The macroscopic capillary length, λc, is a fundamental soil parameter expressing the relative importance of the capillary over gravity forces during water movement in unsaturated soil. In this investigation, we propose a simple field method for estimating λc using only a single-ring infiltration experiment of the Beerkan type and measurements of initial and saturated soil water contents. We assumed that the intercept of the linear regression fitted to the steady-state portion of the experimental infiltration curve could be used as a reliable predictor of λc. This hypothesis was validated by assessing the proposed calculation approach using both analytical and field data. The analytical validation demonstrated that the proposed method was able to provide reliable λc estimates over a wide range of soil textural characteristics and initial soil water contents. The field testing was performed on a large database including 433 Beerkan infiltration experiments, with the 99% of the experiments yielding realistic λc values. The generated λc values were then used in conjunction with four different methods for estimating saturated soil hydraulic conductivity, Ks. Estimated Ks values were close to those generated by a reference method, with relative error < 25% in nearly all cases. By comparison, assuming constant or soil-dependent λc values caused relative errors in Ks of up to 600%. Altogether, the proposed method constitutes an easy solution for estimating λc, which can improve our ability to estimate Ks in the field.

Di Prima S., Stewart R.D., Castellini M., Bagarello V., Abou Najm M.R., Pirastru M., et al. (2020). Estimating the macroscopic capillary length from Beerkan infiltration experiments and its impact on saturated soil hydraulic conductivity predictions. JOURNAL OF HYDROLOGY, 589(10), 1-11 [10.1016/j.jhydrol.2020.125159].

Estimating the macroscopic capillary length from Beerkan infiltration experiments and its impact on saturated soil hydraulic conductivity predictions

Bagarello V.;Iovino M.;Lassabatere L.
2020

Abstract

The macroscopic capillary length, λc, is a fundamental soil parameter expressing the relative importance of the capillary over gravity forces during water movement in unsaturated soil. In this investigation, we propose a simple field method for estimating λc using only a single-ring infiltration experiment of the Beerkan type and measurements of initial and saturated soil water contents. We assumed that the intercept of the linear regression fitted to the steady-state portion of the experimental infiltration curve could be used as a reliable predictor of λc. This hypothesis was validated by assessing the proposed calculation approach using both analytical and field data. The analytical validation demonstrated that the proposed method was able to provide reliable λc estimates over a wide range of soil textural characteristics and initial soil water contents. The field testing was performed on a large database including 433 Beerkan infiltration experiments, with the 99% of the experiments yielding realistic λc values. The generated λc values were then used in conjunction with four different methods for estimating saturated soil hydraulic conductivity, Ks. Estimated Ks values were close to those generated by a reference method, with relative error < 25% in nearly all cases. By comparison, assuming constant or soil-dependent λc values caused relative errors in Ks of up to 600%. Altogether, the proposed method constitutes an easy solution for estimating λc, which can improve our ability to estimate Ks in the field.
Settore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-Forestali
Di Prima S., Stewart R.D., Castellini M., Bagarello V., Abou Najm M.R., Pirastru M., et al. (2020). Estimating the macroscopic capillary length from Beerkan infiltration experiments and its impact on saturated soil hydraulic conductivity predictions. JOURNAL OF HYDROLOGY, 589(10), 1-11 [10.1016/j.jhydrol.2020.125159].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10447/426738
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