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Field-Scale Mapping of Soil Organic Carbon with Soil-Landscape Modeling

机译:土壤有机碳与土壤景观建模的田间规模

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Predicting soil organic carbon (SOC) at a field scale plays an important role in field management practices for studies in both soil quality and carbon sequestration.Examining SOC concentration with soillandscape relations provided an alternative technique for mapping SOC concentrations.The objectives of this study were to develop soil-landscape models for a crop field by quantifying the relationships between SOC concentration and terrain attributes derived from digital elevation models (DEMs),and to refine the models by delineating the sub-watersheds within the field.Separated soil sample sets were obtained from a 115 ha field located in the coastal plain region of Georgia for model development and model validation.The high accuracy GPS measurements over the field were obtained with a survey grade GPS system.The DEMs with 1,2,4,and 8 m grid sizes were created by interpolating the GPS data,and the terrain attributes were further derived from the DEMs.Correlation coefficients between SOC concentration and terrain attributes were analyzed and indicated that the topographic wetness index was the best single predictor for mapping SOC concentration.The study found that prediction of SOC concentration using the DEM with 2 m grid size yielded the best accuracy in both cases.The effects of grid sizes on the sub-watershed delineation and prediction accuracy were also discussed.
机译:预测现场规模的土壤有机碳(SoC)在土壤质量和碳封存中的研究中起着实地管理实践起着重要作用。通过Soillandscape关系阐述SoC集中,为测绘了SoC浓度提供了一种替代技术。这项研究的目标是通过量化来自数字高度模型(DEMS)的SOC浓度和地形属性之间的关系来开发裁剪领域的土壤景观模型,并通过划分田间内的子流域来改进模型。获得了分类的土壤样本集从一个115公顷的田野,位于格鲁吉亚沿海平原地区进行模型开发和模型验证。使用测量级GPS系统获得了对该领域的高精度GPS测量。使用1,2,4和8米网格的DEM通过插入GPS数据来创建大小,并且地形属性进一步来自DEMS.CORELINATION系数之间分析C浓度和地形属性并表明地形湿度指数是用于测绘SOC浓度的最佳单个预测因子。该研究发现,使用2米网格尺寸的DEM对SOC浓度的预测产生了两种情况的最佳准确性。效果还讨论了子流域描绘和预测准确性的网格尺寸。

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