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Abstract: Knowledge of erosion rates and sediment yields from gullies is critical for the effective prioritisation of management efforts aimed at reducing the impact of gully-derived sediments on water quality. This paper describes a rapid assessment method for estimating sidewall gully erosion rates for already established gully networks. It combines a conceptual-empirical model of the cycle of gully initiation and stabilisation with an easy-to-apply technique for assessing gully extent and dimensions. The method is illustrated using a case study of the Avon-Richardson Catchment of north-central Victoria, Australia. It is estimated that a total of 4.6×106 tonnes of sediment have been generated in that catchment from gully erosion since the latest major phase of gullying in the mid 1800s. This is equivalent to 8.9tha−1 y−1 if sediment generation was evenly distributed spatially and temporally across the 3300km2 catchment over 160years prior to 2010. Current rates of gully erosion are estimated to be 4700ty−1 (equivalent to 1.4tha−1 y−1). The results are comparable with observed rates of sidewall erosion in the Avon-Richardson Catchment. Further testing is required to build confidence in its applicability to assess sediment yields and for assisting regional authorities to plan remediation efforts. [Copyright &y& Elsevier]

Assessment of nitrogen (N) loss forms and pathways from farming systems is important for improved understanding of potential off-farm impacts on high value environmental assets. The objective of this study was to estimate N losses in different pathways in dairy systems across the range of climate, soil and farm management by using west Gippsland (Victoria, Australia) as case study area, and to characterise the sensitivity of the adopted model parameters. We combined the point scale models DairyMod and Howleaky to estimate dissolved N (DN) and particulate N (PN) loads in runoff, and N leaching (LN) in deep drainage from representative dairy farms in west Gippsland. Monte Carlo error propagation with Latin hypercube sampling was performed to identify sensitive model parameters and assess potential uncertainty in N load predictions. The combined model was capable of simulating climate-soil-animal-pasture management interactions and estimating DN, PN and LN at an annual scale; which were estimated at up to 18 kg-N ha −1 , 15 kg-N ha −1 and 312 kg-N ha −1 , respectively. The combined model demonstrated that more intensive feeding as mixed ration, and nutrient budgeting that takes into account the fertiliser equivalent of recycled nutrients can achieve an increase in milk production by up to 13% and a decrease in N loads by up to 31% compared to the intensive system in the case study catchment. Soil type and farm management explained much of the variability (up to 76%) observed in LN and DN loads, whereas climate and soil type had significant influence on PN loads (62–77%). Year-to-year variation, particularly under dry conditions had a marked influence on N loads. Soil N, vegetation cover, rooting depth and soil maximum drainage rate must be well characterised in order to reduce potentially high uncertainty in the estimation of N losses in heterogeneous catchments. [ABSTRACT FROM AUTHOR]