Lewis, S.E., Smith, R., Brodie, J.E., Bainbridge, Z.T., Davis, A.M., and Turner, R. (2011) Using monitoring data to model herbicides exported to the Great Barrier Reef, Australia. In: Proceedings of 19th International Congress on Modelling and Simulation. pp. 2051-2056. From: MODSIM 2011 19th International Congress on Modelling and Simulation, 12–16 December 2011, Perth, WA, Australia.

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Abstract

The run-off of agricultural herbicides which inhibit photosystem II (PSII) in plants, have been identified as key pollutants of concern by the Great Barrier Reef Water Quality Protection Plan 2009 ('Reef Plan'). As such, a target has been set for 2013 to reduce the annual load of PSII herbicides exported to the Great Barrier Reef (GBR) by 50%. Historically, monitoring of PSII herbicide loads entering the GBR has been spatially and temporally limited. More recently, monitoring has been extended both on a spatial and temporal scale; however, not all catchments that export to the GBR are monitored. Hence, an adequate data set required to calculate the PSII herbicide loads to assess the progress towards Reef Plan’s target does not currently exist and therefore a modeling approach was developed. The approach utilised existing monitoring data to calculate herbicide run-off coefficients (g.ha-1) for key agricultural land uses of the whole GBR catchment area (i.e. sugarcane, grazing, dry land cereal crops and horticulture). Run-off coefficients were calculated for the six most commonly detected PSII herbicides in GBR catchments; diuron, used for sugarcane and dry land cereal crops; atrazine, used for sugarcane, dry land cereal crops and horticulture; hexazinone, used for sugarcane and horticulture; ametryn, used for sugarcane; simazine, used for dry land cereal crops; and tebuthiuron, used for grazing. We calculated an ‘average’ annual load for each of the monitored catchments from available monitoring data of either ‘event’ or annual loads (which commonly was available over a few years and captured considerable inter-annual discharge variability) coupled with the mean discharge of each catchment that was specified in the latest online discharge data. Each river was categorised by the predominant land use in its catchment. To calculate an annual run-off coefficient an assumption was made that the entire herbicide load was sourced from the predominant land use. A regionally specific runoff coefficient for each of the key land uses in the GBR was then calculated from the average of the catchment coefficients. Coefficients were then applied using the QLUMP 1999 land use data for each basin of the GBR catchment area to estimate a mean annual load. The modeled load calculations were validated with monitoring data from a combination of passive and grab sampling. Standard deviation of these runoff coefficients were used to estimate the uncertainties of these total PS-II herbicide loads exported from each GBR basin.

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