POWRE: Soil Hydraulic Properties as Affected by Soil Solution Chemical Composition

University Of California-Riverside, Riverside CA

Investigators

Abstract

0074841 Lebron This project addresses the problem of quantifying the influence of solution composition on soil hydraulic properties. The knowledge of these properties is necessary to assess transport of contaminants in soil and subsequent remediation, to predict release and sequestration of CO2, and to interpret and improve the use of remotely sensed soil data such as determination of salinity from electrical resistivity data and determination of water content from satellite information. Flow and transport of water and solutes in soils are controlled by size, geometry and characteristics of the soil porosity. Most of the characteristics of the soil pores are microscopic, such as roughness and circularity. Conventional models of liquid distribution, flow and solute transport rely solely on cylindrical pores, while ignoring the role of surface area, angularity, and connectivity. Neural networks have been used to predict water retention properties in soils using macro and microscopic parameters. These models have tremendous potential to derive pedotransfer functions (PTFs) to predict hydraulic parameters. However the PTFs available in the literature do not consider the chemical composition of the soil solution nor data considering the mineralogy of the clay minerals in the soil. Clay mineral and chemical composition are known to be critical determinants of the hydraulic properties in soils with swelling clays, especially if they are affected by sodicity. The main objective of this project is to quantify the influence of salinity, sodicity and pH on the geometry, size, and distribution of the soil pore space. This quantification will provide the information for developing PTFs using neural network and bootstrap methodology and is intended to improve our capability to predict soil hydraulic properties.