Numerical Determination of Unsaturated Hydraulic Conductivity From Time-Series Outflow Data

2021 ◽  
Author(s):  
Melih Birhan KENANOĞLU ◽  
Nabi Kartal TOKER
1992 ◽  
Vol 117 (3) ◽  
pp. 415-421 ◽  
Author(s):  
R. Wallach ◽  
F.F. da Silva ◽  
Y. Chen

For effective management of irrigation and fertilization, a complete understanding of the hydraulic properties of container media is essential. This study was conducted to test the applicability of an existing predictive model for calculating the unsaturated hydraulic conductivity K(h) of tuff (Scoria, granulated volcanic ash). Two texturally different types of tuff as well as five fractions (0-1, 1-2, 2-4, 4-8, and > 8 mm), obtained from the natural material by sieving, were investigated. A 0- to 1-mm fraction of quartz sand was also tested and compared to the corresponding fraction of tuff. Water retention curves 0(h) (main drying and primary wetting scanning curves) of the media were measured over a 0- to 120-cm suction range, which covers the range of horticultural interest. The saturated hydraulic conductivity K was measured after the determination of the range of validity of Darcy's law. The model parameters were determined by curve-fitting of the measured retention data, and the K(h) relationship was obtained by multiplying the calculated relative hydraulic conductivity curve K,(h). The model prediction of K(h) was validated following direct and indirect approaches. The results showed that a reliable prediction of the unsaturated hydraulic conductivity of coarsely textured container media consisting of tuff is possible using a model commonly used for regular soils.


1995 ◽  
Vol 05 (02) ◽  
pp. 585-593 ◽  
Author(s):  
FLORIS TAKENS

In this paper we study the numerical determination of the different reduction entropies (or α-entropies) of dynamical systems from time series. This method is advocated as a more suitable way to investigate the different aspects of sensitive dependence on initial positions than the determination of Lyapunov exponents, especially in the case of “noisy” time series.


Soil Science ◽  
1988 ◽  
Vol 145 (4) ◽  
pp. 235-243 ◽  
Author(s):  
L. R. AHUJA ◽  
B. B. BARNES ◽  
D. K. CASSEL ◽  
R. R. BRUCE ◽  
D. L. NOFZIGER

Sign in / Sign up

Export Citation Format

Share Document