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Characterization of Fate and Transport Processes and Contaminant Distribution in Karst Groundwater SystemsNorma I. Torres (norma.torres@upr.edu), Jonathan Toro-Vázquez (jonathan.toro@upr.edu), Elienisse Rodriguez (elienisse.rodriguez@upr.edu), and Ingrid Y. Padilla (ingrid.padilla@upr.edu)
Department of Civil Engineering and Surveying, University of Puerto Rico at Mayagüez
Introduction
Objectives
References
Methodology Preliminary Results
Study areaPuerto Rico Northern Karst
Aquifer system (Fig. 3a):
Fig. 3. (a) Hydrogeology of Puerto Rico
(b) Historical groundwater
contamination in the North
Coast of PR1
(a)
(b)
AB C
Previous studies in the
northern karst aquifers of Puerto
Rico show significant
distribution of contaminants
beyond demarked sources of
contamination1 (Fig. 3b).
Most extensive and
productive aquifer of the
island6.
Affected by a long history
of toxic spills, chemical
waste and industrial solvent
release into the subsurface7.
Contaminated sites has been under active remediation during the
past decades7.
Chlorinated Volatile Organic
Compounds (CVOCs)7
Solvents
Degreasers
Paint Removers
Study focuses on CVOCs (Fig. 4)
Characterize of fate and transport processes in karst groundwater
systems at laboratory and field-scales.
Assess spatial and temporal contaminant distribution of contaminants
in karst groundwater systems (regional scale).
Presence in the
environment
Presence in listed
superfund sites in PR and the US
Potential exposure
and human health
problems
Water quality records of regulatory agencies
(2011-2015)
Current sampling and analysis
(1981-2015)
GIS: spatial and temporal maps of
attributes
Detection maps
Concentrations distribution maps of total CVOCs
Total CVOCs=sum of the
concentrations of the detected
CVOCs in the study area
Proximity analysis
Descriptive
analysis, detection
frequencies per
site, sample, and
contaminant,
temporal
distribution of
contaminants
ANOVA
Chi-Square Test
Logistic regression
models
Tracer test study: Rhodamine and Uranine
2.0 g of Rhodamine and 3.2 g of Uranine were
injected in “El Tallonal Cave”(Fig. 8).
Fig. 8. Location of the sampling points in the Tallonal Cave
Incomplete recovery of tarcers (Fig. 9).
Method of moments was
used to determine the
coefficient of dispersion (D)
between the three points.
Karst aquifers:
Highly productive
aquifers1: characterized
by springs, caves,
sinkholes, interconnected
fissures, fractures and
conduits2 (Fig. 1).
Vulnerable to
contamination: high
capacity to store and convey
contaminants to zones of
potential exposure1 (Fig. 2).
Contamination may be
influenced by
anthropogenic and/or
hydrogeological factors5.
Fig. 1. Cross section of a karst aquifer3
Fig. 2. Groundwater flow in a karst system4
High heterogeneity and anisotropy:
Prevents accurate prediction in contaminant fate and transport.
Challenges in understanding the impacts of hydrologic conditions
changes on fate and transport processes.
Limited technologies to characterize and quantify flow and transport
processes at field-scale.
Dispersion among tracers varies with distance and flow rate (Fig. 7):
Dispersion values tend to increase with distance for both uranine and rhodamine wt.
Uranine and rhodamine dispersion tend to increase for high flow rates.
Rhodamine wt dispersion values are slightly higher than for uranine.
cm2/minRhodamine WT
Base Flow = 0.25 GPM Base Flow = 0.5 GPM Base Flow = 1 GPM
Uranine
Base Flow = 0.25 GPM Base Flow = 0.5 GPM Base Flow = 1 GPM
Limestone Length (cm)
Lim
esto
ne
Hei
gh
t (c
m)
145 cm
59
cm
59 cm
Karstified Limestone Physical Model (KLPM) (Fig. 5):
Rhodamine and Uranine tracers tests under several flow conditions
(Fig. 6.).
Fig. 5. Illustration of the
KLPM
3
4
1
2
7
8
5
6
9
12
11
10
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
IN OUT
Fig. 6. Scheme of the ports on the KLPM
Spatio-temporal concentration distribution (STCD) developed using
Golden Software Surfer v12.
Fate and transport parameters were estimated for multi-tracers using
CXTFIT code8 (Equation 1).
Equation 1. Dimensionless
Mobile-Immobile Equation
0
1000
2000
3000
4000
5000
6000
0 500 1000 1500
Conce
ntr
atio
n (
pp
b)
Time (sec.)
Concentration of tracers in point A
0
200
400
600
800
1000
0 500 1000 1500
Conce
ntr
atio
n (
pp
b)
Time (sec.)
Concentration of tracers in point B
0
50
100
150
200
250
300
350
400
-400 100 600 1100 1600
Conce
ntr
atio
n (
pp
b)
Time (sec.)
Concentration of tracers in point C
Rhodamine Uranine
Fig. 11 Detection frequencies and
concentrations of most detected CVOCs.
CVOCs were detected as single entities or mixtures in 64% of the samples and 77% of the
sites sampled (Fig. 10).
Most frequently detected CVOCs include: TCE, PCE, TCM, cis-1,2-DCE, 1,1-DCE and CCl4,
with average concentrations ranging from 0.0045 to 0.1203 mg/L (Fig. 11).
Results from the Moment analysis for the coefficient of dispersion:
Laboratory Scale
Methodology Preliminary Results
Points B-A C-B C-A
D (cm2/min) 1.62 4.14 3.22
Rhodamine Uranine
Points B-A C-B C-A
D (cm2/min) 0.94 3.83 2.88
Analysis showed that CVOCs total concentrations are significantly higher in:
Wells located in the upper aquifer, within areas of low sinkhole coverage and low
hydraulic conductivities, and wet season
Wells within a distance of 0 to 3.2 km from superfund sites, 3.2 to 6.4 km from RCRA-
CA sites, and more than 6.4 km from landfills.
Fig. 10. Detection of CVOCs in the study area
Analysis showed that detection of CVOCs are significantly higher
in:
Wells located in the upper aquifer, within areas of low and
intermediate sinkhole coverage, intermediate and high hydraulic
conductivities, and dry season (hydrogeological factors)
Wells within a distance of 0 to 3.2 km from superfund sites, 3.2 to
6.4 km from RCRA-CA, and 3.2 to 6.4 km from landfills
(anthropogenic factors).
Logistic regression model indicates that:
The detection of CVOCs in the karsts aquifers of NPR is influenced
by a combination of contaminant source and hydrogeological factors.
Conclusions
Total (average) CVOCs concentration (mg/L)
Spatial distribution of concentrations showed an extensive spatial
groundwater contamination with CVOCs from multiple sources (Fig. 12).
Fig. 12. Total CVOCs concentrations
distribution in the study area
At the lab scale, the spatial distribution of the estimated fate and
transport parameters for the tracers revealed high variability related
to preferential flow heterogeneities and scale dependence.
Field scale and lab-scale tracer analysis showed differences in fate
and transport parameters that result from different system conditions
at both scales (flow, dimensions, etc.)
The regional scale analysis of contaminant distribution suggested that
CVOCs are persistent contaminants in karst systems, even under
active remediation, they are present in groundwater for more than 30
years.
Detection and spatial distribution of CVOCs are influenced by the
type of source of contamination, and the characteristics of the karst
system.
Adequate characterization of flow, fate, and transport processes in
karst aquifers will enhance the ability to predict and minimized the
potential for exposure of contaminants to humans and ecosystems,
and provide tools for better decisions on the management of
groundwater systems.
(1) Padilla, I.Y., C. Irizarry, and K. Steele. (2011). Historical Contamination of Groundwater Resources in The North Coast Karst
Aquifers Of Puerto Rico, Dimensión, Año 25 Vol 3, 7-12, 2011.
(2) United States Geological Survey (USGS). (2012). USGS Groundwater Information. Retrieved January 13, 2013, from
http://water.usgs.gov/ogw/karst/pages/whatiskarst.
(3) Physical Geology . (nd). Laboratory 12-Groundwater Processes, Resources, and Risks. Retrieved November 10, 2015 from
http://www.ocean.odu.edu/~spars001/physical_geology/laboratory/laboratory_12/handout_laboratory_12.html
(4) United Nations Environment Programme. (nd). Groundwater: Water Flowing Under the Land Surface. Retrieved November 10,
2015 from http://www.unep.or.jp/ietc/Publications/Short_Series/LakeReservoirs-2/9.asp
(5) Torres, N.I., Yu, X., Padilla, I.Y., Macchiavelli, R.E., Ghasemizadeh, R., Kaeli, D., Cordero, J.F., Meeker, J.D., Alshawabkeh, A.N.
(2018). The influence of hydrogeological and anthropogenic variables on phthalae contamination in eogenetic karst groundwater
systems. Environmental Pollution, 237, 298-307.
(6) Lugo A.E., Miranda Castro, L., Vale, A., López, T. Del M., Hernández Prieto, E., García Martinó, A., Puente Rolón, A.R., Tossas,
A.G., McFarlane, D.A., Miller, T., Rodríguez, A., Lundberg, J., Thomlinson, J., Colón, J., Schellekens, J.H., Ramos, O., and
Helmer, E. (2001). Puerto Rican Karst-A Vital Resource, U.S. Forest Service Gen. Tech. Report WO-65.
(7) Padilla I.Y., Rivera, V.L., and Irizarry, C. (2015). Spatiotemporal Response of CVOC Contamination and Remedial Actions in
Eogenetic Karst Aquifers. Proceedings of the 14th Multidisciplinary Conference on Sinkholes and the Engineering and
Environmental Impacts of Karst, October 5-9, 2015. Rochester, Minnesota, pp. 337-345.
(8) Moran, M. J., Zogoroski, J. S., and Squillace, P. J. (2007). Chlorinated Solvents in Groundwater of the United States.
Environmental Science and Technology , 41, 74-81.
(9) Tang, G., M.A. Mayes, J.C. Parker and P.M. Jardine. (2010). CXTFIT/Excel-a modular adaptable code for parameter estimation,
sensitivity analysis, and uncertainty analysis for laboratory and field tracer experiments. Computers & Geosciences. 36(9): 1200-
1209. DOI:10.1016/j.cageo.2010.01.013
Fig. 4. (a) Importance of studying CVOCs, (b) Products where are CVOCs are
commonly found
(a)(b)
Fig. 7. Spatial distribution of the coefficient of dispersion on the KLPM.
Fig. 9. Concentration of tracers in points A, B, C
Preliminary ResultsMethodology
𝒗 = 𝟎. 𝟏𝟓𝒄𝒎
𝒎𝒊𝒏 𝒗 = 𝟎. 𝟑
𝒄𝒎
𝒎𝒊𝒏 𝒗 = 𝟎. 𝟐
𝒄𝒎
𝒎𝒊𝒏
𝒗 = 𝟎. 𝟏𝟔𝒄𝒎
𝒎𝒊𝒏 𝒗 = 𝟎. 𝟑𝟐
𝒄𝒎
𝒎𝒊𝒏 𝒗 = 𝟎. 𝟔𝟓
𝒄𝒎
𝒎𝒊𝒏
𝒗 = 𝟐𝟒𝟔. 𝟗𝒄𝒎
𝒎𝒊𝒏 𝒗 = 𝟐𝟏𝟎. 𝟑
𝒄𝒎
𝒎𝒊𝒏
𝒗 = 𝟐𝟐𝟔. 𝟖𝒄𝒎
𝒎𝒊𝒏
Preliminary Results (cont.)
Field Scale
Regional Scale
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