Environmental impacts of irrigated sugarcane production: Nitrogen lost through runoff and leaching

Terrestrial pollutant runoff to the Great Barrier Reef: An update of issues, priorities and management responses

“…Comparable studies in the Burdekin catchment (Bainbridge et al, 2010;Maher et al, 2008) showed that the bulk of the suspended sediment reaching the mouth of the Burdekin River came from only two out of the five major sub-catchments. Studies in cropping lands have clearly shown that the overwhelming source of DIN discharge is from fertiliser use Waterhouse et al, 2012;Thorburn et al, 2011b;Thorburn and Wilkinson, in press). …”

“…Discharge of nitrogen from natural landscapes is predominantly in the form of DON Harris, 2001), including in runoff from undisturbed forests in the GBR catchment (Brodie and Mitchell, 2006). In contrast, nitrogen discharge from agricultural and urban lands is dominated by DIN derived from fertiliser and sewage wastes Thorburn et al, 2011b), and PN derived from soil erosion . This shift from a predominantly DON discharge to a predominantly PN and DIN discharge may cause noticeable changes in coral and macroalgal communities (Fabricius, 2005).…”

Water quality variation along streams with similar agricultural development but contrasting riparian vegetation

“…Wet Tropics floodplains are intensively farmed, with sugarcane cultivation the major user of nitrogen fertilizers, causing significant impact on stream water quality and nutrient exports (e.g. Pearson et al, 2003;Hunter and Walton, 2008;Mitchell et al, 2009;Thorburn et al, 2011Thorburn et al, , 2013. In the Mulgrave catchment, riparian forest, including vegetation along farm drains, has largely been retained and improved through replanting schemes (Werren, 1998;Mackay et al, 2010) so that these streams currently represent what may be achievable in other parts of the region with appropriate riparian rehabilitation and management.…”

The error in agricultural systems model prediction depends on the variable being predicted

“…Model evaluations dominantly focus on comparing individual predictions to specific measurements (Frolking et al, 1998;Del Grosso et al, 2008;Thorburn et al, 2011;R€ otter et al, 2012;Asseng et al, 2013). However, theory shows that squared error of an average will always be as small as or smaller than average squared error.…”