Supplementary Figures and Tables

OSDS Validation The existence of OSDS in West Maui 2017 was validated by identifying the current status according to Maui County Wastewater Infrastructure Records (Table S3), and confirmed by a field team in West Maui, who identified sewer mains, and contacted local residents, property managers, and county representatives.

OptionsWe initially considered incorporating connection to sewer as an additional option, but it was screened out as beyond the scope at this stage for three reasons: 1) although county actions do focus on connection to sewer, current state policy is focused on supporting upgrades, 2) benefits were entirely dependent on treatment efficacy, 3) costs were deemed too variable to contribute to a meaningful cost-benefit analysis without much further consultation with additional parties.

OSDS in Hawaiʻi are classified by a) the type of wastewater treatment system, which treats wastewater by mechanical or biological means to reduce harmful contaminants, and b) the type of wastewater disposal system, which discharges the treated wastewater into the environment (Table 1; Whittier and El-Kadi, 2014). The most common OSDS in West Maui are cesspools, which have no wastewater treatment. The next most common are septic systems that discharge to a leach field. Waste collects in a tank, where solid material passively separates and settles, and lengths of perforated pipe distribute liquid effluent across the surrounding soil where natural filtering and bacterial action remediates some of the wastewater contaminants before entering the groundwater. OSDS types vary in their capacity to remove nitrogen from wastewater (Table 4), and installation, operation and maintenance costs (Table S4). They are also subject to different constraints to their utilisation (Table S3, Figure S2).

Table S1. OSDS Classes

OSDS Class Individual Wastewater System and Disposal TypeClass I Any system receiving soil treatment. This includes disposal types listed as

bed, trench, and infiltration/chambers. Class II Septic systems discharging to a seepage pit. The effluent receives primary

treatment only.Class III Aerobic units discharging to a seepage pit. The effluent receives primary

and secondary treatment.Class IV All cesspools where the effluent receives no treatment.Note: Seepage pits are dry wells that disperses effluent from septic tanks. The effluent receives no treatment other than settling of solids that occurs in the septic tank.

Table S2. Matrix of system nitrogen reduction rates by each treatment-disposal combination. Numbers represent: % of influent nitrogen remaining in system effluent after treatment (Whittier & El Kadi 2009, WRRC 2008, WRRC Report 2015-01). In all cases, nitrogen reduction rates are dependent upon good system maintenance.

Cesspool SepticATU

NSF 40

AdvancedTreatment

NSF 40/245

100 66 57 47None 100 0     53

Seepage Pits 100   34 43 53Leach Field 59   61 66 72=Infiltration

Chambers 59   61 66 72

Drip Irrigation + Standard 59     66 72

Evapotranspiration 59     66 72

Constraints

Table S3. Matrix of site condition recommendations, adapted from WRRC (2008); NR = Not Recommended, P = Possible, R = Recommended. ATU = Aerobic Treatment Unit.

Treatment   Disposal 

Site conditions influencing selection of treatment and disposal system Se

ptic

ATU

NSF

40

Adv

ance

dTr

eatm

ent

NSF

40/

245

Seep

age

pit /

Leac

h Fi

eld

/ In

filtra

tion

cham

ber /

be

ds /

Drip

Ir

rigat

ion

Evap

otra

n-sp

iratio

n

High water table P R R NR NR R PImpermeable soil or rock formation P R R P NR R RSteep terrain P R R R NR R NR

Flood zonesNR NR NR NR NR NR NR

Close to inland surface water (both streams and other bodies of water)

NR R R NR P R P

Close to coastal waters P R R P P R PHigh density of cesspools P R R NR P R PProtection of groundwater resources P R R P P R RProtection of drinking water P R R NR NR R RHydrogeology P R R P P R P

Our analysis doesn’t take into consideration fine-scale site restrictions such as minimum distance to large trees, property lines, etc. (OSDS spatial data is TMK centroid, not exact location of system). But as these restrictions apply generally, to all types of systems, and our analysis involves upgrades (rather than entirely new systems), we assumed that these criteria were previously met.

Costs

Table S4. Cost Assumptions

*Operation & maintenance (O&M) costs are estimated as annual averages** All costs are general estimates; can vary with specific site conditions

TREATMENT SYSTEMSCost ($) Notes Reference

Cesspool:

Initial Installation 15,000

*not included in cost calculations; analysis does not consider new cesspools (illegal) WRRC (2008)

O&M Pumping 200 $150-550 per visit, every 2-3 yrs WRRC (2008)

Septic:

InitialInstallation and material 9,850

Mid-value of $7,000-12,700 range; includes material, equipment, labor WRRC (2008)

O&M Pumping 200 $150-550 per visit, every 2-3 yrs WRRC (2008)

ATU - International Wastewater Tech

Initial Tanks 10,000

(AQUA Engineering and Coral Reef Alliance, 2015)

Installation 22,000

(AQUA Engineering and Coral Reef Alliance, 2015)

Electrical install 3,000

(AQUA Engineering and Coral Reef Alliance, 2015)

Total initial costs 35,000

O&MInspections & Service 750

(AQUA Engineering and Coral Reef Alliance, 2015)

Septage pumping 550

(AQUA Engineering and Coral Reef Alliance, 2015)

Pump/blowers 2,309

15 kWhr/day, with power rates @ $0.4217, based on 2013 residential power estimates given from Hawaiʻi Electric Light Company

(AQUA Engineering and Coral Reef Alliance, 2015)

Total Operating 3,609

Costs/Annum

ATU WaiPono Pure

Initial

Tank(s), installation, and materials 18,000

(WaiponoPure, 2017, April)

O&MInspections & Service 900

Quarterly inspections for first two years; bi-annual thereafter

(WaiponoPure, 2017, October)

Power Consumption 180

$15/month; air compressor 71W continuous; effluent pump 1/2 HP, 115V, 60Hz, 10.0A, 12 mins/hour

(WaiponoPure, 2017, October)

Spare & Replacement Parts 112.50

Air compressor $180 every 3 years; effluent pump $315 every 6 years

(WaiponoPure, 2017, October)

Other* 100Contingency for service adjustments & parts

(WaiponoPure, 2017, October)

Total Operating Costs/Annum

1292.50

DISPOSAL SYSTEMSSeepage pitInitial Installation 10,000 WRRC (2008)O&M Pumping 200 $150-550 per visit, every 2-3 yrs WRRC (2008)

Leach fieldInitial Installation 12,500 Mid-value of $7,000 – 18,000 range WRRC (2008)

O&M

Replacement costs for septic system leach fields 8,750

Leach fields of septic systems typically fail within 7 years due to contaminant loading in soil; replacements costs estimated as 70% of installation cost. Note: this would not be required as frequently with advanced treatment systems.

Dennis Poma, Nguyen Le pers. comm.

Drip irrigation

Initial Installation 22,000

The costs associated with the specific systems for recycling water are quite specific; can vary drastically

Dennis Poma, Nguyen Le pers. comm.; WRRC (2008)

O&M 0

Without a definitive concept of a proposed system, O&M costs cannot be generalized WRRC (2008)

EvapotranspirationInitial Installation 20,000 Mid-value of $15,000 – 25,000 range WRRC (2008)

O&M Inspection 20

Simple inspection of observation wells; plus electrical costs for pumping when needed WRRC (2008)

Figure S1. Lifetime (30-yr) cost of upgrades, in USD (2017) (Calculated based on Supplementary Table S2) in $/km within each flow tube of each alternative.

Groundwater and Transport Modeling

BackgroundPollution can be delivered to the reef via surface water and subsurface groundwater transports. Both transport processes will deliver dissolved contaminants, but particulate contaminants are primarily delivered in large quantities by surface water transport. Due to the combined effect of soil filtration and slow transport velocities of groundwater relative to surface water, groundwater only delivers dissolved pollutants (Storlazzi and Presto, 2005; Street et al., 2008). Within the study area where wastewater is generated, the streams are ephemeral in the lower elevations (Gingerich and Engott, 2012; Glenn et al., 2012; Street et al., 2008) resulting in groundwater discharge being the primary nutrient delivery process. While the episodic surface water discharges deliver a large sediment load to the ocean, it is chronic discharge groundwater that delivers the majority of the nutrient load (Glenn et al., 2013a; Street et al., 2008). The focus of this paper is cost/benefit analysis of wastewater which is disposed of in the subsurface and delivered to the reef making coastal and submarine groundwater discharge the focus of this research.

Wastewater contains a plethora of contaminants primarily pharmaceuticals and personal care products (PPCPs), disease causing microbes, dissolved organic matter resulting in high biological and chemical oxygen demand, and highly elevated nutrient concentration (nitrogen and phosphorus species predominantly) (Hunt, 2007; Hunt and Rosa, 2009; Lowe et al., 2007). Each of the pollutants must initially be considered when evaluating benefits that can be realized from wastewater disposal system upgrades.

Wastewater PPCPs in groundwater appear to not be a significant threat to coastal ecosystems in Hawaii. Only a few PPCPs at trace levels have been detected in Hawaii groundwater that is influenced by wastewater disposal. These include Amoxicillin, caffeine, sulfamethoxazole, and Carbamazepine in wastewater impacted groundwater (DOH, 2018b; Hunt, 2007; Hunt and Rosa, 2009; USGS, 2016), There have been no detections of endocrine disruptors in wastewater influenced groundwater in Hawaii.

Pathogens in wastewater pose a health risk to humans that come in contact with sewage contaminated waters. As described above the transport of wastewater to coastal water where human contact may occur is a subsurface process. To pose a health risk that should be considered in the cost/benefit analysis, the pathogens must survive the subsurface transport process and arrive at the coastal groundwater discharge points in sufficient numbers to be infectious. A 105 pathogen removal rate from wastewater concentrations was used by Crockett (2007) as the threshold that would reduce the annual risk of infection to 1 in 10,000 in a population exposed to water that had been subject to this magnitude of pathogen reduction. The first step in reaching the 105 population reduction threshold occurs in the soil. Tasato and Dugan (1980 ) found a 70 to 90 percent reduction if the population fecal indicator bacteria (Fecal Streptococcus, Fecal Coliform, and Total Coliform) when domestic wastewater was passed through a soil lysimeter containing Hawaii soils. This is followed by long transport times. Salmonella and Fecal Streptococci, the most persistent pathogens assessed, would reach a 105 population reduction in about 92 days compared to 12 days for Coliforms. With groundwater velocities much less than a meter to 4 m/d, only OSDS located within 0.5 kilometer of the coast would pose a health risk. This is a conservative estimate since it does not account for vadose zone travel time or the dilution effect that occurs when the contaminated groundwater is discharged into the coastal waters.

Nutrients remain as the primary contamination risk to coastal waters. Of the nutrients, nitrogen and phosphorus are the primary wastewater related nutrients that are delivered to the nearshore marine ecosystems (Glenn et al., 2012; Hunt, 2007; Hunt and Rosa, 2009). Nitrogen historically has been considered to be the limiting nutrient in nearshore marine ecosystems (National Academic Press, 1993). Nitrogen as a limiting nutrient in marine ecosystems is also indicated by more recent research (Braken et al., 2015; Elser et al., 2007). In Hawaii, phosphorus from domestic wastewater disposal poses a much lower risk to the nearshore marine ecosystems than nitrogen, since the domestic wastewater is discharged into the soil. Phosphorus sorbs on to the soil greatly reducing the mass of this contaminant delivered to the groundwater (Manahan, 2004). By contrast, the nitrogen concentrations in the groundwater down gradient from the large concentration of cesspools was found to be significantly elevated with a maximum nitrogen concentration of 13.7 mg/L and a maximum nitrate concentration that was nearly 9 mg/L, while the maximum total phosphorus concentration was less than 0.2 mg/L (DOH, 2018b). For the reasons stated above, nitrogen became the metric of this study for the cost/benefit analysis domestic wastewater system upgrades.

The speciation of nitrogen changes significantly from what is present in raw wastewater to that which is ultimately discharged to the marine ecosystems by groundwater. Initially the dominant nitrogen species in raw wastewater the organic form urea (CH4N2O) (Lowe et al., 2007 and 2009). Much of the urea mineralizes to inorganic nitrogen as ammonia (NH3) and predominantly to the ionic form ammonium

(NH4+). The ammonium ion is stable as long as the wastewater is anaerobic. Under aerobic conditions

ammonium is oxidized to nitrite (NO2-) then to the fully oxidized species, nitrate (NO3

-). Nitrite is a short-lived intermediary between ammonium and nitrate. When analysed for, nitrite is not detected or is only found in trace concentrations in Hawaii basal groundwater (DOH, 2018b; Hunt, 2004; Hunt and Rosa, 2009; USGS, 2016). When water is aerobic nitrate is stable making it by far the dominant species of dissolved inorganic nitrogen. Maui’s basal groundwater resides in lava rock aquifers that are aerobic with saturations percentages greater than 80% being the norm (DOH, 2018b; Hunt and Rosa, 2009) resulting in nitrate being a persistent and mobile contaminant, and the dominant species of dissolved inorganic nitrogen in the groundwater discharging to the nearshore marine ecosystems.

A significant fraction of the dissolved nitrogen in raw wastewater occurs in the organic form. Most scientific literature focuses on the nutrient loading from dissolved inorganic nitrogen (DIN) since this form is most readily available for algae growth. However, there is increasing interest in the nutrient loading from dissolved organic nitrogen (DON). Since modern wastewater treatment is becoming more effective at reducing DIN, DON a higher fraction of the total nitrogen load. In some cases the DON fraction in treated wastewater is greater than the DIN fraction (Qin et al., 2015). While the fraction of total nitrogen that is DON can be significant, from a cost/benefit analysis perspective it the relative impact on the nearshore marine ecosystems that is important. Qin et al. (2015) investigated the fraction of DON that plays a role in accelerating algae growth. They found that 28 to 61 percent of the DON exhibited bioavailability for algae uptake. A review of available wastewater data for Hawaii shows that DON accounts for 2 to 38 percent of the total dissolved nitrogen with an average value of 24 percent (Glenn et al., 2012; Hunt, 2007; Hunt and Rosa, 2009; USGS, 2016). When passed through a soil lysimeter that fraction decreases to 12 percent (Tasato and Dugan, 1980 ). Applying these results to coastal nutrient load in Hawaii, bioavailable DON only accounts for 10 percent or less of the biologically available nitrogen load within the study area. Investigating the nutrient cycle in detail is not the primary focus of this study. Since the role of DON in the coastal nutrient enrichment is still being investigated and that DON is a small fraction of the bioavailable nitrogen load, we choose to focus on the reduction of DIN as metric for our cost benefit analysis. We use “nitrogen” to refer to all species that result in biologically available nitrogen to the nearshore ecosystem since there is significant species transformation from point of wastewater discharge to coastal discharge of sewage contaminated groundwater. It is important to note that at the point of groundwater discharge into the nearshore marine ecosystem, nitrate dominates the biologically available nitrogen for West Maui (see discussion above).Nitrogen, and predominantly nitrate, is the primary contaminant of concern with domestic wastewater disposal. The degree to which different domestic wastewater systems reduce the nitrogen load is an important metric to the cost/benefit analysis. As described above much of the wastewater urea mineralizes to ammonia (NH3) with the ionic form ammonium (NH4

+) being the dominant species (Lowe et al., 2007). For cesspools the effluent chemistry is consistent with that of raw wastewater since there in no treatment prior to discharge making organic nitrogen and ammonium the dominant nitrogen species (Lowe; Lowe et al., 2007). In a septic tank the wastewater is generally anaerobic and the conversion of DON to ammonium is rapid making ammonium the dominant nitrogen species with DON accounting for the remainder. Septic tanks may remove nitrogen in the wastewater stream by volatilization of ammonia and sorbing of nitrogen to particulate matter that is removed during septic tank pumping. The Water Environment Research Foundation (Lowe et al., 2007) conducted a literature review of reported values of nitrogen in raw wastewater and in septic tank effluent. The average raw wastewater nitrogen concentration was 87 mg/L compared to 58 mg/L for septic tank effluent. It is important to note that these values are not a direct comparison of influent into a septic tank versus effluent out of a septic tank. However, the values do suggest nitrogen removal within the septic tank.

The primary alternatives considered by this study were septic systems discharging effluent to a soil treatment unit. The amount of nitrogen reduction during soil treatment is highly variable depending on hydraulic loading, soil type, availability of a carbon source and chemistry of the effluent (McCray et al., 2009). Water Environment Research Foundation (McCray et al., 2009) in their review of wastewater soil treatment performance did a literature review of the effectiveness of soil treatment in reducing the wastewater nitrogen load. Their conclusion was that soil treatment did reduce the nitrogen load but there was no quantifiable rate of reduction as the data were too variable. One of the major variables is soil type. (Tasato and Dugan) tested soil treatment performance by passing domestic wastewater through soil lysimeters. Four Hawaii soil types were tested with average removal rates range inform 25 to 57 percent. When the average removal rate considering all four soil types the average reduction was 42 percent. A higher level of treatment occurs if an aerobic treatment unit (ATU) is used instead of a septic tank. The primary purpose of the ATU is to reduce the biological oxygen demand, total suspended solids, and control the pH (NSF International, 2009). However, when effluent quality of ATUs is compared to that of a septic, on average, the total nitrogen is somewhat less than effluent from a septic tank when both discharge to a seepage pit (WRRC, 2008). If the effluent from the ATU is disposed of through soil treatment or an evapotranspiration unit, significant nitrogen reduction is realized (Table S-2) (WRRC, 2008; and WRRC Report 2015-01).

A survey of onsite treatment systems (WRRC, 2008) describes enhanced nitrogen removal as a two-step process. The first is secondary treatment that results in the aerobic transformation of ammonium to nitrate. This is commonly done by aeration in a holding tank. The second step is tertiary treatment that results in denitrification. This is commonly creates anaerobic conditions using tickling filters, sequencing batch reactors, or intermittent sand filters. The system has to be engineered to ensure enough organic matter is present to support the population of denitrifying bacteria required to convert dissolve nitrate to gaseous nitrogen species. Advanced nitrogen removal commonly results in nitrogen reduction rates of 40 to 80 percent (WRRC, 2008). The only municipal wastewater treatment plant in the study area is the Lahaina Wastewater Reclamation Facility that injects about 3 mgd of treated wastewater into four injections about 0.5 km from the shoreline. This facility subjects the wastewater to secondary treatment, then additional biological nutrient and solids removal in a sand filter (Glenn et al., 2012). The treated wastewater is then disinfected by use of ultraviolet light prior to injection (County of Maui, 2014). The wastewater treatment process reduces the total nitrogen to an average concentration of about 6 mg/L (Fackrell et al., 2016; Glenn et al., 2012; Hunt and Rosa, 2009). Nearshore sampling of a spring that isotopic analysis indicated was predominantly treated wastewater showed a significant degree of denitrification occurred between injection and discharge of the treated wastewater at the nearshore submarine springs (Fackrell et al., 2016; Glenn et al., 2012). The nitrogen reduction was about an order of magnitude (Fackrell et al., 2016).

Groundwater ModelThe numerical groundwater flow and transport modeling sought to achieve three goals:

1. Replicate the groundwater flow patterns in northwest Maui and more specifically the distribution of coastal fresh groundwater discharge;

2. Replicate the distribution of nutrients (primarily nitrate) in the groundwater of northwest Maui; and

3. Estimate the distribution and magnitude of the coastal nutrient load and identify the source of the nutrients to the extent practical.

Replicating the distribution of nutrients in the aquifer and the estimating the coastal nutrient load requires modeling codes that simulate groundwater flow, plot groundwater flow paths, and simulate

contaminant transport. The USGS code MODFLOW 2005 simulates the movement of groundwater by solving the groundwater flow equations for a grid of cells (Harbaugh, 2005). MODPATH (Pollock, 2016) uses the MODFLOW solution to track the path of virtual particles either with the flow of groundwater (forward tracking) or the exact opposite direction of groundwater flow (reverse tracking). MODPATH was used to develop groundwater flow tubes to sub-divide the model for computation of coastal nutrient flux. Nutrient transport was simulated using the modeling code MT3DMS (Zheng and Wang, 1999). This transport modeling code uses the MODFLOW solution to simulate the movement of contaminants in the groundwater. MT3DMS can simulates contaminant processes of advection (movement with the flow of groundwater due to differences in hydraulic head potential), dispersion (spreading of the plume due to heterogeneities in the aquifer), and molecular diffusion (movement due to a concentration gradient). MT3DMS also simulates sorption (the attachment of the contaminant to the aquifer matrix) and degradation. MT3DMS is ideal for this study since it can simulate the transport of multiple contaminants species simultaneously.

The groundwater model combined USGS calculated recharge for Maui (Johnson et al., 2014), with land use coverages from the State of Hawaiʻi Office of Planning Statewide GIS program (http://planning.Hawaiʻi.gov/gis/) to identify and simulate nutrient sources for current and future conditions.

All of the modeling codes described above perform calculations in algebraic array based on a rectangular grid of cells. The Groundwater Modeling System (GMS) (Aquaveo, Provo, Utah) graphical user interface was used to convert a conceptual model that is in the form geographical information system elements consisting of shapes with data parameter values attached to the numerical modeling grid using ArcGIS 10.1 (ESRI, 2012).

Model DescriptionA groundwater flow and transport model simulated nutrient leachate delivery from on-land recharge zones to points of coastal discharge using USGS groundwater flow code MODFLOW (Harbaugh, 2005) and contaminant transport code MT3D-MS (Zheng and Wang, 1999; Supplementary Methods). Both codes used the Groundwater Modelling System (Aquaveo, Provo, UT, USA) user interface to populate models. The modelling uses the concept of a flow net to divide the model domain into 25 flow tubes. The flow net’s flow lines represent an impermeable boundary (Freeze and Cherry, 1979, pg 168-170) that trace from the coast up to the 420 m msl groundwater contour, where they converge. An assumption of flow nets is that there is no groundwater exchange between flow tubes, thus the nutrient mass applied to each flow tube, either as recharge or wastewater injection, remains in that flow tube (Delevaux et al.) Coastal nutrient mass discharge flux is the sum of the mass from the individual sources into each flow tube. This is based on an assumption that much of the applied nutrients nitrify to nitrate, a conservative and mobile species in groundwater, and do not sorb onto the aquifer matrix (Delevaux et al., 2018).

The groundwater model simulated groundwater flow nutrient transport in the Honokowai, Honolua, and Honokohau Aquifer Systems of northwest Maui (Mink and Lau, 1990). This selection of aquifers completely covered the study watersheds. Figure S2 shows the model domain relative to the study watershed boundaries. The aquifer boundaries were chosen since they boundaries between aquifers are more consistent with the groundwater flow regime that watersheds are.

Figure S2. Groundwater model domain relative to the study watershed boundaries

The model domain was mapped to a three-dimensional grid for MODFLOW to perform the groundwater flow calculations. The model grid consisted of 527,360 cells arrange in 4 layers, 320 columns and 412 rows. Of these cells only 291,840 were active as the others fell outside of the boundary of the conceptual model. In plan view the cell size was uniform at 50 m on a side. Vertically the cell size varied with the thickness of the simulated aquifer.

This study adapted the USGS model of (Gingerich and Engott, 2012) that used the density dependent modeling code SUTRA (Voss and Provost, 2002) to simulate groundwater flow in west Maui. MODFLOW assumes a uniform groundwater density and cannot dynamically simulate the interaction between the freshwater lens and the underlying saltwater that buoyantly supports the freshwater lens. MODFLOW does have the advantage of the direct linkage with the modeling code MT3DMS for simulation of contaminant transport. To simulate the freshwater discharge to the nearshore environment, we assigned and equivalent freshwater head to all submarine boundary cells. The equivalent freshwater head is the depth of the mid-point of the submarine boundary cell times 0.025 to account for the difference in density between freshwater and saltwater. Motz and Sedighi (2009) compared the outputs of the density dependent flow modeling code SEAWATs (Langevin et al., 2008) with MODFLOW to compare the simulation of freshwater discharge to the coastal marine zone between the two model types. They found that when the coastal and submarine fresh groundwater discharge was simulated using

equivalent freshwater head based on water depth, that MODFLOW adequately simulated the water table elevation and the coastal freshwater flux. Thus the combination of MODFLOW and MT3DMS meets the needs of modeling goals and significantly stream lines the modeling process.

There are many unknown geomorphic processes such as similar to the paleo stream channel identified by Hunt and Rosa (2009) that will influence entry points of nutrients into the nearshore environment. While known geology such as the aforementioned stream is included, there is likely to also be unmapped geology that may influence flowpaths.

Boundary ConditionsThe model boundary conditions assign parameter values as the model boundaries while the numerical grid calculates the values of hydraulic head and inter-cell flow within the model grid. The upper boundary of the model is the top of the water table where an assigned flux based on the groundwater recharge estimated by the USGS Maui (Johnson et al., 2014). The lateral boundaries of the model were delineated along the designated aquifer boundaries (Mink and Lau, 1990) and were assigned a no-flow condition. This is consistent the generally accepted conceptual model that there is very limited exchange of groundwater between aquifers (Wilson Okamoto Corporation, 2008). The bottom boundary was a no flow boundary based on the elevation of the midpoint of the freshwater/seawater transition zone as simulated by Gingerich (2012).

Geologic zones and associated hydraulic conductivities were taken from Gingerich (2012). Since the groundwater model grid is rectangular and the lava bedding is more radial in geometry, no horizontal anisotropy was simulated. The hydraulic conductivities assigned were the longitudinal values from Gingerich (2012). Well pumping rates, groundwater discharge to streams, and target groundwater elevations were also taken from Gingerich (2012). Streams were simulated as drains with the conductance of the stream arcs adjusted so that the simulated discharge of groundwater to the streams approximated that modeled by Gingerich (2012).

NUTRIENT TRANSPORT MODELINGAs described above the distribution of nutrients in the groundwater was simulated using the transport modeling code MT3DMS (Zheng & Wang, 1999; and Zheng, 2010). Both nitrate and phosphate were modeled. However, phosphate has a rate of sorption to the soil (Canter, 1985; Froelich, 1988), resulting in low groundwater concentrations except where the injected municipal wastewater discharged at the coast in submarine springs (Glenn et al., 2012). The primary sources of nitrate modeled were:

Golf course fertilizer,

Landscaping fertilizer from developed open spaces,

Legacy fertilizer leached from former sugar cane and pineapple cultivation,

Onsite sewage disposal leachate,

Application of recycled wastewater, and

Subsurface injection of treated wastewater.

Table S5 lists the concentrations or leaching rates used for the model and the basis for the values selected. The assumption is that the dominant form of nitrogen is nitrate and it is a conservative and mobile species in the groundwater. Nitrate is the stable form of nitrate under oxidizing conditions and dominant aquifer material is basalt where there is very little opportunity for sorption to the aquifer matrix (Delevaux et al., 2018).

Table S5. Nitrate Sources and Basis for modeled concentration (mg/L) and 15N

Nitrate Source SpeciesSimulation Method

Modeled Concentration

(mg/L)Natural1 Natural Recharge 0.3Former Sugar Cane Ag.2 Sugar Recharge 11.7Former Pineapple Ag.2 Pineapple Recharge 0.5Coffee3 Other Recharge 1.8Golf Course4 Golf Course Recharge 6.3 to 13.8*Developed Open Space5 Developed Open

SpaceRecharge 0.3 to 5.9*

Recycled Water Application6

Reuse Recharge 13.8

Wastewater Injection7 Injection Well injection 5Cesspools8 OSDS Well injection 87Septic System with Soil Treatment8

OSDS Well injection 51

1Average from west Maui wells not affected by ag. (DOH, 2016), 2Adjusted recharge concentration so modeled concentration equaled that in wells located in former sugar cane and pineapple areas (Glenn et al., 2012; DOH, 2016), 3Adjusted recharge concentration to match leaching rate of (Fenilli et al., 2008), 4Adjusted concentration in recharge to get a leaching rate of 49 kg/ha/yr (Throssell et al., 2009) based on USGS reported recharge rates for 1978 through 2007 (Johnson et al., 2014), 5Assumed same fertilizer practices as golf courses adjusted for the fraction of the recharge polygon that was DOS. 6Adjusted recharge concentration to equal that measured in a spring at Black Rock Lagoon by Hunt and Rosa, 2009, 7Data from DOH (2016) and Glenn et al (2012), 8Based on raw wastewater values and nitrate removal rates reported by Tasato and Dugan (1980 ), Lowe (2009); McCray (2009).

Nitrate Transport Model validationThe simulated groundwater nitrate was compared with data from DOH compliance sampling (DOH, 2016a), and with the studies of Glenn et al (2012) and Hunt and Rosa (2009) that measured groundwater nitrate concentrations in West Maui (Supplementary Data).

Data used for calibration was from years between 2008 and 2016 and gathered from a review of available samples at DoH, and published and grey literature (Supplementary Data). There was very good agreement between the measured and modeled groundwater nitrate with the exception of two outliers. The two outliers are located at the upper edge of the former sugar cane fields and in close proximity to wells where there was good agreement between the model results and the measured data (see circled area). There is variability in this area that was not captured by the model. Figure S3 shows the measured versus simulated values. The average error was -0.11 mg/L while the RMS error was 0.5 mg/L. The model used recharge from detailed analysis of the USGS (Johnson et al., 2014), which means that the water input to the model is peer reviewed and valid.

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.00.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

f(x) = 0.710279843843082 x + 0.0813810437673953R² = 0.745142921197542

Measured Nitrate (mg/L N)

Sim

ulat

ed N

itrat

e (m

g/L N

)

Figure S3.Validation of groundwater model showing predicted (x) against observed values (y)

1234567891011121314151617181920212223242526272829

0.000.020.040.060.08

Nitrate Flux (kg/m/d)

Figure S4. Bar Chart of total N flux (kg/m/d) for each of the 31 flow tube segments in the study area.

INTERFACE BETWEEN GW MODEL AND DECISION MAKING MODELThe primary purpose of the groundwater flow and transport modeling was to provide the coastal nitrate flux distribution for the cost/benefit analysis. This analysis was best done using GIS and a method was needed to calculate the coastal nitrate over discrete segments of coastline. This study used the concept of a flow net to divide the model domain into 25 flow tubes. In a flow net, a flow line represents an impermeable boundary (Freeze & Cherry, 1979; pg 168-170). The flowlines are delineated using the particle tracking model MODPATH in the reverse tracking mode to trace flow lines from the coast up to the interior recharge zones of the model. Polygons were created from the intersections of the flow path

arcs with coastal and 420 m msl groundwater contour. Above the 420 m msl groundwater elevation contour the flow lines converged resulting in widths that were only a few cells wide. Since in flow nets, there is no groundwater exchange between flow tubes, the nutrient mass applied to each flow either as recharge or wastewater injection, remains in that flow tube until captured by a well, discharged to a stream, or discharged to the ocean. The quantity of water captured by wells or discharged to steams is negligible so the coastal nutrient mass discharge flux becomes the sum of the mass from the individual sources into each flow tube. This analysis is done in ArcGIS 10.1 using the spatial union tool that combined the geometry and attributes of the flow tube, recharge, OSDS, and injection well coverages.

GROUNDWATER MODEL FINDINGS

Table S6. Summary of Groundwater Model Findings

Source (kg/d)(% Flux)

Sugar 214.3 46.8Pineapple 11.7 2.6OSDS 64.1 14.0Natural 79.8 17.4Dev. Open Space 37.3 8.2Coffee 0.7 0.2Wastewater Injection 1.4 0.3Golf Courses 48.3 10.6Total Flux 458 100

Figure S5. Pie Chart showing a summary of the contribution of each potential N source across the entire area of study

The greatest volume of coastal Nitrate contribution by source nitrate appears to be legacy nitrate from past sugar cane agriculture (90%; Figure 3, Table 8). OSDS is the next largest source by type overall (5%) followed closely by Golf Courses and Developed Open Space (4% each). Denitrification of the injected wastewater results in low nitrate flux at flow tube 8 (Figure 3). The high rate of injection (about 11,000 m3/d) displaces the higher nitrate groundwater from upgradient around the coastal discharge zone for the injectate.

Spatial Processing Data sources for all spatial processing are described in Table S7.

AlternativesSpatial data layers for these conditions were used to attribute OSDS point data with associated values in ArcMap 10.1 (ESRI, 2012). Slope values were extracted from a raster layer generated from Digital Elevation Model data using the Slope tool in the Spatial Analyst toolbox, and attributed to overlaid OSDS points. OSDS points that intersected with a flood zone polygon layer were selected and categorized as such.

ValuesReef distances were generated using the Near tool in the ArcMap Spatial Analyst toolbox. They were calculated from each of the shoreline segments, representing coastal interfaces of the groundwater flow tube polygons, to the nearest edge of reef structure class polygon from the NOAA Benthic Habitat Map (Pacific Islands Fisheries Science Center, 2017). Distances were then attributed to each of the OSDS units within the associated flow tube polygon. Values for recreational value of coastal segments were generated from Flickr InVEST model outputs, which predicts the spread of person-days of recreation in space based on number of geotagged photo uploads to the Flickr website (Wood et al., 2013a). The InVEST model was run on the study area for all available years (2010-2014), for an output of 100-m2 hexagons. Visitation values are represented as Photo User Days (PUD), and weightings are the sum of the visitation raster cells for each coastal segment, standardized by length of coastal interface. Coastal segment areas were defined by a 100m flat-end buffer for each of the coastal interface segments from the groundwater flow tubes. The segment-specific PUD values were then attributed to the associated OSDS, consistent with the manner in which reef distance weightings were applied.

Table S7. Data sources

Spatial dataset SourceHawaiʻi State 10 DEM Hawaiʻi State GIS Website, tab 010 Image and Base Maps

http://planning.hawaii.gov/gis/download-gis-data/

OSDS point shapefile 2007

On-site sewage disposal systems (OSDS) for the island of Maui as of 2010. State of Hawaiʻi Department of Health. Accessed from Hawaiʻi Statewide GIS Program. https://www.arcgis.com/home/item.html?id=108b8d29611a4a5e8bed2f7c658ddf68

OSDS point shapefile 2017

(DOH (OSDS point shapefile 2007; adjusted based on field validation conducted by Tova Callender). Available here: https://www.dropbox.com/sh/563akg2qlwuzx8n/AAD1a-0CJywZFqQ3yJjZVZrta?dl=0

Slope, generated from 5 m resolution DEM

NOAA-CSC. (2014). Interferometric Synthetic Aperture Radar based Digital Elevation Model. Retrieved from: https://coast.noaa.gov/dataregistry/search/dataset/info/coastalifsar

Flood zone Flood Hazard Areas – State of Hawaiʻi, Federal Emergency Management Agency (FEMA). March 2012. Accessed from Hawaiʻi Statewide GIS Program. http://planning.hawaii.gov/gis/

Leach field suitability Whittier, R.B., El-Kadi, A., 2014. Human health and environmental risk ranking of on-site sewage disposal systems for the Hawaiian Islands of Kauai, Molokai, Maui, and Hawaiʻi. Final report prepared for State of Hawai'i Department of Health. Safe Drinking Water Branch.

Coastal recreation (Flickr Photo User Days)

Sharp, R., Tallis, H.T., Ricketts, T., Guerry, A.D., Wood, S.A., Chaplin-Kramer, R., Nelson, E., Ennaanay, D., Wolny, S., Olwero, N., Vigerstol, K., Pennington, D., Mendoza, G., Aukema, J., Foster, J., Forrest, J., Cameron, D., Arkema, K., Lonsdorf, E., Kennedy, C., Verutes, G., Kim, C.K., Guannel, G., Papenfus, M., Toft, J., Marsik, M., Bernhardt, J., Griffin, R., Glowinski, K., Chaumont, N., Perelman, A., Lacayo, M. Mandle, L., Hamel, P., Vogl, A.L., Rogers, L., Bierbower, W., Denu, D., and Douglass, J. 2016. InVEST +VERSION+ User’s Guide. The Natural Capital Project, Stanford University, University of Minnesota, The Nature Conservancy, and World Wildlife Fund. http://data.naturalcapitalproject.org/nightly-build/invest-users-guide/html/recreation.html

Complex reef habitat: NOAA West Maui Dominant Benthic Structure habitat map

Pacific Islands Fisheries Science Center, 2017: Dominant Benthic Structure and Biological Cover Habitat Maps for West Maui and West Hawaiʻi from 2010-06-15 to 2010-08-15. NOAA National Centers for Environmental Information, https://inport.nmfs.noaa.gov/inport/item/32811

West Maui County Infratructure Database

https://mauicounty.maps.arcgis.com/apps/View/index.html?appid=2adf24d194f7473ab71c7e4cc7b3061a

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