Environmental impacts of irrigated sugarcane production: Herbicide run-off dynamics from farms and associated drainage systems

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Environmental impacts of irrigated sugarcane production: Herbicide run-off dynamics from farms and associated drainage systems A.M. Davis a,∗ , P.J. Thorburn b , S.E. Lewis a , Z.T. Bainbridge a , S.J. Attard c , R. Milla d , J.E. Brodie a a

Catchment to Reef Research Group, Australian Centre for Tropical Freshwater Research, James Cook University, Townsville, Qld 4811, Australia CSIRO Ecosystem Sciences, 41 Boggo Road, Dutton Park, Qld 4102, Australia CSIRO Ecosystem Sciences, Ayr, Qld 4807, Australia d Department of Employment, Economic Development and Innovation, Oonoomba, Townsville, Australia b c

a r t i c l e

i n f o

Article history: Received 23 February 2011 Received in revised form 18 June 2011 Accepted 20 June 2011 Available online xxx Keywords: Great Barrier Reef Pesticides Water quality Furrow irrigation Run-off

a b s t r a c t Irrigation is vital to most of the sugarcane produced in Australia’s ecologically sensitive Great Barrier Reef catchment area, although little is known regarding pesticide losses under irrigated sugarcane production. This study determined the dynamics of off-site paddock-scale pesticide movement and subsequent concentrations in local receiving environments in fully irrigated sugarcane farming systems of the lower Burdekin floodplain region, the largest sugar producing area in Australia. Chemical movement (both mass and concentration) in paddock surface run-off followed a similar pattern across sites in the region for several of the commonly applied herbicides such as diuron, atrazine and ametryn. Highest losses (loads and event concentrations) occurred in the first irrigation run-off events following application, with subsequent irrigation losses tailing off rapidly. Significant losses could also occur during wet season rainfall run-off events from paddocks with recent pesticide applications. There was a strong seasonal signal evident in catchment monitoring results. Pesticide concentrations in nearby receiving creek systems were invariably an order of magnitude or more lower than values collected at paddock-scale, highlighting the considerable dilution that takes place over relatively short distances. While the concentrations found in receiving creek systems were considerably lower than direct paddock run-off, they regularly exceeded some ecological guidelines and results of pesticide risk modeling suggested concentrations, particularly under dry season conditions, posed considerable ecological risk to aquatic ecosystems. Crown Copyright © 2011 Published by Elsevier B.V. All rights reserved.

1. Introduction As the area of global cropland increases (Scanlon et al., 2007), particularly land converted to irrigated agriculture, the environmental consequences of off-site pesticide movement on aquatic ecosystem health have emerged as a prominent natural resource management issue (Clark et al., 1999; Graymore et al., 2001; Cerejeira et al., 2003). An example of this issue is the potential detrimental effects of off-site movement of herbicides on the ecosystem health of Great Barrier Reef marine ecosystems, which has brought issues surrounding the use of herbicides within the Great Barrier Reef catchment area into sharp focus (Anon, 2003; Lewis et al., 2009; Brodie et al., in press). While receiving relatively less attention than potential effects on marine ecosystems, recent research has also highlighted herbicide presence in high

∗ Corresponding author at: Australian Centre for Tropical Freshwater Research, James Cook University, ATSIP Building, Townsville, Qld 4811, Australia. Tel.: +61 747815989; fax: +61 747815589. E-mail address: [email protected] (A.M. Davis).

value coastal wetlands and freshwater ecosystems (Davis et al., 2008). Understanding the dynamics of pesticide loss from farming systems and how this off-site movement influences receiving environments is an essential component of improved natural resource management. Sugarcane (Saccharum spp.) cultivation constitutes one of the dominant land-uses in the Great Barrier Reef catchment area (Furnas, 2003). While pesticide usage is a significant and integral component in Australian sugarcane production, the environmental implications of pesticide usage have proved an ongoing issue for the industry, whether driven by human health or ecosystem health considerations (Cavanagh, 2003). Australian sugar production is particularly reliant on a wide variety of herbicidal applications, and a more restricted range of insecticidal controls (Johnson and Ebert, 2000; Cavanagh, 2003). Recent industry transitions toward new farming practices, particularly minimum or zero tillage systems, have exacerbated this reliance on herbicides, particularly for the control of weeds in ratoon crops (Hargreaves et al., 1999; Johnson and Ebert, 2000). Due to high crop water demands, irrigation is a vital component of sugarcane production in many parts of the world, including

0167-8809/$ – see front matter. Crown Copyright © 2011 Published by Elsevier B.V. All rights reserved. doi:10.1016/j.agee.2011.06.019

Please cite this article in press as: Davis, A.M., et al., Environmental impacts of irrigated sugarcane production: Herbicide run-off dynamics from farms and associated drainage systems. Agric. Ecosyst. Environ. (2011), doi:10.1016/j.agee.2011.06.019

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Fig. 1. Map of lower Burdekin waterways depicting major land uses and catchment pesticide sampling locations. Note the area of internationally (RAMSAR) and nationally recognised wetlands. Land use categories are based on 2004 Queensland Land Use Mapping (QLUMP) shape files obtained from the Queensland Department of Natural Resources and Water (DNRW) for the Burdekin catchment.

Australia. Over 40% of sugarcane production area in Australia’s Great Barrier Reef catchments (accounting for ∼60% of crop production) occur in areas of highly seasonal rainfall, necessitating full or supplementary irrigation. The capacity for irrigation, while offering considerable agronomic benefit, also imposes an additional level of risk for off-site pesticide loss (Simpson and Ruddle, 2002). The dynamics of pesticide loss from non-irrigated sugarcane production farms and associated environmental impacts have been relatively well-described (Selim et al., 2000; Southwick et al., 2002; Cheesman, 2004). Information on the processes of herbicide loss from irrigated sugarcane, as well as environmental implications, are, however, relatively sparse at a global scale (although see Oliver and Kookana, 2006a,b). Given the extent of irrigated sugarcane, particularly in the Great Barrier Reef catchment area, this lack of data constitutes a considerable knowledge gap regarding the impact of irrigated sugarcane agroecosystems on the natural environment. The lower Burdekin River catchment (in north eastern Australia) constitutes both the largest furrow irrigated region in Australia, and the country’s largest sugarcane producing region. While paddock scale herbicide loss data are relatively limited, research has steadily accumulated in the Burdekin region addressing pesticide movement dynamics over a range of scales from the surface watergroundwater interface (Keating et al., 1996; Klok and Ham, 2004), floodplain waterway and drainage systems (Müller et al., 2000; Ham, 2007; Davis et al., 2008), end of riverine catchments (Davis et al., 2008) and most recently to riverine flood plumes in adjacent marine environments (Davis et al., 2008; Lewis et al., 2009). Results have highlighted a range of challenges for interpretation of monitoring data such as seasonal contrasts in water quality;

chronic, sub-lethal exposure times; and potential interactive effects between multiple toxicants with similar target sites and modes of action (Davis et al., 2008). The Burdekin River watershed forms a sizable proportion (33%) of the entire Great Barrier Reef catchment area. The dominant land use in the catchment is pastoral cattle production, accounting for over 80% of total catchment area (Dight, 2009a). The Burdekin River also drains one of Australia largest floodplain and delta environments (∼1250 km2 ). The delta, together with adjacent Burdekin River Irrigation Area, a surface-water irrigation scheme developed in the 1980s (Petheram et al., 2008), account for only a minor proportion of total catchment area (∼1%). However the region supports one of Australia most intensively cultivated and productive agricultural areas, with over 120,000 ha of irrigated crops, dominated (∼100,000 ha) by sugarcane (Fig. 1). The region represents Australia’s largest single sugar producing environment, yielding approximately 30% of Australia’s total sugar production (Anon, 2010). The remaining area is planted to mango plantations, cotton and mixed horticulture (Fig. 1). In addition to the area’s high economic value, the lower Burdekin floodplain also supports environments with significant ecological values, at both national and international levels. The Burdekin River delta encompasses a number of overlapping wetland complexes listed on either Australia’s National Directory of Important Wetlands or included on RAMSAR’s list of wetlands of international significance (Fig. 1; ANCA, 1996). Notable biota includes significant seagrass meadows, inter-tidal mangrove forests, supra-tidal samphire communities, aquatic bed macrophytes and emergent communities associated with fresh and brackish waters, forested

Please cite this article in press as: Davis, A.M., et al., Environmental impacts of irrigated sugarcane production: Herbicide run-off dynamics from farms and associated drainage systems. Agric. Ecosyst. Environ. (2011), doi:10.1016/j.agee.2011.06.019

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wetlands, floodplain palm savanna, gallery forest and lowland rainforest communities associated with river channel levees and floodout areas. These coastal wetland complexes provide breeding and feeding habitat for a diversity of waterbirds, plants, mammals, amphibians and reptiles designated as rare, vulnerable or endangered. The site includes areas of the Great Barrier Reef World Heritage Area and is contiguous with the Great Barrier Reef Marine Park area (ANCA, 1996). This manuscript presents data on herbicide losses from irrigated sugarcane farms in conjunction with water quality monitoring data from adjacent stream networks which drain the croplands of the lower Burdekin floodplain to highlight the associated environmental impacts to both marine and freshwater ecosystems in the region. The dynamics of herbicide run-off losses under conventional irrigated farming practices will be detailed in terms of losses of product applied; peak concentrations and temporal dynamics. This paper will also address the broader implications of these losses at a catchment-scale, with a focus on the ecological effects of surface herbicide run-off in the receiving waterbodies of the lower Burdekin floodplain. While clearly defined water quality guidelines for gauging ecosystem risk from herbicide exposure have been recently developed for Great Barrier Reef marine ecosystems (GBRMPA, 2009), and approaches to address interactive effects from multiple contaminants are currently emerging (Lewis et al., 2011), guidelines for the Great Barrier Reef’s freshwater ecosystems are poorly developed in comparison (Davis et al., 2008). An emerging approach to predict ecosystem risk of a mixture of herbicides (as measured in monitoring) to freshwater ecosystems will be applied to lower Burdekin sub-catchment and catchment scale water quality monitoring results. 2. Materials and methods 2.1. Study area The Burdekin sugarcane region stands apart from Australia’s other primary sugarcane producing regions. It has comparatively low annual rainfall and high solar radiation, which, together with plentiful irrigation water supplies and high fertilizer inputs result in the highest productivity in Australia (∼120 t cane ha−1 ). However, these inputs and an almost total reliance on furrow irrigation mean that risks of environmental impacts from cropping in the Burdekin may be higher than in other sugarcane production areas. The lower Burdekin floodplain is drained by the Burdekin River, Haughton River, Barratta Creek and a number of additional natural and artificial drainage channels (Fig. 1). A notable hydrologic characteristic of the region is that due to local topography north of the main Burdekin River channel, the majority of the drainage from canelands between the Burdekin and Haughton Rivers flows into the Barratta Creek system. A similar situation occurs to the south of the main Burdekin River channel where most drainage occurs through smaller coastal creek systems. Many of these smaller creek and drainage lines, which historically had intermittent flows, are now perennial systems with constant flow throughout the year. The flows are due to (1) both the direct (deliberate use as irrigation water supply conduits) and the indirect (irrigation tailwater influx) effects of recent water resource development in the dry season, and (2) wet season rainfall run-off. 2.1.1. Burdekin sugar industry Sugarcane is a semi-perennial crop. In the Burdekin, it is mainly planted in autumn (April–May) and harvested 15–18 months later. The crop is then allowed to re-grow (ratoon) and harvested approximately annually (harvesting season is June–December). All crops are harvested mechanically. Productivity of the crop declines after

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3–5 harvests. At this time it is destroyed, and the field is fallowed for ∼6 months until the next sugarcane crop is planted. This sequence, planting to planting, is called a cropping cycle, with the crops denoted plant crop, first ratoon crop, etc. Unlike other sugarcane growing districts in Australia, almost all (∼95%) of the Burdekin sugarcane crop is burnt prior to harvest to remove dead leaves and make harvesting easier. The lower Burdekin region’s wet–dry tropical climate exhibits strong seasonality in the form of pronounced wet and dry seasons. High intensity summer wet season rainfall (occurring between November and April) contrasts with minimal rainfall over the remainder of the year (Dight, 2009a). The regions’ dry-tropical monsoonal climate, coupled with low and variable rainfall (average rainfall ca. 1000 mm yr−1 ) has seen the sugarcane industry rely on irrigation since floodplain lagoons were first used to complement local rainfall in the 1880s (Kerr, 1994). Irrigation inputs in the region are typically around 2000 mm per crop (Charlesworth et al., 2002; Thorburn et al., 2011), and almost entirely applied by furrow systems involving lay-flat surface fluming and flow controlling cups or siphons located at the head of paddocks. Paddock tailwater is in some cases recaptured and recycled (ca. 30% of total farmed area), or otherwise leaves the farm via drainage channels. In some areas developed on freely draining soils, however, run-off losses can be minimal, with the dominant loss pathway of excess irrigation or rainwater via deep drainage (Dight, 2009a). Herbicide use on the lower Burdekin floodplain (Table 1) is broadly consistent with those used across the Australian sugarcane industry (Hamilton and Haydon, 1996; Johnson and Ebert, 2000).

2.2. Paddock surface run-off pesticide monitoring, sample collection and load calculations Paddock scale data were collected from seven farms distributed across the lower Burdekin floodplain, spanning a wide range of soils, applied herbicides and application dates (Table 2). All paddock-scale monitoring took place on commercial farms, with management operations conducted by collaborating farmers in accordance with their standard practice. The herbicide application and management practices monitored on these farms represented relatively conventional practices in the region at the time of the study, i.e. broadcast application from boom sprayers, heavy reliance on residual herbicides. The efficacy of several pre-emergent herbicides such as atrazine or diuron is contingent upon some process of early incorporation via cultivation or ‘watering in’ by irrigation or rainfall (O’Grady and Sluggett, 2000; Simpson and Ruddle, 2002). Paddocks are therefore typically irrigated during the 2- to 6-day period following herbicide application, unless sufficient rain falls during this critical period. Paddock row widths (centre to centre) are typically 1.5 m, with a slow industry shift toward matching row spacing with field equipment (a move to 1.8 m row spacing). The majority of paddocks have undergone slope modification to assist with irrigation and drainage, with paddock slopes typically ranging between 1:800 and 1:1200. The majority of paddock run-off monitoring effort focused on the initial irrigation events following herbicide application. At several instrumented sites, paddock run-off volumes were measured using either Parshall flumes or ultrasonic dopplers installed in paddock drainage outfalls (following Hawdon et al., 2007). Multiple discrete water quality samples were also collected using automated water sampling equipment throughout selected run-off events. Details of run-off and water sampling methods for Farms 3 and 7 are given by Thorburn et al. (2011; their Mulgrave and Delta sites, respectively). To provide additional data on herbicide concentrations in irrigation tailwater run-off, multiple discrete herbicide samples were also manually collected during irrigation events at a

Please cite this article in press as: Davis, A.M., et al., Environmental impacts of irrigated sugarcane production: Herbicide run-off dynamics from farms and associated drainage systems. Agric. Ecosyst. Environ. (2011), doi:10.1016/j.agee.2011.06.019

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Table 1 Summary table outlining the commonly utilized herbicides in sugarcane production on the lower Burdekin floodplain (Davis et al., 2008), target pests, application details and environmentally relevant chemical properties. Target weeds

Typical application period and rates (g a.i. ha−1 )

Mode of action

Phenylureas Diuron

Grasses

April–December (247–3510)

Photosystem II inhibition

35.6

75

1067

Triazines/triazinones Atrazine

Broad leaf weeds

29

100

Grasses

200

37

316

Hexazinone

Grasses and broad leaf weeds

Photosystem II inhibition Photosystem II inhibition Photosystem II inhibition

35

Ametryn

February–December (1980–2970) April–July (1097–2000) August–December (165–728)

33,000

90

54

Broad leaf weeds and vines

Year-round (1100–2200)

Auxin growth regulator

23,180

10

56

Glycines Glyphosate

Grasses

Year-round (2160–3240)

Amino acid inhibitor

10,500

12

21,699

Bipyridinyls Paraquat

Grasses

April–December (300–700)

Photosystem I inhibition

620,000

3000

1,000,000

Chemical active ingredient (a.i.)

Phenoxy/pyridine acids 2,4-D

Solubility in water (mg L−1 )

Half-life in soil (DT50: days)

Organic carbon sorption constant (KOC )

Chemical properties compiled using the ‘Footprint’ Pesticide Properties Database: http://sitem.herts.ac.uk/aeru/footprint/en/index.htm.

number of less intensively monitored sites lacking discharge monitoring capacity. At sites where run-off discharge was measured, herbicide loads (active ingredient) were calculated from continuous time series discharge data and discrete point source water quality data by linear interpolation using the BROLGA program (version 2.11; Queensland Department of Natural Resources and Water, 2007).

2.3. Sub-catchment and end of catchment pesticide sample collection Sub-catchment and end-of-catchment water quality monitoring sites were selected to reflect the diffuse surface water discharge across the lower Burdekin floodplain. A total of nine sampling sites were monitored over the period January 2005 to April 2010 (Fig. 1).

Table 2 Description of lower Burdekin monitored sugarcane farms, herbicide active ingredient (a.i.) application rates and timing. Farm number and relevant catchment water quality monitoring sites

Soil type

Paddock area (ha)

Row length (m)

Active ingredient applied

Application date (year-month)

Farm1 B1, B2, B3

Grey vertosol

15

1000

Farm 2 B1, B2, B3

Grey vertosol

8

500

Farm 3 B2, B3

Grey vertosol

40

1200

Farm 4 B1, B2, B3

Black vertosol

40

1000

Farm 5 B1, B2, B3

Sodosol

38

1000

Farm 6 P1

Kandosol

20

500

Farm 7 P1

Grey vertosol

20

650

Atrazine Atrazine Atrazine Ametryn Ametryn Ametryn 2,4-D 2,4-D 2,4-D Atrazine Atrazine Ametryn Ametryn Glyphosate Diuron Diuron Atrazine Atrazine Atrazine Diuron Hexazinone Atrazine Diuron Paraquat 2,4-D Diuron Atrazine 2,4-D Paraquat Atrazine Diuron

Dec-05 Dec-05 Dec-05 Dec-05 Dec-05 Dec-05 Dec-05 Dec-05 Dec-05 Apr-07 Apr-07 Apr-07 Apr-07 Mar-07 Oct-04 Dec-06 Oct-04 Oct-04 Sep-09 Sep-09 Sep-09 Nov-09 Nov-09 Nov-09 Nov-09 Oct-06 Oct-06 Oct-06 Oct-06 Oct-05 Nov-05

a.i. application rate (g a.i. ha−1 ) 1500 1500 1500 1500 1500 1500 620 620 620 1980 1980 400 400 1620 225 375 580 580 450 234 165 1800 450 375 469 300 300 500 1300 1530 244

Catchment water quality monitoring site acronyms refers to site locations outlined in Figs. 1 and 2: B1, Upper Barratta Creek; B2, East Barratta Creek; B3, West Barratta Creek; P1, Plantation Creek.

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Most sites selected had sugarcane as a dominant land use in the upstream catchment area (Barratta Creek, Sheep Station Creek, Plantation Creek, Iyah Creek and Healey’s Lagoon). An additional site on Yellow Gin Creek contained no sugarcane in its watershed and was included to allow comparisons with water quality draining a local pastoral grazing catchment. The number of samples collected through time varied according to funding availability; however, attempts were made to collect samples at all sites during times of both high and low flow. High flow events typically occurred in the wet-season (November-April) where flow was driven by high rainfall. Low flow conditions (May–October) were dominated by irrigation tailwater in the sampling sites draining sugarcane catchments. Particular effort was paid to the collection of frequent samples during the rising stages of flood events, the period when contaminant concentrations tend to be highest. Grab samples were collected manually at all sites through the use of a sampling pole. A total of 275 samples were collected over the monitoring period, including 205 high flow event samples and 70 samples collected during low flow, dry season conditions (a detailed summary of the number of samples collected according to site and season are available in Table A.1). Additional duplicate samples were collected at selected sites for analytical precision estimates. 2.4. Analytical methodology All pesticide samples collected during paddock and subcatchment scale run-off events were sampled into 1 L amber glass bottles, supplied by the Queensland Health and Forensic Scientific Services (QHFSS) laboratory. Samples were then refrigerated at 4 ◦ C and couriered to the QHFSS laboratory in Brisbane, Queensland for analysis. The amber bottles were pre-cleaned with acetone and ethanol and blow-dried with nitrogen fitted with a carbon filter. The water samples were analyzed by liquid chromatography mass spectrometry (LCMS) and gas chromatography mass spectrometry (GCMS) at the National Association of Testing Authorities accredited QHFSS laboratory. Organochlorine, organophosphorus and synthetic pyrethroid pesticides, urea and triazine herbicides and polychlorinated biphenyls were extracted from the sample with dichloromethane. The dichloromethane extract was concentrated prior to instrumentation quantification by GCMS and LCMS (QHFSS method number 16315). Phenoxyacid herbicide water samples, which were collected in separate 1 L amber glass bottles, were acidified and extracted with diethyl-ether. After evaporation and methylation (methanol, concentrated sulfuric acid and heat) the samples were extracted with petroleum ether and analyzed by GCMS (QHFSS method number 16631). Duplicate samples collected for analytical precision estimates produced values for pesticides of key interest (ametryn, atrazine, diuron) typically within ±15%. For full method description see Lewis et al. (2009). 2.5. Assessment of ecosystem risk in receiving environments Summary boxplots were constructed using the SPSS software package (SPSS 2007) for three of the most commonly detected herbicide residues in lower Burdekin sub-catchments (i.e. ametryn, atrazine and diuron) in order to depict pesticide concentration trends during both low flow and event conditions. Any results below detection limits were treated as a zero concentration (nondetect). Low flow concentrations were compared to a number of current ANZECC and ARMCANZ (2000) water quality guideline levels to highlight potential ecosystem risk from the effects of individual toxicants. Since no event flow guidelines are available for freshwater ecosystems, the current ANZECC and ARMCANZ (2000) guidelines (developed specifically for low flow or ambient conditions) were used to also provide an indication of risk in these conditions. During event flows, pollutants are transported

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into the marine environment and so the GBRMPA (2009) ecosystem protection trigger values for the Great Barrier Reef provide a somewhat better indication to assess ecosystem risk during high flow events. The GBRMPA (2009) guidelines were developed for the marine-estuarine components of the Great Barrier Reef Marine Park using available toxicity data for fish, molluscs, algae, diatoms and crustaceans and provide context to data collected from the endof-catchment sites which are in close proximity to the estuarine zone. To provide a more meaningful assessment of ecosystem health than given by single pesticide-specific guidelines such as those available in ANZECC and ARMCANZ (2000), we also analyzed dryseason herbicide concentration data with the Predict the Ecological Risk of Pesticides in freshwater ecosystems (PERPEST; Version 3.0) model (Van den Brink et al., 2002; Van Nes and Van den Brink, 2003). This model uses a case-based reasoning approach, drawing on empirical ecotoxicological data to predict the ecological risks of pesticides in freshwater ecosystems. The PERPEST model has a range of features that make it particularly suitable (in light of current guideline limitations) to perform a retrospective assessment of monitoring results from the Burdekin floodplain. These include the capacity to predict the interactive effects of multiple contaminants, model variable acute and chronic exposure times and also incorporate stream hydrology into predictive models (Van den Brink et al., 2002). PERPEST modeling scenarios depicting herbicide effects on eight structural and functional community endpoints (community metabolism; fish and tadpoles; macrocrustaceans and insects; macrophytes; molluscs; periphyton; phytoplankton; and zooplankton) under typical dry season water quality conditions were calculated at the seven sub-catchment monitoring sites from collated monitoring data. PERPEST was applied using arithmetic mean herbicide concentrations for several of the more commonly detected sugarcane associated herbicides (atrazine, ametryn, diuron, hexazinone, 2,4-D) from combined dry season monitoring data collected at all sub-catchment and end-of-catchment monitoring sites. The model simulated a continuous 60-day constant exposure (a likely exposure scenario for this region), indicating the probability of five effect classes on ecological endpoints (following Van den Brink et al., 2002): (1) No effects demonstrated: No consistent adverse effects are observed as a result of the treatment. Observed differences between treated test systems and controls do not show a clear causality. (2) Slight effects: Confined responses of sensitive endpoints (e.g. partial reduction in abundance). Effects observed on individual sampling dates only and/or of a very short duration directly after treatment. (3) Clear short-term effects, lasting <8 weeks: Convincing reductions in sensitive endpoints. Recovery, however, takes place within 8 weeks. Effects observed on a sequence of sampling dates. (4) Clear effects, recovery not studied. Clear effects (e.g. severe reductions of sensitive taxa over a sequence of sampling dates) are demonstrated, but duration of the study is too short to demonstrate complete recovery within 8 weeks after the last treatment. (5) Clear long-term effects, lasting >8 weeks: Convincing reductions in sensitive endpoints and complete recovery of these endpoints later than 8 weeks after the last treatment. Negative adverse effects reported over a sequence of sampling dates. Details of site specific water quality concentrations and model inputs are available in Table B.1.

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3. Results 3.1. Paddock scale herbicide run-off data The amount of diuron lost from paddocks in the initial irrigation following application varied between 0.03 and 1.9% of the active ingredient applied, with a maximum recorded concentration of 120 ␮g L−1 (Table 3). For atrazine, losses were between 0.7 and 2.6%, with a maximum measured run-off concentration of 780 ␮g L−1 . Ametryn losses varied between 1.5 and 6.4%, with a maximum measured concentration of 420 ␮g L−1 . Losses of 2,4-D varied between 0.5 and 3.4% applied, with a maximum measured concentration of 280 ␮g L−1 . A single irrigation event following a glyphosate application was monitored, with 0.5% of active ingredient applied leaving the paddock in run-off and a peak measured concentration of 54 ␮g L−1 . The only chemical that was not detectable in tailwater run-off following application was paraquat, which was below analytical detection limits (<0.1 ␮g L−1 ) during irrigations occurring soon after application at two sites. In circumstances where paddocks were monitored through multiple irrigations, losses of all chemicals (mass and concentration) were greatest in the first irrigation run-off event following application, before diminishing rapidly in subsequent irrigations and, in some cases, being below detection limits. One year after application of these herbicides concentrations in run-off water were below detection (0.01 ␮g L−1 ) for all chemicals. Two paddocks were monitored through multiple post-herbicide application irrigations as well as the first major wet-season rainfall events, where >250 mm rainfall occurred over a 6-day period. On one of these paddocks (Farm 5) where significant rainfall occurred within 7 weeks of application, herbicide loads totaled 0.06% of atrazine applied and 0.38% diuron applied over a 6-day rainfall-driven run-off event. Rainfall run-off losses from the second paddock, where application occurred 3 months prior to the rainfall event (Farm 4) totaled <0.01% of all products applied (Table 3). In both cases, these wet season rainfall-driven load losses were substantially lower than those occurring in the initial dry season irrigation events following product application to paddocks. 3.2. Sub-catchment and end-of-catchment pesticide monitoring results A total of 19 different pesticide residues, including 18 herbicides or their breakdown products, and a single insecticide (imidacloprid), were detected across the nine monitored sites over the course of the study (Fig. 2, Table C.1 provides additional data on pesticide residue sample numbers, detections across sites and seasons and concentration ranges). The majority of positive pesticide detections occurred in catchments dominated upstream by sugarcane production, although low level single detections of two herbicides, fluometuron (0.04 ␮g L−1 ) and diuron (0.01 ␮g L−1 ), occurred in the grazing dominated catchment of Yellow Gin Creek during a 2006 flood event. Ametryn, atrazine (including its breakdown products desethyl and desisopropyl atrazine) and diuron were the chemicals most frequently (>50% of samples; Fig. 2) detected across the majority of sites monitored under both high flow and low flow conditions (results for atrazine, diuron and ametryn shown in Fig. 3). The majority of detected herbicides (ametryn, atrazine, diuron, hexazinone, 2,4-D, MCPA, metolachlor, terbutryn, metribuzin and fluroxypyr) are all products currently registered for use in the sugar industry. The remaining herbicides such as fluometuron, prometryn, simazine and bromacil are registered for weed control in other crop types (i.e. cotton, cereals or mixed cropping), or in the case of tebuthiuron, registered for woody plant control on grazing lands (Australian Pesticides and Veterinary Medicines Authority, 2011).

Atrazine Diuron Desethylatrazine Desisopropylatrazine Ametryn Tebuthiuron Hexazinone Metolachlor Simazine Imidacloprid Bromacil Terbutryn Prometryn Fluometuron 2-4,D MCPA Fluroxypyr Propazine Metribuzin

a

b c 0%

20%

40%

60%

80%

100%

Detection frequency (%)

Fig. 2. Bar graph of pesticide detection frequency (%) in water samples collected across nine lower Burdekin waterway monitoring sites for the period 2005–2010. Detection limits for most herbicides was 0.01 ␮g L−1 , apart from 2,4-D, propazine and MCPA (0.1 ␮g L−1 ). Analytical procedures for pesticides are indicated as follows: a, LCMS; b, phenoxyacid GCMS; and c, GCMS.

Sampling sites that received significant surface water run-off from sugarcane farms during high intensity wet season flood events (i.e. all except Yellow Gin Creek) had both a similar suite of herbicide residues present and relative herbicide concentrations (Fig. 3). The highest herbicide concentrations in most waterways during high flow events occurred during the rising limb of flood hydrographs (data not shown) as expected (Davis et al., 2008) as ‘first flushes’ of accumulated catchment contaminant loads entered local waterways in the early stages of flood events. This phase was followed by rapid dilution during the peak and recession of flood events with lower concentrations of several chemicals continuing during the tail end of these events. The spatial consistency in high flow herbicide residue composition and concentrations across the lower Burdekin floodplain contrasted with low flow, dry-season monitoring results. There were pronounced differences between water quality characteristics at various sites through the duration of dry-season conditions, particularly between monitoring sites located on the Barratta Creek complex and other lower Burdekin waterways. The highest recorded concentrations of ametryn (2.5 ␮g L−1 ), atrazine (27 ␮g L−1 ), diuron (8.5 ␮g L−1 ) and 2,4-D (9.5 ␮g L−1 ) during any season were all recorded at Barratta Creek sites during irrigation tailwater dominated low flow conditions (Fig. 3). Concentrations of diuron, atrazine and ametryn (as well as chemicals such as hexazinone and 2,4-D not depicted in boxplots) were relatively high and persisted throughout the dry season in Barratta Creek compared to other systems. Depiction of median dry season concentration values for herbicides, such as atrazine and diuron, highlights consistent detection above some ecosystem health guidelines (Fig. 3A and C). Atrazine concentrations in low flow samples were above ANZECC and ARMCANZ (2000) 99% ecosystem protection limits (0.7 ␮g L−1 ) in 91%, 73% and 89% of samples at Upper, East and West Barratta Creek sites respectively. Diuron concentrations in low flow samples were above the ANZECC and ARMCANZ (2000) ‘low reliability’ ecosystem protection limits (0.2 ␮g L−1 ) in 91%, 73% and 89% of samples at Upper, East and West Barratta Creek sites respectively. 3.2.1. PERPEST modeling PERPEST modeling of herbicide exposure scenarios highlighted sites located in the Barratta Creek catchment as being at high risk of impaired ecosystem function compared to other lower

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Table 3 Application rates and losses of herbicides from irrigated lower Burdekin sugarcane farms. Active ingredient applied

Farm number

a.i. application rate (g a.i. ha−1 )

2,4-D 2,4-D 2,4-D 2,4-D 2,4-D Ametryn Ametryn Ametryn Ametryn Ametryn Atrazine Atrazine Atrazine Atrazine Atrazine Atrazine

Farm 1 Farm 1 Farm 1 Farm 5 Farm 6 Farm 1 Farm 1 Farm 1 Farm 2 Farm 2 Farm 1 Farm 1 Farm 1 Farm 2 Farm 2 Farm 3 Farm 3 Farm 4 Farm 4 Farm 4 Farm 5 Farm 5 Farm 5 Farm 5 Farm 6 Farm 7 Farm 7 Farm 7 Farm 3 Farm 3 Farm 3 Farm 3 Farm 4 Farm 4 Farm 4 Farm 5 Farm 5 Farm 5 Farm 5 Farm 6 Farm 7 Farm 2 Farm 4 Farm 4 Farm 4 Farm 5 Farm 5 Farm 6

620 620 620 469 500 1500 1500 1500 400 400 1500 1500 1500 1980 1980 580

Atrazine

Atrazine

Atrazine Atrazine

Diuron Diuron Diuron

Diuron

Diuron Diuron Glyphosate Hexazinone

Paraquat Paraquat

450

1800

300 1530

225 375 234

450

300 244 1620 165

375 1300

Run-off timing post-application (days) 2I 2I 2I 6I 4I 2I 2I 2I 2I 3I 2I 2I 2I 2I 3I 3I 14I 4I 20I 134R 6I 20I 42R 61R 4I 3I 24I 42I 3I 14I 3I 12I 4I 20I 134R 6I 20I 42R 61R 4I 3I 14I 4I 20I 134R 6I 20I 4I

Run-off load (g a.i. ha−1 )

Total loss (% of applied)

Peak recorded event concentration (␮g L−1 )

14.5 15.8 13.2 2.3 NA 22.4 23.7 23.7 33.8 17.1 27.6 30.3 30.3 52.4 25.6 17.9 0.4 21.6 1.2 0.3 12.6 1.2 0.08 1.1 NA 4.1 0.1 0.1 3.9 BD 0.1 0.3 4.5 2.4 0.5 4 0.49 0.23 1.7 NA 0.8 6.1 2.5 1 0.2 BD BD NA

3.1 3.4 2.8 0.48 NA 1.5 1.5 1.5 6.4 4.3 1.8 2.0 1.8 2.6 1.7 3.1 0.07 4.8 <0.01 <0.01 0.70 0.07 <0.01 0.06 NA 0.27 <0.01 <0.01 1.7 BD 0.03 0.08 1.9 1.0 <0.01 0.88 0.11 0.05 0.38 NA 0.30 0.50 3.8 1.5 <0.01 BD BD NA

280 250 250 82 48 400 410 290 350 420 450 600 520 620 780 545 10 119 8.2 0.8 307 18 6.3 3.1 49 157 6 3 120 BD 10 6 25 25 1.5 98 8.2 81 5.9 85 93 54 13.7 10.2 0.5 BD BD BD

I

= irrigation run-off events; R = paddock run-off events due to rainfall; BD = parameter concentrations below analytical detection limits; NA = monitored events where run-off volumes were unavailable, negating the capacity for load calculations, and only concentration data were available. Soil types are based on the classification scheme of Isbell (1996).

Burdekin water quality monitoring locations. PERPEST results for two sites, Upper Barrata Creek (B1) and the Haughton River (H1), are described here (Figs. 3 and 4) to highlight differences between Barratta Creek and other floodplain waterways. Model results for all remaining sites are presented in Appendix D. PERPEST model results indicate that the chronic herbicide concentrations evident at Upper Barratta Creek pose a serious risk to the functioning and structure of aquatic ecosystems. Probabilities of clear effects were calculated to be greater than 50% for macrocrustaceans and insects, periphyton, phytoplankton, and zooplankton, and greater than 25% for macrophytes and community metabolism (Fig. 4). A small probability of clear effect was only indicated for molluscs, while no relevant cases for the scenario were available for fish and tadpoles in the database. Similar PERPEST risk profiles, with probabilities of clear effects greater than 25% for four or more ecosystem components, emerged for East and West Barratta Creek (Figs. D.1 and D.2).

Different predicted levels of ecological risk were apparent from modeling results for the Haughton River site (Fig. 5). Probabilities of clear effects greater than 25% were predicted for periphyton, phytoplankton and zooplankton community endpoints. Other nonBarratta Creek catchment floodplain monitoring sites (Iyah Creek, Plantation Creek, Sheep Station Creek) demonstrated similar, or lower risk profiles to the Haughton River (Fig. D.3, D.4 and D.5). 4. Discussion The interaction between furrow irrigation and herbicide application has had a considerable seasonal effect on water quality across large areas of the lower Burdekin floodplain. Irrigation events soon after herbicide application, rather than rainfall events, are a major mechanism of paddock herbicide loss from lower Burdekin farms under typical climatic conditions. Many of the key herbicides of environmental interest (diuron, atrazine, ametryn,

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Fig. 3. Boxplots summarising herbicide concentration during wet-season flood events (B, D, and F) and low flow conditions (A, C, and E). Summary boxplots present the median value (line in box), interquartile range (containing 50% of values), extreme values (values more than 3 box-lengths from the 75th percentile) and whiskers extending to highest and lowest values (excluding outliers). The dotted red lines in the atrazine and diuron boxplots represent the ANZECC and ARMCANZ (2000) 99% guideline for ecosystem protection and ‘low reliability guideline’ respectively. Dotted blue lines represent GBRMPA (2009) moderate reliability guidelines for 99% ecosystem protection in marine ecosystems. Site codes: B1, Barratta Creek; B2, East Barratta Creek; B3, West Barratta Creek; I1, Iyak Creek; P1, Plantation Creek; S1, Sheep Station Creek; H1, Haughton River; H2, Healey’s Lagoon; Y1, Yellow Gin Creek.

etc.) are applied during the dry season and receive multiple irrigations prior to significant wet season rainfall. Catchment monitoring data highlight irrigation tailwater run-off into receiving waterways during the dry season as a major driver of temporal patterns in herbicide concentrations across the lower Burdekin floodplain. Ecotoxicological modeling of monitoring data suggests these irrigation tailwater inputs into aquatic ecosystems pose significant risks to ecological function, particularly when prolonged, multi-substance exposure is considered.

4.1. Paddock scale herbicide data The maximum concentrations, loads (g a.i. ha−1 ) and proportionate losses of applied chemicals such as atrazine leaving Burdekin sugarcane farms (Table 3) were similar to those found in the other furrow irrigated sugarcane producing area in Australia, the Ord River district (north-western Australia), under conventional farming practices (Oliver and Kookana, 2006a,b). The maximum recorded atrazine concentrations in irrigation tailwater

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Fig. 4. Probability of ecological effect classes as predicted by PERPEST on eight functional and structural aquatic community endpoints at Upper Barratta Creek (B1) under low flow conditions. The numbers of cases (n) in the PERPEST ecotoxicological database used to make predictions of concentration effects on each endpoint are indicated. No relevant cases were available in the modeled concentration ranges for fish and tadpoles, and effects were not evaluated in this study.

run-off in this study also equate closely to levels found in rainfed production systems where significant rainfall events occurred soon after application in Louisiana (USA) sugarcane farms (Selim et al., 2000). Understanding the chemical properties of various pesticide types (solubility, soil-binding characteristics, persistence etc.) is regarded as a fundamental component of managing the risk of excessive off-site movement after application (Wauchope, 1978; Hargreaves et al., 1999; Simpson et al., 2002; Silburn and Kennedy, 2007). A number of the relatively soluble and moderately persistent herbicide species assessed in this study (atrazine, ametryn, 2,4-D and diuron; Table 1) that have low sorption affinity for soil particles (i.e. low KOC values) are inherently susceptible to off-site movement in solution, an attribute clearly supported by both our paddock (Table 3) and sub-catchment (Fig. 2; Table C.1) scale monitoring results. In contrast, other compounds commonly used in the Burdekin, such as paraquat and glyphosate, while quite soluble have higher KOC values (Table 1), reflecting the relative affinity of these compounds for adsorption onto soil particles. Irrigation and rainfall event run-off typically had low sediment concentrations and

therefore little ability to transport paraquat off-site. This theoretically low susceptibility to off-site movement in solution was borne out in several monitored irrigation events where, despite two recent applications of paraquat (irrigated within 4–6 days of application), the compound could not be detected in subsequent tailwater run-off (<0.1 ␮g L−1 , Table 3) from the paddock, suggesting almost total adsorption to soil. While glyphosate received minimal monitoring effort in this study, the limited available data also suggested relatively low propensity for off-site loss in run-off with <1% loss of active ingredient applied leaving the paddock in the first post-application irrigation event (Table 3). While this study has highlighted some of the general patterns of pesticide loss occurring under furrow irrigated sugarcane farming systems, the current dataset is essentially preliminary. More comprehensive monitoring of individual paddocks over multiple years and under varying climatic conditions is required to better elucidate herbicide run-off dynamics. Similarly, a more thorough understanding of the temporal dynamics of soil pesticide concentrations (Silburn and Kennedy, 2007) would add considerable context to future run-off monitoring results. Another notable

Fig. 5. Probability of ecological effect classes as predicted by PERPEST on eight functional and structural aquatic community endpoints at Haughton River (H1) under low flow conditions. The numbers of cases (n) in the PERPEST ecotoxicological database used to make predictions of concentration effects on each endpoint are indicated. No relevant cases were available in the modeled concentration ranges for fish and tadpoles, and effects were not evaluated in this study.

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limitation of this study is the lack of information on herbicide losses to deep drainage. Pesticide contamination of groundwaters under agricultural areas is a common occurrence at a global scale (Graymore et al., 2001; Cerejeira et al., 2003). This issue has received some attention in the lower Burdekin, with Keating et al. (1996) detecting atrazine and its degradation product desethylatrazine (DEA) in 33% of sampled bores across the lower Burdekin region. Most DEA to atrazine ratio values (DAR) identified in this study were low (80% of samples had DAR <1.0 and 65% were <0.5), consistent with rapid leaching to the water table (Adams and Thurman, 1991), and the probable occurrence of preferential flow processes through macropores or cracks. Similarly, Klok and Ham (2004) identified the potential for soluble herbicides (atrazine, diuron, 2,4-D) to leach past crop root zones. 4.2. Sub-catchment and catchment monitoring data Comparison of maximum herbicide concentrations detected in paddock-scale run-off with those observed in nearby receiving stream systems highlighted significant concentration decreases. Given the relative solubility and low soil-water partitioning coefficients (KOC ) of many of the monitored herbicides such as atrazine, ametryn, hexazinone and 2,4-D (Table 1), concentration decreases due to sediment trapping in transit would appear unlikely. Substantial sediment trapping of herbicides with moderate sorption (i.e. diuron) is, however, more feasible. Silburn et al. (2011) identified approximately half of the diuron leaving irrigated cotton furrows was in colloidal form. Moreover, recent stream monitoring of filtered versus unfiltered herbicide proportions in lower Burdekin waterways suggests herbicides such as atrazine, ametryn and hexazinone are transported almost exclusively in the dissolved phase (Davis et al., 2011). Diuron, in contrast, exhibited a higher sorbed proportion in transit and a much higher propensity for sediment partitioning (Davis et al., 2011). It is likely significant dilution of paddock tailwater occurs with water from other irrigated paddocks and possibly groundwater ingress, even over relatively short distances. With increasing catchment area, the drainage systems would be receiving irrigation waters from additional paddocks at different stages of the cropping cycle and irrigation timing since herbicide application. Major floodplain sub-catchment drainages such as Barratta Creek receive relatively high amounts of irrigation tailwater input during the dry season when there is little dilution from other sources such as rainfall. The soils of the Barratta Creek catchment are predominantly sodic with very low permeability (Nelson, 2001), so tailwater run-off is quite substantial on many farms in this area (Dight, 2009a; Thorburn et al., 2011). As a result, the dry-season flow regime of the middle and lower reaches of the Barratta Creek drainage complex, a previously intermittent system, is now dominated by local irrigation tailwater inputs (Dight, 2009b). This irrigation tailwater-dominated flow produces consistently elevated herbicide concentrations throughout the duration of the dry season (Fig. 3). While the same suite of herbicides was also consistently detected in several other lower Burdekin subcatchments (Plantation, Sheep Station and Iyah Creeks) during dry-season flows, concentrations in these systems were generally much lower, and below the relevant ANZECC and ARMCANZ (2000) guidelines. The sub-soils in these catchments are generally more permeable sands, with deep drainage a substantial pathway for loss of irrigation water in many farms in this area (Nelson, 2001; Charlesworth et al., 2002; Stewart et al., 2006; Dight, 2009a; Thorburn et al., 2011). The utility of these creek systems as irrigation water supply conduits entails significant water off-take from the Burdekin River. Continual input of supplemental water into these systems could exert a considerable dilution effect on herbicide concentrations during the dry season.

The wet season catchment monitoring (Fig. 3) highlighted that major rainfall events produce widespread surface water run-off across all sub-catchments, and effectively homogenize surface runoff water quality across the floodplain. The influx of large volumes of rainfall into systems such as Barratta Creek apparently produces a large dissipation and/or dilution effect, diluting the relatively elevated herbicide concentrations evident under dry season conditions (see Cook et al., 2011). Wet season catchment monitoring data from across the lower Burdekin floodplain suggest that concentrations of some herbicides (diuron and atrazine) have the potential to exceed GBRMPA (2009) guidelines, particularly in immediate downstream estuarine and near-coastal waters. Moreover, diuron concentrations are likely to exceed known photosystem inhibition effect concentrations for species of seagrass (0.1 ␮g L−1 : Haynes et al., 2000) and microalgae (0.1 ␮g L−1 : Magnusson et al., 2010) that inhabit estuarine and coastal areas. Additional monitoring would be required to determine the full extent of risk from herbicides delivered from the lower Burdekin to the adjacent marine environment. 4.3. Ecotoxicological risk assessment Contemporary ecotoxicology is increasingly grappling with complex, real-world scenarios emerging from water quality monitoring programs, and the associated limitations with traditional single parameter or species specific approaches to gauging ecosystem risk (Eggen et al., 2004; Rohr et al., 2006). Water quality guidelines are often entirely lacking for several of the more commonly detected herbicides found in Great Barrier Reef freshwater ecosystems (Davis et al., 2008). Available guidelines are often of ‘low reliability’ (see ANZECC and ARMCANZ, 2000), and there is minimal capacity to gauge ecological risk from multiple interacting contaminants. The capacity provided by PERPEST for modeling interactive effects between pesticides, and incorporating exposure scenarios adds considerable context and predictive capacity to interpretation of catchment monitoring results (c.f. Davis et al., 2008). The significant effects from herbicide exposure on primary producers (phytoplankton, periphyton) predicted in this study were not unexpected. A similar array of keystone community components in Great Barrier Reef marine and estuarine environments, including algal endosymbionts in corals and benthic microalgae, have been identified as being at particular risk from exposure to the same suite of photosystem inhibiting herbicides (Jones, 2005; Cantin et al., 2007; Magnusson et al., 2010). An interesting outcome of PERPEST scenario modeling in this case were the probabilities of significant effects on aquatic faunal components such as macroinvertebrates and zooplankton (Figs. 4 and 5). While herbicide effects on marine ecosystems have attracted the majority of research attention, freshwater ecosystems, often with their own significant ecological value, face perhaps the greatest risks of herbicide exposure of any Great Barrier Reef catchment area receiving environment. A notable source of uncertainty associated with application of the PERPEST model that deserves recognition in this study is that the ecotoxicology database used to derive ecological risk models is based largely on temperate datasets (i.e. European and North-American studies; Van den Brink et al., 2002). The direct transferability of temperate pesticide chemical properties and toxicity to a dry-tropical climatic regime and a biota naturally adapted to relative water quality variability is unclear. However, a number of recent studies have demonstrated no discernible differences in systemic effects or pesticide toxicity between temperate and tropical species (Brock et al., 2000; Maltby et al., 2004), although the suite of pesticides studied was limited. The review of Damm and Van den Brink (2010) also highlighted no consistent differences between temperate and tropical systems, although differences

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in pesticide toxicity between different bioclimatic regimes were recognised as complex and difficult to predict. Validation or refinement of preliminary ecological assessment using more locally relevant bioassays is required to more reliably quantify ecosystem risk, although PERPEST modeling provides a more targeted and rapid identification of appropriate study subjects. Similarly, recent research (Schäfer et al., 2011) has highlighted that robust quantification of stream ecosystem exposure to pesticides benefits from a combination of sampling approaches (grab samples, sediment samples, passive samplers), rather than traditional reliance (as in this study) on single monitoring techniques. Another limitation of this study is that modeling addressed only the predicted effects of active ingredients on receiving ecosystems. The added toxicity of associated compounds in many commercial herbicide formulations, above the effects of the active ingredients themselves, are increasingly being appreciated (see Howe et al., 2004; Trumbo, 2005). Similarly, the common detection of intermediate pesticide degradates in this study (see Fig. 2; Table C.1), breakdown products that are in some cases more toxic or persistent in the environment (Graymore et al., 2001; Tixier et al., 2000; Giacomazzi and Cochet, 2004), suggests ecosystem impacts may be underestimated. 4.4. Management practices with potential herbicide water quality benefits Results from this study highlight a seasonal dichotomy in off-site herbicide movement for canefarmers; irrigation-driven runoff during the dry-season (April–November); and rainfalldriven runoff during the wet-season (December–March). The downstream receiving environment and ecological risk also vary between these periods, with dry season irrigation tailwater losses primarily affecting freshwater wetland environments, whereas wet season floods deliver herbicide loads from paddocks to downstream marine environments. Given the general scarcity of paddock scale data on herbicide loss from irrigated sugarcane farms, information relating to improved management practices specific to these production systems is, not surprisingly, in a state of relative infancy. However, many of the improved practices identified for other farming systems are clearly applicable to irrigated sugarcane production and farmers are accordingly able to employ a wide range of management practices to minimise pesticide loss from their field and farm. During the dry season, farmers are able to exert considerably more control over both inputs (irrigation amounts, products, product placement and rates) and particularly the destination of outputs from paddocks (tailwater run-off). Maximising irrigation efficiency to reduce irrigation tailwater losses is an important means of reducing herbicide losses, and there were clear opportunities for improving irrigation efficiency at the time of this study (Raine and Bakker, 1996; Klok et al., 2003). As well, canefarmers are able to capture irrigation run-off in on-farm dams (tailwater recycling pits) to be reused on farm at a later date. Indeed, the irrigation water provided by recycling pits is widely used to supplement supplies in the Burdekin River Irrigation Area (Petheram et al., 2008; Thorburn et al., 2011). Given the intensity of monsoonal wet-season rainfall events in the lower Burdekin region, where several hundred millimetres of rainfall can occur in 24 h, however, few recycle pits have the capacity to capture major wet season rainfall events. The use of enzymes in tailwater recycle pits to consume herbicides before they enter streams is another potential management option for farmers to address herbicide losses in irrigation tailwater (Scott et al., 2010). There are other practices that can reduce pesticide losses. Banded application of chemicals such as atrazine has been shown to reduce herbicide losses in run-off, compared to standard broadcast application, in a number of farming production systems, including

11

sugarcane (Selim et al., 2000; Oliver and Kookana, 2006b; Masters et al., 2011; Silburn et al., 2011; Thorburn and Wilkinson, 2011). Not only can band spraying herbicides to target areas reduce the total amount of active ingredient applied (35–60% depending on row spacing and configuration), it facilitates placement of chemicals in areas onto the top of the sugarcane bed out of direct contact with the irrigation water. Thus, banded application may offer particular environmental benefit in the furrow irrigated systems of the lower Burdekin floodplain, where major losses of herbicides occur in early irrigation events during low rainfall periods (June–November). Shielded sprayers, which are slowly increasing in popularity, make this management technique more practical. These management options (recycle pits, banding) are most applicable to improve dryseason water quality in local receiving environments, particularly high value freshwater and brackish wetlands at the coastal interface. A different, and more limited suite of management options will be needed for weed control in late harvest crops, where herbicides are likely to be applied closer to the wet season (October to December) and climatic constraints limit farmers’ options to reduce risks. Banded application may again have considerable water quality benefit, due to the reduced amount of product applied. Selection of products will also be more important. Products with features such as high soil sorption, low residual capacity or low non-target toxicity will confer additional water quality benefits during these periods (see Wauchope et al., 2001; Shipitalo et al., 2008). As well, management of weeds during fallows to reduce the seed bank and, therefore, weed pressure on the following sugarcane crops will be important. 5. Conclusions Results of this study showed that there can be substantial off-site herbicide movement from fully irrigated sugarcane farms. A strong seasonal signal emerged from paddock-scale monitoring results with off-site chemical movement (both mass and concentration) in surface run-off following a similar pattern across farms in the region for commonly applied herbicides such as diuron, atrazine and ametryn. Greatest losses invariably occurred in the first irrigation run-off events following herbicide application, with losses in subsequent irrigation and rainfall events diminishing rapidly. These seasonal differences in loss dynamics from paddocks were reflected in strong seasonal differences in herbicide concentrations in receiving creeks and waterways across the lower Burdekin floodplain. The highest in-stream herbicide concentrations were typically detected under dry-season conditions (when crops are being irrigated) in the Barratta Creek system which receives large volumes of tailwater from farms during this period. Wet season rainfall events had the effect of homogenizing water quality across floodplain waterways, with similar herbicide concentrations detected in all catchments with upstream intensive agricultural land use. While the concentrations found in receiving creek systems were considerably lower than direct paddock run-off, they often exceeded ecological guidelines and results of pesticide risk modeling suggested concentrations, particularly under dry season conditions, posed considerable ecological risk to aquatic ecosystems. Results of this study highlight freshwater ecosystems (often with their own high ecological values) in close proximity to agricultural land as facing some of the greatest herbicide-associated risks of any Great Barrier Reef receiving environment. Acknowledgements We would like to particularly acknowledge the invaluable assistance and cooperation of contributing canefarmers to this

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research. Joseph Kemei (CSIRO) is thanked for his assistance in data collection. The Australian Government and sugar industry through the Sugar Industry Research and Development Corporation provided considerable funding for some of the paddock-scale aspects of this work. North Queensland Dry Tropics provided the funding for sub-catchment and catchment monitoring, as well as aspects of paddock-scale research under programs such as the Australian Government’s Coastal Catchments Initiative (Water Quality Improvement Plan) and Caring for our Country Reef Rescue program as well as the Queensland Government Department of Employment, Economic Development and Innovation’s Demonstration Farms project. Data for the upper Barratta Creek site for 2009/10 were supplied from the Queensland State Government’s Great Barrier Reef Loads Monitoring program. This research was also supported by the Marine and Tropical Sciences Research Facility, implemented in North Queensland by the Reef and Rainforest Research Centre Ltd. Mark Silburn (DERM) is thanked for comments on an earlier draft manuscript. Two anonymous reviewers are also thanked for comments that greatly improved an earlier version of the manuscript.

Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.agee.2011.06.019.

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Please cite this article in press as: Davis, A.M., et al., Environmental impacts of irrigated sugarcane production: Herbicide run-off dynamics from farms and associated drainage systems. Agric. Ecosyst. Environ. (2011), doi:10.1016/j.agee.2011.06.019