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Proceedings Paper

Estimating soil hydraulic properties from time series of remotely sensed and in-situ measured topsoil water content
Author(s): Christian Stamm; Katrin Schneeberger; Hannes Fluehler; Christian Maetzler
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Paper Abstract

Soil hydraulic properties are needed in many applications. One of the most difficult quantities to assess is the hydraulic conductivity function. One reason for this is the influence of soil structure on the infiltration capacity. In this paper we present an approach to estimate the hydraulic properties based on time-series of water contents measured in the topsoil of an experimental field plot. Based on the van Genuchten-Mualem model for the soil hydraulic functions we investigate how these properties affect the dynamics of the topsoil water content. We postulate that the water retention curve can be estimated from the range of the top soil water contents observable in the field. The experimental evidence obtained in the plot experiment supports this theoretical conjection. With regard to the hydraulic conductivity function simulations of the drying process demonstrate that there is no straightforward, linear effect of the saturated conductivity Ks on the drying rate. Depending on the initial conditions and the water retention curve drying may be faster or slower with increasing values of Ks. Despite this non-linear behavior the simulation results indicate that for certain soils the influence of soil structure on the conductivity function may be observed by monitoring diurnal cycles of water content. The lack of these cycles in the measured data points to a small Ks-value for the soil matrix of the experimental plot. This is in agreement with the infiltration patterns observed on that plot. A further way to detect bimodal pore-size distributions consists in measuring during a number of drying periods that differ substantially in the initial water distribution in the profile. Simulations show larger effects on the drying rate caused by larger Ks-values.

Paper Details

Date Published: 17 March 2003
PDF: 10 pages
Proc. SPIE 4879, Remote Sensing for Agriculture, Ecosystems, and Hydrology IV, (17 March 2003); doi: 10.1117/12.462382
Show Author Affiliations
Christian Stamm, Swiss Federal Institute of Technology (United States)
Katrin Schneeberger, Swiss Federal Institute of Technology (United States)
Hannes Fluehler, Swiss Federal Institute of Technology (United States)
Christian Maetzler, Univ. Bern (United States)


Published in SPIE Proceedings Vol. 4879:
Remote Sensing for Agriculture, Ecosystems, and Hydrology IV
Manfred Owe; Guido D'Urso; Leonidas Toulios, Editor(s)

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