968 resultados para Soil erosion.


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Mode of access: Internet.

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"Motion pictures" : p. 101-104.

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"A compilation of practical tried-and-proved methods which have been developed by state agricultural colleges and extension workers, U.S. soil conservation experts, and county agricultural agents."--p. [2] of cover.

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Includes index.

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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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Efficient planning of soil conservation measures requires, first, to understand the impact of soil erosion on soil fertility with regard to local land cover classes; and second, to identify hot spots of soil erosion and bright spots of soil conservation in a spatially explicit manner. Soil organic carbon (SOC) is an important indicator of soil fertility. The aim of this study was to conduct a spatial assessment of erosion and its impact on SOC for specific land cover classes. Input data consisted of extensive ground truth, a digital elevation model and Landsat 7 imagery from two different seasons. Soil spectral reflectance readings were taken from soil samples in the laboratory and calibrated with results of SOC chemical analysis using regression tree modelling. The resulting model statistics for soil degradation assessments are promising (R2=0.71, RMSEV=0.32). Since the area includes rugged terrain and small agricultural plots, the decision tree models allowed mapping of land cover classes, soil erosion incidence and SOC content classes at an acceptable level of accuracy for preliminary studies. The various datasets were linked in the hot-bright spot matrix, which was developed to combine soil erosion incidence information and SOC content levels (for uniform land cover classes) in a scatter plot. The quarters of the plot show different stages of degradation, from well conserved land to hot spots of soil degradation. The approach helps to gain a better understanding of the impact of soil erosion on soil fertility and to identify hot and bright spots in a spatially explicit manner. The results show distinctly lower SOC content levels on large parts of the test areas, where annual crop cultivation was dominant in the 1990s and where cultivation has now been abandoned. On the other hand, there are strong indications that afforestations and fruit orchards established in the 1980s have been successful in conserving soil resources.