The functional dependence of the relative unsaturated hydraulic conductivity (UHC) Kr (ψ) exp(αψ) upon the matric potential ψ, [L], via the soil-dependent parameter α, [L-1], has been traditionally regarded as a deterministic process (i.e. α ∼ constant). However, in the practical applications one is concerned with flow domains of large extents where α undergoes to significant spatial variations as consequence of the disordered soil's structure. To account for such a variability (hereafter also termed as "heterogeneity") we adopt the mining geostatistical approach, which regards α as a random space function (RSF). To quantify the heterogeneity of α, estimates of local-values were obtained from ∼ 100 locations along a trench where an internal drainage test was conducted. The analysis of the statistical moments of α demonstrates (in line with the current literature on the matter) that the log-transform ζ ln α can be regarded as a structureless, normally distributed, RSF.

Mining Geostatistics to Quantify the Spatial Variability of Certain Soil Flow Properties / Severino, Gerardo; Scarfato, Maddalena; Toraldo, Gerardo. - In: PROCEDIA COMPUTER SCIENCE. - ISSN 1877-0509. - 58:(2016), pp. 419-424. (Intervento presentato al convegno 7th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, EUSPN 2016 / The 6th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, ICTH-2016 / Affiliated Workshops, 2016 tenutosi a gbr nel 2016) [10.1016/j.procs.2016.09.064].

Mining Geostatistics to Quantify the Spatial Variability of Certain Soil Flow Properties

SEVERINO, GERARDO;SCARFATO, MADDALENA;TORALDO, GERARDO
2016

Abstract

The functional dependence of the relative unsaturated hydraulic conductivity (UHC) Kr (ψ) exp(αψ) upon the matric potential ψ, [L], via the soil-dependent parameter α, [L-1], has been traditionally regarded as a deterministic process (i.e. α ∼ constant). However, in the practical applications one is concerned with flow domains of large extents where α undergoes to significant spatial variations as consequence of the disordered soil's structure. To account for such a variability (hereafter also termed as "heterogeneity") we adopt the mining geostatistical approach, which regards α as a random space function (RSF). To quantify the heterogeneity of α, estimates of local-values were obtained from ∼ 100 locations along a trench where an internal drainage test was conducted. The analysis of the statistical moments of α demonstrates (in line with the current literature on the matter) that the log-transform ζ ln α can be regarded as a structureless, normally distributed, RSF.
2016
Mining Geostatistics to Quantify the Spatial Variability of Certain Soil Flow Properties / Severino, Gerardo; Scarfato, Maddalena; Toraldo, Gerardo. - In: PROCEDIA COMPUTER SCIENCE. - ISSN 1877-0509. - 58:(2016), pp. 419-424. (Intervento presentato al convegno 7th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, EUSPN 2016 / The 6th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, ICTH-2016 / Affiliated Workshops, 2016 tenutosi a gbr nel 2016) [10.1016/j.procs.2016.09.064].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/661948
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? 6
social impact