae, cyanobacteria (Cyanobact.), diatoms and dinoflagellates (Diat.&Dinof.), Cryptomonads (Crypt.), Yellow Substances, and Transmittance during the Kayak survey. n.s not significant, * p < 0.05, ** p < 0.01, *** p < 0.001, n = 127. Bold indicates significant differences.
TChl aGreen AlgaeCyanobact.Diat.&Dinof.Crypt.Yellow SubstancesTransmittance
Temp.−0.465 ***−0.433 ***0.315 ***−0.320 ***0.0796, n.s0.297 ***−0.669 ***
Chl a T 0.840 ***−0.108, n.s0.175 *0.0005, n.s−0.509 ***0.352 ***
Green algae −0.284 **−0.26 **0.034, n.s−0.408 ***0.379 ***
Cyanobact. −0.0156, n.s−0.384 ***0.161, n.s−0.297 ***
Diat.&Dinof. −0.238 **−0.143, n.s0.184 *
Cryp. −0.038, n.s−0.090, n.s
Yellow Substances. −0.246 **
Table 2. Fecal streptococci and Escherichia coli concentrations in the sampling stations. Values are expressed as CFU/100 mL. ND: No bacteria were detected in the water sample. Different letters indicate significant differences (p < 0.05) in each bacterial group. Bold indicates counts that exceeded the threshold for sufficient quality, based on ‘sufficient’ classification, established by the Bathing Water Directive [25] and the Spanish [14] of October 11th: 185 CFU/100 mL (coastal waters) and 330 CFU/100 mL (continental water) for fecal streptococci; and 500 CFU/100 mL (coastal waters) and 900 CFU/100 mL (continental waters) for E. coli.
Table 2. Fecal streptococci and Escherichia coli concentrations in the sampling stations. Values are expressed as CFU/100 mL. ND: No bacteria were detected in the water sample. Different letters indicate significant differences (p < 0.05) in each bacterial group. Bold indicates counts that exceeded the threshold for sufficient quality, based on ‘sufficient’ classification, established by the Bathing Water Directive [25] and the Spanish [14] of October 11th: 185 CFU/100 mL (coastal waters) and 330 CFU/100 mL (continental water) for fecal streptococci; and 500 CFU/100 mL (coastal waters) and 900 CFU/100 mL (continental waters) for E. coli.
Sample StationsFecal StreptococciEscherichia coli
Low TourismHigh TourismLow TourismHigh Tourism
Stn 1NDNDNDND
Stn 2NDNDND18 ± 8 a,b,c
Stn 3NDNDND16 ± 4 c
Stn 4270 ± 56 b8967 ± 153 d40 ± 17 a,c,d440 ± 121 e
Stn 5NDND3 ± 3 a5 ± 9 a,c
Stn 6NDND126 ± 45 a,c,f23 ± 13 a,c,f
Stn X1ND77 ± 55 a15 ± 21 a,c,f77 ± 55 a,c,f
Stn X2NDND40 ± 44 a,c,f4 ± 4 a
Spillway203 ± 40 b863 ± 185 c87 ± 32 b,d,f5467 ± 2101e
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Granados-Fernández, M.M.; Arijo, S.; Reul, A.; Guerrero, F.; Gilbert, J.D.; García-Márquez, J.; Bautista, B.; Muñoz, M. Coastal Bathing Water Evaluation Under Contrasting Tourism Pressures at Herradura Bay (S-W Mediterranean). Sustainability 2025, 17, 9792. https://doi.org/10.3390/su17219792

AMA Style

Granados-Fernández MM, Arijo S, Reul A, Guerrero F, Gilbert JD, García-Márquez J, Bautista B, Muñoz M. Coastal Bathing Water Evaluation Under Contrasting Tourism Pressures at Herradura Bay (S-W Mediterranean). Sustainability. 2025; 17(21):9792. https://doi.org/10.3390/su17219792

Chicago/Turabian Style

Granados-Fernández, Miguel María, Salvador Arijo, Andreas Reul, Francisco Guerrero, Juan Diego Gilbert, Jorge García-Márquez, Begoña Bautista, and María Muñoz. 2025. "Coastal Bathing Water Evaluation Under Contrasting Tourism Pressures at Herradura Bay (S-W Mediterranean)" Sustainability 17, no. 21: 9792. https://doi.org/10.3390/su17219792

APA Style

Granados-Fernández, M. M., Arijo, S., Reul, A., Guerrero, F., Gilbert, J. D., García-Márquez, J., Bautista, B., & Muñoz, M. (2025). Coastal Bathing Water Evaluation Under Contrasting Tourism Pressures at Herradura Bay (S-W Mediterranean). Sustainability, 17(21), 9792. https://doi.org/10.3390/su17219792

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