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Assessment of spatial variability of soil physical and hydraulic properties in Netravati catchment, Karnataka State, India

机译:印度卡纳塔克邦内特拉瓦蒂集水区土壤物理和水力特性的空间变异性评估

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Site specific management and precision agriculture seeks to identify and analyze variability in soil properties. Runoff prediction and sediment yield estimation using distributed hydrologic modeling requires spatially distributed soil data especially saturated hydraulic conductivity, water content and particle size distribution. Therefore, soil data becomes one of the major inputs in any watershed management studies. The present study was conducted to analyse spatial variability in soil physical and hydraulic properties in Netravati river basin, Karnataka State, India. The spatial interpolation of soil properties was carried out by using three methods such as Ordinary Kriging (OK), Inverse Distance Weighting (IDW) and Radial Basis Function (RBF). Results indicate that soil properties such as %sand, %silt and %clay are highly variable in nature with standard deviation value of 16.08, 13.27 and 8.82. The OK method is efficient in predicting sand, silt, clay and saturated hydraulic conducted. IDW and RBF methods predicted organic matter content and bulk density with acceptable error of 1.084%, 1.09% and 0.05gm/cc, 0.04gm/cc respectively.
机译:特定地点的管理和精确农业寻求识别和分析土壤特性的变异性。使用分布式水文模型的径流预测和沉积物产量估算需要空间分布的土壤数据,尤其是饱和导水率,水含量和粒径分布。因此,土壤数据成为任何流域管理研究的主要输入之一。本研究旨在分析印度卡纳塔克邦内特拉瓦蒂河流域土壤物理和水力特性的空间变异性。土壤特性的空间插值是通过三种方法进行的,例如普通克里格法(OK),反距离权重(IDW)和径向基函数(RBF)。结果表明,土壤性质(例如沙,泥沙和粘土)性质上具有很大的差异,标准偏差值为16.08、13.27和8.82。 OK方法可有效预测沙子,淤泥,粘土和饱和水力传导。 IDW和RBF方法预测的有机物含量和堆积密度的可接受误差分别为1.084%,1.09%和0.05gm / cc,0.04gm / cc。

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