}northeastern.edu/protect

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