2 resultados para basin soil

em University of Queensland eSpace - Australia


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Two east - west transects were established in southern Queensland to quantify rainfall inputs of chloride and associated ions. Electrical conductivity, pH, and major and minor ions were measured at 9 sites within the Queensland Murray - Darling Basin and 1 site to the east. Variability at some sites was high, possibly a function of the sample collection method. Ionic concentrations decreased with distance inland, a trend similar to that observed elsewhere in Australia, although values closer to the coast were higher than observed in southern and western Australia. Equations to predict both annual average rainfall chloride mass deposition and total salt deposition were derived.

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This paper presents a scientific and technical description of the modelling framework and the main results of modelling the long-term average sediment delivery at hillslope to medium-scale catchments over the entire Murray Darling Basin (MDB). A theoretical development that relates long-term averaged sediment delivery to the statistics of rainfall and catchment parameters is presented. The derived flood frequency approach was adapted to investigate the problem of regionalization of the sediment delivery ratio (SDR) across the Basin. SDR, a measure of catchment response to the upland erosion rate, was modeled by two lumped linear stores arranged in series: hillslope transport to the nearest streams and flow routing in the channel network. The theory shows that the ratio of catchment sediment residence time (SRT) to average effective rainfall duration is the most important control in the sediment delivery processes. In this study, catchment SRTs were estimated using travel time for overland flow multiplied by an enlargement factor which is a function of particle size. Rainfall intensity and effective duration statistics were regionalized by using long-term measurements from 195 pluviograph sites within and around the Basin. Finally, the model was implemented across the MDB by using spatially distributed soil, vegetation, topographical and land use properties under Geographic Information System (GIs) environment. The results predict strong variations in SDR from close to 0 in floodplains to 70% in the eastern uplands of the Basin. (c) 2005 Elsevier Ltd. All rights reserved.