Hydrological and chemical connectivity dynamics in a groundwater-dependent ecosystem impacted by acid sulfate soils

Hydrological and chemical connectivity dynamics in agroundwater-dependent ecosystem impacted by acidsulfate soils

B. Nath,1,2 A. M. Lillicrap,1,3,4 L. C. Ellis,1 D. D. Boland,1,5 and C. E. Oldham1

Received 3 August 2012; revised 28 November 2012; accepted 28 November 2012.

[1] Groundwater-dependent ecosystems (GDEs) in arid and semiarid environments playsignificant ecological roles, and, yet in many parts of the world, these ecosystems have beendrained for agricultural use. In wetlands containing acid sulfate soils, the altered hydrologymay trigger acidification and subsequent trace metal release. Quantifying shifts inhydrological regime and connectivity dynamics across wetlands is critical for understandingthe resilience of these GDEs to anthropogenic impacts. Seasonal water balances for awetland severely impacted by drainage and acidification were combined with laboratorygeochemical data and field observations to develop a conceptual model describinghydrological connectivity across the wetland. The data indicated that, with the onset of thedry season, the superficial aquifer was lowered, exposing sulfides that oxidized to formsulfuric acid and dissolving metal salts. The following dry season enhanced capillary actioncausing upwelling of oxidized products to the surface where evaporative precipitationcreated acidity scalds. Subsequent winter rainfall and infiltration caused groundwater levelsto rise, intersect with the ground surface, and form disconnected acidic pools. As the wetseason progressed, connectivity was established between the pools, resulting in metal-richacid discharge from the wetland. The degree of acid fluxes and metal release was controlledby the physicochemical characteristics of the soils, its exposure to the seasonally variablewetland hydrology, antecedent hydrological conditions, hydrological connectivity (bothvertical and horizontal), and the resulting biogeochemical conditions.

Citation: Nath, B., A. M. Lillicrap, L. C. Ellis, D. D. Boland, and C. E. Oldham (2013), Hydrological and chemical connectivitydynamics in a groundwater-dependent ecosystem impacted by acid sulfate soils, Water Resour. Res., 49, doi:10.1029/2012WR012760.

1. Introduction

[2] The ecological significance of groundwater-dependentecosystems (GDEs) has historically been neglected, and theseecosystems continue to be at risk from human-inducedchanges [Eamus et al., 2006; Mackay, 2006]. Over the pastdecade, there has been increasing recognition of their ecolog-ical significance, particularly in arid and semiarid landscapes[Boulton and Hancock, 2006; Contreras et al., 2011; Murrayet al., 2003]. In such landscapes, intermittent hydrological

connectivity and disconnectivity between GDEs and othercatchment elements (e.g., subcatchments, riparian zones,wetlands, and streams) play an important role in the healthyfunctioning of the ecosystems. In GDEs, local groundwater-surface water interactions control soil pH, redox conditions,dissolved organic matter availability, and plant growth [DuLaing et al., 2009]. Seasonal and decadal hydrological vari-ability affects the mobilization of trace metals [Hrachowitzet al., 2010]. However, a detailed understanding of hydro-logical processes and the resulting biogeochemical dynamicsremains challenging and unanswered.

[3] The retention, mobility, and transport of material (e.g.,chemicals and biota) across the landscape depend on trans-port pathways and hydraulic residence times. For example,small-scale and large-scale spatial heterogeneity creates mul-tiple transport pathways and a residence time distribution(RTD) [Botter et al., 2011; Hrachowitz et al., 2010]. TheRTD has been used as a fundamental characteristic in aquaticsystems with free surfaces [Carleton, 2002; Werner andKadlec, 2000] and in catchments [Bevan, 2001; McDonnellet al., 2010; McGuire and McDonnell, 2006]. These authorsnote the importance of the residence and transit times for theexport of dissolved and particulate constituents or pollutantsfrom lakes and catchments. Given the specific interest inpollutant transformation, we note that a more pertinent

1School of Environmental Systems Engineering, The University ofWestern Australia, Crawley, Western Australia, Australia.

2Now at School of Geosciences, University of Sydney, Sydney, NewSouth Wales, Australia.

3Centre of Excellence for Ecohydrology, The University of WesternAustralia, Nedlands, Western Australia, Australia.

4Department of Agriculture and Food, Albany, Western Australia,Australia.

5Now at School of Civil and Environmental Engineering, University ofNew South Wales, Sydney, New South Wales, Australia.

Corresponding author: C. E. Oldham, School of Environmental SystemsEngineering, The University of Western Australia, Crawley, Western Aus-tralia 6009, Australia. ([email protected])

©2012. American Geophysical Union. All Rights Reserved.0043-1397/13/2012WR012760

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WATER RESOURCES RESEARCH, VOL. 49, 1–17, doi:10.1029/2012WR012760, 2013

parameter is the exposure timescale, �E, which is the time-scale over which the dissolved and particulate constituents orpollutants have the opportunity to be transformed duringtransport. The concept of an exposure timescale has beenpreviously used in surface renewal theory [Dankwerts, 1951]and chemical engineering [Asarita, 1967].

[4] The exposure timescale, �E, of a hydrologically con-nected landscape element (for example, a riparian zone dis-charging to a river) is conceptually understood as follows:

�E ¼V

Q; (1)

where V is the wetted volume of the landscape element(m3), and Q is the volume flux (m3 s�1). For wetlands domi-nated by surface water-groundwater interactions, quantifica-tion of exposure timescales is challenging because oftemporal and spatial variability in flow pathways.

[5] When the landscape is made up of multiple discon-nected elements, e.g., oxbow lakes, isolated surface pond-ing, or seasonally perched wetlands, the isolated watersprovide opportunity for chemical reaction [Cend�on et al.,2010; Eamus and Froend, 2006; Sophocleous, 2002]. Oncereflooded, the landscape becomes hydrologically connected,and accumulated materials can be transported across thelandscape. The exposure timescales of intermittently dis-connected landscape elements can no longer be conceptual-ized as (1), because Q is not defined in a disconnectedlandscape. However, the isolation timescale, � I , provides anequivalent period of opportunity for chemical reaction.Physicochemical processes that occur across isolation time-scales create antecedent conditions, which subsequentlycontrol the export of chemicals from catchments, particu-larly in arid and semiarid environments where disconnectiv-ity is a key seasonal feature of the landscape [Bertrandet al., 2012; Cend�on et al., 2010; Eamus and Froend,2006]. Thus, an intermittently connected landscape may becharacterized by both its isolation timescales and its resi-dence times.

[6] When groundwater-dependent wetlands are impactedby the exposure of acid sulfate soils (ASS), the dynamicsof hydrological connectivity and disconnectivity can con-trol acidity and the release of contaminants [Dent, 1986;Sammut et al., 1995, 1996b; White et al., 1997]. The exportof acidity products during hydrologically connected periodsdepends on the opportunity for accumulation and/or con-sumption of acidity products during the disconnected pe-riod. This antecedent state in turn depends on the balancebetween the isolation and reaction timescales, and, onceconnected, export of chemicals depends on the balancebetween transport and reaction timescales.

[7] Climate or human-induced perturbations of thegroundwater table may create time lags between vertical andhorizontal connectivity of years to decades. For example,prolonged drought may cause the lowering of groundwatertables and result in the isolation and deposition of acidicproducts in the soil profile. These acidic products couldremain in the soil profile for decades until disturbance byland-use change or unusual rainfall/flooding episodes thatcreate sufficient vertical and/or horizontal connectivity toflush accumulated acidity products from the soil matrix.

[8] The processes described above require intermittenthydrological connectivity in both the vertical and horizon-tal directions [Johnston et al., 2004, 2009; Kinsela andMelville, 2004]. However, these processes have rarely beendescribed in terms of isolation timescales ; most ASS andwetland research focuses on periods of hydrological con-nectivity. In this paper, we use a simple water balance for anacidic wetland and field geochemical data to test this concep-tual model of seasonal connectivity dynamics. We also iden-tify isolation timescales to assess the impact of connectivitydynamics on geochemical processes within the wetland.

2. Methods

2.1. Site Description

[9] The Muddy Lakes wetland (approximately 30 ha) is aGDE located on the Swan Coastal Plain, 180 km south ofPerth, Western Australia (Figure 1). The area experienceshot, dry summers (16�C–30�C) and cool, wet winters (7�C–17�C). The mean annual rainfall over the last 15 years hasbeen approximately 700 mm, the majority of which occursbetween May and September, whereas the mean annual

Figure 1. The study area showing location of the eightboreholes (bores 1–8) and two gauging stations (SWN andSWS). The elevations shown are from the LiDAR DEM.Surface runoff and groundwater discharge to the majordrain (flowing north to south) that flows to another wetlandwhose levels are controlled by floodgates to the IndianOcean. Elevation units are meters.

NATH ET AL.: CONNECTIVITY DYNAMICS OF A GROUNDWATER-DEPENDENT ECOSYSTEM

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potential evaporation is approximately 1500 mm. The sitesits between aeolian sand dune deposits of Pliocene to Holo-cene age [Hirschberg, 1987]. Most notable of these is Tam-ala limestone, an aeolian calcarinite that formed elongateddunes parallel to the present coastline [Hirschberg, 1987].The area was drained prior to the 1930s for agricultural de-velopment. The major drain runs north to south, parallel tothe coastline on the western fringe of the wetland, and is fedby groundwater and other farm drains. The site is a season-ally inundated depression in the landscape, drying up inmidsummer and wetting up in the late autumn when themajor drain starts to flow. The major drain continues to flowfor approximately 3 km south of the study area before dis-charging into Geographe Bay, Indian Ocean.

[10] Apart from barren acid scalds, the wetland vegetationhas been disturbed by introduced kikuyu grass Pennisetumclandestinum and in the margins by the salt and acid tolerant,native couch grasses Paspalum vaginatum and Cynodon dac-tylon [Semple et al., 2004]. Despite its degraded state, thewetland retains a high ecological value, sustaining a threat-ened ecological community (Quinalup Dune damplands)[Environmental Protection Authority, Western Australia(EPAWA), 2003] and providing habitat for three Australiannationally listed endangered species: Western Ringtail Pos-sum (Pseudocheirus occidentalis), Quokka (Setonix brachyu-rus), and Baudin’s Black Cockatoo (Calyptorhynchusbaudinii) [EPAWA, 2003].

2.2. Installation of Monitoring Boreholes, GaugingStation, and Field Measurements

[11] Eight groundwater-monitoring boreholes were in-stalled across the site using hollow flight augers. The bore-holes were cased in 50 mm Class 18 polyvinyl chloride(PVC) pipes and were constructed to different depthsdepending on soil stability. The lowest 2 m of each boreholewas screened with 50 mm Class 18 slotted PVC pipes. Thescreens were covered with a geotextile filter sock to preventingress of fines. The screens were packed with clean sand,and a bentonite seal was placed above the screen. The restof the borehole was backfilled with cuttings and grouted atthe surface. Pronounced stratigraphic layering was observedin the boreholes across the top 50–100 cm depth. However,the borehole slots were positioned within relatively homoge-nous fine to medium sands. Soil/sediment samples were col-lected to test for field pH and later chemical analysis in thelaboratory. Immediately upon collection, the soil/sedimentsamples were placed on ice and stored at 4�C until furtheranalysis. Field pH was measured on a sediment-distilledwater slurry (pHF) and after reaction with peroxide (pHFOX)[American Public Health Association (APHA), 1992].

[12] Two gauging stations were also installed at thestudy site at the northern (SWN) and southern (SWS) endsof the major drain extending through the site (Figure 1).Water level and velocity (ISCO 750 AV Flow Module, Tel-edyne ISCO Inc., Lincoln, USA), pH, electrical conductiv-ity (EC), and temperature (YSI 6583 probes, YSI Inc.,Yellow Springs, USA) were measured every 15 min. Flowrates were estimated from the water level and velocity meas-urements. Each gauging station was also equipped with aTeledyne ISCO 6712 automatic water sampler that collected200 mL of drain water every 6 h; four samples were com-bined into a daily sample. Bottles were acid-washed and

rinsed with deionized water three times before being placedinto the autosamplers. Manual measurements of pH and ECof the water samples collected daily from SWS confirmedthe continued performance of the YSI probe.

[13] Hydraulic conductivity of the soil formation wasdetermined using the Hvorslev slug test [Fetter, 1994].Approximately 1 L of water was poured down the bore-holes to provide an instantaneous head (h0) above the nor-mal water level (h) ; the decline in h0 with time was trackedusing a capacitance probe (Scott Parsons Electronics,Albany, Western Australia). The hydraulic conductivitywas calculated as follows:

Ks ¼r2ln L

r

2LT0; (2)

where Ks is the hydraulic conductivity (m d�1), r is the ra-dius of the borehole (m), L is the length of the boreholescreen (m), and T0 is the time taken for h0 to drop to 37%of the original induced head (days). The value of T0 wasdetermined by plotting the relative head change (h0/h) on alog scale against the elapsed time.

2.3. Soil Sample Preparation and Laboratory Analysis

[14] Soil samples were air-dried at 25�C for 48 h andcrushed gently to pass through a 2 mm sieve. To assess thepresence of ASS in the soil profile, the suspension peroxideoxidation combined acidity and sulfate (SPOCAS) suite ofanalyses were conducted [Ahern et al., 2004]. A subsamplewas extracted with KCl solution for the determination ofsoluble and absorbed sulfur (nonsulfidic, SKCl, %), measuredusing inductively coupled plasma atomic emission spectrom-etry (ICP-AES). The pH (pHKCl) and titratable actual acidity(TAA) of the extracted solution were also measured. Anothersubsample was oxidized with H2O2 and analyzed for sulfurusing ICP-AES, which represented total soluble, absorbed,and sulfidic species (SP, %). The titratable potential acidity(TPA) and pH (pHOX) were also measured. When pHOX ofthe solution was greater than 6.5, the samples were analyzedfor ‘excess’ acid neutralizing capacity (ANCE) through titra-tion with HCl (to pH 4). The peroxide oxidizable sulfur(SPOS, %) was calculated as the difference between SP (%)and SKCl (%), giving a measure of the amount of sulfides inthe sample. Soluble ions, metals, acidity, and alkalinity werealso measured in surface soil slurries (one part soil:five partswater) [Rayment and Higginson, 1992].

[15] Mineralogical studies using X-ray diffraction (XRD)were carried out using Cu-K� radiation, operating at 40 kVand 30 mA, and a post-diffraction graphite monochromator.The crystalline mineral phases were quantified usingSIROQUANTTM software (Sietronics Pty. Ltd., Canberra,Australia). Total carbon (TC) and total sulfur (TS) wereanalyzed using an Elementar vario MAX CNS analyzer(Elementar, Hanau, Germany). Total organic carbon (TOC)was analyzed by wet oxidation [Heanes, 1984]. The majorelemental analyses involved preparation of a homogeneousglass bead of 40 mm in diameter and analyzed in a Bruker-AXS S4 Pioneer (Bruker AXS GmbH, Karlsruhe, Germany)X-ray fluorescence (XRF) spectrometer against a referencestandard (Andesite, AGV-2, silicates general). The datawere processed through Spectra PLUS software (PioneerHill Software LLC, USA). The trace element analyses were


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carried out on a pressed pellet prepared from the bulk pow-dered soil samples and compared against a reference stand-ard (Basalt, BHVO-2).

2.4. Water Sampling and Laboratory Analysis

[16] Groundwater samples were collected 12 times (ona monthly basis) between 11 September 2008 and 11September 2009. Groundwater level (relative to local da-tum) was measured prior to sample collection. Three bore-hole casing volumes of water were removed prior to samplecollection. The pH, EC, temperature, and Eh were measuredon-site using a TPS multimeter (TPS 90FL-T, TPS Aus-tralia). The samples were then filtered through mixed cellu-lose (0.2 mm) filter papers. The filtered samples weredivided into two; half of each sample was acidified with afew drops of concentrated HNO3 for subsequent analysis ofmajor cations and trace elements, whereas nonacidifiedsamples were analyzed for acidity, alkalinity, SO2�

4 , andCl�. All samples were stored on ice, transferred to the labora-tory, and then stored in the dark at 4�C until analysis. Watersamples were analyzed in the laboratory for acidity (by titra-tion with 0.01 M NaOH to pH 8.3, APHA 2310 B [APHA,1992], including the peroxide oxidation step), alkalinity (byacid titration using 0.05 M HCl to pH 4.5, APHA 2320 B[APHA, 1992]), SO2�

4 and Cl� using ion chromatography,major cations using ICP-AES, and trace element concentra-tions using inductively coupled plasma mass spectroscopy.

2.5. Water Balance Calculations

[17] A wetland water balance was attempted to (a) esti-mate the fraction of the total wetland water volume thatwas above versus below the ground surface and (b) to esti-mate net groundwater flows into and out of the wetland.The water balance also indicated how both of these dynam-ics changed with season. The undulating terrain at the siteintersected with a rising and falling groundwater table, cre-ating a series of ephemeral pools about 0.5 m in depth and afew meters in width that were intermittently connected overwinter, both via surface flows and the high groundwater ta-ble. This hydrological dynamic is similar to that observed inpeat wetlands, with their hummocks and hollows [Freiet al., 2012], and is significantly different from the standingwaters typically observed in many wetlands and on whichmost wetland water balances are based [see, for example,Jolly et al., 2008; Krasnostein and Oldham, 2004]. Thishydrological dynamic creates challenges for our water bal-ance and quantification of connectivity in the wetland.

[18] Initially, the water balance was classically concep-tualized as follows:

�V ¼ Pþ GWIN þ R� ET � QOUT � GWOUT ; (3)

where �V is the change in storage of the wetland withtime, P is the direct precipitation experienced by the wet-land, GWIN is the groundwater inflow to the wetland, R isthe surface runoff into the wetland, ET is the evapotranspi-ration, GWOUT is the groundwater outflow, and QOUT is thewetland outflow. All units are m3 d�1.

[19] Meteorological data were sourced from the SILOData Drill service provided by the Queensland Departmentof Natural Resources [QNRM, 2009]. Daily rainfall datawere used to estimate the total volume of precipitation (P)

received by the wetland. Extensive drainage of adjacent ag-ricultural lands ensured negligible surface runoff into thewetland; no surface flow pathways to the wetland wereobserved over 4 years of monitoring. Evapotranspirationwas estimated using the Morton [1983] areal evapotranspi-ration model that was multiplied by the wetland surfacearea to estimate the ET volume on a daily time step.

[20] A digital elevation model (DEM) was developedusing Light Detection and Ranging (LiDAR), with a hori-zontal resolution of 1 m � 1 m and a vertical accuracy of0.15 m Australian height datum (AHD). The horizontal posi-tional accuracy was 0.6 m. The DEM was used to obtainAHD elevations of the boreholes, and then groundwater anddrain surface water height data were converted to AHD. Themonthly water elevation data were converted to a raster grid(water elevation grid) via kriging interpolation using a vari-able search radius and a spherical semivariogram model. Forincreased accuracy, no limit was set on the maximum datapoints, and z tolerance was set to 0.01. The raster calculatorin the ArcGIS Spatial Analyst Tools (ESRI Inc., CA, USA)was used to subtract the DEM grid from the water elevationgrid; all values greater than zero represented expression ofsurface water. The ArcGIS 3D Analyst Tool then allowedcalculation of surface water volumes. The areas of surfacewater were converted to polygon shape files, and the numberand area of surface water pools analyzed statistically foreach month. The total wetted volume was calculated fromthe water elevation grid using 0 m AHD as the lower bound-ary condition. Changes in surface water storage with time,�Vs, were calculated as the difference between surfacewater volumes at consecutive sampling periods divided bythe number of days between sampling periods.

[21] To estimate the volumes of subsurface water thesurface water volume was subtracted from the total wettedvolume; the remainder was multiplied by the specific yield.A constant specific yield (in both time and space) of 0.2was used for this calculation [Davidson and Yu, 2008]. Thelithostratigraphy was dominated by fine to medium sands;measured local hydraulic conductivities (KSAT) rangedfrom 0.3 to 6 m d�1. The classification developed by Rawlset al. [1982] indicates for these soil types; we expect hy-draulic conductivity from 1 to 6 m d�1 and specific yield inthe range of 0.3–0.5. CSIRO [2010] calibrated their SouthWest Aquifer Modeling System (SWAMS, CSIRO, Aus-tralia) using specific yield (among other parameters) andvalidated results against local piezometer data. For the su-perficial sandy aquifer of the region, specific yield valuesof 0.2–0.5 produced reliable modeling outcome. Specificyield varies as a function of depth to water table [Childs,1960] and, at our site, may therefore vary with time inresponse to the rising and falling water table. Johnstonet al. [2009] showed that saturated hydraulic conductivity,Ksat, varied strongly in the sulfuric horizons found in ASSwetlands; we expect specific yield to show similar hetero-geneity. However, in the absences of high-resolution con-ductivity or yield data at our site, we assumed aconservative value at the lower end of the SWAMS rangeand will discuss the implications of our choice below.Finally, the changes in subsurface storage with time, �Vss,were calculated as the difference between groundwater vol-umes at consecutive sampling periods divided by the numberof days between sampling periods.


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[22] The wetland outflow, QOUT, was defined as the volu-metric discharge through the major drain at SWS. The vol-umes were calculated by multiplying the flow velocitymeasured at SWS gauging station by the wetted cross-sec-tional area. The estimates of groundwater flow into, and outof, the wetland were complicated by possible contributionsfrom both regional and local groundwater flows, so we com-bined these terms into an unknown net groundwater inflow:

QIN ¼ GWIN � GWOUT : (4)

[23] The resulting water balance for the wetland is givenas follows:

�Vs þ�Vss ¼ QIN þ P� QOUT � ET : (5)

2.6. Flux Estimates

[24] Estimates of surface fluxes out of the wetland viathe major drain did not rely on the water balance but couldbe calculated directly from outflow measurements at SWS.The fluxes of Al, SO2�

4 , and titratable acidity (mol of Hþ)from the wetland through the drain were estimated duringthe period from 11 September 2008 to 11 September 2009.The dissolved metals and acidity products were likely to begenerated within the wetland during surface rainwater flush-ing and/or subsurface sediment-water interactions [Johnstonet al., 2004]. The fluxes were estimated as follows:

XFD ¼

XQOUT Cð Þ; (6)

where FD is the flux estimated on a daily basis, QOUT is thevolumetric daily discharge through the major drain atSWS, and C is the concentration of relevant chemical pa-rameters at SWS.

[25] Total salt fluxes, FECS , were determined from EC

values (after converting to TDS) measured daily at SWS.Monthly chemical concentrations at SWS were transformedinto daily data, using linear interpolation or linear averag-ing, as appropriate. The calculated fluxes of major ionswere summed to provide an additional estimate of total saltfluxes, FMI

S . The two estimates of total salt fluxes agreedwell (Figure 2) and gave confidence to our interpolationfrom monthly to daily chemical concentrations and, there-fore, our estimates of chemical fluxes from the study site.

3. Results

3.1. Groundwater Levels and Wetland Water Balance

[26] The groundwater levels in the boreholes exhibitedstrong seasonality, decreasing during summer and increas-ing during winter (Figure 3). The difference betweensummer and winter water levels ranged from 0.82 to 1.1 m.In autumn, the local groundwater gradient is directly to-ward the sea, i.e., toward the west (Figure 4). This is thedirection of regional flow [Commander, 1984]; however, thelocal groundwater gradient shifts toward the southwest overwinter and spring. There is an ephemeral lake to the norththat creates a localized groundwater mound and is the likelydriver of the southwest groundwater gradient (Figure 4).Note that the ephemeral lake is disconnected from the studysite with respect to surface water.

[27] The variability in water levels and changing hydro-logical dynamics created seasonally and spatially variableponding across the wetland (Figure 5). The horizontal con-nectivity of the ponded areas, and the vertical connectivitybetween ponded areas and groundwater, determined thedischarge to drains.

[28] During the winter months, the higher groundwaterlevels in the northern end of the wetland (bores 7 and 8,Figure 3a) and the limited horizontal connectivity of sur-face pools (Figure 5) suggest that recharge to groundwateroccurred to the southwest. Such ‘‘flow-through’’ wetlanddynamics are typical for GDEs on the sandy Swan CoastalPlain [Jolly et al., 2008]. Through the middle section of thewetland (bores 1–3), the groundwater gradient was essen-tially flat, with little or no groundwater discharge to themajor drain (Figure 3b). Across the southern section,ponded areas with limited horizontal connectivity at thesurface (Figure 5) provided ‘‘windows’’ to a groundwatergradient (Figure 3c) suggesting that recharge of ground-water occurred to the southwest.

[29] Precipitation occurred during winter to early spring;summer and autumn were generally dry except for intermit-tent storms (Figure 6a). Evapotranspiration was greatestduring early summer when ponded surface water was

Figure 2. Comparison of salt fluxes estimated from (a)measured EC values (after converting to TDS) and (b) majorion concentrations. A strong positive correlation wasobserved between the two estimates, and the seasonaldynamic of measured and calculated salt fluxes agreed well.


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present; it declined from the beginning of autumn until theend of winter (Figure 6a). There was no measured wetlandoutflow over summer, and it then peaked after winter rains(Figure 6a), with a maximum of 3315 m3 of water (runoffdepth � 10 mm) on 19 July 2009.

[30] The wetland storage (�V) showed large seasonalfluctuations associated with periods of high precipitation orhigh evapotranspiration (Figure 6a); however, at all times,it was dominated by superficial groundwater (97%–99%).Note the 3 to 4 month lag between (a) the time of maxi-mum precipitation and maximum wetland storage and (b)the time of maximum evapotranspiration and minimumwetland storage.

[31] Net groundwater inflow to the wetland (QIN)occurred from throughout the winter months until earlysummer (August-January; Figure 6b). Negative groundwaterinflow (i.e., groundwater outflow) occurred during February(Figure 6b) in response to the cessation of drain outflow dur-ing the period of maximum wetland volume (cf., Figure 6a).Groundwater inflow peaked again in June with the onset ofwinter rains but before the drain started to flow. We notethat the estimated superficial groundwater volume and,therefore, the net groundwater inflow are dependent on ourassumed value of specific yield (0.2), which is at the lowerend of the range typical for sands. If we assume Sy ¼ 0.5,the dynamics of the net groundwater inflow remain similar,though the magnitude of peaks is adjusted (Figure 6b).

3.2. Sediment Geochemical Characteristics andHydrogeochemical Patterns

[32] The field measurement of the soil pH (pHF andpHOX) provides a preliminary indication of the presence of

potential and actual acid sulfate soils, which was later con-firmed by SPOCAS analysis of selected samples [Ahernet al., 2004]. The SPOCAS results showed the presence ofmeasurable quantity of TPA (bores 1, 5, and 7) and TAA(bore 7; Table 1). The soils in bore 1 at 24 to 92 cm depthcontained high sulfide concentrations (12% of TS) includ-ing the presence of pyrite, as determined by XRD analysis(Table 2). XRF analysis indicated the soil samples con-tained high levels of iron, carbon, and sulfur as well asmeasurable elevated As concentrations (Table 2). TheXRD analysis indicated the dominant minerals were quartz,feldspar, and calcite. The chemical analysis of extracts fromsurface precipitate slurries (one part soil:five parts water)indicated high concentrations of Al (up to 11 mg L�1), titrat-able acidity (up to 592 mg L�1), Fe (up to 251 mg L�1), andSO2�

4 (up to 1230 mg L�1; Table 3).[33] The groundwater showed two distinct geochemical

characteristics: bores 3, 5, and 7 were enriched with sul-fates, whereas bores 1, 2, and 6 were more enriched withbicarbonates (Figure 7). The pH, Eh, and depth to thegroundwater showed strong seasonality, with alternatingperiods of oxic and anoxic conditions (Figures 8 and 9).During late winter and early spring, waterlogging associ-ated with a rising water table created reducing conditionsin the organic-rich sediments, subsequent reduction ofFe-oxide and Mn-oxide, and an increase in As, Fe, and Mnconcentrations in soil water (Table 4, see bore 3). Duringthis time, we observed the formation of iron monosulfidesin the drain water close to the SWS monitoring station. Theformation of iron monosulfides is common in ASS environ-ments and typically accumulates at the bottom of drains[Smith and Melville, 2004]. During summer, high rates of

Figure 3. Seasonal trends in water levels across east-west borehole transects. (a) The northern transect(bores 8 and 7) was dominated by surface water over winter with groundwater being recharged. (b) Inthe middle transect (bores 1–3), the groundwater gradients were essentially flat over winter/spring. (c) Inthe southern transect (bores 4–6), there was a groundwater gradient toward the drain.


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evaporation and evapotranspiration caused a decline in thewater table, facilitating reoxidation of the surface sedi-ments. When the water table intersected the borehole slots(for example, at bore 3 during drier periods of the year),acidic conditions were detected. In contrast, the ground-water at bore 6 was near pH-neutral and anoxic duringmuch of the study period (Figure 9). At bore 6, the watertable remained above the slots throughout the year and thusexhibited low concentrations of acidity, Al, Fe, and SO2�

4 ,and high concentrations of As and Mn. The redox condi-tions at this bore were independent of water level.

4. Discussion

4.1. Hydrological Connectivity Dynamics

[34] The conceptual model of seasonal hydrological con-nectivity across the wetland and the subsequent release andtransport of acidity products offsite are shown in Figure 10.Evapotranspiration during summer drives capillary action,which transports groundwater or soil water upward until itreaches the evaporation front [Rose et al., 2005]. The su-perficial soil water becomes hydrologically disconnected orisolated from the underlying groundwater (i.e., vertical dis-connectivity). This process leads to the precipitation and

accumulation of dissolved acidity products in superficial soilhorizons [Minh et al., 1997]. The accumulation of surficialsalts, creating bare surface scalds, has been documented foracid-mine-drainage-affected sites [Hammarstrom et al.,2005] and ASS sites [Rosicky et al., 2004]. In wetland domi-nated by sandy soils, initial winter rains infiltrate and drive arise in groundwater levels that dissolve acid salts previouslyprecipitated in the upper soil profile.

[35] When the groundwater levels intersect the groundsurface levels, ponding of Fe(II)-rich water occurs at thesurface, and Fe(II) oxidation and acidification commence.Although these surface ponds may be vertically connectedto the groundwater, they may still be horizontally discon-nected from surface flows to the drain, and thus aciditywould not be discharged from the wetland (Figures 3 and 5).Once the ponded water is hydraulically connected to thedrain, a first flush mechanism is initiated. Surface waters arecontinuously connected horizontally and, once the watertable rises and intersects the drain, provide ongoing dis-charge to coastal waters. We note that this conceptual modeldoes not include a first flush event in which the first majorrainfall after a prolonged dry period washes surface acid andsalt deposits into adjacent waters [Kinsela and Melville,2004; Lin and Melville, 1993]. In this wetland, the risinggroundwater table provides the connectivity that flushesacid out of the system.

[36] Over spring-early summer, outflow from the wet-land ceases and the surface water retreats back to a seriesof disconnected pools before completely drying out. Theseephemeral standing waters display strong patchiness inboth space and time. The patchiness of the surface poolsprovides an indication of the ‘‘exposure’’ length and time-scales. However, the time lag between the onset of rainsand the first flush event would be strongly dependent onantecedent conditions, e.g., the length and intensity of thepreceding dry period [Wilson et al., 1999]. The longevityof the pools provides opportunity for Fe oxidation and sub-sequent production of acidity products. The patchiness ofthe pools was quantified by analysis of the total surfacewater volume (provided by the water balance) and the sur-face elevations (provided by the DEM). Comparison ofponding variability over seasons (Figure 11) highlights thelag between cessation of rainfall (in October) and the mini-mum number and surface area of ponds (in May). It alsoillustrates the variable connectivity between ponds andbetween the ponding surface water and the drain. Theseephemeral pools, containing high concentrations of dissolvedacidity products, discharge only once they are connected tothe drain.

[37] The oxidation of Fe(II) can be modeled using therate law given by the following equation [Stumm and Lee,1961]:

d Fe IIð Þ½ �dt

¼ �kabio PO2 OH �½ �2 Fe IIð Þ½ �; (7)

where PO2 is the partial pressure of oxygen (0.21 atm), andkabio is the rate constant (1.5 � 1013 L2 mol�2 atm�1 min�1

at 25�C). This rate law predicts extremely low rates of oxi-dation under acidic conditions.

[38] The rate constant k in equation (7) can be con-verted into a pseudo-first-order rate constant for ambient

Figure 4. Groundwater levels (m) in boreholes for March2009 (black-dotted contours) and September 2009 (dark-dotted gray contours). The extent of surface water forSeptember 2009, as calculated from the analysis of LiDARDEM and groundwater height measurements, is shown inlight gray shades. The location of boreholes is shown ascrosses, and the two gauging stations are shown as stars.The groundwater levels have a westerly gradient in autumn(March 2009) and a southwesterly gradient during latespring.


7

Figure 5. Seasonal ponding and connectivity of surface water at the study site. Images are derivedfrom the analysis of LiDAR DEM and groundwater measurements, from September 2008 to October2009. Red dots indicate boreholes, and green dots indicate drain gauging stations.


8

Figure 6. Seasonal variation in the water balance terms. (a) Measured daily drain outflow, precipitationand evapotranspiration, and calculated wetland water volume using specific yield ¼ 0.2. All units are in m3.(b) Changes in the volume of measured drain outflow, precipitation, evapotranspiration, and calculated netgroundwater outflow (indicated for Sy ¼ 0.2 and 0.5). All units are in m3 d�1.

Table 1. SPOCAS Results From Selected Soil Samples Collected at Different Depths of the Boreholesa

Sites Depth (cm) pHF pHOX pHKCl SP (%) SKCl (%) SPOS (%)ANCE

(mol Hþ/t) TPA (mol Hþ/t)TAA

(mol Hþ/t)

Bore 1 300 6.8 2.0 6.7 2.36 0.11 2.25 <2 1650 <2Bore 2 325 7.8 7.6 9.1 0.08 0.01 0.07 4480 <2 <2Bore 3 100 7.8 7.7 9.3 0.01 <0.01 0.01 220 <2 <2Bore 4 400 8.0 8.4 9.5 0.44 0.05 0.39 860 <2 <2

625 8.6 8.2 9.6 0.04 0.01 0.03 5100 <2 <2Bore 5 125 3.7 7.2 9.0 0.04 0.03 0.01 83 <2 <2

200 6.1 2.8 7.7 0.25 0.04 0.21 <2 97 <2Bore 6 25 8.3 8.8 9.5 0.06 0.04 0.02 2520 <2 <2

125 5.0 8.0 9.8 0.02 0.01 0.01 580 <2 <2200 6.2 7.1 9.5 0.07 0.02 0.05 61 <2 <2

Bore 7 50 3.0 6.4 6.0 0.05 0.05 <0.01 5 <2 8150 4.0 2.4 4.8 0.52 0.03 0.49 <2 310 52

Bore 8 500 7.2 8.3 9.7 0.35 0.04 0.31 956 <2 <2

apHF, pH measured in the field after suspended the soils in distilled water; pHOX, pH of the soils after reaction with H2O2; pHKCl, pH of the soils afterreaction with KCl; SP, total soluble and absorbed sulfide species; SKCl, total nonsulfidic sulfur; SPOS, peroxide oxidizable sulfur (difference between SP

and SKCl); ANCE, ‘‘excess’’ acid neutralizing capacity; TPA, titratable potential acidity; TAA, titratable actual acidity.


9

Tab

le2.

Ele

men

tal

Com

posi

tion

ofS

elec

ted

Soi

lsC

olle

cted

atD

iffe

rent

Loc

atio

nsa

Sit

esD

epth

(cm

)S

oil

Des

crip

tion

sS

iO2

(%)

TiO

2

(%)

Al 2

O3

(%)

Fe 2

O3

(%)

MnO

(%)

MgO

(%)

CaO (%

)N

a 2O

(%)

K2O

(%)

P2O

5

(%)

LO

I(%

)A

s(m

gkg�

1)

TO

C(%

)T

C(%

)T

S(%

)M

inor

Min

eral

s

Bor

e1

Sur

face

Bla

ck,o

rgan

ic-r

ich

loam

321.

20.

872.

60.

051.

723

0.26

0.36

0.22

37bd

l11

160.

05N

/A8–

14B

row

n,fi

nesa

nd38

0.82

0.94

1.6

0.03

2.0

250.

240.

440.

1630

bdl

3.9

9.5

0.02

N/A

14–2

4D

ark

gray

orga

nic-

rich

loam

130.

310.

325.

30.

020.

212.

10.

140.

110.

3378

4.0

2633

0.22

N/A

24–9

2B

lack

orga

nic-

rich

loam

3.0

0.49

0.29

170.

050.

381.

20.

040.

090.

0676

6.0

2124

12P

yrit

eB

ore

2S

urfa

ceB

lack

,org

anic

-ric

hsa

ndy

loam

441.

71.

21.

60.

061.

322

0.22

0.51

0.22

252.

02.

67.

30.

01N

/AB

ore

3S

urfa

ceO

rgan

ic-r

ich

blac

ksa

nd83

0.54

2.6

0.71

0.02

0.11

0.44

0.38

1.7

0.06

9.7

8.0

4.4

4.1

0.01

N/A

Bor

e4

Sur

face

Bla

ck,o

rgan

ic-r

ich

sand

ylo

am54

3.7

1.7

3.3

0.13

0.91

150.

250.

690.

2420

4.0

4.1

7.3

0.00

3N

/AB

ore

5S

urfa

ceB

lack

,org

anic

-ric

hsa

ndy

loam

540.

361.

71.

10.

081.

16.

70.

261.

10.

4232

2.0

1215

0.07

N/A

Bor

e6

Sur

face

Pea

ty,b

lack

top

soil

660.

321.

80.

610.

040.

3313

0.30

1.1

0.15

162.

02.

55.

30.

001

N/A

Bor

e7

Sur

face

Dar

k,or

gani

c-ri

chsa

ndy

loam

640.

623.

85.

30.

030.

221.

00.

311.

10.

1622

1510

100.

06G

oeth

ite

12–2

5D

ark

coar

sesa

nd,l

ittl

ecl

ay88

0.70

3.0

1.9

0.02

0.12

0.17

0.39

1.6

0.02

3.1

6.0

0.68

0.68

bdl

N/A

25–9

0G

ray

coar

sesa

nd,F

em

ottl

ing

920.

612.

80.

820.

010.

120.

110.

411.

80.

010.

9316

0.26

0.25

0.01

N/A

Bor

e8

Sur

face

Dar

kbl

ack

top

soil

571.

41.

71.

40.

050.

9917

0.26

0.83

0.16

192.

02.

26.

3bd

lN

/AS

WN

Sur

face

Bro

wni

shye

llow

Fe

crus

ts10

0.64

0.56

100.

040.

180.

520.

130.

160.

7775

9.0

1515

8.3

Pyr

ite

10–1

00O

rgan

ic-r

ich,

peat

ym

ater

ial

284.

61.

321

0.18

0.30

0.72

0.18

0.59

1.4

405.

033

381.

9P

yrit

eS

WS

Sur

face

Dar

kbr

own,

Fe

crus

ts29

1.6

0.94

380.

260.

140.

790.

230.

493.

723

bdl

6.9

7.8

0.29

N/A

a XR

Dda

tain

dica

ted

that

all

site

sw

ere

dom

inat

edby

quar

tz,

pota

ssiu

mfe

ldsp

ar,

calc

ite,

and

min

orm

iner

als

assh

own

inth

efi

nal

colu

mn.

bdl,

belo

wde

tect

ion

lim

it;

LO

I,lo

sson

igni

tion

;T

OC

,to

tal

orga

nic

carb

on;

TC

,tot

alca

rbon

;T

S,t

otal

sulf

ur.N

/A,n

otav

aila

ble.

Tab

le3.

Geo

chem

ical

Dat

aof

Che

mic

alE

xtra

cts

Fro

mS

urfa

ceS

oil

Sam

ples

Col

lect

edat

Thr

eeL

ocat

ions

inJu

ne20

09a

Sit

espH

F

Aci

dity

(mg

L�

1)

Alk

alin

ity

(mg

L�

1)

SO

2� 4(m

gL�

1)

Cl�

(mg

L�

1)

Ca2þ

(mg

L�

1)

Mg2þ

(mg

L�

1)

Naþ

(mg

L�

1)

Kþ

(mg

L�

1)

Al

(mg

L�

1)

As

(mg

L�

1)

Fe

(mg

L�

1)

Mn

(mg

L�

1)

Cd

(mg

L�

1)

Pb

(mg

L�

1)

Zn

(mg

L�

1)

Ni

(mg

L�

1)

SW

N2.

659

2<

112

3011

912

316

525.

9�

0.5

5.56

2.3

448

0.06

0.18

685.

94B

ore

16.

6<

124

615

870

140

5175

2611

8.72

251

6980

0.39

3.54

398

36S

WS

4.0

N/A

238

355

8212

036

0.47

�0.

52.

6746

7510

0.15

0.23

867.

7

a N/A

,not

avai

labl

e.


10

temperature and pressure conditions and for a predefinedpH as follows:

k0 ¼ kabio PO2 OH �½ �2; (8)

yielding k0 ¼ 3 � 10�2 min�1 and 3 � 10�8 min�1, at pH 7and 4, respectively; these values will be used for the analy-ses below.

[39] The size distribution of the ponds and how thisvaries over seasons (Figure 11 and Table 5) allow us toquantify the range of pool sizes and, therefore, the distribu-tion of exposure length and timescales. The characteristiclength and timescales are physically constrained, and themaximum duration of ponding at this site is approximately6 months, �E � 180 days (approximately 1.5 � 107 s).Then using

Fe IIð Þ½ �� ¼ Fe IIð Þ½ �0exp �k0�Eð Þ; (9)

we estimate the extent of Fe(II) oxidation over the 6 monthsof surface ponding to be 100% in the circum-neutral poolsand approximately 1% in the pools with pH 4. These simpleanalyses, using the water balance and DEM to provide esti-mates of �E, together with estimated rate constants, providesome insight into causes of geochemical heterogeneityobserved within both the soil profiles and the surroundingsoil water. These predictions require verification by high-resolution field measurements and also via the virtualexperiments explored by Frei et al. [2012].

4.2. Links Between Seasonal HydrologicalConnectivity and Transport of Acidic Salts

[40] Two dominant geochemical conditions, i.e., acid form-ing and carbonate buffering, occur at the site and interact withseasonal hydrology to add complexity to the geochemical

Figure 7. Piper diagram illustrating the averaged hydro-chemistry of the surface water- and groundwater-monitoringsites.

Figure 8. Seasonal variations of (a) water level (m below surface), (b) Eh (mV), (c) As (mg L�1), (d)pH, (e) Al (mg L�1), (f) Fe (mg L�1), (g) acidity (mg L�1), (h) SO2�

4 (mg L�1), and (i) Mn (mg L�1)concentrations observed in the groundwater bore 3. When the water table intersected the borehole slot-ting zones (0.75–2.75 m), fluctuating groundwater levels were observed with variable Eh-pH conditions.


11

signatures. Where groundwater acidification was greater thanthe buffering capacity of the formation, the groundwaterbecame acidic and vice versa. The concentrations of Al, As,Fe, and SO2�

4 showed high-temporal variability consistentwith the observed changes in pH and Eh conditions. Thestrong positive correlation (r2 ¼ 0.77) observed between Feand SO2�

4 concentrations in groundwater and surface waters(Figure 12) suggests the oxidative breakdown of sulfidic min-erals (e.g., iron monosulfides), releasing Fe, SO2�

4 , and Hþ

ions to the soil water (Table 4). The subsequent precipitationof these dissolved minerals on the wetland surface oversummer resulted in acid scalds (Figure 13). Iron coatingswere observed on plant roots during summer aerobic condi-tions; this has been previously suggested as a significant sinkfor As [Keon and Hemond, 2002]. Waterlogging over the sub-sequent winter may create reducing conditions and slowlyrelease this As to the soil water (Figures 8 and 9).

[41] The fluxes of Al, SO2�4 , and titratable acidity (i.e.,

mol of Hþ) from the wetland showed a very similardynamic to the measured/estimated salt fluxes (Figure 2a).The fluxes were very low or insignificant from October2008 to June 2009, during low discharge of drain water,and peaked in December 2008 and then from June toSeptember 2009 coinciding with rainfall events. Theobserved peaks indicated early hydrological controls on massfluxes out of the wetland. The decline in Hþ fluxes over latewinter suggests a successive depletion of surface species anddilution of discharged solutes following extended periods ofrainfall. With the onset of the dry summer, increasing evapo-transpiration triggered a rapid decline in the volumetric dis-charge concomitant with the loss of water from the ponding

surface. Evaporative precipitation deposited orange andyellow acidity products (up to 38% Fe2O3 and 8.3% TS,Table 2) along the drain bed and in the wetland depressions.These precipitates, in turn, became one of the sources ofacidity during the subsequent wet season.

4.3. Environmental Impacts of Acidic Metal-RichDischarges

[42] The discharge of acidic metal-rich waters fromASS-affected catchments has contributed to ecologicaldamage [Green et al., 2006; Rosicky et al., 2004; Sammutet al., 1995] by directly inhibiting plant growth and affect-ing the availability of plant nutrients [Rosicky et al., 2006].The formation of acidic bare surface scalds may kill off orexclude vegetation [Rosicky et al., 2004].

[43] Acid discharge from the major drain was calculatedto determine the potential danger to aquatic life down-stream [Sammut et al., 1996a]. The measured pH value ofthe discharged waters at SWS during the study period wasused to conservatively estimate the production of sulfuricacid from the wetland study area. This conservative esti-mate showed that the major drain discharged approximately720 kg ha�1 yr�1 of sulfuric acid, leading to a release of23.5 t from 11 September 2008 to 11 September 2009. Thisdischarge rate is significantly higher than previously pub-lished estimates of coastal ASS floodplain discharge, 100–200 kg H2SO4 ha�1 yr�1 for the Tweed River floodplainand 200–300 kg H2SO4 ha�1 yr�1 for the Richmond River[White et al., 1997].

[44] Freshwater quality guidelines were used to assessthe potential impact of the acid metal-rich discharge on

Figure 9. Seasonal variations of (a) water level (m below surface), (b) Eh (mV), (c) As (mg L�1), (d)pH, (e) Al (mg L�1), (f) Fe (mg L�1), (g) acidity (mg L�1), (h) SO2�

4 (mg L�1), and (i) Mn (mg L�1) con-centrations observed in the groundwater bore 6. The water table remained above the borehole slottingzones (2.0–4.0 m) and stable Eh-pH conditions were observed.


12

Tab

le4.

Geo

chem

istr

yof

Wat

erS

ampl

esC

olle

cted

Fro

mB

oreh

oles

(3an

d6)

and

Gau

ging

Sta

tion

s(S

WN

and

SW

S)a

Sit

esS

ampl

ing

Dat

e

Wat

erL

evel

(mB

elow

Sur

face

)pH

Eh

(mV

)E

C(m

Scm�

1)

Aci

dity

(mg

L�

1)

Alk

alin

ity

(mg

L�

1)

Ca2þ

(mg

L�

1)

Mg2þ

(mg

L�

1)

Naþ

(mg

L�

1)

Kþ

(mg/

L)

HC

O� 3

(mg

L�

1)

Cl�

(mg

L�

1)

SO

2� 4(m

gL�

1)

Al

(mg

L�

1)

As

(mg

L�

1)

Fe

(mg

L�

1)

Mn

(mg

L�

1)

Zn

(mg

L�

1)

Bor

e3

11S

epte

mbe

r20

081.

225.

8514

017

6290

<1

184

1348

8.4

<1

7284

60.

830.

033

250

0.21

0.06

Dep

th:

2.75

mbe

low

surf

ace

1O

ctob

er20

081.

166.

5914

311

2016

125

173

1541

6.0

153

4843

40.

410.

009

430.

160.

05

Slo

ttin

gde

pth

:0.

75–2

.75

m24

Oct

ober

2008

1.26

6.58

9413

705

5018

115

357.

761

5964

00.

520.

021

120

0.17

0.06

13N

ovem

ber

2008

1.30

6.5�

7315

199

2519

916

3512

3165

663

0.67

0.01

812

00.

190.

054

Dec

embe

r20

081.

366.

31�

8914

255

5019

015

2911

6165

556

0.69

0.02

410

00.

190.

0522

Dec

embe

r20

081.

426.

26�

102

1432

825

186

1332

1431

6258

50.

960.

037

110

0.14

0.05

14Ja

nuar

y20

091.

565.

94�

6515

476

<1

250

1835

17<

167

848

1.50

0.04

114

00.

160.

0828

Feb

ruar

y20

091.

764.

8716

311

8982

<1

104

9.1

3614

<1

6651

76.

300.

046

140

0.08

0.07

27M

arch

2009

1.82

4.43

181

1210

50<

178

8.9

3511

<1

7144

712

0.04

714

00.

070.

1323

May

2009

1.62

3.93

193

1526

65<

173

3.8

2913

<1

6747

033

0.04

118

30.

070.

1511

July

2009

0.98

4.8

197

726

88<

164

5.3

393.

5<

144

260

9.09

0.00

331

0.03

0.07

11S

epte

mbe

r20

091.

066.

5651

603

N/A

120

733.

929

4.8

142

4471

110.

013

9.51

0.05

0.07

Bor

e6

11S

epte

mbe

r20

080.

676.

564

775

1521

588

9.7

4227

262

5815

50.

820.

066

100.

100.

02D

epth

:4.

0m

belo

wsu

rfac

e1

Oct

ober

2008

0.65

6.43

100

747

1615

087

1143

2018

359

169

4.80

0.02

721

0.11

0.37

Slo

ttin

gde

pth

:2.

0–4.

0m

24O

ctob

er20

080.

786.

7625

683

525

021

212

4121

305

5944

20.

990.

090

170.

090.

0613

Nov

embe

r20

080.

886.

57�

7581

15

150

7912

4417

183

5719

10.

340.

030

210.

080.

054

Dec

embe

r20

080.

966.

53�

6073

55

150

689.

947

1618

356

161

0.08

0.03

615

0.08

0.02

22D

ecem

ber

2008

1.06

6.61�

7773

75

125

758.

844

1915

356

155

0.19

0.03

36

0.07

0.02

14Ja

nuar

y20

091.

26.

57�

9591

133

100

9015

4520

122

5825

30.

100.

031

260.

140.

0228

Feb

ruar

y20

091.

366.

65�

5668

45

125

689.

843

2015

355

177

0.06

0.05

217

0.07

0.05

27M

arch

2009

1.46

6.79�

9681

540

230

121

8.9

4520

281

5417

60.

100.

034

5.9

0.05

0.07

23M

ay20

091.

266.

47�

940

9N

/A74

383.

027

1374

3662

0.58

0.03

14.

690.

050.

0611

July

2009

0.59

6.64�

3263

71

112

735.

347

2211

257

115

0.04

0.04

412

0.09

0.07

11S

epte

mbe

r20

090.

496.

8810

744

N/A

134

866.

847

2313

460

156

3.16

0.12

932

0.18

0.10

SW

Nga

ugin

gst

atio

n11

Sep

tem

ber

2008

SW

2.9

N/A

171

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13

downstream ecosystems. Dissolved Al is highly toxic toaquatic and terrestrial organisms; for example, high Al con-centrations can cause damage to fish gills [Dussault et al.,2003]. The trigger value for Al in freshwater environmentswith pH <6.5 is 0.8 mg L�1 [Australian and New ZealandEnvironment Conservation Council and Agriculture andResource Management Council of Australia and New Zealand(ANZECC and ARMCANZ), 2000]. The Al concentrationsin the wetland discharge waters were mostly >1.2 mg L�1

(mean: 2.4 mg L�1). The study site is surrounded by agricul-tural and urban development and provides an important refuge

to endangered and ecologically important species that may beimpacted by the acid metal-rich waters of the wetland. Inaddition, the presence of acidic stagnant water benefits acid-tolerant mosquitoes, which has implications for the spread ofmosquito-borne diseases such as Ross River virus [Flexmanet al., 1998; Ljung et al., 2009].

4.4. Potential Management Options Controlling AcidicDischarges

[45] The most cost-effective solutions to manage aciddischarge from ASS-contaminated wetlands are drainage

Figure 10. Conceptual model of acidification process at the study site.


14

redesign or reflooding [Johnston et al., 2004; Sammutet al., 1996a; White et al., 1997]. Reflooding or inundationaims to re-establish reducing conditions to generate alkalin-ity and counter acidification [Dent, 1986; White et al.,1997, 2007]. The method depends on the supply of dis-solved organic carbon for the growth of sulfate reducingbacteria and the generation of sufficient alkalinity to neu-tralize acidic waters [Johnston et al., 2005]. Our sedimentdata indicated abundant TOC (between 0.26% and 33%,Table 2) suitable for bacterial growth and the reduction ofiron and sulfate as described by the following chemicalreactions [Dent, 1986]:

Microbial Fe reduction:

4FeOOHþ CH 2Oþ 8H þ ! 4Fe 2� þ CO 2 þ 7H 2O:

Microbial sulfate reduction:

SO42� þ 2CH 2Oþ 2H þ ! H 2Sþ 2CO 2 þ 2H 2O:

[46] Acidity is consumed during both iron and sulfatereduction. The generated sulfide can react with Fe2þ and

precipitate as secondary pyrite, FeS2, which neither producesnor consumes hydrogen ions, or iron monosulfides, whichproduces hydrogen ions [Kalin et al., 2006]:

Fe 2þ þ H 2S! FeS þ 2H þ

[47] The precipitation of FeS or FeS2 removes metalacidity from the system.

[48] A potential complication associated with re-floodingof Muddy Lakes may arise due to the large seasonal varia-tion in groundwater levels. Under these conditions, it maybe difficult to keep the site permanently inundated. Also,the alternative drying and wetting conditions induced bythe fluctuating groundwater table may destabilize the ironmonosulfides causing a rerelease of acidity and adsorbedcontaminants [Bush et al., 2004; Smith and Melville,2004]. Control strategies should be adopted to minimizegroundwater losses and evaporation during late summer.The application of thick mulches, such as straw, onto thescalds can create capillary breaks and reduce the evaporativeconcentration of acid salts at the land surface [Minh et al.,1997; Rosicky et al., 2006]. Mulching in conjunction withridging and once-off liming may encourage the re-establish-ment of native vegetation. Mulching combined with re-flooding may also provide additional sources of labile or-ganic carbon to support microbial reduction of sulfate andthe production of alkalinity. During dry periods (i.e.,

Figure 11. Size distribution of the ponds over differentseasons; the date of each snapshot is given in Table 5.

Table 5. Changes in the Number, Maximum Surface Area, andTotal Surface Area of Pools, Calculated From the Analysis of theLiDAR DEM and Groundwater Height Measurements From July2008 to October 2009, Including the Dates Shown in Figure 5

Event DateNumberof Pools

Surface Areaof LargestPool (m2)

Total SurfaceArea of

Pools (m2)

1 4 July 2008 155 9200 43,9002 15 August 2008 153 9300 43,7003 11 September 2008 153 9800 43,8004 1 October 2008 165 9900 49,3005 24 October 2008 161 10,700 37,0006 13 November 2008 154 10,100 29,2007 4 December 2008 133 9700 23,3008 22 December 2008 87 3700 14,0009 16 January 2009 43 2000 580010 23 May 2009 35 600 310011 15 June 2009 66 3600 12,10012 11 July 2009 185 29,100 63,00013 1 August 2009 187 30,000 66,00014 22 August 2009 27 41,600 83,70015 11 September 2009 191 37,400 76,20016 1 October 2009 184 12,900 59,000

Figure 12. The correlation between Fe and SO2�4 concen-

trations in boreholes 3 and 6 and gauging stations (SWNand SWS).

Figure 13. Example of surface acid scald at the study site.


15

October-March), the presence of mulch may also limit theexposure of monosulfide layers to oxygen and thus mini-mizes the cyclic buildup of acid salts.

[49] During reflooding, the changing redox conditionscould lead to the reductive dissolution of minerals resultingin the enrichment of pore water with As, Fe2þ, and other re-dox-sensitive elements [Johnston et al., 2011]. Our datademonstrated that the groundwater underlying the wetlandexhibited seasonal changes in redox status, and increasedconcentrations of redox-sensitive species were observed.Such redox-triggered release of toxic metal(oid)s must bemonitored through a pilot-scale study at the site beforeimplementing a flooding strategy.

5. Conclusions

[50] Our conceptual model highlights interactionsbetween seasonal hydrological processes and biogeochemi-cal characteristics of wetland. The model indicates the timelag among acidity generation in the subsurface, precipitationof acidity products at the surface, and the dissolution andtransport of acidic salts offsite through the major drain. Therelease of acidity products and trace metals threatens thesurvival of endangered species and communities livingwithin the wetland as well as aquatic ecosystems in adjoin-ing waterways. The conceptual understanding of the acidifi-cation processes and the seasonal hydrological connectivitywill facilitate improved management of the wetland ecosys-tems and the protection of downstream waters.

[51] Acknowledgments. The authors would like to express thanks toAzra Mat Daud, Gary Newman, Paul Livsey, and many others for their as-sistance in the collection of field data. This project was funded by the Aus-tralian Federal Government through the Natural Heritage Trust RegionalCompetitive Component project 53454.

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Hydrological and chemical connectivity dynamics in a groundwater-dependent ecosystem impacted by acid sulfate soils

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