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首页> 外文期刊>Soil Science Society of America Journal >Feasibility of Sequential and Coupled Inversion of Time Domain Reflectometry Data to Infer Soil Hydraulic Parameters under Falling Head Infiltration
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Feasibility of Sequential and Coupled Inversion of Time Domain Reflectometry Data to Infer Soil Hydraulic Parameters under Falling Head Infiltration

机译:时域反射计数据序贯耦合反演推断跌落水头入渗条件下土壤水力参数的可行性

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摘要

Accurate estimation of soil hydraulic properties is a prerequisite for efficient soil and water management. On a small scale, time domain reflectometry (TDR) measurements obtained during an infiltration event can be used for estimating soil hydraulic properties either using a sequential or a coupled inversion approach. In the traditional sequential approach, the TDR measurements are inverted into water content averages based on travel time analysis and subsequently used for calibrating a hydrologic model. Travel time analysis has been reported to be subjective and difficult to use for analyzing TDR measurements obtained during infiltration. In this paper, we extend the sequential inversion approach by using water content profiles (WCPs) obtained via inverse modeling of TDR measurements and introduce a coupled inversion approach which directly uses the TDR measurements for constraining the inversion for hydraulic properties without first inverting them into WCPs or averages. By comparing the feasibility of these approaches to infer three Mualem-van Genuchten (MVG) hydraulic parameters (alpha, n, K-s) from TDR measurements obtained under falling head infiltration, we concluded that the coupled approach is more practical and less uncertain than the sequential approach. In particular, the coupled inversion approach allows to simultaneously monitor ponding depth and water infiltration, which avoids the laborious task of manually measuring the ponding depths and can thus enable rapid estimation of the soil hydraulic parameters for multiple locations through automatic measurements of ponded infiltration for multiple rings through TDR multiplexing.
机译:准确估算土壤水力特性是有效进行土壤和水管理的先决条件。在小规模情况下,在渗透事件中获得的时域反射法(TDR)测量结果可用于使用顺序或耦合反演方法估算土壤水力特性。在传统的顺序方法中,基于行程时间分析,将TDR测量值转换为平均水含量,然后用于校准水文模型。据报道,行进时间分析是主观的,难以用于分析渗透过程中获得的TDR测量值。在本文中,我们通过使用通过TDR测量反演获得的含水量剖面(WCP)扩展了顺序反演方法,并介绍了一种耦合反演方法,该方法直接使用TDR测量来限制水力特性的反演,而无需先将其转换为WCP或平均值。通过比较这些方法从落头渗透下获得的TDR测量值推断三个Mualem-van Genuchten(MVG)水力参数(alpha,n,Ks)的可行性,我们得出结论,与连续方法相比,耦合方法更实用,不确定性更低方法。尤其是,耦合反演方法允许同时监视池深和水的渗透,从而避免了手动测量池深的繁琐工作,因此可以通过自动测量多个池的入渗来快速估算多个位置的土壤水力参数。通过TDR多路复用而振铃。

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