Suppr超能文献

不同土层粉质壤土和壤土地壤水分保持曲线的原位估算。

In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths.

机构信息

School of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada.

出版信息

Sensors (Basel). 2021 Jan 10;21(2):447. doi: 10.3390/s21020447.

Abstract

The soil water retention curve (SWRC) shows the relationship between soil water (θ) and water potential (ψ) and provides fundamental information for quantifying and modeling soil water entry, storage, flow, and groundwater recharge processes. While traditionally it is measured in a laboratory through cumbersome and time-intensive methods, soil sensors measuring in-situ θ and ψ show strong potential to estimate in-situ SWRC. The objective of this study was to estimate in-situ SWRC at different depths under two different soil types by integrating measured θ and ψ using two commercial sensors: time-domain reflectometer (TDR) and dielectric field water potential (e.g., MPS-6) principles. Parametric models were used to quantify θ-ψ relationships at various depths and were compared to laboratory-measured SWRC. The results of the study show that combining TDR and MPS-6 sensors can be used to estimate plant-available water and SWRC, with a mean difference of -0.03 to 0.23 mm between the modeled data and laboratory data, which could be caused by the sensors' lack of site-specific calibration or possible air entrapment of field soil. However, consistent trends (with magnitude differences) indicated the potential to use these sensors in estimating in-situ and dynamic SWRC at depths and provided a way forward in overcoming resource-intensive laboratory measurements.

摘要

土壤水分保持曲线 (SWRC) 显示了土壤水分 (θ) 和水势 (ψ) 之间的关系,为量化和模拟土壤水分入渗、储存、流动和地下水补给过程提供了基本信息。虽然传统上它是通过繁琐且耗时的实验室方法来测量的,但测量原位 θ 和 ψ 的土壤传感器显示出了很强的估计原位 SWRC 的潜力。本研究的目的是通过整合使用两种商业传感器:时域反射仪 (TDR) 和介电水势 (例如,MPS-6) 原理测量的原位 θ 和 ψ,来估计两种不同土壤类型下不同深度的原位 SWRC。使用参数模型来量化不同深度处的 θ-ψ 关系,并将其与实验室测量的 SWRC 进行比较。研究结果表明,TDR 和 MPS-6 传感器的组合可用于估计植物可用水和 SWRC,模型数据与实验室数据之间的平均差异为 -0.03 至 0.23mm,这可能是由于传感器缺乏特定于站点的校准或可能存在田间土壤中的空气截留。然而,一致的趋势(具有幅度差异)表明了在深度上使用这些传感器估计原位和动态 SWRC 的潜力,并为克服资源密集型实验室测量提供了一种方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb3a/7826571/94c37527e128/sensors-21-00447-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验