974 resultados para Soil erosion -- Queensland, Central
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"IEPA/WPC/83-004."
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Includes index.
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Riley J. Wilson, chairman.
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Numerous studies in the last 60 years have investigated the relationship between land slope and soil erosion rates. However, relatively few of these have investigated slope gradient responses: ( a) for steep slopes, (b) for specific erosion processes, and ( c) as a function of soil properties. Simulated rainfall was applied in the laboratory on 16 soils and 16 overburdens at 100 mm/h to 3 replicates of unconsolidated flume plots 3 m long by 0.8 m wide and 0.15 m deep at slopes of 20, 5, 10, 15, and 30% slope in that order. Sediment delivery at each slope was measured to determine the relationship between slope steepness and erosion rate. Data from this study were evaluated alongside data and existing slope adjustment functions from more than 55 other studies from the literature. Data and the literature strongly support a logistic slope adjustment function of the form S = A + B/[1 + exp (C - D sin theta)] where S is the slope adjustment factor and A, B, C, and D are coefficients that depend on the dominant detachment and transport processes. Average coefficient values when interill-only processes are active are A - 1.50, B 6.51, C 0.94, and D 5.30 (r(2) = 0.99). When rill erosion is also potentially active, the average slope response is greater and coefficient values are A - 1.12, B 16.05, C 2.61, and D 8.32 (r(2) = 0.93). The interill-only function predicts increases in sediment delivery rates from 5 to 30% slope that are approximately double the predictions based on existing published interill functions. The rill + interill function is similar to a previously reported value. The above relationships represent a mean slope response for all soils, yet the response of individual soils varied substantially from a 2.5-fold to a 50-fold increase over the range of slopes studied. The magnitude of the slope response was found to be inversely related ( log - log linear) to the dispersed silt and clay content of the soil, and 3 slope adjustment equations are proposed that provide a better estimate of slope response when this soil property is known. Evaluation of the slope adjustment equations proposed in this paper using independent datasets showed that the new equations can improve soil erosion predictions.
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Date of Acceptance: 05/06/2015 This research was made possible through funding provided by the Leverhulme Trust, the Spanish Ministry of Science and Innovation (Project CGL2010–20672) and Xunta de Galicia (grants R2014/001 and GPC2014/009). N Silva-Sánchez is currently supported by a FPU pre-doctoral grant (AP2010–3264) funded by the Spanish Government. Kirsty Golding, Andy McMullen, and Ian Simpson are thanked for their assistance with fieldwork. Alison Sandison produced the maps. Pete Langdon and two anonymous referees are thanked for comments that helped to improve the paper.
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Date of Acceptance: 05/06/2015 This research was made possible through funding provided by the Leverhulme Trust, the Spanish Ministry of Science and Innovation (Project CGL2010–20672) and Xunta de Galicia (grants R2014/001 and GPC2014/009). N Silva-Sánchez is currently supported by a FPU pre-doctoral grant (AP2010–3264) funded by the Spanish Government. Kirsty Golding, Andy McMullen, and Ian Simpson are thanked for their assistance with fieldwork. Alison Sandison produced the maps. Pete Langdon and two anonymous referees are thanked for comments that helped to improve the paper.
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Date of Acceptance: 05/06/2015 This research was made possible through funding provided by the Leverhulme Trust, the Spanish Ministry of Science and Innovation (Project CGL2010–20672) and Xunta de Galicia (grants R2014/001 and GPC2014/009). N Silva-Sánchez is currently supported by a FPU pre-doctoral grant (AP2010–3264) funded by the Spanish Government. Kirsty Golding, Andy McMullen, and Ian Simpson are thanked for their assistance with fieldwork. Alison Sandison produced the maps. Pete Langdon and two anonymous referees are thanked for comments that helped to improve the paper.
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Concerns of reduced productivity and land degradation in the Mitchell grasslands of central western Queensland were addressed through a range monitoring program to interpret condition and trend. Botanical and eclaphic parameters were recorded along piosphere and grazing gradients, and across fenceline impact areas, to maximise changes resulting from grazing. The Degradation Gradient Method was used in conjunction with State and Transition Models to develop models of rangeland dynamics and condition. States were found to be ordered along a degradation gradient, indicator species developed according to rainfall trends and transitions determined from field data and available literature. Astrebla spp. abundance declined with declining range condition and increasing grazing pressure, while annual grasses and forbs increased in dominance under poor range condition. Soil erosion increased and litter decreased with decreasing range condition. An approach to quantitatively define states within a variable rainfall environment based upon a time-series ordination analysis is described. The derived model could provide the interpretive framework necessary to integrate on-ground monitoring, remote sensing and geographic information systems to trace states and transitions at the paddock scale. However, further work is needed to determine the full catalogue of states and transitions and to refine the model for application at the paddock scale.
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Soil erosion is a major environmental issue in Australia. It reduces land productivity and has off-site effects of decreased water quality. Broad-scale spatially distributed soil erosion estimation is essential for prioritising erosion control programs and as a component of broader assessments of natural resource condition. This paper describes spatial modelling methods and results that predict sheetwash and rill erosion over the Australian continent using the revised universal soil loss equation (RUSLE) and spatial data layers for each of the contributing environmental factors. The RUSLE has been used before in this way but here we advance the quality of estimation. We use time series of remote sensing imagery and daily rainfall to incorporate the effects of seasonally varying cover and rainfall intensity, and use new digital maps of soil and terrain properties. The results are compared with a compilation of Australian erosion plot data, revealing an acceptable consistency between predictions and observations. The modelling results show that: (1) the northern part of Australia has greater erosion potential than the south; (2) erosion potential differs significantly between summer and winter; (3) the average erosion rate is 4.1 t/ha. year over the continent and about 2.9 x 10(9) tonnes of soil is moved annually which represents 3.9% of global soil erosion from 5% of world land area; and (4) the erosion rate has increased from 4 to 33 times on average for agricultural lands compared with most natural vegetated lands.
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Site-specific regression coefficient values are essential for erosion prediction with empirical models. With the objective to investigate the surface-soilconsolidation factor, Cf, linked to the RUSLE's prior-land-use subfactor, PLU, an erosion experiment using simulated rainfall on a 0.075 m m-1 slope, sandy loam Paleudult soil, was conducted at the Agriculture Experimental Station of the Federal University of Rio Grande do Sul (EEA/UFRGS), in Eldorado do Sul, State of Rio Grande do Sul, Brazil. Firstly, a row-cropped area was excluded from cultivation (March 1995), the existing crop residue removed from the field, and the soil kept clean-tilled the rest of the year (to get a degraded soil condition for the intended purpose of this research). The soil was then conventional-tilled for the last time (except for a standard plot which was kept continuously cleantilled for comparison purposes), in January 1996, and the following treatments were established and evaluated for soil reconsolidation and soil erosion until May 1998, on duplicated 3.5 x 11.0 m erosion plots: (a) fresh-tilled soil, continuously in clean-tilled fallow (unit plot); (b) reconsolidating soil without cultivation; and (c) reconsolidating soil with cultivation (a crop sequence of three corn- and two black oats cycles, continuously in no-till, removing the crop residues after each harvest for rainfall application and redistributing them on the site after that). Simulated rainfall was applied with a Swanson's type, rotating-boom rainfall simulator, at 63.5 mm h-1 intensity and 90 min duration, six times during the two-and-half years of experimental period (at the beginning of the study and after each crop harvest, with the soil in the unit plot being retilled before each rainfall test). The soil-surface-consolidation factor, Cf, was calculated by dividing soil loss values from the reconsolidating soil treatments by the average value from the fresh-tilled soil treatment (unit plot). Non-linear regression was used to fit the Cf = e b.t model through the calculated Cf-data, where t is time in days since last tillage. Values for b were -0.0020 for the reconsolidating soil without cultivation and -0.0031 for the one with cultivation, yielding Cf-values equal to 0.16 and 0.06, respectively, after two-and-half years of tillage discontinuation, compared to 1.0 for fresh-tilled soil. These estimated Cf-values correspond, respectively, to soil loss reductions of 84 and 94 %, in relation to soil loss from the fresh-tilled soil, showing that the soil surface reconsolidated intenser with cultivation than without it. Two distinct treatmentinherent soil surface conditions probably influenced the rapid decay-rate of Cf values in this study, but, as a matter of a fact, they were part of the real environmental field conditions. Cf-factor curves presented in this paper are therefore useful for predicting erosion with RUSLE, but their application is restricted to situations where both soil type and particular soil surface condition are similar to the ones investigate in this study.
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Soil erosion is one of the chief causes of agricultural land degradation. Practices of conservation agriculture, such as no-tillage and cover crops, are the key strategies of soil erosion control. In a long-term experiment on a Typic Paleudalf, we evaluated the temporal changes of soil loss and water runoff rates promoted by the transition from conventional to no-tillage systems in the treatments: bare soil (BS); grassland (GL); winter fallow (WF); intercrop maize and velvet bean (M+VB); intercrop maize and jack bean (M+JB); forage radish as winter cover crop (FR); and winter cover crop consortium ryegrass - common vetch (RG+CV). Intensive soil tillage induced higher soil losses and water runoff rates; these effects persisted for up to three years after the adoption of no-tillage. The planting of cover crops resulted in a faster decrease of soil and water loss rates in the first years after conversion from conventional to no-tillage than to winter fallow. The association of no-tillage with cover crops promoted progressive soil stabilization; after three years, soil losses were similar and water runoff was lower than from grassland soil. In the treatments of cropping systems with cover crops, soil losses were reduced by 99.7 and 66.7 %, compared to bare soil and winter fallow, while the water losses were reduced by 96.8 and 71.8 % in relation to the same treatments, respectively.