利用地统计学方法评价红土土壤性质的空间变异性(西孟加拉邦,印度)

Gouri Sankar Bhunia , Pravat Kumar Shit , Rabindranath Chattopadhyay
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引用次数: 59

摘要

不适当的土地管理做法造成的土壤退化是最佳土地生产力的主要损害。土壤性质的空间变异性是农业生产力、食品安全和环境建模所必需的。本研究以印度西孟加拉邦红土为研究对象,利用地质统计学模型了解土壤性质的空间变异性。测定土壤氮(N)、pH、电导率(EC)、磷(P)、钾(K)和有机碳(OC)。利用Kriging技术,利用半变异函数模型绘制了土壤性质的表面图。土壤有机质与氮含量呈正相关,土壤有机质、钾、pH、氮和土壤有机质呈正态分布。K、N和EC的熔核/残核值在0.25 ~ 0.75之间,表明各变量之间存在适度的空间自相关性。磷(P)在东部高度集中,而较高的EC聚集在研究点的东北和西南角。交叉验证结果说明了空间预测的平滑效果。研究结果表明,该模型可以直接揭示红土土壤的空间变异性,有助于农民和决策者改进土壤水管理。
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Assessment of spatial variability of soil properties using geostatistical approach of lateritic soil (West Bengal, India)

Degradation of soil due to unsuitable land management practices is a chief impairment of optimum land productivity. The spatial variability of soil properties is needed for agricultural productivity, food safety and environmental modeling. The present study was conducted in lateritic soils of West Bengal, India to understand the spatial variability of soil properties using a geostatistical model. Nitrogen (N), soil pH, electrical conductivity (EC), Phosphorus (P), Potassium (K) and organic carbon (OC) were measured. Surface maps of soil properties were prepared using the semivariogram model through Kriging techniques. A positive correlation was observed between OC and N. The Quantile-quantile plots showed a normal distribution of EC, K, pH, N, and OC. The value for nugget/sill of K, N, and EC were 0.25–0.75 indicating moderate spatial autocorrelation among the variables. Phosphorus (P) was highly concentrated in the eastern part, whereas the agglomeration of higher EC was found in the north east and south west corner of the study site. The cross validation results illustrated the smoothing effect of the spatial prediction. The present study suggests that the geostatistical model can directly reveal the spatial variability of lateritic soils and will help farmers and decision makers for improving soil-water management.

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