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Study On Spatial Variability And Influencing Factors For Soil Potassium In Yibin

Posted on:2011-03-07Degree:MasterType:Thesis
Country:ChinaCandidate:W Z HuangFull Text:PDF
GTID:2143360308972155Subject:Physical geography
Abstract/Summary:PDF Full Text Request
Soil is the comprehensive result of natural conditions and artificial activity, therefore it has an heterogeneous body in the spatial scale, and with a high degree of spatial heterogeneity. Spatial heterogeneity of soil properties has been the study focus at home and abroad, but most of them concentrated in the smaller scale, and for large scale, especially in the area were rare. In this paper, Yibin is the research object, by analyzing the spatial variability of soil potassium, studying the impact factors and their mechanism of action, and based on these, by the management measures to try to increase the utilization and optimization of soil potassium and optimize the layout of regional agricultural production, especially the comprehensive, rational management for potassium and protection of ecological environment.Based on the analysis of Yibin in 1982 on the basis of soil survey data, combined with the soil pollution survey of Yibin, collected soil samples for 190 in 2007-2008, and then used radial basis function (RBF) neural network in spatial interpolation, obtained the spatial variability of soil potassium and its influencing factors in the study area. The results are as follows:1 Spatial distribution of soil potassium in the study area(1)STK: the average content of STK in 2008 was between 13.86-23.89 g. kg-1, and most were in the middle section of gradeâ…¢level, and no difference with the level of 1982. Higher values (>21.58 g. kg-1) concentrated in the southern of Yibin County, southwest of the Gao County, southwest of Junlian County, northeast of Nanxi County and north of the Yangtze River in Jiangan County, While the lower areas (<17.51 g. kg-1) has two main zones:southwest of Pingshan County and the junction of southern of Junlian County and Gong County. General distribution trend was decreasing from the northeast and southwest to central, north, south in the study area.(2) SAK: in 2008, the average of the SAK was between 42.45-100.09mg. kg-1, and most were in the middle section of gradeâ…¢level, and basically no difference between the 1982 level, but>150 mg. kg-1 (rich) area reductd. Higher values (>85.00mg. kg-1) is only concentrated in the eastern region of Xingwen County, Lower areas (<50mg. kg-1) there were three main zones:southwest of Pingshan County; the junction of south, central of Gong County, eastern of Junlian County, and western of Xingwen County; northeast of Yibin County, the junction of north and central of Cuiping District, north of Jiangan County. General distribution trends in the study area was decreasing from southeast to south, the north.(3) Soil effective potassium:in study area, the average content of soil effective potassium ranged from 42.61-239.83 mg. kg-1 between. And<120 mg. kg-1 of the soil area accounted for more than 60% of the total area, suggested that the majority of the soil was lack of potassium. Higher values (>180.00 mg. kg-1) was only concentrated in the east, including eastern of Jiangan County, Xingwen County. While the lower zone (<100mg. kg-1) concentrated in the southern, including eastern of Junlian County and Gao County, the western of Changning County and Xingwen County, south of Cuiping District and the whole Gong County. In addition, there were scattered in the southwest of Pingshan County. General distribution trends in the study area was decreasing from west to the east.(4) Soil slow potassium:in study area, the average was 313.20-1260.42 mg. kg-1 between the content of <700 mg. kg-1 of the soil area accounted for 70% of total area, suggested that the most of the supply capacity of soil potassium was low. Higher values (> 900.00 mg. kg-1) is only concentrated in the eastern of Xingwen County and a small place in southeast of Jiangan County, While the lower zone (<500 mg. kg-1) concentrated in the south in study area, including the east of Junlian County, most of the southern of Gong County, southwest of Xingwen County. In addition, there were scattered in the southwest of Pingshan County. General distribution trends in the study area was decreasing from west to east.2 Soil potassium content and spatial variation was affected by soil parent material, soil granule, soil organic matter, soil type, landforms, land use type.(1) Soil parent materialsSTK content was follow: Permian rocks weathering> Triassic limestone,sand,shale weathering> Jurassic sandstone and shale weathering >Quaternary sediments>Cretaceous shale weathering;SAK was followe:Permian rocks weathering>Jurassic sandstone and shale weathering>Triassic limestone,sand,shale weathering >Cretaceous shale weathering>Quaternary sediments; The soil effective potassium in the soil from Jurassic sandstone and shale weathering is the highest, and the follow was Permian rocks weathering, Cretaceous shale weathering, Triassic sandstone and shale, limestone weathering, and the soil developed on Quaternary sediments was the lowest; Soil slow potassium from Jurassic sandstone and shale weathering was the highest, then was Permian rocks weathering, Triassic limestone,sand,shale weathering, Cretaceous shale weathering, Quaternary sediments, And the soil slow potassium from Permian rocks weathering, Triassic limestone,sand,shale weathering, Cretaceous shale weathering did not differ. (2) Soil granuleSoil sand content content was significantly negatively correlated with STK, negatively correlated with SAK,no correlation with soil effective potassium, and significantly negatively correlated with soil slow potassium; soil silt content was significantly positively correlated with STK, positively correlated with SAK, no correlated with soil effective potassium, significantly positively correlated with soil slow potassium; soil clay content was positively correlated with STK,SAK, soil slow potassium, no correlated with soil effective potassium.(3) Soil organic matterSoil organic matter and STK had no significant correlation (n= 190, r= 0.062, r0.05 = 0.138, r Yellow lime soil> Alkaline purple soil> Pool paddy soil> Neutral purple soil> Submerged paddy soil> Acidity purple soil> Yellow;SAK was: Alkaline purple soil>Neutral purple soil> Yellow lime soil>Pool paddy Soil> Yellow soil> Submerged Paddy soil> Yellow> Acidity purple soil; Soil effective potassium was: Alkaline purple soil> Neutral purple soil>Pool paddy Soil> Yellow lime soil> Yellow soil> Submerged paddy soil> Yellow> Acidity purple soil; Soil slow potassium as follows: Alkaline purple soil> Neutral purple soil> Pool paddy soil> Yellow lime soil> Submerged paddy soil> Yellow> Yellow soil> Acidity purple soil. The trend of SAK, soil effective potassium, soil slow potassium was consistency.(5) LandformsSTK was:river terrace> shallow hill area> takaoka area> mountainous; SAK was: river terrace, shallow hill area> takaoka area> mountainous; Soil effective potassium was: shallow hill area> river terrace> takaoka area> mountainous; Soil slow potassium was similar to soil effective potassium as:shallow hill area> river terrace>takaoka area> mountainous. STK at 300-500m was the highest content, followed by> 500m,200-300m; while the soil of the 200-300m range, SAK was the highest, followed by> 500m,300-500m; The trend soil effective potassium was similar to SAK, as were 200-300m,> 500m,300-500m; Soil slow potassium between the 300-500m was the highest, and then 200-300m,> 500m. (6) Land use typeThe average content of STK in forest was higher than paddy field and dry land, for the 20.38 g.kg-1, dry land 20.26 g.kg-1, paddy field 20.14 g.kg-1, SAK in dry land is the highest, followed by paddy field, forest. And soil effective potassium,soil slow potassium and SAK were the same, followed by dry land> paddy field> forest.
Keywords/Search Tags:Soil potassium, Spatial variability, RBF neural network, Yibin
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