Odiel River (SW Spain), a Singular Scenario Affected by Acid Mine Drainage (AMD): Graphical and Statistical Models to Assess Diatoms and Water Hydrogeochemistry Interactions
Abstract
:1. Introduction
2. Location Setting
2.1. Hydrological and Mining Framework
2.2. Climatic Framework
3. Materials and Methods
3.1. Sampling
3.2. Field Measurements
3.3. Water Chemical Analysis
3.4. Diatom Analysis
3.5. Statistical Analysis
4. Results and Discussion
4.1. Grouping of Sites
- Group 1 (Green): P1, P2, P4, P8 and 10, located in the Odiel riverbed.
- Group 2 (Red): P3, P5, P6 and PP9 located in highly contaminated tributaries (pH < 3).
- Group 3 (Orange): P11, P12 and P14, slightly affected by AMD (pH ~ 5), located in the Odiel River tributaries.
- Group 4 (Blue): P7, P13 and P15, uncontaminated (pH ~ 7).
4.2. Graphical Treatment
4.3. Statistical Treatment
4.4. Factor Analysis
- Factor 1: Water balance. The most (and positively) affected variables are ∑REE and, at a short distance, Eh. The meaning of this is that the greater the water balance, the greater the values of these two variables. This phenomenon has already been described by [76]. At the opposite extreme, the variable pH is found; this fact is the response to the logarithmic character of pH and also because at lower pH, the water acidity is greater, and thus, the dissolution capacity is greater. Close to pH are the Shannon–Wiener and richness variables, as expected, as for extreme/low pH, extreme/low richness and diversity were found, a fact already described by [6,8,50,78,79]. It should be remembered that this region has a negative hydric balance, so in some of the sampling points, water will be found just in the rainy season. This fact has a significant impact on the survival capacities of different diatom species; thus, both richness and Shannon–Wiener are negatively affected by Factor 2. The same happens with barium, spatially associated with the previous ones in Figure 5, as it is an external element of the primary paragenesis of polymetallic sulphides and its presence is due to the anthropic activity when used as a waterproofing agent.
- Factor 2: AMD Processes. AMD processes are a determinant factor for the values taken by the variables under study. In fact, the sulphides’ oxidation into sulphates causes a release of hydrogenions and, therefore, the pH is directly and negatively affected by AMD processes. At the opposite extreme of Figure 5, three variables are found, most closely linked to AMD, ∑Ficklin, sulphates and TDS, because these variables are very highly and positively influenced by Factor 2. Factor 2 also exerts a positive influence, but much more discreet, on the dissolved REE and Eh. The reasons are different: while REE solubility product conditions its position in Factor 2 lower “weights”, as many of them are more soluble than heavy metals, the Eh is somehow more affected than the previous ones, but clearly lower than the typical AMD indicators—note how this variable appears diametrically opposite to pH, giving almost a specular line at the origin. This fact was already described by [73,76].
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Sampling Point | pH | Eh (mV) /100 | TDS (mg/L) /1000 | Sulphate (mg/L) /10,000 | Barium (µg/L)/10 | ∑Ficklin (µg/L)/100 | ∑REE (µg/L) /10,000 | Shannon-Wiener Index · 2 | Richness /10 |
---|---|---|---|---|---|---|---|---|---|
1 | 7.16 | 2.37 | 0.18 | <0.01 | 4.40 | <0.01 | 0.01 | 6.22 | 4.20 |
2 | 6.99 | 1.41 | 0.17 | 0.04 | 4.16 | <0.01 | 0.04 | 5.14 | 3.40 |
3 | 2.92 | 4.36 | 4.08 | 0.51 | 1.22 | 1.23 | 1.77 | 2.68 | 1.30 |
4 | 4.01 | 3.65 | 0.82 | 0.09 | 3.07 | 0.13 | 1.87 | 5.14 | 3.70 |
5 | 2.99 | 4.77 | 2.71 | 0.35 | 0.79 | 0.21 | 2.76 | 0.88 | 0.50 |
6 | 2.64 | 4.52 | 4.12 | 0.80 | 0.65 | 1.53 | 0.78 | 3.24 | 1.50 |
7 | 6.90 | 1.95 | 0.16 | 0.01 | 7.82 | <0.01 | 0.09 | 2.22 | 0.80 |
8 | 4.43 | 2.13 | 0.68 | 0.06 | 2.29 | 0.08 | 1.25 | 5.64 | 3.50 |
9 | 2.78 | 4.39 | 9.95 | 3.07 | 0.36 | 7.42 | 1.29 | 2.98 | 0.60 |
10 | 3.96 | 3.08 | 0.47 | 0.04 | 1.95 | 0.05 | 0.78 | 5.08 | 4.30 |
11 | 5.60 | 1.80 | 0.83 | 0.03 | 2.47 | 0.01 | 0.52 | 1.78 | 1.40 |
12 | 4.70 | 3.03 | 1.29 | 0.01 | 2.04 | 0.08 | 1.41 | 1.82 | 0.70 |
13 | 7.70 | 0.42 | 0.31 | <0.01 | 1.32 | <0.01 | 0.02 | 5.82 | 3.60 |
14 | 4.90 | 2.19 | 0.60 | 0.03 | 1.96 | 0.02 | 0.52 | 4.58 | 1.60 |
15 | 7.10 | 0.60 | 0.44 | 0.01 | 1.85 | <0.01 | 0.03 | 3.06 | 1.60 |
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pH | Eh (mV) | TDS (ppm) | Sulphate (ppm) | Barium (ppb) | ∑Ficklin (ppb) | ∑REE (ppb) | Shannon Index | Richness | |
---|---|---|---|---|---|---|---|---|---|
Number points | 15 | 15 | 15 | 15 | 15 | 15 | 15 | 15 | 15 |
Average | 4.99 | 235.53 | 1787.07 | 3358.95 | 24.23 | 71.7 | 8768.29 | 1.88 | 21.8 |
Variation coefficient | 36.22% | 70.85% | 146.89% | 235.71% | 78.09% | 266.73% | 94.94% | 45.58% | 64.95% |
Minimum | 2.64 | 16.0 | 155.0 | 18.0 | 3.58 | 0 | 113.39 | 0.44 | 5.0 |
Maxima | 7.7 | 477.0 | 9950.0 | 30,707.0 | 78.2 | 741.6 | 2761.,1 | 3.11 | 43.0 |
Factor Number | Eingenvalue | % of Variance | % of Cumulative Variance |
---|---|---|---|
1 | 4.88 | 67.85 | 67.85 |
2 | 1.43 | 19.87 | 87.72 |
3 | 0.79 | 1.93 | 98.65 |
4 | 0.08 | 1.10 | 99.76 |
5 | 0.02 | 0.24 | 100 |
6 | 0 | 0 | 100 |
7 | 0 | 0 | 100 |
8 | 0 | 0 | 100 |
9 | 0 | 0 | 100 |
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Grande, J.A.; Luís, A.T.; Córdoba, F.; Leiva, M.; Dávila, J.M.; Fortes, J.C.; Santisteban, M.; Ferreira da Silva, E.; Sarmiento, A.M. Odiel River (SW Spain), a Singular Scenario Affected by Acid Mine Drainage (AMD): Graphical and Statistical Models to Assess Diatoms and Water Hydrogeochemistry Interactions. Int. J. Environ. Res. Public Health 2021, 18, 8454. https://doi.org/10.3390/ijerph18168454
Grande JA, Luís AT, Córdoba F, Leiva M, Dávila JM, Fortes JC, Santisteban M, Ferreira da Silva E, Sarmiento AM. Odiel River (SW Spain), a Singular Scenario Affected by Acid Mine Drainage (AMD): Graphical and Statistical Models to Assess Diatoms and Water Hydrogeochemistry Interactions. International Journal of Environmental Research and Public Health. 2021; 18(16):8454. https://doi.org/10.3390/ijerph18168454
Chicago/Turabian StyleGrande, José A., Ana Teresa Luís, Francisco Córdoba, Mercedes Leiva, José Miguel Dávila, Juan Carlos Fortes, María Santisteban, Eduardo Ferreira da Silva, and Aguasanta Miguel Sarmiento. 2021. "Odiel River (SW Spain), a Singular Scenario Affected by Acid Mine Drainage (AMD): Graphical and Statistical Models to Assess Diatoms and Water Hydrogeochemistry Interactions" International Journal of Environmental Research and Public Health 18, no. 16: 8454. https://doi.org/10.3390/ijerph18168454