University of Zagreb, Faculty of Agriculture, Department of General Agronomy, Zagreb, Croatia.
Environmental Management Center, Mykolas Romeris University, Ateities g. 20, LT-08303 Vilnius, Lithuania.
Sci Total Environ. 2017 Apr 15;584-585:535-545. doi: 10.1016/j.scitotenv.2017.01.062. Epub 2017 Jan 18.
Soil pH, electrical conductivity (EC), organic matter (OM), available phosphorus (AP), and potassium (AK) are some of the most important indicators of soil fertility. These soil parameters are highly variable in space and time, especially in agricultural areas, with implications for crop production. The aim of this work was to study the spatial variability of pH, EC, OM, AP and AK using kriging and co-kriging methods in the Rasa River Valley (Croatia). As co-variates for each variable we considered the distance from the sea (DFS), distance from the river channels (DFC), pH, EC, OM, AP and AK. Only the variables with a significant correlation with the predictor were used as predictor variables. The results showed that soils of the study area had high pH, EC, OM and AK values and a low concentration of AP. The spatial variability was high for EC and low for pH levels. pH, EC, OM and AK had significant positive correlations. All these variables had significant negative correlations with AP. The exponential model was the best to model OM, AK and AP. Spherical and Gaussian models were the most accurate to model pH and EC. Spatial dependence was high for soil AK, EC and pH, and moderate for soil OM and AP. The incorporation of auxiliary variables increased the precision of the estimations. CoK_DFS was the best method to predict soil EC and AP, while Cok_EC, was better to estimate soil pH and Cok_pH and Cok_OM predicted soil OM and AK with the best accuracy. The maps produced with the best predictors showed that pH, EC, OM and AK had high levels in the northern and eastern parts of the study area. The opposite trend was identified in relation to the AP spatial pattern.
土壤 pH 值、电导率(EC)、有机质(OM)、有效磷(AP)和钾(AK)是土壤肥力的一些最重要的指标。这些土壤参数在空间和时间上变化很大,特别是在农业区,对作物生产有影响。本工作的目的是使用克里金和协克里金方法研究拉沙河谷(克罗地亚)土壤 pH 值、EC、OM、AP 和 AK 的空间变异性。作为每个变量的协变量,我们考虑了距海的距离(DFS)、距河道的距离(DFC)、pH 值、EC、OM、AP 和 AK。仅将与预测因子有显著相关性的变量用作预测变量。结果表明,研究区土壤具有高 pH 值、EC、OM 和 AK 值和低 AP 浓度。EC 的空间变异性较高,而 pH 值的空间变异性较低。pH 值、EC、OM 和 AK 值呈显著正相关。所有这些变量与 AP 呈显著负相关。指数模型是模拟 OM、AK 和 AP 的最佳模型。球形和高斯模型是模拟 pH 值和 EC 的最准确模型。土壤 AK、EC 和 pH 值的空间相关性较高,而土壤 OM 和 AP 的空间相关性中等。辅助变量的加入提高了估计的精度。CoK_DFS 是预测土壤 EC 和 AP 的最佳方法,而 CoK_EC 则更适合估计土壤 pH 值,CoK_pH 和 CoK_OM 则以最佳精度预测土壤 OM 和 AK。使用最佳预测因子生成的地图表明,研究区北部和东部土壤 pH 值、EC、OM 和 AK 值较高。AP 的空间模式则呈现相反的趋势。