通过频域电磁感应数据评估葡萄园的土壤湿度变化

IF 2.1 Q3 SOIL SCIENCE Frontiers in soil science Pub Date : 2024-01-17 DOI:10.3389/fsoil.2023.1290591
Lorenzo De Carlo, A. C. Turturro, M. C. Caputo
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摘要

在农业领域,准确的水文信息对于推断水文模型所需的水量以及进行适当的水资源管理至关重要。为实现这一目的,地球物理频域电磁感应(FDEM)测量越来越多地与传统的点尺度测量相结合,以提供有效的大面积土壤湿度估算。将电磁特性转换为土壤湿度需要特定的工具,这些工具必须考虑到两种测量的空间变化以及数据和模型的不确定性。在位于意大利南部的一个面积约为 4.5 公顷的葡萄园中,我们测试了一种创新的评估方法,该方法使用美国地质调查局授权的免费软件代码 MoisturEC,将 CMD Mini-Explorer 电磁传感器采集的电磁数据与点尺度土壤水分数据整合在一起。数据分析工具结合了点尺度土壤水分测量的准确性和导电率(EC)数据的空间覆盖范围,可以更准确地估计调查区域的水分分布。结果证实,电磁数据有能力准确绘制农业土壤的含水量图,同时也有必要采用能够更新此类定量估算的综合分析工具,以优化水土管理。
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Assessing soil moisture variability in a vineyard via frequency domain electromagnetic induction data
In agriculture, accurate hydrological information is crucial to infer water requirements for hydrological modeling, as well as for appropriate water management.To achieve this purpose, geophysical frequency domain electromagnetic induction (FDEM) measurements are increasingly used for integration with traditional point-scale measurements to provide effective soil moisture estimations over large areas. The conversion of electromagnetic properties to soil moisture requires specific tools that must take into account the spatial variability of the two measurements and the data and model uncertainties. In a vineyard of about 4.5 ha located in Southern Italy, we tested an innovative assessment approach that uses a freeware code licensed from USGS, MoisturEC, to integrate electromagnetic data, collected with a CMD Mini-Explorer electromagnetic sensor, and point-scale soil moisture data.About 30,000 data measurements of apparent electrical conductivity (sa) allowed us to build a 3D inverted electromagnetic model obtained via an inversion process. Soil properties at different depths were inferred from the FDEM model and confirmed through the ground truth sampling.The data analysis tool allowed a more accurate estimation of the moisture distribution of the investigated area by combining the accuracy of the point-scale soil moisture measurements and the spatial coverage of the electrical conductivity (EC) data. The results confirmed the capability of the electromagnetic data to accurately map the moisture content of agricultural soils and, at the same time, the need to employ integrated analysis tools able to update such quantitative estimations in order to optimize soil and water management.
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