| Project/Area Number |
60560246
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
農業土木
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| Research Institution | Tottori University |
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Principal Investigator |
YANO Tomohisa Faculty of Agriculture, Tottori University・Associate, 農学部, 助教授 (80032085)
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| Co-Investigator(Kenkyū-buntansha) |
INOUE Mitsuhiro Faculty of Agriculture, Tottori University・Research Associate, 農学部, 助手 (90032309)
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| Project Period (FY) |
1985 – 1986
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| Project Status |
Completed (Fiscal Year 1986)
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| Budget Amount *help |
¥1,600,000 (Direct Cost: ¥1,600,000)
Fiscal Year 1986: ¥400,000 (Direct Cost: ¥400,000)
Fiscal Year 1985: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | Spatial variability / Scaling / Kriging / Matric suction / Unsaturated hydraulic conductivity / Soil water diffusivity / Soil salinity / 等値線図 |
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| Research Abstract |
A technique for determining the scaling coefficients for matric suction, unsaturated hydraulic conductivity and soil water diffusivity was established by minimizing a sum of squares between the measured values and the scale reduced values. Two methods were used in determining the scaling coefficients; the estimates from an experimental equation as the function of the effective saturation and the average of the measured values were used as the scale reduced values. Scaling effect was noticeable for any case and the similar values of scaling coefficients were obtained for the two methods. The sum of squares was smaller in the case that the experimental equation was not used than that the equation was used. It was concluded that the former was very useful because scaling is easily done-for the different properties only by changing the value of coefficients in the reduced variables.
The kriging technique was established in order to estimate the unknown values from the limited number of measured values. The procedure includes the following three steps. First, a semi-variogram is determined as the linear equation of the lag distance. Next, the optimum neighborhood size is determined by minimizing the estimate error. Finally, the value at the arbitrary point is estimated from the measured values within the optimum neighborhood size. The contour maps were made for particle size fraction, ion concentration in the soil solution, soil salinity and solution pH in dune sand and reclaimed land from sea. The contour maps drawn by kriging estimates were far clearer than those drawn only by the measured values. The values of one properry could be estimated from those of another property by using the linear predictive equation between two properties with the similar distribution.
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