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Mapping Soil Salinity in El-Tina Plain in Egypt Using Geostatistical Approach

机译:利用地统计方法在埃及映射埃尔河普通的土壤盐度

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In El-Tina plain soil salinity is the major soil limitation factor for agricultural production. Spatial information on soil salinity is increasingly needed, particularly for better soil management in this area. To explore spatial variability of soil salinity in the study area grid sampling scheme (800 × 800 m) consisting of 96 sample points (81 soil profiles and 15 augers) and 41 observation points was established. Electrical conductivity was determined by laboratory analysis from 1:2.5 soil-water suspensions (EC_(2.5)). Spatial trend and semi-variogram were computed and spatial distribution of field salinity status was further visualized and quantified. Two types of kriging were used: Ordinary Kriging (OK) and Universal Kriging (UK) with three semivariogram models (circular, spherical and exponential). Mean Prediction Errors (MPE), Mean Standardized Prediction Errors (MSPE) and Root-Mean-Square Standardized Prediction Errors (RMSSPE) were used to evaluate the models. The results suggest that the best model to generate soil salinity map was Ordinary Kriging with spherical semivariogram model (MPE and MSPE close to 0, and RSSPE close to 1). The selected model was used to generate salinity map based on standard soil salinity classification.
机译:在El-Tina Plan Parity盐度是农业生产的主要土壤限制因素。越来越需要有关土壤盐度的空间信息,特别是在该地区更好的土壤管理。为了探讨研究区域网格采样方案(800×800米)中的土壤盐度的空间变异(800×800米)组成的96个样品点(81土壤曲线和15座轴)和41个观察点。通过从1:2.5土壤 - 水悬浮液(EC_(2.5))的实验室分析确定电导率。计算空间趋势和半变形仪,并进一步可视化和量化现场盐度状态的空间分布。使用了两种类型的克里格:普通的Kriging(OK)和通用Kriging(UK),具有三个半啮盘模型(圆形,球形和指数)。使用平均预测误差(MPE),平均标准化预测误差(MSPE)和根均线标准化预测误差(RMSSPE)用于评估模型。结果表明,生成土壤盐度图的最佳模型是普通的克里格,球形半造型模型(MPE和MSPE接近0,RSPE接近1)。所选模型用于基于标准土壤盐度分类产生盐度图。

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