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Summary: We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO x ) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO x Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated. [Copyright &y& Elsevier]

Summary: This paper presents a tool for documenting and monitoring water use benefits in the Great Barrier Reef catchments that allows temporal and spatial comparison along the region. Water, water use benefits and water allocations are currently receiving much attention from Australian policy makers and conservation practitioners. Because of the inherent complexity and variability in water quality, it is essential that scientific information is presented in a meaningful way to policy makers, managers and ultimately, to the general public who have to live with the consequences of the decisions. We developed an inexpensively populated and easily understandable water use benefit index as a tool for community-based monitoring of water related trends in the Great Barrier Reef region. The index is developed based on a comparative list of selected water-related indices integrating attributes across physico-chemical, economic, social, and ecological domains currently used in the assessment of water quality, water quantity and water use benefits in Australia. Our findings indicate that the proposed index allows the identification of water performance indicators by temporal and spatial comparisons. Benefits for decision makers and conservation practitioners include a flexible way of prioritization towards the domain with highest concern. The broader community benefits from a comprehensive and user-friendly tool, communicating changes in water quality trends more effectively. [ABSTRACT FROM AUTHOR]

Summary: In many agricultural regions investments are made into improved land management and catchment restoration with the aim of reducing sediment and nutrient delivery to downstream water bodies. This paper presents the results of an 8year field study that evaluated the impact of improved grazing land management (GLM) on a 14km2 sub-catchment of the Burdekin River in northern Australia. Land condition recovery and changes to runoff and sediment yield were measured on hillslopes (using three flumes) and at the end of the catchment (using automatic water sampling). Ground cover was monitored at the beginning of the wet season at hillslope and catchment scales using direct measurement and Quickbird satellite imagery. At the catchment scale, improved GLM resulted in an increase in mean ground cover between 2003 and 2007, relative to a control grazing property. However, the total suspended sediment yield from hillslopes did not decline due to the disproportionately high yields from low (<10%) cover sites particularly in high runoff years. In 2007, when there was above-average rainfall, 97% of the hillslope derived fine sediment was coming from less than 3% of the catchment. Catchment sediment yield also increased, associated with higher rainfall and runoff in latter years of the study. In years of above-average rainfall, it is estimated that less than 40% of catchment sediment yield was derived from hillslope erosion. Channel erosion is considered to contribute the remaining sediment. Rehabilitation of hillslope scalds and gullies is likely to be an important companion to improved GLM to reduce catchment fine sediment yields in this landscape. Evaluation of gully and hillslope scald rehabilitation techniques is required, including the economic feasibility of such options. [Copyright &y& Elsevier]

Summary: Poor land condition resulting from unsustainable grazing practices can reduce enterprise profitability and increase water, sediment and associated nutrient runoff from properties and catchments. This paper presents the results of a 6year field study that used a series of hillslope flume experiments to evaluate the impact of improved grazing land management (GLM) on hillslope runoff and sediment yields. The study was carried out on a commercial grazing property in a catchment draining to the Burdekin River in northern Australia. During this study average ground cover on hillslopes increased from ∼35% to ∼75%, although average biomass and litter levels are still relatively low for this landscape type (∼60 increasing to 1100kg of dry matter per hectare). Pasture recovery was greatest on the upper and middle parts of hillslopes. Areas that did not respond to the improved grazing management had <10% cover and were on the lower slopes associated with the location of sodic soil and the initiation of gullies. Comparison of ground cover changes and soil conditions with adjacent properties suggest that grazing management, and not just improved rainfall conditions, were responsible for the improvements in ground cover in this study. The ground cover improvements resulted in progressively lower runoff coefficients for the first event in each wet season, however, runoff coefficients were not reduced at the annual time scale. The hillslope annual sediment yields declined by ∼70% on two out of three hillslopes, although where bare patches (with <10% cover) were connected to gullies and streams, annual sediment yields increased in response to higher rainfall in latter years of the study. It appears that bare patches are the primary source areas for both runoff and erosion on these hillslopes. Achieving further reductions in runoff and erosion in these landscapes may require management practices that improve ground cover and biomass in bare areas, particularly when they are located adjacent to concentrated drainage lines. [Copyright &y& Elsevier]