PREDICTION OF SOIL WATER RETENTION PROPERTIES BY USING OF ARYA-PARIS MODEL

References: 14th International Multidisciplinary Scientific GeoConference SGEM 2014, www.sgem.org, SGEM2014 Conference Proceedings, ISBN 978-619-7105-14-8 / ISSN 1314-2704, June 19-25, 2014, Book 3, Vol. 2, 223-230 pp

ABSTRACT
The soil water retention curve or the soil water content-matric potential relationship expresses the capacity of soils to store water for plant growth, which is a very important soil property for irrigation and hydrological modelling. Due to relatively long time involved in the determination of water retention curves, there is an increasing interest for models that estimate this property from simple taxonomic data (soil particle size distribution, bulk density, organic matter and other basic properties). Among these models is the Arya-Paris approach, which is based on the similarity between the shapes of particle size distribution and soil water retention curves. In this paper the model of Arya-Paris was used for assessing the water retention curve using soil texture and bulk density data. Arya-Paris model with α values calculated was applied to evaluate pairs of θ (soil water content) - ψ (matric potential). The van Genuchten equation was then used to estimate the water retention curve in the analyzed soils. Two soil types (Rendzic Leptosol and Calcaro-calcic Kastanozem) located in the Dobrogea area from SE of Romania were analyzed. Parameters of the van Genuchten equation, θr, θs, α, n were evaluated using the pairs of values θ - ψ calculated by Arya-Paris model. Van Genuchten equation was then used to assess some parameters that have agronomical significance. Optimum soil water content and soil matric potential for soil workability correspond to the inflection point of the soil water retention curve. Depending on the characteristics of the soil water retention curve at the inflection point the soil physical quality index, S was calculated.

Keywords: Arya-Paris model, water retention curve, van Genuchten equation