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Spatial variability of soil properties and its application in predicting surface map of hydraulic parameters in an agricultural farm

机译:土壤特性的空间变异性及其在预测农田水力参数表中的应用

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Knowledge of spatial variation of soil properties is important in precision farming and environmental modelling. Spatial distribution of water content at field capacity (FC) and permanent wilting point (PWP) at different zones of a farm governs theavailable water for plant growth. These two soil hydraulic parameters play key roles in crop selection for different blocks of a farm, and in scheduling irrigation of crops in a field. In this study, spatial variation of bulk density organic carbon, siltand clay contents for two soil depths (0-15 and 15-30 cm) in the agricultural farm of the Indian Agricultural Research Institute, New Delhi were quantified and the respective surface maps were prepared through ordinary kriging. Particle size distribution shows better spatial correlation structure than bulk density and organic carbon content. Gaussian model fits well with experimental semivariogram of bulk density, and silt and clay contents. Hole-effect model was found to be the best to fit the experimental semivariogram of organic carbon content. Spatial correlation structure for both surface (0-15 cm) and subsurface (15-30 cm) soil layer remains the same, but the magnitude of spatial correlation differs. Cross-validation of the kriged map shows thatspatial prediction of basic soil properties using semivariogram parameters is better than assuming mean of observed value for any unsampled location. Pedo-transfer functions were coupled with the surface map of basic soil properties to generate a map ofwater content at FC and PWP. Evaluation of spatial maps of. FC and. PWP showed reasonable accuracy of these two hydraulic parameters for farm-level or regional-scale application.
机译:了解土壤特性的空间变化对于精确耕作和环境建模非常重要。农场不同区域的田间持水量(FC)和永久枯萎点(PWP)的水分空间分布决定着植物生长的可用水量。这两个土壤水力参数在农场不同区域的作物选择以及田间作物灌溉计划中起着关键作用。在这项研究中,量化了新德里印度农业研究所的两个农田(0-15和15-30 cm)的土壤堆积密度,有机碳,粉砂和粘土含量的空间变化,并绘制了各自的表面图。通过普通克里金法制备。粒度分布显示出比堆积密度和有机碳含量更好的空间相关结构。高斯模型与堆积密度,粉砂和粘土含量的实验半变异图非常吻合。发现空穴效应模型最适合有机碳含量的实验半变异函数。表层(0-15厘米)和地下(15-30厘米)土壤层的空间相关结构保持不变,但空间相关程度不同。克立格地图的交叉验证显示,使用半变异函数参数进行的基本土壤属性的空间预测要好于假设任何未采样位置的观测值的平均值。将Pedo传递函数与基本土壤属性的表面图结合起来,以生成FC和PWP处的水含量图。评价空间图。 FC和。 PWP在农场一级或区域规模的应用中显示了这两个水力参数的合理精度。

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