Evaluation of Water Quality in the Production of Rainbow Trout (Oncorhynchus mykiss) in a Recirculating Aquaculture System (RAS) in the Precordilleran Region of Northern Chile

Abstract

Water quality and the culture performance of juvenile rainbow trout (Oncorhynchus mykiss) were evaluated between 2014 and 2017 in a recirculating aquaculture system (RAS) in the Chilean Altiplano. Key parameters such as temperature, total ammonia nitrogen (TAN), nitrates, and dissolved oxygen were monitored, with values ranging from 7 to 21 °C, <0.1 to 0.63 mg/L, 2.0 to 135 mg/L, and 1.8 to 7.5 mg/L, respectively. Additional parameters—including alkalinity, arsenic, chlorine, true color, conductivity, hardness, phosphorus, pH, potassium, suspended solids, and salinity—were also assessed, comparing different points within the system (head tank, culture tanks, and settling tanks). The results showed that water quality remained within acceptable ranges for aquaculture, although fluctuations in pH and low alkalinity levels caused stress in the fish. Despite these challenges, the specific growth rate (SGR) was 1.49, the feed conversion ratio (FCR) was 1.52, and weight gain reached 298.7%, with a survival rate of 96.2%. This study demonstrates that aquaculture in the Altiplano is feasible and can contribute to the sustainable development of aquaculture in the region. Furthermore, it highlights the importance of comprehensive water quality monitoring to optimize RAS performance in challenging environments.

1. Introduction

In the foothills of northern Chile, particularly in the Arica and Parinacota Region, agriculture, livestock farming, and, to a lesser extent, tourism represent the main sources of income for local communities [1,2]. However, the progressive decline and abandonment of agricultural and livestock activities—largely due to the lack of economic diversification—have contributed to rural depopulation, as younger generations migrate toward urban centers [3]. In this context, aquaculture has emerged as a promising productive alternative for high-altitude settlements [1,4]. Several studies highlight its potential to revitalize rural economies by leveraging existing agricultural infrastructure, such as irrigation reservoirs, greenhouses, and hydraulic systems [4,5]. The reuse of water in land-based aquaculture systems, especially recirculating aquaculture systems (RASs), offers an efficient and sustainable strategy that can complement irrigation practices [5]. These systems are particularly well-suited to the environmental conditions of the Altiplano, where land availability and microclimates provide a favorable setting for the cultivation of freshwater fish [5]. Moreover, high-altitude aquaculture could enhance local food security by offering a reliable protein source, reducing dependency on external food supplies, and contributing to the overall resilience of Andean communities [5].

Among the available aquaculture methods, recirculating aquaculture systems (RASs) stand out for their high water-use efficiency [6]. Compared to flow-through systems, RASs can reduce water consumption by 90% to 99% per unit of production, depending on system design and operational efficiency. While traditional systems may require 30 to 60 L of water per second per ton of fish, a well-optimized RAS can operate with daily water exchange rates as low as 1 to 5% of the total system volume—equivalent to less than 1 L per second for the same biomass [7,8]. In addition, RASs allow precise control of critical environmental parameters, such as temperature, alkalinity, and nitrogen compounds, which is essential in regions where water is a limited resource [9].

Species selection for RASs depends on compatibility with controlled environments, feed conversion efficiency, and economic return. Rainbow trout (Oncorhynchus mykiss) is one of the most widely cultured species in these systems due to its tolerance to high stocking densities, ability to grow under controlled oxygen levels, strong market demand, and well-established production protocols [10]. Moreover, its sensitivity to key water quality parameters, such as dissolved oxygen, temperature, and pH, makes it a suitable model for evaluating RASs in challenging environments. Importantly, rainbow trout has demonstrated adaptability to high-altitude culture systems, maintaining acceptable growth rates when water conditions are properly managed, justifying its study at 3000 m above sea level. Other suitable species include channel catfish (Ictalurus punctatus), tilapia (Oreochromis spp.) [11], sturgeon, and white shrimp (Litopenaeus vannamei), especially in biofloc-based RASs. In contrast, filter feeders such as bivalves are generally less compatible due to their high water volume requirements [12,13].

Unlike flow-through systems, where water quality depends heavily on the incoming source, RASs offer consistent control over key variables, improving conditions such as water cleanliness, dissolved oxygen levels, and the removal of waste residues [14,15].

A recirculating aquaculture system (RAS) is a technology that reuses water in the culture of aquatic organisms through a closed-loop treatment circuit. Its key components include water storage or header tanks, culture tanks, mechanical filters for the removal of suspended solids, and biofilters that convert toxic nitrogenous compounds into less harmful forms. These elements support the maintenance of optimal water quality, enhance water-use efficiency, and reduce environmental impact when compared to conventional aquaculture systems [7].

Water quality is a general condition that determines whether water can be used for specific purposes; it is a relative concept and depends on how the resource is utilized [16]. In aquaculture, water quality is influenced by the physical and chemical properties of water and their interaction with the cultured organisms. Key factors include temperature, dissolved oxygen, salinity, alkalinity, hardness, and nitrogen compounds [17]. However, increasing aquatic pollution and the presence of organic contaminants and heavy metals must also be considered due to their impact on organisms and production goals [18,19].

Each cultivated species has an optimal water quality range necessary for normal development, requiring adjustments to parameters such as temperature, dissolved oxygen, salinity, pH, and alkalinity based on its specific needs. In RASs, water conditions vary between system sections [5]. In water reservoirs, parameters tend to be optimal after biological filtration, whereas at the tank outlets, organic waste and nitrogen compounds accumulate, increasing total ammonia nitrogen (TAN) and reducing dissolved oxygen. In the biofilter, nitrifying bacteria convert ammonium into nitrites and nitrates, reducing water toxicity but requiring high oxygen concentrations to sustain nitrification [7].

Controlling parameters such as temperature, dissolved oxygen, and pH is crucial for fish welfare and growth. Temperature influences both biotic and abiotic processes; an increase in this parameter reduces dissolved oxygen levels, increases ammonia toxicity, and accelerates the decomposition of organic matter, leading to higher oxygen consumption and affecting the metabolism and health of organisms [1,2]. Dissolved oxygen regulation is closely linked to fish health, growth, and survival, making it essential to prevent stress and ensure normal physiological processes. Similarly, extreme pH levels can cause mortality and directly affect the stability of other critical parameters [7,20].

Other parameters, such as alkalinity and hardness, also play a significant role. Alkalinity, which measures the concentration of dissolved alkaline substances, acts as a buffer, stabilizing pH, while hardness reflects the concentration of essential cations such as calcium and magnesium. In both cases, fluctuations in these parameters can lead to pH variations, ultimately affecting fish health [7]. Likewise, water conductivity, which is related to the total ion concentration, impacts fish osmoregulation and overall well-being [17].

In aquaculture, monitoring nitrogen compounds, such as ammonium, nitrite, and nitrate, is crucial. These compounds are generated within the system through fish excretion and the decomposition of organic matter, and their accumulation negatively impacts fish health, particularly in salmonids, which are highly sensitive to ammonia [21]. Biofilters play a key role in removing these compounds, ensuring a healthy environment in intensive aquaculture systems.

Salinity, determined by ions such as chloride, calcium, and potassium, directly influences fish osmoregulation. Chlorides also reduce nitrite toxicity by competing for branchial transport sites [22]. However, high chloride concentrations can affect gas transfer in the gills by increasing the thickness of the blood–water diffusion barrier [23]. Potassium, on the other hand, contributes to osmotic balance [20].

Parameters such as phosphorus, total dissolved solids (TDS), and arsenic are also relevant in aquaculture, as abnormal values can cause issues in production. Phosphorus can promote algal blooms, reducing dissolved oxygen levels [24]. High TDS levels affect fish osmoregulation [25], while arsenic, although less studied, poses a toxicological risk for fish and human consumption [26].

Water color depends on various factors and is influenced by organic compounds and phytoplankton. It can affect light penetration in the water, limiting system productivity [20].

In RASs, continuous monitoring of these compounds ensures optimal culture conditions and production efficiency while minimizing costs and environmental impacts [3,27]. However, despite these advantages, the implementation of RASs also involves significant challenges. These include high initial capital investment in infrastructure and monitoring systems [8], substantial energy demands, and the need for trained personnel to manage complex processes, such as biofiltration and water chemistry [7]. Innovations like renewable energy integration and aquavoltaic systems offer promising solutions to reduce energy consumption and operational costs, enhancing the overall sustainability of RASs [28]. Thus, their feasibility depends not only on technical performance but also on the ability to address economic, energy, and operational limitations—especially in rural or low-infrastructure contexts.

This study aims to evaluate the variability of water quality parameters in a recirculating aquaculture system at 3000 masl. Additionally, it seeks to determine the impact of all studied parameters on the growth and development of rainbow trout juveniles during their first three months of cultivation.

2. Materials and Methods

2.1. Study Area and Recirculating Aquaculture System Characteristics

The study was conducted at the Copaquilla Pukará Cultivation Center (CPCC) (Figure 1), located in the precordillera of northern Chile, in the locality of Copaquilla (18°23′43″ S, 69°37′58″ W). This center is situated 90 km inland from the city of Arica, in the Arica and Parinacota Region, at an altitude of 3000 m above sea level (m.a.s.l.).

The facility operated a recirculating aquaculture system (RAS) (Figure 2) supplied exclusively by untreated local groundwater, the sole reliable water source in this high-altitude desert region. Given the scarcity of surface water and the extreme arid conditions typical of the Chilean Altiplano, groundwater is indispensable for sustaining aquaculture and local agriculture. The RAS consisted of six circular Australian-type tanks designed for the intensive production of rainbow trout (Oncorhynchus mykiss). This system included a central drainage system and hydraulic connections for water supply and aeration. Additionally, it featured fiberglass tanks installed below ground level, which included two sedimentation tanks and a biofilter tank. The system was also equipped with two water suction pumps (Reggio, model SM 150), a high-pressure blower (Sweetwater, 1.5 hp), and an oxygen generator (Oxiti, 8 LPM).

Water was delivered to each culture tank through a central pipeline with a diagonal flow, regulated by valves, creating a circular motion. The tanks were internally lined with an impermeable material (0.9 mm thick laminated PVC) and were equipped with a central drainage and outflow system. Each tank was also fitted with continuous aeration pipes and oxygen distribution lines, either for regular use or emergency situations. The water used in the tanks was subsequently directed to the sedimentation tanks, designed for the removal of suspended solids.

2.2. Water Quality Monitoring

In this study, water quality parameters in the RAS were measured and categorized into two main types. General parameters included temperature (°C), dissolved oxygen (mg/L), as well as ammonium and nitrate concentrations (mg/L). Special parameters consisted of alkalinity (mg/L), arsenic (mg/L), chloride (mg/L), true color (Pt-Co), conductivity (µS/cm), hardness (mg/L), phosphorus (mg/L), pH, potassium (mg/L), total dissolved solids (mg/L), and salinity (PSU). This monitoring strategy enabled a detailed and continuous record of the water’s environmental conditions. The following section details the measurement criteria and usage of each parameter group.

2.2.1. Fundamental Water Quality Parameters in a SAR System

Temperature and dissolved oxygen (DO) were measured daily, three times a day, using a portable oximeter (YSI, model I55, Hanna Intruments Chile, Santiago, Chile). Nitrogenous compounds were assessed biweekly with a multiparameter photometer (Hanna, model HI83303) throughout the 36 month study. To prevent excessive nitrate concentrations in the culture water, 40% water exchanges were conducted in the decanter tanks whenever nitrate measurements indicated high values. Nitrate levels were monitored directly in the fish tanks by placing the sensor on the side opposite the water inlet, at mid-depth. When elevated nitrate concentrations were detected, water was partially replaced in the decanters to maintain optimal water quality in the entire system.

Additionally, complementary measurements of temperature, DO, and nitrogenous compounds were taken at key points in the RAS to assess parameter variability across different system locations. These measurements were conducted monthly for five months, beginning two months before the fish were introduced into the system. The selected sampling points were as follows:

Point 1: Header tank (HT)—the system’s entry point for untreated groundwater, representing the initial water quality conditions entering the RAS.

Point 2: Cultivation tanks 3 and 4 (CT3 and CT4)—located at the end of the water supply line, these tanks receive water of similar quality but are connected to different hydraulic discharge lines. This configuration allows for comparison of potential water quality differences resulting from flow path and treatment performance within the system.

Point 3: Decanting tanks (DT)—responsible for sediment removal and partial water renewal, representing a key stage for evaluating the effectiveness of solid waste management.

2.2.2. Specific Water Quality Parameters in a SAR System

The special parameters and their analysis methods are described in

Table 1. Methodology used, based on the Standard Methods for the Examination of Water and Wastewater [29], for sampling and determining the physicochemical parameters in trout cultivation.

Parameters	Unit	Methodology
Alkalinity	mg CaCO3/L	SMWW 2320B
Arsenic	mg/L	SMWW 3114C
Chloride	mg/L	SMWW 4500Cl-
True Color	Pt-Co	SMWW 2120C
Conductivity	µS/cm	SMWW 2510B
Hardness	mg CaCO3/L	SMWW 2340C
Phosphorus (P-H2PO4)	mg/L	SMWW 4500P-C
pH		SMWW 4500B-H*B
Potassium	mg/L	SMWW 3111B
Total dissolved solids	mg/L	SMWW 2540B
Salinity	PSU	SMWW 2520B

. These measurements were conducted monthly for five months, starting two months before the fish were introduced into the system. The selected sampling points were the same as previously mentioned: the water storage pond (WSP), the outlet water from the fish culture tanks (CT3 and CT4), and the biofilter (DT) (Figure 2).

2.3. Juvenile Growth Assessment

The study was conducted between July 2014 and June 2017. At the end of October 2014, 5000 juvenile rainbow trout (Oncorhynchus mykiss) with an average weight of approximately 15 g were sourced from the Río Blanco hatchery, operated by the Pontificia Universidad Católica de Valparaíso and located in Los Andes, Valparaíso Region. The fish were transported to the experimental facility in Copaquilla (Arica and Parinacota Region, ~3000 m.a.s.l.), where they underwent a gradual acclimation process to the recirculating aquaculture system (RAS) and high-altitude environmental conditions.

Fish were maintained under natural photoperiod conditions typical of the pre-Andean zone, with approximately 13 h of light and 11 h of darkness during spring and summer months. No artificial lighting was used. Feeding was performed manually three times daily at 08:00, 13:00, and 18:00 h using a commercial extruded trout feed for juveniles (Power 250. Ast. 100 ppm), with a particle size of 2–3 mm and a protein content of 40%. Feed rations were adjusted monthly based on estimated biomass, observed feeding behavior, and water temperature, following the manufacturer’s recommendations. Additionally, 24–48 h fasting periods were applied as a management strategy whenever critical water quality parameters (e.g., ammonia or dissolved oxygen) showed significant fluctuations to prevent biological filter stress.

The fish were stocked at an initial density of approximately 0.45 kg/m³, with 1250 fish per 33,000 L tank. To evaluate the effects of water quality parameters on growth, sampling was conducted every 15 days over the first three months. In each sampling event, 2–3% of the tank population was randomly selected, handled carefully without the use of anesthetics, and individually weighed using a digital scale (Mocco, model V-1026,Rimasa, Santiago, Chile). All handling was conducted using water from the same tank, with minimal air exposure (<15 s) and soft rubber nets to protect the skin and mucosa. Although no physiological stress indicators were quantified, fish behavior was monitored daily, and no signs of stress (e.g., erratic swimming, lethargy, reduced feeding) were observed. The absence of mortality related to handling and the maintenance of a high condition factor throughout the study further support the effectiveness of these practices in minimizing stress. After weighing, all fish were promptly returned to their respective tanks. Growth performance was assessed by calculating the feed conversion ratio (FCR), specific growth rate (SGR), weight gain percentage (%GW), survival rate (%S), and applying the exponential growth equation, following the methodology described by Ricker [30].

2.4. Data Analyses

Statistical analyses were performed using Rstudio statistical software version 2024.09.0+375 from Rstudio, Inc. (Washington, DC, USA). Temperature, dissolved oxygen, ammonium, and nitrate were tested for normality using the Anderson–Darling test and for homogeneity of variance using the Bartlett test. Data were evaluated using one-way analysis of variance (ANOVA) and Tukey’s post-hoc test. When normality assumptions were not met, data were evaluated using the Kruskal–Wallis test to assess differences between treatments and the Dunnett test to determine homogeneous groups [31]. The non-parametric Mann–Kendall correlation test (Kendall Tau) was applied to determine the relationship between temperature–oxygen and ammonium–nitrate. Growth was tested for normality using the Anderson–Darling test and Pearson correlation. A principal component analysis (PCA) was performed to evaluate the relationship between water quality parameters. Graphs were made using the ggplot2 package and expressed as mean ± standard deviation (SD).

3. Results

3.1. General Water Quality Parameters

During the colder months of the Southern Hemisphere (April to October), temperatures in the tanks decreased, reaching values below 8 °C. In contrast, during the warmer months (November to March), temperatures increased, exceeding 18 °C between January and March (Figure 3).

The applied non-parametric analysis did not show a significant trend in water temperature during the entire study period (τ = 0.089; p = 0.4535). Similarly, dissolved oxygen levels remained unchanged over time (τ = 0.120; p = 0.3233). On the other hand, Kendall’s correlation coefficient indicated a moderate and highly significant inverse relationship between temperature and dissolved oxygen (τ = –0.475; p = 8.65 × 10⁻⁵) (Figure 3).

Dissolved oxygen (DO) concentrations in the tanks exhibited an inverse relationship with temperature, also influenced by seasonal changes. During colder months, DO levels were higher compared to warmer months, as elevated temperatures lead to increased oxygen consumption by fish, resulting in lower oxygen levels in the water.

Ammonium concentrations showed moderate fluctuations over the 36 months, generally remaining within a range of 0.25–0.75 mg/L (Figure 4). Peak values were observed toward the end of 2016, with a notable spike in October, likely associated with an environmental event.

The temporal evaluation of ammonium concentrations showed no evidence of a significant trend (τ = 0.078; p = 0.5205). In contrast, nitrate showed a slight but statistically significant increasing trend over time (τ = 0.235; p = 0.04908).

Additionally, a positive correlation of moderate magnitude and high significance was identified between the concentrations of both nitrogenous compounds (τ = 0.484; p = 6.56 × 10⁻⁵) (Figure 4).

In contrast, nitrate levels exhibited more pronounced variations, with concentrations reaching up to 1.5 mg/L at several points during the cultivation period. However, each time nitrate levels rose significantly, a subsequent sharp decline was observed, coinciding with water exchanges in the system to reduce its concentration. Overall, the levels of both parameters did not appear to reach values that posed a serious threat to the fish in this culture system.

In

Table 2. General parameter values recorded at different points in the recirculating aquaculture system (RAS). (HT: Header tank; CT3: Cultivation tank 3; CT4: Cultivation tank 4; DT: Decanting tanks). Different superscript letters in the columns indicate statistically significant differences among sampling points within each month (p < 0.05).

Water Quality Parameters	Sampling Point	Without Fish		With Fish			Normal Value
		Sep	Oct	Nov	Dec	Jan
Temperature (°C)	HT	11.00 ± 0.37	14.00 ± 0.33	15.00 ± 0.31	17.00 ± 0.89	21.00 ± 1.29	9 to17°C [32]
	CT3	8.00 ± 0.29 b	9.00 ± 0.55 c	12.98 ± 1.66 b	17.00 ± 0.89 a	20.03 ± 0.74 ab
	CT4	7.00 ± 0.16 c	8.00 ± 0.12 d	13.98 ± 0.15 b	17.03 ± 0.48 a	19.00 ± 0.72 b
	DT	8.03 ± 0.36 b	9.95 ± 0.75 b	14.00 ± 0.14 b	17.03 ± 0.24 a	19.03 ± 0.23 b
Dissolved oxygen (mg/L)	HT	6.31 ± 0.08 c	3.43 ± 0.17 b	4.45 ± 0.10 a	3.14 ± 0.17 b	6.80 ± 0.57 a	7.5 to 12 mg/L [33]
	CT3	7.48 ± 0.08 a	4.90 ± 0.12 a	2.73 ± 0.11 d	1.78 ± 0.01 c	3.52 ± 0.23 d
	CT4	7.48 ± 0.07 a	2.96 ± 0.13 c	3.09 ± 0.12 c	1.82 ± 0.06 c	6.03 ± 0.74 b
	DT	6.75 ± 0.13 b	2.90 ± 0.01 c	3.40 ± 0.03 b	4.84 ± 0.35 a	4.71 ± 0.09 c
Ammonium (mg/L)	HT	<0.1	<0.1	0.12 ± 0.01 c	0.29 ± 0.02 b	0.63 ± 0.02 a	<0.012 mg/L [34]
	CT3	<0.1	<0.1	0.32 ± 0.02 a	0.48 ± 0.02 a	0.41 ± 0.03 b
	CT4	<0.1	<0.1	0.28 ± 0.03 b	0.21 ± 0.01 c	0.20 ± 0.01 c
	DT	<0.1	<0.1	0.27 ± 0.01 b	0.14 ± 0.01 d	0.19 ± 0.01 d
Nitrate (mg/L)	HT	3.83 ± 0.26 a	1.63 ± 0.11 c	111.00 ± 2.24 c	115.00 ± 2.55 d	52.00 ± 1.87 c	<110 mg/L [35]
	CT3	2.63 ± 0.17 b	3.01 ± 0.16 a	121.00 ± 2.41 a	131.00 ± 3.30 b	43.00 ± 1.73 d
	CT4	3.59 ± 0.11 a	2.89 ± 0.16 a	116.00 ± 2.23 b	121.00 ± 1.87 c	62.00 ± 4.05 a
	DT	2.01 ± 0.04 c	2.69 ± 0.10 b	118.00 ± 1.57 b	135.00 ± 1.80 a	58.00 ± 1.30 b

, the measurements of ammonium and dissolved oxygen recorded at different points within the RAS can be observed and compared.

Temperature in December showed normality (A = 0.46826, p = 0.223); however, no significant differences were observed (F = 0.002248, p = 0.999). The HT exhibited higher temperatures compared to CT3, CT4, and the DT, particularly in January and December.

Significant differences in dissolved oxygen levels were observed across all months, with lower values for CT4 and the DT, especially between October and December.

Ammonium concentrations in September and October—when no fish were present—were below 0.1 mg/L. In contrast, significant differences were detected in November (KW = 15.558, p = 0.01), December (KW = 17.857, p = 4.71 × 10⁻⁴), and January (KW = 16.892, p = 7.44 × 10⁻⁴).

Nitrate concentrations exceeded the recommended limit (<110 mg/L) in several months, particularly in January in the HT (135 mg/L). Elevated nitrate levels were also recorded in CT3 and the DT during November and December.

3.2. Specific Water Quality Parameters

Table 3. Parameter value specifics recorded in the recirculating aquaculture system (RAS). (HT: Header tank; CT3: Cultivation tank 3; CT4: Cultivation tank 4; DT: Decanting tanks).

Water Quality Parameters	Sampling Point	Without Fish		With Fish			Normal Values
		Sep	Oct	Nov	Dec	Jan
Alkalinity mg CaCO3/L	HT	38.00	37.00	36.00	36.00	38.00	75–150 mg/L [7]
	CT3	41.00	38.00	37.00	38.00	38.00
	CT4	43.00	35.00	36.00	36.00	36.00
	DT	36.00	36.00	38.00	36.00	38.00
Arsenic mg/L	HT	0.24	0.25	0.16	0.15	0.08	0.05 mg/L [36]
	CT3	0.29	0.29	0.16	0.13	0.07
	CT4	0.24	0.24	0.16	0.13	0.07
	DT	0.27	0.27	0.16	0.14	0.07
Chloride mg/L	HT	65.00	85.00	55.00	55.00	28.00	10–50 mg/L [37]
	CT3	100.00	90.00	73.00	55.00	20.00
	CT4	0.24	0.24	0.16	0.13	0.07
	DT	110.00	70.00	70.00	58.00	10.00
Colour test Pt-Co	HT	5.00	6.00	11.00	27.00	52.00	30–50 TCU [37]
	CT3	8.00	7.00	11.00	24.00	13.00
	CT4	6.00	5.00	11.00	28.00	13.00
	DT	7.00	7.00	12.00	25.00	18.00
Conductivity µS/cm	HT	551.00	568.00	477.00	415.00	447.00	20–500 µS/cm (20 °C) [38]
	CT3	621.00	590.00	513.00	412.00	421.00
	CT4	572.00	550.00	489.00	414.00	418.00
	DT	631.00	570.00	491.00	418.00	417.00
Calcium hardness mg CaCO3/L	HT	163.00	161.00	181.00	99.00	137.00	20–100 mg/L [39]
	CT3	185.00	157.00	125.00	107.00	133.00
	CT4	572.00	148.00	156.00	101.00	129.00
	DT	631.00	161.00	142.00	101.00	134.00
Phosphoric acid mg/L	HT	8.70	8.70	16.00	20.00	41.59	<0.1 mg/L [40]
	CT3	7.25	8.41	14.00	21.00	40.72
	CT4	8.41	8.99	18.00	21.00	43.19
	DT	9.28	11.16	19.00	23.00	41.74
pH	HT	6.80	8.59	6.90	8.30	9.19	6.7–9 [36]
	CT3	6.60	7.92	5.90	8.10	7.95
	CT4	6.50	7.60	6.10	8.20	8.44
	DT	6.50	8.65	6.80	8.60	8.11
Potassium mg/L	HT	8.25	7.00	7.10	8.26	8.25	5–20 mg/L [37]
	CT3	7.50	7.50	6.90	8.21	8.19
	CT4	9.00	9.00	7.70	7.67	7.98
	DT	8.50	12.50	7.80	8.13	8.01
STD mg/L	HT	449.00	462.00	372.00	418.00	392.00	<400 mg/L [36]
	CT3	515.00	465.00	389.00	409.00	366.00
	CT4	476.00	453.00	257.00	409.00	373.00
	DT	483.00	472.00	396.00	400.00	285.00
Salinity PSU	HT	0.27	0.28	0.23	0.20	0.23	0 to 35 PSU [36]
	CT3	0.30	0.29	0.25	0.20	0.22
	CT4	0.28	0.27	0.24	0.20	0.23
	DT	0.31	0.28	0.24	0.20	0.22

presents the values of the specific water quality parameters measured at different points in the RAS, along with their normal or expected reference values.

Phosphoric acid and true color point in similar directions, suggesting that they tend to increase or decrease together. Conversely, arsenic, conductivity, and salinity lie in the opposite direction to phosphoric acid, indicating that as one increases, the others decrease. Meanwhile, calcium hardness and alkalinity are nearly perpendicular to phosphoric acid, suggesting little to no correlation between these variables.

Figure 5 shows the PCA biplot of the water quality variables. The first two dimensions explain 64.8% of the total variability (51.1% by Dim1 and 13.7% by Dim2). Variables such as pH, color, and phosphoric acid are positively associated with Dim1, while conductivity, arsenic, and total dissolved solids (STD) show a negative association. The proximity of chloride, STD, and arsenic suggests a similar contribution pattern, whereas variables like alkalinity and calcium hardness are more closely related to Dim2.

3.3. Juvenile Growth Assessment

Table 4. Growth parameter values for the total fish population in the CPCC.

Variables	Total
Food provided (kg)	274.1
Initial biomass (kg)	60.4
Final biomass (kg)	240.6
Increase in weight (g)	180.3
Initial density (kg/m3)	1.5
Final density (kg/m3)	6
Initial No. of fish	5000
Final No. of fish	4810
Feed conversion ratio (FCA)	1.52
Specific growth rate (SGR)	1.49
Weight gain (%)	298.7
Survival rate (%)	96.2

displays the values obtained for the evaluated growth parameters. Throughout the cultivation period, growth indicators such as SGR, FCR, and %IP showed a steady increase, reflecting the continuous growth of the fish. Additionally, the high survival rate recorded supports the success of the culture during the three-month period, from the introduction of the juveniles in late October to January.

Figure 6 shows the linear relationship between weight and length, with a coefficient of determination (r² = 0.94), indicating that fish weight increases consistently as their length increases. The condition factor (k) ranges from 1.5 to 2.5.

From the initial stocking of trout in the system, with an average weight of 12 g, a progressive weight increase was observed until the end of the sampling period. This growth is illustrated in Figure 7, which presents an upward curve, clearly depicting the weight progression of the specimens.

In

Table 5. Specific growth rate (SGR) and cumulative growth rate (CGR) of Oncorhynchus mykiss.

Culture Day	Weight (g)	SGR (d−1)	CGR (d−1)	Weight Gain (%)
0	15.52 ± 2.51
17	20.68 ± 1.61	0.17	0.17	24.9
32	26.72 ± 3.06	0.21	0.10	22.6
47	32.44 ± 3.37	0.22	0.07	17.6
62	36.17 ± 3.62	0.23	0.06	10.3
78	49.88 ± 4.80	0.24	0.05	27.5
93	59.99 ± 3.64	0.27	0.04	16.9

, the initial and final weights obtained by the fish during the 93 days of the experiment are presented, in addition to the SGR per sampling interval and the percentage gain in weight between sampling.

4. Discussion

Water quality is a critical factor in aquaculture, directly influencing fish growth, health, and survival. In high-altitude farming systems, environmental conditions present additional challenges, such as lower dissolved oxygen availability and more pronounced thermal fluctuations. This study analyzed various water quality parameters in a recirculating aquaculture system (RAS) for rainbow trout farming in the pre-Andean region of northern Chile, at an altitude of 3000 m above sea level. General parameters such as temperature, dissolved oxygen, and nitrogen compounds were assessed, along with specific parameters including pH, alkalinity, and hardness.

This discussion examines the significance of these factors, their implications for high-altitude aquaculture, and the management strategies implemented to optimize system conditions, ensuring the feasibility of trout farming in this challenging environment.

4.1. Water Quality in High-Altitude Aquaculture

Water quality is essential in intensive fish farming, directly influencing productivity and disease incidence [40]. Sustainable aquaculture requires effective water management to ensure the health and growth of cultured species [41,42], beginning with selecting an uncontaminated water source and maintaining optimal environmental conditions [43].

This study used groundwater as the main source, offering advantages such as low turbidity, physicochemical stability, and protection from surface pollutants [44], reducing the need for pretreatment. Gravity aeration from the reservoir to the tanks (Figure 2) was sufficient for initial conditioning. Groundwater also ensures greater supply stability during droughts [45], and its thermal consistency helps buffer temperature fluctuations at high altitudes.

However, challenges include low dissolved oxygen and potentially toxic elements like arsenic or sulfur compounds [46]. In this study, high arsenic concentrations and low alkalinity—typical of Andean groundwater—were observed, which may compromise pH stability. Thus, groundwater use in high-altitude RASs requires proper treatment and monitoring.

Altitude itself poses limitations. At 3000 m.a.s.l. in Copaquilla, reduced atmospheric pressure lowers oxygen solubility [47], which can affect fish health. To address this, constant aeration and oxygenation systems were used to maintain optimal conditions.

Only one trout farming initiative has been documented in the pre-Andean north of Chile (1993–1995) [3]. Currently, no reports exist on salmonid production in this region at the level of technological and productive development presented here. While aquaculture in Chile is centered in the southern coastal zones, the pre-Andean north remains an underutilized area with significant potential.

4.2. Key Water Quality Parameters in a RAS System

Rainbow trout are highly sensitive to temperature, which directly affects their health and physiology [25]. Optimal temperature ranges vary, typically 9–17 °C [25] or 13–18 °C [33]. In this study, fluctuations between 7 and 19 °C—attributed to tank exposure and lack of thermal regulation—were closer to the range proposed by Phillips et al. [32].

Despite suboptimal dissolved oxygen (DO) levels (4.5–7.5 mg/L) compared to the recommended 7.5–12 mg/L [33], no significant mortality occurred, possibly due to compensatory mechanisms like increased gill gas exchange [48]. Nevertheless, ensuring oxygen supply meets demand remains essential for growth.

Higher temperatures reduce oxygen solubility [49,50], which, combined with trout’s high oxygen demand [51,52], can compromise welfare and performance without mitigation [53,54].

Ammonium, a key excretory product, must be managed through water exchange and biofiltration to avoid toxicity [55]. In this study, elevated pH may have favored toxic ammonia (NH₃) formation [7], with observed ammonium levels (0.15–0.80 mg/L) exceeding the 0.012 mg/L threshold [34], though without severe mortality.

Nitrites, not measured directly, may have accumulated due to high ammonium. As nitrite impairs oxygen transport [7], management strategies—like water changes and feed suspension—likely reduced both compounds. Biofilter maturation may have further enhanced nitrite-to-nitrate conversion.

Ammonium and nitrate tended to increase together, likely due to linked biogeochemical processes [56], where ammonium is transformed via nitrification, emphasizing the need for integrated nitrogen control [57,58,59].

Statistical analysis identified seasonal and spatial patterns. Temperature peaked in the main tank (HT) during January and December, potentially stressing fish metabolism.

Despite the continuous operation of the aeration system, fluctuations in dissolved oxygen levels—particularly at points CT3 and CT4 during November and December, where values dropped as low as 1.78 and 1.82 mg/L respectively—can be attributed to a combination of environmental, biological, and operational factors. DO levels fell critically low at CT4 and the DT between October and December, highlighting the need for improved aeration in these sections of the system.

Firstly, these decreases coincide with the period of highest temperatures recorded in the system, which reduces oxygen solubility in water and thus the efficiency of aeration. Secondly, the increased biomass present during these months results in a higher biological oxygen demand (BOD) from both the fish and accumulated organic matter (excreta, uneaten feed, and biofilm). This effect may be more pronounced at points such as CT3 and CT4, where water circulation might be less efficient or aeration insufficient to meet the demand.

Furthermore, differences in the aeration system setup or water flow distribution may create microzones with suboptimal oxygen levels. The specific case of the decanter (DT), which showed a higher value (4.84 mg/L) in December, suggests that solids removal at that point may have temporarily reduced local BOD, unlike the active culture tanks.

Ammonium remained below 0.1 mg/L in September–October (no fish) but rose significantly from November to January, likely due to higher temperatures and insufficient biofiltration.

Nitrate exceeded safe levels (<110 mg/L) at several points, particularly at CT3 and the DT in November and December, possibly due to inefficient ammonium conversion or accumulation. Enhancing biofilter efficiency and water exchange is vital to maintain safe nitrogen levels.

4.3. Specific Water Quality Parameters in a RAS System

The pH values fluctuated throughout the study but generally remained within the tolerable range for aquaculture (6.7–9.0) [36]. However, during the first month post-stocking, levels dropped below optimal (5.90–6.10), likely triggering adaptive responses such as gill remodeling [60]. Similar physiological stress under low pH has been documented by Fivelstad et al. [61], albeit at a high energetic cost. No pH values above 9.0 were observed, avoiding detrimental effects on trout survival and appetite as noted by Fivelstad et al. [62].

Fluctuations in pH can influence other parameters. For instance, low pH increases dissolved CO₂, intensifying metabolic stress [63], a trend consistent with our observations and possibly mitigated through dietary adjustments and constant monitoring. Leduc et al. [64] reported reduced trout growth under unstable pH conditions, supporting the importance of early stabilization. Unlike Fivelstad’s controlled systems [63], where pH was stable from the outset, early instability here was attributed to groundwater inputs and an immature biofilter.

Alkalinity remained below recommended levels (75–150 mg CaCO₃/L) [7], with most readings barely above 40 mg/L. Its buffering capacity proved insufficient, likely contributing to pH-related stress. Despite minor increases after entering the tanks, values remained inadequate. Similar readings in the decanting tanks suggest organic matter decomposition did not enhance alkalinity [65,66]. Although fish survival and growth were not visibly compromised, persistent low levels warrant interventions such as sodium bicarbonate addition [67].

Potassium levels were stable (6.9–8.2 mg/L) during fish presence and within recommended ranges (5–20 mg/L) [37]. Slight increases when fish were absent (7.0–12.5 mg/L) may reflect system dynamics or external inputs. While not a contaminant, potassium is vital for osmoregulation [37], and in aquaponics, KOH supplementation helps regulate pH, enhance biofiltration, and support plant growth [68]. This highlights the potential for future integration of plant-based components in the system.

Phosphorus concentrations rose over time, reaching 40–43 mg/L—well above the aquaculture threshold (<0.1 mg/L) [40]. Feed is the main phosphorus source [69,70], and since fish retain only 15–40% of dietary phosphorus [71,72], the observed accumulation suggests inefficient utilization. Excess phosphorus may cause eutrophication and compromise system balance [69,70].

Initial levels of TDS exceeded trout farming recommendations (<400 mg/L) [36], with values of 450–510 mg/L in the absence of fish. After stocking, levels decreased (250–410 mg/L), possibly due to water changes aimed at nitrogen compound control. Although final levels were slightly above the ideal range, they remained within tolerable limits for freshwater species (<5000 mg/L) [37]. Still, elevated TDS can increase osmotic stress and energy demands [73,74].

Arsenic concentrations exceeded the trout safety limit (<0.05 mg/L) [36], with baseline values of 0.24–0.29 mg/L, likely linked to groundwater contamination, as reported in the Chilean Altiplano and other arid areas [75,76,77]. A slight post-stocking decrease may reflect adsorption onto particulates and organic matter, but levels remained unsafe. Arsenic accumulation in the decanting tank suggests the need for specific removal strategies. Mitigation options include adsorbent media such as activated iron oxide (GFO) [78], modified zeolites [79], or activated alumina [80], as well as ion exchange, pre-oxidation of As(III), and iron-rich or biofilter systems, especially in rural contexts. Selection should consider cost and performance, given the toxicological and food safety risks.

True color (TC) values increased from 5–8 Pt-Co (no fish) to 25–52 Pt-Co post-stocking, surpassing the recommended range (30–50 Pt-Co) [37]. This likely reflects dissolved organic matter accumulation. While not directly harmful to fish [81], elevated TC can reduce light penetration and affect filtration performance.

A principal component analysis (PCA) explained 64.8% of the data variability. The biplot showed a positive association between phosphoric acid and TC and inverse relationships between phosphoric acid and conductivity, arsenic, and salinity. These associations highlight potential indicators of water quality changes, warranting close monitoring.

Overall, the results underscore the importance of continuous water quality monitoring and adequate biological filtration and aeration to maintain optimal conditions for trout farming. Effective management strategies are essential to improve system efficiency and ensure sustainable operations in the Chilean pre-Andean region.

4.4. Impact of Fish Presence on Water Quality in the Culture System

The introduction of fish into the RAS disrupted the initial physicochemical stability, triggering significant changes in water quality [82]. Ammonium excretion, uneaten feed, and organic matter decomposition increased nitrogen compounds, altering chemical dynamics [83]. Fish respiration, along with microbial activity and biofiltration, further contributed to fluctuations in pH and DO.

While the pre-stocking phase showed more stable conditions due to the absence of biological inputs, this stability was artificial and unrepresentative of real aquaculture operations.

4.5. Variations in Water Quality Within the Recirculating System

Water quality varied between sampling points due to biological, chemical, and mechanical interactions within the RAS [84]. The holding tank showed higher temperatures, likely from solar exposure, while DO was lower in the culture tanks due to fish respiration and microbial activity [85].

Nitrogen compounds followed expected patterns, with biofiltration reducing ammonium and increasing nitrate concentrations [43]. Although inter-point differences were not marked, nitrogen transformation was evident.

TDS remained stable throughout the system, suggesting mechanical filtration was effective, though improvements could prevent accumulation in fish tanks. Conversely, pH fluctuated irregularly, possibly due to external or localized chemical factors. These spatial variations emphasize the need for targeted monitoring and control at each system stage.

4.6. Growth

Results align with literature reporting challenges in high-altitude RASs due to low atmospheric pressure [86], low groundwater alkalinity [87], and temperature fluctuations [88]. The feed conversion ratio (FCR) was 1.52, above the ideal 1.0 [89,90], indicating 50% more feed needed per kg of trout. This inefficiency may relate to stress-induced nutrient assimilation issues, shown by phosphorus accumulation post fish introduction. Mitigation includes bioavailable phosphorus sources, solid filtration, controlled feeding, and environmental stabilization [91].

The specific growth rate (SGR) reached 1.49%, lower than in comparable studies [92,93], likely influenced by altitude-related stressors, such as reduced oxygen solubility, thermal fluctuations, and low alkalinity. Management strategies include supplemental oxygenation [94], thermal insulation [95], alkalinity buffering [94], and adjusted feeding [96] to enhance growth and system resilience.

Water quality issues (low DO, elevated ammonia, and arsenic) are known stress factors affecting SGR and FCR in rainbow trout [97,98]. Despite this, survival and condition factors indicate adaptation potential under proper management, though possibly at the cost of growth.

Feeding rates affect SGR significantly; rates at 5% body weight/day increase SGR, whereas feeding to satiation reduces it [99]. Reported SGRs vary widely (Montaña [100]: 4.85–6.8%; Morales [90]: 0.07–3.35%). Environmental stressors (noise, weather) may have reduced appetite without impacting survival, but possibly lowering growth.

Weight increased by 298%, surpassing Sánchez et al. [39] (244.56%), with high survival (87.2–93.78%), consistent with previous findings [101]. The Fulton condition factor (k = 1.5–2.5, r² = 0.94) indicated good nutritional status and growth consistency.

4.7. Regulatory Standards for Water Quality in Fish Farming

Our analysis included a detailed evaluation of water quality parameters in relation to Chilean regulations for waters intended for aquatic life (NCh1333.Of78. Mod. 1987). This regulation considers a limited set of variables, such as pH, dissolved oxygen, alkalinity, turbidity, temperature, color, and the presence of hydrocarbons.

Although the values obtained in this study complied with the established limits, monitoring a broader range of parameters provided a more comprehensive assessment of water quality. This approach is crucial for ensuring sustainability in aquaculture systems, as factors such as the accumulation of nitrogen compounds, suspended solids, or variations in water hardness can impact the health of the organisms and the efficiency of the recirculation system.

4.8. Sustainability of the Culture

Rainbow trout farming in the pre-Andean region of northern Chile is a sustainable option under challenging environmental conditions, relying on water quality and energy efficiency. The use of clean technologies, especially photovoltaic systems, alongside effective water quality management, reduces environmental impact and supports long-term viability. Variations in spring water parameters such as temperature, pH, dissolved oxygen, and nutrients require constant monitoring and control within RASs to ensure fish growth and survival. Strategies like pH regulation and efficient biofiltration help minimize environmental impact and enhance productivity.

Despite higher operational costs at altitude—due to supplemental oxygenation, heating, and treatments like arsenic removal—water savings of up to 95% compared to open systems improve sustainability by reducing scarce water use [102]. The study evaluated solar energy use, benefiting from the region’s high solar radiation [42], which powers pumps and aerators, lowers emissions, and improves system resilience against electricity supply fluctuations [5].

Additional sustainability factors include waste management through recirculation and biofilters [103], alternative fishmeal diets [104], and potential integration of other aquatic organisms to boost resource efficiency and system resilience [105]. Overall, sustainable trout farming in this region depends on combining efficient water management and clean technologies like photovoltaic energy, reducing environmental footprints, ensuring economic viability, and fostering resilience to climate and resource challenges [106,107].

5. Conclusions

This study demonstrates that rainbow trout farming at 3000 m.a.s.l. is feasible under appropriate water quality management. Water parameters generally remained within the limits established by Chilean regulations for aquatic life, and fish growth during the cultivation period confirmed system viability. Variations in water quality across different points and over time highlight the need for continuous, site-specific monitoring to maintain system stability.

Additionally, this work contributes valuable evidence supporting the development of small-scale aquaculture and local producers in northern Chile, one of the world’s most arid regions. Aquaculture emerges as a viable strategy to diversify economic activities in these areas, which are traditionally dependent on agriculture and limited water resources. Future efforts should focus on optimizing feeding regimes, enhancing biofilter efficiency, and refining water recirculation protocols to better control nitrogen accumulation. In parallel, integrating renewable energy sources such as photovoltaic systems could improve the sustainability and operational efficiency of RASs in this environment, supporting long-term system resilience and reducing environmental impact.