Mampostón sub-watershed is the smallest hydrological and hydrographic system of Mayabeque River basin in the center of Mayabeque province, Cuba. This hydrographic unit was remodeled in 1970 with the construction of two artificial reservoirs: Pedroso (with a capacity of 4 Mm³) and Mampostón (150 Mm³) (see figure 1). Both Mampostón and its tributary Ganuza rivers flow their waters (as well as their potential contaminant charge) into Pedroso reservoir. This water is pumped toward the Mampostón reservoir, which has no direct contaminant source, and it is subsequently sent to irrigate the crops in the South-West region of the most important agricultural zone of the western Cuban provinces, via the artificial channel Mampostón-Güira de Melena. Furthermore, the Pedroso reservoir has an overflow channel into the Mayabeque River and its waters are used to irrigate the sugar cane fields located on the eastside of the Mayabeque province. Additionally, an important aquaculture center is located on the Mampostón reservoir, focused in tilapia (Oreochromis spp), tench (Tinca tinca) and catfish (Clarias gariepinus) farming.

The presence of numerous and potential contamination sources in the area (for example, dairy, rum, paint and asphalt factories), whose residual waters are put into the basin tributaries, indicates a real possibility to contaminate the different pluvial ecological systems of the watershed. It is well know that sediments are the main repository of the pollutants in aquatic ecosystems.

In this sense, the main goal of the present research is to study the heavy metal content in sediments of the Mampostón-Pedroso hydrographic system, in order to evaluated its ecological status.

Sediment samples were collected at the beginning of the rainy season in 16 stations, and are located near the previously considered potential contamination sources (see figure 1): four stations in Ganuza river (G1 - 100 m north of a dairy factory, G2 - 50 m south of dairy factory , G3 - 100 m south of rum factory and G4 - 50 m south of paint factory); five stations in Mampostón river (M1 - 100 m south of aluminum factory and 50 m north of asphalt factory, M2 - 50 m south of asphalt factory, M3 - in the national highway bridge, M4 - free zone and M5 - 100 m south of a research center), four stations in Pedroso reservoir (P1 - Americano River flow into reservoir, P2 - Mampostón River flow into reservoir, P3 - south border of reservoir and P4 - overflow channel of Pedroso reservoir), and additionally, in three stations in Mampostón reservoir (PM1 - PM3). In all cases, sediment samples were collected in the middle of the rivers or five meters offshore in the reservoirs.

All samples were dried at 60^oC. Large rock debris, mollusk skeletons and organic debris were removed before sieving. The fine fraction (< 63 mm) was extracted by sieving and newly dried at 60^oC until obtaining a constant weight.

Metal concentrations were determined by external standard method of X-ray fluorescence analysis (XRF), using the Certified Reference Materials (CRM) IAEA-356, IAEA-Soil-5, IAEA Soil-7, BCR-2 and BCSS-1 “Marine sediment” as standards. All samples and CRM were mixed with cellulose (analytical quality) in proportion 4:1 and pressed at 15 tons into 5 grams pellets of 25 mm in diameter and 4-5 mm in height. Pellets were studied using Canberra Si(Li) detector (150 eV energy resolution at 5.9 keV, Be window thickness = 12.0 mm) coupled to a multichannel analyzer. A ²³⁸Pu (1.1 GBq) excitation source with ring geometry was used. All spectra were processed with WinAxil code [1[1] WinAxil code. Version 4.5.2. WinAxil [software]. CANBERRA: MiTAC, 2005.]. Detection Limits were determined according to Padilla et al. [2[2] PADILLA R, MARKOWICZ A, WEGRZYNEK D, et. al. Quality management and method validation in EDXRF analysis. X-Ray Spectrom. 2007; 36(1): 27-34.] (in concentration units) as LD = 3 σ/mt, where m is the sensibility in counts.seg^-1 per concentration unit, σ is the standard deviation of the area of the background windows (peak window at 1.17 times the FWHM) and t is the measuring time (4 hours).

The accuracy was evaluated using the SR criterion, proposed by McFarrell, et. al. [3[3] QUEVAUVILLER PH, MARRIER E. Quality assurance and quality control for environmental monitoring. Weinheim: VCH, 1995.]:

where: C_exp - experimental value, C_rep - reported certified value and σ is the standard deviation of C_exp. Based on this criterion, the similarity between the certified value and the analytical data obtained by proposed methods is divided into three categories: SR ≤ 25% = excellent; 25 < SR ≤ 50% = acceptable, SR > 50% = unacceptable. The analysis of five replica of the CRM IAEA-SL-1 is presented in table 1. All heavy metals determined by XRF analysis are “excellent” (SR ≤ 25%) and the obtained results show a very good correlation (r² = 0.9996) between certified and measured values.

The level of contamination was expressed using the modified degree of contamination (mCd), defined as [4[4] ABRAHIM G, PARKER R. Assessment of heavy metal enrichment factors and the degree of contamination in marine sediments from Tamaki Estuary, Auckland, New Zealand. Environ Monit Assess. 2008; 136(1-3): 227-238.]:

where: n is the number of analyzed elements, i the element and C_f the contamination factor, determined as

where: C_X and C_b are the metal content in studied sample and baseline, respectively. The classification of the sediments according to the modified degree of contamination (mC_d) is the following: mC_d < 1.5 - very low degree of contamination; 1.5 < mC_d < 2 - low degree of contamination; 2 < mC_d < 4 - moderate degree of contamination; 4 < mC_d < 8 - high degree of contamination; 8 < mC_d < 16 - very high degree of contamination; 16 < mC_d < 32 - extremely high degree of contamination; mC_d ≥ 32 - ultra-high degree of contamination. Independently that this method was developed for estuarine sediments, its use for marine and freshwater ecosystems is expanded, due the possibility to evaluate the impact of the contaminants to the biota and its possible risk to the human health.

In order to assess the possible risk to human health, numerical Sediment Quality Guidelines (SQGs) were used.

SQGs have been developed for many potentially toxic substances, i.e., trace elements, chlorinated organic, and polynuclear aromatic hydrocarbons [5[5] MACDONALD DD, INGERSOLL CG, BERGER TA. Development and evaluation of consensus-based sediment quality guidelines for freshwater ecosystems. Arch Environ Contam Toxicol. 2000; 39(1): 20-31.]. Sediments are thus classified as non-contaminated, moderately contaminated and heavily contaminated, based on the SQG of USEPA with the threshold effect level (TEL) and probable effect level (PEL) values [6[6] LONG ER, MACDONALD DD, SMITH SL, CALDER FD. Incidence of adverse biological effects within ranges of chemical concentrations in marine and estuarine sediments. Environ Manag. 1995, 19(1): 81-97., 7[7] United States Environmental Protection Agency. Office of Science and Technology. National Sediment Quality Survey EPA-823-R-04-007. Second ed. Washington DC, 2004.] In order to obtain a more realistic measure of the sediments toxicity, mean quotients were introduced according to the following equation:

where: C_i is the concentration of element i in sediments, PEL_i the guideline value for the element i and n the number of metals. PEL-Q is the probable effect level quotient. These mean quotients can be used in case of existence of multiple contaminants in the sediment, where the adverse effects caused by each chemical are additive and not antagonistic [8[8] VIOLINTZIS C, ARDITSOGLOU A, VOUTSA D. Elemental composition of suspended particulate matter and sediments in the coastal environment of Thermaikos Bay, Greece: delineating the impact of inland waters and wastewaters. J Haz Mat. 2009; 166(2-3): 1250-1260.]. The classification of sediments according to PEL-Q is as follows: PEL-Q values of < 0.1, 0.11 - 1.5, 1.51 - 2.3 and > 2.3 coincide with 10, 25, 50 and 76 %, of toxicity, respectively [9[9] McCREADY S, BIRCH GF, LONG ER. Metallic and organic contaminants in sediments of Sydney Harbour, Australia and vicinity-a chemical dataset for evaluating sediment quality guidelines. Environ Inter. 2006; 32(4): 455-465. ]. Consequently, four relative levels of contamination have been created (low, medium low, medium high and high).

Average concentrations and standard deviations of the studied heavy metal contents in sediments from the rivers and reservoirs from Mampostón sub-watershed are presented in table 2. In general, the metal content in Mampostón river, when compared to contents reported for other Cuban rivers, shows two patterns: it is lower than content reported for the contaminated urban rivers from Havana and Camaguey cities, and similar to those reported for rural rivers from Pinar del Río and Santiago de Cuba. The exception are the Cu and Zn contents in Ganuza river. On the other hand, the heavy metal content in Mampostón and Pedroso reservoirs are in the same order than those reported for other Cuban reservoirs.

The behavior of the Ni content in the studied stations (figure 2) show an irregular pattern, oscillating the Ni-PEL value. It is has been shown that a high Ni-content in Cuban soils and sediments is common. For example, in un-urbanized soils from Havana city was reported a Ni-content of 58 ± 13 mg.kg^-1 [16[16] DIAZ RIZO O, ECHEVARRIA CASTILLO F, ARADO LOPEZ JO, et al. Assessment of heavy metal pollution in urban soils from Havana City, Cuba. Bull Environ Contam Toxicol . 2011; 87: 414-419.], and the average natural Ni-content in Cuban agricultural soils was fixed in 294.2 mg.kg^-1 [17[17] RODRIGUEZ ALFARO M, MONTERO A, MUÑIZ UGARYE O, et al. Background concentrations and reference values for heavy metals in soils of Cuba. Environ Monit Assess . 2015; 187: 4198.]. For this reason, the origin of the Ni content determined in sediments from the Mampostón sub-watershed must be considered as natural.

On the other hand, Cu, Zn and Pb contents show a similar pattern: a maximum value in sediments from the station G2, and practically the same value in sediments from the rest of the studied stations. The comparison with SQGs (figure 2) shows those Cu concentrations in sediments from station G2 are potentially toxic, exceeding the Cu-PEL value in more than 10 folds, while Cu-content exceed the Cu-TEL level in the rest of the studied sediments. Moreover, the highest Zn and Pb contents were measured also in sediments from the station G2, exceeding the corresponding Zn-TEL and Pb-TEL values.

The contamination factors, modified degree of contamination (mC_d) and probable effect level quotient (PEL-Q) values are shown in table 3. Taking into account that Mampostón reservoir is not directly impacted by the different possible contamination sources of the studied area, its average metal contents (see table 2) were taken as baseline to estimated the contamination factors.

The estimated mC_d values indicate that sediments from station G2 are highly contaminated with Cu, Zn and Pb, while sediments from the stations G1, G3, G4, P1 and P2 are lowly contaminated with the same metals. Independently of the results for mC_d, the estimated PEL-Q values (figure 3) show a high degree of contamination for the sediments from the station 2 in Ganuza river, and medium low contamination for the sediments collected in the rest studied stations in Ganuza and Mampostón rivers and Pedroso reservoir, i.e. the 100 % of the sediments from Ganuza-Mampostón rivers and Pedroso reservoir are associated with occasional observation of possible adverse effects.

The sediments collected in Ganuza and Mampostón rivers and in Pedroso reservoir (Mampostón sub-watershed (Mayabeque, Cuba) have shown higher Cu, Zn and Pb contents compared to those collected in Mampostón reservoir. The application of mC_d index classifies as highly or lowly contaminated sediments from Ganuza river and from two of the studied stations in Pedroso reservoir. The application of SQGs and toxicity mean quotients show that 100% of the sediments are associated with occasional observation of possible adverse effects, especially for Cu, Zn and Pb. Taking into account the obtained results, the study of heavy metal content in edible muscle from fish species cultivated in Mampostón reservoir and fishes from Pedroso reservoir is recommended.