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A Comprehensive Performance Assessment of the Modified Philip–Dunne Infiltrometer

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This study aims at furthering our understanding of the Modified Philip–Dunne Infiltrometer (MPDI), which is used to determine the saturated hydraulic conductivity Ks and the Green–Ampt suction head Ψ at the wetting front. We have developed a forward-modeling algorithm that can be used to simulate water level changes inside the infiltrometer with time when the soil hydraulic properties Ks and Ψ are known. The forward model was used to generate 30,000 water level datasets using randomly generated values of Ks and Ψ values. These model data were then compared against field-measured water level drawdown data collected for three types of soil. The Nash–Sutcliffe efficiency (NSE) was used to assess the quality of the fit. Results show that multiple sets of the model parameters Ks and Ψ can yield drawdown curves that can fit the field-measured data equally well. Interestingly, all the successful sets of parameters (delineated by NSE ≥ the threshold value) give Ks values converged to a valid range that is fully consistent with the tested soil texture class. However, Ψ values varied significantly and did not converge to a valid range. Based on these results, we conclude that the MPDI is a useful field method to estimate Ks values, but it is not a robust method to estimate Ψ values. Further studies are needed to improve the experimental procedures that can yield more sensitive data that can help uniquely identify Ks and Ψ values.
Title: A Comprehensive Performance Assessment of the Modified Philip–Dunne Infiltrometer
Description:
This study aims at furthering our understanding of the Modified Philip–Dunne Infiltrometer (MPDI), which is used to determine the saturated hydraulic conductivity Ks and the Green–Ampt suction head Ψ at the wetting front.
We have developed a forward-modeling algorithm that can be used to simulate water level changes inside the infiltrometer with time when the soil hydraulic properties Ks and Ψ are known.
The forward model was used to generate 30,000 water level datasets using randomly generated values of Ks and Ψ values.
These model data were then compared against field-measured water level drawdown data collected for three types of soil.
The Nash–Sutcliffe efficiency (NSE) was used to assess the quality of the fit.
Results show that multiple sets of the model parameters Ks and Ψ can yield drawdown curves that can fit the field-measured data equally well.
Interestingly, all the successful sets of parameters (delineated by NSE ≥ the threshold value) give Ks values converged to a valid range that is fully consistent with the tested soil texture class.
However, Ψ values varied significantly and did not converge to a valid range.
Based on these results, we conclude that the MPDI is a useful field method to estimate Ks values, but it is not a robust method to estimate Ψ values.
Further studies are needed to improve the experimental procedures that can yield more sensitive data that can help uniquely identify Ks and Ψ values.

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