用介电介电常数传感器计算土壤含水量。土壤特定校准的好处

IF 1.8 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY
B. Zawilski, F. Granouillac, N. Claverie, Baptiste Lemaire, A. Brut, T. Tallec
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引用次数: 1

摘要

摘要土壤含水量(SWC)传感器广泛用于科学研究或农业实践管理。最常见的传感技术是基于介质介电常数的传感来估计体积土壤含水量。这些技术包括频域反射(FDR)、时域反射(TDR)、电容甚至遥感技术,如探地雷达(GPR)和基于微波的技术。在这里,我们将重点关注频域反射(FDR)传感器,更具体地说,是对它们的工厂校准的质疑,它没有考虑到土壤的特定特征,因此可能导致不一致的swc估计。我们在法国西南部的两个地块进行了目前的研究,这两个地块是ICOS ERIC网络(欧洲研究和基础设施联盟综合碳观测系统)FR-Lamand FR-Aur的一部分。我们提出了一种简单的土壤特定校准方案,特别适用于粘性土壤,以提高使用商用FDR传感器时swc测定的准确性。我们比较了土壤特定校准与工厂校准后的传感精度。我们的结果强调了对非常粘稠的土壤进行彻底的土壤特定校准的必要性。因此,在局部,我们发现工厂校准导致对实际土壤含水量的严重高估。事实上,我们报告了基于介电常数实部的工厂校准传感器的相对误差高达+ 115%,而基于介电常数模量的工厂校准传感器的相对误差高达+ 245%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Calculation of soil water content using dielectric-permittivity-based sensors – benefits of soil-specific calibration
Abstract. Soil water content (SWC) sensors are widely used for scientific studies or for the management of agricultural practices. The most common sensing techniques provide an estimate of volumetric soil water content based on sensing of dielectric permittivity. These techniques include frequency domain reflectometry (FDR), time domain reflectometry (TDR), capacitance and even remote-sensing techniques such as ground-penetrating radar (GPR) and microwave-based techniques. Here, we will focus on frequency domain reflectometry (FDR) sensors and more specifically on the questioning of their factory calibration, which does not take into account soil-specific features and therefore possibly leads to inconsistent SWC estimates. We conducted the present study in the southwest of France on two plots that are part of the ICOS ERIC network (Integrated Carbon Observation System, European Research and Infrastructure Consortium), FR-Lam and FR-Aur. We propose a simple protocol for soil-specific calibration, particularly suitable for clayey soil, to improve the accuracy of SWC determination when using commercial FDR sensors. We compared the sensing accuracy after soil-specific calibration versus factory calibration. Our results stress the necessity of performing a thorough soil-specific calibration for very clayey soils. Hence, locally, we found that factory calibration results in a strong overestimation of the actual soil water content. Indeed, we report relative errors as large as +115 % with a factory-calibrated sensor based on the real part of dielectric permittivity and up to + 245 % with a factory-calibrated sensor based on the modulus of dielectric permittivity.
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来源期刊
Geoscientific Instrumentation Methods and Data Systems
Geoscientific Instrumentation Methods and Data Systems GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
3.70
自引率
0.00%
发文量
23
审稿时长
37 weeks
期刊介绍: Geoscientific Instrumentation, Methods and Data Systems (GI) is an open-access interdisciplinary electronic journal for swift publication of original articles and short communications in the area of geoscientific instruments. It covers three main areas: (i) atmospheric and geospace sciences, (ii) earth science, and (iii) ocean science. A unique feature of the journal is the emphasis on synergy between science and technology that facilitates advances in GI. These advances include but are not limited to the following: concepts, design, and description of instrumentation and data systems; retrieval techniques of scientific products from measurements; calibration and data quality assessment; uncertainty in measurements; newly developed and planned research platforms and community instrumentation capabilities; major national and international field campaigns and observational research programs; new observational strategies to address societal needs in areas such as monitoring climate change and preventing natural disasters; networking of instruments for enhancing high temporal and spatial resolution of observations. GI has an innovative two-stage publication process involving the scientific discussion forum Geoscientific Instrumentation, Methods and Data Systems Discussions (GID), which has been designed to do the following: foster scientific discussion; maximize the effectiveness and transparency of scientific quality assurance; enable rapid publication; make scientific publications freely accessible.
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