cost analysis to manage viral contamination of groundwater

~

Pergamon

Wat. ScL Tech. Vol. 38. No. 12, pp. 1~. 1998. C 19981AWQ

Published byElsevier ScienceLId

Printed in Great Britain. Allrights IeIer'ied

PIT: S0273-1223(98)00792-6

0273-1223198 S19"00+ 0110

A RISK/COST ANALYSIS TO MANAGE VIRAL CONTAMINATION OF GROUNDWATER D. D. Adelman", J. Stansbury** and M. A. Tabidian*** • Nebraska Natural Resources Commission, P.O. Box 94876, Lincoln; NE 685094876, USA •• 129Engineering Building, University ofNebraska-Lincoln; Omaha, NE 68182-0178, USA ••• Department o/GeologicalSciences, California StateUniversity, Northridge, CA 91330-8266, USA

ABSTRAcr Under the proposed groundwater disinfection rule of the 1986 Safe Drinldng Water Act. municipal water systems have four optionsto demonstrate that naturaldisinfection of viruses occursbetween the virussource and the municipal well. One option is to demonstrate that the necessary set-bade distance exists between these facilities. The objective of this research was to evaluatethe risk that virusconcentrations at a municipal well wouldexceedrecommended levelseven thoughthe virussourcewas separated fromthe well by the setbackdistancerecommended by the EPA. Groundwater transportmodeling was used to evaluatethis risk and computethe necessary distanceupgradient from each Nebraska municipal well for sufficientvirus die-off to occur. The numberof wells with computed die-off distances greater than the regulatory set-backdistances weredivided by the total numberof wells.The results of this researchshow that the potential risk for virus concentrations will exceed recommended virus levels in municipal wells using EPA's set-backdistances. lCl 1998lAWQ Published by ElsevierScienceLtd. Allrightsreserved

KEYWORDS Adsorption; advection; die-off; groundwater; risk; cost; set-back distances. INTRODUCTION The 1986 amendments to the Safe Drinking Water Act require disinfection of all public water supply wellhead discharges. The disinfection rule is intended to protect water supplies from contamination from bacteria and viral sources. Groundwater virus sources include wastewater treatment lagoons, sanitary sewers, sanitary landfills and septic tanks for individual dwellings. In order to obtain an exemption to disinfection, water systems have four options to demonstrate natural disinfection will occur between a virus source and a municipal well (Grubbs and Pontius, 1992). One option is to demonstrate that the time it takes for groundwater to travel from a virus source to a municipal well is sufficient for viruses to die-off to recommended levels. The second option is to demonstrate that the time it takes for a virus particle to travel from a virus source to a municipal wen is sufficient for viruses to die-off. The third option is to demonstrate that "a hydrogeologic feature, such as a thick unsaturated zone, controls potential contaminant flow to the

2

D. D. ADELMAN er al.

well and human activities will not adversely affect the integrity of the feature" (Grubbs and Pontius, 1992). The fourth option is to demonstrate that the necessary set-back distance exists between the virus source and a municipal well for the viruses to die-off. This latter option is generally felt to be the easiest to apply. The US Environmental Protection Agency (EPA) proposed set-back criteria for Nebraska to be 160m. Within the state of Nebraska, more than 2,000 wells falling under the groundwater disinfection rule are used for public water supplies. The objective of this research was to evaluate the risk that virus concentrations at a municipal well would exceed recommended levels even though the virus source was separated from the well by the EPA recommended set-back distance. Cost values for each alternative arbitrary set-back distance were also computed. A multi-criteria decision-making technique, called composite programming (Bogardi et al., 1986), was used to select the most feasible alternative based on these two criteria of risk and cost. METHODS TO COMPUTE SET-BACK DISTANCES Unsaturated zone model - five mechanisms are involved in microbial transport in the unsaturated zone: adsorption, advection, die-off, dispersion and filtration (Gerba et al., 1991). Two processes are generally found to be negligible for virus transport in the unsaturated zone composed of mainly coarser sediments. These are filtration (Gerba et al.• 1991) and dispersion (Yates et al., 1987). Advection, or the mechanism by which soil moisture transports a solute (or microorganism) through the unsaturated zone, is governed by the Buckingham-Darcy Equation (Marshall and Holmes, 1979). This equation assumes the hydraulic conductivity is a function of soil moisture, which varies considerably in the unsaturated zone. Adsorption of virus particles to soil is incorporated into the virus transport model by applying a retardation factor (Gerba et al., 1991). Combining these relationships, the travel time for viruses to be transported from a virus source through the unsaturated zone to the water table is calculated using the following relation (Lokke, 1992):

twt = o-e,*R)/q

(I)

where:

lwt z

e

y

R q

=travel time of viruses through the unsaturated zone to the water table, T; =unsaturated zone depth, L;

= volumetric soil moisture content of the unsaturated zone, dimensionless;

= retardation factor (Gerba et al., 1991), dimensionless

=infiltration rate, LIT.

The third virus transport process, die-off, can be modeled with rust order kinetics (Yates and Yates, 1990) using the relation:

(2) where:

= virus concentration at the water table or bottom of the unsaturated zone, Plaque Forming Unit (PFU)/J.);

=initial virus concentration (EPA, 1992), 10,000 PFUIL

= first order kinetics rate constant which is a function of subsurface temperature (Yates et al., 1987), lIT. The rate constant was calculated from a linear regression equation discussed by Yates et al (1987) where the independent variable was subsurface temperature and the dependent variable was the rate constant. The regression equation is based on die-off rate constants for several different waterborne virus species. The results of this research should be applicable to most types of waterborne virus species. Saturated zone model - virus transport was also modeled in the saturated zone considering adsorption, advection, and die-off while dispersion and filtration were again assumed to be negligible. In the saturated

Viralcontamination of groundwater

3

zone, advection consists of two parts: the groundwater flow due to background groundwater velocity and the groundwater velocity due to the pumping well. The former is computed with Darcy's equation while the latter is a function of well capacity, aquifer effective porosity and saturated thickness. These combined velocities divided by a retardation factor give a virus velocity value that is a function of both advection and adsorption. Die-off was again assumed to be a function of first order kinetics. Using that relation, the travel time required in the saturated zone to reduce the virus concentration from that at the water table (CwJ to the acceptable concentration at the well (C f) is: tsz

=(In(Cf I ewe» I (-k)

(3)

where: tsz

Cr

=Virus saturated zone travel time required to reach acceptable die-off, T; and =Final virus concentration, 1 PFUIlO' Liter (EPA, 1992).

Simulation procedure - Nebraska was divided into six unsaturated zone regions with similar characteristics. Model parameters for the unsaturated zone model were assigned based on the characteristics of each of these regions. The variable lwt in equation I was computed for a well out of the 2,000 Nebraska municipal wells. The virus concentration at the water table (CwJ was then computed using equation 2 and input to equation 3 to compute tsz. This is the travel time required in the saturated zone to reduce the virus concentration to an acceptable level. A longitudinal groundwater flow distance in the saturated zone corresponding to tsz (i.e. the distance required to reduce the virus concentration to acceptable levels) was based on the following equation (Bear and Jacobs, 1965): tt

=«n·R)/(K·i»·(x-(Q/(6.28·K·b·i»·ln(l+«6.28·K·b·i)/Q)·x»

(4)

where: tt

n K i x Q b

= virus particle travel time, T;

=porosity for county that well exists in, dimensionless;

= saturated zone hydraulic conductivity, 114.3 m1day(EPA, 1992); = hydraulic gradient, 0.0001 mlm (EPA. 1992);

=longitudinal distance incremented in steps of 1.52m; =well capacity for each municipal well, Orr; =aquifer saturated thickness for each municipal well, L.

The variable x in equation 4 was initially set equal to 1.52m and the variable tt calculated. If this above travel time was less than tsz, the longitudinal distance was incremented by 1.52m and a new travel time computed. The longitudinal distance was incremented until the travel time was the same as tsz. The calculated longitudinal groundwater flow distance was the set-back distance necessary for die-off to reduce virus concentrations to acceptable levels at the well. The same procedure was followed for the other 2,000 wells. Once the needed set-back distance was calculated for each well, these distances were compared to six potential regulatory set-back distances of 30,61,91, 122, 152 and 183m. This total was divided by the total number of municipal wells. The fractions of wells with needed set-back distances exceeding each selected potential regulatory set-back distance is the potential probability (risk) that excessive virus levels may occur in the wells. The risk decreases as the required set-back distances increase and the virus source depth decreases. EPA has proposed 160m (525 feet) as the required set-back distance for Nebraska given its average groundwater temperature of 15°e. The modeled set-back distance would represent the longitudinal component of a virus source wellhead protection area. The lateral distance of this protection area was computed using the following relation:

4

D. D. ADELMAN et al.

w = Q/«SdistltsV·b)

(5)

where: w =lateral distance (width), L; Sdist = modeled set-back distance, L. An average lateral distance for wells with needed set-back distances exceeding each selected potential regulatory set-back distance was computed. This average lateral distance was multiplied by each potential regulatory set-back distance to calculate wellhead protection areas for each of those set-back distances. This area was multiplied by a typical unit land cost. Although this land would not necessarily need to be purchased, this cost represents the relative cost associated with each potential regulatory set-back distance. Each alternativecost was normalized, or made a decimalfractionof one, using the relation:

Nest

=(Costx·MinimumCost)/(Maximum Cost-Minimum Cost)

(6)

where: L Cost, MinimumCost MaximumCost Nest

=cost for each potential regulatoryset-backdistance "x" cost, dollars; = least cost alternative,dollars; =highest cost alternative, dollars; =normalizedcost, dimensionless.

Like cost, risk was normalizedwith an equation similar to equation.6.

Filtration and dispersion - Gerba et al. (1991) published default and worst case parameter values to model the five subsurfacemicrobial transportmechanisms(adsorption,advection,die-off, dispersion and filtration). As discussed earlier, filtration and dispersion are assumed to be negligible in this research and were not modeled. Gerba et al (1991) stated that filtration would be negligiblein coarse textured materials like gravel in the subsurface saturated zone. However, finer sediments are known to exist in the unsaturated zone in Nebraska and the assumption of negligible filtration in these fine sediments and the effects of dispersion may need further study. Using data from Gerba et al (1991) the following relation may be used to analyze the importanceof filtration in the unsaturatedzone:

(7) where:

C Co Lambdllt

z

=virus concentrationat depth z, PFUIL; .. initial virus concentration, 10,000PFUIL; .. filtration coefficient,dimensionless; = unsaturatedzone depth, L.

Additionof a dispersion component to the saturatedzone model may be possible using the following relation (Bear, 1979):

(8) where: C(x,t) Co

C1

erfc R

=concentrationat longitudinal distance x after time t, MlL3; =concentrationat negative infinitedistance; .. concentrationat positive infinitedistance; =complementaryerror function .. retardation factor, dimensionless;

6

~ 1.2 a.

I

1

~ 0.8 § J9 0.6

.!!I

o

~0.4

~

c:

·~0.2 c: Ql

~

0 20

40

60 80 100 120 140 160 180 200 Setback Distances, meters

- dpth=1.2m - depth=1.8 ... depth=2.4 .... depth=3.1 ....depth=3.7 Figure2. Virussourceset-backdistances for variable virussourcedepths.

Figure 2 shows the computed trade-off distances for five different virus source depths . The optimum (based on risk-cost trade-off) required set-back distances for virus source depths of 1.2. 1.8. 2.4. 3.1, and 3.7m are 61.61.91.4.121.9. and 121.9m respectively. CONCLUSIONS EPA (1992) has proposed a set-back distance of 160m for municipal wells in Nebraska. This set-back distance represents a significant cost for utilities. This study shows that, based on risk-cost trade-off. less conservative set-back distances may be more appropriate. This appears to be especially true for shallowdepth virus sources .

REFERENCES Bear.J. (1979). Hydraulics of Groundwater. McGraw-Hili. Inc,New York,567. Bear,J. and Jacobs,M. (1965).On the movement of waterbodiesinjected into aquifers. J. Hydrol. , 3, 37-57. Bogard], I.. Kelly,W. B. and Fried,J. (1986). Risk versuscost in groundwaternitratepollution. ProcoftM Agriculturallmpacu 011 GroundWater· A COllferellce, National WaterWellAssociation, August11-13, Omaha, Nebraska, 482-507. EPA (1992). DraftGround·Water Disinfectioll Rule. EPA-81l1P·92·00I, Officeof Water. US Environmental Protection Agency, Washington, DC. Gerb&, C. P.• Yates, M. V. and Yates, S. R. (1991). Quantitation of factors controlling viral and bacterial transport in the subsurface. In "Modeling the Environmental Fate of Micro-Organisms" edited by C. J. Hurst, American Society for Microbiology, Washington. DC, 77-87. Grubbs. T. R. and Pontius,F. W. (1992).USEPAreleases draft groundwaterdisinfection rule. J Am Waf Wl:.r Ass. 84(9),25-31. Lokke, D. M. (1992). Vadose Zone Travel Time Modeling WithApplication to Nitrates. Unpublished MS Thesis, University of Nebraska·Lincoln, 174. Marshall, T. J. and Holmes, J. W. (1979). Soil Physics. Cambridge University Press. UK,345 p. Yates, M. V., Yates, S. R., Wagner, J. and Gerbe, C. P. (1987). Modeling virus survival and transport in the subsurface. J. Contaminant Hydro!.• I, 329-345. Yates,M. V. and Yales,S. R. (1990). Modeling microbial transport in soil and groundwater. ASM News. 56, 324-327.